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This study aims to examine the relationships among International Financial Reporting Standards (IFRS) adoption, earnings management, and corporate efficiency.

First, the authors employ the epsilon-based measure (EBM) of the data envelopment analysis to measure the corporate performance of the Taiwanese electronics industry from 2011 to 2014. Second, the authors regress the IFRS adoption and earnings management on corporate efficiency.

The findings show that the corporate efficiency deteriorated after IFRS adoption. Although the regression analysis shows that the relationship between earnings management and corporate efficiency is significantly positive, the authors find that IFRS adoption is effective in unveiling earnings management. Moreover, IFRS adoption moderates the impact earnings management and corporate efficiency.

This study provides reference for decision-makers in the application of accounting principles and in the understanding of the IFRS impact adoption.

IFRS adoption can either facilitate or limit the earnings management that would affect corporate efficiency significantly and help the electronics industry as well as investors to know the changes in accounting principles and their effects on corporate efficiency.

The authors use the EBM of efficiency model to measure corporate efficiency and employ the modified Jones model to measure earnings management.

First, this study assesses the link between research and development (R&D) expenses and firm efficiency. Second, this study explores how family control moderates the link between the two.

This study uses two measures of time-based firm efficiency, namely, a window slacks-based measure (WSBM) and a window epsilon-based measure (WEBM) of data envelopment analysis (DEA). Then, 216 firm-year observations are analyzed in the Taiwanese cultural and creative industries from 2005 to 2017.

This study finds that R&D expenses significantly worsen firm efficiency, and that family control positively moderates this effect. A further test separating the sample into family-controlled and nonfamily-controlled firms indicates that R&D expenses negatively affect the efficiency of nonfamily-controlled firms but positively affect that of family-controlled firms.

The existing literature has examined the link between R&D expenses and corporate performance. However, the process by which R&D expenses affect corporate performance from a production perspective remains unknown.

Overall, this study provides insights for policymakers to scrutinize resource management and R&D expenses from the production and resource-based perspectives.

Due to recent technological advances, the retail industry has changed significantly. This paper examines a novel unmanned retail mode-unattended convenience store to identify the possible operational problems and develop appropriate managerial recommendations.

A data-driven two-stage epsilon-based measure (EBM) data envelopment analysis (DEA) method was developed to evaluate operational performance data from 33 unattended convenience stores and assess the impacts on efficiency of the internal factors, and a Tobit regression analysis was employed to examine the external environment.

It was found that the overall economic performances were relatively low and fluctuated significantly; however, the social performances were slightly higher. The out-of-stock rate was found to have a negative impact on efficiency, and regional characteristics were found to have significant effects on performance.

This study sought to identify current operational problems with unattended convenience stores to provide managerial insights. The cross-sectional assessment suggested that to achieve better performance, particular attention needed to be paid to store locations and surrounding store environments.

First, this paper establishes a novel theoretical framework to evaluate the economic and social operational performances at unattended convenience stores. Second, it contributes to research on unattended convenience stores and the unmanned retail industry and offers significant guidance on detecting operational deficiencies and improving future performances.

This study aims to propose a refined dynamic network slacks-based measure (DNSBM) to evaluate the efficiency of China's regional green innovation system which consists of basic research, applied research and commercialization stages and explore the influencing factors of the stage efficiency.

A two-step procedure is employed. The first step proposes an improved DNSBM model with flexible settings of stages' input or output efficiency and uses second order cone programming (SOCP) to solve the non-linear problem. In the second step, least absolute shrinkage and selection operator (LASSO) and Tobit models are used to explore the influencing factors of the stage efficiency. Global Dynamic Malmquist Productivity Index (GDMPI) and Dagum Gini coefficient decomposition method are introduced for further discussion of the productivity change and regional differences.

On average, Chinese provincial green innovation efficiency should be improved by 24.11% to become efficient. The commercialization stage outperforms the stages of basic research and applied research. Comparisons between the proposed model and input-oriented, output-oriented and non-oriented DNSBM models show that the proposed model is more advanced because it allows some stages to have output-oriented model characteristics while the other stages have input-oriented model characteristics. The examination of the influencing factors reveals that the three stages of the green innovation system have quite diverse influencing factors. Further discussion reveals that Chinese green innovation productivity has increased by 39.85%, which is driven mainly by technology progress, and the increasing tendency of regional differences between northern and southern China should be paid attention to.

This study proposes an improved dynamic three-stage slacks-based measure (SBM) model that allows calculating output efficiency in some stages and input efficiency in the other stages with the application of SOCP approach. In order to capture productivity change, this study develops a GDMPI based on the DNSBM model. In practice, the efficiency of regional green innovation in China and the factors that influence each stage are examined.

The purpose of this study is to provide the benchmarking guideline to improve managing maintenance man-hour in producing sorties of fighter jet aircraft in the Korean Air Force by measuring relative efficiency of aircraft in a fleet.

Using actual operational data from 2014 to 2018, this paper measures the relative efficiencies of aircraft by data envelopment analysis (DEA) model. To analyze the efficiencies across different operational units and among aircraft with different attributes, non-parametric statistical techniques and tobit regression are employed.

The overall management of maintenance man-hour turns out to be 63.2% efficient compared to the best practice. Operational unit possessing aircraft with different configurations shows the poorest performance implying efficiency depends on the complexity of job processes. Identification of aircraft on the best-practice frontier indicates the efficiency is closely related with the reliability of components and the age of aircraft.

Performance of aircraft maintenance has a tremendous impact on military readiness, utilization of work force, and the quality and safety of flight operations. This study confirmed there exists plenty of room for performance enhancement and presents a reference to find a balance in the performances of maintenance practices across different installations as well as among different types of aircraft.

Application of DEA to engineering systems has been limited in literature, especially in military operations. Thus, this study presents meaningful guidelines to which fleet manager can refer to when establishing strategic maintenance plans to balance the utilization of manpower.

The purpose of this paper is introducing an alternative model to measure the relative efficiency of observations with undesirable products. Describing the reference set and benchmarking.

In this paper, an alternative definition of weak disposability assumption is introduced to handle undesirable outputs. Actually, two types of undesirable outputs are addressed and a substitute definition of weak disposability is presented.

Using this assumption a linear production technology set along with a performance analysis model is constructed to assess the relative efficiency of the decision-making units. To illustrate the radial application of the proposed approach, a real case on transportation system of USA during 1992-2009 is given.

To date, data envelopment analysis studies have investigated undesirable outputs by the assumption of weak disposability, defined as the proportional contraction of good and bad products, which leads to the null-joint assumption between good and bad outputs. Therefore, the only way to produce no undesirable outputs is producing zero desirable outputs. So the production process should be stopped while it is not economically cost-effective. However, in some processes there are some undesirable outputs, which are decreased with non-same percentages. So these undesirable outputs can be stopped while the good outputs have a strictly positive value. In this situation, the good outputs are not null-joint with this type of bad outputs. In the current paper, a new definition of the weak disposability of outputs was represented while two groups of undesirable outputs were considered. Hence, desirable outputs and the first kind of undesirable outputs were decreased proportionally. However, the reduction value was different for the second kind of undesirable outputs. Hence, the null-joint assumption is removed from the production technology. Then, a new technology was proposed based on five postulates as inclusion of observations, free disposability of desirable outputs and inputs, new weak disposability, convexity and minimum extrapolation.

China has proposed two-stage goals of carbon peaking by 2030 and carbon neutralization by 2060. The carbon emission reduction effect of the power industry, especially the thermal power industry, will directly affect the progress of the goal. This paper aims to reveal the spatial-temporal characteristics and influencing factors of carbon emission efficiency of the thermal power industry and proposes policy suggestions for realizing China’s carbon peak and carbon neutralization goals.

This paper evaluates and compares the carbon emission efficiency of the thermal power industry in 29 provinces and regions in China from 2014 to 2019 based on the three-stage slacks-based measure (SBM) of efficiency in data envelopment analysis (DEA) model of undesired output, excluding the influence of environmental factors and random errors.

Empirical results show that during the sample period, the carbon emission efficiency of China’s thermal power industry shows a fluctuating upward trend, and the carbon emission efficiency varies greatly among the provincial regions. The carbon emission efficiency of the interregional thermal power industry presents a pattern of “eastern > central > western,” which is consistent with the level of regional economic development. Environmental factors such as economic level and environmental regulation level are conducive to the improvement of carbon emission efficiency of the thermal power industry, but the proportion of thermal power generation and industrial structure is the opposite.

This paper adopts the three-stage SBM–DEA model of undesired output and takes CO₂ as the undesired output to reveal the spatial-temporal characteristics and influencing factors of carbon emission efficiency in China’s thermal power industry. The results provide a more comprehensive perspective for regional comparative evaluation and influencing factors of carbon emission efficiency in China’s thermal power industry.

This chapter considers the productivity of 77 airlines between 1980 and 2013. We do so by estimating a stochastic frontier and decomposing the total factor productivity growth into efficiency, technical and scale efficiency change. Our results show that, on average, airlines increased productivity over the period but that, while efficiency and technical change improved, scale efficiency results indicate that the average airline moved away from the most productive scale size. This was especially so in the two decades after 1980. Comparisons between geographical areas, business models, networks and alliances are also made.

This paper aims to investigate the situation and evolution of sustainability performance in China.

This paper adopts the global Malmquist-Luenberger (GML) productivity index based on data envelopment analysis and Tobit regression for analysis.

The results indicate the following: China’s sustainability performance has been improving since 2005 and is closely related to the national development strategy and supportive policy; regional gaps in sustainability are a prominent problem represented by the fact that South Central China is becoming a sustainability collapse zone; interprovincial heterogeneity is evident with the varying development speed and conditions; and the level of sustainability performance has a significantly positive correlation with the urbanization rate, investment completed in the treatment of industrial pollution, government appropriation for education and per capita area of paved roads, but it has a negative correlation with the possession of private vehicles.

As an application, this study assessing the GML productivity index of 30 provinces in China from 2005 to 2015 and analyse the sustainability performance on three regional levels (i.e. country level, regional level and provincial level). Tobit regression is also applied to recognize the factors related to the GML index with the results taken as references for policy suggestions. The results have implications for a comprehensive understanding of China's sustainability performance and policymaking in this field.

This study aims to investigate the association between intellectual capital (IC) and bank efficiency of Taiwanese bank branches.

This study manually collects sample data from 107 non-public financial reports of the bank branches of Taiwan Business Bank Company Limited. As this study concerns bank branches, this study uses questionnaires related to IC to measure the implementation of IC at branch level. This study employs data envelopment analysis (DEA) models (BCC, EBM and BootBCC) to identify bank branches' efficiency. This study uses partial least square-based structural equation modeling analysis to assess the impact of IC and bank efficiency.

Result reveals that relational capital (RC) significantly and negatively impacts bank efficiency. Findings also imply that human capital (HC) and structural capital (SC) do not contribute to bank efficiency in Taiwan.

Spending effort in building relationships with customers diverts banks' resources. More inputs that are used may not be converted to outputs immediately. Bank branches should focus on enhancing their service quality to attract customers to use the facilities provided by branches.

To the best of the authors' knowledge, this empirical study is the first to examine the association between IC and bank branches' efficiency in Taiwan by integrating primary and secondary data. For IC components, this study conducts a survey by designing the questionnaires related to IC to assess the implementation of IC at bank branches in Taiwan. In terms of efficiency, this study uses bank financial data and DEA models to identify bank branches' efficiency.