Dynamic performance assessment of bus transit with the multi-activity network structure

This paper proposes a multi-activity dynamic network data envelopment analysis model that combines the multi-activity, network and dynamic DEA models to assess the performance in terms of individual activities, individual processes, individual periods and overall operation. The main advantage of this model is that the linkages among activities and processes, the shared inputs among activities and processes, and the carry-over items among periods are included in a unified model. It can provide more appropriate performance measures. An empirical application of 20 bus transit firms in Taiwan for the period 2004–2012 is provided. Based on the operational characteristics of bus transit firms, both desirable and undesirable outputs are also incorporated into this model. The results show that none of the bus transit firms was effective in terms of the operational effectiveness, and the sources of operational ineffectiveness among bus transit firms were different. Over the period 2004–2012, the period-operational effectiveness scores maintained stable variance, the period efficiencies of highway and urban bus services appeared to have similar patterns, and transit bus firms performed well in the consumption process.     

DEA and ranking with the network-based approach: a case of R&D performance

This study enhances the network-based approach, which is a novel method to increase discrimination in data envelopment analysis. The enhancements include removing the bias caused by a scale difference among organizations and highlighting the approach's ability to identify the strengths and weaknesses of each organization. The former makes the approach applicable to both the constant returns of scale (CRS) and the variable returns of scale (VRS) models. The network-based approach applies the centrality concept developed in social network analysis to discriminate efficient decision making organizations as determined by standard data envelopment analysis (DEA). More specifically, the results of data envelopment analysis are transformed into a directed and weighted network in which each node represents a decision making organization and the link between a pair of node represents the referencing relationship between the pair. The centrality value for each efficient organization provides the base for discrimination and ranking. This network-based approach suggests aggregating DEA results of different input/output combinations such that the merits of each organization under various situations can be considered. The final ranking of this approach favors organizations that have their strengths evenly spread and tends to screen out specialized efficient organizations. As a real world example, the approach is applied to evaluate and rank the R&D (research and development) performance of Taiwan's government-supported research institutes. The cross-organizations and within-organization strengths for each efficient research institute are identified after applying the approach. A two-stage R&D evaluation model separates the R&D process into the technology development and technology diffusion stage. The resulting performance map differentiates the research institutes into four categories—Achievers, Marketers, Innovators, and Underdogs.     

Measuring departmental and overall regional performance: applying the multi-activity DEA model to Taiwan׳s cities/counties

This study measures the departmental and overall efficiency in Taiwan׳s counties/cities by applying a multi-activity data envelopment analysis (MADEA) model. The model overcomes the problems of panel data, undesirable outputs, shared inputs, and environmental variables and intertemporal efficiency changes (productivity) by applying the Malmquist–Luenberger (ML) index. We include data on the economic development, social welfare, police and security, and education departments for 20 counties/cities in Taiwan for the period 1999–2013. We find that the police security department is the most efficient in most counties/cities in the period 1999–2013, and the economic development department is the second efficient one in 2002–2005 and after 2009. Furthermore, there exist urban–rural gaps in the efficiency scores between counties and cities, between service-type and non-service-type counties/cities, and among different regions. With regard to the efficiencies over time (ML indices and their decompositions), we find that the production frontiers of the social welfare and education departments in Taiwan׳s counties/cities expanded continuously during this period. Finally, we also find that urban–rural gaps and gaps between service-type and non-service-type counties/cities exist in terms of technological changes and ML productivity indices in the social welfare and education departments. The area differences of technological changes exist in 4 departments and in overall. Our results will help the mayors of counties/cities understand the strengths and weaknesses of the regions they govern.     

Evaluating the efficiency of dual-use technology development programs from the R&D and socio-economic perspectives

This study applies a network data envelopment analysis model called network slacks-based measure (NSBM) to examine the R&D efficiency and socio-economic efficiency of Taiwan's dual-use (military and general public) technology development programs. We also employ the additive super-efficiency model to distinguish programs at different stages and conduct an analysis on the strengths and weaknesses of internal resource utilization. The results of this study show that the R&D efficiency is substantially higher than the socio-economic efficiency. Among the dual-use technology development programs, material and chemical engineering programs demonstrate relatively higher performance. This study provides insights into the policy of resource utilization.     

Measurement of tourist hotels׳ productive efficiency,occupancy, and catering service effectiveness using a modified two-stage DEA model in Taiwan

This study develops a modified two-stage model to evaluate productive efficiency, occupancy, and catering service effectiveness of Taiwan׳s international tourist hotels. The difference between the modified and original two-stage model is that the modified two-stage model allows for multiple efficiencies to be calculated in the unique stage and the concept of intermediate input is introduced.The modified model was tested using 58 Taiwanese international hotels and the results show the modified model offers a more efficient and effective approach in calculating all the efficiencies in a single data envelopment analysis (DEA) implementation as opposed to independent efficiency calculations.     

基于DEA的高等学校内部院系绩效评价

内部院系绩效评价是高等学校加强内部管理的关键。本文利用X大学的数据,采用数据包络分析法对有关院系的办学绩效进行评价,得出了各学院的总体技术效率、纯技术效率和规模效率值,对有关投入产出指标的松弛量进行了分析,从而指明了调整内部院系资源配置和改进绩效的方向,最后对研究模型的敏感性进行了分析,结果表明模型具有较高的效度。     

Efficiency measurement for hierarchical network systems

The conventional data envelopment analysis (DEA) models for measuring the relative efficiency of a set of decision making units (DMUs), without considering the operations of the component processes, often produce misleading results, and network models have thus been recommended. This paper discusses the development of a network DEA model for systems with a hierarchical structure. It is shown that the hierarchical structure is equivalent to a parallel structure, with the components being the units at the bottom of the hierarchy. Due to the characteristics of a parallel system, the efficiency of a hierarchical system is thus a weighted average of those of the units at the bottom of the hierarchy. A hypothetic example shows that the proposed model is able to distinguish the order of the efficient DMUs evaluated by the conventional DEA model. Moreover, it provides the efficiencies of the functions of the DMU, which enables managers to identify areas of weakness, and thus better focus efforts to improve overall performance.     

基于DEA的能源效率评价模型研究

在全要素能源效率框架下,根据能源系统的特点,基于DEA方法建立能源效率评价模型,对中国30个行政区域进行实证研究.针对能源效率的概念缺少统一标准的现状,从综合投入、技术效率和有效产出3个角度界定能源效率概念,为能源效率研究提供清晰的概念框架;构建以能源消费总量、从业人员总数和固定资产折旧为投入指标以及以经济产出和环境影响为产出指标的能源效率评价指标体系,在此基础上构建能源经济效率和能源环境效率评价指标体系;结合主成分分析法建立可处理非期望产出的DEA能源效率评价模型.通过实证研究发现,评价模型在理论研究方面可以有效应用于能源效率的评价.并较好地满足系统分析的要求;在生产实践方面可以为能源效率提供更合理的计量和考核标准,并为中国实现节能减排目标、制定相关政策和措施提供决策支持.     

Efficiency decomposition in network data envelopment analysis with slacks-based measures

Conventional data envelopment analysis (DEA) treats the production system as a black box when measuring efficiency, ignoring its internal structure. By taking the operations of the component processes of the system into consideration, several network DEA models have been developed. Of these, the slacks-based measure (SBM) approach has attracted much attention for its ability to provide suitable efficiency measures, especially for weakly efficient production units. This paper proposes a general SBM model for network systems, and is able to decompose the system efficiency into a weighted average of the process efficiencies. This relationship holds for all types of network structure. An example shows that the network model has stronger discriminating power than the conventional black-box model, and the system efficiency is indeed a weighted average of the process efficiencies. The decomposition of the system efficiency helps identify key factors to improve the performance of a production unit.     

Theory of integer-valued data envelopment analysis under alternative returns to scale axioms

Kuosmanen and Kazemi Matin [Theory of integer valued data envelopment analysis. European Journal of Operational Research 2009;192:658–67] developed an axiomatic foundation for a data envelopment analysis (DEA) model that assumes subsets of input and output variables to be integer valued. In this paper we extend and generalize the axiomatic foundation for the integer DEA under variable, non-decreasing and non-increasing returns to scale. These model variants are achieved by introducing new axioms of natural convexity and natural augmentability. We also develop mixed integer linear programming (MILP) formulations for computing efficiency scores in these environments. An empirical example illustrates the approach.     

A two-phase robot selection procedure

In this paper, a two-phase methodology is proposed for robot selection. In phase 1, data envelopment analysis is used as a means to determine the technically efficient robot alternatives, considering cost and technical performance parameters. Using data envelopment analysis permits us to consider the fact that the performance parameters specified by the vendors are generally unattainable in practice. In the second phase, a fuzzy robot selection algorithm is utilized to rank the technically efficient robots according to both predetermined objective criteria and additional vendor-related subjective criteria. The algorithm is based on calculating fuzzy suitability indices for the technically efficient robot alternatives, and then, ranking the fuzzy indices to select the best robot alternative. A comprehensive example is provided to illustrate the decision procedure. The algorithm proposed in here is also applicable to a broader area of decision problems, e.g. facility site selection, determination of the best CNC machine or flexible manufacturing system among a set of mutually exclusive alternatives.     

Hierarchical network systems: An application to high-technology industry in China

In real world situations, there is a hierarchical structure exists in a specific organization and each component has its network process. However, such hierarchical network system has not been well studied in previous literature, and misleading results often are produced. The current paper discusses a data envelopment analysis (DEA) modelling technique for a network structure where a hierarchical system consists of components having two-stage series processes. An additive network DEA is proposed to evaluate the performance of this type of network structure. The overall and divisional efficiencies of the system and each component can be derived, and the relationship between system efficiency, divisional efficiency and the ones of components is discussed. The newly developed additive network DEA is nonlinear and cannot be converted into a linear program. A semidefinite programming (SDP) approach is developed for effectively solving this model and the global solution can be guaranteed. Another linear multiplicative network DEA also developed for this hierarchical system. The two newly developed models are illustrated with a case of the performance evaluation of high-technology industry in China.     

How to better identify the true managerial performance: State of the art using DEA

Our motivation is to detail a potential improvement on the three-stage analysis published by Fried et al. [Accounting for environmental effects and statistical noise in data envelopment analysis. Journal of Productivity Analysis 2002;17:157–74] that can distinguish true performers from those that may be advantaged by favourable environments or measurement errors. The method starts with data envelopment analysis (DEA), and continues with stochastic frontier analysis to explain the variation in organisational performance in terms of the operating environment, statistical noise and managerial efficiency. It concludes with DEA again using adjusted data to reveal a measure of performance based on management efficiency only. Our proposed contributions include (i) a comprehensive approach where total input and output slacks are identified simultaneously for non-radial inefficiencies before levelling the playing field, (ii) identifying percent adjustments attributable to the environment and statistical noise, and (iii) using a fully units-invariant DEA model.     

An illustration of dynamic network DEA in commercial banking including robustness tests

The main motivation of this article is to illustrate dynamic network data envelopment analysis (DN-DEA) in commercial banking with emphasis on testing robustness. To this end, sixteen foreign banks in China are benchmarked against thirty-two domestic banks for the post-2007 period that follows major reforms. When network and dynamic dimensions are brought together, a more comprehensive analysis of the period 2008–2010 is enabled where divisional and between-period interactions are reflected in efficiency estimates. Weighted, variable returns-to-scale, non-oriented dynamic network slacks-based measure is used within the framework of the intermediation approach to bank behavior. A bank network (i.e., a decision-making unit, DMU) is conceptualized as comprised of two divisions or sub-DMUs, namely, interest-bearing operations and non-interest operations linked by number of referrals. Undesirable outputs from sub-DMUs 1 and 2 (non-performing loans, and proportion of fruitless referrals, respectively) are treated as carry-overs that impact the efficiency of the following periods. Under robustness testing, the illustrative application discusses discrimination by efficiency estimates, dimensionality of the performance model, stability of estimates through re-sampling (leave-one-out method), and sensitivity of results to divisional weights and returns-to-scale assumptions. The results based on Chinese commercial banks are illustrative in nature because of simulated data used on two of the variables.     

How car dealers adjust prices to reach the product efficiency frontier in the Spanish automobile market

This paper investigates the relationship between the dynamics of price discounts at the dealership level and product efficiency in the Spanish auto market. Using data envelopment analysis (DEA), product efficiency scores are estimated for 2092 different vehicles commercialized during 2010, using an innovative database that accounts for more than 75 technical attributes of each model. By alternating official and discounted prices on the DEA specification, we are able to propose a measure of competitive improvement in the retailing stage. We also introduce a decomposition of this measure into two indices that account for the “commercial effort” made by the dealer and the “intensification of competition” that results from the discounting efforts of the other dealers. Finally, we explore the importance of a number of drivers of dealer discounts. As expected, the results confirm the existence of an inverse relationship between product efficiency and dealer discount. Also as expected, discounts are significantly larger for generalist brands, aged models and gasoline engines.     

Changes in productivity of Spanish university libraries

This paper analyzes productivity growth, technical progress, and efficiency change in a sample of 34 Spanish university libraries between 2003 and 2007. Data envelopment analysis and a Malmquist index are combined with a bootstrap method to provide statistical inference estimators of individual productivity, technical progress, pure efficiency, and scale efficiency scores. To calculate productivity, a three-stage service model has been developed, examining productivity changes in the relationships between the libraries' basic inputs, intermediate outputs, and final outputs. The results indicate a growth in the productivity of the libraries (relationship between basic inputs and intermediate outputs) and in the productivity of the service (relationship between basic inputs and final outputs). The growth in productivity in both relationships is due to technical progress. If the variable representing the use of electronic information resources is removed from the final output, the result is a significant reduction in productivity.     

Statistical precision of DEA and Malmquist indices: A bootstrap application to Norwegian grain producers

Previous applications of data envelopment analysis (DEA) and its subsequent Malmquist indices to efficiency and productivity measurements have been criticised for not providing statistical inferences regarding the significance of observed results. In this paper, DEA and a Malmquist index are combined with a bootstrap method in order to provide succinct statistical inferences that determine the performance of grain producers in Eastern Norway. The data cover the period between 1987 and 1997. Results reveal: (i) a significant degree of inefficiency (approximately 11%) and an average productivity progress of 38% over the period considered; (ii) the formidable productivity progress observed is primarily explained by technical efficiency changes that enabled producers to catch up with front runners; and (iii) environmental factors, such as weather conditions, impact both efficiency and productivity. Finally, the analysis reveals that using bootstrapping to make statistical inferences suggests that researchers should be careful in making performance comparisons based on conventional DEA methods, as any discovered differences may not be significant.     

带权重约束的DEA超效率评价模型及其应用研究

针对产学研协同创新项目的相对效率比较问题,数据包络分析（DEA）法是比较有效的数量分析方法。但DEA法所构建的优化模型中,由于约束条件没有充分考虑评价指标体系内部指标之间客观存在的内在权重大小信息,从而导致模型过分强调了评价单元的投入产出特征差异,甚至出现了原本非常重要的指标其权重却为0的不合理现象。本文提出DEMATEL法和数据包络分析法有机结合的思想,将运用DEMATEL法获得的指标之间内在的权重大小信息,纳入DEA法非阿基米德无穷小量ε限制的CCR模型及其超效率模型的约束条件,创新模型的可行域,构建了权重约束型ε-CCR模型和超效率ε-CCR模型。并以美国2014-2015年度国家科学基金会产学研合作研究中心发布的年度报告数据,对美国71个以高校为主导的产学研协同创新中心的相对效率进行了实证分析。实证结果显示,权重约束型超效率ε-CCR模型比没有权重约束的超效率ε-CCR模型更有效,不仅能对多个评价单位进行全排序,而且能克服无权重约束的超效率ε-CCR模型存在的评价结果不合理现象。这些结果有助于进一步推动DEA法的理论创新和应用推广,并能为多投入多产出项目的决策提供新的方法,使实际问题决策更合理更科学。     

Time-staged outputs in DEA

This paper examines the issue of handling outputs in DEA that occur at different stages in time. As a backdrop for the research we examine a data set involving the evaluation of efficiencies of business schools. The data focuses explicitly on a particular institution, namely the business school ENCSH (Escuela de Negocios, Ciencias Sociales y Humanidades) at ITESM (Instituto Tecnologico y de Estudios Superiores Monterrey) in Mexico. This school of business is evaluated relative to 41 peer institutions in the USA, using data envelopment analysis as the principal evaluation instrument. Using internships and jobs as outputs, and various quality measures as inputs, we demonstrate that this problem setting gives rise to the phenomenon of time-staged outputs. Specifically, the two outputs occur at different points in time, meaning that one of them plays a dual role. While this problem might potentially be viewed as a type of network DEA model, we demonstrate that a modification of the conventional DEA methodology is a more appropriate structure to handle this situation.     

Applying data envelopment analysis on accounting data to assess and optimize the efficiency of Greek local governments

The efficiency and effectiveness of local governments has become one of the main points of interest in public sector administration, as decision and policy making gradually move from the central to the local level. This paper introduces an efficiency analysis framework based on accrual accounting data obtained from the local governments’ financial statements. Data envelopment analysis is used to obtain efficiency estimates, which are analyzed through a second stage regression against a set of efficiency explanatory factors. Furthermore, the optimal reallocation of the municipalities’ inputs and outputs is explored to provide policy recommendations that a central government could implement in a budget reduction context. Detailed empirical results are presented from a panel data set of Greek municipalities over the period 2002–2009.