Future of Work and Digital Management Journal 3092-720X In Press 2027 03 01 Identifying the Dimensions and Components of Smart Manufacturing Systems in the Automotive Industry: Emphasizing the Application of Artificial Intelligence and the Internet of Things Identifying the Dimensions and Components of Smart Manufacturing Systems in the Automotive Industry: Emphasizing the Application of Artificial Intelligence and the Internet of Things 1 16 EN Journal Article 2026 06 13 <table> <tbody> <tr> <td> <p>The present study aimed to identify the dimensions and components of smart manufacturing systems in the automotive industry with an emphasis on the application of Artificial Intelligence (AI) and the Internet of Things (IoT), and to develop a comprehensive implementation model based on the perspectives of industry and academic experts. This study was conducted using a qualitative exploratory approach. Participants consisted of 14 experts from the automotive industry and academia who were selected through purposive sampling based on their expertise in smart manufacturing, Industry 4.0 technologies, artificial intelligence, industrial automation, and digital transformation. Data were collected through semi-structured, in-depth interviews and analyzed using thematic analysis with the support of MAXQDA 2020 software. The coding process was performed in two iterative stages, including initial and secondary coding. Through continuous comparison, refinement, and integration of codes, 84 unique open codes were extracted and subsequently organized into axial categories and higher-order themes. To ensure rigor and trustworthiness, member checking, peer review, and audit trail procedures were employed throughout the analytical process. The findings revealed a comprehensive paradigm model for the implementation of smart manufacturing systems in automotive parts manufacturing. The model identified two major causal conditions, including domestic and international competitive pressure and infrastructural, functional, and technological challenges. Contextual conditions comprised human resources, skills and organizational culture, as well as economic and implementation considerations. Intervening conditions included cybersecurity and risk management, and system quality and reliability. Four major strategic dimensions were identified, namely advanced automation and robotics, artificial intelligence-driven data analytics, Industrial Internet of Things (IIoT) and connectivity development, and smart supply chain and logistics management. The implementation of these strategies was found to result in structural and functional improvements, economic efficiencies, enhanced customer orientation, production flexibility and personalization, and the development of management and technological knowledge. Collectively, the findings demonstrated that successful smart manufacturing implementation requires the integrated alignment of technological, organizational, strategic, and human-resource factors. The study provides a holistic framework for understanding and implementing smart manufacturing systems within the automotive industry. The proposed model demonstrates that artificial intelligence and Internet of Things technologies function as central enablers of intelligent production environments, but their effectiveness depends on organizational readiness, technological infrastructure, cybersecurity capabilities, and strategic management support.</p> </td> </tr> </tbody> </table> https://journalfwdmj.com/index.php/fwdmj/article/download/280/290