Factors affecting the adoption of information and

Information Technology for Development

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Factors affecting the adoption of information and communication technology in small and medium enterprises: a perspective from rural Saudi Arabia Adnan Mustafa AlBar & Md. Rakibul Hoque To cite this article: Adnan Mustafa AlBar & Md. Rakibul Hoque (2017): Factors affecting the adoption of information and communication technology in small and medium enterprises: a perspective from rural Saudi Arabia, Information Technology for Development, DOI: 10.1080/02681102.2017.1390437 To link to this article: http://dx.doi.org/10.1080/02681102.2017.1390437

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Date: 14 November 2017, At: 21:47

INFORMATION TECHNOLOGY FOR DEVELOPMENT, 2017 https://doi.org/10.1080/02681102.2017.1390437

Factors affecting the adoption of information and communication technology in small and medium enterprises: a perspective from rural Saudi Arabia Adnan Mustafa AlBara and Md. Rakibul Hoqueb Department of Information Systems, King Abdulaziz University, Jeddah, Saudi Arabia; bDepartment of Management Information Systems, University of Dhaka, Dhaka, Bangladesh

Downloaded by [Dhaka University], [Md Hoque] at 21:47 14 November 2017

a

ABSTRACT

KEYWORDS

Small and medium enterprises (SMEs) can play an important role in the national economy of developing countries. The adoption of information and communication technology (ICT) has enabled local SMEs to participate in the international market. However, little research has addressed issues related to SMEs adopting ICTs, especially in rural areas of Middle Eastern developing countries such as Saudi Arabia. Using the extended technology-organizationenvironment framework with personal innovativeness, this study examined the factors that influence the adoption of ICTs among SMEs in rural areas of Saudi Arabia. The study found that relative advantages, top management support, culture, regulatory environment, owner/manager innovativeness and ICT knowledge had a significant relationship with ICT adoption among SMEs in Saudi Arabia, whereas compatibility, complexity and a competitive environment had no significant relationship with ICT adoption. The findings of this study will potentially help SME managers/owners and the Saudi government in the successful adoption and diffusion of ICT in SMEs located in rural areas in Saudi Arabia.

ICT; SMEs; rural areas; developing countries

1. Introduction With the increasing globalization of the world economy, information and communication technology (ICT) has transformed business organizations in developing countries in general and in the Arab world in particular (Alrawabdeh, Salloum, & Mingers, 2012). ICT plays a crucial role in bridging the gap between business organizations in developing and developed countries. Moreover, it also plays a vital role in bridging the gap between business organizations in urban and rural areas in developing countries (ITU, 2011). Business organizations can make more efficient, competitive and innovative decisions through the use of ICT. Researchers in both developed and developing countries have revealed the strong positive relationship between ICT and firm performance (Apulu & Latham, 2011; Rastrick & Corner, 2010). ICT moves other inputs (i.e. labor, capital) in the production of goods and services and has a positive impact on organizational CONTACT Adnan Mustafa AlBar [email protected] Department of Information Systems, King Abdulaziz University, Jeddah, Saudi Arabia James Pick is the accepting Associate Editor for this article. © 2017 Commonwealth Secretariat


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A. M. ALBAR AND R. HOQUE

performance. Dewan and Kraemer (2000) found a positive and significant relationship between IT investment and profit. In recent years, the adoption of ICT in small and medium enterprises (SMEs), which represent the majority of the world’s companies, has caused a revolution in their businesses (Consoli, 2012). SMEs worldwide are using ICT to cut costs and improve efficiency. ICT can provide genuine advantages for SMEs, supporting them so that they can compete with large firms. It is claimed that ICTs can increase SMEs’ productivity and efficiency in different ways, including making technical improvements, reducing transaction costs and shifting the production function (Harindranath, Dyerson, & Barnes, 2008). Therefore, it is essential for SMEs to employ ICT tactically within their organizations in a manner that enables them to maximize its benefits. Nevertheless, although the adoption and diffusion of ICT have a positive impact, ICT has acceptance problems among SMEs, particularly in rural areas of Middle Eastern developing countries such as Saudi Arabia. SMEs are generally slower than large firms to adopt ICT, rendering rural SMEs vulnerable (Tan, Chong, Lin, & Eze, 2009). The major barriers to better utilization of ICT for SMEs are a lack of top management support, owners/managers who lack innovativeness, resistance and a lack of skilled employees (Arendt, 2008). It is also argued that the digital divide will increase, and consequently organizations in developing countries, especially SMEs in rural areas, confront greater difficulties than their competitors both in their own country and in developed countries (Apulu, Latham, & Moreton, 2011). Therefore, a better understanding of the factors that influence the adoption of ICTs among SMEs in rural areas is a critically important policy issue in developing countries such as Saudi Arabia. Recently, Saudi Arabia has engaged in the considerable development of its ICT infrastructure. The government of Saudi Arabia provides extensive support and has invested in continued growth in the ICT infrastructure (Al-Maliki, 2013). In 2015, ICT investments in the Kingdom of Saudi Arabia totaled Saudi Riyal (SAR) 17.83 billion. Packaged and inhouse developed software accounted for the greatest share of ICT investments at 47%, followed by IT equipment investments at 26% and communications equipment at 27% (CITC, 2015). Saudi Arabia is one of the fastest growing IT markets in the Middle East, representing 50% of the total ICT investments in the Gulf Cooperation Council (GCC). Statistics show that more than 80% of Saudi industrial companies use computers and their applications (ICT Report, 2015). ICT services spending reached SAR 120 billion in 2015, with annual growth rate of approximately 7% (CITC, 2015). According to Communications and Information Technology Commission (CITC) estimates, the ICT sector’s contribution represents approximately 6% of total GDP. Furthermore, various e-government projects, such as electronic payment gateways, electronic tax systems and online information exchanges have been implemented, significantly influencing both individuals and business organizations in Saudi Arabia (Alshehri, Drew, & Alfarraj, 2012). Despite these developments in the ICT sectors and ample resources, SMEs in rural Saudi Arabia have not been able to keep pace with digital development. Indeed, Saudi Arabia is confronted by a significant risk of digital divide between urban and rural organizations (AlSobhi & Weerakkody, 2010) . The digital divide is considered a significant obstacle that hinders many rural SMEs from adopting ICT. Until recently, however, very few studies have been focused on the adoption of ICT among rural SMEs, particularly in the context of Saudi Arabia. This study is an attempt to fill this identified gap by analyzing the

INFORMATION TECHNOLOGY FOR DEVELOPMENT

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factors that influence ICT adoption among SMEs in rural Saudi Arabia. The technologyorganization-environment (TOE) framework has been used and extended with owner– manager innovativeness as the theoretical underpinning of this research. The remaining sections of this paper are organized as follows. Section 2 contains the literature review. A brief overview of SMEs in Saudi Arabia is presented in Section 3. Section 4 briefly explains the theoretical framework and Section 5 proposes the research methodology. We present the research findings in Section 6. Further discussion is provided in Section 7 and the conclusion is presented in Section 8.


2. Literature review In most countries, SMEs are sources of economic growth and considered major economic players (Ramdani, Chevers, & Williams, 2013). The widely accepted definition refers to “Small Sized Enterprises with between 1 to 49 employees, while Medium Sized Enterprises are firms with between 50 to 100 employees” (Berisha-Namani, 2009). The SME sector can make an important contribution in the transition to a market economy by creating employment, generating income, fostering technological advancement and promoting other aspects of social development (Ahmad, Abdul Rani, & Mohd Kassim, 2010). SMEs can accelerate the pace of social and economic development, especially in rural areas of developing countries. Furthermore, they can provide an environment in which to develop employees’ managerial and technical skills. The Kingdom of Saudi Arabia is the largest and most populated of the GCC states in the Middle East. It is one of the world’s top 20 most competitive economies and attractive investment destination in the Middle East (Ahmad & Agrawal, 2012). According to the Saudi Arabia General Investment Authority, the Kingdom of Saudi Arabia is a fast emerging economic center and the largest oil-exporting country in the world. It is an economic giant in its region, with 25% of the world’s proven oil reserves (Samirad, 2014). Various reports, indices and rankings related to oil reserves, the free market, per capita income, business climate, fiscal freedom and market reforms, etc., concur. Over the last few years, business enterprises have witnessed notable growth in Saudi Arabia. Currently, 93.1% of Saudi Arabia’s firms are individual enterprises, 4.7% are limited partnerships and 0.6% are joint enterprises (SAMA, 2014). These enterprises are mainly concentrated in three areas: commerce, construction and building, and manufacturing. Most of Saudi Arabia’s organizations are small, based on the number of employees. SMEs in Saudi Arabia are primarily located in rural areas. SMEs in developing and Arab countries such as Saudi Arabia support large organizations in marketing and supplying materials (Tambunan, 2008). It is widely accepted that SMEs have a greater ability than large firms to adopt new and innovative ideas and technology. In recent years, the growth of ICT has had a substantial impact on how SMEs function. ICTs include technologies such as the Internet, Extranets, Intranets, ERP and other such technologies that improve an organization’s services and operations. The use of ICT opens up an opportunity for firms to gain a competitive advantage over their competitors. It is claimed that “through the use of ICT, SMEs can develop capabilities for managing resources, and develop capacity for information gathering and dissemination and gain access to rapid flow of information” (Ndubisi & Kahraman, 2005). Kutlu and Özturan (2008) argue that SMEs can use ICT as a tool to reduce transaction costs, create innovation,


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facilitate market niches and create stronger links with customers and suppliers. ICT helps SMEs meet the challenges of an ever-changing environment. ICT can play a significant role in the operations of rural SMEs, which are considered an important potential area of ICT application. Galloway and Mochrie (2005) found a lag in ICT uptake by rural SMEs because of a gap in supply and demand. Although ICT access in rural SMEs has the potential to promote economic development, the latest technologies are not appropriate because such firms lack the propensity for growth and diversification. Efforts to adapt technology to rural SMEs may not provide results at the desired or expected rate (Galloway, 2007). SME firms can achieve above-industry-average returns from IT investments by creating IT governance structures and managing IT risk. Because of the numerous benefits of ICT, SMEs are attempting to adopt ICT applications to support their businesses. SMEs’ adoption of ICT differs from that of larger enterprises because of SMEs’ unique characteristics. The factors found by researchers to be critical to SMEs’ adoption of ICT are summarized in Table 1. Tan, Choy Chong, Lin, and Cyril Eze (2010) found that financial support, security and resistance to organizational change are significant factors that influence the adoption of ICT in developing countries. Bayo-Moriones and Lera-López (2007) revealed that factors such as infrastructure, top management support, the environment and skilled employees influence ICT implementation in an organization. Levels of ICT adoption in SMEs are influenced by external and internal factors such as firm size, prior technology use, self-efficacy and government support. The review of existing literature makes it clear that numerous studies have been conducted on the use, impact, adoption and diffusion of ICT by SMEs. Some researchers have attempted to identify the factors that influence the adoption of ICT among SMEs. Many previous studies have revealed that the adoption of ICT by SMEs remains lower than expected. Some barriers, such as a lack of knowledge about ICT, a lack of government support, a lack of ICT infrastructure, a lack of support from banks and management problems, have been identified as causes of the low adoption of ICT by SMEs. However, there has been very limited research on issues concerning the adoption of ICTs in rural SMEs in developing countries. The above literature also shows that there is no notable research on SMEs’ adoption of ICT in rural areas of Saudi Arabia, even though such SMEs are considered a productive base of the Saudi economy. Therefore, this study has been undertaken to bridge the gap.

3. SME sectors in Saudi Arabia According to the Saudi Arabian Monetary Agency (SAMA), SMEs represent more than 90% of Saudi Arabia’s business establishments, which number 1.97 million. The number of SMEs is expected to grow to 2.5 million by 2015 (Ismail, 2012). Small enterprises with less than five employees have accounted for the largest share of Saudi Arabia’s firms, representing 45.5% of total enterprises. Enterprises with 5–59 employees and enterprises with more than 60 employees constitute 42% and 3.8% of Saudi firms, respectively (Almoawi & Mahmood, 2011). Saudi Arabia is moving in the right direction by promoting SMEs throughout the Kingdom to develop its economy further. SMEs in Saudi Arabia have the capacity to employ a large labor force, particularly in rural areas and especially among young people, taking pressure off the public sector to do so (Adaileh, 2012). This is attractive in Saudi Arabia because of the simplicity of SMEs’ establishment, the simplicity of their


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Table 1. Factors affecting ICT adoption among SMEs. Country

Governmental policy, lack of knowledge, information system planning, degree of ICT readiness, lack of a long-term strategy Customer pressure, ICT infrastructure, skilled personnel, government policy

Italy

Customer and supplier pressure, strategic and organizational change, qualified personnel, organizational structure, training Business benefits, security, lack of internal IT expertise, staff attitudes, role of CEO/owner Lack of ICT personnel, management problems, insufficient compatibility with existing ICT and organizational culture Compatibility, complexity, relative advantage, organizational readiness, partners’ pressure, government support, competitive pressure, customers’ pressure ICT skills of owner and manager, business strategy and objectives, competitive pressure, customer and supplier pressure, government regulation, complexity, ICT infrastructure, management support ICT support, skilled human resources, training, compatibility

UK Switzerland


Factors identified

USA, Spain, Portugal and Poland USA

Canada

UK

Spain Malaysia

Australia

Italy Spain Nigeria Sweden Germany UK

ICT adoption benefits, new business opportunities, unavailability of ICT, qualified personnel, lack of confidence, security, regulatory environment Lack of strategic vision, managerial and technological knowledge, reluctance of employees to adapt to new technology, organizational resources and resistance to technology-related change Lack of compatibility, lack of sufficient information from vendors, supporting plans/ strategies Technology strategy, training and socialization, size of firm Lack of financial resources, lack of government support, lack of support from banks, poor infrastructural facilities, lack of skills Business size, suppliers’ pressure, marketing strategy, innovativeness of CEO External pressure, perceived benefits, relative advantage, competitive pressure, CEO/owner knowledge of IT, CEO/owner innovativeness Compatibility, complexity, trialability, observability, relative advantage, top management support, organizational ICT readiness, ICT expertise, competitive pressure, external ICT support

No. of SMEs 56 Spanish, 25 Portuguese 1028 Polish, 592 USA 42 799 400 6717 237

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297

Authors Wielicki and Arendt (2010) Lohrke, Franklin, and Frownfelter-Lohrke (2006) Colombo, Croce, and Grilli (2013) Harindranath et al. (2008) Hollenstein (2004) Ifinedo (2011)

Alshawi et al. (2011)

406

Lopez-Nicolas and Meroño-Cerdán (2009) Tan et al. (2009)

250

Love and Irani (2004)

128

Corrocher and Fontana (2008)

25 25 1170 8 102

Bruque and Moyano (2007) Apulu et al. (2011) MacGregor (2004) Fink and Disterer (2006) Ramdani et al. (2013)

administrative structure and the small amount of capital needed for their initial foundation and operation. It is widely believed that it is difficult to establish a common definition of SME that would be acceptable to the Gulf countries, and in particular, to Saudi Arabia. Indeed, Saudi Arabia has no official definition of SMEs. Generally, the definition of SMEs in Saudi


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Arabia uses various quantitative criteria such as the number of employees. According to the Saudi Arabian General Investment Authority (SAGIA) micro-enterprises have fewer than 25 employees, small enterprises have between 25 and 59 employees and mediumsize enterprises have between 60 and 99 employees (Ahmad, 2012). In terms of capital, small companies are those with 5 million Saudi Riyals (USD 1.3 million) of capital, whereas medium-size ones have capital between 5 and 20 million Saudi Riyals (USD 5.3 million) (GAN, 2014). The SME sector is composed of micro-enterprises and small and medium enterprises. SMEs’ contribution to GDP is the main catalyst of economic activity in Saudi Arabia. Their contribution to GDP could increase to 37% by the end of 2015. The estimated investment in SMEs will be more than USD 70 billion by the end of 2015 (Zawya, 2014). Currently, SMEs employ more than 4.5 million people representing more than 80% of the total workforce, mostly foreign workers (Alsulami, 2014). The government and banks are providing much-needed funding to SMEs. The Ministry of Finance, through its Saudi Industrial Development Fund, along with Saudi banks, has established the “Kafalah” program, a new system for financing SMEs. The program encourages banks to finance businesses up to SR200 million ($53.3M) with loan guarantees. So far, the program has benefited approximately 1113 small and medium-sized enterprises. Other programs have also been implemented by Saudi Credit and Savings Bank, Abdul Latif Jameel’s “Finance Program” and the Centennial Fund to finance young people, small enterprises, and training courses for youth. The Prince Sultan Abdulaziz Fund for women entrepreneurs is another good initiative for the growth of SMEs in Saudi Arabia. However, similar to most developing and Arab countries, SMEs in Saudi Arabia also face various obstacles. SMEs’ main problems and constraints are bureaucracy, a lack of financial support and a lack of credit options. Inadequate government support, an unfriendly business environment, unpredictable policy changes, and a lack of training are also considered important problems hindering SME growth in Saudi Arabia (Ahmad, 2012). SMEs in Saudi Arabia are also challenged by weak bonds between SMEs and large enterprises, the lack of a policy structure and regulation and a lack of government support. SMEs in Saudi Arabia also face challenges in adopting ICT for their business operations. The main reasons for the non-usage of ICT among SMEs are their belief that there is no need to use technology in their work and a lack of training facilities (CITC, 2015).

4. Theoretical framework and hypothesis Numerous theories and models, such as the diffusion of innovations theory, resourcebased theory, the unified theory of acceptance and use of technology, institutional theory, the perceived e-readiness model, the organizational imperative model, the IT business value model, the e-readiness assessment model and the managerial imperative model, have been developed and used to investigate the adoption of ICT at the firm level. Different theories and models have different focuses and are designed to investigate different aspects of ICT adoption. Some theoretical models focus only on external environmental factors, whereas others examine technological factors. Moreover, most of the previous studies based on technology adoption theories emphasize the adoption of IT both at the individual level and in the context of developed countries.



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However, the TOE framework developed by Tornatzky and Fleischer (1990) provides a holistic and guiding theoretical basis to investigate the adoption of ICT at the organizational level by addressing a wide variety of perspectives. The TOE framework is an organization-level framework that explains that three different factors of an organization’s context influence adoption decisions. These three factors are the technological context, the organizational context and the environmental context. The technological context describes both the internal and external technologies relevant to the firm. The organizational context is defined in terms of the resources available to support the acceptance of innovation. The environment context represents the setting in which a firm conducts its business (Zhang & Wang, 2013). The TOE framework has been used to explain the adoption of technology (Baker, 2012), the Internet (Martins & Oliveira, 2009), websites (Oliveira & Martins, 2008), open systems (Chau & Tam, 1997), e-business (Wen & Chen, 2010) and cloud computing (Borgman, Bahli, Heier, & Schewski, 2013). The TOE framework is only one comprehensive model in the context of developing countries that identifies the technological, organizational and environmental factors that affect technology adoption. Different studies have combined the TOE framework and Roger’s theory of adoption and diffusion of innovations (ADT) to understand IT adoption. The TOE framework is consistent with the ADT, in which Rogers Everett (1995) emphasized technological characteristics. Roger’s theory is identical to the technology context of the TOE framework, but the TOE framework includes a new and important component: the environmental context. Some authors used the TOE framework together with theories such as the ADT to understand IT adoption (Chong, Lin, Ooi, & Raman, 2009; Wang, Wang, & Yang, 2010; Zhu, Dong, Xu, & Kraemer, 2006). Chong et al. (2009) add the ADT’s relative advantage, complexity and compatibility to the TOE framework. Zhu et al. (2006) combined the ADT’s relative advantage and compatibility with the TOE framework. Wang et al. (2010) add the ADT’s relative advantage, compatibility and complexity to the TOE framework. However, only a few studies have applied the TOE framework to investigate technology adoption in the context of the Arab world. Therefore, the TOE framework has been used and extended with personal innovativeness as the theoretical underpinning of the research (Figure 1). This study extended the TOE model by including the individual context considering the fact that adoption of ICT relies heavily on the individual decision of owners/managers of SMEs in Arab countries such as Saudi Arabia (Almoawi & Mahmood, 2011).

4.1. Technological context The technological context has a high impact on organization’s adoption of ICT. However, it is claimed that very few studies have examined the impact of technological characteristics on SMEs’ adoption of ICT (Ramdani et al., 2013). The technological context includes relative advantage, compatibility and complexity. Relative advantage is defined as “the degree to which an innovation is perceived as being better than the idea it supersedes” (Rogers, 2003, p. 229). It explains the benefits and losses an organization will experience when it accepts or rejects a technology. ICT provides many benefits to SMEs, such as reducing operating and administrative costs, increasing productivity and improving business processes and growth (Markus & Tanis, 2000). Previous studies found that relative advantages


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Figure 1. Research model.

significantly influence the adoption of ICT among SMEs in developing countries such as Saudi Arabia (Grandon & Pearson, 2004). Compatibility is defined as “the degree to which an innovation is perceived as consistent with the existing values, past experiences, and needs of potential adopters” (Rogers, 2003, p. 240). It is one of the most important determinants of SMEs’ adoption of ICT (Premkumar, 2003). If ICTs are compatible with existing work practices, SMEs will be more likely to adopt them (Chang, Park, & Chaiy, 2010). Grandon and Pearson (2004) found that compatibility involves statistically significant factors that influence SMEs’ adoption of ICT. Complexity is defined as “the degree to which an innovation is perceived as relatively difficult to understand and use” (Rogers, 2003, p. 257). The faster, more immediate adoption of ICT depends on easy-to-understand and easy-to-use technology. Several studies found complexity as a determinant factor of ICT adoption by SMEs (Thong, 1999); most such studies found that complexity is negatively associated with the organizational adoption of ICT (Grover, 1993). Based on the above discussion, this study proposes the following hypotheses. H1: Relative advantage will have a direct and positive effect on the adoption intention of ICT within Saudi SMEs. H2: Compatibility will have a direct and positive effect on the adoption intention of ICT within Saudi SMEs. H3: Complexity will have a direct and negative effect on the adoption intention of ICT within Saudi SMEs.

4.2. Organizational context Organizational context is considered an important determinant with a strong impact on SMEs’ adoption of ICT (Premkumar, 2003). It includes top management support, employees’ ICT skills and organizational culture. An organization’s successful adoption of any technology requires support from top management (Wang & Shi, 2009). Numerous previous studies have shown that top management support influences the adoption of technology, and a positive relation between top management support and SMEs’ adoption of ICT has



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been reported (Alam & Noor, 2009). The ICT decision maker is very likely to be in an SME’s top management team in developing countries such as Saudi Arabia and the ICT adoption process is directly affected by his or her decision and support (Bruque & Moyano, 2007). The adoption of ICT in the Arab world is not only challenging but also risky for business organizations such as SMEs because of the strong influence of cultural and social boundaries (Aldraehim, Edwards, Watson, & Chan, 2013). Research has shown that the effective adoption of ICT in an organization depends on the organization’s culture and countries that will communicate with that organization (Westrup, Liu, El Sayed, & Al Jaghoub, 2003). Lopez-Nicolas and Meroño-Cerdán (2009) showed that diverse organizational cultures such as clan, hierarchy and market have an impact on an organization’s use of ICT. Twati and Gammack (2006) found a strong relationship between organizational culture and an SME’s adoption of ICT. Based on the above discussion, this study proposes the following hypotheses. H4: Top management support will have a direct and positive effect on the adoption intention of ICT within Saudi SMEs. H5: Saudi organizational culture will have a direct and positive effect on the adoption intention of ICT within Saudi SMEs.

4.3. Environmental context The environmental context has a high impact on adoption of ICT by SMEs. It includes the regulatory environment, the competitive environment, supplier pressure and customer pressure. The regulatory environment is an important environmental factor that affects an organization’s adoption of technology. The literature suggests that SMEs operating in an environment restrained by government policies and other regulations have a low rate of ICT adoption (Dasgupta, Rajesh, & Sethi, 1999). It is argued that government policies and regulations, intellectual property, consumer protection laws and compliance can facilitate or inhibit SMEs’ adoption of ICT (Al-Somali, Gholami, & Clegg, 2011). A competitive environment has long been recognized as an important driver of the organizational adoption of ICT (Jeyaraj, Rottman, & Lacity, 2006). Numerous studies have acknowledged the impact of competitive pressure on ICT adoption. Lin and Lin (2008) revealed that competitive pressure is an important factor for SMEs’ successful adoption of ICT in highly competitive environments. Premkumar and Ramamurthy (1995) argued that competitive pressure can make it a strategic necessity for SMEs to adopt new technologies to compete in the marketplace. Intensity of competition is associated with the degree of ICT adoption (Lertwongsatien & Wongpinunwatana, 2003). Alshawi, Missi, and Irani (2011) found that competitive pressure is an important factor in SMEs’ adoption of ICT. In the context of Saudi Arabia, where the market is relatively small, SMEs will adopt ICT when their competitors do so (Almoawi & Mahmood, 2011). Hence, we hypothesize that H6: A less stringent regulatory environment will have a direct and positive effect on the adoption intention of ICT within Saudi SMEs. H7: A competitive environment will have a direct and positive effect on the adoption intention of ICT within Saudi SMEs.

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4.4. Individual context Individual context is considered one of the important determinants of SMEs’ adoption of ICT. It includes owner/manager innovativeness and owner/manager ICT skills and knowledge. Some researchers have shown that SME owner/managers are the key decision makers whose decision influences the firm’s activities both now and in the future (Smith, 2007). The ICT adoption decision – from the planning stage to implementation – is strongly influenced by the owner/manager’s innovativeness. If owners and managers are more innovative, they are more likely to accept new innovation in SMEs, such as technology (Bruque & Moyano, 2007). Lee and Runge (2001) found that the owner/manager’s innovativeness is the most important factor in the adoption of ICT. The owner/manager’s existing competencies in ICT use, ICT skills and knowledge and personal experience with ICT positively influence the adoption of ICT (Carson & Gilmore, 2000). Dubelaar, Sohal, and Savic (2005) found that the owner/manager’s ICT knowledge can influence the adoption of ICT. Almoawi and Mahmood (2011) revealed that an owner/ manager’s lack of ICT knowledge is the main barrier to SMEs’ adoption of ICT. Similarly, Chang (2006) acknowledged the positive relationship between the owner/manager’s technological knowledge and an SME’s adoption of ICT. Based on the above discussion, this study proposes the following hypotheses. H8: Owner/manager innovativeness has a direct and positive effect on the adoption intention of ICT within Saudi SMEs. H9: Owner/manager ICT knowledge has a direct and positive effect on the adoption intention of ICT within Saudi SMEs.

5. Methodology 5.1. Research setting The unit of analysis for this study is SMEs because the research objective is to examine the factors that influence the adoption of ICT among SMEs in rural areas of Saudi Arabia. The research population was SMEs in Jeddah, an important commercial hub in Makkah Province, Saudi Arabia. This study examined Jeddah for several reasons. First, Jeddah is an important thriving business center in Saudi Arabia. Second, Jeddah enterprises are showing a readiness to adopt the latest technologies. Third, rural areas of Jeddah depend on SMEs, and most of the area’s SMEs have access to ICT. Two rural areas from the northern part of Jeddah (Asfan and Thuwal) and two rural areas from the southern part of Jeddah (Bahra and Hadda) were selected as the sample frame. To obtain some measure of generalizability, a random sampling of businesses listed in the Council of Saudi Chambers of Commerce and Industry (CSCCI) directory was used (Saunders, 2009). The size of the sample is an important factor to ensure both the representativeness of the sample and its suitability for executing the appropriate statistical tools. Various sample sizes have been recommended in the past, and different theories for reaching an ample sample size have been suggested (Hulland, Oliveira, Rodrigues, & Ruegg, 2011) . However, sample-size requirements may vary according to the type of statistical analysis, and a variety of opinions are also observed in the literature, even when the same tools are applied (Tabachnick & Fidell, 1996). Nunnally (1978) recommends a sample size equivalent


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to 10 observations per model variable. In this study, there are 10 variables for multivariate data analyses. Based on the above-mentioned examples and notions from previous studies, this study must adopt a sample size at least 100 or more because structural equation modeling (SEM) was the main tool used for data analysis. A quantitative, cross-sectional survey was used to collect data. The survey questionnaire method was selected in this study for its utility in collecting primary data (Saunders, 2009). The respondents were SMEs’ IS managers. If an SME had no IS manager, the respondents were CEOs or owners. These individuals generally have extensive knowledge about the organization, have access to the organization’s information and have the ability to complete the survey questionnaire.

5.2. Measurements All of the measure’s items within the proposed model were developed from prior studies and modified to fit the research context of our study. The items for Relative Advantages, Complexity and Compatibility were adapted from Premkumar and Roberts (1999); Top Management Support was adapted from Thong, Yap, and Raman (1996); Organizational Culture and ICT Adoption Intention were adapted from Elbeltagi, Al Sharji, Hardaker, and Elsetouhi (2013); Regulatory Environment was adapted from Ramsey and McCole (2005); Competitive Environment was adapted from Thong (1999) and Al-Qirim and Corbitt (2002); Owner/ manager Innovativeness was adapted from Agarwal and Prasad (1998); and Owner/ manager ICT Knowledge was adapted from Thong and Yap (1995). Most of the variables were scored on a 5-point Likert scale (from “1” = strongly disagree to “5” = strongly agree), with high scores representing greater standing on the variables of interest. Age was measured in years. Gender was measured as a dichotomous variable (i.e. 1 = male, 0 = female). Table 2 lists the variable, item and associated references for each variable.

5.3. Questionnaire design and data collection The research questionnaire had three parts. Part A contains relevant information about the organization. Part B contains the demographic questions asked of the respondents. Respondents were asked about their gender, age, marital status, educational qualifications and IT experience. Part C includes questionnaires for the different constructs of the research model. The questionnaire was originally developed in English and then translated into the local language (Arabic). The local version has gone through several revisions until both the English and Arabic versions were judged to be similar by a group of experts. The questionnaire was verified by three MIS experts to ensure its appropriateness. Next, a pilot study of 10 respondents was conducted in a pretest to revise the wordings, format, content, sequence, layout, simplicity and clarity of the survey instrument (Akter, D’Ambra, & Ray, 2010). The feedback was used to design and test the effectiveness of the final questionnaire and facilitated a smooth data collection. The expert panel review, the pre-testing and the pilot study were used to refine the items. The face-to-face, in-person, one-on-one and infield (on-site) survey interaction techniques were adopted because they provide maximum response rates compared to telephone, postal mail and online surveys in a developing country context (Andaleeb, 2001). Moreover, they improve accuracy, minimize missing data and avoid delays in the

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Table 2. Summary of measurement items. Construct Technological context Relative advantages

Compatibility


Complexity

Organizational context Top Management Support

Organizational Culture

Item

Source

RA1: The ICT will enhance the efficiency of our business Premkumar and Roberts (1999) RA2: The ICT will improve the performance of our business RA3: The adoption of ICT will provide timely information for decision-making COP1: ICT is compatible with the current situation of our Premkumar and Roberts (1999) organization COP2: ICT is compatible with our organization’s current values and goals COP3: ICT is compatible with our work style COM1: We believe that ICT is very difficult to use Premkumar and Roberts (1999) COM2: The skills required to use these technologies are too complex for our employees COM3: Integrating ICT into our work practices will be very difficult TM1: Top management enthusiastically supports the Thong et al. (1996) adoption of ICT TM2: Top management has allocated adequate resources to the adoption of ICT TM3: Top management actively encourages employees to use ICT in their daily tasks OC1: Our organization is very responsive and changes Elbeltagi et al. (2013) easily OC2: There is a high level of agreement about how we do things in this company OC3: There is a shared vision of what this organization will be similar to in the future

Environmental Context Regulatory Environment RE1: Government laws and regulations support ICT initiatives and implementation RE2: The use of ICT was driven by government-provided incentives RE3: The use of the ICT was driven by organizational needs. Competitive CE1: We believe we will lose our customers to our Environment competitors if we do not adopt ICT CE2: We feel it is a strategic necessity to use ICT to compete in the marketplace CE3: We believe we will lose our market share if we do not adopt ICT Individual context Owner/manager OM1: If we heard about a new information technology, we Innovativeness would look for ways to experiment with it OM2: Among our peers, we are usually the first to try out new information technology OM3: We do not hesitate to try new information technology Owner/manager ICT OK1: We have the necessary skills and knowledge Knowledge to use ICT OK2: We are familiar with ICT OK3: We have the experience to use ICT Adoption ICT Adoption Intention IA1: We have a high intention to use ICT in our organization IA2: We intend to learn about using ICT IA3: We plan to use ICT to manage our business

Ramsey and McCole (2005)

Thong (1999) and Al-Qirim and Corbitt (2002)

Agarwal and Prasad (1998)

Thong and Yap (1995)

Elbeltagi et al. (2013)

context of a developing country (Malhotra, 2008). Trained research assistants distributed a copy of the questionnaire and an envelope to each respondent, explained the purposes of the study, assured the anonymity of respondents and their organization, explained how the questionnaire was to be filled out, and described how the completed questionnaires


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would be collected. Two hundred surveys were distributed among SMEs in rural areas of Jeddah, Saudi Arabia. One hundred and fifty-three were returned, 137 of which were usable.

5.4. Data analysis


Data for this study were analyzed using the partial least squares (PLS) method, a statistical analysis technique based on the structural equation model (SEM) (Götz, Liehr-Gobbers, & Krafft, 2010). SmartPLS software was used for analysis of the data. It is one of the prominent software applications for partial least squares structural equation modeling (PLS-SEM) (Hair, Hult, Ringle, & Sarstedt, 2013).

6. Findings 6.1. Demographics The demographic characteristics of the respondents and their firms are presented in Table 3. The overwhelming majority of respondents were male (89%) and held the position of CEO (62%). There is no large gap between manufacturing and service organizations. Most of the respondents (70%) are more than 30 years old and had more than 3 years of IT experience (64%).

6.2. Measurement model Reliability and validity should be measured before testing the hypothesis (Bagozzi, Yi, & Phillips, 1991). Reliability was assessed by considering Cronbach’s alpha and composite Table 3. Profile of respondents and firms. Description Type of organization Manufacturing Services Comprehensive (all business) Position in organization Owner CEO IS Manager Gender Male Female Age Less than 20 years 21–30 years 31–40 years 41–50 years More than 50 years IT usage experience Less than 1 year 1–3 years 4–6 years 7–9 years More than 10 years

Frequency

Percentage

61 54 22

44 40 16

23 85 29

17 62 21

122 15

89 11

4 37 68 23 5

3 27 49 17 4

12 37 57 24 7

9 27 42 17 5

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Table 4. The measurement model.


IA OI RE COM OK COP OC CE RA TM

AVE

CR

Cronbach’s alpha

0.81 0.80 0.61 0.75 0.77 0.88 0.80 0.66 0.77 0.77

0.92 0.92 0.82 0.90 0.91 0.95 0.92 0.85 0.91 0.91

0.88 0.88 0.68 0.87 0.85 0.93 0.91 0.74 0.85 0.86

Note: AVE: average variance extracted; CR: composite reliability; IA: ICT Adoption; OI: Owner/Manager Innovativeness; RE: Regulatory Environment; COM: Complexity; OK: Owner/Manager ICT Knowledge; COP: Compatibility; OC: Organizational Culture; CE: Competitive Environment; RA: Relative Advantages; TM: Top Management Support.

reliability. Composite reliability and Cronbach’s alpha values of 0.60–0.70 are acceptable in exploratory research. Composite reliability and Cronbach’s alpha values below 0.60 indicate a lack of internal reliability (Hair et al., 2013). Table 4 shows that all the constructs have Cronbach’s alpha and composite reliability values of more than 0.68, which is higher than the recommended value. Thus, the constructs were deemed to have adequate reliability. Validity was assessed by considering both convergent and discriminant validity. Convergent validity is considered satisfactory when measurement constructs have an average variance extracted (AVE) of at least 0.50 and the items loading are well above 0.50 (Hair et al., 2013). Table 4 presents AVE and Table 5 shows the item loading. The AVE ranged from 0.61 to 0.88 and item loading ranged from 0.70 to 0.97, both of which are greater than the recommended level. Therefore, the conditions for convergent validity were met. Discriminant validity was assessed by the square root of the AVE and the cross-loading matrix. The square root of the AVE of a construct must be larger than its correlation with other constructs for satisfactory discriminant validity (Henseler, Ringle, & Sinkovics, 2009). The square roots of AVE, shown in Table 6, were greater than their corresponding correlation, indicating that our data had good discriminant validity.

6.3. Structural model The structural model was constructed to identify the path relationships among the constructs in the research model. The bootstrap method was used to test the hypothesis. The study tests the relationship between endogenous and exogenous variables using a path coefficient (β) and t-statistics. The study found that Owner/Manager Innovativeness (t = 2.510, β = 0.043), Regulatory Environment (t = 2.435, β = 0.075), Owner/Manager ICT Knowledge (t = 8.981, β = 0.566), Organizational Culture (t = 2.731, β = 0.062), Relative Advantages (t = 4.821, β = 0.305) and Top Management Support (t = 2.586, β = 0.061) had significant effects on the intention to use ICT, whereas Complexity (t = 1.109, β = 0.045), Compatibility (t = 1.321, β = 0.056) and Competitive Environment (t = 0.627, β = 0.023) had no significant effect on the intention to use ICT. Therefore, H1, H4, H5, H6, H8 and H9 were supported, whereas H2, H3 and H7 were not (Figure 2) (Table 7).

IA1 IA2 IA3 OI1 OI2 OI3 RE1 RE2 RE3 COM1 COM2 COM3 OK1 OK2 OK3 COP1 COP2 COP3 OC1 OC2 OC3 CE1 CE2 CE3 RA1 RA2 RA3 TM1 TM2 TM3

IA

OI

RE

COM

OK

COP

OC

CE

RA

TM

0.8541 0.9240 0.9242 0.1615 0.3513 0.3976 0.2316 0.2783 0.2841 0.3241 0.0746 0.0973 0.8273 0.7550 0.7528 −0.4196 −0.3991 −0.3316 −0.0218 0.1442 0.1096 0.4272 0.4044 0.5150 0.7003 0.7359 0.8149 0.3790 0.3617 0.6646

0.2660 0.3724 0.3573 0.8383 0.9178 0.9343 0.3475 0.4349 0.1501 0.0388 −0.0504 −0.0867 0.3416 0.2030 0.2710 −0.2882 −0.2718 −0.1479 0.1554 0.2612 0.2751 0.2977 0.0914 0.1643 0.3176 0.2283 0.3106 0.1588 0.2089 0.2411

0.2865 0.3525 0.2842 0.3546 0.3586 0.3606 0.7742 0.8615 0.7069 0.0261 −0.0741 −0.1358 0.3514 0.0342 0.2266 −0.2812 −0.2252 −0.1652 0.1709 0.2666 0.2619 0.0378 0.0993 0.2771 0.3573 0.1505 0.3110 0.2013 0.2126 0.2447

0.2760 0.2284 0.2152 −0.0085 −0.0269 0.0290 0.0164 −0.0160 −0.0469 0.9722 0.7908 0.8352 0.2002 0.2385 0.1122 0.0332 −0.0023 0.0264 −0.1266 −0.0695 −0.0690 0.2678 0.4138 0.3229 0.2128 0.2899 0.2753 0.0846 0.0466 0.1904

0.7290 0.8220 0.8411 0.1437 0.3098 0.3177 0.1775 0.1576 0.2184 0.2459 0.0755 0.1031 0.8855 0.8723 0.8801 −0.4679 −0.4273 −0.3802 −0.0402 0.0906 0.0601 0.4082 0.3677 0.4862 0.6811 0.7288 0.7555 0.3720 0.3455 0.6603

−0.3144 −0.4542 −0.3410 −0.1595 −0.3039 −0.2041 −0.1823 −0.1469 −0.2378 0.0087 0.0755 0.0077 −0.3649 −0.3713 −0.4709 0.9624 0.9011 0.9569 −0.5699 −0.6167 −0.5760 −0.0273 −0.0963 −0.0468 −0.4052 −0.3114 −0.3079 −0.3226 −0.3220 −0.3864

0.0755 0.2254 0.0973 0.2391 0.3099 0.2324 0.2049 0.2687 0.1910 −0.0589 −0.0632 −0.0668 0.1120 0.0070 0.1214 −0.6127 −0.5724 −0.5789 0.7921 0.9645 0.9209 −0.0570 −0.1091 −0.0731 0.1776 0.0572 0.0652 0.0015 0.0943 0.0990

0.4614 0.5325 0.5097 0.1193 0.2051 0.2430 0.0889 0.1441 0.1819 0.4470 0.2009 0.2679 0.5162 0.4254 0.4317 −0.1001 −0.0463 −0.0396 −0.2494 −0.1215 −0.0863 0.7971 0.7834 0.8545 0.5503 0.5013 0.5302 0.2071 0.2746 0.4409

0.6864 0.7919 0.8233 0.1620 0.3237 0.3240 0.2812 0.2517 0.1992 0.3375 0.1389 0.1520 0.7937 0.7097 0.6535 −0.4076 −0.3634 −0.3003 −0.0744 0.1026 0.0748 0.5174 0.3975 0.5314 0.8317 0.8865 0.9219 0.3399 0.3143 0.6467

0.4533 0.5092 0.5839 0.1211 0.1929 0.2754 0.1842 0.1288 0.2763 0.1740 0.0469 0.0432 0.5379 0.4847 0.4649 −0.3648 −0.4170 −0.3319 −0.0183 0.0908 0.0406 0.3309 0.2812 0.3095 0.4337 0.4364 0.5474 0.8474 0.8756 0.9163



Table 5. Cross-loading matrix.

15



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Table 6. Correlation matrix and square root of the AVE. IA OI RE COM OK COP OC CE RA TM

IA

OI

CE

COM

OK

COP

OC

RE

RA

TM

0.9014 0.3709 0.3416 0.2637 0.8867 −0.4120 0.1495 0.5570 0.8540 0.5744

0.8978 0.3939 0.0008 0.3116 −0.2577 0.2893 0.2267 0.3240 0.2374

0.7835 −0.0226 0.2372 −0.2430 0.2847 0.1813 0.3093 0.2533

0.8695 0.2094 0.0202 −0.0665 0.4083 0.2954 0.1408

0.8793 −0.4561 0.0922 0.5226 0.8202 0.5653

0.9405 −0.6269 −0.0681 −0.3846 −0.3975

0.8955 −0.0967 0.1106 0.0806

0.8123 0.5973 0.3777

0.8809 0.5392

0.8802



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Figure 2. Findings of the SEM model. Table 7. Structural model. Hypothesis H1 H2 H3 H4 H5 H6 H7 H8 H9

Path

β

t-statistics

p-Value

Comments

RA -> IA COP-> IA COM -> IA TM -> IA OC -> IA RE -> IA CE -> IA OI -> IA OK -> IA

0.305 0.056 0.045 0.061 0.062 0.075 0.023 0.043 0.566

4.821 1.321 1.109 2.586 2.731 2.435 0.627 2.510 8.981

.000* .188 .258 .014* .020* .015* .532 .031* .000*

Supported Not Supported Not Supported Supported Supported Supported Not Supported Supported Supported

*Significant at p < .05. N = 137.

7. Discussion Although numerous studies have examined the factors of ICT adoption, few studies have tested those factors on SMEs. This study is one of the first to examine ICT adoption in rural Saudi Arabian SMEs using an extended TOE framework. Based on the results of this study, some factors were identified as being responsible for Saudi Arabian SMEs adopting ICT. This study found a positive relationship between environmental factors such as the regulatory environment and ICT adoption among SMEs in rural areas of Saudi Arabia. It seems that the government regulation and Saudi law provide sufficient protection regarding the use of ICT by SMEs. Regulatory environment is very important for ICT adoption as it can facilitate or hinder the enterprises to adopt ICT (Cavalcanti, 2006; Dholakia & Kshetri,


18


2004). Conversely, this study did not find any significant relationship between competitive environment and ICT adoption. This finding is consistent with previous studies. Thong (1999) concludes that there is no relationship between competitive environment and SMEs’ adoption of ICT. Premkumar and Roberts (1999) also did not find any relationship between competitive environment and SMEs’ adoption of ICT. This study revealed that the relationship between the owner/manager’s ICT knowledge and ICT adoption was statistically significant. This result is consistent with the results of Elbeltagi et al. (2013). They have shown strong support for the association between owner/manager ICT knowledge and innovativeness in ICT adoption. In SMEs, the primary decision maker is the owner/manager, whose knowledge determines the level of support for ICT adoption (Ramdani et al., 2013). In the Arab world, innovativeness and the owner/manager’s ICT knowledge played a critical role in ICT adoption (Elbeltagi et al., 2013). In Saudi Arabia, the owner–manager makes the majority of decision including ICT adoption decision in their organization. The owner-manager of SMEs in Saudi Arabia usually has full control of financial resources and active participation in IT investment. As a consequence, the owner/manager’s ICT knowledge and their innovativeness are necessary for ICT adoption in SMEs of Saudi Arabia. Organizational factors such as top management support and culture are also regarded as the important factors that affect the adoption of ICT. The result of this research shows that top management support could partly explain the adoption of ICT in Saudi Arabia. The IT adoption literature has provided evidence that top management support positively influences higher levels of ICT adoption and use in SMEs (Ghobakhloo, Hong, Sabouri, & Zulkifli, 2012; Hoque, Saif, AlBar, & Bao, 2015). Top management’s opinion carries more weight in the Arab world, where top managers’ roles are undoubtedly very important, especially in SMEs. This study also revealed a positive relationship between organizational culture and ICT adoption. Baker, Al-Gahtani, and Hubona (2011) confirmed the impact of culture on the adoption of IT in developing countries such as Saudi Arabia. Saudi Organization is responsive to the Saudi government use of ICT in businesses and government organizations. Currently, the private and public sectors of Saudi Arabia are rapidly increasing their spending on ICT. SMEs have also nurtured an organizational culture to adopt ICT. However, technological factors such as complexity and compatibility have no significant impact on ICT adoption among rural SMEs in Saudi Arabia. Al-Ghaith, Sanzogni, and Sandhu (2010) found no association between complexity, compatibility and ICT adoption in Arab countries. Owner/managers are uninformed about the importance of complexity and compatibility because the adoption of technology in Arab firms primarily depends on the government-sanctioned technology adoption policy. This study found the strongest relationship between relative advantage and ICT adoption in SMEs. This result is consistent with research on technology innovation. Mohr, Sengupta, and Slater (2009) found that relative advantage is a driving force for the adoption of ICT. Peltier et al. (2012) revealed that relative advantage is the key predictor of ICT adoption. AlGhaith et al. (2010) explored the significant effect of relative advantage on ICT and eservice adoption in Saudi Arabia. In Saudi Arabia, organization needs to see relative advantage so that they allocate resources for adoption of ICT. The advantages SMEs get from using ICT were perhaps one of the main reasons for adoption. The findings of this study can be used to develop strategies and policies to increase the rate of ICT adoption among SMEs in Saudi Arabia. ICT Sustainability plan and



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financial support may encourage SMEs in Saudi Arabia to adopt ICT. In addition, effective coordination among all agencies and ministries is essential to inspire SMEs to adopt ICT. This study suggests that the government should establish technology resource centers to educate owners and managers about the potential of new technologies. Moreover, the government should organize conferences or workshops to enhance the knowledge of SME owners and managers in Saudi Arabia. The business organizations and business support agencies should play a role in providing technical support for greater ICT adoption among SMEs in Saudi Arabia. The CSCCI can act as a link between SMEs and those organizations that will serve that sector. They can identify the ICT training needs of SMEs and can arrange training program for them. The CSCCI can facilitate the financing of SMEs to buy the latest technology. The findings can give ICT service providers an insight about the factors that influence the ICT adoption and support for decision-making and marketing. Finally, this study’s findings are important to the policy-makers and managers who are likely to assist in increasing the adoption of ICT.

8. Conclusion SMEs play a vital role in Saudi Arabia’s economy. Business organizations in Saudi Arabia, particularly SMEs, have been significantly influenced by advances in ICT. This study’s primary contribution is to extend the TOE framework for examining the factors that influence the adoption of ICTs among SMEs in rural areas of Saudi Arabia. The result from PLSSEM analysis has shown that the TOE model is truly a robust tool for ICT adoption in SMEs. Moreover, the theoretical model provides us with the factors that influence the adoption of ICT by SMEs in Saudi Arabia. If these factors have a significant effect, then SMEs in Saudi Arabia will be more willing to adopt ICT. This study has some limitations. We surveyed only rural areas in Saudi Arabia, which may raise concern about the generalizability of the findings. Future research should devote more attention to SMEs in urban areas. This research is cross-sectional. Unless information is gathered for different time frames, the contingent and causality effects of users’ level of experience with the system cannot be confirmed. Further research can use longitudinal data to address this limitation. Finally, this study follows only quantitative research approaches. Future research can follow both quantitative and qualitative research approaches. Despite some of these limitations, this study represents a milestone that will help future researchers in Arab countries to understand the factors that enable ICT adoption in SMEs.

Disclosure statement No potential conflict of interest was reported by the authors.

Funding This work was supported by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah [Grant No. 611-830-D1435]. The authors, therefore, gratefully acknowledge the DSR technical and financial support.

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Notes on contributors Adnan Mustafa AlBar is an Associate Professor at the Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Saudi Arabia. He was appointed as the first IS chairman where he lead team who prepared the IS undergraduate curriculum. He was then appointed as the vice dean for students affairs deanship for development for two years. Dr. Adnan had supervised the team who implemented the University SAP ERP project for three years. He has attended training programs inside the University and overseas. He teaches enterprise architecture course at the undergraduate level and enterprise modelling course at master program. He is the founder and managing director of IT Expert House where he lead a team of consultants to provide consultation for the private sectors. Dr. AlBar is a senior member of IEEE and member of the executive committee of the IEEE Western Saudi Arabia Section, a member of ACM and ISACA. His main research is in enterprise information systems, Mobility in the enterprise, enterprise architecture, business process management and technology adoption at the organizational level. You can find more about him at http://ambar.kau.edu.sa/ Md. Rakibul Hoque is an Assistant Professor of Management Information Systems at University of Dhaka, Bangladesh. His research interests include technology adoption, e-Health, mHealth and ICT4D. Dr. Hoque has published number of research articles in peer-reviewed academic journals, and has presented papers in international conferences. He had the opportunity to work in a number of research projects in Bangladesh, Australia, China and Saudi Arabia. His research has been funded through governments of Bangladesh, Saudi Arabia and China. Dr. Rakibul is the member of Association for Information Systems (AIS), UNESCO Open Educational Resources Community, Information Systems Audit and Control Association (ISACA), IEEE and Internet Society.

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