Generative AI Integration and Managerial Decision-Making Quality in Emerging-Economy SMEs: Evidence from Istanbul Using PLS-SEM, NCA, and fsQCA
DOI:
https://doi.org/10.63556/tisej.2026.1963Keywords:
Generative AI, Managerial decision-making quality, TOE-TAM framework, Necessary Condition Analysis, fsQCAAbstract
Policy across the emerging world presses small and medium-sized enterprises toward generative artificial intelligence (GenAI), yet enthusiasm has run ahead of firm evidence that channeling managerial reasoning through such tools sharpens the decisions firms actually make. The distinction anchoring the analysis is between holding access to GenAI and weaving it substantively into how managers think; the latter, the depth of integration into managerial cognition, is modeled here as the conduit translating enabling conditions into decision quality within emerging-economy SMEs. Responses from 312 owner-managers and senior managers of Istanbul SMEs are examined through an integrated TOE-TAM lens joining PLS-SEM with Necessary Condition Analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA). Depth of integration drives decision quality (β = 0.612) and process innovation performance (β = 0.574) alike. Top management support and perceived usefulness behave as necessary conditions, each carrying an empirical floor (42% and 38%) beneath which high decision quality never materializes, while three sufficient configurations reach that outcome by separate routes.
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