The relationship between cost orientation, innovation orientation and business model innovation : an organizational ambidexterity perspective

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The Relationship between Cost Orientation, Innovation

Orientation and Business Model Innovation: An

Organizational Ambidexterity Perspective

MSc. Business Administration: Strategy Master’s thesis – final version

B.L. Akkermans 11152133

Thesis Supervisor: Dr. S. von Delft

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Statement of originality

This document is written by Bart Akkermans who declares to take full responsibility for the contents of this document:

“I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.”

B.L. Akkermans 11152133

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Abstract

Business model innovation (BMI) has become influential in management research. To advance research regarding BMI, scholars have argued for the necessity to study the antecedents of BMI. Following these calls, this study explores the role of different strategic orientations, namely cost and innovation orientation, for BMI. The strategic orientation of the firm reflects the fundamentals of a firm’s BM, sine a BMI changes the relationship and the interactions within a firm, between firms and the way the firm operates in the market. Furthermore, this study considers the moderating variables technological turbulence, competitive intensity and market uncertainty that are expected to strengthen the strategic orientation – BMI relationships. Using a sample of 58 managers, structural equation modelling shows that innovation and cost orientation are antecedents of BMI. The moderating paths are non-significant, yet, the direct link between technological turbulence and BMI is significant which implies that environmental factors influence firms and affect BMI. The confirmation of both innovation and cost orientation as antecedent of BMI explicitly confirms a relationship that, so far, has only implicitly been suggested in separate research streams. Although previous studies discuss ambidexterity as a trade-off between pairs of conflicting activities, the results imply that regardless whether firm activities are from exploitative (cost oriented) or exploratory (innovation oriented) nature, both contribute to BMI.

Key words: business model innovation, strategic orientation, innovation orientation, cost orientation, ambidexterity, technological turbulence, competitive intensity and market uncertainty.

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Acknowledgements

In special I would like to thank my supervisor, Dr. Stephan von Delft, for his guidance throughout the thesis process. His suggestions often resulted in eye-opening and valuable insights. I would further like to thank my parents for their support during my weekend-visits. Last but not least I would like to thank my girlfriend, for her patience throughout the last months.

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1. Introduction

The concepts of business models (BMs) and, more recently, business model innovation (BMI) have become influential in management research in recent years (Spieth, Schneckenberg, & Ricart, 2014; Zott, Amit, & Massa, 2011). BMs have been identified as an important determinant of sustained competitive advantages (Casadesus-Masanell & Ricart, 2011; Johnson et al., 2008), can have a positive influence of firm performance (Zott & Amit, 2007) and allow firms to commercialize new ideas and technologies (Chesbrough, 2010). According to Osterwalder and Pigneur (2010, p.14) a BM can be defined as: “the rationale of how an organization creates, delivers and captures value”. BMI refers to changing the way the firm creates, delivers and captures value.

A recent literature review by Foss and Saebi (2017) shows that BMI research has largely developed among four partly overlapping streams of research: (1) conceptualizing BMI, (2) BMI as an organizational change process, (3) BMI as an outcome and (4) consequences of BMI. The first and second streams of research primarily study the antecedents of BMI. Several scholars have argued for the necessity of studying antecedents of BMI to advance BMI literature: “cumulative theorizing and successful empiricism requires clear identification of the causal structures in a theory” (Foss & Saebi, 2017, p.211). In other words, research on BMI should clearly identify the antecedents and consequences of the focal phenomenon (Foss & Saebi, 2017).

BMIs can originate from many potential sources within the firm (Teece, 2010). According to Teece (2010) business model innovators often possess, or develop, an understanding of the ‘deep truth’ about the fundamentals of their consumer needs, competitors and technological innovations. In almost every practical case, a BMI is the result after considerable trial-and-error (Chesbrough, 2010; Sosna, Trevinyo-Rodríguez, & Velamuri, 2010; Teece, 2010).

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7 Understanding the untapped potential of the ‘deep truth’ of business fundamentals thus advances research regarding the antecedents of BMI. To understand the ‘deep truth’, strategic orientations are particularly relevant since they direct firms’ interactions with customers, competitors, and other actors in the marketplace and guide a firm’s marketing and strategy-making activities and investment decisions into resources (Noble, Sinha, & Kumar, 2002). Essentially, strategic orientations reflect the fundamentals of the ‘deep truth’ as noted by Teece (2010). This implies that strategic orientations can be studied as antecedents of BMI; they are the firm’s set of values that guide the firm’s attempt to achieve business goals. However, to identify strategic orientations most relevant when studying antecedents of BMI, a step beyond BMI literature is required.

BMI requires firms to explore new value propositions, revenue models and ways to organize and transact in product-factor markets. This iterative process is discovery-driven and requires trial-and-error learning (Christensen, Bartman & Van Bever, 2010; Sosna et al., 2010). However, exploration-oriented activities alone are insufficient to achieve BMI (Christensen et al., 2010). As Christensen et al. (2010 p. 31) note, “At some point (…). The business unit is now no longer in the business of identifying new unmet needs but rather in the business of building processes – locking down the current model”. Thus, firms must also exploit their current activities to generate additional profitability, reduce costs and optimize processes (Christensen et al., 2010). During BMI, firms must accordingly balance exploration and exploitation – a capability known as ambidexterity. While prior literature has dealt with the question of how to manage strategic dualities as well as how firms can respond to tensions and trade-offs between pairs of conflicting activities (He & Wong, 2004; Kortmann, 2015), an integration of work on ambidexterity with work on BMI is missing. To fill this gap, this study considers innovation and cost orientation as higher-level proxies for explorative and exploitative activities during BMI. Investigating the role of strategic dualities to achieve BMI

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8 in a dynamic business environment is important because firm activities rely on a trade-off between balancing different activities as a result of competition for scarce resources (March, 1991), and (2) understanding drivers of BMI allow scholars and business practioners to understand BMs and allow the development of possible competitive advantages.

To fully understand the relation between innovation and cost orientation as antecedents of BMI, this study further considers the firm’s environmental context (Zhou, Yim, & Tse, 2005). According to Miller (1988) are firm’s dependent on their environmental context. It is therefore expected that the presence of any environmental factor strengthens the proposed strategic orientation – BMI relationships. Following Zhou, Yim and Tse (2005), this study considers market uncertainty, competitive intensity and technological turbulence as moderating variables in the strategic orientation – BMI relationship. In sum, this study asks:

“What is the effect of cost orientation and innovation orientation on BMI, and under what conditions will there be differences in the relationship between these orientations and BMI?”

Results of this study show that innovation and cost orientation are indeed antecedents of BMI. The confirmation of both strategic orientations as antecedent of BMI integrates literature on BMI, strategic orientations and ambidexterity arguing for the simultaneous pursuit of both exploratory and exploitative activities namely, innovation- and cost-oriented strategies. The results therefore explicitly confirm a relationship that, so far, has only implicitly been suggested in separate research streams. While this study could not show a significant effect of competitive intensity and market uncertainty on BMI, a direct, positive effect of technological turbulence on BMI is identified. This suggests that environments characterized by rapid technological developments in a specific industry or market, foster BMI.

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9 This paper is organized in several sections. The following section covers an overview of existing theory based on which the hypotheses are formulated. After the literature review the research methods are described wherein the type of research, sample, data collection and data analysis are discussed. The fourth chapter covers the analysis and the results of the study. The paper concludes with a discussion, limitations and suggestions for future research.

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2. Literature Review and Hypotheses Development

2.1 literature Review

2.1.1 Business Models and Business Model Innovation

There are various definitions of business models (Foss & Saebi, 2017). A business model depicts “the content, structure, and governance of transactions designed so as to create value through the exploitation of business opportunities” (Zott et al., 2011 p.1024). According to Teece (2010, p.173), a business model is concerned with “delivering, capturing and creating value for the firm and its customers”. This study adopts the definition of a BM from Osterwalder and Pigneur (2010, p.14), who argue that a BM can be defined as “the rationale of how an organization creates, delivers and captures value”. This definition is broadly consistent with other definitions (see Table 1).

Table 1: Selected Definitions of Business Models

Author(s) Definitions

Zott et al. (2011 p.1024) “The content, structure, and governance of transactions designed so as to create value through the exploitation of business opportunities.”

Teece (2010 p.73) “A business model defines how the enterprise creates and delivers value to customers, and then converts payments received to profits.” Osterwalder and Pigneur (2010 p.14) “The rationale of how and organization

creates, delivers and captures value.”

Afuah and Tucci (2001 p.3). “The method by which a firm builds and uses its resources.”

Timmers (1998 p.2) “An architecture of the product, service and information flows, including a description of the various business actors and their roles; a description of the potential benefits for the various business actors; a description of the sources of revenues”

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11 Magretta (2002 p.4) “Stories that explain how enterprises work. A good business model answers Peter Drucker’s age-old questions: Who is the customer? And what does the customer value? It also answers the fundamental questions every manager must ask: How do we make money in this business? What is the underlying economic logic that explains how we can deliver value to customers at an appropriate cost?”

Morris et al. (2005 p.727) “Concise representation of how an interrelated set of decision variables in the areas of venture strategy, architecture, and economics are addressed to create sustainable competitive advantage in defined markets” Chesbrough and Rosenbloom (2002 p.529) “The heuristic logic that connects technical

potential with the realization of economic value”

Zott and Amit, (2010 p.216) “A system of interdependent activities that transcends the focal firm and spans its boundaries”

Teece (2010 p.179) “A business model articulates the logic, the data and other evidence that support a value proposition for the customer, and a viable structure of revenues and costs for the enterprise delivering that value”

BMI is essentially about developing new ways to create, deliver and capture value and moves beyond other defined, complementary, categories, such as product, service and process innovation (Lutz Preuss, 2011; Wells, 2008). BMI is important for the success of an organization and can lead to the development of a sustained, competitive advantage (Casadesus-Masanell & Ricart, 2011).

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12 2.1.2 Antecedents of Business Model Innovation

BMI is perceived to be a necessary response to “strategic discontinuities and disruptions, convergence and intense global competition” (Doz & Kosonen, 2010 p.370). However, relatively few articles discuss the antecedents of BMI (Foss & Saebi, 2017). While a few prior empirical studies have explored the role of internal factors such as dynamic capabilities as well as external factors such as a change in competition or customer demand as antecedents of BMI (Johnson et al., 2008; Teece, Pisano, & Shuen, 1997), our knowledge about antecedents of BMI is still sparse (Foss & Saebi, 2017).

The innovation of BMs can originate from many potential sources within the firm (Teece, 2010). Successful BMI is often explained as a consequence of trial-and-error or experimentation processes (Chesbrough, 2010; Sosna et al., 2010). Sosna et al. (2010) argue that BMs should be innovated through experimentation, evaluation and adaptation in a trial-and-error approach involving all departments of a firm. In a Xerox case study, Chesbrough (2010) shows that BMI is not a manner of superior foresight ex ante, but it requires significant trial-and-error, and quite a bit of adaption ex post. Since BMI changes the relationship and the interactions within and across firm boundaries, BMI affects how the focal firm operates in the market (Foss & Saebi, 2017).

This interaction is guided by a firm’s strategic orientation(s), defined as: “the guiding principles that influence a firm’s marketing and strategy-making activities” (Noble et al., 2002 p.25). The strategic orientation of a firm reflects fundamental beliefs of how to operate in a market and determine strategy making activities as well as investment decisions. As such, the strategic orientation(s) of a firm influence fundamental choices about how to create and capture value and can thus be considered as an important, yet understudied, antecedent to BMI.

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13 To identify strategic orientations most relevant to study as antecedent of BMI, a step beyond BMI literature is required. Literature distinguishes several strategic orientations (Gatignon & Xuereb, 1997; Noble et al., 2002; Yang, Wang, Zhu, & Wu, 2012). To explain the rationale of studying innovation and cost orientation as antecedents of BMI, first, both orientations are defined and explained.

2.1.3 Innovation Orientation

Innovation orientation is often used as a driver of firm performance. Innovation orientation refers to “the capacity of a firm to engage in innovation: that is, “the introduction of new processes, products or ideas in the organization” (Hult, Hurley & Knight, 2004 p.430).

However, innovation orientation can also be seen as antecedent of BMI in response to a changing, disrupted or increased competitive environment (Baker & Sinkula, 2002; Foss & Saebi, 2017). So far, innovation has mostly been examined as moderator of different strategic- and market orientations and business performance (Hult, Hurley, & Knight, 2004). Only a handful of studies acknowledged innovation orientation as a construct in its own right (Siguaw, Simpson, & Enz, 2006). Siguaw, Simpson and Enz (2006) demarcated the domain of innovation orientation by creating an innovation orientation framework that allows the construct to be studied on its own. Hence, long-term survival through innovation appears based not on specific, discrete innovations or on a single market or learning orientation but rather on an overarching, organization-wide knowledge structure termed: innovation orientation (Siguaw et al., 2006). In this view, innovation orientation allows firms to recognize shifts in market dynamism and to vary processes as a dynamic capability (Siguaw et al., 2006).

This paper defines innovation orientation as Siguaw et al. (2006, p.560): “A multidimensional knowledge structure composed of a learning philosophy, strategic direction, and transfunctional beliefs that, in turn, guide and direct all organizational strategies and

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14 actions, including those embedded in the formal and informal systems, behaviours, competencies, and processes of the firm to promote innovative thinking and facilitate successful development, evolution, and execution of innovations”. The innovation orientation construct is dynamic in that a firm’s innovation orientation is constantly evolving as the key elements of a (1) learning philosophy, (2) strategic direction and (3) transfunctional acclimation shift. Where the learning philosophy focuses on the organizational competencies. The strategic outcomes emphasize the innovation outcome and the transfunctional acclimation shift relates to firm performance. Thus, a real source of competitive advantage is: “an innovation orientation, specifically its knowledge development and strategic intent that directs functional competencies” (Siguaw, Simpson & Enz, 2006 p.561). Innovation orientation can be seen as an overarching principle that directs firms. It allows firms to learn, guide strategic decisions and the acclimation function accustoms firms to a new climate or environment in dynamic markets. Innovation orientation is related to exploratory firm activities (Kortmann, 2015). It allows firms to continuously explore new opportunities to introduce new processes, products or ideas in the organization. Innovation-oriented firms emphasize the innovation outcome and have the opportunity to actively change the way the firm creates, delivers and captures value (Osterwalder & Pigneur, 2010).

2.1.4 Cost Orientation

Production, or cost-oriented firms have their basic input-output thinking in optimization (Fritz, 1996). Corporate goals are enhancing productivity, utilizing capacity, cutting costs and increasing market share (Fritz, 1996). In relation to strategic management the firm focuses on cost leadership and standardization (Dess & Davis, 1984). Cost orientation refers to the pursuit of efficiency throughout all parts of the value chain (Dess & Davis, 1984; Grawe, Chen, & Daugherty, 2009; Olson, Slater, & Hult, 2005). The firm places a high level of importance on in-depth knowledge regarding the costs of providing products and services to

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15 the market (Grawe et al., 2009). Employees within cost-oriented firms seek opportunities to eliminate waste associated within all areas of the firm (Grawe et al., 2009). According to Grawe et al. (2009 p.285) cost-oriented firms are focused on: “reducing non-value-added services, identifying cost-saving sourcing options, and developing lower cost alternative product and service delivery methods”.

Miles, Snow, Meyer and Coleman (1978) argue that firm strategies are the result of the way the firm resolves entrepreneurial, engineering and administrative problems. A ‘defender’ strategy tries to protect a market by pursuing operational efficiency while serving customers. The firm focuses on efficiency, control and low overhead costs, which is similar to firms that have a cost orientation. A study by Laforet (2008) shows that cost-oriented (defender) firms engage less in innovation and operate in relative stable markets that require less radical internal change from firms. The firm is not actively seeking for ‘new’ ways to capture and deliver value (Osterwalder & Pigneur, 2010). Furthermore, exploitative firm activities, related to cost orientation (Kortmann, 2015), show firm behaviour in relation to current firm activities. There is no emphasis on the development of new firm activities (Gibson & Birkinshaw, 2004).

Concluding, innovation and cost orientation are both at the end of a continuum and emphasize different firm activities. However, in practice, the distinction between different firm activities is less straightforward. Firms often engage in either innovation- or cost-oriented activities (He & Wong, 2004). To explain the necessity of engagement in both innovation- and cost-oriented activities a step beyond BMI literature is required.

2.1.5 Exploratory and Exploitative Firm Behaviour

In practice, firm activities rely on a trade-off between balancing different activities as a result of competition for scarce resources (March, 1991). This trade-off is guided by ambidexterity-oriented decisions: “the capability of top management teams to manage contradictory strategic

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16 directions, namely adaptability and alignment” (Kortmann, 2015 p.666). They allow businesses to make choices about how much to invest in different types of activities.

Adaptability-oriented decisions determine the extent and effectiveness to which a firm adapts to changes in the environment, while alignment-oriented decisions specify how efficiently internal activities can be aligned to support the overall objective of the firm (Gibson & Birkinshaw, 2004). Kortmann (2015) shows that adaptability-oriented decisions relate to an innovation orientation as a result of the experimentation for new solutions, openness to new ideas and learning processes among employees (Hurley & Hult, 1998; Siguaw et al., 2006). Simultaneously, alignment-oriented decisions relate to a cost orientation as a result of the facilitation of the efficient utilization of resources supporting the achievement of efficiency-related objectives (Gibson & Birkinshaw, 2004; Tushman & O’Reilly, 1996).

During BMI, firms must accordingly balance exploration and exploitation (Kortmann, 2015). Exploitative activities cover all activities of a firm in relation to executing its current business (exploitation) and exploratory firm behaviour is characterized by search, discovery and experimentation (exploration) (He & Wong, 2004).

Various scholars argue for simultaneous investment in exploration and exploitation because: (1) exploitation and exploration are self-reinforcing (Levinthal & March, 1993), (2) jointly pursuing exploration and exploitation yields synergies (He & Wong, 2004), (3) and it leads to long-term adaption to new developments (exploration) and short-term alignment with existing markets (exploitation) (Gibson & Birkinshaw, 2004). It is therefore necessary for a firm to implement strategic orientations that foster exploratory innovation behaviours and exploitative organization behaviours. Since research regarding strategic orientations as antecedents of BMI, is largely underdeveloped (Foss & Saebi, 2017), it makes sense to, as a minimal starting point, study strategic orientations that convey both exploratory and

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17 exploitative firm activities to establish the possible relationship between strategic orientations as antecedents of BMI.

As previously described, cost orientation is related to operational efficiency. It relates to a stable set of products with incremental innovations. This view is supported in accordance with Olson (2005), who highlights that cost-oriented firms strive for operational efficiency in both primary and secondary activities such as marketing and research and development. Instead of developing new products or innovations, purely cost-oriented firms rather exploit their activities and develop incremental exploitative innovations (Kahn, Barczak, & Moss, 2006). In contrast, innovation orientation is associated with the openness to new ideas and their proactive pursuit (Hurley & Hult, 1998). Embracing an innovation-oriented strategy postulates a firm’s capacity to be innovative. With a strong influence on exploratory innovation behaviours, an innovation orientation provides firms with greater flexibilities and capabilities to develop both discontinuous and incremental innovations (Damanpour & Gopalakrishnan, 1999; Tushman & O’Reilly, 1996). It is therefore necessary to implement strategic orientations that foster exploratory firm behaviours, such as innovation orientation (Siguaw et al., 2006; Talke, Salomo, & Kock, 2011; Tellis, Prabhu, & Chandy, 2009), and exploitative organization behaviours, such as cost orientation (Chen, Damanpour, & Reilly, 2010; Olson et al., 2005).

Since research on the relation between strategic orientations and BMI is scarce, it is necessary to start off with at least strategic orientations that cover the ‘core’ activities firm’s execute. Thus, to advance research regarding the antecedent of BMI, innovation and cost orientation are the strategic orientations to examine. In the next chapter innovation and cost orientation are linked to BMI.

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18 2.2 Hypotheses Development

2.1.1 Innovation, Cost Orientation and Business Model Innovation

Although it is clear that innovation and cost orientation are related to the activities firms’ execute, few prior empirical studies have explored the antecedents of BMI (Johnson et al., 2008; Teece, Pisano, & Shuen, 1997). Our knowledge about the antecedents of BMI is therefore sparse (Foss & Saebi, 2017). To enhance our understanding of BMs in general and BMIs, it is therefore important to understand how two, foundational, firm orientations- innovation and cost orientation- influence and affect BMI.

Innovation-oriented firms engage in exploratory activities, leading to radical and incremental innovations (He & Wong, 2004). Innovation-oriented firm’s continuously search for new opportunities to create, deliver and capture value. Firm’s that actively search for new opportunities therefore have a higher change of discovering innovations that lead to new ways to deliver and create value, which lead to the development of BMIs. Innovation orientation can therefore be seen as antecedent of BMI as a response to a changing, disrupted or increased competitive environment (Baker & Sinkula, 2002; Foss & Saebi, 2017).

Since innovation-oriented firms actively seek for new ways to create, deliver and capture value the likelihood of discovering new innovations leading to BMIs is high. It is therefore expected that innovation orientation and BMI are positively related. Therefore, it is hypothesized:

H1: Innovation Orientation is positively related to Business Model Innovation.

Cost-oriented firms also emphasize new ways to create, deliver and capture value. There is however, based on the literature, an emphasis on being more efficient and refinement of current firm activities. Cost-oriented firms have their basic input-output thinking in

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19 optimization (Fritz, 1996). According to Grawe et al. (2009, p.285), cost-oriented firms focus on “reducing non-value-adding services, identifying cost-saving sourcing options, and developing lower cost alternative product and service delivery methods”. Essentially, cost-oriented firms perform exploitation-cost-oriented activities (Kortmann, 2015). This continuous search for optimization and search following from exploitation-oriented activities is expected to result into BMIs that aim to make the firm more efficient and productive.

Where innovation-oriented firms emphasize BMIs to find new ways to create, deliver and capture value, cost-oriented firms engage in BMI in order to continuously improve their efficiency and optimize cost-savings. It is thus hypothesized:

H2: Cost Orientation is positively related to Business Model Innovation.

To better understand the relationship between the strategic orientations studied here and BMI, this study further considers technological turbulence, competitive intensity and market uncertainty as moderators of the strategic orientation – BMI relationship.

2.2.1 Market Uncertainty, Technological Turbulence and Competitive Intensity

According to Miller (1988) firms are to a certain degree dependent on their environment. Therefore, regardless the strategic orientation – BMI relationship it is likely that the proposed relationships are moderated by the firms’ environment.

Innovation-oriented firms often operate in dynamic and uncertain environments, while a cost orientation is associated with stable and predictable environments (Miller, 1988). To react to a changing environment, strategic discontinuities, disruptions and increasing competition, adaptation is required to (re-)balance exploratory and exploitative activities (Gibson & Birkinshaw, 2004), and in turn leading to the development of BMIs. Where these BMIs are often the result of the opportunity to address new customers, fend off low-end

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20 disruptors, respond to a shifting base of competition or adaptation to the firm’s environment (Johnson, Christensen & Kagermann, 2008). It is therefore expected that every environmental factor, will have an effect on the hypothesised relationships. Hence, the presence of environmental factors will therefore strengthen or weaken the strategic orientation – BMI relationships (Doz & Kosonen, 2010; Osterwalder & Pigneur, 2010).

To understand the different effects of innovation and cost orientation on BMI, the environmental context of the firm must be considered (He & Wong, 2004; Zhou et al., 2005). In a study by Zhou et al. (2005) the authors distinguish three different environmental forces: market uncertainty, technological turbulence and competitive intensity.

The prevailing theory, where support is found for Zhou et al.’s (2005) environmental forces, is often referred to as contingency theory: adapting the organization to the environment (Morgan, 2006). The theory assumes that there is no one best way of organizing a firm; it all depends on the firm’s environment. The more turbulent the environment, the more adhocracy or organic the organization should be and vice versa. The following section covers the discussion of every environmental factor and the expected strengthening or weakening effect on the proposed strategic orientation – BMI relationship.

Market uncertainty is defined as “the rate of change in the composition of customers

and their preferences” (Kohli & Jaworski, 1990 p.57). Organizations that operate in uncertain markets are required to modify their products and services more radical to satisfy customer preferences (Jaworski & Kohli, 1993). While stable markets require less product or service modification (Jaworski & Kohli, 1993). In uncertain markets, the composition of customers and their preferences change at a higher rate. This is in line with a study by Johnson, Christensen and Kagermann (2008) in relation to BMI and market uncertainty, BMIs are often the result of a change in the composition of (potential) customers. Uncertain markets require

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21 firms to continuously develop new ways to live up to the standards of customers and satisfy their needs. Essentially, uncertain markets require firms to continuously develop new ways to create, deliver and capture value. The proposed relationship between innovation and cost orientation and BMI is expected to strengthen when, all conditions being equal, the addition of an ‘environmental force’ such as the uncertainty of markets increases. In this situation, the uncertainty of the market will shift the firm’s customer base or their preferences (Jaworski & Kohli, 1993). This will automatically put more pressure on the firm to undertake action to prevent losing customers. In turn, the firm is required to undertake action via new innovations, products or services. Following, to commercialize on these new innovations, address new customers, or to become more efficient and more effective BMI will likely be the result. Hence, it is expected that, when the uncertainty of markets increases, the proposed relationship between innovation, cost orientation and BMI is strengthened. Therefore it is hypothesized:

H3a: When markets are uncertain, the positive relation between Innovation Orientation and Business Model Innovation is stronger.

H3b: When markets are uncertain, the positive relationship between Cost Orientation and Business Model Innovation is stronger.

Technological turbulence is defined as: “the rate of technological change in a market”

(Jahworski & Kohli, 1993 p.57). Technological turbulent markets are characterized by organizations that work with nascent technologies that are undergoing rapid change and where competitive advantages are obtained through technological innovation (Jahworski & Kohli, 1993). By contrast, organizations that work with stable (mature) technologies are:

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22 “relatively poor positioned to leverage technology for gaining a competitive advantage” (Jahworski & Kohli, 1993 p.58).

Technological turbulent markets thus require firms to adapt to changing technological standards to live up to the standards of the market and to prevent current technologies becoming obsolete or even worse, losing a former competitive advantage to others. One possibility to adapt to a changing technological standard is via product innovation (Jahworski & Kohli, 1993). So far, technological turbulent markets have only been directly linked to product innovations that allow firms to develop competitive advantages. However, to commercialize new technologies the firm must develop new ways to create, deliver or capture value. In example, when technological turbulence is low, a firm is able to live up to the standards of the market via simple (product) innovations executed through its current BM. Contrary, when technological turbulence is high, the firm is dependent on the development of radical new ways to create, deliver or capture value to be commercialized via BMIs irrespective of whether the firm is innovation- or cost-oriented. Hence, it is expected that regardless whether the firm is innovation- or cost-oriented the strategic orientation – BMI relationships will be strengthened when markets are technological turbulent. Therefore it is hypothesised:

H4a: When Technological Turbulence is high, the positive relationship between Innovation Orientation and Business Model Innovation is stronger.

H4b: When Technological Turbulence is high, the positive relationship between Cost Orientation and Business Model Innovation is stronger.

Competitive intensity refers to “the degree of competition that a firm faces within its

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23 perform well, customers are ‘stuck’ with the firms product. However, in competitive intense markets, firms must be creative and innovative to improve their current BM. A competitive environment stimulates a firm to innovate and improve its current business activities (Porter, 1980). Additionally, as Johnson, Christensen and Kagermann (2008) note, a BMI is often the response to a shifting basis of competition. The shifting base of competition requires firms to adapt to new market standards or customers and discover new methods to create, deliver and capture value. Hence, when markets are competitive, it is expected that the proposed strategic orientation – BMI relationship is strengthened irrespective of whether the firm is innovation- or cost-oriented. It is therefore hypothesised:

H5a: When Competitive Intensity is high, the positive relationship between Innovation Orientation and Business Model Innovation is stronger.

H5b: When Competitive Intensity is high, the positive relationship between Cost Orientation and Business Model Innovation is stronger.

In conclusion, environmental factors affect firms and their current business activities (Miller, 1988; Zhou et al., 2005). Based on the literature, it is expected that, the addition of any environmental factor will strengthen the hypothesized strategic orientation – BMI relationships (see figure 1). This, to allow the firm to stay ahead of competition, prevent falling behind and in order to live up to the standards of (new) customers and markets. However, the degree to which environmental factors influence BMI is likely to be different. This study aims to determine the effect of both innovation and cost orientation on BMI moderated by three environmental forces: technological turbulence, competitive intensity and market uncertainty as defined by Zhou et al. (2005) and Jaworski and Kohli (1993).

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24 Figure 1: Conceptual Model Business Model Innovation

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3. Data and Method

3.1 Sample

A survey was conducted to determine, and analyse, whether there exists a relationship between innovation orientation, cost orientation and BMI, how they affect BMI, and whether these relationships are moderated by market uncertainty, technological turbulence and competitive intensity.

Purposive sampling is used since there are no sampling frames available and judgement was needed to select respondents (Saunders, Thornhill & Lewis, 2009). The questionnaire was completed by managers that have the opportunity to change the firm’s BM, or are at least able to influence the design of the firm’s BM. To ensure that every respondent is knowledgeable to adequately respond to the questions under examination, the study applies the following key informant criteria: (1) current job experience, (2) overall work experience and (3) involvement in strategic-, innovation- and operational-decision making (see Appendix A). In total, 97 managers have, via a personalized Linked-in message, been asked to complete the survey. From the initial sample of 75, this study discards 17 entries, due to missing data or mismatches with the key informant criteria. The study excludes all respondents that do not indicate management positions or score lower than five on a seven-point Likert scale, ranging from ‘strongly disagree’ (1) to ‘strongly agree’ (7). This resulted in a final sample size of 58 which indicates a response rate of 77.32%. The characteristics of the sample are presented in Table 2.

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26 Table 2: Sample statistics (N= 58)

Item Percentage Absolute number

Job title CEO 12.07% 7 CFO 1.72% 1 General Manager 10.34% 6 Business Manager 39.66% 23 Management Consultant 6.90% 4 Founder 22.41% 13 Other 6.90% 4 Age 20- 29 46.55% 27 30- 39 17.24% 10 40- 49 13.79% 8 50 and older 22.41% 13 Firm size Between 0 – 50 employees 70.69% 41 Between 51 – 200 employees 17.24% 10 >200 employees 12.07% 7 Firm age Between 1 – 5 years 34.48% 20 Between 6 – 15 years 22.41% 13 >15 years 43.10% 25

Overall work experience

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Between 6 – 10 years 20.69% 12

Over 11 years 53.45% 31

Current job experience

Over 11 years 27.59% 16

3.2 Measures

All measures are adopted from prior studies. The variables are measured on a 7 point Likert-scale (ranging from 1 = Strongly disagree to 7 = Strongly agree).

Innovation Orientation. Innovation orientation is adopted from Kortmann (2015),

using six items to measure innovation orientation: ‘New technology innovations are readily accepted and used in our firm’ (IO_1). ‘Employees that resist innovation or perceive innovation as too risky are the exception rather than the rule (IO_2)’, ‘Our employees are encouraged to actively seek innovative ideas (IO_3)’, ‘Innovation is readily accepted in program/project management (IO_4)’, ‘If new ideas do not work, our employees are not penalized (IO_5)’ and ‘Our management actively seeks and integrates innovative ideas (IO_6)’.

Cost Orientation. Cost orientation is likewise adopted from Kortmann (2015). Five

items were used to measure the degree to which the firm is cost-oriented: ‘Improving the operating efficiency of the business is a top priority (CO_1)’, ‘We have a continuing overriding concern for operating cost reduction (CO_2)’, ‘We continuously seek to improve our processes so that we can lower costs(CO_3)’, ‘We closely monitor the effectiveness and efficiency of our business processes (CO_4)’ and ‘Cost and resource efficiency are important elements of our strategy (CO_5)’.

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Technological Turbulence. Technological turbulence is a six item construct obtained

from Narver, Slater, Douglas and MacLachlan (2004): ‘The technology in our markets is changing rapidly (TO_1)’, ‘Technological developments in our markets are rather minor (TO_2)’, ‘Technological changes provide big opportunities in our industry (TO_3)’, ‘Technological changes provide big opportunities in our markets (TO_4)’, ‘It is very difficult to forecast where the technologies in our markets will be in the next five years (TO_5)’ and ‘A large number of new products in our markets have been made possible through technological breakthroughs (TO_6)’. Where: ‘Technological developments in our markets are rather minor’ is a measured on a reversed scale.

Competitive Intensity. Competitive intensity is the second of the three moderating

variables used in this study. To measure competitive intensity, the widely adopted scales from Jaworski and Kohli (1993) are used. The construct is measured with six items: ‘Our competitors are relatively weak (reversed item) (CI_1)’, ‘Anything that one competitor can offer others can match readily (CI_2)’, ‘There are many “promotion wars” in our industry (CO_3)’, ‘Price competition is a hallmark in our industry (CI_4)’, ‘Competition in this industry is cutthroat (CI_5)’ and ‘One hears of a new competitive move almost every day (CI_6)’.

Market Uncertainty. Market uncertainty is the last moderating variable used in this

study. To measure market uncertainty, again, the scales from Narver et al. (2004) are used. The items have a Cronbach’s alpha of 0.73 and the construct is measured with four items: ‘Customers in our markets are very receptive to new product ideas (MU_1)’, ‘In our markets, customers’ preferences change relatively fast (MU_2)’, ‘New customers tend to have product-related needs that are different from those of existing customers (MU_3)’ and ‘We mainly address the same customer base that we did in the past (reversed item) (MU_4)’.

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Business Model Innovation. To measure BMI the items from Pedersen, Gwozdz, and

Hvass (2016) are used. The construct is measured with nine items. Respondents indicate on a 7 point Likert-scale to which degree their firm focuses on ‘existing’ or ‘new’ products, services or markets. ‘Focus is on improving EXISTING products and/or services or Focus is on developing radically NEW products and/or services (BMI_1)’, ‘Focus is on serving EXISTING markets and customer segments or Focus is on identifying and serving entirely NEW markets and customer segments (BMI_2)’, ‘Focus is on nurturing EXISTING resources and competences (technology, people, IT systems, etc.) or Focus is on developing and/or acquiring NEW resources and competences (technology, people, IT systems, etc.) (BMI_3)’, ‘Focus is on improving EXISTING core processes and activities (design, logistics, marketing, etc.) or Focus is on developing NEW core processes and activities (design, logistics, marketing etc.) (BMI_4)’, ‘Focus is on deepening relationships with EXISTING strategic business partners (suppliers, distributors, end users, etc.) or Focus is on establishing relationships with NEW strategic business partners (suppliers, distributors, end users, etc.) (BMI_5)’, ‘Focus is on improving EXISTING tools for building customer relationships (personal service, memberships, bonus systems, etc.) or Focus is on developing NEW tools for building customer relationships (personal service, memberships, bonus systems etc.) (BMI_6)’, ‘Focus is on selling products and/or services through EXISTING channels (own stores, partner stores, online, etc.) or Focus is on selling products and/or services through NEW channels (own stores, partner stores, online, etc.) (BMI_7)’, ‘Focus is on minimising EXISTING costs incurred when operating the company or Focus is on making MAJOR changes in the combination of costs incurred when operating the company (BMI_8)’, ‘Focus is on improving sales from EXISTING revenue streams (products, services, leasing, sponsorships etc.) or We have developed NEW ways of generating revenue (products, services, leasing, sponsorships etc.) (BMI_9)’.

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30 To ensure that the respondent understands every construct measured in the questionnaire, the respondent was first introduced to the survey by explaining the purpose of the study. Prior to the questions the respondent was given an explanation of the construct that is measured.

3.3 Data Analysis and Method

This paper examines the relationship between multiple latent variables. Therefore, a multivariate analysis – called structural equation modelling (SEM) – is used. There are two types of structural equation modelling: CB-SEM (Covariance Based) and PLS-SEM (Partial Least Squared). The first is used to develop a theoretical covariance matrix based on a specified set of structural equations. Furthermore, CB-SEM is primarily used to confirm theories (Hair et al., 2011). PLS-SEM is used when the objective of the research is prediction rather than confirmation of structural relationships and is preferred when theories are less developed (Hair et al., 2011). This method is useful when there is little prior knowledge on how certain variables are related and when the research is constrained by small sample sizes (Hair et al., 2011). Both of these conditions apply to this paper. SmartPLS 3.0 is used to analyse the data.

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4. Analysis and Results

4.1 Evaluation of the Measurement Model

The measurement models used, measure the relationship between the latent variables and their indicators. As past literature acknowledges, the “misspecification of measurement models can bias inner model parameter estimation and lead to incorrect assessments of relationships in PLS path modelling” (Gudergan, Ringle, Wende, & Will, 2008 p.1239). The use of an incorrect measurement model undermines the content validity of constructs, misrepresents the structural relationships between them, and ultimately lowers the usefulness (Coltman, Devinney, Midgley & Venaik, 2008). Hence, prior to the analysis of the measurement model, it is necessary to determine first, whether the measurement models are formative or reflective.

With reflective measurement models, causality flows from latent constructs that are measurable with a battery of positively correlated items, where a formative measurement model shows causality flows in the opposite direction, from the indicator to the construct (Coltman et al., 2008). To decide whether the measurement model is reflective or formative, three considerations are important: (1) the nature of the construct, (2) the direction of causality between the indicators and the latent construct and (3) the characteristics of the indicators used to measure the construct (Coltman et al., 2008). In this study all measures are reflective because the indicators represent the effects of the underlying construct, suggesting there is causality from the construct to its indicators (Coltman et al., 2008).

To establish the reliability and validity of the latent variables in the measurement model (1) the individual item reliability, (2) internal consistency reliability (Cronbach’s alpha), (3) convergent validity and (4) discriminant validity are first being assessed.

Individual item reliability refers to the correlation of the latent variables with its

indicator (Gelhard & von Delft, 2016). For adequate individual item loadings, the indicators outer loadings should be above 0.70, exploratory research is however satisfied with values

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32 between 0.60 and 0.70 (Hair et al., 2011). There were several items which did not exceed the threshold of 0.6, the following items were therefore dropped: IO_2, IO_5, TT_2, TT_2_R, CI_2, CI_3, MU_4, MU_4_R, BMI_1, BMI_2, BMI_4 and BMI_9. Table 3 gives a representation of the items used in this study.

Table 3: Outer loadings

Variable Item Outer loadings

Innovation Orientation IO_1 0.771

IO_3 0.882

IO_4 0.766

IO_6 0.777

Cost Orientation CO_1 0.726

CO_2 0.811 CO_3 0.783 CO_4 0.621 CO_5 0.656 Technological Turbulence TT_1 0.754 TT_3 0.932 TT_4 0.889 TT_6 0.783

Competitive Intensity CI_3 0.755

CI_4 0.710

CI_5 0.743

CI_6 0.802

Market Uncertainty MU_1 0.677

MU_2 0.862

MU_3 0.805

Business Model Innovation BMI_3 0.761

BMI_5 0.660

BMI_6 0.758

BMI_7 0.709

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Internal consistency reliability is a measure indicating how well indicators measure the same

construct (Hair et al., 2014). To determine the internal consistency Cronbach’s alpha and the composite reliability are taken into account. Unlike Cronbach’s alpha, the composite reliability does not assume that all indicators are equally reliable, making it more suitable for PLS-SEM, since it prioritizes indicators according to their reliability during model estimation (Hair et al., 2011). For adequate values of the internal consistency reliability, Cronbach’s alpha should exceed 0.70 (Hair et al., 2011). In this study, ‘Market Uncertainty’ shows a Cronbach’s alpha below the usual 0.7 threshold, implying that the construct has low reliability (see Table 4). However, Cronbach’s alpha is sensitive to the number of scale items and generally tends to underestimate internal consistency reliability (Hair et al., 2014). Therefore, taking into account the composite reliability of the construct being above the 0.7 threshold it is decided to not exclude the item.

Table 4: Consistency reliability

Construct Composite Reliability Cronbach’s Alpha

Innovation Orientation 0.865 0.791

Cost Orientation 0.844 0.781

Technological Turbulence 0.907 0.867

Competitive Intensity 0.839 0.786

Market Uncertainty 0.827 0.691

Business Model Innovation 0.865 0.807

Convergent validity refers to the degree to which two measures of constructs that

theoretically should be related, are in fact related (Hair et al., 2011). Reflective measurement models’ validity assessment focuses on convergent validity. Researchers therefore need to examine the average variance extracted (AVE). An AVE of 0.5 and higher indicates a

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34 sufficient degree of convergent validity, meaning that the latent variable explains more than half of its indicator’s variance (Hair et al., 2011). The results indicate that there is convergent validity for all constructs (AVE > 0.50). The AVE of the constructs used in this study are represented in Table 5.

Table 5: Average Variance Extracted

Construct Average Variance Extracted (AVE)

Innovation Orientation 0.615

Cost Orientation 0.523

Technological Turbulence 0.711

Competitive Intensity 0.567

Market Uncertainty 0.616

Business Model Innovation 0.563

Discriminant validity represents the extent to which the constructs is empirically

distinct from other constructs or, in other words, it tests whether measurements that should not be related, are in fact unrelated (Hair et al., 2014). To assess the existence of discriminant validity the Fornell and Larcker (1981) criterion is used. This method states that the construct shares more variance with its indicators than with any other construct (Hair et al., 2014). In order to test this requirement, the AVE of each construct should be higher than the highest squared correlation with any other construct. The results in Table 6 show that this requirement is met for all constructs and the control variables. A second option, to verify discriminant validity is to examine the cross loadings of the indicators. To ensure discriminant validity, an indicator’s loading should be higher than all of its cross loadings (Hair et al., 2011). The results in Appendix C show all indicator loadings are higher than its cross loadings. Finally, because in research studies, the Fornell-Larcker criterion and cross loadings not always

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35 reliably detect a lack of discriminant validity (Henseler, Ringle & Sarstedt, 2015), a relatively new criterion, the Heterotrain-Monotrait Ratio (HTMT) is consulted. The HTMT-criterion shows that all values are below the 0.90 threshold (Appendix D). Together with the Fornell-Larcker criterion and the item loadings, it is possible to conclude that discriminant validity has been established for all constructs.

Table 6: Discriminant Validity (Fornell-Larcker criterion)

Construct ME SD 1 2 3 4 5 6 1. IO 5.858 1.017 0.784 2. CO 5.459 1.304 0.199 0.723 3. TT 5.586 1.442 0.330 0.130 0.843 4. CI 4.194 1.611 0.122 0.579 0.124 0.753 5. MU 4.477 1.607 0.339 0.390 0.376 0.550 0.785 6. BMI 4.856 1.682 0.446 0.421 0.491 0.351 0.509 0.750 7. Firm age 2.086 0.876 0.045 0.107 -0.138 -0.017 -0.108 -0.197 8. Firm size 1.413 0.695 -0.025 0.001 -0.142 -0.173 0.023 -0.195 Note: ME = Mean and SD = Standard Deviation.

4.2 Evaluation of the Structural Model

In this section the structural model that measures the relationships between the latent variables is evaluated. The following criteria are therefore being assessed: path coefficients, determination coefficient (R²) and the effect size (ƒ²).

Path coefficients. A path coefficient shows to what extent the latent variables are

important in explaining BMI, allowing to indicate the level of significance (Hair et al., 2011). In this study, the path coefficients determine to what extent innovation and cost orientation are positively related to BMI. To test the significance of the estimated paths, a complete bootstrapping procedure is executed with 500 samples. For a significant level of 10% the

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T-36 value should exceed 1.65 (Wong, 2013). The results (Table 7) show that the relationships IO  BMI (2.000) and CO  BMI (2.115) are significant. Innovation and cost orientation are confirmed to be antecedents of BMI. Therefore, hypothesis 1 and 2 are supported (see Figure 2).

Table 7: Path Coefficients

Linkage Original sample Sample mean Standard deviation T – value P – value IO  BMI 0.266 0.239 0.133 2.000 0.046 CO  BMI 0.345 0.372 0.163 2.115 0.035 TT  BMI 0.249 0.197 0.125 1.996 0.047 TT x IO  BMI _-0.103 _-0.088 _0.144 _0.717 _0.474 TT xCO BMI _0.050 _0.026 _0.180 _0.277 _0.782 CI  BMI -0.044 -0.012 0.146 0.297 0.766 CI x IO  BMI _-0.031 _-0.022 _0.168 _0.182 _0.856 CIx CO  BMI _0.196 _0.198 _0.212 _0.923 _0.357 MU  BMI 0.194 0.197 0.169 1.150 0.251 MUxIO  BMI _0.079 _0.051 _0.163 _0.487 _0.626 MUxCO BMI _-0.165 _-0.156 _0.263 _0.627 _0.531 F. age  BMI* _-0.152 _-0.142 _0.141 _1.072 _0.284 F. size  BMI* _-0.124 _-0.108 _0.126 _0.987 _0.324

* F. age and F. age represent the control variables: ‘Firm age’ and Firm size’.

Determination effect, refers to the prediction power of the research model. The R² is a

measure of the model’s predictive accuracy (Hair et al., 2014). The effect ranges from 0 to 1 with 1 representing complete predictive accuracy. Since the R² is embraced by a wide variety of disciplines, one must rely on “rough” rules of thumb regarding an acceptable value for R²

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37 (Hair et al., 2014). In management research 0.75, 0.50 and 0.25 respectively describe substantial, moderate and weak predictive accuracy. In this study, the original sample has an R² of 0.528 which implies a moderate predictive accuracy.

Effect size, refers to the quantitative measure of the strength of a phenomenon. The

effect size for each path model can be determined by calculating Cohen’s ƒ (Hair et al., 2014). The ƒ² is computed by noting the change in R² when a specific construct is eliminated from the model. Based on the ƒ² value, the effect size of the omitted construct for a particular endogenous construct can be determined such that 0.02, 0.15 and 0.35 represent small, medium and large effects (Cohen, 1988). In this study for innovation orientation, cost orientation, technological turbulence, competitive intensity and market uncertainty effect sizes of respectively 0.099, 0.130, 0.089, 0.002 and 0.038 are found, implying small, to large effects.

4.3 Moderating Effects

Moderation occurs when the effect of an exogenous construct on an endogenous construct depends on the values of another variable, which influences (moderates) the relationship (Hair, 2014). In this study, it is examined whether the relation between innovation orientation and BMI and cost orientation and BMI is moderated by three environmental factors, namely technological turbulence, competitive intensity and market uncertainty. As the results indicate in Table 7, there are no significant moderating effects. The moderating latent variables show small effects on the path coefficients. However, despite not being hypothesised, the direct path: TT  BMI (1.996) is significant (T-value ≥ 1.65) (Wong, 2013). The significant path implies that technological turbulent markets are also an antecedent of BMI. The other non-hypothesised direct paths: CI  BMI and MU  BMI show an effect, but non-significant. With no significant moderating paths, hypothesis 3a, 3b, 4a, 4b, 5a and 5b are not supported (see Figure 2).

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38 4.4 Control Variables

To test for control effect this study uses ‘Firm age’ and ‘Firm size’ as possible influencers of the expected relationships between the hypothesised paths. To determine the effect of the control variables, both control variables have been linked to the endogenous construct in the model. Again, the 500 sample bootstrapping procedure is used to derive the effects. However, as Table 8 indicates, there are no significant control effects perceived. ‘Firm age' and ‘Firm size’ show only small, non-significant, effects.

Table 8: Control Effects Linkage Original sample Sample mean Standard deviation T-value P-value Firm age -0.125 -0.142 0.141 1.072 0.284 Firm size -0.124 -0.108 0.126 0.987 0.324

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5. Discussion

5.1 Theoretical Implications

Previous literature highlighted BMI to be a necessary response to “strategic discontinuities and disruptions, convergence and intense global competition” (Doz & Kosonen, 2010 p. 370). However, few studies have empirically tested the effect of different drivers to engage in BMI. In a recent literature review Foss and Saebi (2017) argue that, to advance BMI research, studies should at least clearly identify the antecedents and consequences of the focal phenomenon. This study therefore examined innovation and cost orientation as antecedents of BMI.

Both strategic orientations allow to be studied as higher-level proxies for exploratory and exploitative activities necessary, during BMI. While prior literature has dealt with the question of how to manage strategic dualities as well as how firms can respond to tensions and trade-offs between pairs of conflicting activities (He & Wong, 2004; Kortmann, 2015), an integration of work on ambidexterity with work on BMI was missing. The use of both innovation and cost orientation as higher-level proxies for exploratory and exploitative activities during BMI therefore integrates three streams of literature namely, strategic orientation literature, ambidexterity literature and BMI literature. The confirmation of both innovation and cost orientation as antecedent of BMI explicitly confirms a relationship that, so far, has only implicitly been suggested in separate research streams. Although previous studies discuss ambidexterity as a trade-off between pairs of conflicting activities, the results imply that regardless whether firm activities are from exploitative or exploratory nature, both contribute to BMI.

Furthermore, the study results are in line with and extend a rudimentary argument developed by Zott and Amit (2007) arguing both efficiency and novelty-centered BMs are not mutually exclusive. The results of this study show that a cost and innovation orientation are

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40 also not mutually exclusive and both are required simultaneously. Overtime, the pursuit in an innovation and cost-oriented strategy, by scholars defined as ambidexterity, allows BMI. Hence, a theoretical and practical contribution is made by integrating different streams of research and providing explicit orientations reflecting both exploratory and exploitative activities, namely innovation and cost orientation.

Second, in line with previous literature it was expected that technological turbulence, competitive intensity and market uncertainty would strengthen the strategic orientation – BMI relationship. While this study could not show a significant effect of competitive intensity and market uncertainty on the relation between the strategic orientations studied and BMI, a direct, significant effect of technological turbulence on BMI is identified. Markets characterised by rapid technological changes therefore require firms to develop BMIs to, for instance, commercialize on new technologies via BMIs different from the firms’ former BM.

In congruence with previous studies this research confirms the existing relationship between strategic orientations and BMI. Altogether, by testing, and confirming, the effect of different strategic orientations on BMI this study raises critical awareness for the importance of discovering the relatively unexplored relationships between strategic orientations and BMI holding both interesting theoretical explanations and practical implications. Consistent with previous studies the results show that BMI is a dynamic concept influenced by both internal and external factors. The explicit description of BMI antecedents extends future research that considers both BMI and ambidexterity literature allowing scholars to further explore the identified relationships.

Concluding, the outcome of this study partially satisfies the research question. Despite being able to confirm the existing relationship between innovation, cost orientation and BMI, the results do not show under what conditions there will be differences in the relationship

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41 between innovation and cost orientation and BMI, because of the non-significant moderating effects.

5.2 Managerial Implications

The addition of another piece to the giant puzzle of BMI literature provides managers and other business practioners valuable insight regarding the drivers of BMI. The increasing popularity of BM literature over the past decade is largely the result of BMs being able to capture everything within the firm were value is added (Casadesus-Masanell & Ricart, 2011). Essentially, BMs are becoming the primary building block of sustained competitive advantages (Casadesus-Masanell & Ricart, 2011). Yet, managers do often not completely understand their firms’ BMs and have difficulty innovating their current BM(s) (Johnson, Christensen & Kagermann, 2008). This study contributes to that specific area by providing valuable insights for managers regarding the antecedents of BMI.

With managers continuously facing the ‘ambidexterity-dilemma’ resulting in a trade-off between balancing different firm activities to either exploit current activities or explore new opportunities (Kortmann, 2015), this research shows that the pursuit in either exploratory (innovation-oriented) and exploitative (cost-oriented) firm activities contribute to BMI. Business practioners should therefore treat the engagement in exploratory and exploitative activities as complementary, allowing the firm to develop BMIs following from exploiting their current activities or exploring new opportunities. The results show how important the reconciliation is for managers to implement both innovation and cost-oriented strategies simultaneously.

To implement innovation and cost-oriented strategies, managers should support behaviour that allow employees to introduce new processes, products or ideas in the organization and enable the pursuit of efficiency and cost reduction throughout all parts of the value chain. Furthermore, in addition to support both strategic orientations, managers should

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42 function as role models for values, beliefs and behaviour associated with, on first sight, contradictory orientations. Another obvious implication is the necessity for managers to become explicitly aware of the resource allocation between exploratory and exploitative strategic orientations.

Second, the findings indicate the need for managers to be responsive to environmental contexts to pursue the effective strategic orientations in a specific context. Furthermore, the results indicate that technological turbulent markets are also an antecedent of BMI. Conducting an environmental analysis would therefore allow managers to determine the force of their environmental influences to consequently respond by consequently innovating elements of the firm’s BM to adapt.

Concluding, in line with previous studies, the outcomes of this paper show that BMI is a dynamic concept that can be influenced by many different internal- and external forces and influences. Alternatively, the dispersed set of antecedents of BMI also challenges business practioners in managing the organizational tension between exploratory and exploitative activities. Yet, organisations that are able to pursue both innovation- and cost-oriented strategies foster BMI that allow firm’s to develop sustainable competitive advantages.

The relationship between cost orientation, innovation orientation and business model innovation : an organizational ambidexterity perspective