Input-Output Analysis for Sustainability by Using DEA Method: A Comparison Study between European and Asian Countries

Abstract

Policymakers around the world are confronted with the challenge of balancing between economic development and environmental friendliness, which entails a robust set of measures in energy efficiency and environmental protection. The increasing complexity of these issues has imposed pressure on the Asian countries that have been acting as global factories. This paper proposes a meta-frontier slacks-based measure (SBM) data envelopment analysis (DEA) model, with the hope that policymakers clarify the relationship between labor force, energy consumption, government expenditures, GDP, and CO 2 emissions. Clarification of the causal relationship can serve as a template for policy decisions and ease concerns regarding the potential adverse effects of carbon reduction and energy efficiency on the economy. The results show: (1) Developing countries should establish their own climate change governance and policy frameworks; (2) Developed economies should seek to lower carbon emissions; (3) Energy policies play a pivotal role in energy efficiency improvement; (4) Top-down efforts are critical for the success of carbon reduction policies; (5) Learning from the success of developed countries helps to improve the effectiveness of energy policies; (6) Environmental policies should be formulated, and new production technologies, pollution prevention measures, and treatment methods should be introduced; (7) Governments are suggested to build long-term independent management institutions to promote energy cooperation and exchange.

The Integrated Approach for Sustainable Performance Evaluation in Value Chain of Vietnam Textile and Apparel Industry

“…DEA was first used for non-profit organizations; however, DEA methodology has been discussed in many papers and applied in various types of industries over the last decade. For example, Tsai (2016) adopted DEA method to clarify the relationship among labor forces, energy consumption, government expenditures, GDP, and CO 2 emissions, and the result provided some useful recommendations for both European and Asian countries [32]. DEA was used to improve patent strategies in Korea; the purposes of this research was to find which patent applications are strong or weak in South Korea and some solutions are recommended to make weak industries become strong [33].…”

Data envelopment analysis models for the assessment of efficiency of sustainable forest management in Poland

“…DEA method allows for an analysis of multidimensional processes in forestry, because a number of inputs and outputs can be used simultaneously. Moreover, the lack of input and output prioritizing and the lack of determination of functional dependency be-tween these two is an advantage of this method (Tsai et al 2016). But, the obtained results are dependent on the limitations of the method, which include sensitivity to values that significantly differ from the others and a change in the number of examined units, as well as the need to maintain the proportions whereby the number of the examined units will be 3-5 times bigger than the number of inputs and outputs (Hollingsworth 2016).…”

Measuring the Meta Efficiency and Its Determinants on Efficiency in the Korean Coffee Shop Franchise

“…The DEA model uses all observed franchising networks to assess the relative efficiency of each observed chain, comparing its productive results to those of all the sample chains. Table 1 tabulates previous Sustainability 2020, 12,2398 3 of 20 studies on franchise efficiency, which are based on the employed methodology, DMUs' characteristics, and different inputs/outputs variables. [15] explored the franchising network performance, and more specifically, the relative franchising network efficiency of the US franchising sector, using a population of 150 franchising networks whose data are published in the Entrepreneur's 25 Annual Franchise 500 ® (www.entrepreneur.com/franchises/500.…”

“…That is, the metafrontier production function is defined as a common boundary that envelops the group frontiers (GF) [7][8][9]. Additionally, this metafrontier methodology offers a technology gap ratio (TGR), which is expressed as the distance between the group frontier and the metafrontier [11,12]. Based on the results of the metafrontier analysis, this study investigated the efficiency difference among coffee shop franchisors' groups in Korea based on the Kruskal-Wallis test.…”