Date of Conferral

2023

Degree

Doctor of Business Administration (D.B.A.)

School

Information Systems and Technology

Advisor

Betsy Macht

Abstract

Small- and medium-sized enterprise (SME) manufacturing executives and managers are concerned with the rapid technological changes involving artificial intelligence (AI), machine learning, and big data. To compete in the global landscape, effectively managing digital and artificial intelligence changes among SME manufacturing executives and managers is critical for leaders to compete in 2023 and beyond. Grounded in the dynamic capabilities view theory, the purpose of this quantitative correlation study was to examine the relationship between strategic dexterity, absorptive capacity, and competitive advantage. The participants were 66 executives and managers of SME manufacturing organizations who use big data and analytics daily and agreed to complete the AI Analytics Survey Questionnaire using Wu et al.’s survey. The results of the multiple linear regression were significant F(2, 63) = 54.29, p < .001, R2 = .63. In the final model, both predictors were significant: strategic dexterity (t = 2.48, p = .02, ß = .391) and absorptive capacity (t = 2.61, p = .01, ß = .439). A key recommendation is for SME manufacturing executives and managers to understand how to integrate, build, and orchestrate their strategic digital assets when implementing absorptive capacity strategies within their organization. The implications for positive social change include the potential to provide SME manufacturing executives and managers with an understanding of how these technologies can be integrated into the future of data analytics and automation, the support towards a digital economy, and the social effects of artificial intelligence on the underserved and underrepresented groups.

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