Understanding Ecosystem Data

Abstract

There is a growing body of empirical studies on business ecosystems. Driven by different questions these studies typically employ a wide variety of data sources -ranging from open to proprietary, structured to unstructured -that contain a broad range of entities, relationships, activities, and issues of interest. Individually, these data sources offer the ability to investigate very targeted business ecosystem questions.However, when linked and combined these data sources can potentially open up many new lines of inquiry. The purpose of this study is to provide an overview of the scope and complexity of the business ecosystem data landscape, discuss what type(s) of information is captured in them, identify how data sources overlap and differ, discuss strengths and weaknesses, and suggest new types of analyses that could be generated when combined. In doing so this study aims to help researchers and practitioners with the data identification and selection process and stimulate novel data-driven ecosystem intelligence. The study concludes with theoretical and managerial implications.

Ecosystem Intelligence for AI-based Assistant Platforms

“…The need to investigate ecosystem data in a structured way has been recognized in [23], and ecosystem intelligence has been suggested as a promising datadriven approach to understand ecosystems in [24]. Ecosystem intelligence is the structured analysis of ecosystem-related data to support decision-making, and only recently a call for more research on ecosystem intelligence was published [25]. Ecosystem-related data contains a broad range of entities, relationships, activities, and issues of interest [25].…”

“…Ecosystem intelligence is the structured analysis of ecosystem-related data to support decision-making, and only recently a call for more research on ecosystem intelligence was published [25]. Ecosystem-related data contains a broad range of entities, relationships, activities, and issues of interest [25]. Ecosystem intelligence and modeling are parts of empirical research on ecosystems reviewed in [26] and [27].…”

Introduction to the Minitrack on Managing the Dynamics of Platforms and Ecosystems

“…Then in 2020, the dynamic aspects of platforms and ecosystems gave focus to the "Managing the Dynamics of Platforms and Ecosystems" minitrack, exploring how platforms and ecosystems change, evolve, and adapt to technological, social, economic and political changes. Some of these papers took a data-centric view-offering an epistemological framework to support the coordinated use of multiple datasets in a data-driven ecosystem analysis [32], proposing a method for measuring the heterogeneity of startups' digital infrastructure [33], and identifying four archetypes of data marketplaces [34]. Strategies for organizing on and for platform ecosystems were investigated from the perspectives of organizational routines [35] and the balance of cooperation and competition [36].…”

The platform as ecosystem

“…4] and as algorithmic systems (e.g., Alaimo and Kallinikos, 2021;Alaimo and Kallinikos, 2018;Broughton Micova and Jacques, 2020). Others studied 'ecosystem data' (Basole, 2020) and social media as 'data platforms' and data-based 'service ecosystems' (Alaimo and Kallinikos, 2017;Alaimo et al, 2020).…”

“…To better understand these critical roles, it is relevant to study what the cooperation and collaboration between companies and organisations in a platform ecosystem-as materialised, for instance, in the (observable) technological (APIbased) integrations and organisational relationships-revolves around in practice. For instance, the larger ecosystem around social media revolved not just around data in general, but around the interaction and exchange of audiences-a much more specific resource that has facilitated a thriving economy of data-based tools, products, and services (e.g., Alaimo et al, 2020;Basole, 2020;[▸Chs. 3 and 4]).…”