ABSTRACT
In recent decades, waste generation has increased gradually because of the development of the quantity and size of businesses, together with the high growth rate of the population. However, in 2019, like other industries, the waste management industry was affected by the COVID-19 pan-demic, particularly in relation to aspects concentrated on strategy. Subsequently, appropriate waste management in all aspects of the community, specifically for waste management enterprises, was demanded. This research aims to assess the profitable efficiency, position, technical, and technological innovation and compare the global major waste management corporations by integrating the negative super-slacks-based measure model and the negative Malmquist model in data envelopment analysis. Various inputs and outputs are initially selected from nine waste management companies’ financial statements from 2017 to 2020, including negative values, to attain their performance. The empirical results indicated that waste management companies’ managers could make better investment or strategy decisions for superior performance. At the same time, collaborators from other sectors could find their potential partners in the waste management industry. In general, considering the efficiency, Veolia Environment (DMU3) and Heritage-Crystal Clean Company (DMU8) were the most efficient companies. Meanwhile, Covanta Holding (DMU2) and Republic Services Corporation (DMU5) required additional development to improve their performance. Besides, because of the disparity in technical and technological innovation, most decision-making units could not achieve consistent improvement in terms of technical, technological change, and total production. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
ABSTRACT
The two main approaches that countries are using to ease the strain on healthcare infrastructure is building temporary hospitals that are specialized in treating COVID-19 patients and promoting preventive measures. As such, the selection of the optimal location for a temporary hospital and the calculation of the prioritization of preventive measures are two of the most critical decisions during the pandemic, especially in densely populated areas where the risk of transmission of the virus is highest. If the location selection process or the prioritization of measures is poor, healthcare workers and patients can be harmed, and unnecessary costs may come into play. In this study, a decision support framework using a fuzzy analytic hierarchy process (FAHP) and a weighted aggregated sum product assessment model are proposed for selecting the location of a temporary hospital, and a FAHP model is proposed for calculating the prioritization of preventive measures against COVID-19. A case study is performed for Ho Chi Minh City using the proposed decision-making framework. The contribution of this work is to propose a multiple criteria decision-making model in a fuzzy environment for ranking potential locations for building temporary hospitals during the COVID-19 pandemic. The results of the study can be used to assist decision-makers, such as government authorities and infectious disease experts, in dealing with the current pandemic as well as other diseases in the future. With the entire world facing the global pandemic of COVID-19, many scientists have applied research achievements in practice to help decision-makers make accurate decisions to prevent the pandemic. As the number of cases increases exponentially, it is crucial that government authorities and infectious disease experts make optimal decisions while considering multiple quantitative and qualitative criteria. As such, the proposed approach can also be applied to support complex decision-making processes in a fuzzy environment in different countries. © 2021 Tech Science Press. All rights reserved.
ABSTRACT
Today, over 80% of global trade is seaborne. In a world of global supply chains and complex industrial development processes, seaports and port operators play an integral role of utmost importance and act as an incentive to the development of the marine economy and particularly, the national economy in general. Most importantly, the supply chain and demand shocks of Covid-19 on container ports and the container shipping industry have intensified competition among terminal operators. Thus, it is imperative that managers evaluate competitiveness by measuring their past and current performance efficiency indexes. In so doing, we present a hybrid data envelopment analysis (DEA) model that combines the DEA Malmquist method and the epsilon-based measure (EBM) for the first time to address the issue of performance evaluation of seaport terminal operators. The applicability of the proposed hybrid approach is illustrated with a case study of the top 14 seaport companies in Vietnam. First, the Malmquist model is used to assess the total productivity growth rates of the companies, and its decomposition into technical efficiency change (catch-up) and technological investment (frontier-shift). Second, the EBM model is used to calculate the efficiency and inefficiency score of each company. Besides indicating the best-performing companies from certain aspects during the research period (2015–2020), the results reflect that the gap of applying the EBM method in the field of the maritime industry was successfully addressed, and together with the Malmquist model, the integrated framework can be an effective and equitable evaluation model for any area. Furthermore, the managerial implication provides a useful guideline for practitioners in the maritime sector in improving their operational efficacy and helps customers in selecting the best seaport companies in the outsourcing strategy. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.