The aim of this study is introducing a technique to illuminate composite issue, aspects or system factors, the complicated problems need to be structured with graphical illustration and analyzed casual interdependence and influences throughout the organization. Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology is proposed to for researching and solving complex and intertwined problem groups because of its capability in verifying interdependence between variables and try to improve them by offering a specific chart to reflect interrelationships between variables. In this technique experts plays complementary and approval role in all steps and sections. , key factors will be clarified by using the direct-influenced matrix and then it specifies priorities of each factor. The end product of the DEMATEL process is a visual demonstration-the Impact-Relations Map (IRM)-by which respondents organize their own actions in the world. First In this study, DEMATEL methodology in explained and then kind of different problems which can be solved by DEMATEL, will discussed and finally the method of DEMATEL is detailed completely.

Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology has been proposed to solve complex and intertwined problem groups in many situations such as developing the capabilities, complex group decision making, security problems, marketing approaches, global managers, and control systems. DEMATEL is able to realize casual relationships by dividing important issues into cause and effect group as well as making it possible to visualize the casual relationships of subcriteria and systems in the course of casual diagram that it may demonstrate communication network or a little control relationships between individuals. Despite of its ability to visualize cause and effect inside a network, the original DEMATEL has not been able to find the cause and effect group between different networks. Therefore, the aim of this study is proposing the expanded DEMATEL to cover this deficiency by new formulations to determine cause and effect factors between separate networks that have bidirectional direct impact on each other. At the end, the feasibility of new extra formulations is validated by case study in three numerical examples of green supply chain networks for an automotive company.

Environmental protection and sustainable development are getting increasing attention in the automobile industries. Environmental consciousness has increased, and sustainability has become an important requirement for the management of end-of-life vehicles (ELVs). The proper management of ELVs can bring improved sustainability performance for any society or organisation. There are several alternative options for ELVs management such as reuse, repair, reconditioning, remanufacturing and recycling. Environmental legislation is forcing original equipment manufacturers (OEMs) to manage their products at the end of their life cycle to reduce their potential environmental impact. An appropriate selection model for sustainable ELV management alternatives in the dynamic, competitive and regulatory environment can enable a firm to satisfy economic, environmental, social and technological requirements. This study proposes an integrated model to select the dimensions and criteria for evaluating sustainable alternatives for the proper management of ELVs. First, the DecisionMaking Trial and Evaluation Laboratory (DEMATEL) method is used to select the most important dimensions and criteria for sustainable alternative selection. Next, a hierarchy has been constructed to develop a systematic technique to solve the alternatives selection problem. An analytic hierarchy process (AHP) and extent analysis method on the fuzzy AHP (FEAHP) model have been used based on the hierarchy to evaluate the most suitable alternatives from the sustainability point of view. The strength of the proposed model is that it compares the results of both methods, the imprecision of experts' opinions is considered in the evaluation process and the model is easy to use.

Prosperity is one of the five critical areas for Sustainable Development according to the 2030 Agenda. This research develops a prosperity model for a tourism destination and examines stakeholders’ perception of the role of sustainable tourism development in enhancing the prosperity. A set of 18 sustainability indicators were used and identified through a hybrid model that combines results from a systematic literature search and four-stage convergent interviews. Results from 171 participants from five different groups of stakeholders revealed that sustainable tourism development enhances the prosperity of the target destination in general. Sustainability was found to be a medium to strong predictor of key prosperity dimensions, particularly environmental quality and sociocultural empowerment. Finally, the level of relationships were quantified to assist destination managers in identifying where to expend effort and resources to improve the implementation of sustainable tourism while considering the key dimensions of prosperity.

Green supply chain management (GSCM) has become a practical approach to develop environmental performance. Under strict regulations and stakeholder pressures, enterprises need to enhance and improve GSCM practices, which are influenced by both traditional and green factors. This study developed a causal evaluation model to guide selection of qualified suppliers by prioritizing various criteria and mapping causal relationships to find effective criteria to improve green supply chain. The aim of the case study was to model and examine the influential and important main GSCM practices, namely, green logistics, organizational performance, green organizational activities, environmental protection, and green supplier evaluation. In the case study, decision-making trial and evaluation laboratory technique is applied to test the developed model. The result of the case study shows only “green supplier evaluation” and “green organizational activities” criteria of the model are in the cause group and the other criteria are in the effect group.