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Title Sowing the seeds for sustainability: A business model innovation perspective on artificial intelligence in green technology startups
ID_Doc 30541
Authors Jorzik, P; Antonio, JL; Kanbach, DK; Kallmuenzer, A; Kraus, S
Title Sowing the seeds for sustainability: A business model innovation perspective on artificial intelligence in green technology startups
Year 2024
Published
DOI 10.1016/j.techfore.2024.123653
Abstract In today's data-driven era, ubiquitous concern about environmental issues pushes more startups to engage in business model innovation that promotes environmentally friendly technologies. The goal of these startups is to create technology-based products and services that enhance environmental sustainability. In this context, artificial intelligence promises to be a key instrument to create, capture, and deliver value. However, the existing literature lacks a deep understanding of how startups using AI innovate their business models to achieve a positive environmental impact. Therefore, this paper investigates how green technology startups utilize AI from a business model innovation perspective for environmental sustainability. We conduct a qualitative, exploratory multiple-case study using the Eisenhardt methodology, based on interview data analyzed using qualitative content analysis. We derive five predominant manifestations for AI-driven business model innovation and identify archetypical connections between business model dimensions. Further, we establish three overarching archetypical associations among the cases. In doing so, we contribute to theory and practice by providing a deeper account of how green technology startups attempt to maximize their positive environmental impact through AI. The results of this study also highlight how business model innovation driven by AI can support society in securing a more environmentally sustainable future.
Author Keywords Business model innovation; Artificial intelligence; Green technology startups; Sustainability; Entrepreneurship; Startups
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Social Science Citation Index (SSCI)
EID WOS:001301206000001
WoS Category Business; Regional & Urban Planning
Research Area Business & Economics; Public Administration
PDF https://doi.org/10.1016/j.techfore.2024.123653
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