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This paper presents a new output‐oriented classification of multiple attribute decision‐making (MADM) techniques, not based on common subjective comparisons, but mostly on quantitative and computer‐aided comparisons and results. Several classifications of MADM techniques exist, all of which are either input‐oriented (based on the type of input data) or process‐oriented (depending on the process of calculating the final results using the input data). The classification provided in this paper is based on measuring the performance of 17 MADM techniques (SAW, ELECTRE I, TOPSIS, ORESTE, PROMETHEE I, EVAMIX, MAUT, REGIME, MAPPAC, TACTIC, VIKOR, ARGUS, COPRAS, SMART, PACMAN, MOORA, and ARAS) in seven performance variables (simplicity in learning and deploying, speed, complexity of calculations, the number of inputs, the quality of the underlying logic, the quality of rankings, and the rate of growth in large problems) and clustering them using fuzzy c‐means clustering method. Results indicate that the considered techniques can be best classified into two clusters.

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Purpose – The purpose of this paper is to illustrate the application of statistical tools and techniques for quantitative assessment of spiritual capital (SC) based on a questionnaire survey in the organizations which undergo large-scale organizational change projects. Design/methodology/approach – A sample of 65 individuals from three organizations were interviewed. The paper uses the 12 principles of transformation available to spiritual intelligence (referred to as SQ characteristics) to assess SC in a two-phase integrated algorithm of principal component analysis (PCA) and fuzzy clustering. Findings – The paper proposes a two-phase integrated algorithm. In the first phase, PCA is used to reduce the scores of items related to each of SQ characteristics and aggregate them into a single and unique measure. In the second phase, PCA is applied for total SQ quantification. For verification and validation, fuzzy clustering is employed along with PCA to cluster the people in the survey into different classes, which may possess different stocks of SC and rank them based on their level of SQ. The results of PCA are verified and validated by fuzzy clustering revealing the applicability and usefulness of PCA for SC quantification. Research limitations/implications – The paper is based on individual judgments about their own SQ characteristics hence the results of questionnaire survey may be biased by individual personal characteristics. Future research can apply the proposed algorithm and check for its reliability using other psychometric instruments available in the field. Originality/value – The paper contributes by filling a gap in the quantitative management tools literature, in which empirical studies on validated multivariate analysis of spirituality have been scarce until now.

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PurposeEnvironmental awareness is increasing among people in developing countries. In this regard, companies should consider ecological goals in addition to financial goals. Since the food industry is recognised as one of the largest emitters of CO2, profit and ecological objectives are optimised in radio-frequency identification (RFID) based closed-loop supply chain in the food industry in this paper.Design/methodology/approachBased on the literature, companies with a green entrepreneurial orientation (GEO) can turn ecological problems into opportunities using their proactiveness. In this regard, a new mixed-integer non-linear mathematical model is presented for optimising a new multi-product RFID-based closed-loop supply chain with a GEO in the food industry. The case study in this paper is Ofogh-e Kourosh company which is located in Iran. The GAMS software is used to code this model.FindingsThe optimum number of new products and materials flow was found among the closed-loop supply chain entities. Some factors as price, quality and warranty of products were considered, and the number of reopening of facilities if needed was set. The optimum node for RFID installation was found.Originality/valueThe paper presents a multi-objective mathematical model for optimising a multi-product RFID-based closed-loop supply chain with a GEO in the food industry. In addition, this paper gives insights into how can model this type of supply chain considering ecological and financial attributes.