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Oct 1, 2012 - The Management of Accounting and Taxation ...... Master's degree in computer sciences, option: knowledge and information systems.
Proceedings of the

15th European Conference on Knowledge Management Polytechnic Institute of Santarém Portugal

4-5 September 2014

Volume 1 Edited by Carla Vivas and Pedro Sequeira

A conference managed by ACPI, UK

           

  The Proceedings of the   15th European Conference on   Knowledge Management    ECKM 2014    The Santarém School of Management   and Technology  Polytechnic Institute of Santarém,   Santarém, Portugal    4‐5 September 2014   

Volume One    Edited by   Dr Carla Vivas and Dr Pedro Sequeira       

Copyright The Authors, 2014. All Rights Reserved.  No reproduction, copy or transmission may be made without written permission from the individual authors.  Papers have been double‐blind peer reviewed before final submission to the conference. Initially, paper abstracts were read  and selected by the conference panel for submission as possible papers for the conference.  Many thanks to the reviewers who helped ensure the quality of the full papers.  These Conference Proceedings have been submitted to Thomson ISI for indexing.  Further copies of this book and previous year’s proceedings can be purchased from http://academic‐bookshop.com  E‐Book ISBN: 978‐1‐910309‐35‐3  E‐Book ISSN: 2048‐8971  Book version ISBN: 978‐1‐910309‐34‐6  Book Version ISSN: 2048‐8963  CD Version ISBN: 978‐1‐910309‐36‐0  CD Version ISSN: 2048‐898X  The Electronic version of the Conference Proceedings is available to download from   DROPBOX. (http://tinyurl.com/ECKM2014) Select Download and then Direct Download to access the Pdf file. 

Published by Academic Conferences and Publishing International Limited  Reading  UK  44‐118‐972‐4148  www.academic‐publishing.org 

Contents  Paper Title 

Author(s) 

Page  No. 

Volume One 

 

Preface 

 

ix 

Committee 

 



Biographies  

 

xiv 

Learned Helplessness of Prisoners: Psychology and  Knowledge Management Perspective  

Juneman Abraham and Rigel Adiratna 



The Management of Accounting and Taxation  Knowledge in Portugal 

Rute Abreu, Fátima David and Liliane Segura 



Linking ICT to the Development of Knowledge‐Based  Economy Pillars 

Kamla Ali Al‐Busaidi 

15 

Developing a Learning Disabilities Preliminary Diagnosis  Expert System 

Ghitha Al‐Kalbani, Maryam Al‐Ajmi, Samia Al‐Fazari  and Kamla Ali Al‐Busaidi 

22 

Zakat Expert System 

Afaf Al‐Riyami, Asma Al‐Harthy , Khadija Al‐Amri and  Kamla Ali Al‐Busaidi 

31 

6Investigation of Knowledge Management Support for  Business Intelligence in the Saudi Public Sector 

Hala Alrumaih and Nesrine Zemirli   

39 

A Knowledge Management Framework for the Effective  Integration of National Archive Resources in China  

Xiaomi An, Wenlin Bai, Hepu Deng and Wenrui  Zhong 

47 

Comparison of the Intellectual Capital Between Finland  and Spain 

Nekane Aramburu, Josune Sáenz, Marta Buenechea,  Mika Vanhala and Paavo Ritala 

55 

Knowledge Sharing Within Extended Enterprises: Case of  Pierre‐Emmanuel Arduin, Julien Le Duigou, Diana  Penciuc, Marie‐Hélène Abel and Benoît Eynard  Product Lifecycle Management systems 

63 

Barriers in Knowledge Sharing vs the Ability to Create  Tourism Supply Chains 

Urszula Bąkowska‐Morawska 

72 

Knowledge Management in Public Administration: Brazil  Versus Portugal 

Fábio Ferreira Batista and Florinda Matos 

82 

Effect of ICT on Information Sharing in Enterprises: The  Case of Ministry of Development 

Özlem Gökkurt Bayram and Hakan Demirtel 

94 

Blueprinting a Knowledge Sciences Center to Support a  Regional Economy 

Denise Bedford, John Lewis and Brian Moon

102 

Developing an Open Source, Adaptable and Sustainable  Method for Conducting Knowledge Management  Maturity Modeling and Assessment  

Denise Bedford, Margaret Camp, Dessie Hein, Tyler  Liston, Jeffery Oxendine and  Dean Testa 

111 

Developing an Interactive View on Intra‐Organisational  Knowledge Sharing 

Madeleine Block and Tatiana Khvatova 

120 

Variations in Preferences for the use of Social Networks;  Demographic Analysis of Posted Content 

Pavel Bogolyubov, Andrey Artemiev, James da  Lança, Jay Gopal and Boyka Simeonova 

131 

Ettore Bolisani, Enrico Scarso and Luca Giuman  Wiki as a Knowledge Management System in a Small  Project‐Based Company: Benefits, Issues and Managerial    Challenges 

138 

Communities of Practice and Renewable Distributed  Energy: The CIVIS Experience 

Matteo Bonifacio, Andrea Capaccioli, Giacomo  Poderi, Maurizio Marchese and Vincenzo D’Andrea 

148 

Putting Your Money Where Your Mouth is: Monetizing  Knowledge Using Communication Roles 

Karl Joachim Breunig and Hanno Roberts 

156 



Paper Title 

Author(s) 

Page  No. 

Knowledge Management in Municipalities: What Affects  Customer Satisfaction? 

Elisabeth Brito, Leonor Pais, Lisete Mónico and  Liliana Jorge 

164 

Sustainability of Open Distance E‐Learning Institutions  as Knowledge Producers: A Theoretical Perspective  

Sheryl Buckley and Apostolos Giannakopoulos 

173 

The ICT Systems Developments in Maintenance – From  Data Processing Into Knowledge Driven Approaches  

Jaime Campos

182 

The Specific Valorisation of Competitive Intelligence  Profiling on the Software Industry 

Alexandru Capatina and Gianita Bleoju 

189 

Knowledge Management Practices for Corporate Social  Responsibility: A Family Business Perspective 

Antonio José Carrasco Hernández and Daniel  Jimenez Jimenez 

198 

Towards a Methodology for Lessons Learned Practice in  Complex Product Development 

Koteshwar Chirumalla

205 

The Development of the Polish Qualifications  Framework as an Application of Knowledge  Management in Public Policy  

Agnieszka Chłoń‐Domińczak Łukasz Sienkiewicz and  Katarzyna Trawińska‐Konador 

214 

Designing and Testing an AHP Methodology to Prioritize  Critical IC Elements for Product Innovation  

Ricardo Costa and Ana Paula Ramos  

223 

Knowledge Management on PMO’s Perspective: A Sys‐ tematic Review 

José Adson Cunha, José Figueiredo, Florinda Matos and João Thomaz 

233 

COBIT5 An Approach to Analysing an Organization’s  Knowledge and Knowledge Management During due  Diligence 

Bostjan Delak, Nadja Damiji and Grzegorz Marek  Majweski 

242 

Knowledge and Intellectual Capital in Smart City  

Renata Paola Dameri, Francesca Ricciardi and Bea‐ trice D’Auria 

250 

Exploring the Impact of Mental Models on Teamwork  and Project Performance 

Brit‐Eli Danielsen, Rune Kristiansen Valle, Trine  Marie Stene 

258 

KMSS: A Knowledge Management System for Senology 

Souad Demighaand Corinne Balleyguier 

268 

The Knowledge Fecundity Framework: Enabling  Integrative Knowledge Management Strategy 

Sally Eaves 

278 

Knowledge Transfer – a Means to Manage the Interplay  Between Changes and Time‐usage in Construction  Projects  

Anandasivakumar Ekambaram, Agnar Johansen, Jan  Alexander Langlo and Pedro Rondón 

288 

A Conceptual Model to Design a Collective Intelligence  System Supporting Technology Entrepreneurship 

Gianluca Elia, Alessandro Margherita, Giuseppe  Vella, Francesca Grippa and Andrea Cappilli 

297 

Virtual Communities of Practice – Experiences From  VCoP  

Martina Ergan, Tone Vold and Etty Nilsen 

306 

The Role of Competence Brokering in Regional  Innovation and Development 

Leif Estensen, Terje Bakken and Anandasivakumar  Ekambaram 

311 

Knowledge Absorption in Organisations – Development  of a Conceptual Process Model  

Nina Evans and Rachelle Bosua 

321 

Epistemology: The Feeble Philosophical Foundation of  Knowledge Management 

Doron Faran

330 

Engaging to Perform: Job Satisfaction as a Mediator 

Pedro Ferreira and Elizabeth Real de Oliveira 

336 

Wiki as a Knowledge Management Tool: The Case of a  Non‐Profit Administrative Entity 

Vitor Hugo dos Santos Ferreira 

343 

ii 

Paper Title 

Author(s) 

Page  No. 

The Role of Human Resource Management in  Knowledge Management: The cases of Training and Ca‐ reer Management 

Elisa Figueiredo, Leonor Pais, Samuel Monteiro and  Lisete Mónico 

353 

Personal Knowledge Sharing: Web 2.0 Role Through the  Lens of Generations 

Zoltán Gaál, Lajos Szabó and Nóra Obermayer‐ Kovács 

362 

Shifting From a Local to Sector‐Based Strategy for  Supporting the Sharing of Knowledge and Skills: The  Case of 911 Emergency Call Centres 

Charles Gagné and Georges Toulouse 

371 

Computer Assisted Reasoning as a Support for  Knowledge Management  

Johan Garcia  

377 

A Model to Measure the Contribution Degree of Know‐ How/Knowing‐That of the Organization 

Sahar Ghrab, Ines Saad, Gilles Kassel and Faiez  Gargouri 

386 

Developing a Community of Practice to Learn, Share and  Improve in Emergency Management 

Raquel Gimenez, Josune Hernantes, Leire Labaka,  Jose Maria Sarriegi and Ana Laugé 

395 

Merging Knowledge Management with Project  Management 

Meliha Handzic  and Nermina Durmic 

402 

An Empirical Comparison Study of the Effect of Chief  Knowledge Management Officers and Knowledge  Management Systems on Innovation and Financial  Outcomes 

Harold Harlow  

410 

Advancements, Challenges and Future Research in  Knowledge Management: Results From a Global Expert  Study 

Peter Heisig 

419 

TSM: An Instrument That Supports Industrial Doctoral  Projects  

Ilona Heldal, Eva Söderström, Lars Bråthe and  Robert Murby 

428 

The Crafting of Online Knowledge Construction 

Inge Hermanrud

438 

Volume Two 

 

Knowledge Management in an Academic Context: A  Framework for Successful Intranet 2.0 Implementation 

Eli Hustad, Fredrik Kydland and Marit Aakre 

444 

Knowledge Management Practices and Firm  Performance – Empirical Findings From Finland 

Henri Inkinen and Aino Kianto 

455 

Organizational Culture and Knowledge Transfer:  Evidence From the Bruneian Public Organization  Employees   

Md. Zahidul Islam, Mohammad Habibur Rahman,  Ikramul Hasan and Hazri Bin Haji Kifle 

463 

Knowledge Elicitation Through Collaborative Modelling:  A Case Study of the British Railway Industry 

Mahsa Jahantab, Alexeis Garcia‐Perez and Siraj  Shaikh 

471 

Culture and Performance: A Learning Orientation for the  Daniel Jiménez‐Jiménez; Juan R. Fernández‐Gil;  Micaela Martínez‐Costa  Financial Sector  

480 

Managerial Factors Behind the Development of Trust in  Inter‐Organizational Knowledge Networks 

Rita Juceviciene and Giedrius Jucevicius 

489 

The Organisation’s Learning in the Multinational  Company: What Kind of Knowledge Sources Does  Influence It? 

Palmira Juceviciene and Vyda Mozuriuniene   

499 

From Knowledge to Smart City: A Conceptual Study 

Robertas Jucevicius and Giedrius Jucevicius 

508 

Knowledge Management – Time to Rethink the  Discipline 

Nowshade Kabir

516 

iii 

Paper Title 

Author(s) 

Page  No. 

Alexander Kaiser, Florian Kragulj and Stefan Gächter Recent Developments and Approaches to Knowledge  Creation and Learning in Systems. A Proposal for Further  Innovation  The Impact and Possible use of the Zen Methods in  Knowledge Management 

Marcela Katuščáková

An Empirical Study of Knowledge Management Practices  Yasmina Khadir‐Poggi and Mary Keating    in Small Asset Management Firms Based In Ireland 

524 

531  539 

Radwan Kharabsheh, Khalid Jarrar and Boyka  Simenonva 

547 

Enabling Knowledge Creation: Does Employees’ Training  Stimulate R&D Activities? 

Tomasz Kijek and Marek Angowski 

556 

Process‐Oriented Knowledge Management in SMEs 

Holger Kohl, Ronald Orth, Erik Steinhöfel 

563 

The Impact of Competitive Strategies on Responsive  Market Orientation, Proactive Market Orientation,  Learning Orientation and Organizational Performance  

The Cause and Impact of the Development of Coworking  Jaroslava Kubátová   in the Current Knowledge Economy 

571 

The Role of Intellectual Capital in a Credit Cooperative: A  Carmem Leal, Carla Susana Marques, Carlos Peixeira  Marques and Elizomar Braga‐Filho  Multivariate Analysis  

578 

Knowledge Management and Transfer: Modeling Inter‐ actions in Small Businesses 

Monique Lortie, Idriss Kefi1 and Lise Desmarais    

586 

TK Aware Business Process Simulation: A Case Study  With Slovenian High‐Achieving Company From the SME  Sector 

Grzegorz Marek Majewski, Boštjan Delak and Nadja  Damij 

593 

The Collaborative Enterprise in the Knowledge Econo‐ my: Motivational Profiles  

Simone Manfredi and Roberta Antonelli 

601 

Strategic Knowledge Management, Innovation and Per‐ formance: An Initial Study of Portuguese Footwear  Companies 

Carla Susana Marques, Carmem Leal, Carlos Peixeira  Marques and Ana Rita Cardoso 

609 

The Influence of User eSkills on Online Health Care Ser‐ vices Success 

Eva Martínez‐Caro,  Juan Gabriel Cegarra‐Navarro  and Antonio Juan Briones‐Peñalver  

619 

Knowledge Management in Multinational Companies:  The Repatriates’ Role in the Competitive Advantage in  Subsidiaries 

Dora Martins and Eduardo Tomé 

628 

"Customer" Knowledge Management in Healthcare 

Sara McCracken and John Edwards 

637 

Inter‐Organizational Knowledge Sharing Networks: A  Study on a Business Network 

Andreia Meireles, Leonor Pais and João Daniel 

641 

Development and Initial Validation of a Survey for Intel‐ lectual Capital in Universities 

Patricia Mercado‐Salgado, Pedro Gil‐Monte and  María del Rosario Demuner‐Flores 

650 

Impact of Knowledge Acquisition to Strategic Infor‐ mation Systems Plan Implementation in Ethiopia 

Peter Mkhize

659 

Storytelling and Leadership Skills of Managers 

Ludmila Mládková

667 

Knowledge Management Implementation in UK Public  Sector 

Sandra Moffet

676 

From Data to Knowledge: KM Implementation in the UK  Car Retail Industry 

Sandra Moffett, Stephanie Conn ,Andrea Reid and  Karise Hutchinson 

684 

Influence of Knowledge Management Practices on Mu‐ nicipalities’ Image Among Their Users 

Lisete Mónico, Leonor Pais, Elisabeth Brito and  Ornela Harris 

692 

iv 

Paper Title 

Author(s) 

Page  No. 

Knowledge Management and HRM – Theoretical and  Empirical Links 

Samuel Monteiro and Leonor Pais 

700 

Polish National Knowledge Management Styles: Studies  in Selected Companies Representing Creative Industries 

Mieczysław Morawski

708 

Alignment Model of Knowledge Management Strategies  with Human Resource Strategies  

Mirali Seyed Naghavi and Shahla Sohrabi 

715 

Critical Success Factors for Effective Knowledge Sharing:  Integrating Intra‐Organizational Communication and KM  Tools 

Martin Nkosi Ndlela

724 

Systematic Description of Nursing Actions Based on Goal  Satoshi Nishimura, Yoshinobu Kitamura, Munehiko  Sasajima,and Riichiro Mizoguchi  Realization Model 

730 

Knowledge Management Perspectives: The Portuguese  MNCs of Romania and Poland 

Frederico Nunes and Carmina Simion 

740 

Maturity Model for Knowledge Management and Stra‐ tegic Benefits 

Mírian Oliveira and Cristiane Drebes Pedron 

748 

Knowledge Management in Small and Micro Enterprises:  Mirian Oliveira, Cristiane Drebes Pedron, Felipe  Nodari and Rodolfo Ribeiro  Applying a Maturity Model 

757 

Knowledge Sharing: Brazilian x Portuguese Companies 

Mírian Oliveira, Carla Curado, Mario Romão and  Antonio Carlos Gastaud Maçada 

765 

Modes of Information (Knowledge) Sharing: A Case  Study 

Gary Oliver

774 

The use of social networks in undergraduate projects  guiding: Mundus Spectaculum 

Beatriz de Almeida Pacheco, Ilana deAlmeida Souza‐ Concilio, Simone Freitas 

783 

Deepening the Understanding of Knowledge Manage‐ ment Dimensions 

Leonor Pais , Lisete Mónico, Nuno Rebelo dos San‐ tos and Sara Almeida 

792 

The Innovation Lessons: Organizational Narratives of  Applied Knowledge in Technology‐Based Organizations 

Margarida Piteira and Jorge Gomes 

802 

Managing Knowledge Generation at Universities 

Evgeny Popov and Maxim Vlasov  

811 

Managing Hospitals: Who Knows Best, and at What Lev‐ el? Organizational and Operational Learning in Public  Management Reforms 

Vítor Raposo, Teresa Carla Oliveira and Diana  Tarrafa 

817 

The Importance of Knowledge Management in the Suc‐ cession Process of Family Businesses 

Paula Rodrigues, Ana Pinto Borges and Alberto  Aleixo 

826 

Building Organisational Agility Through an Unlearning  Context 

José Roldán, Juan Gabriel Cegarra and Gabriel  Cepeda 

834 

Antecedents and Consequences of Knowledge Man‐ agement Performance 

José Roldán, Juan Real and Silvia Sánchez‐Ceballos

843 

Fostering Knowledge Sharing Through Intrinsic Reward 

Svetlana Sajeva

854 

Volume Three 

 

Smart Intangible Knowledge Assets Valuation 

Maria‐Isabel Sánchez‐Segura, Alejandro Ruiz‐Robles,  Fuensanta Medina‐Dominguez and Antonio  Amescua Seco 

862 

Software Agents: Solution to KM Anxiety of Japanese in  Limited Trust Situations 

Thomas Schalow

868 

Innovating Management or Managing Innovation, What  Matters for the Brazilian SMEs? 

Camilo Augusto Sequeira, Markus Will and Eloi  Fernández y Fernández 

874 



Paper Title 

Author(s) 

Page  No. 

Evaluation Criteria of Experts for Knowledge Manage‐ ment System of a Business School 

Gulzada Serzhan, Gulffarida Tulemissova, Svetlana  Iskakova and Ermek Ramazanov 

879 

Dynamics of Innovation Networks: The Role of HEIs in  Venture Creation 

Jorge Manuel Marques Simões, António Anacleto  Viegas Ferreira, Rodrigo Morais and Guida Coelho 

885 

Knowledge Management in Call Centres: The Work  Team as Unit of Analysis 

Cristina Souza de Castro, Leonor Pais and Lisete  Mónico 

893 

KM Practices, Innovation Strategies and Firm Perfor‐ mance: Evidence From 16 European Economies 

Inga Stankevice

903 

Compliance ‐ why do People Follow Procedures?  

Trine Marie Stene

912 

Successful and Safe Operation ‐ A Combination of Indi‐ vidual, Team and Organization Training  

Trine Marie Stene, Brit‐Eli Danielsen and Rune Kris‐ tiansen Valle 

923 

Integration of Knowledge Management into Business  Process 

Marta Christina Suciu, Cristina Andreea Florea and  Ileana Teodorescu 

932 

Concept of Knowledge and Research: How to Study Tacit  Vlastimil Švec, Radim Šíp and Jana Krátká  Dimension of Knowledge 

939 

Inter‐Professional Learning for Teaching – Using Digital  Tools 

Ann Svensson and Gunilla Forssell Eriksson 

946 

Knowledge Transfer in Hub‐And‐Spokes Industrial Dis‐ tricts: Power and Socio‐Cultural Relationships in the  Basilicata Oil District, Italy 

Giovanna Testa

954 

Development of the Knowledge Economy and Regional  Innovation Policy: Russian Practice 

Elena Tkachenko and Sergey Bodrunov 

964 

KM and Politics at the Highest Level: An Exploratory  Analysis   

Eduardo Tomé, Paula Figueiredo, Dora Martins3 and  Klaus Bruno Schebesch 

974 

Aligning Knowledge Sharing Strategy With Organization‐ al and Cultural Contexts: An Information System Per‐ spective 

Thierno Tounkara and Pierre‐Emmanuel Arduin 

983 

Knowledge Capital Earnings of a Company Listed on  Warsaw Stock Exchange 

Anna Ujwary‐Gil

994 

Knowledge Sharing with International Residents in  Times of Disaster: The Role of the Public Sector 

Jiro Usugami

1001 

Corporate Intellectual Capital Disclosure in the Baltic  States: A Comparative Empirical Study 

Lina Užienė  

1010 

The Port as a “Non Consensual” Organisation: An IC  Management Perspective 

José Vale, Manuel Branco and João Ribeiro 

1020 

Education Quality and Economic Performance in Europe 

Ana Cláudia Valente, Isabel Salavisa and Sérgio  Lagoa 

1028 

The Practice of Entrepreneurial Excellence: An Overview  of Methodologies for Achieving Excellence in the  Knowledge Economy Context 

José Maria Viedma, Maria do Rosário Cabrita,  Florinda Matos and Virgílio Cruz‐Machado 

1037 

Integrating Knowledge Management in a Business Strat‐ Carla Vivas, Pedro Sobreiro and Rui Claudino  egy Process Operationalized Using Process Management    Approach  New Takes on Learning in Organizations When Using  Role Play Simulation 

Tone Vold, Sule Yildirim‐Yayilgan and Jan‐Oddvar  Sørnes 

vi 

1045 

1055 

Paper Title 

Author(s) 

Page  No. 

Conceptual Framework for Development of Computer  Technology Supporting Cross‐Linguistic Knowledge Dis‐ covery 

Igor Zatsman, Nadezhda Buntman, Mikhail  Kruzhkov, Vitaly Nuriev and Anna Zalizniak 

1063 

Critical Success Factors for Knowledge Management in  SMEs in the KIBS Sector 

Malgorzata Zieba  

1072 

PHD Research Papers 

1081 

Knowledge Sharing and Information Security: A Para‐ dox? 

Ghosia Ahmed, Gillian Ragsdell and Wendy Olphert

1083 

Effective Knowledge Management Using Tag‐Based Se‐ mantic Annotation for web of Things Devices 

Mohammad Amir, Y. Fun Hu and Prashanti Pillai 

1091 

Information and Knowledge in Spanish Science and  Technology Parks 

Ivett Aportela Rodríguez  

1099 

Knowledge Sharing in Virtual Communities: A Compari‐ son of Three Different Cultures 

Shahnaz Bashir, Abel Usoro and Imran Khan 

1108 

The Tension Between Competitive and Collaborative  Forces in Agricultural Research: Impact on Knowledge  Sharing Within a Public Research Organisation 

Patricia Bertin, Jenny Fry and Gillian Ragsdell   

1118 

Trust and Employee Competence Utilization – Empirical  Testing of a Model  

Britta Bolzern‐Konrad and Ērika Šumilo 

1127 

Intellectual Capital as an Engine of Growth: Analysis of  Causality for North Cyprus Economy 

Behiye Çavuşoğlu  

1137 

Identification of Tacit Knowledge Associated With Expe‐ rience: A Chinese Software Industry Study 

Hui Chen, Gillian Ragsdell and Ann O’Brien   

1147 

“Overcoming Trust Barriers: Evaluating Inter‐ Organisational Knowledge Sharing in UK Online Retail  Sector” 

Rozina Chohan, Mahmood Shah, Mitchell Larson  and Mary Welch 

1156 

Knowledge Processes, Absorptive Capacity and Innova‐ tion: Contributions for a Systematic Literature Review 

Vítor Costa and Samuel Monteiro   

1164 

Semantic‐Based Framework for Innovation Manage‐ ment 

Lamyaa El Bassiti and Rachida Ajhoun 

1173 

Identifying Future Research Directions in Knowledge  Management from a Latin American and the Caribbean  Perspective: An Exploratory Study 

Ernesto Galvis‐Lista, Lucía Rodríguez‐Aceves, Peter  Heisig 

1183 

Knowledge Management in Lithuanian Innovative Busi‐ ness Organizations 

Ingrida Girnienė and Zenona Atkočiūnienė 

1193 

A Possible Approach for Evaluating Knowledge Workers:  Case Study in a Romanian's University 

Maria Luminita Gogan   

1202 

An Innovative Model for Evaluating National Intellectual  Capital 

Maria‐Luminita Gogan   

1211 

Intellectual Capital and Human Capital, State of art and  Proposal of Framework 

Belkacem Iskhar and Latifa Mahdaoui 

1219 

MADM Methods in Practice: Linking Competencies to  Employees' Appraisal and Total Reward  

Katerina Kashi and Petra Horváthová 

1229 

The Role of Knowledge Management in Organisational  Performance 

Stanford Makore and Chuks Eresia‐Eke  

1240 

Perspectives and Implications of Sharing Processes  Within Organisations: The Case Study  

Tereza Otcenaskova and Vladimir Bures   

1249 

vii 

Paper Title 

Author(s) 

Page  No. 

A Knowledge Creation Innovation for Web‐Knowledge‐ Base System Using Knowledge Management, and Data  and Knowledge Engineering 

Patcharaporn Paokanta, Napat Harnpornchai,  Michele Cecarelli 

1255 

Knowledge Sharing Using web Mining for Categorization  and Disambiguation of Structured and Unstructured  Data 

Leandro Ramos da Silva and Nizam Omar 

1265 

Good Practices in Virtual Leadership – The E‐3cs Rule  (Communication, Trust and Coordination) 

João Paulo Rodrigues da Silva Samartinho, Paulo  Fernando Lopes Resende da Silva Jorge and Manuel  Alves de Faria 

1272 

The Role of Brand Knowledge in the Creation of Cus‐ tomer Capital 

Noelia Sánchez‐Casado; Anthony Wensley; Eva  Tomaseti‐Solano and Juan‐Gabriel Cegarra‐Navarro 

1283 

Models for Describing Incident Knowledge Sharing Prac‐ tices: The Case Study of UK Hospital  

Negar Monazam Tabrizi  

1291 

Knowledge Management in Open Innovation Context 

Erika Tauraitė‐Kavai 

1301 

Application of Semantic Network for Knowledge Sharing  in the Field of Marketing 

Stanislav Vojir and Zdenek Smutny 

1306 

Transactive Memory System Measurement Methods –  Review and Future Perspectives 

Volker Wagner

1314 

Masters Research Papers  Leadership Role and Competencies of Managers in  Knowledge Intensive Context  

1323  Mustafa Doruk Mutlu  

Work In Progress Paper 

1325  1333 

From Complex Maths to Simple Stories: A Knowledge  Management Approach to Education  

Nicole Bittel and Marco Bettoni 

1335 

The Knowledge Management Context of Cloud Based  big Data Analytics  

Irina Neaga and Shaofeng Liu

1339 

Customer Capital Management in Business Intelligence  Projects: An Exploratory Study 

Lívia Vasconcelos, Florinda Matos and João Thomaz

1344 

Late Submission   Approach for Processes and Methods for The Integra‐ tion of Knowledge Transfer in Project Work 

1349  Prof. Dr.‐Ing. habil. Christian‐Andreas Schumann;  Dipl.‐Inf. Claudia Tittmann 

viii 

1351 

Preface   These proceedings represent the work of researchers presenting at the 15th European Conference on Knowledge Manage‐ ment (ECKM 2014). We are delighted to be hosting ECKM at the The Santarém School of Management and Technology ‐ Poly‐ technic Institute of Santarém, Portugal on the 4‐5 September 2014.   The conference will be opened with a keynote from Nuno Manuel C.F. Guimarães, University Institute of Lisbon, Portugal.  The second day will be opened by Rui Lança who is a consultant in the area of Team Coaching and Leadership in Portugal.  ECKM is an established platform for academics concerned with current research and for those from the wider community  involved in Knowledge Management, to present their findings and ideas to peers from the KM and associated fields. ECKM is  also a valuable opportunity for face to face interaction with colleagues from similar areas of interests. The conference has a  well‐established  history  of  helping  attendees  advance their  understanding  of  how  people,  organisations,  regions  and  even  countries  generate  and  exploit  knowledge  to  achieve  a  competitive  advantage,  and  drive  their  innovations  forward.  The  range of issues and mix of approaches followed will ensure an interesting two days.  264 abstracts were initially received for this conference. However, the academic rigor of ECKM means that, after the double  blind peer review process there are 129 academic papers, 28 PhD research papers, 1 masters research pape, and 3 Work in  Progress papers published in these Conference Proceedings.   These papers reflect the continuing interest and diversity in the field of Knowledge Management, and they represent truly  global  research  from  some  many  different  countries,  including  Algeria,  Argentina,  Australia,  Austria,  Belgium,  Bosnia  and  Herzegovina, Brasil, Canada, China, Colombia, Czech Republic, Finland, France, Genova, Germany, Hungary, Indonesia, Iran,  Israel,  Italy,  Japan,  Jordan,  Kazakhstan,  Lithuania,  Madrid,  Mexico,  ,  Morocco,  Norway,  Oman,  Poland,  Portugal,  Romania,  Russia, Russian Federation, Saudi Arabia, Slovakia, South Africa, Spain, Sweden, Switzerland, Thailand, Tunisie, Turkey, Turk‐ ish Republic of Northern Cyprus, UK, United Arab Emirates, USA.  We hope that you have an enjoyable conference.   Dr Carla Vivas and Dr Pedro Sequeira  Co‐Conference Chairs  September 2014 

ix 

Conference Committee  Conference Executive  Dr Carla Vivas, Polytechnic Institute of Santarém, Santarém, Portugal  Pedro Sequeira, Polytechnic Institute of Santarém, Santarém, Portugal  Dr Susana Leal, Polytechnic Institute of Santarém, Santarém, Portugal  Maria Barbas, Polytechnic Institute of Santarém, Santarém, Portugal    Mini track chairs  Dr. Thomas Schalow, University of Marketing and Distribution Sciences, Kobe, Japan  Assoc. Prof. Dr. Mustafa Sağsan, Near East University, Turkish Republic of Northern Cyprus  Dave Snowden, Cognitive Edge  Dr. Juan Gabriel Cegarra, Universidad Politécnica de Cartagena, Spain  Dr. Gabriel Cepeda, University of Seville, Spain  Dr Peter Heisig, Leeds University Business School, UK   Dr Florinda Matos, Polytechnic Institute of Santarém, Portugal  Dr Sandra Moffett, University of Ulster’s, Northern Ireland, UK  Dr Jan M. Pawlowski, University of Jyväskylä, Finland  Prof Aino Kianto, Lappeenranta University of Technology, Finland  Dr Radwan Kharabsheh, Hashemite University, Jordan    Committee Members  The conference programme committee consists of key individuals from countries around the world working and researching  in the Knowledge Management and IS community. The following have confirmed their participation:  Mahmoud Abdelrahman (Manchester Business School, UK); Dr. Mohd Syazwan Abdullah (Universiti Utara Malaysia, Malay‐ sia); Habib Abubakar (African Development Bank Group, Tunisia); Pichamon Adulavidhaya (Bangkok University, Thailand); Dr.  Ali  Alawneh  (Philadelphia  University,  Jordan);  Dr.  Abdallah  Al‐Shawabkeh  (University  of  Greenwich,  UK);  Prof.  Dr.  Eckhard  Ammann (Reutlingen University, Germany); Albena Antonova (Sofia University, Bulgaria); Dr. Nekane Aramburu (University  Of  Deusto,  San  Sebastian,  Spain);  Dr.  Derek  Asoh  ("Ministry  of  Government  Services,  Ontario,  Canada);  Ass  Prof.  George  Balan (Romanian‐German University, Romania); Dr Tabarak Ballal (The University of Reading, UK); Dr. Joan Ballantine (Uni‐ versity of Ulster, UK); Dr. Pierre Barbaroux (French Air Force Academy / Research Center of the French Air Force, France);  Prof. Dr. Aurelie Aurilla Bechina Arnzten (College University of Bruskerud, Norway); Prof. Julie Béliveau (University of Sher‐ brooke, Canada); Dr. David Benmahdi (Université Paris 8, France); Ass Prof. Maumita Bhattacharya (Charles Sturt University,  Albery,  Australia);  Prof.  Dr.  Markus  Bick  (ESCP  Europe  Wirtschaftshochschule  Berlin,  Germany);  Heather  Bircham‐Connolly  (University  of  Waikato,  Hamilton,  New  Zealand);  Dr.  Claudia  Bitencourt  (Universidade  do  Vale  do  Rio  dos  Sinos  ,  Brazil);  Nicole  Bittel  (Swiss  Distance  University  of  Applied  Sciences,  Switzerland);  Pavel  Bogolyubov  (Lancaster  University  Manage‐ ment  School, Dpt.  of  Management  Learning  and  Leadership,  UK);  Prof.  Karsten  Böhm  (University  of  Applied  Sciences,  Kuf‐ stein, Austria); Dr. Ettore Bolisani (University of Padua, Vicenza, Italy); Prof. Ionel Bostan (University of Iasi, Faculty of Eco‐ nomics, Romania); Prof. Constantin Bratianu (Academy of Economic Studies, Bucharest, Romania, Romania); Dr. Antonio Juan  Briones (Universidad Politécnica de Cartagena, Spain); Prof. Elisabeth Brito (University of Aveiro, ESTGA, Portugal); Dr. Sheryl  Buckley (Unisa, South Africa); Dr. Dagmar Caganova (Slovak University of Technology Faculty of Materials Science and Tech‐ nology, Slovakia); Prof. Leonor Cardoso (University of Coimbra, Portugal); Prof. Sven Carlsson (School of Economics and Man‐ agement,  Lund  University,  Sweden);  Dr.  Gabriel  Cepeda  Carrion  (Universidad  de  Sevilla,  Spain);  Dr.  Juan‐Gabriel  Cegarra‐ Navarro (Universidad Politécnica de Cartagena, Spain); Daniele Chauvel (SKEMA Business School , France); Satyadhyan Chick‐ erur (B V Bhoomaraddi College of Engineering and Technology, Hubli,, India); Ana Maria Correia (Universidade Nova de Lis‐ boa, Portugal); Dr. Bruce Cronin (University of Greenwich Business School, UK); Anikó Csepregi (University of Pannonia, De‐ partment  of  Management,  Hungary);  Roberta  Cuel  (University  Of  Trento  –  Faculty  Of  Economics,  Italy);  Prof  Marina  Dabic  (Nottingham Trent University, UK); Dr. Farhad Daneshgar (University of New South Wales, Australia); Dr. Ben Daniel (Univer‐ sity of Saskatchewan, Saskatoon, Canada); Prof. Monica De Carolis (University of Calabria, Italy); Prof. Annunziata De Felice  (University of Bari, Italy); Dr. John Deary (Independent Consultant, UK, Italy & Dubai); Dr. Paulette DeGard (The Boeing Com‐ pany,  Seattle, USA);  Dr.  Izabela  Dembinska  (University  of  Szczecin,  Poland);  Dr.  Charles  Despres  (Conservatoire  des  Arts  et  Metiers, Paris, France); Dr. Mihaela Diaconu ("Gheorghe Asachi" Technical University, Romania); Zeta Dooly (Waterford Insti‐ tute of Technology , Ireland); Dr. Yan Qing Duan (Luton Business School, University of Luton, UK); Nasser Easa (University of  Stirling, Scotland, UK); Sally Eaves (Sheffield Hallam University, UK); Prof. John Edwards (Aston Business School, UK); Dr. An‐ andasivakumar Ekambaram (SINTEF, Norway); Jamal El Den (Charles Darwin University, Australia); Dr. Steve Eldridge (Man‐ chester Business School, , UK); Isaac Enakimio (University of Greenwich/Kent and Medway Health Informatics, USA); Dr. Scott  Erickson (Ithaca University, USA); Mercy Escalante (Sao Paulo University, Brazil); Dr. Mansour Esmaeil Zaei (Panjab University,  India); Dr Iancu Eugenia (Stefan cel Mare University, Romania); Nima Fallah (University of Strasbourg, France); Dr. Doron Fa‐ ran  (Ort Braude  College,  Israel);  Dr.  Péter Fehér (Corvinus  University  of  Budapest,  Hungary);  Dr. Silvia  Florea  (Lucian  Blaga  University of Sibiu, Romania); Dr. Andras Gabor (Budapest University of Economic Sciences and Public Administration, Hun‐ gary);  Brendan  Galbraith  (University  of  Ulster,  UK);  Ass  Prof.  Balan  George  (German‐Romanian  University,  Romania);  Elli  x 

Georgiadou (Middlesex University, UK); Dr. Lilia Georgieva (Heriot‐Watt University, UK); Prof. Secundo Giustina (University of  Salento,  Italy);  Prof.  Secundo  Giustina  (University  of  Salento,  Italy);  Dr.  Andrew  Goh  (International  Management  Journals,  Singapore);  Gerald  Guan  Gan  Goh  (Multimedia  University,  Melaka,  Malaysia);  Dr  Golestan  Hashemi  Golestan  (Iranian  Re‐ search Center of Creanovatology , Innovation Science, Iran); Dr. Miguel Gonzalez‐Loureiro (University of Vigo, Spain); Dr. Lo‐ ganathan Narayansamy Govender (University of Kwazulu‐Natal, South Africa); Francesca Grippa (Scuola Superiore ISUFI, Uni‐ versity  of  Salento,  Italy);  Norbert  Gronau  (University  of  Potsdam,  Germany);  David  Gurteen  (Gurteen  Associates,  UK);  Dr.  Leila  Halawi  (Bethune  Cookman  University,  USA);  Linda  Cathrine  Hald  (NTNU,  Norway);  Dr.  Matthew  Hall  (Aston  Business  School,  UK);  Prof.  Meliha  Handzic  (International  Burch  University  ,  Bosnia  and  Herzegovina);  Dr.  Harold  Harlow  (Wingate  Univeristy,  USA);  Deogratias  Harorimana  (Southampton  Solent  University,  ,  UK);  Dr.  Mahmoud  Hassanin  (Pharos  Univer‐ sity,Alexandria, Eygpt); Dr. Liliana Hawrysz (Opole Univarsity of Technology, Poland); Prof. Igor Hawryszkiewycz (University of  Technology,  Sydney,  Australia);  Dr.  Ciara  Heavin  (University  college  cork,  UK);  Dr.  Peter  Heisig  (Leeds  University  Business  School,  UK);  Dr  Nina  Helander  (University of  Vaasa, Finland);  Remko Helms  (Universiteit  Utrecht,  The  Netherlands);  Dr.  Ali  Hessami (Vega Systems Ltd., UK); Dr. Eli Hustad (University of Agder, Norway); Fahmi Ibrahim (Glasgow Caledonian Univer‐ sity,  UK);  Dr.  Thomas  Jackson  (Loughborough  University,  UK);  Dr.  Harri  Jalonen  (Turku  University  of  Applied  Sciences,  Finland);  Prof.  Brigita  Janiunaite  (Kaunas  University  of  Tehnology,  Lithuania);  Dr.  Daniel  Jimenez  (Universidad  de  Murcia,  Spain); Prof. Palimra Juceviciene (Kaunas University of Technology , Lithuania); Prof. Robertas Jucevicius (Kaunas University of  Technology , Lithuania); Dr. Magdalena Jurczyk‐Bunkowska (Opole University of Technology, Poland); Selvi Kannan (Victoria  University, Melbourne, Australia); Dr. Silva Karkoulian (Lebanese American University Beirut Campus, Lebanon); Dr. Sarinder  Kaur Kashmir Singh (University Malaya, Malaysia); Dr. Marcela Katuščáková (University of Žilina, Slovakia); Prof. Dr. Turksel  Kaya  Bensghir  (TODAIE‐Public  Administration  Institute  for  Turkey  and  the  Middle  East,  Turkey);  Dr.  Radwan  Kharabsheh  (Hashemite  University  Jordan,  Jordan); Dr.  Prof.  Aino  Kianto  (Lappeenranta  University  of  Technology,  Finland);  Monika  Kli‐ montowicz (University of Economics in Katowice, Poland); Ute Klotz (Lucerne University of Applied Sciences and Arts, Switzer‐ land); Dr. Andrew Kok (Western Cape Government, South Africa); Ass.Prof.Dr. Jaroslava Kubatova (Palacky University, Czech  Republic); Dr. Bee Theng Lau (Swinburne University of Technology, Australia); Rongbin W.B Lee (The HongKong Polytechnic  University, Hong Kong); Prof. Dr. Franz Lehner (University of Passau, Germany); Jeanette Lemmergaard (University of South‐ ern Denmark, Denmark); Prof. Ilidio Lopes (Polythenic Institute of Santarém, Portugal); Prof. Monique Lortie (Universit du Qu  bec Montreal, Canada); Dr. Maria de Lourdes Machado‐Taylor (CIPES, Portugal); Dr. Agnes Maciocha (Institute of Art, Design,  and Technology, Ireland); Avain Mannie (Dept of Finance, Port Elizabeth, South Africa); Prof. Virginia Maracine (Academy of  Economic Studies, Bucharest, Romania); Dr. Farhi Marir (London Metropolitan University, UK); Prof. Dora Martins (ESEIG‐IPP  (Superior School of Industrial and Management Studies, Polytechnic of Porto), Portugal); Prof Antonio Martins (Universidade  Aberta, Portugal); Prof. Maurizio Massaro (Udine University, Italy); Fiona Masterson (National University of Ireland, Galway,  Ireland); Florinda Matos (ISCTE‐IUL, Lisbon, Portugal , Portugal); Prof. Jane McKenzie (Henley Business School, UK); Dr. Dalila  Mekhaldi (University of Wolverhampton, UK); Dr. Robert Mellor (Kingston University, UK); Prof. Dr. Kai Mertins (Fraunhofer‐ IPK,  Germany);  Dr.  Anabela  Mesquita  (School  of  Accounting  and  Administration  of  Porto  (ISCAP)  /  Politechnic  Institute  of  Porto (IPP), Portugal); Kostas Metaxiotis (National Technical University Athens, Greece); Dr. Antonio Leal Millan (Universidad  de Seville, Spain); Dr. Kristel Miller (Queens University, Northan Ireland); Ludmila Mladkov (University of Economics Prague,  Czech Republic); Dr. Sandra Moffett (University of Ulster, Londonderry, UK); Prof. Samuel Monteiro (University of Beira Inte‐ rior, Portugal); Dr. Mahmoud Moradi (University of Guilan, Iran); Dr. Arturo Mora‐Soto (Carlos III University of Madrid, Ma‐ drid);  Prof.  Oliver  Moravcik  (Slovak  University  of  Technology,  Slovakia);  Prof.  Mieczysaw  Morawski  (Wroclaw  University  of  Economics, Faculty of Economics, Management and Tourism, Poland); Aboubakr Moteleb (B2E Consulting, UK); Dr. Mary Mu‐ henda  (Uganda  Management  Institute,  Uganda);  Aroop  Mukherjee  (King  Saud  University,  Saudi  Arabia);  Dr.  Birasnav  Mut‐ huraj (New York Institute of Technology, Bahrain); Arash Najmaei (MGSM, Australia); Dr. Elena Irina Neaga (School of Man‐ agement (Plymouth Business School) Plymouth University, UK); Dr. Gaby Neumann (Technical University of Applied Sciences  Wildau, Germany); Dr. Emanuela Alia Nica (Center for Ethics and Health Policy (CEPS) and University "Petre Andrei" Iasi, Ro‐ mania); Dr. Cristina Niculescu (Research Institute for Artificial Intelligence of the Romanian Academy, Romania); Klaus North  (FH Wiesbaden, Austria); Dr Nora OBERMAYER‐KOVACS (UNIVERSITY OF PANNONIA/FACULTY OF ECONOMICS, Hungary); Dr.  Jamie  O'Brien  (St.  Norbert  College,  USA);  David  O'Donnell  (Intellectual  Capital  Research  Institute  of  Ireland,  Ireland);  Gary  Oliver (University of Sydney, Australia); Dr. Ivona Orzea (Academy of Economic Studies, Romania); Dr. Kaushik Pandya (Shef‐ field Business School, City Campus, UK); Dr. Paul Parboteeah (Loughborough University, UK); Dr. Dan Paulin (Chalmers Uni‐ versity  of  Technology,  Sweden);  Jan  Pawlowski  (University  of  Jyväskylä,  Austria);  Dr.  Corina  Pelau  (Academy  of  Economic  Studies, Bucharest, Romania); Monika Petraite (New York Institute of Technology, Lithuania); Rajiv Phougat (IBM, USA); Prof.  Paulo  Pinheiro  (Universidade  da  Beira  Interior,  Portugal);  Prof.  Mário  Pinto  (Polytechnic  Institute  of  Porto,  Portugal);  Prof.  Selwyn Piramuthu (University of Florida, Gainesville, USA); Dr. Gerald Polesky (IBM. 11425 N. Bancroft Dr, Phoenix, USA); Dr.  John  Politis  (Charles  Darwin  University,  Australia);  Dr.  Nataša  Pomazalová  (FRDIS  MENDELU  in  Brno,  Czech  Republic);  Dr.  Stavros Ponis (National Technical University Athens, Greece); Prof. Asta Pundzienė (Kaunas University of Technology , Lithua‐ nia);  Dr.  Devendra  Punia  (University  of  Petroleum  &  Energy  Studies,  India);  Dr.  Gillian  Ragsdell  (Loughborough  University,  UK); Dr. Lila Rajabion (Penn State University, Mont Alto , USA); Prof. Thurasamy Ramayah (Universiti Sains Malaysia, Malay‐ sia); Dr. M S Rawat (DCAC, University of Delhi, India); Prof. Dr. Ulrich Reimer (University of Applied Science St. Gallen, Switzer‐ land); Dr. Marcin Relich (University of Zielona Gora, Poland); Gerold Riempp (EBS,Germany, Germany); Eduardo Rodriguez (IQ  Analytics, Ottawa, Canada); Dr. Inès Saad (Amiens School of Management , France); Dr. Josune Sáenz (University of Deusto,  San Sebastián, Spain); Prof. Lili Saghafi (Canadian International College, Egypt); Mustafa Sagsan (Near East University, Nicosia,  Northern Cyprus, CYPRUS); Prof. Svetlana Sajeva (Kaunas University of Technology, Lithuania, Lithuania); Dr. Kalsom Salleh  xi 

(Faculty  of  Accountancy,  University  Technology  MARA,  Malaysia);  Dr.  María‐Isabel  Sanchez‐Segura  (Carlos  III  University  of  Madrid, Spain); Dr. Antonio Sandu (Mihail Kogalniceanu University, Romania); Prof. Helena Santos‐rodrigues (IPVC, portugal);  Prof. Dan Savescu (Transilvania University of Brasov, Romania); Dr. Ousanee Sawagvudcharee (Centre for the Creation of Co‐ herent Change and Knowedge, Liverpool John Moores University, Thailand); Dr. Golestan Hashemi Sayed Mahdi (Iranian Re‐ search Center for Creanovatology , TRIZ & Innovation Science, Iran); Enrico Scarso (Università Degli Studi Di Padova, Italy); Dr.  Thomas Schalow (University of Marketing and Distribution Sciences, Japan); Dr. Christian‐Andreas Schumann (University of  Zwickau, Germany); Prof. Jurgita Sekliuckiene (Kaunas University of Technology , Lithuania); Dr. Maria Th. Semmelrock‐Picej  (Alpen‐Adria Universität Klagenfurt, Austria); Amani Shajera (University of Bahrain, Bahrain); Dr. Mehdi Shami Zanjani (Uni‐ versity of Tehran, Iran); Peter Sharp (Regent’s College, London , UK); Dr. Michael Shoukat (UMUC, USA); Dr. Evangelia Siachou  (Hellenic  American  University  ,  USA);  Dr.  Kerstin  Siakas  (Alexander  Technological  Educational  Institute  of  Thessaloniki,  Greece);  Prof.  Umesh  Kumar  Singh  (Vikram  University,  Ujjain,  India);  Dave  Snowden  (Cognitive  Edge,  Singapore);  Dr.  Siva  Sockalingam (Glasgow School for Business and Society, UK, UK); Prof. Dr. Marta‐Christina Suciu (Academy of Economic Stud‐ ies Bucharest, Romania); Christine Nya‐Ling Tan (Multimedia University, Melaka, Malaysia); Dr. Llewellyn Tang (University of  Nottingham Ningbo , China); Ass.Prof.Dr. Gintare Tautkeviciene (Kaunas University of Technology , Lithuania); Dr. Sara Ted‐ mori  (Princess  Sumaya  University  for  Technology,  UK);  Dr.  Eduardo  Tomé  (Universidade  Europeia,  Lisbon.  ,  Lisbon);  Dr.  Zuzana Tuckova (Tomas Bata University in Zlín, Czech Republic); Prof. Alexandru Tugui (Alexandru Ioan Cuza University, Ro‐ mania); Geoff Turner (University of Nicosia, Cyprus); Dr. Anna Ujwary‐Gil (Wyzsza Szkola Biznesu‐National‐Louis University,  Poland);  Andras  Vajkai  (University  of  Pécs,  Hungary);  Dr.  Changiz  Valmohammadi  (Islamic  Azad  University‐South  Tehran  Branch, Iran); Dr. Christine van Winkelen (Henley Business School, University of Reading, UK); Dr Murale Venugopalan (Am‐ rita  School  of  Business,Amrita  Vishwa  Vidyapeetham  University,  India);  Prof.  Jose  Maria  Viedma  (Polytechnic  University  of  Catalonia, Spain); John Walton (Sheffield Hallam University, UK); Maria Weir (Independent Consultant, Italy); Christine Welch  (University of Portsmouth, UK); Florian Welter (IMA/ZLW & IfU ‐ RWTH Aachen University, Germany); Anthony Wensley (Uni‐ versity of Toronto, Toronto, Canada, Canada); Dr. Sieglinde Weyringer (University of Salzburg, Austria); Roy Williams (Univer‐ sity  of  Portsmouth,  UK);  Dr. Lugkana Worasinchai (Bangkok  University, Thailand,  Thailand);  Prof.  Les  Worrall (University  of  Coventry, UK); Dr. Mohammad Hossein Yarmohammadian (Health Management and economic research Center, Isfahan Uni‐ versity of Medical Sciences, Iran); Prof. Qinglong Zhan (Tianjin University of Technology and Education, China); Dr. Malgorzata  Zieba (Gdansk University of Technology, Poland); 

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Biographies  Conference Co‐Chairs  Dr Carla Vivas is an Assistant Professor at the School of Management and Technology (Polytechnic  Institute of Santarém) where she teaches Management, Operations Management, Logistics and Stra‐ tegic M anagement. She has a PhD in Management.  Her main research interest areas include: Stra‐ tegic Management, innovation and internationalization strategies in SMEs.    Pedro Sequeira is Director of the Research Unit of the Polytechnic Institute of Santarém; General Secre‐ tary  of  European  Network  of  Sport  Science,  Education  &  Employ  ment  (ENSEE);  Professor  at  Sport  Sci‐ ences School of Rio Maior – Polytechnic Institute of Santarém.   

Programme Co‐Chairs  Dr Susana Leal is Assistant Professor at the Polytechnic Institute of Santarém, Portugal. She  PhD from University of Coimbra, Portugal, and has articles published in Journal of Business  The International Journal of Hum an Resource Management, and Creativity Research Journal.  search deals with Organizational Behavior and Corporate Social Responsibility 

has  a  Ethics,  His  re‐

Maria  Barbas  is  a  teacher  in  Polytechnic  Institute  of  Santarém  and  invited  teacher  in  Universidade  Aberta.  Coordinates  teams  in  elearning;  examiner  jury  for  the  defense  of  monographs;  UIIPS  member,  effective researcher at the Center for Research and Teaching Technology in Training of Trainers (Univer‐ sity  of  Aveiro)  and  contributing  member  of  the  Center  for  Advanced  Studies  in  Management  and  Eco‐ nomics (CEFAGE‐University of Évora); guest member of editorial writing in International Symposiums and  Journals;  scholarship  Postdoctoral,  winner  of  National  and  International  Awards;  executor  of  copyright  registration; participant in the program Lifelong Learning; reviewer in journals and national and interna‐ tional conferences. Guidance of Master, doctoral and post‐doctoral theses. 

Keynote Speakers  Nuno  Guimarães  graduated  in  Electrotechnical  Engineering  at  the  Technical  University  of  Lisbon  (IST/UTL), Portugal (1983), where he also completed his MsC (1987) and PhD (1992) in Electrotechnical  and Computer Engineering. Nuno Guimarães is currently (2014) Full Professor (Professor Catedrático)  at ISCTE‐IUL ‐Instituto Universitário de Lisboa, Portugal. From June 2012 to March 2014, he was Pro‐ Rector for International Issues of ISCTE‐IUL and since March 2014 he has been Pro‐Rector for Interna‐ tionalisation and E‐Learning of ISCTE‐IUL. Nuno has extensive evaluation experience with a number of  programmes, including EU Telematics Programme, Education & Training, PRATIC/INETI – National Pro‐ gramme  AdI,  EU  ESPRIT  Programme,  FCT  Programmes,  Key  Area  Multimedia  Tools  and  Applications  (KA3),  EU  IST  Pro‐ gramme, POSI‐2.2 National Programme, AdI Networks of Excellence and EU FP7 Expert).   Rui Lança is a Consultant and Trainer in Coaching, Leadership and Team Coaching for companies from a  number of different industries as well as for the University sector. He holds a Postgraduate Diploma in  Leadership and People Management from INA  and he has an Executive Master degree from the Un.  Catholic  and  EGE  in  Audit  Management  as  well  as  a  Master  in  Sports  Management  and  a  degree  in  Sports Science, both from FMH – UTL. Rui was a Trainer and Facilitator at the European Council 2002‐ 2008 and is author of several books including  'How to form teams of high performance‘ and ‘Coach to  Coach’, both in Portuguese. His areas of expertise include Organizational and Team Coaching, Leader‐ ship, Facilitation and Team Dynamics, Communication Impact and Interpersonal Relations.          xiii 

Mini Track Chairs  Dr Juan Gabriel Cegarra‐Navarro is associate professor of the Business Administration Department of  the Universidad Politécnica de Cartagena (Spain). He has been a visitin g professor at the University of  Manchester and at the University of Hull in the UK.     Dr Peter Heisig is founder and coordinator of the Global Knowledge Research Network including 30+ p  artners worldwide. He has been working in KM since 1989 and his research interest is around the crea‐ tion and use of knowledge in organisations and society. After leading the Fraunhofer KM Competence  Centre for a decade, he worked with Cambridge University and is currently a Senior Research Fellow at  Leeds University Business School.     Dr. Radwan A. Kharabsheh is a lecturer in international business and the assistant dean, international  affairs  at  the  Hashemite  University  in  Jor  dan.  His  research  interests  include  organizational  learning,  knowledge management and international joint ventures. He is member of ANZIBA and ANZMAC and  the Sydney University Centre for Peace Studies and Conflict Resolution.     Aino Kianto, D.Sc. (Econ. & Bus. Adm.) is a Professor at the School of Business at Lappeenranta Univer‐ sity of Technology, and the Academic Director of Master’s Program in Knowledge Man agement. Her  main research interests are in the areas of knowledge management, intellectual capital and innovation.    Florinda Matos PhD Social Sciences, Organizational Behavior Studies,  Technical University of Lisbon.  Masters  Degree  in  Business  Sciences,    ISCTE‐IUL  Business  School;  Engineering  Degree  in  Agricultural  Engineering  &  Licentiate  Degree  in  Management  of  Agricultural  Business,  Po  lytechnic  Institute  of  Santarém.  Lectures  and  is  a  business  consultant.  Researches    Knowledge  Management,  Intellectual  Capital, Business Strategy, Marketing, Organizational Behavior, Innovation and Entrepreneurship. Pres‐ ident of ICAA ( Intellectual Capital Accreditation Association) www.icaa.pt  Dr Sandra Moffett Senior Lecturer of Computer Science with University of Ulster’s School of Computing  and Intelligent Systems, Magee Campus. Core member of Business and Management Research Institute.   Expertise on Knowledge Management contributes to her being one of UK leading aut hors in this field.   Received  a  number  of  research  awards  and  citations  for  her  work.    External  funding  has  enabled  Dr  Moffett  to  undertake  extensive  quantitative/qualitative  research  to  benchmark  KM  implementation  within UK companies.      

Biographies of Presenting Authors   Rute Abreu is an Accounting and Finance Professor at the Instituto Politécnico da Guarda, Portugal. She received her PhD  Degree in Accounting and Finance from the Universidad de Salamanca, Spain (2009). She researches on social responsibility,  accounting  and  finance.  She  publishes  several  papers  and  participates,  all  over  the  world,  frequently  in  conferences  and  meetings.  Rigel Adiratna, graduated from Faculty of Humanities, Bina Nusantara University, Jakarta, majored in Psychology. In 2014,  she  attended 2  months  Overseas  Studies  Program  (English  literature)  at  Oxford.  Working  experience:  Intern  at  Indonesian  Child Protection Commission, Talent Development officer (intern) at United Tractors, and Therapist at Yayasan Baik, Indone‐ sia.   Ghosia Ahmed is a PhD student in the School of Business and Economics at Loughborough University.  Her research draws  attention  to  the  largely  unexplored  area  of  ‘knowledge  security’  to  explore  whether  a  conflict  exists  between  knowledge  sharing and information security practices, and, the subsequent implications of this on knowledge sharing.  

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Kamla Ali Al‐Busaidi is an Associate Professor of Information Systems at Sultan Qaboos University in Oman. She received her  Ph.D. in Management Information Systems from Claremont Graduate University in California. Her research interests include  knowledge management systems and learning management systems. She has published articles in several international con‐ ference proceedings, book chapters, and journals.  Asma Al‐Harthy is a student at the college of economics and Political Science at Sultan Qaboos University in Oman.  She ma‐ jored in finance with a minor in information systems. Her research interests include the utilization of information technolo‐ gies to improve decision making in the finance field. Ghitha Al‐Kalbani is a student at the college of Economics and Political Sciences at Sultan Qaboos University in Oman. She  majored  in  information  systems.  Her  research  interests  include  knowledge  management,  social  learning  and  social  intelli‐ gence.  Xiaomi An, is a professor of records and knowledge management at School of Information Resources Management, Renmin  University of China (RUC). She is leader of Knowledge Management Team at Key Laboratory of Data Engineering and Knowl‐ edge Engineering, Ministry of Education at RUC. She has chaired 30 projects, published 16 books and 195 academic papers.  Roberta Antonelli is PhD student at University of Cassino and Southern Lazio.  Ivett María Aportela Rodríguez Bachelor’s Degree in Library and Information Science and Master’s Degree in Communication  from the Universidad de la Habana (Cuba). Now she is Assistant Professor and Doctoral candidate in the Library and Informa‐ tion Science Department at Universidad Carlos III de Madrid (Spain). She worked as an information specialist and manager at  an Information Consultancy in Cuba.  Nekane Aramburu is PhD in Economics and Business Administration and Director of the Strategy and Information Systems  department in Deusto Business School (University of Deusto, Spain), where she is also the Academic Director of the Advanced  Health Management Programme. Her research is focused on the fields of: Strategic Management, Knowledge Management,  Organizational Learning, and Innovation.  Pierre‐Emmanuel Arduin is a postdoctoral researcher funded by the Laboratory of Excellence Control of Technological Sys‐ tems  of  Systems  (Labex  MS2T),  he  is  also  lecturer  at  Paris‐Dauphine  University,  KM  and  IT  consultant  within  several  large  companies. He studied Psychology, Computer Science and Management, and now focuses on Knowledge Management, link‐ ing knowledge with individual interpretation processes.  Zenona Atkočiūnienė  Academic  degree ‐   Prof.  Dr. (HP) (Communication and  Information Science) Employment ‐ Commu‐ nication faculty of Vilnius University. Position ‐ Head of the Information and communication Institute  Research  interests  –    Knowledge  management ; Creative industries ; Creativity and Innovation;  Knowledge management practices  from a cross‐ cultural perspective; Science communication.  Urszula  Bakowska‐Morawska,  born:  26.09.1976;  place:  Kalisz  Town,  Poland;    scientific  discipline:  management  science;  workplace:  Wroclaw  University  of  Economics;position:  Associate Professor since  2006;  number of publications: 40, in this book: 1; research in the field: strategic management in tourism sector, aspect cooperation in tourism, supply chain in tourism problems, non-work interests: travel, healthy life. Shahnaz Bashir is a Doctoral researcher in the School of Computing, University of the West of Scotland, UK.  She obtain M.Ed  in Teaching and Learned Higher education and Curriculum Development  from AIOU Islamabad, B.Ed from university of Pe‐ shawar,  MA  Urdu  from  University  of  Peshawar,  Diploma  in  Computer  from  Khan  Academy  and  Certificate  in  teaching (CT)  from AIOU Islamabad.  Her research interests include Societal Culture, Knowledge Management, Knowledge Sharing and Vir‐ tual Communities. Her contributes to computing school conferences, seminars and publishes in school journals.    Fabio  Ferreira  Batista,  PhD    is  a  Senior  Researcher  at  Institute  of  Applied  Economic  Research  (Ipea)  and  professor  of  Knowledge  Management  at  Catholic  University  in  Brasilia,  Brazil.  He  is  the  author  of  the  book  Knowledge  Management  Framework  for  Brazilian  Public  Administration  (2012)  and  has  conducted  research  about  KM  in  the  public  sector  in  Brazil  since 2003.  Denise Bedford is currently the Goodyear Professor of Knowledge Management at Kent State University and is adjunct fac‐ ulty at Georgetown University’s Communication Culture and Technology program.   She teaches a range of course s in knowl‐ edge management and enterprise architecture.  Her current research interests include communities of practice, use of se‐ mantic  analysis  methods  and  technologies,  knowledge  economy,  knowledge  cities,  intellectual  capital  and  communities  of  practice.   

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Iskhar belkacem, has a General Education Diplomain electric engineering. Engineer in computer sciences, option: advanced  information  systems.  Master’s  degree  in  computer  sciences,  option:  knowledge  and  information  systems.  PhD  student  at  high  school  on  computer  sciences,  Algiers,  Algeria.  Computer  teacher  at  preparatory  school  on  economic  and  commercial  sciences and management sciences, Constantine, Algeria.  “Learning processus design from enterprise’s business”, STIC 2011  conference Tébessa, Algeria.  “The Capitalization of Enterprises' Business in an E‐learning Context,” ICELW 2011, New York.  Nicole Bittel holds a master of arts from the University of Zurich in pedagogy with a thesis on storytelling. Currently she is a  research associate at FFHS, where she is project leader in e‐Collaboration, focusing on applying storytelling to learning and  knowledge management.   Madeleine Block, PhD is a lecturer at the Faculty of Sociology at the Saint‐Petersburg State University in Russia. Her main  field  of  interest  is  knowledge  management;  her  current  research  is  related  to  the  issues  of  understanding,  evaluating  and  optimising knowledge sharing within organisations.   Pavel Bogolyubov is a Management and Business Development Fellow at Lancaster University Management School, UK. He  gained his first degree in Physics at Herzen University in St. Petersburg, Russia, and an MBA from Bradford School of Man‐ agement, UK. Prior to returning to academia, he spent ten years working in various Continuous Improvement roles in FMCG  multinationals across Europe.  His research interests are centred around “softer” aspects of Web 2.0 and its role in KM.  Ettore Bolisani is Associate Professor at the University of Padua. He was Research Associate at Manchester University, visit‐ ing scholar at Coventry University, visiting lecturer at Kaunas Technological University. He authored papers on communities  of practice, knowledge protection, KIBS, knowledge measurement. He was Chair of ECKM 2009. He is first president of the  International  Association  for  Knowledge  Management,  and  co‐editor  (with  Meliha  Handzic)  of  the  Book  Series  on  “Knowl‐ edge Management and Organisational Learning” (Springer).  Matteo Bonifacio is Assistant Professor in Organizational Sciences and Research and Innovation Policy at the University of  Trento. He was a member of the group of Policy Advisers to the President of the European Commission (BEPA) on research,  higher education and innovation where he co‐authored the EC report on Social Innovation  Elisabeth  Brito  Doctorate  in  Psychology  (area  of  expertise  in  Organizational  Psychology).  Professor  at  the  Águeda  Higher  School  of  Technology  and  Management,  University  of  Aveiro,  also  coordinating  the  degree  of  Quality  Management.  Knowledge management, quality management services and client satisfaction are her main research interests. Author of var‐ ious book chapters and scientific papers.   Sheryl Buckley is an Associate Professor in the School of Computing at the University of South Africa.  Her interests are In‐ formation Science, e‐learning, business intelligence and communities of practice.  She is committee member of a number of  international and local organizations and an active peer reviewer.  I have presented and published papers locally and interna‐ tionally.  Barry Byrne is a serving officer in the Irish Defence Forces.  He is also an adjunct assistant professor in the Computer Science  Department of Trinity College Dublin.  Barry is leading an enterprise‐wide project developing policies, procedures and tech‐ nological solutions to improve Knowledge Management.  Barry presented at ECKM 2013 and is delighted to be back this year.  Maria Do Rosario Cabrita holds a PhD and is Assistant Professor and researcher at the Universidade Nova de Lisboa, Portu‐ gal, and teaches at the Portuguese Banking Management School in Lisbon. She has several years of experience in executive  positions in international banks. Her current field of research is focused on intellectual capital, knowledge management and  measuring intangibles.  Jaime Campos is an Associate Professor at the department of Informatics, Linnaeus University, Sweden. His main research  interest includes the application of Knowledge Management Systems, Information and Communication Technologies espe‐ cially Web technologies as the Semantic web and Web 2.0, Agent and Mobile technologies for the Industrial domain.  Andrea Cappilli, graduated in 2012 from University of Salento (Italy) in Management Engineering. Since 2013 he is involved  in a 2‐year industrial training program aimed to develop Entrepreneurial Innovators capable to design and orchestrate tech‐ nology entrepreneurship ecosystems within territories and companies. The program is led by the Apulian Technological Dis‐ trict DHITECH, in collaboration with universities and Industrial partners.  Antonio  José  Carrasco‐Hernandez  is  a  Professor  of  management  at  the  University  of  Murcia  (Spain).  His  current  research  focuses on the relationships among innovation, human resource management and family firms. He has recently published in  Family Business Review, Management Research and The Electronic Journal of Knowledge Management. 

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Cristina Castro is a PhD Student at University of Coimbra. Master in Work, Organizational and Personnel Psychology at Uni‐ versity of Coimbra and at University of Barcelona, granted with a WOP‐P Master Scholarship for 2007‐2009. Learning & Qual‐ ity  Manager  in  a  worldwide  Financial  Company,  responsible  for  knowledge  management,  training  and  performance  en‐ hancement in Service Areas. Knowledge management is her main research interest.   Behiye Tüzel Çavuşoğlu In 2004 Çavuşoğlu started her professional career at Near East University Department of Economics  as  a  lecturer. Since 2013  she  has  been continuing her  career  also  with  vice  chairman.She has  many  published articles  and  conference proceedings.Çavuşoğlu also acting as a member of board at Knowledge Management Research Center.   Hui Chen is a PhD candidate at School of Business and Economics, Loughborough University. She holds an MSc in Information  Management from University of Sheffield and a BSc from Renmin University of China. Her main research interests are: Identi‐ fication and Classification of Shareable Tacit Knowledge Associated to Experience, Knowledge Sharing, Knowledge Manage‐ ment and Records Management.  Koteshwar  Chirumalla  is  postdoc  researcher  at  the Division  of  Design and Visualisation  at Mälardalen  University,  Sweden.  He received  his  Ph.D.  in  the  area  of  Product  Innovation, with  a  focus  on  lessons  learned  practice.  His research  is  focused  on the development of new knowledge management methods and tools to support the early stages of product innovation  projects.  Dr Agnieszka Chlon‐Dominczak is an Assistant Professor at Warsaw School of Economics and Educational Research Institute.  Previously a Deputy Minister in the Ministry of Labour and Social Policy. Co‐author of the pension reform in Poland intro‐ duced  in 1999. Consultant of World Bank, ILO and the OECD. Researcher and author of publications in demography, pen‐ sions, labour markets  and education.   Rozina Chohan is a PhD student based at Lancashire Business School, UCLan, Preston, United Kingdom. She is also based at  Department  of  Computer  Science  Shah  Abdul  Latif  University,  Khairpur,  Pakistan.  Her  background  is  BSc.  in  Computer  Sci‐ ence,  MSc.  in  IT  Service  Management.  Rozina  Chohan  is  a  corresponding  author  and  can  be  contacted  at:  RCho‐ [email protected]  Stephanie Conn graduated from the University of Ulster with a Bachelor of Science in Creative Computing and is currently  undertaking  a  MSc  in  Professional  Practice  whilst  in  employment  by  the  University  of  Ulster  under  a  Knowledge  Transfer  Partnership project. The knowledge‐base company is Mervyn Stewart Ltd, Belfast, the two year project is focused on Knowl‐ edge Management in the Motor Retail Industry.   Ricardo V. Costa is a lecturer at Maia University Institute – ISMAI, where he coordinates the Business Management Course  (first cycle), and a researcher at UNICES. He graduated in Economics at Universidade do Porto, and received is Phd in Business  Management from Universidade de Vigo, in Spain. He got an Executive MBA in Business Strategy from Escuela de Negocios  Caixanova, in Vigo, and attended the “Program in International Management” at Georgetown University in Washington. His  main research interests are intellectual capital, product innovation and corporate finance.  Vitor Costa I hold a master degree in work and organizational psychology from University of Beira Interior, Covilhã, Portugal.  Presently, I’m a work and organizational psychology Ph. D. candidate at University of Beira Interior. My research interests are  knowledge management, absorptive capacity, strategic human resources management and innovation.   Carla Curado is a tenured Assistant Professor of Organizational Behavior and Human Resources Management at ISEG, Eco‐ nomics and Business School at Universidade de Lisboa. She received her PhD in management from the Technical University of  Lisbon. She currently teaches postgraduate, master and doctoral programs related to strategy and organizational behavior  Brit‐Eli  Danielsen.  Training  manager  of  N‐USOC  (Norwegian  User  Support  and  Operations  Centre),  NTNU  Social  Research,  CIRiS. Rune Kristiansen Valle. Master student in psychology, NTNU  Boštjan Delak, Ph.D, CISA, CIS, is a senior consultant at ITAD, Technology Park, Ljubljana, Slovenia. From 2008 he conducted  more than 60 IS audits and from 1998 he delivered more than 70 IS due diligences in 15 countries across Central and Eastern  Europe. His research interest is IS due diligence.  Souad Demigha is a Doctor in Computer Science from the University of Paris1 Sorbonne (Paris). She is a researcher at CRI  (Centre de Recherche en Informatique) at the Sorbonne University and Lecturer at the University of Paris XI (Orsay). Her Re‐ search field deals with : information systems, medical imaging, elearning systems, artificial intelligence (case‐based reason‐ ing), knowledge‐ based systems, knowledge management and data warehousing systems. She is the author or co‐author of  21 international scientific papers. 

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Sally Eaves is a committed ‘practitioner‐researcher’, spanning IT Service Management positions within the Communications  Sector alongside academic roles, primarily with Sheffield Hallam University. Affording a particular interest in methodological  innovation, knowledge management and entrepreneurial innovation, she is a reviewer for titles such as JMMR and active in  professional bodies, notably The British Academy of Management.   Anandasivakumar Ekambaram (Siva) works as a research scientist at SINTEF – Technology and Society, Industrial Manage‐ ment  Department,  Trondheim,  Norway.  He  obtained  his  doctoral  degree,  which  focuses  on  project  management  and  knowledge transfer in organizations, from the Norwegian University of Science and Technology (NTNU). Besides his research  work, he is involved in teaching activities at NTNU.  Martina Ergan is a part‐time student in Master in Business Administration at Buskerud and Vestfold University College, Nor‐ way. She is also a fulltime employee and a student adviser at Hedmark University College, Norway. Her master thesis is about  participation in Virtual Communities of Practice established in Norwegian organizations.  Leif Estensen works as a senior advisor at SINTEF – Technology and Society, Industrial Management Department, Trondheim,  Norway. He has a master's degree in Mechanical Engineering from Norwegian University of Science and Technology (NTNU).   He  has  more  than  20  years  of  experience  as  a  researcher  and  a  competence  broker  in  regional  development  initiatives  in  Norway.    Nina Evans is Associate Head of the School of IT and Mathematical Science (ITMS) at the University of South Australia. She  holds tertiary qualifications in Chemical Engineering, Education and Computer Science, a Masters in IT, an MBA and a PhD.  She teaches Knowledge Management and ICT Leadership on Masters’ and Doctorate level. Her research interests focuses on  Knowledge  Management,  Business‐IT  fusion,  ICT  Education  and  Information  Asset  Management.  She  has  published  in  nu‐ merous international journals and conferences.   Doron Faran (PhD) is a lecturer in ORT Braude College in Karmiel, Israel. His areas of interest include organizational learning,  epistemology and methodology. Besides his academic duties he leads the College's strategic thinking and advises the presi‐ dent.  Vitor Hugo Ferreira has received his PhD from Lisbon University (ISEG) in Innovation. He is associate professor at Polytechnic  Institute of Leiria and a Business Consultant. He is author of scientific published works, chair at GBATA and reviewer in differ‐ ent journals. He is executive director at the D.Dinis Business School and was coordinator of the MSc in Management Control.  Elisa Figueiredo is Professor at the Department of Management and Economics of the School of Technology and Manage‐ ment at Guarda Polytechnic Institute, Guarda, Portugal, PhD in Organizational Psychology. Consultant and trainer in human  resource management and organizational behavior. Her research interests are focused on knowledge management and hu‐ man resource management.  Charles Gagné is a Knowledge Transfer Advisor at IRSST’s Knowledge Transfer and Partner Relations Department. The KTPR  mandate consists of ensuring the use of research results and their diffusion to partners and stakeholders involved in the pre‐ vention of occupational accidents.  Ernesto Galvis‐Lista  is an Associate Professor in Engineering Faculty at the Universidad del Magdalena in Santa Marta – Co‐ lombia since 2007.  Also he is a PhD student at Universidad Nacional de Colombia in Bogotá. Galvis completed his undergrad‐ uate and master studies at Universidad Industrial de Santander. His research interests lie in the area of Software Engineering  Processes and Knowledge Management.  Johan Garcia is an Associate Professor of Computer Science at Karlstad University in Sweden. His research interest span com‐ puter aided reasoning support, computer networking and computer forensics, and he has published extensively within these  topics. Dr Garcia has participated in several European Union and National projects as a project coordinator, work‐package co‐ leader and project participant.  Sahar Ghrab is a PhD student in the MIS (Modelling, Information  & System) laboratory (Amiens‐France) and in the MIRACL  (Multimedia, InfoRmation Systems and Advanced Computing Laboratory) laboratory (Sfax Tunisia).  Apostolos Giannakopoulos (Paul) is an Academic Support Coordinator at Unisa, South Africa, managing the tutoring system.  He graduated in 2012 with a PhD in Mathematics Education. He taught for 10 years in Colleges and 22 years at the Universi‐ ties Mathematics and computers. Problem solving in general and graduation rates are his specialization.   Raquel Gimenez is a PhD student in the Department of Management of Tecnun, Engineering School (University of Navarra) in  San Sebastian, Spain. She obtained her Industrial Management Engineering Graduate class (2013) from Tecnun. She has par‐ xviii 

ticipated in the ELITE European research project. Her research fields are emergency management, communities of practice  and wiki technology.   Ingrida Griniene is a PhD student and a lecturer of Information and Communication at the Faculty of Communication of Vil‐ nius  University,  Vilnius,  Lithuania.  Her  research  interests  and  publications  are  in  information  management,  organizational  learning, human resource management, knowledge management and innovation. Scientific experience: participation in the  international and national projects.  Maria Luminita Gogan received the M.Sc. in Accountancy and IT Management (2009), the B.Sc. in Accounting Management,  Expertise and Audit (2011) and currently she is PhD student, also at the University "Politehnica" of Timisoara ‐ Romania. Her  PhD thesis is concern with researches in the field of intellectual capital in order to identify key elements for increasing com‐ petitiveness. Some of her research results have been published in proceedings of international scientific conferences.  Meliha  Handzic  is  Professor  of  Management  and  Information  Systems  at  the  International  Burch  University,  Sarajevo  and  Suleyman Sah University, Istanbul. Her PhD is from the University of New South Wales, Sydney. Meliha’s main research inter‐ ests lie in the areas of knowledge management and decision support. She has published extensively on these topics in leading  journals.   Dr. Harold Harlow’s research interests include developing measures of intellectual capital and tacit knowledge. Doctoral de‐ gree (DBA) in strategic management from Alliant International University (San Diego, California); MBA in Finance from Xavier  University  (Cincinnati,  OH);  undergraduate  degree  in  mechanical  engineering  technology  (BT.)  from  University  of  Dayton.  Industry  experience  includes  executive  positions  as  vice  president,  director,  CEO  and  senior  manager  at  IBM  and  Novatel,  QUALCOMM, Air Weigh and Rockwell Collins Aviation respectively.     Dr Peter Heisig is founder and coordinator of the Global Knowledge Research Network including 30+ partners worldwide. He  has been working in KM since 1989 and his research interest is around the creation and use of knowledge in organisations  and society. After leading the Fraunhofer KM Competence Centre for a decade, he worked with Cambridge University and is  currently a Senior Research Fellow at Leeds University Business School.   Ilona Heldal is a Professor in Informatics (focus: Interactive Systems) and a Program Director for the Indistrial PhD Program in  Applied  Informatics,  ApplyIT.  Her  main  research  interest  is  collaboration  and  interaction  in  virtual  environments  and  how  visualizations support collaboration. She also is interested in initiating collaboration and cooperation projects.  Inge Hermanrud (PhD) is an Associate Professor at Hedmark University College, Norway. Inge teaches courses in human re‐ source management. His published work appears in journals like Informing Science, Journal of Cases in Information Technol‐ ogy and Nordic Journal of Social research. His research focuses on knowledge sharing across dispersed employees in public  organizations.   Eli Hustad is an Associate Professor at the University of Agder in Kristiansand, Norway. She holds a Ph.D. from the University  of Oslo. Her research and teaching focus on enterprise‐wide information systems, knowledge networking, KM 2.0 and utiliza‐ tion of social media in businesses.   Henri Inkinen, M.Sc. (Econ. & Bus. Adm.) is a Doctoral Student at the Technology Business Research Center (TBRC) at Lap‐ peenranta  University  of  Technology.  His  research  interests  are  in  the  areas  of  intellectual  capital  and  knowledge  manage‐ ment practices. He has been involved with these issues through his work experience within knowledge‐intensive industries.  Mahsa Jahantab is  a PhD  student  doing  Knowledge  Management  research  at  the  Faculty  of  Engineering and  Computing  of  Coventry University, UK. She has completed an MSc in Engineering Project Management at Coventry University in 2010 and a  BSc in Electrical Engineering at American University in Dubai in 2008.   Dr Daniel Jiménez Jiménez Associate profession, Management and Finance Department, University of Murcia,Spain. Resear‐ ches  innovation,knowledge  management,  absorptive  capacity,  human  resources  and  organizational  learning.    Published  in  many  journals  and  participated  in  various  research  projects  related  to  organizational  cultura,  innovation  and  information  technologies.  Vice Deam of School of Labour and Employment Relations at the University of Murcia.  Palmira Juceviciene – Ph. D., Habil. Dr., full professor at Kaunas University of Technology. Research interests – individual and  organizational  learning,  knowledge  creation  and  management,  learning  organizations  and  regions,  human  resource  devel‐ opment, higher education. Dr. Juceviciene has published more than 200 scholarly articles and 10 books. Consultant in indi‐ vidual and organizational learning, learning organizations and regions, human resource development. 

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Rita Juceviciene holds a PhD degree in Management and is Senior Lecturer at Kaunas University of Technology (Lithuania).  Her research interests cover various aspects of inter‐organizational trust that she had been researching during her PhD stud‐ ies and research stays at the University of Geneva, University of Lausanne (Switzerland) and University of Cambridge (UK).  Giedrius Jucevicius is a Professor at the Strategic Management Department, School of Economics and Business, Kaunas Uni‐ versity of Technology (Lithuania). He holds a PhD in Management, has been visiting scholar at HEC University of Lausanne  (Switzerland), Lund university (Sweden), etc. His academic interests include comparative international management, business  model innovation, inter‐organizational relations and trust, clusters and industrial systems.   Robertas Jucevicius is a Professor and Director of the Business Strategy Institute at Kaunas University of Technology, Lithua‐ nia. He holds a PhD in Economics and Habilitated Doctor in Management. He is also a visiting fellow at the University of Cam‐ bridge (UK), as well as Fulbright (USA) and Wallenberg (Sweden) fellow and the member of the Council for National Progress  of Lithuania.   Nowshade Kabir is the CEO of Knolee Group, a Canadian investment and consulting company focused on technology invest‐ ment. He has M. Sc. in Computer Science, MBA and Ph. D. in Information Technology. His present interests are Big Data, In‐ novation,  Knowledge  Management,  Semantic  Technologies,  Entrepreneurship  and  Strategic  Management.  He  is  presently  pursuing a DBA in the joint program of Grenoble Graduate School of Business and Newcastle University Business School.     Katerina Kashi I am currently studying second year of PhD study, department of Business Economics and Management. I spe‐ cialize  on  human  resources  issues,  especially  employees’ training  and  development  and  employees’  total  reward  linked  to  competency models. My working experiences include: office assistant and office manager in USA, where I lived for nearly a  decade.  Marcela  Katuščáková  Lecturer  at  the  University  of  Žilina.  Masters  and  PhD.  graduate  of  the  Comenius  University  in  Brati‐ slava. She is working in research and education, specializing in information and knowledge management, scientific collabora‐ tion, storytelling and text mining. She has worked in the field of knowledge management implementation in research pro‐ jects such as the Memory of Slovakia and KNIHA SK.  Yasmina Khadir‐Poggi is a Doctoral student in the School of Business Studies at Trinity College Dublin. Besides, she is a Senior  Lecturer in International Business at American College Dublin. Her research interests include knowledge intensity in organisa‐ tion, knowledge workers management and the subsequent knowledge‐based development.   Tomasz  Kijek  holds  PhD  in  Economics  and  conducts  teaching  and  research  activities  in  the  Department  of  Economics  and  Management at the University of Life Sciences in Lublin, Poland.  His research interests focus on innovation, innovation capi‐ tal, intellectual capital, knowledge and a firm’s competitiveness. He is the author and co‐author of several scientific publica‐ tions, including chapters of monographs and articles.  Florian Kragulj   is a research and teaching assistant in the fields of knowledge‐based management and information systems  at the Vienna University of Economics and Business, Vienna, Austria. He graduated in Business Administration as well as in  Cognitive Science and had recently a research stay at the Eötvös Loránd University Budapest.  Jaroslava  Kubátová,  Ph.D.  Associate  Professor  at  Palacky  University  Olomouc,  Czech Republic.  Head  of the  Department  of  Applied  Economics  Areas  of  Expertise:  Human  Capital  Management  and  Knowledge  Management  with  ICTs  utilization  http://www.linkedin.com/in/jaroslavakubatova, https://www.researchgate.net/profile/Jaroslava_Kubatova2  Carmem Leal has a Master (2004) and Phd (2011) degrees in Management by UTAD. She is Assistant Professor of Financial  Accounting  at  University  of  Trás‐os‐Montes  e  Alto  Douro.  Her  research  on  Management  Control  (Intellectual  Capital)  has  been presented at numerous international conferences. At the moment she investigates Intellectual Capital within enterpris‐ es’ performance and Financial Management.  Monique  Lortie  Ph.D.,  is  a  tenure  professor  at  Université  du  Québec  à  Montréal.  She  graduated  in  Industrial  Engineering  from École Polytechnique de Montréal and completed her graduated studies in Ergonomics in France. Her main field of re‐ search is the occupational health and safety from which various issues on knowledge transfer and management are explored.   Grzegorz Majewski  MSc degree awarded by Warsaw School of Economics and another by University of the West of Scot‐ land.  Worked for companies in telecommunication and finance industries.  PhD in Computing awarded by University of the  West of Scotland.  Active in  research field presenting his papers at international conferences and publishing in refereed jour‐ nals.  His current research focuses on Knowledge Management, Business Process Simulation, Innovation Management, Social  Networks, e‐Learning and Immersive Virtual Worlds. 

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Carla Susana Marques has a PhD in Management. She is Assistant Professor in the University of Trás‐os‐Montes e Alto Douro  (UTAD) and Coordinator of the ‘Innovation, Markets and Organization’ research group in UTAD’s Centre for Transdisciplinary  Development Studies. Her research on innovation and entrepreneurship has been presented at numerous international con‐ ferences and published in international journals.  Dra. Eva Martínez‐Caro is Associate Professor of Business Management at the School of Industrial Engineering, Universidad  Politécnica  de  Cartagena.  Her  research  areas  of  interest  include  knowledge  management,  technology‐based  learning  envi‐ ronments and technology management.  Dora Martins did her PhD thesis on expatriates’ management on Portuguese companies and continues researching this topic.  She has also attended several international conferences. She teaches in the degree and master course of Human Resources  Management at Superior School of Industrial and Management Studies, Polytechnic of Porto, Portugal.  Dr. Fuensanta Medina‐Dominguez is assistant professor at Carlos III University of Madrid. Her research interests include SE  and software process improvement. Contact her at [email protected].  Andreia Meireles, MSc, is a Doctoral researcher at Faculty of Psychology and Sciences of Education – University of Coimbra.  Knowledge management is her main research interest. At the present, she is ending a research project that approaches inter‐ organizational knowledge sharing networks. Undergraduate and post‐graduate teaching experience in human resource man‐ agement, knowledge management, and work and organizational psychology.  Patricia  Mercado  Salgado  Investigadora  de  la  Facultad  de  Contaduría  y  Administración  de  la  Universidad  Autónoma  del  Estado de México. Licenciatura y Maestría en Administración. Doctorado en Administración (Organizaciones) obtenido en la  Universidad  Nacional  Autónoma  de  México.  Miembro  del  Sistema  Nacional  de  Investigadores  (Conacyt).  Coordinadora  del  Doctorado en Ciencias Económico‐Administrativas). Miembro del Cuerpo Académico Gestión del Capital Intelectual.   Peter Mkhize completed his PhD in 2012. He is currently working for University of South Africa as a senior lecturer. He has  published few journal and conference papers on e‐Learning and knowledge management. Among other research interests is  human capital development, social networks, communities of practice.   Ludmila Mládková works as an associate professor at the University of Economics Prague, Faculty of Business Administra‐ tion, Department of Management. She specializes in knowledge management, management of knowledge workers and man‐ agerial leadership. Her activities involve lecturing, writing and work with Ph.D. students.   Lisete M. Mónico is Professor at the University of Coimbra, Ph.D. in Social Psychology, European Diploma of Advanced Stud‐ ies in Social Psychology. Member of the Institute of Cognitive Psychology, dedicates her professional activity to research in  Social Psychology and Quantitative Data Analysis. Author of one book and several book chapters and peer reviewed articles.  Samuel Monteiro Assistant Professor, University of Beira Interior – Portugal. PhD in Organizational Psychology (2011) ‐ Uni‐ versity of Coimbra. MSc in Organizational Psychology (2007) ‐ University of Porto. BSc degree in Psychology (2003) – (Work  and Organizational Psychology) ‐ University of Coimbra. Researcher of the business and organizational management line of  research at NECE – UBI ‐ Research Unit in Business Sciences.  Mieczysław  Morawski,  born:  10.05.1962;  place:  Jelenia  Góra  Town,  Poland;    scientific  discipline:  management  science;  workplace: Wroclaw University of Economics;position: professor since 2008; number of publications: 130, in this book: 11;  research in the field: personal aspect of knowledge management, national management style, human capital management  non‐work interests: travel the world, forecasts the development of civilization.  Mustafa Doruk Mutlu. Mustafa completed his undergraduate study in Gazi University, Turkey and master study in Warwick  Business School, United Kingdom. He continues his PhD in Sheffield University. His current research focuses on knowledge  worker team personality composition working in R&D context.     Martin  Nkosi  Ndlela,  is  an  associate  professor  at  Hedmark  University  College  in  Norway.  His  research  interests  within  knowledge  management  include  knowledge  sharing  and  communication,  communities  of  practice  and  the  role  of  infor‐ mation and communication technologies. Ndlela has a keen interest in knowledge sharing in the public sector focusing main‐ ly on emergency organizations.  Irina  Neaga  is  a  Lecturer  in  Logistics  dealing  with  supply chains  and  logistics  systems,  and  researching  of knowledge  man‐ agement for collaborative logistics, decisions and operations. She worked for industry, research consortia, and higher educa‐ tion  in  Romania,  United  Kingdom,  Finland,  Canada,  and  The  Netherlands.  She  contributed  to  European  and  Academia‐ industry collaborative research projects.  xxi 

Satoshi Nishimura is a third year PhD student at Department of Engineering in Osaka University. He received Master of Engi‐ neering at Osaka University on 2012. His research interest is knowledge representation of human action based on ontology  engineering.   Felipe Nodari is a doctoral student at Pontifical Catholic University of Rio Grande do Sul (PUCRS), School of Business, Brazil.  His current research interests include Knowledge Management, Knowledge Sharing, Information Management and Manage‐ ment Information Technology.  Ana Nunes is Bachelor of Economics by Faculdade of Economia of Porto and Master in Finance by INDEG/ISCTE – IUL. She  worked as Risk Analyst at Ricoh Portugal, as Brand and Communication at BNP Paribas Corporate & Investment Banking and  at  Planning  &  Control  Analyst  at  EDP  Soluções  Comerciais.  Since  April  2013  she  is  Financial  Controller  at  EDP  Soluções  Comerciais.  Dr. Nóra Obermayer‐Kovács is an Assistant Professor at the Department of Management, University of Pannonia. She ob‐ tained her Ph.D. (Conscious knowledge management in knowledge economy) in Economics and Management in 2008. She  has published numerous articles and presented at national and international conferences. Her main fields of interest include  knowledge management, knowledge sharing, organizational culture.   Okeke Okeoma John‐Paul Currently a doctoral researcher at the University of East London with interests in knowledge man‐ agement. Current research is focused on evaluating knowledge management within the Nigerian Oil Petroleum Corporation  focusing on the knowledge processes within the firm and how they are integrated in its operational and business processes.   Mírian  Oliveira  obtained  her  doctoral degree  in  Business  Administration  from  the  Federal  University  of Rio  Grande  do Sul  (UFRGS) in 1999. She is a professor and researcher at Pontifical Catholic University of Rio Grande do Sul (PUCRS), School of  Business, Brazil. Her current research interests include Knowledge Management, Knowledge Sharing, Information Manage‐ ment and Research Method.  Tereza Otčenášková, is Ph.D. candidate at the Faculty of Informatics and Management (University of Hradec Králové, Czech  Republic), where she received Master Degree in Information Management. She received BA Diploma at the University of Hull,  United Kingdom. She leads tutorials and cooperates within various projects. Her areas of interest include knowledge man‐ agement and decision‐support systems.  Leonor Pais  Professor at the University of Coimbra and Porto Business School of University of Porto. Pre‐graduate and post‐ graduate  teaching  activity  in  work  and  organizational  psychology  area.  Portuguese  Coordinator  of  the  European  WOP‐P  Master supported by the European Commission. Knowledge management, human resources management and decent work  are her main research interests. Author of various book chapters and scientific papers.   Patcharaporn Paokanta has been a lecturer in the areas of Data Management, E‐Commerce, System Analysis and Design, and  Information Technology at Chiang Mai University (CMU), Thailand. She is studying for a Ph.D. in Knowledge Management at  CMU. She was awarded an ERASMUS MUNDUS scholarship (E‐Link Project) at the University of Sannio in Italy. She has pub‐ lished articles in international journal and conference proceedings, including ICIC Express Letter, IJCTE, IJIIP, ISABEL 2010 and  BHI 2012.  Margarida C. Piteira is assistant professor of human resources. Her research activity has been driven in the area of organiza‐ tional innovation and human resources management, with particular interest in the method of cases. At present she is mem‐ ber of the executive board Research Centre in Economic and Organizational Sociology   Dr. Mohammad Habibur Rahman is Associate Professor at Mohammed Bin Rashid School of Government, Dubai. He received  his PhD from the University of Wales and held visiting positions at Syracuse University in USA and York University in Canada.  He published papers on governance, local government, and knowledge sharing.  Vítor Raposo PhD in Business Management and Organization. Assistant professor at the Faculty of Economics, University of  Coimbra. Researcher and vice‐director of the Center for Studies and Health Research of the University of Coimbra and col‐ laborator of the Portuguese Observatory of Health Systems. Main research interests related with health governance, knowl‐ edge management and information management in health.  Elizabeth Real de Oliveira is Dean of Faculty of Business and Economics of Lusiada University. She holds a PhD in Manage‐ ment by the University of South Wales (former University of Glamorgan). Her research interests include corporate social re‐ sponsibility, HRM, employee engagement and employer branding. She has a wide experience as professor and consultant. 

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Paavo Ritala, D.Sc. (Econ. & Bus. Adm.) is a Professor at the School of Business at Lappeenranta University of Technology,  and an Academic Director of Master’s Programme in Strategy, Innovation and Sustainability. His main research interests are  in the areas of inter‐organizational networks, business models, knowledge management and innovation.   Hanno Roberts is a full professor in Management Accounting & Control at BI Norwegian School of Business. His research in‐ terests are in intellectual capital, local information systems, and management accounting and control for the knowledge in‐ tensive firm. He is on the Editorial Boards of multiple journals and teaches executive and MBA courses around the world.  Paula Cristina Lopes Rodrigues graduated in Economics. Masters degree on Cultural Marketing, finishing PhD on Measure‐ ment of Brand Equity in Fashion Companies, both in Economics University of Porto. Teaches Marketing, Statistc and Econo‐ metrics at Universidade Lusíada Famalicão and Porto. Published papers/books on marketing/statistics Direction of Faculty of  Economics and Business (2010), Lusíada University of Porto. Held  conferences and published l articles in Marketing.   José L. Roldán, PhD. Associate Professor of Management, Universidad de Sevilla (Spain). Current research interests include  technology  acceptance  models,  knowledge  management,  and  partial  least  squares  (PLS).  Published  in  Journal  of  Business  Research, British Journal of Management, International Business Review, European Journal of Information Systems, and In‐ dustrial Marketing Management, among others. He is currently on the editorial board of The Data Base for Advances in In‐ formation Systems.   Svetlana  Sajeva  is  currently  Associated  Professor  at  School  of  Economics  and  Business,  Kaunas  University  of  Technology,  Kaunas, Lithuania. Her area of research interests covers knowledge management, knowledge‐intensive organization’s man‐ agement and development of human resources. Svetlana Sajeva can be contacted at: [email protected].  João Samartinho Adjunct Professor of School of Management and Technology, Polytechnic . Institute of Santarém.  Invited  Professor  of  School  of  Education.  Head  of  Department  of  Computer  Science  and  Quantitative  Methods.  Researcher  UIIPS  Investigation Unit of Polytechnic Institute of Santarém. Chairman of the Cientific Board of School of Management and Tech‐ nology, November 2003 to April 2010   Noelia Sanchez‐Casado is a PhD Student at the Universidad Politécnica de Cartagena. Her research interests are in the area  of knowledge management, social media and marketing.  Maria‐Isabel Sanchez‐Segura has a PhD in Computer Science from Madrid Technical University. She is a faculty member of  the Carlos III University of Madrid. Her research interests include software engineering with a focus on processes and intelli‐ gent organizations. She is a member of the IEEE Computer Society. Contact her at [email protected]  Thomas Schalow is a professor in the Department of Economics and Information Science at the University of Marketing and  Distribution Sciences in Kobe, Japan, where he has taught for the past 15 years. He has also previously lectured at the Na‐ tional University of Singapore. His Ph.D. is from Princeton University.  Camilo Augusto Sequeira . has a Master’s degree in Electronic Engineering from Catholic University, Rio de Janeiro, and has  taught in both undergraduate and graduate programs. He has an MBA from Salford University, England. Sequeira has been  top executive for multinational companies and international lecturer. He is currently a consultant and a researcher for the  Institute of Energy of PUC‐Rio.  Gulzada  Serzhan, Lecturer at International Academy of Business, Almaty, Kazakhstan, IT Faculty Member   Radim Šíp, Ph.D. (1975) is a teacher and researcher at Faculty of Education, Masaryk University, Brno, Czech Republic. He  awarded Ph.D. in philosophy. He is the author of the first monograph on Richard Rorty on pragmatism in the Czech milieu. He  is dealing with pragmatism, neuroscience, cognitive science, and philosophy and history of science.   Inga Stankevice guest lecturer at the Department of Management and junior research assistant at the Department of Strate‐ gic Management, Kaunas University of Technology (Lithuania). Research stays at Bergen University (Norway), University of  Geneva  (Switzerland),  Nottingham  University  Business  School  (UK).  Holds  10  scientific  awards,  has  nearly  30  publications,  participated in 7 research projects.  Erik Steinhöfel studied Industrial Engineering focusing on Innovation Management at University of Applied Sciences Berlin  and University of Technology, Sydney. Became senior researcher at Fraunhofer IPK, Division Corporate Management. Expert  in  strategic  and  operational  knowledge  management,  project  manager  for  Intellectual  Capital  Statements.  Comprehensive  experience in innovation management and strategic planning.  Trine Marie Stene  Research Manager), NTNU Social Research, CIRiS (Centre for Interdisciplinary Research in Space). Senior  research scientist at SINTEF. PhD in Education and Master in Psychology  xxiii 

Dr Ann Svensson holds a PhD in informatics and is an assistant professor at University West, Sweden. Her research interests  are e‐learning and collaboration within e‐learning as well as knowledge management with a particular focus on complex and  professional work within and across organizations.   Erika  Tauraitė‐Kavai  2nd  year  doctoral  student,  Doctoral  studies  in  Social  Sciences,  Management  and  Administration,  ISM  University, Vilnius Lithuania.Erika has 14 years of international professional experience in market research, public policy ana‐ lytics and innovation management. In 2012 she started her PhD studies. Her research focuses on knowledge management  practices in open innovation context.  Giovanna Testa holds a PhD in Business Administration and Governance and is a researcher in economics and business man‐ agement at the University of Naples “Parthenope”. Her research focuses mainly on mechanisms of knowledge transfer and  sharing. The most recent studies are focused on industrial districts, from their operation to their characteristic features, par‐ ticularly oil districts.  Tkachenko Elena (1969) – the Doctor of Economics, the professor of the Department of the Enterprise Economics  and Indus‐ trial Management ( St. Petersburg State  University Of Economics). Author more than 120 scientific and  methodical works,  including 10 textbooks and 7 monographs. The sphere of scientific interests –innovations, investments, management of the  intellectual capital, Industrial development  Eduardo Tome PhD in Economics (2001), with a Thesis on the European Social Fund presented at the Technical University in  Lisbon. Since then he published 24 papers in peer‐reviewed Journals and presented 48 papers in international conferences.  He has also authored three book chapters. From September 2013 he is working at Universidade Europeia in Lisboa.   Thierno Tounkara PhD in computer science at University Dauphine of Paris (2002) . Works at  Business School “Telecom Ecole  de  Management”  (TEM)  as  professor  in  Information  Systems  Department.  Delivers  courses  in  information  system  design,  project management, Enterprise Resource Planning (ERP) and KM. Written scientific articles on KM and Engineering. Worked  at ONERA, First Aerospace Research Player in France, as KM engineer, 3 years. In 2000, joined French Knowledge Manage‐ ment Club, association rallying a lot of French companies.  Katarzyna Trawińska‐Konador graduated with a major in German and Dutch from the University of Warsaw. She studied at  the University of Leuven in Belgium, the Freie Universität in Berlin and the University of Vienna.  Ms. Trawińska‐Konador ac‐ quired extensive hands‐on professional experience in education working as director for studies at private continuing educa‐ tion  institutions.  Her  main  fields  of  professional  interest  include  vocational  education and  training, continuing,  non‐formal  and informal education, and distance education.  Dr.  Anna  Ujwary‐Gil  PhD  from  Warsaw  School  of  Economics,  College  of  Management  and  Finance.  Fellow  of  Foundation  Scholarship and Training (Norwegian Funds). Currently Editor‐in‐Chief of Journal of Entrepreneurship, Management and In‐ novation. In 2010, book entitled "Intellectual Capital and Market Value of a Company" (Ch&Beck, Warsaw 2009) received a  prestigious award granted by Polish Academy of Sciences.  Jiro Usugami is a professor at Aoyama Gakuin University,Tokyo. His research topics include Knowledge Management in  disaster risk reduction and Cross Cultural Management.  Lina Užien Associate Professor, Department of Strategic Management, School of Economics and Business, Kaunas University  of Technology. PhD in Management and Business Administration (2005) from Kaunas University of Technology. Scientific in‐ terests lie in intellectual capital measurement and management at corporate and regional levels. Professional activities in‐ clude university lecturing, corporate consulting and project work.  José Vale lives in Porto, Portugal, and he is an invited lecturer at Aveiro University  and at the Porto polytechnic in the areas  of management, strategy and accounting. Presently is doing a PhD in Accounting and Management Control at the faculty of  economics in Porto University, studying Intellectual Capital in a seaport context.  Ana Cláudia Valente Researcher at DINÂMIA’CET‐IUL. Fields of research are human capital and innovation mainly skills and  work  organization  studies  and  education  and  employment  policies  analysis.  Is  currently  a  national  expert  in  the  CEDEFOP  network for skills forecasting and labour market developments. Ph.D. in Economics, specialization in Industrial Economics and  Innovation, by ISCTE ‐ Lisbon University Institute.  Mika Vanhala, D.Sc. (Econ & Bus. Adm.) is a post‐doctoral researcher in Knowledge Management at School of Business,  Lap‐ peenranta University of Technology, Finland. His primary research interest is the relationship between HRM practices, organ‐ izational trust and organizational performance. Mika’s research has been published in Management Decision, Personnel Re‐ view and Management Research Review.     xxiv 

Stanislav  Vojir  graduated  from  applied  informatics  (Knowledge  technologies,  Information  systems  and  technologies).  Cur‐ rently, he is internal PhD student at Faculty of Informatics and Statistics, University of Economics in Prague. He deals with  problem of business rules in conjunction with datamining of association rules.  Tone Vold Assistant Professor is lecturing at Hedmark University College since 2000. Since her Master in Informatics in 2005,  Vold’s areas of interests now include social sciences and she currently teaches within the areas of Organizational Studies and  Knowledge Management.    Volker Wagner is a teaching assistant at the chair for human resource management at the University of Hamburg. He is cur‐ rently working on his PhD in the fields of social cognition and shared cognitive structures in organisations. He studied Eco‐ nomics and Business Administration at the University of Hohenheim with majors in HRM and Organizational Psychology.  Igor Zatsman has the PhD (Information‐Computer Science). Currently, he is the head of research department at the Institute  of Informatics Problems of the Russian Academy of Sciences. He has the highest research diploma, obtained after the PhD.  Research  interests  are  in  the  fields  of  Cognitive Informatics, Modeling Emerging  Meanings  Processes  and  Their  Tracing by  Computer.  Malgorzata Zieba PhD, Eng.  is an assistant professor at the Faculty of Management & Economics of Gdansk University of  Technology, Poland. She has taken part in several national and international projects. Her scientific interests oscillate around  knowledge management and modern concepts of management in SMEs. She has a record of around 30 publications.    

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Learned Helplessness of Prisoners: Psychology and Knowledge  Management Perspective   Juneman Abraham and Rigel Adiratna  Bina Nusantara University, Jakarta, Indonesia  [email protected]    [email protected]   Abstract: The author posits that knowledge creation and management nowadays do not occur in prisons in Indonesia since  the  existence  of  learned  helplessness  phenomena  among  its  prisoners.  This  study  contributes  by  identifying  predictor  variables of prisoner’s learned helplessness. The design of this research is quantitative‐predictive correlational design. This  research hypothesized that social rejection and three types of neurotic personality orientations (moving away from people,  moving against people, and moving toward people) are able to predict learned helplessness of prisoners. As it is known in  the  literature  of  Knowledge  Management,  learned  helplessness  lessens  one’s  effort  to  understand  complex  issues.  In  addition, prospective approach to knowledge management suggests that learned helplessness should be transformed into  learned optimism. The participants of this research were 163 inmates from Cipinang IA Penitentiary Institution and Pondok  Bambu  IIA  Prison  in  DKI  Jakarta,  the  capital  of  Indonesia.  The  measurement  tools  of  this  study  were  adapted  and  developed from Rejection Sensitivity Questionnaire, Karen Horney’s Three Orientations, and Learned Helplessness Scales.  Multiple  linear  regression  analyses  showed  that  social  rejection  and  the  tendency  of  “moving  toward”  are  not  able  to  predict  learned  helplessness.  The  tendency  of  “moving  away”  and  of  “moving  against”  are  able  to  predict  learned  helplessness  in  the  negative  ways.    All  results  of  this  research  will  be  discussed  by  employing  relevant  psychological  theories and knowledge management perspective. The implication of result of this research toward efforts in facilitating  learning as well as knowledge creation and management of prisoners in prison is proposed in the Discussion section of this  article.  The  authors  are  of  the  position  that  if  all  these  things  are  well  facilitated,  the  prisoners  will  be  a  valuable  social  capital for Indonesia.  Keywords: learned helplessness, knowledge management, psychology 

1. Introduction Prisons in Indonesia are always fascinating to study, mostly because prisons are miniature representatives of  social  issues  in  Indonesia  (Larasati  n.d).  In  prisons,  we  find  oppression  of  minorities,  corruption,  drugs  and  orgy,  institutional  reformation,  conflict  transformation,  deradicalization  of  convicted  terrorist,  and  others.  Therefore, the author assumes that (1) solving the issues in Indonesian prisons will contribute enormously to  settlement of social problems in Indonesia, (2) social and psychological capital—including knowledge—findings  in Indonesian prisons are crucial for the settlement of social issues in Indonesia.  It is a fact that crimes and modus operandi of criminals move faster and more sophisticated compared to law  enforcement  by  its  officers  (Fajar  Online  2011;  Purnomo  2013).  Based  on  this  issue,  the  author  argues  that  knowledge of inmates must be appreciated, meaning that their knowledge must be viewed as significant in the  context of crime prevention and eradication. Unfortunately, convicts are usually positioned as a social entity  that  must  firstly  be  intervened,  treated,  educated,  transformed  (as  object),  and  not,  before  all  else,  to  be  understood and respected for their knowledge (as subject, both as an individual or a group).  Prisoners  have  their  own  logic  (Sarwono  2013)  which  may  be  different  from  the  logic  of  non‐prisoners.  Utilization  of  prisoner’s  knowledge  is  not  taboo.  Sarwono  (2012  p.  58)  described  his  activities  in  studying  terrorists:  “We  are  successful  in  engaging  the  ikhwan  (Islamic  terminology  for  brother)  in  discussion  regarding  their  believe  and  action,  although  at  the  beginning  of  the  discussion  they  refuse  ...  (Discussion) is effective strategically and tactically (for example, with regard to killing people that  do not attack Islam, killing women and children, or with regard to their decision on whether Java  and Bali can be regarded as jihad area).”   If  we  look  back  to  the  history  of  Indonesia,  knowledge  creation  and  exchange  in  prisons  are  a  typical  experience  of  the  founding  fathers  of  Indonesia—Soekarno,  Hatta,  and  Syahrir—during  the  colonial  era.  Prisons  bring  about  creative,  productive,  transformative  experience,  which  facilitate  those  individuals  to  a  deeper understanding of the “truth” that they have fought for (Laksana 2013). In prison, they read books and  perform knowledge exchange through meaningful social relation. 

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  Juneman Abraham and Rigel Adiratna  Maruna  (2011)  emphasized two  basic  issues  regarding  how  psychology  should  relate to  prisoners.  He  states  that psychologists need to see transformation opportunities of personality, cognitive ability, and other issues  with  regard  to  prisoners.  The  strength  of  prisoners  must  also  be  given  proper  attention  in  addition  to  their  weaknesses. If prisoners are viewed as a deviance or pathology, psychologists must be careful not to fall on the  trap of individualization or attribute the cause of the deviance or pathology solely on the personality of the  individual. Psychologists should consider that deviance has social loci, namely social contexts, power dynamics,  and  interpersonal  situations.  Those  thoughts  indicate  that  knowledge  exchange  can  also  be  conditioned  in  social interactions.    However, inmates are often only seen as objects. Prisoners are often considered as the enemy by society, as  part of the out‐group‐low‐status opponents; hence they are treated offensively, or—in a more passive way— they  get  humiliation  or  exclusion  (Fiske,  Harris  and  Cuddy  2004).  Even  when  they  are  out  of  the  prison,  ex‐ prisoners  face  many  issues when  reintegrated  into  society,  such  us unemployment,  homelessness,  and  legal  obstacles  to  accessing  public  services,  which  lead  to  recidivism  (Wheeler  and  Patterson  2008).  Wheeler  and  Patterson  propose  that  in  reducing  recidivism,  it  is  vital  to  perform  coordinated  community  services  for  prisoners  that have  already been  stigmatized  by  society. However,  this  service  should  be  a  continuum  since  prisoners  are  in  prison.  According  to  the  author,  the  main  purpose,  among  others,  is  to  decrease  learned  helplessness experienced by prisoners even since they are in prison.    Knowledge  creation  and  management  nowadays  do  not  occur  in  prison  in  Indonesia  since  the  existence  of  learned  helplessness  phenomenon  among  its  prisoners.  Learned  helplessness  reduces  one’s  effort  to  understand  complex  issues  (Schwartz  and  Te’eni  2010).  Learned  helplessness  is  described  as  one’s  personal  belief that he/she is not able to do anything to increase his/her performance, and as the consequence, he/she  does  not  desire  to  achieve  any  reward  or  to  avoid  punishment  (Lieder,  Goodman  and  Huys  2013;  Reivich,  Gilham, Chaplin and Seligman 2005). Schill and Marcus (1998) explain that learned helplessness is influenced  by  attribution  style.  The  psychological  process  is  as  following:  imprisonment  creates  one’s  sense  of  losing  personal control of him/herself and his/her actions. If individuals want to exert more control, for example by  questioning orders and debating with prison officers, they will lose more of their rights and limited facilities. In  such  chronic  situation,  inmates  will  be  conditioned  to  belief  that  the  negative  events  that  happened  are  caused  by  internal,  stable,  and  global  reasons.  In  other  words,  inmates  adopt  and  developed  helpless  attribution style or pessimistic explanatory style.    Lieder et al (2013) also show that learned helplessness can be generalized—because it is assumed as a learning  process—or creates depression in other new situation. The knowledge management perspective suggests that  learned helplessness should be transformed into learned optimism (Thatchenkery and Chowdhry 2007).    The  author  assumes  that  differences  in  personality  and  social  factors  obtained  throughout  life  (since  childhood)  influenced  the  degree  of  their  learned  helplessness  for  every  (ex‐)  prisoner.  The  author  chooses  Karen  Horney’s  Three  Orientations  (moving  against  people,  moving  away  from  people,  and  moving  toward  people) as well as social rejection as the predictors (Figure 1).    Karen Horney’s Three Orientations variable is chosen because its psychoanalysis concept speaks about defence  that  people  create  to  deal  with  their  basic  anxiety  (Coolidge,  Segal,  Benight  and  Danielian,  2004;  Walborn  2014) —a sense of hopelessness that is primitive in a hostile world. This “hostile world” is actually a projection  of the child’s inner world. This inner world is the result of experience in facing the environment and parenting  that  is  severely  and  chronically  maladaptive.  The  child  wanted  to  fight  the  parents,  but  he/she  is  also  dependent on them; hence his/her sense of resistance is repressed. In psychoanalysis, this results in a reaction  formation where the child becomes excessively affectionate towards the parents, but, on the other hand, sees  the world as hostile. Furthermore, growing up, this individual developed an “idealized (not real) self” rooted in  a  neurotic  necessity  for  affection  and  admiration—by  performing  what  is  assumed  as  expected  by  the  parents—but  never  felt  satisfied  or  contented.  Walborn  (2014)  in  his  analysis  added  that  the  same  anxiety  does  not  result  only  from  experience  of  interacting  with  the  parents,  but  also  through  interacting  with  capitalistic world which solely appreciate people based on their material possession and physical appearance,  not  by  who  they  are.  In  the  struggle  to  achieve  the  idealized  self,  people  use  three  defensive  strategies,  namely  (1)  moving  towards  people  (compliant  trend),  (2)  moving  against  people  (aggressive  trend),  and  (3)  moving away from people (detached trend). Horney argues that neurotic adults experience fixation on one of  those three orientations, however, healthy adults have the flexibility to move between those three.  

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  Juneman Abraham and Rigel Adiratna   

Karen Horney’s Three Orientations

Learned Helplessness of Prisoners

Social Rejection

  Figure 1: The hypothetical model   Social  rejection  in  this  study  is  measured  based  on  subjective  sensitivity.  The  construct  being  measured  is  social  rejection  sensitivity.  Rejection  sensitivity  is  a  disposition  to  defensively  (anxiously  or  angrily)  expect,  readily  perceive  (even  when  events  are  ambiguous),  and  overreact  (e.g.,  aggressing  against  or  withdrawing  from others) to rejection (Wang, McDonald, Rubin and Laursen 2012; Wang and Nesdale 2012). Sensitivity to  rejection  and  continuous  overreaction  is  a  part  of  the  natural  learning  process.  High  level  of  sensitivity  is  a  result of initial rejection and prolonged experiences of caregivers and significant others (Kross et al 2007).    Watson and Nesdale (2012) found that rejection sensitivity correlate negatively with (1) confidence in building  and  maintaining  meaningful  social  relation,  and  (2)  perceived  efficacy  in  controlling  social  situation.  In  addition,  they  also  speculate  that  individuals  with  high  rejection  sensitivity  will  assume  that  their  failure  in  social  relation  is  due  mostly  by  the  immutable  negative  characteristics  of  their  personalities.  This  further  strengthens the feeling of the individuals regarding their social incapability and fruitlessness. However, Watson  and  Nesdale  states  that  the  speculation  requires  further  investigation.  The  author  observed  that  the  latter  symptom  is  compatible  with  helpless  attribution  style  described  previously  above,  which  is  experienced  by  prisoners or ex‐prisoners.    This  study  will  first  test  the  predictive  hypotheses  as  described  above,  and  will  further  provide  discussion  regarding the implication of the empirical findings on knowledge sharing in prisons. 

2. Methods  This  study  used  the  design  of  quantitative,  predictive  correlational  research,  with  data  analysis  technique  in  the form of multiple linear regression analyses. The predictor variables are Karen Horney’s Three Orientations  and  social  rejection  sensitivity,  and  the  criterion  variable  is  learned  helplessness.  Participants  of  this  study  were  inmates  of  Cipinang  IA  Correctional  Facility  and  Pondok  Bambu  Class  IIA  Prison,  in  Jakarta,  Indonesia,  both  new  inmates  (inmates  serving  their  first  prison  sentence)  and  recidivist  inmates  (inmates  with  two  or  more  prison  sentence).  The  number  of  participants  is  163  consisting  of  64  men,  99  women  (Mean  of  age  =  33.14  years  old;  Standard  deviation  of  age  =  8.48  years  old).  Participants  were  taken  using  convenience  sampling technique, and they were asked to fill the questionnaire in Indonesian.    The instrument for measuring learned helplessness is adapted and developed from Learned Helplessness Scale  (LHS)  constructed  by  Quinless  and  Nelson (1988).  This  instrument  initially  has 20  items  categorized  into  five  dimensions. The first dimension is Internality‐Externality, with sample scale items: (1) When I do not succeed  at  a  task,  I  find  myself  blaming  my  own  stupidity  for  my  failure,  (2)  If  I  complete  a  task  successfully;  it  is  probably because I became lucky. The second dimension is Globality‐Specific, with sample scale items: (1) I am  unsuccessful  at  most  tasks  I  try,  (2)  I  do  not  have  the  ability  to  solve  most  of  life's  problems.  The  third  dimension is Stability‐Instability, with sample scale items: (1) When I do not succeed at a task, I do not attempt  any similar tasks because I feel that I will fail them also, (2) I do not try a new task if I have failed similar tasks  in the past. The fourth dimension is Ability‐Inability to Control, with item: (1) No matter how much energy I put  into a task, I feel I have no control over the outcome, (2) I feel that I have little control over the outcomes of  my work. The fifth dimension is Individual's Choice of Situation, with items: (1) I do not accept a task that I do  not think I will succeed in, (2) I do not place myself in situations in which I cannot. LHS has response options  from Strongly Disagree (score of 1) to Strongly Agree (score of 6). The higher the total score of the participants  in this scale shows a higher learned helplessness. The results of reliability and validity test on 90 participants  (for  instrument  tryout)  indicate  that  LHS  is  reliable  with  an  internal  consistency  index  (Cronbach’s  Alpha)  of  0.833 with corrected item‐total correlations ranged from 0.377 to 0.701 after dismissing 10 items.   

3

  Juneman Abraham and Rigel Adiratna  The  instrument  for  measuring  Karen  Horney’s  Three  Orientations  is  adapted  and  developed  from  Karen  Horney’s Social Movement assessment instrument constructed by Wheeler (1991). This instrument consists of  108 items categorized into three dimensions. The first dimension is Aggression (moving against people), with  sample scale items: (1) When people talk about me and say things I do not like, I have a tendency to become  angry and say things back about them, (2) If I see someone I dislike approaching me from a distance, I have a  tendency  to  meet  him  or  her  ready  to  argue  or  show  my  dislike.  The  second  dimension  is  Avoidance‐ Passiveness  (moving  away  from  people),  with  sample  scale  items:  (1)  When  a  discussion  turns  into  an  argument, I have a tendency to withdraw from the conversation, and (2) When my roommate repeatedly eats  food  of  mine  that  I  had  been  saving  especially  for  myself,  I  have  a  tendency  to  avoid  the  person  and  the  situation.  The  third  dimension  is  Compliance  (moving  toward  people),  with  sample  scale  items:  (1)  When  someone embarrasses me by spilling something on me, I have a tendency to tell them it is OK and accept and  apology, (2) When people tell me things about me that I do not want to hear, I have a tendency to listen to  what  they  are  saying  and  see  how  I  can  change  what  they  do  not  like  about  me.  This  scale  has  response  options from Never (score of 1) to Always (score of 6). The higher the total score of the participants in each of  the  three  sub‐scales  (aggression,  avoidance‐passiveness,  compliance)  shows  an  increasing  level  of  neurotic  trend by the participants on the related scale. The reliability and validity test results show that this instrument  is reliable with an internal consistency index for aggression, avoidance, and compliance, respectively of 0.912,  0.917,  and  0.908.  The  corrected  item‐total  correlations  ranged  from  0.250  to  0.732  for  aggression  (after  dismissing 2 items), 0.320 to 0.616 for avoidance (after dismissing 2 items), and 0.254 to 0.682 for compliance  (after dismissing 7 items).    The  instrument  for  measuring  social  rejection  is  adapted  and  developed  from  Rejection  Sensitivity  Questionnaire  (RSQ)  constructed  by  Downey  and  Feldman  (1996).  There  are  18  situations  to  which  that  participants must respond. The sample of situations are as follow: (1) You  approach  a  close  friend  to  talk   after  doing  or  saying  something  that  seriously  upset him/her, (2) You  call  your  boyfriend/girlfriend  after   a  bitter  argument  and  tell  him/her  you  want  to see  him/her, (3) You  ask  a  friend  if  you  can  borrow   something  of  his/hers, (4) You  ask  a  friend  to  do  you  a  big  favor, (5) You  ask  your  spouse if  he/she   truly  loves  you. The RSQ instruction is as following: "Each of the items describes things one sometimes asks of  other  people.    Please  imagine  that  you  are  in  each  situation.    You  will  be  asked  to  answer  the  following  questions: (a) How concerned or anxious would you be about how the other person would respond? (b) How do  you  think  the  other  person  would  be  likely  to  respond?"  The  response  options  for  (a)  are  from  Very  Unconcerned (score of 1) to Very Concerned (score of 6). The response options for (b) are from Very Unlikely  (score of 1) to Very Likely (score of 6). Scoring on participants’ responses follows the Downey and Feldman’s  manual (1996). The reliability and validity test results indicate that LHS is reliable with an internal consistency  index  of  0.834  with  a  corrected  item‐total  correlations  ranged  from  0.259  to  0.654  without  any  item  being  dismissed. 

3. Result and discussion  Multiple linear regression analysis indicates coefficients of determination (R2) value and beta coefficients (β) as  shown in Table 1.  Table 1: Coefficients of determination and beta coefficients in the predictive model with Learned Helplessness  as the criterion variable (n = 163)  Model  1 

Predictors  Social Rejection Sensitivity & Orientation  of Moving Away from People 

F  F(2, 162) =  6.652; p =  0.002** 



Social Rejection Sensitivity & Orientation  of Moving Against People 

F(2, 162) =  6.344; p =  0.002** 



Social Rejection Sensitivity & Orientation  of Moving Toward People 

F(2, 162) =  0.560; p =  0.572 

Note:    * p  0.05) is allegedly due to the  nature of the consequences of having attributes of SRS by individuals, namely negative and positive; thus the  correlated scores might diminish each other. On one hand, SRS has negative consequences as proved in the  previous studies. This is because SRS is associated with actual rejection (self‐fulfilling prophecy phenomenon),  depression, loneliness, social withdrawal, jealous in partnerships, low self‐efficacy, relationship dissatisfaction  and  breakdown,  and  doubt  or  unwillingness  to  take  social  risks  (Addis  2012;  Wang  et  al,  2012;  Watson  and  Nesdale 2012; Zimmer‐Gembeck and Nesdale 2012). Individuals’ social cognitions, feelings, and interpersonal  behaviors such as these indeed lead to helplessness. However, there are evidence that positive consequences  of  social  rejection.  Kim, Vincent,  and  Goncalo  (2012)  states  that  experience  of  social rejection can  stimulate  creativity.  Creativity  is  a  psychological  resource  which  is  precisely  the  opposite  of  learned  helplessness.  However,  creativity  in  this  context  only  emerged  on  individuals  with  independent  self‐concept.  The  psychological  mechanism  is  as  following:  Social  rejection  interacts  with  independent  self‐concept  and  this  interaction strengthens individuals’ desire to further differentiate themselves from others through moderating  variables need for uniqueness. This cognition will in turn lead to more creative effects. Subsequent researchers  are  advised  to  measure  independent  vs.  interdependent  self‐concept  in  order  to  obtain  a  complete  picture  regarding the relationship between SRS and Learned Helplessness.    Negative correlation between Orientation of Moving against People with Learned Helplessness  (β = ‐0.260; p  [10 Dec, 2011].  Cong, X.; Pandya, K. V. (2003) Issues of knowledge management in the public sector. Electronic Journal of Knowledge  Management. V. 1, No 2, (pp. 25‐33).  Dalkir, K. (2013). Knowledge management in theory and practice, The MIT Press, Cambridge, MA  Denning, S.. (2011) The Leader´s Guide to Storytelling. Mastering the Art and Discipline of Business Narrative. Jossey‐Bass,  San Francisco.  Gespública (2007). Instrumento para a Avaliação da Gestão Pública. Ciclo 2007. Ministério do Planejamento, Orçamento e  Gestão, [Online], Available:  www.prefeitura.sp.gov.br/arquivos/secretarias/subprefeituras/pqgp/materiais_consulta/0001/Instrumento_Avaliaca o_GESPUBLICA.pdf [4 May 2014].  Eiriz, V.; Simões, J.  e  Gonçalves, M.(2007). Obstáculos à gestão do conhecimento nas escolas de gestão e economia do  ensino superior público em Portugal. Comportamento Organizacional e Gestão, vol.13, n.2 pp. 153‐167. [Online],  Available:  

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  Fábio Ferreira Batista and Florinda Matos  http://www.scielo.gpeari.mctes.pt/scielo.php?script=sci_arttext&pid=S087296622007000200002&lng=pt&nrm=iso>.  ISSN 0872‐9662. [4 May 2014].  Gomes, M.V.D. (2005). Gestão do Conhecimento na Administração Pública: Paradigma para o Judiciário Fluminense. FGV,  Rio de Janeiro.   KPMG. Insights from KPMG´s (2002). European Knowledge Management Survey 2002/2003. Online], Available:  http://ep2010.salzburgresearch.at/knowledge_base/ kpmg_2003.pdf [10 Dec, 2011].  Ma, Z. and Yu, K. (2010). Research paradigms of contemporary knowledge management studies: 1998‐2007, Journal of  Knowledge Management,  V. 14, No 2, (pp 175‐189)  Miranda, M.M.S. (2010). Base de Dados de Melhores Práticas: Um Estudo no Tribunal Regional Federal da Primeira Região.  MGCTI/UCB, Brasília.  Monavvarian, A. and Kasaei, M. (2007). A KM model por public administration: the case of Labour Ministry. Journal of  Information and Knowledge Management Systems. V. 37 No 3, (pp 348‐367).  Paixão, R.L. (2004). Gestão do Conhecimento: Estudo de Casos no Setor Público. UFRJ, Rio de Janeiro.  Silva, R. V.; Neves, A. (2003). Gestão de Empresas na Era do Conhecimento. Lisboa: Edições Sílabo.  Snowden, D. (2002) Unique characteristics of the public sector and KM. Ago.  [Online], Available: act‐ [email protected]> [5 April 2014].  Sveiby, K. E. (2001). Intellectual Capital and Knowledge Management. [Online], Available: http://www.sveiby.com/articles/  [4 May 2014]. 

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Effect of ICT on Information Sharing in Enterprises: The Case of  Ministry of Development  Özlem Gökkurt Bayram1 and Hakan Demirtel2  1  Department of Information and Records Management, Faculty of Languages History and  Geography, Ankara University, Ankara, Turkey  2  Department of Information Society, Ministry of Development, Ankara, Turkey  [email protected]  [email protected]    Abstract:  Information  sharing  at  enterprise  level  is  getting  more  important  because  of  growing  value  and  volume  of  knowledge exponentially. Information and communication technologies (ICT) are adding value to knowledge management  efforts  and  trying  to  make  these  efforts  more  efficient.  It  is  another  fact  that  the  growing  use  of  ICT  has  changed  significantly the knowledge creation and knowledge usage processes. Besides, it has become a necessity to use ICT tools to  access and analyse the information because of huge amount of knowledge stored electronically. In this paper the effect of  information  systems  developed  and  used  by  government  is  investigated  by  means  of  information  sharing  at  enterprise  level.  For  this  purpose,  the  systems  owned  by  Ministry  of  Development  (MoD)  of  Republic  of  Turkey  such  as  electronic  records management system, document management system, intranet web site, official web site and MoD‐Search system  are come up for review and effects of them on information sharing are examined. Knowledge sharing motivation factors  defined  in  the  literature  such  as    sense  of  achievement,  sense  of  responsibility,  recognition  of  job  done,  operational  autonomy, promotional opportunities, challenge of work (Herzberg 1968, Herzberg 1987, De Sitter 1994, Hendriks 1999)  are set for examination criteria. So that, a questionnaire are applied to knowledge workers at the MoD to measure these  factors and results are analysed.    Keywords: knowledge sharing, information and communication technologies (ICT), knowledge sharing motivations 

1. Introduction  Today, information and communication technologies (ICT) have diffused into almost every area of life leading  to  progress  in  many  fields.  Now,  organizations  can  carry  out  numerous  tasks  and  transactions  using  ICT.  Conversion  of  transactions  to  electronic  environment  increases  data  creation  rapidly.  Besides,  as  advanced  web‐based  and  other  communication  technologies  have  enabled  interaction  with  customers  using  such  systems, all sorts of feedback received from users are recorded on these systems. As a result of this rapid data  flow, the amount of data created enhances and conventional methods remain insufficient to process recorded  data. Organizations that process data with the help of ICT facilities facilitate creation of personal knowledge on  the one hand, and head towards values supporting creation of new knowledge on the other.     Organizational culture is important in knowledge creation. Organizational public knowledge must be utilized in  processes of knowledge creation besides private knowledge created within the organization. Otherwise, it is  stated that organizational competitive power can be affected adversely (Matusik & Hill 1998, Matusik 2002).  Organizations need credible systems where knowledge is recorded according to defined rules and rapid access  is provided to such knowledge. Therefore, it is important to record all private and public knowledge used in  organizational processes and to share this knowledge to increase recognition. In this respect, use of ICT must  play a facilitative role. ICT tools develop embedded search functions facilitating access to content in electronic  databases on Internet and organizational webpages and also improve technics in full‐text search, keyword and  descriptors. However, it is of utmost importance to evaluate, on an organizational basis, to what extent users  have internalized the use of technics and technologies.    

2. Rationale and problem (literature review)  In the literature, creation of organizational knowledge is addressed on the basis of SECI approach developed  by Nanoka (1994). SECI model includes basic dynamics regarding knowledge creation. In this model, two forms  of knowledge, namely tacit and explicit knowledge, regenerates constantly by shifting from tacit knowledge to  explicit  and  then  to  tacit  knowledge  again  within  a  cycle  consisting  of  processes  of  socialization,  externalization, combination and internalization in creation process (Nanoka 1994).       Waterfall  Model  (Sun  2004),  Hierarchical  Spiral  Model  (Sun  ve  Hao  2006),  Integrated  Life‐cycle  Model  (Cruywagen  et  al.  2005)  can  be  considered  among  other  models  of  knowledge  management.  It  is  seen  that 

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  Özlem Gökkurt Bayram and Hakan Demirtel  sharing of all sorts of knowledge, tacit or explicit, is important in models of knowledge management. In these  processes,  ICT  can  contribute  significantly  to  prompt  creation  of  knowledge,  facilitate  sharing  and  flow  of  knowledge.      Secure access to knowledge and sharing of accurate knowledge creates considerable competitive advantage in  organizational activities. Knowledge is shared through organisational learning in systems of knowledge where  ICT facilities are used efficiently on organizational level. However, it has been stated that the group that most  use knowledge in an organization is the one that create and share knowledge most actively at the same time  (Hopfgartner et al. 2008). Besides, developing organizational culture in this direction is inevitable for creating  awareness  on  and  dissemination  activity  in  sharing  of  knowledge.  Motivational  factors  must  be  utilized  properly among staff of organization in order to activate dissemination of information.            It  has  been  stated  that  motivation  of  knowledge  sharing  depends  on  factors  of  reputation,  reciprocity,  autonomy,  community,  and  alturism  (Hopfgartner  et  al.  2008,  Hung,  Lai  &  Chang  2011).  In  addition,  some  theories  such  as  social  exchange,  social  capital,  social  cognition,  expectancy  theories  and  the  theories  of  reasoned  action  and  planned  behaviour  explain  attitudes  of  staff,  who  work  knowledge‐intensive  in  an  organization (Tsai & Cheng 2012).      Studies  on  the  role  of  ICT  in  knowledge  sharing  at  organizational  level  enlist  primary  technologies  of  SECI  model  as  blogs,  e‐mail  systems,  e‐collaborative  systems,  e‐forums,  e‐learning/online  learning,  information  TM repository, instant messaging, NetMeeting , audio conferencing, people finder, podcast, video conferencing,  and wiki. In these studies, the weight of these tools in steps defined by SECI model is also investigated (Lee &  Kelkar 2013). More efficient and precise access is targeted through use of tags, ranking and recommendations  tools in sharing of the content forms stated above (Chennamaneni, Teng & Raja 2011). In this study conducted  by  Chennamaneni  and  colleagues,  elements  influencing  behaviours  of  knowledge  sharing  are  examined  and  the impact of knowledge systems on behaviour is assessed in the context of technological priorities. It is stated  that ICT usage contributes to knowledge sharing through abolition of barriers among employees, easier access  to  knowledge,  process  improvement  (McGrath  and  Hollingshead  1994)  and  sharing  of  meta‐knowledge  (Hendriks 1999). Hendriks, taking this approach as starting point, reviewed the impact of ICT upon knowledge  sharing  on  the  basis  of  SECI  model  by  utilizing  motivational  factors  generally  accepted  in  the  literature.  Nevertheless, this study focused on the impact of ICT on general motivation for knowledge sharing rather than  direct knowledge sharing peculiar to ICT systems. The study focused specifically on knowledge system used by  an organization and assessed the influence of genuine ICT systems used by that organization for access to and  sharing of knowledge upon access and sharing.         In  this  context,  this  study  has  been  conducted  taking  into  consideration  the  benefits,  as  a  case  study,  of  a  research on the impact of ICT‐based systems used by organizations upon knowledge sharing. 

3. Methodology  The  research  primarily  specifies  the  ICT  systems  of  the  Ministry  of  Development  (MoD)  towards  knowledge  access  and  sharing  and  gives  preliminary  information  about  such  systems.  Then  a  questionnaire  is  designed  with  a  view  to  identify  the  usage  of  these  systems  in  terms  of  knowledge  management.  The  target  of  the  questionnaire is to assess the contribution of ICT systems to knowledge access and sharing.    Conventional methods of knowledge sharing have been included in answer choices of questionnaire to set out  rates of usage of ICT systems.    Additionally,  the  motivational  factors  in  usage  of  the  above‐mentioned  ICT  systems  and  other  methods  in  knowledge  sharing  have  been  investigated.  For  this  purpose,  the  criteria  that  are  defined  in  literature  as  motivations  for  usage,  sense  of  success,  sense  of  responsibility,  recognition  of  job  done,  operational  autonomy, promotional opportunities and challenge of work (Herzberg 1968, Herzberg 1987, De Sitter 1994,  Hendriks 1999), are incorporated into research to identify which of these criteria are prominent in knowledge  sharing via ICT systems.         

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  Özlem Gökkurt Bayram and Hakan Demirtel  The  questionnaire  was  sent  to  777  employees  of  the  Ministry  of  Justice  as  online  application.  The  data  of  questionnaire answers given online were evaluated using Excel programme. Totally 253 persons participated in  the questionnaire and replied all questions. 

4. Analysis for the ministry of development   There  are  several  methods,  either  ICT‐based  or  conventional,  in  access  to  or  sharing  of  organizational  knowledge. Within this framework, not only ICT systems, but also conventional methods were included in the  questionnaire to analyse the present situation in the Ministry and to understand the contribution of ICT.    

4.1 ICT systems towards knowledge access and knowledge sharing  Within the framework of the study, all knowledge systems were scrutinized and ICT systems facilitating direct  knowledge access and knowledge sharing were included in the scope of analysis.        KB‐eb  Electronic  Records  Management  System  (MoD‐ERMS):  This  system  is  used  by  whole  Ministry.  All  formal  correspondence  within  the  Ministry  has  been  carried  out  over  this  system  where  all  managers  and  employees use e‐signature.    MoD  Intranet  Site  (MoD‐IntraNet)  :  It  contains  all  organizational  announcement  and  prepared  forms,  shortcuts for access to other ICT systems, discussion forms and collaboration tools.    Archives and Document Management System (ADMS): The electronic system that stores and provides access,  within defined authorization framework, to  working papers created by the ministerial staff as well as other  source documents used for knowledge creation.      MoD  official  web  site:  The  website  that  includes  all  official  knowledge  and  outputs  as  well  as  news  and  announcements about the Ministry.    MoD‐Search  Knowledge  System  (MoD‐Search):  There  is  metadata  set  for  resource  discovery  within  the  Ministry. All systems of knowledge sharing have been adapted to this set, and this searching system allows for  resource discovery from a single point.         Official  e‐mail  system:  It  is  the  institutional  e‐mail  system  with  @kalkinma.gov.tr  extension.  All  employees  have an official e‐mail account. This system has functions of meeting organization and calendar management.  

4.2 Conventional methods for knowledge access and knowledge sharing   The  conventional  methods  directly  related  to  the  subject  are  classified  in  four  main  groups,  intra‐ organizational  dialogue  and  collaboration,  intra‐organizational  meetings/trainings,  communication  within  project  groups  and  printed  organizational  records/documents/publications.  Besides,  documents  in  personal  computers,  despite  their  ICT  basis,  are  considered  as  conventional  methods  because  of  their  private  characteristics.  

4.3 Information about participation in questionnaire  The  questionnaire  was  sent  to  777  employees  with  different  titles  and  answered  completely  by  253  employees. The number and share of employees, who replied the questionnaire (respondents), according to  their titles are given below (See Table 1). Accordingly, the highest rate of participation is reached at 54% by  those having the title of “assistant expert.”  Total participation rate is 33% which is considered as a sufficient  proportion.     Table 1: Number and ratio of employees receiving and/or replying the questionnaire according to title  Title 

Total Replied Ratio

Director General and upper positions

14 



43% 

Head of department 

51 

17 

33% 

Expert 

286 

92 

32% 

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  Özlem Gökkurt Bayram and Hakan Demirtel  Title 

Total Replied Ratio

Assistant Expert 

139 

75 

54% 

Director 

11 



18% 

Administrative personnel 

145 

35 

24% 

Technical personnel 

41 

10 

24% 

IT personnel 

90 

16 

18% 

Total 

777 

253 

33% 

Most respondents stated that they used ICT applications mentioned in the study every day (83%). The rate of  respondents  who  use  ICT  applications  more  than  once  a  week  including  those  using  every  day  attains  96%  totally (See Table 2).  Table 2: Usage frequency of ICT systems by participants  Usage of ICT systems 

Number of users Ratio

Every day 

210 

83% 

More than once a week

34 

13% 

Once a week 



2% 

Once a mount 



1% 

Never 



1% 

Total 

253 

100%

All  the  ratios  for  everyday  usage  of  ICT  systems  are  high  enough  for  all  groups  except  technical  personnel  group. The lower ratio in comparison to the others for this group might be the subject for further analysis (See  Figure 1).    

  Figure 1: Everyday usage ratio by titles 

4.4 Evaluations about the questionnaire  4.4.1 Access to knowledge  The primary three tools of knowledge access most preferred by the staff of the Ministry of Development are  MoD‐Net  intranet  site  (226),  official  e‐mail  system  (216),  and  MoD‐ERMS  system  (215)  consecutively  (See  Table  3).  As  seen  in  the  levels  of  usage,  the  Ministry  staff  prefers  for  ICT  applications  for  knowledge  access  rather than conventional methods. The usage frequency of MoD‐Net intranet site at 89 % is noteworthy. The  choice  of  intra‐organizational  dialogue  and  collaboration,  which  is  the  most  commonly  used  conventional  method  for  knowledge  access  (174)  could  only  rank  5th.  In  this  field,  the  first  four  methods  consist  of  ICT  applications.   Table 3: ICT systems and conventional methods to access knowledge  ICT systems/conventional methods  MoD‐ERMS  MoD‐Net 

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Number of usage  Ratio  215 

85% 

226 

89% 

  Özlem Gökkurt Bayram and Hakan Demirtel  ICT systems/conventional methods  ADMS 

Number of usage  Ratio  100 

40% 

MoD official web site 

185 

73% 

MoD‐Search 

36 

14% 

Official e‐mail system 

216 

85% 

Intra‐organizational dialogue and collaboration 

174 

69% 

Intra‐organizational meetings/trainings 

156 

62% 

Communication within project groups 

62 

25% 

Printed organizational records, documents, publications

130 

51% 

Documents in personal computers 

163 

64% 

MoD‐Net  intranet  site  is  the  most  preferred  system  to  access  knowledge.  It  is  seen  that  it  has  quite  equal  usage ratios for all user groups. It can be defined as a successful information system and satisfies all the needs  of user groups successfully (See Figure 2).  

  Figure 2: Use of MoD‐NET to access knowledge by titles  4.4.2 Knowledge sharing  For the staff of the Ministry of Development, the three most preferred tools of knowledge sharing have been  identified  as  official  e‐mail  system  (238),  MoD‐ERMS  system  (176)  and  intra‐organizational  dialogue  and  collaboration  (166) consecutively (See Table 4). In terms of rates of usage, the Ministry staff gives preference  to ICT applications for knowledge sharing. It is remarkable that the rate of e‐mail usage peaks at 94% regarding  knowledge sharing.     Table 4: ICT systems and conventional methods to share knowledge  ICT systems/conventional methods 

Number of usage  Ratio 

MoD‐ERMS 

176 

70% 

MoD‐Net 

106 

42% 

ADMS 

77 

30% 

MoD official web site 

61 

24% 

Official e‐mail system 

238 

94% 

Intra‐organizational dialogue and collaboration 

166 

66% 

Intra‐organizational meetings/trainings 

141 

56% 

Communication within project groups 

63 

25% 

Printed organizational records, documents, publications

76 

30% 

Documents in personal computers 

88 

35% 

Official e‐mail system is the most preferred system for knowledge sharing. The system is very popular for all  user groups. Only technical personnel group, whose usage is far behind of the average value. The needs of this  group should be determined in future investigations to increase the usage rates (See Figure 3).    

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  Figure 3: Use of official e‐mail system to share knowledge by titles  4.4.3 Effective tools of knowledge access and knowledge sharing   The  participants  of  questionnaire  were  asked  about  the  most  effective  tools  of  knowledge  access  and  knowledge sharing. The most effective tools for participants are specified as official e‐mail system (177), MoD‐ ERMS  (153),  and  MoD‐Net  (148),  with  rates  of  preference  for  these  three  systems  as  70%,  60%,  58%  consecutively,  all  above  50%.  The  rate  of  marking  for  conventional  methods  could  not  exceed  30%.  This  situation is interpreted as participants believe in the benefits of ICT tools in knowledge access and knowledge  sharing (See Table 5).  Table 5: Efficient ICT systems/conventional methods to access and share knowledge  ICT systems/conventional methods 

Number of users  Ratio 

MoD‐ERMS 

153 

60% 

MoD‐Net 

148 

58% 

ADMS 

48 

19% 

MoD official web site 

59 

23% 

MoD‐Search 



0.4% 

Official e‐mail  system 

177 

70% 

Intra‐organizational dialogue and collaboration 

75 

30% 

Intra‐organizational meetings/trainings 

29 

11% 

Communication within project groups 



1% 

Printed organizational records, documents, publications

27 

11% 

Documents in personal computers 

12 

5% 

4.4.4 Motivations for knowledge sharing   The prominent motivational factors taking into consideration all tools of knowledge sharing are challenge of  work (46%), sense of success (35%) and sense of responsibility (35%) (See Figure 4 and Table 6). It is seen that  motivational factors in knowledge sharing rather focus on ICT systems as in all other findings. Whereas official  e‐mail  system  ranks  first  for  motivations  of  sense  of  success  (61%),  sense  of  responsibility  (54%)  and  recognition of job done (62%), MoD‐ERMS is prominent for motivations of operational autonomy (70%) and  challenge  of  work  (83%).  Among  conventional  methods,  intra‐organizational  meetings/trainings  is  the  only  conventional  method  in  the  first  place  as  regards  promotional  opportunities  motivation.  Choice  of  the  motivation of challenge of work as high as 83% for MoD‐ERMS (209 choices) demonstrates the importance and  indispensability of ICT tools for knowledge sharing (See Table 6).        It  has  been  observed  that  when  only  ICT  systems  are  taken  into  consideration  in  knowledge  sharing,  motivational  factors  change  slightly  enlisted  as  challenge  of  work,  recognition  of  job  done  and  sense  of  responsibility.          However,  it  is  observed  that  there  are  ICT  systems,  which  are  under  the  average  of  knowledge  sharing  motivations. The most conspicuous system among others, is MoD‐Search with 9%. On the other hand, ADMS 

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  Özlem Gökkurt Bayram and Hakan Demirtel  (22%) and MoD official web site (29%) with knowledge sharing ratios are appeared as the first priorities to be  renewed. 

  Figure 4: Motivation factors   Table 6: Motivations for knowledge sharing in terms of ICT systems and conventional methods  ICT systems/conventional methods  MoD‐ERMS 

sense  operatio promotion sense of  recogniti challen of  nal  al  Averag responsibil on of job  ge of  succes autonom opportuni e  ity  done  work  s  y  ties  27%  46%  58%  70%  14%  83%  50% 

MoD‐Net 

39% 

32% 

30% 

26% 

30% 

42% 

33% 

ADMS 

25% 

24% 

24% 

15% 

14% 

30% 

22% 

MoD official web site 

28% 

26% 

22% 

25% 

30% 

40% 

29% 

MoD‐Search 

6% 

8% 

6% 

9% 

10% 

14% 

9% 

Official e‐mail  system  Intra‐organizational dialogue  and collaboration  Intra‐organizational meetings/trainings 

61% 

54% 

62% 

30% 

37% 

63% 

51% 

50% 

49% 

36% 

29% 

45% 

54% 

44% 

48% 

42% 

33% 

27% 

47% 

53% 

42% 

Communication within project groups  Printed organizational records,  documents, publications  Documents in personal computers 

33% 

33% 

27% 

20% 

32% 

38% 

31% 

39% 

32% 

31% 

32% 

42% 

44% 

37% 

32% 

40% 

23% 

23% 

46% 

45% 

35% 

Average 

35% 

35% 

32% 

28% 

32% 

46% 

35% 

5. Conclusion  ICT applications make important contributions to formation of organizational memory through recording of all  organizational knowledge assets, either structural or non‐structural, in a scrutinized manner and to creation of  new  knowledge  through  sharing  of  among  employees.  According  to  the  results,  ICT  applications  have  much  more preferable than conventional methods in processes of knowledge access and knowledge sharing.     For  ICT  to  assume  an  efficient  role  of  in  knowledge  management,  not  only  infrastructural  elements,  system  architecture and functionality of application, but also compatibility with individual and organizational learning  culture  contribute  to  dissemination  of  knowledge.  According  to  Hendriks  “The  key  to  success  in  knowledge  sharing  is  that  the  personal  ambition  should  match  the  group  ambition.  Therefore,  also  the  touchstone  for  successful ICT applications for knowledge sharing is the question how they relate to these ambitions, and to  the motivation of knowledge workers to match them.” (Hendriks 1999). In this study, the findings of research  conducted  in  MoD  as  an  organizational  case  study  have  revealed  that  there  is  a  correlation  between  the  individuals’ desire to get information about their jobs and attitudes towards using organizational knowledge  sources  and  that  ICT  applications  influence  access  to  and  sharing  of  organizational  knowledge  widely.  Knowledge sharing motivation factors described in literature have been presented through ICT systems in MoD  where those factors are supported by more than 50% usage rate of e‐mail and ERM systems.  Frequent usage  of  ICT  systems  by  the  organization  employees  is  crucial  to  develop  future  sustainability  criteria  for  these  systems.  Renewing  information  systems  in  terms  of  content  and  technical  aspects  should  be  considered 

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  Özlem Gökkurt Bayram and Hakan Demirtel  according to the user needs to keep continuation in raising motivation levels of sharing knowledge. In addition,  the survey revealed some ICT systems that have low motivation impact. In this sense, what factors might be  related to the low motivation levels of sharing knowledge for MoD_Search, ADMS,  and MoD official web site  should  be  examined  for  the  future,  with  a  view  of  finding  the  organizational  cultural  approach  to  value  ICT  systems.     Another finding of the research is that ICT applications are more efficient than conventional methods in terms  of motivations of knowledge sharing at organizational level.  The survey results showed that digital culture has  had  a  widespread  positive  impact  on  sharing  knowledge  across  the  Organization.  Only,  the  reasons  of  low  usage by technical personnel group among all user groups need to be investigated in depth.    Efficient  and  widespread  knowledge  sharing  at  organizational  level  has  great  importance  in  increasing  organizational competitiveness and providing sustainability. In order to carry out this function, it is necessary  to  establish  knowledge  systems  that  keep  records  of  all  organizational  knowledge  assets  and  thereby  to  disseminate knowledge sharing. Proper use of motivational factors influences active and ubiquitous sharing of  knowledge in a positive direction.         

References  Chennamaneni A.,Teng J., Raja M.K. (2012), “A unified model of knowledge sharing behaviours: theoretical development  and empirical test”, Behaviour & Information Technology, Vol 31, No.11, pp 1097‐1115.  Cruywagen, M., Fourie, L.C.H., Gevers, W.R. 2005. “Understanding the role of enterprise portals in knowledge  management”, 7th Annual Conference on World Wide Web Applications, 29‐31 August, Cape Town.  De sitter, L.U. (1994), “Synergetisch proceduren: Human resources Mobilisation in de produktie; een inleiding in  strutuurbouw (Synergetic production: Human resources mobilisation in production; an introduction to structuration),  Assen, Van Gorcum.  Hendriks P. (1999), “Why Share Knowledge? The Influence of ICT on the Motivation for Knowledge Sharing”,  Knowledge &  Process Management, Vol 6, No. 2, pp 91‐100.  Herzberg, F. (1968), Work and the nature of man, London, Granada Publishing.  Herzberg, F. (1987), “One more time ‐ How do you motivate employees?”, Harvard Business Review, Vol 65, No. 5, pp 109‐ 120.   Hopfgartner, F. et al (2008), “Search trails using user feedback to improve video seach”, In: Proceedings of the 16th ACM  international conference on multimedia, Vancouver, Canada. New York: ACM, pp 339‐348.   Hung S.,Lai H. and Chang W. (2011), “Knowledge‐sharing motivations affecting R&D employees' acceptance of electronic  knowledge repository”, Behaviour & Information Technology, Vol. 30 Issue 2, pp 213‐230.   Lee, S.C. and Kelkar R.S. (2013), “ICT and knowledge management: perspectives from SECI model”, The Electronic Library,  Vol 31, No. 2, pp 226‐243.  Matusik, S.F. and Hill, C.W.L (1998), “The utilization of contingent work, knowledge creation, and competitive advantage”,  Academy of Management Review, Vol 23, No. 4, pp 680‐697.  Matusik, S.F. (2002), “An empirical investigation of firm public and private knowledge”, Strategic Management Journal, Vol  23, No. 5, pp 457‐467.   McGrath, J.E. and Hollinshead, A.B. (1994), Groups with technology. Ideas, evidence, issues, and agenda, Thousand Oaks,  CA, Sage.  Nanoka, I. (1994), “Dynamic theory of organizational knowledge creation”, Organization Science, Vol 5, No. 1, pp 14‐37.  Sun, Z. 2004. “A waterfall model for knowledge management and experience management”, Proc of 4th Iinternational  Conference on Hybrid Intelligent Systems, Japan, IEEE Press, pp 472‐475.  Sun, Z., Hao, G. 2006. “HSM: A hierarchical spiral model for knowledge management”, Faculty of Commerce‐Papers, p 36.  Tsai M. and Cheng N. (2012), “Understanding Knowledge Sharing between IT Professionals ‐ An Integration of Social  Cognitive and Social Exchange Theory”, Behaviour & Information Technology, Vol 31, No. 11, pp 1069‐1080.   

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Blueprinting a Knowledge Sciences Center to Support a Regional Economy Denise A. D. Bedford1, John Lewis2 and Brian Moon3 1 Goodyear Professor of Knowledge Management, Kent State University Kent Ohio 2 Founder, Explanation Age LLC; Adjunct Faculty, Kent State University, Kent Ohio 3 Chief Technology Officer, Perigean Technologies; Adjunct Faculty, Kent State University, Kent Ohio [email protected]

Abstract. As cities and regions transform from an industrial to a knowledge economy, there is a need to build new working relationships among academic, business communities, labor and workforce, civil society, and the technology sector – to create Knowledge Cities. A Knowledge City values all kinds of knowledge, is grounded in an economy that runs on st knowledge and intellectual capital, and encourages knowledge markets and transactions. The 21 century knowledge economy is dependent upon knowledge cities and regions, representing a major shift from the industrial economy. Transforming an industrial city to a Knowledge City is not a trivial task. It requires that all members of the society make the transition together. Currently, there are no institutions that can facilitate this role. This paper considers how a Knowledge Sciences Center might fulfill that role, and reports on the thoughts of over 200 participants of the Knowledge Sciences Symposium held in Canton, Ohio, and Washington DC in 2013. Keywords: Knowledge sciences center, knowledge cities, knowledge economy, economic transformation, Knowledge Sciences Symposium

1. Knowledge Sciences Symposium There is a need to redefine many of our institutional relationships and the way that our institutions work as we st transition to a knowledge economy and a knowledge society in the 21 century. No aspect of society remains unchanged in a knowledge economy – every sector, every individual, every organization and business changes. What we value shifts – intellectual capital is as important as is financial or physical capital (Andriessen 2004) (Bontis 2001) (Bontis 2002) (Bounfour and Edvinsson 2005) (Kratke 2011). In an industrial economy, academia was a haven for cutting-edge knowledge. It was where you went to learn. Solutions to industrial economy challenges are structured and managed because industrial economy challenges are linear, predictable and manageable. In the knowledge economy, there is as much or more knowledge being created outside of academia as there is within (Peters 2007). Knowledge economy challenges are chaotic, dynamic and “wicked”. The knowledge economy is not as segmented or hierarchically structured as was an industrial economy – the transformation requires that all sectors and all stakeholders move together rather than move individually. Businesses understand the challenges of competing in a knowledge-based economy. Academia needs to learn from and deliver outcomes that can be used by business. Technology needs to move away from an industrial way of working or designing products for structured work to designing for a knowledge economy. The labor force needs to continuously learn – and learn not just from business or from union provided training – but to engage with academia. Learning today goes beyond formal degree programs. MOOCs, workshops, online webinars, in house training, and continuous lifelong learning are the norm. Academia needs to provide learning opportunities not just for those who can pay for formal credentials but to those who need to learn (Vardi 2012) (Rodriguez 2012). Knowledge Cities are emerging all around the globe from the remnants of industrial cities (Baqir and Kathawalla 2004) (Brenner and Kell 2003) (Carillo 2004) (Carollo 2006) (Castells and Hall 1994) (Dvir and Pasher 2004) (Edvinsson 2006) (Ergazakis et al 2009) (Garcia 2007) (Goldberg Pasher and Sagi 2006) (Matthiessen Schwarz and Find 2006) (Metaxiotis and Ergazakis 2008) (Ovalle Barquez and Salomon 2004) (Papalambros 2011) (van Winden et al 2012). The transition, though, does not always include all members or organizations of the industrial city.

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Denise A. D. Bedford, John Lewis and Brian Moon In September 2013, an emergent community of 200 people from across the country gathered in Canton, Ohio, and in Washington DC, to hold a Knowledge Sciences Symposium (www.kent.edu/slis/programs/iakm/symposium/index.cfm). The purpose of the Symposium was to bring together knowledge management thought leaders from businesses and organizations, technology sector, academia, civil society organizations and the broader workforce to design a blueprint for a Knowledge Sciences Center in order to support the transformation of st local industrial economies into the 21 century knowledge economy. The Symposium discussions were preceeded by five webinars in July 2013. The Symposium participants (“Participants”) designed a blueprint for st a 21 century Knowledge Sciences Center that focused on learning and career development, research and development, advocacy, advising and outreach and partnerships. The goal of this paper is to share that blueprint with the knowledge management community in order to elicit feedback and to find other people interested in moving the vision forward.

1.1 Rationale for a Knowledge Sciences Center Participants envisioned a Knowledge Sciences Center as a source that would help a local economy and society st make an effective transition to the 21 century knowledge economy. It was important to capture within the name of this Center the idea that the activities would go beyond what has typically been described as Knowledge Management. As a science, the range of activities would need to span the theoretical and academic foundations as well as the commercial and practical applications. The Knowledge Sciences Center we envisioned required a new blueprint if it was to serve this purpose.

1.2 Existing Models There are many examples of research institutes,, science centers and think tanks, but none that aligned with the community and economy focus of the Knowledge Sciences Center. Research institutes and science centers are designed to leverage expert knowledge, often focused on theoretical research or the R&D needs of specific funding organizations (Anttiroika 2004) (Appold 2003) (Chen and Choi 2004) (O’Mara 2005). The intended stakeholders are other highly credentialed or deeply resourced organizations, and the engagement models are heavily dependent upon public or endowment funding sources. Another example of a science center is a Think Tank where experts focus on investigating current topics for the purpose of advocacy or public policy development (Mendizabal 2010) (Goodman 2005). While these models certainly serve a purpose, Participants agreed that they do not meet the needs of a city or region making the transition to a knowledge economy. There was a clear consensus that a new model was needed.

2. Design Issues The Participants envisioned a new kind of Center that would act as a bridge between the worlds of academia, business, labor and technology, and could find no existing models to use as a blueprint. The design and vision emerged as we explored five issues (Figure 1). We needed to know who would participate in the center (Issue 1). We needed to know what kinds of activities the center would support to achieve its goals (Issue 2). We needed to know how stakeholders would engage (Issue 3). We needed to know how we would fund the Center (Issue 4). Finally, we needed to know what it would look like – physically and virtually (Issue 5). How do we engage? What do we do?

Issue 3

Issue 2

Who are the stakeholders? Issue 1

How do we fund? Issue 4

Knowledge Sciences Center

Figure 1. Knowledge Center Vision and Design – Five Key Issues

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What does it look like? Issue 5

Denise A. D. Bedford, John Lewis and Brian Moon Issue 1: Who are Participants in a Knowledge Sciences Center? We began the discussion of stakeholders with an assumption that there were five primary interest groups, including academic, business, labor, civil society and technology developers. It quickly became obvious that these groups were neither comprehensive nor inclusive of possible stakeholders. We realized we needed to look at potential stakeholders from multiple perspectives. In the end, the Participants concluded that any member of the community that was being served by the Knowledge Sciences Center was a potential stakeholder, including but not limited to: academic, religious, and educational institutions, libraries, localized ownership, NGOs, governmental organizations – federal, state, local, county , academics, congressional staff, service organizations (boy scouts, girls scouts, youth groups, 501(3)c organizations, charitable organizations, military support organizations, professional societies, chambers of commerce, city visitors’ bureaus, unions, local government agencies such as fire, police, emergency management, innovators in search of partners, elected government officials, and voluntary sector organizations. The list of participants clearly requires a different kind of organization than traditional institutes, science centers or think tanks. Understanding stakeholders along a single dimension such as their economic role presented a risk, but understanding stakeholder interests and needs will be necessary for brainstorming the types of activities, products and services the Center should provide. As a first step, Participants suggested a Knowledge Sciences Center should prepare persona. Persona templates would help to understand stakeholders’ goals, their different roles and responsibilities, their technology environment and skill levels, social media behaviors, and pain points. All of these dimensions are critical to planning activities, to designing access and supporting collaborative environments, to financing activities and to designing engagement models. Issue 2: What Do We Do? A core question for the blueprint is, “What does the Center do for these stakeholders?” We were fortunate to have more than 200 seasoned knowledge management professionals share their ideas on activities. We were also fortunate that this group had an implicit understanding of what we meant by knowledge sciences – its goals, its scope – and by what it means to practice knowledge management - its methods and tools. The participants proposed five areas of focus drawing upon their profound knowledge of the field and the challenges inherent to the transformation (Figure 2).

Figure 2. Business Capabilities of a Knowledge Sciences Center The five broad areas were: (1) Learning and Career Development; (2) Research and Development; (3) Advocacy; (4) Advising; and (5) Networking and Partnerships. A significant portion of the in-person meetings in Ohio and Washington DC were devoted to brainstorming activities for these five areas. As shown in Tables 15, there was no shortage of ideas.

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Denise A. D. Bedford, John Lewis and Brian Moon Table 1. Learning and Development Activities Activity Name Center of Excellence Reference materials

Knowledge Sciences Learning Programs

(KS)

KS Book and Journal Clubs KS TV Knowledge Sciences Learning Center Knowledge Visitor Center KS FAQs Student Internships Practicum

and

Brief Description Business Growth Maps, Case Studies, Lessons Learned/Smart Lessons, Information Repositories – Wikimedia Repositories for Other Hubs/Chapters, KM Body of Knowledge, KM Standards, Knowledge Visualizations, Open Repository or Wiki, Real Work Scenarios, Roadmaps, ROI Methods, Scalable Solutions, Standards Organizations, , KM Principles MOOCS, ADDIE Model Training and Collaborative Workshops, Webinars, in House Training Programs for Organizations, Retraining Programs With Economic Development Units. Open Discussions of Recent Works to Help Promote Research Uptake KM Tedtalks, Open Webinars, KM Internet Travel Channel, Community of Practice Study Tours (Virtual and Physical) Certificate Programs, Competitions for Knowledge Games, Learning Games – Simulations, Pointers to Courses, Pointers to Programs, Transformation Learning Support Orientation to rhe Knowledge Society and Knowledge Economy, KM Tourism, KM Concierge Basic Q&A for KM Novices, FAQs for Individual Topics, KM Study Guides Project and Internship Opportunities, Student Resumes and CVs, Matchup Projects and Industry Needs

Table 2. Research and Development Activities Activity Name KS Experimental Test Lab and Incubator

Knowledge Collaborative Development

Sciences Research &

Knowledge Sciences Information Access Improvement Knowledge Challenge Workshops and Projects Knowledge Elicitation Lab General Research & Development Knowledge Economy Future State Visions Knowledge Sciences Research for Economic Sectors and Industries

Brief Description Access to Smart Knowledge Systems, Technology Transfer Facilitation and Adoption, Novel Approaches to Licensing Or Purchasing Tools for Groups Or Communities, Guidebooks for Scalable and Right-Sized Solutions, Technology Transfer Opportunities, Identification of Reasonably Priced Platforms for Small and Medium Sized Organizations, Evaluate Products for Vendors, Focus Group Testing for Vendors, Open Source Software Development for Knowledge Sciences Community – in Collaboration With Other Disciplines Collect Research Needs Ideas , Creation of Use Cases and Case Studies, Enterprise Scalable Solutions, Interoperable Solutions, New Approaches to Translation and Interpretation of Regulations, Policies and Standards, Provide Real World Problems for The Center to Work On, Research Agenda, Research Needs Statements, Standards and Guidelines for Findability Knowledge Sciences Languages, Knowledge Sciences Organization Systems (e.g., Classification Schemes, Thesauri, Authoritative Lists) Global Expert Teams, Special Topics, Wicked Problem Teams Knowledge Elicitation Training, Knowledge Loss Prevention and Capture Strategies Assess Research Capabilities, Benchmarking Opportunities, Knowledge Cities Index, Knowledge Economy Models, Knowledge Society Behavior Codes and Ethics, Project Assessments, KM Rsearch Agendas, Innovation Research Economic Sector Scans, Industry Scans Knowledge Society Futures. Knowledge Futures for Specific Organizations

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Denise A. D. Bedford, John Lewis and Brian Moon Table 3. Advocacy Activities Activity Name Active Engagement with Knowledge Economy Transformation Executive marketing and communication about KM KM Competencies

Activity Examples Adaptive Society Change Information Technologies, Innovation to Gain Market Share, Libraries Coached to Communicate Knowledge Management in Real-World Terms Knowledge Sharing Workshops, Lessons Learned Engaging With Corporate Executives Cost Reducing Solutions, Early Maturity Needs, Efficient and Effective Solutions , Facilitation Services, Larger Strategic Perspective , Problem Solving Approaches That Leverage KM, Standards Graphs Showing ROI Marketing Center for All Things KM, Ability to Integrate with Other Domains, Providing Opportunities for Professionals to Socialize and Exchange Ideas

Sponsorship and Representation at Major Conferences and Social Activities Development of KM Legal and Ethical Codes KM Standards Development and Promotion

Advocacy With Professional Societies, Collaboration With Human Capital and Human Resource Management Establish Committees to Define Standards for KM Professionals, Develop Standards for KM Professionals, Assess the Validity for Standards for KM Professionals, Disseminate Standards for KM Professions Criteria for Teaching and Selection, Subversive Missions - Influencing Education and R&D, Gaming and Simulation, Education Technology, Cognitive Sciences, Lifelong Learning, Communications Receiving and Broadcasting Knowledge Management Projects Throughout the KSC Network, Promoting Stakeholder Capabilities Working with Publishers to Develop Pricing Models That Support Broad Access to Knowledge Management Research and Development, Case Studies and Thought Papers, Develop Online Open Access Journals and Trade Publications to Promote Stakeholder Knowledge and Learning. KM Awards and Recognition of Leading Organizations and Individuals

Promotion of KM at all levels of education Promotion of KM Project Opportunities Promotion of Open Access KM Journals Knowledge Awards

Management

Industry

Table 4. Outreach and Partnership Activity Name Annual KM Surveys Consulting and Advising Development and Collection of Metrics and Stories Funding proposals and opportunities Knowledge Management Mentorships Open Virtual Laboratory

Brief Description Understand Stakeholder Needs, Local and Networked Resources Establish Requirements, Create “People Finder” (e.g., through LinkedIn), Differentiate Types of Consulting the Center Does / Pilots, Develop a Methodology for Matching Stakeholders with Expertise for Consulting Purposes / Services, Identify Tools Repository Performance Plan Examples, Price Points, Provide Strategic Maps and Assistance to Cities and Towns Crowdsourced Solutions, Crowdsourced Funding for KM Research Needs, Short Term Services Mentoring Across Organizations, Mentoring Across Ages Learning Management System, Sandbox Tool – Simulators, Prototypes, “Authoritative” Tools, Customer Relation System, Profile, Access Rights, Track & Trend Analysis, Library of Access to Authoritative KM Content, Ontologies, Analysis, Blogs, Social Media Presence, Tool “Reviews”/ Recommendations

Table 5. Advising Activities Activity Name Broadcasting KS Activities Networking and Public Outreach

Open Meetings Spaces Outreach to Other Disciplines and Economic Sectors Social Media Support for Dynamic Conversations

Activity Examples “News” Source for Innovative KM Practices, KM Blogs, Investigative Reporting, Electronic Calendar of Global KM Events Community Networking, Linking Consultants and Clients, Affinity Grouping within and across Sectors, Networking across City Organizations, Links From Citizens to Thought Leaders, Knowledge Connectors – Linking Those with Problems and Those with Solutions, Knowledge Practitioners Directory Experiments, Brainstorming Sessions, Knowledge Jams, Partnership Outreach and Extension Service Links to Twitter Feeds Related to Knowledge Sciences

The list serves as a catalog of opportunities for any group that wishes to take up the challenge of building a Knowledge Sciences Center. It serves as a tool for prioritizing and implementing activities as relationships with stakeholders develop. Clearly, there are variations in cost, value, duration and sustainability, and lead times.

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Denise A. D. Bedford, John Lewis and Brian Moon The significant number of activities recommended reinforces both the need for and the lack of existing support provided by current players. It is clear that no one organization or institution can fulfill all of these needs. Only through working in a consortium or cooperative environment can a Knowledge Sciences Center meet these needs. Different activities and stakeholders also mean different engagement models. Issue 3: How Do We Engage? The Center’s engagement strategy is complex. Multiple engagement models would be required because different kinds of activities require different ways of working. Multiple models are needed because stakeholders’ interests, environments and resources vary. Participants discussed five possible engagement models, including: (1) Traditional academic R&D model; (2) Agricultural extension service model; (3) Knowledge services corps model similar to that of the Peace Corps; (4) Consortium model; and (5) Business franchise model. The first envisioned model would support applied research that is needed by the community or for which there is no other logical source. This engagement model looks like a traditional academic science center where knowledge resides in the center and is channeled out to the community. Such a model assumes there would be formal contracts in place with funding agencies or organizations, and that all research standards, records and protocols would need to be maintained. In order to support research, access to library resources is also required. The Center would have to work with the university or college to contract for access. The second envisioned model resembles that of an agricultural extension service. This model would support the development of solutions needed by the community, the non-formal learning needs of the community, and technology transfer issues. In this model the Center uses visits to stakeholders as a way of staying in touch with the needs of the local community, gather input to policy formulation, and provide targeted client advice. This engagement model would be a good fit for Learning and Career Development, and Advising activities. The third envisioned model resembles a Knowledge Services Corps – similar to a missionary model or Peace Corps structures where knowledge evangelists engage directly with the community to foster conversations and knowledge transactions while leveraging the Center’s infrastructure and resources. This engagement model might leverage graduate students, students fulfilling practicum or internship requirements, who were supported by community scholarships, or volunteers earning community service or continuing education credits. This model would align well with Outreach and Partnership activities. Tje fourth envisioned model resembles that of a consortium where the Center acts as a cooperative partner with other universities, institutions, and agencies to support activities. This model supports activities that require or benefit from a collaborative environment. This engagement model would be a good fit for Advocacy activities, where the Center would partner with other organizations to move initiatives and standards forward on behalf of the larger community. And a fifth envisioned model – business franchise – was suggested. This was a particularly interesting model because it would allow the Center to reach out into the community through a hub-spoke model, and because it would provide conceptual buy-in and ownership relationships. “Franchise owners” at local libraries or universities or agencies would provide space or connectivity through which stakeholders could engage with the Center. Issue 4: How Do We Fund the Center? As a Knowledge Sciences Center our goal would be to mobilize and promote ideas. As with any such venture, funding will be necessary for sustained effect. Participants were asked to consider what kind of an innovative funding model would support Learning and Career Development, Research and Development, Advocacy, Advising and Networking. The answer to this question was similar to other answers – multi-faceted, dynamic and flexible. Funding models – as engagement models – must be relevant to the activity and to the stakeholders. Learning and Career Development activities may leverage a variety of funding models ranging from entirely open source contributed courses accessible on MOOCs, to no-fee open webinars, to fee-based workshops and on-site training courses, to formal certification or testing services. Advocacy activities would leverage in kind resources, community grants, crowd-funding, or direct sponsorship.

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Denise A. D. Bedford, John Lewis and Brian Moon Research and Development may be funded through grants, research funding awards, and joint sponsored funding. Research may also be supported by in-kind contributions of the members of global expert teams. The model will depend on the nature and intensity of the research. R&D projects that support technology development or evaluation may be sponsored by technology vendors or venture capitalists. Research that has a direct community application may be funded through crowd-sourced or in-kind contributions. The nature of the funding must also take into consideration the intellectual property rights of the products and services. In some cases, established intellectual property provisions will apply. In other cases, creative commons and open source models might be more appropriate. Another funding model would be pay-for-service. This may be appropriate for Advising activities. Again, there would need to be a progressive pricing strategy to ensure that all members of the community can afford to participate in these activities. The lowest pricing option should be an in-kind contribution or a barter system. In-kind contributions strengthen the Center by increasing its stock of knowledge. Where the Center might support in-kind contributions or contributed services, it would be necessary for stakeholders to have access, and the Center to support the idea of a “knowledge bank”. The idea would be that as stakeholders contribute to the Center, they earn intellectual credit that can be applied to future requests. Also proposed was a fee-based membership model.. The challenge with membership models,though, is that they lock and organization into providing predictable and pre-defined services to members. This typically leads to the need to define generic products and services rather than on-demand or stakeholder-focused activities. We have observed that institutions based on memberships over time can become bogged down in the administrative tasks of supporting members. The membership model might also price many community members out of most engagements. The Participants thought that a membership model should be considered only after all other options had been explored. In addition, to having a stock set of funding models, the Center would need to have a robust list of funding sources and opportunities. On-going fundraising relevant to current or planned engagements would be one of the Center’s major operations. Issue 5: What Does the Center Look Like? The Participants were of one mind in recommending both a virtual and a physical preference. The sentiment was that the physical presence should be minimalist and networked to increase visibility. The physical space should ideally be located on a university or college campus to ensure there is easy access to faculty and students, as well as to research protocol support. However, participants suggested that a remote or satellite campus might be more appropriate to ensure that the Center can establish its own innovationoriented, dynamic and community-focused organizational culture. The nature of the space should be open, heavily technology-enabled, with spaces for stakeholders to meet and work. The physical space should feel like an open knowledge sharing environment. As the Center grows, there may be a need for spaces for visiting scholars or short-term team work spaces. Depending on the nature of the stakeholders, their competencies and environments, the physical Center may need to provide access to the Center’s virtual space. We would also expect “Center franchisees” to provide community-based access to the Center. The Center’s virtual structure includes online collaboration environments, access to social media and cloud-based repositories. The Center is also virtually linked to other similar-Centers. The Center’s virtual presence might leverage cutting edge technologies under development or testing by technology developers or vendors. The heavy reliance on virtual access would present both challenges and opportunities. In terms of challenges we would expect that many stakeholders would not have affordable high-bandwidth access. We also expect that digital literacy rates might be low for some stakeholders. This presents opportunities, though, for coaching and mentorships particularly where students and community members contribute training time in exchange for other services.

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3. The Blueprint The participants generated a wealth of ideas and options. While a number of support activities might be consistently supported through stable funding sources, it is clear that many will be ‘designer-oriented’. In other words, a stakeholder engagement and funding design model might need to be put in place for each activity. This is not the way that most organizations work. Thus, the participants agreed that an engagement design model would need to be developed for the Center. The model favored by the participants was an emergent engagement design (Figure 3). The design process would begin with a proposed activity. To ensure that the Center stays true to its goal of facilitating the community or local area’s transition to a knowledge economy, deployment needs to be carefully managed and aligned with demand. The Center would put in place the virtual infrastructure, and engage stakeholders in activities that required low investments but could demonstrate high value. As value is recognized and promoted, stakeholder engagements would expand and build the Center’s reputation.

Stakeholder Competencies Ownership Issues

Stakeholder Environment Engagement Design

Activity Engagement Model

Outputs and Outcomes Funding Options Figure 3. Knowledge Center Activities

4. Observations and Next Steps The purpose of sharing these ideas is to encourage communities around the world to consider starting a Knowledge Sciences Center. We hope that this paper and its presentation at the ECKM-2014 Conference will encourage others to take up the challenge of creating a knowledge sciences center. We hope that others will share their experiences and ideas on the design issues we have raised and the blueprint that emerged from the Symposium discussions. A second Knowledge Sciences Symposium is being planned for 2014 to carry these ideas forward.

References Andriessen, D. (2004). Making sense of intellectual capital: designing a method for the valuation of intangibles. Routledge. Anttiroiko, A. V. (2004). “Science cities: their characteristics and future challenges”, International Journal of Technology Management, 28(3), 395-418. Appold, S.(2003). “Research parks and the location of industrial research laboratories: An analysis of the effectiveness of a policy intervention”, Research Policy 33, 225 – 243. Baqir, M. N., & Kathawala, Y. (2004). “Ba for knowledge cities: a futuristic technology model”, Journal of Knowledge Management, 8(5), 83-95. Bontis, N. (2001). “Assessing knowledge assets: A review of the models used to measure intellectual capital”. International Journal of Management Reviews, 3(1), 41-60. Bontis, N. (2002). National Intellectual Capital Index: Intellectual Capital Development in the Arab Region. United Nations, NY. Bounfour, A. and Edvinsson, L. (2005). Intellectual Capital for Communities: Nations, Regions and Cities, ButterworthHeinemman, Boston. Carrillo, F. J. (2004). “Capital Cities: A Taxonomy of Capital Accounts for Knowledge Cities”, Journal of Knowledge Management, Special Issue on Knowledge-based Development II, Knowledge Cities, 8(5), 28-46. Carrillo, F. J. (2006). Knowledge Cities – Approaches, Experiences, Perspective. Butterworth-Heinemann, 2006.

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Denise A. D. Bedford, John Lewis and Brian Moon Castells, M. (2000), The rise of network society, Blackwell Publishers Castells, M. and Hall, P. (1994). Technopoles of the World: The Making of Twenty-first Century Industrial Complexes. London: Routledge. Chen, S and Choi, C.J. (2004). “Creating a Knowledge-based City: The example of Hsinchu Science Park”, Journal of Knowledge Management, Vol. 8, No. 5, 73 – 82 Dvir, R., & Pasher, E. (2004). “Innovation engines for knowledge cities: an innovation ecology perspective”, Journal of Knowledge Management, 8(5), 16-27. Edvinsson, L. (2006). “Aspects on the city as a knowledge tool”, Journal of Knowledge Management 10(5), 6-13. Ergazakis, E., Ergazakis, K., Metaxiotis, K. and Charalabidis, Y. (2009) “Rethinking the development of successful knowledge cities: an advanced framework”, Journal of Knowledge Management 13(5), 214-227. Ergazakis, K., Metaxiotis, K., Psarras, J. and Askounis, D. (2006). “A unified methodological approach for the development of knowledge cities”, Journal of Knowledge Management 10(5), 65-78 Garcia, B. C. (2006). “Learning conversations: knowledge, meanings and learning networks in Greater Manchester”. Journal of Knowledge Management 10(5), 99-109, Garcia, B.C. (2007). “Working and learning in a knowledge city: a multilevel development framework for knowledge workers”, Journal of Knowledge Management 11(5), 18-30, Goldberg, M., Pasher, E., and Sagi, M. L. (2006). “Citizen participation in decision-making processes: knowledge sharing in knowledge cities” . Journal of Knowledge Management 10(5), 92-98, Goodman, J. C. (2005). What is a Think Tank? National Center for Policy Analysis. Haughton, G. and Hunter, C. (2003), Sustainable Cities, Routledge. Kratke, S. (2011). The Creative Capital of Cities: Interactive Knowledge Creation and the Urbanization Economies of Innovation. Blackwell, 2011 Matthiessen, C. W., Schwarz, A. W. and Find, S. (2006). “World cities of knowledge: research strength, networks and nodality”, Journal of Knowledge Management 10(5), 14-25, Mendizabal, E. (2010). on the business model and how this affects what think tanks do, http://onthinktanks.org/2010/10/03/on-the-business-model/ Retrieved 2011-11-02. Metaxiotis, K. and Ergazakis, K. (2008). “Exploring stakeholder knowledge partnerships in a knowledge city: a conceptual model”. Journal of Knowledge Management 12(5), 137-150, O’Mara, M. P. (2005). Cities of Knowledge: Cold War Science and the Search for the Next Silicon Valley. Princeton University Press, 2005. Ovalle, M., Barquez, J. A. A., and Salomon, S. D. M. (2004). “A compilation of resources on knowledge cities and knowledge-based development”. Journal of Knowledge Management. 8(6), 107-127. Papalambros, Panos Y. (2011). "A New Knowledge Ecosystem." Journal of Mechanical Design 133.perspective’’, Journal of Knowledge Management, 8(5), 16-27. Peters, M. A. (2007). Knowledge economy, development and the future of higher education. Rotterdam: Sense Publishers. Rodriguez, C. O. (2012). “MOOCs and the AI-Stanford Like Courses: Two Successful and Distinct Course Formats for Massive Open Online Courses”. European Journal of Open, Distance and E-Learning. van Winden, W., de Carvalho, L., van Tuijl, E. and van Haaren, J. (2012). Creating Knowledge Locations in Cities: Innovation and Integration Challenges. Routledge. Vardi, M. Y. (2012). “Will MOOCs destroy academia?” Communications of the ACM, 55(11), 5.

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Blueprinting a Knowledge Sciences Center to Support a Regional Economy Denise A. D. Bedford1, John Lewis2 and Brian Moon3 1 Goodyear Professor of Knowledge Management, Kent State University Kent Ohio 2 Founder, Explanation Age LLC; Adjunct Faculty, Kent State University, Kent Ohio 3 Chief Technology Officer, Perigean Technologies; Adjunct Faculty, Kent State University, Kent Ohio [email protected]

Abstract. As cities and regions transform from an industrial to a knowledge economy, there is a need to build new working relationships among academic, business communities, labor and workforce, civil society, and the technology sector – to create Knowledge Cities. A Knowledge City values all kinds of knowledge, is grounded in an economy that runs on st knowledge and intellectual capital, and encourages knowledge markets and transactions. The 21 century knowledge economy is dependent upon knowledge cities and regions, representing a major shift from the industrial economy. Transforming an industrial city to a Knowledge City is not a trivial task. It requires that all members of the society make the transition together. Currently, there are no institutions that can facilitate this role. This paper considers how a Knowledge Sciences Center might fulfill that role, and reports on the thoughts of over 200 participants of the Knowledge Sciences Symposium held in Canton, Ohio, and Washington DC in 2013. Keywords: Knowledge sciences center, knowledge cities, knowledge economy, economic transformation, Knowledge Sciences Symposium

1. Knowledge Sciences Symposium There is a need to redefine many of our institutional relationships and the way that our institutions work as we st transition to a knowledge economy and a knowledge society in the 21 century. No aspect of society remains unchanged in a knowledge economy – every sector, every individual, every organization and business changes. What we value shifts – intellectual capital is as important as is financial or physical capital (Andriessen 2004) (Bontis 2001) (Bontis 2002) (Bounfour and Edvinsson 2005) (Kratke 2011). In an industrial economy, academia was a haven for cutting-edge knowledge. It was where you went to learn. Solutions to industrial economy challenges are structured and managed because industrial economy challenges are linear, predictable and manageable. In the knowledge economy, there is as much or more knowledge being created outside of academia as there is within (Peters 2007). Knowledge economy challenges are chaotic, dynamic and “wicked”. The knowledge economy is not as segmented or hierarchically structured as was an industrial economy – the transformation requires that all sectors and all stakeholders move together rather than move individually. Businesses understand the challenges of competing in a knowledge-based economy. Academia needs to learn from and deliver outcomes that can be used by business. Technology needs to move away from an industrial way of working or designing products for structured work to designing for a knowledge economy. The labor force needs to continuously learn – and learn not just from business or from union provided training – but to engage with academia. Learning today goes beyond formal degree programs. MOOCs, workshops, online webinars, in house training, and continuous lifelong learning are the norm. Academia needs to provide learning opportunities not just for those who can pay for formal credentials but to those who need to learn (Vardi 2012) (Rodriguez 2012). Knowledge Cities are emerging all around the globe from the remnants of industrial cities (Baqir and Kathawalla 2004) (Brenner and Kell 2003) (Carillo 2004) (Carollo 2006) (Castells and Hall 1994) (Dvir and Pasher 2004) (Edvinsson 2006) (Ergazakis et al 2009) (Garcia 2007) (Goldberg Pasher and Sagi 2006) (Matthiessen Schwarz and Find 2006) (Metaxiotis and Ergazakis 2008) (Ovalle Barquez and Salomon 2004) (Papalambros 2011) (van Winden et al 2012). The transition, though, does not always include all members or organizations of the industrial city.

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Denise A. D. Bedford, John Lewis and Brian Moon In September 2013, an emergent community of 200 people from across the country gathered in Canton, Ohio, and in Washington DC, to hold a Knowledge Sciences Symposium (www.kent.edu/slis/programs/iakm/symposium/index.cfm). The purpose of the Symposium was to bring together knowledge management thought leaders from businesses and organizations, technology sector, academia, civil society organizations and the broader workforce to design a blueprint for a Knowledge Sciences Center in order to support the transformation of st local industrial economies into the 21 century knowledge economy. The Symposium discussions were preceeded by five webinars in July 2013. The Symposium participants (“Participants”) designed a blueprint for st a 21 century Knowledge Sciences Center that focused on learning and career development, research and development, advocacy, advising and outreach and partnerships. The goal of this paper is to share that blueprint with the knowledge management community in order to elicit feedback and to find other people interested in moving the vision forward.

1.1 Rationale for a Knowledge Sciences Center Participants envisioned a Knowledge Sciences Center as a source that would help a local economy and society st make an effective transition to the 21 century knowledge economy. It was important to capture within the name of this Center the idea that the activities would go beyond what has typically been described as Knowledge Management. As a science, the range of activities would need to span the theoretical and academic foundations as well as the commercial and practical applications. The Knowledge Sciences Center we envisioned required a new blueprint if it was to serve this purpose.

1.2 Existing Models There are many examples of research institutes,, science centers and think tanks, but none that aligned with the community and economy focus of the Knowledge Sciences Center. Research institutes and science centers are designed to leverage expert knowledge, often focused on theoretical research or the R&D needs of specific funding organizations (Anttiroika 2004) (Appold 2003) (Chen and Choi 2004) (O’Mara 2005). The intended stakeholders are other highly credentialed or deeply resourced organizations, and the engagement models are heavily dependent upon public or endowment funding sources. Another example of a science center is a Think Tank where experts focus on investigating current topics for the purpose of advocacy or public policy development (Mendizabal 2010) (Goodman 2005). While these models certainly serve a purpose, Participants agreed that they do not meet the needs of a city or region making the transition to a knowledge economy. There was a clear consensus that a new model was needed.

2. Design Issues The Participants envisioned a new kind of Center that would act as a bridge between the worlds of academia, business, labor and technology, and could find no existing models to use as a blueprint. The design and vision emerged as we explored five issues (Figure 1). We needed to know who would participate in the center (Issue 1). We needed to know what kinds of activities the center would support to achieve its goals (Issue 2). We needed to know how stakeholders would engage (Issue 3). We needed to know how we would fund the Center (Issue 4). Finally, we needed to know what it would look like – physically and virtually (Issue 5). How do we engage? What do we do?

Issue 3

Issue 2

Who are the stakeholders? Issue 1

How do we fund? Issue 4

Knowledge Sciences Center

Figure 1. Knowledge Center Vision and Design – Five Key Issues

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What does it look like? Issue 5

Denise A. D. Bedford, John Lewis and Brian Moon Issue 1: Who are Participants in a Knowledge Sciences Center? We began the discussion of stakeholders with an assumption that there were five primary interest groups, including academic, business, labor, civil society and technology developers. It quickly became obvious that these groups were neither comprehensive nor inclusive of possible stakeholders. We realized we needed to look at potential stakeholders from multiple perspectives. In the end, the Participants concluded that any member of the community that was being served by the Knowledge Sciences Center was a potential stakeholder, including but not limited to: academic, religious, and educational institutions, libraries, localized ownership, NGOs, governmental organizations – federal, state, local, county , academics, congressional staff, service organizations (boy scouts, girls scouts, youth groups, 501(3)c organizations, charitable organizations, military support organizations, professional societies, chambers of commerce, city visitors’ bureaus, unions, local government agencies such as fire, police, emergency management, innovators in search of partners, elected government officials, and voluntary sector organizations. The list of participants clearly requires a different kind of organization than traditional institutes, science centers or think tanks. Understanding stakeholders along a single dimension such as their economic role presented a risk, but understanding stakeholder interests and needs will be necessary for brainstorming the types of activities, products and services the Center should provide. As a first step, Participants suggested a Knowledge Sciences Center should prepare persona. Persona templates would help to understand stakeholders’ goals, their different roles and responsibilities, their technology environment and skill levels, social media behaviors, and pain points. All of these dimensions are critical to planning activities, to designing access and supporting collaborative environments, to financing activities and to designing engagement models. Issue 2: What Do We Do? A core question for the blueprint is, “What does the Center do for these stakeholders?” We were fortunate to have more than 200 seasoned knowledge management professionals share their ideas on activities. We were also fortunate that this group had an implicit understanding of what we meant by knowledge sciences – its goals, its scope – and by what it means to practice knowledge management - its methods and tools. The participants proposed five areas of focus drawing upon their profound knowledge of the field and the challenges inherent to the transformation (Figure 2).

Figure 2. Business Capabilities of a Knowledge Sciences Center The five broad areas were: (1) Learning and Career Development; (2) Research and Development; (3) Advocacy; (4) Advising; and (5) Networking and Partnerships. A significant portion of the in-person meetings in Ohio and Washington DC were devoted to brainstorming activities for these five areas. As shown in Tables 15, there was no shortage of ideas.

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Denise A. D. Bedford, John Lewis and Brian Moon Table 1. Learning and Development Activities Activity Name Center of Excellence Reference materials

Knowledge Sciences (KS) Learning Programs KS Book and Journal Clubs KS TV Knowledge Sciences Learning Center Knowledge Visitor Center KS FAQs Student Internships and Practicum

Brief Description Business Growth Maps, Case Studies, Lessons Learned/Smart Lessons, Information Repositories – Wikimedia Repositories for Other Hubs/Chapters, KM Body of Knowledge, KM Standards, Knowledge Visualizations, Open Repository or Wiki, Real Work Scenarios, Roadmaps, ROI Methods, Scalable Solutions, Standards Organizations, , KM Principles MOOCS, ADDIE Model Training and Collaborative Workshops, Webinars, in House Training Programs for Organizations, Retraining Programs With Economic Development Units. Open Discussions of Recent Works to Help Promote Research Uptake KM Tedtalks, Open Webinars, KM Internet Travel Channel, Community of Practice Study Tours (Virtual and Physical) Certificate Programs, Competitions for Knowledge Games, Learning Games – Simulations, Pointers to Courses, Pointers to Programs, Transformation Learning Support Orientation to rhe Knowledge Society and Knowledge Economy, KM Tourism, KM Concierge Basic Q&A for KM Novices, FAQs for Individual Topics, KM Study Guides Project and Internship Opportunities, Student Resumes and CVs, Matchup Projects and Industry Needs

Table 2. Research and Development Activities Activity Name KS Experimental Test Lab and Incubator

Knowledge Sciences Collaborative Research & Development Knowledge Sciences Information Access Improvement Knowledge Challenge Workshops and Projects Knowledge Elicitation Lab General Research & Development Knowledge Economy Future State Visions Knowledge Sciences Research for Economic Sectors and Industries

Brief Description Access to Smart Knowledge Systems, Technology Transfer Facilitation and Adoption, Novel Approaches to Licensing Or Purchasing Tools for Groups Or Communities, Guidebooks for Scalable and Right-Sized Solutions, Technology Transfer Opportunities, Identification of Reasonably Priced Platforms for Small and Medium Sized Organizations, Evaluate Products for Vendors, Focus Group Testing for Vendors, Open Source Software Development for Knowledge Sciences Community – in Collaboration With Other Disciplines Collect Research Needs Ideas , Creation of Use Cases and Case Studies, Enterprise Scalable Solutions, Interoperable Solutions, New Approaches to Translation and Interpretation of Regulations, Policies and Standards, Provide Real World Problems for The Center to Work On, Research Agenda, Research Needs Statements, Standards and Guidelines for Findability Knowledge Sciences Languages, Knowledge Sciences Organization Systems (e.g., Classification Schemes, Thesauri, Authoritative Lists) Global Expert Teams, Special Topics, Wicked Problem Teams Knowledge Elicitation Training, Knowledge Loss Prevention and Capture Strategies Assess Research Capabilities, Benchmarking Opportunities, Knowledge Cities Index, Knowledge Economy Models, Knowledge Society Behavior Codes and Ethics, Project Assessments, KM Rsearch Agendas, Innovation Research Economic Sector Scans, Industry Scans Knowledge Society Futures. Knowledge Futures for Specific Organizations

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Denise A. D. Bedford, John Lewis and Brian Moon Table 3. Advocacy Activities Activity Name Active Engagement with Knowledge Economy Transformation Executive marketing and communication about KM KM Competencies

Activity Examples Adaptive Society Change Information Technologies, Innovation to Gain Market Share, Libraries Coached to Communicate Knowledge Management in Real-World Terms Knowledge Sharing Workshops, Lessons Learned Engaging With Corporate Executives Cost Reducing Solutions, Early Maturity Needs, Efficient and Effective Solutions , Facilitation Services, Larger Strategic Perspective , Problem Solving Approaches That Leverage KM, Standards Graphs Showing ROI Marketing Center for All Things KM, Ability to Integrate with Other Domains, Providing Opportunities for Professionals to Socialize and Exchange Ideas

Sponsorship and Representation at Major Conferences and Social Activities Development of KM Legal and Ethical Codes KM Standards Development and Promotion

Advocacy With Professional Societies, Collaboration With Human Capital and Human Resource Management Establish Committees to Define Standards for KM Professionals, Develop Standards for KM Professionals, Assess the Validity for Standards for KM Professionals, Disseminate Standards for KM Professions Criteria for Teaching and Selection, Subversive Missions - Influencing Education and R&D, Gaming and Simulation, Education Technology, Cognitive Sciences, Lifelong Learning, Communications Receiving and Broadcasting Knowledge Management Projects Throughout the KSC Network, Promoting Stakeholder Capabilities Working with Publishers to Develop Pricing Models That Support Broad Access to Knowledge Management Research and Development, Case Studies and Thought Papers, Develop Online Open Access Journals and Trade Publications to Promote Stakeholder Knowledge and Learning. KM Awards and Recognition of Leading Organizations and Individuals

Promotion of KM at all levels of education Promotion of KM Project Opportunities Promotion of Open Access KM Journals Knowledge Management Industry Awards

Table 4. Outreach and Partnership Activity Name Annual KM Surveys Consulting and Advising Development and Collection of Metrics and Stories Funding proposals and opportunities Knowledge Management Mentorships Open Virtual Laboratory

Brief Description Understand Stakeholder Needs, Local and Networked Resources Establish Requirements, Create “People Finder” (e.g., through LinkedIn), Differentiate Types of Consulting the Center Does / Pilots, Develop a Methodology for Matching Stakeholders with Expertise for Consulting Purposes / Services, Identify Tools Repository Performance Plan Examples, Price Points, Provide Strategic Maps and Assistance to Cities and Towns Crowdsourced Solutions, Crowdsourced Funding for KM Research Needs, Short Term Services Mentoring Across Organizations, Mentoring Across Ages Learning Management System, Sandbox Tool – Simulators, Prototypes, “Authoritative” Tools, Customer Relation System, Profile, Access Rights, Track & Trend Analysis, Library of Access to Authoritative KM Content, Ontologies, Analysis, Blogs, Social Media Presence, Tool “Reviews”/ Recommendations

Table 5. Advising Activities Activity Name Broadcasting KS Activities Networking and Public Outreach

Open Meetings Spaces Outreach to Other Disciplines and Economic Sectors Social Media Support for Dynamic Conversations

Activity Examples “News” Source for Innovative KM Practices, KM Blogs, Investigative Reporting, Electronic Calendar of Global KM Events Community Networking, Linking Consultants and Clients, Affinity Grouping within and across Sectors, Networking across City Organizations, Links From Citizens to Thought Leaders, Knowledge Connectors – Linking Those with Problems and Those with Solutions, Knowledge Practitioners Directory Experiments, Brainstorming Sessions, Knowledge Jams, Partnership Outreach and Extension Service Links to Twitter Feeds Related to Knowledge Sciences

The list serves as a catalog of opportunities for any group that wishes to take up the challenge of building a Knowledge Sciences Center. It serves as a tool for prioritizing and implementing activities as relationships with stakeholders develop. Clearly, there are variations in cost, value, duration and sustainability, and lead times.

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Denise A. D. Bedford, John Lewis and Brian Moon The significant number of activities recommended reinforces both the need for and the lack of existing support provided by current players. It is clear that no one organization or institution can fulfill all of these needs. Only through working in a consortium or cooperative environment can a Knowledge Sciences Center meet these needs. Different activities and stakeholders also mean different engagement models. Issue 3: How Do We Engage? The Center’s engagement strategy is complex. Multiple engagement models would be required because different kinds of activities require different ways of working. Multiple models are needed because stakeholders’ interests, environments and resources vary. Participants discussed five possible engagement models, including: (1) Traditional academic R&D model; (2) Agricultural extension service model; (3) Knowledge services corps model similar to that of the Peace Corps; (4) Consortium model; and (5) Business franchise model. The first envisioned model would support applied research that is needed by the community or for which there is no other logical source. This engagement model looks like a traditional academic science center where knowledge resides in the center and is channeled out to the community. Such a model assumes there would be formal contracts in place with funding agencies or organizations, and that all research standards, records and protocols would need to be maintained. In order to support research, access to library resources is also required. The Center would have to work with the university or college to contract for access. The second envisioned model resembles that of an agricultural extension service. This model would support the development of solutions needed by the community, the non-formal learning needs of the community, and technology transfer issues. In this model the Center uses visits to stakeholders as a way of staying in touch with the needs of the local community, gather input to policy formulation, and provide targeted client advice. This engagement model would be a good fit for Learning and Career Development, and Advising activities. The third envisioned model resembles a Knowledge Services Corps – similar to a missionary model or Peace Corps structures where knowledge evangelists engage directly with the community to foster conversations and knowledge transactions while leveraging the Center’s infrastructure and resources. This engagement model might leverage graduate students, students fulfilling practicum or internship requirements, who were supported by community scholarships, or volunteers earning community service or continuing education credits. This model would align well with Outreach and Partnership activities. Tje fourth envisioned model resembles that of a consortium where the Center acts as a cooperative partner with other universities, institutions, and agencies to support activities. This model supports activities that require or benefit from a collaborative environment. This engagement model would be a good fit for Advocacy activities, where the Center would partner with other organizations to move initiatives and standards forward on behalf of the larger community. And a fifth envisioned model – business franchise – was suggested. This was a particularly interesting model because it would allow the Center to reach out into the community through a hub-spoke model, and because it would provide conceptual buy-in and ownership relationships. “Franchise owners” at local libraries or universities or agencies would provide space or connectivity through which stakeholders could engage with the Center. Issue 4: How Do We Fund the Center? As a Knowledge Sciences Center our goal would be to mobilize and promote ideas. As with any such venture, funding will be necessary for sustained effect. Participants were asked to consider what kind of an innovative funding model would support Learning and Career Development, Research and Development, Advocacy, Advising and Networking. The answer to this question was similar to other answers – multi-faceted, dynamic and flexible. Funding models – as engagement models – must be relevant to the activity and to the stakeholders. Learning and Career Development activities may leverage a variety of funding models ranging from entirely open source contributed courses accessible on MOOCs, to no-fee open webinars, to fee-based workshops and on-site training courses, to formal certification or testing services. Advocacy activities would leverage in kind resources, community grants, crowd-funding, or direct sponsorship.

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Denise A. D. Bedford, John Lewis and Brian Moon Research and Development may be funded through grants, research funding awards, and joint sponsored funding. Research may also be supported by in-kind contributions of the members of global expert teams. The model will depend on the nature and intensity of the research. R&D projects that support technology development or evaluation may be sponsored by technology vendors or venture capitalists. Research that has a direct community application may be funded through crowd-sourced or in-kind contributions. The nature of the funding must also take into consideration the intellectual property rights of the products and services. In some cases, established intellectual property provisions will apply. In other cases, creative commons and open source models might be more appropriate. Another funding model would be pay-for-service. This may be appropriate for Advising activities. Again, there would need to be a progressive pricing strategy to ensure that all members of the community can afford to participate in these activities. The lowest pricing option should be an in-kind contribution or a barter system. In-kind contributions strengthen the Center by increasing its stock of knowledge. Where the Center might support in-kind contributions or contributed services, it would be necessary for stakeholders to have access, and the Center to support the idea of a “knowledge bank”. The idea would be that as stakeholders contribute to the Center, they earn intellectual credit that can be applied to future requests. Also proposed was a fee-based membership model.. The challenge with membership models,though, is that they lock and organization into providing predictable and pre-defined services to members. This typically leads to the need to define generic products and services rather than on-demand or stakeholder-focused activities. We have observed that institutions based on memberships over time can become bogged down in the administrative tasks of supporting members. The membership model might also price many community members out of most engagements. The Participants thought that a membership model should be considered only after all other options had been explored. In addition, to having a stock set of funding models, the Center would need to have a robust list of funding sources and opportunities. On-going fundraising relevant to current or planned engagements would be one of the Center’s major operations. Issue 5: What Does the Center Look Like? The Participants were of one mind in recommending both a virtual and a physical preference. The sentiment was that the physical presence should be minimalist and networked to increase visibility. The physical space should ideally be located on a university or college campus to ensure there is easy access to faculty and students, as well as to research protocol support. However, participants suggested that a remote or satellite campus might be more appropriate to ensure that the Center can establish its own innovationoriented, dynamic and community-focused organizational culture. The nature of the space should be open, heavily technology-enabled, with spaces for stakeholders to meet and work. The physical space should feel like an open knowledge sharing environment. As the Center grows, there may be a need for spaces for visiting scholars or short-term team work spaces. Depending on the nature of the stakeholders, their competencies and environments, the physical Center may need to provide access to the Center’s virtual space. We would also expect “Center franchisees” to provide community-based access to the Center. The Center’s virtual structure includes online collaboration environments, access to social media and cloud-based repositories. The Center is also virtually linked to other similar-Centers. The Center’s virtual presence might leverage cutting edge technologies under development or testing by technology developers or vendors. The heavy reliance on virtual access would present both challenges and opportunities. In terms of challenges we would expect that many stakeholders would not have affordable high-bandwidth access. We also expect that digital literacy rates might be low for some stakeholders. This presents opportunities, though, for coaching and mentorships particularly where students and community members contribute training time in exchange for other services.

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3. The Blueprint The participants generated a wealth of ideas and options. While a number of support activities might be consistently supported through stable funding sources, it is clear that many will be ‘designer-oriented’. In other words, a stakeholder engagement and funding design model might need to be put in place for each activity. This is not the way that most organizations work. Thus, the participants agreed that an engagement design model would need to be developed for the Center. The model favored by the participants was an emergent engagement design (Figure 3). The design process would begin with a proposed activity. To ensure that the Center stays true to its goal of facilitating the community or local area’s transition to a knowledge economy, deployment needs to be carefully managed and aligned with demand. The Center would put in place the virtual infrastructure, and engage stakeholders in activities that required low investments but could demonstrate high value. As value is recognized and promoted, stakeholder engagements would expand and build the Center’s reputation.

Stakeholder Competencies Ownership Issues

Stakeholder Environment Engagement Design

Activity Engagement Model

Outputs and Outcomes Funding Options Figure 3. Knowledge Center Activities

4. Observations and Next Steps The purpose of sharing these ideas is to encourage communities around the world to consider starting a Knowledge Sciences Center. We hope that this paper and its presentation at the ECKM-2014 Conference will encourage others to take up the challenge of creating a knowledge sciences center. We hope that others will share their experiences and ideas on the design issues we have raised and the blueprint that emerged from the Symposium discussions. A second Knowledge Sciences Symposium is being planned for 2014 to carry these ideas forward.

References Andriessen, D. (2004). Making sense of intellectual capital: designing a method for the valuation of intangibles. Routledge. Anttiroiko, A. V. (2004). “Science cities: their characteristics and future challenges”, International Journal of Technology Management, 28(3), 395-418. Appold, S.(2003). “Research parks and the location of industrial research laboratories: An analysis of the effectiveness of a policy intervention”, Research Policy 33, 225 – 243. Baqir, M. N., & Kathawala, Y. (2004). “Ba for knowledge cities: a futuristic technology model”, Journal of Knowledge Management, 8(5), 83-95. Bontis, N. (2001). “Assessing knowledge assets: A review of the models used to measure intellectual capital”. International Journal of Management Reviews, 3(1), 41-60. Bontis, N. (2002). National Intellectual Capital Index: Intellectual Capital Development in the Arab Region. United Nations, NY. Bounfour, A. and Edvinsson, L. (2005). Intellectual Capital for Communities: Nations, Regions and Cities, ButterworthHeinemman, Boston. Carrillo, F. J. (2004). “Capital Cities: A Taxonomy of Capital Accounts for Knowledge Cities”, Journal of Knowledge Management, Special Issue on Knowledge-based Development II, Knowledge Cities, 8(5), 28-46. Carrillo, F. J. (2006). Knowledge Cities – Approaches, Experiences, Perspective. Butterworth-Heinemann, 2006.

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Denise A. D. Bedford, John Lewis and Brian Moon Castells, M. (2000), The rise of network society, Blackwell Publishers Castells, M. and Hall, P. (1994). Technopoles of the World: The Making of Twenty-first Century Industrial Complexes. London: Routledge. Chen, S and Choi, C.J. (2004). “Creating a Knowledge-based City: The example of Hsinchu Science Park”, Journal of Knowledge Management, Vol. 8, No. 5, 73 – 82 Dvir, R., & Pasher, E. (2004). “Innovation engines for knowledge cities: an innovation ecology perspective”, Journal of Knowledge Management, 8(5), 16-27. Edvinsson, L. (2006). “Aspects on the city as a knowledge tool”, Journal of Knowledge Management 10(5), 6-13. Ergazakis, E., Ergazakis, K., Metaxiotis, K. and Charalabidis, Y. (2009) “Rethinking the development of successful knowledge cities: an advanced framework”, Journal of Knowledge Management 13(5), 214-227. Ergazakis, K., Metaxiotis, K., Psarras, J. and Askounis, D. (2006). “A unified methodological approach for the development of knowledge cities”, Journal of Knowledge Management 10(5), 65-78 Garcia, B. C. (2006). “Learning conversations: knowledge, meanings and learning networks in Greater Manchester”. Journal of Knowledge Management 10(5), 99-109, Garcia, B.C. (2007). “Working and learning in a knowledge city: a multilevel development framework for knowledge workers”, Journal of Knowledge Management 11(5), 18-30, Goldberg, M., Pasher, E., and Sagi, M. L. (2006). “Citizen participation in decision-making processes: knowledge sharing in knowledge cities” . Journal of Knowledge Management 10(5), 92-98, Goodman, J. C. (2005). What is a Think Tank? National Center for Policy Analysis. Haughton, G. and Hunter, C. (2003), Sustainable Cities, Routledge. Kratke, S. (2011). The Creative Capital of Cities: Interactive Knowledge Creation and the Urbanization Economies of Innovation. Blackwell, 2011 Matthiessen, C. W., Schwarz, A. W. and Find, S. (2006). “World cities of knowledge: research strength, networks and nodality”, Journal of Knowledge Management 10(5), 14-25, Mendizabal, E. (2010). on the business model and how this affects what think tanks do, http://onthinktanks.org/2010/10/03/on-the-business-model/ Retrieved 2011-11-02. Metaxiotis, K. and Ergazakis, K. (2008). “Exploring stakeholder knowledge partnerships in a knowledge city: a conceptual model”. Journal of Knowledge Management 12(5), 137-150, O’Mara, M. P. (2005). Cities of Knowledge: Cold War Science and the Search for the Next Silicon Valley. Princeton University Press, 2005. Ovalle, M., Barquez, J. A. A., and Salomon, S. D. M. (2004). “A compilation of resources on knowledge cities and knowledge-based development”. Journal of Knowledge Management. 8(6), 107-127. Papalambros, Panos Y. (2011). "A New Knowledge Ecosystem." Journal of Mechanical Design 133.perspective’’, Journal of Knowledge Management, 8(5), 16-27. Peters, M. A. (2007). Knowledge economy, development and the future of higher education. Rotterdam: Sense Publishers. Rodriguez, C. O. (2012). “MOOCs and the AI-Stanford Like Courses: Two Successful and Distinct Course Formats for Massive Open Online Courses”. European Journal of Open, Distance and E-Learning. van Winden, W., de Carvalho, L., van Tuijl, E. and van Haaren, J. (2012). Creating Knowledge Locations in Cities: Innovation and Integration Challenges. Routledge. Vardi, M. Y. (2012). “Will MOOCs destroy academia?” Communications of the ACM, 55(11), 5.

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Developing an Interactive View on Intra‐Organisational Knowledge  Sharing  Madeleine Block1 and Tatiana Khvatova²  1 Saint‐Petersburg State University, Saint‐Petersburg, Russia  ²Saint‐Petersburg State Polytechnic University, Russia  [email protected]   tatiana‐[email protected]    Abstract:  Management  of  knowledge  within  organisations  is  supposed  to  foster  innovative  solutions  and  enhance  competitive advantage. Knowledge is held by, and found within individuals, groups and their interrelations. A key part of  knowledge management is having an understanding of the knowledge and information flow among people, groups and the  organisation  as  a  whole.  Such  insight  enables  intervention  and  fostering  of  effective  knowledge  sharing  processes.  However, in order to understand the knowledge flow and interrelations among organisational actors, we must first identify  which  patterns  exist,  and  what  the  real  paths  are  within  organisations.  In  this  article,  the  social  network  approach  is  applied  to  organisational  settings  and  used  as  research  methodology  for  gaining  insight  into  the  intra‐organisational  knowledge sharing process. The overall aim of this research is to investigate how potential actors within a specific network  can be identified and interlinked in order to support effective knowledge sharing and collaboration. In this research, the  extent  of  relationships  between  organisational  actors  is  central.  As  such,  we  view  the  concept  of  social  capital  with  the  central  proposition  that  networks  of  social  relationships  constitute  a  valuable  resource  for  the  conduct  of  social  interaction.  From  these  findings,  this  research  taes  a  step  back,  and  seeks  to  identify  and  analyse  information  and  knowledge flow among organisational actors. Here, social network analysis enters on stage, in order to map and analyse  the  actual  state  of  the  knowledge  sharing  network  within  organisations.  In  the  next  step,  we  refer  to  the  contingency  theory of organisations in arguing that the certainty degree of a task has a great impact on the organisational structure.  Accordingly,  in  organisations  where  a  higher  task  certainty  is  given,  employees  have  little  need  and  choice  of  creating  work‐related  interactions  beyond  the  static  structure  which  is  displayed  in  the  formal  organisational  chart.  Today´s  fast,  internationally connected environment inevitably increases the complexity of tasks within organisations which cannot be  pre‐described.  In  this  way,  employees  may  build  up  informal  networks  in  order  to  accomplish  their  tasks,  and  the  organisational  structures  become  more  organic  and  self‐organised.  In  this  research,  we  discuss  this  circumstance  and  perform a comparative view of the informal networks and the formal organisational chart. As such, the research provides a  case  study,  exploring  intra‐organisational  knowledge  sharing  among  financial  departments  of  an  international  industry  company. The study is based on a questionnaire which evaluates the extent of interrelation between financial departments  according  to  employees’  self‐reported  opinions.  Empirical  data  was  collected  through  an  email survey  distributed  to  the  financial  departments,  involving  ten  leaders  and  97  specialists.  For  analysis  of  the  collected  data,  statistical  quantitative  analysis  and  for  visualisation  of  the  knowledge  network,  social  network  analysis  software  were  used  as  research  techniques.     Keywords: knowledge sharing; organisation; social network approach; empirical research 

1. The concept of social capital as a theoretical umbrella  The interactive approach chosen in this article refers to the most common notion in social sciences, which is  that  individuals  cannot  act  separately  from  each  other,  but  instead  they  are  interrelated  and  interactively  connected.  This  is  why  knowledge  sharing  does  not  occur  automatically,  but  takes  place  within  social  interactions perceived as beneficial by the participants. At this stage, the concept of social capital helps to gain  a better understanding of knowledge sharing within cooperative relationships, such as among individuals and  departments within organisations.    The term `social capital´ has been made well‐known by such writers as Pierre Bourdieu (1986), James Samuel  Coleman (1990), and Robert David Putnam (1993), among others. Nowadays, scholars generally agree that the  core  notion  of  social  capital  theory  is  that  `networks  of  relationships  constitute  a  valuable  resource  for  the  conduct of social affairs´ (Nahapiet and Ghoshal 1998, p. 243). In other words, social capital is an investment in  social relationships with expected outcomes in the short or long term (Block 2013, p. 99, 133).    Regarding  intra‐organisational  knowledge  sharing,  we  refer  to  Nahapiet  and  Ghoshal  (1998),  who  applied  social capital theory to the intra‐organisational context, while the first empirical study was conducted by Tsai  and Ghoshal (1998). Based on Bourdieu and Putnam´s elements of social capital, Nahapiet and Ghoshal (1998,  p. 243‐244) propose three social capital dimensions: a structural dimension, cognitive dimension and relational 

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  Madeleine Block and Tatiana Khvatova  dimension  (Block  2013,  pp.  111,  133).  In  this  article  the  focus  is  on  the  structural  dimension.  While  the  relational dimension of social capital represents the affective side of relationships and the cognitive dimension  relates  to  a  shared  context  and  understanding  among  participants,  the  structural  dimension  refers  to  social  relations and structures that are considered as an important source of social capital. Social structures reflect a  normative integration mechanism, enacted by the organisation, and which acts as a kind of `social control´. On  the other hand, structural dimension refers to the patterns of connections among involved actors which are  closely  interlinked  with  the  social  network  theory.  In  this  study,  social  structures  within  organisations  constitute the channels for knowledge sharing, providing actors with opportunities to access the resources of  others, such as knowledge, and to share their own knowledge (Block 2013, p. 113; Tsai and Ghoshal 1998, p.  252).  

2. Understanding the actual state of intra‐organisational knowledge sharing interactions  In the social sciences arena, the structural dimension of social capital, which is founded on research into social  interactions, has particularly been the focus of social network researchers. They seek to identify various kinds  of  patterns,  and  to  visualise  these,  their  theory  being  that  the  pattering  of  social  relations  inevitably  has  consequences  for  the  participants  (Freemann  2004,  p.2).  Referring  to  the  social  network  theory,  this  study  aims to explain and visualise the knowledge sharing relationships among actors within an organisation.    Since the 1930s, modern social network theory has been present and employed in social sciences. However, as  a  recognised  perspective  it  finally  appeared  only  in  the  late  1970s,  represented  by  such  scientists  as  Russell  Bernard,  Lawrence  Kincaid,  and  Nan  Lin.  In  general,  social  network  researchers  explain  individual  behaviour  not  as  a  function  of  characteristics  of  the  same  individual,  but  rather  by  aspects  of  the  individual´s  social  environment  (Borgatti  et  al.  2009,  p.  894).  The  focal  point  of  the  Social  Network  Analysis  (SNA)  is  the  relationships between actors, based on an assumption of the importance of the way actors are related to each  other within the network (Richards, Seary and Fraser 2008, pp. 1‐3). In SNA terminology a network is a set of  relations between actors, while actors represent nodes in the network and are defined as the smallest units in  the  network,  or  rather  known  as  actors  which  or  who  contain  and  pass  information.  The  tie  is  defined  as  a  connection  between  two  nodes,  meaning  that  there  is  some  passing  of  information  between  them  (Giuffre  2013, pp. 12‐13; Hanneman and Riddle 2005, 1st Chapter).    SNA  has  been  applied  in  various  research  fields.  For  example,  in  management  studies  there  have  been  attempts to apply the SNA in the field of knowledge management to help organisations improve sharing and  make use of the knowledge held by individuals, groups and the organisation as a whole. Yet this is far from  being  complete.  In  this  context,  this  study  interlinks  and  aims  to  explore  knowledge  sharing  paths  within  organisations  with  the  help  of  the  SNA.  For  this  purpose,  we  refer  to  a  case  study  conducted  among  ten  financial  departments  of  an  international  industry  company.  These  financial  departments  are  classified  into  four  main  units.  Table  1  shows  the  distribution  of  units  and  departments,  the  number  of  employees  within  participating financial departments and the total number of respondents to the survey.  Table 1: Distribution of financial departments and classification of survey respondents  Unit and department Employees Respondents Percentage Unit 1: Accounts Receivable (AR) Accounts Receivable Northern Europe (AR NE) 12 7 58,33% Accounts Receivable Western Europe (AR WE) 5 4 80,00% Accounts Receivable Central Europe (AR CE) 10 8 80,00% Accounts Receivable UK and North America (AR UK/NA) 2 2 100,00% 15 9 60,00% Unit 2: Accounts Payable (AP) 14 8 57,14% Unit 3: Cash Management (CM) Unit 4: Purchase Invoice Handling (PI) Purchase Invoice Handling Northern Europe (PI NE) 23 8 34,78% Purchase Invoice Handling Western Europe (PI WE) 10 6 60,00% Purchase Invoice Handling Central Europe (PI CE) 14 6 42,86% Purchase Invoice Handling UK and North America (PI UK/NA) 2 1 50,00% Total 107 59 55,14%  

The  data  for  the  SNA  of  the  knowledge  sharing  interaction  ties  were  collected  from  two  questions  of  the  survey. The following questions were asked:  ƒ

`Could you please identify the department where you work?`; 

ƒ

`Could you please identify the department(s) you contact for task‐related issues?`.  

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  Madeleine Block and Tatiana Khvatova  Answers to both questions were submitted by the 59 employees of the ten departments. During analysis of  the  network,  two  matrices  were  composed:  a)  person‐by‐department  network  and  b)  department‐by‐ department network. Absence of ties between individuals and departments were coded as zero, and presence  of  ties  with  one.  Network  analysis  was  done  using  UCINET  (Borgatti  et  al.  2002)  and  NetDraw  programmes  (Borgatti 2002).    In order to map the actual state of the knowledge sharing network of the financial departments, we refer to  attributes such as centrality and network size.     The  latter  feature  provides  important  insights  about  the  network  structure  of  relations,  i.e.  as  larger  the  network is, the more complex is the network. The proportion of all possible relationships in the network that  are  actually  present  equates  to  the  measure  of  network  density  informing  us  about  the  speed  at  which  knowledge is spread among the actors. A relatively high density network enables the development of a form of  collective identity, and is more likely to be more effective for collective action such as knowledge sharing. In  this paper, we argue that (task‐related) knowledge sharing is more likely to happen in a network where the  density of ties among the individuals is relatively high, yet not too strong.     Centrality can be defined as the extent to which an actor has a central, favourable or less favourable position  in  the  whole  network.  In  this  study,  we  look  at  two  measures  of  centrality  (Kilduff  and  Tsai  2005,  p.  132):  degree centrality  and  closeness  centrality. The  measure of  degree  centrality  expresses  the  number of  direct  relations a node has in the network. Usually it is assumed that the more ties a node has, the more power s/he  will get through more opportunities and less dependencies. The degree centrality is assessed with the help of  the  number  of  ties  sent  (out‐degree)  indicating  influence  on  others;  and  the  number  of  ties  received  (in‐ degree) showing the node´s popularity within the network. While centrality degree does not consider indirect  ties to a third node, closeness centrality refers to indirect relations and the ability of an actor to reach many  others, i.e. how close, on average, an actor is to every other actor within the network. It is assumed that the  closer a node to all other in the network is, the more favourable is his/her position. The shortest path between  any two network participants is called `geodesic´ and reflects often the most efficient relation between nodes.  A small geodesic length, on average, indicates a relatively close position to others within the network, while a  large average geodesic length reflects relatively distant relations to the rest of the network.    Person‐by‐department network    Figure  1  shows  the person‐by‐department sociogram,  wherein  nodes  and  ties  of  the network  among  the 59  employees allocated to the ten financial departments are presented. The strength of the knowledge sharing  process is represented for individuals by the number of ties, and for departments by the size of the symbol –  the  bigger  the  size,  the  larger  its  central  position.  The  arrow  states  the  direction:  from  a  person  to  a  department. 

  Figure 1: Person‐by‐department network 

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  Madeleine Block and Tatiana Khvatova  The network shown in Figure 1 consists of 207 actual existing relations, which equates to a network density  rate of 4.4%. The small network density confirms that a network in larger size becomes more complex in which  connecting  to  everyone  else  becomes  increasingly  difficult.  Further  results  of  the  analysis  indicate  that  the  number of departments contacted by each employee ranges from 0 to 7 out of 9 possible departments. For  example, node numbers 1 and 30 are in contact with 7 departments along with their own, and node number  25  with  3  other  departments.  Only  two  nodes  out  of  59  have  no  ties  to  any  department,  i.e.  they  do  not  contact  other  departments  for  task‐related  issues.  So,  this  map  of  relationships  shows  that  almost  every  person is somehow involved in the knowledge sharing process. Regarding the departments, the results show a  strong central position of two departments called `AP´ and `CM´. These are the most involved and requested  of all. On the other hand, the `AR UK/NA´ and `PI UK/NA´ departments take only a marginal central position in  this network.    Department‐by‐department network    The department‐by‐department sociogram of the ten departments is displayed in Figure 2. It can be observed  that  every  department  is  part  of  the  knowledge  sharing  process  by  being  connected  through  a  tie.  The  calculated  network  density  with  65.60%  is  clearly  higher  than  for  the  larger  person‐department  network.  It  means that sharing of information and knowledge is more likely to happen among the ten departments.    Similarly  to  Figure  1,  the  layout  of  the  sociogram  is  aligned  with  the  attribute  of  centrality,  and  shows  the  central position of both `AP´ and `CM´ departments. 

  Figure 2: Department‐by‐department network  Due to the symmetric data of the department‐by‐department network, it is possible to calculate the degree  centrality for each node. The results in Figure 3 show the in‐degree and out‐degree of each node whereas the  first two columns represent the actual number, and the third and fourth column the standardised value. For  example, the `CM´ department is most actively in contacts with other departments – all nine possible. On the  other  hand,  `AP´  is  the  department  most  requested  by  all  the  other  departments.  It  means  that  both  departments  keep  a  central  position  in  this  network.  At  the  other  extreme,  the  `PI  UK/NA´  department  contacts  other  departments  the  least  often  (2  out  of  9  possible),  while  the  `AR  UK/NA´  department  is  least  contacted by others (contacted by only 3). 

  Figure 3: Centrality degree for department‐by‐department network 

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  Madeleine Block and Tatiana Khvatova  The square symmetric matrix of the department‐by‐department network further allows for investigation into  the interactions between each pair of departments and thus, for measuring the closeness centrality. Figure 4  represents a matrix of geodesic distances between two departments (row‐column crossing). 

  Figure 4: Matrix of geodesic distances for department‐by‐department network  The geodesic distance between two departments is the path with the shortest length. For example, looking at  the interaction between the row `PI NE´ and column 3 (AR CE), we see a `2´. This means that `PI NE´ and `AR  CE´ are indirectly related by just one intermediator, which produces two edges. The table shows that the `PI  UK/NA´  department  has,  on  average,  the  longest  paths  with  other  departments,  while  department  CM  is  directly interconnected with everyone.    The average geodesic among reachable pairs is 1.356. In general, the relatively small geodesic length indicates  a relatively close relation from one department to the rest of the network.  

3. Studying congruence between knowledge flow and knowledge sharing performance  In  the  above‐described  part  of  the  research,  the  question  was  how  to  map  the  actual  state  of  knowledge  sharing relations. Hereafter, the actual level of knowledge flow is centred and is compared with the existing  organisational chart in order to predict the knowledge sharing performance.     It is presumed that if the task is certain, it will fit to more rigid organisational structure, because employees  will not need to actively search for knowledge sharing partners; it is sufficient to follow what is prescribed by  organisational  instructions.  However,  reality  shows  that  this  framework  works  until  such  time  as  some  turbulence  occurs  in  the  environment  and  task  certainty  disappears,  increasing  a  misfit  between  actual  employee behaviour and organisational structure. This means that organisational structure should be modified  in  order  to  come  closer  to  fit,  i.e.  to  adapt  to  environmental  contingencies.  In  this  context,  we  refer  to  the  contingency theory of organisational structure with the underlying assumption that there is no one best way  to  organise,  and  that  the  selected  way  to  organise  cannot  be  effective  under  all  conditions  as  conditions  constantly change (Galbraith 1973, p.2). In other words, organisational design is arguably most effective when  the structure of an organisation fits the contingencies. The contingency theory sees organisations as adapting  to their changing (internal) environmental contingencies in order to regain higher performance. As shown in  Figure 5, higher performance leads to increasing contingency variables such as a surplus of resources and to a  growth  in  size  or  diversification  causing  misfit  with  the  existing  organisational  structure.  In  turn,  a  misfit  engenders lower performance and encourages the organisation towards another structural change, so a move  from misfit to another fit, and so on (Donaldson 2001, p. 20). 

  Figure 5: Cycle of structural misfit‐fit‐relationship 

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  Madeleine Block and Tatiana Khvatova  Particular  for  the  intra‐organisational  contingency  perspective,  to  which  we  refer  in  this  paper,  is  that  managers can control the organisational structure and its changes. Therefore, they will only change structures  to  another  fit  if  it  generates  higher  performance  than  the  old  fit  (Donaldson  2001,  p.  26).  With  regard  to  knowledge  sharing  performance,  the  following  questions  are  addressed:  does  the  formal  organisational  structure  reflect  the  real  task‐related  knowledge  flow?  What  kind  of  model  could  describe  the  knowledge  sharing  performance?  Does  the  knowledge  sharing  performance  depend  on  the  organisational  structure?  Furthermore, the identification of fits and misfits offers guidance to managers about what the organisational  design may adapt to.     The literature review of organisational research on the relationship between tasks and organisational structure  provides several studies. For example, in the research by Van de Ven and Delbecq (1974, p. 183) it is stated  that appropriate organisational structure depends on both task difficulty and task variability. In the article by  Becerra‐Fernandez and Sabherwal (2001, p. 29‐30), it is argued that two task dimensions (task orientation and  task  domain)  require  different  types  of  organisational  knowledge  which  implies  that  different  knowledge  management processes are required. Lawrence and Lorsch (1967, p. 7) suggested that if a group is created to  perform  more  certain  tasks,  it  will  usually  have  a  more  formal  structure  than  a  group  performing  more  uncertain  tasks.  Therefore,  they  believed  that  the  design  of  an  organisation  and  its  effectiveness  are  contingent upon environmental variables.    By  applying  the  contingency  theory  to  intra‐organisational  knowledge  sharing,  we  take  up  the  relationship  between fit or rather misfit of the formal organisational structure and the actual knowledge sharing behaviour  predicting  knowledge  sharing  performance.  We  argue  that  knowledge  sharing  performance  depends  on  the  contingencies under which it takes place, i.e. it is affected by the context, for example, by uncertainty versus  certainty of tasks. Mathematically it is more convenient to validate the contingency theory through the misfit‐ performance‐relationship. Fit occurs where the level of formal structure matches the level of actual structure.  Accordingly,  misfit  (M)  is  where  the  formal  structure  (X)  differs  from  the  contingency  variable  of  actual  . Conventionally, the misfit‐performance‐relationship is done by  knowledge sharing behaviour (Y):  using the difference score method which determines the performance (Z) as a result of the difference scores  (X‐Y)  representing  congruence  between  the  two  states  of  organisational  variables  –  formal  and  actual  .  This  demonstrates  that  the  bigger  misfit  is,  the  lower  the  knowledge  sharing  behaviour:  performance will be. Edwards and Parry (1993) suggested expanding the equation and viewing the equation as  polynomial regression for assessing the influence of misfit on performance. They propose to use the squared  terms of the differences and its expansion which results in the following equation (Edwards and Parry 1993, p.  1579):    , 

  where X is the structural variable, Y the contingency variable, and Z the performance.    The  use  of  the  polynomial  regression  equation  has  two  methodological  advantages:  at  first,  squared  term  means  avoiding  problems  with  negative  values  of  misfits  occurring  through  difference  scores;  secondly  the  polynomial regression overcomes the collinearity problem of the X and Y variables (Edwards and Parry 1993,  pp.  1578‐1579).  Finally,  polynomial  models  describe  not  only  the  influence  of  factors,  but  also  their  interactions including the polynomial higher order terms to show that some effects indeed arise due to them  (Eliseeva  2005,  p.  116).  However,  coefficients  from  quadratic  equations  are  more  difficult  to  interpret.  Therefore, similar to Edwards and Parry (1993) we use the response surface methodology in order to describe  and verify the important features of surfaces corresponding to the polynomial regression equation.    Regarding the present case study, the performance of knowledge sharing – abbreviated by Z – is predicted by  the relationship between the contingency variable (Y) and the structural variable (X). For the latter variable X –  the formal knowledge sharing behaviour represented by the organisational chart was quantified according to  from whom employees are supposed to obtain knowledge. In Figure 6 the organisational chart representing  the  financial  departments  shows  not  only  the  managerial  hierarchy  but  rather  a  process‐oriented  structure  and their task‐related connectivity.    

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  Figure 6: Formal organisational chart  The organisational chart suggests the strict rule about communication for each department. For example, it is  prescribed that to do the job, the ARNE employee should contact at first her/his colleagues from ARNE, the  neighbouring department, then the other two departments from their own group, plus outside the AP and CM  department,  while  the  communication  to  the  PI  departments  are  the  last  in  the  chain.  According  to  the  prescribed  formal  task‐related  communication  paths  points  were  given  with  a  maximum  of  five  and  summarised for each department.    For  the  contingency  variable  (Y)  we  take  the  actual  knowledge  flow  which  is  characterised  by  the  desire  of  employees  to  address  colleagues  from  other  departments  for  advice.  Based  on  the  data  resulting  from  the  addressed  question:  `Could  you  please  identify  the  department(s)  you  contact  for  task‐related  issues?`,  ten  scenarios for different groups were reconstructed and quantified. The desire to communicate was measured  by looking at the organisational chart – the farther an employee goes and the more unconventional the path  they  choose  to  acquire  knowledge,  the  more  points  s/he  gets  (maximum  five).  The  chi‐square  test  was  conducted  to test  the  misfit  between  the formal  knowledge  flow  (X)  and  the  actual knowledge  flow  (Y),  i.e.  .    The  misfit  exists  ( ²=153.91,  degrees  of  freedom=51,  significant  at  the  0.05  level)  and  it  is  essential.    The underlying questions for analysis of the knowledge sharing performance (Z) among financial departments  (see Table 1 and Figure 6) are:  ƒ

`Could you please indicate the frequency with which other departments provide you with information and  knowledge required for you to do your work?`; 

ƒ

`Could you please indicate the value of the information and knowledge which other departments provide  you with in order for you to do your work?`;  

The  questions  were  graded  on  five‐point  Likert‐type  scales  and  the  consistency  of  the  questions  for  the  variables  was  tested  using  Cronbach  alphas,  which  were  0.95  and  0.83  respectively  for  every  corresponding  part of the questionnaire, which shows perfect consistency of the constructs.   ) is measured as a weighted sum of the 

The level of knowledge sharing performance for every person (

number of times (question a) knowledge is provided by another department ( of knowledge value (question b) that the exchange brought (  

) multiplied by the indicator 

): 



  where    is  the number  of departments a  person  i  addressed.  Afterwards,  the  average  mean  of  knowledge  sharing performance (Z) was calculated for every department. There were some missing items in responses.  Following listwise deletion, 52 out of 59 respondents were used in the analysis, a 55.14% response level. The 

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  Madeleine Block and Tatiana Khvatova  response rates differed across groups (see Table 1); however, overall differences were not significant at 0.05  level.  As  a  result,  the  performance  of  knowledge  sharing  among  the  financial  departments  equates  to  the  . The  following regression model:  coefficients of the polynomial regression equation are represented in Table 2 and the hypothetical surface is  shown in Figure 7.  Table 2: Coefficients for the polynomial regression equation   Equation 

     

N was 52; 



16.092* 

  ‐0.461 

  0.238* 

  0.008* 

  ‐0.022 

  0.013 

R² 

F‐test 

0.155* 

1.686* 

 are unstandardised regression coefficients. 

* means significance at p