Paper Number
2402
Paper Type
Complete Research Paper
Abstract
The development and implementation of Data-Driven Business Models (DDBM) have proven to be complex and challenging endeavors, requiring collaboration among various types of actors, that is Data Providers, Data Facilitators, and Data Users. We address the current lack of research on the complex interactions and dependencies among these actors through a qualitative-explorative case study in the automotive and public sector. In total, we conducted 19 interviews with an European Data Facilitator and associated organizations. Using the Resource Dependence Theory (RDT) as a theoretical lens, we identify six patterns of dependence among the actors and three major strategies for managing these dependencies. Additionally, we find that the interactions show different levels of complexity and the Data Facilitator being the most dependent actor. Thus, we contribute to an emerging research stream and provide practical implications for DDBMs.
Recommended Citation
Bellin, Pepe; Homner, Norbert; Mertes, Dominik; Fielt, Erwin; and Matzner, Martin, "Data Facilitator in a Squeeze? Patterns of Dependence in Data-Driven Business Models" (2024). ECIS 2024 Proceedings. 1.
https://aisel.aisnet.org/ecis2024/track11_dss/track11_dss/1
Data Facilitator in a Squeeze? Patterns of Dependence in Data-Driven Business Models
The development and implementation of Data-Driven Business Models (DDBM) have proven to be complex and challenging endeavors, requiring collaboration among various types of actors, that is Data Providers, Data Facilitators, and Data Users. We address the current lack of research on the complex interactions and dependencies among these actors through a qualitative-explorative case study in the automotive and public sector. In total, we conducted 19 interviews with an European Data Facilitator and associated organizations. Using the Resource Dependence Theory (RDT) as a theoretical lens, we identify six patterns of dependence among the actors and three major strategies for managing these dependencies. Additionally, we find that the interactions show different levels of complexity and the Data Facilitator being the most dependent actor. Thus, we contribute to an emerging research stream and provide practical implications for DDBMs.
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