A survey of DEA applications

The literature of data envelopment analysis (DEA) encompasses many surveys, yet all either emphasize methodologies or do not make a distinction between methodological and application papers. This study is the first literature survey that focuses on DEA applications, covering DEA papers published in journals indexed by the Web of Science database from 1978 through August 2010. The results show that on the whole around two-thirds (63.6%) of DEA papers embed empirical data, while the remaining one-third are purely-methodological. Purely-methodological articles dominated the first 20 years of DEA development, but the accumulated number of application-embedded papers caught up to purely-methodological papers in 1999. Among the multifaceted applications, the top-five industries addressed are: banking, health care, agriculture and farm, transportation, and education. The applications that have the highest growth momentum recently are energy and environment as well as finance. In addition to the basic statistics, we uncover the development trajectory in each application area through the main path analysis. An observation from these works suggests that the two-step contextual analysis and network DEA are the recent trends across applications and that the two-step contextual analysis is the prevailing approach.     

Data envelopment analysis 1978–2010: A citation-based literature survey

This study surveys the data envelopment analysis (DEA) literature by applying a citation-based approach. The main goals are to find a set of papers playing the central role in DEA development and to discover the latest active DEA subareas. A directional network is constructed based on citation relationships among academic papers. After assigning an importance index to each link in the citation network, main DEA development paths emerge. We examine various types of main paths, including local main path, global main path, and multiple main paths. The analysis result suggests, as expected, that Charnes et al. (1978) [Charnes A, Cooper WW, Rhodes E. Measuring the efficiency of decision making units. European Journal of Operational Research 1978; 2(6): 429–444] is the most influential DEA paper. The five most active DEA subareas in recent years are identified; among them the “two-stage contextual factor evaluation framework” is relatively more active. Aside from the main path analysis, we summarize basic statistics on DEA journals and researchers. A growth curve analysis hints that the DEA literature’s size will eventually grow to at least double the size of the existing literature.     

DEA for non-homogenous parallel networks

In practice, systems are often composed of a group of sub-units. Each sub-unit has a set of performance metrics that are classified as inputs and outputs in data envelopment analysis (DEA). Conventional DEA views such a system as a “black-box”, other DEA-based models are developed to investigate the inner structure, either with a serial structure where components are connected by intermediate products, or with a parallel system under the key assumption that all sub-units are associated with the same type of inputs and outputs (in differing amounts) without the links. In many applications, however, this property of identical input/output factors may not hold. For example, factories may have various manufacturing lines whose inputs and outputs differ from one another. The current paper proposes a series of DEA models to accommodate settings where non-homogenous sub-units operate in parallel network structures with intermediate measures or links. Both the overall performance of the entire parallel network system and efficiency decomposition for each sub-unit can be evaluated through our method.     

Opening the black box of efficiency analysis: An illustration with UAE banks

Standard data envelopment analysis (DEA) does not provide adequate detail to identify the specific sources of inefficiency embedded in interacting divisions of an organization. On the other hand, network DEA gives access to this underlying diagnostic information that would otherwise remain undiscovered. As a first study of its kind, the paper illustrates an application of non-oriented network slacks-based measure using simulated profit center data that, in turn, rely on actual aggregate data on domestic commercial banks in the United Arab Emirates (UAE). The study also contributes to a perennial research problem, namely, inability of the outside researcher to access internal data for developing or testing new methods. In addition to these contributions to the Operations Research literature, focusing on UAE contributes to banking literature because this rapidly expanding part of the Middle East seldom appears in frontier efficiency literature.     

Path to “Stardom” in Globally Distributed Hybrid Teams: An Examination of a Knowledge‐Centered Perspective using Social Network Analysis

Although distributed teams have been researched extensively in information systems and decision science disciplines, a review of the literature suggests that the dominant focus has been on understanding the factors affecting performance at the team level. There has however been an increasing recognition that specific individuals within such teams are often critical to the team's performance. Consequently, existing knowledge about such teams may be enhanced by examining the factors that affect the performance of individual team members. This study attempts to address this need by identifying individuals who emerge as “stars” in globally distributed teams involved in knowledge work such as information systems development (ISD). Specifically, the study takes a knowledge‐centered view in explaining which factors lead to “stardom” in such teams. Further, it adopts a social network approach consistent with the core principles of structural/relational analysis in developing and empirically validating the research model. Data from U.S.–Scandinavia self‐managed “hybrid” teams engaged in systems development were used to deductively test the proposed model. The overall study has several implications for group decision making: (i) the study focuses on stars within distributed teams, who play an important role in shaping group decision making, and emerge as a result of a negotiated/consensual decision making within egalitarian teams; (ii) an examination of emergent stars from the team members’ point of view reflects the collective acceptance and support dimension decision‐making contexts identified in prior literature; (iii) finally, the study suggests that the social network analysis technique using relational data can be a tool for a democratic decision‐making technique within groups.     

母子公司战略一致性的路径及实现机制 ——基于相互依赖关系视角

由复杂依赖关系构成的国有企业集团需要确定各子公司在战略目标上达成共识的程度,如何协调依赖关系以促成战略一致成为集团企业亟须解决的问题。本文通过多案例研究方法,基于相互依赖关系视角,构建了母子公司依赖关系与战略一致性的研究框架。通过定性比较分析(QCA),本文解读产生战略承诺的两类构型特征,一类是具有高开放性和低能动性的锁定式建构,另一类是具有低关系形态、高能动性和集权管控的能动式依赖。本文又立足关系规则,构建能够引发主动精神的策略,触发式探索策略可以减弱开放的锁定性和能动的短视性,嵌入式即兴策略可以增加子体的即兴创作和母体的适度规则,以促进子公司主导行为的生成。本文结合能动性与管控模式拓展了相互依赖关系视角的战略研究,对于国有企业集团内部协调运行提供借鉴与启示。     

A use of a nonparametric statistic for DEA frontier shift: the Kruskal and Wallis rank test

A new use of the nonparametric statistic, referred to as the “Kruskal and Wallis rank test”, is proposed in this study. The nonparametric statistic examines whether or not any frontier shift occurs among observed periods. To document its practicality, the proposed statistic is incorporated into the framework of Window Malmquist Analysis (WMA) that is structured by combining Data Envelopment Analysis (DEA) window analysis with the Malmquist index approach. As an important case study, this research applies the new technique to examine the performance of Japanese postal services from 1983 to 1997. Two policy implications are derived from the empirical study.     

Brokerage and governance for business networks: a metasynthesis-based discussion

This article reviews and discusses empirical literature on the micro-mechanisms of Burt’s concept of brokerage for inter-firm business networks from a governance perspective. Using a combination of a literature review and a qualitative metasynthesis, research gaps are first identified in the literature about these micro-mechanisms and then filled with interpretations, stemming from a qualitative metasynthesis of 13 in-depth case studies on brokerage for business network environments. The paper discusses three related elements and their inter-relationship in the brokerage process: the enabling factors for brokerage in business networks; the brokerage activities, particularly the combination of “bonding”, “bridging”, exclusion, and moderation/negotiation in different network configurations; and the outcomes of brokerage for business networks. We argue that network managers should take care of these elements when using brokerage to govern business networks. For example, the positional factors of agents in the network who take over brokerage functions need to be monitored and a balance of their embeddedness in the network and independence of focal firms should be safeguarded. Moreover, activities associated with brokerage should be steered and controlled in order to generate network benefits such as a higher collaborative stance of the partaking firms or learning processes amongst them.     

LASSO variable selection in data envelopment analysis with small datasets

The curse of dimensionality problem arises when a limited number of observations are used to estimate a high-dimensional frontier, in particular, by data envelopment analysis (DEA). The study conducts a data generating process (DGP) to argue the typical “rule of thumb” used in DEA, e.g. the required number of observations should be at least larger than twice of the number of inputs and outputs, is ambiguous and will produce large deviations in estimating the technical efficiency. To address this issue, we propose a Least Absolute Shrinkage and Selection Operator (LASSO) variable selection technique, which is usually used in data science for extracting significant factors, and combine it in a sign-constrained convex nonparametric least squares (SCNLS), which can be regarded as DEA estimator. Simulation results demonstrate that the proposed LASSO-SCNLS method and its variants provide useful guidelines for the DEA with small datasets.     

基于“蚂蚁金服”事件网评文本的互联网金融监管蕴意挖掘

以“蚂蚁金服”事件网络评论为样本,借鉴生命周期理论划分评论发展阶段,运用词云图与语义网络进行文本特征可视化和关联分析,并基于LDA模型和语义情感分析考察各阶段评论主题演进趋势和特征,从而挖掘事件的互联网金融监管蕴意。研究表明:相关评论主题在不同阶段各有侧重,但总体呈现逐步细化、深入的特征;“平台垄断”“数据保护”主题最为突出;监管参与者范围扩大成为主要关注点;爆发和平息阶段的评论感情倾向变化较大。为此,互联网金融监管应注重平台防垄断、用户数据保护及多主体协同监管,重点关注爆发与平息阶段的互联网金融舆情引导。     

基于管理类国际权威期刊的中国管理科学与工程学科研究现状分析

基于管理科学与工程学科2010~2019年发表在46份国际权威期刊上的13391篇论文数据,利用文献计量学分析方法,从文献发表记录和基金资助文献两个维度对管理科学与工程学科19个领域的研究现状进行分析。研究结果表明:近10年来,管理科学与工程学科的研究热点主要集中在“博弈论”“创新”“定价”“项目管理”“动态规划”和“供应链管理”等方向。美国、中国、英国、加拿大、德国的发文量排名前5位。在发文量最多的5个国家中,中国国家自然科学基金委员会资助的论文数量排名第一位,且信息系统与管理、管理系统工程是获得资助最多的领域。此外,在国家自然科学基金资助项目中,“供应链”是最热门的主题,“交通管理”和“优化”等主题受到较大关注。在中国大陆机构中,香港城市大学、香港科技大学、香港理工大学、香港中文大学和清华大学的发文量位居前5位。     

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.     

A network DEA quantity and quality-orientated production model: An application to Australian university research services

The motivation for this analysis is the recently developed Excellence in Research for Australia (ERA) program developed to assess the quality of research in Australia. The objective is to develop an appropriate empirical model that better represents the underlying production of higher education research. In general, past studies on university research performance have used standard DEA models with some quantifiable research outputs. However, these suffer from the twin maladies of an inappropriate production specification and a lack of consideration of the quality of output. By including the qualitative attributes of peer-reviewed journals, we develop a procedure that captures both quality and quantity, and apply it using a network DEA model. Our main finding is that standard DEA models tend to overstate the research efficiency of most Australian universities.     

再论管理研究中的关系:“关”与“系”的交互视角

在系统回顾现有关系研究文献基础之上,结合关系研究和社会网络理论,区分双边联系(即“关”)和多边网络(即“系”)两大不同视角,重新梳理文献。在此基础上,对未来关系研究如何整合“关”视角和“系”视角提出了系统性建议,尤其是构建“关”与“系”二者整体性与动态性交互的核心机制体系,提出了包括信任转让、信任转化、“佛面”效应、多重结构四大交互机制,通过阐述“关”“系”互动机制,重新解读“关系”。     

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.     

基于自由处置性的网络系统效率评价模型研究

网络系统生产可能集是构建网络DEA模型的基础,而相邻生产子过程的投入产出连接条件则是构造生产可能集的关键。现有的网络DEA模型在本质上都假设所有子过程的投入产出都满足强自由处置性,然而在实际生产管理活动中,这一假设未必成立。本文从各类自由处置公理出发,系统地研究了各种类型的子过程投入产出连接条件,构建了一般网络系统的生产可能集,给出了相应的等价形式,并构建了相应的网络DEA模型用于评价决策单元的效率。最后利用本文提出的方法和模型对我国上市银行的效率进行了评价。本文的研究对于一般网络系统的绩效评价和改进具有重要的意义。     

Cyber risk assessment in small and medium-sized enterprises: A multilevel decision-making approach for small e-tailors

The role played by information and communication technologies in today's businesses cannot be underestimated. While such technological advancements provide numerous advantages and opportunities, they are known to thread organizations with new challenges such as cyberattacks. This is particularly important for small and medium-sized enterprises (SMEs) that are deemed to be the least mature and highly vulnerable to cybersecurity risks. Thus, this research is set to assess the cyber risks in online retailing SMEs (e-tailing SMEs). Therefore, this article employs a sample of 124 small e-tailers in the United Kingdom and takes advantage of a multi-criteria decision analysis (MCDA) method. Indeed, we identified a total number of 28 identified cyber-oriented risks in five exhaustive themes of “security,” “dependency,” “employee,” “strategic,” and “legal” risks. Subsequently, an integrated approach using step-wise weight assessment ratio analysis (SWARA) and best–worst method (BWM) has been employed to develop a pathway of risk assessment. As such, the current study outlines a novel approach toward cybersecurity risk management for e-tailing SMEs and discusses its effectiveness and contributions to the cyber risk management literature.     

The topology of collective leadership

Over the past decade, there has been a surge of both theoretical and empirical research to explore the possibilities of shared leadership, a reorientation of leadership away from understanding the actions and interactions of “leaders” to understanding the emergent, informal, and dynamic “leadership” brought about by the members of the collective itself. Naturally, this focus on topology (or structural patterning) has prompted researchers to leverage the advancements in network analytic methodology to understand this paradigm of leadership. Despite the recognition of the unique advantage of studying collective leadership using network analysis, there has been a translational gap. The current paper aims to fill this gap, bridging the core ideas that epitomize collective leadership to the social network metrics and analytics needed to fully understand its antecedents and consequences.     

网络舆情扰动下房地产投资者“追涨杀跌”行为扩散研究

一旦房地产投资者“追涨杀跌”行为发生大范围扩散,将诱发房地产市场的价格严重偏离甚至动荡。本文从传播学与行为金融学交叉视角,基于复杂网络理论构建了房地产投资者“追涨杀跌”行为的网络扩散模型,进而仿真分析了网络舆情与投资者行为偏好交互作用下房地产投资者“追涨杀跌”行为扩散的演化特征。研究表明：房地产投资者越偏向于随机建立关联,“追涨杀跌”行为越可能快速扩散;网络舆情因素在“追涨杀跌”行为扩散过程中发挥主导作用,同时对投资者行为偏好因素发挥较强的“强化效应”或“抑制效应”;当媒体权威性足够高或网民情绪足够乐观时,通过综合调节网络舆情和投资者行为偏好因素能够有效实现预防和限制“追涨杀跌”行为扩散的目的。