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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]

Improving energy efficiency is regarded as a key path to tackling global warming and achieving the Sustainable Development Goals (SDGs). In 2020, the energy consumption of the world's ten major energy-consuming countries accounted for 66.8% of the global total. This paper applied data envelopment analysis (DEA) to calculate these ten major energy-consuming countries' total-factor energy efficiency (TFEE) at national and sectoral levels from 2001-2020, and explored the influencing factors of total-factor energy efficiency with the Tobit regression model. The results showed significant difference in the ten countries' energy efficiency. The United States and Germany topped the list for total-factor energy efficiency, while China and India were at the bottom. Meanwhile, the energy efficiency of the industrial subsector has increased significantly over the past two decades, while that of the other subsectors has been relatively flat. The industrial structure upgrading, per capita GDP, energy consumption structure, and foreign direct investment had significant impacts on energy efficiency with national heterogeneity. Energy consumption structure and GDP per capita were determinative factors of energy efficiency. [ABSTRACT FROM AUTHOR]

The need of translating increasing outlays into better outcomes on various public programmes has attracted the attention of researchers worldwide to focus more on the quality of public spending, often assessed in terms of its efficiency. The present article is a contribution to the existing literature on the subject in that it assesses the efficiency of government expenditure of Indian states for two most basic social services—elementary education and nutrition during 2014–2015 and 2018–2019 using data envelopment analysis and Malmquist productivity index techniques, in both input‐oriented as well as output‐oriented settings under variable returns to scale assumption; it constructs the average performance index for children at elementary education and malnutrition index for women and children to utilise them as output indicators; and it adopts a robust bootstrap truncated regression procedure to avoid various econometric issues while estimating the impact of selected environmental factors on bias‐corrected inefficiency scores. The major findings of this article seem to suggest that, while states should be provided greater flexibility in their fiscal operations, they have to complement their fiscal autonomy with good governance to improve the efficiency of their spending on basic social services. Towards this end, states like Bihar, Jharkhand and those belonging to North‐Eastern and Himalayan regions need special attention with a different set of development policies. [ABSTRACT FROM AUTHOR]

Since the 1980s, many electricity markets around the world have undergone restructuring aimed at improving efficiency. In 2002, the Chinese government also introduced a vertical unbundling reform to dismantle vertical monopolies and boost efficiency in the power sector. This study estimates the unified, operational, and environmental efficiency to comprehensively assess the impact of China's vertical unbundling on the production performance of thermal power firms. A non-radial data envelopment analysis (DEA) approach is employed to measure these efficiencies. Subsequently, a difference-in-difference model is used to assess the reform's effects. Empirical results show that the vertical unbundling improved the unified efficiency of firms. Further analysis indicates that the reform improved the operational efficiency of firms by increasing their capacity utilization and coal quality. Additionally, we find that the reform led to an increased utilization of source control technologies but resulted in a reduction in the use of end-of-pipe treatments. Due to the opposing effects on different pollution treatment stages, the reform did not have a significant impact on environmental efficiency. [ABSTRACT FROM AUTHOR]

The European Union (EU) budget allocated to agri-environmental schemes (AES) has increased consistently over the past 20 years. European citizens should expect effective spending of these public funds, so investigation of the effects of these schemes on both environmental benefits and farm efficiency is warranted. We examine the effects of European agri-environmental schemes on farm-level eco-efficiency. Our analysis combines data envelopment analysis and impact assessment methods to evaluate the impact of scheme payments on eco-efficiency measures. Our results suggest that there is considerable scope for eco-efficiency improvements, both for dairy and crop production. Results also show that the average change in eco-efficiency scores does not vary significantly between AES participants and non-participants, which questions the effectiveness of present AES. [ABSTRACT FROM AUTHOR]

This paper analyzes the efficiency and efficiency changes of 57 Turkish natural gas distribution firms in the period 2016-2021 with input-oriented Data Envelopment Analysis (DEA) and Malmquist Total Factor Efficiency (TFP) Index, respectively. The efficiencies of the distribution firms are analyzed using both the aggregated data of all years and the six‐year multiperiod analysis. According to the results of the aggregated model, the technical efficiency, pure technical efficiency, and scale efficiency of the firms on average are 77.4%, 81.2%, and 95.4%, respectively. 32 (14) scale-inefficient firms have increasing (decreasing) returns to scale. Only three of the 10 firms that are technically efficient in the aggregated model are found to be fully efficient in all periods. Natural gas distribution firms are classified as small firms and large firms according to their gas delivery amounts, and the scale efficiency of these firms and the changes in the number of large and small firms with increasing or decreasing returns to scale are examined on a yearly basis. Over the period 2016-2021, total factor productivity decreased by an average 1.8% annually, as a result of an annual average decrease of 1% in technical efficiency and an annual average decrease of 0.8% in technological change. The reduction in technical efficiency is due to 0.6% decrease in pure technical efficiency and 0.4% decrease in scale efficiency. [ABSTRACT FROM AUTHOR]

Malaysia has great geo-economic advantages, especially in becoming a major logistics and investment hub. However, as operational risk events create uncertainties, logistics companies suffer from supply and demand issues which affect their bottom lines, customer satisfaction and reputations. This is a pioneer paper to propose the optimization of the efficiency of listed logistics companies in Malaysia with operational risk factor using a data envelopment analysis (DEA) model. The basic indicator approach (BIA) is used as an output indicator for the operational risk capital requirement factor in the proposed model. This paper has practical and managerial implications with the identification of potential improvements for the inefficient listed logistics companies based on the optimal solution of the DEA model. This proposed model can be applied in emerging fields such as finance and project-based construction companies, where operational risk is a high concern. [ABSTRACT FROM AUTHOR]

Performance measurement of any industry is very crucial in order to cope with the competition, the efficiency analysis is considered as one of the most valuable and essential tools for the same. In this paper, the efficiency is tested for plastic using Data Envelopment Analysis (DEA), which is an important raw-material for many industries. Though the profit after sales of plastic industries exhibits fixed random effects over the years, none of the independent variables are statistically significant. Data Envelopment Analysis has varied applications in measuring comparative efficiency of decision-making units. One of the prime applications is used to measure the efficiency of the manufacturing companies considering discretionary and non-discretionary inputs and to find out the lacks of each unit to increase their performance. This paper calculated the technical efficiency of the 28 plastic manufacturing units of India from 2018-20. The non-parametric DEA approach is used for compute the efficiency score. Furthermore, the results classify the numerous firms according to their performance and identify the "best." Similarly, efficiency methodologies evaluate performance compared to the most efficient organizations. Slag based efficiency analysis is used to evaluate the performance of plastic manufacturing firms. The model considers the profit after tax deduction as an output and raw material, employee benefits, power fuel and lease rent as input variables respectively. By planning their inputs and outputs in conjunction with efficiency that their competitors have attained, plastic manufacturing firms can emulate the efficiency of their competitors. The firms which are more efficient would surely get more global orders and can gain competitive advantage over their competitors. [ABSTRACT FROM AUTHOR]

Purpose: Consensus on how intellectual capital (IC) affects corporate performance is limited because of various measurement models of IC and corporate performance. This study thus aims to further the debate on the relationship between IC and corporate performance from the perspectives of nonlinearity, the capital values of IC and the use of a holistic measure of corporate performance. Design/methodology/approach: Using 1,395 firm-year observations derived from Vietnamese listed companies from 2010 to 2018, this study focuses on (1) presenting an IC model benchmarked on value-creating expenses; (2) using a directional distance function (DDF)-based stochastic nonparametric envelopment of data (StoNED) framework to scrutinize multiple performance indicators and the capital values of people, structures and relationships simultaneously; and (3) adopting firm-year cluster-robust regressions to analyze the nonlinear association between IC and corporate performance empirically with an appropriate U test. Findings: Results suggest that human capital (HC), structural capital (SC) and relational capital (RC) are the main contributors of high corporate efficiency, whereas only HC and RC contribute to high corporate profitability. These results are absent when this study employs the conventional data envelopment analysis (DEA), which is also a multidimensional framework, as the dependent variable. More importantly, IC and its components can improve corporate performance, namely, both corporate efficiency and corporate profitability up to a critical point, after which the effects would drop. Practical implications: Overall, this study highlights not only the need to invest in IC but also its associated costs. That is, policymakers also need to note the marginal cost of investing in IC, which may in the end outweigh the benefits from IC. Originality/value: This study extends IC-related studies by investigating the nonlinear relationship between IC and corporate performance. Moreover, the value of this study also lies in the multidimensional DDF-based StoNED framework. [ABSTRACT FROM AUTHOR]

This study evaluates the profitability and marketability efficiencies of digital firms ranked in Forbes' list of top companies by using a two-stage network data envelopment analysis (DEA) model with multiplicative efficiency aggregation under the second-order cone programming (SOCP) and examines the respective impacts of the 1995–2001 dot-com bubble and the 2007–2009 global financial crisis on the companies' efficiencies by applying impulse response function (IRF) analysis. The data of our 49 sampled companies are derived from the Compustat database. The covered period is 1999–2018. These results present the stable and increasing improvement of profitability and marketability efficiencies; in addition, two crisis events have no significant impact on the performance of digital firms. This research is supposed to offer a reasonable and objective evaluation model to measure the performance of digital firms, providing the managers and investors a reference for making their decision. [ABSTRACT FROM AUTHOR]

• Incorporates the technological development into dynamic efficiency analysis. • Develops a new dynamic DEA model with carry-over and accumulation. • Evaluates the provincial industrial production of China. • Studies the spatial correlation of industrial production in China. In actual industrial production, technology shows an accumulative effect that exceeds the corresponding factor endowment in each period. This accumulation effect is accompanied by the whole industrial production and plays an important role in the evolution of industrialization as a bridge. In order to identify the status quo of industrial production more comprehensively, explore the role of technological accumulation in industrial production, and further promote industrialization, this paper constructs a new multi-period dynamic data envelopment analysis model reflecting the effect of technological accumulation. Furthermore, a spatial autocorrelation analysis is conducted to determine the spatial correlation of regional industrial production and to provide a reference for the coordinated development of industry among regions. A case study of China's industries was conducted, and the main results show the following: (1) The average industrial production efficiency is 0.806, and 17% of provinces have a score of less than 0.65. (2) There is an obvious positive spatial autocorrelation evolution trend in regional industrial production; the eastern coastal area is dominated by High-High clustering, and Low-Low clustering is concentrated in the northwest. (3) Technology accumulation aggravates the dispersion degree of regional industrial production efficiency. Finally, policy implications are put forward to promote industrialization and the coordinated development of interregional industry. [ABSTRACT FROM AUTHOR]

In logistics industry of 12 provinces along China's new western land-sea corridor from 2010 to 2019, this research employed three-stage SBM model that considers undesirable output to measure logistics industrial efficiency and the panel Tobit model to investigate variables impacting logistics efficiency. The study found that after controlling for environmental variables and statistical noise, the logistics industrial efficiency in China's new western land-sea corridor has improved, and the logistics sector efficiency of each province has spatial variability. Generally speaking, the south part goes up and the north part goes down; industrial structure, logistics transportation intensity, and economic development have a favorable influence on logistics sector efficiency. The urbanization rate, government support level, level of infrastructure, and degree of openness all have a negative influence on efficiency. Finally, relevant policy considerations such as logistics transport intensity, pure technical efficiency, scale efficiency, and external environment are proposed. [ABSTRACT FROM AUTHOR]

Promoting industrial ecology and greening is the fundamental requirement of the new development concept, and also the key to realizing high-quality and sustainable development of regional economy. This paper selects the relevant data of eight cities in Anhui section of Huaihe River Economic Belt from 2014 to 2018, and uses the entropy method and the undesirable SBM model to calculate the industrial development level and ecological efficiency during the study period. Moreover, based on the coupling coordination degree model, the synergistic effect between industrial development and ecological efficiency is analyzed, and the spatial-temporal evolution pattern between them is clarified by means of spatial econometric analysis model. Further research suggests that: (1) the synergistic effect between industrial development and ecological efficiency in Anhui section of Huaihe River Economic Belt from 2014 to 2018 is significant, showing a steady strengthening trend. The endogenous power of industrial development keeps strengthening, and the scale effect keeps spillover diffusion. The mean value of overall coupling coordination degree is generally between 0.6 and 0.7. (2) In terms of spatial distribution, the regions with high coupling coordination degree are mainly distributed in the eastern part of Anhui Section (Bengbu and Chuzhou), the lower level area is mainly distributed in the northern part of Anhui Section (Suzhou), and the middle level area is widely distributed. (3) The agglomeration of coupling coordination degree between industrial development and ecological efficiency mainly occurs in low-high (L-H) and high-low (H-L) agglomeration areas. (4) The level of economic development, intensity of R&D and intensity of environmental regulation have significant positive effects on the coupling coordination degree of industrial ecological efficiency and industrial development, and promote the increase of coupling coordination effect. Finally, based on the research results, targeted suggestions are put forward in order to promote the coupling coordination between industrial development and ecological civilization construction, and walk out of a new road of high-quality development of green ecology. [ABSTRACT FROM AUTHOR]

Data Envelopment Analysis (DEA) evaluates a large number of input and output variables using mathematical programming techniques and analyzes the effectiveness of similar decision making units (DMU). Unlike traditional methods, the most important advantage of DEA is that the weights of input and output variables can be defined by the analyzer. In this study, the limitations of the DEA weights were determined using the AHP, which considers expert opinion. In addition, an alternative judgment scale was used for the Saaty judgment scale, which is used as a standard in the AHP method, and thus a more sensitive analysis was performed. There have been studies dealing with the comparison of judgment scales, but few studies on consistency sensitivity are needed. This point has also been addressed in this study. Subsequently, the financial efficiency of 27 companies operating in the food sector in Kosovo was evaluated with the weightrestricted DEA model, first created using the unweighted DEA model and then the AHP model, and the two models were compared. This paper is the first one of its kind since there are no previous studies regarding the examination of the financial efficiency of companies operating in the Kosovo food sector based on the DEAHP method. [ABSTRACT FROM AUTHOR]

Purpose: To analyze the technical efficiency of Brazilian railway companies. Methodology: The technical efficiency of Brazilian railway companies was analyzed through Data Envelopment Analysis (DEA), using the window analysis approach, and considering the Variable Returns of Scale model. The study examined eight companies during a five-year period, which totalizes 90% of the railway passengers in that timespan. The main inputs and outputs of railway systems referred in the international literature were used as variables. Results: Only railway companies classified as large can be considered technically efficient. Among them, São Paulo's metro system was the only one that remained efficient throughout the years analyzed. Medium-sized companies were inefficient in all years of the sample, showing the necessity to reduce their inputs by an average of 19% in order to become technically efficient. The inclusion of financial variable as an input did not significantly change the efficiency indexes assessed. The study reveals the prevalence of increasing returns to scale in the Brazilian railway system. Contributions of the study: This study identifies potential improvements for the companies considered inefficient and reveals they are medium-sized and state-owned, with high-cost financing from government resources. It is also a benchmark for further research on the topic, given the importance of identifying the effect of funding transport operations with government resources on companies' efficiency. In this context, considering this study identifies the prevalence of increasing returns to scale in the Brazilian railway system, it contributes to the analysis of public policies associated with population access to this means of transportation, as constant returns to scale suggests that production increase, which has the number of carried passengers as the main variable, can generate benefits for the companies in terms of efficiency. [ABSTRACT FROM AUTHOR]

Insurance awareness for different insurance branches in the insurance sector in Turkey is increasing day by day, and the number of policies produced in the sector is increasing day by day. In this context, with the aim of evaluating the insurance indicators that increase in quality in terms of quantity and revealing a performance table for the sector, in the study, a list of the top 14 companies in the market share ranking according to the total premium production in the insurance sector, based on some indicators selected between 2016-2019 activity analysis was carried out. Data envelopment analysis was used as the analysis method. As a result of the study, it has been observed from the analysis results that although the efficiency levels of the companies, which are in the top ranks according to the total premium production in the years examined, are generally at good levels, in some years, the opposite process has also been experienced. Accordingly, companies should increase their profitability and premium production by using their employment numbers and insurance policy numbers more efficiently. [ABSTRACT FROM AUTHOR]

This paper presents an efficient outer space branch-and-bound algorithm for globally solving a minimax linear fractional programming problem (MLFP), which has a wide range of applications in data envelopment analysis, engineering optimization, management optimization, and so on. In this algorithm, by introducing auxiliary variables, we first equivalently transform the problem (MLFP) into the problem (EP). By using a new linear relaxation technique, the problem (EP) is reduced to a sequence of linear relaxation problems over the outer space rectangle, which provides the valid lower bound for the optimal value of the problem (EP). Based on the outer space branch-and-bound search and the linear relaxation problem, an outer space branch-and-bound algorithm is constructed for globally solving the problem (MLFP). In addition, the convergence and complexity of the presented algorithm are given. Finally, numerical experimental results demonstrate the feasibility and efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]

With the increasing environmental pollution and environmental awareness, ecological efficiency has become a hot issue. Based on the traditional DEA model of unexpected output, a new super data envelopment analysis and slacks-based measure considering undesirable outputs (S-DEA-SBM-UO) efficiency model is proposed. Moreover, the weight S-DEA-SBM-UO (W–S-DEA-SBM-UO) is applied to evaluate the ecological efficiency of industrial enterprises. The experimental results show that the W–S-DEA-SBM-UO can measure the ecological efficiency including unexpected output more effectively than the conventional DEA-SBM to solve unexpected output. Finally, it is suggested that enterprises should make great efforts to improve the ecological efficiency and it is pointed out that the results have strong theoretical significance and research value for ecological improvement. [ABSTRACT FROM AUTHOR]

We develop an output-oriented data envelopment analysis framework to examine the efficiency of Chinese banks over the period 2007–2017 and further test the relationship between efficiency and corporate social responsibility (CSR). We are the first piece of research considering the number of employees as one bank input and potential increase in the number of employees as one CSR indicator. Additionally, we innovatively propose another three specific CSR indicators: namely donation, balance of green credits and loans to small and medium sized enterprises. The results show that the gain from improving allocative output-efficiency by reallocating variable inputs is less than the gain attained by improving technical output-efficiency. Evidence from the second-stage regression analysis shows that the overall indirect technical efficiency is significantly and negatively affected by the volumes of green credits, while an increase in the volumes of donations will improve the indirect allocative efficiency. [ABSTRACT FROM AUTHOR]

This study analyse the technical efficiency in terms of innovation of the firms in the service sector in the Uruguayan economy. Therefore, we use data from the 2010-2012 Innovation Activities Survey of the National Agency for Research and Innovation (ANII). In a first stage, we estimate the level of efficiency of each company through a Data Envelopment Analysis model, incorporating the inputs and outputs related to the innovative activity of the firms. The results reveal that, despite the effort made in terms of investment in innovation, the results are still very poor. On average, the companies analysed could increase their innovation production by 44.5% given the resources invested. Subsequently, we explore the relationship between innovative efficiency and several characteristics of the firms. In this sense, we found that medium-sized firms have lower efficiency than small and large companies. The results can be useful for both those responsible for the area of innovation of the firms, as well as to the institutions that provide support in the field of innovation (such as the ANII), since they provide substantive evidence to improve the orientation of the innovative strategy to be followed by firms in the service sector. [ABSTRACT FROM AUTHOR]

In recent years, innovation is one of the most important competitive tools used by businesses to achieve sustainable growth. Thanks to innovation, companies can significantly increase their production, finance and marketing performance. In this study, fuzzy data envelopment analysis method was used to determine the performance efficiency of twenty companies operating in software sector in İzmir. For the fuzzy efficiency analysis, university cooperation level, product innovation and process innovation rating scores were taken as input variables. Software development performance, market performance and financial performance scores were taken as output variables. Data on input and output variables were obtained through a questionnaire applied to enterprises. The results obtained with fuzzy data envelopment analysis and classical data envelopment analysis models were examined comparatively. In this study, it is aimed to list the twenty companies operating in the software sector in İzmir province by classical data envelopment analysis and fuzzy data envelopment analysis method. [ABSTRACT FROM AUTHOR]

This study examines the effects of commercially-oriented research and development (R&D) competence and technology commercialisation (TC) policies in public research organisations (PROs) on R&D efficiency of companies when they receive technology transfer from PROs. This study especially uses three-stage data envelopment analysis in order to control the companies' absorptive capacity and innovation hurdles that affect the efficiency. The results show that companies that receive technology transfer from PROs that have good alignment between commercially-oriented R&D competence and TC policies have higher R&D efficiency than companies that do not. On the other hand, the misalignment between PROs' commercially-oriented R&D competence and TC policies can have negative effects on R&D efficiency of companies that receive technology transfer. Consequently, this study discloses that the alignment between technology transferor's commercially-oriented R&D competence and TC policies is critical for improving the R&D efficiency of companies when the companies acquire technologies from external organisations. [ABSTRACT FROM AUTHOR]

China has attracted the attention of the world owing its significant economic achievements, which are supported significantly by its booming industry. However, the issues of energy and pollutants have severely challenged the sustainability of the industry. The efficiency measurement is the premise intended to realize sustainability within the Chinese industry. Because the industry is a complex production system, there exists uncertainties and fuzziness regarding its inputs and outputs. This study proposes the application of an interval to describe these fuzzy data and employ the Enhanced Russell Measure to assess the performance of the Chinese industry, accounting for undesirable output such as pollution. In addition, for the ranking between interval efficiencies, a novel ranking approach based on the holistic acceptability of a possibility degree is proposed. The proposed method provides advice and guidance for decision makers to make appropriate and effective policies to balance industrial development and environmental protection in spite of uncertain and fuzzy data. [ABSTRACT FROM AUTHOR]

The essence of efficiency measurement is to model and estimate the performance of a complex system in a comparable form, and the key to modeling is to make the model as close to reality as possible. Based on data envelopment analysis (DEA) methods, this research proposes a layer-by-layer investigation framework for the black box. To illustrate the rationality of this logical framework, this paper presents a triple-opened dynamic recycling model with a series-parallel structure that allows us to assess the efficiency of the industrial water-related system in China. We obtain and compare the system efficiency under different scenarios for opening the black box. The results show that: (1) China's efforts to improve the performance of the resource use sub-stage through industrial production technology and management have been effective. (2) The performance of China's industrial water-related system strongly relates to the water supply subunit with a positive linear correlation. (3) The water supply subunit is the main foot-dragger in the system, and the government needs to place particular attention on improving the performance of labor in this subunit. • Propose a logical framework of a layer-by-layer investigation of the black box. • Construct a triple opened dynamic recycling model with a series-parallel structure. • Analyze and compare system efficiency under four scenarios. • Reveal the foot-dragger and key influencing indicators of system efficiency. [ABSTRACT FROM AUTHOR]

This study applies 3-stage data envelopment (DEA) of 24 listed companies in the development zone of Hubei Province from 2012 to 2017 based on the panel data; we used the DEA-Tobit model and regression analysis method on the sample in order to measure the factors affecting the innovation efficiency of listed companies and the efficiency of corporate innovation. The results demonstrated that the innovation efficiency of listed companies in the development zone of Hubei Province is relatively low. It is necessary to improve the innovation system of the development zone and give the full initiative to the role of corporate innovation as a mainstay. The four environmental variables of the number of enterprises, government subsidies, foreign direct investment in the development zone, and fixed asset investment have a significant impact on innovation efficiency. The enterprise size, operating capacity, and state-owned shares of the company have a significant positive impact on the innovation efficiency. But the number of years of the establishment has a significant negative impact on innovation efficiency. Moreover, the quality of the workers is not significant. Therefore, we must increase government investment in innovation to expand the scale of listed companies in the development zone, improve the environment for foreign investment, further strengthen the construction of talented people of companies, and enhance the original ability of innovation. [ABSTRACT FROM AUTHOR]

Purpose: Using data on 51 firms traded in the Egyptian Exchange from 2014 to 2016, this paper aimed to assess the efficiency of corporate governance (CG) and intellectual capital (IC) practices and to explore their influence on the probability of a firm's financial distress. Design/methodology/approach: The relative efficiency of CG and IC practices has been measured under the Malmquist data envelopment analysis model. A modified Z-score model was applied to assess firms' financial distress. Findings: The Wilcoxon signed-rank test revealed almost insignificant evidence regarding the improvement of CG and IC efficiency over the study period. The efficiency score of CG practices had no impact on the likelihood of financial distress. However, the efficiency score of IC negatively affected the probability of financial distress. Research limitations/implications: The integration of data envelopment analysis with Tobit regression was required for identifying the significant drivers of efficient CG and IC. Practical implications: The findings shed light on the role of CG and IC in alleviating the degree of financial distress in Egypt as an emerging market, especially the need to raise firms' compliance with the Egyptian CG code from a voluntary to mandatory status. Originality/value: This study, using Malmquist data envelopment analysis, is among the first attempts to assess the relative efficiency of CG and IC practices and their effects on financial distress. [ABSTRACT FROM AUTHOR]

Product modularity can be considered as a product design strategy. It provides many benefits for companies that adapt it. However, there is little empirical evidence to support such an expectation. This study aims to measure the effects of product modularity on the efficiency and productivity of the product engineering area of a bus manufacturer. To reach the proposed objective, a longitudinal case study was conducted on the product engineering department of a company covering a period of three consecutive years. We used Data Envelopment Analysis (DEA) combined with Mann–Whitney U test and Malmquist index. The results show an increase of 18.40% in the efficiency indexes of the company's products engineering. In addition, positive changes can be observed, that is, there was a 63.50% increase in Total Factor Productivity Index (TFPI). The improvements are attributed to the implementation of product modularity in the organization under study. In this sense, the main contribution of this paper to the field is to present the increment of productivity with the insertion of the product modularity in the product engineering in a bus manufacturing company. Thus, product modularity can be considered a technology that increases the Total Factor Productivity Index (TPFI) of the companies that use it. [ABSTRACT FROM AUTHOR]

Stocking strategy for spare parts has a pivotal influence on the productivity and efficiency of industrial plants. Considering the situation of lacking historical statistics causing by uncertainty, this paper proposes a method to optimize spares varieties based on uncertainty theory and uncertain data envelopment analysis (DEA) model. Firstly, a recursive hierarchy structure is established to construct an evaluation system to meet the requirement of avoiding attributes' redundancy. Then, an uncertain spares optimization model (USOM), which is based on uncertain DEA model, is developed to optimize spares varieties. Furthermore, the uncertainty theory is utilized to convert the USOM into an equivalent deterministic model for simplification. Finally, a numerical example is given to illustrate the performance of this model. The results show that the stocking strategy obtained from the proposed decision model can satisfy the purpose of saving resources and prompting continuous operation. [ABSTRACT FROM AUTHOR]

Data Envelopment Analysis (DEA) is a relatively new method, a nonparametric technique used nowadays to evaluate the efficiency of the Decision-Making Units. Using this method, the Decision-Making Units can be compared between each other and the most effective ones can be found. Using the DEA method, the performance of a logistic company with twelve warehouses as DMUs is evaluated in this paper. "DEA Excel Solver" user program was used to solve the problem. [ABSTRACT FROM AUTHOR]

This article uses the industry linkage path algorithm in western energy development application. Based on the theoretical research, this paper introduces the research ideas of complex networks, and uses the research methods of mathematical modeling and computer simulation to construct a network model and its evolution model of industrial linkage system. The results of computer simulation show that the established evolutionary model has a high ability to explain and predict the actual industry linkage network, and it runs reliably and steadily, which provides a feasible research method for the quantitative research of industry linkage network, constructing an analysis paradigm of industrial linkage network. The method and the analysis index of extracting industrial and regional linkage sub graph from the whole figure of industry linkage network are proposed, and the industries and regions that can be linked is identified by measuring the index. In addition, a search method of optimal linkage path is established for a specific regional industry. Finally, an evaluation method of overall linkage efficiency of industrial linkage network based on data envelopment analysis is proposed. [ABSTRACT FROM AUTHOR]

The current context of Vietnam is that Vietnam is a developing country whose geographical shape is long and dynamic. Its logistics is also in the way of development and promising to have good potential. However, lack experience and technology, small and fragmented operation, fierce price competition among local enterprises, domination from foreign logistics giants are that factors that may hinder the growth of the local sector. It is then believed that cooperation among local firms could promote integration of the supply chain, making it more productive and so increase competitiveness of the industry. The study was conducted to evaluate the efficiency of Vietnamese transportation and logistics firms using Malmquist Productivity Index, crafting a clearer picture of how these firms performed in terms of technical efficiency and innovation. Cat Lai Port being a key role in the industry was taken as a case to analyse strategic alliance opportunities using data envelopment analysis and Grey forecasting. Research findings indicate that half of the samples experienced efficiency progress, half experienced performance regress; most of efficiency improvement came from innovation. The study also found that strategic alliances between Cat Lai Port and some firms potentially improve these firms' efficiency. [ABSTRACT FROM AUTHOR]

Nowadays, the activities of companies started to become more complex and diverse as a result of technological developments and increasing human population. This situation requires the efficient use of companies’ resources. It is important for airline companies to carry out their activities effectively with the help of infrastructural improvements and state subsidies for air transportation in our country. This is particularly important both for sectoral and academic development. The data envelopment analysis (DEA), which is the method of this study, is a multi-criteria decision-making method that measures efficiency by evaluating the data set handled by using common inputs and outputs for enterprises or periods covered. This study was conducted in order to measure the efficiency of activities of the airline companies. In addition, this was done in order to measure the shortcomings of the literature and the efficiency of the airline companies. Within the scope of this study, the activity effectiveness of the two companies which are Turkish Airlines and Pegasus Airlines, operating in our country between 2012 to 2015 was measured by using VZA. As a result of the analysis, information about the activity efficiency of the companies in the relevant years is provided by evaluating the obtained results. [ABSTRACT FROM AUTHOR]

A method to establish assessment, classification and prediction criteria to evaluate the productive efficiency and innovation of the companies in the chemical sector of Barranquilla was developed. Concepts of data envelopment analysis, discriminant analysis and artificial neural networks were used. Information associated with variables of labor climate, information management, knowledge management, productivity management and innovation, were collected. The results were then validated with the discriminant analysis and forecasting processes and prediction of the efficiency of the companies in the sector with artificial neural networks were modeled. The results show that the average efficiency in the sector is 52.9%, with 6 companies classified as efficient ones. With the multivariate discriminant analysis techniques, the classification quality could be determined, achieving a 92.6% correct classification. Likewise, the selected neural network model generated a classification accuracy of 98.82%, 95.78% and 94.28% for the training, test and reserve samples, which shows the relevance of the classification model. It is concluded that the analyzed variables are significant to discriminate productive efficiency and innovation. [ABSTRACT FROM AUTHOR]

Data envelopment analysis (DEA) has been widely used in the energy efficiency analysis of industrial production processes. However, the traditional DEA model is not high in the division of the efficiency value of decision making units (DMUs), and produces a large number of DMUs with an efficiency value equal to 1, making it difficult to identify their merits and demerits. Therefore, a novel DEA model based on the affinity propagation (AP) clustering algorithm (AP-DEA) is proposed. Through the AP clustering algorithm, high influence input data of the energy efficiency can be obtained. The merits and demerits of DMUs can then be identified with a high degree of discrimination to obtain better efficiency groups. Finally, the proposed model is applied to evaluate the energy efficiency and optimize the energy configuration of the ethylene and pure terephthalic acid (PTA) production processes in complex petrochemical industries. The experimental results show that this proposed model can improve the efficiency value discrimination of efficiency values by effective DMUs better than the traditional DEA. Moreover, the energy saving potentials of ethylene and PTA production systems are approximately 0.49% and 24.74%, respectively, and the carbon emission reduction of the ethylene production system is approximately 10.04%. • A novel AP-DEA method is proposed. • Energy efficiency evaluation and energy saving model of petrochemical industries is obtained. • This proposed model is efficient in energy saving and carbon emission reduction. • The energy saving potential of ethylene production systems and PTA production systems is 0.49% and 24.74%. • The carbon emission reduction of ethylene production systems is 10.04%. [ABSTRACT FROM AUTHOR]

The industrial technology research institute (ITRI) has become an important platform to promote the transformation of scientific and technological achievements in universities. The influence of environmental factors and random errors is the main problems in the evaluation of ITRI's innovation efficiency, which greatly affects the evaluation results. At present, there are few studies on the ITRI's innovation efficiency, and most existing works do not eliminate environmental and random factors, resulting in biased results. In this paper, for the evaluation of the innovation efficiency of ITRI, the three-stage data envelopment analysis model is utilized. Firstly, in the first stage, based on the original input and output data, the efficiency of each decision making unit is measured by using the input-oriented classic DEA model. Secondly, the stochastic frontier model is constructed in the second stage to eliminate environmental factors and random errors in the original input and output data. Finally, in the third stage, the adjusted input data is brought into the calculation of the first stage to obtain the real innovation efficiency value of ITRI. The extensive experiments are constructed on the relevant indicator data of 80 Chines ITRI, whose results indicate that the evaluation of innovation efficiency is indeed affected by environmental factors and random errors. After eliminating the influences of environmental factors and random error, the innovation efficiency shows a decreasing tendency, which is more in line with Chinese national conditions. [ABSTRACT FROM AUTHOR]

The growing disparity in China's regional carbon emission efficiency is an easily overlooked but crucial issue in China's transition to carbon neutrality. To better understand drivers of widening gap of regional carbon emission efficiency in China from technological progress, industrial inequality, regional inequality, and management inequality, a novel approach is developed by combining a logarithmic mean divisia index and production theoretical decomposition analysis based on multi-layer frontier. The results indicate (i) Except for Ningxia and Xinjiang, the energy utilization efficiency of the remaining provinces continued to improve during the study period. The fossil energy consumption structure in most provinces gets gradually improved, favoring fossil energy with less carbon emissions. The industrial structure of most provinces has not improved significantly. (ii) Improving overall energy efficiency and technological progress is extremely important for carbon emission reduction. Potential energy intensity effect and energy technology efficiency gap effect are the key factors to restrain the increase of carbon emission intensity. (iii) For economically developed regions (such as Beijing and Guangdong), technological factors, potential energy efficiency and scale have a greater impact, while industries, regions, and management efficiency have a smaller impact, indicating that developed regions are at the frontier of efficiency and are improving production and energy structure. Moreover, there is an efficiency gap between underdeveloped regions (such as Xinjiang and Qinghai) and economic regions. Hence, while improving the production structure and energy consumption structure, the efficiency gap with developed regions should be narrowed. • The LMDI-PDA combination model based on multi-layer frontier is constructed. • The impact of inequality in industry, region, management and scale on carbon emission intensity is considered. • The driving factors of carbon emission intensity of 30 provinces are systematically analyzed. • The difference of drivers of carbon efficiency at the industrial level is compared. [ABSTRACT FROM AUTHOR]

In the study, it is examined whether the efficiency of the companies that are traded in the BIST sustainability index, which are started to be calculated as of November 2014 in our country, have changed their efficiency according to previous periods before entering into the scope of the index. For this purpose, the efficiency values of the periods of 2013-2016 were calculated by using Data Envelopment Analysis (VZA) method considering the 13 manufacturing companies included in the sustainability index in the period of November 2015 - October 2016. The change in efficiency values of companies over the period was measured by Malmquist Total Factor Productivity (TFV) index. As a result of Data Envelopment Analysis, it was determined that 7 companies of the 13 were effective both before listing period and after listing period in sustainability index. 4 companies were effective in the previous periods but they were not effective after entry process of sustainability index. Also 2 companies were not effective neither their non-listing period nor listing period of sustainability index. According to Malmquist TFV index, productivity of 7 companies increased over the period of 2015-2016. If the Malmquist TFV index of these 7 companies was examined, an increase in productivity of 6 companies in the period of 2014-2015 and 3 companies in the period of 2013-2014 had been determined. When the two main elements of Malmquist TFV index, technological efficiency and technical efficiency, were examined, it was shown that the productivity of companies increased during the period of 2015-2016 caused by technological efficiency. If we made business-based assessments, the first three companies with a high increase in productivity were VESTEL (43%), TOFAŞ (37%) and Petkim (16%) as of 2015-2016. As a result, it was seen that whether or not the companies take place in the sustainability index didn't make a difference in productivity. [ABSTRACT FROM AUTHOR]

Highlights • We explored the R&D efficiency of the semiconductor industry in Taiwan. • We focused on the patenting perspective. • 42 semiconductor companies of the semiconductor industry in Taiwan were studied. • We identified the companies that may be treated as a benchmark for the rest. • We identified ways for the studied companies for efficiency improvement. Abstract The aim of the study is to explore the Research and Design (R&D) efficiency of the semiconductor industry in Taiwan from a patent perspective. Six evaluation indices are selected as inputs (total assets, staff numbers, and R&D expenditure) and outputs (return on assets (ROA), earnings per share (EPS), and patent number), and then the 4-year annual data of the listed 42 semiconductor companies of the semiconductor industry in Taiwan are obtained. The Data Envelopment Analysis (DEA) is utilized for the efficiency computation among 42 semiconductor companies. Based on the research results, recommendations for semiconductor companies and suggestions for future studies are provided. [ABSTRACT FROM AUTHOR]

This research aims to determine the technical efficiency of Mexico's electricity sector in period 2008-2015, using Data Envelopment Analysis methodology with bootstrap in order to give more validity to observations obtained. With the study it was possible to determine that none of the thirteen divisions analyzed obtained the optimum level of efficiency, however, Baja California and North divisions obtained the highest efficiency indexes in the sector in the study period. Otherwise, the Southeast division was the least efficient. It is concluded that although it has been able to supply the demand for electric energy that the country requires, it is important to continue with studies of this nature, which allow the formulation of policies aimed at improving efficiency of the sector. [ABSTRACT FROM AUTHOR]

Abstract In this study, the industrial eco-efficiency measures of 30 Chinese provinces (municipalities and autonomous regions) from 2001 to 2015 were estimated based on a proposed data envelopment analysis (DEA) model and the non-convex metafrontier-undesirable outputs-super efficiency-slacks-based measure (NCMeta-US-SBM) which simultaneously incorporates non-convex metafrontier technology, undesirable outputs, and super efficiency into slacks-based measure. Subsequently, dynamic spatial econometric models were employed to test the spatial convergence of industrial eco-efficiency. The empirical results show that: 1) the average value of industrial eco-efficiency was the highest in the eastern region (0.67), followed by the western region (0.30) and central region (0.27), indicating the existence of a significant regional disparity. 2) Strong evidence for global and club spatial convergence of industrial eco-efficiency was found. With regard to regional heterogeneity, provinces in the eastern region converged faster than those in the central and western regions; while the convergence speed of industrial eco-efficiency increased after 2008 with respect to temporal heterogeneity. 3) The ownership structure appeared to have a higher impact on industrial eco-efficiency than other controls in the presence of spatial conditional β -convergence. These findings are robust with regard to both spatial econometric model and spatial weighting matrix specifications. Based on the empirical analysis, the following policies promote industrial eco-efficiency in China have been recommended. First, relevant authorities must take effective measures to encourage the central/western regions to adopt clean energy technologies. The energy subsidy policies should strive to break through the technological lock-in and turn to regional green development. Second, full advantage of the spatial effects must be taken and technological exchanges and cooperation among neighboring areas must be strengthened to ensure that the industrial eco-efficiency of the central and western regions converge with those of the eastern coastal areas. Policy implications of multidimensional heterogeneity and adjustment of industrial structure should be highlighted while promoting industrial eco-efficiency. Finally, it is crucial to emphasize factors, such as foreign direct investment (FDI), ownership and industrial structures to attract FDI and optimize the current industrial structure. Graphical abstract Image 1 Highlights • Industrial eco-efficiency measures of 30 Chinese provinces (municipalities, autonomous regions) are estimated based on the proposed DEA model. • Eastern region performs the best, followed by the western and central regions. • Both global and club spatial convergence of industrial eco-efficiency is supported. • Empirical results are robust to different spatial weighting matrix specifications. [ABSTRACT FROM AUTHOR]

A third-party logistics (TLP) provider's outsourcing mode is developed to support the economic activities for various industries. The aim of this research is to assess the efficiency of 10 large TPL providers from past to future by integrating the GM (1,1) model in grey forecasting and an epsilon-based measure model (EBM) in data envelopment analysis (DEA). The GM (1,1) model is utilized to formulate a forecast data in the future over period from 2018 to 2022. Then, via EBM model, past–current–future data are used for computing efficiency of these providers. The empirical values show that 115 cases comprise 79 efficiency cases and 36 inefficiency cases. CHRW, ECHO, and UPS get strong efficiency and keep a stable efficiency score in whole term. EXPD and KRRYF do not achieve efficiency during the period from 2013 to 2022. Excluding CHRW, ECHO, and UPS, seven TPL providers demonstrate upward trend and downward trends in every term. The increasing and decreasing variation index of 10 third-party logistics providers will help customers to select the best TPL providers. [ABSTRACT FROM AUTHOR]

In this paper, we seek to explore the agglomeration externalities of creative industries impacting on industrial efficiency, both at the regional level and at the sector level. Firstly, we apply a data envelopment analysis model to compute the efficiency scores of creative industries in China. The result shows that China's industrial efficiency whether in different provinces or different creative sectors is characterized by huge disparities. Secondly, using the data from China's 31 provinces and 50 creative sectors during the period of 2004–2014, we empirically explore whether and how the development of creative industries agglomeration impact on industrial efficiency, where the agglomeration is distinguished between regional specialization, geographical concentration, and industrial concentration. We find that the three types of agglomeration externalities all play important roles in increasing productive efficiency in creative industries. The study also confirms that industrial efficiency is more likely to be increased by attracting much smaller firms concentrating in a given area, while this effect is mixed in a given creative sector. [ABSTRACT FROM AUTHOR]

Highlights • We decomposed the process for producing shipping service of a container carrier in multiple periods. • The annual efficiency and division efficiency of major container carriers were measured. • The optimal solution for sharing common inputs and adjusting owned fleet capacity was also found from our model. Abstract Taking advantage of a dynamic network data envelopment analysis (DNDEA), this study proposes a model decomposing shipping service production for a container shipping company (CSC) into two processes. Meanwhile, multiple evaluation periods are linked by carry-over activity. The fleet capacity of a CSC is separated into owned fleet capacity (OFC) and chartered-in fleet capacity, which are defined as carry-over activity and specific input, respectively. The efficiency of 13 major global CSCs is empirically evaluated based on a dataset covering a period from 2013 to 2015. The scores for company efficiency and division efficiency of each CSC are measured and examined. In addition, the optimal solution for sharing common inputs and adjusting OFC is also found from our model. [ABSTRACT FROM AUTHOR]

This research aims at analyzing the impact of continuous improvement and learning processes regarding efficiency and production volume in an armament manufacturer. A longitudinal case study comprising a period of six years of analysis in the company production lines was carried out. Data Envelopment Analysis (DEA) combined ANOVA test and linear regression were used. The survey results show that continuous improvement and learning projects were not enough to increase efficiency in two of the three production lines analyzed. Therefore, the variables related to Kaizen events, hours of training and experience of employees did not increase the efficiency of these lines. Moreover, the study elucidates that the production volume negatively impacts efficiency in one of the lines. With the analysis, it is possible to identify which factors are representative to increase production efficiency. Therefore, it is concluded that technology upgrade, in this context, is an important factor to be considered. The research contributed to analyse the relevance of continuous improvement actions, accumulation of knowledge and learning in an armament manufacturer. In addition, it allows managers of companies to evaluate more effectively the production process and technological evolution with a greater understanding of factors that impact on increased operational efficiency. [ABSTRACT FROM AUTHOR]

Conventional Data Envelopment Analysis (DEA) models focus only on initial inputs and final outputs for efficiency evaluation. Thus, these models treat the production process as a ‘black box’, i.e., they do not take into account how exactly inputs are related to outputs. Various models that came later take care of internal processes of DMU. The existing models of internal processes for parallel sub-units consist of three stages: the first stage calculates the relative weights of sub-units, the second stage calculates the efficiencies of sub-units, and in the third stage efficiencies of sub-units are aggregated as the efficiency of DMU. It is observed that when existing models of internal processes are applied to non-homogeneous parallel sub-units, in the first stage, the weight assigned to the maximum efficient sub-unit is one and to other sub-units is zero. This implies that the efficiency of a DMU is equal to the maximum of efficiencies of its sub-units indicating that the efficiency of a DMU is not sensitive to the efficiencies of sub-units other than the sub-unit with maximum efficiency. This paper proposes a single stage DEA approach where the efficiency of a DMU and its sub-units can be measured simultaneously. The advantage of the proposed approach is that the efficiency of a DMU is sensitive to the changes in the efficiency of its sub-units, and weights of sub-units can be assigned a priori by the decision maker. The development of the proposed approach is inspired from the growing interest in evaluating efficiency of higher education system in India. In the proposed application, states are considered as DMUs and universities, colleges and stand-alone institutions are taken as three non-homogeneous parallel sub-units of DMUs. [ABSTRACT FROM AUTHOR]

The trend toward a more competitive electricity market has led to efforts by the electric power industry to develop advanced efficiency evaluation models that adapt to market behavior operations management. The promotion of the operational performance management of the electric power industry plays an important role in China’s efforts toward energy conservation, emission control and sustainable development. Traditional efficiency measures are not able to distinguish sales effects from productive efficiency and thus are not sufficient for measuring the operational performance of an electricity generation system for achieving its specific market behavior operations management goals, such as promoting electricity sales. Effectiveness measures are associated with the capacity of an electricity generation system to adjust its input resources that influence its electricity generation and, thus, the capacity to match the electricity demand. Therefore, the effectiveness measures complement the efficiency measures by capturing the sales effect in the operational performance evaluation. This study applies a newly developed data envelopment analysis-based effectiveness measurement to evaluate the operational performance of the electric power industry in China’s 30 provincial regions during the 2006-2010 periods. Both the efficiency and effectiveness of the electricity generation system in each region are measured, and the associated electricity sales effects and electricity reallocation effects are captured. Based on the results of the effectiveness measures, the alternative operational performance improvement strategies and potentials in terms of input resources savings and electricity generation adjustments are proposed. The empirical results indicate that the current interregional electricity transmission and reallocation efforts are effective in China overall, and a moderate increase in electricity generation with a view to improving the effect on sales is more crucial for improving effectiveness. [ABSTRACT FROM AUTHOR]

Firms and territories are considered extremely interrelated, especially approaching the market of agri-food products detaining the PDO (Protected Designation of Origin) and PGI (Protected Geographical Indication) labels. By aiming at reducing costs and simultaneously exploiting potential benefits, entrepreneurial realities often collaborate through consortia. This aspect takes on a crucial relevance when considering the Italian context, widely known for its high-quality products, the vocation to cooperate, and the high adaptability to insidious locations. In this light, this study assesses the efficiency level of in-the-consortia Italian firms by conditioning for two external factors affecting the input–output process evaluated, i.e. physical riskiness and vocation to cooperate. The Data Envelopment Analysis (DEA) scores are aggregated by using firms' membership in the consortia as the DEA aggregation criterion. More than 600 firms aggregated in 50 consortia allow for a capillary and locally-based study over the 2011–2020 period. The study signals tips about geographical concentration and proximity since it tests whether tradition and attitude to cooperate motivate the agri-food industry efficiency level, in line with the historical regional background of these organizational forms. Finally, suggestions to exploit the market of certified products are discussed both for policy-makers and practitioners, as well as new opportunities for future research. • Cooperation may represent the key to completely improving the agri-food sector. • Certified product consortia efficiently drive the promotion of quality and origin. • Aggregations of firms increase the efficiency of territory-related risk management. • Collaborations gain success in developing the development of rural areas. [ABSTRACT FROM AUTHOR]

Access to sanitation services in Brazil is still deficient, despite the abundant financial resources allocated to it in the last two decades and the objective of the regulatory framework of 2007 of providing universal access and efficient sanitation systems. This article analyzes the impact of the regulatory environment on the water and sewerage companies' levels of efficiency. First, these efficiencies were computed within a dynamic network data envelopment analysis for a sample of 156 Brazilian water and sewerage companies, from 2006 to 2015, considering investments in water, investments in sewage, and operations divisions separately. In the second stage, this research related water and sewerage companies' efficiencies to innovative measures of the regulatory environment by using a panel data model, with data from 2006 to 2015. The efficiency analysis revealed low levels of overall and divisional efficiencies, highlighting the importance of evaluating efficiency over time, and of considering the providers' internal structure, to identify inefficiencies that may compromise the achievement of regulatory objectives. The regression results indicate that the impact on the overall and divisional efficiencies depends on the choice of regulatory incentives, the intensity of the application of those incentives, and even the number of regulatory authorities. • The simple presence of regulation has failed to improve Water Utilities efficiency. • The number of regulators affects the efficiency of regulated Water Utilities. • Regulatory incentives had positive/negative effects on Water Utilities efficiency. • Intensity of incentives may asymmetrically affect the Water Utilities efficiency. • The analysis of incentives is a managerial tool for reaching regulatory objectives. [ABSTRACT FROM AUTHOR]