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The more increasing developments of the automotive industry and usage of vehicles, the more increasing end-of-life vehicles recycling and remanufacturing strategies are needed all around the world. This work tries to explore the crucial barriers of implementation of remanufacturing strategy in the automotive industry, and also addresses substantial interrelationships and interdependencies among the barriers using multi-attribute decision making approaches. The influence and the interrelationship of the barriers of deploying the remanufacturing strategy in the Iranian automotive industry is measured by implementing the Interpretive Structural Modelling (ISM) approach and then the results obtained from Decision-Making Trial and Evaluation Laboratory (DEMATEL) are used to serve two purposes. First, to confirm and verify the results obtained by the ISM method, and secondly to improve upon those results. The obtained barriers included 4 separate categories of Strategic, Economic, Infrastructural, and Market barriers. Experts in the automobile industry were interviewed and their opinions were taken into account to analyze 17 barriers using two mentioned approaches. According to the evaluation process of the barriers for implementation of remanufacturing strategy in the automobile industry indicating that "lack of resources for research and development and information systems and data for product remanufacturing" is the most influential barrier. Government and the policymakers that plans to implement the remanufacturing must consider this factor intensively. The findings presented the insights for policies that needed to be taken into consideration to boost the remanufacturing strategy of the auto industry in Iran. [ABSTRACT FROM AUTHOR]

This study addresses the problem of selecting a supplier bound by sustainability and resilience criteria, focusing on the steel industry as a case in point. A new framework has been presented for the evaluation of suppliers in this study where thirty-two factors are first recognized based on previous publications and fourteen appropriate factors among them are selected based on expert opinions. Then, Interpretive Structural Modelling is used to study the reciprocal effects of factors and MICMAC analysis is performed to select the critical factors among the fourteen factors. Afterward, the Best–Worst Method is performed for weighting the critical factors. Eventually, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied for ranking the suppliers. The results show that the criteria with higher driving powers and lower dependence have higher weights in the Best–Worst Method. Gilan steel company in Iran is examined as a case study in the steel industry to verify the efficiency of the proposed framework. A comparative analysis is performed showing that taking resilience criteria into account alters the supplier ranking results, making these criteria important from a managerial point of view. It is also suggested to managers to consider all four dimensions of these criteria when evaluating suppliers. It is observed that the reputation and position of the supplier in the industry, availability of a support supplier, strategic stock, sensitivity to the political situation, pollution control, social responsibility, and flexibility in service are the main factors to consider. [ABSTRACT FROM AUTHOR]

Introduction: this study aims at presenting a three-stage hybrid SEM-ANN-ISM (SEANIS) model. The model includes Structural Equation Modeling (SEM), Artificial Neural Network (ANN), and Interpretive Structural Modeling (ISM) for the analysis of factors affecting the customer value chain in the health industry of Iran. This study presents a modern approach for the analysis of factors affecting a model. Methods: step 1 uses the Structural Equation Modeling (SEM) to analyze the criteria and sub-criteria of the chain value model. Factor analysis is used to analyze the correlations of criteria and sub-criteria. Finally, the equations are specified and the effect of causal factors on the value chain, the effect of interfering factors on causal factors and strategies, the effect of the value chain on strategies, and the effect of strategies on consequences are confirmed as the main hypotheses of the study. Step 2 includes an artificial neural network and analysis of the effect of sub-criteria on each other and presents the matrix of components. Step 3 is associated with the interpretive structural modeling to identify and present the final hierarchical model. For data analysis and to present the model, SMARTPLS software was used. Results: the final analysis of the value chain model in the health industry includes causal, field, and interfering criteria, strategies, and consequences identifying and confirming the factors affecting the model. Conclusion: final analysis led to the final confirmation of model validity and usability in the health industry. [ABSTRACT FROM AUTHOR]

A procedure developed to identify and facilitate the implementation of waste source separation strategies applicable in higher education centers, as a prerequisite for the expansion of recycling programs. The target materials proper to be separated were selected based on quantitative/qualitative analysis of waste produced on the Nazlou Campus of Urmia University, Iran (as a case study). The barriers to implementation of the program were identified using the interpretive structural modeling (ISM) methodology. Finally, regarding the main obstacles which could be broken down inside the campus complex, an analysis of factors affecting student participation were done. On average, 37.48% of 1.74 tons of waste daily produced on the campus could be recycled. Based on sieve analyses, the categories of non-ferrous metals, glass, and composite packaging have a wider size distribution (i.e., over 150 to under 80 mm) might lead to improper operation of further mechanical separations and be selected as target materials. The weakness of educational programs and persuading the students are considered the main obstacles. A significant relationship was observed between the three training options, namely "installation of announcements," "organizing waste management classes," and "training through holding the exhibition of recycled products" and the student participation in the program (with more emphasis on the last one). Women were estimated to be more likely than men to participate in the program (70 vs 49%). Also, there was a significant relationship between the knowledge and the student's participation. In other words, strengthening public awareness is essential to increase the participation level., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)