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Critics opine that full expensing of research and development (R&D) depresses near-term profits and incentivizes myopic managers to under-invest in R&D, compromising firm efficiency. Advocates of the expensing rule argue that little rigorous research evidence supports the claimed adverse consequences. We examine the impact of the R&D expensing rule on firm efficiency by exploiting an exogenous shock: a shift in the accounting regime in Germany from full expensing to partial capitalization of R&D when it mandated International Financial Reporting Standard (IFRS) adoption in 2005. We employ Stochastic Frontier Analysis and Data Envelopment Analysis to estimate efficiency for the same German firms before and after the IFRS adoption. We find robust evidence of efficiency improvement in the post-period relative to the pre-period for German R&D firms that report R&D expenditures, and for both early adopters and timely adopters. We also document that financially constrained firms and firms experiencing rapid R&D growth prior to the IFRS adoption show greater efficiency improvement. Moreover, we conduct three falsification tests to make sure our results are not attributable to other accounting changes associated with the IFRS adoption, and find no efficiency improvement for the three control groups (German "no-R&D" sample, U.K. firms, and Australian firms), respectively. We conclude that the change in the R&D reporting rule is the likely catalyst for improvements in efficiency of German R&D firms. [ABSTRACT FROM AUTHOR]

This study investigates the existence of solutions for the key plant capacity utilisation (PCU) concepts using general nonparametric technologies. This is done via a theoretical review of existing and some new PCU concepts. Focusing on short-run and long-run output-oriented, attainable output-oriented, and input-oriented PCU notions, we first investigate the existence of solutions at the firm level. Under mild axioms, this question regarding the existence of solutions for these PCU concepts at the firm level is affirmatively answered under variable and constant returns to scale as well as under convex and nonconvex assumptions. However, short-run and long-run output-oriented and attainable output-oriented PCU concepts may not be implementable depending on certain conditions. There are no such reservations for the input-oriented PCU. Then, for this same range of PCU concepts, we explore the more difficult question as to the existence of solutions at the industry level. The output-oriented and attainable output-oriented PCU exist at the industry level under strict conditions: existence and attainability are interwoven at this level. The industry input-oriented PCU is always feasible at the industry model. This theoretical review is supplemented by a semi-systematic empirical review, and an empirical application. We conclude that input-oriented PCU is clearly the best concept. [ABSTRACT FROM AUTHOR]

Numerous studies have focused on digital twins (DTs) and their applications. However, a common method for evaluating the performance of DTs is lacking. Digital twins performance assessment mechanism is crucial when improving or monitoring any process or system in a business, such a strategy could serve as a guide to help researchers and practitioners create more effective digital twins. Guided by these challenges, we propose a structured method for measuring the performance and flexibility of digital twins, and our study provides a procedure for quantitative calculation of the performance of DTs based on four key performance indicators (KPIs). Moreover, we propose a new KPI, DTflex, for determining the flexibility of digital twins. We evaluated the performance of DTflex as a KPI to demonstrate its use as a simple tool for designers and practitioners to quickly compare different DT methodologies, which might provide valuable input for the iterative improvement of DTs to increase their efficiency in future applications. The knowledge provided along with the method proposed in this paper is expected to help researchers and practitioners working in different fields to compare DT methodologies and DT performance which will lead to higher efficiency DT solutions and increased re-usage of existing DTs. [ABSTRACT FROM AUTHOR]

To formulate multi-tier supply chain management strategies with global impact, understanding the roles of various supply chain partners in disseminating sustainability along the supply chain is crucial. We analyze the influence of different supply chain positions on sustainability and financial outcomes of Turkish manufacturing companies listed in İstanbul Stock Exchange (BIST). We propose a sustainability measure, and rank firms according to their sustainability practices in relation to their financial outcomes using data envelopment analysis (DEA). We estimate Seemingly Unrelated Regression (SUR) equations to control for the common financial shocks that can affect sustainability and financial outcomes simultaneously. Our analysis reveals that first-tier and sub-supplier (second-tier and lower-tiers) firms' financial performance is substantially better compared to Original Equipment Manufacturer (OEM) firms while their sustainability outcomes stay behind. We find that this latter effect is more profound for first-tier firms. Although the supplier firms generally comply with the OEM's product standards, our results show that they are not aligned with the OEM in terms of the environmental and social impact of their operations. Given the crucial role of first-tier suppliers in sustainability dissemination along the supply chain, policies should be formulated in this industry amid these characteristics of the sustainability dissemination. [ABSTRACT FROM AUTHOR]

While interests in Industry 4.0 technologies such as cloud computing and the Internet of Things (IoT) are growing, an ongoing challenge is to properly evaluate the performance of the providers of such technologies. Methods have been developed and applied to assess the efficiency of cloud service providers (CSPs) for Industry 4.0. However, most existing methods suffer from such shortcomings as subjective weights and computing complexity, rendering it difficult to succinctly differentiate the performance of CSPs in a competitive market. Besides, the literature has not taken into account many different types of data such as ratios, integers, and undesirable factors that can affect the performance of CSPs. Most importantly, most existing studies do not consider the sustainability of CSPs in evaluating their performance. To address the above issues, we present a comprehensive analytical method based on data envelopment analysis (DEA) to gauge the sustainability of CSPs for Industry 4.0. Validating the usefulness of our method using a real-life dataset, we provide not only a viable means with sound academic underpinning but also significant managerial insights for practitioners to assess the sustainability of CSPs for Industry 4.0. [ABSTRACT FROM AUTHOR]

Shipping is a highly cyclical, volatile, and unpredictable industry. In recent history, economic shocks like the COVID-19 pandemic have heavily disrupted supply chains and tested the resilience and adaptability of shipping lines from both operational and financial perspectives. Therefore, the commercial success of shipping lines is increasingly determined by an optimal balance between reliable logistics operations and financial performance. Given this, chartering strategies of shipping lines are pivotal in achieving fleet optimisation and financial sustainability. Using a Mann–Whitney U test and a data envelopment analysis (DEA), this study provides a view on chartering strategies and efficiency levels of shipping lines in response to the COVID-19 pandemic. The findings reveal that chartering strategies have changed considerably since 2020 and that most shipping lines have pursued a peculiar strategy with a different mix in terms of chartered vessels' size, age, and period of charter. Shipping lines which showed the most marked differences in chartering strategies also yielded higher efficiency scores under DEA, whereas those that did not sustain large changes scored lower in terms of efficiency. This study provides significant insights on and managerial guidance for understanding and benchmarking chartering strategies and their impact on efficiency gains. Highlights: Chartering strategies help achieve fleet optimization and financial sustainability Chartering strategies have changed since 2020 in response to the COVID-19 pandemic Most shipping lines pursued peculiar strategies Those lines that changed significantly chartering strategies yielded higher efficiency scores under DEA Those lines that did not sustain large changes scored lower in terms of efficiency [ABSTRACT FROM AUTHOR]

This study employs modified data envelopment analysis (DEA) models and spatial autocorrelation methods to analyze the characteristics of red tourism transformation efficiency and categorize them into efficiency zones. By utilizing geographic detector models, the interactive driving mechanisms behind spatial differentiation are revealed, providing valuable insights for the high-quality transformation and development of China's red tourism economy. The application of modified DEA models facilitates the evaluation of red tourism resource transformation efficiency by decomposing comprehensive efficiency into single-factor efficiency for individual input and output variables. The results indicate that: (1) Expansion of tourism factors is crucial for achieving red tourism resource transformation in China, with low efficiency in resource endowment investment acting as the primary constraint. (2) Local spatial correlation between production efficiency and resource transformation efficiency demonstrates a decreasing trend from east to west, leading to the classification of China's red tourism resources into five types of efficiency zones. (3) Endogenous ability factors predominantly affect red tourism resource transformation efficiency, with interaction between internal and external factors driving spatial differentiation. [ABSTRACT FROM AUTHOR]

This research explores the nexus between corporate governance and sustainable development, focusing on State-Owned Enterprises (SOEs) in Vietnam. Recognizing the pivotal role of SOEs in the national economy, this study employs a Multi-Criteria Decision-Making approach (MCDM) to assess and enhance the corporate governance frameworks of these entities. First, the Data Envelopment Analysis (DEA) model is employed to identify the most qualified prospective SOEs firms based on several quantitative criteria. Then, the spherical fuzzy analytic hierarchy process (SF-AHP) model is used to identify priority weights for a given set of qualitative criteria, the Evaluation based on distance from average solution (EDAS) model is implemented to rank enterprises in the SOEs sector. To validate the proposed models, a case study conducted within the Vietnamese electric power industry is utilized. The MCDM methodology integrates diverse factors such as business management, corporate social responsibility, and corporate governance shareholder to construct a comprehensive evaluation framework. By applying this approach, the study aims to identify the key drivers and barriers influencing corporate governance practices within Vietnamese SOEs. The study's findings illustrate the efficacy of the suggested approach in evaluating corporate governance performance, providing valuable insights for policymakers, corporate leaders, and stakeholders involved in shaping the governance landscape of SOEs in Vietnam. By aligning corporate governance with sustainable development principles, the research aims to contribute to the ongoing discourse on responsible business practices, offering practical recommendations to enhance the performance and resilience of SOEs in the pursuit of long-term socio-economic and environmental sustainability. [ABSTRACT FROM AUTHOR]

Our objective in this paper is to evaluate the benefits of bus transit. To obtain the more accurate and highly discrimination results, this study establishes an evaluation indicator system from a stakeholder perspective and proposes a novel combined method consisting of dynamic network data envelopment analysis, cross-efficiency evaluation, and Shannon entropy aggregation method. An empirical study of bus transit systems in 33 key Chinese cities from 2016 to 2019 is provided. The results show that the benefit of bus transit in most key cities was ineffective. In contrast to production efficiency, focusing on improving service effectiveness is more conducive to improving the benefits of bus transit. Small cities have higher benefits than large cities. Meanwhile, the benefits of bus transit vary geographically. This evaluation outcome provides a more appropriate basis for decision-making related to the benefits of public transit services, as well as for operational and management studies. [ABSTRACT FROM AUTHOR]

This paper extends the literature on economic consequences of corruption. We simultaneously consider corruption's impacts on output, production efficiency, and environmental performance in an eco-efficiency framework. Pollution is considered as undesirable output in the production process. We construct an eco-efficiency measure from a non-oriented data envelopment analysis model that incorporates a non-convex metafrontier, super-efficiency, and undesirable outputs into a directional distance function. By using panel data from 30 Chinese provinces from 1998 to 2016 in a spatial analysis, we find that corruption, measured by filed-cases of corruption-related crimes, has a significantly negative direct impact on eco-efficiency. The regional spillover effect is not significant for provinces in the same geographical region, but is marginally significant for provinces sharing a common border. [ABSTRACT FROM AUTHOR]

In the era of Industry 4.0, choosing suppliers for online commerce is of utmost importance and calls for the application of efficient, data-centric techniques. Businesses are under increasing pressure to improve their supply chain management strategies and select the best suppliers in the online commerce environment of Industry 4.0. Traditional approaches, however, sometimes don't include a thorough assessment of suppliers across several dimensions. In order to close this gap, this paper proposes a new approach that combines Data Envelopment Analysis (DEA) with the Simple Multi-Attribute Rating Technique (SMART). The first phase is applying DEA to determine how effective suppliers are using the data that has been gathered. DEA offers a quantitative indicator of how efficiently providers convert their inputs into outputs. This combination score enables rating suppliers while simultaneously considering multi-attribute evaluation and quantifying efficiency assessment, then using a number of different criteria, providers are evaluated using the SMART approach. The findings of this analysis help to improve supplier selection procedures in the context of online commerce, which falls under the purview of Industry 4.0. [ABSTRACT FROM AUTHOR]

Introduction: China is exploring methods to achieve economically intensive, green, and high-quality development. Strengthening urban green total-factor production is important for achieving high-quality economic development. Whether the construction of e-commerce demonstration zones (EDZ) can provide new opportunities for high-quality urban development under the dual constraints of energy and environment is a question worth studying. Methods: In order to verify the relationship this study using panel data from 290 prefecture-level cities in China from 2005 to 2020. Data envelopment analysis (DEA) was used to assess the level of high-quality urban development under resource and environmental constraints. The multi-phase difference-difference method (DID) was used to analyze how the e-commerce model city creation policies significantly promoted high-quality urban economic development. Results and Discussion: This study shows that the e-commerce demonstration zone effectively promotes the high-quality development of the city. Heterogeneity tests show that the impact of electric EDZs on high-quality development can be influenced by city size and geographic location (e.g., east coast and mid-west). Based on these conclusions, this study puts forward some suggestions to enhance the attractiveness of small- and medium-sized cities, non-resource-based cities, and western cities by formulating preferential policies. [ABSTRACT FROM AUTHOR]

This article describes the construction of the Luenberger soil quality indicator (SQI) using data on crop yield, non‐soil inputs, and soil profile from three irrigated agroecological zones of Punjab, Pakistan, namely, rice–wheat, maize–wheat–mix, and cotton–mix zones. Plot level data are used to construct a soil quality indicator by estimating directional distance functions within a data envelopment analysis (DEA) framework. We find that the SQI and crop yield relationships exhibit diminishing returns to improving soil quality levels. Using the constructed SQI values, we estimate linear regression models to generate weights that could be used directly to aggregate individual soil attributes into soil quality indicators without the necessity of fitting a frontier to the crop production data. For wheat and rice production, we find that SQI is most sensitive to changes in soil electrical conductivity (EC) and potassium (K). The SQI has direct relevance for site‐specific decision‐making problems where policymakers need to price land resources and conservation services to achieve agricultural and environmental goals. [ABSTRACT FROM AUTHOR]

In the last decade, we have experienced a changing geopolitical context that has caused changes in the energy context. In addition, human activity contributes to global warming or sea level rising, i.e., climate change. A set of action policies have been implemented to continue fighting against this environmental situation (such as the Paris Agreement, the COP27, or the European Green Deal for 2030); therefore, it is necessary to determine whether we are on the right track. It is compulsory to develop predictive models that accurately analyze the current status and the already path undertaken. To this end, this article analyzes the environmental efficiency of the 27 countries of the European Union (excluding the UK) using the so-called data envelopment analysis (DEA). In particular, economic (GDP and GDP per capita), environmental (CO2 and CH4 emissions), electricity production data, the volume of vehicles, and the industrial production rate of the different countries were collected to calculate environmental efficiency. Once these data were collected, the environmental efficiency was calculated using two methods based on the DEA. The results show that out of the 27 countries, only 12 have a relatively high environmental efficiency, although it could be improved, implementing a set of corrections. However, other countries have a low eco-efficiency performance and they must improve in the coming years. We can highlight that rich countries are closer to achieving high environmental efficiency than less developed countries. [ABSTRACT FROM AUTHOR]

This study analyses the impact of corporate social performance (CSP), proxied by the Environmental, Social and Governance (ESG) Index and its pillars and dimensions, on the environmentally adjusted efficiency (EAE) of 239 listed companies, over the period 2016–2021, in the global energy sector. The EAE index, estimated via data envelopment analysis (DEA), assesses the efficiency of companies by considering economic aspects alongside CO2 and energy consumption reduction targets. Our results support the hypothesis that only above a certain level of performance, do CSP practices positively influence EAE, so there is a non‐linear U‐shaped association between the overall ESG score and EAE. The same holds for the social and governance pillars, and the human rights and management subspecific dimensions, on EAE. Other ESG attributes show a positive linear relationship with EAE, namely the environmental pillar, the environmental innovation dimension and the shareholder dimension. Our paper has significant implications for companies, policy makers and researchers insofar as it estimates EAE and indicates which CSP practices should be invested in over the long term to have a positive effect on it. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to investigate the performance of OECD countries' long-term productivity during the period of 1975–2018. Design/methodology/approach: This study employed different approaches to evaluate how efficiency scores vary with changes in inputs and outputs: Data Envelopment Analysis (CRS, VRS and FDH), TOPSIS and TOPSIS of these scores. Findings: The findings suggest that, during the period of this study, countries with higher freedom of religion and with Presidential democracy regimes are positively associated with higher productivity. Originality/value: To the best of the authors' knowledge, this is the first study that uses efficiency models to assess the productivity levels of OECD countries based on several contextual variables that can potentially affect it. [ABSTRACT FROM AUTHOR]

Purpose: The paper aims to craft a non-parametric composite value for the board quality of Indian banks where the weights can be assigned endogenously. Design/methodology/approach: The study employed a non-parametric data envelopment analysis (DEA)-based novel extension known as the benefit of doubt approach. To measure the strength of the Indian bank corporate board in terms of board efficiency (BEF), the study used a mixed approach, i.e. first, the study calculates the percentile ranks of the five attributes that the study assumes are the characteristics of the strong board including board size, number of outside directors, frequency of meetings, non-duality leadership and board gender diversity. Thereafter, the study performs the benefit-to-doubt approach to finally measure the efficiency of the board. Findings: The findings of the study establish that the methodological framework present in the study to measure the strength of the board in terms of BEF has been a much superior method over the other weighted and non-weighted linear average methods. Practical implications: This methodology aids the shareholders, investors and regulatory bodies in rating the Indian banks based on their strength in terms of better monitoring boards and ensuring a smooth agent–owner relationship. Originality/value: The benefit of doubt approach has been a unique and novel methodology to craft the composite value for any multidimensional phenomenon. One of the major benefits of using this approach is that it assigns the weights endogenously to each dimension and thereafter collectively determines the efficiency of such a phenomenon. [ABSTRACT FROM AUTHOR]

The heavy amount of English homework correction has resulted in Teachers' lax examination of homework, insufficient attention to homework problems, and low attention to homework correction. With the continuous growth of the number of educated people, more and more schools begin to have the problem of low efficiency of English homework correction. Therefore, in order to optimize the homework correction system, improve the efficiency of English teachers' homework correction, and give full play to teachers' positive feedback on homework, a smart app on mobile phone can be developed to scan and correct traditional paper homework. Based on image processing technology and neural network algorithm, this paper designs and establishes a mobile app that can recognize and extract English homework topics and handwriting with nearly 90% accuracy through Android system platform. Based on the homework answers entered in the database, the rapid correction of English homework can be realized. After using this software, the overall efficiency of English homework grading has significantly improved. For multiple-choice and fill in the blank questions, the total factor productivity of 14 and 15 units was greater than 1, accounting for 63.6% and 68.1% of the nursing units participating in the study, respectively. This indicates that the efficiency of English homework grading in most units is constantly improving and showing a good development trend. Among them, the homework correction efficiency for multiple-choice questions is only 6 units, and the pure technical efficiency is less than 1, indicating that the improvement of technical means has a significant impact on efficiency. In order to verify the applicability of the software, data envelopment analysis is used to analyze the application of the mobile app to improve the efficiency of English homework correction. the results show that when the smart phone software is not put into use, the efficiency of teachers' English homework correction is poor, and the technical level in the process of correction is too low. After the mobile intelligent software is put into use, the overall efficiency of English homework correction has increased significantly, which can greatly alleviate the pressure faced by English teachers in the process of correcting homework. [ABSTRACT FROM AUTHOR]

Sustainable tourism is the idea of managing the negative impacts or potential for serious harm to the economic, environmental, or social elements of a destination, and thus reaching the goals of sustainable development. This research benchmarks the sustainability of 111 tourist destinations throughout the world, using an advanced integration of a two-stage network DEA under the meta-frontier concept, directional distance function, and network-based ranking methods. The empirical outcomes of these analyses clarify that the sources of sustainable inefficiencies are the self-production process and the technology gap among the tourism regions, rather than the capacity of utilizing the input resources or maintaining the production outcomes. The network-based ranking emphasizes the sufficiency and deficiency of each place, and provides a map of reference among destinations. Based on these, the article reports some managerial suggestions, theoretical implications, and future research directions. [ABSTRACT FROM AUTHOR]

This study sought to assess disaster resilience in Korean metropolitan cities and explore the factors influencing disaster management in these cities. Statistical data from 17 metropolitan cities and provinces in Korea spanning the years 2016 to 2020 were collected. Data envelopment analysis (DEA), a method for estimating relative efficiency using multiple input and output variables, was employed to calculate the disaster resilience scores of these cities. The results indicate higher level of disaster resilience in capital regions and large cities in Korea, with social and economic characteristics significantly influencing resilience. Moreover, the study reveals that robust infrastructure, particularly in terms of housing, strongly impacts resilience scores. The use of DEA allows for the practical evaluation of relative resilience scores without requiring weighted value calculations, making it an effective methodology for assessing city resilience. This study aimed to assess how well Korean metropolitan cities are prepared for disasters and understand what factors affect their disaster management. We collected statistics data on the social, economic, infrastructure, community capital, and institutions of 17 Korean metropolitan cities and provinces from 2016 to 2020. We used a method called data envelopment analysis (DEA) to figure out how well these cities are handling disasters. The results show that capital regions and large cities in Korea are better at handling disasters. This is because factors such as social and economic characteristics have a significant impact on their ability to respond to disasters. Additionally, having strong infrastructure, especially when it comes to housing, plays a big role in how well a city can respond to disasters. Using DEA allowed us to evaluate how well cities are prepared for disasters without needing complicated calculations, making it a useful method for assessing city readiness for disasters. [ABSTRACT FROM AUTHOR]

This research has been carried out with the aim of evaluating the energy, economic and environmental performance of selected countries that export energy resources with the integrated approach of data envelopment analysis (DEA) and game theory. The methodology of this research, including superefficiency and cross-efficiency methods have also been used to rank efficient countries before the cooperation phase. Then, in the cooperation phase, each country is investigated using the method of cooperative games theory and Shapley's value. The resulting model was implemented and the rank of the efficient countries was compared with each other in the super-efficiency and cross-efficiency method (before cooperation) and the Shapley's value method (after cooperation). The results showed that Qatar and Yemen have the highest, Lebanon and Jordan the lowest energy efficiency; Kuwait, Qatar and Turkmenistan have the highest economic efficiency, Iran and Turkey have the lowest economic efficiency; UAE and Qatar have the highest, Iran and Jordan the lowest environmental efficiency. [ABSTRACT FROM AUTHOR]

The ArticulaFito Project conducted a broad analysis of the production base of plants with medicinal, cosmetic, and food value, mapping 26 value chains (CdV) of traditional peoples and communities and family farmers (PCTAFs). The objective is to define criteria to prioritize actions in order to strengthen the mapped CdV, maintaining the identified challenges and opportunities as a reference. Data Envelopment Analysis and Pareto Diagram methodologies were applied to quantitative data extracted from each CdV map. In this way, the CdV set was divided into four groups of performance levels. For each group, an action diagram was drawn, which, ordered the occurrences and their origins, enabling the reporting and indication, in order of priority, of the institutions and actors to be considered in the strengthening process. The group with the best performance had ten species, 70% in the cosmetic segment, in the Amazon biome, and in the northern region, with 80% native under an extractive regime and 20% exotic under a cultivation regime. The Action Diagram generated prioritized actions and investments, optimizing public resources in the productive inclusion of PCTAFs for the sustainable use of (socio) biodiversity. [ABSTRACT FROM AUTHOR]