A business model for the digital B2C/B2B platform. The development based on an ecosystem

Master's Thesis, 2020

140 Pages, Grade: 1.0






1.1 Problem definition
1.2 Objectives and research questions
1.3 Structure of the work

2.1 Digital transformation and its consequences
2.1.1 Transformation of value creation
2.1.2 Ecosystem as a guiding principle of digital strategies
2.1.3 Platform formations as a new digital development stage of business models
2.2 Ecosystem and digital platform
2.2.1 Definition of the term "ecosystem
2.2.2 Definition of the term "digital platform" and classification of digital platforms
2.2.4 Process models for the development of an ecosystem
2.3 Business model
2.3.1 Definition of the term "business model
2.3.2 Individual components of the business model
2.4 Success criteria of a digital platform
2.5 Answering the theoretical questions
2.5.1 Answering the question on modal goal 1
2.5.2 Answering the questions on modal goal

3.1 Initial situation in company AA and description of the problem
3.1.1 Determination of the success factors (field of investigation 1)
3.1.2 Initial situation with regard to the ecosystem structure (field of investigation 2)
3.1.3 Initial situation with regard to the creation of a business model (Field of investigation 2)
3.2 Research plan.
3.2.1 Research design
3.2.2 Methodical procedure for field of investigation 1
3.2.3 Methodical procedure for field of investigation 2

4.1. Determining the success factors as strategic guidelines for the creation of the business model for the digital platform
4.1.1. Meta Review
4.1.2. Group discussion
4.1.3. Display of results for field of examination 1
4.1.4 Interim Conclusion
4.2 Buildingby means of action research
4.2.1 Step 1 - Development of the problem solving concept
4.2.2 Stage 2 - Action planning
4.2.3 Level 3 - Action
4.2.4 Level 4 - Evaluation
4.2.5 Presentation of results for examination field 2
4.2.6. correctingempirical research questions.
4.2.7 Interim conclusion





Appendix 1 Contents of the CD-ROM

Annex 2: Success factors of digital platforms (from literature sources)

Annex 3 Innovation process at AA

Annex 4 Process diagram and innovation degree structure at AA

Appendix 5. risk list

Appendix 6: Ecosystem development concept for AA (March 2019)

Annex 7. drafts for ecosystem development from leads & cooperations and fields of activity

Appendix 8 Results of the text analysis: Identified text passages and used quotations

Appendix 9: Guided interview and group discussion on LinkedIn

Annex 10 Group discussion of the experts

Annex 11 Inductive coding of success factors from the group discussion

Annex 12 Summary of the success factors of the digital platform

Annex 13 Seminar "Ecosystems and Platforms

Annex 14 Seminar by AS

Annex 15 Seminar with the AH

Appendix 16. videoconference with the AH

Annex 17. concept of AT

Appendix 18 Example of a Persona Profile of AA

Appendix 19 3D Printing Business Unit

Appendix 20 Platform Canvas Sets



Augmented Reality

Business to Business

Business to Customer certification experts customer relationship management

Core Value Proposition

Germany, Austria and Switzerland

Research and development

Minimal Viable Environment

Minimal Viable Prototype

Original Equipment Manufacturer

Return of Investment

German: Technischer Überwachungsverein English: Technical Supervisory Association among others

Unique Selling Proposition (unique selling point) virtual reality


Table 1: The Playbook for Digital Transformation

Table 2. Platforms of the digital economy

Table 3 The Lewrick Ecosystem Design Process

Table 4. Success factors of the digital platforms

Table 5: Summary of the success factors of the digital platforms

Table 6: Business models for digital platforms

Table 7 Sample structure for the sample (test field 1)

Table 8: Persons involved in action research for the field of investigation

Table 9. Number of hits for specified keywords

Table 10 Identified articles for content analysis

Table 11 Results of the text analysis

Table 12: Supplementation of the success factors by the statements of the experts

Table 13: Assignment of the individual activities of the action research steps

Table 14. Plan for the development of an ecosystem at AA

Table 15. 3D Printing Ecosystem Areas

Table 16: Platform Idea Canvas 3.0 according to Walter with addition of owner field

Table 17. advantages and disadvantages, as well as strengths/weaknesses for different Actor groups

Table 18 Platform Value Canvas according to Walter

Table 19: Assignment of success factors to the canvas models

Table 20 Platform Governance Canvas according to Walter

Table 21 Platform Service Canvas according to Walter

Table 22 Network Effects Canvas according to Walter

Table 23 Platform Strategy Canvas according to Walter

Table 24 Platform Monetization Canvas according to Walter

Table 25 Platform Architecture Canvas according to Walter

Table 26 Platform Business Model Canvas according to Walter

Table 27: Results of the development of the canvas models of the Platform Innovation Kit


Figure 1 Structural structure of this work

Figure 2: Pipe- and platform-based business models

Figure 3 Value generation for a platform

Figure 4: The business models of the platforms from Internet marketplace to digital ecosystem

Figure 5. 4-step process model for the development of an ecosystem according to Ebner

Figure 6. 10-phase model for designing an ecosystem according to Lewrick

Figure 7. Idea management process at AA

Figure 8: Clustering of ideas to the business unit "3D Printing"

Figure 9: Identification of business areas from the idea management system of the Innova­management process at AA

Figure 10: Ecosystem expansion from leads & cooperation

Figure 11: Implementation of the process for building the digital platform at AA

Figure 12 Global Framework for Action Research Process according to Coghlan

Figure 13: Action research cycle according to Coghlan

Figure 14: General empirical method in action research projects according to Coghlan

Figure 15: Spiral of action research cycles according to Coghlan

Figure 16 Platform Innovation Kit according to Walter

Figure 17. Excerpt from the presentation of the seminar "Ecosystems and Platforms"

Figure 18: Ecosystem actors for 3D printing

Figure 19 Design-Test-Repeat Cycle Visual according to Osterwalder


The digital shift brings with it many changes, including high dynamics and the need to react, pressure on companies to innovate, new distribution channels and complex relationships with customers and partners. Companies are focusing their strategic orientation on digital structures, planning horizons and market boundaries are expanding, and ecosystems and platforms are being created as a result. Digital platforms are seen as the foundation of future value creation systems; they coordinate supply and demand in an ecosystem (partners, developers, customers, other stakeholders). A platform is built modularly to react quickly to market changes and to accelerate the development of new products and services based on the own ecosystem1. The creation of a digital platform is based on analysis and rethinking of the existing structures and finally results in an innovation of the business model. The creation of a data-centric digital platform requires two basic directions: building a digital ecosystem and establishing a business model (business model innovation). An emerging group that is taking advantage of the concept of platforms is referred to as Industry 4.01 2.

1.1. Problem

This work results from the need of the AA company, which is mainly active in the B2B sector, to build a digital platform. The task is complicated by the fact that B2C platforms (including Airbnb, AppStore, Playstore) have already established themselves on the market, while B2B platforms have yet to find their way. In the literature, there are some approaches for building ecosystems and platforms that are comparatively new and whose practical approach needs to be reviewed. There is an initial approach for the 4-step procedure model of Ebner3 for the development of an ecosystem, which has already been developed as a concept for the company AA. The results of the concept investigation are to be taken from chapter 3.1.1. As one of the problems it was identified that a top-down process for the development of the ecosystem for the company AA was not practically realizable. Lewrick4 considers ecosystem building as a further development of digital decentralized value creation based on the combination of design thinking and system thinking. This approach is the preferred one for this work.

In addition, the instruments for developing a business model for digital platforms are to be put to the test. The value creation process to be depicted is no longer linear, but must have an ecosystem­based network structure. Linear business models (e.g. canvas models by Osterwalder1 and Schallmo5 6 ) do not depict the value creation in ecosystems and multi-faceted digital markets. Hoff- meister7 is of the opinion that digital business models can be regarded as control loop fractals (recurring structures). They form a complex structure and can be described with the three control loops input, output and processing8. In this way, an interactive and multi-sided digitized business model pattern is to be created, which can be mapped over several levels. The system should allow to keep growth and quality constantly in view, whereby specific requirements for the B2B sector must be considered: Governance mechanisms, robustness, scalability, data protection guidelines, decision on the degree of openness, inhomogeneous system landscape, checking the compatibility of applications and services, consulting and adaptation to communication standards, intellectual property and competitive advantage9.

1.2. Objectives and research questions

This thesis deals with the development of a suitable business model for a digital platform in the AA company. For this purpose, a suitable process model with appropriate instruments for the development of an ecosystem-based platform must be found. In relation to the given goal the central question of this thesis can be derived:

What is the process for building a successful business model for a digital platform?

In order to achieve the primary research objective, the following modal objectives must be achieved:

- Determination of success factors as strategic guidelines for the business model of the digital platform (in progress: modal g
- Development of the process model for the development of the ecosystem and creation of a business model for the platform (further in work: modal g

For the realization of modal goal 1, the following question was formulated.

Theoretical question:

- Which success factors for digital platforms must be considered from a strategic perspective for business model development?

Empirical research question:

- Which success factors for digital platforms must be considered from a strategic perspective for business model development?

The following questions must be asked in order to implement modal goal 2.

Theory related questions:

1. Which process models and tools are available for the development of the ecosystem?
2. What business models can digital platforms represent?

Empirical research questions:

3. How can an ecosystem be developed specifically at AA?
4. How can a business model for the digital platform be created at AA?

The modal targets are assigned to the investigation fields of the same name: Modal goal 1 to study field 1; modal goal 2 to study field 2. The research methodology is discussed in chapter 3.2. Another objective of this thesis is to show an optimal way how other companies can methodically develop the business model for a platform.

Building a platform is an extensive process, which cannot be completely accomplished in this thesis. For this reason, the focus will be on the process of building the ecosystem and based on this a basis for a future platform will be developed. The development steps of strategic directions like Blue Ocean and Black Ocean will not be discussed. There will be no further development of platforms with regard to the integration of the processes of all actors. The further development of the platform is to concentrate on the illustration of the business processes of the participants, in order to obtain an optimal saving of time for all users of the platform. This is achieved by a separate interface for a client software, which is not developed in this thesis.

The research topic is of practical relevance with regard to the project of the AA company and the coordination of business relations with the partner companies (platform use). The results of this work are important because they directly contribute to the competitive position of the company and have an impact on the future development of the company. This work should also lead to a learning cycle with continuous improvement of the ecosystem and platform business models, because from a scientific point of view, the change in the value creation process through digital ecosystems is a challenge1.

1.3 Structure of the work

This work consists of seven chapters. After an introduction regarding the problem definition, explanation of the objective and the position of the research questions for both fields of investigation in chapter 1, the theoretical foundations for digital transformation and the environmental conditions required for platform formations are provided in chapter 2 in order to achieve the research objective. Subsequently, the technical terms "digital platform", "digital ecosystem" and "business model" are explained, and various classifications of digital platforms are outlined. Individual components of the business model are discussed and an overview of various success criteria for the digital platforms is given. At the end of chapter 2, the theoretical questions regarding the modal goals are answered. In Chapter 3, the starting position for the empirical investigation is recorded and the research plan for two fields of investigation is presented. Chapter 4 deals with the implementation of the research project. The success factors for digital platforms in research area 1 are deductively verified by means of a meta-review and supplemented by inductive findings. In order to expand the state of knowledge, a further data collection will be carried out by means of group interviews. The identified success factors will be combined and transferred to a business model for the platform, which will be created in the context of investigation field 2. Within investigation field 2 an action research is carried out, which describes the stages of the development of an ecosystem and creates the business model based on the findings of investigation field 1. The results are summarized in chap­ter 5, compared with the answers to the theoretical questions (see chapter 2.5), and extended by the new findings. The main research question is answered. Subsequently, the results are discussed in chapter 6 and suggestions and recommendations for further research are provided. In a final review, Chapter 7 summarizes this work and provides future directions of development of the re­search topic. The structure of this work is shown graphically in Figure 1.

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Figure 1. structural structure of this thesis. Own representation.


2.1 Digital transformation and its consequences

The digital transformation can be understood as a new transformational effect of information and communication technology, which stands for the current fundamental change in economy and society1. It is a symbol of all social, political, economic and ecological upheavals resulting from the predominance of digitization and networking10 11. The digital transformation opens up new opportunities for companies, as new distribution horizons (new distribution channels and new distribution markets) and new directions (e.g. open innovation and co-creation) are made possible. As a result of the influences of digitization, the boundaries between material products with digital properties are merging, and complementary digital services are becoming an inseparable part of the product. Influenced by the intensity of global competition, software elements are no longer products in themselves1, they are only the drivers to enable the efficiency of social and business interactions. As a result, business models for the platforms are emerging that deliver a different kind of value creation and competitive advantages.

2.1.1 Transformation of value creation

Information technologies have led to information being used as an independent competitive factor (information leadership)12 13.14 The added value of electronic value creation based on this is generated by the aspects exchange (communication path), overview (structuring path), cooperation (coordi­nation path), selection (selection value), mediation (matching value), processing (transaction value). The digital transformation requires a change and reshaping of the five strategy domains: customers, competition, data, innovation and15 value creation. This results in the new framework conditions (see Table 1), which require new strategic decisions.

Table 1: The playbook for the digital transformation. Elaboration by Rogers 16

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The key performance indicators such as cash flow and ROI, which play an important role in a linear value chain, are becoming less important for digital platforms1. In the case of digital platforms, the focus is on generating positive network effects and activities on the platform, where value is created through efficient (core) interactions17 18. The platform-based business model not only maps the value flow from producers to consumers, but all users of the platform generate value in an ecosystem (see Figure 2). Unlike traditional pipeline companies, the value creation is not under the control of the platform19 20.

A platform accesses its own, (temporarily) shared or external resources. The value results mainly from the connection of resources and network effects among each other.21 The challenge is to set up a platform so that all resources are connected in such a way that they can generate value for each other (see figure 3).

Under the influence of digital change, the individual competitors are often seen as complementary cooperation partners in terms of value creation. Strategic alliances and cooperations accelerate the growth of their own ecosystems.

2.1.2 Ecosystem as a guiding principle of digital strategies

As a result of rapid development of new technologies, the market situation changes rapidly, product and technology life cycles are shortened, and pressure to innovate arises22 23. As a result of global networking, opportunities arise for companies with relatively low capital volumes and know-how deficits in a particular innovation field to form cooperations and mergers in order to face the changed competitive conditions24. An ecosystem represents a high level of further development of business relations, which is a basis for the development of innovation potential. This system represents a multidimensional representation of the network structures with role changes of the different actors. A platform enables numerous constellations between the actors, acts beyond geographical and informational borders. As the platform business models evolve, the linear value chain of internal resources that create value and pass it on to the customer finds its evolution in an ecosystem. In these times of platform growth, an ecosystem is a new supply chain25. The ecosystem contains its own pool of resources and creates value through the collaboration of the different ac­tors. The loss of control over resources becomes the main competitive advantage1. An ecosystem is therefore the value-creating driver of the digital platform.

2.1.3 Platform formations as a new digital development stage of business models

Digitalization enables significant time savings in reaching special offers for customers. However, interactions not only create the basis for the submission of cost-effective personalized offers, but also a channel for creativity and entertainment, a foundation for data collection and binding of the data generated by interactions. The economic use of information in the areas of product offerings around the clock, information supply, information demand, information exchange and information processing promotes the development of new digital and semi-digital business models that com­bine the interaction of the three components information, transaction and communication26 27. The diverse digital possibilities enable the development of innovative business processes and models, which inevitably lead to their further development into platform concepts. Platforms28 are to be re­garded as the central link between digital data and innovative business models. They enable a much broader spectrum than a pure distribution channel, they serve as a communication and data exchange channel, as a basis for the transfer of economic services29. Platform business models are increasingly developing their dynamics through networking (see Figure 4).

Figure 4: The business models of the platforms from Internet marketplace to digital ecosystem. Elaboration by Eco­dynamics GmbH1.

Figure 4 in English: Intelligence (Networks, Data relevance)

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The actors of the digital platform form a digital ecosystem, which evolves through constant ex­changes and interactions between the actors, thus evolving the ecosystem and the platform30 31. The new opportunities offered to the platform users will attract new users and thus contribute to the growth and development of the platform and its ecosystem32. Thus, the preservation of their eco­system through a continuous improvement in the quality and increase in the number of interactions is considered an existential goal of platforms.

2.2 Ecosystem and digital platform

The dynamics of the environment and the convergence of products and services from different competitors to each other require companies to take strategic positions in different ways. A strategy is not only a distant vision, but a specific profile of the activities of a company that differentiate it from its competitors.33 The enterprises are concerned with the development of own ecosystems and transform thereby the creation of value (Blue Ocean and Black Ocean strategies) and construct as differentiated business models as possible, which supply a special value for their customers. This way of thinking is future-oriented, because in the future competition will not take place between products and processes, but between business models. 1In order to enable sustainable success generation, models are needed that can depict structural complexity and interrelationships. Accord­ing to an estimate by Ecodynamics GmbH, the market value of the world's 60 largest platforms has increased34 35 by one trillion US dollars in the first half of 2018. Digital platforms are gaining market share and connecting more users together, and the growth of the ecosystem can be seen as a viable strategy for digital platforms.

2.2.1 Definition of the term "ecosystem”

The term "ecosystem” originates from biology and describes a model of the interactions between living beings and their habitat in a freely selectable section of the biosphere, thus forming a self­regulating system of effects whose structure is in dynamic equilibrium36. With regard to digital plat­forms, we are talking about digital ecosystems that connect different partners with each other and thus provide value for the platform, the addition of new partners maintains the value and is not associated with additional costs. According to Masak,37 a digital ecosystem is a loosely coupled, demand-driven, collaborative environment in which all participants actively operate for their own benefit and profit. In38 Jakob's view, Engelhardt's study39 essentially encompasses the definition that the dynamic and collaborative discovery, aggregation and analysis of all available data and the access to a common digital platform constitute a digital ecosystem. A data-based overall system is created by the platform, and when linked to this system of complementary products (hardware, software, data and/or services) an ecosystem40 41 is created. A platform driven ecosystem can be defined as a group of organizations that are owned by the same owner or strategically linked and 8that derive significant value from at least one of the platform businesses. Further definitions focus the business informatics view. According to Ammon,42 digital ecosystems represent the habitat of digital content by forming a technically delimited system that networks different types of hardware, software, content and services. A digital ecosystem is an environment consisting of hardware and software in which products and services complement each other optimally and media disruptions are avoided1. This thesis refers to the definition of the ecosystem as a group of actors with varying degrees of multilateral, non-generic complementarities that are not fully hierarchically controlled.43 44 At this point it is important to discuss similarities and differences between ecosystem and network. When many different partners are involved and cooperation is not very formal, we speak45 of net­works. A sharply defined and uniform concept of networks is not found in the literature, although nowadays the importance of networks is increasing in all areas. A large part of general character­istics is covered by Sydow's definition46, in which networks represent an alternative, rather hybrid or even independent form of coordination of economic activities in a hierarchically coordinated organ­ization. Common characteristics of networks include the following: at least three cooperation part­ners, voluntary cooperation, project-related coordination. In principle, both the networks them­selves and their parts are free in the type and scope of their organization and can adapt to any market situation47. The main objectives of the network are: Increase of internal efficiency, increase of effectiveness and customer benefit and development of new business potentials48. The listed functions apply to a network as well as to an ecosystem, but there are also differences. In this context Eckert49 points out the differences described below. When setting up a network, the network partners are selected on the basis of their competence base for the development and manufacture of a product, whereas for the ecosystem the network partners are selected on the basis of the potential benefits that can be offered to the users of the platform in a complementary way. In a network, the manufacturer of the product or the coordinator of the service keeps the customer contact, in an ecosystem each individual provider can keep his own contacts. In a network, the company itself controls the core competencies and companies compete with each other via prod­ucts and services. In an ecosystem, the company ties the relevant core competencies to itself and companies compete with other ecosystems as part of a (platform) ecosystem.

2.2.2 Definition of the term "digital platform" and classification of digital platforms

Baums1 considers digital platforms as products, services or technologies that serve as a basis for a variety of companies to offer complementary products, services and technologies. A digital plat­form links several different groups of players in the market, each group benefits from another and cannot interact efficiently without the platform50 51. Matyssek52 believes that platforms are the systems on the basis of which other providers can offer their own solutions. Common to all definitions is that platforms are made up of various interacting and combinable modules that deliver unique value to different user groups. Digital platforms are internet-based forums for digital interaction and trans- action53. They are the hub of an ecosystem of partners, developers, customers and other stakehold­ers, creating a two-way market by coordinating supply and demand from one platform54. TME Re­search identifies closed and open platforms55. In a closed platform the operator or service provider prevents convenient access to unauthorized applications or content (e.g. Apple). An open platform provides API interfaces between applications and modules, gradually connecting new companies. Baums, on the other hand, notes that56 semi-open platforms will find their way. A further classifica­tion is found with Evans57, the platforms are divided into transaction platforms, innovation platforms, integration platforms and investment platforms. The classification of the platforms according to Kollmann58 59 refers to the thrust directions, which define the fields of activity (see table 2), which are defined however not overlap-free.

Table 2. platforms of the digital economy. Own compilation according to Kollmann 10

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In his study, von Engelhardt1 divides digital platforms, which are mostly used in the B2B sector, into two categories: transaction-centric anddata-centric. The transaction-centered platform focuses on its mediation function as a digital marketplace for bringing together supply and demand. The data-centered platform focuses on networking with the aim of linking complementary products (hardware, software, data and/or services) into a digital ecosystem. In doing so, it also identifies hybrid platforms that combine both categories. This work focuses on data-centric platforms, which primarily target the B2B sector, but do not exclude B2C sector.

2.2.4 Process models for the development of an ecosystem

In the literature an initial approach to the 4-step process model of Ebner60 61 62 is found (see figure 5).

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Figure 5 in English:

Lewrick1 sees the building of the ecosystem as a further development of digital decentralized value creation based on the combination of design thinking and system thinking. Ecosystem building is based on 3 levels of matrices: focused partner networks, centered business network and decentralized ecosystem63 64 65 66 67. The process model consists of 10 steps, which are structured cyclically (see figure 6).

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2.3 Business model

A business model can be interpreted in different ways. Following Massa1 et al., Hass68 69 develops the following research areas of business model interpretation: business model as an empirical phe­nomenon (research on existing business models in concrete companies and identification of cross­company business model patterns), business model as a cognitive schema (implicit mental model as a pattern of thought of managers in order to make entrepreneurial decisions), and business model as a formal model (abstraction and simplification of explicitly and implicitly existing business models in order to be able to formally represent them). The last field of research makes central decision fields and decision contexts of companies visible in order to interpret and analyze them in detail70. The thesis deals with the research area business model as a formal model for digital plat­forms, which is underrepresented in the technical literature and is still in an explorative research stage.

2.3.1 Definition of the term "business model”

The construct "business model" is defined in various ways in the literature. According to Müller- Stewens,71 a business model is a design of networked activities that aims to realize a certain value proposition. According to Kuckertz72, a business model describes the interaction of essential com­ponents of a company to generate value. Wirtz2 understands a business model to be a highly sim­plified and aggregated mapping of the flowing resources into the company and their transformation through the internal service creation process into marketable information, products and/or services. In Osterwalder's view3, a business model is a template for a strategy to be implemented through organizational structures, processes and systems. It describes the basic principle according to which an organization creates, communicates and captures values.4 Schallmo5 defines the busi­ness model as the basic logic of a company, which describes which benefits are generated in which way for customers and partners. According to Rusnjak,6 a business model describes in an ab­stracted way a selection of products and services relevant for consideration as well as the tools necessary for the provision of services and the associated information, transfer and financial flows along the value chain(s) of a company. According to Möller,7 the business model provides a frame­work for the presentation and analysis of a company's performance drivers. A digital business model is a framework structure of input, processing and output systems that enables8 scalability of the business in three dimensions (demand, performance, transaction flows) in a digital way. Jaekel9 regards the business model as a structural abstraction that approximates the real organization of a company.

All definitions are to be inferred as common aspect that the business model architecture consists of different cooperating and among themselves combinable components and the realization over the ways for the achievement of financial success supplies10. In this work the business model is examined in the function as analysis tool.

2.3.2 Individual components of the business model

The business model orientation requires the development of a new perspective73. The focus is on the interaction of the individual components (dimensions) of the business model, which are set up differently by different authors12. Gassmann13 defines the business model through who-what-how- value dimensions. Osterwalder1 believes that the business model can be described with nine com­ponents: Customer segments, value proposition, channels, customer relationships, revenue sources, key resources, key activities, key partnerships, cost structure. Rusnjak74 75 identifies as the most important elements of a business model: involved actors (e.g. customers, suppliers, cooperation partners, competitors, etc.) and their goals/motivation, the company's performance/benefit proposition, sales channels, key resources and key activities, relevant costs and revenues as well as success factors and the presentation of relevant strategies. Müller-Stewens76 identifies five dimensions of the business model: value proposition, design of ac­tivities, control of activities, central resources and revenue mechanics. Schallmo77 sees the business model as a construct of five dimensions and thirteen elements: Benefit dimension (services, bene­fits), financial dimension (costs, revenue), value creation dimension (capabilities, resources, pro­cesses), partner dimension (partners, partner channels, partner relationship), customer dimension (customer segments, customer channels, customer relationship).

The analysis of the success factors of the individual business models in different industries con­ducted by Wirtz78 clearly shows that successful business models differ in terms of pronounced econ­omies of scale and network effects. The greatest scalability level and unfolding of the network ef­fects relates to platform business models, which differentiate themselves from linear business mod­els through a multidimensional mapping of the value-added process.

Pöppelbuß79 develops "Smart Service Canvas", which is an extension of Osterwalder's business model The framework comprises four areas: the customer view, the value creation view, the eco­system view and the fit of all views. Based on Osterwalder's Value Proposition Canvas, the cus­tomer view includes80 the additional components context of customer tasks, context things and data; the value proposition view is slightly adapted to Smart Service and complemented by analytical capabilities and data. The ecosystem view describes the technical infrastructure and the digital platform. The fit from the customer and value creation view is explained on three levels: Revenue model, interaction level and Smart Product. 81 Hoffmeister's digital business model consists of these elements: Principals, agents, services, software agents, bonuses, complementors, directions, transactions, business model partners and networks. Hebestreit1 elaborates an ecosystem busi­ness model that identifies four target values (goals, standards, aesthetics, abilities & hurdles) from the perspective of the behavioral psychology of the customer group based on the EmotionalCom- merce© system and transfers them to Osterwalder's Canvas business model.

Bernhard2 bases his study on the components of a platform business model: technologies and data, participants, interactions between participants, value generation and exchange, brand. The interactions within platform business models between the participants of the platform are divided into four types 3: data exchange (collection of data on user behavior to improve the customer ex­perience), products/services (co-creation in product development using several means, such as fan contests), currency/money (exchange of money and other currencies), social currency (intan­gible assets: fame, attention, influence, reputation).

Platform business models are increasingly seen in the literature as continuously repeated process models. Peneva4 is setting up a Platform Design Toolkit, which, starting from the ecosystem can­vas, is increasingly evolving into an experience learning process and increasing in complexity. Wal­ter5 compiles a Platform Innovation Kit for the constant business model development.

2.4 Success criteria of a digital platform

Related to the division of the B2B platforms into data-centered and transaction-centered, von Engelhardt developed6 the success criteria of the digital platforms (see table 4.)

Table 4: Success factors of the digital platforms. Own composition leaning against von Engelhardt 7

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As a result, the establishment of a broad-based ecosystem is one of the strategic guidelines for the development of a digital platform. The success of a digital platform depends crucially on the estab­lishment of the ecosystem; therefore, this is used as a suitable evaluation benchmark. This thesis is dedicated to the investigation of the procedure concept for the establishment of the ecosystem within the framework of investigation field 1.

The success of an ecosystem is based on the factors1 speed, partner selection and development in close customer dialogue. This suggests a cyclical approach, whereby the existing business model is inevitably developed further by the step to the digital ecosystem. The analysis of the environment and trend developments lead to adjustments of old business processes, definition of new market structures and the development of new business models. This business model innovation has to take place in a constant and close customer dialogue82 83. As can be seen from platform developments in the B2B sector84, industrial companies are deliberately planning future business model extensions for their core business models and researching innovation directions.

In order to promote high levels of valuable key interactions, the decisive factors must be met: Pull effect, Simple transaction/interaction and Matching85 . Von Engelhardt86 sees the most important strategic success factors of digital platforms: Services and players, sales and revenue concept, openness, (in)dependence and dynamic strategy. The success criteria identified in the study by Sopra Steria Consulting87 relate to service orientation, scalability, data-driven organization, agility and openness. Von Engelhardt88 counts simplification of transactions, network effects, scalability, expectations of the participants among the characteristics of the digital platform markets. These characteristics can be translated into strategically relevant key factors1. From the identified factors2, von Engelhardt derives the building blocks for business model mapping: Players, Right to exist, price strategy, quality assurance, (in)dependence, dynamic strategy 3.

2.5. Answering the theoretical questions

With reference to the theoretical approaches discussed in Chapter 2, the following conclusion can be drawn to answer the questions based on the literature.

2.5.1. Answering the question about modal goal 1

Theoretical question on the modal goal 1:

- Which success factors for digital platforms must be considered from a strategic perspective for business model development?

The success factors identified in principle for all digital platforms are listed in Table 5 and supplemented with the characteristics. The complete table with quotations as anchor examples is in Appendix 2.

Table 5: Summary of the success factors for digital platforms. Own composition after Engelhardt 4 , Parker 5 and Oberle 6 .

Abbildung in dieser Leseprobe nicht enthalten

Table 5: Summary of the success factors for digital platforms. (continued).

Abbildung in dieser Leseprobe nicht enthalten

According to Engelhardt89 90 91 92, the characteristics of digital platform markets include simplification of transactions, attractiveness of the platform (indirect network effects), scalability, platform dynamics through winner-takes-it-all markets, expectations of the participants (platform attractiveness). 4These characteristics can be translated into strategically relevant key factors, whereby a dynamic strategy is considered a success factor across all components.

The following factors are primarily relevant for the development of a successful system for data- centric platforms (see Table 4):

1. Usability of the overall system
2. Establishment of a broad-based ecosystem
3. Certification of components
4. Data preparation - and evaluation
5. Quality assurance by meeting technical requirements and quality standards
6. Price strategy: group differentiated and asymmetric price structure
7. Integration of the system component and its supplier before market entry
8. Formation of strategic partnerships before market entry
9. Openness of the platform (no technological lock-in)

The factors marked in italics correspond to the success factors identified in Table 5, which apply to all digital platforms. The others consciously refer to data-centric platforms and state that a functioning ecosystem with stable architecture must exist before market entry.

2.5.2. Answering the questions about modal goal 2

Theoretical question on modal goal 2:

- Which process models and tools are available for the development of the ecosystem?

In the literature, an initial approach to Ebner's 4-step process model1 can be found, but it is more oriented towards B2C platforms and the financial sector, which raises the question of the extent to which this model is also suitable for building a B2B platform.93 94 Ebner's approach is also general and focuses on the structure of the ecosystem and emphasizes the importance of customer dialogue. Lewrick's approach, on95 the other hand, focuses on the customer value and the component of the business model. The limits of the approach cannot be determined from a theoretical point of view, they are checked in the practical approach (see chapter 4.2.)

For the implementation of modal goal 2 the following theoretical question has to be answered:

- What business models can digital platforms represent?

The linear business models of Osterwalder1 , Schallmo2 and Gassmann3 cannot completely map the business model of a digital platform.4Osterwalder's canvas model can serve as a basis for mapping different groups of actors, but it has to be supplemented for the project, because digital elements are missing and network systems are not considered.5Schallmo's model focuses more on the partner perspective, but it is still not sufficient to map the entire ecosystem. The Smart Ser­vices Canvas could6 provide an important supplement by a detailed consideration of the business analytics to address the digital aspect of the project. When looking at the above mentioned con­structs, it becomes clear that linear business models cannot map a platform. An analysis tool has to map a scalable business model that can represent both the platform role as an intermediary and other players in the two-way market. It must be taken into account that with B2B platforms the added value should not only be delivered to the business customers but also to the customers of the business customers. For this reason, it is advisable to create a separate canvas for each B2B relationship, since different stakeholders on the customer side7must be considered. In this context, a multi-level construct should be applied. For each stakeholder group, the respective business model should contribute to the core value proposition and the sum of the value propositions should result in the defined core value proposition8. The business models for the platforms and ecosys­tems that represent development stages of the business models for the digital platforms are listed in Table 6. This shows that the individual business models are combined into toolkits to map digital platforms.96

Table 6: Business models for digital platforms. Own elaboration.

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Table 6: Business models for digital platforms. (continued)

Abbildung in dieser Leseprobe nicht enthalten


In this chapter, the general starting position at the AA company is examined and the research design for two fields of investigation is presented. In the following chapter 4 an empirical investiga­tion of the modal objectives is carried out, followed by the evaluation of the empirical results and a comparison of the theoretical basis of the data of the empirical investigation discussed in chapter 2. The logical conclusions based on literature and empiricism from the two fields of investigation are to be linked to answer the main research question of the thesis.97

3.1 Initial situation in company AA and description of the problem

One of the reasons for the difficult entry of B2B platforms is the merging of physical products with services. Consequently, a new customer benefit-oriented service package must be created. Other reasons result from rethinking not only business models but also the complete management of supply chains. The existing supply chains are changing into complex ecosystems due to the influences of the digital world. As a result, existing industry structures are being replaced and companies in the B2B sector have to reorient themselves, as is clearly shown by the example of the AA company. In recent years, AA has been offering a noticeable increase in services in the areas of planning, engineering, energy optimization, procurement and logistics, and has entered into cooperation agreements. The positive personal support and purchase experience generate added value for the customer, which justifies a price difference. It should also be noted that the degree of digitization is not yet well developed, which keeps possible price wars resulting from digitization at bay. Nevertheless, it is noticeable that non-digital market structures are no longer viable and that a new digital market area must be created that has its own characteristics and laws. In order to cope with the digital change, a digital department was set up in the company and a restructuring was carried out. The company's business areas are to be further developed digitally and an innovation process initiated since January 2019 is to lead to innovations (see Annex 3). The increasing importance of digital platforms and ecosystems was recognized by the AA as a new opportunity to position itself for the future. An idea management process has been in place since March 2019 (see Figure 7).

Figure7 (English translation):

Abbildung in dieser Leseprobe nicht enthalten

The ideas are regularly clustered into business areas (see Figure 8) and further developed into development concepts. It quickly became apparent that for each business area, such as "3D printing", the business model could be expanded to such an extent that it could take on platform­based features.

Abbildung in dieser Leseprobe nicht enthalten

Figure 8: Clustering of ideas to the 3D Printing business unit. In-house development.

For structural reasons, there was little communication between the three departments of the AA until 2019, so horizontal structures had to be created. As a result of the reorganization, the over­arching structures were formed, consisting of representatives of the various departments and de­fining fields of activity for the process (see Appendix 4). As a result of the cooperation it was found that in the AA company the business areas were partly not defined or partly the same business areas were developed by different departments. It was found that the innovation management pro­cess, which was originally intended to be an isolated innovation pipeline, provided a starting point for a number of changes in the core business. The installed idea management process according to Geschka98 revealed the previously undefined business areas and possible fields of innovation that could provide a basis for ecosystem expansion (see Figure 9).

Abbildung in dieser Leseprobe nicht enthalten

Figure 9 (English translation):

Abbildung in dieser Leseprobe nicht enthalten

3.1.1 Determination of the success factors (field of investigation 1)

In the AA company,1 von Engelhardt's success factors were used in individual discussions and documentation. No other factors have been researched so far.

3.1.2 Initial situation with regard to the ecosystem structure (field of investigation 2)

The AA company is facing the challenge of building a digital platform. In March 2019 a concept was developed for the AA company based on Ebner's99 100 concept. The process of concept development can be found in Appendix 5. Since the process model is strategically structured and general, it was difficult to identify in the top-down process which direction had to be pursued with which methodol­ogy. It was found that a network of partners already existed, but the methodology for data collection and a visualization tool were missing. The expansion phase was not fully completed. Since no definitive decision was made on what type of platform to build, the goal was to implement and graphically represent a general system with ecosystem modules of contacts and leads from the Salesforce database (see Figure 10, the description of the approach is in Appendix 6).

This approach turned out to be not very target-oriented, as the current choice of partners is very close to the core business and requires a conscious selection and expansion of the ecosystem. Although other possible partners are recommended by existing partners, concepts as a possible basis for partnership are often lacking, especially when digital services are involved. An even greater challenge was the selection of possible joint offerings based on the potential strategic part­ners. As a result, it was decided to add additional categories to the Salesforce database to map partner relationships until an appropriate ecosystem approach was established.

Based on the described situation, a research process was started, which will be carried out within the framework of investigation field 1.

3.1.3. Initial situation with regard to the creation of a business model (Field of investigation 2)

At the beginning of 2019, the following data-centric platform types, among others, were considered at AA: e-commerce platform (setting up online stores for B2B customers), supply-demand platform, technology-based platform (application of AR and VR technology), e-learning platform. The platform should serve both the B2C and the B2B sector. As this is a long-term high-risk project, a risk list was drawn up based on key factors of successful platforms 1and the specific requirements for the B2B sector101 102 (see Annex 7). The risks were assessed and each of the risks was assigned a level of severity in terms of different platform types. Based on the evaluation of the risks and com­pany-specific analyses, it was decided to build a data-centric platform for the region for which an ecosystem installation concept must be developed. Due to the strong regional presence of the AA company, the focus was placed in advance on the development of the ecosystem, which should serve as a guideline for the future platform.

3.2 Research plan

Starting from the task to find a suitable process model with suitable instruments for the development of the ecosystem-based platform, the research is divided into two fields of investigation, for which different methodologies are applied. For field of investigation 1, additional insights into the success factors for digital platforms will be gained by means of meta-reviews and group discussions. Field of investigation 2 is a development process consisting of several stages, which will be carried out continuously. For this purpose, an action research method is applied, the first stage is worked out and a process for the next stages is installed. The first stage ends with the creation of a business model, which also incorporates the new findings from investigation field 1. The methodology is described in detail in chapters 3.2.1 and 3.2.2. The process structure, related to the fields of inves­tigation, is shown in Figure 11.


1 Cf. Hein at al. (2019), p.182

2 Hein at al. (2019), S.182

3 Ebner (2018), p.2, https://tme-ag.de/whitepaper/vorgehensmodell-zum-aufbau-eines-digitalen-oekosystems/, retrieval from 18.11.2019

4 Cf. Lewrick (2018), p.89

5 Osterwalder et al. (2011)

6 Schallmo (2013)

7 Cf. Hoffmeister (2015), p.30 ff

8 Cf. Hoffmeister (2015), p.30 ff

9 Cf. from Engelhardt et al. (2017)

10 Cf. Lemke et al. (2017), p.193

11 Cf. Lemke et al. (2017), p.193

12 Cf. Choudary (2015), p.18

13 Cf. Kollmann (2019), p.57

14 See Kollmann (2019), p.59

15 Rogers (2017), p.18

16 Rogers (2017), p.24

17 See Jaekel (2017), p.113

18 See Jaekel (2017), p.113

19 Parker et al. (2017), p.56

20 Senser (2017), https://entwickler.de/leseproben/apis-als-turbo-der-digitalisierung-579812075.html, retrieval from 18.11.2019

21 Gartner, Inc. https://www.gartner.com/imagesrv/cio/pdf/cio_agenda_insights_2016.pdf, p.2. Retrieval of November 18, 2019.

22 Gartner, Inc. https://www.gartner.com/imagesrv/cio/pdf/cio_agenda_insights_2016.pdf, p.2. Retrieval of November 18, 2019.

23 Petersen (2017), S. 5

24 See Petersen (2017), p. 5

25 See Choudary (2015), p.37

26 See Choudary (2015), p.36

27 Cf. Kollmann (2019), p.64

28 Cf. Moser et al. (2019), p.100

29 Cf. Moser et al. (2019), p.100

30 Hosseini (2019), https://www.profil.bayern/07-2019/topthema/wer-frueh-beginnt-hat-bessere-chancen/, retrieval from 18.11.2019

31 Cf. Moser et al. (2019), p.100

32 Cf. Moser et al. (2019), p.100

33 See Porter (2014), p.14

34 Cf. Gassmann et al. (2017), p.5

35 Schmidt, https://www.netzoekonom.de/2018/06/24/wert-der-plattform-oekonomie-steigt-im-ersten-halbjahr-um-1-billion-dol- lar/, retrieval of 18.11.2019

36 Cf. Lexicon of Geosciences (2000), https://www.spektrum.de/lexikon/geowissenschaften/oekosystem/11525, retrieved from 18.11.2019

37 See Masak (2009), p.186

38 Jacob (2018), p.112

39 by Engelhardt et al. (2017)

40 by Engelhardt et al. (2017), p.17

41 Cf. Reillier et al. (2017), p. 27

42 See Ammon (2013), p.101

43 Ebner (2018), p. 1, https://tme-ag.de/wp-content/uploads/2018/10/TME-Whitepaper-Online-Banking-digitales-%C3%96kosys- tem.pdf, retrieval from 18.11.2019

44 Jacobides et al. (2018), p.16. https://www.researchgate.net/publication/323916602_Towards_a_Theory_of_Ecosystems.Re- trieved from18.11.2019

45 See Geschka (2015), p.67

46 Cf. Sydow et al. (2011), p.56

47 Cf. Simon (2000), p.232

48 Cf. meat (2001), p.48

49 Cf. Eckert (2018), p.209 f

50 Baums (2015), http://plattform-maerkte.de/wp-content/uploads/2015/10/Kompendium-I40-Analyserahmen.pdf, retrieval from 18.11.2019

51 from Engelhardt et al. (2017), p. 5

52 Matyssek (2017), p.168

53 Federal Ministry of Economics and Energy (2017), p. 21

54 Cf. Hein et al. (2019), p.182

55 Cf. Ebner ( 2018 ), p. 2 f, https://tme-ag.de/whitepaper/vorgehensmodell-zum-aufbau-eines-digitalen-oekosystems/, retrieval of 18.11.2019

56 Cf. Baums, p.17 f, http://plattform-maerkte.de/wp-content/uploads/2015/10/Kompendium-I40-Analyserahmen.pdf, retrieval from 18.11.2019

57 Evans (2016), p.7, https://www.thecge.net/app/uploads/2016/01/PDF-WEB-Platform-Survey_01_12.pdf, retrieval from 18.11.2019

58 Kollmann (2019), p.56 f

59 Kollmann (2019), p.56 f

60 by Engelhardt et al. (2017), p.5

61 Ebner (2018), p.2, https://tme-ag.de/whitepaper/vorgehensmodell-zum-aufbau-eines-digitalen-oekosystems/, retrieval from 18.11.2019

62 Ebner (2018), p.2, https://tme-ag.de/whitepaper/vorgehensmodell-zum-aufbau-eines-digitalen-oekosystems/, retrieval from 18.11.2019

63 Cf. Lewrick (2018), p.89

64 Cf. Lewrick et al. (2019), p.49

65 Lewrick et al. (2019), p. 50

66 Cf. Lewrick et al. (2019), p.51 f

67 Cf. Lewrick et al. (2019), p. 50 ff

68 Massa et al. (2017),

69 Cf. Hass et al. (2018), p.30 f

70 Cf. Hass et al. (2018), p.31

71 Cf. Müller-Stewens et al. (2016), p.372

72 Cf. Kuckertz (2015), p.59 Cf. Wirtz (2018), p.4 Cf. Osterwalder et al. (2011), p.19 Cf. Osterwalder et al. (2011), p. 18 Schallmo (2013), S. 16 See Rusnjak (2014), p.31 Möller et al. (2011), p.213 Cf. Hoffmeister (2015), p.36 ff See Jaekel (2015), p.6 Petersen (2018), p.3

73 Petersen (2018), p.3 Petersen (2018), p.3 Cf. Gassmann et al. (2017), p.7

74 Osterwalder et al. (2011), p. 20 ff

75 Rusnyak (2014), p.31

76 Müller-Stewens et al. (2016), p.372

77 Schallmo (2013), p.52

78 Wirtz (2018), p.362 ff

79 Cf. Pöppelbuß et al. (2017), p.97

80 Osterwalder et al. (2015)

81 Hoffmeister (2015), p.46 f

82 Ebner (2018), S.1

83 Moore (2006), p.63

84 Paul (2017), https://warenausgang.com/wie-bleiben-unternehmen-in-einer-digitalen-welt-relevant/, retrieval of 18.11.2019

85 Cf. Parker et al. (2017), p.54

86 from Engelhardt (2019a), S. 16

87 Oberle (2019), https://www.digitale-exzellenz.de/erfolgsfaktoren-digitale-plattformen/, retrieval from 18.11.2019

88 Cf. from Engelhardt et al. (2019a), p.14 ff

89 Cf. from Engelhardt et al. (2019a), p.14 ff

90 Cf. from Engelhardt et al. (2019b), p.136

91 Cf. from Engelhardt et al. (2019b), p. 136 f

92 Cf. from Engelhardt et al. (2019a), p.14 ff

93 Ebner (2018), p.2, https://tme-ag.de/whitepaper/vorgehensmodell-zum-aufbau-eines-digitalen-oekosystems/, retrieval from 18.11.2019

94 Ebner (2018), p.2, https://tme-ag.de/whitepaper/vorgehensmodell-zum-aufbau-eines-digitalen-oekosystems/, retrieval from 18.11.2019

95 Lewrick et al (2019), p. 50 ff

96 Walter (2019), p.99 Walter (2019), p.99 Peneva (2019), p.129 Peneva (2019), p.114 ff Peneva (2019), p.115 Peneva (2019), p.114 ff from Engelhardt et al. (2019), p.137 Choudary (2015), 145 Peneva (2019), p.114 ff Cicero (2019), https://vivaldigroup.com/en/blogs/platform-design-toolkit-simone-cicero/, retrieval from 18.11.2019

97 Peneva (2019), p.114 ff Walter (2019), p.96 ff Walter (2019), p.96 ff

98 Cf. Geschka et al. (2013), p.35

99 by Engelhardt (2019a), p.16

100 Ebner (2018), p.2, https://tme-ag.de/whitepaper/vorgehensmodell-zum-aufbau-eines-digitalen-oekosystems/, retrieval from 18.11.2019

101 by Engelhardt (2017) et al., p.11 et seq. https://docs.google.com/viewer?url=https%3A%2F%2Fwww.digitale-technolo- gien.de%2FDT%2FRedaktion%2FDE%2FDownloads%2FPublikation%2Fautonomik-studie-digitale-plattfor- men.pdf%3F blob%3DpublicationFile%26v%3D6&pdf=true, retrieved from 18.11.2019

102 Hein et al. (2019) et al. , p.193 ff

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A business model for the digital B2C/B2B platform. The development based on an ecosystem
AKAD University of Applied Sciences Stuttgart
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business model, ecosystem, digital platform, business model for digital platform, digital ecosystem, business model development
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Larissa Petersen (Author), 2020, A business model for the digital B2C/B2B platform. The development based on an ecosystem, Munich, GRIN Verlag, https://www.grin.com/document/945231


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