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The pulp and paper industry converts roundwood and recycled fibre, collected from wastepaper into printing and writing papers, and other specialty grades of paper. The pulp and paper mills in Ontario have been facing extreme competitive pressures, which have affected their performance leading to several mill closures. The purpose of this study is to evaluate and compare the relative performance of three types of Ontario's pulp and paper mills (using all fibre, only roundwood fibre, and only recycled fibre). This study uses bootstrap data envelopment analysis in analyzing and comparing the operational efficiency of the Ontario's pulp and paper mills, with 224 sample data observations over a period of 17 years. The results indicate low levels of overall technical and managerial efficiencies in the pulp and paper mills using recycled fibre. The results of the study highlight that the pulp and paper industry needs to divert their attention to streamlining the manufacturing processes, reducing costs, improving raw material usage, and making capital investments in the new and improved technology, in order to improve the operational efficiency and competitiveness of the Ontario's pulp and paper mills. The pulp and paper mills using recycled fibre require huge capital investments, especially for installing the latest de-inking technology. The results of this study provide policy makers with detailed performance analysis so that future input resources can be reallocated to improve the performance of the pulp and paper mills in Ontario. [ABSTRACT FROM AUTHOR]

The present study proposes a Fuzzy Data Envelopment Analysis (FDEA) approach for analyzing the performance of 8 selected paper mills of India. The proposed approach named FDEA considers the use of fuzzy weights in the objective function and makes use of alpha cut to decide the fuzzy interval. The efficiency of paper mills is evaluated based on 3 input parameters (raw material, energy consumption, and water consumption) and 4 output parameters (paper production, Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD) and Greenhouse Gas (GHG) emissions). Further, this paper also analyzes the effect of negative outputs, like BOD, COD, and GHG on the efficiency of paper mills. The study indicates that FDEA can be used efficiently for evaluating the performance of a particular sector under similar conditions. [ABSTRACT FROM AUTHOR]

This paper discusses mechanisms for the allocation of emission permits (AEP) among a group of manufacturing companies aiming at controlling the total emission level of the group. Data envelopment analysis is adopted and extended to construct the AEP models. Proposed methods allocate the permits on the basis of the current input and output levels of individual firms, rather than historical records. Two variations of AEP mechanisms are considered. One situation is that one of the member firms dominates the responsibility of allocating emission permits on behalf of the group (individual AEP scenario). This dominating firm will maximise its own emission permit before allocating permits among other members in the group. The other situation is that a third-party central governing body is centrally responsible for coordinating the AEP among all group members (Central AEP scenario). Proposed mechanisms are applied to analyse efficiencies of a group of paper mills. The result shows that the mode of central AEP mechanism is a better choice than that of the individual AEP mechanism. Central AEP not only maximises the whole efficiency of the group but also improves efficiencies of individual firms. In contrast, with individual AEP, one firm gains efficiency at the loss of others. [ABSTRACT FROM PUBLISHER]

Manufacturing industry is at its most exciting times with digital revolution. Man, machine, material and tools have to co-ordinate with each other seamlessly to maximize efficiency in a mass production environment. Various theoretical models are in practice to measure efficiency of equipment, gauging, services, maintenance, etc. While all the theoretical models are quite accurate in their approach to measuring the activities, they lagging behind in the process of data collection. The data collection methods are manual and not accurate. In this paper, a model is arrived at to collect live data of production, rejection and idle time in a machine tool with the help of electronic sensors. Effort is made to enhance operator engagement by compelling the operator to feed data so that the data collection becomes closed loop. As all data are digital in nature, meaningful information is sent to the management through an Internet of Things platform. This paper focuses on the digital data flow from the shop floor to management through the Cyber Physical System, enabling smart manufacturing in a mass production environment. The proposed model has been implemented and validated in a mass production set-up, engaged in manufacturing plug shell components. [ABSTRACT FROM AUTHOR]

Achieving carbon peaking and carbon neutrality goals is a fundamental requirement for advancing high-quality development in China. Carbon emission efficiency (CEE) indicates the proportion of optimal emissions to actual emissions in the production system, providing a basis for reasonable carbon emission reductions. To facilitate the realisation of China's goals, this paper analyses CEE and the carbon emission reduction potential in China from 2001 to 2020. Considering the heterogeneity of both regions and industries, this paper proposes a three-hierarchy meta-frontier directional distance function (DDF) method to measure CEE under convex and non-convex assumptions of production possibility set (PPS). The empirical results show that the assumption of convex or non-convex axiom on the innermost PPS has a great impact on efficiency distribution, and the distribution of technology gap rate (TGR) is more affected by the selection of convex or non-convex assumption compared with the distribution of CEE. Currently, China's carbon emission efficiency remains low, mostly due to management inefficiency. The primary industry has more advanced emission reduction technologies than the other two industries. The eastern region has a large potential for carbon emission reduction because of its high carbon emission base, despite its high efficiency. [ABSTRACT FROM AUTHOR]

The purpose of this study is to investigate the effect of service trade globalization on low-carbon globalization. Two newly developed non-radial directional distance functions of UEI (Unified Efficiency Index) and EEPI (Energy-Environmental Performance Index) were adopted to evaluate energy and CO2 emission performances of 30 countries during the period 1980–2013. A multiple regression analysis was conducted based on the Tobit model. Results showed that: (1) Service trade openness has a positive effect on energy and CO2 emission efficiency, and the effect has been intensified with time. (2) Emerging service sectors promoted the improvement of energy and CO2 emission efficiency, while the traditional sectors hindered the efficiency improvement. (3) There existed a "catch-up" effect between less developed countries and developed countries on energy and CO2 emission efficiency. Policy implications are thus drawn on how to promote the improvement of energy and carbon emission efficiency in the context of low-carbon globalization. [ABSTRACT FROM AUTHOR]

The aim of this to study is to examine how non-performing loans on the balance sheets of Japanese banks affect their performance by adopting a material balance principle. The paper outlines how the material balance conditions can be applied when modelling banks' production process in the presence of non-performing loans. The paper utilizes the generalized weak G-disposability principle which accounts for the heterogeneity among banks' input quality. We test how an input-oriented model (non-performing loans are treated as an input), the weak disposability assumption and the adopted material balance approach, affect banks' performance levels. We apply our test on a sample of Japanese banks over the period 2013 to 2019. Our findings indicate that the input-oriented model and the material balance estimator even if they present similar distributions, they account differently the effect of non-performing loans' fluctuations over the examined period. In addition, the results under the weak disposability assumption are found to be different compared to the material balance measures and less sensitive to banks' non-performing loans variation levels. We also provide evidence that the generalized weak G-disposability assumption captures better banks' performance fluctuations that has been caused by the restructuring of the Japanese banking industry. [ABSTRACT FROM AUTHOR]

This paper addresses the question whether energy consumption variables and the disaggregation of output matter in the context of efficiency analysis of container terminals. While it is obvious that the energy consumption of refrigerated cargo is higher than the energy consumption of non-refrigerated cargo, this work investigates whether those differences show in an overall efficiency analysis of terminals. This would point to a potentially important input for efficiency measures, to be considered in future productivity and efficiency analysis of terminals. Starting with a discussion on theoretical concepts and variable selection for measuring the energy dimension of terminal efficiency, this is the first paper that applies data envelopment analysis (DEA) comparing results with and without energy consumption, as well as differentiating productive outputs (dry and reefer container handling). The results reveal how the output disaggregation leads to substantially different efficiency scores and are a first step to show the relevance of output disaggregation and the inclusion of the energy variables as inputs in container terminal efficiency studies. [ABSTRACT FROM AUTHOR]

Maintenance effectiveness in manufacturing facilities is a critical factor in achieving significant competitive advantage. Consequently, attaining higher levels of maintenance effectiveness has recently become a primary goal for managers of world-class organizations. This paper presents a study, which will demonstrate how managers can identify best in class performers in terms of maintenance and how to conduct an improvement analysis using data envelopment analysis (DEA) approach. Data on 13 paper mills collected from a large U.S manufacturing company are used to identify low performers and determine which high performer plants to benchmark in order to improve their efficiency. A discussion of results is also presented. The emphasis of this paper is on the application. [ABSTRACT FROM AUTHOR]

This article investigates the effects of the environmental factors and statistical noise on the efficiency of 89 global forest and paper companies in 2001 using the three-stage DEA method. Empirical evidences indicate the existence of environmental effects on the variation in the efficiency scores measurement. Furthermore, the final adjusted efficiency scores are lower than those scores measured in the traditional first-stage DEA. [ABSTRACT FROM AUTHOR]

This editorial summarizes the papers published in issue 15(2) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper combines a conditionally autoregressive process from the spatial statistics literature with a spatial Durbin error model from the spatial econometrics literature. The second paper feeds a multistage and multilevel data envelopment analysis with a microeconomic foundation. The third paper provides empirical evidence that Flegg's location quotient combined with a gravity model produces the most accurate interregional input–output multipliers. The fourth paper investigates the impact of inventor networks on the number of patents per capita in Brazil. [ABSTRACT FROM AUTHOR]

Despite various supervised methods and algorithms, prediction methods do not necessarily provide the optimal values of the outputs. In this paper, an approach is proposed based on the integration of the clustering algorithm and a new mathematical programming model for predicting the efficient and optimal level of hospital outputs. In the first stage, units are evaluated using data envelopment analysis (DEA) and then, high-efficiency units are selected. In the second stage, the selected units are clustered based on the inputs of the units using the fuzzy C-means algorithm. For each unit to be estimated, the corresponding cluster is found and the closest unit to the target unit is determined. Finally, using the proposed new mathematical programming model, the optimal values are estimated based on the more efficient unit. A case study on Iranian hospitals illustrates the implementation of algorithms and methods and shows the abilities of the proposed approach. [ABSTRACT FROM AUTHOR]

Along with the popularity of Olympic Games, evaluating and ranking participating nations has become one of the hottest issues in recent years. Data envelopment analysis (DEA) is extensively used for participating nations' performance evaluation, while the prior literature mainly addresses the maximum efficiency by ignoring the weights diversity, which might lead to unreasonable and biased results. By considering the fixed-sum medals constraint, this paper proposes an integrated approach of stochastic multicriteria acceptability analysis (SMAA) and DEA for evaluating the participating nations. The proposed approach addresses the weights diversity and multiple equilibrium efficient frontiers by investigating the overall feasible space, and two strategies are considered to guarantee the fairness concern for calculating the efficiencies. Besides, the proposed approach provides both rank acceptability and holistic acceptability index to obtain the complete ranking from the best to the worst and to get the relative ranking relationship in the overall feasible space. The proposed approach can provide more reasonable performance measurements since it explores different rank positions and improves the whole satisfaction of all participating nations. Finally, the proposed approach is applied to empirically analyze the participating nations in the Winter Olympic Games from 2010 to 2022 and some valuable analytical results are provided. [ABSTRACT FROM AUTHOR]

The determination of reasonable improvement direction is the key difficulty of directional distance functions in data envelopment analysis target setting method, but there is no consensus direction determination method at present. This paper introduces the concept of minimizing the distance between decision-making units (DMUs) and production frontier for constructing a new endogenous mechanism of improvement direction, and the corresponding target setting method is constructed to setting target for DMUs, which is used to minimize the total projection distance between DMUs and their targets. In addition, the free direction and unit invariant of improvement direction are discussed for meeting the diverse needs of decision makers. [ABSTRACT FROM AUTHOR]

The sharing economy affords new opportunities to the global tourism industry, accelerating the development of tourism at a striking rate. This paper examines productivity of the bed and breakfast (B&B) industry and how to improve the performance of the B&B industry in a sharing economy. A modified global Malmquist index using slack-based measures is developed to measure productivity, and benchmark selection models using technology forecasting are proposed to improve future performance. The future technology is forecasted by averaging the frontier shifts (technology changes) in previous periods. This study challenges the implicit assumption that the technology will be stationary in traditional benchmarking, and suggests that how the information of frontier shifts derived from Malmquist index can be used to forecast future technology in a rational manner. The empirical results inform that there is a productivity growth in the B&B industry in a sharing economy, and the main driver of the growth is technology progress rather than performance improvement. In particular, a counterintuitive but interesting result is that the B&B industry experienced a slight productivity growth after the outbreak of COVID-19. The benchmarks in 2021 and 2022 are forecasted to improve the performance of the B&B industry. [ABSTRACT FROM AUTHOR]

The implementation of the innovative city pilot policy (ICPP) is conducive to promoting the urban industry–university–research collaborative innovation, but there is no clear answer to how industry–university–research knowledge flow is affected by the policy. Based on the knowledge flow process divided into the knowledge creation stage and knowledge transfer stage, this paper uses the two-stage Data Envelopment Analysis (DEA) model to measure the dual efficiency of urban industry–university–research knowledge creation and knowledge transfer. And the paper also adopts the spatial difference-in-difference (SDID) model to study the impact mechanism of ICPP on the knowledge flow dual efficiency. The results show that there are positive spatial spillover effect of the knowledge creation efficiency (KCE) and knowledge transfer efficiency (KTE). And the effects of ICPP on industry–university–research KCE and KTE are both manifested as the promoting impact. Furthermore, ICPP has a significantly positive impact on the urban innovation atmosphere (UIA), and UIA plays a partial mediating role in the impact mechanism of ICPP on KCE and complete mediating role in the relationship of ICPP and KTE. [ABSTRACT FROM AUTHOR]

This study analyses sustainability and competitiveness through measurements of efficiency, using data envelopment analysis. It constructs a meta-frontier non-radial directional distance function (meta-frontier NDDF) approach, which is then used to define a tourism development index and a tourism sustainability index. Using these indexes, the paper evaluates the efficiency of the tourism sector and its dynamic evolution for 27 cities in the Yangtze River Delta, China, (YRD) from 2010 to 2019. Considering regional heterogeneity, this paper analyzes the meta-frontier, group-frontier efficiency and technology gap ratio of urban tourism in the YRD, and explores the competitiveness of the cities. The results show that the more traditional measure of tourism efficiency, namely the tourism development index, which does not take account of the sector's undesirable output (i.e., the negative impacts of carbon emissions from travel), produces overestimates. This study highlights the following practical implications: The increasing competition among tourism destinations requires tourism industry managers to determine the appropriate allocation of resources to promote the sustainable development of urban tourism. In the context of the need for global 'carbon neutrality', more consideration should be given to the negative impact of tourism on the natural environment to enhance the competitiveness of tourist destinations. [ABSTRACT FROM AUTHOR]

This paper provides a modification of a recently developed common weight model for technology selection. The discrimination power of the existing model depends on a discriminating parameter. Although larger values of this parameter can give more discrimination, it should also be small enough to guarantee the existence of at least one efficient DMU. Hence, different values of this parameter should be examined to determine the proper value. In the model proposed here, the largest possible value of the parameter is utilised to maximise the discrimination power, and the existence of an efficient DMU is guaranteed by adding a few constraints. In addition, the paper presents comments on existing models, and the properties and the advantages of the model are explained. The contents of the paper are illustrated by several numerical examples. [ABSTRACT FROM AUTHOR]

The subject of this paper is the assessment of the efficiency of oil companies operating in the Republic of Serbia. This paper presents the possibilities of applying non-parametric methods in researching the efficiency of oil companies in the Serbian market. In addition to the standard variables for measuring technical efficiency, the market share should be taken into account, because the oil market is an example of an imperfect competition market. By applying the quantitative-analytical method (Data Envelopment Analysis), obtained results show the development of the efficiency of oil companies in the relevant market, and indicate that the efficiency of oil companies improved during the analysed period. However, the results also indicate that there is still a problem of misallocation of resources. The reasons for this outcome are interesting and debatable for this industrial area. [ABSTRACT FROM AUTHOR]

Thus far, the data envelopment analysis (DEA) model has not been used to examine the lagged effects of advertising goodwill stock on promotional efficiency. Thus, this study develops a dynamic DEA framework to illustrate the lagged effect of advertising goodwill stock on the dynamic promotional efficiency of major automobile manufacturers in the United States. The advertising goodwill stock in five automobile producers was measured using the econometric model. Subsequently, the advertising goodwill stock was treated as a lagged effect in a dynamic DEA framework. We analyse the empirical results and formulate the following two important findings: First, the results demonstrate that the lagged effect of advertising goodwill stock can lead to changes in the promotional efficiency of advertising. Second, the paper discusses ways that inefficient automobile manufacturers can improve marketing strategy implementation. [ABSTRACT FROM AUTHOR]

Port organisation and specialisation, as well as the geographical location and port size, are factors that appear to impact more on the performance of analysed ports rather than simply technology. Interestingly, although port size is not a factor for achieving efficiency, most of the better performing ports are indeed large and specialised. The current study discusses preliminary results on the impact of automation technology on port efficiency using a two-step approach (i.e. Data Envelopment Analysis and statistical regression) for a sample of 30 ports worldwide. [Extracted from the article]

Online reviewers are site users who share their opinion & experience over the internet and influence the perception & purchasing intentions of potential customers. Therefore, considerable attention is needed to identify credible and trustworthy online reviewers. For marketing through electronic-word-of-mouth (eWOM), it is important to find those online reviewers who have the potential to spread the product image efficiently and can positively influence the buying intention of potential customers. In this paper, we develop an innovative model based on data envelopment analysis (DEA) to identify good quality reviewers that have a commendable impact on readers or potential customers, by considering the determinants related to credibility, trustworthiness, expertise, travel experience, and identity disclosure of online reviewers as inputs/outputs in the DEA-based models. We have also ranked the reviewers using the balance index (BI) based technique. The results of this paper will aid the e-marketers to understand the variables related to reviewers which help them in finding the highly influential reviewers available on their website. The managerial and theoretical implications are also discussed for the practitioners, business managers, and researchers in the e-service sector. [ABSTRACT FROM AUTHOR]

The paper assessed linkage amongst governance mechanisms and efficiency of insurers in Kenya over 8 year period from 2013 to 2020. The study estimated the efficiency of insurers using DEA approach in light of previous literature during the first stage. During the second stage, the bias-corrected efficiency scores were regressed against corporate governance (CG) proxies and control variables using SW (2007) approach on a sample of 53 insurers. Using this two-stage, bootstrapping SW approach, the study documents that the Kenyan insurers are technically inefficient. Overall, the paper presents evidence showing that CG variables influence technical efficiency of insurers in Kenya. Precisely, board independence, gender diversity and audit quality positively and significantly impact Kenyan insurers' technical efficiency. Further, the paper finds that size of the board negatively affect Kenyan insurers' technical efficiency. However, the study established insignificant relationship between CEO duality, intensity of board activities and technical efficiency. The paper makes contribution to the bourgeoning reservoir of empirical works on the insurers' CG-efficiency nexus from an emerging market perspective. Particularly, the article offers empirical insights on some of the least studied CG proxies such as gender diversity, quality of audit and intensity of board activities. The research outcomes also have practical implications for regulators, academia, insurers, government policy makers, practitioners, shareholders and consumers of insurance products by raising their awareness on the influence of CG proxies on the efficiency of the insurers. This is especially beneficial in countries that are pursuing CG and efficiency policy reforms. [ABSTRACT FROM AUTHOR]

The Russian invasion of Ukraine has generated a new impetus towards an enhanced European defence pillar, while many EU members have announced significant increases in their respective defence budgets over the coming years. Expectedly, a large percentage of the capital and technological inputs required to support the efforts towards a common European defence and the increased defence needs of many EU members will be procured from the European Defence Technological and Industrial Base (EDTIB). The European defence companies are among the major suppliers of conventional arms in the world. Their cumulative share of world arms exports is the second largest globally. This paper uses a Benefit-of-the-Doubt (BoD) model via Data Envelopment Analysis (DEA) to comparatively evaluate the sales performance of major European defence industries vis-à-vis other major international arms producers. The sample used in the analysis contains 72 firms and spans the period 2016–2020. The findings indicate that on the whole US defence manufacturers have a dominant presence among the biggest global producers and outrank many major European companies. These findings offer valuable policy recommendations. [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 investigates the relationship between internal corporate social responsibility (ICSR) and firm efficiency. Our research employed a two-stage analysis of 33,413 firm-year observations from between 2008 and 2020. First, we measured the level of firm efficiency using data envelopment analysis (DEA). Second, we used panel regression to investigate the impact of investments made by firms into ICSR on their efficiency. Our results showed that such investments into ICSR (e.g. on employee development) increased firm efficiency during the study period. [ABSTRACT FROM AUTHOR]

In this paper, we empirically analyse the redistributive efficiency of fiscal policy considering its degree of decentralization for a sample of thirty-five countries over the 2000–2016 period. To do this, we follow a two-stage process where we first employ a bootstrap Data Envelopment Analysis (DEA) method to estimate the redistributive efficiency of cash transfers and direct taxes at the central and subnational levels. We obtain evidence that redistributive efficiency has diminished after the Great Recession (2007–2008), and is lower in the Southern European countries, and higher in almost the rest of Europe and the Latin American countries. Second, a bootstrap truncated regression analysis is used to identify the contextual factors that might explain redistributive efficiency variation across countries and time, supporting the argument that good governance is a requirement for decentralization to be efficient in promoting policy outcomes. [ABSTRACT FROM AUTHOR]

This paper is concerned with how to stably arrange the total input resources and output productions when the total outputs can be forecasted in a centralized decision-making environment based on data envelopment analysis (DEA). It usually involves the participation of all individual decision-making units, each contributing in part to the total production. Two stability indexes are defined to assess the stability of production planning, i.e. scale stability, efficiency and technology stability. Then, we propose a DEA-based model to derive the next period production planning. Finally, we illustrate the proposed approach and compare the results between two existing studies and this paper by using three numerical examples. The results show that the proposed production planning in this paper is stabler than existing studies. It implies that the production planning in this paper would be more practicable for real production. [ABSTRACT FROM AUTHOR]

As the "sixth largest city group in the world", the Yangtze River Delta region is an important economic growth point and core economic area in China. While achieving rapid economic growth, the amount of waste generated is increasing day by day, and the investment in environmental protection is constantly increasing. Among them, MSW collection and disposal funds accounted for 57.40% of the fixed assets investment in environmental sanitation in 2017. To improve the efficiency of existing environmental protection investment, this paper is based on the existing academic research at China and abroad, with the help of the Data Envelopment Analysis (DEA) model. This paper analyzed the economic indicators of 27 cities in the Yangtze River Delta for MSW collection, transportation and disposal to measure economic efficiency, identify and improve inefficiencies. The research results show that the average efficiency of the 27 cities in the Yangtze River Delta is at a relatively high level. Six cities have the most effective comprehensive technical efficiency. These six cities constitute the effective frontier of the municipal solid waste transfer system. The overall efficiency has a comparative advantage; 9 cities have the best pure technical efficiency, accounting for 33 of all cities. %, the pure technical efficiency of the remaining 18 cities is low, indicating that these cities have not fully utilized their resource input under the current scale, and the efficiency of resource utilization needs to be improved. Finally, this paper proposes suggestions for improvement from the perspective of environmental sustainability. To improve MSW collection and disposal efficiency, differentiated management should be implemented in cities in the Yangtze River Delta. Implications: This paper conducts an empirical analysis on the efficiency of MSW collection and disposal in the Yangtze River Delta in China in 2017. Based on the calculation of the DEA model, our conclusion is that although the collection and disposal system of MSW in the Yangtze River Delta has been significantly improved, the level of collection and disposal of some MSW has not reached the optimal level: (1) Comprehensive technical efficiency is the most effective Cities accounted for 22% of the total number of cities studied. (2) 33% of the cities in the Yangtze River Delta achieve the best pure technical efficiency; (3) Among the 27 cities, 6 cities have the best scale efficiency, and the remaining 21 cities have not reached the best scale efficiency. [ABSTRACT FROM AUTHOR]

Many of the analytical models commonly used in educational research often aim to maximize explained variance and identify variable importance within models. These models are useful for understanding general ideas and trends, but give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method rooted in organizational management that makes such insights possible. Unlike models alluded to above, DEA does not explain variance. Instead, it explains how efficiently an individual utilizes their inputs to produce outputs, and identifies which input is not being utilized optimally. This paper provides a history and usages of DEA from fields outside of education, and describes the math and processes behind it. This paper then extends DEA's usage into the educational field using a study on child reading ability. Using students from the Project KIDS dataset (n = 1987), DEA is demonstrated using a simple view of reading framework, identifying individual efficiency levels in using reading-based skills to achieve reading comprehension, determining which skills are being underutilized, and classifying new subsets of readers. New subsets of readers were identified using this method, with implications for more targeted interventions. [ABSTRACT FROM AUTHOR]

Education is important at national, local and individual levels. Its benefits accrue both to society and to individuals, and as such provision of education in many countries is paid for at least in part from the public purse. With competing demands for government funding, it is important for education to be provided as efficiently as possible. Efficiency occurs when outputs from education (such as test results or value added) are produced at the lowest level of resource (be that financial or, for example, the innate ability of students). This special issue is devoted to the topic of efficiency in education, and is well-timed given that governments around the world struggle with public finances in the wake of the global financial crisis of 2008. In this paper, we explore and provide an overview of the themes of the special issue and introduce the papers contained therein. [ABSTRACT FROM AUTHOR]

When it comes to performance evaluation, productivity analytics, and benchmarking, Data Envelopment Analysis (DEA) is the most widely used tool. To this aim, the paper considers pre-processed data via DEA and adds the DEA efficiency value into the logistic regression model, which can improve the accuracy of the basic logistic regression model. Based on a sample of U.S. public firms from 2012 to 2016, the empirical results illustrate that, compared to the conventional DEA models, the proposed models yield more useful productivity expression for diversified firms, and that the model-suggested resource reallocation is linked to better firm performance. [Extracted from the article]

This paper explores the foundations for developing incentives for influencing units operating within centrally managed organizations. We begin by laying out the theory of managerial control in principal-agent contexts and draw from the incentive mechanisms developed in the related field of economic regulation. In particular, we highlight issues, differences and similarities in three recently proposed approaches under these circumstances, not only to compare them, but more importantly to motivate and arrive at requirements that should be met by incentivization systems in centrally managed multi-unit organizations. The stipulated requirements are not intended to be exhaustive but rather aim at defining conceptual foundations for further discussions and encouraging avenues for future research in this field. Our investigations are supported by graphical examples and an analysis of empirical data from banking. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate agricultural sustainability as a collective issue involving multiple rather than individual farms. Through the utilization of energy consumption as a proxy, we propose a novel methodology that evaluates the impact of farm consolidations on agricultural sustainability while accounting for resource preferences. Our approach incorporates the ordered weighted averaging (OWA) operator within an inverse data envelopment analysis (IDEA) model to identify post-merger farms that meet preset efficiency targets. We employ a DEA cross-efficiency (DEA-CE) procedure to select merger plans that maximize agricultural sustainability for each preference scenario. By analysing a case study of 43 tomato greenhouse farms in Biskra, northern Algeria, our findings demonstrate that mergers can significantly enhance agricultural sustainability, surpassing the potential of individual farms by a factor of over 15. Additionally, the adoption of the most sustainable merger plan can lead to energy savings of more than 69%. Irrespective of the preference scenario, substantial energy savings in machinery, fertilizers, diesel, and electricity ranging from 22.92% to 73.73% were observed. These results emphasize the strategic role of merger processes in promoting agricultural sustainability and optimizing resource utilization. [ABSTRACT FROM AUTHOR]

A body of empirical literature exists which sets out how the accommodation industry performs across a range of locations. However, research on tourism regions in terms of its accommodation industry remains underdeveloped, especially in the Covid-19 pandemic when tourism faced unprecedented adversity and need to find a way to move forward. In an attempt to address this and take the Australian accommodation industry as a case study, this paper sought to investigate the efficiency of Australian tourism regions in the accommodation industry for the period of 2014/15–2017/18. The findings clearly showed that Australian tourism regions had seen significant growth in terms of their efficiency in the accommodation industry over the surveyed period. The Australian commercial large cities, namely Sydney, Melbourne, Brisbane, and the Goal Coast, represent perhaps the best example, having obtained a higher efficiency than all other tourism regions. Exogenous factors, such as the occupancy rate, the average daily rate, the number of international visitors and the number of domestic visitors overnight were identified as influencing the technical efficiency score of tourism regions, with policy formulation and implementation identified as being key to improving the efficiency of the accommodation industry at the regional level for a post-Covid-19 period. [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 examine scientific research and innovation and commercialization of scientific and technological achievements, we construct a two-stage data envelopment analysis(DEA) model with shared inputs, taking into account the capacity for university construction and the economic benefits of scientific research at colleges and universities. On the basis of this model, the paper explores overall and sub-stage efficiency changes at colleges and universities under two kinds of model. We find that the overall level of scientific research at colleges and universities varies greatly under the model of valuing innovation in science and technology and ignoring commercialization of scientific and technological achievements; the weaknesses in the scientific research system differ under the two models, but the changes in their efficiency are similar. Tsinghua University and the Harbin Institute of Technology have become effective in both models. We further find that the scientific research under a two-stage balanced model is better coordinated. Finally, the paper offers some suggestions on the current of colleges and universities. [ABSTRACT FROM AUTHOR]

In this paper, we present a methodology, by utilising a nonparametric multivariate cumulative sum control chart and data envelopment analysis in tandem, to evaluate and monitor distribution network performance by simultaneously considering multiple performance factors and their interrelationships. While these methods were previously applied individually, we demonstrate that their combined use can provide more powerful results in performance assessment, monitoring and improvement. Our approach contributes to the domain of supply chain analytics and risk management as it can provide new insights into network performance based on real time and past data. We present the application of our approach on data obtained from The Dow Chemical Company. [ABSTRACT FROM AUTHOR]

Recently worldwide Islamic finance has gained considerable attention. However, Islamic financial institutions face multiple risks to sustaining and growing further. Against this backdrop, the paper examines the impact of both liquidity and credit risk on the efficiency of Islamic banks (IBs) operating in Bangladesh. This paper uses IB's data from 2007 to 2018 and offers a two-stage assessment. In the first stage, it uses data envelopment analysis (DEA), and in the second stage regression models to assess the impact of both liquidity and credit risk on the efficiency of the IBs. Efficiency scores confirm that IBs are operating with an 86% efficiency level through a 68% share in the constant returns to scale (CRS). Our results also confirm that both liquidity risk (LR) and credit risk (CR) have a significant impact on the efficiency of the IBs in Bangladesh. A higher score for efficiency is shown by a higher liquidity risk, whereas mixed results are confirmed by credit risk indicators. Moreover, the Z-score (a bank stability measurement) and number of branches (a measurement of the bank's network coverage), have a positive impact on efficiency. On the other side, the size of the bank and the financial crisis period show a negative relationship with the bank's efficiency. The findings of our paper significantly contribute to the Islamic banking sector, especially for the policymakers and academic researchers. [ABSTRACT FROM AUTHOR]

Data envelopment analysis (DEA) has been widely applied in measuring the efficiency of homogeneous decision-making units. Network DEA, as an important branch of DEA, was built to examine the internal structure of a system, whereas traditional DEA models regard a system as a 'black box'. However, only a few previous studies on parallel systems have considered the interdependent relationship between system components. In recent years, parallel interdependent processes systems commonly exist in production systems because of serious competition among organisations. Thus, an approach to measure the efficiency of such systems should be proposed. This paper builds an additive DEA model to measure a parallel interdependent processes system with two components which have an interdependent relationship. Then, the model is applied to analyse the '985 Project' universities in China, and certain policy implications are explained. [ABSTRACT FROM AUTHOR]

Data have been utilised in production research in meaningful ways for decades. Recent years have offered data in larger volumes and improved quality collected from diverse sources. The state-of-the-art data research in production and the emerging methodologies are discussed. The review of the literature suggests that production research enabled by data has shifted from that based on analytical models to data-driven. Manufacturing and data envelopment analysis have been the most popular application areas of data-driven methodologies. The research published to date indicates that data mining is becoming a dominant methodology in production research. Future trends and opportunities for data-driven production research are presented. [ABSTRACT FROM AUTHOR]

Data envelopment analysis (DEA) is a method for measuring performance of decision making units (DMUs). Conventional DEA models view DMUs as black boxes. Network DEA (NDEA) models have been developed to overcome this shortfall. This paper develops a new NDEA model based on modified enhanced Russell measure model. This paper measures performance of humanitarian supply chains (HSCs) by an NDEA model. Capabilities of the proposed model are addressed by theorems. However, in the real world, there might be stochastic data. This paper presents a stochastic version of the proposed NDEA model to measure the performance of HSCs. We analyse main properties of our model. We present a case study to demonstrate the applicability of the proposed model. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to propose a new purely data-driven method for measuring impact of road safety culture based only on the aggregated data on traffic safety indicators rather than on questionnaire surveys. The paper proposes the use of data envelopment analysis (DEA) with undesirable inputs-outputs for quantitative assessment of the impact on road fatalities of road safety culture. This method determines a number of road safety factors and then distinguishes between the effects of specified factors and the cultural factors. The applicability and usefulness of the proposed DEA are illustrated in a real-world application for assessment of the impact of road safety culture on Iran provincial road fatalities in the time period of two years. Results of DEA enable differentiating between provinces according to the impact of cultural aspects on fatality rate. Moreover, results show that road safety culture on average has improved in the time period of two years. The results of this study may be considered as a basis for traffic safety culture (TSC) interventions at provincial level. This paper provides a new opportunity to look at road safety culture across provincial road transportation systems in Iran and represents a critical step toward understanding relationship between safety culture and safety performance. [ABSTRACT FROM AUTHOR]

In contrast to traditional efficiency analysis models in the field of data envelopment analysis (DEA) with undesirable outputs, this paper proposes efficiency models with the joint use of weak and managerial disposability assumptions. First, we develop a deterministic efficiency analysis model to deal with undesirable outputs in a production process. Due to the importance of data variability and uncertainty, the technical efficiency analysis is sensitive to these variations. Using chance-constrained programming theory, we extend our proposed deterministic model to a stochastic production system. To demonstrate the real-world applicability of our proposed models, we employ an empirical application based on actual Iranian gas distribution company data. Although this empirical application is illustrative, our proposed scheme could be used to evaluate the relative efficiency of many real-life production units whose underlying production systems are frequently stochastic. [ABSTRACT FROM AUTHOR]

Data Envelopment Analysis (DEA) presents the typical characteristics of a data-driven approach with the specific objective of determining technical efficiency and production frontiers in Engineering and Microeconomics. However, by construction, the frontier estimator generated by DEA suffers from overfitting problems; something that contrasts with currently accepted models in machine learning. In this regard, DEA can be seen as a preliminary stage of a more complex approach, where the aim is to avoid overfitting in order to determine a proper description of the underlying Data Generating Process that is behind the generation of the observations in a production process. In this paper, we introduce a possible solution to overcome the overfitting problem associated with DEA that is based on cross-validation. This process "peels" the standard DEA frontier (removing certain supporting hyperplanes) until a new convex technology, which also satisfies free disposability in inputs and outputs but not the principle of minimal extrapolation, is determined. Our approach is tested by resorting to a computational experience. Additionally, we illustrate how the new method could be used as a complement to the standard DEA technique through an empirical application based on a PISA (Programme for International Student Assessment) dataset. [ABSTRACT FROM AUTHOR]

This paper investigates Public Sector Performance (PSP), Public Sector Efficiency (PSE), and Data Envelopment Analysis (DEA) scores for 11 CEE countries, using the methodology proposed by Afonso et al. (various years). Our calculations are based on seven components of the public sector, described by 12 opportunity indicators and six Musgravian indicators. Moreover, we adapt and extend the Afonso, Schuknecht, and Tanzi methodology in order to be able to compute annual scores for PSP and PSE. The results show that expenditure performance is higher in the group of medium-sized governments. Additionally, medium-sized government groups obtained the highest efficiency scores. [ABSTRACT FROM AUTHOR]

This paper examines whether regulatory compliance with governance norms explains the profit efficiency of Indian banks. Using a data envelopment analysis approach, a compliance index is built on 48 governance norms defined on board, audit, risk, remuneration, shareholder relationship, and disclosures. The study also identifies the position of banks on a 2 × 2 matrix based on their governance and profit efficiency levels. The econometric analysis establishes that mere regulatory compliance with governance codes does not necessarily ensure higher profit efficiency. Instead, the panel quantile estimates uncover evidence of a positive externality to governance compliance for banks with low profit efficiency levels. [ABSTRACT FROM AUTHOR]

Sustainable transport has received substantial attention globally. Evidently, transportation is a major contributor to global carbon emission, which causes the degradation of environmental quality and safety. Economic-oriented activities are performed in terms of inclination aspect. Thus, this paper aims to analyze whether and how environmental pollution and fatality, economic-oriented transport, and socioeconomic factors affect transport efficiency. For this purpose, panel data from 2000 to 2020 for 35 OECD countries are used. First, data envelopment analysis slack-based measure and windows analysis are employed to measure transport efficiency by using fourteen inputs/output variables. Second, econometric analysis demonstrates the relationship between socioeconomic factors and sustainable transport efficiency. Outcomes suggest that 30.2% increase in sustainable transport efficiency is due to a 1% increase in transport–household expenditures. OECD countries significantly performed with high economic efficiency scores for the examined period. Econometric analysis indicates that socioeconomic factors have a remarkable impact on sustainable transport efficiency. [ABSTRACT FROM AUTHOR]

This paper investigates one of the key factors of sustainable development in the tourism sector: productive efficiency. A firm is technically inefficient when it can produce a higher output level with existing input quantities. Technical inefficiency can be reduced by stimulating the incentive of workers and employing suitable managers. On the other hand, scale inefficiency occurs when an enterprise is not producing in the constant returns to scale region. Such inefficiency can be lessened by reallocating resources to achieve an optimal production scale. Most previous empirical studies of efficiency analysis are based on the assumption of convex production sets. This paper points out that when this assumption does not hold, policies on resources allocation would be misled. To remedy this deficiency, this paper adopts a newly developed empirical frontier to model nonconvexity in the production set. It is found that, in the tourism sector, travel agents and hotels are technically efficient and scale inefficient. Consequently, a policy which leads to the merging of small firms to improve the efficiency of the market will best suit the sustainable development of the tourism sector. Our results are very different from those derived from the existing production frontiers in Data Envelopment Analysis. [ABSTRACT FROM AUTHOR]

This paper analyses the impact of rate capping policy on local council efficiency. It also examines a set of exogenous factors associated with local government efficiency. A semi-parametric framework based on data envelopment analysis is applied to construct an efficient frontier for Victorian local governments. Findings indicate that rate capping policy had no significant effect on the overall economic efficiency of Victorian local governments. Furthermore, the policy appears to have an adverse effect on the efficiency of metropolitan councils during the study period. The heterogeneity of local governments needs to be considered when setting rate caps. [ABSTRACT FROM AUTHOR]