ABSTRACT
At the heart of Covid-19 responses, the transition from fossil sources to green energy is an urgent issue for nations to address the crisis and secure sustainable economies. As a country in a seismically active zone that relies heavily on imported fossil fuels, Taiwan is vigorously taking the next step in renewable energy development, which is pivotal to securing its position in global supply chains. Solar energy is today the most suitable renewable energy source for Taiwan. However, land prices and policies, and challenges of scale still hinder its development. In this context, identifying optimal sites for solar photovoltaic (PV) construction is a crucial task for major energy stakeholders. In this paper, a two-stage approach, combining the data envelopment analysis (DEA) models and the analytic hierarchy process (AHP), has been done for the first time to identify the most suitable locations among 20 potential cities and counties of Taiwan for constructing solar PV farms. DEA models were applied to filter out the areas with the most potential by measuring their efficiency indices with temperature, wind speed, humidity, precipitation, and air pressure, as inputs, and sunshine hours and insolation, as outputs. The locations with perfect efficiency scores were then ranked with the AHP method. Five selected evaluation criteria (site characteristics, technical, economic, social, and environmental) and sub-criteria of each were utilized to prioritize the locations with solar energy potential. AHP was used to determine the relative weights of the criteria and sub-criteria and the final weights of the areas. For criteria weighting results, 'support mechanisms,' 'electric power transmission cost,' and 'electricity consumption demand' with weights of 0.332, 0.122, and 0.086, respectively, were found as the most significant sub-criteria. The final ranking suggests Tainan, Changhua, and Kaohsiung as the top three most suitable cities for constructing solar PV energy systems. © 2013 IEEE.
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.
ABSTRACT
With the effects of the COVID-19 pandemic, the e-commerce trend is driving faster, significantly impacting supply chains around the world. Thus, the importance of logistics and supply chain functions has been amplified in almost every business that ships physical goods. In Vietnam, the logistics service sector has seen rapid expansion. Since more and more businesses are seeking third-party logistics (3PL) providers to outsource the logistics functions, this article aims to offer decision-makers an integrated and consistent model for evaluating and selecting the most efficient 3PLs. To this end, the authors exploit a hybrid multi-criteria method which is fuzzy analytic hierarchy process (FAHP) and fuzzy vlsekriterijumska optimizacija i kompromisno resenje (FVIKOR) while examining the most influential and conflicting criteria regarding economic, service level, environmental, social, and risk aspects. Fuzzy information in the natural decision-making process is considered, linguistic variables are used to mitigate the uncertain levels in the criteria weights. First, FAHP (the weighting method) is adopted to evaluate and calculate each criterion’s relative significant fuzzy weight. FVIKOR (the compromised ranking method) is then used to rank the alternatives. The combination of FAHP and FVIKOR methods provides more accurate ranking results. As a result, reliability and delivery time, voice of customer, logistics cost, network management, and quality of service are the most impactful factors to the logistics outsourcing problem. Eventually, the optimized 3PLs were determined that fully meet the criteria of sustainable development. The developed integrated model offers the complete and robust 3PLs evaluation and selection process and can also be a powerful decision support tool for other industries. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.