THE BUSINESS MODEL PATTERN DATABASE A …...business model concept helps to look “at the forest,...

THE BUSINESS MODEL PATTERN DATABASE— A TOOLFOR SYSTEMATIC BUSINESS MODEL INNOVATION

GERRIT REMANE*, ANDRE HANELT†, JAN F. TESCH‡

and LUTZ M. KOLBE§

University of G€ottingen, Chair of Information Management,Platz der G€ottingen Sieben 5, 37073 G€ottingen, Germany

*[email protected]†[email protected]‡[email protected]§[email protected]

Published 16 June 2016

Companies are more frequently seen shifting their focus from technological innovationtowards business model innovation. One efficient option for business model innovation isto learn from existing solutions, i.e., business model patterns. However, the variousunderstandings of the business model pattern concept are often confusing and contradic-tory, with the available collections incomplete, overlapping, and inconsistently structured.Therefore, the rich body of literature on business model patterns has not yet reached its fullpotential for both practical application as well as theoretic advancement. To help remedythis, we conduct an exhaustive review, filter for duplicates, and structure the patterns alongseveral dimensions by applying a rigorous taxonomy-building approach. The resultingbusiness model pattern database allows for navigation to the relevant set of patterns for aspecific impact on a company’s business model. It can be used for systematic businessmodel innovation, which we illustrate via a simplified case study.

Keywords: Business models; business model innovation; business model patterns; tax-onomy development.

Introduction

In advanced economies, innovative capacity is the strongest determent for nationsand companies gaining competitive advantage (Porter, 1990; Porter and Stern,2001). Therefore, companies often heavily invest in technological innovations bydeveloping new resources, plants, and even business units (Amit and Zott, 2012).

International Journal of Innovation ManagementVol. 21, No. 1 (January 2017) 1750004 (61 pages)© World Scientific Publishing Europe Ltd.DOI: 10.1142/S1363919617500049

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However, due to the increasing environmental turbulence in more and more in-dustries and markets (El Sawy et al., 2010), this approach not only tends to be veryexpensive but also exhibits uncertain returns on investments (Amit and Zott,2012). Furthermore, technological innovations are of little value without appro-priate business models (Chesbrough, 2010) — in fact, a good business model caneven make an inferior technology more successful than a superior one(Chesbrough, 2007). Hence, the design and implementation of new businessmodels has the potential to be more efficient than technological innovation (Teece,2010).

Research on the innovation of business models is spread across a variety offields, including information systems, strategic management, and technology andinnovation management (Abdelkafi et al., 2013; Schneider and Spieth, 2013; Zottet al., 2011). In contrast to other research streams such as product innovation,business model innovation is still at the beginning of its academic elaboration(Bucherer et al., 2012). This is somehow surprising due to the increasing im-portance of business model innovation for management practice, which requiresconceptual toolkits for business model design (Zott and Amit, 2010). Therefore,research on this matter should contribute to a better understanding by providingfirms with specific means, i.e., tools and methods, for business model innovation(Schneider and Spieth, 2013).

One such tool are business model patterns, which describe proven solutions torecurring problems during business model design (Abdelkafi et al., 2013). Theimportance of the concept is underlined by the finding that 90% of all businessmodel innovations are a recombination of existing business model patterns(Gassmann et al., 2014). Therefore, by drawing upon aspects that have alreadybeen proven to be successful for other companies and industries, the use ofbusiness model patterns provides an efficient way to undertake business modelinnovation (Abdelkafi et al., 2013). However, business model patterns must not bemisunderstood; they do not focus on imitating, but rather address efficiency, spurcreativity, and help to overcome cognitive barriers in the business model inno-vation process, which is of special importance in times of transformative change(Chesbrough, 2010).

An illustrative example and often cited instance of business model patterns israzors/blades (e.g., Gassmann et al., 2014; Johnson, 2010; Linder and Cantrell,2000). The pattern describes companies offering a cheap basic product (“razors”)with complements that must frequently be replaced (“blades”). These comple-ments are overpriced, thereby subsidizing the basic product. The pattern name wasderived from Gillette’s marketing efforts at the beginning of the twentiethcentury, when the company gave away razors in order to sell more blades(Gassmann et al., 2014). Since then, several companies have innovated their

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business models by adopting the razors/blades pattern. For instance, Nespresso, asub-brand of the Nestlé Corporation, introduced a new espresso maker that is soldfor less than comparable machines of competitors are (Amit and Zott, 2012). Theespresso maker, however, can only be used in combination with Nespresso-pro-duced coffee capsules. In contrast to traditional producers of coffee machines,Nespresso does not depend on gaining value from selling the machines becausethe company uses the machines to open up an even larger and continuous valuepool by selling the highly profitable capsules (Matzler et al., 2013).

Because business model patterns can be such a powerful tool for businessmodel innovation, several researchers assembled collections of business modelpatterns (e.g., Applegate, 2001; Gassmann et al., 2014; Johnson, 2010; Rappa,2001; Weill et al., 2005). Most researchers, however, have slightly differentunderstandings of the business model pattern concept. For instance, some col-lections discuss prototypical patterns describing holistic business models (e.g.,Weill et al., 2005), while others discuss solution patterns that are specific buildingblocks of business models (e.g., Johnson, 2010) and yet others mix both types ofpatterns (e.g., Gassmann et al., 2014). Furthermore, the patterns among the variouscollections strongly overlap, with many patterns occurring in multiple differentsources. However, no collection is exhaustive; even when applying the mostcomprehensive collection with 55 business model patterns from Gassmann et al.(2014), one misses more than the two-thirds of the available patterns. This di-versity in research is of particular value, as business reality is not uniform anddemands different solutions for different settings. Nevertheless, what is missing isa meta-perspective that describes which business model patterns are suitable forwhich purpose.

With this research we aim to make the valuable existing collections of businessmodel patterns more usable for both future business model pattern research as wellas practice applications. The goal of our work is to provide the respective audi-ences with a tool guiding them to the patterns most suitable for their individualsituations. Thus, we aim to bridge the gap between general business model pat-terns described in prior literature and specific business model innovation endea-vours in research and business practice. To do so, we conduct an exhaustivereview and integrate all patterns into one database. We filter for duplicates andstructure the patterns along several dimensions by applying a rigorous taxonomy-building approach. The database reveals the relevant set of patterns for a specificimpact on a company’s business model. Finally, we describe how to apply thedatabase for systematic business model innovation, which we illustrate using asimplified case study. The database thus increases the efficiency and effectivenessof business model innovations in practice by deriving contingency factors for thetargeted deployment of business model patterns. Furthermore, by filtering,

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structuring and categorizing business model patterns, the database provides acommon ground for the advancement of business model research, which for in-stance can be used to describe transformative effects stemming from technologicalor societal developments across industries.

Background

Before developing and presenting the business model pattern database, we brieflydefine the concepts on which we later build: the business model, business modelinnovation, and business model patterns.

The business model

The business model is a useful lens for understanding a company’s underlyinglogic because it describes what value is provided, how this value is created anddelivered, and how profits can be generated therefrom (Magretta, 2002). Thus, thebusiness model concept helps to look “at the forest, not the trees” (Amit and Zott,2012, p. 49). The concept has a variety of uses, such as capturing value fromtechnological innovations (Chesbrough and Rosenbloom, 2002), defining theboundaries of a firm (Zott and Amit, 2010), and creating a direct connectionbetween business strategy and business processes (Al-Debei and Avison, 2010).

To achieve a common understanding of the business model concept, severalauthors have identified elements belonging to a business model (e.g., Gordijnet al., 2005; Hedman and Kalling, 2003; Johnson, 2010; Osterwalder and Pigneur,2010). Probably the most popular example (Spieth et al., 2014) is the businessmodel canvas by Osterwalder and Pigneur (2010), shown in slightly adapted formin Table 1.

Business model innovation

Defining business models and describing their constituent elements has receivedmuch interest in academia and belongs to a static view on the concept. However,due to heightening environmental turbulence and transformative developments,recent research has shifted to a more dynamic view on business models (Wirtzet al., 2015). Business model innovation, i.e., “designing a new, or modifyingthe firm’s extant activity system” (Amit and Zott, 2010, p. 2), is important forstartups wanting to gain significantly in size as well as for incumbents looking toidentify new growth opportunities (Günzel and Holm, 2013). Business modelinnovations often result in additional yet unused sources of value generation

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(Amit and Zott, 2012). Compared to product innovation, innovations regardingthe business model are often harder to replicate (Amit and Zott, 2012) and cantherefore be a very strong competitive advantage (Magretta, 2002). At the sametime, however, business model innovations of competitors from within andoutside the industry can be a major threat to firms who fail to advance theirbusiness model in accordance with external changes (Amit and Zott, 2012). Forinstance, the new business model of no-frills airlines such as Ryanair haschanged the rules of competition for the whole airline industry (Demil et al.,2015).

A business model innovation happens when a company modifies or improvesone or several elements of its business model (Abdelkafi et al., 2013). Severalauthors describe the phases of business model innovation. For instance, Fran-kenberger et al. (2013) distinguish among initiation, ideation, integration, andimplementation. Schneider and Spieth (2013) mention exploration, exploitation,

Table 1. Elements of a business model.

Meta-componentBusiness modelbuilding block Description

Value proposition Value propositions Gives an overall view of a company’s bundle ofproducts and services.

Value delivery Customer segments An organization serves one or several customersegments.

Channels Value propositions are delivered to customersthrough communication, distribution, and saleschannels.

Customer relationships Customer relationships are established andmaintained with each customer segment.

Value creation Key resources Key resources are the assets required to offer anddeliver the previously described elements.

Key activities Number of key activities performed by keyresources.

Key partnerships Some activities are outsourced and some resourcesare acquired outside the enterprise.

Value capture Revenue streams Revenue streams result from value propositionssuccessfully offered to customers.

Cost structure The business model elements result in the coststructure.

Source: Osterwalder and Pigneur (2010); meta-components renamed according to Günzel and Holm(2013).


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and effects, while Osterwalder and Pigneur (2010) discuss the five phases mobi-lize, understand, design, implement, and manage.

Business model innovation is one of the greatest challenges for today’s man-agers (Chesbrough, 2006). Christensen and Overdorf (2000) demonstrate howestablished firms fail in disruptive innovation due to conflicts with existingtechnologies and business models. Chesbrough (2010) argues that it is not onlyconflict but also confusion that holds managers back from business model inno-vation, as they fail to recognize proper business models. Bohnsack et al. (2014)point out that path dependency cognitively constrains managers in the sense thatthey stay close to what they already know when it comes to the design of newbusiness models. These challenges also render the generic phases for businessmodel innovation – independently of their concrete naming and order — of littlevalue if not supplemented by concrete tools and methods. For instance, theidentification of new business model ideas will probably not happen by followingadvice to do so, but rather by applying tools that facilitate creativity. Furthermore,tools are needed to enable experimentation and overcome cognitive biases such aspath dependence in decision making (Spieth et al., 2014), as business modelinnovations have been described as being depended on trial-and-error-learning(Sosna et al., 2010) or discovery-driven approaches (McGrath, 2010). This es-pecially holds true as business environments become more complex and dynamic(El Sawy et al., 2010).

The importance of tools is underlined by several researchers suggesting thattools are at least as important as the people applying them (Garfield et al., 2001).Paradigm-changing ideas in particular — i.e., the more disruptive ones — can befacilitated significantly by the use of creativity tools (Garfield et al., 2001).Furthermore, tools have been proven to be particularly suitable for facilitatinggroup interaction and idea generation during business model innovation (Eppler etal., 2011). There are several tools that can be applied to support one or severalphases during business model innovation. For instance, Pynnönen et al. (2012)use the customer value model, the business mapping framework, and group de-cision-support systems. De Reuver et al. (2013) propose business model road-mapping, which can be used to identify the ideal transition path once the desiredbusiness model changes are identified. However, the most popular tools forbusiness model innovation are the business model canvas and business modelpatterns. Through an experimental study on the effectiveness of the businessmodel canvas for idea generation and group interaction, Eppler et al. (2011) findthat it significantly increases collaboration while significantly decreasing crea-tivity. In contrast, business model patterns not only facilitate group interaction(Gassmann et al., 2014) but also promote creativity by thinking in analogies(Johnson, 2010).

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Business model patterns

When defining business model patterns, researchers often refer to ChristopherAlexander, a famous architect who is considered to be the father of patterns (e.g.,Abdelkafi et al., 2013; Amshoff et al., 2015; Osterwalder and Pigneur, 2010). Hemade several publications on the use of patterns in architecture — most famously,“A Pattern Language” (Alexander et al., 1977), in which he proposes 253 patternsthat can be used to design even highly complex architecture. Alexander asserts thefollowing definition: “Each pattern describes a problem which occurs over andover again in our environment, and then describes the core of the solution to thatproblem, in such a way that you can use this solution a million times over, withoutever doing it the same way twice” (Alexander et al., 1977, p. x).

From Alexander’s definition, we can learn three important aspects that also holdtrue for business model patterns. First, patterns describe a “solution” to a recurring“problem” that needs to be solved, which also accounts to business model patterns(Abdelkafi et al., 2013). For instance, a business model must capture value andtherefore requires a pricing strategy for which the pattern razors/blades (Johnson,2010) can be a solution. Second, Alexander notes that a pattern describes “the coreof the solution,” which means that a business model pattern often describes asolution for only a certain part of a company’s business model (Weill and Vitale,2001). Hence, complete business models of companies are often a combination ofseveral patterns (Osterwalder and Pigneur, 2010). Third, a pattern should be usable“a million times over” and therefore requires a certain level of generalization(Amshoff et al., 2015; Timmers, 1998). Accordingly, business model patternresearchers integrate one or several of these three aspects into their definitions(Table 2).

The majority of literature on business model patterns comprises lists of patterns.However, when practitioners and researchers attempt to use these collections intheir current form, they face three major challenges: incompleteness, overlap, andinconsistent structure. First, incompleteness means that no single collection ofpatterns is even close to exhaustive. The most comprehensive collection of busi-ness model patterns, from Gassmann et al. (2014), contains 55 patterns. But inother collections, more than 100 additional patterns can be found. Therefore,innovators applying patterns from just one source can be sure to miss the majorityof business model patterns. Second, existing collections have a significant amountof overlap. For instance, the business model pattern virtual community involvescreating and facilitating an online community of people by enabling interactionand service provision (Weill and Vitale, 2001). However, several patterns fromother collections describe a very similar idea, including selling experience, createuser communities, user communities, community model, social networking


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services, community building, and virtual communities (Clemons, 2009; Johnson,2009, 2010; Rappa, 2001; Strauss and Frost, 2014; Timmers, 1998). Hence, ap-plying several collections simultaneously leads to significant redundancies. Third,the patterns are not structured in a consistent manner. Whereas Eisenmann (2001)presents the patterns without an underlying structure, Linder and Cantrell (2000)group their patterns in eight categories and Timmers (1998) arranges the patternsaccording to two dimensions. Due to this lack of consistent structure, it is verychallenging to navigate through the different collections when attempting to applythem for business model innovation. In particular, this limits the possibility offiltering for business model patterns that address the situation of a specific businessmodel innovation endeavour, which would substantially increase the efficiencyand effectiveness of the patterns’ usage.

The three issues of existing business model pattern collections — incomplete-ness, overlap, and inconsistent structure — can, in general, be mitigated by areview. A review summarizes existing literature and thereby “creates a firmfoundation for advancing knowledge” (Webster and Watson, 2002, p. xii). How-ever, existing reviews of business model patterns have insufficiently addressed theissues related to existing literature. Most importantly, no review is exhaustive, buteven the most comprehensive review (Bonakdar et al., 2013) misses more thantwo-thirds of the patterns available. Furthermore, the majority of reviews list dif-ferent patterns but do not systematically analyze the individual patterns by, e.g.,highlighting commonalities and differences. This is because existing reviews dealwith business models in general or their application to a specific case. Thus, theauthors of prior reviews aimed merely to provide a rough overview.

Table 2. Definitions of business model patterns.

Author Definition

Abdelkafi et al. (2013, p. 14) “The relationship between a certain context orenvironment, a recurring problem and the core ofits solution”

Amshoff et al. (2015, p. 4) “Reusing solutions that are documented generally andabstractly in order to make them accessible andapplicable to others”

Gassmann et al. (2014, p. 22) “A specific configuration of the [..] business modeldimensions [. . .] that has proven to be successful”

Osterwalder and Pigneur (2010, p. 55) “Business models with similar characteristics, similararrangements of business model Building Blocks,or similar behaviours”

Timmers (1998, p. 4) “Generalisations of specific business models”Weill and Vitale (2001, p. 21) “The essence of a different way to conduct business”

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Methodology

Drawing on existing knowledge in the field of business model patterns and theassociated gaps in research outlined above, we argue that a meta-perspectiveserving as a navigator through the business model pattern landscape represents animportant contribution but remains missing. The objective of this research was tocreate such a meta-perspective. Therefore, we proceeded in three major phases,which are further detailed in Table 3. The objective of Phase 1 was to mitigate theincompleteness by systematically identifying and reviewing existing collections,while Phase 2 aimed to remedy the overlap by filtering for duplicates and Phase 3focused on creating a consistent structure among all patterns.

Table 3. Research design overview.

Phase 1: Review businessmodel pattern literature

Phase 2: Extract andintegrate business modelpatterns

Phase 3: Structure patternsby impact on businessmodel elements

Objective Exhaustive overview ofbusiness model patternliterature

Integrated list of patternsthat is free ofduplicates

Consistent structure fornavigation through thepatterns

Steps . Search scientific data-bases (e.g., EBSCO) forarticles on businessmodel patterns

. Search for additionalarticles via forward andbackward referencing(Webster and Watson,2002)

. Systematically analyzeoriginal and reviewarticles

. Extract patterns,descriptions, andexamples from originalsources into one com-mon database

. Filter for uselesspatterns

. Filter for duplicates bysearching for

– Identical/similarname

– Similar description– Overlapping

examples

. For each potential du-plicate decide on ag-gregation by at leasttwo researchers

. Apply a taxonomy-building methodologyto create a consistentstructure. (Nickersonet al., 2013)

. Define a meta-characteristics of thetaxonomy

. Run through severaliterations until all pat-terns are classified

Result 22 original and 6 reviewarticles identified

356 business modelpatterns identified, 182after filtering

182 patterns classified byaffected businessmodel elements


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Phase 1: Review business model pattern literature

We searched for relevant literature on business model patterns in several commondatabases, including EBSCO, Web of Science, and Google Scholar. Because notall authors dealing with the topic use the name “business model patterns,” we alsohad to search for other terms, including “atomic business models” (Weill andVitale, 2001, p. 21), “business model analogies” (Johnson, 2010, p. 131), “busi-ness models” (Rappa, 2001, p. 1), “operating business models” (Linder andCantrell, 2000, p. 7), and “profit models” (Tuff and Wunker, 2010, p. 5). Theinitial sources were supplemented by searching for forward and backwardreferencing (Webster and Watson, 2002). Literature from academia and practicewas likewise included in the search. The scope was on business model patterncollections dealing with generic patterns as well as e-business model patterns.Collections focusing on a single industry were not included in this review (e.g.,mobile platform providers (Becker et al., 2012; Ghezzi, 2012), the textile industry(Hodge and Cagle, 2004), project-based firms (Kujala et al., 2010), Spanish in-dustry (Camisón and Villar-López, 2010)). As a result, we identified 22 originalcollections of business model patterns (see Table 4 in results section) as well as sixreviews (see Table 5 in results section), each summarizing several original col-lections. As we also studied all original collections mentioned in the reviewarticles, we are confident that our sample represents a fairly complete picture ofbusiness model patterns mentioned in the existing literature.

Phase 2: Extract and integrate business model patterns

Next, we extracted all 356 patterns mentioned in the 22 collections of businessmodel patterns that were identified in Phase 1 and loaded them into a database. Asour data stems from multiple sources, we had to harmonize the format andproperly filter the instances (Bauer and Günzel, 2013).

We shortened the description of each pattern to one sentence and ensured that atleast one example was provided. If an example was lacking, we manually searchedfor a company that applied the pattern. We next filtered for useless and duplicateinstances. Two patterns — human creator, i.e., creating and selling human assets,and human distributor, i.e., buying and selling human assets (Weill et al., 2005)—were found to be impossible because they are illegal. Therefore, we removed themform the database. Furthermore, we identified potential duplicate patterns bycomparing names, sample companies, and descriptions. For instance, the patternname mass customization occurs in the collection of Gassmann et al. (2014) aswell as Strauss and Frost (2014). According to Gassmann et al. (2014, p. 352), thepattern means that “individual customer needs can be met under mass productionconditions and at competitive prices.” Strauss and Frost (2014, p. 58) maintain that

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mass customization allows one to “customize products and communication on anindividual basis for a large number of people.” After two researchers were unableto identify any significant differences between the two descriptions, the two pat-terns were merged to one instance within the database. Furthermore, we found thatGassmann et al. (2014) mention Dell as an example of a company that imple-mented the pattern. Because Dell is also provided as example for the pattern mass-customized commodity from Linder and Cantrell (2000), we considered this patternto also be a potential duplicate. Linder and Cantrell (2000, p. 7) describe thepattern as one that “offer[s] ‘have it your way’ model options on top of competitiveprices, convenient buying, and fast delivery to win in commodity markets.” Weagreed to also consolidate this pattern with the other two, thus condensing all threeinstances to the pattern mass customization within the database. However, theoriginal sources (i.e., Gassmann et al., 2014; Linder and Cantrell, 2000; Straussand Frost, 2014) and alternative names (i.e., mass-customized commodity) are stilldirectly linked to the pattern. Using the same approach, we summarized a total of172 duplicate business model patterns, resulting in a final list of 182 patterns (seeAppendix A).

Phase 3: Structure patterns by impact on business model elements

The objective of the third phase was to develop a consistent structure for betternavigation through existing business model patterns. To do so, we classifiedpatterns with similar characteristics into common groups, i.e., we developed ataxonomy (Nickerson et al., 2013). Thereby, the homogeneity of objects (i.e.,business model patterns) within a group had to be maximized while the hetero-geneity between groups had to be minimized (Bailey, 1994). As taxonomy re-search often lacks a profound methodology (Nickerson et al., 2013), we appliedthe taxonomy-building approach from Nickerson et al. (2013). Their approach hasbeen proven by its successful application (e.g., Geiger et al., 2012; Haas et al.,2014; Nakatsu et al., 2014), its rigor in clearly defining all necessary steps and theending conditions, and its flexibility in comparison to most other approachesbecause it integrates empirical and conceptual research into one methodology.Hence, “readers of papers that present taxonomies developed using [the] methodcan also be reasonably confident that the taxonomy presented was developed in anestablished way” (Nickerson et al., 2013, p. 354).

The taxonomy development method from Nickerson et al. (2013) contains sevensteps, which typically include several iterations (Fig. 1). The first step is to define ameta-characteristic directly addressing the purpose of the taxonomy. The meta-characteristic must reflect the interests of the users of the taxonomy. All char-acteristics defined later must be logical consequences of the meta-characteristic.


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Second, the ending conditions must be defined. The methodology then runs throughseveral iterations. These iterations can either be empirical-to-conceptual, in whichcase common characteristics for selected objects are identified and grouped intodimensions with corresponding characteristics, or conceptual-to-empirical, whichmeans that dimensions and characteristics are derived from theory and evaluated byobjects that fulfil these characteristics. During these iterations, it is important tounderstand that the characteristics must be mutually exclusive and collectivelyexhaustive, meaning that each object can be assigned to exactly one characteristicfor each dimension. As we will later see, this rule sometimes makes it necessary tosplit one existing dimension into two or more new dimensions because otherwisesome objects (i.e., patterns in our case) would have more than one characteristic forthe same dimension. The iterations end when the previously defined ending con-ditions are met.

We applied the taxonomy development method to our data sample of 182business model patterns that we identified and integrated in the Phases 1 and 2. Wefirst defined the meta-characteristic as the impact of the pattern on a businessmodel’s elements (e.g., the value proposition). Second, we adopted the eightobjective ending conditions and five subjective ending conditions proposed byNickerson et al. (2013) (Appendix B). Afterwards we ran through five iterations,which we have summarized in Fig. 2.

1. Determine meta-characteristic

2. Determine ending conditions

4e. Identify (new) subset of objects 4c. Conceptualize (new) characteristics and dimensions of objects

5e. Identify common characteristics and group objects

5c. Examine objects for these characteristics and dimensions

6e. Group characteristics into dimensions to create (revise) taxonomy 6c. Create (revise) taxonomy

7. Ending conditions met?

Start

End

3. Approach?Empirical-to-conceptual Conceptual-to-empirical

NoYes

Fig. 1. Taxonomy development method (Nickerson et al., 2013, p. 345).

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We first decided on a conceptual-to-empirical iteration and defined five newdimensions. Based on Amshoff et al. (2015) and Strauss and Frost (2014), whofound that business model patterns affect different hierarchical levels, we definedthe first dimension as a hierarchical level of impact, which can either be theholistic business model, i.e., prototypical business model patterns, or businessmodel building blocks, i.e., solution patterns. Furthermore, the meta-characteristicrequired us to determine which business model elements were affected by theapplication of a pattern. Therefore, we added four additional dimensions reflectingthe four business model components from Table 1: value proposition, value de-livery, value creation, and value capture. Afterwards, we examined patterns fromour sample that addressed these dimensions. The pattern solution provider is aprototypical pattern addressing the whole business model, whereas the patternrazors/blades is a prototypical pattern that addresses only certain elements. Fur-thermore, the pattern razors/blades affects the value proposition dimension (byoffering cheap prices) and the value capture dimension (as it describes a pricingstrategy). In addition to these two patterns, we found that the pattern disinter-mediation addresses the value delivery dimension (as it defines a new sales model)while the pattern from push-to-pull impacts the value creation dimension (as itinvolves a new manufacturing methodology).

As the second iteration, we chose an empirical-to-conceptual cycle and addedall patterns from the three sources containing general, prototypical patterns(Andrew and Sirkin, 2006; Chatterjee, 2013; Weill et al., 2005). To adequatelyclassify these instances and at the same time assure mutual exclusiveness andcollective exhaustiveness, we had to split the dimension value proposition. Forinstance, some patterns describe different product types offered (e.g., physical

Hierarchical impact

Degree of digitization

Product type

Strategy for differentiation

Target customers

Value-delivery process

Sourcing

Third parties involved

Value-creation process

Revenue model

Pricing strategy

Direct profit effect

Hierarchical impact

Degree of digitization

Product type


Target customers


Sourcing



Revenue model

Pricing strategy


Hierarchical impact

Product type


Target customers


Sourcing



Revenue model

Pricing strategy


Hierarchical impact

Product type


Value delivery

Value creation

Revenue model


Hierarchical impact

Value propostion

Value delivery

Value creation

Value capture

Iteration 2 Iteration 3 Iteration 4 Iteration 5

Dimensions

Iteration 1

Sum

Approach

5

Conceptual-to-empirical

7

Empirical-to-conceptual

11


12


12


Legend: = New dimension from this iteration = Dimension from previous iteration

Fig. 2. Development of dimensions for the business model pattern taxonomy.


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landlord and financial landlord), whereas other patterns describe different strat-egies for differentiation (e.g., perceived value-based and brokerage). Therefore,we split the dimension value proposition into two new dimensions: product type(adopted from Weill et al., 2005) and strategy for differentiation. For the samereason, we also split the value capture dimension by type of revenue model andimpact on the profit.

In the third iteration, we again ran through an empirical-to-conceptual cycle andclassified all the remaining sources with general patterns (Gassmann et al., 2014;Johnson, 2009, 2010; Linder and Cantrell, 2000; Osterwalder and Pigneur, 2010;Tuff and Wunker, 2010). To adequately classify these patterns, we split thedimension value delivery into target customers and value-delivery process; thedimension value creation was divided into sourcing, third-party involvement, andvalue-creation process. Furthermore, we added the dimension pricing strategy.

During the fourth empirical-to-conceptual iteration, we added those e-businesspatterns whose initial version stems from the internet boom that occurred aroundthe 2000s (Applegate, 2001; Bienstock et al., 2002; Eisenmann, 2001; Hanson,2000; Hartman et al., 2000; Rappa, 2001; Strauss and Frost, 2014; Tapscott et al.,2000; Timmers, 1998; Weill and Vitale, 2001). To better distinguish these patternsfrom the previous ones, we included the dimension degree of digitization.

Finally, we added the remaining sources that contain e-business patterns fromrecent years (Clemons, 2009; Fleisch et al., 2014; Wirtz et al., 2010). At this point,we did not have to add any new dimensions or characteristics and had fulfilled allobjective and subjective ending conditions; hence, we conducted no furtheriterations.

Further details on each step are provided in Appendix C, with the iterationsshown in the first column. The final taxonomy contains 12 dimensions, eachhaving between two and seven characteristics, which are further elaborated uponin the results.

Results

In this section, we successively present and explain the results of the three steps ofour methodological approach: an overview of business model pattern literature, anintegrated list of existing business model patterns, and a taxonomy structuring thepatterns by their impact on a business model.

Overview of business model pattern literature

As described above, we identified 22 original articles as well as six reviews onbusiness model patterns. Original sources of business model patterns identify new

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patterns and typically provide a description and one or several examples for eachpattern. The 22 original sources contain more than 300 business model patterns(Table 4). Roughly two-thirds of the patterns relate to general businesses, whileone-third specifically addresses electronic (e-)businesses. The patterns differ bytheir granularity, as they can either be prototypes of a company’s business modelor solution patterns addressing very specific aspects of a business model (Amshoffet al., 2015). While not all authors provide further details on the applied researchmethodology, those who do either apply conceptual research, e.g., identify pat-terns along the value chain, or empirical analyses of real-world business models.Within their articles, the authors supply different approaches to structure thepatterns. The first group – mostly those presenting fewer than 10 patterns –

arranges the patterns in random order. The second group arranges the patternsalphabetically, and the third group clusters the patterns according to several cat-egories without providing further details on the underlying criteria for clustering.The fourth group comprises authors who explicitly use one or several dimensionsto structure the patterns. For instance, Timmers (1998) arranges the patterns bydegree of functional integration and degree of innovation, whereas Weill et al.(2005) use the rights to be sold (i.e., creator, distributor, landlord, broker) and thetype of asset involved (i.e., financial, physical, intangible, human). This group alsoincludes Gassmann et al. (2014), who supplement their alphabetical list with amapping of each pattern on the affected business model components.

In addition, we identified six reviews of business model patterns, each sum-marizing the patterns of several original sources (Table 5). The most exhaustivereview, from Bonakdar et al. (2013), includes 13 original sources and 94 patterns.In contrast to the other reviews, this review also includes industry-specific pat-terns. Three of the six review articles filter for duplicate patterns (Abdelkafi et al.,2013; Afuah and Tucci, 2000; Lam and Harrison-Walker, 2003), whereas theothers present all patterns that are mentioned in the original sources under in-vestigation. Most reviews structure the patterns by author of the original source.An exception are Lam and Harrison-Walker (2003) arranging the patterns by theirrelational objectives (i.e., direct access, network development, corporate com-munications) and their value-based objectives (i.e., financial improvement, prod-uct/channel enrichment) as well as Abdelkafi et al. (2013) mapping each patternwith the affected business model dimensions.

As we are also conducting a review with this research, we added it to Table 5(last row). Our review covers all 356 patterns mentioned in the 22 original sourcesfrom Table 4. Thus, to the best of our knowledge, our review is significantly morecomprehensive than any other review to date has been. Furthermore, the patternswere filtered for duplicates and organized along multiple dimensions. We elabo-rate on both aspects below.


1750004-15

Table

4.Originalsourcesof

business

mod

elpatterns.

Sou

rce

Num

ber

ofpatterns

Indu

stry

focus

Pattern

granularity

Researchmetho

dology

Patternsstructured

by

And

rew

andSirkin(200

6)3

General

Prototypicalpatterns

n.a.

n.a.

App

legate

(200

1)24

E-business


Con

ceptual,alon

gthevalue

chain

6catego

ries

Bienstock

etal.(200

2)11

E-business

Mixed

Empirical,taxo

nomythroug

hanalysisof

400websites

6dimension

s:nu

mberof

buyers,

numberof

sellers,type

ofseller,pricemechanism

,nature

ofprod

uct,frequency

ofoffering

Chatterjee

(201

3)4

General


Con

ceptual,Porter’sgeneric

strategies

2dimension

s:efficiency

vs.

perceivedvalue,

individu

alfirm

vs.network

Clemon

s(200

9)9

E-business

Mixed

n.a.

2catego

ries

Eisenmann(200

1)8

E-business


n.a.

n.a.

Fleisch

etal.(201

4)8

E-business

Solutionpatterns

Con

ceptual,transfer

ofexistin

gpatternsto

theInternet

ofThing

s

2catego

ries

(which

areinclud

edhere

aspatternsthem

selves)

Gassm

annet

al.(201

4)55

General

Mixed

Empirical,recurringpatternsof

successat23

7bu

siness

mod

elinno

vatio

ns

Alphabetical

order,

supp

lementedby

mapping

onaffected

business

mod

eldimension

Hanson(200

0)18

E-business

Mixed

n.a.

5catego

ries

Hartm

anet

al.(200

0)5

E-business


n.a.

n.a.

John

son(200

9)20

General

Solutionpatterns

n.a.

Alphabetical

order

John

son(201

0)19

General

Solutionpatterns

n.a.

Alphabetical

order

LinderandCantrell(200

0)34

General

Mixed

n.a.

8catego

ries

OsterwalderandPigneur

(201

0)5

General

Mixed

n.a.

n.a.

G. Remane et al.

1750004-16

Table

4.(Con

tinued)

Sou

rce

Num

ber

ofpatterns

Indu

stry

focus

Pattern

granularity

Researchmetho

dology

Patternsstructured

by

Rappa

(200

1)50

E-business

Mixed

n.a.

9catego

ries

(which

areinclud

edhere

aspatternsthem

selves)

Strauss

andFrost(201

4)20

E-business

Mixed

n.a.

1dimension

s:levelof

business

impact

Tapscottet

al.(200

0)5

E-business


Empirical,analysisof

morethan

200case

stud

ies

2dimension

s:econ

omic

control,

valueintegration

Tim

mers(199

8)10

E-business

Mixed

Con

ceptual,alon

gthevalue

chain

2dimension

s:functio

nal

integration,

degree

ofinno

vatio

nTuffandWun

ker(201

0)20

General

Mixed

Empirical,recurringpatternsof

successin

sampleof

more

than

5,00

0inno

vatio

ns

Alphabetical

order

WeillandVitale

(200

1)8

E-business

Mixed

Empirical,from

consultin

gwork

Alphabetical

order

Weillet

al.(200

5)16

General


Con

ceptual,po

ssible

combinatio

nsalon

gtwo

dimension

s

2dimension

s:righ

tsbeingsold,

type

ofassetinvo

lved

Wirtz

etal.(201

0)4

E-business


n.a.

n.a.

Sum

356


1750004-17

Table

5.Reviewsof

business

mod

elpattern

literature.

Autho

rOriginalsourcesin

scop

eNum

ber

ofpatterns

Indu

stry

focus

Filtered

for

duplicates

Patternsstructured

by

Abd

elkafiet

al.

(201

3)And

rew

andSirkin(200

6)49

General

Yes

Autho

r,supp

lemen-ted

bymapping

onaffected

business

mod

eldimension

John

son(200

9)John

son(201

0)OsterwalderandPigneur

(201

0)Weillet

al.(200

5)

Afuah

andTucci

(200

0)Rappa

(200

1)9

E-Business

Yes

n.a.

Tim

mers(199

8)

Bon

akdaret

al.

(201

3)Beckeret

al.(201

2)94

General,e-bu

siness,mob

ileplatform

s,textile

indu

stry,

project-basedfirm

s,andthe

Spanish

indu

stry

No

Autho

rBienstock

etal.(200

2)Cam

isón

andVillar-Lóp

ez(201

0)Chatterjee

(201

3)Ghezzi(201

2)Hod

geandCagle

(200

4)Kujalaet

al.(201

0)LinderandCantrell(200

0)Rappa

(200

1)Tapscottet

al.(200

0)Tim

mers(199

8)WeillandVitale

(200

1)Weillet

al.(200

5)

Hedman

and

Kallin

g(200

3)App

legate

(200

1)43

E-Business

No

Author

Rappa

(200

1)Tim

mers(199

8)

G. Remane et al.

1750004-18

Table

5.(Con

tinued)

Autho

rOriginalsourcesin

scop

eNum

ber

ofpatterns

Indu

stry

focus

Filtered

for

duplicates

Patternsstructured

by

Lam

andHarrison-

Walker(200

3)Afuah

andTucci

(200

0)33

E-Business

Yes

2dimensions:relatio

nal

objectives,value-based

objectives

Eisenmann(200

1)Hanson(200

0)Rappa

(200

1)Strauss

andFrost(201

4)

Zottet

al.(201

0)App

legate

(200

1)37

E-Business

No

Author

Rappa

(200

1)Tapscottet

al.(200

0)Tim

mers(199

8)WeillandVitale

(200

1)

Thisresearch

All22

sourcesfrom

Table

435

6(182

after

filtering

)

General

ande-bu

siness

Yes

Multip

ledimension

sthat

describe

theim

pact

ofpattern

application


1750004-19

Integrated list of business model patterns

The result of our second research phase is a database with 182 business modelpatterns. The database contains all generic and e-business-specific business modelpatterns that were identified through a comprehensive literature review. Eachpattern in the database is described with further details. For instance, the databasecontains the following information for the pattern razors/blades:

. Pattern name: Razors/blades

. Alternative pattern names: Cellphone, razor and blade

. Description: Offer a cheap or free basic product (“razor”) together with com-plements (“blades”) that are overpriced and thereby subsidize the basic product

. Examples: Gillette, Nespresso, Amazon Kindle

. Sources: Gassmann et al. (2014), Johnson (2009), Johnson (2010), Linder andCantrell (2000)

The full list can be found in Appendix A. Although the database already solvestwo important shortcomings of the existing literature— it is exhaustive and free ofduplicates — its practical application would still be difficult as the simultaneousapplication of 182 patterns for business model innovation is likely to be over-whelming unless the relevant subset of patterns for a specific endeavour can beidentified. In the next part we explain the taxonomy remedying this issue.

Taxonomy of business model patterns

The patterns in the database are classified along the 12 dimensions of the taxon-omy. Each pattern is assigned to exactly one characteristic for each of the 12dimensions. Figure 3 visualizes the 12 dimensions and possible characteristics as amultidimensional matrix, which can also be referred to as a morphological box(Zwicky, 1967). The dimensions (D) are grouped by those that are overarching(D1–D2) and those affecting a specific business model component, i.e., valueproposition (D3–D4), value delivery (D5–D6), value creation (D7–D9), and valuecapture (D10–D12), all of which are elaborated upon below.

The overarching dimensions describe aspects affecting several business modelcomponents simultaneously. The first dimension, hierarchical impact (D1), dis-tinguishes whether a business model pattern describes a prototypical businessmodel (e.g., financial trader) or a solution pattern (e.g., channel maximization).Prototypical patterns describe the general set-up of a company’s business model,whereas solution patterns imply actions to change only sub-aspects of it. Fur-thermore, the patterns differ by their degree of digitization (D2). For instance,online brokers, such as Airbnb, employ purely digital business models in which

G. Remane et al.

1750004-20

the operator is not required to own major physical assets. E-retailers, such asAmazon, buy large amounts of physical products and thus do not employ purelydigital business models. However, as they sell everything online, they still dependon digital technologies and are thus digitally enabled. In contrast, the basicbusiness model of physical manufacturers, such as Pepsi, does not necessarilydepend on digital technologies.

Patterns affect the value proposition in terms of either the type of productoffered (D3) or the strategy for differentiation (D4). Product types can be physical(e.g., physical manufacturer), financial (e.g., financial broker), human (e.g.,advisors), intellectual property (e.g., information collection), or hybrid (e.g.,physical freemium). Differentiation is then possible by quality (e.g., quality sell-ing), customization (e.g., mass customization), combined offering (e.g., bundleelements together), convenience (e.g., one-stop convenient shopping), price (e.g.,low-touch approach), or network effects (e.g., multi-sided platforms).

Dimension (D) Characteristics per dimension (number of patterns per characteristic)

Ove

rarc

hing

D1: Hierarchical impact Prototypical pattern (87) Solution pattern (95)

D2: Degree of digitization Purely digital (55) Digitally enabled (35) Not necessarily digital (92)

Val

ue

prop

ositi

on

D3: Producttype Physical (12) Financial (7) Human (5)

Intellectual property (36)

Hybrid (10) Product type not specified

(112) D4: Strategy for differentiation Quality (9)

Customi-zation (8)

Combination (13)

Access/con-venience (6)

Price (22) Network

effects (11)

No impact on differen-tiation (113)

Val

ue d

eliv

ery D5: Target

customersSpecific new customer

segment (10) Lock-in existing

customers (9) Other companies (B2B)

(7) No impact on target

customers (156)

D6: Value-delivery process

Brand and marketing (7)

Sales channel (20) Sales model (9) Customer

relationship management (3)

No impact on delivery process

(143)

Val

ue c

reat

ion

D7: SourcingMake (17) Buy (11) No impact on sourcing (154)

D8: Third parties involved Suppliers (9) Customers (12) Competitors (3)

Multiple parties(18)

No impact on third parties involved

(140) D9: Value-creation process

Research and design (7)

Supply (5) Production (8) Multiple steps (11) No impact on

creation process (151)

Val

ue c

aptu

re

D10: Revenue model Sell (15) Lend (20) Intermediate (18) Advertising (12)

No impact on revenue model

(117) D11: Pricing strategy Premium (11) Cheap (9) Dynamic (12)

Non-transparent (8)

No impact on pricing strategy

(142) D12: Direct profit effect Increase revenue (42) Reduce cost (15) Multiple effects (11)

No direct profit impact(114)

Fig. 3. Dimensions, characteristics, and number of business model patterns per characteristic.


1750004-21

Value delivery is affected by either the target customers in focus (D5) or theprocess of value delivery (D6). Some patterns propose focusing on a specific newcustomer segment (e.g., own the undesirable), while others suggest locking inexisting customers (e.g., digital lock-in) or focusing exclusively on business-to-business (B2B) customers (e.g., value chain service provider). The value-deliveryprocess may be affected regarding brand and marketing (e.g., cool brands), saleschannels (e.g., bricks þ clicks), sales model (e.g., disintermediation), or customerrelationship management (e.g., customer loyalty).

Patterns affect value creation in terms of sourcing (D7), third-party involvement(D8), and the process of value creation (D9). Some patterns explicitly requireinternal production, i.e., make (e.g., entrepreneur), whereas others propose pur-chasing the products or services externally (e.g., physical wholesaler). Somepatterns depend on third-party involvement, such as suppliers (e.g., from push topull), customers (e.g., user designed), competitors (e.g., forced scarcity), ormultiple parties (e.g., collaboration platforms). The value-creation process can beaffected in terms of innovation (e.g., open business models), supply (e.g., e-pro-curement), production (e.g., self-service), or multiple steps (e.g., orchestrator).

The fourth business model component, value capture, is addressed by patternsregarding the revenue model (D10), pricing strategy (D11), or profit (D12). Theproposed revenue models can be summarized as selling (e.g., product sales),lending (e.g., rent instead of buy), intermediation (e.g., broker model), or adver-tising (e.g., free), while the proposed pricing strategies are premium (e.g., expe-rience destination), cheap (e.g., one-stop, low price shopping), dynamic (e.g.,auction), or non-transparent (e.g., razors/blades). Patterns may directly impactprofit either by aiming to increase revenues (e.g., channel maximization) or reducecosts (e.g., self-service) or by multiple effects (e.g., user designed).

Application of the Database for Business Model Innovation

In business model innovation endeavours, the simultaneous application of all 182identified patterns would be rather overwhelming. Even lists from single authorssuch as Gassmann et al. (2014) with 55 patterns, Rappa (2001) with 50 patterns, orLinder and Cantrell (2000) with 34 patterns can lead to a quite complex andunfocused process. The business model pattern database reduces this complexitysignificantly, as it helps to identify the relevant set of patterns for a specificpurpose depending on the specific situation of the innovating firm. For instance,the database can be used to identify relevant patterns for the integration of a roughbusiness idea or technological innovation into a complete business model. Incontrast, prior business model pattern literature has mainly applied patterns during

G. Remane et al.

1750004-22

the first phases of the business model innovation process, i.e., to analyze existingbusiness models (e.g., Weill et al., 2005) or for the generation of new businessideas (e.g., Gassmann et al., 2014).

To demonstrate the different uses of the database, we refer to the businessmodel innovation phases explained by Frankenberger et al. (2013), spanningacross initiation, ideation, integration, and implementation. During initiation, thedatabase aids in better understanding existing business models by guiding theidentification of patterns currently employed. In the next step, ideation, the data-base allows for systematic generation of ideas through transferring patterns to thefocal company. During integration, the database enables the development ofcomplete business models by revealing patterns that can be combined with theinitial ideas. Finally, during implementation, the database serves as a glossary,linking to additional information for the successful execution of each pattern.Table 6 summarizes the objective of each phase, the role of the business modelpattern database, and the results from its application.

In the following we outline generic instructions on how to use the businessmodel pattern database during each phase. For simplicity, we present the phasessequentially, even though iterations between phases (Frankenberger et al., 2013)and parallelization of phases (Osterwalder and Pigneur, 2010) are necessary.Furthermore, business model innovation itself is not a one-time project, but aniterative process that must be anchored within every sustainable organization(Osterwalder and Pigneur, 2010).

Initiation

The objective of the initiation phase is to better understand the innovating firm’sown business model as well as the surrounding ecosystem (Frankenberger et al.,2013). Furthermore, emerging technological, social, environmental, and organi-zational trends that might require business model change must be understood(Demil and Lecocq, 2010). During this phase, business model patterns can be usedto make the underlying business logics of the company, its partners, and itscompetitors more transparent (Tuff and Wunker, 2010).

Using the taxonomy structure of the database, one can identify the patternsimplemented in the focal company’s business model. To guide this process, thefollowing questions (amongst others) may be useful: What is the current strategyfor differentiation (D4)? Which third parties are directly involved in value creation(D8)? How are revenues generated (D10)? Once the patterns implemented in thecurrent business model have been identified, they can be used to gain furtherinsights: Have competitors implemented identical or different patterns? Whichcompanies from other industries have implemented similar patterns? What can be


1750004-23

Table

6.Usage

ofthepattern

database

during

thebu

siness

mod

elinno

vatio

nprocess.

1.Initiation

2.Ideatio

n3.

Integration

4.Im

plem

entatio

n

Objectiv

eof

theph

ase

Und

erstandow

nbu

siness

mod

elandits

surrou

ndingecosystem

Identifynew

ideasfor

business

mod

elinnovatio

n

Integrateideasinto

acompletebu

siness

mod

elPilo

tandcommercializethe

design

edbu

siness

mod

el

Roleof

thebu

siness

mod

elpattern

database

Identifi

catio

nof

currently

implem

entedpatterns

inthefocalfirm

’secosystem

Iterativecycleof

structure

(selectdimension

for

innovatio

n)and

creativ

ity(transfer

patternsto

own

business

mod

el)

Systematic

generatio

nof

oppo

rtun

ities

tospecify

themissing

business

mod

eldimension

sthroug

hadditio

nalpatterns

Glossaryforrelevant

backgrou

ndinform

ation

andcasesfor

implem

entatio

nof

invo

lved

patterns

Resultsfrom

application

ofthedatabase

Overview

ofpatterns

employ

edin

own

business

mod

eland

differencescompared

tocompetitors

Listof

severalbu

siness

mod

elideas(i.e.,

patternsanda

descriptionof

how

totransfer

them

)

Specified

business

mod

elby

combining

severalp

atterns

Success

factorsfrom

prior

implem

entatio

nsof

the

pattern

Source:Phasesadaptedfrom

Frank

enberger

etal.(201

3).

G. Remane et al.

1750004-24

learned from these companies? Thus, by using the database, an analysis can beconducted along the different dimensions, which is structured and systematic butalso flexible enough to account for the specific situation of the respective firm.

Ideation

The ideation phase aims to identify ideas for new business models (Frankenbergeret al., 2013). From an analysis of 14 innovation cases, Frankenberger et al. (2013)found three recurring challenges hindering the generation of new ideas: resistancein overcoming the existing business logic, not thinking in terms of businessmodels, and the absence of creativity tools supporting this process. Businessmodel patterns mitigate all three challenges. They aid in breaking with the currentbusiness logic (Tuff and Wunker, 2010), already reflect the most critical elementsof a business model (Weill and Vitale, 2001), and boost creativity by thinking inanalogies with other industries (Johnson, 2010).

The database allows for the identification of the relevant subset of patterns foran effective idea generation process. To do so, the results from the prior initiationphase can be used. For instance, do the technological, social, environmental, ororganizational trends have a particularly strong impact on any business modelcomponent? Which dimension of the firm’s own business model has been iden-tified as the weakest? On which dimensions have competitors innovated theirbusiness models? Is a new strategy for differentiation required (D4)? Does thecurrent business model generate sufficient profits (D12)? As these questions al-ready indicate, the ideation phase typically requires several iterations. It hastherefore proven most efficient to alternate between two steps. First, one shouldselect of a subset of patterns from the database by filtering for the correspondingdimensions and characteristics that these should address. Second, one should try totransfer each pattern to the focal company during a brainstorming phase. Aftereach iteration, the best patterns and descriptions of how to transfer them are loggedinto a continuously growing list of options for business model innovation.

Integration

Business model patterns only describe the configuration of specific elements of abusiness model (Abdelkafi et al., 2013). Therefore, during integration, the mostpromising ideas collected in the previous phase must be further developed intocomplete business models (Frankenberger et al., 2013), which requires the spec-ification of all business model dimensions (Gassmann et al., 2014).

The dimensions (D3–D12) of the database taxonomy serve as a checklist toassure that value proposition, value delivery, value creation, and value capture


1750004-25

were sufficiently specified. As the patterns on the idea list from the previous phaseare already mapped on these dimensions, the missing pieces for each idea becometransparent. They can now be specified by searching the database for additionalpatterns that address these missing dimensions. Of course, the missing dimensionscould also be specified manually, but the search for additional patterns and thecombination of these patterns with the initial idea results in more sophisticatedinnovations.

Implementation

The former three phases – initiation, ideation, and integration — all target thedesign of a new business model, while the objective of the implementation phaseis to commercialize this new business model (Frankenberger et al., 2013).Therefore, projects must be initiated, milestones defined, a new organizationalstructure set up, budget allocated, and so on (Osterwalder and Pigneur, 2010). Toreduce implementation risks, one can use experimentation, trial-and-error learning,and pilots (Sosna et al., 2010).

The translation of business model designs into concrete activities can be betterperformed by using further tools, such as De Reuver et al. (2013) business modelroadmapping approach. Nonetheless, the business model pattern database providesvaluable information as input for this process, as patterns are derived from suc-cessful implementations that can provide insights on success factors. In this phase,guiding questions might include the following: How are the patterns typicallyimplemented? Which steps have other companies taken to implement them? Whatwere the critical factors for their successful implementation? For each pattern thedatabase directly refers to several sample companies that have implemented thepattern as well as to the authors that have identified the pattern, who often providefurther useful information and sources.

Illustrative Case Study

To further clarify the instructions on using the pattern database during the businessmodel innovation process, we found it useful to provide a simplified, anonymizedcase study. Automotive Aftermarket Inc., which is a division of a multinationalcompany, produces spare parts and primarily sells them to car repair shops. Therather broad product portfolio of Automotive Aftermarket Inc. includes moretraditional spare parts, such as windscreen wipers or headlights, but also elec-tronics, such as sensors or actuators, and connectivity appliances, such as Blue-tooth connectors for cars.

G. Remane et al.

1750004-26

The company was facing increasing pressure from new competitors for severalof its products. Furthermore, market research revealed that technological and so-cial trends will reduce car use and car ownership in future, leading to a threateningdecline of the overall market. Therefore, Automotive Aftermarket Inc. has initiateda business model innovation project with the objective of identifying new businessmodels better addressing the assumed changes in future consumer preferences.The company assumed its competencies in electronics and connectivity appliancesan important facilitator for this, even though it was not mandatory for the newbusiness models to be directly related to them.

Initiation

The initial business model of Automotive Aftermarket Inc. was to sell high qualityspare parts. Surveying the database for such patterns (D4: strategy for differenti-ation ¼ quality) revealed that the company has implemented the premium pattern,gaining higher margins than its competitors. These high prices were enabled fromhaving implemented the pattern ingredient branding, i.e. consequently brandingthe spare parts to make customers aware of brand and quality (D6: value deliveryprocess ¼ brand and marketing). In contrast, most competitors – often from Asia –focused on cost leadership for well-delimited product segments (D4: strategy fordifferentiation ¼ price).

Ideation

The innovation process targeted the identification of completely new businessmodels. Due to the increasing importance of digital technologies for the auto-motive sector, Automotive Aftermarket Inc.’s wanted to further strengthen itsdigital capabilities. Therefore, the first database query was used to identify genericbusiness models (D1: hierarchical impact ¼ prototypical pattern) that were purelydigital or digitally enabled (D2: degree of digitization ¼ purely digital OR digitallyenabled). One idea then was to adopt the pattern multi-sided platform by creatingan integrated mobility platform for urban mobility, allowing customers to compareand book different transport modes by integrating multiple transportation serviceproviders. Ideas from other iterations included the adoption of the marketplaceexchange pattern for intermediating between spare parts manufacturers and repairshops, the financial landlord pattern to offer car insurance by using car connec-tivity sticks that the company was already selling, the sensor as a service patternfor the collection and sale of data from the sensors that the company was pro-ducing for cars, and the peer-to-peer pattern for building a new peer-to-peer carsharing service.


1750004-27

Integration

Automotive Aftermarket Inc. decided to further specify the integrated mobilityportal business model, which was identified by adopting the pattern multi-sidedplatform. Multi-sided platform is a prototypical pattern (D1) that is typicallypurely digital (D2). It uses network effects as a differentiation strategy (D4), i.e.,more customers will make the platform more attractive for transportation serviceproviders and vice versa. To specify the other business model dimensions, furtherpatterns from the database were identified and integrated in a more completebusiness model: The pattern long tail meant that the platform should primarilyaddress customers who plan non-recurring trips – not, for instance, daily com-muters. The pattern customer loyalty led to the idea of combining the platformwith a reward program, while white label resulted in the plan to allow the localauthorities to co-brand the platform. The pattern brokerage was adapted to definethe revenue model via intermediation fees, which should be supplemented bycontextual mobile advertising, for which the target location of each customer couldbe used. As a pricing strategy, it was decided to also offer flat-rates with differenttravel volumes. Finally, the business model dimensions that were still insuffi-ciently defined (e.g., D3: the precise products and services to be offered) werespecified manually.

Implementation

In the case of Automotive Aftermarket Inc., the integrated mobility portal waspiloted in one city in a joint effort with the local authority. The database hadrevealed some valuable information for the implementation of this pilot. For in-stance, Osterwalder and Pigneur (2010) explain that the implementation of thepattern multi-sided platform often involves a chicken-and-egg problem andtherefore may require the subsidization of a customer segment. One samplecompany that successfully implemented the multi-sided platformpattern is MetroNewspaper: The free newspaper attracted a large readership immediately after itslaunch, which made it very attractive for advertisers and led to rapid profitability(Osterwalder and Pigneur, 2010). This example strengthened the idea of offeringthe portal to travellers for free but charging fees from advertisers and, in a secondstage, from transportation service providers.

Limitations of the Research

Our research is subject to limitations. First, taxonomies — in our case, the clas-sification of business model patterns — cannot be universally perfect, but in the

G. Remane et al.

1750004-28

best scenario are a useful solution to a specific problem (Nickerson et al., 2013).We argue that our taxonomy is useful for the specific challenges of business modelinnovators when attempting to apply business model patterns, because the tax-onomy classifies the patterns by their impacts on the business model (which wechose as meta-characteristic of the taxonomy). Furthermore, a comparison of ourtaxonomy with research on business model components (e.g., Abdelkafi et al.,2013; Gordijn et al., 2005; Osterwalder and Pigneur, 2010; Teece, 2010) showsthat most of our dimensions and characteristics can be found in these sources.However, we did not merely copy or combine existing business model conceptsbut rather derived the dimensions and characteristics from analyzing hundreds ofsuccessfully executed examples of business model innovation, i.e., business modelpatterns. Therefore, our taxonomy is not only useful for classifying business modelpatterns but also a business model concept describing the most importantdimensions and characteristics for configuring a business model. Second, wesummarized more than 100 instances of business model patterns as duplicates.However, even when two patterns possess similar names, their original descrip-tions might differ slightly. We could have easily avoided this issue by not filteringfor duplicates, but we are convinced that the benefit of not having to reviewidentical or very similar patterns multiple times outweighs this disadvantage.Third, the mapping of each pattern on the taxonomy dimensions might be biaseddue to the subjective interpretations of the researchers. To avoid such bias, tworesearchers discussed each rating. Furthermore, we conducted several cross-checksby, for instance, comparing all patterns that were assigned to the same charac-teristic of each dimension. Fourth, we do not consider our database to be analgorithm for business model innovation but rather a heuristic tool to support asystematic process. Hence, the database is not an automatic decision supportsystem that determines which pattern is the best; instead, it reveals potentialsolutions for a specific situation. The selection of the best patterns for a company’sspecific situation, however, requires the expertise of managers who also mustconsider other factors, such as the company’s business strategy or the competitivelandscape (Amshoff et al., 2015). In addition to expertise, the business modelinnovation process also requires significant amounts of creativity and experi-mentation. Some potentially effective patterns might not immediately appear at-tractive, while some patterns initially appearing attractive might fail to deliver thedesired outcomes. Finally, although we have demonstrated the usefulness of thetool developed in all four generic phases of the business model innovation process(Frankenberger et al., 2013), we also want to stress that business model patternsprimarily serve as tools for designing the front-end of a business model, i.e.,defining the necessary changes. The translation of these changes into concreteactivities and a transition path is no less important and can be better supported by


1750004-29

other tools, such as De Reuver et al.’s (2013) business model roadmapping.Therefore, our approach must be regarded not as a substitute but rather a com-plement to these existing tools.

Future Research Opportunities

We see two important future research opportunities arising directly from thisresearch. First, only one original source of business model patterns (Fleisch et al.,2014) comes from within the last three years. However, we are facing a new waveof digital transformation due to recent advances in digital technologies (Porter andHeppelmann, 2014). Hence, the identification of new digital business modelpatterns evolving from this transformation can make an important contribution fortheory and practice. Our business model pattern database provides a good structurefor systematically integrating these new patterns with existing research. Second,the database presents a solid foundation for applying business model patterns to aspecific industry and identifying potential future business models. For instance,Abdelkafi et al. (2013) transfer business model patterns to e-mobility and identifyseveral cutting-edge opportunities for new business models. In the future, thedatabase of business model patterns could be transferred to other industries that arealso undergoing fundamental changes, such as automotive, transportation, health,energy, buildings, or machinery.

Conclusion

The objective of this research was to make the valuable existing knowledge ofbusiness model patterns more accessible for both practical application as well astheoretic enhancements of the concept. We addressed several shortcomings of theexisting literature. Our review sheds light on the often confusing and contradictoryuse of the business model pattern concept. It is the first of its kind, because it doesnot limit its scope to a subset of authors or disciplines. The review integratesconcepts from theory with those from practitioners while advancing existingknowledge by systematically structuring the business model pattern landscape.Furthermore, the business model pattern database developed is a ready-to-use toolfor business model innovators. The database clearly describes 182 patterns andimmediately reveals the relevant set of patterns for a specific effect on the businessmodel. In addition, the database can be integrated into the business model inno-vation process. Hence, we hope for the innovation of many future business modelsthrough the application of the business model pattern database as well as theidentification of further patterns that could be added to the database in future.

G. Remane et al.

1750004-30

App

endixA.Integrated

Listof

BusinessMod

elPatterns

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

Add

-on

Offer

abasicprod

uctat

acompetitive

priceandcharge

forseveralextras

Ryanair,SAP,Sega

Gassm

annet

al.(201

4)

Adv

ertisingmod

el(ad-supp

orted,

contentspon

sorship,

hidd

enrevenu

es)

Provide

aprod

uctor

serviceandmix

itwith

advertisingmessages

Goo

gle,

Zattoo,

Spo

tify

Gassm

annet

al.(201

4),Hanson

(200

0),Rappa

(200

1),Tuff

andWun

ker(201

0)Adv

isors

Provide

consultin

gandadvice

Accenture,IBM

App

legate

(200

1)Affiliatio

n(prospectfees)

Refer

custom

ersto

athirdpartyand

receiveacommission

foraspecific

transactioncompleted

(e.g.,click,

give

inform

ation,

buyprod

uct)

Pinterest,Barnes&

Nob

le,

Amazon

.com

Gassm

annet

al.(201

4),Hanson

(200

0),Rappa

(200

1)

Affinity

club

sPartner

with

mem

bershipassociations

andotheraffinity

grou

psto

offera

prod

uctexclusivelyto

itsmem

bers

MBNA

John

son(201

0)

Agent

mod

els(sales

commission

s)Represent

thebu

yeror

thesellerand

earn

commission

sforsuccessful

facilitationof

transactions

Exp

edia.com

,estate

agents

Hanson(200

0),S

trauss

andFrost

(201

4)

Agg

regatio

n(agg

regator,distribu

tor,

multi-partymarketaggregation)

Build

aspecificform

ofbrok

erpreselectin

gprod

ucts/servicesand

target

audience

–hence,keyprocess

ismatchingof

needs

Amazon,Hom

eadvisor

App

legate

(200

1),Bienstock

etal.(200

2),Linderand

Cantrell(200

0),Rappa

(200

1),Tapscottet

al.(200

0)


1750004-31

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

Ago

ra(exchang

e)Build

aspecificform

ofbrok

erallowing

buyerandsellerto

freely

nego

tiate

andassign

valueto

good

s–hence,

keyprocessispricediscov

ery

eBay,Pricelin

e,NASDAQ

App

legate

(200

1),Bienstock

etal.(200

2),Tapscottet

al.

(200

0)

Aikido

Offer

prod

uctsto

thecustom

erthat

are

theop

positeof

whatthecompetitors

areoffering

,therebymaking

competitor’s

streng

thsaweakn

ess

Cirqu

edu

Soleil,Nintend

oWii

Gassm

annet

al.(201

4)

App

licationserviceprov

iders

(vertical

infrastructure

portals)

Allo

wcustom

ersto

usesoftwarethat

isho

sted

onremoteserversfor

continuo

usservicefee

OracleBusinesson

line,

Dou

beTwist

App

legate

(200

1),Eisenmann

(200

1)

Auctio

n(auctio

nbrok

er,e-auction,

exchange,prod

uctbids)

Makecustom

ersnamethemaxim

umpricethey

arewillingto

pay;

the

high

estpricewinstheprod

uctor

service

Sotheby’s,eB

ay,Goo

gle

App

legate

(200

1),Bienstock

etal.(200

2),G

assm

annet

al.

(201

4),Hanson(200

0),

John

son(200

9),Rappa

(200

1),Tim

mers(199

8),Tuff

andWun

ker(201

0)Aud

iencemeasurementservices

Con

duct

marketresearch

onon

line

audience

asagency

forother

custom

ers

Nielsen//N

etratin

gsRappa

(200

1)

Banneradvertising(infom

ercials,

ultram

ercials,advertising

networks,bann

erexchange,pay-

per-click)

Place

advertisingbann

erson

websites

TechW

eb,Lycos

Hanson(200

0),Rappa

(200

1)

G. Remane et al.

1750004-32

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

Barter

Allo

wcustom

ersto

tradeano

n-mon

etarycompensationin

exchange

foraprod

uctor

service

Pepsi,Pay

with

aTweet

Bienstock

etal.(200

2),

Gassm

annet

al.(201

4)

Brand

integrated

content

Asmanufacturerof

otherprod

ucts

create

contentforthesole

basisof

prod

uctplacem

ent

Red

Bull

Rappa

(200

1)

Breakthroug

hmarkets

Investinop

eningnewmarketsto

gain

atleastatempo

rary

mon

opoly

AIG

Insurance


0)

Bricksþ

clicks

(clickandmortar)

Integratebo

than

onlin

e(clicks)andan

offline(bricks)

presence

tobrow

se,

order,andpick

upprod

ucts

Hom

eDepot,Tesco,REI

John

son(200

9),Rappa

(200

1)

Brokerage

(switchb

oard,network

efficiency,op

enmarket-making)

Bring

together

andfacilitate

transactions

betweenbu

yers

and

sellers,charging

afeeforeach

successful

transaction

NASDAQ,Century

21Chatterjee

(201

3),Linderand

Cantrell(200

0),John

son

(201

0),TuffandWun

ker

(201

0)Bun

dleelem

entstogether

(bun

dled

pricing,

bund

lingsales)

Makepu

rchasing

simpleandmore

completeby

packagingrelated

prod

uctstogether

iPod

andiTun

es,fastfood

value

meals

Hanson(200

0),John

son(200

9),

John

son(201

0),Tuffand

Wun

ker(201

0)Businessintelligence

Gathersecond

aryandprim

ary

inform

ationabou

tcompetitors,

markets,custom

ers,andother

entitiesto

predictim

portant

inform

ation

Oilcompanies

forgasprices,

traders

Strauss

andFrost(201

4)


1750004-33

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

Buy

/sellfulfilm

ent

Takecustom

erorders

tobu

yor

sella

prod

uctor

service,

includ

ingterm

slik

epriceanddeliv

ery

CarsD

irect,Respo

nd.com

Rappa

(200

1)

Buy

ingclub

Rou

ndup

buyers

with

attractiv

eprices

andusepu

rchase

volumeto

gain

discou

nts

Letsbuyit.com,mobilcom

-debitel


0)

Chann

elmaxim

ization

Leverageas

manychannelsas

possible

tomaxim

izerevenu

esAOL,Tim

eWarner


0)

Classifieds

Listitemsforsale

orthings

ofinterest

andcharge

listin

gor

mem

bership

fees

inexchange

Mon

ster.com

,Craigslist

Rappa

(200

1)

Collabo

ratio

nplatform

sProvide

asetof

toolsandan

inform

ationenvironm

entfor

collabo

ratio

nbetweenenterprises

DeutscheTelekom

/Globana’s

ICS,ESPRIT

GENIA

LTim

mers(199

8)

Con

nection(internetaccess

prov

ider,ho

rizontal

infrastructure

portals,internet

services

prov

iders)

Provide

physical

and/or

virtualnetwork

infrastructure

togain

(internet)

access

AOL,Sprint,AT&T

Eisenmann(200

1),App

legate

(200

1),Rappa

(200

1),Wirtz

etal.(201

0)

Con

tent

prov

ider

(informationand

serviceprov

iders,selling

content,

onlin

econtentprov

iders,content

publisher,content,content

services)

Provide

contentsuch

asinform

ation,

digitalprod

ucts,andservices

Reuters,WallStreetJournal

onlin

e,IEEEJournals

App

legate

(200

1),Clemon

s(200

9),Eisenmann(200

1),

Rappa

(200

1),Strauss

and

Frost(201

4),W

eillandVitale

(200

1),Wirtz

etal.(201

0)Con

tent-targetedadvertising

Identifythemeaning

ofaweb

page

and

then

automatically

deliv

errelevant

adswhenauser

visitsthat

page.

Goo

gle

Rappa

(200

1)

G. Remane et al.

1750004-34

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

Con

text

Sortand/or

aggregateavailableon

line

inform

ation

Goo

gle

Wirtz

etal.(201

0)

Con

textualmob

ileadvertising

Tailoradvertisingto

thecontext,e.g.,

locatio

n,preferences,or

status

Goo

gleAdS

ense,

Com

muteStream

Clemon

s(200

9)

Con

tractor

Sellservices

prov

ided

prim

arily

bypeop

le,such

asconsultin

g,constructio

n,education,

person

alcare,packagedeliv

ery,

live

entertainm

ent,or

healthcare

Accenture,Federal

Exp

ress

Weillet

al.(200

5)

Coo

lbrands

(brand

edreliable

commod

ity,brandbu

ilding)

Earnprem

ium

prices

with

competitive

prod

uctsthroug

hexpertbrand

marketin

g

Goo

dyear,Nike

Hanson(200

0),Linderand

Cantrell(200

0)

Costleadership

Keepvariable

costslow

andsellhigh

volumes

atlow

prices

Ikea

TuffandWun

ker(201

0)

Costredu

ction[throu

ghtheinternet]

Use

theInternetto

redu

cecostsandthus

increase

efficiency

Cisco

Hanson(200

0)

Cross

selling

Offer

complem

entary

prod

uctsin

additio

nto

thestandard

offering

Shell,

Tchibo,

Aldi

Gassm

annet

al.(201

4)

Crowdfun

ding

Finance

aprod

uct,project,or

company

byagrou

pof

privateinvestorsoften

includ

ingano

n-mon

etary

compensationin

exchange

Marillion,

PebbleTechn

olog

y,Brainpo

olGassm

annet

al.(201

4)

Crowdsou

rcing

Solve

aprob

lem

byou

tsou

rcingitto

the

crow

d(e.g.,an

internet

commun

ity)

Cisco,Procter

&Gam

ble,

Inno

Centiv

eGassm

annet

al.(201

4),John

son

(201

0)Custom

supp

liers

Design,

prod

uce,

anddistribu

tecustom

ized

prod

uctsandservices

Boeing,

McG

raw-H

illApp

legate

(200

1)


1750004-35

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

Custom

supp

liers

ofhardware

Produ

ceandcustom

izeIT

equipm

ento

rcompo

nents

Dell,MicroAge

App

legate

(200

1)

Custom

supp

liers

ofsoftware

Createandcustom

izesoftwareand

license/sellit

And

ersenCon

sulting

,Sapient,

Viant

App

legate

(200

1)

Customer

loyalty

(incentiv

emarketin

g)Increase

custom

erloyalty

throug

hrewardprog

rams

American

Airlin

es,Safew

ayClubCard,

Payback

Gassm

annet

al.(201

4),Rappa

(200

1)Customer

relatio

nshipmanagem

ent

[throu

ghdigitaltechno

logies]

Retainandgrow

business

and

individu

alcustom

ersthroug

hstrategies

that

ensure

their

satisfactionwith

thecompany

andits

prod

ucts,e.g.,by

collectingand

integratingallinform

ationon

each

custom

ertouchpo

int

Com

panies

applying

salesforce.

com

Strauss

andFrost(201

4)

Databasemarketin

gCollect,analyse,

anddissem

inate

electron

icinform

ationabou

tcustom

ers,prospects,andprod

ucts

toincrease

profi

ts

GM

Card,

Blockbu

ster

Inc.

Strauss

andFrost(201

4)

Defactostandard

Develop

anduseprop

rietarycompo

nent

techno

logy

toprov

idehigh

prod

uct

functio

nality,

butalso

license

itbroadlythroug

hout

theindu

stry

toestablishitas

thedo

minantdesign

Sharp

inflat

paneldisplays


0)

Dealersupp

ort[throug

htheinternet]

Use

theinternet

toindirectly

supp

ort

salespartners

GM

Hanson(200

0)

G. Remane et al.

1750004-36

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

Dem

andcollectionsystem

Let

prospectivebu

yers

makeafinal

(binding

)bidforaspecified

good

orserviceandarrang

efulfilm

ent

Pricelin

e.com

Rappa

(200

1)

Dialdo

wnfeatures

Targetless-dem

anding

consum

erswith

prod

uctsor

services

that

may

notbe

superior

butareadequate

and

perhapsmoreconv

enient,simple,

etc.

Motofon

eJohn

son(200

9)

Digitaladd-on

Aph

ysical

assetissold

atasm

all

margin;

over

time,

thecustom

ercan

purchase

oractiv

ateanynu

mberof

digitalservices

with

ahigh

ermargin

Navigationsystem

sFleisch

etal.(201

4)

Digitallock-in

Use

digitaltechno

logies

tolim

itthe

compatib

ility

ofph

ysical

prod

ucts

andthus

lock

custom

ersto

your

ecosystem

App

le’s

iPho

neFleisch

etal.(201

4)

[Digital]infrastructure

retailers

([digital]infrastructure

marketplaces,[digital]

infrastructure

exchanges)

Takecontrolof

inventoryandsell

digitalinfrastructure

Com

pUSA.com

,Staples.com

App

legate

(200

1)

[Digital]serviceprov

ider

Produ

ceanddeliv

erawiderang

eof

services

onlin

eAmerican

Express,Citigroup

App

legate

(200

1)

Digitally

-charged

prod

ucts

Chargeclassicph

ysical

prod

uctswith

abu

ndle

ofnew

sensor-based

digital

services

andpo

sitio

nthem

with

new

valueprop

osition

s

Smartwashing

machine,sm

art

home

Fleisch

etal.(201

4)


1750004-37

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

Digitizatio

nOffer

atradition

ally

physical

prod

uctas

adigitalversion

Wikipedia,Netflix,Dropb

oxGassm

annet

al.(201

4)

Disaggregated

pricing

Allo

wcustom

ersto

buyexactly

–and

only

–whatthey

want

FreeMob

ileTuffandWun

ker(201

0)

Disinterm

ediatio

n(m

anufacturer

direct

mod

el,direct

selling

,multi-levelmarketin

g,direct

tocustom

er)

Deliver

aprod

uctor

servicethat

has

tradition

ally

gone

throug

han

interm

ediary

directly

tothecustom

er

Dell,Nespresso,WebMD

Gassm

annet

al.(201

4),John

son

(200

9),John

son(201

0),

Rappa

(200

1),Strauss

and

Frost(201

4),W

eillandVitale

(200

1)Distributivenetwork

Provide

infrastructure

toconn

ectother

actors

oftheecon

omysuch

aslogistics,energy

,mob

ility,or

commun

ication

Enron

,UPS,AT&T

Tapscottet

al.(200

0)

Domoreto

addressthejob

Loo

kbeyo

ndyo

urtypicaloffering

and

addressotherjobs

your

custom

ers

aretrying

togetdo

ne

UPS

John

son(200

9)

Edu

cators

Createanddeliv

ereducationalo

fferings,

oftenon

line

Harvard

BusinessSchoo

lApp

legate

(200

1)

Efficiency-based

Use

human

orcapitalresources

efficiently

toprod

ucecommon

alities

inacompetitivemarket

Airlin

es,mining,

hospitals

Chatterjee

(201

3)

E-m

ail

Com

mun

icatewith

stakeholders

via

e-mailsrather

than

printandmail

Onlinemailin

gsof

companies,

digitalannu

alrepo

rts

Strauss

andFrost(201

4)

G. Remane et al.

1750004-38

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

E-m

all(virtual

marketplace)

Build

aplatform

foracollectionof

e-shop

s,usually

enhanced

bya

common

umbrella,for

exam

ple,of

awell-kn

ownbrand

ElectronicMallBod

ensee,

MerchantServicesat

Amazon

.com

Rappa

(200

1),Tim

mers(199

8)

Enterpriseresource

planning

Use

anintegrated

back

office

system

toop

timizebu

siness

processesand

therebyredu

cecost

Com

panies

usingSAP

Strauss

andFrost(201

4)

Entrepreneur

Createandsellfinancialassets,often

creatin

gandselling

firm

sKleiner,Perkins,Caufield&

Byers

Weillet

al.(200

5)

E-procurement(onlinepu

rchasing

)Con

duct

tend

eringandprocurem

ent

electron

ically

JapanAirlin

es,Wal-M

art

Strauss

andFrost(201

4),

Tim

mers(199

8)E-retailer(com

merce,catalog

merchant,virtualmerchant)

Assum

econtrolof

inventory,

setano

n-nego

tiableprice,

andsellph

ysical

prod

uctson

line

Amazon

.com

,LandsEnd

.com

,Walmart.com

App

legate

(200

1),Eisenmann

(200

1),Rappa

(200

1),Wirtz

etal.(201

0)E-sho

p(e-com

merce,order

processing

)Build

aweb

shop

tosellprod

uctsor

services

onlin

eFleurop

,Travelocity,Flyeralarm

Gassm

annet

al.(201

4),Strauss

andFrost(201

4),Tim

mers

(199

8)Exclusive

market-making

Bring

together

specific,high

lytargeted,

qualified

audiencesfortrading

Edu

.com

,Orderzone.com


0)

Exp

eriencedestination(exp

erience

selling

)Use

acarefully

design

edenvironm

entto

attractcustom

erswho

payprem

ium

prices

Disneythem

eparks,NikeTow

nStores,Nestlé

Nespresso

Gassm

annet

al.(201

4),Linder

andCantrell(200

0)


1750004-39

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

Exp

erienceselling

Allo

wtheclient

toexperience

the

prod

uct,oftenviaasalesforceanda

pyramid

commission

structure;

tradition

ally

appliedforcosm

etic

prod

ucts

MaryKay

Cosmetics,Amway


0)

Financial

brok

erMatch

buyers

andsellers

offinancial

assets

e*Trade,Schwab

Weillet

al.(200

5)

Financialland

lord

(financing,

instant

gratificatio

n)Let

others

usecash

(orotherfinancial

assets)un

dercertain(often

time-

limited)

cond

ition

s

Bankof

America,

FannieMae,

Aetna


0),Tuff

andWun

ker(201

0),Weill

etal.(200

5)Financial

trader

Buy

andsellfinancialassetswith

out

sign

ificantly

transforming(or

design

ing)

them

MerrillLyn

chWeillet

al.(200

5)

Flat-rate

Chargeafixedpriceandallow

the

custom

erun

limitedaccess

inexchange

BuckarooBuffet,Sandals

Resorts,Netflix

Gassm

annet

al.(201

4)

Flexiblepricing(dyn

amic

pricing

strategies

onlin

e)Varyprices

foran

offering

basedon

demand

American

Airlin

esStrauss

andFrost(201

4),Tuff

andWun

ker(201

0)Forcedscarcity

Lim

itthesupp

lyof

offering

savailable

todriveup

demandandprices

OPEC,Rue

LaLa

TuffandWun

ker(201

0)

Fractionalow

nership

Ago

odispu

rchasedtogether

bya

grou

pof

custom

ers,each

buying

acertainshareof

theusagerigh

t,often

atim

eperiod

Tim

e-sharingcond

os,Net

Jets,

écurie25

Gassm

annet

al.(201

4),John

son

(201

0)

G. Remane et al.

1750004-40

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

Franchising

Allo

wfranchiseesto

useabu

siness

concept,includingbrandand

prod

ucts,in

compensationfor

financialcompensation

Starbucks,Sub

way,McD

onald’s

Gassm

annet

al.(201

4)

Free(freeforadvertising)

Provide

custom

erwith

afree-of-charge

offeranduseothersourcessuch

asadvertisingto

generate

revenu

es

Metro

(freepaper),privateTV

stations,Goo

gle


0),


(201

0)Freem

ium

(freetrial)

Offer

basicservices

forfree,while

charging

aprem

ium

foradvanced

orspecialfeatures

Sky

pe,Dropb

ox,LinkedIn

Gassm

annet

al.(201

4),Hanson

(200

0),John

son(200

9),

John

son(201

0),Tuffand

Wun

ker(201

0)From

push-to-pu

llMakeprod

uctio

nmoreflexible

inorder

toideally

prod

uceaprod

uctjust

whenitisorderedandno

tupfront

asstockarticle

Toy

ota,

Zara,

Dell

Gassm

annet

al.(201

4)

Haggle

Allo

wthebu

yers

tonego

tiate

over

the

price

www.hagglezon

e.com

Bienstock

etal.(200

2)

Horizon

talpo

rtals(portals,po

rtal)

Createapo

rtal

that

prov

ides

agateway

toInternet’s

contentandoffering

s,such

assearch

engine,e-mail,news

etc.

Yahoo

!,Microsoft’s

MSN

App

legate

(200

1),Eisenmann

(200

1),R

appa

(200

1),S

trauss

andFrost(201

4)

HRbrok

erMatch

buyers

andsellers

ofhu

man

services

Rob

ertHalf,EDS

Weillet

al.(200

5)


1750004-41

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

Incomparableprod

ucts

(incom

parableservice)

Use

deep

R&D

skillsto

developand

exploitprop

rietarytechno

logy

toofferun

ique

prod

uctsthat

command

high

margins

Polaroid,

DuP

ont


0)

Infomediary

(informationbrok

ers,IP

brok

er)

Match

buyersandsellersof

inform

ation

orotherintang

ible

assets

Internet

Securities,Individu

al.

com,Valassis

App

legate

(200

1),H

artm

anet

al.

(200

0),Rappa

(200

1),

Tim

mers(199

8),Weillet

al.

(200

5)Inform

ationcollection

Collect

andcommercializeinform

ation

gathered

from

theInternet

Dou

bleC

lick,

Goo

gle

Hanson(200

0)

Infrastructure

services

firm

s(e-businessenabler)

Produ

ceanddeliv

ercomplem

entary

services

fortheInternet

Dou

bleC

lick,

Federal

Exp

ress,

Webvan

App

legate

(200

1),H

artm

anet

al.

(200

0)Ingredient

branding

(category-

build

ing)

Build

abrandof

aprod

uctcompo

nent

that

ispartof

anendprod

uct

Intel,CarlZeiss,Bosch

Gassm

annet

al.(201

4)

Integrator

Cov

ermostpartsof

thevaluechainin-

housein

orderto

keep

controlof

inno

vatio

ns,efficiency

etc.

CarnegieSteel,Ford,

Exx

onMob

ilGassm

annet

al.(201

4),And

rew

andSirkin(200

6)

Inventor

Createandthen

sellintang

ible

assets,

such

aspatentsandcopy

righ

tsLucent’sBellLabs

Weillet

al.(200

5)

IPtrader

(bitvend

or)

Buy

andsellintang

ible

assets

NTLInc.,App

leiTun

esMusic

Store

Rappa

(200

1),W

eilletal.(20

05)

[IT]equipm

ent/com

ponent

manufacturers

Produ

ceIT

equipm

entandcompo

nents

IBM,Com

paq,

Cisco

App

legate

(200

1)

Kno

wledg

emanagem

ent[throu

ghuseof

digitaltechno

logies]

Transform

andstoreacompany’s

data

into

useful

inform

ationand

know

ledg

e

Com

panies

usingan

internal

Wiki

Strauss

andFrost(201

4)

G. Remane et al.

1750004-42

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

Leveragecustom

erdata

(sellin

ginform

ationgathered

from

onlin

eexperience,user

registratio

n)

Collect

custom

erdata

andusethem

commercially,e.g.,fortargeted

advertising

Twitter,23

andMe,

Faceboo

kGassm

annetal.(20

14),Clemon

s(200

9),Rappa

(200

1)

Leveragenew

influencers

Win

over

influencerswho

supp

ortthe

salesprocess

Hindu

stan,Unilever

John

son(200

9)

Licensing

(the

licensor,IP

landlord,

license)

License

orotherw

isegetp

aidforlim

ited

useof

intang

ible

assets

Microsoft

And

rew

andSirkin(200

6),

Gassm

annet

al.(201

4),

Rappa

(200

1),Tuffand

Wun

ker(201

0),Weillet

al.

(200

5)Lock-in

Lockthecustom

ersto

your

ecosystem

bystrong

lyincreasing

thesw

itching

coststhroug

hhigh

hurdles

Lego,

Hew

lett-Packard,Nestlé

BabyN

esFleisch

etal.(201

4),Gassm

ann

etal.(201

4)

Low

-tou

chapproach

(nofrills,low-

pricereliablecommod

ity,

standardization)

Offer

standardized,low

-price

versionof

aprod

uctor

servicethat

istradition

ally

custom

ized

andhigh

erpriced

Sou

thwestairlines,Xiameter

Gassm

annet

al.(201

4),Linder

andCantrell(200

0),John

son

(200

9),John

son(201

0)

Makemoreof

itOffer

internal

know

-how

andother

resourcesalso

asexternal

serviceto

othercompanies

Porsche

Con

sulting

,Festo

Didactic,Amazon

Web

Services

Gassm

annet

al.(201

4)

Marketplace

exchange

Build

aspecificform

ofbrok

eralso

offering

afullrang

eof

services

covering

thetransactionprocess,

from

marketassessmentto

nego

tiatio

nandfulfilm

entforan

indu

stry

consortiu

m

Orbitz,ChemCon

nect

Rappa

(200

1)


1750004-43

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

Masscustom

ization(m

ass-

custom

ized

commod

ity)

Customizeacommod

ityprod

uctto

the

custom

ers’

specificpreferences

Dell,mym

uesli

Gassm

annet

al.(201

4),Linder

andCantrell(200

0),Strauss

andFrost(201

4)Mem

bership

Chargeatim

e-basedpaym

entto

allow

access

tolocatio

ns,offering

s,or

services

that

non-mem

bers

dono

thave

Costco,

Metro

TuffandWun

ker(201

0)

Merchantmod

el(sales)

Actas

who

lesalers/retailerof

good

sand

services

Wal*M

art,Mediamarkt

Bienstock

etal.(200

2),Rappa

(200

1)Micro

transactions

Sellm

anyitemsforas

little

asado

llar–

oreven

only

onecent

–to

drive

impu

lsepu

rchases

Kartrider

TuffandWun

ker(201

0)

Misdirection

Sendcustom

ersto

locatio

nsdifferent

from

whatthey

initially

searched

for

ifthesearched

company

didno

tpay

sufficientlistin

gfees

tothesearch

engine

Goo

gle,

Yahoo

Clemon

s(200

9)

Multi-sidedplatform

s(two-sided

market)

Bring

together

twoor

moredistinct

but

interdependent

grou

psof

custom

ers,

where

thepresence

ofeach

grou

pcreatesvaluefortheothergrou

ps

Visa,MicrosoftWindo

ws,Metro

New

spaper

Gassm

annet

al.(201

4),


(201

0)

Negativeop

eratingcycle(alterthe

usualform

ula,

float,cash

machine)

Generatehigh

profi

tsby

maintaining

low

inventoryandhaving

the

custom

erpayup

fron

t

Amazon

,NextRestaurant,

Group

onGassm

annet

al.(201

4),John

son

(200

9),John

son(201

0),Tuff

andWun

ker(201

0)

G. Remane et al.

1750004-44

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

Networkvalue

Provide

aplatform

thatleadsto

repeated

purchasesby

acore

grou

pof

loyal

custom

ers

Microsoft,Netflix,Playstatio

nChatterjee

(201

3)

Networkedutility

prov

iders

Createanddistribu

tedo

wnloadable

softwareprog

ramsthat

facilitate

commun

ication

ICQ,Acrob

atReader

Eisenmann(200

1)

Objectselfservice

Provide

physical

prod

uctswith

the

ability

toindepend

ently

placeorders

ontheInternet

Smartheatingsystem

s,Internet

refrigerator

Fleisch

etal.(201

4)

One-stopconv

enient

shop

ping

Use

broadselectionandub

iquitous

access

toattractbu

sybu

yers

who

will

payaprem

ium

forconv

enience

WW

Grainger


0)

One-stoplow-price

shop

ping

Use

low

priceandtheconv

enienceof

broadselectionto

attractbu

yers,

then

conv

ertvo

lumeinto

purchase

discou

nts

Walmart,Sup

plyG

enie.com


0)

Onlineadvertisingandpu

blic

relatio

nsBuy

advertisingon

prod

uctsor

services

ofanothercompanies

Produ

ctadvertisingin

radio,

TV,

orInternet

Strauss

andFrost(201

4)

Onlinebrok

ers(brokerage

mod

el,

third-partymarketplace,

marketplace,interm

ediary,

brok

er,metam

ediary,e-bu

siness

storefront)

Use

theinternet

tofacilitatea

transactionbetweenabu

yeranda

seller

ebay,Airbn

bBienstock

etal.(200

2),Hartm

anet

al.(200

0),Rappa

(200

1),

Strauss

andFrost(201

4),

Tim

mers(199

8),Weilland

Vitale

(200

1)Onlinesalesprom

otions

Use

theinternet

tosend

free

prod

uct

samples

ordiscou

ntcoup

onsto

custom

ers

Com

panies

selling

viaGroup

onStrauss

andFrost(201

4)


1750004-45

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

Openbu

siness

mod

els

Createinno

vatio

nsby

system

atically

integratingpartners

into

the

company

’sR&D

process

Procter

&Gam

ble,

Inno

centive

Gassm

annet

al.(201

4),


(201

0)Opencontent(pub

licbroadcastin

g)Develop

openly

accessible

content

collabo

rativ

elyby

aglob

alcommun

ityof

contribu

tors

who

workvo

luntarily

Wikipedia,The

Classical

Statio

nRappa

(200

1)

Opensource

(alliance)

Develop

aprod

uctno

tby

acompany

,bu

tby

apu

blic

commun

itywith

all

inform

ationbeingavailablepu

blicly

Mozilla,

Linux

,Wikipedia

Gassm

annet

al.(201

4),Rappa

(200

1),Tapscottet

al.(200

0)

Orchestrator(value

chain)

Focus

oncore

competenciesand

outsou

rce/coordinate

allother

activ

ities

alon

gthevaluechain

Procter

&Gam

ble,

Nike,

Li&

Fun

gAnd

rew

andSirkin(200

6),

Gassm

annet

al.(201

4),

Tim

mers(199

8)Owntheun

desirable

Seekto

servesegm

entsof

themarket

that

might

notappear

immediately

attractiv

e

AllL

ife

John

son(200

9)

Pay

peruse(m

etered

use,

metered

subscriptio

ns,pay-as-you

-go,

utility

mod

el)

Chargeforeach

useof

aprod

uctor

service

Metered

ISPs,Goo

gle,

Zipcar

Gassm

annet

al.(201

4),Hanson

(200

0),John

son(201

0),

Rappa

(200

1),Tuffand

Wun

ker(201

0)Pay

whatyo

uwant(user-defined)

Invite

custom

ersto

setthepricethey

wishto

pay

Radiohead,One

World

Everybo

dy,Hum

bleBun

dle

Gassm

annetal.(20

14),Tuffand

Wun

ker(201

0)Peer-to-peer(Person-to-person

networking

services)

Facilitatesatransactionam

ongpeers,

i.e.,twoor

moreconsum

ers,throug

hprov

isionof

aplatform

ebay,Napster,Airbn

bGassm

annet

al.(201

4),Rappa

(200

1)

G. Remane et al.

1750004-46

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

Perceived

value-based

Position

company’s

output

asa“want”

item

andcommandapriceprem

ium

—investin

know

ledg

eprofession

als

such

asscientists,engineers,

prog

rammers,or

data

experts

Sem

icon

ductors,softwarefirm

s,ph

arma

Chatterjee

(201

3)

Perform

ance-based

contracting

Determinethefeeforusageof

aprod

uct

notb

yfrequencyof

usebu

tratherby

thequ

ality

oftheresultfrom

theuse

Rolls-Roy

ce,BASF,Xerox

Fleisch

etal.(201

4),Gassm

ann

etal.(201

4)

Phy

sicalbrok

erMatch

buyers

andsellers

ofph

ysical

assets

eBay,Century

21Weillet

al.(200

5)

Phy

sicalfreemium

Aph

ysical

assetthat

issold

together

with

free

digitalservices

while

charging

aprem

ium

foradvanced

digitalservices

And

roid

smartpho

nes

Fleisch

etal.(201

4)

Phy

sicalland

lord

Selltherigh

tto

useaph

ysical

asset

Marriott,Hertz

Weillet

al.(200

5)[Phy

sical]manufacturer

Createandsellph

ysical

assets

Ford,

Pepsi,General

Motors

App

legate

(200

1),Weillet

al.

(200

5)[Phy

sical]who

lesaler(retailer)

Buy

andsellph

ysical

assets

Wal*M

art,Amazon

Rappa

(200

1),W

eilletal.(20

05)

Premium

Price

atahigh

ermarginthan

competitorsforasuperior

prod

uct,

offering

,experience,service,

orbrand

Lexus

TuffandWun

ker(201

0)

Produ

ctas

pointof

sales

Makeph

ysicalprod

uctsbecomesitesof

digitalsalesandmarketin

gservices

that

thecustom

erconsum

esdirectly

Smartpho

nes,cars

Fleisch

etal.(201

4)


1750004-47

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

attheprod

uctor

indirectly

via

anotherdevice

Produ

ctsales(purchase)

Sellaprod

uctforafixedprice

Dell

Hanson(200

0),Rappa

(200

1)Qualityselling

(enh

ance

quality

)Attractcustomerswith

high

quality

and/

orhard-to-find

prod

uctsor

services

forprem

ium

prices

SaksFifth

Avenu

e,Nordstrom

Hanson(200

0),Linderand

Cantrell(200

0)

Query-based

paid

placem

ent

Sellfavo

urable

linkpo

sitio

ning

oradvertisingkeyedto

particular

search

term

sin

auser

query

Goo

gle,

Overture

Rappa

(200

1)

Razors/blades

(cellpho

ne)

Offer

acheapor

free

basicprod

uct

(“razors”)together

with

complem

ents(“blades”)that

are

overpriced

andtherebysubsidizethe

basicprod

uct

Gillette,Nespresso,Amazon

Kindle

Gassm

annet

al.(201

4),John

son

(200

9),John

son(201

0),


0)

Reliablecommod

ityop

erations

(guaranteedavailability)

Provide

predictablecommod

ityprod

uctsor

services

forwhich

custom

ersarewillingto

payasm

all

prem

ium,as

they

arereliable

UPS,AT&T,Hilti


0),

Gassm

annet

al.(201

4)

Rem

oteusageandcond

ition

mon

itoring

Equ

ipprod

uctswith

digital

techno

logies

that

allow

todetect

errors

preventativ

elyandmon

itor

usage

Rolls-Roy

ce,Brother

Fleisch

etal.(201

4)

Rentinsteadof

buy(lease

insteadof

sell,

leasing,

lease)

Tem

porarily

lend

aprod

uctto

the

custom

erandcharge

arent

Xerox

,fashionette,United

Rentals

Gassm

annet

al.(201

4),John

son

(200

9),John

son(201

0),

Rappa

(200

1)

G. Remane et al.

1750004-48

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

Revenue

sharing(retailalliances)

Share

therevenu

eswith

other

companies

inorderto

create

asymbiotic

relatio

nship

Cdn

ow,App

leApp

Store,

Group

onGassm

annet

al.(201

4),Hanson

(200

0),Rappa

(200

1)

Reverse

auction

Set

aceiling

priceforaprod

uctor

serviceandhave

participantsbidthe

pricedo

wn

Elance.com,OnF

orce.com

Bienstock

etal.(200

2),John

son

(201

0)

Reverse

engineering

Break

downaprod

uctof

competitors

into

itscompo

nentsandusethis

inform

ationto

build

acomparable

prod

uct

Bayer,Brilliance

China

Auto,

Pelikan

Gassm

annet

al.(201

4)

Reverse

inno

vatio

nTransfercheaperprod

uctsfrom

less

developedcoun

triesto

more

developedcoun

tries

General

Electric,

Log

itech,

Renault

Gassm

annet

al.(201

4)

Reverse

razors/blades

Offer

anexpensivebasicprod

uct

(“razors”)that

allowsforusageof

cheapor

even

free

complem

ents

(“blades”)

iPod

/iTun

esJohn

son(200

9),John

son(201

0)

Risksharing

Waive

standard

fees

orcostsifcertain

metrics

areno

tachieved,b

utreceive

outsized

gainswhenthey

are

Progressive

TuffandWun

ker(201

0)

Rob

inHoo

dChargewealth

ycustom

ersmorethan

poorer

custom

ersforaprod

uctor

service

Museums,Aravind

Eye

Care

System,TOMSSho

esGassm

annet

al.(201

4)

Scaledtransactions

Maxim

izemargins

bypu

rsuing

high

-vo

lume,

large-scaletransactions

whenun

itcostsarerelativ

elyfixed

MorganStanley

TuffandWun

ker(201

0)


1750004-49

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

Searchagent

Searchou

tthepriceandavailabilityfor

ago

odor

servicespecified

bythe

buyer

Idealo.de

Rappa

(200

1)

Self-service

Delegateapartof

thevaluechainto

the

client

McD

onald’s,IK

EA,BackW

erk

Gassm

annet

al.(201

4)

Sellin

gexperience

Offer

new

experiencesthroug

hparticipationin

acommun

ity,often

virtually

Gam

eBox

,World

ofWarcraft

Clemon

s(200

9)

Sellin

gon

lineservices

Offer

tousesoftwareservices

onlin

eE*T

rade,SurveyMon

key

Clemon

s(200

9)Sellin

gvirtualaccessories

Sellaccessoriesthat

wou

ldbe

difficult

toearn

inon

linegames

World

ofWarcraft,Secon

dlife

Clemon

s(200

9)

Sensoras

aservice

Collect,p

rocess,and

sellsensor

datafor

afee

Streetline.com

,Goo

gleMaps

Fleisch

etal.(201

4)

Service-w

rapp

edcommod

ityDistin

guishcommod

ityprod

uctsby

services

that

areadded

Mindspring,

Earthlin

kLinderandCantrell(200

0)

Servitizationof

prod

ucts(produ

ct-

to-service)

Sellon

goingservices

inadditio

nto

the

prod

uctor

even

selltheservicethe

prod

uctperformsrather

than

the

prod

uct

IBM,Hilti,Zipcar

John

son(200

9),John

son(201

0)

Sharedinfrastructure

Share

acommon

infrastructure

amon

gseveralcompetitors

ABACUS

WeillandVitale

(200

1)

Sho

p-in-sho

p(develop

unique

partnerships)

Build

astorewith

inanotherstore

Tchibo,

DeutschePost,

MinuteC

linic

Gassm

annet

al.(201

4)

Socialsearch

Tailorsearch

results

basedon

auser’s

social

network

Faceboo

k,Airbn

bClemon

s(200

9)

Softwarefirm

sCreatesoftwareandlicense/sellit

Microsoft,Oracle,

Siebel

App

legate

(200

1)

G. Remane et al.

1750004-50

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

Solutionprov

ider

(com

prehensive

offering

,full-serviceprov

ider)

Provide

afullrang

eof

services

inon

edo

maindirectly

andviaalliesand

attempt

toow

ntheprim

ary

consum

errelatio

nship

App

leiPod

/iTun

es,Heidelberger

Druckmaschinen

Gassm

annet

al.(201

4),Linder

andCantrell(200

0),Weill

andVitale

(200

1)

Sub

scription(sub

scriptionmod

el,

subscriptio

nclub

,mem

bership)

Con

tinuo

usly

prov

idecustom

erswith

prod

uctsor

services

andregu

larly

charge

upfron

tfees

Magazines,Blacksocks,Spo

tify

Gassm

annet

al.(201

4),Hanson

(200

0),John

son(200

9),

John

son(201

0),Rappa

(200

1),TuffandWun

ker

(201

0)Sup

ermarket(cat-daddy

selling

)Offeralargevarietyof

prod

uctsatalow

price

Toy

s“R”Us,The

Hom

eDepot,

Staples

Gassm

annet

al.(201

4),Linder

andCantrell(200

0)Sup

pliersupp

ort[throu

ghthe

internet]

Use

theInternet

toim

prov

eprocurem

entandspeedof

deliv

ery

from

supp

liers

GE

Hanson(200

0)

Sup

plychainmanagem

ent

Con

nect

supp

liers

anddistribu

tion

channelsmoreclosely

FedEx

Strauss

andFrost(201

4)

Targetthepo

orFocus

onthebo

ttom-tierclientsof

the

incomepy

ramid

andsellalarge

numberof

cheapprod

uctswith

low

margin

Wal*M

art,Aldi

Gassm

annet

al.(201

4)

The

long

tail

Focus

onselling

alargenu

mberof

nicheprod

ucts,each

ofwhich

sells

relativ

elyinfrequently

Netflix,eB

ay,You

Tub

eGassm

annet

al.(201

4),


(201

0)Transactio

nserviceandexchange

interm

ediatio

n(infrastructure

prov

ider)

Provide

integrated

portal

tocoordinate

complex

transactions

amon

gCelarix,Solbright,PrintCon

nect

Hartm

anetal.(20

00),Linderand

Cantrell(200

0)


1750004-51

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

invo

lved

severalpartiesforspot

markets

Trash-to-cash

Reuse

alreadyused

prod

ucts

DualesSystem

Deutschland

,H&M,cm

rGassm

annet

al.(201

4)

Trustinterm

ediary

(transactio

nbrok

er)

Provide

athird-partypaym

ent

mechanism

forbu

yers

andsellers

tosettleatransaction

PayPal,Escrow.com

,Cyb

erCash

Hartm

anet

al.(200

0),Rappa

(200

1)

Trustservices

Establishmem

bershipassociations

that

abideby

anexplicitcode

ofcond

uct,

andin

which

mem

bers

paya

subscriptio

nfee

Truste

Rappa

(200

1)

Trusted

prod

uctleadership

Develop

long

-lastin

gprod

uctplatform

architectures

tocreate

ano

n-disrup

tiveprod

uctup

gradepath

for

locked-incustom

ers

Cisco,Intel


0)

Ultimateluxu

ryFocus

onselling

tothetop-tier

custom

ersof

theincomepy

ramid

Lam

borghini,Abb

otDow

ning

Gassm

annet

al.(201

4)

Unb

undling

Unb

undlethreetypesof

businesses/

organizatio

nalun

itswith

inon

efirm

asthey

allhave

different

imperativ

es:custom

errelatio

nship,

prod

uctinno

vatio

n,and

infrastructure

Mob

iletelecom

indu

stry,private

bank

ingindu

stry


(201

0)

Und

ertheum

brella

pricing

Und

er-price

themarketleader

anduse

marketin

gto

convince

custom

ers

your

offering

sareequivalent,fast

PrimeCom

puterwith

Digital

Equ

ipmentin

the19

80s,MCI

WorldCom

with

AT&T


0)

G. Remane et al.

1750004-52

(Con

tinued)

Pattern

name(other

names)[m

anu-

ally

addeddescription]

Descriptio

nSelectedexam

ple(s)

Sou

rce(s)

follo

win

prod

uct/service

developm

ent

Userdesign

edCustomersinvent

prod

uctsthat

afterw

ards

areprod

uced

bythe

company

App

leApp

Store,C

reatem

ytattoo,

LegoFactory

Gassm

annet

al.(201

4)

Value

chainintegrator

(value

net

integrator)

Coo

rdinateactiv

ities

across

thevalue

netby

gathering,

synthesizing

,and

distribu

tinginform

ation

Seven

Eleven,

ESPRIT

project

TRANS20

00Tim

mers(199

8),Weilland

Vitale

(200

1)

Value

chainserviceprov

ider

(layer

player)

Onlysupp

ortpartsof

thevaluechain

such

aslogisticsor

paym

ents–bu

tforseveralcompanies

Banks,FedEx,

UPS

Tim

mers(199

8),G

assm

annetal.

(201

4)

Value-add

edreseller

Sellacomprehensive

rang

eof

undifferentiatedprod

uctsbasedon

value-addedservices,e.g.,throug

hconsultativ

eselling

,prod

uct

availability,

service,

and

prom

otionalpricing

Ingram

Entertainment,Pitm

anCom

pany

,Berkshire

Com

puter


0)

Vertical

portals(affinity

portals,

valid

ationthroug

hcommun

itycontent)

Createapo

rtal

that

specializes

ina

particular

area

andprov

ides

very

deep

contentand

functio

nalityin

this

area

Exp

edia,TripA

dvisor,RateB

eer

App

legate

(200

1),Clemon

s(200

9)


1750004-53

Appendix B. Objective and Subjective Ending Conditionsfor Taxonomy-Development

# Objective Condition (OC)

OC1 All objects have been examinedOC2 No objects were merged or split in the last iterationOC3 At least one object is classified under each characteristicOC4 No new dimensions or characteristics were added in the last iterationOC5 No dimensions or characteristics were merged or split in the last iterationOC6 Each dimension is uniqueOC7 Each characteristic is unique within its dimensionOC8 Each cell is unique and not repeated

# Subjective Condition (SC)

SC1 Concise: The taxonomy contains a limited number of dimensionsSC2 Robust: The dimensions and characteristics provide sufficient differentiation among objects

to be of interestSC3 Comprehensive: All objects can be classified and all dimensions of interest are identifiedSC4 Extendible: New dimensions and characteristics can easily be addedSC5 Explanatory: The dimensions and characteristics contain useful information about the

objects of interest

Source: Nickerson et al. (2013).

G. Remane et al.

1750004-54

Appendix C. Development of the Business Model Pattern Taxonomy

Source Pattern Dimensions

Prot

otyp

ical

patt

ern

Solu

tion

pat

tern

Pure

ly d

igit

al

Dig

ital

lyen

able

d

Not

nec

essa

rily

digi

tal

Phys

ical

Fina

ncia

l

Hum

an

Inte

llec

tual

pro

pert

y

Hyb

rid

Prod

uct t

ype

nots

peci

fied

Qua

lity

Cus

tom

izat

ion

Com

bina

tion

Acc

ess/

conv

enie

nce

Pric

e

Net

wor

k ef

fect

s

No

impa

cton

dif

fere

ntia

tio

n

Spec

ific

new

cus

tom

er s

egm

ent

Loc

k-in

exi

stin

g cu

stom

ers

Oth

er c

ompa

nies

(B

2B)

No

impa

cton

targ

etcu

stom

ers

Bra

nd a

nd m

arke

ting

Sale

s ch

anne

l

Sale

s m

odel

Cus

tom

er r

elat

ions

hip

man

agem

ent

No

impa

cton

del

iver

y pr

oces

s

Mak

e

Buy

No

impa

cton

sou

rcin

g

Supp

lier

s

Cus

tom

ers

Com

peti

tors

Mul

tipl

epa

rtie

s

No

impa

cton

thir

d pa

rtie

s in

volv

ed

Inno

vati

on

Supp

ly

Prod

ucti

on

Mul

tipl

est

eps

No

impa

cton

cre

atio

n pr

oces

s

Sell

Len

d

Inte

rmed

iate

Adv

erti

sing

No

impa

cton

rev

enue

mod

el

Prem

ium

Che

ap

Dyn

amic

Non

-tra

nspa

rent

No

impa

cton

pri

cing

str

ateg

y

Incr

ease

rev

enue

Red

uce

cost

Mul

tipl

e ef

fect

s

No

dire

ctpr

ofit

impa

ct

Solution provider X X X X X X X X X XRazors/blades X X X X X X X X X X X XDisintermediation X X X X X X X X X X X XFrom push-to-pull X X X X X X X X X X X X

2 [Physical] manufacturer X X X X X X X X X XContractor X X X X X X X X X XEntrepreneur X X X X X X X X X XFinancial broker X X X X X X X X X XFinancial landlord X X X X X X X X X XFinancial trader X X X X X X X X X XHR broker X X X X X X X X X XInfomediary X X X X X X X X X XInventor X X X X X X X X X XIP trader X X X X X X X X X XLicensing X X X X X X X X X XPhysical broker X X X X X X X X X XPhysical landlord X X X X X X X X X X[Physical] wholesaler X X X X X X X X X XIntegrator X X X X X X X X X XOrchestrator X X X X X X X X X XBrokerage X X X X X X X X X XEfficiency-based X X X X X X X X X X X XNetwork value X X X X X X X X X X X XPerceived value-based X X X X X X X X X X X X

3 Free X X X X X X X X X X X XMulti-sided platforms X X X X X X X X X X X XOpen business models X X X X X X X X X XThe long tail X X X X X X X X X XUnbundling X X X X X X X X X X X XAggregation X X X X X X X X X XAgora X X X X X X X X X X X XBreakthrough markets X X X X X X X X X X X XBuying club X X X X X X X X X XChannel maximization X X X X X X X X X X X XCool brands X X X X X X X X X XDe facto standard X X X X X X X X X XExclusive market-making X X X X X X X X X XExperience destination X X X X X X X X X X X XExperience selling X X X X X X X X X X X XIncomparable products X X X X X X X X X XLow-touch approach X X X X X X X X X XMass customization X X X X X X X X X X X XOne-stop convenient shopping X X X X X X X X X XOne-stop low-price shopping X X X X X X X X X X X XQuality selling X X X X X X X X X X X XReliable commodity operations X X X X X X X X X XService-wrapped commodity X X X X X X X X X XSupermarket X X X X X X X X X XTransaction service and exchangeintermediation

X X X X X X X X X X

Trusted product leadership X X X X X X X X X XUnder the umbrella pricing X X X X X X X X X X X XValue-added reseller X X X X X X X X X XAuction X X X X X X X X X X X XBricks + clicks X X X X X X X X X XBundle elements together X X X X X X X X X X X XDial down features X X X X X X X X X XDo more to address the job X X X X X X X X X X X XFreemium X X X X X X X X X X X XLeverage new influencers X X X X X X X X X X X XNegative operating cycle X X X X X X X X X X X XOwn the undesirable X X X X X X X X X X X XRent instead of buy X X X X X X X X X XReverse razors/blades X X X X X X X X X X X XServitization of products X X X X X X X X X XSubscription X X X X X X X X X XVirtual community X X X X X X X X X XAffinity clubs X X X X X X X X X X X XFractional ownership X X X X X X X X X XCrowdsourcing X X X X X X X X X X X XPay per use X X X X X X X X X X X XReverse auction X X X X X X X X X X X XAdvertising model X X X X X X X X X XCost leadership X X X X X X X X X XDisaggregated pricing X X X X X X X X X X X XFlexible pricing X X X X X X X X X X X XForced scarcity X X X X X X X X X XMembership X X X X X X X X X XMicro transactions X X X X X X X X X X X XPay what you want X X X X X X X X X X X XPremium X X X X X X X X X X X XRisk sharing X X X X X X X X X X X XScaled transactions X X X X X X X X X X

X X

XXX XX XX XX XX XX X

X XX XX XX XX XXXX XX XX X

X X

X XX X

X X

X X

X XXX

X X

X XX X

X X

X XX X

XX

X X

X X

XX

X X

X X

X X

X XXXX X

XX

X XX X

X XX X

X X

Inte

rati

on

D1:Hier. im-pact

D9: Value creation process

D3: Product type

D6: Value delivery process

D5: Targetcustomers

D7: Sourcing

D2: Degree of digiti-zation

D12:Direct profit effect

D11:Pricing strategy

D8: Third parties involved

D10:Revenue model

D4: Strategy for differentiation

1

Weill et al. (2005)

Andrew et al. (2006)

Chatterjee(2013)

Osterwalder and Pigneur(2010)

Linder and Cantrell (2000)

Johnson(2009)

Johnson(2010)

Tuff and Wunker (2010)


1750004-55

(Continued )


Prot

otyp

ical

patt

ern

Solu

tion

pat

tern

Pure

ly d

igit

al

Dig

ital

lyen

able

d

Not

nec

essa

rily

digi

tal

Phys

ical

Fina

ncia

l

Hum

an

Inte

llec

tual

pro

pert

y

Hyb

rid

Prod

uct t

ype

nots

peci

fied

Qua

lity

Cus

tom

izat

ion

Com

bina

tion

Acc

ess/

conv

enie

nce

Pric

e

Net

wor

k ef

fect

s

No

impa

cton

dif

fere

ntia

tio

n

Spec

ific

new

cus

tom

er s

egm

ent

Loc

k-in

exi

stin

g cu

stom

ers

Oth

er c

ompa

nies

(B

2B)

No

impa

cton

targ

etcu

stom

ers

Bra

nd a

nd m

arke

ting

Sale

s ch

anne

l

Sale

s m

odel

Cus

tom

er r

elat

ions

hip

man

agem

ent

No

impa

cton

del

iver

y pr

oces

s

Mak

e

Buy

No

impa

cton

sou

rcin

g

Supp

lier

s

Cus

tom

ers

Com

peti

tors

Mul

tipl

epa

rtie

s

No

impa

cton

thir

d pa

rtie

s in

volv

ed

Inno

vati

on

Supp

ly

Prod

ucti

on

Mul

tipl

est

eps

No

impa

cton

cre

atio

n pr

oces

s

Sell

Len

d

Inte

rmed

iate

Adv

erti

sing

No

impa

cton

rev

enue

mod

el

Prem

ium

Che

ap

Dyn

amic

Non

-tra

nspa

rent

No

impa

cton

pri

cing

str

ateg

y

Incr

ease

rev

enue

Red

uce

cost

Mul

tipl

e ef

fect

s

No

dire

ctpr

ofit

impa

ct

Add-on X X X X X X X X X X X XAffiliation X X X X X X X X X XAikido X X X X X X X X X X X XBarter X X X X X X X X X X X XCross selling X X X X X X X X X X X XCrowdfunding X X X X X X X X X X X XCustomer loyalty X X X X X X X X X X X XDigitization X X X X X X X X X XE-shop X X X X X X X X X X X XFlat-rate X X X X X X X X X XFranchising X X X X X X X X X XIngredient branding X X X X X X X X X XLeverage customer data X X X X X X X X X XLock-in X X X X X X X X X XMake more of it X X X X X X X X X X X XOpen source X X X X X X X X X XPeer-to-peer X X X X X X X X X XPerformance-based contracting X X X X X X X X XRevenue sharing X X X X X X X X X X X XReverse engineering X X X X X X X X X X X XReverse innovation X X X X X X X X X X X XRobin Hood X X X X X X X X X X X XSelf-service X X X X X X X X X X X XShop-in-shop X X X X X X X X X XTarget the poor X X X X X X X X X X X XTrash-to-cash X X X X X X X X X X X XUltimate luxury X X X X X X X X X X X XUser designed X X X X X X X X X X X XValue chain service provider X X X X X X X X X XWhite label X X X X X X X X X X

4 Collaboration platforms X X X X X X X X X X X XE-mall X X X X X X X X X X X XE-procurement X X X X X X X X X X X XOnline brokers X X X X X X X X X XValue chain integrator X X X X X X X X X XAgent models X X X X X X X X X XBanner advertising X X X X X X X X X XCost reduction [through the X X X X X X X X X X X XDealer support [through the X X X X X X X X X XInformation collection X X X X X X X X X XProduct sales X X X X X X X X X XSupplier support [through the internet]

X X X X X X X X X X X X

Business intelligence X X X X X X X X X XContent provider X X X X X X X X X X X XCustomer relationship management[through digital technologies]


Database marketing X X X X X X X X X X X XE-mail X X X X X X X X X X X XEnterprise resource planning X X X X X X X X X X X XHorizontal portals X X X X X X X X X X X XKnowledge management [through use of digital technologies]

X X X X X X X X X X

Online advertising and publicrelations


Online sales promotions X X X X X X X X X X X XSupply chain management X X X X X X X X X X X X

Tapscott et al. (2000)

Distributive networkX X X X X X X X X X X X

Shared infrastructure X X X X X X X X X X X XWhole-of enterprise X X X X X X X X X X[Digital] infrastructure retailers X X X X X X X X X X[Digital] service provider X X X X X X X X X X[IT] equipment/componentmanufacturers

X X X X X X X X X X

Advisors X X X X X X X X X X X XApplication service providers

X X X X X X X X X X

Connection X X X X X X X X X XCustom suppliers X X X X X X X X X X X XCustom suppliers of hardware X X X X X X X X X X X XCustom suppliers of software X X X X X X X X X X X XEducators X X X X X X X X X XE-retailer X X X X X X X X X XInfrastructure services firms X X X X X X X X X XSoftware firms X X X X X X X X X X X XVertical portals X X X X X X X X X X X XHaggle X X X X X X X X X XMerchant model X X X X X X X X X

X X

X X

X XX XX X

X XX X

X XX X

X X X

X X

X XX X

X XX XX X

X X

X XX X

XX

X X

X X

X XX XX X

X X

X X

XX

X XXXXX

X XXX X

Networked utility providers X X X X X X X X X X X X

Inte

rati

on

D1:Hier. im-pact


D3: Product type


D5: Targetcustomers

D7: Sourcing

Gassmann etal. (2014)

Applegate (2001)





D10:Revenue model


Timmers(1998)

Hanson(2000)

Strauss and Frost (2014)

Weill and Vitale (2001)

Bienstock etal. (2002)

G. Remane et al.

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(Continued )


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pro

pert

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rid

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ion

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n

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Rappa (2001) Audience measurement services X X X X X X X X X XBrand integrated content X X X X X X X X X X X XBuy/sell fulfillment X X X X X X X X X XClassifieds X X X X X X X X X XContent-targeted advertising X X X X X X X X X XDemand collection system X X X X X X X X X XMarketplace exchange X X X X X X X X X XOpen content X X X X X X X X X XQuery-based paid placement X X X X X X X X X XSearch agent X X X X X X X X X XTrust intermediary X X X X X X X X X XTrust services X X X X X X X X X X

5 Selling experience X X X X X X X X X XSelling online services X X X X X X X X X XSelling virtual accessories X X X X X X X X X XSocial search X X X X X X X X X XContextual mobile advertising X X X X X X X X X XMisdirection X X X X X X X X X XDigitally charged products X X X X X X X X X XPhysical freemium X X X X X X X X X X X XDigital add-on X X X X X X X X X X X XDigital lock-in X X X X X X X XObject self service X X X X X X X X X XProduct as point of sales X X X X X X X X X X X XRemote usage and condition monitoring

X X X X X X X X X X

Sensor as a service X X X X X X X X X XWirtz et al. (2010)

ContextX X X X X X X X X X

Iteration 1 4 2 2 3 3 3

X X

X XXXX XX XX X

X XX X

X XX XX X

X XX XX XX X

X XX X

X X

X X X XX X

X X

XX

X X

3 3 2 3 2

Inte

rati

on

D1:Hier. im-pact


D3: Product type


D5: Targetcustomers

D7: Sourcing





D10:Revenue model


Clemons (2009)

Fleisch et al. (2014)


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