Technical Efficiency Change Research Articles

Global value chains, trade liberalization, and productivity: a stochastic frontier analysis of Chinese manufacturing firms

ABSTRACT This article estimates the total factor productivity (TFP) growth of Chinese manufacturing firms and quantifies how international sourcing and trade liberalization affect TFP growth. To this end, we estimate stochastic frontier production that decomposes TFP growth into technical changes, returns to scale, and technical efficiency changes. Furthermore, we consider two channels through which external factors affect TFP growth: technical change and technical efficiency change components. We measure international sourcing and trade liberalization by foreign value-added shares and input tariffs, respectively. Several novel findings emerge. First, international sourcing and import tariff reduction positively impact TFP growth by improving technical changes and technical efficiency. Second, international sourcing has a negative effect on the technical changes of processing importers, while it has positive effects on the technical change and technical efficiency change of ordinary importers. Third, input tariff reduction has a substantial and positive impact on the technical efficiency change of processing importers and the technical change of ordinary importers.

Estimating the effects of weather and climate change on agricultural productivity

AbstractExplaining changes in productivity involves explaining changes in output and input quantities. Several economic models can be used for this purpose. This paper considers a model that accounts for weather and output price uncertainty. Changes in productivity are then explained in two steps. First, a stochastic production frontier model is used to decompose a proper productivity index into measures of technical progress, environmental change, technical efficiency change, scale-and-mix efficiency change, and changes in statistical noise. Second, a system of input demand equations is used to further decompose the measure of scale-and-mix efficiency change into a measure of technical progress, a measure of input price change, various measures of changes in expectations, and a measure of changes in allocative efficiency and statistical noise. The methodology is applied to U.S. agricultural data. The effects of weather and climate change on agricultural productivity are found to be small relative to the effects of changes in input prices.

ICT 산업 연구개발투자의 효율성 및 생산성 분석

This paper measured R&D investments efficiency and total factor productivity(TFP) of ICT industries reflecting the time lag of R&D investments and R&D stock as a input, and decomposed the sources of total factor productivity change into technical change and technical efficiency change by the non-parametric Malmquist productivity index. The results of this study are as follows. First, efficiency scores of ICT industries are 39%, and Manufacture of semiconductor components and bare printed circuit boards and loading of electronic components onto PCB showed highest efficiencies. Second, total factor productivity decreased 6.6% annually. But manufacture of semiconductor components and bare printed circuit boards and loading of electronic components onto PCB, and system and package software publishing showed productivity increase, and technical progress contributed to TFP increase. Third, technical efficiency did much for TFP decrease of ICT industries. Technical progress, however, reduced the extent of TFP decrease.

How do renewable energy consumption, financial development, and technical efficiency change cause ecological sustainability in European Union countries?

Achieving ecological sustainability is a critical issue of the current era, and researchers are striving to find viable solutions for sustainable development and ecological wellbeing. This study is an effort to examine the ecological consequences of renewable energy (REC), financial development (FD), and technical efficiency (TE) in 27 countries of the European Union (EU), time ranges from 1980 to 2018. We used second-generation econometric techniques to consider the cross-sectional dependency in the model and the CS-ARDL method to estimate the long-run dynamics of the variables. The Westerlund cointegration technique confirmed the long-run association among REC, FD, TE, and ecological footprint (EF). Furthermore, CS-ARDL results revealed a positive influence of FD on EF, indicating FD is a significant contributor to the ecological footprint of the EU. However, REC and TE promote ecological sustainability in the EU, as both factors negatively affect the EF. Furthermore, the interaction of FD and TE is also estimated to mitigate EF in sample countries. The study recommends that government policies in EU countries must be skewed towards promoting renewable energy usage, lending in green and energy-efficient technology, and technological advancement in the production process.

Comparing efficiency in all-inclusive and bed and breakfast hotel businesses: a multi-period data envelopment analysis in Turkey

PurposeThis paper aims to understand the most efficient hotel system and why efficiency varies across years and between the two differing types of hotel businesses in Turkey.Design/methodology/approachA data envelopment analysis (DEA) analysis was used to characterise the efficiency of all-inclusive (AI) and bed and breakfast (B&B) hotel businesses with one output (total revenue) and three inputs (labour, food and capital costs). The Malmquist approach is then used to discern changes in total efficiency (TTE) and intertemporal shifts in the efficiency frontier (technological change (Tch)).FindingsThe results reveal that the AI hotel operates at 100% efficiency in the summer and year-round. The B&B hotel business operates at 89.6% with variable constant returns to scale during the summer and with 100% efficiency. The results of the Malmquist approach indicate that the total factor productivity grew in the years 2015, 2016, 2018 and 2019, while the other years were marked by inefficiency. Such increases were due to technical efficiency change (TEch) and Tch, which means that managerial and allocative efficiency (AE) were barely achieved. Slight differences were noted in the two time periods (all year and summer), suggesting that the scale of hotel businesses is prepared to operate all year round, and this calls for strategies to mitigate seasonality.Research limitations/implicationsAs to avenues for future research, the limitations of this study are threefold. First, the hotel businesses are not parallel in terms of the duration of their service offerings. Future research may consider including an AI hotel business that is in operation for the whole year. Second, businesses in Turkey are sceptical about sharing their data as it is considered confidential. However, to better generalise the results and encourage hoteliers to consider the positive outcomes of such analysis, the number of observations could be increased by considering more hotel businesses in both categories. Third, a mixture of data representing businesses operating in various countries may reflect if the efficiency scores vary internationally.Practical implicationsOverall, AI hotel businesses are more attractive but less efficient than B&B. Furthermore, the external crisis impacts the efficiency of hotel businesses meaning that hotel managers could keep on exploring AI, perhaps educating their hosts not to waste or not offer huge quantities. Hotel managers may also need to enlarge their seasonal activities to ensure more efficiency.Social implicationsDespite the intentions of AI hotel businesses to increase their profitability with a lower level of service quality, this study shows that the AI hotel business is very attractive but not so efficient due to the higher propensity of guests to consume food and beverages in excess that compromises the definition of efficiency as zero waste. AI is very attractive for family groups or those seeking the pleasure of relaxation at seaside resorts and is also very popular in Turkey. On the other hand, the B&B hotel business is more efficient but less attractive.Originality/valueThe contributions of this paper are threefold. First, the authors analysed the efficiency and inefficiency of hotel businesses within nine years of operations. During this period, Turkey experienced first a tourism boom (2011–2014) followed by stagnation and subsequently a sharp decline due to political instability resulting in an (in)direct impact on tourism (2015–2019). Second, the authors compared the efficiency and inefficiency of AI and B&B hotel businesses. Third, the authors examined the effects of hotel management factors to ensure efficiency.

Efficiency of Investment in Agricultural R & D in Relation to Food Production Index: A Malmquist Index Analysis for the West-African Countries

Investment in R & D in the agricultural sector is one of the means to propel the growth of the sector, but failure to ensure the efficient use of resources allocated to agricultural R & D would lead to wastage and underproduction. Based on this, the paper seeks to look at the efficiency of investment in agricultural R& D in relation to the food production index in the West Africa sub-region. To achieve this objective, the number of full-time researchers and spending in terms of percentage of the share of agriculture to GDP were treated as inputs and the food production index as an output (agriculture output). The study used panel data from 2009 to 2014. The Malmquist index approach was adopted to measure the efficiency of food production in selected West African countries. The mean Malmquist index of 0.991, 1.032, 0.976, 0.995, 1.051, 0.908, 0.966, and 0.961 for Ghana, Benin, Burkina-Faso, Ivory Coast, Niger, Nigeria, Senegal, and Togo, respectively, were recorded. Benin and Niger experienced growth in food production within the period. The remaining countries, however, did not experience growth in food production as their respective means were less than 1 (Mi <1), which was an indication of inefficiencies in the application of investments committed to agricultural R & D. To help identify the role played by various components, technical efficiency change and technological progress change for the respective countries were also calculated. The results of the study show the need to go beyond mere allocation of resources to the agricultural sector and push towards efficient use of resources. The allocation of resources without measures to ensure their proper use would not yield the desired outcome. Various countries exhibited some levels of inefficiency across the dimensions assessed. This, therefore, calls for close attention to the use of agricultural resources. There is a need to ensure efficient use of resources committed to agricultural research and development across respective countries. Measures should be put in place to reduce wastage and redundancy in the allocation of resources for agricultural research and development, to improve efficiency and productivity in the agricultural sector.

INVESTMENTS LIMITING NEGATIVE IMPACT OF FARMS ON THE NATURAL ENVIRONMENT AND CLIMATE AND AGRICULTURAL ACTIVITY EFFICIENCY

The article attempts to evaluate the technical efficiency of farms that in 2015-2016 carried out an investment aimed at reducing pollution of the natural environment with nitrates from agricultural sources. Due to the type of the investment carried out, two groups of farms were distinguished. The first group were farms that carried out adaptive investments for the construction or extension of manure plates or slurry tanks. The second group, on the other hand, were farms investing in the construction of barns and piggeries along with buildings for collecting natural fertilizers. The source of data for the analysis were farms keeping accounting for the Polish FADN in 2014-2019. The results of the analysis showed that the investments carried out in both groups undoubtedly contributed to the significant development of the farms. Income per 1 working person from a farming family (1 FWU) increased in both groups by 95.3% and 78.5%, respectively in 2014-2019. Changes in technical efficiency, measured with the Malmquist index, showed an improvement in efficiency in both groups, but only in the group of farms investing in new buildings the changes were favorable both in terms of efficiency improvement and technological progress. Ultimately, measurement of efficiency showed its increase in the group investing in buildings by 0.7% and in the case of new livestock buildings by 3.4%.

Estimating South African Higher Education Productivity and Its Determinants Using Färe-Primont Index: Are Historically Disadvantaged Universities Catching Up?

Recent high dropout and low graduation rates in the South African higher education institutions as well as government funding cuts and the economic uncertainty due to COVID-19 pandemic have heightened the urgency for the higher education sector to improve its productivity. However, empirical evidence on the productivity growth of the sector remains unexplored. To address this gap, we applied a Färe-Primont index approach to a panel data of 22 public universities over an 8-year period to measure total factor productivity (TFP) and its components—technological change, technical, scale and mix efficiency changes. We also used a feasible generalised least squares model to assess the determinants of productivity and efficiency growth. The results show that the average TFP of the sector for the study period was 0.631, led by historically advantaged universities (0.894), whilst historically disadvantaged universities had lower average TFP (0.823). During the period, TFP increased by 3.43%, largely driven by scale and mix efficiency changes (5.32%) and technical efficiency change (0.83%), whilst technical change declined by 1.80%. In terms of university types, the comprehensive universities achieved the largest TFP growth (6.13%) followed by traditional universities (4.85%), and technology universities by 1.41%. TFP growth was positively influenced by student graduation rates, quality of academics and academic-student ratios. Therefore, policy considerations to improve the sector’s productivity and efficiency should consider investment on research and development, adoption of teaching and research innovations, re-skilling through training and education and aligning admission policies with staffing.

Analysis on Total Factor Productivity and Differences of Industrial Internet Concept Companies

Based on the Malmquist-DEA model and the DEA-BCC model, using the data of 53 industrial Internet-listed companies, the total factor productivity (TFP), technological progress (TC), and technical efficiency changes of the industrial Internet industry were measured from static and dynamic perspectives (EC), and used the coefficient of variation to further analyze the variance variables that measure the differences between enterprises in various subsectors in the industrial Internet industry. The study pointed out that the overall productivity level of the industrial Internet industry in 2015 to 2019 was low, and the fluctuation range was large, especially the sharp drop in productivity in 2016 to 2017, which had a serious impact on the entire industry. At the same time, changes in technical efficiency are the main reason for the decline in total factor productivity after 2015. Among various industries, the Malmquist indices of manufacturing and information transmission, software, and information technology services are all less than 1, and there is little difference in production efficiency and changes between the two. This study provides a reference for the productivity measurement of the industrial Internet industry based on the Malmquist-DEA model and provides practical inspiration for future management activities.

Research on Agricultural Total Factor Productivity and its Influencing Factors in the Central Plains

In the current era of promoting rural revitalization, it is very important to improve the efficiency of agricultural production and then improve the level of agricultural modernization, which will help achieve poverty alleviation and build a beautiful countryside. Focusing on the theme of the improvement of agricultural total factor productivity in the Central Plains region, this paper uses the agricultural production efficiency theory and the nonparametric index method of DEAP-Malmquist to construct a measurement model of agricultural production efficiency in the Central Plains region. Data, the agricultural total factor production efficiency (TFP) and its decomposition values, such as: pure technical efficiency index and scale efficiency change index, carry out horizontal and vertical comparative analysis, to explore the differences in agricultural productivity in various regions and their sources of growth. Then use the panel data regression model to analyze many influencing factors of agricultural TFP, such as: economic development level, labor quality and so on. Finally, according to the empirical results, some policy references are put forward to ensure the safety of grain production in the Central Plains and improve the level of agricultural modernization.

Evaluation of Innovation Efficiency on Chinese Commercial Banks under the Internet Finance: A DEA-Malmquist Index-Based Approach

The development of the digital economy and internet finance greatly impacts the technological innovation of Chinese commercial banks. Therefore, most of the Chinese commercial banks have invested a lot of money in the new information technology applications to adapt to the impacts of internet finance. Consequently, whether these investments have achieved the expected effect and efficiency has been concerned by these banks. For these concerns, we have used relative data from 49 Chinese commercial banks from 2010 to 2020 period and used the DEA-BCC model and DEA-Malmquist index to analyze their innovation efficiency from both static and dynamic perspectives. Our study found that from the static perspective, the innovation efficiency greatly varies among the banks in the study, and most banks have room for improvement in pure technical efficiency and scale efficiency. From the dynamic perspective, the innovation efficiency of the banks in the study is generally on the rise. Changes in technical efficiency play a major role in improving their overall efficiency, and technological progress is the second driving force. Therefore, technological investment should be increased, and technological levels should be improved to improve innovation efficiency. Our study also shows that, according to the ownership types, different groups of banks have differently shown their innovation efficiencies. Joint-stock commercial banks have the highest innovation efficiency, while rural commercial banks have the lowest innovation efficiency. Our study suggests that all Chinese commercial banks should overcome their own shortages in information technological innovation capability to elevate their innovation efficiency, under the background of internet finance.

Productivity assessment of power generation in Kenya: What are the impacts?

Kenya is classified among the fastest developing economies in Sub Saharan Africa. To sustain this growth, energy is seen as a key ‘enabler’ to oil its new long-term development blueprint, Vision 2030, which intends to transform the economy into a middle income country status and a newly industrialized economy. Yet, the recent energy generation capacity is faced with high growing demand, unreliability, and high cost. Applying Sequential Malmquist Index (SMI), the study examines dynamics of productivity of Kenya's hydro and thermal power plants over the 2013–2020 period. We then employ a Tobit regression method to analyze the influence of environmental factors on changes in the productivity index. The empirical findings show that regress in hydro productivity is mainly caused by the technical efficiency change index (TECI). Besides, productivity for thermal plants improved due to the technology change index (TCI). The SMI provides an appropriate estimate for the share of TCI than the conventional Malmquist index for both plants. The estimates from the regression technique highlight that the life of plants, size, rainfall variation influence hydro SMI changes, and fuel type, life, size also affect thermal SMI changes. Targeted policy implications are provided for future development and operations of power plants.

How Eco-Efficiency Is the Forestry Ecological Restoration Program? The Case of the Sloping Land Conversion Program in the Loess Plateau, China

The Forestry Ecological Restoration Program (FERP) aims to restore the world’s degraded forest landscapes to restore biodiversity and mitigate climate change. Scientific evaluation of eco-efficiency of forestry restoration programs (EEoFERPs) is the basis for developing and implementing inclusive and sustainable development policy measures. We take the world’s largest FERP—China’s Sloping Land Conversion Program (SLCP)—as an example. Using 314 county-level panel data in the Loess Plateau, the core area for the implementation of the SLCP, during 2002–2015, this study aims to evaluate the eco-efficiency of the Sloping Land Conversion Program (EEoSLCP) based on a DEA model and to measure the eco-efficiency dynamic changes through a Malmquist index model. The results show that: (1) The overall EEoSLCP of the Loess Plateau is at a low level, with an average efficiency of only 0.357 from 2002 to 2015. EEoSLCP is on an overall upward trend, mainly influenced by technical efficiency. (2) There are significant spatial differences in EEoSLCP among counties on the Loess Plateau, with an overall decreasing distribution trend from south to north and from southeast to northwest. (3) The Malmquist index of the EEoSLCP grew at an average annual rate of 17.7%, with technical efficiency changes being the most important factor driving its growth. Our results suggest that in the future, when implementing or designing FERPs, it is necessary not only to select the appropriate restoration plan precisely while respecting the laws of nature, but also to improve the management and technical level of FERPs accordingly.

Has FDI contributed to Regional Productivity, Technical Efficiency, and Technical Change in Korea?: Focused on 16 Metropolitan Cities and Provinces

Purpose This study composed panel time series data from 1998 to 2019 for 16 metropolitan cities and provinces and analyzed how FDI inflow contributes to technical efficiency and technical change which are the components along with regional productivity. Design/Methodology/Approach In this study, Malmquist productivity analysis was performed to calculate regional productivity, and the calculated productivity, decomposed technical efficiency, and technical change variables were estimated by the impulse response function and forecast error variance decomposition of the panel VAR model. Findings The inflow of FDI contributed to changes in productivity and technical efficiency in 16 metropolitan cities and provinces. However, as confirmed by the results of the impulse response function, the impact of FDI inflow was greater than productivity and technical efficiency than the technical change. As a result of forecast error variance decomposition for this variability, technical change was limited and there was a change in the inflow of FDI in terms of actual productivity and technical efficiency. Research Implications 16 metropolitan cities and provinces need a policy change to enhance industrial competitiveness through the linkage between regional growth structure and technology revolution.

Decomposition of Total Factor Productivity of Cash Crops in Pakistan: A Malmquist Data Envelop Analysis

This paper examined the total factor productivity of cash crops in Pakistan from 1980 to 2018. It uses Malmquist productivity index by applying data envelop analysis to estimate the changes in the production frontier. The Malmquist productivity index is used to decompose total factor productivity into technical change (TECCH) &amp; technical efficiency change (EFFCH). Technical change (TECHCH) means shifts in the frontier or innovation, while efficiency change means catching up to the frontier. The Empirical results show an increase in the productivity of the cash crop in Pakistan. The objective of the study is the decomposition of the total factor productivity of cash crops in Pakistan. Three cash crops (sugarcane, cotton, and rice) and seven inputs (arable land, irrigated land, use of electricity, use of petroleum product, education, credit facility, and machinery) have been used. The study found a 2.2% increase in total factor productivity of cash crops in Pakistan which was mainly due to technological change, and the efficiency score of cash crops in Pakistan has been decreased relative to previous years, which is 8.40% in the period’s t+1, and compared to 10.44% in the period’s t. The government should invest in research and extension in order to provide better seed varieties, better infrastructure, and ensure credit facilities.

The Measuring the Efficiency and Productivity of Regional Water Utility Company (PDAM) in Indonesia from 2012 to 2016

Sufficiently clean water is accessible in Indonesia, where municipally-owned cooperation (BUMD) handles the management of the PDAM. It allows local governments authority over water management in their administrative districts. This organization is responsible for maintaining the region's water supply while earning income from water business operations. However, this effort is not deemed effective since having many PDAMs results in inadequate water quality, low water distribution, and even financial losses. However, the assumption lacks factual evidence as they are not assessed alongside the government audit. To analyze the inefficiencies of water supply services and the productivity growth of PDAMs from 2012 to 2016, this research proposes to use a non-parametric technique, namely data envelopment analysis (DEA) and Malmquist Index Calculation, respectively. The research findings reveal significant inefficiencies among PDAM from various regions in Indonesia. It was found that PDAMs outside Java performed better than those in Java; thus, PDAMs need policy intervention. The operations of larger municipal PDAMs should be restructured to increase productivity. There was no TFP growth (TFPCH) in PDAMs, evidenced by the reduction in pure technical (TECH) and scale efficiency change (SECH). In addition, the positive technological adjustment (TECCH) did not significantly improve efficiency. Regarding the increase in the number of PDAMs resulting from technological improvement, productivity was primarily due to technological advancement.

Analysis on the Efficiency of China’s Leading Logistics Companies

중국의 35개 상장물류기업들은 2015∼2020년의 5년간 효율성이 매우 빠르게 증가하였다. 중국 정부의 물류산업 중장기발전계획을 비롯한 다양한 지원정책들이 효과를 나타내고 있음을 시사한다. 하지만 중국 물류기업들의 효율성 증가는 일부 기업들의 매우 빠른 성장에 기인하고 기업별로 편차가 크다. 기업들의 흥망성쇠도 비교적 빈번할 뿐만 아니라 규모에 대한 효율성도 최근까지크게 개선되지 않고 있다. 총요소생산성지수(TFPI)로 산정한 생산성 역시 5년간 매우 빠르게 상승하였는데, 기술변화지수(TCI)와변화 양상이 매우 유사하였다. 반면 기술적효율성변화지수(TEI)는 같은 기간에 거의 변동이 없었다. 결국, 중국 상장물류기업의 총요소생산성은 내부적인 생산요소의 효율적 결합에 의한 효율화보다는 외부환경 요인으로서 기술 변화가 주도한 것으로 판단된다.This paper analyzes the efficiency and productivity of the leading 35 logistics companies in China from 2015 to 2020 based on the DEA Model and Malmquist Index Method. We use assets, capital, and operating cost of the 35 logistics companies as input variables, while operating revenue, net profit, earning per share, and inventory turnover rate as output ones. In this analysis, we find that China’s leading logistics companies have increased operational efficiency measured by DEA methodology very fast, while the increase was led by a few companies. Furthermore the disparity of increasing rate between them was very big, and the companies have often risen and fallen. The increase in total factor productivity index (TFPI) of the companies during the same period has also been very fast and parallel with that of the Technical Change Index (TCI) whereas the technical Efficiency Change Index (TEI) has little changed, which implies that the productivity increase has been driven not by the endeavor of the companies to combine production factors more efficiently but by the technology change external to the companies.

Analysis of regional agricultural carbon emission efficiency and influencing factors: Case study of Hubei Province in China.

In recent years, China’s industrial economy has grown rapidly and steadily. Concurrently, carbon emissions have gradually increased, among which agricultural production is an important source of greenhouse gas emissions. It is necessary to reduce agricultural carbon emissions by improving their efficiency to achieve the global goal of peak carbon dioxide emissions in 2030. From a dynamic and static point of view, this study puts agricultural carbon emissions into the evaluation index system of agricultural carbon emission efficiency and analyzes the agricultural carbon emission efficiency and its influencing factors in Hubei Province. First, the unexpected output Slacks-based measure (SBM) model in data envelopment analysis was used to evaluate the agricultural carbon emission efficiency of Hubei Province in 2018 and compared it with other provinces horizontally. Second, the Malmquist–Luenberger index was used to analyze the comprehensive efficiency of agricultural carbon emissions in Hubei Province from 2004 to 2018. The role of technological progress and technical efficiency change in the development of low-carbon agriculture in Hubei Province was analyzed. The results showed that agricultural production efficiency in Hubei Province improved from 2004 to 2018, and the overall level was slightly higher than the average level in China. However, agriculture has not eliminated the extensive development modes of high input, low efficiency, high emission, and high pollution. The efficiency of technological progress in agricultural resource utilization in Hubei Province was close to the optimal level. The improvement space was small. Hence, the low efficiency of agricultural technology is a key factor restricting the improvement of agricultural production efficiency. The results provide a reference for low-carbon agricultural policy formulation and expand the policy choice path. This has practical significance.

A Cross-Country European Efficiency Measurement of Maritime Transport: A Data Envelopment Analysis Approach

Maritime transport, which includes shipping and port operations, is the fundamental basis of international trade and globalization. In transportation management, efficiency is critical for verifying performance and proposing the best countermeasure to meet predetermined goals. Various efforts in this field have been made to solve this problem satisfactorily. However, the significant proportion of conventional approaches are based on long-term observations and professional expertise, with only a few exceptions based on practice-based historical data. Data Envelopment Analysis (DEA) is a non-parametric technique for analyzing various output and input variables parallelly. The efficiency of maritime transport in European countries is explored using a two-stage DEA approach based on Malmquist and Epsilon-Based Measure (EBM). First, the Malmquist model analyses countries’ total productivity growth rates and their breakdown into technical efficiency (catch-up) and technology change (frontier-shift). Second, the EBM model is used to determine the efficiency and inefficiency of the maritime transportation systems in each European country. Apart from identifying the best-performing countries in specific areas over the study period (2016–2019), the results highlight that the gap in applying the EBM method to maritime transport has been successfully closed and that the emerging paradigm, when combined with the Malmquist model, can be a sustainable and appropriate evaluation model for other research areas.

A Two-Stage DEA Approach to Measure Operational Efficiency in Vietnam’s Port Industry

Logistics services aid import and export businesses located near ports in terms of ease and efficiency in the globalization era. Furthermore, economic growth and global import–export volumes immediately impact the port industry. This research aims to develop a two-stage Data Envelopment Analysis (DEA) model for measuring the performance efficiency of Vietnam’s top 18 seaports. The DEA resampling technique is used to forecast future performance, and the DEA Malmquist model analyzes efficiency improvement. First, the forecast data for the next three years, from 2021 to 2023, were obtained by resampling Lucas weight prediction with the highest accuracy. The results indicate that 12 out of all ports achieved an average progressive production efficiency over the entire study period of 2018–2023. Further, most ports have advanced slightly in technological efficiency, indicating that the determinants of increased productivity are the technical efficiency change indexes. This work contributes to the body of knowledge by being the first to apply the resampling technique in conjunction with the Malmquist model to forecast performance efficiency in the domain of the seaport sector. Furthermore, the managerial implications serve as a beneficial reference for operation managers, policymakers, and researchers when comparing the operational efficacy of seaports to diverse logistical scenarios.