Essays on Digital Platforms and Ecosystems

The thesis contributes to the growing literature on Digital Platform Ecosystems (DPE) evolution by integrating resource orchestration (RO), dynamic capabilities (DC), and platform classification, offering insights into how DPE develop, adapt, and sustain competitive advantage. Digital Platforms (DP) unlike traditional organisations, leverage digital technologies for continuous evolution and growth (Huang et al., 2017; Rindova & Kotha, 2001). Their architecture fosters generativity (K. J. Boudreau, 2012) and provides the foundation for innovation, adaptation and evolution (Spagnoletti et al., 2015; Yoo et al., 2012). Additionally, they cocreate value at the ecosystem level (G. Parker et al., 2017). Most of the existing studies on DPE evolution have focussed on manufacturing, digital marketplace and social media sectors and have considered various theoretical perspectives such as Complex Adaptive System (CAS), Activity System Perspective, Data-Technology Complementarities and IS Capabilities to understand the evolution mechanisms of DPE (Alaimo, Kallinikos & Valderrama, 2020; Sandberg et al., 2020; Stonig et al., 2022; B. Tan et al., 2015). As the value in DPE is co-created at an ecosystem level, understanding orchestration mechanisms involving ecosystem resources is crucial (Nambisan et al., 2017; G. Parker et al., 2017; Zeng et al., 2023) for explaining DPE evolution. Such RO mechanisms have not been explored much in DPE evolution context (Zeng et al., 2023). The first paper of this thesis examines the DPE evolution mechanism building on resource orchestration (RO) perspective, emphasizing the role of technologies in this process. I did a case study on MoMo which is a leading payment platform in Vietnam and has evolved into a wide spanning DPE. RO literature has mostly focussed on the internal resources of firm and explain structuring, bundling and leveraging resources as the processes that managers adopt for efficient and effective utilisation of resources to gain competitive advantage and create value (Sirmon et al., 2007, 2011). Recent research extends RO perspective to an ecosystem level indicating that interaction of internal and external resources shape scaling mechanisms (Zeng et al., 2023). I build on RO perspective to explain the mechanism of DPE evolution in finance sector in a developing economy focussing on the role of technologies. I explain that ICT (Information and Communication Technology), data (digital) and AI (Artificial Intelligence) play a crucial role in shaping orchestration mechanisms by enabling interactions in the ecosystem and act as key mediating resources. ICT facilitates resource building and bundling for providing solutions and financial inclusion, data enables platform structuring for scaling and growth, and AI drives resource leveraging for enhanced user experience. I introduce new sub-processes enabled by technologies to the RO framework (Sirmon et al., 2011). I also shed light on the dynamics of network effects during the DPE evolution. These were initially driven by technology, then users and thereafter data. The study explains the shifting nature of competitive advantage at various stages that are crucial for DPE evolution (D. P. McIntyre & Srinivasan, 2017; Sirmon et al., 2011). Although first paper of thesis is about management and utilisation of resources, it is extremely important to understand the development of dynamic capabilities (DC) and explaining the role of technologies to address the adaptations and successful evolution of a DPE. This paved the way for second chapter of this thesis which uses the same case of MoMo to explore the development of technology driven dynamic capabilities. Managing complex ecosystem-level interactions require firms to adapt their resources to address various challenges in their environment. DC play an important role in managing extending and adapting resources (Helfat et al., 2009). Although there is a lot of research on DC (Teece, 2012, 2017; Teece et al., 1997; Winter, 2003), only a few studies extend it to an ecosystem level (Feng et al., 2019; Haki et al., 2024; Linde et al., 2021; Teece, 2017) and the existing literature provides limited understanding of the routines and processes involved within an ecosystem context (Felin & Foss, 2012). In the second paper, I explore the development of DC in the DPE evolution context exploring the role of technologies and shed light on how these capabilities can be utilised for attaining sustainable competitive advantage. I explain that DC play an important role in DPE evolution. I also provide useful insights about technology driven DC. I found that ICT driven DPE seizing capabilities, data driven DPE sensing capabilities and AI driven DPE reconfiguring capabilities are required for the successful evolution of the DPE. The paper explains the sub-processes involved and extend the view to previous chapter elaborating that IT driven seizing capabilities are crucial for building and bundling resources whereas data driven sensing capabilities are crucial for structuring platform portfolio and AI driven reconfiguring capabilities are crucial for leveraging capabilities. These capabilities further enable the mechanisms of DPE resource acquisition, DPE resource allocation and DPE resource deployment fostering sustainable competitive advantage through development, adaptation and enhancement of value proposition leading to successful evolution of the DPE. My case setting is a payment platform that originated in Vietnam and I explained its evolution mechanism focussing on resources and capabilities. To be able to understand the DPE evolution and its patterns across industries it is extremely important to consider a static view of digital platforms. Most of the current classifications on digital platforms do not consider a static and a unifying framework of classification of digital platforms (M. Cusumano et al., 2020; Derave et al., 2024; Gawer, 2014). In the third chapter, I contribute to the literature on digital platforms by developing a classification of digital platforms on the basis of their origins. This offers a static view of digital platforms so that their true characteristics could be understood and generalised. I use the insights from existing literature and industry examples to classify platforms as commercial, social media and industrial. This would pave the way towards identifying patterns in the evolution of platforms emerging from different sectors focussing on their origins. The third chapter is aimed at building a unifying foundational classification framework of digital platforms. This taxonomy of digital platforms is based on their origins providing a static view instead of dynamic view of digital platforms. This could help to understand the pattern (in similarities and differences) in the mechanism of development of digital platform ecosystems arising from different industries. To summarize, through a case study of MoMo, a leading payment platform in Vietnam, this research identifies technology-driven resource orchestration and capability-building mechanisms in DPE evolution. Additionally, it develops a classification framework for digital platforms based on their origins, providing a static view which could be helpful to analyze evolution patterns across industries. This work advances understanding of how DPEs evolve, adapt, and sustain long-term growth.