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Wen-Min Lu

Bio: Wen-Min Lu is an academic researcher from Chinese Culture University. The author has contributed to research in topics: Data envelopment analysis & Intellectual capital. The author has an hindex of 31, co-authored 116 publications receiving 3591 citations. Previous affiliations of Wen-Min Lu include National Defense University & National Defence University, Pakistan.


Papers
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Journal ArticleDOI
TL;DR: 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, and suggests that the two-step contextual analysis and network DEA are the recent trends across applications.
Abstract: 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.

622 citations

Journal ArticleDOI
TL;DR: The five most active DEA subareas in recent years are identified; among them the “two-stage contextual factor evaluation framework” is relatively more active.
Abstract: 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.

482 citations

Journal ArticleDOI
TL;DR: This study applies a network clustering method to group the literature through a citation network established from the DEA literature over the period 2000 to 2014, and presents the research fronts, a coherent topic or issue addressed by a group of research articles in recent years.
Abstract: Research activities relating to data envelopment analysis (DEA) have grown at a fast rate recently. Exactly what activities have been carrying the research momentum forward is a question of particular interest to the research community. The purpose of this study is to find these research activities, or research fronts, in DEA. A research front refers to a coherent topic or issue addressed by a group of research articles in recent years. The large amount of DEA literature makes it difficult to use any traditional qualitative methodology to sort out the matter. Thus, this study applies a network clustering method to group the literature through a citation network established from the DEA literature over the period 2000 to 2014. The keywords of the articles in each discovered group help pinpoint its research focus. The four research fronts identified are “bootstrapping and two-stage analysis”, “undesirable factors”, “cross-efficiency and ranking”, and “network DEA, dynamic DEA, and SBM”. Each research front is then examined with key-route main path analysis to uncover the elements in its core. In addition to presenting the research fronts, this study also updates the main paths and author statistics of DEA development since its inception and compares them with those reported in a previous study.

217 citations

Journal ArticleDOI
TL;DR: In this paper, the authors applied the dynamic slack-based measure (DSBM) model to evaluate the performance of 34 Chinese life insurance companies for the period 2006-2010. And they found that the mean efficiency scores of life insurers are relatively stable, ranging from 0.905 to 0.973.
Abstract: This study applies the dynamic slack-based measure (DSBM) model to evaluate the performance of 34 Chinese life insurance companies for the period 2006–2010. This study also examines the relationship between intellectual capital and performance using the truncated regression approach. Our findings indicate that over the period of the study, the mean efficiency scores of life insurers are relatively stable, ranging from 0.905 to 0.973. We verify that the efficiency scores of the DSBM model differ significantly from those of the traditional data envelopment analysis (DEA) model, which supports the use of the DSBM model. Our regression analysis reveals that intellectual capitals are significantly positively associated with firm operating efficiency. Our findings corroborate prior studies which show that intellectual capital can make a company rich. In this dynamic business world, life insurers' managers should invest and fully utilize intellectual capital to gain a competitive advantage.

151 citations

Journal ArticleDOI
TL;DR: This study applies data envelopment analysis with the traditional DEA model, most productive scale size concept, returns to scale approach, and bootstrap method to assess the operating performance, set scale efficient targets, and determine efficiency rankings of Asian container ports.

144 citations


Cited by
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Book
29 Nov 2005

2,161 citations

Dissertation
01 Jan 1975

2,119 citations

Posted Content
01 Jan 1995
TL;DR: In this article, the potential applicability of frontier methods in agricultural economics is discussed, along with the construction of technical, allocative, scale and overall efficiency measures relative to these estimated frontiers.
Abstract: In this paper recent developments in the estimation of frontier functions and the measurement of efficiency are surveyed, and the potential applicability of these methods in agricultural economics is discussed. Frontier production, cost and profit functions are discussed, along with the construction of technical, allocative, scale and overall efficiency measures relative to these estimated frontiers. The two primary methods of frontier estimation, econometric and linear programming, are compared. A survey of recent applications of frontier methods in agriculture is also provided. (This abstract was borrowed from another version of this item.)

821 citations

Journal ArticleDOI
TL;DR: This paper aims to report an extensive listing of DEA-related articles including theory and methodology developments and "real" applications in diversified scenarios from 1978 to end of 2016.
Abstract: In recent years there has been an exponential growth in the number of publications related to theory and applications of Data Envelopment Analysis (DEA). Charnes, Cooper, and Rhodes (1978) introduced DEA as a tool for measuring efficiency and productivity of decision making units. DEA has immediately been recognized as a modern tool for performance measurement. Since then, a large and considerable amount of articles has been appeared, including significant breakthroughs in theory and a great portion of works on DEA applications, both public and private sectors, to assess the efficiency and productivity of their activities. Although there have been several bibliographic collections reported, a comprehensive analysis and listing of DEA-related articles covering its first four decades of history is still missing. This paper, thus, aims to report an extensive listing of DEA-related articles including theory and methodology developments and "real" applications in diversified scenarios from 1978 to end of 2016. Some summary statistics of the publications' growth, the most utilized academic journals, authorship analysis, as well as keywords analysis are also provided.

774 citations

Journal ArticleDOI
TL;DR: This study reviewed a total of 403 papers published from 1994 to 2014 in more than 150 peer reviewed journals and indicated that, in 2013, scholars have published papers more than other years.
Abstract: Two decades was systematically reviewed on fuzzy MCDM techniques from 1994 to 2014.The database for review was 403 papers from more than 150 high-ranking journals.403 scholarly papers were grouped in four different main fields.Papers were classified based on utilizing, developing and proposing research papers. MCDM is considered as a complex decision-making tool involving both quantitative and qualitative factors. In recent years, several fuzzy FMCDM tools have been suggested to choosing the optimal probably options. The purpose of this paper is to review systematically the applications and methodologies of the fuzzy multi decision-making (FMCDM) techniques. This study reviewed a total of 403 papers published from 1994 to 2014 in more than 150 peer reviewed journals (extracted from online databases such as ScienceDirect, Springer, Emerald, Wiley, ProQuest, and Taylor & Francis). According to experts' opinions, these papers were grouped into four main fields: engineering, management and business, science, and technology. Furthermore, these papers were categorized based on authors, publication date, country of origin, methods, tools, and type of research (FMCDM utilizing research, FMCDM developing research, and FMCDM proposing research). The results of this study indicated that, in 2013, scholars have published papers more than other years. In addition, hybrid fuzzy MCDM in the integrated method and fuzzy AHP in the individual section were ranked as the first and second methods in use. Additionally, Taiwan was ranked as the first country that contributed to this survey, and engineering was ranked as the first field that has applied fuzzy DM tools and techniques.

724 citations