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Orchestrating a Platform Ecosystem. The Effects of Platform Control on Platform Performance

©2018 Seminararbeit 38 Seiten


This paper examines the effects of control mechanisms on a platform. First, the theoretical background of important terms in this field is given to gain a common understanding, which is necessary for classification as well as results. In this thesis, platforms are defined as products and services, which bring together user groups and enable transactions between the groups by providing infrastructure to do so. Second, literature dealing with this field of study is processed to provide a comprehensive and transparent overview about current research, including the platform type, dependent variables, and findings.

Input, output, process, clan, self-control, as well as open and closed platforms, rules & values and boundary resources are identified as the most relevant control mechanisms. Thereby the first research question what types of control mechanisms are discussed in literature, is answered. The findings then are analyzed for these different types of control to address the remaining research questions how control mechanisms effect platforms and when this is useful. It can be pointed out that most mechanisms go along with advantages and disadvantages, as theory suggests. Thus, decision makers have to be clear about the goal they want to achieve when changing platform governance or control to use these effects for their advantage. If a platform aims at optimizing e.g. the degree of openness, this depends on the question: what is optimal for the platform?

As ecosystems typically face the trade-off between quality (e.g. apps) and quantity (e.g. number of users), platform owners have to strategically position the platform somewhere along this continuum. The finding that some control mechanisms are superior to others for achieving certain goals, however, can directly be beneficial to managers. Also, the methods applied by the studies are analyzed, coming to the conclusion that case studies represent the predominant method in this field. Lastly, the results are discussed, contributions and limitations of this work are considered. Also, shortcomings and research gaps in this field are highlighted and future research areas are exemplified. Especially the conduction of an event study and adopting a more strategic approach are intriguing for a master thesis to fully cover the implications of managers’ decision regarding platform ecosystems.


Table of Contents

List of Figures

List of Tables

1 Introduction

2 Theoretical Foundation
2.1 Platform and platform ecosystems
2.2 Network effects
2.3 Control and governance mechanisms
2.4 Governance challenges

3 Methodology

4 Results
4.1 Literature classification
4.2 Summary of research findings
4.2.1 Effects of input control
4.2.2 Effects of output control and process control
4.2.3 Effects of clan control and self-control
4.2.4 Effects of opening a platfomi
4.2.5 Effects of boundary resources
4.3 Analysis of methods used in literature

5 Discussion

6 Conclusion


Appendix A: Results of the literature review process

Appendix B: General overview about identified literature

Appendix C: Classification of literature based on researched control mechanism

List of Figures

Figure 1 ะ The players in a platform ecosystem in Pipelines, Platforms, and the New Rules of Strategy (Harvard Business Review, 2016, p. 6)

Figure 2: Classification of control based on control theory

List of Tables

Table 1: Overvieพ about dimensions of platform orchestration. Own representation based on Hein et al, 2016, p.4

1 Introduction

More than four years ago, The Economist wrote “Proliferating digital platforms will be at the heart of tomorrow’s economy, and even government” (The Economist, 2014). This shows the importance of platforms in today’s world, which is also proofed by the fact that Apple, Google, and Microsoft lead the ranking of the most innovative companies published by The Boston Consulting Group (Ringel, Zablit, Grassi, Manly, & Möller, 2018). The commonality between these three big players and other companies in the ranking such as Facebook, Uber, Alibaba, and AirBnB - all of which are ranked within the top 15 most innovative companies - is that their business model is either based on a platfomi or substantial parts of the business model rely on a platform. Additionally, together with Facebook the three most innovative companies form also the peak of the world’s most valuable brands (Forbes, 2017). One reason for the success of these companies, most of which have been founded within the last two decades, is that platforms allow to overcome entry barriers and are increasingly used in the sharing economy, which is essentially about reciprocally borrowing items. Hereby, orchestrating the platform plays a decisive role for its value maximization, as orchestration mechanisms guard the platform against threats but also constrain production and consumption by defining which parties are allowed to enter the platform and what these parties are allowed to do (Van Alstyne, Parker, & Choudary, 2016).

Although many of the most valuable and most innovative companies are platfomi based, research on this topic is missing and encouraged by researchers. Tiwana et al. (2010) cite six reasons, why platforms “present a significant challenge and opportunity for infomiation systems research” (Tiwana, Konsynski, & Bush, 2010, pp. 676-677). One of these is tackled in this thesis and concerns that governing a platfomi successfully is only possible by precisely balancing control and autonomy. Additionally, Goldbach and Kemper (2014) claim that investigating control mechanisms in ecosystems is an amply area for future research. One area concerns control of key platfomi components to gain competitive advantage (Yoo, Henfridsson, & Lyytinen, 2010). Manner et al. (2012) suggest a similar topic for the research agenda to gain an understanding of how governance and control mechanisms should be matched with the platfomi. Finally, even though orchestrating platforms has obtained some attention, there is little known about concrete effects (Maurer & Tiwana, 2012; Song, Xue, Rai, & Zhang, 2017). Being knowledgeable about these effects, however, is critical to adequately account for common trade-offs associated with controlling a platform and thus for choosing the most suitable mechanisms (Wareham, Fox, & Cano Giner, 2014).

This seminar thesis aims at reviewing the current platform literature and providing a comprehensive framework in this field based on Webster and Watson (2002) in order to answer the questions (i) which mechanisms to orchestrate a platform are discussed in literature? (ii) How do these mechanisms affect the platform? And (iii) in which situation is this impact useful?

The paper begins with theoretical backgrounds of central temis of this thesis, namely platforms, platfomi ecosystems, network effects and control mechanisms. This section does not only provide definitions but also covers central challenges of governance mechanisms in the context of platforms in order to give an understanding of the problems and tensions platfomi owners face. Afterwards, the underlying methodology of this paper is introduced. Thereafter, the result section gives an overview about the different research findings of governance mechanisms’ effects on platforms. Based on these findings, implications for the business world are discussed, research gaps are identified, and promising avenues for future research are highlighted. Finally, the conclusion summarizes the insights gained.

2 Theoretical Foundation

Since this thesis uses terminology, which is quite technical and lacks a commonly agreed definition, the following section provides the theoretical foundation in order to have a conmion understanding of the terminologies.

2.1 Platform and platform ecosystems

Technically speaking the notion platform is “the extensible codebase of a software-based system that provides core functionality shared by apps that interoperate with it, and the interfaces through which they interoperate” (Tiwana, 2014, p. 7). The defining characteristic is a set of components that enables and strengthens variety and evolvability of a system by restricting the connections among other components of the system (Baldwin & Woodard, 2009). In general, however, platforms are products and services, which can take various shapes, including technology, mobile, application, software, or even specialized platforms, all of which have in conmion that they bring together user groups and “provide infrastructure and rules that facilitate [...] groups’ transactions [...]” (T. Eisenmann, Parker, & Van Alstyne, 2006, p. 2). This is done with the information and interactions platforms have and which constitute the source of value and the competitive advantage, platforms can create (Basóle & Karla, 2011; Van Alstyne et ah, 2016). Despite platforms’ huge potential to strongly increase value, there is an inevitably major driver, which is the ecosystem that surrounds the platform and that shapes most of its utility. This ecosystem consists of the platfomi itself and complementary apps (Tiwana, 2014). Even though there are different types of platforms, their ecosystems all have the same structure and consist of the same players, namely owners, providers, producers, and consumers (Van Alstyne et al, 2016). Figure 1 defines their roles and highlights their relationships.

What can also be seen in Figure 1 is that there is data exchange between producers and consumers, which is central to every successful platfomi as will be explained in chapter 2.2. Furthermore, the size of the ecosystem mainly depends on these two groups, as owner and providers only supply the infrastmcture of a platfomi.

Abbildung in dieser Leseprobe nicht enthalten

Figure 1 ะ The players in a platform ecosystem in Pipelines, Platforms, and the New Rules of Strategy (Harvard Business Review, 2016, p. 6)

2.2 Network effects

The above-mentioned data exchange between consumers and producers is the central reason why these parties are attracted to each other. In consequence, as the size of these groups increases, the value of the platfomi increases; this phenomenon is called network effect and describes a situation in which the value of a platfomi to an user depends to a significant amount on the other side of the network (Katz & Shapiro, 1985, 1994; G. G. Parker & Van Alstyne, 2005; Van Alstyne et ak, 2016). In consequence, to stimulate network effects, a platfomi must be able to attract consumers to gain more producers and vice versa (Wessel, Thies, & Benlian, 2017). Network effects can be split up in those that benefit the user side and those that benefit the platfomi side and accordingly network effects are not necessarily symmetric (Song et ah, 2017). Such an asymmetry could also occur, because the value created by the platfomi and the value captured by network users are not necessarily equal and even if they are, the asymmetry could also be a temporal one, meaning the value is captured long-temi but not short- temi (Song et ah, 2017).

2.3 Control and governance mechanisms

Governing a platfomi is central to ensure that the interplay between all participants is in the best interest of the platfomi owner. There are several approaches to control or orchestrate platforms. The following section introduces the predominant concepts to categorize control mechanisms, elucidates the most important ones, and provides an overview of platfomi owners’ options.

Many authors use the fundamentals of control theory to distinguish between control mechanisms (Goldbach, Benlian, & Buxmann, 2017; Goldbach & Kemper, 2014; Maurer & Tiwana, 2012; Mukhopadhyay, De Reuver, & Bouwman, 2016; Tiwana et al., 2010; Wessel et al., 2017). Control theory differs between fomial and informal control. Formal control consists of process, output, and input control and informal control includes clan and self-control (Maurer & Tiwana, 2012; Ouchi, 1979). Figure 2 illustrates the relations of these control types.

Abbildung in dieser Leseprobe nicht enthalten

Figure 2: Classification of control based on control theory

Output control refers to the practice of rewarding one party for achieving a certain prespecified performance target, whereas in process control such targets are not given, but certain procedures and methods must be followed (Goldbach et al., 2017; Kirsch, Sambamurthy, Ko, & Purvis, 2002; Wessel et al., 2017). Input control describes the selection of partners, which have a certain attribute or can provide desired resources (Mukhopadhyay et ah, 2016). Clan control is characterized by the commitment of different group member to mutual goals and self-control refers to the commitment of individuals to their own goals (Ouchi, 1979).

As illustrated in Table 1 below, one of the most prominent examples of process control is a predefined development and publishing procedure for applications in mobile ecosystems. When a platform owner wants to control the output, differentiated revenue share agreements with developers would be one way to do so and finally input can be controlled by restricting access to platforms, e.g. only allowing a certain subgroup that fulfills specific criteria to enter the platfomi (Mukhopadhyay et ah, 2016). An example for self-control would be giving developers’ more freedom to decide on an applications’ functionality and tools for developing these applications (Goldbach et ah, 2017). Clan control could be exerted by giving developers a collective goal to ensure there is no incentive to gain advantage over another developer (Maurer & Tiwana, 2012).

Another predominant way to establish a differentiation between control modes is to distinct between open and closed platforms (Benlian, Hilkert, & Hess, 2015; Boudreau, 2010; T. R. Eisenmann, Parker, & Van Alstyne, 2008; Ondrus, Gannamaneni, & Lyytinen, 2015; G. Parker & Van Alstyne, 2017, 2008). Hereby, Boudreau (2010) suggests two ways to open a platform, either granting other firms access to the platfomi to allow complementary innovation around the platform or giving up some control over the platfomi. Eisenmann et al. (2008) have a different understanding and define open as not restricting the platform's participation, development, or use or restricting in a reasonable, non-discriminatory way, as also can be seen in Table 1.

A less dominant, yet valuable classification resulted from a literature review conducted by Hein, Schreieck, Wiesche and Kremar (2016) revealing six dimensions of platfomi governance: governance stmcture, resources & documentation, accessibility & control, tmst & perceived risk, pricing, and external relationships. This classification extends the dominant clustering introduced earlier, as these classical categories only reappear in the dimension accessibility & control. Moreover, platfomi owners can also use a more subtle and indirect way to orchestrate their platfomi by pricing, managing external relations, strengthening tmst, or by changing the degree of transparency (Hein, Schreieck, Wiesche, & Kremar, 2016; Schreieck, Wiesche, & Kremar, 2016). Inspired by their approach to differentiate between controlling mechanisms, the present paper establishes own dimensions for those mechanisms presented in depth in the results section so that managers’ influence options become sharper. Additionally, this clustering underlines that platfomi owners can govern several parts of their platfomi. However, the result section is built upon the individual mechanisms and not the dimensions. These dimensions are illustrated in Table 1 and only consist of those control mechanisms central for this thesis so that the overview about different control mechanisms does not go beyond the scope of a brief introduction in the theoretical background.

Abbildung in dieser leseprobe nicht enthalten

Table 1: Overview about dimensions of platform orchestration. Own representation based on Hein et ah, 2016, p.4

The first dimension chosen is governance, it includes rules and values of a platform, as well as informal control modes, such as self- and clan control. All of these are assigned to the same class, because in contrast to other mechanisms, there is no explicit and sharp mechanism in place to constantly monitor the platform (Huber, Kude, & Dibbem, 2017). The second dimension, accessibility, consists of all mechanisms that somehow restrict access to the platform by certain criteria or limiting the extent of control parties other than the platfomi owner have. These mechanisms ensure that the quality of platforms does not suffer from e.g. a bulk of new applications with poor or flawed usability or functionality. The third major category is control and encompasses those mechanisms within the platform. Which is to say mechanisms that govern platform content and processes. These mechanisms concern all members that successfully entered the platform.

Summarizing this chapter, it becomes clear that platforms can be controlled, governed, and orchestrated in various ways. Having a variety of options, however, is not necessarily beneficial to platform owners, as every intervention in a platform has the potential to be harmful or even value destructive. Therefore, before establishing or changing the governance of ones’ platfomi, the party in charge must be aware of the trade-offs associated with governing the platform in order to consider advantages and disadvantages as discussed in the following chapter.

2.4 Governance challenges

A central challenge of platform governance is to retain sufficient control to ensure the quality of the platfomi and simultaneously surrender enough control to foster innovation by producers or developers (Boudreau, 2010; Tiwana et ah, 2010). This tension is also described by Wareham et al. (2014), who argue that the challenge of designing the platfomi governance is to “appropriately bound participant behaviour without excessively constraining the desired level of generativity” (Wareham et ah, 2014, pp. 1195-1196). Hereby, a generative system can create new output without getting input from any source. This argument has been highlighted in literature frequently, referring to the need of technology ecosystems to be stable and evolvable at the same time (Wareham et ah, 2014). It is closely connected to the decision, whether the platfomi should be open or closed, and identically, considering that an open platfomi could increase the network effects or reduce user’s concern to be locked-in in the platfomi, meaning they cannot easily leave the platfomi and enter another, opening a platfomi also reduces users’ switching costs and increases competition (G. Parker & Van Alstyne, 2008). Besides this stability-evolvability trade-off, three others have been identified by Wareham et al. (2014): standard-variety, control-autonomy, and collective- individual. The first one refers to the output of platforms: while interfaces of the platfomi remain stable, other parts, even core components need to change over time. Control-autonomy refers to the actors of platforms, arguing that even though a larger number of developers can be beneficial and increase the speed of innovation, too much unsupervised developers could also cause agency-costs or reduce the platfomi’ร quality. Finally, the last tension deals with the identification of complementers: governance must not only incentivize individuals to deliver a good service or product to the platfomi but also provide an incentive for members to work together and create complementary innovation (Wareham et ah, 2014).

3 Methodology

The present paper deals with the impact of orchestrating platforms on several factors, such as innovation, revenue, perfomiance, or network effects. Originally, the focus was limited on the effect on network effects but has been extended towards a wider range of variables. This is, because on the one hand other factors could represent indirect effects on network effects, such as an increase in revenue, caused by an increase in users, or an increase in innovation, caused by a growing number of developers. And on the other hand, these variables characterize a successful platform.

To guarantee that for this 22-page thesis the largest possible amount of literature has been identified and taken into consideration, a structured approach reconmiended by Webster and Watson (2002) has been applied. Since infomiation systems are an interdisciplinary field, various journals from different areas of expertise were consulted to create this thesis. However, the “basket of eight”1, including the leading journals in the field of infomiation systems has been the origin of the literature review. The databases of those journals have been searched for keywords, starting with central temis such as “platform governance” to more specific ones as “impact of control on platfomi ecosystems” as can be comprehended in Appendix A.

It can also be seen in Appendix A that the category “Further Journals” consists of bundles of journals to preserve clarity and transparency. The bundle “Infomiation Systems” consists of further journals in this field that do not belong to the basket of eight. “Management & Organization” consists of journals such as “Organization Science” and “Management Science”. The last bundle “Business & Economics” includes journals such as the “Journal of Economic Perspectives”. These bundles of journals have been identified by adding fundamental articles, which have been quoted by most of the papers in the basket of eight. The last category of sources covers the


1 The “basket of eight” consists of the journals MIS Quarterly (MISQ), Information Systems Research (ISR), Information Systems Journal (IS J), Journal of Information Technology (JoIT), Journal of Management Information Systems (JoMIS), Journal of Strategic Information Systems (JoSIS), Journal of the Association for Information Systems (JoAIS), and European Journal of Information Systems (EJoIS).


ISBN (eBook)
ISBN (Paperback)
Institution / Hochschule
Universität Mannheim
2018 (November)
orchestrating platform ecosystem effects control performance

Titel: Orchestrating a Platform Ecosystem. The Effects of Platform Control on Platform Performance