Contribution of systems thinking to business model

Int. J. Technology Intelligence and Planning, Vol. 9, No. 4, 2013

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Contribution of systems thinking to business model research and business model innovation Bastian Halecker* Innovation Management and Entrepreneurship, University of Potsdam, August-Bebel Strasse 89, D-14482 Potsdam, Germany E-mail: [email protected] *Corresponding author

Matthias Hartmann University of Applied Science, (Hochschule für Technik und Wirtschaft /HTW) Berlin, Treskowallee 8, D-10318 Berlin, Germany E-mail: [email protected] Abstract: Systems thinking (ST) offers leaders in management a systematic way of thinking for increased understanding and more effective work. However, ST has been seldom used in the past in combination with either business models or business model innovation (BMI). Because business model research is still diverse, and the process of BMI is a challenging and complex management task, the application of ST in this field is promising. This paper aims to contribute to the cross-fertilisation between ST and business model. To do so, we have reviewed the literature on systems theory and business models and identified an ST approach. The application of this ST approach to BMI is illustrated in a simplified case study example. Through this paper, we aim to contribute to business model research by conceptualising BMI types and BMI directions as well as by reviewing model theory. Additionally, the systemoriented framework provides a clear holistic agenda for practitioners to innovate business models. Keywords: systems thinking; systems theory; business model research; BMI; business model innovation. Reference to this paper should be made as follows: Halecker, B. and Hartmann, M. (2013) ‘Contribution of systems thinking to business model research and business model innovation’, Int. J. Technology Intelligence and Planning, Vol. 9, No. 4, pp.251–270. Biographical notes: Bastian Halecker is a PhD student at the University of Potsdam, where his research is focused on business model innovation, in established firms, especially with regard to systems thinking methodology. Prior to university, he worked as a consultant in an international consulting company mainly focused on the pharmaceutical industry. Matthias Hartmann holds a PhD from the University of Erlangen-Nuremberg and is a professor of Business Administration at the University of Applied Sciences (Hochschule für Technik und Wirtschaft, HTW) in Berlin.

Copyright © 2013 Inderscience Enterprises Ltd.

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B. Halecker and M. Hartmann He previously worked as a senior manager at A.T. Kearney Management Consultants. His area of research is focused on strategic technology and information management as well as operations and supply chain management. This paper is a revised and expanded version of a paper titled ‘How can systems thinking add value to business model innovation?’ presented at the 24th ISPIM Conference, Innovating in Global Markets: Challenges for Sustainable Growth, Helsinki, Finland, 16–19 June, 2013.

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Introduction “The system concept can be a useful way of thinking about the job of managing.” (Johnson et al., 1964, p.367)

Systems thinking (ST) has a long tradition (Ackoff, 1962; Beer, 1966; Churchman, 1968) with several origins (Bertalanffy, 1956) and represents a point of view rather than a method (Johnson et al., 1964). In recent years, ST has been revitalised so that researchers can better understand increasingly complex structures and disruptive changes within firms and their environments. Systems thinking can therefore support decision-making processes. The fundamental systems ideas have not changed significantly over last decades, but they are being revitalised within innovation research (i.e., Dodgson et al., 2011; Galanakis, 2006) and current strategic management discourse (Laszlo et al., 2009; Warren, 2005; Weil, 2007). Changing markets and environmental forces have caused firms to constantly rethink their existing business models. Every company has a business model (CasadesusMasanell and Ricart, 2010; Teece, 2010) that provides a source of competitive advantage (Markides, 2008). A business model articulates the economic logic of a firm (Chesbrough and Rosenbloom, 2002; Teece, 2010). Furthermore, a business model is described as a system of interdependent activities (Zott and Amit, 2010), and it manifests in the causal relationship between choices and consequences (Casadesus-Masanell and Ricart, 2010). A system is a set of interacting elements with interrelationships among them (Bertalanffy, 1956), and the term system covers a broad spectrum of concepts and approaches (Johnson et al., 1964). Even though a business model is referred to as a system (i.e., Teece, 2010; Zott and Amit, 2010) non-business model studies explain the characteristics and meaning of the term systemic in combination with business models. Increasingly clear evidence supports the existence of cross-fertilisation between systems thinking and business models. Therefore, it is necessary to understand the philosophy of systems thinking to see its benefits for business model work (Petrovic et al., 2001; Renz, 2007). Current research lacks insight into how ST can be applied to business model innovation (BMI). Therefore, our paper will apply systems thinking to BMI. This paper is guided by theory and focused on practice to contribute clearly to both fields by addressing the following research question: How can systems thinking contribute to business model research and the business model process? To answer this question, we first provide a compact review of systems thinking approaches within systems theory literature. Secondly, by applying systems thinking to BMI, we contribute to theory and practice to stimulate the field. Additionally, we demonstrate that ST can act as a theoretical anchor point in business model research as is required by Zott et al. (2011).

Contribution of systems thinking to business model research

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This paper is structured in two sections. In the first section, we focused on existing literature in the field of systems theory and business models, extracting common points within the different approaches and contributing to theory. In the second section, we explored the application level of systems thinking. On the basis of the evaluation of these perspectives, we chose one approach and applied it to an illustrative case example. On the basis of the findings of this case example, we derived first insights and recommendations for future research.

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A systematic literature review approach

The research within this paper is based on a comprehensive literature review (Boote and Beile, 2005; Hart, 1998) in the fields of systems theory and business model research. First, we reviewed systems theory literature that has a historical tradition with different strands of systems thinking and different perspectives on how to group those strands. Much has been published on systems thinking and practice since Bertalanffy (1956) published systems theory for the first time. We used existing literature reviews (Cabrera, 2006; Midgley, 2003) to gain an overview of the diverse system fields, with their many system approaches, and focused on those most relevant for academia and practitioners. Secondly, we mapped the relevant approaches by defining categories (function, cybernetics, integration) and looked for a dominant focus of each approach. Thirdly, we identified the systems approach that could best be applied to BMI. Fourthly, we reviewed business model literature in management journals ranked C or above that have been published in the EBSCO Business Source Complete with the keyword ‘business model’ in the title or abstract. The challenge presented by this research was to review the literature of two different and extensive areas. Great confusion has arisen in systems literature over the past two decades between similar concepts, such as systems thinking, systems science, systems theory and systems methods. Furthermore, no shared understanding of business models currently exists in academia (Zott et al., 2011), making it difficult to find a common starting point in this field (George and Bock, 2011).

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The promise of systems thinking

3.1 Overview of systems thinking and application fields in management In the early writings of different systems theories, no indication of the term systems thinking can be found. Around the 1980s, the term ST arose (e.g., Checkland, 1981) but was used inconsistently – there is thus no clear definition (Forrester, 1994). Within systems thinking, one sees the world as systemic; emergence and interrelatedness are the fundamental ideas of systems thinking (Flood, 2010). A systems thinking is a persuasive way if thinking to simplify thought and therefore decision-making; it is a prerequisite for successful action in a complex world. Furthermore, ST can be seen as a scientific concept (Bertalanffy, 1956; Johnson et al., 1964). In short, ST is an influential mode of thought that uses systems theory and systems thinking approaches (Figure 1), to model social systems (see also Flood, 2010; Skyttner, 2005).

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B. Halecker and M. Hartmann Connection of different systems terms

However, ST is more than the use of casual loop diagrams, as explained in The Fifth Discipline (Senge, 1990); rather, it is a starting point for model conceptualisation (Forrester, 1994). The aim and promise of ST is to provide a better big-picture view and help to dissolve complexity (Johnson et al., 1964) without breaking phenomena into parts driven by functional orientation (Flood, 2010). Employing the systems perspective and understanding ST require seeing the forest (of relationships) and not only the trees (Richmond, 1987). Finally, from the perspective of ST, Aristotle’s statement “the whole is greater than the sum of its parts” gains extended meaning because ‘greater’ stands for the interrelationships between single parts (Ropohl, 2012). Systems thinking emerged from the need to help researchers and practitioners transform the daily chaos of events and decisions into an orderly way of structuring situations and creating a common formal starting point for different views. Recently, quite a bit of research has used systems thinking in innovation management to deal with complexity (i.e., Dodgson et al., 2011; Galanakis, 2006). Furthermore, several studies have been conducted to address effectiveness in systems thinking interventions (Cavaleri and Sterman, 1997; Huz et al., 1997; Maani and Maharaj, 2004). These studies conclude that the application of systems thinking is productive and worthwhile, showing significant shifts in participants’ goal structure, change strategies, decision-making and task performance. Additionally, greater alignment of participant mental models and better understanding of system structure have been seen, both of which are prerequisites for the development of robust strategies (see also Maani and Maharaj, 2004). However, there remains a gap with regard to empirical research about the efficacy of systems thinking.

3.2 Review of systems thinking literature to find an applicable approach for business model innovation The origins of systems thinking, from which the main concepts derive, are general systems theory (GST) as a metatheory (Bertalanffy, 1956) and cybernetic theory (Ashby, 1956; Wiener, 1954). Systems thinking received much attention in 1972 with the publication of The Limit to Growth while using systems dynamics to create scenarios for future global development (Meadows, 1972). Several theories have developed out of GST, such as Operations Research, Informatics and Organisations Theory. All these theories are similar in functional and structured abstraction, usage of models for constructions and mediation between theory and practice (Ropohl, 2012). System dynamics became more popular after the publishing of The Fifth Discipline


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(Senge, 1990), which focused on dynamic problem solving and improved learning in complex systems and organisations. Senge (1990) argues that to become a learning organisation requires five disciplines – the fifth is systems thinking. During the past two decades, many popular systems thinking texts have been published, making ST a necessary skill in selected higher management education programmes (Cabrera, 2006). Nonetheless, ST is still a niche topic, with high growth potential in science, business (Checkland, 2000) and social environments (Laszlo et al., 2009). Two major viewpoints on systems distinguish between different systems approaches. First, thinking about systems advocates thinking about real systems by focusing on real-world entities (e.g., health systems, accounting systems). Secondly, systems thinking as a conceptual construct calls for inquiry into real-world entities, which assumes that the social construction of the world is systemic (e.g., Cabrera, 2006; Flood, 2010). These approaches are also known as hard ST (seeing the world as a system) and soft ST (looking at the world systemically) (Checkland, 1981; Jackson, 1991), and they represent forms of applied systems thinking. Both views have relevance and significance, but for the purposes of the social sciences and research in management fields, soft systems thinking is more appropriate. This discussion demonstrates that ST is an influential mode of thought and provides many perspectives and means of application. The scientific or practical application can be implemented through several ST approaches. As described before, systems approaches have a rich historical tradition (Skyttner, 2005), and thus many different perspectives exist on how to group them. There is no shortage of approaches within the systems field, but we sought a perspective that could be applied to business models and BMI. The following overview is an excerpt of the reviewed literature (Table 1). Table 1

Synopsis of related systems thinking approaches

Category

Approach

Author (Year)

Focus on

Bertalanffy (1956)

Function, structure, hierarchy

Ropohl (1979)

Function, structure, hierarchy

Ashby (1956) and Wiener (1954)

Steering, communication, and control

Beer (1972)

Steering, dynamic, feedback, complexity

Systems dynamics (SD)

Forrester (1961, 1971)

Process, dynamics, feedback, environment

Soft systems methodology (SSM)

Checkland (1981, 2000)

Organisational process modelling, soft problems

FunctionGeneral systems theory oriented systems thinking Technological systems theory CyberneticCybernetic theory(first oriented systems order) thinking Management cybernetics (second order)

Critical systems heuristics Ulrich (1970) (CSH)

Practical philosophy, boundaries

System-oriented management science

Controlling, strategies, management

Integrated Systems theory in systems thinking innovation management

Ulrich (2001)

Pfeiffer (1971) and Function, structure, process, Pfeiffer et al. (1977) controlling

Source: Authors derived from literature review

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Many scholars have argued that systems thinking require a simultaneous understanding of function, structure and process of a system (Gharajedaghi, 2007; Laszlo et al., 2009). Only Pfeiffer’s approach integrates the dimensions of function, structure and process – along with the cybernetic approach of controlling, which is necessary to keep systems steered and regulated. Therefore, Pfeiffer’s approach is appropriate for both hard and soft systems thinking (Jackson, 1991). We have chosen Pfeiffer’s approach for deeper analysis because it demonstrates a rich interplay between situations, management communities and methodology. This interplay generates a convincing and real sense of robustness, which is required for every systems approach (Homer, 1996). A second reason for selecting this approach relates to the different ways Pfeiffer understands interrelationships. The approach deals with different perspectives (e.g., focusing on technology and innovation) while addressing a holistic view. Furthermore, this approach is well structured and based on a long tradition of ST within the German scientific community (i.e., Gutenberg, 1951; Pfeiffer, 1971; Ropohl, 1979) and is cited in many high-quality journal publications (i.e., Augsdorfer, 2005; Brunswicker and Hutschek, 2010; Jung, 2004). We complement Pfeiffer’s approach by asking the following questions: •

What is the system’s function?

•

What is the system’s structure?

•

What is the system’s process?

•

What are the system’s controlling principles?

These questions can help to describe and explain every system before, while, or after performing any change, whether applying those changes to the whole or to single parts. Following Pfeiffer’s systems thinking approach, we thus recognise every object or firm as a system with a concrete function or purpose. That function is reflected in an object’s structure, which consists of five factors (Pfeiffer, 1971): input, human resources, organisation, technologies and output. The system is subjected to a process and controlled through steering and regulation. Systems thinking require a holistic, interdisciplinary and integrated approach. A holistic systems approach captures these components of function, structure, process and controlling systematically. An interdisciplinary approach consists of considering different scientific disciplines or communities, such as economics and technology (or innovation management and technology management), and operating with numerous thinking tracks (i.e., dynamic, operational, quantitative, scientific) simultaneously (Maani and Maharaj, 2004) when studying a firm or an object. Integration means identifying interdependencies within a firm and its environment because no business phenomenon or element exists in an isolated system. While a business phenomenon has to be seen in a general view focused as a whole (Ulrich and Probst, 1991), the root-cause effects differ in space and time. During the decision-making process, all influencing factors and interdependencies need to be considered in an interdisciplinary manner to reveal uncovered connections and avoid time-consuming analysis.


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A systemic view on business model innovation

4.1 Business model definition After explaining systems thinking and choosing an approach, we analysed the business model literature from a systemic point of view, which entails starting with a practical (real) definition and then using a semiotic lens to discover the nominal definition (to understand the meaning of the term). Such a procedure is important because the term business model is a loaded phrase with no agreed upon meaning within the field. Finally, we give a brief view on current BMI types and processes outside existing literature. Zott et al. (2011) have shown that there is no common understanding of what defines a business model either in academia or in practice. This fact makes integrated research in the field almost impossible (George and Bock, 2011). Thus, studies should not simply ask the question “What is a business model?” but rather ask “What do business models do?” (Doganova and Eyquem-Renault, 2009) and further “How can a business model be innovated?” (Schneider and Spieth, 2013). Given the fact that business model has been defined as a system (Teece, 2010; Zott and Amit, 2010) and the term system is used several times in business model literature (Casadesus-Masanell and Ricart, 2010; Demil and Lecocq, 2010; Morris et al., 2005; Zott et al., 2011), we accept the definition that a business model is “the content, structure and governance of transactions designed so as to create value through the exploitation of business opportunities” (Amit and Zott, 2001, p.511). A company can have several business models (Hedman and Kalling, 2003) and several systems. This practical definition and understanding of business model is close to that of systems thinking.

4.2 A semiotic view on the terms model and innovation Before conducting further research of BMI literature, we used a semiotic view of the term BMI to briefly understand the nominal definition of the term. Semiotics, as part of speech analysis, is closely linked to systems thinking because both approaches aim to start with understanding, which means objects of the world are described through words (Seiffert, 1996). Semiotics can be seen as a prerequisite of every systems thinking approach because a clear understanding of the terms needs to be gained before one can analyse and understand these systems. We focus only on the terms model and innovation because business is broadly understood in literature. While business model remains a term with growing usage, little is said about the term model in this context. We looked into model theory and its implication for research (Baden-Fuller and Morgan, 2010). A model is always an abstract representation of reality to add greater understanding and to answer questions (Ropohl, 1979; Schwaninger, 2004). Furthermore, models simplify complex interrelations between objects, and through abstraction a model can reduce complexity (Ropohl, 2012; Stachowiak, 1973). Models have a long history in biology and economics, where they are used to help solve problems as well as to increase knowledge (Baden-Fuller and Morgan, 2010; Ropohl, 2012). In literature, models are classified as formal and mental models (Gharajedaghi, 2007; Schwaninger, 2004). A mental model, also called shared mental model, is built subjectively to provide simplification of its realities (Gharajedaghi, 2007). A formal model helps to structure the reality in a clear and logical way, has a higher degree of

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precision than mental models, and is mostly used in the natural sciences (Schwaninger, 2004). Both are intended to simplify complex interrelationships, making them more accessible and understandable (Ropohl, 2012; Stachowiak, 1973). From the perspective of time, models can be divided in static and dynamic models (Baetge, 1974; Skyttner, 2005). Static models eliminate the variable of time and present a snapshot of a specific point of time in a short- or long-term view. Dynamic models consider time interdependencies and therefore the effects of time, meaning one element has to focus on another timeframe. The more dynamic a model is, the closer it gets to reality (Baetge, 1974). Any model (mental or formal; static or dynamic) can function in one or more of the following capacities: as a description model, explanation model, design model, decision model, change model, or simulation model (Schwaninger, 2004). The clarification of the function is essential for modelling per se (Baetge, 1974). Our contributions from reviewing the model theory for the practice of business modelling and future research are the following: •

A business model can be assigned to a mental model (Petrovic et al., 2001) due to its abstract description of complex businesses to simplify analysis, understanding and development.

•

A business model is mainly static rather than dynamic (Demil and Lecocq, 2010) because the majority of elements are focused within the same timeframe. (In the future, business models have to become generally more dynamic.)

•

Business models can have different functions; they are currently used primarily for description and explanation (Amit and Zott, 2001; Magretta, 2002; McGrath, 2010; Zott et al., 2011) as well as for design and decision (Chesbrough and Rosenbloom, 2002; George and Bock, 2011; Teece, 2010), but in the future, their use as change or simulation models could increase.

•

Finally, without a business model, the complex business and environment cannot be structured clearly enough for management to make decisions toward future development (Baden-Fuller and Morgan, 2010; Magretta, 2002).

Two major challenges come along with modelling reality in business models: •

The individual interpretation of reality is strongly subjective, and

•

the current situation during the modelling process plays a major role in determining which aspects are considered.

The term innovation was first defined by Schumpeter (1939) and is today considered a key factor with regard to competitive advantages and technical progress for firms (e.g., Pfeiffer, 1971; Knyphausen-Aufsess, 1995) and nations (Abernathy and Clark, 1985). According to Pfeiffer, innovation is a convergence of potential-push and demand-pull (Pfeiffer, 1971). When technological potential meets demand, an innovation originates (potential-induced innovation). If there is a demand from the market and a specific technological solution (the potential) is invented for such a purpose, then it is called a demand-induced innovation (Pfeiffer, 1971). Innovation can be seen subjectively (new to a firm or market) or objectively (new to the world) (Pfeiffer, 1971).


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4.3 Processes, directions, and types of business model innovations BMI, also described as strategic innovation (Markides, 2006), is the process by which new value is created and captured through the change of one or more elements of a given business model (Amit and Zott, 2001; Bucherer, 2010; Demil and Lecocq, 2010; Teece, 2010). In literature, process views and directions are quite different. Some scholars characterise the BMI process as a process of experimentation and learning (McGrath, 2010; Sosna et al., 2010); as an evolutionary process (Hedman and Kalling, 2003); or as a continuous reaction to incremental and radical changes (Demil and Lecocq, 2010). A clear view on the direction that BMI comes from and goes to is more or less missing but this direction has to be clear in successful innovation of the business model (Achtenhagen et al., 2013; Giesen et al., 2007). The earlier description of innovation could possibly increase the clarity in the directions of BMI. Potential-induced and demand-induced innovations lead in opposite directions. In one case, an innovative business model is invented, and there is an attempt to identify market demand for the invention. Within this potential-driven perspective, it is unclear whether the business model will be useful as a market solution. In a second case, following a demand-driven perspective, the market requires new value and therefore a new business model. In the latter case, it is unclear which business model will respond best to the demands of the market (e.g., see Chesbrough and Rosenbloom, 2002). Expanding interest in business models and especially in BMI has led to an increasingly wide and diverse body of literature still rife with new issues and open questions. In recent years, a few emerging BMI processes and concepts have been developed. Most processes have been qualitative and explored and mostly derived from other innovation or general process models (e.g., Bucherer et al., 2012; Sosna et al., 2010). Nevertheless, after these first investigations, field understanding of these processes is still limited. There remains a gap, hindering effective transfer from concept to reality. One of the biggest questions yet to be answered is “How can firms emphasise the identification, development, and support of new ideas for BMI?” (Schneider and Spieth, 2013). Inventing business models requires an understanding of the particular situation of the existing business model, especially the structure elements, including internal and external interdependencies between the business model and environment (Baden-Fuller and Morgan, 2010; Berglund and Sandström, 2013; Demil and Lecocq, 2010; George and Bock, 2011) as well as among business model, environment, and strategy (Klang and Hacklin, 2013). Within the BMI, it is necessary to manage the trade-off between business model consistency and reality in time and space (Demil and Lecocq, 2010). Few business model concepts have been applied to real-world settings thus far, resulting in a lack of conceptual work and an increase in questions about how to better understand such phenomena. Parallel to the BMI process and direction, research currently lacks sufficient understanding about BMI types. Regarding these types, we identified several different approaches (i.e., Chesbrough, 2006; Giesen et al., 2007; Morris et al., 2013), which focus more on either typologies or taxonomies than they do on results (Baden-Fuller and Morgan, 2010). Hence, there is no common view about when a BMI is reached. Figure 2 shows one way to distinguish BMI as a result, in two different types of BMI (Pfeiffer, 1980; Zollenkop, 2006). The first type is principle BMI, which means the business model has changed radically within its structural elements (new potentials) and radically in

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targeted markets (new demands). The second type is gradual BMI with marginal to radical (fundamental) changes in either potential-area or demand-area (see Bourreau et al., 2012; Markides, 2006). However, a business model may be innovative only from a subjective perspective, meaning that every company must design its own business model according to specific circumstances. Appropriate business model management (Demil and Lecocq, 2010) can help maintain a balance between principle and gradual innovation. Figure 2

Business model innovation types from result perspective

These differentiations of BMI as process and type are necessary and can been seen as one major step concerning the commonly accepted definition that is currently missing from literature (Schneider and Spieth, 2013). Nevertheless, it seems to be clear and accepted knowledge that BMI as a new form of innovation (i.e., Casadesus-Masanell and Zhu, 2013; Markides, 2008) plays a major role in sustainable company success (i.e., Chesbrough, 2006; Sosna et al., 2010; Zott et al., 2011) and is a vehicle for transformation and renewal (Demil and Lecocq, 2010; Johnson et al., 2008).

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Systems thinking in business model innovation

5.1 Arguments for the application of systems thinking to business model innovation “The best BMI opportunities require systems thinking and systems solutions.” (Kaplan, 2012, p.82)

First, some problems are local and thus easy to solve in space and time (e.g., a broken chair; Richmond, 1987). Business models are neither local nor static issues (Bourreau et al., 2012; Bucherer et al., 2012; Chesbrough, 2010), so the evolution and innovation of business models requires a dynamic approach (Demil and Lecocq, 2010; Morris et al., 2005). BMI is extremely complex because it can lead to major holistic change within


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established businesses (Bucherer et al., 2012; Casadesus-Masanell and Ricart, 2010). Working with business models includes problem solving at a complex level. The impact of such BMI is by no means local because change effects or intervention are physically separated by time delays. Complexity demands systems thinking (Richmond, 1987). Given that complexity within business models is increasing with little critical discussion thus far, it seems an appropriate time to apply ST as a new approach while simultaneously facilitating management during this challenging task (Amit and Zott, 2001; Chesbrough, 2006; Johnson et al., 2008). Secondly, as described earlier, the necessity of an integrated ST approach demonstrates the importance of interdependencies in ST. Systems, and therefore their interdependencies, are constantly changing due to external environmental and permanent internal changes (i.e., driven by learning processes; Baetge, 1974). These same changes occur with respect to business models because the elements and interdependencies are influenced by a given organisation and external environment (i.e., Baden-Fuller and Morgan, 2010; George and Bock, 2011), as well as by the related ecosystem (Borgh et al., 2012). Within business models and in connection to environment, many interdependencies exist (Demil and Lecocq, 2010) that must be considered holistically when one works with or changes businesses (Berglund and Sandström, 2013). Business model literature currently lacks knowledge and concepts surrounding this issue. However, interdependencies demand systems thinking (Richmond, 1987) and therefore can be helpful for BMI. Third, systems are models of entireness, and they do not exist in reality. Their production is the result of thinking (Stachowiak, 1973; Ropohl, 2012). As explained earlier, a model describes or explains a social phenomenon or is employed as a decisionmaking tool (Flood, 2010) and supports management on a strategic level (Forrester, 1994). Models are required for systems thinking (Richmond, 1987), especially in open and social systems (Bertalanffy, 1956) such as firms and organisations. Model development from the systems thinking perspective is a iterative process, involving a certain amount of trial and error as well as significant time and effort (Homer, 1996), and is therefore similar to BMI processes (Baden-Fuller and Morgan, 2010). Furthermore, modelling business under dynamic conditions is similar to modelling systems for simulation or experimentation (Bossel, 2004). Thus, business models are a modern form of systems modelling.

5.2 Application of systems thinking to business model innovation Before we applied ST to BMI, we included the four systems components from Pfeiffer’s approach in a framework to analyse the current business model holistically and to provide a clear agenda for innovating the business model. As we have shown before, this systemoriented framework can be used in conjunction with several remaining gaps and questions in the area of BMI (e.g., Schneider and Spieth, 2013). We will now apply a systems thinking perspective to BMI through the presented framework. When applying ST to BMI, we ask questions regarding or explain activities concerning the function, structure, process and controlling of a business model. To provide a clear explanation and to better aid understanding, this paper uses a simple illustrative case example to demonstrate the application (Hartmann, 1999; Pfeiffer, 1997).

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The chosen firm belongs to the metal industry and has one major business concept – to develop, produce, and sell conventional-looking systems and products, most of which are keys. Mechanical locking products are omnipresent in several application systems (room doors, car doors, lock boxes, etc.). One locking system generally has many keys, one or more locks, and a locking mechanism. Mechanical locking systems have been used for centuries and should protect property against external access. From a systemic point of view, the main business structure of the firm can be described in a simplified way through five factors (Pfeiffer, 1971): •

resources/technologies: mainly turning machines (CNC) and several milling machines for the manufacture of metal keys; simple ERP programme to support resource planning

•

people: knowledge of metal processing, CNC machines and using ERP software; partial knowledge about material composition

•

organisation: based on classic manufacturing layout

•

input: metal suppliers and other raw material providers

•

output: focused on the market for conventional metal keys.

Within the relevant market, many changes occur with regard to new technologies (microelectronic) and new competitors (emerging markets), resulting in mechanical keys being replaced with new alternatives. It becomes obvious that future (key) technologies threaten older ones. The question arises: Will the everyday mechanical key in conventional locking systems still be valid in coming years? Or are there existing technological alternatives with the same problem-solving potential? What does that mean for the current business model and the offered value? How can the firm identify a new, innovated business model? To answer this question, we use the system-oriented framework to provide structure and guidance to frame and to focus thought (Figure 3). Figure 3

System-oriented framework to guide business model innovation


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5.2.1 Function The functional view of a business model can lead to innovative insights by looking at the input and outcomes or results produced (Gharajedaghi, 2007). Defining the firm’s product or value proposition from a phenomenological, descriptive view – which sees the key simply as a door opener – may hinder innovation of the current business model. The major question of a business model takes into account the real function or value proposition that arises (Gassmann and Zeschky, 2008) – in our case, “what is the function of a key?” This question reflects the value proposition of a company’s business model and should be the starting point for BMI processes (e.g., Doganova and Eyquem-Renault, 2009; Johnson et al., 2008; Magretta, 2002). From the ST perspective, and separated from context, a key functions as an information memory (i.e., the milled structure of a key stores specific information, or access to something). Through this functional abstract view, seeing a key as information memory opens perspectives for innovation. This view shares similarities with the concept of a crossindustry searching strategy (Brunswicker and Hutschek, 2010). For example, a chip card or a fingerprint can also be described as information memory. Thus, the firm ought to innovate in one of these directions (chip card production or fingerprint recognition systems). A new business model could be created to develop, produce, and sell chip cards, which are also technical objects that store information. In this way a completely new field of business application could be reached. In short, from a functional abstract view, determining the innovation direction of a business model is crucial and reduces dependency on simply imitating business models (Enkel and Mezger, 2013). From our perspective, principle innovation can mainly be derived from rethinking function via functional abstract view, followed by various artefact interactions (Eppler et al., 2011). Therefore, the functional abstract view presents a technique to enlarge the room of innovation and to identify new business model opportunities.

5.2.2 Structure If the firm concentrates on the information memory market, the entire business structure, including its interdependencies, must change – and the business model along with it. The overall operation management and the way in which value is created within the business model (Demil and Lecocq, 2010; Morris et al., 2013; Teece, 2010) would also need to change. Furthermore, employee knowledge would have to extend to working with plastic material (chip cards) rather metal keys, or else concentrate on the handling of biometric data. The machines, as well as the organisation, would need to move toward plastic or biometric technology. In the end, new suppliers would be needed to obtain the appropriate resources at the right time. Every structural element of the business model would change after the new function was defined. When any of these structural elements changed, all the elements and their functions would need to be revised, due to their interrelation.

5.2.3 Process Following the static view of the function and structure of a firm’s business model, the next two steps – process and controlling – represent a dynamic view. Business model research focuses to some extent on dynamic aspects (Bourreau et al., 2012; Bucherer et al., 2012; Chesbrough, 2010), which are required by Demil and Lecocq (2010) and

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Morris et al. (2005). Process describes the realisation of the structure in time and space. From the space perspective, the key manufacturer must decide how the facilities are used and the material flow is designed with regard to site layout and existing resource configuration (Chesbrough, 2010). From the temporal perspective, a decision must be reached regarding the iteration of process activities and time-to-market aspects (Baden-Fuller and Morgan, 2010; Markides and Sosa, 2013). Additional questions often arise, such as the following: When should they start working with the new technology and therefore with the new business model? When should they re-skill employees to establish new knowledge? To handle these questions and to establish an order for decisions, a form of business model roadmapping could be implemented (Reuver et al., 2013). Time and space perspectives can therefore help to operationalise the concept (function and structure) into reality.

5.2.4 Controlling According to ST, controlling can be divided into steering and regulation (Ulrich and Probst, 1991). Controlling, necessary to keep the system or business model steered and regulated, is known in business model literature as the guiding principles or rules (Morris et al., 2005), or governance (Zott and Amit, 2010). In our case, steering means that the key manufacturer sets new objectives to steer on different levels based on the functional, structural, and process changes. The need for regulation results from internal or external disturbances, such as new fingerprint technology; these disturbances can also be seen as disruptive innovations (Christensen, 1997; Markides, 2006). The biggest challenge is to identify disruptive innovations or relevant disturbances quickly – ideally before they occur. If disruptions have already occurred, regulations must allow for them while ensuring adjustment as quickly as possible. In summary, to apply ST to BMI, one must consider and analyse the four dimensions of function, structure, process, and controlling of the firm’s current business model. To innovate the business model on a principle level, the agenda must begin with rethinking the function of a business model, further identifying changes in the other three dimensions. With this in mind, it is possible to use BMI in a holistic, interdisciplinary and integrated manner – that is, in fact, systems thinking.

6

Contribution

In this paper, we propose a system-oriented framework to cross-fertilise the field of systems thinking and BMI. This paper is one of the first to do so, exploring new insights and perspectives. We discovered that business model research could improve discussion and understanding if aspects of model theory were considered more often in the research and practice of business modelling. New insights are derived from a system-oriented view of BMI process, direction, and type. The directions can be categorised as either potentialdriven or demand-driven, which provides a helpful way to explore existing questions in business model literature. The two major types of BMI s explained in Section 4.3 can encourage further discussion about the degree of BMI. With our investigation, we add a new systemic view of business models to the existing views of Doganova and EyquemRenault (2009).


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We are hopeful that this perspective will become a part of theorising the fundamental debate within business model research. As we argued clearly, application of systems thinking to BMI makes sense from a theoretical perspective. From our perspective, using systems thinking in BMI is a fruitful combination in practice because working with business models and creating BMI are some of the most complex and challenging management tasks and require an approach that takes into account complexity, interdependencies and modelling assistance. The chosen approach, a proposed framework, enables better management of the complex present and volatile future of a firm’s business model, and it provides a clear agenda with a new perspective on innovating business models. The detailed benefits of our study are manifold for both academia and practice, clearly demonstrating the purpose of using ST in BMI: •

ST offers a common formal starting point for different views on complex business models

•

ST includes an entire business model with all components and elements through a holistic view (function, structure, process, controlling)

•

ST enables an interdisciplinary view from different scientific communities (e.g., innovation management and technology) on BMI

•

ST facilitates an integrated view for the identification of interdependencies of complex root-cause effects within a business model and in exchange with environments

•

ST reveals previously uncovered connections and avoids isolated business model analysis

•

ST facilitates the search for new business model ideas through the functional abstract view and assessment of those business ideas and by answering the question “How can firms emphasise the identification, development, and support of new ideas for BMI”?

Several future directions for academia can be identified. First, business model research can benefit from systems thinking. Future research on this topic can create a clearer link between these two fields and build a theoretical foundation for business model research or collect empirical data for more evidence. Secondly, research on BMI is currently focused primarily on processes and needs to expand to overall concepts including exploration, evaluation, and action-taking in order to improve work with business models. Thirdly, ST skills can be developed further in terms of management practice and transferred to work with business models. Here empirical research can be conducted to demonstrate the effectiveness of systems thinking application in management. Fourthly, computer-based simulation games can help teach systems thinking. Business model simulations based on ST would be an excellent instrument for management working with business models to employ to simulate what the various changes or innovations might mean for business models in general.

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