To stay competitive in a business environment, continuous performance evaluation based on the triple bottom line standard of sustainability is necessary. There is a gap in addressing the computational expense caused by increased decision units due to increasing the performance evaluation indices to more accuracy in the evaluation. We successfully addressed these two gaps through (1) using principal component analysis (PCA) to cut the number of evaluation indices, and (2) since PCA itself has the problem of merely using the data distribution without considering the domain-related knowledge, we utilized Analytic Hierarchy Process (AHP) to rank the indices through the expert’s domain-related knowledge. We propose an integrated approach for sustainability performance assessment in qualitative and quantitative perspectives. Fourteen insurance companies were evaluated using eight economic, three environmental, and four social indices. The indices were ranked by expert judgment though an analytical hierarchy process as subjective weighting, and then principal component analysis as objective weighting was used to reduce the number of indices. The obtained principal components were then used as variables in the data envelopment analysis model. So, subjective and objective evaluations were integrated. Finally, for validating the results, Spearman and Kendall’s Tau correlation tests were used. The results show that Dana, Razi, and Dey had the best sustainability performance.

https://www.mdpi.com/2071-1050/12/3/789/pdf

An integrated Multi-Criteria Decision Making Model for Sustainability Performance Assessment for Insurance Companies

In this paper, we propose an objective principal components weighting scheme for all-time Winter Olympic gold, silver and bronze medals based solely on the number of medals won. Our results suggest...

Olympic rankings based on objective weighting schemes

Abstract There exist two types of Data Envelopment Analysis (DEA) approaches to the Olympic Games: conventional and fixed-sum outputs (FSO). The approach proposed in this paper belongs to the latter category as it takes into account the total number de medals of each type awarded. Imposing these constraints requires a centralized DEA perspective that projects all the countries simultaneously. In this paper, a multiobjective FSO approach is proposed, and the Weighted Tchebychef solution method is employed. This approach aims to set all output targets as close as possible to their ideal values. In order to choose between the alternative optima, a secondary goal has been considered that minimizes the sum of absolute changes in the number of medals, which also renders the computed targets to be as close to the observed values as possible. These targets represent the output levels that could be expected if all countries performed at their best level. For certain countries, the targets are higher than the actual number of medals won while, for other countries, these targets may be lower. The proposed approach has been applied to the results of the Tokyo 2020 Olympic Games and compared with both FSO and non-FSO DEA methods. 

/pdf/multiobjective-centralized-dea-approach-to-tokyo-2020-1ehgz2l9.pdf

Multiobjective centralized DEA approach to Tokyo 2020 Olympic Games

Competitor classification schemes have been a part of sport since its origins. Eligibility criteria have developed towards inclusion and increasing diversity. The pool of competitors has expanded f...

Classification in sport: A question of fairness

Summer Olympic games in Rio 2016 were the biggest and the most important sport event in 2016. Athletes’ performance at Olympics is always of a high interest and serve as a basis for various parametric and non-parametric analyses. In this article, we construct data envelopment analysis model to analyze countries’ performance in Summer Olympic games in Rio 2016. The traditional model structure is based on GDP-population theory. In this article, we go beyond this traditional model structure and introduce economic active population and corruption factors into the model. Similarly, the Olympic success is measured regarding medal ranking of each country. Nevertheless, we enlarge traditional golden, silver and bronze medals output structure, including medal ranking up to 8th position. This model structure enables us to also measure performance of lower performed countries that are traditionally not ranked in the medal rankings. As a complement to the achieved results, we decompose the results regarding World Bank’s income classification to be able to make conclusion of countries’ performance.

L. A. Andrade

Papers

Measuring countries’ performance at the Summer Olympic Games in Rio 2016