Technical Efficiency Change Research Articles

The Use of the Data Envelopment Analysis–Malmquist Approach to Measure the Performance of Digital Transformation in EU Countries

Currently, the process of the digital transformation of EU countries is very important and often discussed. It will not only bring new opportunities for companies and the broader population but will also enable the transition to a more ecological economy. An important goal is to speed up the digitalization processes taking place in companies. It is very important to use already established digitalization elements more efficiently. This also resulted in the motivation for the given research. The aim of this paper is to quantify the change in the efficiency of the digital transformation of EU countries. As part of this research, the Variable Returns to Scale Data Envelopment Analysis (VRS DEA) model and the Malmquist index (MI) based on the DEA approach were applied. The results of the model made it possible to assess how the changes in technical efficiency and technological changes contributed to the changes in efficiency. The long-term theoretical added value of this paper lies in its proposal for countries and their governments to monitor not only the number of introduced digital elements, but also the efficiency of their use relative to some aggregate output; for example, GDP (Gross Domestic Product) or unemployment rate. The added value of this research is that less developed countries use digitalization elements more effectively than developed countries.

DEA-Based Malmquist Productivity Approach for Assessing Total Factor Productivity Change in Malaysian Public Universities

This study uses the non-parametric frontier method to examine the productivity growth of Malaysian public universities from 2017 to 2021. It examines changes in productivity at university groups and individual institutions, using three inputs (academic staff, undergraduate student enrolment, and postgraduate student enrolment) and three outputs (undergraduate and postgraduate qualifications awarded and publications). This study analyses productivity changes and breaks them down into technical efficiency and technological change using the Data Envelopment Analysis (DEA)-based Malmquist productivity index (MPI). The analysis reveals that public universities in Malaysia have seen an average annual increase in MPI of 0.5% over the period of the study. However, when the components of this productivity change are examined, it becomes evident that Malaysian public universities have had an annual average 1.3% increase in technology along with a 0.8% decline in technical efficiency. Further evaluation of the indexes reveals disparities between Malaysian university groups. Technical, comprehensive, and research universities make up the group that performs the best to the worst. Although Malaysian public universities’ productivity is increasing, it is mostly due to technology, which comes at the expense of decreased technical efficiency.

Research on Input-Output Efficiency and Influencing Factors of Listed Logistics Enterprises

This paper mainly analyzes the input-output efficiency of 25 listed logistics enterprises from 2012 to 2020, and draws the following conclusions: 1) From the perspective of the change of comprehensive technical efficiency, the comprehensive technical efficiency change index of most enterprises is less than 1, which indicates that the improper management mode and decision-making of these enterprises hinder the improvement of enterprise efficiency. The comprehensive technical efficiency of listed logistics enterprises is analyzed by using the BCC model, and the conclusion is that the comprehensive technical efficiency of most listed logistics enterprises is less than 1 during 2012-2020, which indicates that the input-output of most listed logistics enterprises is not optimal. 2) Regional GDP, the proportion of employees with bachelor's degree or above and the total asset turnover have no significant influence on the input-output efficiency of listed logistics enterprises; The total assets of enterprises are negatively correlated to the input-output efficiency.

The measurement, level, and influence of resource allocation efficiency in universities: empirical evidence from 13 “double first class” universities in China

China’s higher education system is shifting from quantitative expansion to connotative development to advance its quality. Since 2015, Chinese governments have been implementing a strategic policy for higher education called “double first-class”, which aims to promote a number of Chinese top universities to construct world-class universities or to establish world-class disciplines. “Double first-class” universities have received a large amount of educational resources through this policy. Taking advantage of resources efficiently is an important element in promoting the development of higher quality higher education. However, research on resource allocation in China’s “double first-class” universities is incomplete. Current research has not clarified the level of resource allocation efficiency or the factors affecting China’s “double first-class” universities. With the help of the superefficient data envelopment analysis (DEA)-Malmquist–Tobit model, this study actively explores the current status of the resource allocation efficiency of China’s “double first-class” universities to fill this gap in the field. Specifically, the development level and change trend of the resource allocation efficiency of 13 “double first-class” universities in China from 2015 to 2019 were measured with the help of the superefficient DEA-Malmquist model. The internal and external factors affecting the resource allocation efficiency of “double first-class” universities are also analysed with the help of the Tobit model. The overall level of resource allocation efficiency of “double first-class” universities is high, but the internal variability is large. From the perspective of efficiency decomposition, it is found that both technical efficiency change (EFch) and technical progress efficiency (TEch) play important roles in improving the total factor productivity (TFP) of resource allocation. Compared with TEch, EFch plays a more significant pulling role. This study confirms that the factors affecting resource allocation efficiency are complex. Among them, the regional economic environment, faculty title structure, and degree of international exchange have significant roles in promoting the resource allocation efficiency of “double first-class” universities, but local financial support and the time of policy implementation have certain negative effects.

Impacts of Capital Formation and Investment Sources on Total Factor Productivity: The Example of Nigeria’s Agriculture

The study was designed to analyse the impact of capital formation and investment sources on Nigeria's agricultural productivity from the period 1980 - 2021. The time series data were analysed with Malmquist Data Envelopment Analysis (DEA) and the tobit regression models using DEA, the Total Factor Productivity Change, which quantifies the degree of productivity, was estimated at 1.022, which implies an average productivity progress of 2.2% annually. Again, since the value of technical efficiency change is less than technological change, it implies that the productivity gains are mainly attributable to technological progress instead of efficiency improvements in the periods under the study. The results of tobit regression indicate that domestic capital formation significantly influences agricultural TFP, highlighting the importance of government expenditure on agriculture (GEA) and gross fixed capital formation (GFCF) in enhancing productivity, although with minimal effects. Human capital formation (HCF) also showed positive impacts on Total Factor Productivity TFP, suggesting that improvements in workforce skills and knowledge are crucial for agricultural efficiency. However, FDI exhibited no significant correlation with TFP, implying that local investments are more beneficial than foreign aids in the context of Nigeria's agricultural sector. The findings emphasize the need for robust policy frameworks that align capital disbursements with agricultural production periods to optimize TFP. This study contributes to the discourse on agricultural productivity by providing empirical evidence on the critical role of capital investments in enhancing TFP within developing economies like Nigeria.

Empirical evidence of the relationship between regulatory efficiency, market openness, and bank productivity in economies at different income levels: Evidence from selected Asian and MENA countries

Research background: Economic freedom plays a pivotal role in ensuring the progressive productivity of banks. It fosters a favorable economic climate and acts as a catalyst for the generation of innovative ideas. In addition, economic freedom allows new domestic and foreign entrants in the banking sector which leads to increased competition as well as wider range of product offerings and thus potentially affect bank efficiency. Purpose of the article: This study aims to identify the effects of regulatory efficiency and market openness in terms of economic freedom on the bank’s productivity at three income levels: lower-middle, upper-middle, and high-income economies. Methods: A sample of 15 countries are included in the study from differing income levels. The study uses the data envelopment analysis (DEA) based Malmquist productivity index (MPI) approach to measure banks’ productivity. This non-parametric approach measures the relative efficiency of banks by considering the production change while taking into account technical efficiency change and technological change in order to capture a comprehensive view over time. Then, regression analysis was performed utilizing the ordinary least squares (OLS) approach, fixed effect (FE), and random effect (RE) panel multiple regression estimation methods are utilized to measure economic freedoms and other determinants’ effect on banks’ productivity change over time. Findings & value added: The results show that banks in high-income economies are more productive and have higher growth rates than those in upper- and lower-income economies. Furthermore, starting, obtaining permits, and closing businesses under business freedom have a detrimental effect on banks’ output, whereas the effects of labor freedom on employing, managing, and supervising staff members have a substantial favorable impact on banks’ productivity. Moreover, financial freedom and investment freedom under the market openness dimension negatively influence banks’ productivity. Government intervention is required to introduce regulations that allow foreign countries to provide labor at lower wages, introduce tax allowances, and control inflation rates. Thus, the empirical results of this study will benefit regulators and policymakers in developing a system and plan to increase banks’ productivity based on indicators of business, labor, financial, and investment freedom.

Rising Tides of Knowledge: Exploring China’s Higher Education Landscape and Human Capital Growth

AbstractThis study examines the status of human capital in China’s higher education system by analyzing the quantity of higher education institutions as a metric. The results show a general enhancement in human capital in all regions, along with an optimized structure. This is demonstrated by a decline in the primary education demographic, a consistent growth in secondary education, and a rapid surge in the higher education demographic. The percentage of junior college students has remained steady, whereas the ratios of undergraduate and graduate students have been consistently increasing. The Malmquist index method is used to analyze changes in total factor productivity (TFP) among provinces and regions by breaking it down into technical level and efficiency changes. From 2005 to 2010, there was a general increase in total factor productivity (TFP) and technical proficiency, although technical efficiency showed only slight enhancement. TFP and technical level growth decelerated from 2011 to 2020, while technical efficiency stayed above 1. These findings indicate that China’s total factor productivity (TFP) growth is mainly driven by technological advancements, with minimal improvements in technical efficiency.

Coupling coordination of the digital-energy system and its impact on energy efficiency:Evidence from the “2+26” cities of Beijing-Tianjin-Hebei, China

The digital economy and energy are crucial drivers of economic transformation, and the global development trend is toward the deep integration of the two. Previous studies carried out at the provincial scale, show it is difficult to grasp the change characteristics of prefecture-level cities. From the scale of urban agglomeration, energy management problems in different regions can be more accurately grasped. This study examines the Beijing-Tianjin-Hebei area and its seven surrounding regions, commonly known as the “2 + 26” cities. Panel data from 28 prefecture-level cities between 2011 and 2019 are utilized for analysis. First, the area's energy efficiency was assessed using the DEA-SBM model. Second, the development coordination relationship among the digital system and energy system is evaluated by using the coupling coordination degree model. Finally, the process of coupling coordination of digital-energy systems affecting energy efficiency was examined using a three-step stepwise regression and bootstrap mediation model. The findings demonstrate that: (1) The “2 + 26” cities' energy efficiency is considerably different. The distribution of the high efficiency zone changes from “high in the south and low in the north” to the state of radiating southward with Beijing and Tianjin as the center. (2) “2 + 26” cities are in the dynamic evolution stage of low to medium coupling degree, accounting for 89.3 % of all cities. The coupling coordination degree of digital-energy system has increased throughout the entire city by 49 %. (3) Energy efficiency improved by 64.7 % while the coupling coordination degree of the digital energy system grew by 1 %. The total effect of technical efficiency changes on energy efficiency accounted for 8.2 %. The research results could provide differentiated policy recommendations for regional energy use.

Provincial Coal Flow Efficiency of China Quantified by Three-Stage Data-Envelopment Analysis

The exploration of regional variations in coal flow efficiency (CFE) in China and the collaborative strategies for emission reduction are vital for accelerating the progress of ecological civilization within the coal industry and achieving an optimal allocation of coal resources. To unveil the evolutionary traits of actual CFE and its decomposition, this study employs a current technology based on a combined super-efficient measure (SBM), global SBM, the stochastic frontier approach (SFA), and the global Malmquist–Luenberger index (GML) model on panel data from 2010 to 2021 across 30 provinces in China. The research conclusions are as follows. First, significant efficiency gaps are observed among provinces, showcasing superior performance in the north and east regions. Moreover, the impact of environmental factors and random disruptions on individual slack variables varies, resulting in a decrease of 0.18 and 0.43 in the CFE of source-area and sink-area when these factors are not taken into account. Thirdly, a clear distinction emerges between the technical efficiency change index (EC) and the best-practice gap change index (BPC). Lastly, the CFE displays regional disparities marked by an upward trajectory and fluctuating patterns resembling a “W” shape.

The effect of COVID-19 pandemic on the efficiency of training and research hospitals in Turkey

The Coronavirus disease 2019 (COVID-19), which emerged in December 2019, caused an increase in the demand for healthcare services globally. Hospitals’ operational and financial performances are thought to have been negatively affected by COVID-19 because they had to postpone providing non-urgent healthcare services to prevent infection. This study aimed to evaluate how the COVID-19 pandemic has affected the efficiency of training and research hospitals in Turkey. The study population comprised 51 training and research hospitals. The Malmquist Total Factor Productivity index was used to examine the changes in the efficiency of the training and research hospitals between 2017–2018, 2018–2019, 2019–2020, and 2020–2021. In addition, a repeated-measures ANOVA test was used to evaluate whether a significant difference existed in the efficiency levels of the hospitals in the pre-COVID-19 pandemic periods (2017–2018 and 2018–2019) and during them (2019–2020 and 2020–2021). No significant difference was found between hospitals' technical and scale efficiency levels before and during the pandemic, but the change in total factor productivity was significant (F = 34.18; p < 0.001). Our research findings provide clues about how hospitals' behaviours changed during the pandemic compared to before the pandemic. It was observed that efficiency decreases in hospitals at the onset of the pandemic disappeared with the adaptation process to the new normal. Technical efficiency decreased in two periods (2017–2018 and 2020–2021) when total factor productivity increased. Reverse changes in total factor productivity and technical efficiency indicate that technological change drives total factor productivity. This study identified differences in hospital efficiency during both ordinary and extraordinary periods. It would benefit managers and policymakers to recognise these differences and focus on managerial skills that ensure technical efficiency in extraordinary circumstances to mitigate possible efficiency losses.

The economic impact of E-commerce on the U.S. airports: Cost savings and productivity growth

The rise of e-commerce, fueled by digitalization and shifting in consumer demand, has revolutionized air cargo. While all e-commerce stakeholders are engaged in fierce competition to increase their market share, airports as integral elements of the air cargo supply chain could not be apathetic to this competition. This study examines the economic implication of e-commerce on high cargo volume airports, focusing on cost savings and productivity growth. Utilizing the Farrell measure of input-oriented technical efficiency, we estimate scope economies for the U.S. airports between 2009 and 2019. The results reveal higher scope economies for high cargo volume airports, indicating greater cost savings resulting from e-commerce activities. In addition, the Malmquist index is employed to assess productivity growth. The index is decomposed into technical change, efficiency change, and scale change. The findings show a 3.3% overall productivity growth in the U.S. airport industry, primarily driven by technical change. Besides, high cargo volume airports exhibit higher productivity growth compared to low cargo volume airports, with 4.1% and 2.9% growth rates, respectively. The gap between high cargo volume and low cargo volume airports widened in 2017, aligning with the pre-pandemic peak in e-commerce activity. Furthermore, high cargo volume airports experience higher efficiency gains and technical advancements. While efficiency gains are attributed to improved performance and increased capacity utilization, the technical advancements can be explained by the digitalization and customized operations associated with e-commerce. Overall, the results highlight the significant contribution of e-commerce to cost savings and productivity growth in high-cargo volume airports.

How to improve fishery eco-efficiency by building marine ranch in China

Based on the panel data of the province and municipality in 2010–2021, this paper measures the fishery eco-efficiency by using the SBM-DEA model and empirically analyses how China’s marine ranch construction improves the fishery eco-efficiency by using the double-difference fixed-effect model. The results show that, firstly, China’s marine ranch construction can improve the fishery eco-efficiency. Secondly, China’s marine ranch construction promotes fisheries eco-efficiency by improving the input efficiency of labor, fish species, fishing vessel, fishery technology extension, aquaculture area and by reducing pollutant outputs. Thirdly, the fishery eco-efficiency of the marine ranch construction region has increased annually since 2015, and technological changes, scale efficiency changes and technical efficiency changes can all contribute to the fishery eco-efficiency improvement, and increase in order. Based on the results of the empirical analyses, this paper proposes policy recommendations to improve the fishery eco-efficiency in the conjunction with the construction of marine ranch in China.

Efficiency Analysis of Life Insurance Companies in Indonesia and Malaysia

This study focuses on measuring the performance of life insurance companies in Indonesia and Malaysia. Input oriented Data Envelopment Analysis (DEA) uses panel data to extract the efficiency score of 5 life insurance companies from Indonesia and 5 life insurance companies from Malaysia for the year of 2015-2019. DEA-based Malmquist Total Factor Productivity (TFP) Index used to measure the efficiency change along the study period. This study utilizes asset and operating expenses as input variables, as for output variables, this study utilizes premium and investment income. Based on an efficiency score computed by DEA, most of the life insurance companies in both countries perform efficiently during the study period. However, life insurance companies in Indonesia still perform more efficiently than Malaysian life insurance companies. The results of the Malmquist TFP Index for life insurance companies in both countries show that there is 2.5% improvement in technical efficiency change, 1.5% deterioration in technology efficiency change, 0.6% improvement in pure efficiency change, 1.9% improvement on scale efficiency change, and 0.9% increase in TFP change. It shows that the main reason for TFP increased is due to improvement of technical efficiency change.

Evaluation of China’s Marine Aquaculture Sector’s Green Development Level Using the Super-Efficiency Slacks-Based Measure and Global Malmquist–Luenberger Index Models

Given China’s rapidly expanding marine aquaculture industry, the associated ecological issues have garnered widespread attention. Therefore, it is crucial to speed up the green growth of marine aquaculture in order to save the environment and use resources sustainably. In order to statically assess and dynamically analyze the green development efficiency levels of marine aquaculture in nine coastal provinces of China from 2012 to 2021, this study uses the non-expected output super-efficiency Slacks-Based Measure model and the Global Malmquist–Luenberger index method. Additionally, it integrates input–output redundancy rates to analyze the causes of efficiency loss. Static efficiency primarily reflects whether a region’s inputs and outputs at a given point in time reach an effective efficiency level, while the level of dynamic efficiency mainly gauges the dynamic changes in the efficiency of green production. The results show that, from 2012 to 2021, China’s marine aquaculture industry’s average static efficiency of green output was 0.705. The southern marine economic zone exhibited the highest static efficiency value in the green development of marine aquaculture, displaying a stepped distribution pattern of “south–north–east” in decreasing order. The input–output redundancy analysis reveals that the primary causes of static efficiency loss in China’s marine aquaculture industry are attributed to varying degrees of redundant inputs and carbon emission outputs. Looking through the lens of the GML index, the annual average growth rate of the green total factor productivity in China’s marine aquaculture stands at 11.1%, with an annual average change in technical efficiency of 1.8%, while the annual average change in technological progress amounts to 9.1%, suggesting that technological advancement is the primary driver of the rise in green total factor productivity in China’s marine aquaculture sector. According to the study, in order to encourage China’s marine aquaculture industry to grow sustainably, efforts should be made not only to accelerate technological advancements but also to enhance technical efficiency. Policies that are specifically designed for the local environment should be developed to support the sustainable development of the marine aquaculture sector and to make resource allocation easier.

A firm-specific Malmquist productivity index model for stochastic data envelopment analysis: an application to commercial banks

In the data envelopment analysis (DEA) literature, productivity change captured by the Malmquist productivity index, especially in terms of a deterministic environment and stochastic variability in inputs and outputs, has been somewhat ignored. Therefore, this study developed a firm-specific, DEA-based Malmquist index model to examine the efficiency and productivity change of banks in a stochastic environment. First, in order to estimate bank-specific efficiency, we employed a two-stage double bootstrap DEA procedure. Specifically, in the first stage, the technical efficiency scores of banks were calculated by the classic DEA model, while in the second stage, the double bootstrap DEA model was applied to determine the effect of the contextual variables on bank efficiency. Second, we applied a two-stage procedure for measuring productivity change in which the first stage included the estimation of stochastic technical efficiency and the second stage included the regression of the estimated efficiency scores on a set of explanatory variables that influence relative performance. Finally, an empirical investigation of the Iranian banking sector, consisting of 120 bank-year observations of 15 banks from 2014 to 2021, was performed to measure their efficiency and productivity change. Based on the findings, the explanatory variables (i.e., the nonperforming loan ratio and the number of branches) indicated an inverse relationship with stochastic technical efficiency and productivity change. The implication of the findings is that, in order to improve the efficiency and productivity of banks, it is important to optimize these factors.

Performance measurement of international shipping companies before and during COVID‐19: A DEA Malmquist index and window analysis approach

AbstractFor the past several decades, the container shipping industry has grown rapidly. As a result, container shipping companies (CSCs) play a vital role in the global cargo transportation market. Thus, measuring the efficiency of CSCs is a primary concern of managers and practitioners. When the COVID‐19 pandemic broke out, the industry was severely disrupted and presented with unprecedented challenges. For this reason, evaluating how CSCs performed and learning the practices they took to achieve successful business results during this period have become necessary. To serve that purpose, this article used a hybrid method that combined data envelopment analysis Malmquist index with window analysis to analyze the world's nine leading CSCs' performance over time and their efficiency relative to each other, using data collected within a 5‐year period from 2016 to 2020. Our findings revealed different characteristics and trends in efficiency among these CSCs in terms of technical efficiency change, technological change, and total productivity change. Then, managerial implications were discussed to understand the best practices of successful CSCs as well as the circumstances in which some of them underperformed during this time. In closing, the study summarized a fact‐based guideline CSCs could take as management reference should a similar crisis occur.

Towards decoupling in chemical industry: Input substitution impacted by technological progress

The chemical industry is one of the fundamental industries of economic development. Coordinating the relationship between economic growth and carbon emissions (EGCE) is crucial in realizing the carbon neutrality target. The Tapio model and decomposition models are used to assess the degree of decoupling within the Chinese chemical industry and identify pivotal factors impeding progress. The energy efficiency decomposition model explores the crux of failure to achieve strong decoupling. This framework further decomposed the energy intensity to uncover how technical efficiency, technological progress, and input substitution changes affect energy intensity and CO2 emission. The paper found that the EGCE of the chemical industry were stable in a weak decoupling mode from 2009 to 2019. The reliance on technological progress to reduce energy intensity and emissions is insufficient (accounting for only 18.2%), far below the cumulative contribution from economic growth (accounting for 57.76%), which has become the crux of the strong decoupling failure. Technological advancements drive energy substitution for labour, resulting in 244.41 Mt of cumulative carbon emissions. The improper factor input allocation hinders the desired reduction in energy intensity and carbon emissions. A series of policy implications are proposed based on the insights derived from the decomposition analysis to foster sustainable practices in the chemical industry.

Efficiency and productivity growth in US food manufacturing industries: Exporters, ownership changes, and firm characteristics

AbstractThis study employs a stochastic production frontier framework to measure productivity growth among exporters, non‐exporters, and firms experiencing ownership changes through mergers and acquisitions in US food manufacturing. Analyzing a panel data set that integrates Economic Censuses and transaction‐level exports, the results reveal the coexistence of more productive exporters, driven by technical efficiency, alongside less productive non‐exporters. Exporters in arm's length transactions show productivity growth driven by technical efficiency change, while those in related party transactions benefit mainly from technological change. Firms undergoing ownership changes exhibit positive productivity growth with a greater contribution from technical efficiency compared to those without such changes.

Urban green total factor productivity in China: A generalized Luenberger productivity indicator and its parametric decomposition

In this study, by taking the distance elasticity shares as the input weights in the production function, the generalized Luenberger productivity indicator (GLPI) was proposed to analyze the urban GTFP in China, and the stochastic frontier analysis (SFA) was used for parametric decomposition to obtain the technological change (TC), technical efficiency change (TEC), and scale efficiency change (SEC). The results show that the entire model and specific parameters passed the test, and the production function equation has good economic and statistical significance, which shows that it is feasible to use the parameter approach to measure and decompose the GLPI. Second, the value of the GLPI showed a rapid growth trend between 2000 and 2019, with a cumulative increase of 140.59%, indicating that various inputs were saved by 3.43% in a specific proportion, and that remarkable achievements have been made in the sustainable development of Chinese cities. Third, TC, TEC, and SEC all showed significant spatiotemporal heterogeneity, in which SEC was the main numerical component and TC was the driving force of the GLPI. Through mathematical proof in theory and data matching in reality, it is confirmed that the GLPI proposed in this study is scientific and applicable.

Total Factor Productivity Growth in the Indian Food Processing Industry: A Non-parametric Investigation

This study analysed total factor productivity growth (TFPG) in the Indian food processing industry in the organised sector. The results showed that TFPG in this industry resulted from technical progress and that the role of change in technical efficiency was insignificant. Therefore, for sustainable output growth, the application of new technologies must be followed by adaptation. In this context, policymakers should consider sub-sectoral heterogeneity when designing policies for the Indian food processing industry so that the rates of applying technology and its adaptability can be matched for each industry sub-sector. Thus, the study offers a strong note of caution about investments in technological improvements.