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The study aims to profile the scientific retractions in the top five global universities and provide descriptive statistics on specific subjects.

The data for reasons behind retractions is manually extracted from the Retraction Watch Database. The top five global universities according to the Times Higher Education global ranking of 2024 are selected for this study.

The study found that Stanford University emerged with the highest number of retractions in the assessment across institutions in the field of basic life sciences and health sciences. Notably, the predominant reasons for these retractions were identified, with “unreliable results” being the most prevalent, accounting for 53 retractions. Following closely was the category of “errors in results and/or conclusions”, contributing to 51 retractions. MIT has the longest time between publication and retraction of any subject group, with an average of 1,701 days.

This study has some limitations, as it only analysed the retractions of the top five global universities.

The study provides a comprehensive analysis of retractions in academic publishing, focusing on reasons, time gaps, article types and accessibility categories across prestigious universities. The paper underscores the critical role of retractions in maintaining the integrity of scientific literature, emphasizing the importance of transparent correction and responsible peer review to ensure the reliability and trustworthiness of published research. Results show that common reasons for retractions include duplication, fake peer review and plagiarism, underlining the need for ethical research standards.

The study aims to promote the use of qualitative methods in service research by investigating how these methods are reported in service journals, how the level of reporting has evolved and whether methodological reporting influences the downloads or citations received by qualitative articles.

Methodological reporting practices were identified through content analysis of 318 qualitative articles published in three major service research journals and comparison with prior methodological literature. Regression analysis was used to test how the level of methodological reporting influences article downloads and citations.

The study identifies 29 reporting practices related to 9 key methodological reporting areas. The overall level of methodological reporting in published qualitative articles has increased over time. While differences in the level of reporting between service journals persist, they are narrowing. The level of methodological reporting did not influence downloads or citations of qualitative articles.

Service scholars using qualitative methods should pay attention to methodological reporting as it can improve the chances of being published. Factors such as theoretical contributions are likely to have a greater influence on article impact than methodological reporting.

No prior study has explored methodological reporting practices across different qualitative methodologies or how reporting influences article impact. For authors, reviewers and editors, the study provides an inventory of reporting practices relevant for evaluating qualitative articles, which should lower barriers for qualitative methods in service research by providing practical guidelines on what to focus on when reporting and assessing qualitative research.

The purpose of this study is to examine research on academic libraries and the social web published from July 1, 2019, to June 30, 2023.

The article search and filtering procedures mirrored those of Choi and Harper (2020) and Carlsson (2015), resulting in a total sample size of 93 articles. These articles underwent examination based on the same eight variables (i.e. journal outlet, research theme, publication year, social web type, method, keyword, study participant type and study country) as employed by Choi and Harper (2020) and Carlsson (2015), with the addition of two new variables (i.e. research purpose and the impact of COVID-19).

The research article volume has consistently maintained a stable trend. A notable difference from Choi and Harper (2020) and Carlsson (2015) is the rise of “user perspectives” as the second most prevalent theme. Unlike Choi and Harper (2020), the “survey” method is predominant. Many research purposes, excluding “marketing and promotion,” lack attention. Additionally, there’s a dearth of studies on the impact of COVID-19.

The findings from the study not only offer a snapshot of the current research landscape on academic libraries and their engagement with the social web but also offer insights for future scholarly endeavors.

There is a limited effort in exploring the recent literature regarding the role of the social web in academic libraries. This study serves as a valuable guide for contributing to this dynamic research stream and provides various up-to-date implications.

Foreign subsidiaries of multinational enterprises (MNEs) operate in complex and competitive international environments, implement market and non-market strategies, manage resources and value-added activities and contribute to the overall performance of their parent firms. Thus, the research question on the determinants of MNE foreign subsidiaries’ performance is of interest to managers and academic researchers. The empirical literature has flourished over the recent decades; however, the domains are fragmented, and the findings are inclusive. The purpose of this study is to systematically review, analyse and synthesize the empirical articles in this area, identify research gaps and suggest a future research agenda.

This study uses the qualitative content analysis method in reviewing and analysing 150 articles published in 24 scholarly journals during the period 2000–2023.

The literature uses a variety of theoretical perspectives to examine the key determinants of subsidiary performance which can be grouped into six major domains, namely, home- and host country-level factors; distance between home and host countries; the characteristics of parent firms and of subsidiaries; and governance mechanisms (the establishment modes and ownership strategy, subsidiary autonomy and the use of home country expatriates for transferring knowledge from the headquarters and controlling foreign subsidiaries). A range of objective and subjective indicators are used to measure subsidiary performance. Yet, the research shows a lack of broader integration of theories and presents inconsistent theoretical predictions, inconclusive empirical findings and estimation bias, which hinder our understanding of how the determinants independently and jointly shape the performance of foreign subsidiaries.

This study provides a comprehensive, nuanced and systematic review that synthesizes and clarifies the determinants of subsidiary performance, offers deeper insights from both theoretical, methodological and empirical aspects and proposes some promising avenues for future research directions.

Understanding and mitigating stock price crash risk is vital for investors and regulators to ensure financial market stability. This study aims to unveil significant research trends and opportunities.

This study adopts the bibliometric and systematic review approach to analyse 485 Scopus-indexed articles through citation, keyword co-occurrence, bibliographic coupling, and publication analyses and delve into the depth of crash risk literature.

This bibliometric review reveals not only a surge in crash risk publications over the last decade but also delineates several emerging thematic threads within this domain. We identify seven distinct themes that have gained prominence in recent literature: bad news hoarding, board characteristics, capital market factors, corporate policies, ownership impact, corporate governance, and external environmental influences on crash risk. This thematic analysis provides a comprehensive overview of the evolving landscape of crash risk research and underscores the multifaceted nature of factors contributing to market instability.

This study makes a substantial contribution by furnishing a thorough examination of existing studies, pinpointing areas where knowledge is lacking, and shedding light on emerging trends and debates within the crash risk literature.

This study identifies current research trajectories and propels future exploration into agency perspectives, audit quality, and corporate disclosures within crash risk literature.

The trend among the financial investors to integrate cryptocurrencies, the very first completely digital assets, in their investment portfolio, has increased during the last decade. Even though cryptocurrencies share certain common characteristics with other investment products, they have their own distinct characteristic features, and the behavior of this asset class is currently being studied by the research scholars interested in this domain.

Using the text mining approach, this article examines research trends in the field of cryptocurrencies to identify prospective research needs. To narrow down to ten topics, the abstracts and the indexed keywords of 1,387 research publications on cryptocurrency, blockchain and Bitcoins published between 2013 and 2022 were analyzed using the topic modeling technique and Latent Dirichlet allocation (LDA).

The findings show a wide range of study trends on various aspects of cryptocurrencies. In the recent years, there have been lots of research and publications on the topics such as cryptocurrency markets, cryptocurrency transactions and use of blockchain in transactions and security of Bitcoin. In comparison, topics such as use of blockchain in fintech, cryptocurrency regulations, blockchain smart contract protocols and legal issues in cryptocurrency have remained relatively underexplored. After using the LDA, this paper further analyzes the significance of each topic, future directions of individual topics and its popularity among researchers in the discussion section.

While similar studies exist, no other work has used topic modeling to comprehensively analyze the cryptocurrencies literature by considering diverse fields and domains.

Recent emerging information technologies like digital twin (DT) provide new concepts and transform information management processes in the architecture, engineering and construction (AEC) industry. Although numerous articles are pertinent to DT applications, existing research areas and potential future directions related to the state-of-the-art DT in project operation and maintenance (O&M) are yet to be studied. Therefore, this paper aims to review the state-of-the-art research on DT applications in project O&M.

The current review adopted four methodological steps, including literature search, literature selection, science mapping analysis and qualitative discussion to gain a deeper understanding of DT in project O&M. The impact and contribution of keywords and documents were examined from a total of 444 journal articles retrieved from the Scopus database.

Five mainstream research topics were identified, including (1) DT-based artificial intelligence technology for project O&M, (2) DT-enabled smart city and sustainability, (3) DT applications for project asset management, (4) Blockchain-integrated DT for project O&M and (5) DT for advanced project management. Subsequently, research gaps and future research directions were proposed.

This study intends to raise awareness of future research by summarizing the current DT development phases and their impact on DT implementation in project O&M among researchers and practitioners.

This paper undertakes a structured literature review to analyse the literature on performance management and measurement (PMM) in universities over the last four decades. Over that time, PMM has emerged as an influential force in universities that impacts their operations and redefines their identity.

A structured literature review approach was used to analyse a sample of articles on PMM research from a broad range of disciplines over four decades. This was undertaken to understand the impacts of PMM practices on universities, highlight changes over time and point to avenues for future research.

The analysis highlights the fact that research on PMM in universities has grown significantly over the 40 years studied. We provide an overview of published articles over four decades regarding content, themes, theories, methods and impacts. We provide an empirical basis for discussing past, present and future university PMM research. The future research avenues offer multiple provocations for scholars and policymakers, for instance, PMM implementation strategies and relationships with various government programs and external evaluation and the role of different actors, particularly academics, in shaping PMM systems.

Unlike a traditional literature review, the structured literature review method can develop insights into how the field has changed over time and highlight possible future research. The sample for this literature review differs from previous reviews in covering a broad range of disciplines, including accounting.

This comprehensive review study aims to analyze the current state of technology adoption (TA) within the textile industry, with a particular focus on the economic, environmental, and social dimensions.

Twenty-four articles from the Scopus database, spanning from January 2015 to March 2024, were meticulously selected for analysis. The review uses a qualitative approach, synthesizing diverse perspectives to provide a holistic understanding of TA in the textile sector.

The review highlights a noticeable lag in the adoption of new technologies, particularly in developing nations like India, within the textile industry. Despite significant technological advancements, there remains a gap between innovation and implementation. Sustainable approaches to mitigate environmental impacts emerge as a key focus, underscoring the need for operational enhancements and policy interventions.

The study’s reliance on articles from the SCOPUS database presents a limitation, potentially overlooking relevant research from other sources.

Practitioners in the textile industry can benefit from the review’s insights by understanding the importance of integrating technological advancements sustainably. By leveraging innovative solutions and collaborating with policymakers, firms can enhance operational efficiency while minimizing environmental impacts, thus ensuring long-term competitiveness.

Efforts to advance TA in the textile industry have significant social implications, including job creation, improved working conditions and reduced environmental harm.

Study addressed the insights for policymakers, industry practitioners and researchers seeking to drive technological innovation while addressing socio-economic and environmental challenges.

An emerging research stream focuses on the place-based ecosystems where artificial intelligence (AI) innovations emerge and develop. This literature builds on the contextual turn in management research and, specifically, work on entrepreneurial ecosystems. However, as a nascent research area, the literature on AI and entrepreneurial ecosystems is fragmented across academic and practitioner boundaries and unconnected disciplines because of disparate and ill-defined concepts. As a result, the literature is disorganized and its main insights are latent. The purpose of this paper is to synthesize research on AI ecosystems and identify the main insights.

We first consolidate research on the “where” of AI innovation through a scoping review. To address the fragmentation in the literature and understand how entrepreneurial ecosystems are associated with AI innovation, we then use content analysis to explore the literature.

We identify the main characteristics of the AI and ecosystems literature and the key dimensions of “AI entrepreneurial ecosystems”: the local actors and factors in geographic territories that are coordinated to support the creation and development of AI technologies. We clarify the relationships among AI technologies and ecosystem dimensions and uncover the latent themes and underlying structure of research on AI entrepreneurial ecosystems.

We increase conceptual precision by introducing and defining an umbrella concept—AI entrepreneurial ecosystem—and propose a research agenda to spur further insights. Our analysis contributes to research at the intersection of management, information systems, and entrepreneurship and creates actionable insights for practitioners influenced by the geographic agglomeration of AI innovation.