Malmquist Productivity Index Research Articles

Balancing economic and environmental strategies in regional hinterland transport: a dynamic network cross efficiency analysis

Balancing economic and environmental strategies in regional hinterland transport: a dynamic network cross efficiency analysis

The efficiency and productivity-changing trend of PHCIs since the 2009 health reform in China based on a three-stage DEA and Malmquist Productivity Index.

In China, most primary health care institutes (PHCIs) support ground-level medical services which are essential to residents' health levels. The Chinese government implemented a health reform in 2009 to strengthen PHCIs through increased fiscal inputs. However, how efficiently these inputs were converted into PHCIs' services remains unclear. We aimed to examine the efficiency of PHCIs' medical services and investigate if any changes occurred following the implementation of the health reform. We aggregated data from PHCIs from Hainan's 18 districts (2011-21), treating those from the same district as one decision-making unit (DMU). We used three-stage data envelopment analysis (DEA) to assess the efficiencies of these PHCIs, adjusting the approach for environmental factors, managerial ineffectiveness, and statistical errors potentially arising from the background variability of measured data that deviates from the input and output values, allowing all DMUs to be compared in a homogeneous environment. We used the adjusted efficiency scores to evaluate the efficiency of PHCIs in Hainan each year and the Malmquist Productivity Index (MPI) to explore the productivity change of PHCIs over time. After adjusting for environmental factors between 2011-21, technical efficiency (TE) decreased from 0.825 to 0.745, pure technical efficiency (PTE) increased from 0.936 to 0.954, and scale efficiency (SE) decreased from 0.883 to 0.783. Seven districts had full PTE (1.0) and two districts had full TE (1.0) after adjustment. The mean MPI from 2011 to 2021 was 0.9430, indicating a 5.7% decrease in PHCIs' efficiency. After excluding the low productivity index possibly influenced by COVID-19 (2019 to 2021), PHCIs' efficiency decreased by 0.49%, with a mean MPI of 0.9951. The efficiency of PHCIs in Hainan has declined slightly since the health reform. Low level of scale efficiency posed a significant impact on the overall efficiency of the medical services in PHCIs. Among potential inefficient technological performances, future policy formulation might focus more on the imbalanced allocation of resources in less-developed regions and PHCIs' lack of attractiveness to local patients.

Productivity dynamics of U.S. airlines and COVID-19 crisis: insights from a two-stage network Malmquist productivity index

ABSTRACT This study examines quarterly productivity changes of U.S. airlines before, during, and after the COVID-19 crisis using a new two-stage network Malmquist productivity index. Findings reveal significant initial productivity losses at the pandemic’s onset, followed by a rebound in later quarters as airlines adapted. While airlines excelled at generating revenue, significant productivity gains were achieved through enhanced resource utilization. Moreover, technological innovations also played a crucial role in driving this productivity recovery. Notably, although all three carrier types – Full-service, Low-cost, and Regional – demonstrated comparable rates of productivity change throughout the study period, a difference in their efficiency levels remained.

Evaluating the multi-period operating efficiency of logistics firms in East Asia

ABSTRACT This paper assesses multi-period operational efficiencies of logistics firms in East Asia using DEA (Data Envelopment Analysis) and MPI (Malmquist Productivity Index). The study examines changes in efficiency and productivity from 2014 to 2023, focusing on firms in South Korea, China, Japan, Taiwan, and Hong Kong. Results show that Hong Kong and Chinese firms have a higher level of scale efficiency, while South Korean and Taiwanese firms report problems with technical and scale efficiency. Notably, the analysis highlights the critical role of technological change, particularly after the COVID-19 pandemic, as a major driver of productivity improvements. These findings offer key insights for policymakers and industry leaders seeking strategies to enhance the competitiveness of logistics firms in a volatile global environment.

Investigating the evolution of construction safety in Chinese provincial-level administrative regions: a thirteen-year analysis

The analysis of construction safety is essential for identifying weaknesses in management practices and offering strategic insights to enhance overall safety performance. The evolution of construction safety across Chinese provincial-level administrative regions from 2009 to 2021 was examined using the Malmquist productivity index (MPI) and the data envelopment analysis (DEA) window model, with a focus on input-output efficiency and variable returns to scale. Over the past thirteen years, the traditional DEA model has consistently identified five provinces as benchmarks, with the eastern region particularly excelling in construction safety. In the investigation of temporal evolution using DEA-MPI, most regions exhibited higher scores in technical change compared to efficiency change, indicating that improvements in construction safety across Chinese provincial-level administrative regions have primarily been driven by frontier technical innovations. Notably, the central region demonstrated significant improvements in construction safety development between 2009 and 2021. The DEA-window model not only delivered similar performance rankings for provincial-level administrative regions that aligned with those of the traditional DEA model but also provided more precise performance scores, indirectly corroborating the temporal analysis results from the DEA-MPI evaluation. This study employs input-output methodology for identifying provincial construction safety benchmarks and examining provincial construction safety evolution, providing construction policymakers with data-driven and actionable insights to develop targeted macro-level safety improvement strategies.

비모수적 접근법에 의한 저비용 항공사의 생산성 평가와 개선 방안

The potential market size of the air transportation industry is growing, and the merger of Korean Air and Asiana Airlines is leading to a reorganization of low cost carriers. Accordingly, this study aims to analyze the productivity of domestic low cost carriers (LCCs) and find ways to improve productivity. For this purpose, this study used aviation statistical data from the Aviation Information Portal System from 2019 to 2024. The productivity of Jeju Air (JJA), Jin Air (JNA), Air Busan (ABL), T'way Air (TWB), and Air Seoul (ASV) was analyzed using the Malmquist Productivity Index (MPI), a non-parametric approach. The analysis results are as follows. First, in the case of domestic flights, when comparing MPI by period, overall MPI decreased by 1.09% on average. When decomposing MPI, TCI (0.9873) had a greater impact than TECI (1.0019). When looking at the MPI by low cost carrier, Air Busan (ABL), Air Seoul (ASV), Jeju Air (JJA), T'way Air (TWB), and Jin Air (JNA) had high productivity index in that order. Second, in the case of international flights, when looking at the MPI by period, the overall MPI increased by 3.71%. It was found that TCI (1.0313) had a greater impact on MPI than TECI (1.0056). When comparing the MPI by low cost carrier, Jin Air (JNA), Air Busan (ABL), Air Seoul (ASV), T'way Air (TWB), and Jeju Air (JJA) had high productivity index in that order. This study has implications in that it examines the productivity of low cost carriers in a situation where previous studies are insufficient despite the importance of productivity management in service companies.

Empirical research of foreign direct investments efficiency in the European Union on the edge of pandemic outbreak.

The study focuses on the effects of the COVID-19 pandemic on the economy and foreign direct investments in the European Union countries. Using data envelopment analysis constant and variable returns to scale models, and the Malmquist productivity index, we measured the efficiency of economic resource utilization concerning foreign direct investments and gross domestic product. These efficiencies were assessed in 2019, before the full outbreak of COVID-19, and in 2020, when uncertainty and the consequences of the pandemic were most pronounced. Despite the challenges posed by the pandemic, the European Union displayed economic resilience in the first year, with no significant reduction in foreign direct investment efficiency. Lower-income European Union countries saw an increase in foreign direct investment efficiency, attributing this to positive changes in managerial efficiency. This suggests that decisions made by authorities positively impacted foreign direct investment flows in economically less developed European Union regions despite restrictive measures and market uncertainties.

Evaluating hospital performance with additive DEA and MPI: the Isfahan University of Medical Science case study

BackgroundHospitals are a vital pillar of the health system, and measuring their performance by an appropriate quantitative model is crucial. This study evaluated the performance of hospitals affiliated with Isfahan University of Medical Sciences. It deals with the nature of dynamics (the performance of evaluation indicators over time), examining controllable, uncontrollable, and undesirable input and output indicators.MethodsThis study evaluated the performance of 26 Isfahan University of Medical Science hospitals in terms of efficiency and productivity with hybrid Data Envelopment Analysis (DEA) models, namely, the additive classic, Malmquist productivity index (MPI), and super-efficiency models, from 2019 through 2022. Thirteen indicators (four inputs and nine outputs) were selected as model variables by brainstorming in the expert panel.ResultsThe average technical efficiency of hospitals during the four periods was 0.86, indicating an average inefficiency of 14%. Malmquist productivity index results over four periods showed hospitals operating with an average of 11% positive growth, reflecting an overall increase in productivity. Notably, some hospitals with high technical efficiency displayed lower total productivity growth rates due to fluctuations in specific indicators. On average, in the four under study years, 12 hospitals were efficient, of which 75% (9 hospitals) had performance progress (average MPI > 1). On the contrary, among the 14 inefficient hospitals during the four studied years, more than 90% of the hospitals had improved performance.ConclusionThis study introduces a multidimensional and dynamic model for evaluating hospital performance. While classic DEA models provide a statistical performance evaluation, the Malmquist Productivity Index reveals dynamic performance changes over time. These findings underscore the need for hospitals to adopt advanced quantitative models to optimize resource allocation and enhance service delivery.

Revisiting fiscal performance of non-special category states of India: a global Malmquist index approach

Purpose This paper aims to analyse the fiscal performance of non-special category states of India. Design/methodology/approach This study applied a global Malmquist productivity index (GMPI) to measure the state fiscal performance, using eight fiscal indicators to measure the fiscal stance of 17 non-special category states of India over the period 2000–2020. Findings The findings reveal significant inter-state variations in all the fiscal indicators over the period. Goa, Haryana, Kerala, Chhattisgarh, Odisha and Jharkhand have been the best fiscal performers in recent years. The states Chhattisgarh, Jharkhand and Odisha present an interesting case; their fiscal performance index (productivity) score increased more than 1% during the sample period as compared to other states. This improvement is primarily associated with revenue efficiency, expenditure quality and size of capital outlay. Research limitations/implications The conventional Malmquist productivity index uses a geometric mean form of two contemporaneous measures of productivity change and this index faces a potential linear programming infeasibility problem in measuring cross-period directional distance functions. Therefore, productivity growth measured using indexes should be interpreted with caution. Therefore, the results obtained based on the GMPI might be missing the sensitive check. Originality/value This study is a pioneering initiative in India, constructing a fiscal performance index to measure and rank the non-special category states of the country based on GMPI, thus addressing limitations in previous studies on index formation techniques and selecting fiscal indicators.

A DEA-based Malmquist Productivity Index for Analysing University Performance and Competitiveness

Objective: To conduct a comparative analysis of university performance and competitiveness for leading Polish and Ukrainian universities using the constant returns to scale (CRS) results-oriented model and DEA-based Malmquist productivity index. Research Design & Methods: Using the CRS results-oriented model and DEA-based Malmquist productivity index, an assessment of the efficiency of Polish and Ukrainian higher education institutions in 2019–2021 has been carried out. Sources of data include reports from university rectors, international educational rankings and data from the SciVal Scopus database. The use of input and output indicators, which characterise the didactic and research activities of universities and affect their efficiency, has been justified. Input indicators are the number of university teachers, total university costs calculated per employee, total university costs calculated per student, and output indicators including the number of graduates, the annual number of employee publications in Scopus indexed journals, and the number of citations of employee publications according to SciVal Scopus. Findings: First, the productivity of some Polish and Ukrainian universities differ, as do the factors of the growth of that productivity. Second, more reputable universities (including benchmarking units) have less potential for productivity growth than less productive regional universities. The relevance of the results obtained was guaranteed by the size of the group of universities analysed. That number was larger than the minimum for maintaining a sufficient number of degrees of freedom. Implications / Recommendations: As a result of analysis with the application of performance-oriented CRS model and Malmquist index, it was found that large reputable universities have less potential for productivity growth (this applies to benchmarking units mainly in Poland). Ukrainian universities are not only more diversified in terms of indicator dynamics, but have greater reserves of productivity growth. Contribution: The article contributes to the scientific literature on university performance and the evaluation of competitiveness. The use of the CRS model and Malmquist index in the analysis of university competitiveness enables better characterisation and evaluation of the input and output indicators, identify benchmarking units and productivity growth reserves.

Evaluating the Efficiency of Turkish Banking Sector Using Data Envelopment Analysis and Malmquist Productivity Index: Covid-19 Pandemic and After

Covid-19 pandemic has created a deep crisis with social, cultural, economic, and political consequences all over the world. In this study, we used the Malmquist Total Factor Productivity Change Index (TFPCH) and Data Envelopment Analysis (DEA) methods to assess the efficiency and performance of banks during the Covid-19 pandemic and in the post-pandemic era. We performed the application for 17 banks in Türkiye of which data structure is suitable for analysis. For the analysis, data from 2019, the beginning of the Covid-19 epidemic, to 2022, when the epidemic almost ended, were used. The highest value of the general efficiency average of banks is 0.943 in 2020. 2020 is also the year with the highest number of effective banks with a total of 9 effective banks. The highest value of the TFPCH general average is 1.543 in the 2021-2022 period. It was determined that the state banks had the highest average efficiency percentage and the highest TFPCH average for the entire period of 2019-2022.

An Efficiency Analysis of Sugarcane Farming in India: An Interstate Comparison of Performance with Data Envelopment Analysis and Malmquist Index

Background: This paper aims to evaluate the agricultural production of sugarcane in major sugarcane-producing states of India. Even though agriculture’s share of India’s GDP is decreasing, it still plays a significant role in the labor force by accounting for a sizable number of jobs. Recognizing the importance of sugarcane farming and the variations in resource availability among the states is crucial. The study highlights the importance of enhancing production management and resource allocation to increase sugarcane production and optimize inputs. Methods: The present research employs sophisticated statistical techniques, including Data Envelopment Analysis (DEA) and the Malmquist Productivity Index (MPI), to investigate the influence of variables such as land area and labor utilization on the efficacy of sugarcane cultivation at the state level spanning from 2017 to 2022. It uses DEA to analyze the connection between various agricultural inputs and the efficiency of food grain production and provides recommendations for improved resource allocation among Indian states. Result: The results of the investigation indicate that the mean efficiency of sugarcane cultivation across India is approximately 84.2%. Notably, states such as Uttar Pradesh, Tamil Nadu and Karnataka have demonstrated the highest levels of efficiency in terms of input utilization in sugarcane farming. Conversely, Bihar and Uttarakhand have emerged as the least efficient states in this regard. Furthermore, an analysis using the Malmquist productivity index indicates that Uttar Pradesh has exhibited the most significant average productivity growth, with Maharashtra and Gujarat following closely behind. Conversely, states such as Andhra Pradesh, Punjab, Haryana and Tamil Nadu have demonstrated only marginal enhancements in productivity. The study’s insights on sustainable sugarcane production and enhanced farmer-level regulatory frameworks have the potential to greatly benefit sugarcane-producing states. By implementing these ideas, we can work towards boosting revenue and reducing poverty in rural areas.

The impact of health policy and organisational models on Italian hospital productivity growth

The impact of health policy and organisational models on Italian hospital productivity growth

Unveiling Productivity Dynamics Among Regional Rural Banks in India

This study employs the non-parametric Malmquist productivity index to evaluate the total factor productivity (TFP) change among the regional rural banks (RRBs) in India from 2016 to 2023. The analysis of productivity change among the RRBs holds intrinsic significance due to its potential impact on overall performance and to the delivery of quality services among the rural population. To evaluate the productivity change under varying combinations of input and output selections, two distinct approaches were used: the intermediation approach and the production approach. The empirical results reveal substantial variation in average TEP estimates across the RRBs under consideration throughout the sample period. Furthermore, the observed productivity changes predominantly emanated from technological change (TC) rather than efficiency improvements. Additionally, we found that the smaller RRBs were performing better than their larger counterparts. These empirical findings bear noteworthy policy implications, offering valuable insights for policymakers and regulators to formulate effective strategies to ensure the competitiveness and sustainability of RRBs in India.

Evaluating the research and development (R&D) efficiency of the Chinese construction industry

PurposeThe construction industry has been investigating “where Henry Ford is in the industry system.” Given that listed construction enterprises are the backbone of the promotion of the high-quality development of the industry, their research and innovation are of considerable importance. This study aims to comprehensively assess the research and development (R&D) status quo and trends within various types of construction enterprises in order to identify effective strategies to enhance R&D efficiency in the construction industry.Design/methodology/approachBased on the data won from annual reports and the CSMAR database for the period 2016–2020, this study examines 104 listed construction enterprises in China. By applying both the data envelopment analysis (DEA) method and the Malmquist productivity index, this research compares and analyzes the static and dynamic differences in R&D efficiency across different types of construction enterprises.FindingsResults suggest that the magnitude of change in the Malmquist decomposition index of 104 listed construction enterprises gradually narrowed, but the comprehensive technological level remained relatively low. Although state-owned enterprises had an advantage in scale efficiency, meaning they could maximize output with given inputs, their technological progress efficiency, also known as the degree of technological innovation, was significantly lower than that of private enterprises. As one finding, state-owned enterprises in comparison with private enterprises experience significant R&D inefficiency. It represents the main cause of their low degree of technological innovation and efficiency.Originality/valueThis study assesses the R&D efficiency of listed construction enterprises in China from the perspective of different market segments, state-owned and private enterprises and suggests approaches to improve strategies for various corporate types. Thus, the study’s new findings contribute to addressing the challenge of low R&D levels in the construction industry in the fields of engineering, construction and architectural management.

Analisis Efisiensi dan Produktivitas Bank Pembiayaan Rakyat Syariah di Jabodetabek Periode 2019-2023

This research aims to analyze the efficiency and productivity of BPRS in Jabodetabek, totaling 17 BPRS during the 2019-2023 observation period. This research uses the BCC or VRS model as a basic model in analyzing bank efficiency and productivity using Data Envelopment Analysis and the Malmquist Productivity Index. This research uses input variables, namely third party funds and operational expenses, as well as output variables, namely operational income and financing. The results obtained from efficiency analysis using DEA show that there are still many BPRS in Jabodetabek that have not achieved maximum efficiency. The average Jabodetabek BPRS efficiency score fluctuates from year to year during the period 2019 to 2023, with an overall average efficiency of 0.716648. Meanwhile, the average productivity of BPRS in Jabodetabek is 1,102. In 2020 there was a decline in the efficiency and productivity of BPRS due to the Covid-19 pandemic. But Back shows recovery in 2021 to 2023.

Monitoring sustainable waste management in OECD countries: A Malmquist productivity approach

Monitoring sustainable waste management in OECD countries: A Malmquist productivity approach

A Metafrontier and Malmquist Productivity Index Approach for Analyzing Biased Technological and Efficiency Change in Taiwanese Traditional Chinese Medicine

This study assesses changes in resource productivity in traditional Chinese medicine (TCM) system across Taiwanese counties and cities from 2016 to 2019, stratifying the analysis by population densities. Employing a data envelopment analysis (DEA) metafrontier Malmquist productivity index model, this research relaxes Hicks’ neutrality assumption of technical change, allowing for the measurement of biased technological change and technical gap ratio changes. The empirical findings reveal a decline in TCM system productivity, primarily attributed to reduced technological advancements. Notably, higher productivity changes were observed in counties and cities with lower population densities, contrasting with those having higher population densities, where productivity changes were limited. The results suggest that areas with lower population densities hold significant potential for technological enhancement, as evidenced by intergroup technology updates and technological leadership indices. Furthermore, the estimates of productivity change and technological bias underscore the inadequacy of assuming Hicks’ neutral technological change for analyzing TCM system productivity in Taiwan. These findings highlight the need for improved TCM system technology and innovation within the healthcare system to address the urban-rural gap effectively.

Revisiting the Productivity Paradox: What is Next for the BRICS and European Banking Systems?

Information technology is a critical driver of productivity growth in modern economies. However, there has been no convincing explanation for the observed discrepancy in the literature, increasing suspicion on whether IT can improve institutional performance in contemporary banking markets. The fallacy of productivity adds credence to Robert Solow’s dictum, “You can see the computer age everywhere except in productivity statistics”. We employ two extensive bank-level datasets of 5,794 institutions across 37 nations to estimate the total factor productivity (TFP) payoffs from IT in BRICS and European markets. A DEA-based, Malmquist productivity index quantifies TFP change and its respective components. Findings provide evidence against the paradox as both regions experience IT-fueled productivity growth. Nevertheless, such associations vary across banking sector development, rationalizing how IT spending can explain productivity differences across nations. For BRICS banks, a significant proportion of TFP growth originates from frontier expansion instead of frontier progression, signaling a widening of technology gap. Contrastingly, IT has diminished the technology gap between European banks. Intra-country comparisons suggest that if IT-driven productivity growth is regarded as a nation’s long-term goal, industry characteristics should govern the distribution of knowledge capital.

Bank Productivity: A Meta-Regression Analysis

Purpose: This study aims at examining studies employing the Malmquist Productivity Index (MPI) in calculating banks’ productivity. It also seeks to determine the factors affecting the total factor productivity change of banks through meta-regression analysis. Methodology: On December, 2023, relevant works were systematically reviewed using Web of Science (WoS), Scopus, and Google Scholar. The literature review employed a comprehensive search involving all files with the keywords such as ‘‘productivity” and “bank’’. The research process adhered to the PRISMA guidelines. Findings: Key features of the 35 studies incorporated in the analysis are presented. The samples of 65.71% of the studies are Asian countries. The bank productivity of 45.71% was calculated through the DEA-MPI method. The studies under consideration were sourced from diverse populations. These studies share key similarities in terms of subject and methodology. Random Effects Model was used to test heterogeneity across studies. The common effect size is 19.361 (z= 4.23, 95% CI: [10.384, 28.338]). Inter-study heterogeneity was determined through Cochran Q test and I^2 index (I^2= % 100, df=32.000, Q=141163533.762, p