A new DEA approach to rank alternatives in MCDA

One of the principal subjects in multiple criteria decision analysis is ranking alternatives. Here, we present a new method to rank alternatives by using data envelopment analysis. In this paper, one ranking method is proposed based on applying an artificial alternative called aggregate alternative. The method is based on the fact that one efficient alternative with a better performance has stronger effects on the group of other alternatives. That means its deletion forces the remaining alternatives to get smaller efficiency. The described idea in this paper is inspired of Lotfi and et al. (2011). One feature of the proposed method is that it does not need to determine the weight of the prior. Two examples are used to illustrate how the proposed method works in actual practices, and the results are compared with those obtained from the TOPSIS method

Assessing the Relative Efficiency and Productivity Growth of the Taiwan LED Industry: DEA and Malmquist Indices Application

[[abstract]]With the rapid acceleration of global competition the need has arisen for a more systematic performance evaluation system. This research develops a two-stage performance evaluation system to help maximize performance evaluation success. The performance evaluation is an important approach for enterprises to give incentives and restraint to their operators. It is also an important channel for enterprise stakeholders to obtain performance information. This study analyzes the current evaluation system for the Taiwan LED industry. This research measures the performance of ten LED companies in Taiwan for the period 2003–2009. The proposed method is practical and useful. The evaluation model indicates that proposed method is more reasonable and easier to grasp than other methods. As a result, it is easier to popularize this evaluation method in enterprises. The proposed method presents a complete assessment model that helps managers identify items for improvement, while simultaneously promoting cost and time efficiencies in the LED industry.[[incitationindex]]SCI[[booktype]]紙

Analysis of the impact of DMUs on the overall efficiency in the event of a merger

This paper addresses several mechanisms for overall ranking Decision Making Units (DMUs) according to the contribution of DMUs to the relative efficiency score of a merger considering aggregate units The possible organization of agents outside each possible merger naturally influences the relative efficiency score, which motivates the use of games in partition function form and specific ranking indices for DMUs based on the Shapley value. Several computational problems arise in their exact computation when the number of DMUs increases. We describe two sampling alternatives to reduce these drawbacks. Finally, we apply these methods to analyse the efficiency of the hotel industry in SpainThis work has been supported by FEDER/Ministerio de Ciencia, Innovación y Universidades - Agencia Estatal de Investigación, Spain under grants MTM2017-87197-C3-2-P and MTM2017-87197-C3-3-P, and by the Xunta de Galicia through the European Regional Development Fund (Grupos de Referencia Competitiva ED431C-2017/38) and by the Consellería de Cultura, Educación e Universidades, Xunta de Galicia, Spain (Grupos de Referencia Competitiva ED431C-2020/03).S

Dealing with endogeneity in data envelopment analysis applications

Although the presence of the endogeneity is frequently observed in economic production processes, it tends to be overlooked when practitioners apply data envelopment analysis (DEA). In this paper we deal with this issue in two ways. First, we provide a simple statistical heuristic procedure that enables practitioners to identify the presence of endogeneity in an empirical application. Second, we propose the use of an instrumental input DEA (II-DEA) as a potential tool to address this problem and thus improve DEA estimations. A Monte Carlo experiment confirms that the proposed II-DEA approach outperforms standard DEA in finite samples under the presence of high positive endogeneity. To illustrate our theoretical findings, we perform an empirical application on the education sector

Optimal staff assignment to multiple projects based on efficiency scores

Predmet istraživanja ove doktorske disertacije je razvoj novog pristupa selekciji konsultanata i njihovo optimalno raspoređivanje na određene pozicije (aktivnosti) na jednom ili više projekata. Adekvatan plan rasporeda konsultanata se prepoznaje kao jedan od najvažnijih faktora za efikasnu i pravovremenu realizaciju jednog ili više projekata čije aktivnosti mogu da se odvijaju istovremeno, a da se pri tome poštuju kadrovska i budžetska ograničenja. Ovaj problem je nepolinomijalne složenosti (NP težak) odnosno postaje sve složeniji sa povećanjem dimenzija odnosno broja projekata, broja kosultanata i aktivnosti koje je neophodno realizovati. Donosilac odluke bi trebalo da se vodi jedinstvenim kriterijumom pri određivanju rasporeda tako da uspešno kreira balansiran i efikasan plan rasporeda konsultanata. Efikasnost plana zavisi od različitih ulaznih i izlaznih kriterijuma kao što su obučenost i kvalifikacije konsultanta ali i njihova cena i ocene pri realizaciji sličnih aktivnosti u prošlosti. Očigledno je da je priroda kriterijuma različita i da oni po svojoj prirodi mogu biti i kvantitativni i kvalitativni, što dalje otežava modeliranje procesa i određivanje jedinstvene mere efikasnosti. Prema tome, osnovno je pitanje kako da se kreira efikasan raspored koji će obezbediti optimalno angažovanje raspoloživih konsultanata na više poslova na jednom ili više projekata koji se odvijaju istovremeno, posebno ukoliko nekoliko konsultanata može da realizuje istu aktivnost sa različitim učinkom odnosno nivoom perfomansi. U ovoj doktorskoj disertaciji se predlaže korišćenje i proširivanje modela analize obavijanja podataka (DEA - Data Envelopment Analysis) kao tehnike pomoću koje se integrišu svi ulazni i izlazni kriterijumi i kreira se jedna mera kojom se ocenjuje efikasnost. Predloženo proširenje se odnosi na kreiranje odgovarajućeg DEA modela mešovitog (celobrojnog) linearnog programiranja pomoću koga se istovremeno ocenjuje efikasnost i vrši raspoređivanje konsultanata na pozicije (aktivnosti) na jednom ili više projekata. Kao rezultat optimizacije dobija se jedinstvena ocena efikasnosti za svakog konsultanta za svaku potencijalnu aktivnost na osnovu istorijskih podataka o ključnim indikatorima performansi, simultano sa njihovim dodeljivanjem aktivnostima koje će izvršavati tako da se maksimizira ukupna efikasnost realizacije svih aktivnosti na svim projektima.The main subject in this dissertation is development of a new approach to the selection of staff and their optimal assignment to certain positions in one or more simultaneous projects. An adequate staff assignment is recognized as one of the most important factors for the efficient and timely implementation of projects whose activities can take place at the same time. This problem is very complex and becomes more and more complicated with the increase in the number of projects, the number of staff and the activities that need to be realized. The decision maker should be guided by a unique criterion so that it successfully creates a balanced and efficient assignment plan. The efficiency depends on different input and output criteria, such as the training and qualifications of the staff, but also their costs and scores in the implementation of similar activities in the past. It is obvious that the nature of the criteria is different and they can be both quantitative and qualitative, which further complicates the process of interlacing and the determination of a single measure of efficiency. Therefore, the fundamental question is how to streamline an effective schedule that will ensure optimum engagement of available staff on multiple activities in one or more projects that take place at the same time, especially if several staff members can implement the same activity with different level of performance. This doctoral dissertation proposes using and modification of the Data Envelopment Analysis (DEA) as a technique that integrates all input and output criteria and creates a single measure of efficiency. The proposed modification refers to the creation of an appropriate mixed-integer linear programming DEA model, which simultaneously assesses the efficiency and make the assignment plan of the staff member to positions (activities) in one or more projects. As a result of optimization, a unique assessment of efficiency for each staff member for each potential activity is obtained based on historical data on key performance indicators, simultaneously with their assignment to activities to be performed in order to maximize the overall efficiency of the implementation of all activities on all projects