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Over the last decade, many studies have adopted the data envelopment analysis (DEA)-type metafrontier framework to relax the constraint of technological heterogeneity. In conventional metafrontier analyses, either radial or nonradial DEA models are used in two separate DEA efficiency analyses. The results of a metafrontier analysis may be biased if this approach is adopted in a nonradial DEA model. One possible problem is that the value of the technology gap ratio is greater than one because the technology gaps to be estimated for decision-making units (DMUs) under different technology groups relative to the metatechnology have no connection between group frontiers and metafrontiers. Furthermore, the direction of projection of each DMU onto the metafrontier is totally independent of the direction to the efficiency frontier of the respective group frontier. Our proposed integration of group technology and metatechnology constraints into a union model offers a possible solution to the existing metafrontier problem and provides more robust metafrontier results regardless whether radial or nonradial DEA models are used. Four numerical examples and one empirical application are demonstrated, and the results appear to support the use of our proposed model.

The recent capacity expansion, the pressure to fully utilize capacity, and the increasingly intense competition among cruise companies have greatly challenged revenue management in the cruise indus...

Conventional profit and allocative efficiencies suffer from a critical deficiency if input and output prices are different between decision-making units (DMUs) in the market when assuming given uniform input and output prices under a homogeneous technology. Price differences and technology gap considerations are more relevant to firms in reducing profit loss under a non-homogeneous technology with non-perfect market competition. This study proposes a new value-based meta-profit inefficiency decomposition considering the presence of both a new technology gap and price inefficiency. As an illustrative empirical application, we present an example of 35 Taiwanese banks representing two types of banking organizations: financial holding companies (FHCs) and non-FHCs. The new decomposition we propose helps to identify the profit–loss due to group technical, group price, new technology gap and meta-mix inefficiencies of DMUs.

Malaysia was faced with a life-threatening crisis in combating COVID-19 with a number of positive cases reaching 5305 and 88 deaths by 18th April 2020 (the first detected case was on 25th January 2020). The government rapidly initiated a public health response and provided adequate medical care to manage the public health crisis during the implementation of movement restrictions, starting 18th March 2020, throughout the country. The objective of this study was to investigate the relative efficiency level of managing COVID-19 in Malaysia using network data envelopment analysis. Malaysia state-level data were extracted from secondary data sources which include variables such as total number of confirmed cases, death cases and recovered cases. These variables were used as inputs and outputs in a network process that consists of 3 sub processes i) community surveillance, ii) medical care I and iii) medical care II. A state-level analysis was performed according to low, medium and high population density categories. The efficiency level of community surveillance was highest compared to medical care processes, indicating that the overall inefficiency is greatly influenced by the inefficiency of the medical care processes rather than the community surveillance process. Results showed that high-density category performed well in both community surveillance and medical care II processes. Meanwhile, low-density category performed better in medical care I process. There was a good overall performance of the health system in Malaysia reflecting a strong preparedness and response level to this pandemic. Furthermore, resource allocation for rapid response was distributed effectively during this challenging period.

To examine the top cruise lines' operational efficiency in three dimensions, namely, production, marketing, and profitability, this study adopts a network data envelopment analysis approach considering shared and quasi‐fixed input factors. The empirical results reveal the following findings. First, the production process tends to outperform marketing and profitability processes. Second, inefficiency of a cruise line mostly stems from overconsumption of the exogenous inputs in each process and the shared input. Third, the relationships between operational efficiency of cruise lines and some categorical factors are examined. Finally, some managerial implications derived from the empirical results are formulated for cruise lines.

This study aims to evaluate the Nerlovian economic efficiency of Taiwanese commercial banks and its determinants by assuming the presence of an imperfectly competitive market using a two-stage esti...

Typically, the meta-frontier network data envelopment analysis model can be used to evaluate the technological gaps in individual stages simultaneously. However, the technological gap in each stage could also have a biased effect, i.e. one which improves the productivity of a subset of input or output factors. Since decision-making units may face different operational technologies, and have two-stage network structures, this study develops a new approach to investigate the favored direction of technology shift. The novelty of this approach is to identify that the technological gaps could affect the overall production function, both with the input technological bias in the first stage and with the output technological bias in the second stage. By comparing the difference between meta-technology and group technology, the favored direction of technology shift for individual decision-making units can be judged. The proposed approach is illustrated using data from 109 Taiwanese tourist hotels in 2015.

While the assessment of higher education systems is informative to both policy makers and individuals, it is subjective and performed according to experts' judgment. The present study proposes a relatively objective approach, hierarchical data envelopment analysis (H-DEA), to rank higher education systems. Unlike the subjective approach, H-DEA utilizes endogenous weight determination, allowing assessors to identify the relative importance of each attribute and subattribute. Utilizing the U21 Ranking of National Higher Education System 2020 data, our analysis indicates that the output attribute is a crucial factor influencing the overall performance of higher education systems, even considering countries' stage of development and culture. The computed weights of the H-DEA framework show various attributes' different contributions by group. Resources allocated to the higher education system are important for developing countries, while a high degree of internationalization and a strong link between academia and industry matter for advanced countries. Surprisingly, Asian and Western cultures experience similar performance in their higher education systems, reflecting the Asian higher education system's development toward the Western style. The performance of countries with non-Asian-non-Western cultures, as expected, lags behind, and putting more resources into these countries' higher education system is a way to enhance the overall performance.

Tourist hotels may face different production frontiers and bias of technology between the group frontier and meta-frontier due to technological heterogeneity. This paper develops a meta-frontier da...

This study proposes a hierarchical data envelopment analysis (H-DEA) approach to construct a multi-dimensional indicator, and applies it to reassess the 2014 Global Food Security Index created by the Economist Intelligence Unit (EIU) across 110 countries. Instead of using expert opinions to assign weights, the proposed model endogenises the weights, and thus avoids the problems of subjective weighting for international comparisons. The results show that although the ranking is not significantly different from that of the EIU, the optimal scores and weights differ by income levels. Additionally, this work articulates the value of a well-founded performance evaluation method by leveraging experts’ opinions and data-driven techniques through constructing a best-practice frontier with observation-specific weights. It is suggested that food availability should be the top policy priority in low- to medium-income and Sub-Saharan African countries where food deficits are most prevalent. The findings can serve as guidance to improve the design of the ongoing efforts for global food security.

Taking advantage of a dynamic network data envelopment analysis (DNDEA), this study proposes a model decomposing shipping service production for a container shipping company (CSC) into two processes. Meanwhile, multiple evaluation periods are linked by carry-over activity. The fleet capacity of a CSC is separated into owned fleet capacity (OFC) and chartered-in fleet capacity, which are defined as carry-over activity and specific input, respectively. The efficiency of 13 major global CSCs is empirically evaluated based on a dataset covering a period from 2013 to 2015. The scores for company efficiency and division efficiency of each CSC are measured and examined. In addition, the optimal solution for sharing common inputs and adjusting OFC is also found from our model.

To insure a proper and meaningful productivity assessment of DMUs with different production technologies, this article develops a difference-based profit metafrontier Luenberger productivity indicator. Adopting the proposed model, we empirically measure the profit inefficiency and examine the profit productivity convergence for samples banks consisting of 31 Taiwanese banks and 50 Chinese city banks over 2010–2014. Empirical results show that Chinese banks perform better in profit efficiency than Taiwanese banks. While Chinese banks have better technology in profit creation than Taiwanese banks, the latter may reap much higher profit gain than the former if they can adopt the profit metafrontier. The results of the profit metafrontier Luenberger productivity indicator analysis show that both Chinese and Taiwanese banks have experienced declines in profit productivity. However, the results also indicate a divergence in productivity growth for Chinese city banks and a convergent productivity growth for Taiwanese banks. JEL CLASSIFICATION: D20, G21, P34

Ferry transportation plays an essential role in transportation services between a mainland and its offshore islands, as well as among those islands. However, low volume routes frequently operate at a loss because they are socially necessary but not profitable. Thus, a government may provide financial support to such ferry routes. Since budgetary resources for offshore ferry routes are limited, this paper offers a performance-based method constructed through data envelopment analysis to help governments allocate subsidies to individual offshore ferry routes. The proposed method considers the concepts of cross-efficiency and structural efficiency, simultaneously. The allocation results for a current ferry subsidy allocation policy and the proposed method are compared. The results may provide valuable suggestions for allocation policies for subsidies to ferry firm.

Medication management is a complex but critical process within the healthcare delivery system. The pharmacy department in healthcare facilities is responsible for acquisition, distribution and dispensing of medication to patients that involves a series of network process. This process can be categorized into two main subprocesses: i) pharmacy store and ii) patient services (i.e., ambulatory and inpatient pharmacy). The objective of this study was to investigate the relative efficiency level of the two subprocesses of pharmacy services in Malaysia's public hospitals. We used a nonconvex metafrontier technology to estimate technical efficiency of hospital pharmacies between specialist and nonspecialist hospital categories under the dynamic network data envelopment analysis (DNDEA) framework. For overall efficiency, both specialist and nonspecialist categories had similar mean efficiency scores. However, when measuring the efficiency level according to pharmacy store and patient services separately, the nonspecialist category had a higher mean efficiency score in pharmacy store, whereas for patient service efficiency, both categories had similar results. The patient service efficiency level was lower consistently over time, suggesting that the overall inefficiency of hospital pharmacy is greatly influenced by the inefficiency of the patient service. This suggests that systematic improvements in patient service efficiency should be a higher priority than pharmacy store efficiency to further increase the overall efficiency level. We believe that our findings will provide valuable information to policymakers towards achieving an efficient public healthcare service.