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With rapid industrialization and urbanization, municipal solid waste (MSW) management has become a serious challenge worldwide, especially in developing countries. The Beijing Municipality is a representative example of many local governments in China that are facing MSW management issues. Although there have been studies in the area of MSW management in the literature, less attention has been devoted to developing a structured framework that identifies and interprets the barriers to MSW management in megacities, especially in Beijing. Therefore, this study focuses on identifying a comprehensive list of barriers affecting the successful implementation of MSW management in Beijing.

Through an extensive review of related literature, 12 barriers are identified and classified into five categories: government, waste, knowledge dissemination, MSW management process and market. Using an integrated approach including the decision-making trial and evaluation laboratory (DEMATEL), maximum mean de-entropy algorithm (MMDE) and interpretive structural modeling (ISM), a conceptual structural model of MSW implementation barriers is constructed to provide insights for industrial decision-makers and policymakers.

The results show that a lack of economic support from the government, imperfect MSW-related laws and regulations, the low education of residents and the lack of publicity of waste recycling knowledge are the main barriers to MSW management in Beijing. Combined with expert opinions, the paper provides suggestions and guidance to municipal authorities and industry practitioners to guide the successful implementation of MSW management.

The findings of this study can provide a reference for MSW management in other metropolises in China and other developing countries.

This study proposes a hybrid DEMATEL-MMDE-ISM approach to resolve the subjectivity issues of the traditional ISM approach and it analyzes the barriers that hinder MSW management practices in Beijing.

The purpose of this study is to identify a comprehensive list of main enablers of successful implementation of green manufacturing (GM) practices in small and medium-sized enterprises (SMEs). Based on the inputs from Irish SMEs' experts, a validated conceptual hierarchy model of the identified enablers is developed to analyse and prioritise the most dominant ones.

Data were collected using a questionnaire survey responded by various professionals in Irish manufacturing SMEs. Experts' opinions were analysed using interpretive structural modelling (ISM) and cross-impact matrix multiplication applied to classification (MICMAC) to distinguish the mutual influences amongst the nine identified enablers.

The findings revealed that from the Irish SMEs' perspective, strong green supply chain relations are the outcome of successfully implementing GM and not a driver of the other enablers. Furthermore, lower manufacturing costs are found to arise as a result of GM practices in SMEs.

It is discussed that emulating the actions of larger companies will not necessarily yield the same results for SMEs. Innovation will become a cornerstone of remaining competitive in a sustainable environment, which is facilitated by closer green supply chain relations.

The reported findings in this article contribute to theory and practice of GM and SMEs research domains by systematically identified, classified and ranked enablers in a conceptual hierarchal model from the perspective of Irish SMEs. This research lays the foundations for further analysis of the GM practices enablers in a time when UN mandates and EU regulations are increasingly impacting SMEs all around Europe and especially Ireland.