Future of Work and Digital Management Journal 3 Serial Number 8 2025 06 23 Designing a Systemic Model of Green Technological Innovation in the Steel Industry Designing a Systemic Model of Green Technological Innovation in the Steel Industry 1 15 EN Journal Article 2025 02 01 <table> <tbody> <tr> <td> <p>The aim of this study is to design a systemic model of green technological innovation in the steel industry. The research was conducted in two phases. In the first phase, using Stafford Beer's approach and the emancipatory paradigm within a framework of team-based integration, the dimensions of the model were identified through seven key processes (initial meeting, agenda setting, topic selection, summarization, and final meeting). This phase adopted a qualitative approach, an applied orientation, an inductive method, and utilized a synchronization protocol tool (structured dialogues and feedback loops). The statistical population consisted of 30 managers, deputies, and consultants from Khuzestan Steel Company, organized into 12 teams.</p> <p>In the second phase, a five-step process was employed to quantitatively validate the model. This included designing a Likert-scale questionnaire, simple random sampling (113 out of 165 employees with at least a Master’s degree based on Morgan’s table), data collection, and statistical analysis using SMART PLS software to assess model fit, validity, and reliability. This phase used a deductive approach, quantitative method, and confirmatory factor analysis. Model validity in the first phase was confirmed through alignment with Stafford Beer's approach, and in the second phase through face and content validity methods (CVR and Lawshe’s coefficient). Reliability in the first phase was ensured through process robustness and in the second phase through Cronbach’s alpha (0.795). Twelve key indicators were identified: energy management, waste management, greenhouse gas reduction, water efficiency, innovation in production processes, green product design, sustainable raw material supply, environmental management, training, investment in research and development, health and safety, and social responsibility. Confirmatory factor analysis showed that all indicators have high validity and are significantly related to green innovation. Waste management (beta coefficient = 0.713) had the strongest effect, and investment in research and development (T = 4.696) played the most significant role. The goodness-of-fit indices (SRMR = 0.05, NFI = 0.92, d-ULS = 0.07, d-G = 0.06, Chi-square = 2.5, GOF = 0.8107) indicated an excellent model-data fit. This model provides an effective tool for implementing green innovations in the steel industry.</p> <p> </p> </td> </tr> </tbody> </table> https://journalfwdmj.com/index.php/fwdmj/article/download/64/89