Integrating spherical fuzzy delphi with XGBoost and GNN for multi-dimensional analysis of TQM in industry ۴.۰ transition

Industry ۴.۰ introduces not only innovative technologies but also artificial intelligence, the IoT, and robotics, while considering the context of its organismal paradigm. For Iranian Small and Medium-Sized Enterprises (SMEs), managing the maturity versus the challenge posed by constraints in economics and technology will be challenging. This study investigates the levels of readiness of Iranian SMEs for Industry ۴.۰, while evaluating and prioritizing key soft and hard Total Quality Management (TQM) factors using several advanced methods, including the Spherical Fuzzy Delphi method, Extreme Gradient Boosting (XGBoost), and Graph Neural Networks (GNNs). The soft TQM factors include, but are not limited to, leadership by senior management, employee empowerment, and teamwork, with the aim of developing a shared and adaptive culture in the organization. In contrast, hard TQM factors include instantaneous improvement, production management, and process control, focused on strong technological skills. Research in the area has self-evidently established that the softs and hards are interdependent and underscored the criticality of responding to both perspectives of readiness for Industry ۴.۰ in an integrated way. Also, interestingly, the study demonstrates GNN applications for revealing the nonlinearity of TQM factors, which provide useful insights for the dynamics of their interconnectedness. It highlights a handful of specific challenges that SMEs in Iran experience, including financial barriers and lack of infrastructure, and specific recommendations around surmounting the barriers. This research successfully fills the gap related to the specific research at hand, and also presents a comprehensive data-driven framework to facilitate policy coordination and managers' guidelines to enhance the readiness of SMEs for digital transformation. These findings pave the way toward contributing to the academics for future advances and extends to providing applied strategies to assist SMEs in seeks for success in the rapidly-changing world economy.

کلیدواژه ها:

Industry ۴.۰ readiness ، Total Quality Management ، Xgboost ، graph neural networks ، digital transformation