Developing a Model for the Adoption of Generative Artificial Intelligence in Marketing Decision-Making and Business Development in Companies

Document Type : Original Article (Mixed)

Author

Department of Information Technology Management, SR.C., Islamic Azad University, Tehran, Iran.

10.22034/jvcbm.2026.590334.1786
Abstract
The rapid advancement of artificial intelligence (AI) technologies and the increasing role of data in organizational decision-making have made AI adoption in supply chain management an important research topic. This study examines the factors affecting managers’ behavioral intention to use AI in supply chain decision-making. The Unified Theory of Acceptance and Use of Technology (UTAUT) was adopted as the theoretical framework and extended by incorporating information quality, perceived privacy, and uncertainty avoidance. This applied study employed a descriptive-survey design. Data were collected from 384 managers and experts in companies located in Tehran using a structured questionnaire and analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS. The results indicated that performance expectancy, effort expectancy, peer influence, facilitating conditions, information quality, perceived privacy, and uncertainty avoidance all had significant positive effects on behavioral intention. Among these factors, uncertainty avoidance and information quality showed the strongest effects. The findings highlight the importance of reducing uncertainty and providing accurate, reliable information to facilitate AI adoption in supply chain management.

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Articles in Press, Accepted Manuscript
Available Online from 21 December 2026

  • Receive Date 08 May 2026
  • Revise Date 16 July 2026
  • Accept Date 03 August 2026