scholarly journals Effects of aspiration-induced adaptation and migration on the evolution of cooperation

2014 ◽  
Vol 25 (07) ◽  
pp. 1450025 ◽  
Author(s):  
Yu Peng ◽  
Xu-Wen Wang ◽  
Qian Lu ◽  
Qing-Ke Zeng ◽  
Bing-Hong Wang
Keyword(s):  
Data Envelopment Analysis ◽  
Prospect Theory ◽  
Evolution Of Cooperation ◽  
Square Lattice ◽  
Data Envelopment ◽  
Aspiration Level ◽  
Aspiration Levels ◽  
Emergence Of Cooperation ◽  
And Migration ◽  
The Individual

In the light of the prospect theory (PT), we study the prisoner's dilemma game (PDG) on square lattice by integrating the deterministic and Data envelopment analysis (DEA) efficient rule into adaptive rules: the individual will change evolutionary rule and migrate if its payoff is lower than their aspiration levels. Whether the individual choose to change the evolutionary rule and migrate is determined by the relation between its payoff and aspiration level. The results show that the cooperation frequency can hold unchange with the increasing of temptation to defect. The individual chooses to adopt DEA efficient rule and to migrate that can induce the emergence of cooperation as the payoff is lower than its aspiration.

scholarly journals A DEA Analysis Using Quality And Advertising As Determinants Of Strategic Group Membership In The Automobile Industry

2010 ◽  
Vol 14 (4) ◽  
Author(s):  
Eric C. Jackson
Keyword(s):  
Data Envelopment Analysis ◽  
Automobile Industry ◽  
Rank Test ◽  
Data Envelopment ◽  
Market Segment ◽  
Strategic Group ◽  
Time Period ◽  
The Family ◽  
Dea Analysis ◽  
The Individual

This manuscript considers sales within an automotive strategic group.  Sales within the “Family Car” segment are examined. The efficient uses of inputs relative to the sales generated as determined by Data Envelopment Analysis are compared. The relative efficiencies are used to identify strategic groups within the market segment and to suggest how resources may be utilized more efficiently.  Data Envelopment Analysis, (DEA), is used to compare three inputs and one output for several automobile manufacturers competing for sales in the same market segment.  The three inputs used are two aggregate measures of quality and one measure of the dollar volume spent on advertising by the firms. The output measure used is the volume of sales each year over a five-year period. A Kruskal and Wallis rank test is performed to confirm that the data is comparable over the five year time period. Specifically, comparisons are made to establish that no significant changes in quality or advertising expenditures have occurred during the study period. Once it has been established that no significant changes occurred during the study period for the input and output measures for the individual automotive models. Next, firms are compared using the DEA efficiencies and are grouped according to these efficiencies.  The efficiency measurements indicate that there are two distinct clusters of companies formed within the market segment.  The most efficient cluster is composed of five firms. The least efficient cluster is composed of five firms. An intermediate cluster of two firms exists that is neither extremely efficient nor extremely inefficient in it’s utilization of resources but may be more closely aligned with the efficient firms than with the inefficient group. This stratification into groups within the market segment by efficiency suggests that practitioners might be able to adjust their utilization of resources to compete in a different strategic group. It also suggests that success within a strategic group may be impacted by how firms utilize strategic levers within their control.

Data envelopment analysis methods in sustainable agricultural development research

2021 ◽  
pp. 179-205
Author(s):  
Katarzyna Smędzik-Ambroży ◽  
Agnieszka Sapa
Keyword(s):  
Sustainable Development ◽  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Economies Of Scale ◽  
Scale Effects ◽  
Three Dimensions ◽  
Data Envelopment ◽  
Farm Accountancy Data Network ◽  
Business Entities ◽  
The Individual

Sustainable development of business entities can be analysed in terms of three dimensions, i.e., economic, social and environmental ones. The economic dimension of sustainable development can be assessed, inter alia, by entities’ technical efficiency defined as the relation of outputs to inputs. One of the methods that is used to assess the technical efficiency of business entities compared to other entities is the Data Envelopment Analysis (DEA) method. The aim of the chapter is to determine the relative technical efficiency of representative agricultural farms from the individual European Union countries in 2018. Moreover, the scale efficiency indexes and the area of scale effects (increasing or decreasing) of the analysed farms were also determined. In the study the data from the Farm Accountancy Data Network (FADN) for 2018 were applied. In order to achieve the assumed research goals, the input-oriented DEA model was used, and the technical efficiency indexes of farms were estimated with the assumption of constant return to scale (CRS) and variable return to scale (VRS). This allowed, among others, for indicating the countries with farms achieving the highest technical efficiency (Belgium, Spain, Italy, Malta and Netherlands assuming CRS, and Belgium, Spain, Italy, Malta and Netherlands, Greece, Ireland, Romania and Slovenia assuming VRS), the lowest technical efficiency (the Czech Republic and Slovakia) within surveyed group of farms. All relatively inefficient farms (except Slovakia) functioned in the area of increasing economies of scale.

Data Envelopment Analysis and Cross-Efficiency Evaluation in the Management of Sports Teams: The Assessment of Game Performance of Players in the Spanish Handball League

2013 ◽  
Vol 27 (3) ◽  
pp. 217-229 ◽  
Author(s):  
Óscar Gutiérrez ◽  
José L. Ruiz
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Efficiency Evaluation ◽  
Sports Teams ◽  
Premier League ◽  
Support Tools ◽  
Sports Team ◽  
Overall Performance ◽  
The Individual ◽  
Game Performance

Data Envelopment Analysis (DEA) and cross-efficiency evaluation are shown as support tools for sports team management in the context of a study of assessment of the individual game performance of handball players of the Spanish premier league. A sample of 66 players that play as backs in their teams is evaluated from the perspective of their offensive game. DEA yields a measure of the overall performance of the game of the players, and allows to identifying relative strengths and weaknesses by means of a benchmarking analysis. The cross-efficiency evaluation has provided a peer-appraisal of the players with the different patterns of game that the 10 players rated as efficient have used in the DEA assessments, and has made it possible to derive a full ranking of players.

How to pick your staff? Using data envelopment analysis

2014 ◽  
Vol 37 (9) ◽  
pp. 815-832 ◽  
Author(s):  
Susanne Warning
Keyword(s):  
Data Envelopment Analysis ◽  
Personnel Selection ◽  
Multiple Criteria ◽  
Data Envelopment ◽  
Human Resource Managers ◽  
Content Type ◽  
Optimal Weights ◽  
Resource Managers ◽  
Using Data ◽  
The Individual

Purpose – This purpose of this paper is to present a tool for facilitating personnel selection when multiple heterogeneous human resource managers use multiple criteria. Two problems result from such a situation. First, when multiple criteria are applied, it is unusual for one candidate to dominate the other candidates in all areas, which requires assigning weights to the different criteria to be able to rank the candidates. Second, in a heterogeneous selection committee, finding weights that accurately reflect the individual preferences of all members is difficult. Design/methodology/approach – To deal with the multidimensional setting of selecting personnel, this paper introduces data envelopment analysis with assurance region (DEA-AR) to determine individually optimal weights for each applicant. Findings – DEA-AR leads to a score for each applicant that can serve as a signal for productivity and, thus, for evaluating the candidate. Based on linear programming, DEA-AR not only aggregates multiple dimensions into a single score but also incorporates managers’ preferences. In addition, the procedure is transparent and fair. It seems to be highly appropriate for selecting personnel. Based on a simulated dataset of applicants, the use of DEA-AR for selecting personnel is illustrated and discussed. Originality/value – DEA-AR provides a tool for supporting personnel selection or pre-selection. This model is based on a mechanical procedure and considers managers’ ideas about weights.

Common set of weights in data envelopment analysis under prospect theory

2020 ◽  
Vol 38 (1) ◽  
Author(s):  
Yu Yu ◽  
Weiwei Zhu ◽  
Qinfen Shi ◽  
Shangwen Zhuang
Keyword(s):  
Data Envelopment Analysis ◽  
Prospect Theory ◽  
Data Envelopment ◽  
Common Set Of Weights

scholarly journals 2-Tuple Unbalanced Linguistic Multiple Criteria Group Decision Making using Prospect Theory Data Envelopment Analysis

2021 ◽  
Author(s):  
Imran Khan ◽  
Anjana Gupta ◽  
Aparna Mehra
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Prospect Theory ◽  
Group Decision Making ◽  
Group Decision ◽  
Programming Model ◽  
Multiple Criteria ◽  
Data Envelopment ◽  
Linguistic Term ◽  
Criteria Weights

Abstract The linguistic terms in a balanced linguistic term set describing qualitative data are symmetrical around the central linguistic word. With the growing complexity of the problems, the symmetric linguistic term set appears to be confined. This work examines the multiple criteria group decision-making problems where decision-makers employ a 2-tuple unbalanced linguistic term set to provide entries of alternative-criteria matrices.We adopt a data envelopment analysis (DEA) method and create a linear programming model to evaluate alternative-criteria weights for each decision-maker. The value function from prospect theory models the non-rational aspect of risk in criteria. The values of prospect gain and prospect loss on cost and benefit criteria are computed and used to create a DEA model that evaluates the weights of each criterion on each alternative. Finally, the entropy values of the cross-efficiency scores deliver a ranking of the alternatives. A numerical example illustrates the proposed methodology

scholarly journals Measuring and evaluating efficiency and effectiveness using goal programming and data envelopment analysis in a fuzzy environment

2003 ◽  
Vol 13 (1) ◽  
pp. 35-60 ◽  
Author(s):  
Sheth Nimish ◽  
Konstantinos Triantis
Keyword(s):  
Data Envelopment Analysis ◽  
Optimal Solution ◽  
Data Envelopment ◽  
Fuzzy Environment ◽  
Aspiration Levels ◽  
Efficiency And Effectiveness ◽  
Programming Techniques ◽  
Fuzzy Constraint ◽  
Fuzzy Goal ◽  
Insertion Process

Generally, in most situations optimal achievement of multiple goals is rarely possible for crisp mathematical programming techniques. In such cases, a compromise achievement of goals that leads to a satisfying solution rather than an optimal solution bears more relevance. The present research introduces a Fuzzy Goal Data Envelopment Analysis (Fuzzy GoDEA) framework to measure and evaluate the goals of efficiency and effectiveness in a fuzzy environment. Fuzzy GoDEA accommodates crisp input and output data but allows imprecise specification of the aspiration levels for the efficiency and effectiveness goals. A membership function is defined for each fuzzy constraint associated with the efficiency and effectiveness goals and represents the degree of achievement of that constraint. Further, the Fuzzy GoDEA framework is extended into several variations that (i) allow the assignment of relative importance to the goals of efficiency and effectiveness and (ii) model scenarios where one of the goals of efficiency and effectiveness is crisp and the other fuzzy. The Fuzzy GoDEA framework is implemented for a newspaper preprint insertion process (NPIP). .

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