Inhaltszusammenfassung

<span style="color: #333333">Environmentally oriented business models (EBMs) enable environmental entrepreneurs (EEs) to pursue economic viability while generating positive environmental impact. Generative artificial intelligence (GenAI) could transform such models through efficiency and innovation, yet it may also undermine their sustainability value through resource demands and social risks. Despite this tension, we know little about how EEs use and perceive GenAI concerning their dual miss...<span style="color: #333333">Environmentally oriented business models (EBMs) enable environmental entrepreneurs (EEs) to pursue economic viability while generating positive environmental impact. Generative artificial intelligence (GenAI) could transform such models through efficiency and innovation, yet it may also undermine their sustainability value through resource demands and social risks. Despite this tension, we know little about how EEs use and perceive GenAI concerning their dual mission. Drawing on qualitative data from 128 German EEs, we combined thematic analysis, hierarchical clustering, and co-occurrence analysis to identify five roles of GenAI in EBMs: (1) seldom-used tool, (2) marketing content producer, (3) core green activity booster, (4) assistive sparring partner, and (5) growth accelerator. Across these roles, EEs reported challenges related to technical immaturity, unclear benefits, regulatory uncertainty, biases, and environmental harm, and its missing specialization in dual mission contexts. We develop three propositions on the tensions of GenAI for the dual mission of EBMs.</span>» weiterlesen» einklappen

Autoren