This research explores how artificial intelligence's (AI’s) distinct capabilities (interactivity, autonomy, inscrutability and abstraction), manifested as unique characteristics, impact decision-making in resource-limited social entrepreneurship, assessing their effect on competitive advantage with resource allocation as a key moderator. By analyzing such tensions, this research aims to bridge critical gaps in understanding how emerging technologies influence decisions in social entrepreneurship.
By adopting a dual theoretical framework (next-generation perceived characteristics of innovations [PCI] and resource-based view), this research employs a quantitative empirical approach by gathering data through e-surveys (n = 269) from a professional database and two prominent conferences in AI and social entrepreneurship.
Linear and nonlinear relationships among AI characteristics and decision-making emerge, with the potential for moderation effects influenced by resource allocation.
This research makes four key contributions: empirically examining how distinct AI capabilities, manifested through unique characteristics, influence decision-making in the social entrepreneurship context; conceptually introducing “abstraction” as a novel AI capability; theoretically integrating the next-generation PCI framework with the resource-based view for a novel theoretical lens and practically developing a calibration graph as a “prototype” tool to quantify AI abstraction for resource-limited social entrepreneurship, thus potentially enabling optimal decision-making and consequently competitive advantage.
