A capability-based approach to Business Model Innovation and the role of discretionary slack

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A capability-based approach to Business

Model Innovation and the role of

Discretionary Slack

Master Thesis

Amsterdam Business School

Executive Programme in Management Studies- Strategy Track Student: Samantha Ann Reilly

Studentnr: 10505598

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Abstract

Business model innovation has been identified as a key driver of competitive advantage. Despite the importance of this topic, the literature lacks a full theoretical understanding of the concept. The role of relevant organizational capabilities that firms apply to pursue business model innovation is still unclear. Secondly, the role of discretionary slack as an organizational antecedent has been overlooked in the business model innovation literature. Finally, the literature on business model innovation lacks quantitative empirical research. This study bridges these gaps with the development of a conceptual model, determining the role of discretionary slack and the relevant organizational capabilities that drive business model innovation. This conceptual model is empirically tested with quantitative research. This study draws on dynamic capabilities and innovation literature identifying learning orientation, sensing, seizing and reconfiguring capabilities and discretionary slack as relevant organizational antecedents for business model innovation.

The data is collected by a structured online survey performed under firms in the Netherlands, from all industries, ranging from a turnover of 0-500 million.

The results show that sensing capabilities are direct positively related to business model innovation. Learning orientation and discretionary slack are positively indirectly related to business model innovation as their relation is mediated by sensing capabilities. In line with previous research, learning orientation and discretionary slack are identified as drivers of sensing, seizing and reconfiguring capabilities. No evidence was found to support a relationship between seizing, reconfiguring capabilities and business model innovation. This research contributes to the theoretical conceptualization of business model innovation by identifying relevant organizational capabilities to pursue business model innovation. This research contributes to prior literature by identifying the role of discretionary slack as a relevant antecedent to business model innovation. Practioneers gain insight in how to approach business model innovation with the identification of sensing and learning capabilities and discretionary slack as drivers of business model innovation.

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1. Introduction

Since the 1990s there has been an increasing attention for Business Models (BMs). The internet enabled firms to fundamentally change the way they organize and engage in economic exchanges, this includes the ways in which firms interact with suppliers and customers (Mendelson, 2000). This provided firms with the potential to experiment with novel BMs. Dell, a computer manufacturer, implemented a customer-driven build-to-order BM, which replaced the traditional build-to-stock model of selling computers through retail stores. AirBnB disrupted the hotel industry by connecting hosts and travelers with its

marketplace platform. Apple introduced the iPod with the iTunes store, combining hardware, software and service. Academics and practioneers started to identify the BM as a potential source of value creation and competitive advantage (Markides & Charitou, 2004).

After the BM was acknowledged as driver of innovation, the BM itself has increasingly been considered as subject to innovation (Chesbrough, 2010). Business model innovation was identified as a specific form of innovation. Business model innovation occurs when the firm is able to design innovative value offerings that increase customer value and at the same time employ new value chain structures, novel revenue models and reconfiguration of the resource base (Chesbrough, 2010). Nowadays firms are confronted with changes in the competitive environment due to new technologies, inter-industry competition and new BMs offering better value propositions. Firms need to innovate their established BM to adapt it to changes in environment to sustain performance. It has been realized that companies which have been successful for some time, run the risk to fail, if they continue doing for too long what used to be right, without adapting their BM to changes in the competitive situation (Doz and

Kosonen, 2010). Therefor there is increasing acknowledgement that business model

innovation is a crucial source of competitive advantage (Hamel and Välikangas, 2003),(Amit and Zott, 2010).

Despite the importance of business model innovation, the literature lacks a full theoretical understanding of the concept. In the literature there has been a focus on the importance, causes, dimensions and barriers of business model innovation (Schneider and Spiegt, 2013). The aim of these studies was to gain a first understanding of the business model innovation phenomenon. In their recent review of business model innovation literature Schneider and Spiegt (2013) conclude that “business model innovation’s core elements and the process of

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5 their identification, design, and evolution remain largely unknown.” . Relevant organizational antecedents have to be further researched to operationalize business model innovation.

The purpose of business model innovation is to secure alignment to the changing

environment. The capabilities needed to address changes in the business environment have been identified as dynamic capabilities. Dynamic capabilities allow a firm to identify and exploit opportunities, synchronize business processes and models with the business

environment, and/or shape the business environment in its favor (Teece et al, 1997). Three clusters of dynamic capabilities can be identified to ensure environmental fitness. Sensing capabilities enable the identification of new opportunities and threats. Seizing capabilities address these opportunities and threats. Reconfiguring capabilities redeploy resources accordingly and guarantee continued renewal. These capabilities are build and driven by learning capabilities. As these capabilities drive organizational change and environmental fitness, they are a suitable starting point in unraveling relevant organizational antecedents of business model innovation (Mezger, 2014). This study proposes a conceptual model with sensing, seizing, reconfiguring and learning capabilities to ensure business model innovation. In addition the role of discretionary slack as a relevant organizational antecedent is identified. Despite the fact that discretionary slack has been identified as important determinant of innovation in the innovation literature, its relation to business model innovation has not been studied. In the literature there has been a lot of attention for the barriers of business model innovation. Business model innovation is characterized by high risk, uncertainty, volatile and delayed return (Troilo et al, 2014). Discretionary slack plays in an important role in coping with these barriers. Discretionary slack are human and financial resources, in excess of what is needed for the immediate continuation of the firm. These slack resources are thus available to spend on sensing, seizing and reconfiguring activities. Therefor encouraging search

activities for new business opportunities that cannot be justified in terms of short term return (Troilo et al, 2014). Allowing seizing activities because slack encourages experimentation (Levinthal & March, 1981). Enabling reconfiguration of resources and the mobilization of extra resources. There is a need for slack in resources, to provide to the new BM, while continuing the established BM.

This study builds on the work of Mezger (2014) and dynamic capabilities literature (Teece et al, 1997) and proposes a conceptual model with sensing, seizing, reconfiguring, learning capabilities and discretionary slack as relevant organizational antecedent to pursue business

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6 model innovation. This contributes to the conceptual development of business model

innovation and more specifically to the capability based conceptualization on how to perform business model innovation. Although the large research base on business model innovation, there are hardly any quantitative studies empirically supporting the findings. Almost all literature on business model innovation has an exploratory approach using qualitative research. This study fills this gap by empirically testing the conceptual model.

The remainder of this study is organized as follows. The first chapter will provide an overview of the literature on BMs, business model innovation and dynamic capabilities. Building on that, follows the theoretical framework and the conceptual model. Five

hypotheses are developed on the relationship of discretionary slack and the capabilities for business model innovation. Then the methodology is described. The conceptual model will be empirically tested based on a dataset of 71 small and medium sized enterprises. Next the research findings are presented and discussed. Finally the theoretical and managerial

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2. Literature Review

This chapter provides the theoretical grounding of business model innovation. In the first paragraph, the question; “What is a BM?” will be addressed. The second paragraph will give more insight in the business model innovation concept. The theoretical roots, which lie in the dynamic capabilities view, will be presented in the third paragraph.

2.1 Business Models

Business models (BM) are stories that explain how enterprises work. A good business model answers the following questions: Who is the customer? What does the customer value? 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? (Margretta 2002).

Since the mid 1990’s there has been an increasing interest in the BM concept. This gain in popularity is caused by the following trends.

• New information and communication technology create new business opportunities. The internet and decline in computing and communication cost have led to many new BMs like Facebook, AirBnB, Twitter and Uber. The new BMs entail new ways to create value and new exchange mechanisms (Amit & Zott, 2010).

• Developments in the global economy changed the traditional balance between customer and supplier. The internet and the establishment of open global trading regimes, mean that customers have more choices, almost all customer needs can find expression, and supply alternatives are more transparent (Teece, 2010). This change in balance between customer and supplier demands a focus on value creation for customers. The BM construct provides an answer to address this change because it promotes an outside-in perspective, as continually engaged with and adapting to changing customer values. Business models that don’t create value for customers don’t create value for the firms that seek to serve those customers (Mcgrath, 2010). Therefor scholars are increasingly acknowledging that business models are a potential source of competitive advantage (Markides & Charitou, 2004).

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8 Despite the abundance of academic literature on BMs, it appears that academics and

practioneers have yet to define a common and widely accepted definition and interpretation. The main reason for the lack of coherence on this subject, is that the concept is developed by various researchers from different fields, like social sciences, management, communication and psychology.

Most scholars define BMs by their elements. Johnson, Christensen, & Kagermann (2008) argue that BMs “consist of four interlocking elements, that, taken together, create and deliver value” . The elements consist of: value proposition, profit formula, key resources and key processes. Their explanation bears much resemblance to Morris et al (2005) and Osterwalder & Pigneur (2011).

Figure 1. Business Model Canvas by Osterwalder & Pigneur (2010)

Amit & Zott (2001, 2010) consider the BM as the “the content, structure, and governance of transactions designed so as to create value through the exploitation of business opportunities”. Based on the fact that transactions connect activities, the authors further evolved this

definition to conceptualize a firm’s BM as “a system of interdependent activities that

transcends the focal firm and spans its boundaries”. They argue that activity systems capture the essence of BMs and propose two sets of aspects that BM designers need to consider: 1.design elements (content, structure, and governance) that describe the architecture of the activity system

2. design themes (novelty, lock-in, complementarities, and efficiency) that describe the sources of value creation of the activity system (Amit & Zott 2001, Amit & Zott 2010).

Key activities Value Proposition Channels Cost structure Key resources Key Partners Revenue Customer Customer Relation ship

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9 Although the conceptual differences among researchers there are some mutual themes. There is widespread acknowledgement that BM is a new unit of analysis that is distinct from the product, firm, industry, or network; it is centered on a focal firm, but its boundaries are wider than those of the firm. BMs emphasize a system-level, holistic approach to explaining how firms “do business”. The activities of a focal firm and its partners play an important role in the various conceptualizations of BMs that have been proposed. BMs seek to explain both value creation and value capture (Amit & Zott, 2001).

In the more recent literature there is an increasing attention for the dynamic nature of BMs. BMs need to change to adapt to changing environments. Furthermore, BMs are becoming more often the starting point for innovation strategies to capitalize on new market

opportunities or new technologies. This is referred to as business model innovation. The next paragraph will give insight in the business model innovation concept.

2.2 Business Model Innovation

Globalization and technological advancements lead to the increasing speed of everything. Product cycles and design cycles are getting shorter. Competition is coming from unexpected places, known as interindustry competition. Traditional industries are being disrupted by new BMs that create more value for customers (Mcgrath, 2010). Existing BMs are copied or become irrelevant because of technological advancements. These environmental changes induce both risks and opportunities. Firms need to adapt their BM to these environmental changes. A currently successful BM is not a given. Moreover, it has been realized the firms that have a successful BM run the risk to fail if they keep doing what used to be right, without adapting to environmental changes (Doz and Kosonen, 2010). The telephone manufacturers Nokia and Blackberry are examples of firms that became a victims of their own success.

Business model innovation has been regarded as a crucial organizational capability to achieve sustainable competitive advantage (Hamel and Välikangas, 2003; Amit and Zott,

2011).Despite the importance of the concept, there has not yet emerged a precise definition of business model innovation.

Chesbrough (2010) defined business model innovation as a novel way to create and capture value, which is achieved through a change in one or multiple components in the BM. It can

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10 involve changes in only a few elements of the BM like suppliers and channels or it can be radical, leading a total new BM. It builds on the BMs capacity to integrate all of the firm's current BM elements, its external environment, and its interfaces with customers and partners. Therefor the scope, renewing a firm’s core business logic, is different from product or process innovation. Product innovation can be a driver of business model innovation. The Apple Ipod is an example of new technology brought to market in a differentiated BM. Chesbrough (2010) argues that an idea or technology brought to market in two different BMs, will yield different business outcomes.

Demil & Le Coq (2010) argue that business model innovation is a substantial change in the structure of its costs and/or revenues, change in using a new kind of resource, developing a new source of revenues, reengineering an organizational process, externalizing a value chain activity. It is about consciously renewing the value creation architecture. Amit and Zott

(2001) argue that business model innovation is about designing a new or modified the existing activity system. It requires firms to adapt, renew, acquire, or build up new resources and competences and (re)combine these in novel ways.

There are the following limitations to the literature on business model innovation. Business model innovation is a relatively new field in strategy literature. Hence there are no widely accepted definitions of BMs and business model innovation, which make the construct difficult to operationalize (Amit & Zott, 2011). The concept has been developed is different silo’s from innovation management to strategic management. Therefor the concept has no theoretical base and lacks conceptual base (Schneider and Spiegt, 2013). Most literature on business model innovation is highly anecdotal, managerial orientated and lacks empirical grounding.

BMs need to change over time to achieve sustainable competitive advantage. In addition, successful firms apply a pro-active approach (M. Johnson, 2010). They don’t wait until circumstances force them to change their BM. They view business model innovation as a continual necessary process or competence like product or process innovation. In the end business model innovation is about managing organizational change (Chesbrough, 2010) to ensure environmental fitness. In strategic management literature, the dynamic capabilities view has addressed the issue of pursuing environmental fitness. This theory identified specific capabilities needed to create, reconfigure and modify existing competences and resources to

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11 adapt to environmental changes (Teece et al, 1997). These capabilities are also relevant to business model innovation. Thus reshaping BMs requires specific capabilities that enable business model innovation. Therefor dynamic capabilities view is identified as the theoretical foundation of business model innovation (Teece, 2010). The next paragraph will elaborate on the Dynamic Capabilities View.

2.3 Dynamic capabilities

The Dynamic Capabilities View aims to explain competitive advantage by focusing on capabilities that enable a firm to adapt to the changing environment or shape its environment. These capabilities are defined as dynamic capabilities. Dynamic capabilities are the

capabilities that allows the firm to integrate, build and reconfigure internal and external competences to address rapidly changing environments (Teece et al, 1997). The term 'dynamic' refers to the capacity to renew competences to adapt to the changing business environment. The term 'capabilities' emphasizes the key role of strategic management. Strong dynamic capabilities enable firms to orchestrate their resources effectively. They enable a firm to identify and exploit opportunities, synchronize business processes and models with the business environment, and/or shape the business environment in its favor (Teece et al, 1997).

The dynamic capabilities view is an extension of the resource base perspective. This perspective was one of the core theories in strategic management, explaining competitive advantage. In this view firms are bundles of resources that are heterogeneous distributed among firms (Barney, 1986). A resource is an tangible or intangible asset that the firm owns or controls. It is built around the main idea that firms should obtain valuable, rare, non-imitable, non-substitutional (VRIN) resources in order to achieve a competitive advantage (Barney, 1997). Later Peteraf and Barney (2003) identified another dimension in this perspective. Firms active in high competitive markets can still be successful without VRIN resources. They argued that not the resources but the way the resources are used is critical. Firms that have access to the same resources may very well differ in performance. Hereby the focus shifted towards capabilities as an explanation of competitive advantage. These

capabilities lie in how the firm “gets things done” (Teece et al, 1997). They are managerial processes, procedures, routines, best practices, know-how, management of knowledge.

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12 In 1997 Teece coined the term dynamic capabilities. He played a key role in the development of the Dynamic Capabilities View. He distinguishes between “ordinary capabilities” and “dynamic capabilities”. Ordinary capabilities are capabilities that reflect activities like operations, administration, governance. The activities necessary to produce a product or service. The capabilities are aimed at technical efficiency and examples are operational excellence, performance management, quality control. These are “zero order” capabilities and necessary for key activities. Dynamic capabilities are of an higher order. The aim of these capabilities is to continuously assure environmental fit and therefor to create and capture more value. These capabilities orchestra the ordinary capabilities to fine-tune these with the

changing environment. Their aim is to continuously asses the value creation and capture of processes, routines, resources and “soft assets” in relation to the environment. Teece et al (1997) defined soft assets as values, culture and organizational experience. Change is there for key. They govern how ordinary capabilities are developed, combined and integrated. Zahra et al (2006) distinguishes between ordinary and dynamic capabilities, where product

development is ordinary capability. The ability to reform the way the firm develops products is a dynamic capability.

In line with the traditional resource based view, dynamic capabilities are not easily transferred or imitated. They are idiosyncratic to the firms, because they were built over time. They were influenced by the firms strategy, market position and firm history. These intangible assets can’t be acquired in the market place neither can they be replicated overnight. Different capabilities vary in abstraction level. The higher the abstraction level the more difficult it is to replicate the capability. But they are not completely inimitable, best practices and routines can be copied.

Teece (2007) identified three clusters of dynamic capabilities that are most important to pursue environmental fitness. These are sensing, the identification of new opportunities, seizing, addressing these opportunities and reconfiguration of the asset base accordingly to ensure continues renewal.

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13 1. Sensing

Sensing is the ability to recognize new opportunities and threats. This capability is about scanning the business ecosystem, learning about and interpreting new technical possibilities, identifying unmet consumer needs and new markets. This entails not only recognition of changes in the current industry or used technology base, but also learning about developments in other industries and not related technology.

It requires access to information and the ability to recognize the opportunity. The ability to recognize these opportunities is not equally divided among individuals and firms. Creativity and knowledge about user needs play an important role. It is important that sensing, creativity and learning are embedded in organizational processes. Where Teece (2007) initiated a broad perspective on this capability, different scolars identified these activities as sub capabilities. Den Hertog et al (2010) identified two sub capabilities related to sensing: identification of user needs and identification new technological options. As most innovations steam from the combination of these two leading to new products, services and BMs. Identification of user needs is the capability to empathically understand users and sense their (potential) needs (Den Hertog et al, 2010). The identification of new technological options provide opportunities to create new services, products, channels. Day (1994) identified market sensing capability as the systematic, thoughtful, anticipatory process of gathering market and trend intelligence. Focussing more on competition and complementors.

If firms engage in these activities on ad-hoc basis, it is not a dynamic capability. In order to speak of a dynamic capability the activities have to embedded in processes or routines. Therefor it is a costly activity, because it requires building the competences to gather and interpret this diverse information.

Activities related to sensing are often influenced by organizational design. Firms that are very decentralized and have vertical communication structures are often better at sensing new opportunities (Teece, 2010). Decentralization leads to higher interaction of employees with clients, suppliers and complementors, enhancing the identification of opportunities. Vertical communication structures stimulates the information flow. Knowledge from employees working at the customer front-line or working with suppliers flows efficiently through the organization to top management

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14 The information obtained by “sensing” allows management to draw up hypotheses about changes in the market environment and forecast future stage of the market to identify and exploit new opportunities

2. Seizing

Seizing entails the mobilization and deployment of resources internally and externally to address the sensed opportunities. During the sensing process top management has identified the most promising opportunities, in the seizing process it addresses these opportunities like inventions, innovations to create new products, services and business models. This capability also entails the ability to assimilate new knowledge with existing knowledge and create new knowledge.

Activities related to seizing involve identifying, establishing control or influence over, then coordinating complementary assets. An important activity is the selecting, improving and adjusting the organization, for example, by building a global supply chain, establishing alliances and joint venture.

The identification of new opportunities is not a straight forward process. During the sensing process management drew up hypotheses about changes in the market environment. If these hypotheses challenge the dominant logic within the organization, they most likely lead to resistance. New and radical ideas challenge the status quo, which often leads to resistance. Another threat to this process is bias in the decision-making process. Bureaucratic, layer upon layer, decision making procedures often favor incremental competency improvements over innovation. Managers have to be aware of these biases. Despite differences in outlook, top management needs to create some consensus by either persuading or overruling opponents. Sometimes these differences cannot be overcome, resulting in not acting on the opportunity. It is important that the firm’s management systems encourage employees to challenge outmoded traditions and practices to keep a culture of open minded inquiry

Acting on the opportunity almost always requires investments. Investment in a specific technology, process, product or BM. With the identification of opportunities, arise many interrelated investment decisions. Important aspects of the investment decision are building

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15 the related technological competences and complementary assets and creating network

externalities. Investment in these new opportunities often means investing in different areas simultaneously to be successful. Managerial investment skills that identify this intertwining are crucial. Traditional finance instruments like discounted cash-flow method do not

acknowledge these interdependencies. Current financials investment tools are not suitable to judge these kinds of strategic investments. Funds are often allocated to the investment with the highest returns and the lowest risk. New opportunities often entail high uncertainty and therefor risk resource starvation. Chesbrough (2007) suggest to put aside a separate pool of money to finance these investments to reduce competition for resources.

Besides where and how much to invest, when to invest is also a critical issue. The first mover sometimes stays ahead. Another strategy can be to position itself in complementary assets and enter the market when the new entrant has done the prospecting and the market risk is

lowered. .

The BM plays a crucial role in the seizing of opportunities as it determines the value creation and capture.

3. Reconfiguration

Reconfiguring is about continues renewal of the organization to maintain environmental fitness. Success leads to routines and processes. Routines and processes are necessary to be efficient. Changing routines and processes is costly and will often lead to resistance. But it can be necessary in response to environmental change. Thus reconfiguring is about

continuously evaluating the environmental fitness and managing change to restore

environmental fitness. This change is achieved by redeployment of resources and assets. This can be done by updating process and routine. This can be asset re-alignment, for example in combination with mergers and acquisitions. Another important element is co-specialization. Managers should be able to identify, develop and utilize necessary co-specialization networks and co specialized assets. Furthermore it is about selectively phasing out old products,

adjusting lines of communication, changing methods and processes and organizational culture.

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16 Despite the important contribution of the dynamic capability view to strategic management literature, there is also been critique on the paradigm. The concept has been criticized for being vague and difficult to operationalize. There is lack of agreement on what is an ordinary or dynamic capability in relation to the environmental context (Zahra, 2006). The way dynamic capabilities have been researched make it difficult to separate the capabilities from its effect and therefor lacks direction (Priem and Butler, 2001). The theory lacks theoretical grounding because it does not allow for “lawlike generalizations” (Priem and Butler, 2001). Arend & Bromiley (2009) argue that the value added to existing concepts is limited because of the lack of coherent theoretical foundations, weak empirical support, and unclear

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3. Theoretical Framework

The key to long term success is continued alignment of the firm with its changing

environment. Firms need to adapt their BM to ensure environmental fitness. Business model innovation is an important process to establish this. Business model innovation is the process of discovering, designing and modifying the firm’s extant activity system in which it builds on the BMs capacity to integrate all of the firms BM elements, its external environment and its interfaces with customers and partners (Amit and Zott, 2010). Firms need dynamic capabilities to pursue business model innovation. Teece et all (1997) identified dynamic capabilities as necessary to keep the firm aligned with the changing environment. Research of the last few years has focused on identifying specific dynamic capabilities in relation to, for example, product innovation, process innovation, organizational learning, alliances and also business model innovation.

Mezger (2014) developed an capability-based framework on how firms systematically engage in business model innovation. He studied the relevant processes and routines practiced by firms engaged in innovating their BM. He identified that dynamic capabilities lie at the core of business model innovation:

1. Sensing: The capability to identify opportunities for new business models. 2. Seizing: The capability to systematically convert new knowledge into shaping the

business model designs to address such an opportunity

3. Reconfiguration: The capabilities to adapt the resources, knowledge base and business-model specific activities across the value chain.

Furthermore he highlights the relevance of organizational learning

Sensing Seizing Reconfiguring

Learning driven approach

Market, Technology and BM sensing: The ability to translate market, technology opportunities to new BMs Recombining technology, market and BM knowledge with innovation focus on the BM level as a whole. Selection and sourcing of core competences and resources

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18 Figure 2. own illustration

Mezgers’ (2014) framework is supported by the work of Eppler et al (2011), Doz and Kosonen, (2010), Achterhagen et al (2013) and Leigh (2014), who all identify these

capabilities to be relevant to business model innovation. Therefor it is a suitable starting point for this study. Sensing capabilities identify a misfit between the current BM and the

environment. Seizing capabilities support change to realign the BM to its environment.

Reconfiguring capabilities guarantee the continuous evaluation of the BM to keep it aligned to the business environment. These capabilities are built by organizational learning. Hence business model innovation indirectly benefits from organizational learning. Additionlly discretionary slack is introduced as an organizational antecendent supporting sensing, seizing and reconfiguring capabilities and therefor indirectly positively influencing business model innovation.

3.1 Sensing capabilities and business model innovation

The identification of new business opportunities is a crucial first step and capability in

business model innovation (Eppler et al 2011), (Doz and Kosonen, 2010), (Achterhagen et all, 2013). This capability is similar to sensing from the dynamic capabilities view. It is about processes in which the business environment of today and tomorrow is systematically gathered and interpreted. It is important to identify technological, regulatory and behavioral changes in the market and understand their potential impact, and how one could exploit these new technologies and market opportunities. Technological evolution leads to opportunities for new BMs as shown by the rise of e-commerce BMs. Most business models in a certain

industry are based upon a particular set of constraints. When one of these constraints disappears or new ones arise, this often creates opportunities for new business models (Johnson, 2010). In addition Mezger (2014) showed that firms with a high level of technical know-how are better at identifying these business opportunities. This know-how leads to high “technical sensing capabilities” which enable firms to systematically identify BM

opportunities arising from technological advancement. Another aspect of this capability is knowledge of BMs and the current BM (Giesen, 2007). Firms need to have deep insight in the current BM. This entails knowledge about how the model creates value and what the role is in

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19 the ecosystem. In other words, its relation to customers, competitors, suppliers and customers. Knowledge of BMs is important to understand the impact of different models.

Within sensing activities, two search mechanisms can be identified (Nelson & Winter, 1973). The first search mechanism is the incremental search. This is searching within the current domain of knowledge of the firm. The traditional way of gathering knowledge is via

development inside the own R&D department. Nowadays more firms are outside-in oriented. The firms network is involved to absorb information about changes in the ecosystem.

Examples of this involvement is cooperation with suppliers, complementors and customers. This could lead to co-development of co-production. The second search type is searching outside the current knowledge domain of the firm. This means searching in other industries and new technological domains. This type of searching adds variety to knowledge repertoires. This search type is also important in identifying competitive threats coming from other

industries, known as interindustry competition. Business model innovation can often lead to the entrance in new markets. Therefor business model innovation of competitors from outside the industry boundaries can lead to new competitive threats.

Additionaly Teece (2010) stresses the importance of understanding the customer and the value that the BM can deliver. Increasingly, understanding customers, markets, channels and competitors is needed to create value. One needs to distil fundamental truths about customer desires, customer assessments, the nature and likely future behavior of costs, and the

capabilities of competitors when designing a commercially viable business model (Teece, 2010).

Hence, frims with strong sensing capabilities are able to identify relevant changes in the business environment, that provide opportunities for new BMs or/and threats to the current BM. Therefor the following hypotheses is formulated:

Hypotheses 1 Sensing capabilities have a positive effect on business model innovation

3.2 Seizing capabilities and business model innovation

The identification of new business opportunities does not necessary lead to new business models perse. Seizing capabilities allow these insights to be translated to new business model

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20 configurations (Mezger, 2014). Seizing capabilities are about the design of and

experimentation with new BMs.

BM design demands choices related to technology, market segments, revenue models, bundles vs unbundled strategies etc. New business models emerge from the combination of new technological knowledge, new customer knowledge and knowledge about BM

configurations. It is necessary to combine these knowledge domains to successfully design new BMs. This means that firms asses all BM components and possible configurations instead of focusing solely on product offering or core processes. A firm can construct a blueprint to visualize the new BM. There are different blueprints or constructs available like the Business Model Canvas (Osterwalder et al, 2011). This modelling approach provides a pro-active way to actually “play” with alternative business models, by enabling firms to simulate various possibilities (Chesbrough, 2010). Knowledge about BM configurations is important because BMs from other industries can be very suitable to address new business opportunities. The razor and blade BM from Gilette has been copied by many firms in

different industries. Related to the BM design are the boundaries of the firm. When designing the business architecture these are crucial. It relates to the following questions. How do we protect our innovations and capabilities? Where do we outsource or integrate, what network externalities are relevant?

Seizing capability also entails experimentation, testing processes and finally the adaptation of the firms activities, structures accordingly. This means reconsidering the value chain, building and re-evaluating the resource and competence set. This is a risky process as it is very

complex to determine which resources and competences are valuable and represent a core asset to the new BM. Testing a new business model in the marketplace requires significant investment. The firm is faced with investment decisions regarding when, where and how to invest. With the co-existence of the current and the new model, starts the competition for resources. Often leading to resistance towards the new business model. Managers might resist if the new business model threatens the value of their department. Topmanagement has to manage this resistance. Johnson (2010) argues that it is best to start the new business model in a separate business unit.

Firms that are strong in designing new BMs and experimentation with new BMs, thus show strong seizing capabilities are more likely to succeed in business model innovation.

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21 This argumentation leads to the following hypothesis:

Hypothesis 2: Seizing capabilities have a positive effect on business model innovation

3.3 Reconfiguring capabilities and business model innovation

Reconfiguring capabilities ensure the continues adaptation of the firm to the changing

environment. Therefor these capabilities are about continuously evaluating the environmental fit. The BM, assets, processes, resources are evaluated in relation to the business environment to ensure a logic fit. Firms with these capabilities are open to the fact that they can become obsolete and acknowledge the need for change. The activities that made them successful in the past, may not fit the changing external environment. Reconfiguring capabilities are necessary to ensure internal and external fit. External fit ensures consistency between choices regarding the BM and the external environment. If environmental conditions change, the model may require adaptation. For example a BM with high operating leverage, high margins, moderate volumes and fixed revenue sources may see margins erode due to changes in the competitive landscape. The BM then becomes untenable as the economics don’t match the BM anymore.

Internal fit is concerned with consistency and reinforcement within and between the components of the business model. Each component affects the other components. Reconfiguring capabilities are also necessary for the actual reconfiguration of assets,

processes, resources. They are related for example to reorganizing the organization, design of information flow systems, enhancing a change culture. Business model innovation requires redeploying human, physical and capital resources in a sense that they are able to serve for new value creation purposes (Zott and Amit, 2010). Hence reconfiguring capabilities are needed to pursue business model innovation.

Hypothesis 3: Reconfiguring capabilities have a positive effect on business model innovation

3.4 Learning orientation and business model innovation

Dynamic capabilities have been found to develop via knowledge and organizational learning (Teece, 2007). On the other hand are learning processes, mechanisms, routines, when

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22 firm builds these learning capabilities over time. Learning capabilities enable knowledge of the individual level to transfer to the organizational level. Various types of learning processes are important predictors of the capability base in the future. There are several learning

processes. Absorptive capacity is specifically highlighted in the business model innovation context (Mezger, 2014).

Absorptive capacity

Firms can not only rely on internal knowledge. External knowledge plays an increasingly important role. The learning processes by which external knowledge is integrated in the firm, is referred to as absorptive capacity. This supports firms in turning external knowledge into commercially viable innovations. Absorptive capacity can be identified as an organization outside-in information processing capability (Berghman et al, 2012). Absorptive capacity can be conceptualized by various distinctions. Potential absorptive capacity describes the capability to identify and acquire useful external knowledge. Realized absorptive capacity refers to the capability to exploit external knowledge for commercial purposes. In the innovation literature absorptive capacity has been identified as an independent variable explaining innovation as an dependent variable. The variables are linked by an efficiency factor. The higher the efficiency factor the higher the innovation performance resulting from absorptive capacity (Gebauer et al, 2012).

Absorptive capacity can also be conceptualized by three sequential learning processes: - Exploratory Learning; identification and acquisition of external knowledge

- Exploitative Learning: interpreting, understanding and applying the external knowledge - Transformative Learning: combining existing knowledge and newly generated knowledge in a systematic and structural way. The new knowledge is integrated in the organizational

knowledge by procedural mechanisms.

Gebauer et al (2012) have shown that these learning processes play a key role in business model innovation. This relationship builds on the fact that absorptive capacity is positively related to pro-active behavior. It is related to reconfiguration of new knowledge and it enhances the identification of new opportunities.

Learning processes therefor are a predictor of the capability base in the future. Learning orientation has been identified to positively affect the development of sensing, seizing and

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23 reconfiguring capabilities. This study proposes that the benefits of Learning to business model innovation are mediated by sensing, seizing and reconfiguring capabilities.

Hypothesis 4A: Learning orientation has a positive effect on sensing capabilities Hypothesis 4B: Learning orientation has a positive effect on seizing capabilities

Hypothesis 4C: Learning orientation has a positive effect on reconfiguring capabilities Hypothesis 4D: Sensing capabilities mediate the effect of Learning orientation on business model innovation

Hypothesis 4E: Seizing capabilities mediate the effect of Learning orientation on business model innovation

Hypothesis 4F: Reconfiguring capabilities mediate the effect of Learning orientation on business model innovation

3.5 Discretionary slack and business model innovation

This study focuses on discretionary slack, defined as “a pool of resources in an organization that is in excess of the minimum necessary to produce a given level of organizational output” (Nohria and Gulati, 1996). Discretionary slack refers to resources that managers perceive to be available for discretionary use, in that they are not committed to specific organizational activities or contexts, but instead are unabsorbed and available for alternative uses. Slack is one of the key determinants of innovation (O’Brien, 2003).

Firms face many challenges, from an obsolete BM to day to day problem solving. The day to day problem solving or “fire fighting” is necessary to ensure the short term survival of the firm. Whereas business model innovation is a more continues process related to the long term survival of the firm.

Firms that are resource constraint tend to focus on day to day problem solving to survive. These activities show their direct return. The activities related to sensing, seizing,

reconfiguring and business model innovation do not show their direct return. Therefor the are perceived as high risk. Additionally the activities related to sensing, seizing, reconfiguring and business model innovation require significant investment in time, human and financial resources (Troilo et al, 2014).

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24 Business model innovation is overall a costly practice (Chesbrough, 2010). Discretionary slack helps the firm to cope with high risk by offering a cushion in resources. Slack resources help firms cope with discontinuities and change. Therefor Slack resources are necessary to undertake business model innovation.

Sensing is a high risk activity since the outcome of the activity is hard to predict. Search activities may or may not lead to the identification of new business opportunities. Their effectiveness is hard to measure. Often the investment in these search activities cannot be directly justified in their return to their firm. Their returns will only be visible in the long term. Especially searching outside the current knowledge domain is extremely difficult and costly (Teece, 2007). Thus sensing activities entail high risk and uncertain returns. Firms that suffer from resource scarcity, or in other words have few slack resources, focus more on efficiency and managers tend to be more risk averse (Troilo et al, 2014). Their efforts are aimed at short term survival and thefore they focus more on direct problem solving than sensing the business environment to explore new markets and technologies (Troilo et al, 2014). The benefits of sensing activities will be visible on the long term. Troilo et al (2014) state: “Slack encourages search activities that cannot be justified in terms of their expected return for the organization”. Therefor firms with slack resources are more like to practice sensing than firms with resource scarcity. In addition it is the realized insights gained with sensing that lead to business model innovation. The influence of discretionary slack on business model innovation is therefor mediated by sensing. The benefits of discretionary slack are transferred to business model innovation via sensing. Discretionary slack facilitates business model innovation by allowing slack search. This leads to the following hypotheses:

Hypothesis 5A: Discretionary slack has positive effect on sensing capability

Hypothesis 5B: Sensing capability mediates the relation of discretional slack on business model innovation

Seizing entails experimentation, designing and building new BMs. Slack positively contributes to creativity. Creativity is necessary to perform innovation. Creativity leads to creative business solutions and challenging the routine way of doing things. Slack favors creativity because employees and managers are more open to risky propositions and untried ideas. Slack relaxes managerial control (Nohria and Gulati, 1996).

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25 The legitimacy of experimentation is less questioned. It enables employees to spend more time on innovative and high risk projects (Nohria and Gulati, 1996). The experimenting process involves costs. These the cost of conducting the test, both in terms of the direct cost, and in the cost of failure if the experiment does not yield the hoped-for learning, the time required to obtain feedback from the experiment and the amount of information learned from the test (Mcgrath, 2010). Discretionary slack helps the firm to cope with these costs by offering a cushion in resources.

Creativity and experimentation are crucial elements is the design of new BM configurations and therefor for the activities related to seizing capability (Mezger, 2014). Discretionary slack benefits business model innovation by allowing experimentation and creativity as a part of the seizing capability. Therefor firms with slack resources are more like to practice seizing than firms with resource scarcity. In addition it is the benefits realized with creativity and experimentation as a part of seizing capabilities that lead to business model innovation. The influence of discretionary slack is therefor mediated by seizing capabilities. The benefits of discretionary slack are transferred to business model innovation via seizing capabilities. This leads to the following hypotheses:

Hypothesis 5C: Discretionary slack has positive effect on seizing capability

Hypothesis 5D: Seizing capability mediates the relation of discretional slack on business model innovation

The reconfiguration phase requires co-existence of the current and new model.

Reconfiguration of the BM often demands the development of new resources, competences and capabilities and shifting resources to the new model. Hence here starts the competition for resources. This often leads to resistance towards the new model. Resistance towards

reconfiguring the resource base has been identified as one of the most important barriers of business model innovation. In practice it means transferring resources from the existing BM towards the new BM. Knowing when to shift resources from the old to the new model is difficult. The existing BM provides stable and positive cash flows. The investment risk can be based on the historical track record of the BM. Whereas the new BM needs high investments and suffers startup losses and the outlook is uncertain. The new BM needs time for growth, to allow the market opportunity to unfold. Johnson, Chistensen, Kagermann (2010) stress the

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26 importance of patience and remark that building new BM’s is a long term effort. The

investment return of implementing the new BM is uncertain and often delayed. Therefor it can be considered as a high risk activity. Discretionary slack is known to help firms to cope with high risk by offering a cushion in resources.

Restistance towards reconfiguring the resource base also lies in organizational conflict. The manager of the physical store department is likely to resist transferring resources from his department to setting up a new department based on online-sales. Discretionary slack reduces organizational infighting and conflict. Slack allows managers to give more discretion as to how the resources are to be used (Nohria and Gulati, 1996).

Lack of additional resources undermine the ability to reconfigure the BM. To protect the new BM from resource starvation, Chesbrough (2007) argues to put a separate pool of cash aside to finance new BMs. The firm needs a cushion in resources to enable business model

innovation. In other words it needs slack. This highlights the necessity of resource availability to undertake reconfiguring activities. Discretionary slack protects the new BM from resource starvation.

Therefor firms with slack resources are more likely to practice reconfiguring activities than firms with resource scarcity. In addition it is the benefits gained with reconfiguring that lead to business model innovation. The influence of discretionary slack is therefor mediated by reconfiguring capabilities. The benefits of discretionary slack are transferred to business model innovation via reconfiguring capabilities. Discretionary slack facilitates business model innovation by allowing reconfiguring activities. This leads to the following hypotheses:

Hypothesis 5E: Discretionary slack has positive effect on reconfiguring capabilities Hypothesis 5F: Reconfiguring capabilities mediate the relation of discretional slack on business model innovation

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27 Based on this argumentation, the following conceptual model is build:

Figure 3. BMI Sensing Seizing Reconfiguration Learning orientation Discretionary Slack

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4. Methodology

This chapter explains the research design. First the research method will be discussed, followed by the sample. The chapter closes with the strengths and limitations of the chosen research design.

4.1 Research design

The purpose of this study is to give insight in the relevant capabilities needed to pursue business model innovation and the role of discretionary slack. The generalizable conclusions of this study contribute to the literature on dynamic capabilities and business model

innovation. The central question is: What is the effect of sensing, seizing, reconfiguring and learning capabilities and discretionary slack on business model innovation. The research approach of this thesis is deductive research. Previous theories from the literature are tested to answer the research question. The developed hypotheses, based on prior literature, are tested with quantitative data. This research is based on a positivism philosophy. It is an explanatory study. The research method is ‘Survey’ and will be discussed in the following section.

4.2 Survey

The data was collected by an online survey. Because this study is based on a single data collection method it is a mono method study. The survey is a suitable method for explanatory studies. It is a relatively economical and fast way to collect data. There has been chosen for the online survey, because of the limited resources and time. The data was collected according to the following steps:

1.Building conceptual model

To answer the central question, a conceptual model and hypotheses were developed, based on prior literature. The conceptual model consists out of the following variables: Discretionary slack, Learning Orientation, Sensing capability, Seizing capability, Reconfiguring capability and business model innovation.

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29 2.Operationalizing variables

Based on prior research the relevant measures and scales are defined to operationalize the variables. By using measures and scales from previous studies the criteria for reliability and validity are met. The used measures, scales and their source can be found in Appendix I.

As business model innovation may be influenced by other variables, control variables were added. The following control variables are added to the model: firm age, firm size (in number full time employees), industry and market turbulence.

The history of a firm determines its path dependency. The routines, processes and culture are created to cope with its environment. Often older firms rely more on path dependent routines than young firms due to their short history. Firm that rely strong on path dependent routines have more difficulty in adapting their organization. Market turbulence influences the rate a which one needs to innovate. When the market is turbulent firms are more challenged to pursue environmental fit.

3.Development of questionnaire and cover letter

The online questionnaire was built using Qualtrics. A pre-test was conducted to make sure the introduction in the cover letter and the questions were clear. 5 respondents took place in the pre-test. The pre-test led to small adjustments in the questionnaire.

4.Survey distribution

The survey was distributed among the sample. The sample will be discussed in the section below.

4.3 Sample

The population of this study are small and medium sized enterprises, from all industries, located in the Netherlands. Start-ups are excluded. Previous research has shown that start-ups and incumbents differ in their approach to business model innovation. This study focuses solely on incumbents. Therefor firms existing less than one year are not included in the sample.

A non-probability sampling technique called convenience sampling was used to select a sample to collect data. Due to the time restrictions of this research this sampling technique has been selected because it allows for easy and fast access (Kwak and Radler, 2002).

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30 Respondents were self-selected from personal network. Using personal network is easier and increases the willingness to participate (Teddlie and Yu, 2007)

The participation criteria are: - Group turnover is 0-500 million

- Headquarters is located in the Netherlands - min of 1 year existence

- respondent is CEO or general manager -CEO/general manager is mayor shareholder

There is a focus on the CEO or general manager as respondent, because in general this is the person overseeing the strategic issues. The respondents will be motivated by offering a summary of this study and a free workshop Business Model Bootcamp on how to innovate your BM. Invitations to participate in the survey were send through email.

4.4 Strengths & limitations of the research design

The strength of the method “online survey” is that it allows easy and fast access to data (Kwak and Radler, 2002). The online survey was distributed online and invitations were send personally by email. One advantage of the online survey is that respondent can fill in the survey to their convenience. This enhances response. Therefor it was realistic to gain and analyse the data within the timeframe of this study. There are also limitations to take in consideration. The first limitation is the risk that the survey is completed by respondents for whom the survey is not meant (Evans and Mathur, 2005). The survey is meant for CEO/ general manager, there is a risk that the respondent delegates the survey completion to a third person. This risk has been reduced by sending the survey to the personal emailadres of the respondent. Additionally there is a control question in the survey assessing the functional level of the respondent. The second limitation is that respondents are forced to answer in limited choices (Evans and Mathur, 2005). Thirdly, the questions in the questionnaire can be misunderstood (Evans and Mathur, 2005). A test was conducted. The feedback of the pre-test was used to clarify the topics and tweak some of the questions.

The sample is collected by non-probability sampling, gathered by the personal network. This method is susceptible to selection bias (Lucas, 2014). Therefor the sample could not

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31 represent the population very well. and thus the population is not well represented. This bias could exist due to a homogenous network (Lucas, 2014).

The data is collected at one point in time. Therefor changes in the capabilities cannot be measured. This would be interesting as business model innovation is a process that takes time. The sample consists of SME’s, where start-ups are excluded. Start-ups and large sized differ in many aspects of SMEs. This could influence the generalizability.

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5. Results

The survey was sent out to 435 firms. Data was obtained by 110 respondents. Resulting in a response rate of 25%. The non complete files are removed from analyses, resulting in 103 complete files. One of the sample criteria is that the respondent is CEO or top management. Although the survey was send to the personal email accounts of the respondents, a control question was added to the survey to ensure this criteria. The survey starts with the question: What is your employment level? Respondents with an employment level other than CEO or top management are excluded from analysis. The reliability of the data is further evaluated by the survey duration. The survey duration varies between 2.05 minutes and 1668 minutes. There are serveral surveys with a duration > 20 minutes. Although this indicates that the respondent didn’t complete the survey at once, the surveys are all fully completed and therefor not deleted. Futhermore the data set is checked for extraordinary responses. In total 71 cases are used to analyze the dataset.

5.1 Description of the sample

The sample can be described using the control variables. Most firms in the sample, 37%, are between 16 and 50 years old. 65% of the firms is older than 15 years and 18% is older than 50 years. Therefor the firms in the sample are relatively old. BMs need to change over time to stay successful. Therefor it can be assumed that relatively old firms have changed their BM in the past.

The size of the firm is measured in full time employees (FTE). There is a good distribution among smaller and larger firms. A little more than half (58%) of the firms in the sample is smaller than 100 (FTE) and the rest is larger than 100 FTE. 40% of the firms in the sample have between 0-50 employees.

The sample can be divided by industry, identifying for 13 industries. The industries

wholesaling, retail and service industry are most represented by respectively 14, 20 and 16 respondents.

Half of the respondents identify their market as slowly growing. Of the other half, most identity their market growth to stagnate or decrease. Only 6% of the respondents are active in

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33 a high growth market.

5.2 Reliability Analysis

To answer the central question of this study, six variables were measured. To assess the reliability of these variables a Cronbach’s Alpha test is conducted and the distribution of the variables is checked for normality. All variables were measured with several measurement items. The Cronbach’s Alpha test checks the consistency of these items with regard to the variable. A Cronbach Alpha above 0,7 indicates a good reliability. When the required minimum Cronbach Alpha of 0,7 was met, a rounded mean of the associated items was computed. Finally descriptive statistics were used to test for normality. Normality can be assumed when the mean is close to the median and when skewness and kurtosis levels are near 0.

The dependent variable business model innovation was measured with five items on a 7 point likert scale. The Cronbach Alpha of 0,802 indicates a good reliability. The reliability could increase to 0,809 if item “cost structure” was deleted. A Cronbach Alpha of >0,7 is

considered as a minimal standard, which is met. The increase of the Cronbach Alpha of 0,007 is too small to justify deleting this item. The high Cronbach Alpha justifies computing a rounded mean. The rounded mean is 4,1183. Therefor the average answer to the five items measuring business model innovation on a 7-point likert scale was “neutral”. Therefor the respondents identify average business model innovation activities. The distribution for business model innovation is close to a normal distribution. The mean is close to the median of 4,2. There is a slight skewness of -0,248 and low Kurtosis level of -0,363. The skewness and Kurtosis levels are close to 0.

The variable Sensing was measured with seven items on a 7 point likert scale. The Cronbach Alpha of 0,771 indicates a good reliability. If the item “new products and services” is deleted, the Cronbach Alpha would rise to 0,79. This increase is too small to justify removal. The high reliability justifies computing a rounded mean. The rounded mean is 4,6031. On average the firms from the sample answer “somewhat agree” to the seven items measuring sensing activities. Therefor the firms show moderate sensing capabilities. This variable shows a

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34 normal distribution. The rounded mean is close to the median of 4,714. The distribution is slightly skewed with a skewness of -0,43. The Kurtosis level is low with -0,064.

The variable Seizing is measured with five items on a 7-point likert scale. There is a high Cronbach Alpha of 0,892. The Cronbach Alpha could increase to 0,895 if the item “able to implement big changes” would be deleted. Due to the high reliability and relatively low increase of reliability, this item is not deleted. Therefor a rounded mean can be computed. The mean of Seizing is 4,8995. Therefor the average answer to the items measuring seizing capabilities was “somewhat agree”. The firms from the sample show moderate seizing

capabilities but more than sensing capabilities. The mean is close to the median of 5,200. The distribution is slightly skewed with -0,402. The Kurtosis level is low with -0,439. Therefor the distribution is close to normal.

The variable Reconfiguring is measured with eight items on a 7-point likert scale. This variable shows a Chronbach Alpha of 0,887. Deleting items does not enhance the Cronbach Alpha. This variable also has a high reliability which justifies computing a rounded mean. The rounded mean is 5.3128 and therefor higher than the variable Sensing and Seizing. The firms from the sample show stronger reconfiguring capabilities than sensing and seizing. The distribution is close to normal. The mean is close to the median of 5,375. Also this

distribution is slightly negatively skewed with -0,584. The Kurtosis level is close to 0 with 0,465.

The independent variable Discretionary slack is measured with three items on a 7 point likert scale. The Cronbach Alpha is 0,716. This seems low compared to the previous computed Cronbach Alpha’s, but a 0,716 is still above 0,7 and therefor sufficient reliable to compute a rounded mean. The Cronbach Alpha would increase to 0,763 if we deleted the item “slack in assets”. Since there are only three items, measuring Discretionary slack and the minimal required score is met, there was chosen not to remove this item. The mean of the variable is 4.4836. Therefor in general respondents find that they have somewhat slack. This score is lower than the scores on the dynamic capabilities Sensing, Seizing and Reconfiguring. Also this variable is normally distributed with low skewness and Kurtosis levels of respectively -0,364 and -0,543.

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35 The independent variable Learning is measured by three items on a 7 point likert scale. The Cronbach Alpha is 0,893. This outcome is far above the minimum of 0,7. This indicates a good reliability. Deleting one of the items would not enhance the Cronbach Alpha. The

rounded mean is 5,3765. Of all measured capabilities this capability has the highest score. The respondents identify strong learning capabilities within their firm. The outcomes of the

variable is normally distributed. The mean is close to the median of 5,333. Also this variable is slightly skewed with a skewness of -0,77. The Kurtosis is 0,65. Therefor both skewness and Kurtosis levels are low supporting normality.

5.3 Correlations

The statistical relationship between the variables can be analyzed with correlation. The correlation coefficients between the variables and their significance are shown in the table below.

Tabel 7. Correlation Matrix

1 2 3 4 5 6 BMI Sensing ,406** Seizing ,234* ,613** Slack 0,157 ,343** ,259* Reconfiguring 0,146 ,661** ,599** ,254* Learning 0,208 ,364** ,439** 0,167 ,447**

**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).

There is a positive correlation between business model innovation and Sensing. The correlation is moderate strong with a correlation coefficient of 0,406 and significant at the 0,01 level. The correlation between Seizing and Business Model Innovation is positive and moderate, and significant at the 0,05 level. This means that if Sensing capabilities increase or if Seizing capabilities increase business model innovation increases as well. This is conform the literature and the hypotheses. The relationship between Sensing and business model innovation is the strongest of the two due to the highest correlation coefficient (0,406) and the highest significance (0,000).

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36 There is also a positive correlation between Reconfiguring and business model innovation, but the correlation is weak (0,146) and not significant. The correlation between Discretionary slack (0,157) and business model innovation and Learning (0,208) and business model innovation is also weak and not significant

Discretionary slack does show a positive and significant correlation with Sensing (0,343), Seizing (0,259) and Reconfiguring (0,254). The relationship with Sensing is significant at the 0,01 level, the relation with Seizing and Reconfiguring is significant at the 0,05 level.

Therefor the relationship with between Discretionary slack and Sensing is the strongest of the three capabilities. The correlation between Discretionary slack and the three dynamic

capabilities is moderate but significant. This means that more Discretionary slack leads to higher effectiveness of the dynamic capabilities sensing, seizing and reconfiguring. This is conform the hypotheses.

Learning also shows a positive and significant relationship with all three dynamic capabilities. The correlation is moderately strong with 0,364 for Sensing, 0,439 for Seizing, 0,447 for Reconfiguring. The correlation is for all three dynamic capabilities significant at the 0,01 level. This supports the theory and the hypotheses. This means that higher learning capabilities leads to higher effectiveness of the capabilities Sensing, Seizing and Reconfiguring capabilities.

5.4 Regression Analysis

A regression analysis is performed to test the model and test hypothesis 1,2 and 3. Two models are compared. Model 1 consists out of the control variables as independent variables. The second model computes the regression analysis with the control variables and Sensing, Seizing and Reconfiguring.

A capability-based approach to Business Model Innovation and the role of discretionary slack