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.

Background: This study presents a comprehensive review of blockchain technology with a sustainability orientation in supply chains and logistics. Methods: The publications are extracted from the Scopus and Web of Science databases, comprising 552 publications between 2017 and 2022. Several bibliometric laws and techniques, namely three-field analysis, Bradford’s Law, Lotka’s Law, and thematic maps, are applied in R with the bibliometrix package. Content analysis is also carried out based on 185 publications to appreciate the industry-based view of the field. Results: The bibliometric results indicate that this field is on the rise. Authors, sources, affiliations, countries, keywords, and their relationships are also addressed. The findings of the content analysis and thematic maps reveal that some of the most highlighted themes in the literature include traceability, COVID-19, the internet of things, and Industry 4.0. The most popular industry in this field is discovered to be food and agriculture. Conclusions: This paper contributes to the still relatively scarce literature on how blockchain technology fosters sustainable supply chains and logistics, providing a closer look at blockchain use, methodologies, and future directions for different industries concerning food, agriculture, fashion, textile and apparel, manufacturing, automotive, maritime and shipping, healthcare and pharmaceutical, mining and mineral, and energy.

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.

The rising competition and social media usage increased the importance of university brand personality and strategic marketing in higher education. This study explores the interrelationships between brand-generated content (BGC) and user-generated content (UGC) on social media and universities’ competitive strategy and brand personality. BGC that included four universities’ tweets and UGC that consisted of consumer comments were analyzed by content and correspondence analysis in R programming language. The findings indicated that BGC was in alignment with universities’ generic strategies. BGC-UGC dispersions across brand personality were in alignment for the differentiator university, while there was a mismatch between BGC and UGC for low-cost universities. The differentiator university was associated with being prestigious, cosmopolitan, and conscientious, while the low-cost universities were associated with sincerity. The findings supported the applicability of generic business strategies to the higher education context and showed the strategic link between brand personality and the pursued generic strategy.

Bu çalışmanın amacı farklı sektörlerde faaliyet gösteren lider rakip firmaların sosyal medya etkinliklerinin ölçülmesidir. Bu kapsamda, 2018 Şubat ayı boyunca Twitter kullanıcılarının kozmetik, pazaryeri ve elektronik sektöründe faaliyet gösteren rakip firmalar hakkında yaptıkları paylaşımlar ve bu firmaların kurumsal Twitter hesaplarından yapmış oldukları paylaşımlar Sosyal Medya Madenciliği yöntemi ile analiz edilmiştir. Firmalar hakkındaki tweet sayısı, tweet değeri (olumlu, olumsuz, nötr), takipçi kazanımı, yanıt sayısı, retweet sayısı ve beğeni sayısı başlıklarından oluşan Twitter etkinliğinin ölçüm kriterleri ele alınarak bir başarı sıralaması yapılmış ve en başarılı firmanın kozmetik, en düşük sıralamaya sahip firmanın ise elektronik sektöründen olduğu tespit edilmiştir. Tweet değerini saptayabilmek için Duygu Analizi gerçekleştirilmiştir ve olumlu tweet oranının kozmetik firmaları için daha fazla olduğu sonucuna ulaşılmıştır.