Directional Distance Research Articles

Cross country comparisons of environmental efficiency under institutional quality. Evidence from European economies

PurposeThe paper aims at addressing the following research questions: does institutional quality improve countries' environmental efficiency? And which pillars of institutional quality improve countries' environmental efficiency?Design/methodology/approachBy specifying a directional distance function in the context of stochastic frontier method where GHG emissions are considered as the bad output and the GDP is referred as the desirable one, the work computes the environmental efficiency into the appraisal of a production function for the European countries over three decades.FindingsAccording to the countries' performance, the findings confirm that high and upper middle-income countries have higher environmental efficiency compared to low middle-income countries. In this environmental context, the role of institutional quality turns out to be really important in improving the environmental efficiency for high income countries.Originality/valueThis article attempts to analyze the role of different dimensions of institutional quality in different European countries' performance – in terms of mitigating GHGs (undesirable output) – while trying to raise their economic performance through their GDP (desirable output).HighlightsThe paper aims at addressing the following research question: does institutional quality improve countries' environmental efficiency?We adopt a directional distance function in the context of stochastic frontier method, considering 40 European economies over a 30-year time interval.The findings confirm that high and upper middle-income countries have higher environmental efficiency compared to low middle-income countries.The role of institutional quality turns out to be really important in improving the environmental efficiency for high income countries, while the performance decreases for the low middle-income countries.

CO2 emissions abatement costs and drivers for Indian thermal power industry

Indian power industry contributes nearly half of its overall CO2 emissions. In this study, we answer three related questions. First, what is the abatement cost of CO2 emissions for the Indian thermal power industry under three different policy scenarios - business as usual, emissions reduction only, and simultaneous emissions reduction and energy efficiency enhancement. Second, what are the determinants of these abatement costs of CO2 emissions. Third, which abatement policy scenario is more beneficial. For this, we employ a plant level dataset covering 93% of installed capacity and use a parametric quadratic directional output distance function to estimate marginal abatement costs by applying deterministic linear programming methods. Our findings are: First, the abatement costs range between US$ 46.43–71.11 per ton CO2, depending on the policy scenario chosen. Second, plant age, location, size, ownership, and CO2 intensity are all significant drivers of abatement costs. Third, while greater emissions reductions are possible under the emissions reduction only scenario vis-à-vis simultaneous emissions reduction and energy efficiency enhancement scenario, both scenarios are compatible with meeting the Paris agreement goals. This paper helps decision makers to allocate CO2 abatement targets to plants in line with their abatement costs and potential.

The impact of digital transformation on green total factor productivity of heavily polluting enterprises.

Digital transformation has become an important engine for economic high-quality development and environment high-level protection. However, green total factor productivity (GTFP), as an indicator that comprehensively reflects economic and environmental benefits, there is a lack of studies that analyze the effect of digital transformation on heavily polluting enterprises' GTFP from a micro perspective, and its impact mechanism is still unclear. Therefore, we aim to study the impact of digital transformation on heavily polluting enterprises' GTFP and its mechanism, and explore the heterogeneity of its impact. We use Chinese A-share listed enterprises in the heavily polluting industry data from 2007 to 2019, measure enterprise digital transformation indicator using text analysis, and measure enterprise GTFP indicator using the GML index based on SBM directional distance function, to investigate the impact of digital transformation on heavily polluting enterprises' GTFP. Digital transformation can significantly enhance heavily polluting enterprises' GTFP, and this finding still holds after considering the endogenous problem and conducting robustness tests. Digital transformation can enhance heavily polluting enterprises' GTFP by promoting green innovation, improving management efficiency, and reducing external transaction costs. The improvement role of digital transformation on heavily polluting enterprises' GTFP is more obvious in the samples of non-state-owned enterprises, non-high-tech industries, and the eastern region. Compared with blockchain technology, artificial intelligence technology, cloud computing technology, big data technology, and digital technology application can significantly improve heavily polluting enterprises' GTFP. Our paper breaks through the limitations of existing research, which not only theoretically enriches the literature related to digital transformation and GTFP, but also practically provides policy implications for continuously promoting heavily polluting enterprises' digital transformation and facilitating their high-quality development.

Mapping the Social, Economic, and Ecological Impact of Floods in Brisbane

Flooding has become one of the most dangerous and expensive disasters due to urbanization and climate change. Tools for assessing flood impact are required to support the shift of flood mitigation management from post-disaster recovery and reconstruction to community-driven pre-disaster warning and preparation. This study aims to develop an integrated approach to spatially assess the economic and social losses and ecological gain and identify the geographical factors of locations with high impacts of floods in Brisbane using the datasets collected from both the 2011 and 2022 flood events. Water depth, inundated area, land cover, ecosystem service value, mortality, and morbidity were considered to assess flood impacts. It is found that downstream (above 23,500 m from the upper stream) riverside communities (within 800 m of the river) with low altitudes (below 15 m) are more likely to experience significant flood damage. Flood impacts have bell-shaped developments with elevation and direct distance to the upstream river source and an exponential decline with distances to the river. These findings have implications for formulating future urban land use and community-tailored mitigation strategies, particularly for flood warning and preparation.

Bank efficiency and undesirable output: An analysis of non-performing loans in the Brazilian banking sector

This study aims to analyze the impact of non-performing loans (NPLs) on the technical efficiency of banks in the Brazilian banking sector and to identify determinants of bank efficiency. The Directional Distance Function (DDF) method is used to measure banks’ technical efficiency and identify the factors that affect it. The results show that NPLs negatively impact efficiency, compromising banking operations and reducing the ability to produce new loans, affecting profitability. From 2003 to 2019, foreign banks were, on average, more efficient than domestic public and private banks. During COVID-19 (2020–2022), federal public banks were the most efficient. The analysis also suggests that the low efficiency of domestic public banks is associated with the lower technical quality of state public banks. The practical implications of this study are that banks must manage their NPLs effectively to improve their efficiency and profitability. This study's originality lies in analyzing the determinants of bank efficiency in Brazil, which can help banks improve their efficiency and performance.

Local government competition, new energy industry agglomeration and urban ecological total factor energy efficiency: A new perspective from the role of knowledge

The contradiction between industrial agglomeration and energy constrains the development of cities. Government competition can affect the flow of factors for industrial agglomeration. Based on the data of 274 cities in China from 2005 to 2020, this paper constructs improved non-radial directional distance function (NDDF) and dynamic spatial durbin model (SDM). The paper further uses a threshold effect model and a mediating effects model to examines the impact and spillover effects of local government competition (LGC), new energy industry clustering and their integration on ecological total factor energy efficiency (ETFEE) from the perspective of the role of knowledge. To solve the problem of endogeneity, this paper uses the presence or absence of highway entrances and exits in cities in 2004 as an instrumental variable. The study found that new energy industry agglomeration and LGC can promote ETFEE in the short term, but it will inhibit ETFEE in the long term. New energy industry agglomeration affects local ETFEE through two types of mediating effects: narrowing knowledge breadth and widening knowledge distance between cities. At the same time, new energy industry agglomeration and LGC has a significant spatial spillover effect on urban ETFEE in the short term. Areas with high urban ETFEE can promote the improvement of ETFEE in neighbouring areas. However, from the perspective of regional differences, it finds that the concentration of new energy industries and LGC have different effects on ETFEE. There is a significant impact in the eastern region, but not in the central and western regions. Finally, the paper gives constructive advice for the adaptation of the knowledge structure and the improvement of energy efficiency through the national and governmental levels.

Complex determination of automatic robotic total stations' measurements' accuracy in underground spaces and comparison with results on the surface

The total station is the most basic geodetic measuring instrument, locally the most accurate and versatile. Its accuracy is the cornerstone of its use and is defined by the standard deviations of horizontal direction, zenith angle and slope distance measurements. These accuracy parameters are given by the manufacturer, but these are only valid under optimum measurement conditions. To ensure the credibility and reliability of the measurements, these values must be periodically ascertained or determined for atypical measurement configurations or measurement conditions. Standardised procedures are used for this purpose, but in our opinion, they do not reflect the full influence of the measuring conditions and other measuring aids. A comprehensive determination of the accuracies (variation components) from the alignment, where all possible influences in a given situation are applied, may be considered the most appropriate for determining the angular accuracy of measurements. Such atypical conditions are certainly represented by geodetic measurements in the confined spaces of an underground mine. Thus, an experimental determination of the accuracy of four different robotic total stations was carried out at the Center of experimental geotechnics in a mine Josef teaching centre (CTU in Prague), and the Fӧrstner method was used to determine the variation components. A network of 6 stations and 8 target points was designed. The grid size was approximately 32x21 m with 4 - 31 m lengths. A network with the same configuration was also duplicated at the surface to assess whether the accuracy is different in underground and how the results will correspond to the accuracy claimed by the manufacturers. The result of the testing is that the accuracy claimed by the manufacturers is maintained even under such difficult measurement conditions in narrow corridors and with short sights. The overall evaluation also found that the accuracy achieved underground and on the surface is identical, although it varies from instrument to instrument.

Research on Simulation of Coating Fusion and Solidification Process in Electro-Spark Deposition

As a surface-strengthening technology, electro-spark deposition (ESD) is widely used in the strengthening and repair of key components of high-end equipment. In this paper, a fusion and solidification model of ESD coating is established. The method of heat–fluid–solid interaction is adopted to simulate the material’s flow and fusion process in the droplet dropping into the molten pool. The distribution law of the coating-matrix material inside the coating was studied. Through the heat transfer between the molten material and the matrix material, the condensation and solidification process of the coating-matrix material is simulated, the temperature change in the coating area during the solidification process is analyzed, and the solidification law of the molten material is studied. The results show that the deposition time reaches 80 μs, and the content of electrode material at the bottom of the molten pool reaches 4.5%. The content of electrode material in the upper region of the material gushing out of the molten pool is higher than that in the bottom region. The material outside the molten pool solidifies first, and the molten material in the molten pool gradually solidifies from the bottom up; the shape of the solidification interface is similar to the boundary of the molten pool. Through the single-point deposition experiment of electro-spark deposition, the surface morphology of the deposition point was observed. The depth of the concave part of the contour can reach 16 μm. The difference between the two contour curves in the horizontal direction is not much; the error of the diameter is about 4%. The element distribution of the surface and the section of the deposition point are analyzed. The diffusion distance in the depth direction of the coating is about 4μm, and the transverse diffusion distance inside the coating is 364 μm. The error is 7.6% compared with the experimental results. The cross-section structure of the deposition point was observed, and the error between the experimental results and the simulation results in diameter is about 11%. It was found that the material distribution in the sedimentary area is basically consistent with the simulation results, and the simulation results are verified from the side.

How does Information and Communication Technology (ICT) industry agglomeration affect carbon emission efficiency? Evidence from China.

The Information and Communication Technology (ICT) industry takes on critical significance in promoting economic development and reducing carbon emissions. From the agglomeration perspective, how the ICT industry agglomeration affects carbon emission efficiency (CEE) in 30 provinces in China from 2006 to 2020 is innovatively investigated. We measured CEE using a dynamic directional distance function-based DEA model. Then, based on the research hypotheses, the specific impact and transmission mechanism of ICT industrial agglomeration on CEE are revealed using a spatial Dubin model and a threshold panel model. The results show that: (1) the ICT industry agglomeration exerts a remarkable inverted "U-shaped" effect on CEE. This non-linear effect is significant in the eastern and central regions, but not in the western region. (2) ICT industry agglomeration can affect CEE in neighboring regions. The spatial spillover effect shows an inverted "U-shaped" in the central region, positive in the western region, and insignificant in the eastern region. (3) when green technology innovation exceeds the threshold value (4.948), ICT industry agglomeration positively affects CEE, and when energy structure exceeds the threshold value (0.389), their marginal effects are significantly negative. The threshold effect also shows regional heterogeneity. This research proposes policy recommendations focusing on accelerating the ICT industry transformation, leveraging the spillover and technological advantages of agglomeration, and enhancing regional cooperation.

Evaluating the Efficiency of Human Capital at Small and Medium Enterprises in the Manufacturing Sector Using the DEA-Weight Russell Directional Distance Model

The present research aims to analyze the efficiency of human capital in relation to sales in each of the subsectors of economic activity within Mexican small- and medium-sized enterprises in the manufacturing industry. To accomplish this, a panel data set covering the years 2009–2020 is utilized. The inputs used are investment in training, salary, and days worked, with sales as the output. Initially, due to the high variability (cv > 1) of both the inputs and the output, the information is divided into three groups by quartiles: Group 1 < 25%, Group 2 = 25–75%, and Group 3 > 75%. As a first step in the analysis, a hypothesis test identifies a significant increase in sales for those subsectors that reported investing in training compared with those that did not. As a result, for the efficiency analysis, SMEs that report not investing in training are removed from the sample. Subsequently, to confirm the statistical explanation of the inputs for the output, a regression analysis is performed. With an input-oriented DEA model, it is found that most subsectors exhibit high overall and pure efficiency (≥0.75) as well as increasing returns to scale. Interestingly, the research introduces a novel approach by proposing subgroups within SMEs, providing a more precise analysis. The findings of this study emphasize the fundamental role of human capital as a key driver of economic growth and innovation within the manufacturing sector. This research also highlights variations in efficiency among different subsectors, underscoring the need for tailored strategies for each. These results offer practical guidance for companies seeking to optimize their operations and contribute to the economic development of a developing country. In conclusion, this paper contributes both theoretically and practically to understanding the interaction between human capital and financial indicators. The results underscore the importance of investing in workforce development, ultimately promoting economic growth, improving productivity, and advancing social progress.

The effects of kinesiophobia on postural control with chronic ankle instability

BackgroundPatients with chronic ankle instability (CAI) often experience injury-related fear following ankle injuries, a condition known as kinesiophobia. Little research has investigated the impact of kinesiophobia in patients with CAI. Research questionHow does kinesiophobia impact the static and dynamic balance of individuals with CAI? MethodsFifty patients with CAI were divided into 2 subgroups based on their responses to the Tampa Scale of Kinesiophobia: 25 with kinesiophobia (CAI-K) and 25 without kinesiophobia (CAI-N). These groups were compared to 20 control participants. All participants performed a single-leg balance test with eyes open (EO) and eyes closed (EC). They also performed the Y-balance test (YBT) with EO. Romberg ratios were calculated as EC/EO and used for statistical analysis. ResultsNo differences in static balance with EO and EC were found among three groups. However, the CAI-K group displayed a higher Romberg ratio in the mediolateral direction during static balance than both CAI-N and control groups. Additionally, both CAI-K and CAI-N groups displayed higher Romberg ratio in the anterior–posterior than controls. During YBT, the CAI-K group showed reduced reach distance in the anterior direction than CAI-N and control groups. SignificanceThe CAI-K group relies more on visual feedback during static balance in the mediolateral direction than CAI-N and control groups. Furthermore, the CAI-K group displayed less anterior reach distance during YBT compared to the CAI-N and control groups. Clinicians should consider both psychological and physical factors when designing rehabilitation programs.

Directional distance functions data envelopment analysis method with endogenous direction for target setting

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.

Agricultural tridimension pollution emission efficiency in China: An evaluation system and influencing factors

We innovated traditional one-sided agricultural carbon emission efficiency research, comprehensively explored the agricultural tridimension pollution emission efficiency (ATPEE), constructed an ATPEE evaluation system considering technological heterogeneity characteristics based on the meta-frontier nonradial directional distance function (NDDF) model in a total-factor framework, evaluated the ATPEE in 30 mainland China provinces from 1997 to 2021 for the first time, and empirically studied the factors influencing the ATPEE in China with the Tobit model. The results showed the following: (1) ATPEE improvement potentials of 75.16 % and 50.88 % occur under the meta and group frontiers, respectively. (2) The eastern region represents the potential optimal agricultural tridimension pollution emission technology, while the central and western regions exhibit a large gap with the national potential optimal technology level. (3) The ATPEE loss in the eastern and western regions mainly results from management inefficiency, while that in the central region largely results from technology gap inefficiency. (4) The effects of the industrialization rate, urban–rural income gap, agricultural production structure, financial support for agriculture, natural conditions and effective irrigation rate on the ATPEE in the different regions vary.

The impact of digital infrastructure on energy-environmental efficiency: empirical evidence from China

Frontier studies have focused on the environmental performance of traditional infrastructure, but have generally neglected the effects and mechanisms of digital infrastructure on energy-environmental efficiency. This study attempts to use fixed effect models and mediating effect model based on panel data from 30 provinces in China from 2010 to 2017 to assess the impact of digital infrastructure on energy environmental efficiency and identify its mechanism. The non-radial directional distance function is used to measure energy environmental efficiency. The empirical results show that digital infrastructure promotes energy-environmental efficiency, which remains robust after a series of tests. Technological progress and energy industry advancement are the pathways through which digital infrastructure affects energy-environmental efficiency. Furthermore, we find that the positive effect of digital infrastructure on energy and environmental efficiency is significant in the east and where factor mismatch is high. Therefore, policymakers should develop digital technology and enact various environmental policies to effectively increase the construction of digital infrastructure, promote investment in technology research and development, accelerate the energy technology progress, and improve energy efficiency.

Numerical study on the heat transfer characteristics of hydrocarbon fuel in the cooling channel filled with porous media

Regenerative cooling channel is only heated by a single wall in practical applications, resulting in serious thermal stratification. Under the action of porous media, the wall temperature decreases, which avoids the heat transfer deterioration caused by velocity distortion near the high temperature wall. Compared with the cooling channel without porous media, the porous media improves the homogeneity of the coolant heat sink, and the physical and chemical heat sink non-uniformity coefficient at the outlet is close to 0 with the change of aspect ratio. The increase of the height of the cooling channel increases the heat transfer distance in the height direction, which increases the heat transfer resistance of the heat flux and makes the uniformity of the heat sink worse. The positive feedback between the coolant flow rate and the non-uniform heat flux on the parallel filled channel wall can be effectively suppressed. The porous media greatly reduces the radial transfer shortens the axial distance between the upper and lower walls maximum temperature difference, and reduces the thermal stress of channel during the cooling process.

Evaluating the synergistic effect of digitalization and industrialization on total factor carbon emission performance

Combating climate change and reducing carbon dioxide emissions are serious challenges shared by countries around the world. In the current era, digitalization has a significant impact on CO2 emissions. However, prior studies have not assessed the synergy between digitalization and industrialization on carbon emission performance. The principal component analysis and non-radial directional distance function (NDDF) are used to measure the digitalization and total factor carbon emission performance of Chinese 245 prefecture-level cities from 2003 to 2019. This study establishes a fixed effects model to study the panel data. The findings are as follows: (1) Digitalization can significantly promote Chinese cities' CO2 emission reduction. This result still holds after several robustness checks. (2) The heterogeneity results indicate that digitalization mainly improves central cities’ carbon emission performance. Meanwhile, the impact of digitalization is more obvious after 2011. (3) Digitalization improves urban carbon emission performance through energy efficiency, industrial transformation, and technological innovation. (4) It is worth noting that digitalization synergizes with industrialization to improve carbon emission performance in Chinese cities. This study provides empirical evidence and some constructive policy recommendations for the government to push the collaborative development of the digitalization and low-carbon economy.

Can China's carbon intensity constraint policies improve carbon emission performance? Evidence from regional carbon emissions

Carbon Intensity Constraint Policies (CICPs) are vital for addressing climate change challenges and advancing sustainable development. Since 2010, China has rolled out three five-year CICPs. However, there is limited understanding of their impact on carbon emission performance (CEP). Addressing this, this study pioneers the exploration of the CICP's impact on China's CEP. Drawing from government intervention and green paradox theories, this study highlights a concerning scenario: local governments achieve emission targets via excessive intervention. For deeper insights, this study melds the overall technology frontier concept with a non-radial, non-angle directional distance function, introducing a novel efficiency model rooted in the Data Envelopment Analysis (DEA) method. This offers a CEP measure across 30 Chinese provincial regions from 2002 to 2019. Using the quasi-difference-in-differences (quasi-DID) and moderated mediation models, this study ascertains the presence of the green paradox, uncovers its reasons, and suggests mitigation strategies. The results indicate that high government intervention diminishes CEP. This negative effect intensifies under greater regional fiscal pressure. Alarmingly, local authorities' eagerness to meet targets shows a counterproductive, inverted N-shaped trend regarding CICPs' time-based influence on regional CEP. Moreover, the impact varies based on regional economic development levels and stages. This study has ensured the robustness of the findings via parallel trend tests, parallel exclusion policies, a strengthened quasi-DID framework, and diverse control variable configurations. This study underscores the need for more balanced government intervention. It offers valuable policy insights, guiding China's upcoming CICP phase to realize the ambition of peaking carbon by 2030 and achieving carbon neutrality by 2060.

The underlying radial acceleration relation

ABSTRACT The radial acceleration relation (RAR) of late-type galaxies relates their dynamical acceleration, gobs, to that sourced by baryons alone, gbar, across their rotation curves. Literature fits to the RAR have fixed the galaxy parameters on which the relation depends – distance, inclination, luminosity, and mass-to-light ratios – to their maximum a priori values with an uncorrelated Gaussian contribution to the uncertainties in gbar and gobs. In reality these are free parameters of the fit, contributing systematic rather than statistical error. Assuming a range of possible functional forms for the relation with or without intrinsic scatter (motivated by modified Newtonian dynamics with or without the external field effect), I use Hamiltonian Monte Carlo to perform the full joint inference of RAR and galaxy parameters for the Spitzer Photometry and Accurate Rotation Curves (SPARC) dataset. This reveals the intrinsic RAR underlying that observed. I find an acceleration scale $a_0=(1.19 \pm 0.04 \, \text{(stat)} \pm 0.09 \, \text{(sys)}) \: \times \: 10^{-10}$ m s−2, an intrinsic scatter $\sigma _\text{int}=(0.034 \pm 0.001 \, \text{(stat)} \pm 0.001 \, \text{(sys)})$ dex (assuming the SPARC error model is reliable), and weak evidence for the external field effect. I make summary statistics of all my analyses publicly available for future SPARC studies or applications of a calibrated RAR, for example direct distance measurement.

Enhanced Combined Protection Scheme Using Dual Setting Directional Overcurrent and Distance Relays Considering Severe Line Contingencies

An electrical power system must have an optimal protection system for enhanced reliability. Numerous studies have attempted to address issues with protection schemes, such as coordination constraint violations due to change in network configuration. Furthermore, in a few articles, the N-1 line contingency is considered without considering the line contingency selection criterion, resulting in a large number of constraints to deal with in the optimization problem. This paper proposes a new relay coordination scheme for dual setting directional overcurrent relay (DOCR) and distance relay based on the severity index of line outages, which is calculated by using an active and reactive performance index. The proposed protection strategy is improved with the help of an intelligent selection of the relay characteristics coefficient for dual setting DOCR along with the other relay settings. Another significant contribution is to provide a comparative analysis of standard and user-defined relay characteristics using genetic algorithm and grey wolf optimization algorithms. The modified IEEE-14 bus test system and IEEE-39 bus test system is used to validate the efficacy of the proposed protection scheme.

Generalized theory for measuring efficiency of individuals and groups

We present a cohesive generalized framework for an aggregation of the Nerlovian profit indicators and of the directional distance functions, frequently used in productivity and efficiency analysis in operations research and econometrics (e.g., via data envelopment analysis or stochastic frontier analysis). Our theoretical framework allows for greater flexibility than previous approaches, and embraces many other approaches as special cases. In the proposed aggregation scheme, the aggregation weights are mathematically derived from assumptions made about the optimization behavior and about the chosen directions of measurement. We also discuss various interesting special cases of popular directions, including the case of Debreu-Farrell-type efficiency.