Approaches to Efficiency Assessing of Regional Knowledge-Intensive Services Sector Development Using Data Envelopment Analysis

The sector of knowledge-intensive services is one of the fastest-growing sectors in the present-day economy of knowledge, which explains the scientific interest in developing methods of its quantitative assessment. The object of the research is the development of new approaches to the mathematical modeling of the efficiency of the regional knowledge-intensive services sector, based on a distance function approach to assess productivity changes. An approach was proposed to analyze the efficiency of this sector using data envelopment analysis and Malmquist productivity index and its components. The article presents the results of the assessment of indicators characterizing the development of knowledge-intensive services in education, innovation, and ICT obtained from 80 Russian regions for the period 2010–2020. To perform the analysis, the following input variables were used: volume of investments in fixed assets in ICT; share of personnel employed in the ICT; share of internal expenditures on R&D in GRP; the number of personnel engaged in R&D; share of innovative-active organizations and registered patents; funding for higher education institutions; and the number of higher education institutions graduated. Output variables were number of used advanced production technologies in the region; share of innovative goods, works, and services in GRP, and use of the intellectual property. As a result of applying the data envelopment analysis, Malmquist productivity index and its components, data were obtained on the positive dynamics of the development of the knowledge-intensive services sector in Russian regions and conclusions were drawn about the sector’s growth sources due to economies of scale.

A Study on the Efficiency Analysis of Global Terminal Operators Based on the Operation Characteristics

Shipping and port industries are undergoing rapid environmental changes because of the reorganization of carrier alliances, enlargement of ships, and an increase in global uncertainty. Thus, the sustainable operation of container terminals requires a new assessment of port efficiency and measures to enhance efficient operation. Hence, we classified 21 global terminal operators (GTOs) into stevedore, carrier, and hybrid GTOs based on their operation characteristics and derived a sustainable container terminal operation method using data envelopment analysis efficiency and Malmquist productivity index analysis. The results showed that stevedore GTOs exhibited improved efficiency when the terminal infrastructure was expanded. However, the returns to scale and technical change factors in the productivity change trend decreased. Meanwhile, the objective of carrier GTOs is cost reduction, unlike stevedore and hybrid GTOs, which focus on generating profits. Consequently, carrier GTOs were the most inefficient with little intention to improve efficiency. A systematic efficiency improvement strategy through the acquisition of a terminal share was effective for hybrid GTOs. However, similar to stevedore GTOs, investment in technical change was insufficient for hybrid GTOs. The efficiency analysis we conducted for each operation characteristic is expected to provide useful basic data for establishing efficiency improvement strategies for every GTO.

An evaluation of the productivity change in public transport sector using DEA-based model

This study aims to build a framework for measuring the productivity in the public transport sector through a data envelopment analysis (DEA) technique. This paper extends the Malmquist productivity index (MP1) and Luenberger productivity indicator (I.P1) evaluation with the concept of an input-oriented new slack model (NSM). NSM model measures the efficiency with the effect of slacks and satisfies unit invariance, radial and translation invariance properties. In particular, the purpose of the proposed extension is to obtain the overall productivity change in terms of technical change (Frontier Shift) and technical efficiency change (Catch-up Effect) for Rajasthan State Road Transport Corporation (RSRTC) bus depots from 2008 to 2019. For this purpose, the number of buses, number of employers, fuel consumption and route distance arc are considered input variables, while passenger-kilometres occupied and vehicle utilisation are output variables. Finally, the result demonstrates that the average total factor productivity (TFP) growth of 46 depots using MPI and LPI over the study period is 1.956% and 1.409%, respectively. This study enables policy-maker and managers to evaluate the input to reach consistent output up to an optimum level and understand the process of improving the productivity level for the bus depots.

Total Factor Productivity Growth of Ghanaian Electricity Distribution Utilities Using Data Envelopment Analysis and Malmquist Index (2000–2020)

The increasing need for electricity access to drive economic growth, social development, poverty alleviation and environmental sustainability requires that efficient allocation of scarce and competing resources in the generation, transmission and distribution subsectors of the electricity sector is indispensable. This paper analyses total factor productivity growth in a single input multiple-output framework in Ghana. The technique applied is data-orientated nonparametric Data Envelopment Analysis using Win4Deap 2 software. Total Factor Productivity Change is evaluated through Malmquist Productivity Index (MPI), as well as technological change (TECHC) and efficiency change (EFFCH) using firm-level panel data. Sources of productivity growth comparison are made between Electricity Company of Ghana (ECG) and the Northern Electricity Distribution Company (NEDCO) for the periods 2000 to 2020. The results show TECHCH marginally declined at an average annual rate of 0.3% and drives the electric power distribution productivity regress in ECG and NEDCO from 2000 to 2020. Further, the results indicate stagnation in scale efficiency, pure efficiency and efficiency change when estimated over 20 years. At firm levels comparison, the study shows that the Northern Electricity Distribution Company recorded a productivity growth rate of 4.9%, mainly due to technical progress. However, the Electricity Company of Ghana experienced a slight deterioration of productivity performance due to a 5.3% decline in technical efficiency. The study offers several policy recommendations on how the underperforming firm can learn to improve efficiency and technical to reduce electricity transmission losses.

Inefficiency of public hospitals: a multistage data envelopment analysis in an Italian region

Background The objective of this study was to assess public hospital efficiency, including quality outputs, inefficiency determinants, and changes to efficiency over time, in an Italian region. To achieve this aim, the study used secondary data from the Veneto region for the years 2018 and 2019. Methods A nonparametric approach—that is, multistage data envelopment analysis (DEA)—was applied to a sample of 43 hospitals. We identified three categories of input: capital investments (Beds), labor (FTE), operating expenses. We selected five efficiency outputs (outpatient visits, inpatients, outpatient visit revenue, inpatient revenue, bed occupancy rate) and two quality outputs (mortality rate and inappropriate admission rate). Efficiency scores were estimated and decomposed into two components. Slack analysis was then conducted. Further, DEA efficiency scores were regressed on internal and external variables using a Tobit model. Finally, the Malmquist Productivity Index was applied. Results On average, the hospitals in the Veneto region operated at more than 95% efficiency. Technical and scale inefficiencies often occurred jointly, with 77% of inefficient hospitals needing a downsizing strategy to gain efficiency. The inputs identified as needing significant reductions were full-time employee (FTE) administrative staff and technicians. The size of the hospital in relation to the size of the population served and the length of patient stay were important factors for the efficiency score. The major cause of decreased efficiency over time was technical change (0.908) rather than efficiency change (0.974). Conclusions The study reveals improvements that should be made from both the policy and managerial perspectives. Hospital size is an important feature of inefficiency. On average, the results show that it is advisable for hospitals to reorganize nonmedical staff to enhance efficiency. Further, increasing technology investment could enable higher efficiency levels.

Operational Performance Evaluation of Korean Ship Parts Manufacturing Industry Using Dynamic Network SBM Model

The purpose of this study is to analyze the efficiency and productivity of the Korean ship parts manufacturing industry. To this end, the manufacturing process was divided into two stages (operating activities, financial activities), and the Dynamic Network SBM model and Malmquist Productivity Index were used. We collected analysis data from KIS-VALUE, and analyzed 40 companies from 2014 to 2020. As a result of the analysis, from 2014 to 2017, the average operating efficiency was 0.7825, the average financial efficiency was 0.5208, and the average total efficiency was 0.4537. It was found that improving efficiency requires improving both activities simultaneously, rather than focusing on a specific activity. Operating activities DMI was 1.0025, financial activities DMI was 0.9236, and OMI was 0.9464. In order to improve OMI, it is necessary to improve the financial activities DMI, which is the cause of the decrease in productivity. In order to improve financial activities DMI, government policy or technology change to improve DFS was found to be necessary. Finally, the effect of environmental factors on efficiency was analyzed by tobit regression. It was found that Firm Size had a negative (−) effect on efficiency, and Firm Age had a positive (+) effect on efficiency. The analysis results of this study will help to understand the relationship between input and output, which has been treated as a black box in the manufacturing industry, in two stages; and this will serve as a guideline for those working in Korea’s ship parts manufacturing industry to establish policies.

Effective Decision Making: Data Envelopment Analysis for Efficiency Evaluation in the Cloud Computing Marketplaces

Assessing business performance is a critical issue for practicing managers, and business performance has always been of interest to managers and researchers. In recent years, the world has experienced a rapid growth in the cloud computing service sector thanks to its benefits to business organizations and economic development. Therefore, the performance efficiency of this sector has been concerned as one of the keys in today’s economic environment. This study aimed to assess the performance efficiency of cloud computing service providers in the United States of America, one of the biggest global markets in terms of cloud computing, by applying the data envelopment analysis models. The efficiency of cloud computing providers was evaluated based on the assumption of the non-cooperative game among cloud computing providers in which providers selfishly choose the best strategy to maximize their payoff with three stages. In the first stage, the performance of these providers over the past period was measured by a super slack-based measure. In the second stage, the performance in the future period was predicted by the new data envelopment analysis model: the past–present–future model based on resampling. In the last stage, the efficiency improvement was investigated by adopting the Malmquist productivity index. The findings of this study indicated that the percentage of inefficient providers would increase from 10% in the period from 2017 to 2020 to 20% for 2021 and 2024. Moreover, 30% of providers showed a regress in performance efficiency over the research period of 2017 to 2024. The results of this study provide an insight picture to the decision-makers, and this research will fill the gap in the literature as the first study that measures and predicts the performance efficiency of cloud computing service providers, which will provide a helpful reference for future studies.

Business Efficiency Evaluation of Machine Tool Manufacturers by Data Envelopment Analysis (DEA): A Case Study of Taiwanese Listed Machine Tool Companies

Data envelopment analysis (DEA) is widely used to measure the business efficiency of many industries, among which the Taiwanese machine tool industry is well-known for its complete supply-chain system. Relying on DEA and Malmquist Productivity Index to analyze the business efficiency of Taiwanese listed machine tool manufacturers from 2018 to 2019, this study compared the changes in their business efficiencies and productivities. According to the five change indicators of Malmquist, only the technical efficiency, pure technical efficiency, and scale efficiency of the overall industry posted some growth during the research period, showing that the whole industry is actively improving its technical efficiency and striving to achieve the scale efficiency. However, technical change and total factor productivity declined slightly, indicating that the industry still makes more technical progress. Thus, companies should adjust their inputs and outputs to improve the production boundary for technical progress. The purposes of this study are to identify the success factors of the excellent performance of manufacturers and the benchmarking indicators of the decision-making unit on the efficient frontier results to provide some references for formulating future business strategies and direction.

Business Efficiency Evaluation of Machine Tool Manufacturers by Data Envelopment Analysis (DEA): A Case Study of Taiwanese Listed Machine Tool Companies

Data envelopment analysis (DEA) is widely used to measure the business efficiency of many industries, among which the Taiwanese machine tool industry is well-known for its complete supply-chain system. Relying on DEA and Malmquist Productivity Index to analyze the business efficiency of Taiwanese listed machine tool manufacturers from 2018 to 2019, this study compared the changes in their business efficiencies and productivities. According to the five change indicators of Malmquist, only the technical efficiency, pure technical efficiency, and scale efficiency of the overall industry posted some growth during the research period, showing that the whole industry is actively improving its technical efficiency and striving to achieve the scale efficiency. However, technical change and total factor productivity declined slightly, indicating that the industry still makes more technical progress. Thus, companies should adjust their inputs and outputs to improve the production boundary for technical progress. The purposes of this study are to identify the success factors of the excellent performance of manufacturers and the benchmarking indicators of the decision-making unit on the efficient frontier results to provide some references for formulating future business strategies and direction.

Does globalisation have an impact on dual banking system productivity in selected Southeast Asian banking industry?

PurposeGlobalisation has influenced many countries, over the last few decades with financial globalisation and liberalisation bringing regulatory reforms in the banking sector. Thus, this study aims to fill a gap in the literature by examining the influence of globalisation on Islamic and conventional bank productivity in Southeast Asia.Design/methodology/approachThe sample comprised 155 banks (23 Islamic and 132 conventional) from 4 countries from 2008 to 2017. Panel data techniques will be used, together with data envelopment analysis (DEA)-based Malmquist productivity index (MPI), to investigate the impact of chosen main determinants on bank productivity. A panel regression analysis will be performed after generating the productivity index from the DEA-based MPI frontier.FindingsAccording to the findings, Islamic banks are statistically significantly more productive than conventional banks, and the findings of the t-test are corroborated by the findings of nonparametric tests. Furthermore, the findings of the panel regression model reveal that bank specific factors and macroeconomic variables are significant determinants to bank productivity. Surprisingly, the findings also show that the influence of social globalisation elements tends to be negatively related to conventional bank productivity.Originality/valueThis study adds to the existing literature by bridging the globalisation gap in the productivity of the dual banking industry, particularly in the specific context of Southeast Asia, given that the area is representative of Islamic and finance globally.