In the realm of multi-criteria decision-making (MCDM) problems, the selection of a weighting method holds a critical role. Researchers from diverse fields have consistently employed MCDM techniques, utilizing both traditional and novel methods to enhance the discipline. Acknowledging the significance of staying abreast of such methodological developments, this study endeavors to contribute to the field through a comprehensive review of several novel weighting-based methods: CILOS, IDOCRIW, FUCOM, LBWA, SAPEVO-M, and MEREC. Each method is scrutinized in terms of its characteristics and steps while also drawing upon publications extracted from the Web of Science (WoS) and Scopus databases. Through bibliometric and content analyses, this study delves into the trend, research components (sources, authors, countries, and affiliations), application areas, fuzzy implementations, hybrid studies (use of other weighting and/or ranking methods), and application tools for these methods. The findings of this review offer an insightful portrayal of the applications of each novel weighting method, thereby contributing valuable knowledge for researchers and practitioners within the field of MCDM.

In recent years, multi-criteria decision-making (MCDM) techniques have expanded the corpus of existing techniques and demonstrated their effectiveness with applications in various fields. In this study, bibliometric analysis was conducted to evaluate the research trend on new ranking-based MCDM methods in the last decade, namely WASPAS, MABAC, EDAS, CODAS, COCOSO, and MARCOS. The various keyword combinations are searched on the Web of Science and the Scopus databases. Bibliometric analysis is carried out in R with the Biblioshiny app for the bibliometrix package. In total, 1,215 related publications are analyzed. The sources, authors, countries, and publications are examined in terms of production and total citation, and the most frequent keywords with trend topics are obtained. The summaries of the findings are as follows: The number of publications has increased over the years for all the methods. The most cited studies belong to the authors of the methods and fuzzy implementations related to the methods. For the author's impact and productivity, Zavadskas and Pamučar stand out. Turkey and India rank in the top five in terms of the number of publications produced on all methods. China is the most cited country for the three methods. According to keyword analysis, different research topics such as sustainability, renewable energy, optimization, supplier selection, hydrogen production and transport are investigated through these methods and other techniques are utilized such as SWARA, AHP, TOPSIS, Best-Worst, DEMATEL, MAIRCA, and CRITIC.

Purpose: The differences between the criteria affecting the logistics performance of countries and their importance levels are meaningful in terms of policy development processes. It has been determined that the criteria are weighted equally in the emerging markets logistics index. For this reason, the study reweighted the criteria of the Emerging Markets Logistics Index and investigated the effects of weighting on the ranking. In this respect, the study aims to make the index more objective. Methodology: In the study, Multi-Criteria Decision Making methods were utilized. Within this context, MEREC (Method Based on the Removal Effects of Criteria) was used to determine the criteria weights, while MABAC (Multi Attributive Border Approximation Area Comparison) and MAIRCA (Multi Attributive Ideal Real Comparative Analysis) methods were preferred to rank the alternatives. Findings: In the study, it was concluded that the weighted values of the criteria are more consistent with the literature. Additionally, the new weights obtained have an effect on the ranking values of the countries. Orginality: It is important that emerging markets provide an opportunity to develop infrastructure to increase logistics productivity and provide a platform for the implementation of new technologies in logistics operations. Furthermore, these markets enable the diversification and development of logistics services through the expanding consumer demand. This study differs from other studies in the literature because it preferred the Agility Emerging Markets Logistics Index (AEMLI) instead of the Logistic Performance Index (LPI) and used MEREC-based MABAC-MAIRCA methods.

Küreselleşme, artan talep ve çelik üretim teknolojilerinin gelişiminin bir sonucu olarak azalan demir cevheri kaynakları ve hurda malzeme bulunabilirliğinin sınırlı olması sektörün hammadde temininde dış ticaret, üretim ve maliyet kriterlerini öne çıkarmaktadır. Türkiye’nin demir çelik endüstrisinde hammadde bağımlılığını ve dış ticaret verimliliğini ortaya çıkarmak çalışmanın ana amacı olarak ifade edilmektedir. Bu amaç doğrultusunda Türkiye’nin en iyi performans gösterdiği ülkelerin ve yılların belirlenmesi hedeflenmektedir. Bu bağlamda çalışmada 2008 finansal krizinin de etkilerini değerlendirebilmek adına 2008-2022 dönemi incelemeye alınmıştır. Çalışmada çok kriterli karar verme (ÇKKV) yöntemlerinden faydalanılmıştır. Çalışmada kriter ağırlıklarının belirlenmesinde “CRiteria Importance Through Intercriteria Correlation” (CRITIC) ve alternatiflerin sıralanmasında ise ”Compherensive Distance Based Ranking” (COBRA) yöntemi tercih edilmiştir. Türkiye demir çelik endüstrisinin demir cevherinden üretim yöntemine göre en iyi performans gösterdiği yılların sırasıyla 2021, 2008 ve 2022; hurda malzemeden üretim yöntemine göre ise 2021, 2019 ve 2008 olduğu bulgusu elde edilmiştir. 2009 ve 2015 yıllarının her iki üretim yönteminde de en düşük performansa sahip oldukları görülmüştür. Ülkeler özelinde gerçekleştirilen uygulamada İtalya’nın en yüksek Rusya’nın ise en düşük performans değerine sahip olduğu sonucuna ulaşılmıştır. Çalışma, demir çelik endüstrisinde hammadde bağımlılığı konusunu üretim yöntemlerine göre sınıflandırması, ihracat ile ilişkilendirerek ticaret verimliliğini dikkate alması ve Türkiye özelinde hem yılları hem de ülkeleri incelemesi bakımından literatürdeki diğer çalışmalardan farklılaşmaktadır.

This study aims to investigate the relationship between students’ satisfaction criteria with a hybrid model, conducting both DEMATEL and Canonical Correlation Analysis. The dataset is obtained from Turkey University Satisfaction Survey (TUSS) 2020, consisting of a total of 192 universities and 39,386 students. TUSS has six factors, namely, "campus and the fulfilment of campus life”, “academic support and interest”, “richness of learning opportunities and resources”, “personal development and career support”, “satisfaction with the learning experience”, and “satisfaction with the institution’s management and operation”. DEMATEL is conducted to understand the cause and effect relationship and group these factors into two categories as dependent and independent sets. To investigate the relationship between these sets more deeply, Canonical Correlation Analysis is (CCA) carried out. The results of CCA are interpreted through canonical weights, canonical loadings, canonical cross-loadings, the proportion of explained variance, and redundancy index. The findings of the study suggest that to increase the overall satisfaction towards the institution, academic support and interest, as well as personal development and career support, should be delved into very carefully.