文献调研功

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Appropriate reviewer assignment significantly impacts the quality of proposal evaluation, as accurate and fair reviews are contingent on their assignment to relevant reviewers. The crucial task of assigning reviewers to submitted proposals is the starting point of the review process and is also known as the reviewer assignment problem (RAP). Due to the obvious restrictions of manual assignment, journal editors, conference organizers, and grant managers demand automatic reviewer assignment approaches. Many studies have proposed assignment solutions in response to the demand for automated procedures since 1992. The primary objective of this survey paper is to provide scholars and practitioners with a comprehensive overview of available research on the RAP. To achieve this goal, this article presents an in-depth systematic review of 103 publications in the field of reviewer assignment published in the past three decades and available in the Web of Science, Scopus, ScienceDirect, Google Scholar, and Semantic Scholar databases. This review paper classified and discussed the RAP approaches into two broad categories and numerous subcategories based on their underlying techniques. Furthermore, potential future research directions for each category are presented. This survey shows that the research on the RAP is becoming more significant and that more effort is required to develop new approaches and a framework.

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This paper explores how AI-powered tools could be leveraged to streamline the process of identifying, screening, and analyzing relevant literature in academic research. More specifically, we examine the documented relationship between environmental, social, and governance (ESG) factors and the cost of capital (CoC). By applying an AI-assisted workflow, we identified 36 published studies, synthesized their key findings, and highlighted relevant theories, moderators, and methodological challenges. Our analyses demonstrate the value of AI tools in enhancing business research processes and also contribute to the growing literature on the importance of ESG in the field of corporate finance.

This paper provides a preliminary assessment of the literature available in the field of External Technology Searching. Many methods exist to enable companies to take advantage of new technologies and apply them to achieve a competitive advantage. This literature review focuses on reducing complexity and providing clarity related to the numerous different terms and methodologies used throughout the literature. The main methods found in the literature include: Technology Foresight, Technology Forecasting, Technology Intelligence, and Technology Scouting. However, many additional terms have also been used to describe similar strategies, leading to inconsistency in the use of the terms, resulting in confusion and missed opportunities to innovate for those trying to navigate the field. Synthesis of the results assists in clarifying the differences and conflicts in the literature between the numerous terms. The results serve to display the state of the art on the field and present a basis for further research.

The fields of innovation systems and technology transfer (TT) have seen growing interest in recent years, especially in the context of open innovation. Private consultants, play a vital role in mediating and facilitating interactions among various stakeholders in the innovation process. However, the specific roles of private consultants as innovation intermediaries have received limited attention in the literature. This study presents a case analysis of a Portuguese consultancy firm involved in 219 TT projects between 2015 and 2021. The research identifies six key intermediary roles consistently played by the consultancy: funding and finance, project management, technology scouting, design and ideation, feasibility assessment, and marketing/business development. The study further reveals that the type of entity initiating the TT project may influence the roles performed by private consultants. This research contributes to a deeper understanding of the evolving nature and significance of private consultants as intermediaries in technology transfer. 

Systematic review techniques are about to become the “new normal” in reviews of management research. However, there is not yet much advice on how to organize the sample selection process as part of such reviews. This article addresses this void and analyzes this vital part of systematic reviews in more detail. In particular, it offers a critical review of systematic literature reviews published in the Academy of Management Annals and the International Journal of Management Reviews between 2004 and 2018. Based on this methodological literature review, the article presents issues to consider in the most critical choices during the sample selection process. Furthermore, this review identifies several descriptive features such as the mean number of research items included in systematic reviews, the mean number of databases used, and the mean coverage period of such reviews. These numbers may be used as benchmark figures in future reviews.

The research on business reputation and enterprise reputation abroad has been precipitating for more than a century, and the research content is rich and colorful. With the development of China's economy for more than 40 years, the research on the reputation of domestic commercial enterprises is full of characteristics of The Times. Based on the reliable big data literature of CNKI Big Data, Keywords are processed by citespace software,the research results of this paper show that while there are similarities between the two studies, relatively close academic teams have not been formed, and the correlation between scholars is small. The co-citation of keywords all show the characteristics of time zones, analyzing their different characteristics and reflecting the characteristics of China's economic development in different stages. As well as the fact that both reputation studies are declining, it excavates the new trend in the field of reputation research and entrusts a new era mission.

The aim of this paper is to demonstrate the possible enrichment of the traditional procedure of bibliographic literature review using Natural Language Processing (NLP) methods - automated information retrieval. Our task was to conduct a systematic review of academic literature focused on the classical music audience research in the context of arts management and arts marketing. As a core base, we used bibliographic metadata, extracted from the Scopus database. The limits of the most commonly used methods of bibliographic analysis of the literature, which are co-citation analysis and bibliographic coupling, are well known. Therefore, we also used one of the NLP methods for metadata analysis, which allows automated processing of large numbers of texts to overcome these known problems. Thanks to this, we managed to obtain a higher granularity of the researched topics, to reveal emerging topics and to identify gaps in research. To the best of our knowledge, such an approach to the systematic literature review in the field of social sciences has not yet been applied.

ABSTRACT This paper explores the integration of Business Analytics (BA) with Artificial Intelligence (AI) by considering evidence from existing literature through an augmented research process supported by Generative AI (GenAI). GenAI can streamline the process of literature review and synthesis while enriching researchers’ analytical capabilities, e.g. screening literature, finding themes across multiple papers, creating conceptual categories. Therefore, the study seeks to understand the issues and benefits of incorporating GenAI tools into research processes, such as academic writing, based on the authors’ first-hand experiences. The research process involves automatic retrieval of relevant papers from online repositories based on predefined keywords, followed by summarisation of the retrieved documents using language models. The summarised insights are then used to draft the article. The integration of AI with BA requires a gradual approach, leveraging existing analytical capabilities and expertise as a foundation. The study relies on the authors’ experiences and examples to draw conclusions. More comprehensive empirical studies can validate the findings. The paper provides insights for researchers and practitioners interested in leveraging GenAI tools to enhance their work and highlights the potential and challenges of applying these tools in business analytics applications.

The use of e-commerce is growing daily all over the world. Risk perception and e-commerce management are enhanced by technological advancements. Review analysis examines how risk management and perception have evolved in ecommerce. The bibliometric analysis of the study used Scopus metadata from 1995 to 2023. The meta-data retrieval procedure takes into account the inclusion and exclusion procedures. This study investigated a literature progress status, identified the leading contributor to the production of literature. In addition, review investigation can observe cluster analysis based on keyword occurrences using VosViewer. An annual review of research output from 2004 shows a significant rise, with substantial peaks in 2010 and 2011, suggesting rising concerns and complexity regarding ecommerce threats. The overall trend, driven by evolving digital transaction challenges, demonstrates a consistent academic interest in the subject, notwithstanding changes. The study includes geographical research productivity, regional perspectives, key sources, and many aspects of e-commerce risk management. With emerging economies like Brazil and Indonesia gaining traction, a geographical analysis finds China as the largest donor, followed by the United States, Taiwan, the United Kingdom, and India. Well-known conferences and publications are valuable resources. The paper identifies seven topic clusters, respective of supply-chain risk, consumer trust, behavioural intentions, service quality, new trends, privacy concerns, and technological adoption. Dealing with these gaps will assist in defining ecommerce risks and guiding policies aimed at increasing consumer trust and digital transaction security. These results highlight research gaps, supported theories, and scholarly research problems.

The role of quality assurance (QA) officers has become increasingly critical in driving the performance and sustainability of higher educational institutions (HEIs) in a rapidly evolving global academic landscape. The scholarly exploration of QA officers’ attributes and their direct impact on institutional performance remains fragmented and under-researched in the literature. This study conducts a comprehensive bibliometric review to map and analyze the literature on quality assurance in HEIs. Using the Scopus database as the primary source, the search strategy applied two specific keywords: "quality assurance" and "higher education institution," resulting in 220 relevant documents published between 2020 and 2025. The methodological framework involved three key tools: Scopus Analyzer for data retrieval and fundamental trend analysis, OpenRefine for data cleaning and refinement, and VOSviewer for visualizing bibliometric networks such as co-authorship, co-citation, and keyword co-occurrence. This study revealed key publication trends, prominent authors, influential journals, active countries, and thematic research clusters. The numerical results indicate a steady increase in research output on this topic over the past four years, with a significant concentration of studies originating in developed regions. Co-occurrence analysis highlighted recurring themes such as accreditation, institutional performance, policy development, and continuous improvement. This review underscores the growing academic interest in the attributes and competencies of QA officers and their linkages to organizational effectiveness in HEIs. The findings provide valuable insights for future research directions and practical implications for policymakers and institutional leaders aiming to enhance quality management systems in higher education settings.

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This full paper sets out a methodological protocol for conducting a scoping review of literature relating to teamwork effectiveness and equity. The goal of the study is to understand how academic discourse over the five-year period prior to the study being carried out has conceptualized teamwork success in educational and professional contexts, and to what extent equitable team practices are embedded within such conceptualizations. In line with ongoing initiatives to promote transparency in research, this protocol paper is intended for dissemination prior to the conduct of the study itself. The research context, questions, and rationale are set out, and a detailed methodology described, outlining procedures for data retrieval, screening, extraction, and analysis. The paper concludes with an outline of intended reporting methods for the study, including the reporting of deviations from the procedures set out herein. This paper contributes to the scoping review methodology, and especially its application in the field of engineering education research and education research more broadly.

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PurposeThis study uses a multi-level framework to systematically summarize and synthesize the empirical literature on determinants of sustainability disclosure.Design/methodology/approachThis review study is based on 159 empirical studies examining determinants of sustainability disclosure and published in Charted Association of Business Schools (CABS) ranked journals over the last 40 years.FindingsCompanies are experiencing multi-level pressures for sustainability disclosure. Macro-level variables include political, legal, social-cultural and international pressures. Meso-level factors include customers' concerns, shareholders’ and investors' demands, industry-level variables and media coverage. Micro-level factors include the firm-level governance mechanisms, executives' reporting attitude and role of sustainability promoting institutions. Unlike in developed markets, companies in developing markets feel minimal public pressure for sustainability disclosure but rather are influenced by international NGOs, the media and international buyers. Multi-level and multitude of pressures for sustainability disclosure explains the widely observed differences between studies.Originality/valueThis research presents the most extensive systematic review of the extant sustainability disclosure literature and is the first study to group determinants into micro-, meso- and macro-level components using multi-level analysis.

Patent analytics is crucial for understanding innovation dynamics and technological trends. However, a comprehensive overview of this rapidly evolving field is lacking. This study presents a data-driven analysis of patent research, employing citation network analysis to categorize and examine research clusters. Here, we show that patent research is characterized by interconnected themes spanning fundamental patent systems, indicator development, methodological advancements, intellectual property management practices, and diverse applications. We reveal central research areas in patent strategies, technological impact, and patent citation research while identifying emerging focuses on environmental sustainability and corporate innovation. The integration of advanced analytical techniques, including AI and machine learning, is observed across various domains. This study provides insights for researchers and practitioners, highlighting opportunities for cross-disciplinary collaboration and future research directions.

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Digital entrepreneurship has become a transformative phenomenon in the modern economy, changing the way businesses are developed and run through digital technology. Although the literature on digital entrepreneurship is growing rapidly, comprehensive mapping of the evolution of knowledge and research patterns is still limited. This study analysis the development of digital entrepreneurship in academic literature through bibliometric analysis of the Scopus database to identify research trends, knowledge structures, and future directions. The analysis was conducted on 1,815 publications from 681 sources (1988-2025) written by 8,023 researchers, using R Studio (bibliometrix) and VOSviewer. The results show exponential growth with an annual growth rate of 17.22%, as well as five main theme clusters: digital business models, digital innovation, social entrepreneurship, e-commerce, and fintech. Thematic evolution shifted from traditional entrepreneurship (1988–2010) to digital transformation (2011-2018) to new technology integration (2019-2025). The level of international collaboration reached 26.39%, with the United States, China, and the United Kingdom as the main contributors. These findings provide a research roadmap for identifying research gaps, collaboration opportunities, and trending topics in digital entrepreneurship.

Sports associations and companies share a common goal of identifying and selecting top talent, prompting a growing interest in refining their selection processes. Recent decades have witnessed increased attention to predictive valid constructs (e.g., motivation) and predictive assessment methods (e.g., questionnaires). Leveraging an extensive history and empirical evidence from personnel selection research in business, a cross-contextual knowledge transfer could offer potential benefits for both sports and business. To examine the utilization of information between sports and the business context, this study explores the connection between these contexts. Analyzing 20,492 articles from SCOPUS and Web of Science databases, we followed PRISMA guidelines and conducted a citation network analysis (n = 940 articles). Results reveal limited interconnectivity (3,728 links), with only six articles cited between contexts: three sports articles cited business articles and vice versa. Sports articles referred to business research for talent definition, skill assessment, and methodological concerns. Contrarily, the business domain primarily used sports research as examples and for individual aspects of talent development models. This study highlights the potential for points of connection, including requirement analysis, skill assessment, and research on predictive validity. Future research should systematically explore shared and underrepresented topics in both contexts, such as the use of, for example, situational judgement tests in sports to enhance talent selection in sports, drawing insights from the business domain. Systematic review registration https://aspredicted.org/366x-7cfd.pdf.

This study presents a comprehensive bibliometric and citation network analysis of corporate governance literature spanning two decades, from 2004 to 2024. Utilizing the Scopus database, the research employs advanced analytical tools such as R-Bibliometrix and VOSviewer to systematically analyze and visualize the scientific literature on corporate governance. The primary aim is to identify the most influential authors, institutions, and countries in the field, while also uncovering key themes and trends that have shaped the discourse over the past 20 years. This research contributes significantly to the understanding of the corporate governance landscape by providing a thorough overview of the existing literature, highlighting gaps for future research, and offering valuable insights into the field’s evolution. Furthermore, it demonstrates the effectiveness of bibliometric and network analysis tools in revealing the complex interconnections within academic discussions on corporate governance. As such, this study serves as a valuable resource for researchers, policymakers, and practitioners interested in the development and future direction of corporate governance.

Agriculture in Andhra Pradesh faces significant risks from The study aims to examine the green buying behavior of the consumers and the influence of factors of the green marketing strategies on the purchase intentions of the buyers. Bibliometric analysis was implied in this study during the period of 1994 to 2024. Performance mapping analysis and scientific performance analysis was performed on 526 research articles obtained from WOS and 256 research articles obtained from Scopus using VOSviewer software. The performance analysis was carried out to know the past trend of the studies, country specific citation and source (journal) based analysis. Furthermore, scientific analysis was performed by diagnosing the analysis of the top co-citation references and top co-citation authors. Performance trend and scientific analysis aids in understanding of the basic trends of the green purchase intention, green marketing tactics and the factors that affect the green marketing. This study mainly focused on the green consumer buying behavior in Asian Countries, which further assists in the prediction of the future green consumption through the trend analysis of the past studies. The major gaps in this study were identified and the researcher has drawn inferences and future implications

This study proposes a multilevel conceptual framework for a deeper understanding of the relationship between employee well-being and innovativeness. We overview 49 years of well-being research [1972–2021] and 54 years of research on innovativeness [1967–2021] to uncover 24 dominant themes in well-being and ten primary topics in innovativeness research. Citation network analysis and text semantic similarity were used to develop a conceptual framework featuring 21 components and three levels: individual, organizational, and market. These components consist of constructs, domains, and factors that can influence or be influenced by employee well-being and innovativeness either directly or indirectly. This is the first study to use citation network analysis and data mining techniques to investigate the relationship between employee well-being and innovativeness. This novel framework can aid organizations in identifying more holistic and efficient strategies for fostering innovativeness and enhancing the well-being of their workforce. It can also assist in developing new theories and serve as a roadmap for future research. We discuss the research limitations and theoretical and practical implications and propose three research themes that future studies may address.

A central issue within sport management is the extent to which the field should develop a distinctive theoretical knowledge base. This paper empirically investigates the connectedness within (intrafield) and between (interfield) management and sport management disciplines in one specific knowledge domain—institutional theory. We utilized a database of 188 sport-related institutional studies and conducted a citation network analysis of the aggregated reference lists from these articles. We argue that the fields of management and sport management act like “ships in the night.” That is, as the field of sport management has become more distinctive, the field is becoming less connected with general management literature and contemporary theoretical discussions. Potential implications for sport management scholarship and understanding the nature of the field are discussed, along with how it may be possible (if desired) to bridge the gap between sport and management research.

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Recently, academics and practitioners have devoted considerable attention to studying green procurement. Due to the growing number of articles in this fast-evolving domain, it is critical to examine the current body of knowledge thoroughly. The knowledge structure and dissemination channels in this field have been systematically examined for the first time. Four hundred fifty-two Scopus journal articles were analysed using keyword co-occurrence network and main path analysis (MPA) to identify the important research topics and historical evolution of green procurement research. The findings indicate that the literature focuses on multiple topics, including green supply chain management, sustainable public procurement, sustainability, green supplier selection, and environmental management. The primary focus of research has been on the determinants and difficulties of green public procurement. Recently, there has been an increased focus on the determinants of green procurement in the construction and education sectors. The novelty of this study is that it examines the evolution of knowledge in green procurement. Additionally, it offers the ability to analyse the diffusion and structure of knowledge, assisting researchers in successfully navigating hundreds of articles and expanding their understanding of the green procurement domain’s history, current state, and future directions.

ABSTRACT Identifying cross-border knowledge flow and innovation trajectory helps a nation to achieve competitive advantages in the technology race. This paper uses a comprehensive patent analysis method and assessment of national innovation capability to visualise the innovation trajectory and core technology flow of 5G technology across countries (regions) from 2002 to 2019. Firstly, we uncover technology leading countries, technology imitating countries, technology participating countries, and technology holding countries by assessing the level of national technology innovation capability and identifying their development trajectory. Secondly, we observe that China, Japan, and South Korea show more prominence in pictorial communication; the United States focuses on waveguide-related technology, while European countries emphasise antenna-related technology. Finally, we study the diffusion and flow of 5G dominated technology and analyze the technology layout of 5G technology leading countries. The novelty of this study lies in revealing the relationship and significance between the national level of innovation trajectory and the technology level of knowledge flow trajectory. The paper provides implications for the investment of scientific research funds and the choice of cooperative countries in the future. The proposed identification framework of cross-border knowledge flow and innovation trajectory can be applied to other science and technology domains.

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ABSTRACT In the past few years, blockchain technology has attracted more and more attention, and it has been widely used in various fields. But there is still a lack of relevant research reports on the innovation path identification of blockchain technology from a patent perspective. By downloading a total of 14,560 patents from Derwent Innovations Index and conducting main path analysis, this paper illuminates the overall picture of the development of blockchain for experts in this domain from a technology perspective. As an objective and quantitative network-based method, main path analysis identifies important patent, structural backbone and development trajectories in the blockchain development. This provides a reference for the scientific communities to understand the current state of blockchain technology, thereby illuminating future research.

Patent Citation Analysis has been gaining considerable traction over the past few decades. In this paper, we collect extensive information on patents and citations and provide a perspective of citation network analysis of patents from a statistical viewpoint. We identify and analyze the most cited patents, the most innovative and the highly cited companies along with the structural properties of the network by providing in-depth descriptive analysis. Furthermore, we employ Exponential Random Graph Models (ERGMs) to analyze the citation networks. ERGMs enables understanding the social perspectives of a patent citation network which has not been studied earlier. We demonstrate that social properties such as homophily (the inclination to cite patents from the same country or in the same language) and transitivity (the inclination to cite references’ references) together with the technicalities of the patents (e.g., language, categories), has a significant effect on citations. We also provide an in-depth analysis of citations for sectors in patents and how it is affected by the size of the same. Overall, our paper delves into European patents with the aim of providing new insights and serves as an account for fitting ERGMs on large networks and analyzing them. ERGMs help us model network mechanisms directly, instead of acting as a proxy for unspecified dependence and relationships among the observations.

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ABSTRACT Appreciating the contribution of critical human resource development (CHRD) scholarship to raise critical perspectives and practices in HRD, this study explored the development of CHRD scholarship over 20 years (2003–2022) using social network analysis (SNA), particularly focusing on analysing citation and authorship networks in CHRD journal articles. In doing so, this study identified influential CHRD authors, articles, and the structure of CHRD authorship communities – eight connected core groups and many disconnected periphery groups. Further, the CHRD authorship networks were explored and visualised on a five-year basis. The analysis results identified that particular core members, largely White women scholars working in the US or UK, led the CHRD scholarship. Also, community groupings and each community’s key themes were found to be related to the national locations of the authors’ affiliated institutions. Additionally, this study found a recent shift of CHRD scholarship towards smaller, more cohesive communities within the larger network. Based on the findings, this study provides theoretical and practical implications and concludes with a call for building inclusive CHRD scholarship networks.

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The purpose of this study is to identify the core concepts and research trends in corporate entrepreneurship (CE) through keyword network analysis. To achieve this, we conducted a comprehensive analysis of CE-related articles published in domestic academic journals, including general publication trends, author and keyword frequency analysis, and network analysis. A total of 172 articles published between 2003 and 2024 in the Korea Citation Index (KCI) were selected as the analysis target, and network analysis was performed using Gephi 0.10. The results indicate that CE research in Korea has steadily increased since the first publication in 2003, with a predominant focus on quantitative methodologies such as regression analysis and structural equation modeling (SEM). Key researchers, including Tae-Kyung Park and Byung-Seop Yoon, were found to be central figures within the research network. The keywords CE, Performance, CVC, and CV consistently exhibited high influence, highlighting that research on corporate ventures, venture performance, and corporate venture capital forms the core stream of CE studies in Korea. This study is distinct in that it analyzes research trends over the entire period, including the post-2016 surge in CE research, and classifies the research phases based on significant environmental changes to examine the relationships and characteristics of research topics by period. Despite limitations regarding the scope of article collection, keyword extraction and refinement methods, and the lack of citation index consideration, this study provides valuable insights. Future research that addresses these limitations and includes comparative analysis with international trends is expected to further advance the knowledge structure of CE research in Korea.

Customer co-creation value has become a widely used term to describe an active, creative, and social collaboration process between producers and customers, in order to help companies assess the value of customers. Therefore, customers become active participants in an innovation process and have always been identified as a co-creator of value. Although the topic of customer co-creation value represents an emerging phenomenon in the business ecosystem, extant literature appears largely unexplored, and a recent systematic review is missing. This paper thus aims to bridge the gap by carrying out a systematic literature network analysis. By analyzing the citation network, the keywords co-occurrence, and the global citation score retrieved from Scopus, this document explores how the literature has evolved over time, which papers played a key role in the progress of knowledge, which methodological approaches dominated, and the existence of promising research areas that have been scarcely explored or that have involved scholars in recent years.

The sharing economy concept has been firmly incorporated into various scientific fields and applied broadly in practice. This paper aims to gain a detailed insight into the contemporary intellectual structure of the sharing economy in the fields of economics, business and management. Using a two-stage approach: a critical literature review and social network analysis (SNA), the dominant research niches and under-investigated issues within sharing economy were identified, along with the most influential authors and papers. Author collaboration and citation connection of papers have also been examined. It was concluded that sharing economy knowledge is gradually approaching the stage of maturity bearing in mind the growing number of articles, the presence of emerging research niches, as well as scarcity of approaches directed to purely quantitative analysis. Additionally, it was discovered that despite the study focus on the predefined research field, sharing economy concept exhibit a remarkable level of postdisciplinarity.

Objective The paper conducts a network analysis of the fragmented literature on brand and addiction. Method A thematic map, thematic evolution, word cloud, co-citation analysis, and cooperation networks were utilized to identify brand addiction study trends and topics. Results The data show that marketing and psychiatry have interdisciplinary groupings and multidisciplinary publications. These groups reflect societal changes, particularly the shift from traditional to digital challenges. Fast food addiction is different from alcohol and cigarette addictions due to its ease and extensive marketing. The decline in internet and gambling addiction suggests a shift in priorities. Conclusions This research helps researchers, policymakers, and practitioners in addiction prevention and intervention. The study also understands brand addiction and its effects on psychology, psychiatry, and management by providing insights into emerging topics, thematic maps and evolution of studies, collaboration opportunities, geographical distribution of studies, and more.

The foundational component of RBI's developmental function is financial literacy. Despite the abundance of programmes, financial education remains mostly unexplored. The purpose of this study is to investigate the topic's conceptual framework and offer a comprehensive understanding of financial literacy in India. The scholarly literature on financial literacy in the Indian context is the main focus, and trends, key writers, theme clusters, and the most pertinent and often cited works and authors are identified. With the use of R software, a comprehensive bibliometric study is carried out on 414 Scopus indexed publications, encompassing keyword network analysis and citation analysis through the use of VOS viewer. KEYWORDS: Financial literacy, Bibliometric analysis, R Software, VOS viewer

A B S T R A C T Environmentally friendly vehicles (EFVs) research has witnessed an exponential growth in recent years. In this article, we apply bibliometric network techniques to examine consumers ’ EFVs behavior research based on 662 Web of Science (WoS) and Scopus documents written by 1590 authors representing 61 countries and spanning three decades (1993 – 2023). Results show that the most impactful journals publishing consumers ’ EFVs behavior research are Energy Policy, Transportation Research Part A: Policy and Practice, Journal of Cleaner Production, Transport Policy, Technological Forecasting and Social Change, and Energy Economics . Furthermore, reference publication year spectroscopy (RPYS) was used to identify “ citation classics ” that lay the historical foundation for consumers ’ EFVs behavior research. The thematic evolution analysis reveals that emerging trends in this domain are related to environmental concerns, total cost of ownership, and adoption intention. This study provides valuable insights for future researchers by mapping the evolution of EFVs research over the past three decades, revealing connections among influential authors, key nations, and leading institutions, and uncovering current trends within the broader field of consumers ’ EFVs behavior.

In recent decades, advances in technology have led to the adaptation of business models to the connected era. This has resulted in the modification of the goals of both startup and cooperative models, leading to the emergence of a new hybrid business model combining the two and known as cooperative startups. The present study aims to investigate the evolution, functioning and characteristics of cooperative startups as a potential research area that may be of future relevance due to its potential growth. To this end, a bibliometric analysis using Web of Sciences academic database and VOSViewer software is conducted to identify specific characteristics, opportunities, and challenges that cooperative startups should understand in order to achieve business success. In this regard, a co-citation analysis, bibliographic coupling and keyword concurrency analysis are computed to understand the literature published in this research field to date. The findings of this analysis contribute to the creation of knowledge on cooperative startups identifying 19 future research questions linked to 5 research categories in cooperatives startups: strategy, members of the team, performance, finance and economy and innovation. The results provide insights on the challenges and characteristics of this new business model that is characterized by the management of investments and economy democracy while boosting innovation and handling competence. Finally, theoretical and practical implications are presented.

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This study aims to explore the evolution of the human resources field in Western academia during the 1970s and 1980s, focusing on the trends in research topics across different decades. The analysis utilizes citation co-citation analysis, multivariate statistical analysis, and social network analysis. The research data were drawn from the Web of Science (WoS) database, comprising 1278 documents. By distinguishing between different time periods, the study identifies shifts in the field across two distinct time frames, visualized through multidimensional scaling maps. The results indicate that the 1970s were dominated by seven major research streams, while the 1980s introduced eight research streams, with “human resources” emerging for the first time as a prominent research frontier. The volume of literature, co-citation frequency, and citation counts all increased over time, reflecting the growing vibrancy and expanding scope of research in the field. Although citation co-citation analysis provides objective quantitative insights, issues such as the purpose of citations, the extent to which cited documents influence citing documents, and the varying layers of citation impact may introduce potential errors in the co-citation analysis results.

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Systematic literature reviews (SLRs) advance management theory and practice by synthesizing knowledge in a structured and transparent manner. However, inconsistent reporting of search strategies limits replicability and methodological rigor. To address this gap in reporting standards, the main objective of this article is to explore successful search strategies for SLRs in management research. We further propose a distinction between transparency (conceptual replication) and practical replication to clarify what constitutes a replicable review in this field. We conducted a systematic review of 57 SLRs published in the International Journal of Management Reviews and propose five criteria that search strategy reporting should meet to ensure replicability: (1) provision of a search query, (2) reporting of the query execution date, (3) indication of the search timespan, (4) clear presentation of inclusion/exclusion criteria, and (5) specification of the document sections screened (e.g., title, abstract, full text). Our findings show that most reviews support conceptual replication by providing the search query, timespan, inclusion/exclusion criteria, and screened document sections; however, practical replication remains rare due to missing details – especially the search execution date. To improve future SLRs, we recommend: (1) disclosing the review team’s underlying research paradigms and beliefs to clarify the perspective behind the synthesis, and (2) ensuring diverse team composition from the outset – or, if constrained, explicitly acknowledging such limitations. Ideally, review teams should encompass diverse contexts and paradigms aligned with the scope of the review.

Background: A good search strategy is essential for a successful systematic literature study. Historically, database searches have been the norm, which has later been complemented with snowball searches. Our conjecture is that we can perform even better searches if combining the two search approaches, referred to as a hybrid search strategy. Objective: Our main objective was to compare and evaluate a hybrid search strategy. Furthermore, we compared some alternative hybrid search strategies to assess whether it was possible to identify more cost-efficient ways of searching for relevant primary studies. Method: To compare and evaluate the hybrid search strategy, we replicated an SLR on industry-academia collaboration in software engineering. The SLR used a more traditional approach to searching for relevant articles for an SLR, while the replication was conducted using a hybrid search strategy. Results: In our evaluation, the hybrid search strategy was superior in identifying relevant primary studies. It identified 30 percent more primary studies and even more when focusing only on peer-reviewed articles. To embrace individual viewpoints when assessing research articles and minimise the risk of missing primary studies, we introduced two new concepts, wild cards and borderline articles, when conducting systematic literature studies. Conclusions: The hybrid search strategy is a strong contender for being used when conducting systematic literature studies. Furthermore, alternative hybrid search strategies may be viable if selected wisely in relation to the start set for snowballing. Finally, the two new concepts were judged as essential to cater for different individual judgements and to minimise the risk of excluding primary studies that ought to be included.

In recent years, crisis communication has become increasingly crucial for Indonesian institutions and companies, involving diverse stakeholders, communication forms, and contexts before, during, and after perceived crisis events. This study aimed to map, analyze and compare published studies in both global and national contexts. By adhering to the PRISMA 2020 standards for systematic literature reviews, the study consisted of five phases: (1) research questions, (2) eligibility criteria and sources of information, (3) search selection, (4) process of study selection, and (5) data coding and synthesis from Zotero bibliographic management. The study revealed that academic publications on crisis communications were primarily focused on the Asia and European continents and utilized either qualitative or quantitative research methods. It is shown that the outcome of crisis communication management is mostly around reputation repair, control, and also risk management changes and improvements, which highlight the importance of a corporate reputation in shaping organizational resilience. Future studies should concentrate on proactive crisis communication management strategies since it is essential for mitigating the side effects of the crisis communication itself while emphasizing the role of reputation repair, control, and also risk management changes in fostering stakeholders’ trust.

Abstract This paper explores the critical interplay between entrepreneurial decision-making and information synthesis, offering actionable insights for librarians aiming to support entrepreneurial success. Entrepreneurs synthesize information from diverse sources, including library resources, primary research like customer interviews, and personal experience, to create outputs such as business models and plans. This paper explores the role of librarians and secondary research in fostering entrepreneurs’ skills in organizing and synthesizing information from varied sources. By integrating insights from library and entrepreneurship research, the paper highlights how secondary research and librarians enhance information synthesis capabilities.

Curiosity is a concept studied particularly in psychology. Today, it is used by practitioners in marketing to support strategies of attractiveness, motivation, or to capture attention. This article proposes a multidisciplinary synthesis of this concept through a bibliometric analysis and a literature review. A conceptual framework is proposed for marketing researchers interested in curiosity, offering a new definition of the concept, its antecedents, and its effects. A research agenda prioritized by practitioners can serve as the basis for future work. Curiosity, traditionally explored in psychology, has found its place in marketing as a means for enhancing appeal, motivation, and attention. This article offers a comprehensive multidisciplinary overview of curiosity by combining bibliometric analysis and literature review. It introduces a new framework for marketing researchers interested in curiosity, presenting a fresh definition, its precursors, and outcomes. It also outlines a research agenda shaped by practitioners to guide future inquiries.

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Artificial Intelligence (AI) and Machine Learning (ML) are currently hot topics in industry and business practice, while management-oriented research disciplines seem reluctant to adopt these sophisticated data analytics methods as research instruments. Even the Information Systems (IS) discipline with its close connections to Computer Science seems to be conservative when conducting empirical research endeavors. To assess the magnitude of the problem and to understand its causes, we conducted a bibliographic review on publications in high-level IS journals. We reviewed 1,838 articles that matched corresponding keyword-queries in journals from the AIS senior scholar basket, Electronic Markets and Decision Support Systems (Ranked B). In addition, we conducted a survey among IS researchers (N = 110). Based on the findings from our sample we evaluate different potential causes that could explain why ML methods are rather underrepresented in top-tier journals and discuss how the IS discipline could successfully incorporate ML methods in research undertakings.

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No abstract available

This study presents a bibliometric analysis, using spatial approach, of 943 articles from 2003 to March 2025 showing the growing importance of CDSs in the literature and their role in credit risk management. The Web of Science’s Core Collection database was used for bibliometric mapping. The bibliographic data were grouped and analyzed using VOSviewer to create network visualization maps that included country-wise, document-wise, and source-wise citations analysis, bibliographic coupling, and the co-occurrence of keywords. Subsequently, significant terms were identified through the analyses where risk assessment, risk management, and credit derivatives were found to be the most used keywords. Further, USA turns out to be the country where the most research was published on CDSs with maximum citations, highlighting the growing popularity of this research topic in this region. In addition, bibliographic coupling appears to capture information from 13 clusters formed during the analysis on bibliographically linked documents with their link strength. The bibliometric analysis of the CDS literature illustrates the intellectual framework of research on this topic, traces the progression of the research topic over time, and identifies the areas where this research field might develop in the future.

In the new era of adopting and managing new and robust technologies in banking, the use of blockchain technology has significantly transformed overall banking systems. To add new insights to the body of existing knowledge, the authors conducted a systematic review with bibliographic network mapping to identify and analyse the factors contributing to adopting blockchain in the banking industry. Following the latest protocols of the PRISMA flowchart, this study acknowledged 16 relevant publications from 2590 papers in the databases, namely Scopus, ScienceDirect, Web of Science, and IEEE Xplore. The bibliographic data were grouped and analysed using VOSviewer to create network visualization maps that included citation and co‐citation, bibliographic coupling, co‐authorship, and co‐occurrence of terms. Subsequently, significant terms were identified through the analyses and compared with those found in the 16 relevant papers. The aggregate findings suggest that multiple influencing factors have been recognized and later categorized into three thematic drivers: transparency‐driven security, collaborative interoperability, and organizational infrastructure. The current research provides valuable insights for policymakers, technologists, researchers, consultants, and practitioners of information systems by proposing a technological framework, which will aid in developing tailored strategies to facilitate the sustainable practice of blockchain in the banking industry to a wider extent.

Introduction: Fintech, an acronym for Financial Technology, refers to companies offering financial services through innovative technology, such as web platforms and mobile applications, benefiting individuals and businesses. The evolution of Fintech is characterized by rapid technological development and the proliferation of startups. In Latin America, the sector is growing significantly, with key markets like Mexico and Brazil, offering new opportunities to improve financial inclusion, a fundamental aspect for economic and social development.Objective: To characterize Fintech as an innovative component in the financial sector.Methods: A literature review was conducted by consulting databases such as PubMed and ResearchGate, selecting 17 articles mainly from the last five years. Relevant information was extracted to develop this research.Discussion: Since 2014, Fintech has transformed the global financial sector, gaining regulatory and market prominence. It improves efficiency and accessibility but still depends on trust in intermediaries for electronic payments, posing risks that could be mitigated with technologies like blockchain. Fintech competes and collaborates with traditional banks using technologies such as artificial intelligence. However, its growth presents regulatory and consumer protection challenges. Generational and digital gaps also limit adoption.Conclusions: Fintech is an innovative pillar that enhances accessibility, efficiency, and financial inclusion, especially in Latin America. Regulatory, security, and generational challenges require attention to ensure safe and equitable adoption. Regulation and financial education are key to maximizing benefits and promoting economic and social development

The integration of neuromarketing in digital marketing introduces new insights into consumer behavior by combining neuroscience and marketing principles. However, this approach requires a comprehensive understanding of ethical limitations and the responsible management of consumer data. Attie et al. (2021) state that the ethical issues raised regarding neuromarketing and AI are like the ones raised regarding advertising and marketing in general. The primary ethical challenge lies in direct access to consumers’ cognitive processes, which can intrude on personal privacy and involve the handling of sensitive information. This raises crucial ethical issues, such as privacy protection, potential misuse of data, and the need for transparency within both neuromarketing and digital marketing contexts. This article provides a bibliographic review of empirical studies on these ethical concerns, drawing from impactful scientific journals indexed in the Web of Science (WoS) database. The objective is to propose specific ethical guidelines that can serve as a code of ethics, establishing a framework for ethical conduct in neuromarketing applications within digital marketing.

The research on ‘climate-related financial risks’, still in its infancy, is gaining momentum as businesses and investors are becoming increasingly aware of the heightened risks posed by climate change and the importance of environmentally sustainable activities. The present study brings out a synthesis of the literature on climate risk in the financial sector for the period ranging from 2010 to 2023. Using bibliometric tools such as citation, co-citation, keyword co-occurrence analysis and other network analysis, the study aims to examine the trend of the research domain; influential aspects (sources, affiliations, articles and topics); prominent themes; intellectual and conceptual structures; and collaboration among researchers, universities and countries. The study enhances the understanding of ‘climate-related financial risks’, aiding policymakers, regulators and future researchers in incorporating various elements of the financial system while assessing the impact of climate change on financial stability.

The present study investigated the processes information professionals, working in a business environment, follow to meet business clients’ information needs and particularly their involvement in information synthesis and analysis practices. A combination of qualitative and quantitative data was collected via a survey of 98 information professionals across North America and follow-up interviews with eight Canadian information professionals. It was found that there is an increasing need for value-added services, which incorporate synthesis and analysis but the level of information professionals’ involvement differs depending on a range of factors such as clients’ needs and attitudes, information professionals’ knowledge of the subject area and their length of time working in a particular organization. Information synthesis and analysis in a business context is mostly a collaborative process and principles of analysis are required throughout the entire cycle of information seeking. For the effective transition of information professionals to information synthesists and analysts more effective support may be required to develop a set of essential skills and knowledge.

Background: The primary objective of this study was to examine the advancements in sustainable supplier selection through multi-criteria decision making (MCDM) from the years 2013 to 2022. In the recent past, researchers have carried out a significant amount of research in this field over the course of several years; Methods: a total of 121 scientific publications sourced from the Scopus database were chosen for analysis, employing the bibliometric method and graphical visualization of the VOS viewer application to visually analyze and map research networks and collaboration patterns, aiding in the evaluation of scientific impact and knowledge dissemination; Results: the findings of this study indicate that the research trend in sustainable supplier selection through MCDM witnessed its most significant growth in the year 2019. Researchers predominantly disseminated their scientific findings through articles, accounting for 81% of the publications, followed by conference papers at 14%, and book chapters at 2.5%; Conclusions: the primary area of focus in these studies pertains to decision-making processes involved in sustainable supplier selection. The implications and theoretical contributions derived from this research, coupled with the latest advancements, serve as a foundation for further exploration and development of sustainable supplier selection research through MCDM.

Business problems today are complicated and involve considering numerous dimensions to be weighed against each other, leading to opposing goals that must be compromised on to discover the best solution. Multi-Criteria Decision Making or MCDM plays an essential role in this situation here. MCDM techniques and procedures analyze, score, and select between options that have various conflicting criteria. This systematic review investigates applications of MCDM methods within Management Information Systems (MIS) based on evidence from 40 peer-reviewed articles selected from the Scopus database. Key methods discussed are Analytic Hierarchy Process (AHP), TOPSIS, fuzzy logic-based methods, and Analytic Network Process (ANP). These methods were applied across MIS strategic planning, re-source assignment, risk assessment, and technology selection. The review contributes further by categorizing MCDM application into thematic decision domains, evaluating methodological directions, and mapping the strengths of each method against specific MIS problems. Theoretical guidelines are suggested to align the type of decision with an appropriate MCDM strategy. The study demonstrates how the addition of MCDM enhances MIS capability with data-driven, transparent decision-making power. Implications and directions for future research are presented to guide scholars and practitioners.

Objective: The objective of this research was to analyze the contributions of green marketing as a source of competitive advantage for organizations.   Methodology: The research adopted the systematic review methodology, following the PRISMA guidelines, to analyze articles on sustainable management practices, green marketing and competitive advantage. Search platforms such as Google Acadêmico and Scielo were used, with inclusion criteria for scientific articles in Portuguese published between 2018 and 2023. Exclusion criteria were applied to discard non-pertinent works, resulting in the selection of 7 articles.   Results and data analysis: As a result, it was possible to see that the systematic review highlighted green marketing as a source of competitive advantage for organizations, by integrating environmental concerns into market strategies. This enables differentiation, operational efficiency, and more sustainable production processes. In addition, the adoption of sustainable practices attracts consumers engaged with sustainability, increasing the profitability of production models. Certifications such as ISO 14001 demonstrate a commitment to sustainability, giving competitive advantage. Thus, green marketing favors the company's image and, at the same time, engages consumers in sustainable practices, contributing to the positioning of the organization in the market as a socio-environmentally responsible company.   Conclusion: It is concluded, therefore, that green marketing not only improves the competitiveness of companies, but also fosters a culture of sustainability and preservation of natural resources, representing a significant contribution to organization, society and the environment.

The study focuses on data-driven product selection for Amazon entrepreneurship. Most scholarly work on this domain isolates single levers—keywords, pricing, or competitor benchmarking—yet offers no integrative roadmap that marries market intelligence with operational feasibility. This fragmentation leaves small- and medium-sized sellers ill-equipped to navigate saturated, policy-heavy niches. To bridge this gap, the study formulates and tests a five-stage product-selection framework designed to convert scattered insights into a coherent, data-driven decision flow. We fuse qualitative screening with quantitative modelling: Stage 1 filters categories for structural entry barriers; Stage 2 validates sub-niches via sentiment- and trend-analysis; Stage 3 stress-tests keyword relevance; Stage 4 profiles competitors across lifecycle and compliance variables; and Stage 5 runs a Monte-Carlo-based financial feasibility model that embeds FBA fees, ad-spend volatility, and logistics shocks. Data were captured with Helium 10, Google Trends, and MerchantWords, then triangulated against recent peer-reviewed literature (2019–2025). Sellers relying on ad-hoc intuition face a 2.8-times higher risk of entering over-saturated niches and a 37% lower probability of breakeven within six months. Conversely, the integrative framework improved market-entry accuracy by 46% and increased forecasted profit margins by 18% under median-case scenarios, with sensitivity tests confirming that dynamic cost inputs—rather than keyword volume—drive most forecast error. The study is the first to operationalise a holistic Amazon product-selection protocol that simultaneously accounts for demand signals, competitive intensity, and cash-flow resilience, offering a replicable template for SMEs and groundwork for future AI-augmented recommendation engines.

Environmental problems, combined with a finite supply of fossil fuels, have made the use of renewable energy sources necessary. Biomass is a renewable source of energy that has played a very important role in energy production in recent years. Because there are a number of technologies that can be used to convert biomass into energy, it is important to select the best option. The fact that multiple options are available that need to be evaluated based on a set of decision-making criteria makes this a multicriteria decision-making problem. This paper takes the first step in proposing an evaluation framework and identifying the importance of the relevant decision-making criteria in biofuel production technology selection. To determine the importance of the selection criteria, experts were asked to respond to an online questionnaire based on the best–worst method. The results indicate that air pollution, land use change, and human expertise are the three most important criteria for selecting the best biofuel production technology in our case country, Iran.

The importance of desk research and therefore electronic databases, which have an important place in the management of foreign trade operations, needs more emphasis than in previous periods. This study makes a ranking among alternative markets by using the data obtained from marketing intelligence sources and a methodology for solving decision problems arising in the selection of target market for Turkish iron & steel exporters, and the TOPSIS method, which is one of the multi-criteria decision-making methods. The criteria used in the evaluation of alternative markets included in the study were determined by making use of the literature of international trade theories and the marketing intelligence resources presented within the scope of the study. In addition, a face-to-face interview was made with an iron & steel company exporting the product with the code 7210 in Samsun in the target market selection, and the existing criteria were submitted for approval and the different proposed criteria were included in the analysis. The AHP method was used to determine the criteria weights with the interviewed firm. According to the results of the research, in which 31 different alternatives were listed in the context of a total of 15 criteria; In the ranking of target market alternatives for Turkish iron & steel companies exporting the product with GTIP code 7210, Spain ranks first, Czech ranks second and Belgium ranks third. In line with these results, the research focuses on the top three alternative markets and identifies six different potential customers with three different methods.

: Artificial Intelligence (AI) tools become essential across industries, distinguishing AI-generated from human-authored text is increasingly challenging. This study assesses the coherence of AI-generated titles and corresponding abstracts in anticipation of rising AI-assisted document production. Our main goal is to examine the correlation between original and AI-generated titles, emphasizing semantic depth and similarity measures, particularly in the context of Large Language Models (LLMs). We argue that LLMs have transformed research focus, dissemination, and citation patterns across five selected knowledge areas: Business Administration and Management (BAM), Computer Science and Information Technology (CS), Engineering and Material Science (EMS), Medicine and Healthcare (MH), and Psychology and Behavioral Sciences (PBS). We collected 15 000 titles and abstracts, narrowing the selection to 2000 through a rigorous multi-stage screening process adhering to our study’s criteria. Result shows that there is insufficient evidence to suggest that LLM outperforms human authors in article title generation or articles from the LLM era demonstrates a marked difference in semantic richness and readability compared to those from the pre-LLM. Instead, it asserts that LLM is a valuable tool and can assist researchers in generating titles. With LLM’s assistance, the researcher ensures that the content is reflective of the finalized abstract and core research themes, potentially increasing the impact and accessibility and readability of the academic work.

Competition to get into specialty training is increasingly exponentially, exposing issues with the current selection process. Flaws include biases in portfolio scoring matrices against those at financial disadvantage, incentivising application to multiple specialties, employing solely non-clinical criteria for selection for interview, and inappropriate use of the multi-specialty recruitment assessment. Increasing competition puts greater emphasis on these components in selection, with many potential negative ramifications. Efforts must now be made to address the flaws highlighted. We propose that this starts with incorporating clinical measures, such as multi-source feedback and clinical self-development activities, in portfolio scoring. However, an increased number of available training posts is what is ultimately needed to reduce the intense competition for jobs, take pressure off the current system, and allow its flaws to be addressed.

The selection of appropriate data analysis tools is a critical step for nonprofit organizations seeking to manage and interpret information effectively. This article reviews the practical use of spreadsheets, proprietary software, and open-source platforms, considering affordability, usability, and organizational needs. It explores core features of Microsoft Excel, Google Sheets, and LibreOffice for entry-level management tasks, as well as SPSS, R, and Python for advanced statistical modeling, automation, and predictive analytics. Criteria for tool selection include budget, staff expertise, dataset complexity, system compatibility, and community support. Case studies illustrate how nonprofits use these tools for donor engagement, budgeting, survey evaluation, and automation of repetitive tasks. By aligning tool choice with organizational capacity and applying best practices for training, backups, and standardized workflows, nonprofits can strengthen analytical capabilities, streamline operations, and generate reliable insights that support evidence-based decision-making and accountability.

Among the extrinsic problems faced by the people of Bangladesh, load shedding carries much weight. This study prescribes a solution by offering a feasible alternative source of energy: solar panel. Solar panels are effective in providing an equivalent amount of energy at a reasonable cost compared to existing power plants. Though there is usage of solar panels in Bangladesh, the concept is not commercially prevailed for consumer markets in remote areas. The main objective of the study is to provide a blend of different attributes that consumers may consider for purchasing solar panels. By conducting depth interviews, 3 key attributes have been derived, i.e., capacity, installment, and price; along with different levels. 48 respondents were offered 20 different profiles of attribute levels to put ratings at a 100-point scale. It has been found from the analysis that people mostly prefer 100 watt panels to purchase in 12 installments each for BDT 1500-2000. Yet, corporations in Bangladesh have scope to work on it and commercialize efficiently.

The current business climate has generated considerable uncertainty and disrupted supply chain processes. Suppliers have frequently been identified as the primary source of hazards responsible for supply chain disruptions. Using a strategic approach to supplier selection that prioritizes providers with resilience features, mitigating the risk exposure inherent in supply chains is possible. This study proposes a comprehensive gray multiple-criteria decision making (MCDM) method incorporating resilience attributes to supplier selection. To determine criteria weights, the gray PSI and gray BWM methodologies were used, and to evaluate and prioritize resilient providers, the gray MCRAT and gray COBRA methodologies were applied. According to the results obtained by the suggested methodology, the supplier that demonstrated the greatest degree of resilience was determined to be the provider categorized as SPIR 4. The sequential sequence of the SPIR numbers is as follows: SPIR 5, SPIR 1, SPIR 3, SPIR 2, and SPIR 6. The data demonstrate that the developed approach produced accurate results.

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No abstract available

This article introduces a scientometric investigation regarding the use of Multi-Criteria Decision-Making (MCDM) techniques in the area of portfolio optimization. The study, which employs a carefully selected dataset of 108 scholarly articles that are drawn from the Scopus database, covers the period 2003 to 2026, and maps the intellectual landscape, identifies the leading methodologies, and tracks the trends of migration. We perform a systematic analysis of the occurrence, impact, and application domains of 20 different MCDM methods, which include Data Envelopment Analysis (DEA), the Analytic Hierarchy Process (AHP), TOPSIS and PROMETHEE, among others. The study employs key indicators such as the number of publications, the number of citations, the geographical distribution of authors, as well as the dispersion of journals, to assess the impact and uptake of the various techniques. The analysis demonstrates the dominance of DEA as a method, which is often combined with other MCDM methods and metaheuristics. A trend towards hybridization, which includes the combination of MCDM with fuzzy set theory, machine learning, and evolutionary algorithms, has been recognized as one of the main factors contributing to the innovation of recent techniques. In addition, the study points out the increasing adoption of Environmental, Social, and Governance (ESG) factors and big data analytics into the portfolio selection process. The survey presents a quantitative picture of the domain and provides researchers and practitioners with valuable insights through the identification of the established pillars, the emerging hotspots, and the future research trajectories in the field of MCDM-based portfolio optimization.