Government Support, AI Adoption, and SME Innovation Performance: An Institutional Theory Perspective
DOI:
https://doi.org/10.63808/bem.v2i1.401Keywords:
AI adoption intensity, SMEs, Innovation performance, Organizational learning capability, Organizational readinessAbstract
Artificial intelligence (AI) is increasingly central to innovation in small and medium-sized enterprises (SMEs), yet resource constraints limit their ability to exploit it. Governments worldwide provide institutional support to encourage SME AI adoption, but whether such support translates into innovation depends on internal organizational conditions that remain poorly understood. Drawing on institutional theory, this study treats government support as a source of coercive, normative, and mimetic pressure and develops an integrative conceptual model in which it influences SME innovation performance through AI adoption intensity, with organizational learning capability as a mediator and organizational readiness as a moderator. The model specifies that government support raises adoption intensity, which in turn enhances innovation performance; that organizational learning capability partially mediates this effect; and that organizational readiness strengthens the link between government support and adoption intensity. A quantitative, cross-sectional design is proposed: structured questionnaires will collect no fewer than 200 valid responses from SMEs, analyzed using partial least squares structural equation modeling (PLS-SEM). Theoretically, the study is expected to extend institutional theory from the adoption/non-adoption dichotomy to a continuous adoption-intensity construct and to position organizational learning as the channel transmitting adoption into innovation. Practically, it can inform the design of differentiated government policy and SME capability building.
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