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This paper presents a meta entropy dynamic two‐stage DDF model, incorporating significant patents in financial technology (fintech) into the analysis to examine the operational and market efficiencies of banks in Taiwan, providing new insights for research on banking performance and government policy. The results show the following. (1) The most efficient bank is Cathay Financial, while the bottom three are First Financial, E.SUN Financial, and Hua Nan Financial. (2) Financial holding companies (FHCs) outperform non‐FHCs in both operational and market stages. (3) The number of patents has a positive impact on the market stage efficiency of banks. [ABSTRACT FROM AUTHOR]

Sustainable development is the primary goal of the current global economic transformation. The banking industry, as an intermediary institution within the financial system, not only serves as a crucial foundation for national economic development but also plays a key role in the global transition to sustainability and a low‐carbon economy. Banks can leverage the influence of financing to direct funds towards sustainable ventures and simultaneously develop green financial products, guiding ordinary consumers to make more environmentally friendly choices. How the banking industry can effectively improve operational efficiency while considering sustainable development is one of the key focuses of ongoing development in the banking sector. The main aim of this study is to incorporate the aspect of sustainable development into the evaluation of operational efficiency, aligning with the goals of corporate sustainable development. It allows for an analysis of how decision‐makers in the banking industry can adjust resources to maintain stable and sustainable profitability while promoting sustainable development. This study selected 13 financial holding banks and 19 non‐financial holding banks in Taiwan as research subjects, covering the period from 2016 to 2021. Utilizing a meta assurance regions (AR) parallel dynamic two‐stage slacks‐based measure model with "operational stage" and "market and sustainability parallel stage," the research explores the efficiency performance of banks considering sustainable development. It examines the differences in efficiency performance at various stages among different types of banks. The research findings are as follows: (1) among the banking industry in Taiwan, operational stage efficiency ranks the highest, followed by sustainable stage efficiency, while market stage performance lags behind. (2) Financial holding banks outperform non‐financial holding banks on average in operational stage, market stage, and sustainable stage efficiency. (3) Fubon Financial, TFH, CATHAY HOLDINGS, and SKFH are benchmark performers among financial holding banks. (4) Non‐financial holding banks exhibit a higher average technical gap ratio compared to financial holding banks, indicating that non‐financial holding banks have fewer inefficient areas to improve. However, the technical efficiency of both groups of banks approaches each other over the years. (5) In the sustainable stage, financial holding banks demonstrate superior environmental indicators and corporate treatment efficiency compared to non‐financial holding banks. [ABSTRACT FROM AUTHOR]

Climate change has directly impacted coffee‐producing regions in Africa. This study uses the two stage Dynamic Network Directional Distance Function (DN‐DDF) and Malmquist Productivity Index (MPI) methods to evaluate the efficiency and productivity changes of agricultural production and sustainable development in 19 African coffee‐producing countries from 2014 to 2018. According to the empirical results, Central African Republic, Ethiopia, Liberia, Uganda, and Zambia have the highest overall efficiency. This study has three main contributions: (1) using a two‐stage model to evaluate the impact of agricultural production efficiency on sustainable development efficiency, (2) using a dynamic model with forest area as a cross‐period variable to reflect the real‐world phenomenon of coffee relying on forest mixed planting, and (3) objectively evaluating the impact of extreme weather on agricultural production by using rainfall as an exogenous variable to address previous research shortcomings. The results of this study can promote the improvement of agricultural production efficiency in African coffee‐producing countries and provide important reference value for sustainable development goals. [ABSTRACT FROM AUTHOR]

China, the world's largest developing country, faces a severe water shortage. As the government has set a goal of limiting water use to 7000 × 108 m3 by 2035, how to control the increase in water use will be a thorny issue for China. Unbalanced and uncoordinated regional socio-economic development is an important feature of China. Research on the interaction between provincial water use will help to optimize the rational allocation of water resources and control of water use. In this paper, SNA (social network analysis) method is first used to explore the characteristics of social network relationship between inter-provincial water use, construct a two-stage model of SNA–LMDI, and decompose the driving factors of inter-provincial water use evolution. We found the following points. (1) From 2000 to 2018, the spatial correlation network structure of water use is tending to be stable, and the stability and risk resistance of the whole network are enhanced. (2) From different angles to quantify the centricity analysis, can be found that eastern provinces located right in the heart of water network, obviously larger impact on water resources utilization in other provinces, Shanghai and Beijing is located in the former two, and central and western provinces in the edge position. (3) The national water use spatial correlation network can be divided into four blocks, net beneficial block, bidirectional spillover block, brokers block, and net spillover block. (4) Technological progress and industrial structure adjustment were the primary and secondary factors inhibiting the increase of total water use, while income increase was the main factor promoting the increase of total water use, population scale expansion had a weak role in promoting the increase of total water use. Some policy implications are put forward related to our research conclusions. [ABSTRACT FROM AUTHOR]

The purpose of this research is to elaborate a three-stage hybrid measure data envelopment analysis (DEA) with meta-frontier model, and then estimate the technical efficiency of Taiwanese semiconductor integrated circuit (IC) companies by using data from 2005 to 2016 on 92 firms. The study divided the Taiwanese semiconductor IC companies into two groups (IC design and IC manufacturing/packaging/testing) based on their different production characteristics and using the concepts of DEA meta-frontier models proposed by [O'Donnell, CJ, DP Rao, GE Battese (2008). Meta-frontier frameworks for the study of firm-level efficiencies and technology ratios. Empirical Economics, 34(2), 231–255] to estimate their efficiencies. The empirical results of this study show that the adjustment range of the average meta-efficiency values of all firms is higher than the adjustment range of the financial turbulent in 2007–2009 and 2011–2013. Second, before and after the adjustment, the distribution of the meta-technology ratio (MTR) changed slightly. The main reason may be that the global economic recession triggered by the 2007–2009 global financial tsunami and the 2011–2013 European debt crisis offset the impact of technological progress. Finally, under the considerations of environmental factors, the ratio of export to total sales, the degree of diversification, research and development spillover effects and the ratio of investment to mainland China are the main determinants influencing the operational performance of Taiwanese semiconductor IC firms and the impacts on MTR. [ABSTRACT FROM AUTHOR]

Previous studies have failed to analyze a bank's operation performance and non‐performing loans at the same time. Therefore, this research uses the Dynamic Two‐stage directional distance function (DDF) Recycle with Assurance Regions (ARs) model to explore the efficiency of Taiwanese banks in their operation stage and recycling stage. The research results are as follows. (1) The six‐year overall average efficiency is.7966. Taipei Star Bank has the best efficiency, and Fubon, Bank SinoPac, and Union Bank have the worst efficiency rankings. (2) Most banks have good efficiency in the operation stage, while efficiency in the recovery cycle stage fluctuates. [ABSTRACT FROM AUTHOR]

The Report: Intergovernmental Panel on Climate Change (IPCC) set a goal global warming of 1.5°C on global temperature change. Extreme climate changes have increased the demand for electricity consumption by people and enterprises. In fact, China's total power generation in 2019 exceeded 25% of the world's amount, and its thermal power generation accounted for more than 70%. Although past research on electricity efficiency seldom discusses the issue of climate change, the topic still remains important. This research thus considers extreme temperature days (climate change variable) as exogenous variable and uses the Two-Stage Meta Under exogenous undesirable EBM model to examine power efficiency in China. The results are as follows. (1) In the west only Qinghai's GDP, CO2, PM2.5, and electricity consumption have technology gap ratio (TGR) efficiency values of 1 in the 5 years. (2) China's electricity consumption has the same trend with the TGR efficiency of CO2 and is higher than PM2.5. (3) The national overall efficiency, meta overall efficiency, and TGR overall efficiency are the worst in China's west region. [ABSTRACT FROM AUTHOR]