Divisional Efficiencies Research Articles

A network data envelopment analysis based paradigm to benchmark fiscal performance – an analysis of fiscal outlay efficiency among Indian states

PurposeThe fiscal outlay efficiency matters when the performance-based allocation of funds is made to state governments by the central government in a federal structure of an economy like India. Also the efficiency cannon of public expenditure is a key aspect in the field of public economics. Thus, a study to evaluate the efficiency in fiscal outlay of Indian states has been conducted.Design/methodology/approachThe paper offers a three divisions–based paradigm under Network Data Envelopment Analysis framework to compare the performance of fiscal entities (say Indian state governments) in converting available fiscal resources into desired short-run and long-run growth and development objectives. The network efficiency score has been taken as a measure of the quality of fiscal outlay management that is trifurcated into divisional efficiencies representing budgeting process, fiscal outlay efficiency process and fiscal outlay effectiveness process.FindingsIt has been noticed that the states are under performing in achieving short-run growth targets and so the efficiency process division has been identified a major source of fiscal under performance. Suboptimum allocation of fiscal expenditure under various heads within the fiscal resources, as explained under budgeting process, is another major cause of fiscal under performance.Practical implicationsThe study purposes a three divisions–based paradigm that takes into account efficiency of a state in (1) planning budget, (2) achieving short-run growth targets and (3) achieving long-run development targets. These three stages are named as budgeting process efficiency, fiscal outlay efficiency and fiscal outlay effectiveness, respectively. Therefore, a new paradigm called BEE paradigm is proposed to evaluate performance of fiscal entities in terms of fiscal outlay efficiency.Originality/valueIn existing literature on measuring efficiency of public expenditure, the public sector outputs have been made as function of fiscal expenditure as input treating the said outlay as an exogenous variable. In present context, the fiscal expenditure has been treated endogenous to the budgeting process. A high inefficiency on account of budgeting process supports this treatment too.

Data envelopment analysis of two‐stage processes: an alternative (non‐conventional) approach

AbstractNetwork data envelopment analysis (NDEA) is an extension of standard DEA that models the efficiency assessment of decision‐making units (DMUs) by considering their internal structure. While in standard DEA, the DMU is regarded as a single process, in NDEA, the DMU is viewed as a network of interconnected sub‐processes (stages, divisions), where the flow of the intermediate products (measures) is essential in the efficiency assessment. In the prevalent conventional methodological approach to NDEA, the sub‐processes are assumed as distinct entities with distinct inputs and outputs. Thus, each sub‐process has its own production possibility set (PPS), which can be derived axiomatically from a set of assumptions using the minimum extrapolation principle. The PPS of the overall system is defined as the composition of the individual PPSs. The conventional approach comprises all the methods, in which the system and the divisional efficiencies are computed jointly in a single mathematical program. A fundamental property connecting the system with the divisional efficiencies is that a system is overall efficient if and only if its divisions are all efficient. In NDEA, regardless of the method used, there are cases where none of the observed DMUs is rendered overall efficient as corroborated by real‐world case studies. This is the main issue we discuss in this paper and the motivation to propose an alternative, non‐conventional, approach to address it in the frame of two‐stage processes. We consider the two‐stage process as a system that can be viewed from two perspectives depending on the role of the intermediate measures: the system as producer and as consumer of the intermediates. As our approach is based on standard DEA, it satisfies the basic desirable properties. The fundamental NDEA property, that the overall system is efficient if and only if both perspectives are efficient, is met. The efficient frontier of the system is explicitly defined by the overall efficient observed DMUs, and the inefficient DMUs are projected on the efficient frontier of the system. A convergent procedure is presented for this purpose. The proposed models are equivalently expressed in both the multiplier and the envelopment forms due to strict primal‐dual correspondence and can operate under both constant and variable returns‐to‐scale assumptions. We use the case of 22 automotive manufacturers for the fiscal year 2019 as an example to illustrate our approach. Comparison with other NDEA methods is also provided.

The impact of regulation on the Brazilian water and sewerage companies’ efficiency

Access to sanitation services in Brazil is still deficient, despite the abundant financial resources allocated to it in the last two decades and the objective of the regulatory framework of 2007 of providing universal access and efficient sanitation systems. This article analyzes the impact of the regulatory environment on the water and sewerage companies' levels of efficiency. First, these efficiencies were computed within a dynamic network data envelopment analysis for a sample of 156 Brazilian water and sewerage companies, from 2006 to 2015, considering investments in water, investments in sewage, and operations divisions separately. In the second stage, this research related water and sewerage companies' efficiencies to innovative measures of the regulatory environment by using a panel data model, with data from 2006 to 2015. The efficiency analysis revealed low levels of overall and divisional efficiencies, highlighting the importance of evaluating efficiency over time, and of considering the providers’ internal structure, to identify inefficiencies that may compromise the achievement of regulatory objectives. The regression results indicate that the impact on the overall and divisional efficiencies depends on the choice of regulatory incentives, the intensity of the application of those incentives, and even the number of regulatory authorities.

Exploring the efficiency of hospital and pharmacy utilizations in Taiwan: An application of dynamic network data envelopment analysis

BackgroundBuilding continuity of care by enabling optimal collaboration between hospitals and community pharmacies is critical. However, existing research on healthcare efficiency has largely focused on hospital services, and few studies have evaluated hospital services alongside pharmaceutical services. ObjectiveTo set up a dynamic network production model to assess the divisional efficiency of hospital and pharmacy utilizations and to investigate the dynamic changes and spatial differences for a more productive utilization of healthcare services. MethodsA dynamic network data envelopment analysis was applied on two interdependent healthcare divisions, hospitals and community pharmacies, in order to assess utilization efficiencies in both divisions simultaneously. Subsequent analyses were performed with a set of decision making units consisting of Taiwan's cities. Data were gathered from the Ministry of Health and Welfare and the Bureau of National Health Insurance, spanning 2014–2019. ResultsThe mean scores for overall healthcare, hospital, and pharmacy among cities were 81.9%, 89.2%, and 76.7% respectively. It appears that pharmacy is not very efficient, possibly because of the low rate of prescription release. A 13.26% reduction in pharmacists in the pharmacy sector is suggested, but the number of community pharmacies remains the same in cities and counties in 2019, based on the results of the slack-based measure. The bootstrapped-truncated regression indicated the different business districts had statistically significant determinants of overall efficiency, including hospital efficiency and pharmacy efficiency. ConclusionsThis study illustrated the inefficient operations of most hospital and pharmacy divisions in Taiwan's southern cities. It is hoped to draw the government's attention to the existing inefficiency in the allocation of healthcare and pharmaceutical resources. For future studies, a dynamic network model can be adapted to introduce the Malmquist productivity index in order to compare divisional productivity changes over time. Other topics for future research include handling undesirable outputs (quality variables) and information on input/output prices.

Tourism efficiency decomposition and assessment of forest parks in China using dynamic network data envelopment analysis

Forest resources are essential not only in the provision of tourism services, but also as the assets of ecological preservation, and so this study divides the overall operation process of forest parks into production and service processes in an unprecedented way. A modified slacks-based dynamic network data envelopment analysis (SBM-DNDEA) model is proposed to measure the overall, production, and service efficiencies of forest parks in China at a provincial level during the period 2009 to 2018. In the model, cumulative afforestation and reforestation area and social tourism employment are defined as carry-over items between production and service processes, respectively, in consecutive periods. In addition, an alternative aggregation procedure given by the model based on a weighted endogenous mechanism is proposed, which is easier to use and interpret in practical applications. The spatial-temporal differences and features are concluded and analyzed at the provincial and regional level. The results show differences in the overall efficiency, the production efficiency, and the service efficiency of forest parks across provinces in China. The study also finds that in terms of spatial differences, there is less variation in production efficiency among the five regions, but significant differences in service efficiency. The Southeast and the Southwest demonstrate the highest service efficiency score at more than 0.68. This is followed by the Northeast and the Northern, with a service efficiency score between 0.3 and 0.4. The Northwest has the lowest service efficiency score, at less than 0.3. Through these analyses, best performers and practices was identified and valuable insights was gained on how each province can improve associated inefficiencies. • A modified SBM-DNDEA model for measuring provincial efficiency of forest parks in China is proposed. • The overall efficiency is a endogenously weighted average of period-specific divisional efficiencies. • The provision of tourism services performance of forest parks varies greatly among provinces. • The spatial characteristics of forest park efficiency have also been categorized.

Circular water economy performance evaluation based on dynamic network data envelopment analysis

In this study, a looplike dynamic network data envelopment analysis (DEA) framework is proposed to assess technical efficiency in Germany's water economy at the federal state level. In the wake of growing political attempts in Europe to strengthen circular, sustainability-oriented practices in a variety of economic realms, our tailored approach enables, arguably for the first time, simultaneous analysis of public water provision, wastewater services and natural water endowment while accounting for water demand in an encompassing feedback-type context. Our model addresses the issues of water sector infrastructure and environmental sustainability. By measuring divisional efficiencies in addition to composite network efficiency over time, we extend previous static ‘black box’ DEA studies to provide comprehensive and in-depth insight into water economy dynamics. Our framework goes beyond the existing models by unifying distinct yet interrelated water economy processes under an encompassing circular technical efficiency evaluation paradigm to underpin holistic, environmentally-prudent water resource management concerning infrastructure, production, consumption, cleaning, recycling and reuse. Our empirical case study reveals high levels of efficiency in Germany on the whole, and we find little variation among regions in terms of composite water economy efficiency. The natural water endowment segment, which correlates more strongly with the overall water economy than any other network component, exhibits considerable efficiency score volatility. Furthermore, we find that the wastewater treatment section harbours many best-practice regions. Our results also show that the most substantial performance-optimising input reduction required pertains to land area consisting of vegetation and water, which suggests both natural resource endowment efficiency underperformance and sustainability overachievement in the sense of an excess capacity to free up resources for other uses. The largest output increase called for concerns consumers, with regard to water sector value added. Regional water sector infrastructure utilisation appears to be generally adequate, although several federal states fail to meet the optimal levels.

Evaluation of the efficiency of the local tax administration in Taiwan: Application of a dynamic network data envelopment analysis

• A modified SBM-DNDEA model for measuring technical efficiency of local tax offices in Taiwan. • The overall efficiency is an endogenously weighted average of period-specific divisional efficiencies. • The results of the dynamic NDEA model differed significantly from the static NDEA model. • The tax offices in remote or rural counties are the ones most in need of efficiency improvements.

Two-stage network DEA with shared resources: Illustrating the drawbacks and measuring the overall efficiency

Overall efficiency in the network data envelopment analysis (DEA) literature can be measured for two-stage decision-making units (DMUs) characterized by technologies dealing with shared resources (or inputs) and hitherto many DEA-based models have been presented in this context. However, each of these models has two of the following five drawbacks: (1) Non-linearity, (2) Obtaining an overall efficiency greater than one, (3) Requiring to assign variable weights for combining the divisional efficiencies, (4) Adopting constant weights for combining the divisional efficiencies, and (5) Inability to find the efficient two-stage DMUs. To deal adequately with these drawbacks, this study contributes to network DEA by proposing an input–output-oriented linear model to measure the overall efficiency of two-stage DMUs with shared resources. Finally, a comparative analysis is made among our proposed model and the other existing models to illustrate the superiority of our model over the other ones, and then an empirical example on twenty manufacturing supply chains is provided to demonstrate the applicability of our proposed model.

A Novel Enhanced Russell Graph Efficiency Measure in Network DEA

Hitherto, the presented models for measuring the efficiency score of multi-stage decision-making units (DMUs) either are nonlinear or require to specify the weights for combining their divisional efficiencies. The nonlinearity leads to high computational complexity for these models, especially when used for problems with enormous dimensions, and also assigning various weights to the divisional efficiencies causes to obtain different efficiency scores for the multi-stage network system. To tackle these problems, this study contributes to network DEA by introducing a novel enhanced Russell graph (ERG) efficiency measure for evaluating the general two-stage series network structures. Then, the proposed model is extended into the general multi-stage series network structures. This study also describes the managerial and economic implications of measuring the efficiency score of the multi-stage DMUs and provides two numerical and empirical examples for illustrating the use of our proposed model.

Does China's new energy vehicle industry innovate efficiently? A three-stage dynamic network slacks-based measure approach

Innovation ability is vital to the new energy vehicle(NEV) industry in China. To bridge the previous studies’ gaps, a dynamic network slacks-based measure(DNSBM) model, coupled with the three-stage innovation framework, is employed to evaluate the industrial innovation efficiency. Overall, dynamic efficiencies and the divisional efficiencies of the R&D, manufacturing, and marketing process are present, drawing on 17 listed companies’ data from 2012 to 2019. Additionally, the Malmquist index measures industrial productivity and its decomposition, including the Frontier-shift and Catch-up effect. The firm-level efficiencies’ analysis ends up following the types of enterprises and divisional performance. The findings reveal that the overall innovation efficiency was low, and marketing and manufacturing efficiency were higher than those of the R&D division. Then, the annual overall and divisional productivities were low, whereas the cumulative productivities were high. In the end, all enterprises’ performance differentiated, and commercial-vehicle firms’ efficiencies were higher than those of the passenger-vehicle firms except for the marketing division. Meanwhile, the state-owned companies’ efficiencies were higher than those of private companies’ except for the marketing process. The theoretical and practical implications are available for the policymakers, managers, and academic researchers from this study.

Location Efficiencies of Host Countries for Strategic Offshoring Decisions Amid Wealth Creation Opportunities and Supply Chain Risks

Purpose - Offshoring has emerged as one of the major trends in international trade and has become one of the strategies for achieving competitiveness in the global market. In spite of this, the expected gains of offshoring can be offset by hidden costs and risks, such as those associated with the COVID-19 andemic, the trade war between the USA and China, and the ongoing trade dispute between Korea and Japan. To obviate such business failure and prevent critical business blunders, offshoring strategies that efficiently consider both risk elements and potential wealth creation are urgently need. The first purpose of this study is to contribute to the development of more advanced offshoring strategies to help host countries select the best locations to manage supply chain risks and create unique value. The second purpose is to specifically analyze the current status of Korea and provide Korean companies with implications to be considered when deciding whether to offshore or re-shore. Design/methodology - A Network DEA model was applied to measure the comparative location efficiency of national competencies for offshoring strategy from perspectives of wealth creation opportunities (profitability and marketability) and supply chain risk management. The location efficiencies are compared among a total 70 countries selected from the Global Competitiveness Index (GCI) and globally attractive locations outlined by Kearney (2017). For the secondary analysis of efficiency, a t-test examining the nature of competitive advantage and the level of sophistication in production processes was implemented in three divisions. We then analyzed differences in offshoring performance in terms of the identified national traits. Moreover, Tobit regression analysis is conducted to investigate the correlation between value-added business activities and each divisional efficiency, seeking to determine how each degree of value-added business activity influences the increase in offshoring productivity. Findings - Regarding overall location efficiency for offshoring performance, only the USA and Italy were identified as being efficient as host countries for offshoring, under circumstances of advanced development, such as productivity and risk management. Korea ranks 13th among 70 countries. The determinants of national competitiveness depend on national traits (the nature of competitive advantage and business sophistication). Countries with labor/resource advantages and labor-intensive industries are more competitive in terms of marketability than others. In contrast, countries with strong technology-intensive industries benefit offshoring companies, particularly in the technology sector, with the added advantage of supply chain risk management. As the perception of a value chain is broader in a country, it can achieve both production sophistication and competitive advantages such as marketability and SCRM. Originality/value - Existing studies focus on offshoring effectiveness from a company perspective. This paper contributes to comparing country efficiency in producing core competencies related to an offshoring strategy and also segments countries into three performance-based considerations associated with the global offshoring market. It also details Korea s position as an offshoring location according to national efficiency and competency.

Evaluating radial efficiency considering environmental factors: A generalization of classical DEA

Environmental issues are becoming a significant and serious worldwide problem. Undesirable outputs like waste and pollution are by-products of desirable outputs in a production system. To motivate environment-friendly production, undesirable outputs should be included in the performance assessment of firms, organizations and countries. Data Envelopment Analysis (DEA) is one of the most successful methods of efficiency evaluation. Unfortunately, there is no reliable radial efficiency measure for environmental assessment in DEA. In this paper, the conventional modeling in DEA is extended to develop a new radial model for efficiency assessment in the presence of undesirable outputs. This method enables more accurate modeling of the problem. It opens a new door to the issue, and shows more reliabilities than the existing methods. The new efficiency measure is more rigorous, and provides higher discriminating power. Evaluating divisional efficiency is another advantage of the model. It also provides credible targets with greater practical accessibility for each inefficient decision making unit. The model is studied by an axiomatic approach and employed to evaluate the performance of 28 countries in economic, social and environmental dimensions. The results show that only one country achieves efficiency, and the average environmental efficiency is considerably lower than the operational efficiency among the studied countries.

Efficiency Measurement of Cloud Service Providers Using Network Data Envelopment Analysis

An increasing number of organizations and businesses around the world use cloud computing services to improve their performance in the competitive marketplace. However, one of the biggest challenges in using cloud computing services is performance measurement and the selection of the best cloud service providers (CSPs) based on quality of service (QoS) requirements <xref ref-type="bibr" rid="ref13" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[13]</xref> . To address this shortcoming in this article we propose a network data envelopment analysis (DEA) method in measuring the efficiency of CSPs. When network dimensions are taken into consideration, a more comprehensive analysis is enabled where divisional efficiency is reflected in overall efficiency estimates. This helps managers and decision makers in organizations to make accurate decisions in selecting cloud services. In the current study, the non-oriented network slacks-based measure (SBM) model and conventional SBM model with the assumptions of constant returns to scale (CRS) and variable returns to scale (VRS) are applied to measure the performance of 18 CSPs. The obtained results show the superiority of the network DEA model and they also demonstrate that the proposed model can evaluate and rank CSPs much better than compared to traditional DEA models.

Efficiency of the teaching-industry linkage in the Australian vocational education and training

The vocational education and training (VET) sector plays a crucial role in Australia’s education system. Associated closely between the VET provision and industry, VET training quality is continually at the heart of debates in the process of implementing the Australian VET reform agenda. In response of key themes of this reform process, investigating the training efficiency of VET through the linked efficiency between teaching and industry responsiveness is imperative. The paper aims to address this objective by using the dynamic network data envelopment analysis in a balanced panel data for 2008–2012. This advanced model allows to assess simultaneously the efficiency of two nodes, teaching and industry responsiveness, and the overall dynamic training efficiency of VET based on fields of education in a network structure. We found that the overall training efficiency of VET is, on average, 0.835 while the mean divisional efficiencies of the teaching efficiency and industry responsiveness are 0.763 and 0.908, respectively. Sensitivity analysis is conducted to examine dynamic changes of the efficiency of the teaching and industry linkage following various period weights. Policy implications are drawn for the Australian VET sector.

Production scale-based two-stage network data envelopment analysis

We develop a new network data envelopment analysis (DEA) approach for two-stage network systems considering a match between the production scale of the substages and the intermediate measure levels. Several explicit production axioms are introduced to build a production possibility set. New models are developed based on the production possibility set and a frontier projection procedure with the production scale matching process. Unlike the existing approach which assumes the intermediate measures are free-setting decision variables, the new envelopment network DEA models project the intermediate measures of a unit using the radial projection technique. Correspondingly, the resulting multiplier network DEA models allow for weight flexibility on the intermediate measures while holding a total value flow equivalence between a unit's two stages. We show that our approach does not suffer the known network DEA pitfalls. It identifies the overall efficiency, divisional efficiencies, and frontier projection using either an envelopment or a multiplier network DEA model, i.e., the primal-dual correspondence holds in our approach. Our approach also avoids uncertainties in determining divisional efficiencies by generating a unique pair of divisional efficiencies for each unit. Additionally, the adoption of the production scale matching process explains clearly the frontier projection procedure from the practical point of view. The proposed approach is illustrated with a numerical example and compared with the existing approaches with a case study of commercial bank branches.

Recommending investment opportunities given congestion by adaptive network data envelopment analysis model: Assessing sustainability of supply chains

Nowadays, forward-thinking companies move beyond conventional structures of organizations and consider all parties of the supply chain. The objective of this paper is to present an adaptive network data envelopment analysis (DEA) model to evaluate overall and divisional efficiency of sustainable supply chains in the presence of desirable and undesirable outputs. Our adaptive network DEA model can assess overall and divisional efficiency of supply chains given managerial and natural disposability. Also, it suggests new investment opportunity given congestion type. A case study is presented.

Airline energy efficiency measures based on an epsilon-based Range-Adjusted Measure model

This study proposes an Epsilon-Based Range-Adjusted Measure which enhances accuracy of the conventional RAM model that is widely used in the literature of airline energy efficiency. The model is then utilized to investigate the efficiency of major airlines from different regions of the world. Results reveal that Scandinavian Airlines was the most efficient airline and could be served as the benchmark for all these airlines. On the other hand, divisional efficiencies reveal that this airline can still improve its service efficiency so that overall efficiency is enhanced even further.

Efficiency comparison of airline groups in Annex 1 and non-Annex 1 countries: A dynamic network DEA approach

This study compares the performance of the world's largest airline groups from Annex 1 and non-Annex 1 countries during the period 2010 to 2016. A recently proposed slacks-based network DEA model is further extended to a dynamic framework in order to measure airline groups' overall efficiency directly at the system, which is superior to the weighted sum of divisional efficiencies that is commonly used in the literature. A new definition of capital is also introduced taking into account the income-generating capacity of employed aircraft. The findings show that, although the aviation industry's emissions were not subject to the Kyoto Protocol, airline groups with hubs based in Annex 1 countries have performed better in terms of managing their overall production processes as well as operations and services efficiencies. Hence, one may argue that the Kyoto Protocol has wielded a positive influence on airline groups' decision-making process in general, and their operations and services in particular. On the other hand, sales efficiency results are not completely in line with this hypothesis as they show several Annex 1 airline groups are found to be highly inefficient among their rivals.

Serial network DEA models with a single intermediate measure

In conventional two-stage network data envelopment analysis (DEA) models involving one single intermediate output, the divisional efficiencies of non-cooperative models and centralized models are equivalent to the standard constant return to scale (CRS) efficiencies of each stage. The current study demonstrates that the above result also holds true for general network structures, including those of more than two stages, with only one intermediate measure linking network components.

Efficiency measurement for general network systems: a slacks-based measure model

Traditional radial DEA models treat DMUs as black boxes, whose internal structures are ignored, and measure input and output changes proportionally. On the other hand, network DEA models consider the internal structure of a DMU as a network system where sub-processes are connected by intermediate products aside from consuming main inputs and producing final outputs. The interest in network DEA has increased over the years producing different types of formulations including the network slacks-based measure DEA (NSBM). NSBM is a non-radial network approach suitable for measuring efficiencies when inputs and outputs may change non-proportionally. However, NSBM models and some of its recent developments failed to adhere to three important efficiency measurement issues: (a) able to properly define overall and divisional efficiencies, (b) able to identify Pareto-Koopmans efficiency status, and (c) able to show equivalence of primal (multiplier) and dual (envelopment) forms of the network DEA model. This study addressed these issues based on the NSBM approach and compared the results of the proposed network SBM model with other existing models in the literature. A numerical study on 10 electric power companies further illustrated the use and significance of the proposed network SBM model in efficiency measurement.