Unlocking the value from car data: A taxonomy and archetypes of connected car business models

被引:0
|
作者
Felix Sterk
Alexander Stocker
Daniel Heinz
Christof Weinhardt
机构
[1] Institute of Information Systems and Marketing (IISM) at the Karlsruhe Institute of Technology (KIT),
[2] Virtual Vehicle Research GmbH,undefined
来源
Electronic Markets | 2024年 / 34卷
关键词
Business models; Connected cars; Data monetization; Taxonomy; Archetypes; Cluster analysis; O3; L8;
D O I
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中图分类号
学科分类号
摘要
The automotive industry is relocating from viewing cars as standalone products to an all-encompassing ecosystem built around connected cars enabling data-driven business models. The vastly increasing amount of data collected by connected cars grants a unique driving experience for its users while providing companies operating in the automotive industry access to valuable information and, ultimately, cost and revenue benefits. In this article, we develop an empirically and theoretically grounded taxonomy of data-driven business models in the connected car domain to explore the impact of car connectivity and data availability on business models. Building on this, we conduct a cluster analysis revealing seven business model archetypes for the connected car domain: data platforms, location-based services, fleet management, diagnostics and maintenance, driving analytics, cyber-physical protection, and connected infotainment. Our findings advance the theoretical knowledge of data-driven business models, provide researchers with a systematic analysis of connected car-enabled business models, and enable decision-makers to identify strategic opportunities for leveraging connected car technology to enrich their business portfolios.
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