Normalization is one of the stages that have an impact on the results of MCDM problems. Choosing the right normalization technique leads the decision maker to the right results. Accordingly, the purpose of this study is to determine the most appropriate normalization technique for the ROV method. In this study, a real case is analyzed, eight different normalization methods are compared with each other on the basis of a multi-stage framework. The findings show that the model used in this study can be successfully applied in the selection of normalization technique. This study provides a decision support and reference for the selection of nomalization technique for MCDM methods in terms of the framework used. Another importance of this study is the first testing the suitability of different normalization techniques for the ROV method.

This study examines the Logistics Performance Index (LPI) rankings developed by the World Bank from a methodological perspective and proposes an alternative decision support framework. LPI serves as an interactive tool that helps countries identify challenges, innovative solutions, and opportunities in their trade and logistics sectors. In this study, the efficiency of logistics operations in 118 countries was evaluated using an integrated multi-criteria decision-making (MCDM) model objectively weighted by the Entropy method. Countries were ranked using the MCRAT, SAW, TOPSIS, and FUCA methods. According to the findings, large datasets provide more robust insights for sensitivity analyses, and wider weighting coefficient combinations make the data more meaningful. In addition, it is suggested to use low-compensation methods instead of classical additive methods for LPI. Unlike other studies in literature, this research applied an innovative sensitivity analysis to test the robustness of the model and comprehensively examined the effects of weighting techniques based on over 2500 different MCDM results. The findings suggest that the FUCA method should be recommended to decision-makers for calculating LPI rankings due to its simplicity, practicality, low compensatory power, and low sensitivity. This study offers methodological improvements when evaluating logistics performance and provides significant contributions to decision-making processes. The findings are expected to provide a valuable resource for policymakers and businesses in understanding a country’s position in global competition, as well as serving as a reference for researchers evaluating the logistics performance of countries.

Bu çalışmada, Borsa İstanbul (BIST) Kimya, Petrol Kauçuk ve Plastik Ürünler sektöründeki firmaların finansal performansının Çok Kriterli Karar Verme (ÇKKV) yöntemi ile ölçülmesi amaçlanmıştır. Bu doğrultuda, 39 firmanın 2021 yılı finansal performansı belirlenen finansal oranlar temelinde Simultaneous Evaluation of Criteria and Alternative (SECA) yöntemi ile ölçülmüştür. SECA yöntemi ile kriterlerin ağırlıkları ve alternatiflerin performans sıralamaları eş zamanlı olarak belirlenmiştir. Sonuçların güvenilirliğini ve sağlamlığını test etmek amacıyla duyarlılık analizi gerçekleştirilmiştir ve SECA modeli ile elde edilen sonuçlar Method based on the Removal Effects of Criteria (MEREC) tabanlı Simple Additive Weighting (SAW), Weighted Aggregated Sum Product Assessment (WASPAS), Range of Value (ROV) ve Biswas ve Saha ÇKKV modelleri ile karşılaştırılmıştır. Son aşamada ise rasyonel bir sıralama elde etmek için Copeland yöntemine başvurulmuştur. Copeland yöntemi ile elde edilen sıralama sonunda finansal performans bakımından ilk üç sırada ANGEN, ALKIM, ACSEL firmalarının yer aldığı tespit edilmiştir. Kullanılan modelin finansal performans ölçümü için uygun olduğu tespit edilmiştir.

Bu çalışmada, BIST perakende ve ticaret endeksinde işlem gören firmaların 2017-2021 dönemi finansal performansının ÇKKV yöntemleri ile ölçülmesi amaçlanmıştır. İşletmelerin bilançolarından elde edilen yedi kriterin yer aldığı çalışmada, kriterlerin önem dereceleri LOPCOW tekniği ile alternatiflerin performans skorları ise RSMVC yöntemi ile belirlenmiştir. Son aşamada, kullanılan modelin duyarlılık analizi iki aşamada gerçekleştirilmiş, farklı ağırlıkların ve farklı ÇKKV yöntemlerinin sonuçlar üzerinde etkili olduğu saptanırken, sıralamalar arasında pozitif yönlü yüksek bir ilişki tespit edilmiştir. LOPCOW-RSMVC modeli BIST perakende ve ticaret sektöründe finansal performans ölçümü için ilk kez kullanılmıştır. Bu bakımından, çalışmanın literatüre katkı sunacağı düşünülmektedir.

Building on the social support theory and the job demands-resources (JD-R) model, the current research explores the role of coworker task support on the perceived uncertainty, job stress, and emotional exhaustion of hospitality employees affected by the COVID-19 crisis. Moreover, this research investigates the moderating impact of supervisor support and family support on the relationship between perceived uncertainty and emotional exhaustion. The data were collected from 353 hospitality employees currently working in the hospitality industry in Pakistan. Partial least squares structural equation modeling (PLS-SEM) was employed using SmartPLS 3.3.3 software to examine the proposed hypotheses and to analyze the research model. The results point out that coworker task support has no significant relationship with emotional exhaustion. Furthermore, perceived uncertainty and job stress fully mediated the association between coworker task support and emotional exhaustion. Additionally, supervisor support and family support significantly moderated the association between perceived uncertainty and emotional exhaustion. This research contributes to the literature by expanding our knowledge of the role of social support in alleviating the perceived uncertainty, job stress, and emotional exhaustion of hospitality employees during the COVID-19 crisis. The theoretical and practical implications of the study are further discussed.