A new conceptual lens for marketing: a

A new conceptual lens for marketing: a configurational perspective based on the business model concept Alexander Leischnig, Björn S. Ivens & Nadine Kammerlander

AMS Review Official Publication of the Academy of Marketing Science ISSN 1869-814X Volume 7 Combined 3-4 AMS Rev (2017) 7:138-153 DOI 10.1007/s13162-017-0107-6

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Author's personal copy AMS Review (2017) 7:138–153 https://doi.org/10.1007/s13162-017-0107-6

THEORY/CONCEPTUAL

A new conceptual lens for marketing: a configurational perspective based on the business model concept Alexander Leischnig 1 & Björn S. Ivens 2 & Nadine Kammerlander 3 Received: 25 January 2017 / Accepted: 4 December 2017 / Published online: 28 December 2017 # Academy of Marketing Science 2017

Abstract The business model concept has received strong interest among both practitioners and academics. As recent reviews of the literature on business models indicate, the number of articles that deepen the understanding of the role and nature of the business model concept as well as its antecedents and consequences has grown rapidly in the last years (e.g., Zott et al. in Journal of Management, 37(4), 1019-1042, 2011; Wirtz et al. in Long Range Planning, 49(1), 36-54, 2016). Yet, this substantial body of work that covers multiple perspectives and includes studies in a variety of contexts and settings has so far produced a fragmented research landscape that has largely developed in silos. Drawing on configuration theory (Ketchen et al. in Academy of Management Journal, 36(6), 1278-1313, 1993; Meyer et al. in Academy of Management Journal, 36(6), 1175-1195, 1993) and recent literature adopting a configurational approach (Fiss in Academy of Management Journal, 54(2), 393-420, 2011; Leischnig et al. in Journal of Business Research, 69(9), 3576-3583, 2016a), the purpose of this article is to discuss how marketing research and practice may benefit from a business model perspective and configurational thinking. We suggest that a business model can fruitfully be understood as a configuration of components embracing multiple domains and whose interdependent and interconnected structures influence the extent to which a firm can achieve strategic objectives and superior performance. We discuss which elements in business models are particularly linked to the field of marketing and how the role of these elements may differ in alternative configurations of business models. We conclude with an agenda for researchers from marketing and related disciplines that identifies avenues for further research on business models as configurations. Keywords Business models . Marketing . Configuration theory

Introduction Marketing theory and practice have always evolved along with developments in the social, political, and technological

* Björn S. Ivens [email protected] Alexander Leischnig [email protected] Nadine Kammerlander [email protected] 1

School of Business and Management, Queen Mary University of London, Mile End Road, London E1 4NS, UK

2

Competence Center for Digital Business Models, University of Bamberg, Feldkirchenstr, 21, 96052 Bamberg, Germany

3

WHU – Otto Beisheim School of Management, Burgplatz 2, 56179 Vallendar, Germany

environments, and along with developments in other environments in which firms apply the marketing concept. The current rate of change, however, appears to be high compared to earlier periods (e.g., Achrol and Kotler 2012; Erevelles et al. 2016; Rust and Huang 2014; Wind 2014). Manifold trends, such as increased digitization and customization, the rise of the sharing economy and the circular economy, and globalization on the one hand and regional protectionist movements on the other, provide major opportunities for firms while also posing threats. For managers and academics alike, this transformation of the field creates the need for a new perspective—one that accounts for the fact that if a firm is to adapt to volatile market conditions and achieve its overall goals, marketing activities need to be integrated and coordinated with other value-related activities effectively and efficiently. This article suggests that a business model perspective may provide a useful lens through which to better understand the complex interplay between marketing activities and firm-internal and -external factors.

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The business model concept, which refers to the way a firm operates and creates value for its stakeholders while capturing value for itself (Casadesus-Masanell and Ricart 2010), has attracted strong interest from both practitioners and academics. As indicated by recent reviews of the literature on business models, the number of articles that provide deeper understandings of the role and nature of business models – as well as their antecedents and consequences – has grown rapidly in recent years (e.g., Wirtz et al. 2016; Zott et al. 2011). However, this substantial body of work, which covers multiple perspectives and includes studies in a variety of contexts and settings, has so far produced a rather fragmented research landscape, especially with reference to the marketing domain. This may explain why the business model has long been seen as a concept that is Brelatively poorly understood^ (Osterwalder et al. 2005, p. 3) and why research on the concept can still profit from efforts to provide a sound theoretical grounding (Teece 2010). Envisioning economic activities as multi-level phenomena—in which interrelated sets of activities performed by different actors are coordinated and managed through an overarching logic—constitutes one of the central characteristics of the business model concept and related literature. Scholars typically express the multi-level character of a business model by categorizing activity sets in the form of lower-level building blocks or elements (e.g., key resources, value propositions, or cost structure in Osterwalder and Pigneur 2010) that are combined through managerial decision processes to form idiosyncratic higher-level business models. As prior work indicates (e.g., DaSilva and Trkman 2014; Lambert and Davidson 2013; Shafer et al. 2005; Zott et al. 2011), the business model literature falls under four broad themes. First, there are articles that discuss higher-level business model issues: Instead of referring to concrete business models or their building blocks, these articles examine the theoretical perspectives that allow scholars to explain the existence, management, innovation, and ultimately success of business models (e.g., Doz and Kosonen 2010; Markides and Charitou 2004; Zott and Amit 2010). Second, there are articles that define the business model concept and its constituent elements, review the business model literature, or discuss the relationship between business models and alternative concepts such as strategy (e.g., Casadesus-Masanell and Ricart 2010; Teece 2010; Zott et al. 2011). Third, some articles discuss concrete business models, that is, specific combinations of business model elements, such as a business model that is dominant in a given industry or pursued by a specific firm (e.g., Storemark and Hoffmann 2012). Fourth, some articles discuss the individual building blocks or elements of business models; this category includes articles with a focus on revenue models (e.g., Hoffman and Novak 2005; Piercy 2009). Business model scholars have different academic backgrounds; they come from, for example, the areas of strategy,

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entrepreneurship, innovation management, information systems, operations research, and marketing. In discussing the potential contributions that marketing can make to business model research and, in turn, the potential contributions that a business model approach can bring to marketing science, Ehret, Kashyap and Wirtz (2013, p. 650) observe that B[e]ngaging with business models provides marketers an opportunity to revitalize and strengthen the entrepreneurial dimension of marketing approaches. It would be a mistake to understate the real and potential contribution of marketing to business models.^ To date, the discipline of marketing has made significant contributions to the business model literature. These contributions fall predominantly under the third and fourth themes identified above. For example, marketing scholars discuss a business model for firms that are active in solution business (Storbacka 2011) as well as the move toward such a model (Ferreira et al. 2013); such scholars also discuss a business model for value co-creation (Storbacka et al. 2012), the introduction of fees after having practiced free business models (Pauwels and Weiss 2008), outcome-based contracts as a business model (Ng et al. 2013), the move toward service-focused elements in business models (Barquet et al. 2013; Kindström and Kowalkowski 2014; Palo and Tähtinen 2013) or a service science perspective on business models (Maglio and Spohrer 2013), business model innovation vs. replication (Aspara et al. 2010), and e-business models (Muzellec et al. 2015; Shin and Park 2009; Timmers 1998). Marketing has made fewer contributions to the first two themes, that is, to the general business model literature and, more specifically, to its theoretical underpinnings and development (Coombes and Nicholson 2013). The few existing articles (e.g., Mason and Spring 2011; Robertson 2017; Sorescu et al. 2011; Stewart and Zhao 2000) study aspects such as business model innovation or the extent to which business models are inherently transformed when they are partially digitalized. However, these articles do not provide detailed guidance with respect to the theoretical underpinnings that may enable explanations of the role of marketing in business models. This is an astonishing research gap, since theorizing about business models might provide marketing scholars and practitioners with a lens that allows them to analyze and understand – in a more holistic way – the complex and interrelated challenges all actors involved in business model management face in a digitizing world. Drawing on configuration theory (Ketchen et al. 1993; Meyer et al. 1993) and recent work adopting a configurational approach (Fiss 2011; Leischnig et al. 2016a), the purpose of this article is to discuss how marketing research and practice may benefit from a business model perspective and configurational thinking. We suggest that a business model can be understood as a configuration of components embracing multiple domains and whose interdependent and interconnected

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structures influence the extent to which a firm can achieve strategic objectives and superior performance. We discuss which elements of business models are particularly linked to the field of marketing and how the role of these elements may differ in alternative configurations of business models. In particular, this article discusses how a configurational perspective can support marketing scholars and practitioners in investigating and understanding business model thinking in a digital economy. We conclude with an agenda for researchers from marketing and related disciplines that identifies avenues for further research on business models as configurations.

Conceptual background The nature and role of business models While consensus on a definition of business models is still missing, prior work on the topic agrees that a business model encompasses and describes the underlying logic of a firm, the way it operates, and the way in which it creates value for its stakeholders while capturing value for itself (CasadesusMasanell and Ricart 2010; Demil et al. 2015). Business models delineate Bas a system, how the pieces of a business fit together^ (Magretta 2002, p. 6). Prior studies use different terms, such as dimensions, building blocks, components, or design elements, to describe the pieces of business. For example, based on a business model canvas perspective, Osterwalder and Pigneur (2010) identify nine building blocks that characterize a firm’s business model. Amit and Zott (2001), as another example, point to content, structure, and governance of transactions as design elements of business models. As Zott and Amit (2010, p. 2) note, Bthe overall objective of a focal firm’s business model is to exploit a business opportunity by creating value for the parties involved, i.e., to fulfill customers’ needs and create customer surplus while generating a profit for the focal firm and its partners.^ As such, business models and business model thinking may serve as tools that guide firms in exploring a market and innovating (Doganova and Eyquem-Renault 2009), and they may function as moderators for firm-internal cause-and-effect relationships, such as the impact of top management team composition on organizational performance (Patzelt et al. 2008).

Business model design When firms seek to design business models, they must make several choices. These choices can be grouped into policy choices, asset choices, and governance choices (CasadesusMasanell and Ricart 2011). Policy choices refer to fundamental decisions that firms make concerning their activities across their operations, such as the principles guiding the location of

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offices and factories, or general sustainability practices. Asset choices concern the resources that firms deploy to execute activities. Governance choices refer to the ways in which firms arrange decision-making rights over policy and asset choices. The managerial choices that firms make influence the nature of business models, and one can consider alternative themes around which business models can be orchestrated. For example, some firms focus on novelty as the dominant theme for value creation, while others stress efficiency, lockin, or complementarities (Amit and Zott 2001; Zott and Amit 2007). Novelty refers to offering novel value to customers, for instance by offering substantially improved products or services that fulfill so-far-unexplored customer needs. Apple’s introduction of the iPhone – and the repeated launch of new versions with new features – is an example of a business model that relies mostly on novelty. In contrast, efficiency relates to decreased production cost and increased speed. Typical examples of such business models can be found at retailers, low-cost airlines, logistics firms, or suppliers of commodities. Business models may also show lock-in effects, when customers are incentivized to engage in repeated transactions with the firm, for instance due to high switching costs. One important example of lock-in based business models is offering services that require specific (proprietary) platforms. Finally, complementarities refer to the bundling of values – vertically or horizontally – across the value chain. An example of such a business model is Amazon’s transformation from simply an online bookstore to a firm providing a variety of physical and virtual goods for sale and lease, as well as premium services.

Business model change Because business models per se reflect a static snapshot in time (Demil and Lecocq 2010), firms challenged by volatility and unpredictability in their environments need to constantly reconsider their business models, adapt them to changing demands, and engage in business model innovation or transformation. Adapting business models to changes in the environment, however, is often considered a major challenge, especially for well-established firms (Chesbrough 2010). One of the primary reasons for this challenge can be seen in the number and interconnected structure of the components that characterize a business model. Based on a review of prior work on business models, Shafer et al. (2005) identify no fewer than 42 components of business models, such as branding, cash flow, customer information, firm identity, and product innovation, all of which are related to each other. In addition, a more recent analysis of the business model literature by Wirtz et al. (2016) identifies nine sub-sets of


business models, with each of these models comprising two or more elements. For business models to become effective, these multiple components and elements have to work together and complement each other, thus enabling firms to realize business opportunities, create and deliver value for customers, and generate value for themselves. Hence, business models have been referred to as recipes that detail ingredients and specific approaches, and combine both to accomplish overall goals (Baden-Fuller and Morgan 2010). Conflicts regarding required asset reconfigurations and top management’s cognitive rigidity, however, may pose barriers that hinder firms from adapting their business models and developing new recipes (Chesbrough 2010).

Theoretical perspective Tenets of configuration theory The primary theoretical perspective that we adopt in this article is that of configuration theory, which includes four primary tenets. Configuration theory builds on a holistic synthesis as the dominant mode of inquiry (Meyer et al. 1993) and assumes that organizations are systems of interconnected strategic, structural, and procedural elements. These elements tend to coalesce because their interdependence and interconnected structures make them fall into patterns (Meyer et al. 1993; Miller 1996). Hence, configurations can contain building blocks from different domains (Dess et al. 1993) and thus represent conjunctions of multiple elements that commonly occur together and that are orchestrated and connected within a unifying theme (Meyer et al. 1993; Miller 1996). Configuration theory aims to explain how order emerges from the interplay of elements (Meyer et al. 1993). It holds that there is a limited set of configurations of elements that enable organizations to accomplish the same strategic goals and achieve superior performance in similar ways (Ketchen et al. 1993). Configuration theory thus incorporates the idea of equifinality (Doty and Glick 1994; Gresov and Drazin 1997), which is defined as a situation in which Ba system can reach the same final state from different initial conditions and by a variety of different paths^ (Katz and Kahn 1978, p. 30). In our context, this implies that while the number of business models prevailing in an industry at one point in time may be limited, firms very often have several options for how they can set up successful business models. It also implies, first, that the different business models that co-exist in an industry at a specific point in time are not necessarily the only ones that allow firms to achieve profitability and, second, that new entrants or competitors may threaten a firm in the future by introducing or switching to new configurations of business model elements.

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Moreover, configurational theory considers that the elements within configurations can differ in their causal essentiality for an outcome of interest and can thus be classified as core and peripheral conditions (Fiss 2011). Core conditions represent those elements for which empirical evidence demonstrates a strong causal connection with the outcome of interest, whereas peripheral conditions are those elements for which empirical evidence indicates a weaker causal relationship with the outcome in question (Fiss 2011). Peripheral factors tend to surround core conditions in a configuration and underline their central features (Fiss 2011; Grandori and Furnari 2008). Finally, a central notion considered in configuration theory is that of causal asymmetry. Causal asymmetry implies that elements Bfound to be causally related in one configuration may be unrelated or even inversely related in another^ (Meyer et al. 1993, p. 1178). For instance, the possession of tangible assets has been considered a key element of business models in the accommodation industry. However, the rise of firms practicing new business models in this industry, such as Airbnb, indicates that this element’s relevance can sharply decrease and that access to (rather than possession of) tangible assets is a key part of performance-enhancing business models. We discuss this aspect in more detail below. Thus, depending on how elements combine into configurations, valence reversals or irrelevance of specific elements may occur. Causal asymmetry also implies that configurations of elements that are sufficient for an outcome tend to be poor explanations for the reverse of the same outcome because the composition of configurations for the reversed outcome may change substantially (Fiss et al. 2013). In summary, configuration theory and configurational thinking accommodate conjunctural causality, equifinality, causal essentiality, and causal asymmetry (Fiss 2011; Ketchen et al. 1993; Meyer et al. 1993). As such, they provide a useful theoretical lens for the study of complex causal patterns among business model elements. As our discussion above has shown, complex causality constitutes an integral characteristic of business models, thus warranting a configurational perspective on the business model.

The business model as configuration The central argument of this article is that business models can be conceived as configurations of components that enable firms to realize business opportunities by creating value for stakeholders while capturing value for themselves. Each of the components in a business model configuration denotes, per se, a configuration of elements aimed at contributing to the accomplishment of the firm’s overall objectives. For instance, the customer relationship management (CRM) component of a business model consists of various elements, such as a CRM system, a customer loyalty program, and customer-oriented


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personnel. The configuration of components in the business model is orchestrated by a unifying theme and is the result of strategic choices made by the firm. The notion of business models as configurations is backed up by several prior studies that have adopted a configurational perspective to study the concept (see Table 1 for key studies). For instance, Zott and Amit (2010) note that the design of a business model can be conceived of as the configuration of activities enabled by business model stakeholders and their resource endowments. In addition, based on a Penrosian view of the firm, Demil and Lecocq (2010) argue that business models are configurations of RCOV core components (i.e., resources and competences, organizational structure, and value proposition). In addition, they note that these configurations are subject to a permanent state of disequilibrium. Using a configurational approach to examine the relationships between business model design and performance, Kulins et al. (2016) provide a vision of three alternative configurations of design themes sufficient for firms to achieve high market value. The findings of their study reveal that the combination of efficiency and novelty, or the combination of novelty and lock-in, or the combination of efficiency, complementarities, and lock-in design themes lead to high market value. Using the same approach but with a focus on different antecedents, Aversa et al. (2015) investigate how business model configurations are associated with performance among firms competing in Formula One racing. The findings of their study reveal that two business model configurations (i.e., one focused on selling technology to competitors, the other focused on developing and trading human resources with competitors) are associated with high performance, which is attributable to capability-enhancing complementarities. Finally, through an extensive analysis of the business model literature, Table 1

Taran et al. (2016) develop a list of 71 business model configurations consisting of particular combinations of value drivers (i.e., value proposition, value segment, value configuration, value network, and value capture building blocks).

Advantages of studying business models as configurations Understanding the business model as a configuration has several advantages. First, it provides a sound theoretical foundation that connects existing streams in the business model literature: the business model as a recipe (Baden-Fuller and Morgan 2010); as a system that is made up of components, linkages among the components, and dynamics (Afuah and Tucci 2001); as an activity system (Zott and Amit 2010); and as a set of choices and the consequences of these choices (Casadesus-Masanell and Ricart 2011). Thus, the configurational lens provides a frame that integrates predominant perspectives and conceptualizations of business models. Second, the configuration theoretical perspective on the business model enables theory development and testing at different levels of granularity. It can be applied to the study of elements (e.g., resources) sufficient for particular business model components (e.g., activities) as well as to the study of configurations of business model components sufficient for successful business models. For example, Demil and Lecocq (2010, p. 230) emphasize that B[t]he resources accumulated over an organization’s history continually react with each other in unique combinations to determine the firm’s idiosyncratic bundle of capabilities that differentiate it in its sector.^ By structuring and bundling resources, firms can build capabilities and, in turn, leverage them to exploit business opportunities (Sirmon et al. 2007). Using the example of digital

Sample studies adopting a configurational perspective on business models

Study

Focus

Configurational notions

Zott and Amit (2007) and (Zott and Amit 2010)

Business model design

Demil and Lecocq (2010)

Business model evolution

Amit and Zott (2015)


Aversa et al. (2015)

Business model configuration

Taran et al. (2016)

Business model innovation

Kulins et al. (2016)


Business models are configurations of design elements (i.e., content, structure, and governance of transactions) orchestrated and connected by business model design themes (e.g., novelty and efficiency). Business models are configurations of RCOV core components (i.e., resources and competences, organizational structure, and value proposition) that are subject to a permanent state of disequilibrium. Business models are consistent when decisions about its components lead to sustainable performance. Design of a business model can be conceived as the configuration of activities enabled by business model stakeholders and their resource endowments. Business models are configurations of constituent elements. A firm can have more than one business model (i.e., configurations of business models). Equifinal business model configurations for high performance exist. Business models are configurations of primary and secondary value drivers (i.e., value proposition, value segment, value configuration, value network, and value capture building blocks). Business model design is a configuration approach. Multiple configurations of business model design themes are sufficient for high firm market value.


services, Clark et al. (2012) show how firms can assemble (and re-assemble) resources and capabilities in a complementary and/or co-specialized way to create new value propositions for existing or new customer groups. Furthermore, proposing an activity system perspective, Zott and Amit (2010, pp. 218) note that interdependent activities constitute essential components of business models and that it is the Bpurposeful weaving together^ of those interdependent activities that captures the essence of business model design. The configurational view captures this notion and can contribute to the understanding of which configurations of assets and activities enable firms to realize business opportunities. Knowledge about such configurations elucidates the interconnected structures and the complex causal patterns among factors at different levels of granularity. Moreover, such knowledge facilitates inferences regarding the content, structure, and governance mechanisms of business models, that is, the key design elements of business models (Zott and Amit 2010). Furthermore, it might also point to multiple alternative configurations that support superior firm performance. As Baden-Fuller and Morgan (2010, p. 166) note, Bthere is no one way by which a business can make money, but many generic types, and many possible variations within each.^ Hence, equifinal business model configurations for superior firm performance likely exist. These configurations may differ in their particular composition, but they represent alternative pathways that enable firms to create, deliver, and capture value (e.g., Taran et al. 2016). Third, the configurational perspective helps evaluate interdependence among single Bingredients^ and the extent to which those ingredients produce complementarity or substitution effects under a unifying theme. The components of a business model need to be synchronized and orchestrated when firms want to increase their competitive advantage. One illustrative example of such interplay was the decades-long success and market dominance of the OAG pocket flight guide, a subscription-based timetable of all flights in the U.S. targeted at business travelers. The market- and financial success of this product was driven by a nuanced coordination of all business model aspects. If only one aspect of the business model had been changed—such as pricing (low enough to ensure that purchasing was under the discretion of assistants), revenue channels (subscription), quality (updated regularly to mirror up-to-date flight information), or target group (sedulous business travelers)—the market leader’s dominance would have vanished immediately. However, given the orchestration of the various components, it was only the disruptive change of digitization that ultimately ended OAG’s dominance after several decades of success. Fourth, and related to the preceding point, the theoretical perspective advocated here contributes to the understanding of the role that particular elements (e.g., technological, human, or information resources) or components (e.g., marketing or

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innovation) can play within configurations, especially in regard to their causal essentiality for outcomes of interest. For example, product and process innovation likely represent core components of business models centered on novelty as the dominant theme of value creation, whereas customer relationship management and product and service customization should appear as core components in lock-in driven business models (Amit and Zott 2001). The core/periphery distinction (Fiss 2011) facilitates the prioritization of components in regard to goal achievement. Finally, the configurational lens can offer insights into business model dynamics, that is, compositional changes in a business model. Changes can include expansion (e.g., by adding activities or expanding existing activities), revision (e.g., by eliminating activities or substituting them), or, in an extreme form, termination (e.g., by giving up an entire business model) (Cavalcante et al. 2011). Changes typically occur in response to environmental and/or firm-internal forces (Demil and Lecocq 2010). For example, rapid changes in technology, the entrance of new competitors in a market, or shifts in customer preferences may pose environmental constraints that push firms to adapt an existing business model. In addition, changes in a firm’s resource endowment (e.g., through inventions or discoveries, new access to financial resources, or recruitment of talents) or strategy shifts (e.g., due to changes in top management teams) may lead to alterations of a firm’s business model. The configurational perspective on business models may then contribute to explaining business model dynamics by describing the interplay among business model components and external and internal forces. This perspective may reveal business models that can withstand such forces, thus pointing to robust configurations of components, or it may indicate the external and/or internal forces under which the configuration of a business model changes, thus pointing to tipping points (Gladwell 2006) for business model dynamics. In summary, the above account of the business model as a configuration helps connect existing perspectives on the concept based on a sound theoretical foundation and provides explanations for key processes such as business model design and change. As such, this perspective offers a system of inquiry that enables marketing researchers to engage in theory development and testing of business models as well as of the components and elements they contain (see Table 2).

Marketing in business model configurations Institutions, processes, and capabilities as elements of marketing The understanding of business models as configurations raises the question of how particular activities of a firm can

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AMS Rev (2017) 7:138–153 Configurational perspective on business models

Configurational perspective considers: Conjunctural causality Equifinality Causal asymmetry Causal essentiality

Derived questions for marketing research

Business model configurations depict: Components that contribute to goal achievement The interplay of these components The role of specific components Business model configurations help infer: Content Structure Governance Dynamics Configurational perspective on business models contributes to: Business model design Business model change

contribute to the realization of the overall objectives of value creation, value delivery, and value capturing. If the business model is understood as a configuration, an activity will generate value if it is an essential part of the configuration that is sufficient for the accomplishment of the overall goals of the firm. In what follows, we focus on marketing and assess its potential role within business models. For this purpose, we draw on core notions of the definition of marketing suggested by the American Marketing Association (AMA) (2013). According to this definition, marketing refers to Bthe activity, set of institutions, and processes for creating, communicating, delivering, and exchanging offerings that have value for customers, clients, partners, and society at large.^ In addition to that definition, we consider the discussion of marketing capabilities as levers that marketing institutions rely on to perform marketing activities through efficient and effective processes. In the following, we discuss three different aspects of marketing—institutions, processes, and capabilities—and link them to business model configurations. Marketing institutions According to Gundlach and Wilkie (2009, p. 259), the AMA’s (2013) definition of marketing Backnowledges that institutions such as manufacturers, wholesalers, retailers, and marketing research firms are an important part of marketing.^ More generally, institutions encompass individual and organizational actors that participate in marketing activities. These actors fulfill different roles and pursue at least partially differing objectives. However, they are jointly involved in performing marketing tasks. From this vantage point, business models as configurations that include marketing can be interpreted as configurations that encompass marketing institutions (such as customers,

How do marketing and non-marketing components combine to form business model configurations for business success? What configurations of marketing and non-marketing components are equifinal for business success? What marketing and non-marketing components complement, substitute, or suppress each other and why? What role (core vs. peripheral) do marketing components play in success-enhancing business model configurations? How do firm-internal and -external forces affect business model configurations, their composition, and their components? Which tipping points need to be passed to increase or decrease the role of marketing components in business model configurations?

retailers, and M&S staff) and non-marketing institutions (such as controllers or production employees) and integrate them in a meaningful system. The marketing channel literature is one of the oldest streams of research in the field and has focused on the role that intermediaries play in linking production and consumption. In recent years, contributions discussing disintermediation, re-intermediation, and the appearance of new digital intermediaries have stressed the importance of institutions and their use role in marketing (e.g., Berthon et al. 2003; Chircu and Kauffman 1999; Rosenbloom 2013). The observation that markets increasingly move toward network structures and that the outsourcing of marketing processes to specialized marketing institutions, such as event agencies, market research firms, and advertising agencies, reflects this trend and has increased the need for marketers to carefully consider the possible configurations that they can use to perform their focal activity. Marketing processes Second, marketing as an activity is embedded in core business processes (Srivastava et al. 1999). Marketing connects the customer with the product, service delivery, and financial accountability (Moorman and Rust 1999), thus contributing to the processes of value creation, delivery, and capture. For example, Homburg et al. (2015) show that marketing participates in decision-making in several areas that cover both marketing issues (i.e., pricing, advertising messages, distribution strategy, design of customer service and support, customer satisfaction measurement, and customer satisfaction improvement) and non-marketing issues (i.e., strategic direction of the business unit, choice of strategic business partners, new product development, major capital expenditures, and expansion into new geographic markets).


In addition, they demonstrate that marketing’s overall influence within the firm has a significant positive effect on firm performance. From this vantage point, business models as configurations that include marketing can be interpreted as configurations that encompass marketing processes and non-marketing processes and integrate them in a meaningful system. Srivastava et al. (1999) note that marketing processes are central contributors to the core business processes of a firm, that is, the product development management process, the supply chain management process, and the customer relationship management process. Hence, marketing must connect to these processes both as a discipline and through marketing sub-processes. The connection can take different forms and, thus, lead to different process-based configurations. Marketing capabilities For its processes to operate efficiently and effectively, marketing leverages sets of capabilities. Capabilities are Bcomplex bundles of skills and accumulated knowledge, exercised through organizational processes that enable firms to coordinate activities and make use of their assets^ (Day 1994, p. 38). Marketing capabilities can be classified as specialized and architectural capabilities (Vorhies et al. 2009). Specialized capabilities are the functionally focused capabilities that emerge from the integration of specialized employee knowledge, such as product and service development; personal selling; pricing, advertising and promotion; and distribution capabilities. Architectural capabilities are the capabilities that direct the coordination of specialized capabilities, thus focusing resource deployment on goal achievement. Examples of architectural marketing capabilities are environmental scanning, market planning, skill development, and internal coordination and communication capabilities. As prior work indicates, marketing capabilities per se have significant positive effects on performance outcomes (e.g., Morgan et al. 2009; Vorhies et al. 2009; Vorhies and Morgan 2005). For example, information processing – not only between marketing actors but also between marketing actors and non-marketing actors – represents a key driver of the development of marketing capabilities (Vorhies 1998). Business models as configurations that include marketing can then be interpreted as configurations that encompass marketing capabilities and non-marketing capabilities and integrate them in a meaningful system.

Components of marketing and components of business models Comparing the literature streams that discuss institutions, processes, and capabilities in marketing, on the one hand, and the business model components that have been identified in the business model literature, on the other hand (e.g., Hedman and Kalling 2003; Morris et al. 2005; Osterwalder and Pigneur

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2010; Shafer et al. 2005; Wirtz et al. 2016), it becomes obvious that—without exception—the latter systematically encompass components that tap into the domain of marketing (e.g., branding, customer relationship management, customer value, distribution, market offering, pricing). The marketingrelated components mentioned in enumerations of business model elements vary in type and in number, but none of these lists excludes them. Thus, marketing could be considered as an essential ingredient of business model configurations, and one could conclude that configurations that lack marketing activities are likely to fail. The variation in type and number of marketing activities in existing business model conceptualization links back to the different themes (e.g., novelty or efficiency) around which business model components can be orchestrated (Amit and Zott 2001; Zott and Amit 2007). From a configuration theoretical perspective, marketing institutions, processes, and capabilities constitute a sub-set of all of the components of a business model. As such, marketing processes should complement non-marketing processes, which may be conducted by other actors within the firm and beyond (e.g., customers, suppliers), in a synergistic way to bring about Ba system of mutually enhancing elements^ (Milgrom and Roberts 1995, p. 204). In a similar vein, marketing institutions and marketing capabilities require integration with non-marketing counterparts to unleash reinforcing effects that contribute to the accomplishment of overall performance goals. Empirical studies support this account. For example, Song et al. (2005) demonstrate that complementarity of marketing capabilities and technological capabilities, as typically developed in the R&D or manufacturing functions of a firm, can improve performance outcomes. From a marketing perspective, the model suggests that alignment must be sought with non-marketing processes, institutions, and capabilities and that marketing initiatives cannot be designed without regard to the non-marketing elements of a business model. At the same time, from a corporate management perspective, the model also suggests that marketing elements represent important contributors to a firm’s overall business model and that the corporate-level must ensure that, when designing and implementing a business model, the marketing and non-marketing elements of the business model are well aligned and coalesce.

A configurational approach to explain marketing’s role in digitized business models A configurational approach is particularly important when explaining marketing’s role in digitized business models. Digitization has important effects on business models (Leischnig et al. 2016b; Loebbecke and Picot 2015), as it affects the individual components of business model configurations as well as their interplay. Given such fundamental changes, we also expect marketing’s role to change in those


business model configurations. In the following, we will focus on three prevailing digital business model configurations and elaborate on marketing’s modified role in such configurations. First, digitalization fosters the trend toward asset-light business model configurations (Reddy and Reinartz 2017). In such digital business models, tangible assets (e.g., hotel rooms, cars) are replaced by intangible ones, such as brands, distribution management, and the availability of a digital platform that allows matching demand and supply (lock-and-key model). An archetypal model of such digital, asset-light business model can be found in the hotel industry: While in the past, possession of tangible assets, namely physical hotel buildings, was a key determinant of success, new entrant Airbnb does not own any significant real estate. This company focuses on matching the accommodation supply of landlords and the accommodation demands of guests by providing a technologically sophisticated digital platform and by capitalizing on a strong brand. Instead, in the traditional, assetfocused hotel industry, marketing’s role was strongly focused on advertising and customer service (Zervas et al. 2017). Platforms in this configuration of business model generate revenues through fees for each successful match, not through direct pricing for the rooms and related services provided by the firm. In the digitized, asset-light business model, the role of marketing institutions, processes, and capabilities changes. In the traditional business model configuration, marketing focused on customers (e.g., hotel guests) and potential intermediaries (e.g., travel agencies) as the fundamental marketing institutions. In the digitized configuration, new institutions (e.g., landlords) become core marketing institutions in the business model configuration and thus require attention from corporate marketing. Marketers managing such a business model need to dedicate time and effort to increase brand awareness, create a positive brand image among those newly relevant institutions, and attract them to the new platform. With regard to processes, the role of distribution becomes emphasized within the digital, asset-light business model configuration. Moreover, customer feedback processes move from a more peripheral role in the traditional, asset-focused configuration to a core role in the digital, asset-light business model configuration. One key success factor of a digital asset-light platform business model is that it allows customers to rate the actual service providers and vice versa. Building on prior experience with how to efficiently and effectively collect, analyze, and use customer feedback, marketers thus need to develop processes to integrate customer ratings as an element of platform solutions. With regard to capabilities, the fast and simple matching of supply and demand has become key. Hence, marketers need to understand which mechanisms will be perceived as intuitive, safe, effective and efficient both for landlords and guests. In addition, digital asset-light business model configurations

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require marketers to focus even more on building up a strong brand. Because most customers only use one or very few platforms for a specific service they are seeking (HennigThurau et al. 2010), branding becomes a core capability in such business model configurations. Therefore, the relevance of marketing increases in asset-light, platform-based business model configurations and requires marketers to develop new capabilities and processes. A second important form of digital business model configurations is the customization of offered products and goods. A digitized ERP system, together with direct customer interaction, as well as new technologies such as 3D–printing and the internet of things, allows firms to tailor products to customer needs and to customize products. Examples of such customization-based business model are the firm Me & Goji (now owned by Element Bars), which allows customers to customize their cereals, thereby choosing from dozens of individual ingredients (summing up to billions of theoretical cereal variants), and Shutterfly Inc., a US-based company specializing in personalized photos and services to, for example, produce keepsakes. While marketing-related institutions may remain rather unchanged when moving to such a business model, the required marketing- and non-marketing processes, and in particular their interplay, likely do change: Information provided by customers through the ordering process needs to be smoothly transferred to the purchasing and production departments of the firm. As such, tailored digital business model configurations require not only efficient and effective marketing processes, such as communication with customers, but also closer integration and coordination of marketing and non-marketing processes, which becomes a core element of such configurations. Instead of selling predefined products, the firm now markets products that are built by following an order. Consequently, marketers in such organizations need to optimize intra-firm interaction and communication processes. In terms of capabilities, firms practicing such a business model need to instill agility into their production and supply chain systems in order to respond to customer demand with competitive speed. Moreover, while it does not predefine the finished goods, the firm’s mass customization system requires the capability to understand which basic elements should be included in the product configurator. This capability is crucial not only to avoid complexity costs for the firm but also to avoid confusion and information overload among potential customers. A third pervasive digital business model configuration is that of sales of digitized goods and services via online channels. An archetypal example is the case of digitized publishing, where publishers aim to sell information or entertainment to their customers. Business cases include major newspapers such as the New York Times and the publishing branch of Amazon. What is striking here is the importance of price-


setting processes and related capabilities. While established news and entertainment firms are typically well versed in market research (what does the customer want?), product development, and sales activities, it is the pricing model that makes the digital business models of publishing challenging. In contrast to physical goods, virtual goods can often easily be copied and multiplied, and customers are increasingly used to consuming free product and service offerings. Thus, marketing skills such as setting the right prices and defining sophisticated revenue models turn out to be a core competency in this business model configuration. This, in turn, requires the capability to communicate value effectively. Because consumers’ willingness-to-pay depends on the amount of value they perceive in an offering, the sales of digital goods and services depends crucially on the ability of marketers to explain the value proposition convincingly, not only in absolute terms but also in comparison with the often-numerous competitor offerings. In addition to the change in business model components and their interactions, digitization also increases the number of equifinal business model configurations a firm can practice at the same time. In other words, digitization enables organizations to develop multiple business models and run them in parallel to increase overall firm performance (Benson-Rea et al. 2013). For instance, Tesco, over the years, has grown to become the largest brick-and-mortar retailer in the UK. In the course of digitalization, it also started to offer online delivery services as well as click-and-collect options, with customers picking up products they order online at a physical outlet the next day. While multiple business model configurations allow firms to target different customer groups, minimize their risk through diversification, and, in turn, improve their firm performance (Aversa et al. 2017), this approach also carries significant risk: Some of the asset configurations might conflict with each other. For instance, Casadesus-Masanell and Tarzijan (2012) describe the cases of established airlines that have attempted to introduce no-frills offerings to compete against low-cost rivals and have failed to align both business models. In order to execute multiple business models in parallel, a clear and nuanced understanding of customers is necessary. This capability encompasses identifying the key cause-effect relations of marketing and sales processes as well as other processes, such as supply chain management. These causeeffect relations need to be identified in each business model configuration. However, the firm also needs the capability to understand the complex interaction effects between the business models it practices in parallel. Only if the multiple facets of the various customer groups are well understood, and also dynamically monitored over time, can such multiple business model configurations be successful in the mid-and long term. Marketing, especially marketing intelligence, provides the tools, systems, and knowledge to monitor and understand

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customers; in a digitized world with multiple business model configurations in parallel, this capability will need to be developed at a higher level. More specifically, in a digitized world, marketers of organizations with multiple, potentially conflicting, potentially synergistic business model configurations need to ensure they have the processes to collect relevant data and learn how to gather, store and make sense of this big data. Table 3 summarizes these examples of business model changes in a digital economy as well as their implications for marketing.

Discussion The purpose of this article is to discuss what a configurational approach to business model thinking contributes to marketing research and practice. In particular, it discusses how a configurational perspective can support marketing scholars and practitioners in investigating and understanding business model thinking in a digital economy. Drawing on configuration theory (Fiss 2011; Ketchen et al. 1993; Meyer et al. 1993), this article proposes a useful perspective on business models, offers a definition of the concept, and outlines benefits that the configurational lens can provide for business model design and change. The configurational perspective constitutes a useful way to tackle complex causality and deepen the understanding of such issues as conjunctural causality, equifinality, causal essentiality, and causal asymmetry. As such, the configurational perspective may serve as a system of inquiry to improve knowledge of business model configurations that are sufficient for effective value creation, delivery, and appropriation. Against this background, we offer the following avenues for further research.

Substantive directions for future research There is a need for more research that examines the complex causality inherent to business models and the role that marketing components play in these complex causal situations. The existing lists of components and elements, as provided in the business model literature as well as in the institutionsprocesses-capabilities view suggested in this article, may serve as starting points to design empirical studies and examine how these factors work together and contribute to overall business success. In particular, research should be directed toward identifying configurations of marketing and nonmarketing institutions, processes, and capabilities that yield superior performance. Such research may be conducted with a focus on one specific industry or across industries. It could, for example, start by analyzing well-known business models, such as the Bfreemium^ model or the Block-in^ model, and provide a better understanding of the elements these models encompass. For example, it is unclear whether these larger

Business Example

AirBnB, Uber

Me & Goji (now: Element Bars), Shutterfly

Amazon, New York Times

LAN airlines, Tesco

Change to asset-light business models

Change to customer-tailored business models

Change to sales of digitized goods and services

Change to multiple, simultaneously run business model configurations

Implications for Marketing Strategy and Decisions

Business Model Changes in the Digital Economy

Table 3

Causal essentiality: - Increased availability and importance of handling Bbig data^ and customer communication Equifinality: - Technology enables communication with customers through multiple channels such as internet, smartphone applications, phone, etc. Causal essentiality and causal asymmetry: - Customers more and more used to free offerings - Digitized goods can be easily copied and multiplied Equifinality: - Digital goods available in unlimited number to various different customers Equifinality: - New technologies and digital solutions allow addressing multiple customer groups at the same time - Diversification mitigates risk and maximizes revenues, however, is also often associated with failure because of conflicting assets

Causal asymmetry and causal essentiality: - Core elements of previous business models such as tangible assets get replaced by intangible assets - Increased importance of platforms

Elements of Configurational Perspective to explain the Business Model Change

- Better understanding of the various customer groups and their precise value functions required - Dynamic monitoring of customer groups required - Adaptation of marketing and sales activities to specific customer groups

- Service providers such as landlords become important additional marketing institutions - Shift from advertising and customer service to distributions processes and process of how to handle customer feedback - Brand building capabilities more important - Processes of handling customer requests and transferring information to non-marketing departments such as purchasing and production more important - Improved communication skills required, in particular interaction among marketing and non-marketing units - Forecast of customer demands become less important capabilities - Broader range of customer communication channels required - Increased importance of price setting capabilities - Market research needs to adapt their established processes and routines to find out about the consumers’ willingness to pay for digital products - More sophisticated revenue models required

Contribution to Marketing Strategy and Decisions

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categories of business models always employ precisely the same configurations of elements or whether there are Bsubbusiness models^ that follow a similar principle but by combining marketing and non-marketing elements in different ways. However, even a comparison of business models, such as that by Gassmann et al. (2014), would provide interesting insights into the extent of differences among the 55 alternative business models these authors identify. The results of such inquiries would offer insights into patterns of components sufficient for achieving the focal outcome and might uncover themes other than those already identified in the literature. In addition, such inquiries would deepen knowledge of the causal essentiality of particular components in configurations targeting a particular outcome. This knowledge is particularly useful for business model design and innovation. Key research questions derived from these considerations are the following: What business model configurations are sufficient for business success? How do marketing and non-marketing components combine to form these configurations? What role (core vs. peripheral) do marketing components play in well-performing business model configurations? A further avenue for future research concerns how firminternal and external forces shape business models. Marketing research has produced numerous studies that analyze how environmental conditions affect marketing processes, decisions and the like. For example, Calantone et al. (2003) study the effect of environmental turbulence on new product development planning strategy. Other research fields have also studied the effect of the same, as well as of other environmental factors (e.g., environmental complexity) on institutions, processes, and capabilities in areas such as manufacturing or purchasing (e.g., Azadegan et al. 2013). This research typically studies the effect of firm-internal or firm-external antecedent variables on individual outcome variables. To the best of our knowledge, there is a gap in the literature with respect to the forces that lead to specific configurations of business models. Thus, future empirical research should collect data that encompass both measures that capture business model configurations and measures of firm-internal and -external forces to identify robust business model configurations and/or tipping points for change. For example, more research is needed about environmental factors, such as environmental turbulence, and their impact on business model configurations. On the basis of our theoretical discussion, research may differentiate between forces shaping the marketing components of a given business model and forces shaping non-marketing components. Such knowledge is particularly useful for business model transformation. Research questions derived from this line of reasoning include the following: How do firm-internal and external forces affect business model configurations, their composition, and their components? Which tipping points

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have to be passed to increase or decrease the role of marketing components in business model configurations? In addition, future studies could assess how the marketing components of business models relate to components provided by other actors. A comprehensive understanding of business model configurations, as well as of the role that marketing components may play in them, contributes to both theory and marketing practice. In particular, studies may identify possible conflicts between marketing and non-marketing institutions, processes, and capabilities. From a theoretical point of view, such research may inform about design alternatives and the possible contribution of marketing to performance outcomes. From a managerial point of view, such research may help clarify and justify the role of marketing within the firm and enable marketing employees to explain it more clearly to other actors. Such research would also allow managers to avoid implementing marketing and non-marketing combinations of processes, institutions, and capabilities that are incompatible and, hence, lead to sub-optimal performance outcomes. In the marketing literature, several studies examine the interplay between marketing and other functions within firms. For example, some articles focus on the specific interfaces between marketing and R&D (e.g., Gupta et al. 1986), marketing and manufacturing (Calantone et al. 2002), finance (Zinkhan and Verbrugge 2000), or – within the field of marketing – the interface between sales and marketing (Dewsnap and Jobber 2000). Other studies focus on cross-functional integration between marketing and other functions (e.g., Brettel et al. 2011; Krohmer et al. 2002; Song et al. 1998). While this body of work identifies, for example, success factors and barriers to the alignment between marketing and specific other functions, or measures the impact of the degree of cross-functional dispersion of marketing on firm performance, it does not provide insights into the complex interplay among marketing institutions, processes, and capabilities or their nonmarketing equivalents. A configurational perspective on business models will allow the identification of the combinations of marketing and non-marketing elements that yield equally positive or negative outcomes. Thus, this perspective allows highlighting the other functions within the firm with which marketing actors need to be well aligned. Accordingly, these interfaces should receive special attention from management. For example, when practicing a business model that is closely related to the timing of cash flows or ensuring certain levels of firm liquidity, marketers may need to be strongly aligned with accounting and finance. In other configurations, for example when the business model is built around mass customization, the most important alignment tasks may concern the link between marketing and the supply chain, or between marketing and production. Identifying these interface challenges becomes relevant when firms consider changing their business model.


Depending on the key interfaces in the existing business model, moving to a new business model may require increasing alignment and collaboration at new interfaces and (at least partially) reducing alignment and cooperation at other interfaces. Firms need to prepare carefully for such changes. The extent to which these changes are either more or less challenging depends on several factors, such as the thought worlds of the units involved (e.g., Homburg and Jensen 2007). The stronger the difference between the respective thought worlds, the longer the change process is likely going to take and the more complex it will be. Hence, for managers it is worthwhile to analyze whether the long-term benefits of a switch towards a specific business model overcompensate the financial and non-financial costs of the change. In the event that an analysis shows that other configurations of elements represent an equifinal business model, it is possible to avoid a difficult implementation by switching to another business model that is less difficult to put in place. Configuration theory provides the foundation on which such theoretically interesting and managerially relevant research can be conducted. Research questions that pertain to this are the following: What configurations of marketing and non-marketing institutions, processes, and capabilities are equifinal for business success? What marketing and nonmarketing institutions, processes, and capabilities complement, substitute, or suppress each other and why? Which interfaces between marketing and other units require particular management attention in a given business model?

Methodological directions for future research To realize such endeavors and explore, describe, and probe configuration theories that extend beyond contingency theories (e.g., Meyer et al. 1993), recent advances in empirical methods offer helpful tools, most notably fuzzy-set Qualitative Comparative Analysis (fsQCA; Ragin 2008). FsQCA has attracted strong interest in configurational research (e.g., Geigenmüller and Leischnig 2017; Misangyi et al. 2017) and is beginning to attract interest from business model scholars (Rumble and Mangematin 2015; Täuscher 2017). While an extensive discussion of this method is beyond the scope of our article, we would like to briefly describe the method to illustrate its key features. FsQCA is set-theoretic research approach that views cases (e.g., individuals or organizations) as combinations of attributes (i.e., antecedent conditions and outcome conditions; Fiss 2011; Ragin 2008). The basic idea behind fsQCA is to analyze the relationships among these conditions in terms of set relations (Fiss 2011; Ragin 2008). Evaluation of the set relations requires that the antecedent conditions and the outcome of interest be expressed in fuzzy-set membership scores. Fuzzy sets are formalized representations of the conditions under investigation, and cases can be evaluated in terms of their membership in

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sets. FsQCA describes cases that show desired values for the outcome in question by examining the degree to which antecedent conditions or configurations thereof are present. Thus, fsQCA describes how the membership of cases in (configurations of) antecedent sets is linked to membership in the outcome set (Fiss 2011; Ragin 2008). FsQCA considers multiple conjunctural causality (Ragin 2008) and takes into account that an outcome rarely has a single antecedent, that antecedents rarely operate in isolation from one another and that a specific antecedent may have opposite (i.e., positive or negative) effects depending on context (Greckhamer et al. 2008). In addition, fsQCA considers causal asymmetry and incorporates the notion of equifinality, thus offering insights into pathways for the presence and the absence of an outcome of interest (Ragin 2008). As such, it provides a useful tool for configurational research and analysis.

Conclusion This article argues for the usefulness of configuration theory and explains how a configurational perspective can support marketing scholars and practitioners in investigating and understanding business model thinking in a digital economy. With the continuing rise of both digitalization and managerial awareness of the business model concept, we expect the further development of a research stream around these two concepts in the field of marketing. We call for both conceptual and empirical research that tests the usefulness of configuration theory.

References Achrol, R. S., & Kotler, P. (2012). Frontiers of the marketing paradigm in the third millennium. Journal of the Academy of Marketing Science, 40(1), 35–52. https://doi.org/10.1007/s11747-011-0255-4. Afuah, A., & Tucci, C. L. (2001). Internet business models and strategies. New York: McGraw-Hill. American Marketing Association (2013): Marketing definition, https:// www.ama.org/AboutAMA/Pages/Definition-of-Marketing.aspx Amit, R., & Zott, C. (2001). Value creation in e-business. Strategic Management Journal, 22(6–7), 493–520. https://doi.org/10.1002/ smj.187. Amit, R., & Zott, C. (2015). Crafting business architecture: The antecedents of business model design. Strategic Entrepreneurship Journal, 9(4), 331–350. https://doi.org/10.1002/sej.1200. Aspara, J., Hietanen, J., & Tikkanen, H. (2010). Business model innovation vs replication: Financial performance implications of strategic emphases. Journal of Strategic Marketing, 18(1), 39–56. https://doi. org/10.1080/09652540903511290. Aversa, P., Furnari, S., & Haefliger, S. (2015). Business model configurations and performance: A qualitative comparative analysis in

Author's personal copy AMS Rev (2017) 7:138–153 formula one racing, 2005–2013. Industrial and Corporate Change, 24(3), 655–676. https://doi.org/10.1093/icc/dtv012. Aversa, P., Haefliger, S., & Reza, D. G. (2017). Building a winning business model portfolio. MIT Sloan Management Review, 58(4), 49–54. Azadegan, A., Patel, P. C., Zangoueinezhad, A., & Linderman, K. (2013). The effect of environmental complexity and environmental dynamism on lean practices. Journal of Operations Management, 31(4), 193–212. https://doi.org/10.1016/j.jom.2013.03.002. Baden-Fuller, C., & Morgan, M. S. (2010). Business models as models. Long Range Planning, 43(2), 156–171. https://doi.org/10.1016/j.lrp. 2010.02.005. Barquet, A. P. B., de Oliveira, M. G., Amigo, C. R., Cunha, V. P., & Rozenfeld, H. (2013). Employing the business model concept to support the adoption of product–service systems (PSS). Industrial Marketing Management, 42(5), 693–704. https://doi.org/10.1016/j. indmarman.2013.05.003. Benson-Rea, M., Brodie, R. J., & Sima, H. (2013). The plurality of coexisting business models: Investigating the complexity of value drivers. Industrial Marketing Management, 42(5), 717–729. https://doi.org/10.1016/j.indmarman.2013.05.011. Berthon, P., Ewing, M., Pitt, L., & Naudé, P. (2003). Understanding B2B and the web: The acceleration of coordination and motivation. Industrial Marketing Management, 32(7), 553–561. https://doi. org/10.1016/S0019-8501(02)00279-1. Brettel, M., Heinemann, F., Engelen, A., & Neubauer, S. (2011). Crossfunctional integration of R&D, marketing, and manufacturing in radical and incremental product innovations and its effects on project effectiveness and efficiency. Journal of Product Innovation Management, 28(2), 251–269. https://doi.org/10.1111/j.1540-5885. 2011.00795.x. Calantone, R., Dröge, C., & Vickery, S. (2002). Investigating the manufacturing–marketing interface in new product development: Does context affect the strength of relationships? Journal of Operations Management, 20(3), 273–287. https://doi.org/10.1016/ S0272-6963(02)00009-8. Calantone, R., Garcia, R., & Dröge, C. (2003). The effects of environmental turbulence on new product development strategy planning. Journal of Product Innovation Management, 20(2), 90–103. https:// doi.org/10.1111/1540-5885.2002003. Casadesus-Masanell, R., & Ricart, J. E. (2010). From strategy to business models and onto tactics. Long Range Planning, 43(2), 195–215. https://doi.org/10.1016/j.lrp.2010.01.004. Casadesus-Masanell, R., & Ricart, J. E. (2011). How to design a winning business model. Harvard Business Review, 89(1/2), 100–107. Casadesus-Masanell, R., & Tarzijan, J. (2012). When one business model isn’t enough. Harvard Business Review, 90(1), 132–136. Cavalcante, S., Kesting, P., & Ulhøi, J. (2011). Business model dynamics and innovation: (re)establishing the missing linkages. Management Decision, 49(8), 1327–1342. https://doi.org/10.1108/ 00251741111163142. Chesbrough, H. (2010). Business model innovation: Opportunities and barriers. Long Range Planning, 43(2), 354–363. https://doi.org/10. 1016/j.lrp.2009.07.010. Chircu, A. M., & Kauffman, R. J. (1999). Strategies for internet middlemen in the intermediation/disintermediation/reintermediation cycle. Electronic Markets, 9(1–2), 109–117. Clark, J., El Sawy, O., & Pereira, F. (2012). Capabilities, configurations and customer-contexts: A business model framework for the process of digital service innovation. UCS Marshall School of Business. PTC 2012 Proceedings. Coombes, P. H., & Nicholson, J. D. (2013). Business models and their relationship with marketing: A systematic literature review. Industrial Marketing Management, 42(5), 656–664. https://doi. org/10.1016/j.indmarman.2013.05.005.

151 DaSilva, C. M., & Trkman, P. (2014). Business model: What it is and what it is not. Long Range Planning, 47(6), 379–389. https://doi. org/10.1016/j.lrp.2013.08.004. Day, G. S. (1994). The capabilities of market-driven organizations. Journal of Marketing, 58(4), 37–52. https://doi.org/10.2307/ 1251915. Demil, B., & Lecocq, X. (2010). Business model evolution: In search of dynamic consistency. Long Range Planning, 43(2), 227–246. https://doi.org/10.1016/j.lrp.2010.02.004. Demil, B., Lecocq, X., Ricart, J. E., & Zott, C. (2015). Introduction to the SEJ special issue on business models: Business models within the domain of strategic entrepreneurship. Strategic Entrepreneurship Journal, 9(1), 1–11. https://doi.org/10.1002/sej.1194. Dess, G. G., Newport, S., & Rasheed, A. M. (1993). Configuration research in strategic management: Key issues and suggestions. Journal of Management, 19(4), 775–795. https://doi.org/10.1177/ 014920639301900403. Dewsnap, B., & Jobber, D. (2000). The sales-marketing interface in consumer packaged-goods companies: A conceptual framework. Journal of Personal Selling & Sales Management, 20(2), 109–119. Doganova, L., & Eyquem-Renault, M. (2009). What do business models do?: Innovation devices in technology entrepreneurship. Research Policy, 38(10), 1559–1570. https://doi.org/10.1016/j.respol.2009. 08.002. Doty, D. H., & Glick, W. H. (1994). Typologies as a unique form of theory building: Toward improved understanding and modeling. Academy of Management Review, 19(2), 230–251. Doz, Y. L., & Kosonen, M. (2010). Embedding strategic agility: A leadership agenda for accelerating business model renewal. Long Range Planning, 43(2), 370–382. https://doi.org/10.1016/j.lrp.2009.07. 006. Ehret, M., Kashyap, V., & Wirtz, J. (2013). Business models: Impact on business markets and opportunities for marketing research. Industrial Marketing Management, 42(5), 649–655. https://doi. org/10.1016/j.indmarman.2013.06.003. Erevelles, S., Fukawa, N., & Swayne, L. (2016). Big data consumer analytics and the transformation of marketing. Journal of Business Research, 69(2), 897–904. https://doi.org/10.1016/j.jbusres.2015. 07.001. Ferreira, F. N. H., Proença, J. F., Spencer, R., & Cova, B. (2013). The transition from products to solutions: External business model fit and dynamics. Industrial Marketing Management, 42(7), 1093– 1101. https://doi.org/10.1016/j.indmarman.2013.07.010. Fiss, P. C. (2011). Building better causal theories: A fuzzy set approach to typologies in organization research. Academy of Management Journal, 54(2), 393–420. https://doi.org/10.5465/AMJ.2011. 60263120. Fiss, P. C., Marx, A., & Cambré, B. (2013). Configurational theory and methods in organizational research: Introduction. In P. C. Fiss, B. Cambré, & A. Marx (Eds.), Configurational theory and methods in organizational research. Research in the sociology of organizations (pp. 1–22). Bingley: Emerald. https://doi.org/10.1108/S0733558X(2013)0000038005. Gassmann, O., Frankenberger, K., & Csik, M. (2014). The business model navigator. Harlow: Pearson Education Limited. Geigenmüller, A., & Leischnig, A. (2017). A configurational perspective on alliance management capabilities. In T. K. Das (Ed.), Managing alliance portfolios and networks. Research in strategic alliances (pp. 71–90). Charlotte, NC: Information Age Publishing. Gladwell, M. (2006). The tipping point: How little things can make a big difference. Boston: Little, Brown. Grandori, A., & Furnari, S. (2008). A chemistry of organization: Combinatory analysis and design. Organization Studies, 29(3), 459–485. https://doi.org/10.1177/0170840607088023. Greckhamer, T., Misangyi, V. F., Elms, H., & Lacey, R. (2008). Using qualitative comparative analysis in strategic management research:

Author's personal copy 152 An examination of combinations of industry, corporate, and business-unit effects. Organizational Research Methods, 11(4), 695–726. https://doi.org/10.1177/1094428107302907. Gresov, C., & Drazin, R. (1997). Equifinality: Functional equivalence in organization design. Academy of Management Review, 22(2), 403– 428. Gundlach, G. T., & Wilkie, W. L. (2009). The American marketing Association's new definition of marketing: Perspective and commentary on the 2007 revision. Journal of Public Policy & Marketing, 28(2), 259–264. https://doi.org/10.1509/jppm.28.2.259. Gupta, A. K., Raj, S. P., & Wilemon, D. (1986). A model for studying R&D. Marketing interface in the product innovation process. Journal of Marketing, 50(2), 7–17. https://doi.org/10.2307/ 1251596. Hedman, J., & Kalling, T. (2003). The business model concept: Theoretical underpinnings and empirical illustrations. European Journal of Information Systems, 12(1), 49–59. https://doi.org/10. 1057/palgrave.ejis.3000446. Hennig-Thurau, T., Malthouse, E. C., Friege, C., Gensler, S., Lobschat, L., Rangaswamy, A., & Skiera, B. (2010). The impact of new media on customer relationships. Journal of Service Research, 13(3), 311– 330. https://doi.org/10.1177/1094670510375460. Hoffman, D. L., & Novak, T. P. (2005). A conceptual framework for considering web-based business models and potential revenue streams. International Journal of Marketing Education, 1(1), 7–34. Homburg, C., & Jensen, O. (2007). The thought worlds of marketing and sales: Which differences make a difference? Journal of Marketing, 71(3), 124–142. https://doi.org/10.1509/jmkg.71.3.124. Homburg, C., Vomberg, A., Enke, M., & Grimm, P. H. (2015). The loss of the marketing department’s influence: Is it really happening? And why worry? Journal of the Academy of Marketing Science, 43(1), 1– 13. https://doi.org/10.1007/s11747-014-0416-3. Katz, D., & Kahn, R. L. (1978). The social psychology of organizations (2nd ed.). New York: Wiley. Ketchen, D. J., Thomas, J. B., & Snow, C. C. (1993). Organizational configurations and performance: A comparison of theoretical approaches. Academy of Management Journal, 36(6), 1278–1313. https://doi.org/10.2307/256812. Kindström, D., & Kowalkowski, C. (2014). Service innovation in product-centric firms: A multidimensional business model perspective. Journal of Business & Industrial Marketing, 29(2), 96–111. https://doi.org/10.1108/JBIM-08-2013-0165. Krohmer, H., Homburg, C., & Workman, J. P. (2002). Should marketing be cross-functional? Conceptual development and international empirical evidence. Journal of Business Research, 55(6), 451–465. https://doi.org/10.1016/S0148-2963(00)00176-4. Kulins, C., Leonardy, H., & Weber, C. (2016). A configurational approach in business model design. Journal of Business Research, 69(4), 1437–1441. https://doi.org/10.1016/j.jbusres.2015.10.121. Lambert, S. C., & Davidson, R. A. (2013). Applications of the business model in studies of enterprise success, innovation and classification: An analysis of empirical research from 1996 to 2010. European Management Journal, 31(6), 668–681. https://doi.org/10.1016/j. emj.2012.07.007. Leischnig, A., Henneberg, S. C., & Thornton, S. C. (2016a). Net versus combinatory effects of firm and industry antecedents of sales growth. Journal of Business Research, 69(9), 3576–3583. https:// doi.org/10.1016/j.jbusres.2016.01.005. Leischnig, A., Wölfl, S., & Ivens, B. (2016b). When does digital business strategy matter to market performance? In Association for Information Systems (AIS), Proceedings of the International Conference on Information Systems, Dublin/Ireland. http://aisel. aisnet.org/icis2016/ISStrategy/Presentations/13/. Loebbecke, C., & Picot, A. (2015). Reflections on societal and business model transformation arising from digitization and big data

AMS Rev (2017) 7:138–153 analytics: A research agenda. Journal of Strategic Information Systems, 24(3), 149–157. https://doi.org/10.1016/j.jsis.2015.08.002. Maglio, P. P., & Spohrer, J. (2013). A service science perspective on business model innovation. Industrial Marketing Management, 42(5), 665–670. https://doi.org/10.1016/j.indmarman.2013.05.007. Magretta, J. (2002). Why business models matter. Harvard Business Review, 80(5), 86–92. Markides, C., & Charitou, C. D. (2004). Competing with dual business models: A contingency approach. Academy of Management Executive, 18(3), 22–36. https://doi.org/10.5465/AME.2004. 14776164. Mason, K., & Spring, M. (2011). The sites and practices of business models. Industrial Marketing Management, 40(6), 1032–1041. https://doi.org/10.1016/j.indmarman.2011.06.032. Meyer, A. D., Tsui, A. S., & Hinings, C. R. (1993). Configurational approaches to organizational analysis. Academy of Management Journal, 36(6), 1175–1195. https://doi.org/10.2307/256809. Milgrom, P., & Roberts, J. (1995). Complementarities and fit strategy, structure, and organizational change in manufacturing. Journal of Accounting and Economics, 19(2), 179–208. https://doi.org/10. 1016/0165-4101(94)00382-F. Miller, D. (1996). Configurations revisited. Strategic Management Journal, 17(7), 505–512. https://doi.org/10.1002/(SICI)10970266(199607)17:73.0.CO;2-I. Misangyi, V. F., Greckhamer, T., Furnari, S., Fiss, P. C., Crilly, D., & Aguilera, R. (2017). Embracing causal complexity: The emergence of a neo-configurational perspective. Journal of Management, 43(1), 255–282. https://doi.org/10.1177/0149206316679252. Moorman, C., & Rust, R. T. (1999). The role of marketing. Journal of Marketing, 63(Special Issue), 180–197. https://doi.org/10.2307/ 1252111. Morgan, N. A., Vorhies, D. W., & Mason, C. H. (2009). Market orientation, marketing capabilities, and firm performance. Strategic Management Journal, 30(8), 909–920. https://doi.org/10.1002/smj. 764. Morris, M., Schindehutte, M., & Allen, J. (2005). The entrepreneur's business model: Toward a unified perspective. Journal of Business Research, 58(6), 726–735. https://doi.org/10.1016/j.jbusres.2003. 11.001. Muzellec, L., Ronteau, S., & Lambkin, M. (2015). Two-sided internet platforms: A business model lifecycle perspective. Industrial Marketing Management, 45(2), 139–150. https://doi.org/10.1016/j. indmarman.2015.02.012. Ng, I. C., Ding, D. X., & Yip, N. (2013). Outcome-based contracts as new business model: The role of partnership and value-driven relational assets. Industrial Marketing Management, 42(5), 730–743. https:// doi.org/10.1016/j.indmarman.2013.05.009. Osterwalder, A., & Pigneur, Y. (2010). Business model generation: A handbook for visionaries, game changers, and challengers. Hoboken: John Wiley & Sons. Osterwalder, A., Pigneur, Y., & Tucci, C. L. (2005). Clarifying business models: Origins, present, and future of the concept. Communications of the Association for Information Systems, 16(1), 1–25. Palo, T., & Tähtinen, J. (2013). Networked business model development for emerging technology-based services. Industrial Marketing Management, 42(5), 773–782. https://doi.org/10.1016/j. indmarman.2013.05.015. Patzelt, H., Zu Knyphausen-Aufseß, D., & Nikol, P. (2008). Top management teams, business models, and performance of biotechnology ventures: An upper echelon perspective. British Journal of Management, 19(3), 205–221. https://doi.org/10.1111/j.1467-8551. 2007.00552.x. Pauwels, K., & Weiss, A. (2008). Moving from free to fee: How online firms market to change their business model successfully. Journal of Marketing, 72(3), 14–31. https://doi.org/10.1509/jmkg.72.3.14.

Author's personal copy AMS Rev (2017) 7:138–153 Piercy, N. F. (2009). Strategic relationships between boundary-spanning functions: Aligning customer relationship management with supplier relationship management. Industrial Marketing Management, 38(8), 857–864. https://doi.org/10.1016/j.indmarman.2009.03.015. Ragin, C. C. (2008). Redesigning social inquiry: Fuzzy sets and beyond (Vol. 240). Chicago: University of Chicago Press. https://doi.org/10. 7208/chicago/9780226702797.001.0001. Reddy, S., & Reinartz, W. (2017). Digital transformation and value creation: Sea change ahead. GfK Marketing Intelligence Review, 9(1), 10–17. Robertson, T. S. (2017). Business model innovation: A marketing ecosystem view. AMS review, online first version: Link.springer.com/ article/10.1007/s13162-017-0101-z, 1-11. Rosenbloom, B. (2013). Functions and institutions: The roots and the future of marketing channels. Journal of Marketing Channels, 20(3–4), 191–203. https://doi.org/10.1080/1046669X.2013. 803423. Rumble, R., & Mangematin, V. (2015). Business model implementation: The antecedents of multi-sidedness. In Business Models and Modelling (pp. 97–131). Bingley, UK: Emerald Group Publishing Limited. https://doi.org/10.1108/S0742-332220150000033021. Rust, R. T., & Huang, M. H. (2014). The service revolution and the transformation of marketing science. Marketing Science, 33(2), 206–221. https://doi.org/10.1287/mksc.2013.0836. Shafer, S. M., Smith, H. J., & Linder, J. C. (2005). The power of business models. Business Horizons, 48(3), 199–207. https://doi.org/10. 1016/j.bushor.2004.10.014. Shin, J., & Park, Y. (2009). On the creation and evaluation of e-business model variants: The case of auction. Industrial Marketing Management, 38(3), 324–337. https://doi.org/10.1016/j. indmarman.2007.06.017. Sirmon, D. G., Hitt, M. A., & Ireland, R. D. (2007). Managing firm resources in dynamic environments to create value: Looking inside the black box. Academy of Management Review, 32(1), 273–292. https://doi.org/10.5465/AMR.2007.23466005. Song, X. M., Thieme, R. J., & Xie, J. (1998). The impact of crossfunctional joint involvement across product development stages: An exploratory study. Journal of Product Innovation Management, 15(4), 289–303. https://doi.org/10.1016/S07376782(97)00108-2. Song, M., Droge, C., Hanvanich, S., & Calantone, R. (2005). Marketing and technology resource complementarity: An analysis of their interaction effect in two environmental contexts. Strategic Management Journal, 26(3), 259–276. https://doi.org/ 10.1002/smj.450. Sorescu, A., Frambach, R. T., Singh, J., Rangaswamy, A., & Bridges, C. (2011). Innovations in retail business models. Journal of Retailing, 87, S3–S16. https://doi.org/10.1016/j.jretai.2011.04.005. Srivastava, R. K., Shervani, T. A., & Fahey, L. (1999). Marketing, business processes, and shareholder value: An organizationally embedded view of marketing activities and the discipline of marketing. Journal of Marketing, 63(4), 168–179. https://doi.org/10.2307/ 1252110. Stewart, D. W., & Zhao, Q. (2000). Internet marketing, business models, and public policy. Journal of Public Policy & Marketing, 19(2), 287–296. https://doi.org/10.1509/jppm.19.2.287.17125. Storbacka, K. (2011). A solution business model: Capabilities and management practices for integrated solutions. Industrial Marketing Management, 40(5), 699–711. https://doi.org/10.1016/j. indmarman.2011.05.003.

153 Storbacka, K., Frow, P., Nenonen, S., & Payne, A. (2012). Designing business models for value co-creation. In S. L. Vargo & R. F. Lusch (Eds.), Towards a better understanding of the role of value in markets and marketing, review of marketing research (Vol. 9, pp. 51–78). Bingley, UK: Emerald Group Publishing Limited. Storemark, K., & Hoffmann, J. (2012). A case study on the business model of Chloé. Journal of Global Fashion Marketing, 3(1), 34– 41. https://doi.org/10.1080/20932685.2012.10593105. Taran, Y., Nielsen, C., Montemari, M., Thomson, P. P., & Paolone, F. (2016). Business model configurations: A five-V framework to map out potential innovation routes. European Journal of Innovation Management, 19(4), 492–527. https://doi.org/10.1108/ EJIM-10-2015-0099. Täuscher, K. (2017). Using qualitative comparative analysis and system dynamics for theory-driven business model research. Strategic O rg a n i z a t i o n , f o r t h c o m i n g , h t t p s : / / d o i . o rg / 1 0 . 11 7 7 / 1476127017740535. Teece, D. J. (2010). Business models, business strategy and innovation. Long Range Planning, 43(2), 172–194. https://doi.org/10.1016/j.lrp. 2009.07.003. Timmers, P. (1998). Business models for electronic markets. Electronic Markets, 8(2), 3–8. https://doi.org/10.1080/10196789800000016. Vorhies, D. W. (1998). An investigation of the factors leading to the development of marketing capabilities and organizational effectiveness. Journal of Strategic Marketing, 6(1), 3–23. https://doi.org/10. 1080/096525498346676. Vorhies, D. W., & Morgan, N. A. (2005). Benchmarking marketing capabilities for sustainable competitive advantage. Journal of Marketing, 69(1), 80–94. https://doi.org/10.1509/jmkg.69.1.80. 55505. Vorhies, D. W., Morgan, R. E., & Autry, C. W. (2009). Product-market strategy and the marketing capabilities of the firm: Impact on market effectiveness and cash flow performance. Strategic Management Journal, 30(12), 1310–1334. https://doi.org/10.1002/smj.798. Wind, Y. J. (2014). Toward a new marketing paradigm. In L. Mouthinho, E. Bigne, and A. K. Manrai (Eds.), The Routledge companion to the future of marketing (pp. 3–24). New York: Routledge, Taylor and Francis Group. 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. https://doi.org/10.1016/j.lrp. 2015.04.001. Zervas, G., Proserpio, D., & Byers, J. W. (2017). The rise of the sharing economy: Estimating the impact of Airbnb on the hotel industry. Journal of Marketing Research, in press. Zinkhan, G. M., & Verbrugge, J. A. (2000). The marketing/finance interface: Two divergent and complementary views of the firm. Journal of Business Research, 50(2), 143–148. https://doi.org/10.1016/ S0148-2963(99)00027-2. Zott, C., & Amit, R. (2007). Business model design and the performance of entrepreneurial firms. Organization Science, 18(2), 181–199. https://doi.org/10.1287/orsc.1060.0232. Zott, C., & Amit, R. (2010). Business model design: An activity system perspective. Long Range Planning, 43(2), 216–226. https://doi.org/ 10.1016/j.lrp.2009.07.004. Zott, C., Amit, R., & Massa, L. (2011). The business model: Recent developments and future research. Journal of Management, 37(4), 1019–1042. https://doi.org/10.1177/0149206311406265.