Sustaining Superior Performance in Business Ecosystems: Evidence from Application Software Developers in the iOS and Android Smartphone Ecosystems

Abstract

We study the phenomenon of business ecosystems in which platform firms orchestrate the functioning of ecosystems by providing platforms and setting the rules for participation by complementor firms. We develop a theoretical framework to explain how the structural and evolutionary features of the ecosystem may shape the extent to which participating complementor firms can sustain their superior performance. The structural feature, which we refer to as ecosystem complexity, is a function of the number of unique components or subsystems that interact with the complementor's product. We incorporate the evolutionary features by considering the role of generational transitions initiated by platform firms over time as well as the role of complementors' ecosystem-specific experience. Evidence from Apple's iOS and Google's Android smartphone ecosystems supports our arguments that higher ecosystem complexity helps app developers sustain their superior performance, and that this effect is stronger for more experienced firms. In contrast, platform transitions initiated by Apple and Google make it more difficult for app developers to sustain their performance superiority, and that this effect is exacerbated by the extent of ecosystem complexity. The study offers a novel account of how the performance of complementor firms in platform-based business ecosystems may be shaped by their ecosystem-level interdependencies. ABSTRACTWe study the phenomenon of business ecosystems in which a platform firm orchestrates the functioning of the ecosystem by providing a platform and setting the rules for other complementor firms to participate in it. We develop a theoretical framework to explain how the structural and evolutionary features of the ecosystem may shape the extent to which participating complementor firms can sustain their superior performance. The structural feature, which we refer to as ecosystem complexity, is a function of the number of unique components or subsystems that interact with the complementor's product. We incorporate the evolutionary features by considering the role of generational transitions initiated by platform firms over time as well as the role of complementors' ecosystem-specific experience. Evidence from Apple's iOS and Google's Android smartphone ecosystems supports our arguments that higher ecosystem complexity helps app developers sustain their superior performance, and that this effect is stronger for more experienced firms. In contrast, platform transitions initiated by Apple and Google make it more difficult for app developers to sustain their performance superiority, and that this effect is exacerbated by the extent of ecosystem complexity. The study offers a novel perspective on how the performance of complementor firms in business ecosystems may be shaped by the rules and actions of the central platform firms.2

Demand Heterogeneity in Platform Markets: Implications for Complementors

“…Research addressing demand for complementary goods is still sparse and has mostly focused on the role of network externalities and competition (Boudreau 2012, Boudreau andJeppesen 2015) or on the effects of product characteristics (e.g., Eckhardt 2016, Kapoor and Agarwal 2017, Yin et al 2014. Our work builds on this emergent but growing body of literature by investigating how changes in the composition of the installed base affect demand for complementary goods.…”

“…Recent research has also begun to explore how network externalities affect competition within platforms, or between producers of complementary goods (Boudreau 2012, Boudreau and Jeppesen 2015, Kapoor and Agarwal 2017, Yin et al 2014. 2 The primary intuition is that the size of the platform's installed base-the number of consumers who have adopted the platform-positively relates to demand for complementary goods, as there is a larger potential market for complementors to pursue.…”

Platform Architecture and Quality Trade-offs of Multihoming Complements

“…This rests on the idea that the larger the number of unique components interacting with a complement (Kapoor and Agarwal 2017), and the higher the interdependence between system components that cannot be easily abstracted by standardized interfaces (Baldwin and Clark 2000;Sorenson et al 2006), the more complex the system. Modular architectures reduce complexity by decomposing the product into independent (i.e., loosely coupled) components interconnected through pre-specified interfaces (Baldwin and Clark 2000;Schilling 2000;Yoo et al 2010).…”

“…Platforms differ in their technological performance and complexity for complementors (Baldwin and Woodard 2009;Anderson et al 2014). Platform complexity, as we define it, refers to the number of interdependent components of the platform's core technology that interact with the platform's complements through specialized interfaces (Baldwin and Clark 2000;Kapoor and Agarwal 2017). The greater the interdependencies among programming tasks and the core technology components (e.g., processor cores), and the larger the number of specialized processors requiring a specific programming language for optimal utilization (i.e., no clean interface to handle the interdependencies), the more complex the platform.…”

Business ecosystem research agenda: more dynamic, more embedded, and more internationalized

“…Platform research has been extended into several streams, including pricing structure over supply and demand (Armstrong 2006), platform competition (Zhu and Iansiti 2012), suppliers' technology strategy (Cusumano 2010) and customers' multi-homing strategy (Landsman and Stremersch 2011), as well as some social issues in the platform (Suarez 2005). Furthermore, various complementors besides the focal firm with the platform have been studied in order to identify the determinants of successfully nurturing a platform-based ecosystem (Boudreau and Jeppesen 2015;Kapoor and Agarwal 2017;Pierce 2009). …”