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This study collected the bibliographic data of 2034 journal articles published in 2000–2021 from Web of Science (WoS) core collection database and adopted two bibliometric analysis methods, namely historiography and keyword co-occurrence, to identify the evolution trend of construction risk management (CRM) research topics.

CRM has been a key issue in construction management research, producing a big number of publications. This study aims to undertake a review of the global CRM research published from 2000 to 2021 and identify the evolution of the research topics relating to CRM.

This study found that risk analysis methods have shifted from simply ranking risks in terms of their relative importance or significance toward examining the interrelationships among risks, and that the objects of CRM research have shifted from generic construction projects toward specified types of construction projects (e.g. small projects, underground construction projects, green buildings and prefabricated projects). In addition, researchers tend to pay more attention to an individual risk category (e.g. political risk, safety risk and social risk) and integrate CRM into cost, time, quality, safety and environment management functions with the increasing adoption of various information and communication technologies.

This study focused on the journal articles in English in WoS core collection database only, thus excluding the publications in other languages, not indexed by WoS and conference proceedings. In addition, the historiography focused on the top documents in terms of document strength and thus ignored the role of the documents whose strengths were a little lower than the threshold.

This review study is more inclusive than any prior reviews on CRM and overcomes the drawbacks of mere reliance on either bibliometric analysis results or subjective opinions. Revealing the evolution process of the CRM knowledge domain, this study provides an in-depth understanding of the CRM research and benefits industry practitioners and researchers.

This study aims to explore the dissemination and evolutionary path of online public opinion from a crisis management perspective. By clarifying the influencing factors and dynamic mechanisms of online public opinion dissemination, this study provides insights into attenuating the negative impact of online public opinion and creating a favorable ecological space for online public opinion.

This research employs bibliometric analysis and CiteSpace software to analyze 302 Chinese articles published from 2006 to 2023 in the China National Knowledge Infrastructure (CNKI) database and 276 English articles published from 1994 to 2023 in the Web of Science core set database. Through literature keyword clustering, co-citation analysis and burst terms analysis, this paper summarizes the core scientific research institutions, scholars, hot topics and evolutionary paths of online public opinion crisis management research from both Chinese and international academic communities.

The results show that the study of online public opinion crisis management in China and internationally is centered on the life cycle theory, which integrates knowledge from information, computer and system sciences. Although there are differences in political interaction and stage evolution, the overall evolutionary path is similar, and it develops dynamically in the “benign conflict” between the expansion of the research perspective and the gradual refinement of research granularity.

This study summarizes the research results of online public opinion crisis management from China and the international academic community and identifies current research hotspots and theoretical evolution paths. Future research can focus on deepening the basic theories of public opinion crisis management under the influence of frontier technologies, exploring the subjectivity and emotionality of web users using fine algorithms and promoting the international development of network public opinion crisis management theory through transnational comparison and international cooperation.

This study aims to map the conceptual structure and evolution of the recent scientific literature published in marketing journals to identify the areas of interest and potential future research directions.

The 100 most influential marketing academic papers published between 2018 and 2022 were identified and scrutinized through a bibliometric analysis.

The findings further upheld the critical role of emerging technologies such as Blockchain in marketing and identified artificial intelligence and live streaming as emerging trends, reinforcing the importance of data-driven marketing in the discipline.

The data collection included only the 100 most cited documents between 2018 and 2022, and data were limited only to Scopus database and restrained to the Scopus-indexed marketing journals. Moreover, documents were selected based on the number of citations. Nevertheless, the data set may still provide significant insight into the marketing field.

Influential authors, papers and journals identified in this study will facilitate future literature searches and scientific dissemination in the field. This study makes an essential contribution to the marketing literature by identifying hot topics and suggesting future research themes. Also, the important role of emerging technologies and the shift of marketing toward a more data-driven approach will have significant practical implications for marketers.

To the best of the authors’ knowledge, this is the first comprehensive study offering a general overview of the leading trends and researchers in marketing state-of-the-art research.

Existing tourism review articles have limited review topics and cover a relatively short period. This review paper aims to extend the coverage of the previous literature and enhances the completeness of tourism-related studies to provide comprehensive tourism-related literature from 1945 (World War II onward) to 2022. Specifically, this paper reveals the major research themes present in published tourism research during this time period and highlights the evolution of tourism research from the preliminary phase, the transversal phase, to the growth phase.

The present study visualizes tourism research through networks of coauthors and their countries and regions, cocitation analysis of keywords and explores the thematic evolution of tourism research after the World War II (i.e., 1945–2022) from Web of Science and Google Scholar through bibliometric analysis.

Findings reveal that the themes of tourism research in the past years can be divided into seven major research themes. The tourism research evolution from World War II to 2022 can be categorized into three stages: preliminary (1945–1970), transversal (1971–2004) and growth (2005–2022). In addition, the research themes of tourism are not static but evolve according to the dynamics of the society and the industry, and that seven main research themes have been formed, namely, “heritage tourism,” “medical tourism,” “adventure tourism,” “dark tourism,” “sustainable tourism,” “rural tourism” and “smart tourism.”

The present study expands and refines the comprehensive literature in tourism research, as well as reveals the trends and dynamics in tourism research through network analysis and thematic evolution research methods.

现有的旅游评论文章在审查主题方面有限, 并且涵盖的时间相对较短。本综述文章扩展了先前文献的涵盖范围, 增强了与旅游相关研究的完整性, 提供了从1945年（第二次世界大战之后）到2022年的全面旅游相关文献。具体而言, 本文揭示了此期间发表的旅游研究中的主要研究主题, 并突出了旅游研究从初步阶段、横向阶段到增长阶段的演变。

本研究通过共同作者及其国家的网络、关键词的共同引用分析, 将旅游研究可视化, 并探索二战后旅游研究的主题演变。本研究通过文献计量学分析, 将 Web of Science (WoS) 和 Google Scholar 中的旅游研究（即 1945–2022 年）可视化。

研究结果显示, 过去几年的旅游研究主题可分为七大研究主题。从第二次世界大战到 2022 年的旅游研究演变可分为三个阶段：初步阶段（1945–1970 年）、横向阶段（1971–2004 年）和成长阶段2005–2022 年）。此外, 旅游的研究主题并不是静态的, 而是根据社会和行业的动态而演变, 形成了七个主要研究主题, 即“遗产旅游”、“医疗旅游”、“冒险旅游”、“黑暗旅游”、“可持续旅游”、“乡村旅游”和“智慧旅游”。

本研究通过网络分析和主题演变研究方法扩展和完善了旅游研究方面的综合文献, 并揭示了旅游研究的趋势和动态。

Los artículos de revisión existentes sobre turismo tienen temas de revisión limitados y cubren un periodo relativamente corto. Este artículo de revisión amplía la cobertura de la bibliografía anterior y mejora la exhaustividad de los estudios relacionados con el turismo para ofrecer una bibliografía exhaustiva sobre el turismo desde 1945 (Segunda Guerra Mundial en adelante) hasta 2022. En concreto, este documento revela los principales temas de investigación presentes en la investigación turística publicada durante este periodo de tiempo y destaca la evolución de la investigación turística desde la fase preliminar, la fase transversal, hasta la fase de crecimiento.

El presente estudio visualiza la investigación turística a través de redes de coautores y sus países y regiones, análisis de co-citación de palabras clave, y explora la evolución temática de la investigación turística después de la Segunda Guerra Mundial (es decir, 1945–2022) a partir de Web of Science y Google Scholar mediante análisis bibliométricos.

Los resultados revelan que los temas de la investigación turística de los últimos años pueden dividirse en siete grandes temas de investigación. La evolución de la investigación turística desde la Segunda Guerra Mundial hasta 2022 puede clasificarse en tres etapas: preliminar (1945–1970), transversal (1971–2004) y de crecimiento (2005–2022). Además, los temas de investigación del turismo no son estáticos, sino que evolucionan según la dinámica de la sociedad y de la industria, y que se han formado siete temas principales de investigación, a saber: “turismo patrimonial”, “turismo médico”, “turismo de aventura”, “turismo oscuro”, “turismo sostenible”, “turismo rural” y “turismo inteligente”.

El presente estudio amplía y perfecciona la amplia bibliografía existente en el campo de la investigación turística, además de revelar las tendencias y la dinámica de la investigación turística mediante el análisis de redes y los métodos de investigación de evolución temática.

This study aims to analyze review research in hospitality, identifying the structure and most recent developments in current hospitality review studies while providing exploratory insights for future research in this research area.

Using bibliometric analysis, content analysis and a quantitative systematic literature review, this study provides a comprehensive review and critical analysis of 128 review studies published in leading hospitality journals (International Journal of Contemporary Hospitality Management, International Journal of Hospitality Management and Journal of Hospitality Marketing and Management).

This paper presents a comprehensive and in-depth discussion based on the title, journal source, author contribution, year of publication, sample size, selected period, database selection, methodology, data collection methods, themes, regional selection, keywords, abstracts and results of the hospitality review studies analyzed. The findings provide new insights to advance the theoretical and practical implications of review studies in hospitality.

This research provides critical insights for both hospitality review studies and academic and industry hospitality personnel.

As a pioneering study in research on review studies, the results of this paper focus not only on a systematic overview and assessment of recent hospitality review works but also on the future agenda of hospitality and review studies.

With the increasing number of Web services, correct and efficient classification of Web services is crucial to improve the efficiency of service discovery. However, existing Web service classification approaches ignore the class overlap in Web services, resulting in poor accuracy of classification in practice. This paper aims to provide an approach to address this issue.

This paper proposes a label confusion and priori correction-based Web service classification approach. First, functional semantic representations of Web services descriptions are obtained based on BERT. Then, the ability of the model is enhanced to recognize and classify overlapping instances by using label confusion learning techniques; Finally, the predictive results are corrected based on the label prior distribution to further improve service classification effectiveness.

Experiments based on the ProgrammableWeb data set show that the proposed model demonstrates 4.3%, 3.2% and 1% improvement in Macro-F1 value compared to the ServeNet-BERT, BERT-DPCNN and CARL-NET, respectively.

This paper proposes a Web service classification approach for the overlapping categories of Web services and improve the accuracy of Web services classification.

The potential of vehicle ad hoc networks (VANETs) to improve driver and passenger safety and security has made them a hot topic in the field of intelligent transportation systems (ITSs). VANETs have different characteristics and system architectures from mobile ad hoc networks (MANETs), with a primary focus on vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. But protecting VANETs from malicious assaults is crucial because they can undermine network security and safety.

The black hole attack is a well-known danger to VANETs. It occurs when a hostile node introduces phony routing tables into the network, potentially damaging it and interfering with communication. A safe ad hoc on-demand distance vector (AODV) routing protocol has been created in response to this issue. By adding cryptographic features for source and target node verification to the route request (RREQ) and route reply (RREP) packets, this protocol improves upon the original AODV routing system.

Through the use of cryptographic-based encryption and decryption techniques, the suggested method fortifies the VANET connection. In addition, other network metrics are taken into account to assess the effectiveness of the secure AODV routing protocol under black hole attacks, including packet loss, end-to-end latency, packet delivery ratio (PDR) and routing request overhead. Results from simulations using an NS-2.33 simulator show how well the suggested fix works to enhance system performance and lessen the effects of black hole assaults on VANETs.

All things considered, the safe AODV routing protocol provides a strong method for improving security and dependability in VANET systems, protecting against malevolent attacks and guaranteeing smooth communication between cars and infrastructure.

Misinformation surrounding the Sustainable Development Goals (SDGs) has contributed to the formation of misbeliefs among the public. The purpose of this paper is to investigate public sentiment and misbeliefs about the SDGs on the YouTube platform.

The authors extracted 8,016 comments from YouTube videos associated with SDGs. The authors used a pre-trained Python library NRC lexicon for sentiment and emotion analysis, and to extract latent topics, the authors used BERTopic for topic modeling.

The authors found eight emotions, with negativity outweighing positivity, in the comment section. In addition, the authors identified the top 20 topics discussing various SDGs and SDG-related misbeliefs.

The authors reported topics related to public misbeliefs about SDGs and associated keywords. These keywords can be used to formulate social media content moderation strategies to screen out content that creates these misbeliefs. The result of hierarchical clustering can be used to devise and optimize response strategies by governments and policymakers to counter public misbeliefs.

This study represents an initial endeavor to gain a deeper understanding of the public’s misbeliefs regarding SDGs. The authors identified novel misbeliefs about SDGs that previous literature has not studied. Furthermore, the authors introduce an algorithm BERTopic for topic modeling that leverages transformer architecture for context-aware topic modeling.

Microribbon with meander type based on giant magnetoimpedance (GMI) effect has become a research hot spot due to their higher sensitivity and spatial resolution. The purpose of this paper is to further optimize the line spacing to improve the performance of meanders for sensor application.

The model of GMI effect of microribbon with meander type is established. The effect of line spacing (Ls) on GMI behavior in meanders is analyzed systematically.

Comparison of theory and experiment indicates that decreasing the line spacing increases the negative mutual inductance and a consequent increase in the GMI effect. The maximum value of the GMI ratio increases from 69% to 91.8% (simulation results) and 16.9% to 51.4% (experimental results) when the line spacing is reduced from 400 to 50 µm. The contribution of line spacing versus line width to the GMI ratio of microribbon with meander type was contrasted. This behavior of the GMI ratio is dominated by the overall negative contribution of the mutual inductance.

This paper explores the effect of line spacing on the GMI ratio of meander type by comparing the simulation results with the experimental results. The superior line spacing is found in the identical sensing area. The findings will contribute to the design of high-performance micropatterned ribbon with meander-type GMI sensors and the establishment of a ribbon-based magnetic-sensitive biosensing system.

Vehicle allocation problems (VAPs), which are frequently confronted in many transportation activities, primarily including but not limited to full truckload freight transportation operations, induce a significant economic impact. Despite the increasing academic attention to the field, literature still fails to match the needs of and opportunities in the growing industrial practices. In particular, the literature can grow upon the ideas on sustainability, Industry 4.0 and collaboration, which shape future practices not only in logistics but also in many other industries. This review has the potential to enhance and accelerate the development of relevant literature that matches the challenges confronted in industrial problems. Furthermore, this review can help to explore the existing methods, algorithms and techniques employed to address this problem, reveal directions and generate inspiration for potential improvements.

This study provides a literature review on VAPs, focusing on quantitative models that incorporate any of the following emerging logistics trends: sustainability, Industry 4.0 and logistics collaboration.

In the literature, sustainability interactions have been limited to environmental externalities (mostly reducing operational-level emissions) and economic considerations; however, emissions generated throughout the supply chain, other environmental externalities such as waste and product deterioration, or the level of stakeholder engagement, etc., are to be monitored in order to achieve overall climate-neutral services to the society. Moreover, even though there are many types of collaboration (such as co-opetition and vertical collaboration) and Industry 4.0 opportunities (such as sharing information and comanaging distribution operations) that could improve vehicle allocation operations, these topics have not yet received sufficient attention from researchers.

The scientific contribution of this study is twofold: (1) This study analyses decision models of each reviewed article in terms of decision variable, constraint and assumption sets, objectives, modeling and solving approaches, the contribution of the article and the way that any of sustainability, Industry 4.0 and collaboration aspects are incorporated into the model. (2) The authors provide a discussion on the gaps in the related literature, particularly focusing on practical opportunities and serving climate-neutrality targets, carried out under four main streams: logistics collaboration possibilities, supply chain risks, smart solutions and various other potential practices. As a result, the review provides several gaps in the literature and/or potential research ideas that can improve the literature and may provide positive industrial impacts, particularly on how logistics collaboration may be further engaged, which supply chain risks are to be incorporated into decision models, and how smart solutions can be employed to cope with uncertainty and improve the effectiveness and efficiency of operations.