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Taiwan's bed and breakfast (B&B) industry has grown rapidly during the last decade, which has helped boost the local economy. In this study, we employed the directional distance function with a quasi-fixed input to evaluate the meta-frontier efficiency of 18 counties and cities with B&B businesses in Taiwan. The empirical results demonstrate that the lowest meta-frontier technical efficiency occurred in 2018 because the central and eastern areas in Taiwan were affected by natural and anthropogenic disasters. In addition, we found that the meta-frontier efficiency of the northern region was greater than that of other regions. The meta-frontier inefficiency of the northern and central regions mainly came from their group technical inefficiency, whereas that of the B&B industry was caused by the technology gap. Moreover, the application of the Boston Consulting Group matrix demonstrated that the most efficient B&Bs were mainly located in the northern and central regions. • An alternative meta-frontier framework is used to analyze meta-frontier technical efficiency. • The meta-frontier technical efficiency decreased in 2018 before recovering in 2019 and further improving in 2020. • This study employs an approach to understand the cause of inefficiency in each county and city. • B&B owners can use the results of this study to reconsider their management and marketing strategies. [ABSTRACT FROM AUTHOR]

Based on a new production-theoretical decomposition analysis (PDA), this paper decomposes the changes of carbon dioxide emissions in China's provinces into seven drivers. This study finds that economic development, energy structure and energy efficiency are positive driving factors of carbon dioxide emission increase; technological advance, reduction in energy intensity and improvements of carbon dioxide emission efficiency are the negative driving factors; the east, central and west have significant variation on CO 2 changes and some decomposition parts. [ABSTRACT FROM AUTHOR]

Different carbon emitting nations and regions use different production technologies. To analyze potential sources of carbon intensity reduction, this study applied a metafrontier function and a non-radial data envelopment analysis (DEA) approach to propose a new carbon emission performance index. An empirical study of carbon emissions from 58 countries between 2001 and 2007 led to three key findings. First, different reference technologies lead to significant differences in carbon emission performance. Assessing carbon emission performance using the group frontier as the evaluation criterion consistently yields equal or greater performance than when using the metafrontier as the benchmark. Second, the carbon emission performance of Asia is lower than that of Europe and the Americas, but Asia has the greatest potential to reduce carbon intensity. Production technology levels in Asia have lagged behind levels in Europe and the Americas; these gaps, however, have gradually narrowed. Finally, ineffective management and gaps in production technologies are the two main contributors to carbon dioxide intensity. Management factors are more significant overall for Asia, Europe and America; However, different individual countries have different perspective on the sources of potential carbon intensity. [ABSTRACT FROM AUTHOR]

Abstract: Conventional Data envelopment analysis is based on the Debreu–Farrell optimal solution in evaluating the decision-making unit’s efficiency. Even if Farrell efficiency is achieved, there may exist slacks in individual input or output. To solve this problem, the Russell measure can be used to address the inherent shortcomings of the Farrell measure and devise an optimal solution for the Pareto–Koopmans concept of efficiency. However, the non-proportional radial measure may lead to distorted efficiency measurement of inefficient decision-making units, due to assumptions about its implicit importance of inputs and outputs. Therefore, this paper uses a simple method in calculating the weighting measurements, in order to override this assumption using the concept of entropy. By introducing entropy, the Russell measure easily uses input, output, and system weighting to evaluate performance. In addition, we also use the entropy-concepts applied to slack-based measure. Moreover, we illustrate this entropy-based Russell measure using data gathered from 24 of Taiwan’s commercial banks in order to rank and compare it with the conventional Russell measure. [Copyright &y& Elsevier]

Abstract: Data envelopment analysis (DEA) mainly utilizes envelopment technology to replace production function in microeconomics. The input and output of decision making units (DMUs) are projected into the attributes to evaluate or measure their performance. However, if the inputs and outputs are linguistically termed or are fuzzy-numbered, conventional DEA can not easily measure the performance. Therefore, we propose the use of a fuzzy super-efficiency slack-based measure DEA to analyze the operational performance of 24 commercial banks facing problems on loan and investment parameters with vague characteristics. After our analysis, we find that the fuzzy slack-based measure of efficiency (Fuzzy SBM)/fuzzy super-efficiency slack-based measure of efficiency (Fuzzy Super SBM) can not only effectively characterize uncertainty, but also have a higher capability to evaluate bank efficiency than the conventional Fuzzy DEA approach. [Copyright &y& Elsevier]