An empirical analysis of performance implications of different business models

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An Empirical Analysis of Performance Implications of

Different Business Models

Student: Zarnishan Mansimova – 11386533

MSc. in Business Administration - Strategy Track

Supervisor: Dr. S. Von Delft

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Statement of Originality 

This document is written by student Zarnishan Mansimova, 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.

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ABSTRACT

The implications of business model choice for firm performance have received significant attention from the scholars. However, the studies do not fully address these implications since many of them along with employing different definitions of the business model concept, have focused on entrepreneurial firms or specific industries. Therefore, there is a shortcoming with regards to generalizable understanding of the performance effects of business models and the business model performance relationship of incumbent firms. We tried to address this shortcoming by analyzing a set of publicly traded incumbent companies operating in different industries. Morris, Allen, Schindehutte framework was used to identify different generic business models employed by the firms in our sample. The target sample consisted of 142 publicly listed on Euronext Amsterdam and Brussels. This study did not find a statistically significant relationship between a business model and a firm performance. Implications are far reaching, since a particular business model does not yield a superior financial performance, future research should shift its focus in a number of different directions such as implementation of business model, interaction of business model with environmental factors, life-cycle of a business model, etc. From a managerial perspective, this study implies that in order to improve the firm performance, management should not solely focus on a change of business model or should not directly relate underperformance to a poor business model choice.

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1. Introduction

Business model is generally defined as the logic of how firms create and capture value from products and services they offer (Teece, 2010, Casadesus-Masanell and Ricart, 2010, Johnson et al., 2008). The concept has received significant attention not only in practice, but also in literature (Wirtz et al., 2016). The surge of studies on the business model concept, corresponding with the emergence of internet firms, is not a coincidence. Advances in technology have changed the balance of the customer-supplier relationship, as these developments have provided customers with more choices and transparency about the availability of these choices. These changes have led managers to rethink not only how they address different customer needs, but also how they appropriate value (Teece, 2010). As a result, the business model concept has become an appealing topic for strategy scholars, as it offers new options for creating and capturing value in dynamic and uncertain environments (Mc Grath, 2010).

Business models play a crucial impact on a firm performance (Zott et al., 2011). If well designed, a business model provides a firm a competitive advantage (Afuah and Tucci, 2001) (Casadesus- Masanell, and Ricart, 2010). Wal-Mart, Dell, and Apple are well-known examples of companies that achieved superior performance and outperformed their rivals by employing more effective business models (Johnson et al., 2008). For example, when Apple started selling the iPod, bundling it with the iTunes music store, it disrupted the market. Soon this combination accounted for almost 50% of Apple’s revenue, even though the company was not the originator of digital music players.

Although these examples provide anecdotal evidence, and observations by scholars generally agree on importance of the business model for firm performance, the direct link between business models and firm performance has not been fully addressed by researchers. To date, no

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extensive empirical analysis on such a link has been performed (Zott and Amit, 2007). The understanding of the business model to performance relationship remains highly context specific (Teece, 2010). This can be related to several reasons, such as the relative novelty of the concept in the strategy literature, the multi-theoretical nature of the concept, or the lack of agreed definition and components (Wirtz et al., 2016, Morris et al., 2006), all of which hinder our ability to measure the concept in a unified way (Morris et al., 2006).

Many studies have focused on certain types of business models, especially on e-commerce firms and entrepreneurial firms (e.g. Afuah and Tucci 2001, Zott and Amit, 2007). Therefore, to further expand the field of study, we look into the relationship between the business model of incumbent firms and their financial performance. This is an important shortcoming in the literature, as incumbent firms play a critical role in every economy and industry. Established companies dominate the global economy, with 10% of the world’s established public companies delivering 80% of all profits. Companies with more than $1 billion in annual revenue generate nearly 60% of global revenues, and comprise 65% of market capitalization (Economist, 2016, September). Analyzing the set of incumbent firms would bring valuable insight to how business models are defined for a large portion of the economy, and whether the choice of business model results in a superior financial performance. Moreover, some previous studies (e.g. Suarez, Cusumano & Kahl, 2013; Patzelt, Knyphausen-Aufseb & Nikol, 2008) have focused on certain type of firms that specialize in one area and employ a firm-specific definition of business models. This, we believe, further hinders ability of these studies to shed light on business model

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What are the performance implications of different business models?

In order to define business models utilized by incumbent firms, we adopt the Morris, Allen, and Schindehutte (MSA) framework introduced by Morris et al. (2005). The MSA framework comprehensively defines business models as a set of six decision areas, including value proposition, market, internal capabilities, competitive strategy, economic factors, and personal/ investor factors. This framework is then applied to a set of companies (142 in total) listed on the Euronext Amsterdam and Brussels exchanges. In total, four generic business models were defined. These business models are then matched with the financial data in order to address the research question.

After running a series of regressions, while at the same checking the robustness of the results, we did not find any statistically significant relationships between business models and firm performance. Regardless, this study makes several contributions to the literature. Firstly, by focusing on the performance effects of business models of incumbent firms, this paper provides insights on what type of business models these firms utilize. As was previously mentioned, incumbents are important part of global industries, therefore these insights are valuable for the business model, strategy, and business literature in general. Secondly, this paper further contributes to business model literature by conducting empirical research that focuses on different types of firms operating in various industries. This is a valuable contribution, since previous studies have mainly focused on e-commerce firms or on certain types of firms, which have provided more context specific understanding of the topic and have hindered generalizability of the study results for different type of firms and business models. Finally, the result of this study implies that future research should switch its focus in a number of different directions, such as the implementation of business models, the interaction of business models

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with environmental factors, the life-cycle of a business model, etc.

The rest of the paper is divided into four sections. Firstly, we review the relevant literature on business models, and the business model-performance relationship. Secondly, we discuss our research design, sample, measurement, and methods. Thirdly we present the results of the analysis. In the final section, we discuss the implications of the results, explain limitations of the study, provide directions for future research and conclude with some final thoughts.

2. Literature Review

2.1. Business model definition

All firms explicitly or implicitly operate a business model (Teece, 2010), however business models have only recently become the focus of both researchers and practitioners (Zott et al., 2011). Despite a fair number of studies, the literature on business models lacks an agreed definition of the concept by scholars (Zott et al., 2011; Teece, 2010). A uniform approach to the concept is still developing (Wirtz et al., 2016). However, generally, a business model is defined as the logic based on which a firm creates and captures value from the products and services they offer (Teece, 2010, Casadesus-Masanell and Ricart, 2010, Johnson et al., 2008). This is in contrast to a body of literature which takes a rather pragmatic approach to business models. While some scholars view business models in terms of different processes within a firm or as a business architecture (e.g. Amit and Zott, 2001), the majority of authors (e.g. Casadesus-Masanell and Ricart, 2010, Johnson et al., 2008, Morris et al., 2005, Osterwalder, Pigneur, 2010) emphasize the structure of business models and outline certain components of the concept (Wirzt

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(p. 22). This definition mainly focuses on the value creation part of the business model, however value capture, i.e. making money from the value created, is an inseparable part of the concept (Teece, 2010).

The studies which focus on structure, and explain the components of business models, vary in their approach to the concept and in the content of the components (Wirtz et al., 2016). Johnson et al., (2008), Casadesus-Masanel & Ricart (2010), and Baden-Fuller, & Mangematin (2013) define business models as consisting of only a few components. Conversely, Osterwalder & Pigneur (2010) and Morris et al. (2005) define the concept more comprehensively as a set of different components.

Johnson et al. (2008) argues that a business model consists of four elements: the customer value proposition, the profit formula, key resources, and key processes. These elements together comprise a business model, and subsequently combine to create and capture value. Baden-Fuller & Mangematin (2013) also offers a typology of the concept that consist of four elements, with two of them (customer value proposition and profit formula) being similar to those in the Johnson et al. (2008) definition. Specifically, the Baden-Fuller & Mangematin (2013) typology of business models includes customers, customer engagement, monetization of customer value, the value chain, and linking mechanisms of actors in the value chain. The authors argue that each of these elements are linked to either value creation, value capture, or both. Although these definitions are valuable, especially in terms of providing a general picture of the concept, a more detailed explanation what a business model should include seems more useful, since it will not neglect critical dimensions of the concept (Wirtz et al., 2016) This kind of definition will also enable us to establish dynamic links between the components of concept, as well as with other elements of the firm, such as competitive advantage and firm performance. Therefore, building

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on this argument, for the purpose of our study we adopt the MSA framework introduced by Morris et al. (2005). The authors conceptualize business models as a set of six decision areas, which include the value proposition, market, internal capabilities, competitive strategy, economic factors, and personal/investor factors. The MSA framework builds upon the previous literature, culminating in a set of questions to characterize each element of the company as described above. The framework provides a comprehensive and measurable set of components of the business model concept, which also enables this framework to be applicable to a diverse group of industries and firms. The MSA framework has also been adapted and empirically applied by Morris et al. (2006) in generating generic business models. The next section explains the framework and its applicability in detail.

2.1.1. MSA framework

As already was mentioned, the MSA framework was first introduced by Morris et. al (2005), building on a number of different elements in the literature. Figure 1 depicts the overall framework, and Table 1 describes the components of each decision area, while also providing instructions for the application of the framework. The six decision areas included in the model are represented in the following questions:

1. How does the firm create value?

This question focuses on the value proposition of the firm. The decisions here concerns selection of the product or service mix, and how the value proposition is delivered to customers. In order to create value, a firm needs to design its value proposition in a way that helps its

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1. For whom does the firm create value?

This question concerns the type and scope of the market in which the firm operates. Who is the customer and where in the value chain does the firm position itself? Customers are at the heart of any business model, and without profitable customers, no firm can be successful (Osterwalder &Yves Pigneu, 2010).

2. What is the firm’s internal source of advantage?

Here, the focus is on the internal capabilities of the firm that underlie its competitive advantage. Capabilities refer to the firm’s ability to perform certain set of activities. Hamel (2001) defines core competencies as an internal capability, or set of skills that the firm performs better than its competitors. Therefore, these competencies are integral part of any business model and crucial for firm success (Applegate, 2001).

3. How does the firm differentiate itself?

This question is concerned with how the firm positions itself in the marketplace. Specifically, the question is focused on the choice of the basis of differentiation that determine the way in which firm competes (Casadesus-Masanel, 2010). The MSA framework includes 5 bases of differentiation: operational excellence, product capabilities (e.g. quality, availability characteristics), innovation leadership, low cost, and intimate customer relationships.

4. How does the firm make money?

This question directly addresses the “value capture” part of business models. To put it differently, it defines how the firm creates value for itself, while delivering value to the customer (Johnson et al., 2008). The MSA framework defines the value capture mechanism of a business model in four dimensions: operating leverage (the extent to which the cost structure is dominated by fixed versus variable costs), the firm’s emphasis on higher or lower volumes in terms of

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market opportunity and internal capacity, the firm’s ability to achieve relatively higher or lower margins, and the firm’s revenue model, including the flexibility of revenue sources and prices.

5. What are the firm’s time, scope, and size ambitions?

Differences among firms are reflected in their competitive strategy, resources and competences, profit model, and economic performance. Therefore, authors also include the entrepreneur’s time, scope, and size ambitions, or what they also termed as the firm’s “investment model”. These models are subsistence, income, growth, and speculation. A firm employing the subsistence model focus only on its survival, and its ability to meet basic financial requirements. The income model involves making investments to the extent that they generate an ongoing and stable income stream for the principals. With the growth model, in order to grow its value, along with significant initial investment, the firm also makes substantial reinvestments. In firms employing a speculative model, the entrepreneur’s main focus is to show the firm’s profit potential with the aim to be able to sell it afterwards.

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Figure 1. The MSA framework: Defining business model (Morris et al., 2005)

Table 1. Application of the MSA framework. Adopted from Morris et al., 2005

1. Value Proposition (VP): How does the firm create value?

(select one from each set)

VP: primarily products/primarily services/heavy mix   VP: standardized/some customization/high customization   VP: broad line/medium breadth/narrow line  

VP: access to product/ product itself/product bundled with other firm's product/service  

VP: internal product or service

delivery/outsourcing/licensing/reselling/value added selling VP: direct distribution/indirect distribution

Business Model Value proposition Market factors Internal capability factors Competitiv e strategy factors Economic factors Personal/ investor factors

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2. Market Factors: For whom does the firm create value?

(select one from each row)

• type of organization: B2B/B2C/both/other  

• market scope: local/regional/national/international  

• value chain: upstream supplier/downstream supplier/ /wholesaler/ retailer/service provider   

• exchange type: transactional/relational  

3. Internal capability factors:

What is the firm’s internal source of advantage?

(select those that apply)

• production/operating systems   • selling/marketing  

• information management  

• technology/R&D/creative or innovative capability   • financial transactions

• supply chain management   • networking/resource leveraging  

4. Competitive strategy factors:

How does the firm differentiate itself?

(select those that apply)

• image of operational excellence/consistency/dependability   • product or service quality/selection/features/availability   • innovation leadership  

• low cost/efficiency  

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5. Economic factors:

How does the firm make money?

(select one from each row)

• pricing & revenue sources: fixed/mixed/flexible   • operating leverage: high/med/low  

• volumes: high/medium/low   • margins: high/medium/low  

6. Personal/Investor factors:

What are the firm’s time, scope, and size ambitions?

(select one)

• income model/growth model/speculative model/subsistence model

2.2. The business model and performance relationship

The business model and performance relationship is one of the areas of research in the business model literature that has received a fair amount of attention by scholars (Wirtz et al., 2016). Business models can be crucial in explaining firm performance (Zott et al., 2011). The survival and prosperity of firms is directly linked to their ability to both create and capture value (Shafer et. al. 2004). As an architecture of value creation, delivery and capture, business models are critical to a firm’s success (Teece, 2010). The same idea or technology taken to market through two different business models will generate different outcomes (Chesbrough, 2009).

Firm performance itself is a result of a two-stage process: value creation, and value capture (Coff, 1999, Mizik & Jacobson, 2003). While value created refers to the amount the customer is willing to pay for the firm’s offering, value is captured when the firm earns more than the costs of creating this value (Porter, 1985). For example, IBM previously created superior value by bringing the most innovative computers to market, however Intel and

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Microsoft were ultimately able to capture much of the profit from this innovation (Coff, 1999). Therefore, it comes as no surprise that the performance implications of business models are linked to the value created and captured through it (Zott et al., 2011). By taking this link into consideration, and integrating MSA framework, Figure 2 illustrates the business model-performance relationship.

Figure 2. The business model performance relationship

Amit & Zott (2001) argue that no single theory is able to completely explain the value creating potential of a firm. Therefore, they conclude that the business model concept, drawing

Firm

Performance

Value Creation

- Value proposition - Market factors - Capability factors - Competitive advantage factors - Personal/Investor factors

Business Model

Value Capture

Economic factors

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(Schumpeter, 1934), transaction cost economics (Williamson, 1975) and strategic network theory (Jarillo, 1995). Morris et al. (2005) argue that the business model concept is grounded on principal underpinnings of business strategy, and they have built the MSA framework on these theoretical perspectives.

Porter’s (1985) value chain framework identifies activities that firm performs, and then studies the performance effects of those activities. The framework helps to determine the activities a firm should perform, and the required configuration of these activities that enable the firm to compete in the industry. The value chain explores the firm’s primary activities, which have a direct impact on value creation, as well as support activities, which affect value only through their impact on the performance of the primary activities. According to this framework, value can be created through differentiating along every activity or set of activities, resulting in products or services that either lower costs or improve performance of offerings for customers. Business model concepts builds upon this framework, since it comprises configuration of activities firms perform, and also includes choices of activities through which firms differentiate themselves (internal capability factors and competitive strategy factors; Morris et al., 2005). According to the RBV, creating configurations of resources and capabilities that are valuable, rare, inimitable, and firm specific may facilitate value creation (Peteraf, 1993, Barney, 1991). The theory argues that firms differ in terms of the resources and capabilities they possess, therefore unique combinations of these resources and capabilities can lead to superior value creation and subsequently competitive advantage. In this sense, business models embody the competencies that contributes to a firm’s competitive advantage, and are consistent with the value creation mechanism identified by the RBV (Morris et al., 2005).

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value creation. New combinations can represent the introduction of new products or services, new methods of production, new markets, new sources of supply, or new ways of industry organization. Consistent with this theory, a business model that embodies unique combinations can create a superior value (Morris et al., 2005). In literature on the business model concept, it has been linked to innovations in two ways (Zott et al, 2001). Firstly, it is viewed as a model through which firms commercialize innovation. Secondly, business models themselves can be a source of innovation by delivering existing products and services in new ways.

In transaction costs economics (Williamson, 1975), reduced transaction costs represent the major source of value creation. The theory generally concerns itself with the choice of an efficient governance form by the firm that minimizes its transaction costs. Therefore, the theory strives to explain the conditions under which a firm should internalize or outsource certain activities. In this sense, through the choices involved in its business model, a firm decides how to set its boundaries efficiently and create more value.

The strategic network theory also sheds some light on the value created through business models. Effective positioning, and trying to create valuable relationships within the larger value network of customers, suppliers, and partners can be an important factor for value creation (Morris et al, 2005).

A firm’s ability to capture the value created can be explained by bargaining power theory and game theory. According to game theory, bargaining power between different actors

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or the cost the buyer incurs by these offerings. Business models, providing a structure of costs and revenues, delineate the firm’s mechanism of value capture (Teece, 2010). In the MSA framework, this ability of business models is captured in the economic factors section (Figure 2, Table 2).

The empirical and conceptual studies completed to date have examined the relationship between business models and performance by focusing on certain types of business models or firms. Some studies such as Afuah & Tucci (2001) and Zott & Amit (2007) have mainly focused on the business models of e-commerce firms. While Afuah and Tucci (2001) conducted a conceptual study, Zott and Amit (2007) empirically examined the relationship between business models and firm performance. In their study, Afuah & Tucci (2001) explore how the advent of internet has led to the surge of internet business models, and how this affected firm performance. The authors define a business model as one of the determinants of the firm performance, basing this argument on the function of the components of a business model and the linkages between these components. In particular, they argue that business models are critical to firm performance, due to them defining the type of value firm offers, the type of customers to who they offer this value, the scope of products and services that carry this value, the pricing of the value, the type of activities and capabilities that create the value, and the strategies that firms can use to maintain a competitive advantage.

Zott and Amit (2007) have examined the performance effects of two different business model design themes - novelty-centered and efficiency-centered design themes of entrepreneurial firms that generate their revenues fully or partly from online transactions. A novelty-centered business model is defined as creating and capturing value in new ways, by employing new ways of conducting economic transactions. An efficiency-centered business model, in contrast, is

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focused on imitating existing economic transactions by conducting them in a more efficient way. The authors argue that the performance of new entrants is highly dependent on the design of boundary-spanning transactions with suppliers, customers, and partners. In order to prove this relationship, they tested how business model design themes, “as the context, content, and structure of boundary spanning transactions” (Zott and Amit, 2007, p. 183), influence the performance of these firms. More specifically, the authors have taken the chosen business model as the independent variable, and linked it to the stock performance of entrepreneurial firms, moderated by the environment. The authors found a significant positive relationship between novelty-centered business models and firm performance. As Afuah and Tucci (2001) note, they also relate this relationship to the value creation potential of the business model design and the firm’s ability to appropriate that value.

Another stream of study on the business model-performance relationship has focused on very specific types of firms and business models (Suarez, Cusumano & Kahl, 2013; Patzelt, Knyphausen-Aufseb & Nikol, 2008). Although these studies frame the business model concept differently by employing different definitions or focusing on certain components, they have found that in certain circumstances, some business models are superior to others. Suarez, Cusumano & Kahl (2013) have examined the relationship between business model choice and the performance of prepackaged software product firms, and found that it depends on the extent to which the business model emphasizes services as a source of revenue. The empirical examination found that software product firms that generate a high majority of their revenue

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result to the accumulation of experience when a firm is focused on certain activities. Patzelt, Knyphausen-Aufseb & Nikol (2008) have explored the moderating effect of business models on top management team composition and organizational performance relationship. The authors focused on biotechnology companies, and examined two types of business models that biotechnology firms might adopt: platform and therapeutics. The study included 226 biotechnology firms based in Germany. The authors found that the top management team’s industry experience has more positive performance effect for firms operating under the therapeutics model than for those operating under the platform model. The authors link this relationship to the managerial competences required for each business model to achieve high performance.

A further stream of studies has conceptually studied the link between business models, technology, and firm performance (Baden-Fuller & Haefliger, 2013; Boons & Ludeke-Freund, 2013). Baden-Fuller & Haefliger (2013) have conceptualized a framework that views business models as a mediator between technology and firm profitability. According to the framework of business models, the questions of who is the customer, how to engage with customer needs, and how to deliver and monetize value defines the link between technology and profitability. Thus, a poor choice can lead to low performance, and a good choice can lead to superior performance. Boons & Ludeke-Freund (2013) view the business model concept as an important tool that links sustainable innovation with firm performance. The authors relate profitability of sustainable technology to its embeddedness in a superior business model that successfully links the value proposition with the supply chain, customer interface and revenue model.

The reviewed literature seems to have a consensus on the fact that there is a ositive relationship between financial performance and business models. However, there are a number

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of shortcomings. The definition of business model is not aligned across the studies, thus running a risk that each study defines the business model differently to fit the industry or type of company (i.e. entrepreneurial, e-commerce, etc.), hence losing the ability to generalize the results. Based on the above literature review, it can be predicted that there is a direct relationship between business model and firm performance, which implies that the firms employing different business models will vary in their performance. To examine this relationship, as was already mentioned, we will focus on the business models employed by incumbent firms operating in different industries, and compare them against the firm performance.

3. Research design

As noted earlier, this research concentrates on the empirical relationship between business model choice and firm performance. Business models are defined using the MSA framework, while firm performance is captured via return on assets. Furthermore, a number of control variables are used in order to account for other factors that may drive firm performance.

Sample

To conduct this research, we studied the business models of incumbent firms operating in different industries. We considered public companies only, to ensure data availability. Therefore, we examined the business models of firms that are listed on the Euronext Amsterdam and Euronext Brussels exchanges. This is in order to ensure that the information is available in English, and to have the population limited in size to avoid using sampling and performing analysis on a sample set. The data was extracted directly from Euronext, and contained an initial

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(Hellmann & Puri, 2002). Moreover, during the data collection, 125 firms were removed from the list due to a lack of sufficient information, and no availability of company websites and annual reports in English. Therefore, the final sample consists of 142 firms.

2.3. Independent Variable & Control Variables

To determine firm performance, we used the return on assets ratio (ROA). ROA is one of the most commonly used measures of firm performance for incumbent firms, as can be seen from the reviewed literature. The choice of the firm performance proxy varies, with choices ranging from Tobin’s Q, to return on equity and return on assets. ROE was ruled out due to it being more sensitive to capital structures (Hitt et al., 1997). Tobin’s Q is defined approximately as the ratio of market value to book value of the firm. There are well-known measure issues associated with Tobin’s Q, one being the volatility behind the market value of the firm’s equity can potentially distort the measurement (Shane & Spicer, 1983). Given that we concentrated only on a cross-section of companies, instead of also looking at a time dimension for each company, for our sample Tobin’s Q can potentially have significant noise due to equity performance of the firm in that given year. ROA, which is defined as the ratio of net income to total assets, is book value based. The required data to calculate ROA was derived from the annual reports of the sampled firms. To ensure time alignment between the independent variable (current business models) and dependent variable (performance), we focused on financial results and annual reports from 2016. For a number of firms, however, the 2015 fiscal year was used due to unavailability of 2016 results.1

The financial performance of the company is not solely driven by the business model it operates. In order to isolate the impact of various other potential variables, the analysis will

1

For some companies, the accounting year end is March. Given that these companies are public, it can take up to 180 days to provide audited financial statements.

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include a number of controls. For this purpose, we will control for firm size (in terms of number of employees), industry, firm age, and capital structure (using a ratio of equity to liabilities). These variables are the most commonly used in the business literature to establish common ground for financial performance comparisons (Murphy, Trailer & Hill, 1996).

Regarding the impact of age, one stream of research argues that since older firms have more experience and have generated learning over time, they are not challenged by the liabilities of newness and therefore they can generate superior performance. However, another stream of research, argues that these firms tend to inert and be bureaucratized. This implies that, they are unlikely to be flexible to adapt to changing conditions, and are likely to be outperformed by newer and more flexible firms (Majumdar, 1997) Age will be measured by the number of years from the founding of the company

Size of the firm expected to have a positive impact on firm performance, since larger firms are likely to employ better technology, be more diversified, and better managed. Moreover, larger firms may also benefit from economies of scale (Himmelberg et al., 1999). However, larger firms may experience inefficiencies related to bureaucracy, and larger monitoring costs (Margaritis & Psillaki, 2009). In Zott & Amit (2007) the company size, proxied by the number of employees, was used as one of the factors.

Profitability of the industry can affect the performance of the firms operating within it (Dess, 1979, 1981). Therefore, we also control for industry effects. In order to differentiate the industry effect, we utilize the European standard for industry classification NACE codes. We

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Table 2 Descriptive statistics

N Minimum Maximum Mean Standard Deviation Return on Assets 142 -0.835 0.26 0.030 0.123 Liability to Equity 142 -35.332 18.96 1.703 5.242 Size (Number of employees) 142 20 73,5725 17010 71665 Age of the company 142 1575.0 2007.0 1944.507 71.8631

2.4. Business model clusters

For each company in the sample, it was rated along the 6 decision areas. The data required to identify the business models was derived from company websites and annual reports. Website and annual report sections such as company profile, strategy, products and services, brands, history, and financial statements were used to collect data for each of 6 areas noted above. Next, each component of the question was treated as dichotomous variable and binary coded where a positive response is 1, or else is 0. To give an example, assume company named XYZ, which is active in the onshore wind industry in the region of Wallonia, Belgium. The firm supplies rotor bearings to onshore wind developers, which appreciate XYZ’s service and use it as a preferred bidder. On the basis of this example, this company, under questions 2, will be (i) assigned 1 to B2B, while 0 B2C, both and other, (ii) assigned 1 to regional while 0 to local and international (iii) assigned 1 to upstream supplier while 0 to the remaining within this group and finally (iv) assigned 0 to relational while 0 to transactional.

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Upon collecting the data for all firms, and classifying the firm characteristics into an appropriate dichotomous group, we derive the business models by applying cluster analysis to the collected data. Cluster analysis is generally applied to classify a sample of objects based on studied characteristics of interest when there is little information about the population (Punji & Stewart, 1983). Given that the lack of characteristic should not represent a common characteristic, from the 0 and 1 classification we derived a similarity matrix by using the Jaccard Index. This matrix, consisting of coefficients between 0 and 1, representing the similarity between different companies, were clustered together using hierarchical clustering, between group linkages, and clustering on the back of squared Euclidean distance. The initial range was set between the 2-cluster option to the 9-cluster option. Each cluster-option was then analyzed using dendograms, agglomeration schedules and the distribution of companies in each cluster. As a result of the analysis, the 4-cluster option was deemed appropriate since it provided an even distribution of companies in each group, while at the same time providing a reasonable level of differentiation between the groups based on the dendogram and the amalgamation schedule. In order to validate our clustering methodology, we also run clustering using K-mean classification methodology. The 4-cluster approach resulting from the K-means classification had c.60% rank correlation with the hierarchical methodology, with a number of companies in each group being similar.

The following table provides the decomposition of the dichotomous decision element of the MSA frameworks per 4-clusters defined above.

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Primarily services 5 0 23 24 Heavy mix 15 5 0 3 Customization Standardized 4 34 14 5 Some Customization 11 8 7 8 High Customization 32 2 4 16 Breadth of the

product line Broad Line _{Medium Breadth} 2 ₃₆ 14 ₁₇ 1 ₆ 5 ₅

Narrow Line 9 13 18 18

Depth of the

product line Deep line _{Medium Breadth} 22 ₁₅ 20 ₉ 4 ₉ 6 ₉

Shallow Line 10 14 12 13

Product Forms Access to Product 4 13 5 5

Product Itself 30 25 17 20

Bundled with Other Firms' Products 13 5 3 2

Distribution Direct 43 14 23 27

Indirect 4 29 2 0

Source of

Production Internal Production/ Service Delivery 43 _Outsourcing ₀ 31 ₁ 23 ₁ 27 ₀

Licensing 3 1 1 0

Reseller 0 4 0 0

Value-added seller 1 6 0 0

Organization

Type B2B Organization _{B2C Organization} 41 ₀ 17 ₁₁ 5 ₂ 21 ₀

Government/Other 0 0 0 0

Combination 6 15 18 6

Market Scope Local 0 0 0 0

Regional 0 0 1 1

National 2 0 5 2

International 43 43 19 24

Value Chain Wholesale 1 12 0 0

Retail 1 6 1 0

Up-stream supplier 26 11 1 2

Down-stream supplier 10 13 1 0

Service provider 11 1 22 25

Customers 0 0 0 0

Exchange Type Transactional 7 40 20 2

Relational 39 3 4 25

Core

Competences Product/Operating Systems _{Selling and marketing} 41 ₃ 35 ₁₈ 20 ₇ 13 ₇

Information Management 11 2 6 6

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Networking/Resource Leveraging 22 11 7 19

Supply chain management 11 17 2 1

Financial transactions 1 2 10 15

Source of

Differentiation Image of Operational Excellence _{Product/Service Quality} 20 ₂₈ 9 ₃₇ 10 ₁₉ 6 ₁₉

Innovation Leadership 34 19 9 2

Low Cost/Efficiency 5 10 2 1

Intimate Customer Relationship 5 3 7 22

Pricing and

Revenue Source Fixed _Mixed 6 ₂₇ 30 ₁₂ 16 ₉ 4 ₆

Flexible 14 1 0 17

Operating

Leverage High _Medium 15 ₂₀ 9 ₂₁ 17 ₅ 23 ₂

Low 13 13 3 2 Volume High 22 39 20 4 Medium 17 4 4 16 Low 8 0 2 7 Margins High 8 5 4 13 Medium 16 14 12 4 Low 24 24 9 10 Time-scope and

size ambitions Growth Model _{Income Model} 18 ₂₉ 20 ₂₃ 5 ₂₀ 6 ₂₁

2.4.1. Cluster definition and the case study

The clustering analysis generated four clusters. The clusters differ significantly from eah other. However, some factors are substantially homogeneously distributed across all clusters. These factors include source of production and market scope. Since our sample includes publicly listed incumbent firms, the majority of the companies have a market scope that exceeds the boundaries of their home countries. Therefore, most of the companies have an international market scope. Even though there have been some cases in which the source of production is

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firms, they tend to pursue growth or income models. Below we summarize significant characteristics of each cluster and provide one example for each cluster.

Cluster 1: Customized product firm- 33%

The majority of the firms in this cluster offer highly customized products in the B2B segment, with some of them offer mix of products and services. Most of the firms are upstream suppliers with medium breadth and a deep line of products. However, there are also firms that position themselves as downstream suppliers or service providers. These firms have core capabilities in networking and resource leveraging, R&D, and production, and differentiate themselves with innovation leadership and product quality. The majority of exchanges are relational and distribution is direct. The source of revenue and pricing is somewhat mixed. Operating leverage and volume of production is mostly medium to high, while margins are low to medium.

An example of a firm in this cluster is Abylynx, a Belgian biopharmaceutical company. The company specializes in proprietary product development. The main research focus of the company is Nanobodies – a new class of therapeutic proteins. It has 45 proprietary programs and partnerships in 5 disease areas. This means that the company has medium and deep line of offerings. The company has both its own and collaborative development programs. Abylynx has partnerships with large pharmaceutical companies, and generates revenue from licensing of proprietary products and from R&D activities. The offerings are not standardized, and the volume is small, with only 8 products in clinical development. The company’s core competences lie in its R&D capabilities and somewhat in its partnerships. Based on partnerships and long-terms relations, the exchanges are relational and the distribution of offering is direct. Abylynx pursues development of differentiated and innovative products.

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Cluster 2: Standardized product firm – 30%

This cluster includes firms that mainly offer standardized products in B2B and B2C segments. There are both upstream and downstream suppliers in this cluster. Most of the exchanges are transactional, distribution is direct and the sources of revenue and pricing are fixed. The majority of firms have core competences in selling and marketing, supply chain management, production, and technology, with the source of differentiation mainly being product quality, with moderate to low emphasis on innovation leadership and low cost. The firms have a high volume of production, with low to medium operating leverage and margins.

ABInBev is a global beer brewer with Belgian roots. The company specializes in production and sales of different beer brands. ABInBev operates in 50 markets, selling its products in over 150 markets, and has 35 brands of beer. This means that the company has a narrow and deep line of offerings, and a high volume. Having deep historic roots in brewing, the company has core competences in development and production of different types of beer. Being committed to building great brands, and investing continuously in marketing, the company has core competences in marketing. The company’s Budweiser and Stella Artois brands are the number one and number four beer brands in the world, respectively. The company differentiates itself by quality of the products, as the company positions itself as a traditional brewer of beer that produces the best quality beers by using only finest natural ingredients. Pricing and source of revenue is mostly fixed, since the firm generates revenue mainly from the sales of beer. The company sells its products through indirect distribution channels, and the exchanges are

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The firms in this group mostly offer standardized services to both B2B and B2C customers. They offer a narrow and shallow line of services. The exchanges are transactional, the firms have core capabilities in financial transactions and technology, and they differentiate themselves through service quality and operational excellence. Pricing and revenue sources are mainly fixed, operating leverage is high, volume of sales is high, and the margins are somewhat medium. The majority of firms pursue an income model.

Aegon is a global financial services company. The company offers life insurance, pensions, and asset management services, and has global as well as local brands in markets it operates in. Therefore, the company has a medium and deep line of offerings. The services are relatively standardized and are offered to both B2B and B2C segments. The core capabilities of the company are mainly in financial transactions, and the firm pursues operational excellence and service quality to differentiate itself. The volume of services is high, the company operates in more than 20 markets and serves 30 million customers, and exchanges are mainly transactional due to the large proportion of its B2C segment.

Cluster 4: Customized B2B service firm- 19%

This cluster includes the firms that offer highly customized B2B services. The offerings are narrow and shallow to medium line. Exchanges are relational, the firms have core competences in financial transactions, networking, and resource leveraging, and differentiate themselves with service quality and intimate customer relations. Pricing and revenue sources are flexible, operating leverage is high, margins are high to low, volume of the services is medium. The majority of firms in this cluster pursue an income model.

Sofina is an investment company that specializes in three areas: long-term minority investments, investments in venture capital and private equity funds, and investments in fast

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growing businesses. This means that the company has a medium and relatively shallow line of offerings. Each investment is unique; therefore, the value proposition is highly customized. With 23 employees and 23 investments in its portfolio, Sofina has medium volume. As an investment company, Sofina’s core competences lie in financial transactions. The company relates its uniqueness to strong emphasis on long term and close relationships with its partners, decades of expertise and experience, being pragmatic and solution oriented that makes it a reliable partner.

4. Parametrization & Results

4.1. Parametrization

In order to run the regression between the independent variable and the dependent variables, the following parameterization was used:

𝑅𝑅𝑅𝑅𝐴𝐴𝑖𝑖 = 𝛽𝛽0+ 𝛽𝛽1𝐵𝐵𝐵𝐵𝐶𝐶𝑖𝑖1 + 𝛽𝛽2𝐵𝐵𝐵𝐵𝐶𝐶𝑖𝑖2+ 𝛽𝛽3𝐵𝐵𝐶𝐶𝐵𝐵𝑖𝑖3+ 𝐵𝐵𝑡𝑡={1,2…11)𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝑇𝑇𝑖𝑖𝑡𝑡={1,2…11}+ 𝛽𝛽12𝐴𝐴𝐴𝐴𝐸𝐸𝑖𝑖

+ 𝛽𝛽13𝐼𝐼𝐼𝐼𝑆𝑆𝐸𝐸𝑖𝑖 + 𝛽𝛽14𝐿𝐿𝐼𝐼𝐵𝐵𝑇𝑇𝑅𝑅𝐸𝐸𝑄𝑄𝑖𝑖+ 𝜀𝜀𝑖𝑖

Where,

𝑖𝑖 = Observation in our dataset 𝑅𝑅𝑅𝑅𝐴𝐴𝑖𝑖 = Return on asset

𝐵𝐵𝐵𝐵𝐶𝐶𝑖𝑖1 = Business model cluster 1 dummy variable

𝐵𝐵𝐵𝐵𝐶𝐶𝑖𝑖2 = Business model cluster 2 dummy variable

𝐵𝐵𝐵𝐵𝐶𝐶_𝑖𝑖3_{= Business model cluster 3 dummy variable}

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𝜀𝜀𝑖𝑖 = error term

Initial check of a scatter plot between the independent variable and the dependent variable did not reveal any non-linearity. In order to check for multicollinearity, we analyzed the correlation matrix of the variables, revealing no significant correlations between the variables.

4.2. Results

A top to bottom regression approach was used, where for the first regression all of the variables were included. At every iteration, one of the controls was dropped, until the regression was run using solely the business model classifications. These results are presented in the first table below. In order to check the robustness of our regression against outliers, both independent and control variables were winsorized at 95%. The results utilizing the winsorized data are presented in the second table below. For every regression, checks were completed to monitor for the homogeneity of outcomes, autocorrelation, and the normal distribution of residuals.

The significance of the variables is tested using T-statics. In order to test the join effect of the dummy variables, an F-test for joint significance was performed.

From the tables, we can observe that there is no direct link business classification via the MSA framework and firm performance. Even when controlling for industry, age, size, and capital structure of the company, the analysis does not yield any significant impact of the selected business model on firm performance. These results hold even after the same regression analysis was performed on the winsorized data, implying a minor effect of outliers on the outcome of this analysis. The lack of relationship is not only considering the combined effect, but also the intra business model classification. None of the separate business models has significantly better performance compared to other business model classification.

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One of the surprising outcomes was the lack industry effect on asset return. Given that different industries following different economic cycles, one would expect that different industries would be a significant effect, given this study’s use of a single financial year of data. The only variable that has a significant impact, at 10% significance, is the ratio of liabilities to equity, and that only becomes weakly significant based on the winsorized data. This ratio has a negative impact, implying that additional leverage (more payables, short and long-term debt, and the financial market) to lower returns on asset.

Table 4. Regression results based on the actual data. BMC stands for the business model cluster. Superscript above BMC denotes the appropriate cluster. Age is proxied by the year of incorporation of the company. Size is proxied by the number of employees. LIBTEQ stands for the ratio of liabilities to equity. Linear regression was used. The number of observations used for the regression is 142, concentrating over public companies listed on the Euronext Amsterdam and Brussels exchanges.

Regression 𝜷𝜷_𝟎𝟎 𝑩𝑩𝑩𝑩𝑪𝑪𝟏𝟏 𝑩𝑩𝑩𝑩𝑪𝑪𝟐𝟐 𝑩𝑩𝑩𝑩𝑪𝑪𝟑𝟑 𝑨𝑨𝑨𝑨𝑨𝑨 𝑺𝑺𝑺𝑺𝑺𝑺𝑨𝑨 𝑳𝑳𝑺𝑺𝑩𝑩𝑳𝑳𝑨𝑨𝑳𝑳 𝑺𝑺𝑰𝑰𝑰𝑰𝑺𝑺𝑳𝑳𝒊𝒊𝒕𝒕={𝟏𝟏,𝟐𝟐…𝟏𝟏𝟏𝟏} (Joint F-statistic) 𝑹𝑹 𝟐𝟐 Adj 𝑹𝑹𝟐𝟐 1 Coefficient 33.46 0.03 (0.05) (0.13) (0.0) 0.01 0.03 6% -7% P-value 26% 87% 78% 32% 33% 90% 74%

F-statistic of joint significance 0.73 0.44

2 Coefficient 40.26 0.04 (0.03) (0.12) (0.1) 0.01 6% -6% P-value 25% 79% 84% 35% 31% 91%

3 Coefficient 40.30 0.04 (0.03) (0.12) (0.1) 6% -5% P-value 24% 79% 84% 35% 31%

4 Coefficient 7.67 0.06 (0.00) (0.12) 5% -5% P-value 56% 70% 99% 35%

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Table 5: Regression results based on the winsorized data. BMC stands for the business model

cluster. Superscript above BMC denotes the appropriate cluster. Age is proxied by the year of incorporation of the company. Size is proxied by the number of employees. LIBTEQ stands for the ratio of liabilities to equity. Linear regression was used. The number of observations used for the regression is 142, concentrating over public companies listed on the Euronext Amsterdam and Brussels exchanges.

Regression 𝜷𝜷_𝟎𝟎 𝑩𝑩𝑩𝑩𝑪𝑪𝟏𝟏 𝑩𝑩𝑩𝑩𝑪𝑪𝟐𝟐 𝑩𝑩𝑩𝑩𝑪𝑪𝟑𝟑 𝑨𝑨𝑨𝑨𝑨𝑨 𝑺𝑺𝑺𝑺𝑺𝑺𝑨𝑨 𝑳𝑳𝑺𝑺𝑩𝑩𝑳𝑳𝑨𝑨𝑳𝑳 𝑺𝑺𝑰𝑰𝑰𝑰𝑺𝑺𝑳𝑳𝒊𝒊 𝒕𝒕={𝟏𝟏,𝟐𝟐…𝟏𝟏𝟏𝟏 (Joint F-statistic) 𝑹𝑹𝟐𝟐 _Adj_𝑹𝑹𝟐𝟐 1 Coefficient 19.4 0.16 0.03 (0.00) (0.08) (0.03) (0.19) 11.3% -0.8% P-value 29% 23% 91% 63% 41% 79% 7.1%

2 Coefficient 16.1 0.10 (0.02) (0.07) (0.06) (0.05) 9.0% -2.7%

P-value 39% 54% 91% 60% 51% 57%

3 Coefficient 14.3 0.10 (0.02) (0.07) (0.05) 8.7% -2.1%

P-value 44% 52% 90% 56% 56%

4 Coefficient 3.56 0.12 (0.00) (0.07) 8.5% -1.6% P-value 6% 46% 98% 57%

5 Coefficient 3.80 0.10 (0.00) (0.05) 1.5% -0.6% P-value 7% 39% 99% 67%

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5. Discussion and Conclusion.

5.1. Discussion

This study endeavored to investigate the relationship between business models and firm performance. Various authors have argued that there is a direct relationship between these two. Moreover, some empirical studies have found significant relationships between business model and firm performance (e. g. Zott & Amit, 2007; Suarez, Cusumano & Kahl, 2013). These studies, along with the general definition of business model, have employed different definitions of the concept, and have been narrow studies examining specific business models or firms. By employing the MSA framework to define different generic business models, we examined the relationship between business models and performance for incumbent firms operating in different industries. We predicted that the choice of business model will affect firm performance, therefore there will be significant performance differences between firms employing different business models. However, our study did not prove this effect. The possible theoretical explanations for the results of this study may guide future research in shifting its focus to new directions of study. The result of the study can be explained by several reasons.

Firstly, firms employing similar business models can implement it differently. Some firms may fail to apply the business model properly, and subsequently fail to fully use the value creating and value capturing potential of the business model. Brea-Solis, Casadesus-Masanell & Grifell-Tatje (2015), in their study of Walmart’s business model evaluation and the company’s sources of advantage, have found a similar result. The study showed that even though Walmart’s

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operating similar business models that are at different stages of the lifecycle and implementation of the model may yield different performance results. For example, firms at later stages of the implementation of a certain business model, may perform better than newly adopters, since experience and learning generated over time enable them to perform similar activities better and more efficiently. Therefore, these variances, may erode the differences in performance implications of different business models.

Secondly, the results can also be related to strategy and environmental factors. Our definition of business model also included the competitive strategy factors of the firm. Firms operating similar business models and competitive strategy combination in different environments may have delivered different performance results. For example, Miller (1988) found that in uncertain (unpredictable and dynamic) environments, while innovation leadership strategy is positively associated with firm performance, this relationship is negative for firms pursuing a cost-leadership strategy. A further study by McArthur and Nystrom (1999) has found an interaction between environmental factors, firm strategy, and firm performance. Even though in our study we controlled for industry effects, it may not isolate different dimensions such as dynamism, complexity, hostility, or competitiveness of the environment within which the firm operates.

We cannot prove contribution of these possible reasons to the result of our study, since neither implementation and lifecycle of business models, nor moderating effect of environmental factors, were within the scope of our analysis. We only examined the direct relationship between different business models and firm performance. However, these two possible explanations can inspire future research on the topic.

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From a managerial perspective, this study implies that in order to improve firm performance, management should not solely focus on business model change or should not directly relate underperformance to a poor business model choice. This may help them avoid the temptation of altering the firm’s business models when trying to further improve the firm performance or dealing with underperformance. By doing this, managers will be able to switch their attention to more important issues, at the same time saving on resources, time and effort.

This study has several limitations which can also provide directions for future research. First, although the use of the MSA framework to define types of business models enables measuring and quantifying business models of different firms, to a certain extent it relies on the subjective interpretation of the information by the researcher. Even though we tried to minimize this effect by removing firms that do not provide clear information about the business model factors in their websites and annual reports, future research may benefit from matching this method with other, less subjective ways of data collection such as surveying and interviewing. Second, the size of the dataset does not allow us to draw generalizable conclusions about the result of the study. Therefore, future research may also benefit from applying the analysis to a broader data set. Third, our analysis does not capture the lifecycle of business models, and variations in firm performance depending on the change in the business model. Hence, future research may consider taking a longitudinal approach to research of business models and firm performance. Fourth, researchers can also study how interaction of different/certain business model components or emphasis on certain components affects the firm performance. Finally, as

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5.2. Conclusion

In this study, we tried to examine the performance implications of different business models. To provide a generalizable understanding of the business model-performance relationship, and to expand the field of study, we focused on the generic business models employed by incumbent firms operating in different industries. For this purpose, we examined the business model-performance relationship of 142 publicly listed firms. Applying the MSA framework (Morris et al., 2005) and cluster analysis to generate the business models operated by these firms, we identified four generic business models. The analysis did not find any significant relationship between different business models and firm performance, since none of the business model clusters we identified was associated with superior performance. In the discussion section, we outlined the possible explanations of the results, which also implies that future research of the topic needs to switch its focus to the study of these possible explanations.

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References

1. Afuah, A., & Tucci, C. L. (2001). Internet business models and strategies: Text and cases. New York: McGraw-Hill

2. Amit, R., & Zott, C. (2001). Value creation in e-business. Strategic management journal, 22(6-7), 493-520.

3. Beard, D. W., & Dess, G. G. (1981). Corporate-level strategy, business-level strategy, and firm performance. Academy of management Journal, 24(4), 663-688.

4. Brea-Solís, H., Casadesus-Masanell, R. and Grifell-Tatjé, E. (2015), Business Model Evaluation: Quantifying Walmart's Sources of Advantage. Strategic Entrepreneurship Journal, 9: 12–33.

5. Baden-Fuller, C., & Haefliger, S. (2013). Business models and technological innovation. Long range planning, 46(6), 419-426.

6. Baden-Fuller, C., & Mangematin, V. (2013). Business models: A challenging agenda. Strategic Organization, 11(4), 418-427.

7. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of management, 17(1), 99-120.

8. Boons, F., & Lüdeke-Freund, F. (2013). Business models for sustainable innovation: state-of-the-art and steps towards a research agenda. Journal of Cleaner Production, 45, 9-19.

(41)

10. Chesbrough, H. (2010). Business Model Innovation: Opportunities and Barriers. Long Range Planning, 43(2-3), 354–363.

11. Coff, R. W. (1999). When competitive advantage doesn't lead to performance: The resource-based view and stakeholder bargaining power. Organization science, 10(2), 119-133.

12. Hamel, G. (2000). Leading the revolution. Boston, MA: Harvard Business School Press. 

13. Hellmann, T., & Puri, M. (2002). Venture capital and the professionalization of start-up firms: Empirical evidence. The journal of finance, 57(1), 169-197.

14. Himmelberg, C. P., Hubbard, R. G., & Palia, D. (1999). Understanding the determinants of managerial ownership and the link between ownership and performance. Journal of financial economics, 53(3), 353-384.

15. Hitt, M. A., Hoskisson, R. E., & Kim, H. (1997). International diversification: Effects on innovation and firm performance in product-diversified firms. Academy of Management journal, 40(4), 767-798.

16. Jarillo, J. C. (1995). Strategic networks: creating the borderless organization. Routledge. 17. Johnson, M.W., Christensen, C.M. and Kagerman, H. 2008. Reinventing Your business

model. Harvard Business Review.

18. Majumdar, S. K. (1997). The impact of size and age on firm-level performance: some evidence from India. Review of industrial organization, 12(2), 231-241.

19. Magretta, J., (2002). Why business model matter? Harvard Business Review.

20. Margaritis, D., Psillaki, M. (2010). Capital structure, equity ownership and firm performance. Journal of Banking & Finance, 34(3), 621-632.

(42)

21. McGrath, R. G. (2010). Business models: A discovery driven approach. Long range planning, 43(2), 247-261.

22. McArthur, A. W., & Nystrom, P. C. (1991). Environmental dynamism, complexity, and munificence as moderators of strategy-performance relationships. Journal of Business Research, 23(4), 349-361.

23. Miller, D. (1988). Relating Porter's business strategies to environment and structure: Analysis and performance implications. Academy of management Journal, 31(2), 280-308.

24. Mizik, N., & Jacobson, R. (2003). Trading off between value creation and value appropriation: The financial implications of shifts in strategic emphasis. Journal of marketing, 67(1), 63-76.

25. Morris, M., Schindehutte M., and Allen, J. (2005). The entrepreneur’s business model: toward a unified perspective. Journal of Business Research, 58 (6), 726–735.

26. Morris, M., Schindehutte, M., Richardson, J., & Allen, J. (2006). Is the business model a useful strategic concept? Conceptual, theoretical, and empirical insights. Journal of Small Business Strategy, 17(4), 27-5

27. Osterwalder A., Pigneur Y. 2010. Business model generation: a handbook for visionaries, game changers, and challengers. – John Wiley & Sons

28. Patzelt, H., Knyphausen-Aufseß, Z., & Nikol, P. (2008). Top management teams, business models, and performance of biotechnology ventures: An upper echelon

(43)

30. Porter, M. E. (1985). Competitive advantage: creating and sustaining superior performance. 1985. New York: FreePress.

31. Punj, G., & Stewart, D. W. (1983). Cluster analysis in marketing research: Review and suggestions for application. Journal of marketing research, 134-148.

32. Schumpeter, J. A. (1934). The theory of economic development: An inquiry into profits, capital, credit, interest, and the business cycle (Vol. 55). Transaction publishers.

33. Shafer, S. M., Smith, H. J., & Linder, J. C. (2005). The power of business models. Business horizons, 48(3), 199-207.

34. Suarez, F. F., Cusumano, M. A., & Kahl, S. J. (2013). Services and the business models of product firms: an empirical analysis of the software industry. Management Science, 59(2), 420-435.

35. Teece, D. J. (2010). Business Models, Business Strategy and Innovation. Long Range Planning, 43(2-3), 172–194.

36. The rise of the superstars, The Economist, September, 2016

37. Williamson, O. E. (1975). Markets and hierarchies. New York, 26-30.

38. Wirtz, B. W., Pistoia, A., Ullrich, S., & Göttel, V. (2016). Business models: Origin, development and future research perspectives. Long Range Planning, 49(1), 36-54.

39. Zott, C., Amit, R., & Massa, L. (2011). The Business Model: Recent Developments and Future Research. Journal of Management, 37(4), 1019–1042.

40. Zott, C., & Amit, R. (2007). Business Model Design and the Performance of Entrepreneurial Firms. Organization Science, 18(2), 181–199.

41. Zott, C., & Amit, R. (2008). The Fit between Product Market Strategy and Business Model: Implications for Firm Performance. Strategic Management Journal, 29 (1), 1-26

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An empirical analysis of performance implications of different business models