Strategies in online food delivery ecosystems. Characterization and evolution over time

Contents

Abstract

Zusammenfassung

Contents

List of Figures

List of Tables

List of Abbreviations

1 Introduction

2 Theoretical background
2.1 Existing research streams on the interdependence across organizations
2.2 Ecosystem research stream
2.2.1 Definition and characteristics of ecosystems
2.2.2 Types of ecosystems
2.2.3 Characteristics of platform-based ecosystems
2.2.4 Value creation and value capture in ecosystems
2.2.5 Ecosystem strategies

3 Research questions

4 Conceptual framework

5 Application of developed conceptual framework
5.1 Case context
5.2 Research methodology of multiple-case study
5.2.1 Case selection
5.2.2 Data collection
5.2.3 Data analysis

6 Empirical results
6.1 Launch strategy
6.1.1 Pizza.de
6.1.2 Lieferando
6.1.3 Lieferheld
6.1.4 Foodora
6.1.5 Deliveroo
6.1.6 Summary launch strategy
6.2 2007-2010: The lone rider
6.3 2011-2014: The arena fills up
6.4 2015-2018: The time for delivery logistics
6.5 2019-today: The chained monopolist

7 Discussion
7.1 Final evaluation
7.1.1 Review of conceptual framework
7.1.2 Review of empirical taxonomic framework
7.2 Answering the research questions
7.3 Managerial implications
7.4 Limitations
7.5 Further research

8 Conclusion

9 References

Abstract

Background: The business ecosystem perspective provides a holistic view on the interdependence across organizations. Yet, existing literature reveals little theoretical foundation with respect to ecosystem strategies in the context of platforms. Prior research includes a static view on ecosystem strategies leading to characterizations such as the “component” or “system” strategy. Recently, a newly presented strategy, the “bottleneck” strategy, provides a dynamic view on ecosystem strategies. Unfortunately, much literature exclusively study cooperation and competition between ecosystem partners, however, neglects to explain how and why cooperation and competition between rival ecosystems generally occurs. Objective and research question: Hence, the aim of this paper is to complement existing research on dynamic ecosystem strategies in the context of platforms. Two research questions will be answered: 1) How do competitive strategies of rival platform-based ecosystems evolve over time? 2) How can competitive strategies of rival platform-based ecosystems be characterized? Method: A longitudinal, multiple-case study will be conducted. This multiple-case study is pursuing an inductive, theory-building approach as there is limited theoretical foundation on strategies in platform-based ecosystems. Five online food delivery ecosystems in the German market are analyzed. Results: This work proposes a new framework to determine the temporal state of platform- based ecosystem strategies and how to systematically characterize platform-based ecosystem strategies. The conceptual framework is structured in three phases: 1) Building the pie 2) growing the slice of the pie, and 3) capture thickest layer of the slice. Every phase exhibits distinct characteristic of competition and cooperation between rival ecosystems and ecosystem partners. Discussion: Several contributions are made by this paper. Firstly, platform literature and ecosystem literature have been combined leading to a conceptual framework of how platform-based ecosystem strategies evolve over time. This extends the existing research stream of ecosystem strategies by adding a dynamic lens. Secondly, the theoretical, structuralist approach of describing the configuration of an ecosystem proposed by Adner (2017) has been applied practically to an empirical case - online food delivery. Third, the developed conceptual and empirical framework serve as a tool for practitioners to engage in ecosystem strategy analysis.

Zusammenfassung

Hintergrund: Die Perspektive, die gegenseitige Abhängigkeit zwischen Organisationen als Ökosystem zu betrachten, bietet eine ganzheitliche Sicht. Die vorhandene Literatur offenbart jedoch wenig theoretische Grundlagen in Bezug auf Ökosystemstrategien im Kontext von Plattformen. Bisherige Arbeiten umfassen eine statische Sicht auf Ökosystemstrategien, die zu Charakterisierungen wie der „Komponenten“ oder „System“ Strategie führen. Die sog. „Engpass“ Strategie bietet erstmalig eine dynamische Sicht auf Ökosystemstrategien. Allerdings untersucht die bestehende Literatur hauptsächlich die Zusammenarbeit und den Wettbewerb zwischen Ökosystempartnern, vernachlässigt jedoch die Erklärung, wie und warum Kooperation und Wettbewerb zwischen konkurrierenden Ökosystemen auftreten. Ziel und Forschungsfrage: Ziel dieser Arbeit ist es daher, die bestehende Forschung zu dynamischen Ökosystemstrategien im Kontext von Plattformen zu ergänzen. Zwei Forschungsfragen werden beantwortet: 1) Wie entwickeln sich Wettbewerbsstrategien konkurrierender plattformbasierter Ökosysteme im Laufe der Zeit? Und 2) Wie können Wettbewerbsstrategien konkurrierender plattformbasierter Ökosysteme charakterisiert werden? Methodik: Eine Längsschnitt-Fallstudie mit mehreren zu untersuchenden Ökosystemen wird durchgeführt. Diese multiple Fallstudie verfolgt einen induktiven, theorentwickelnden Ansatz, da es nur begrenzte theoretische Grundlagen über Strategien in plattformbasierten Ökosystemen gibt. Es werden fünf Ökosysteme im Umfeld von online Essensbestellungen auf dem deutschen Markt analysiert. Ergebnisse: Diese Arbeit schlägt ein neues konzeptionelles Modell vor, um den zeitlichen Ablauf plattformbasierter Ökosystemstrategien zu bestimmen und plattformbasierte Ökosystemstrategien systematisch zu charakterisieren. Dieser konzeptionelle Rahmen ist in drei Phasen gegliedert: 1) Aufbau des Kuchens 2) Wachstum des Stücks des Kuchens und 3) Erobern der dicksten Schicht des Kuchenstücks. Jede Phase weist unterschiedliche Merkmale hinsichtlich des Wettbewerbes und der Zusammenarbeit zwischen konkurrierenden Ökosystemen und Ökosystempartnern auf. Diskussion: Mehrere wissenschaftliche Beiträge werden durch diese Arbeit geleistet. Erstens werden Plattformliteratur und Ökosystemliteratur kombiniert, was zu einem konzeptionellen Rahmen für die Beschreibung der temporalen Entwicklung plattformbasierter Ökosystemstrategien führt. Zweitens wurde der von Adner (2017) vorgeschlagene theoretische, strukturalistische Ansatz zur Beschreibung der Konfiguration eines Ökosystems praktisch auf einen empirischen Fall angewendet - die Online­Essensbestellung. Drittens dienen die entwickelten konzeptionellen und empirischen Modelle Praktikern als Instrument zur Analyse von Ökosystemstrategien.

List of Figures

Figure 1: Market size (l) and online penetration (r) of take-away food delivery

Figure 2: Overall approach for answering the research question of this master thesis

Figure 3: Three ecosystem strategy phases

Figure 4: Description of ecosystem strategy phases

Figure 5: General food delivery ecosystem

Figure 6: Historic development of online food delivery ecosystems in Germany

Figure 7: Phases of OFD market in Germany

Figure 8: Number of listed restaurants

Figure 9: KPIs of Lieferando

Figure 10: Absolute desktop website traffic

Figure 11: Desktop website traffic market share

Figure 12: Delivery rider

Figure 13: Google Trend analysis for all five ecosystems

Figure 14: Commission rate and take rate of Lieferando

Figure 15: Revenue, Adjusted EBITDA, EBITDA margin of Lieferando

List of Tables

Table 1: Sample firms

Table 2: Funding of sample firms

Table 3: Reviewed press articles

Table 4: Empirical framework

Table 5: Ecosystem strategies in phase 1

Table 6: Ecosystem strategies in phase 2

Table 7: Unit economics for marketplace ecosystem model

Table 8: Unit economics for delivery logistics ecosystem model

Table 9: Ecosystem strategies in phase 3

Table 10: Ecosystem strategies in phase 4

Table 11: Relative importance of taxonomic criteria

Table 12: Idiosyncratic and generic criterions of empirical taxonomy

List of Abbreviations

Abbildung in dieser Leseprobe nicht enthalten

1 Introduction

The significance of online food delivery (OFD) ecosystems is evident in our everyday lives. Not only in major cities, but also in small town and even villages, OFD gained popularity rapidly. Without a doubt, OFD is a fast-paced business. This pace is especially evident in the speed and number of takeovers. For example, in 2016 at its IPO, Takeaway.com, a Dutch company, had a market capitalization of around €993 million ($1.1 billion) (Lunden, 2016). In December 2018, Takeaway.com announced the acquisition of the German brands of Delivery Hero: Lieferheld, Pizza. de and Foodora. With this, Takeaway.com and its German brand Lieferando rose to become a market monopoly in Germany. In January 2020, Takeaway.com merged with the British provider Just Eat (Lunden, 2019). Just a few months later, in June 2020, the merged company Just Eat Takeaway.com announced the takeover of US OFD player Grubhub (Lunden & Korosec, 2020). By today, the combined company has a market capitalization of approximately $13bn (Yahoo! Finance, 2020). Concurrently, in August 2020 Delivery Hero, a German OFD player that has been listed since 2017, was promoted to the most important German share index: the DAX. The fast pace is also expressed in the fact that the market continues to produce new players. Wolt, founded in Finland, entered the German market, and became Lieferando’s new competitor in Germany in August 2020. Whether this new player can survive against market monopolist Lieferando is questionable. These insights reveal another characteristic of OFD: It is not only face-paced, but also a very large and valuable industry.

The significance of the industry is also visible during the COVID 19 pandemic. While most of the revenue streams for restaurants come to a standstill because they could not serve patrons at their tables, customers are ordering more food online than before. For example, Lieferando’s sales in the first half of 2020 more than doubled compared to the first half of 2019, now reaching €161m (Just Eat Takeaway.com, 2020). The number of orders increased by 76% during the same period (Just Eat Takeaway.com, 2020).

Two indicators are of particular interest when comparing different OFD markets. The first one is the total market size of take-away delivery food. This includes all orders that are intended to be consumed outside the restaurant. UK represents the biggest take-away delivery market with a market size of €6.5bn in 2015, Germany ranking second place in Europe having an addressable market of €4.5bn (Ferraz et al., 2016). Second, out of all those take-away orders, how many have been placed online vs offline? Hence, how big is online penetration? The online penetration for countries within Europe differs significantly. In 2017, 60% of take-away food is transacted online in the UK. In the Netherlands, 33% have been transacted online in 2017. Comparing this to Germany’s online penetration of 20% in 2017, one can imagine the upside potential for OFD ecosystems to grow (Ferraz et al., 2018). Figure 1 illustrates the market size as well as the online penetration for selected countries.

Abbildung in dieser Leseprobe nicht enthalten

Figure 1: Market size (l) and online penetration (r) of take-away food delivery for selected countries; Source: Estimate numbers from Ferraz et al. (2016)

At the beginning of this research endeavor stood the idea of understanding competitive strategies of platform-based ecosystems. OFD exhibits suitable characteristics to serve as a case for this aim. OFD platforms, such as Lieferando, manage a complex environment of restaurants, delivery riders and customers aiming to connect hungry customers with restaurants. The participants of this environment are mutually dependent: There is no value for customers to visit the webpage of an OFD platform, when there is no restaurant to order form. And vice versa, there is no value for restaurants to be listed on the OFD platform, when no customer is willing to order food from this platform. Hence, the OFD platform aims to balance each side of this market.

Existing research offers several perspectives to analyze such constellations. Literature on network economics refer to this context as multisided markets (see Caillaud & Jullien, 2003; Rochet & Tirole, 2003, 2006). Multisided in that a platform firm mediates transactions between two sides of a market, e.g., between customers and restaurants. The hallmark of research about platform competition is the concept of network effects, i.e., positive feedback loops (Cennamo & Santalo, 2013). However, a sole view from the platform’s perspective and its size may not be sufficient to characterize and analyze the strategy.

The business ecosystem perspective provides a more holistic view on the interdependence across organizations. Yet, existing literature on business ecosystems reveals little theoretical foundation to find a structured answer to the proclaimed endeavor. Prior research includes a static view on ecosystem strategies leading to characterizations such as the “component” or “system” strategy (Arora & Bokhari, 2007; Farrell et al., 1998). Only recently, a newly presented strategy, the “bottleneck” strategy, provides a dynamic view on ecosystem strategies (Hannah & Eisenhardt, 2018). The bottleneck strategy describes the internal balance of competition and cooperation between ecosystem partners. Unfortunately, much literature exclusively study cooperation and competition between ecosystem partners, however, neglects to explain how and why cooperation and competition between rival ecosystems generally occurs.

Hence, the aim of this paper is to complement existing research on dynamic ecosystem strategies in the context of platforms. This work proposes a new framework to determine the temporal state of platform-based ecosystem strategies and how to systematically characterize it.

The structure of this thesis includes the following eight chapters.

Chapter 1 stresses the importance of business ecosystems, in theory and practice.

Chapter 2 will further elaborate the theoretical background of this thesis. Due to the relative novelty of the topic and the interdisciplinary classification in science, this chapter is divided into existing research on interdependence across organizations and ecosystem research. It will detail the definition of a business ecosystem, the different types, its characteristics, and ecosystem strategies.

Chapter 3 condenses these insights into research questions and defines the scope of the thesis.

Chapter 4 presents the conceptual framework that has been developed. This framework leads as an instrument to find a structured answer to the research questions. It represents a three- step strategy process of platform-based ecosystems.

In chapter 5, the empirical setting of the conducted case study is described. The case study serves as a first cycle to refine the conceptual framework. This chapter includes the case context, the case selection, as well as data collection and data analysis. In the data analysis section, an empirical framework to characterize ecosystem strategies is presented.

Chapter 6 provides the results of the case study analysis of five OFD ecosystems. This includes their launching strategy as well as their ecosystem strategy development over time.

In chapter 7, the three-step conceptual framework as well as the empirical framework to characterize ecosystem strategies will be reviewed. Furthermore, the research questions will be answered. Moreover, practical implications for businesses are provided, and limitations of this thesis as well as future research directions are presented.

Finally, in chapter 8, a conclusion of this thesis is presented by summarizing the key insights and results, as well as showing the contribution of knowledge.

2 Theoretical background

This chapter starts by exploring existing scientific research on the interdependence of companies. Different perspectives, from network theory to supply chains, are introduced. The basis for this thesis represents the ecosystem perspective. Hence, the later subchapters lay the theoretical foundation by illustrating the unique characteristics of this perspective. This includes a common definition of an ecosystem, types as well as characteristics of ecosystems, and finally also ecosystem strategies, the main topic of this work.

2.1 Existing research streams on the interdependence across organizations

In strategy literature, several research streams relate to the notion of ecosystems. Research on networks, alliances, and supply and value chains share the similar thought of widening the scope of analysis from a single organization to including its environment. In all these streams scientists examine the interdependence of multiple firms creating and capturing value. However, there are distinct differences in how interdependencies are discovered and managed. Network literature is rooted in the analysis of social networks and deals with formal inter-organizational relationships that are entered voluntarily (Kapoor, 2018). While literature about networks applies a broader view between the ties of multiple actors forming the network structure, alliance literature focuses on the dyadic tension between two actors and how these actors cooperate for their mutual benefit (Jacobides et al., 2018; Kapoor, 2018). Therefore, two actors in a network may form an alliance through their ties, and multiple webs of alliances determine the network structure.

The value chain perspective introduced by Porter (1985) takes into consideration the focal firm as well as their suppliers, distributors and buyers. However, it takes a micro perspective on the internal activities performed by the focal firm. Also, the emphasis lies on the interdependence between actors of a sequential chain, and hence on bilateral interactions, rather than on a complex structure of interdependencies, as it is the case with ecosystems (Adner, 2017; Kapoor, 2018). Furthermore, the supply chain perspective (see Simchi-Levi et al., 2000), as the notion indicates, focuses on the supply-side interactions of actors and thereby misses to consider demand-side complementarities and the structure of interdependencies (Kapoor, 2018).

In contrast, the starting point in ecosystem research is the focal value proposition (Adner, 2017; Shipilov & Gawer, 2020). Based on the focal value proposition, activities and actors that perform the necessary activities are recognized through their linkages and position in the ecosystem (Adner, 2017).

2.2 Ecosystem research stream

The previous chapter outlined existing scientific fields of this master thesis, such as networks and alliances. The following chapter aims to explore the relevant theoretical ecosystem concepts for this thesis. First, a common definition for an ecosystem will be established and defining characteristics explored. Second, distinct types of ecosystems are presented. Third, the state of research on strategies on ecosystems will be examined. Furthermore, throughout this chapter, essential linkages to related research streams will be drawn, such as platforms and multi-sided markets.

2.2.1 Definition and characteristics of ecosystems

The ecosystem perspective attracted increasing attention during the past years, for academics and practitioners alike, as can been seen, for example, from the number of mentions in companies’ annual reports (Adner, 2017; Birkinshaw, 2019; Jacobides et al., 2018; Pidun et al., 2019).

The business world borrowed the term ecosystem from biology and uses it to describe a group of interdependent, but standalone companies that interact in order to solve a business problem (Adner, 2017; Jacobides et al., 2018). So far, research presented a multiplicity of definitions of an ecosystem, some of them rather vague (see Moore, 1997), others more specific, e.g., by building on the concept of complementarities (see Jacobides et al., 2018). Adner (2017) provides a clear definition of an ecosystem with distinct components, stating that “the ecosystem is defined by the alignment structure of the multilateral set of partners that need to interact in order for a focal value proposition to materialize.” (Adner, 2017, p. 42). In other words, an ecosystem represents a group of independent players that individually create a product or service, which taken together comprises a coherent solution (Hannah & Eisenhardt, 2018; Pidun et al., 2019).

This definition encompasses several characteristics: First, at the core of any ecosystem is a value proposition (Adner, 2017; Kapoor, 2018; Pidun et al., 2019). The value proposition naturally creates the boundary for the ecosystem thereby answering the question: What activities are necessary to generate the value proposition, and consequently, who needs to be part of the ecosystem for the value proposition to materialize? Second, the ecosystem participants create value through complementary activities, products or services (Jacobides et al., 2018). An ecosystem cannot deliver its value to the customer unless all ecosystem participants contribute their component to the ecosystem. Hence, the co-created value exceeds the sum of value created by the individual ecosystem participant. Third, an ecosystem is multilateral by nature (Adner, 2017; Jacobides et al., 2018). Multilateral in this case means there is a multiplicity of partners and relationships which cannot be decomposed to simple dyads. Multilateral interdependence that are decomposable into bilateral interactions do not need the ecosystem construct. Bilateral relationships can be explored scientifically through the concepts mentioned in the previous chapter, e.g., the value chain concept. Last, ecosystems are not fully hierarchically controlled (Jacobides et al., 2018). Instead, alignment between the partners is reached through a set of standardized rules for each role in the ecosystem. Based on these standardized rules an ecosystem can decide how open it is for outsiders that want to join and what ecosystem-specific investments are necessary for participation (Jacobides et al., 2018; Pidun et al., 2019).

As explained above, the starting point for any ecosystem is its value proposition. The value proposition gives rise to more specific considerations regarding the structure of an ecosystem: (1) Which activities are required for the value proposition to materialize, (2) which actors undertake these activities, (3) where in the flow of activities are the different actors positioned, and (4) what is being transferred between the actors? Hence, activities, actors, positions and links may define the structure of an ecosystem (Adner, 2017). This structuralist approach of depicting an ecosystem places emphasis on the activities, whereas an affiliation approach focuses on the actors and their ties to a focal actor, leading to characterizations such as platforms or hub-and-spoke. However, as Adner (2017) mentions as well, these two approaches are not mutually exclusive. Instead, in a distinct setting, a combination of both may be useful, leaving open what this setting might be. The four structuralist elements as well as the affiliation approach will be of relevance in this master thesis, when the general OFD ecosystem will be described.

2.2.2 Types of ecosystems

The previous chapter laid the theoretical foundation for this master thesis by exploring the question of how an ecosystem is defined and how its structure can be depicted. The following chapters will build on this by further explaining different types of ecosystems.

One way to define different types of ecosystems is based on their structure (Kapoor, 2018). According to Pidun et al. (2019) there are two basic types of ecosystems: solution ecosystems and transaction ecosystems. Similarly, Kapoor (2018) refers to product-based and platform- based ecosystems. Solution ecosystems are represented by a focal firm and its product or service, which is enriched by offerings of several complementors. The focal firm acts as the core firm coordinating and aligning the complementers. In solution ecosystems the final customer buys the focal firm’s product, plus, has the opportunity to choose among all offerings that are supplied by the complementors (Jacobides et al., 2018). This set of producers, the focal firm as well as the complementors, are bound together through certain interdependencies, such as standardized rules or technical standards. Examples include Googles Android App store (Yoffie et al., 2019), where users can liberally select and combine various apps, or smart home solutions (Pidun et al., 2019).

The other type, transaction ecosystems, facilitate exchange and trade between customers and suppliers via a central platform. This platform may or may not be digital. Typical examples include Uber or eBay that match independent customers with independent suppliers. In the case of Uber, riders are matched with drivers, at eBay buyers and sellers are brought together at a marketplace. Regularly, this type is also referred to as multi-sided, two-sided or double­sided markets respectively (Gawer & Cusumano, 2014). In this case, two-sided means there are independent and distinct groups on one side of the market (demand) and distinct groups on the other side of the market (supply) (Evans, 2003a; Rochet & Tirole, 2003, 2006). The platform in between serves as the intermediary between the two sides, engaged in matching them.

Note that even if there is a digital platform involved in a business ecosystem, this does not mean that this ecosystem represents a transaction ecosystem automatically. Consider the case of an automotive OEM that wants to partner with insurance companies, gas stations, local authorities, and a platform operator to introduce a new mobility solution. The platform operator might be a small startup which provides one complement to the total solution. However, the platform might not be the orchestrator of this business ecosystem. Instead, the automotive OEM takes over this role indicating that this ecosystem exhibits characteristics of a solution ecosystem. Hence, a platform might be a necessary feature for a transaction ecosystem, however, the presence of a platform is not sufficient to decide whether it is a solution or transaction ecosystem.

Interchangeably, transaction ecosystem are also called platform ecosystems (Cennamo & Santalo, 2013; Parker et al., 2016; Rothe et al., 2018), digital business ecosystem platforms (Senyo et al., 2019), platform-based ecosystems (Gawer & Cusumano, 2014; Ozalp et al., 2018) or transaction platforms (Yoffie et al., 2019). For the rest of the thesis the term platform- based ecosystem will be used to ensure consistent terminology.

To sum up, in a platform-based ecosystem, a platform is embedded as the central actor in the ecosystem and transactions between two or more sides of the market are mediated through the platform.

2.2.3 Characteristics of platform-based ecosystems

The key distinguishing feature of a platform-based ecosystem is the aim to grow the relevant sides of the market enabled by network effects (Adner, 2017). Network effects are positive feedback loops and may be direct or indirect.

Positive direct network effects exist when a large number of users on one side in turn attract even more users on the same side of the market, leading to exponential growth in the user base (Evans, 2003b; Gawer & Cusumano, 2014; McIntyre & Srinivasan, 2017; Rochet & Tirole, 2003, 2006). This is the case in many social networks, such as Facebook: the more of my friends have a Facebook profile, the higher the incentive for me to also create a Facebook profile to see and share experiences. This creates a positive feedback loop, i.e., more users attract even more users.

Positive indirect network effects arise when different sides of the market mutually benefit from the growth and characteristics of the other side (Boudreau & Jeppesen, 2015; Evans, 2003b; Rochet & Tirole, 2006; Zhu & Iansiti, 2012). Taking Facebook again as the example, positive indirect network effects exist between advertisers that want to publish their advertisements on Facebook and the number of users: the higher the number of users, the more attracted are advertisers. Ultimately, “network economics theory on multisided markets asserts that growth in the installed user base and the availability of complementary products are the main mechanisms driving a platform’s value and market share.” (Cennamo & Santalo, 2013, p. 1333). However, indirect network effects give rise to the so-called chicken-or-egg problem (Caillaud & Jullien, 2003). For example, to attract more sellers, Amazon requires a larger user base. But users will participate on the platform only if they expect many buyers to offer their products there. This leads to questions about which side of the market is more valuable and which less. Consequently, participation for different ecosystem partners is incentivized or charged.

Furthermore, the logic of network effects and self-reinforcing positive (as well as negative) dynamics create a winner-take-all (WTA) (or most) paradigm, in which the platform with the most users and complementors will outperform competition (see Caillaud & Jullien, 2003; Eisenmann et al., 2006). Following the WTA paradigm means to pursue a get-big-fast strategy (Lee et al., 2006). As a consequence, this leads to aggressive strategies to grow the relevant sides of the market, e.g., by promoting users to join the ecosystem by setting low prices through discounts, or by locking in complementors through sweetheart deals or exclusive contracts to prevent them from multi-homing, i.e., the participation in multiple platforms (Cennamo & Santalo, 2013). In addition, the logic of the WTA paradigm leads to the conclusion that deep pockets are crucial to be able to offer competitive pricing. Hence, a platform with higher liquidity is able survive the costly WTA competition longer (Cennamo & Santalo, 2013).

However, scientists start questioning the unconditional logic of network effects (McIntyre & Srinivasan, 2017). Cennamo and Santalo (2013) show that pursuing multiple get-big-fast strategies concurrently is detrimental to platform performance, when the distinct platform position in a competitive environment remains unconsidered. In that sense, platform size, i.e., the number of users, and complementors as well as additional providers, is complemented with the platform identity (Cennamo, 2019). The platform identity is characterized by the technological architecture, i.e., technological performance, functionalities, ease of access, and the platform scope, i.e., different markets the platform serves in terms of consumers’ preferences. Both dimensions, platform size and platform identity, affect the platform value and determine the competitive position of the platform.

To understand the competitive dynamics between rival platforms, Cennamo (2019) suggests to compare two or more rival platforms along these two dimensions as well as the changes on these two dimensions resulting from competitive actions. For example, assuming Uber has a certain number of drivers and riders (platform size) and aims to attract young, tech-savvy users that are using mobile apps (platform identity). Furthermore, Uber decides to introduce the possibility for the elderly to order Uber offline without the need to own a smartphone. This competitive action changes Uber’s platform identity (i.e., a smartphone is not needed anymore) as well as size (i.e., more potential users). Hence, the competitive dynamics between Uber and traditional cab companies may intensify, given the unchanged competitive profile of taxi business. Ultimately, the model predicts that competition will escalate into a WTA battle, when two or more rival platforms show similar characteristics in the platform identity domain, and hence emphasize platform size (Cennamo, 2019). In conclusion, it is not sufficient to analyze platforms and their competitive actions by only looking at their size or identity individually. An integrating perspective, as Cennamo (2019) proposes, enables a clearer picture to explain competitive dynamics between rival platforms.

Equally and overlapping to Cennamo and Santalo (2013) and Cennamo (2019), a growing number of publications emphasizes other factors such as entry timing (Eisenmann et al., 2006; Zhu & Iansiti, 2012), platform quality (McIntyre, 2011; McIntyre & Srinivasan, 2017; McIntyre & Subramaniam, 2009), strengths of ties and multi-homing opportunities (Afuah, 2013;

Belleflamme & Peitz, 2019; Zhu & lansiti, 2019). Yet, significant uncertainty remains about the interplay of those factors and about optimal strategies in platform development and management (McIntyre & Srinivasan, 2017; Senyo et al., 2019). To be more specific: McIntyre and Srinivasan (2017) explicitly raise the question of “what firm-level characteristics and strategies enable the persistence of competitive advantage over time and across platforms?” (McIntyre & Srinivasan, 2017, p. 153).

To sum up, characteristics of platform-based ecosystems initially focused on network effects and how companies can create WTA markets. Recently, research questioned this logic by adopting a more comprehensive view. Besides the pure platform size, platform identity and hence defining characteristics such as quality, variety and entry timing were taken into consideration.

2.2.4 Value creation and value capture in ecosystems

In ecosystems, firms cooperatively create value. This value is captured competitively between the participating firms by exploiting their market power. Balancing coopetition, the interplay of competition and cooperation, is necessary for the ecosystem success (Pidun et al., 2020).

In a platform-based ecosystem, value creation can be determined mathematically by the number of successful transactions and the average transaction value. Consequently, one aim is to increase the number of transactions, for example by increasing the number of participating users and complementors, or by increasing retention rate of existing users. The average transaction value may be improved by focusing on customer satisfaction or the variety and quality of complementors.

Value capture refers to the question of whom you charge in the ecosystem and what you charge, hence, the pricing strategy. Many platform-based ecosystems charge one side little or nothing (Evans, 2003a), consequently, below marginal cost. Getting the pricing strategy right is relevant as it is of utmost importance to know which side of the market should get charged and which side subsidized to avoid failure (Yoffie et al., 2019).

Fairly distributing value among the ecosystems participants is equally important as creating value as an analysis of successful and failed ecosystems shows (Pidun et al., 2020). Therefore, the upcoming chapter will describe strategies to handle the tension between cooperation and competition, and hence, value creation and value capture, in ecosystems.

2.2.5 Ecosystem strategies

Currently, there is a rather limited body of literature examining ecosystem strategies. At the core, this research is concerned with strategies to balance cooperation and competition across organizations. So far literature identified three broad and generic strategies that focal firms within an ecosystem pursue: (1) the system strategy, (2) the component strategy and (3) the bottleneck strategy.

These three strategies explain how many and which components of an ecosystem to enter. Initially, the system as well as the component strategy have been developed by Farrell et al. (1998), independently from ecosystem research (see Moore, 1997 who was the first to develop a definition of a business ecosystem). Only in combination, findings from Farrell et al. (1998) and Moore (1997) led to the definition of the system and component ecosystem strategy. A focal firm within an ecosystem is pursuing a system strategy when it engages in multiple components of the ecosystem and hence competes in most or all of these components (i.e., compete with rival system as well as component firms). In the component strategy a focal firm focuses on one or a few components within the ecosystem and cooperates with complementors to achieve a coherent value proposition (cooperate with complementary component firms, compete with rival component firms). As Hannah and Eisenhardt (2018) acknowledge, these two strategies depict a static picture of strategy in ecosystems, raising the question how they evolve over time.

Only recently, as research on ecosystems received a boost, Hannah and Eisenhardt (2018) conducted a multiple case study within the nascent residential solar industry in the U.S., complementing the system and component strategy by identifying the bottleneck strategy. The bottleneck strategy provides a dynamic view about the decision of a focal firm to enter a component within the ecosystem. In this strategy, a focal firm dynamically enters the component that constitutes a bottleneck through a complex interplay of cooperation and competition. Depending on the crowdedness of the bottleneck (i.e., number of competing firms in the bottleneck) firms will emphasize cooperation (crowded bottleneck) or competition (uncrowded bottleneck). Here, the difficulty is to predict the emergence of a bottleneck and how long it will stay relevant in the ecosystem (Hannah & Eisenhardt, 2018).

Former research endeavors in the stream of ecosystem strategies revealed important insights into how focal firms balance cooperation (Adner & Kapoor, 2010; Gawer & Henderson, 2007; Hannah et al., 2016; Ozcan & Eisenhardt, 2009) and competition (Ferraro & Gurses, 2009; Gawer & Cusumano, 2002; Jacobides et al., 2006; Jacobides et al., 2016) within an ecosystem. However, it is implicitly assumed but not examined in a structured way that competition between rival ecosystems occurs. The perspective of cooperation and competition between rival ecosystems has been neglected despite its relevance.

For example, a strategic action that is primarily intended to change the inner dynamics within an ecosystem, also has implications on rival ecosystems, and vice versa. A focal firm should thoroughly analyze the implication of a strategic action. Consider a strategic action of a focal firm in an ecosystem which aims at capturing more value by entering the complementors component. This action may lead to the undesired side effect of complementors leaving the ecosystem and joining a rival ecosystem or to multi-home, if switching costs are low. In other words, within-ecosystem and between-ecosystem dynamics are likely to influence each other (Jacobides et al., 2018). To summarize, research on ecosystem competition operates at two levels: within and between ecosystems. Within ecosystem competition spotlights tensions of activities, roles and positions, whereas between ecosystem competition focuses on the collective advantage of creating and capturing value relative to rival ecosystems (Adner, 2017). The latter, having received less research attention in the past despite its indisputable impact on ecosystem success, is the sweet spot for the master thesis: Understanding competitive strategies between rival platform-based ecosystems.

To conclude the background chapter, it becomes apparent that research on ecosystems and platforms is highly intertwined. However, theoretical concepts (e.g., the structuralist approach of an ecosystem by Adner, 2017), and frameworks (e.g., the framework to analyze platform- based competition by Cennamo, 2019) have developed in isolation.

Several contributions are made by this master thesis. First, combining these streams of research, ecosystem literature benefits by building on existing concepts and frameworks about competition from the platform literature, thereby preventing the “reinvention of the wheel”.

Second, latest concepts and frameworks from ecosystem and platform literature exist in theory, however, have not yet been applied and tested in an empirical setting.

Third, as the state of theory in ecosystem literature is just at the beginning of its rise, this master thesis contributes to the ecosystem literature by engaging in theory development. The importance of theory building is demonstrated by a recent literature review on digital business ecosystems by Senyo et al. (2019) analyzing 101 publications. Out of all publications, alarming 72% were without theoretical foundation, hence, only 28% used theory. Additionally, the analysis shows that research on digital business ecosystems is dependent on theory borrowing (e.g., from network theory). This demonstrates that there is a significant need for more theory development in the field of digital business ecosystems.

3 Research questions

Based on the theoretical insights the master thesis aims to shed light on competitive strategies between rival platform-based ecosystems. The unit of analysis for understanding competitive strategies is the platform company as the orchestrator of the platform-based ecosystem. Thus, the following two research questions are answered:

Research question 1: How do competitive strategies of rival platform-based ecosystems evolve over time?

This leads to the second research question:

Research question 2: How can competitive strategies of rival platform-based ecosystems be characterized?

To answer the research questions, the following logic will apply to this work (see Figure 2).

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Figure 2: Overall approach for answering the research question of this master thesis

In chapter 4, a conceptual, theoretical framework to describe competitive strategies of platform-based ecosystems over time is developed. Chapter 5 will illuminate the empirical framework to characterize ecosystem strategies by exploring OFD ecosystems as objects of investigation. Next, empirical results of a multiple-case study of OFD ecosystem strategies in the German market are derived in chapter 6. In chapter 7, empirical results will be discussed by reviewing the conceptual and empirical frameworks. Additionally, chapter 7, will discuss limitations and further research. The work ends with a conclusion in chapter 8.

As a first step in answering the research questions, a conceptual framework describing how platform-based ecosystem strategies evolve over time has been developed. This model combines existing theory on platform strategies and ecosystem strategies. The framework follows a simple logic, inspired by baking, and sharing a pie.

The general temporal logic of platform-based ecosystem strategies is theoretically structured in three phases: (1) build the pie, (2) grow your slice of pie, and (3) capture the thickest layer of your slice (see Figure 3).

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Figure 3: Three ecosystem strategy phases: (l) collectively build the pie, (m) share the pie between multiple ecosystems, (r) capture thickest layer as platform in your ecosystem

First, in the build phase, one or many platform-based ecosystems aim to develop a new market, represented by the size of the pie. This may be approached by raising consumer and supplier awareness for a completely new product or service, or by initiating a channel shift. For example, in OFD industry, people were used to order food offline via telephone. The challenge was to educate consumers and restaurants to join the internet ordering revolution. Ultimately, it is crucial to ramp up market volume quickly. Hence, even when multiple platform-based ecosystems coexist, cooperation between them is key to collectively increase the market volume. Other platform-based ecosystems that offer a similar value proposition are no competition at this point of time as focus is lying on increasing total market volume. Within a platform-based ecosystem, the orchestrator of the ecosystem is engaging in as many relationships with consumers and suppliers as possible by setting low access barriers. Consequently, the build phase is characterized by cooperation between ecosystems and within each ecosystem.

Second, in the grow phase, it is time to rearrange and fight for the biggest slice of the collectively created pie. In other words, a platform-based ecosystem aims to increase market share. Ideally, market share may be measured by gross merchandise value (GMV). GMV represents the total value of products and services sold by all ecosystem partners. Any strategic action shall intend to increase the market share of the ecosystem. Market share is an important measure in markets subject to network effects (Cennamo & Santalo, 2013; Hannah & Eisenhardt, 2018). Therefore, competition between rival platform-based ecosystems intensifies, while cooperation between ecosystem partners remains to be important.

Third, in the last phase, the capture phase, within its ecosystem the platform wants to capture the thickest layer of the slice. Stated differently, given the market share of one ecosystem, the aim of the platform is to capture as much value as possible for itself, thereby maximizing profitability. Due to the asset-light nature of (digital) platforms, EBITDA, is the key metric to steer value capturing. Increasing EBITDA can be done in three ways: Increasing revenue, while keeping cost flat, reducing cost at a constant revenue level, or do both. To accomplish this, the platform is now entering competition with its ecosystem partners. One way for the platform to capture more value is to strategically grow into the partners business by vertically entering their activities. For instance, from being a marketplace only, Lieferando entered the delivery logistics business, which was initially covered by restaurants.

Figure 4 gives a comprehensive overview of the three phases and its characteristics. Additionally, it depicts the three phases as a sequence. However, these three phases do not necessarily follow a linear process. Rather, they develop concurrently. For example, a strategic action of a platform-based ecosystem may primally intend to increase its own market share. Still, the same strategic action may also affect the overall market volume. Consider, Deliveroo’s concept of “Deliveroo Editions” in the UK. Deliveroo harnesses available data about consumer order preferences and available restaurants, to offer equipped kitchen facilities to restaurants in yet untapped neighborhoods. Restaurants can rent a delivery-only “ghost kitchen” without owning any facility. This concept aims to increase Deliveroo’s market share, and at the same time increases the size of the overall market, as new und yet unserved customers are addressed. To summarize, any strategic action relates to one or multiple of these three phases. Simultaneously, different strategic actions emphasize one or the other phase more.

This model represents the first step in answering the research questions. In the subsequent chapters, the conceptual framework will be applied and tested in a case study setting.

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Figure 4: Description of ecosystem strategy phases

Now, as the conceptual framework has been developed, it is important to ground and assess it in real-world cases. Therefore, the conceptual framework will be applied to OFD ecosystems in the German market in a multiple-case study setting. In the context of digital business ecosystems, most publications used single case studies, limiting generalizability of their findings (Senyo et al., 2019). Therefore, multiple-case studies are needed to make findings more robust (Yin, 2018).The following subchapters deal with (1) the case context and (2) the case study research methodology.

5.1 Case context

The setting for this multiple-case study will be the OFD industry. The OFD industry is an excellent empirical environment for analyzing competitive strategies of platform-based ecosystems for several reasons. First, in the OFD industry multiple rival platform-based ecosystems coexist (or did so in the past), such as Lieferando, Lieferheld, Foodora, Pizza.de and Deliveroo in Germany. Hence, longitudinal comparison between heterogenous ecosystem strategies is possible. Second, some markets, such as Germany or the Netherlands, are at a mature state, with only some if not one platform-based ecosystem surviving (e.g., in Germany only Lieferando still operates in the market). This allows ex-post analysis of the industry’s losers as well as winners. Third, because the OFD industry has become a central part of many people’s life’s, and experiences continuous strong growth, it is an interesting and important case in itself (Blumtritt, 2019; Hesselink, 2016; Malek et al., 2018). Last, many industries have been studied so far (such as video game consoles, mobile operating systems, solar industry, ride-hailing, etc.), however - to the best knowledge of the author - no study yet analyzed competitive ecosystem strategies in the OFD industry. This study explores five platforms in the German OFD industry from 2007 to 2019.

Generally, an OFD ecosystem can either be a two-sided or a three-sided market. A two-sided market involves a platform company which needs to attract both, restaurants (supply-side) and customers (demand-side) concourrently. Some OFD ecosystems represent three-sided markets in that a platform company not only facilitates exchange between restaurants and customers, but also employs and coordinates delivery riders. Consequently, platform delivery riders become an essential part of the ecosystem. In contrast, in two-sided markets, restaurants are responsible for delivering the order with their own delivery riders.

To further clarify the case, the configuration of activities and actors of the general OFD ecosystem will be described by using the four structural elements - activities, actors, links and positions - as proposed by Adner (2017). To begin with, the underlying foundation of any ecosystem is a value proposition (Adner, 2017). For OFD ecosystems, the value proposition is the convenient and time-efficient provision of food to customers, thereby offering a large variety of tastes. Customers no longer have to plan their meals ahead, think about available restaurants in their area, browse multiple websites for the restaurant’s menu, and finally, also no longer have to order food by phone, i.e., offline ordering. All these activities are replaced through a single online interface. Ordering online represents a fundamental shift of the configuration of activities compared to the times when customers picked up their phone to order from the same restaurant repeatedly because they did not know or were too sluggish to explore the manifold opportunities of restaurants in their area. What is more: Because the historical way of ordering food offline via phone represents a bilateral relationship between a restaurant and a customer, and hence lacks multilateral interdependence, there was no need to employ the ecosystem perspective. In contrast online ordering requires the ecosystem perspective as will be explained when describing the links and positions of OFD ecosystems.

For the OFD ecosystems value proposition to materialize, a distinct set of activities is required: The restaurant and food options must be collected and presented, customer awareness must be raised, food selection by the customer must be made, order must be placed, payment must be transferred, order needs to be prepared, and order must be delivered.

Even though the fundamental activities with OFD compared to ordering offline have not changed, in a general sense, the impact of online ordering on positions and links gives rise to a new set of relationships and interactions. In contrast to ordering food offline, now, there is an intermediary between the customer and the restaurant: The platform. The platform facilitates the matching process between the two sides and controls who can participate under which conditions in the ecosystem. This created a new dynamic between the respective parties. It required the platform company to incentivize participation for customers as well as for restaurants. For customers to join the ecosystem, compared to offline ordering, either there must be less cost associated with ordering online or an added value. For example, less cost appears as customers save time when searching and browsing the menu of multiple restaurants. An added value is reached through a larger variety of restaurants that is available on the platform. Restaurants in turn will join the ecosystem when they believe they generate extra revenue by attracting additional customers via the platform, or e.g., save money through less marketing activities. As a result, the platform will only flourish as more customers and more restaurant join the ecosystem. The platform is directly dependent on the presence of restaurants and customers concurrently. In case there exist only restaurants or only customers, the value of the platform is at best marginal. Stated differently, restaurants will not be interested in joining the ecosystem if there is no customer to order with them, and customers will not join the ecosystem when there are no restaurants to order food from. Hence, there is mutual interdependence between the platform, the restaurant, and the customer. The success of all participating actors involved depends on the existence of the other.

The core actors of the OFD ecosystem represent the platform, the restaurants, and the customers. In case of an OFD ecosystem in which the platform company employs and coordinates delivery drivers itself, they are also an essential actor of the ecosystem. Taking a closer look at the participating actors reveals that payment provider, IT infrastructure provider and other service partner also belong to the OFD ecosystem. They may be essential for the ecosystem to operate, like electricity is, however, they do not have a significant role or interaction in the ecosystem. For example, involvement of a specific payment provider may be an argument for a customer’s decision to join a particular OFD ecosystem. Still, the question arises whether a customer consciously decides to stay away from an OFD ecosystem when a particular payment method is not supported. Figure 5 gives a comprehensive overview of the key actors of an OFD ecosystem, shows the positions among the actors, and their respective links and activities. The following section will explain the activities of the different actors in more depth.

The platform company is the intermediary between the customer and the restaurant. The platform company develops and operates the platform. The technical foundation of the platform most often relies on proprietary technologies. The platform also aggregates and forwards the menu provided by the restaurant to the customer through a single online interface. Vice versa, the orders and payments by the customers are directed to the restaurants. Customer payments are discounted by a commission fee based on the GMV. Furthermore, the platform handles marketing activities to acquire customers and engages in sales activities to control which restaurants are joining the ecosystem.

Restaurants provide their menu to the platform as well as prepare the orders forwarded by the platform company. They are also responsible to deliver the order to the customer. They do so via their own delivery riders or by employing the ones provided by the platform. Furthermore, restaurants may also be directly in contact with the customer if there is a customer complaint.

Customers are browsing the platform to choose their favorite restaurant and dish, place an order on the platform, may pay via the platform and give a customer rating and feedback to the restaurants via the platform.

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