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The paper aims to provide an overview of the state-of-the-art of the event industry in the context of digitalization to understand how digital technologies change the event industry and what research topics are the most promising for further exploration.

A bibliometric analysis of the existing body of knowledge on the topic was conducted and the results were visualized using CiteSpace 5.8.R3. A total of 1999 articles and proceeding papers from the Web of Science Core Collection published between 2007 and 2022 were selected for our analysis. Based on the articles and proceeding papers in the Web of Science Core Collection database, we selected a set of publications for our analysis. The data were obtained through specific keywords related to our research topic. The method involves a process of three main stages: data collection, data processing and the bibliometric analysis.

Co-citation analysis indicated that issues of crowd management and tracking human mobility during mass events are important for the event industry and that technologies such as the Internet of Things, special-purpose mobile applications and systems make it easier for an event organizer to handle the issues. The findings demonstrated a weak scientific collaboration between countries in the topic studied and shift of research hotspots to study of satisfaction, motivation and behavioral patterns of events attendees. Based on this analysis, three directions for future research were revealed.

The results should be interpreted in light of our sample, because the analysis was conducted within our sample which has boundaries. We collected data from all categories in the Web of Science Core Collection database, but we considered only articles and proceeding papers as opposed to all possible types of scientific publications and other databases. In the study, we focused on detecting the state-of-the-art of the event industry in the context of digitalization overall. More specific topics that could be analyzed remain, for example, the dependency of digital technologies from the event type, etc.

This study reflects the state-of-the-art of the event industry in the context of digitalization. It provides researchers with key developmental trends in the event industry, which assists them in more deeply understanding the evolution of research hotspots in the field during last 15 years and defining future research agenda. The paper presents an overview of digital technologies used in various types of events and describes the issues and results related to the implementing digital technologies. The results obtained were extremely important, as they can be used by event managers and organizers to enhance customers’ experience during the events.

This study reflects the state-of-the-art of the event industry in the context of digitalization. This is the first attempt to make an overall analysis of scientific papers published in the Web of Science Core Collection on the topic studied without excluding any categories. The search procedure is transparent, and the results can be reproduced in other search fields using the same approach. Based on this analysis, three directions for future research were revealed including technological aspects of online event-based social networks, issues of crowd management and security at mass events and issues of attendees’ acceptance of novel digital technologies.

The health of an economy is heavily dependent on the productivity of the economy's major industries including construction. While most macro-measures of productivity in the USA construction industry indicate a decline, corresponding studies at the individual task level indicate an increase in productivity. Therefore, this paper aims to identify areas where productivity challenges exist and thus provide recommendations for improvement in the construction industry.

A model that relates the way construction projects are executed with the sources of data that inform productivity analyses is developed and presented. This effort/value-flow model informs the data analysis that is performed to determine productivity trends for management and field labor. Further analysis for field labor productivity using field data and management productivity was separately conducted. Management productivity was particularly difficult to gauge, resulting in the use of surrogate measures.

It was observed that while both field labor and management productivities at the industry level have been decreasing, the decrease in management productivity was five times that of field labor productivity. A similar trend was observed for management productivity at the project level.

The primary contribution of this paper to the body of knowledge and industry is the introduction of a holistic analysis of USA construction productivity. Recommendations to improve management productivity include the use of technology, especially project management software.

This study aims to examine the blockchain landscape in supply chain management by drawing insights from academic and industry literature. It identifies the key drivers, categorizes the products involved and highlights the business values achieved by early adopters of blockchain technology within the supply chain domain. Additionally, it explores fingerprinting techniques to establish a robust connection between physical products and the blockchain ledger.

The authors combined the interpretive sensemaking systematic literature review to offer insights into how organizations interpreted their business challenges and adopted blockchain technology in their specific supply chain context; content analysis (using Leximancer automated text mining software) for concept mapping visualization, facilitating the identification of key themes, trends and relationships, and qualitative thematic analysis (NVivo) for data organization, coding and enhancing the depth and efficiency of analysis.

The findings highlight the transformative potential of blockchain technology and offer valuable insights into its implementation in optimizing supply chain operations. Furthermore, it emphasizes the importance of product provenance information to consumers, with blockchain technology offering certainty and increasing customer loyalty toward brands that prioritize transparency.

This research has several limitations that should be acknowledged. First, there is a possibility that some relevant investigations may have been missed or omitted, which could impact the findings. In addition, the limited availability of literature on blockchain adoption in supply chains may restrict the scope of the conclusions. The evolving nature of blockchain adoption in supply chains also poses a limitation. As the technology is in its infancy, the authors expect that a rapidly emerging body of literature will provide more extensive evidence-based general conclusions in the future. Another limitation is the lack of information contrasting academic and industry research, which could have provided more balanced insights into the technology’s advancement. The authors attributed this limitation to the narrow collaborations between academia and industry in the field of blockchain for supply chain management.

Practitioners recognize the potential of blockchain in addressing industry-specific challenges, such as ensuring transparency and data provenance. Understanding the benefits achieved by early adopters can serve as a starting point for companies considering blockchain adoption. Blockchain technology can verify product origin, enable truthful certifications and comply with established standards, reinforcing trust among stakeholders and customers. Thus, implementing blockchain solutions can enhance brand reputation and consumer confidence by ensuring product authenticity and quality. Based on the results, companies can align their strategies and initiatives with their needs and expectations.

In essence, the integration of blockchain technology within supply chain provenance initiatives not only influences economic aspects but also brings substantial social impacts by reinforcing consumer trust, encouraging sustainable and ethical practices, combating product counterfeiting, empowering stakeholders and contributing to a more responsible, transparent and progressive socioeconomic environment.

This study consolidates current knowledge on blockchain’s capacity and identifies the specific drivers and business values associated with early blockchain adoption in supply chain provenance. Furthermore, it underscores the critical role of product fingerprinting techniques in supporting blockchain for supply chain provenance, facilitating more robust and efficient supply chain operations.

This study aims to investigate the structural characteristics, spatial evolution paths and internal driving mechanisms of the knowledge transfer (KT) network in China’s patent-intensive industries (PIIs). The authors' goal is to provide valuable insights to inform policy-making that fosters the development of relevant industries. The authors also aim to offer a fresh perspective for future spatiotemporal studies on industrial KT and innovation networks.

In this study, the authors analyze the patent transfer (PT) data of listed companies in China’s information and communication technology (ICT) industry, spanning from 2010 to 2021. The authors use social network analysis and the quadratic assignment procedure (QAP) method to explore the problem of China’s PIIs KT from the perspectives of technical characteristics evolution, network and spatial evolution and internal driving mechanisms.

The results indicate that the knowledge fields involved in the PT of China’s ICT industry primarily focus on digital information transmission technology. From 2010 to 2021, the scale of the ICT industry’s KT network expanded rapidly. However, the polarization of industrial knowledge distribution is becoming more serious. QAP regression analysis shows that economic proximity and geographical proximity do not affect KT activities. The similarity of knowledge application capacity, innovation capacity and technology demand categories in various regions has a certain degree of impact on KT in the ICT industry.

The current research on PIIs mainly focuses on measuring economic contributions and innovation efficiency, but less on KT in PIIs. This study explores KT in PIIs from the perspectives of technological characteristics, network and spatial evolution. The authors propose a theoretical framework to understand the internal driving mechanisms of industrial KT networks.

This research outlines the technological structure of the entire Japanese manufacturing and service industry using the patent information from research and development (R&D) activities to set R&D goals.

By analyzing the technological development capability of individual companies, the direction of the companies' R&D activities and current state of technological fusion between them can be understood. A group of companies participating in a particular product/service market must have the same technological development capabilities. As a result, the ratio of patent applications by a company to the total number of applications in a technical field will be similar across companies. This study uses the inter-company correlation coefficient of the ratio of patent applications by technical field as an index of technological development capability. A total of 167 major companies covering the major industries of Japan were analyzed. The analysis period was 15 years from 2004 to 2018, and the technical fields were rearranged to 42 fields with reference to the International Patent Classification (IPC)-Technology Concordance used by the World Intellectual Property Organization (WIPO). Considering the fluctuation in patent application opportunities, the number of patent applications was collected for at least three years for the analysis of patent applications by technical field, company and industry.

Examining the entire Japanese industry, the research found that chemicals, ceramics, non-ferrous metals and electrical/electronic equipment act as intermediaries between the respective groups and are linked to the transportation equipment, electrical/electronic equipment and information and communication services industries that are currently driving the Japanese economy. However, the technical connections between these groups are relatively loose. Over the last 15 years, the propagation structure of technical knowledge information has not changed. The progress of technological fusion remains within the scope of commerce and is conditioned by commerce.

Studies focusing on the technological development capability between companies and the technological structure of the Japanese manufacturing and service industries are almost non-existent since 2000 when Japan's economic growth slowed. The analytical methods presented in this research can be applied to individual companies to gain an understanding of technical positions of companies and can be useful for planning a technical environment, business or R&D strategy.

The purpose of this study is to reveal the research trends in guest experiences of service robots in the hospitality industry.

In this study, a review was carried out on the Web of Science (WoS) database with the assistance of bibliometric analysis techniques. Cluster analysis was also employed for this to group important data to determine the relationships and to visualize the areas in which the studies are concentrated. The thematic content analysis method was used to reveal on which customer experiences and on which methods the focuses were.

On the subject of experiences of service robots, the greatest number of publications was in 2021. In terms of country, China has come to the fore in the distribution of publications. As a result of thematic content analysis, it was determined that the leading factor was the main dimension of emotional experience. In terms of sub-dimensions, social interactions attracted more attention. Most of the studies discussed were not based on any theory. Apart from these, the Technology Acceptance Model (TAM), the Service Quality Model (SERVQUAL) and Perceived Value Theory (PVT) were featured more prominently among other studies.

In this study, only the WoS database was reviewed. In future studies, it would be possible to make contextual comparisons by scanning other databases. In addition to quantitative research designs, social dimensions may be examined in depth following qualitative research methods. Thus, various comparisons can be made on the subject with mixed-method research designs. Experimental research designs can also be applied to where customers have experienced human-robot interactions (HRIs).

In the hospitality industry, it is critical to uncover every dimension of guests' robot acceptance. This study, which presents the current situation on this basis, guides future projections for the development of guest experiences regarding service robots in the hospitality industry.

The academic experience of top management team (TMT) has a positive impact on firms' innovation performance. However, existing studies predominantly focus on the educational qualifications and institutional prestige of TMT, failing to comprehensively evaluate whether TMT possess genuine academic experience and the role of academic competence. This article aims to examine whether TMT academic competence has a potential influence on firm innovation performance and to understand the mechanisms behind this relationship.

Using firm-level metrics of Chinese listed firms and TMT scholarly publication data spanning 2000–2021, this paper investigates whether TMT academic competence can promote firms' innovation performance and conducts a moderated mediating effect analysis.

(1) Academic competence of TMT can contribute positively to firms’ innovation performance; (2) university–industry collaboration partially mediates this relationship; (3) the mediating effect is enhanced by cognitive proximity and (4) distance proximity does not diminish the mediating effect.

Outcome of this study can assist academia in further understanding the impacts of TMT on firm innovation and aid government in promoting university–industry collaboration. Simultaneously, it can help firms adjust their TMT selection and training strategies to enhance innovation performance.

This article, as the first to construct an index of academic competence and to explore whether it has an impact on firms' innovation performance and its inherent mechanism, can provide a new research perspective for the study of the impact of TMT's characteristics on firms' innovation.

The main aim of this study is to review different aspects of Industry 5.0 (I5.0) along with Kaizen measures to foster this novel aspect of industrial sustainability. The study makes a comprehensive study to explore the implementation status of I5.0 in industries, key technologies, adoption level in different nations and barriers to I5.0 adoption together with mitigation actions.

To do a systematic study of the literature, the authors have used preferred reporting items for systematic reviews and meta-analysis (PRISMA) methodology to extract articles related to the field of the study.

It has been found that academic literature on the I5.0 is continuously growing as the wheel of time is running. Most of the studies on I5.0 are conceptual-based, and manufacturing and medical industries are the flag bearer in the adoption of this novel aspect. Further, due to I5.0's infancy, many organizations face difficulty to adopt the same due to financial burden, resistive nature, a well-designed standard for cyber-physical systems (CPS) and an effective mechanism for human–robot collaboration. Further studies also provide avenues for future research in terms of the identification of collaborative mechanisms between machines and wells, the establishment of different standards for comparison and the development of I5.0-enabled models for different industrial domains.

The study is the first of its kind that reviews different facets of I5.0in conjunction with Kaizen's measures and application areas and provides avenues for future research to improve an organization's environmental and social sustainability.

Digital transformation (DT) innovation is a monumental contribution that has had a profound effect on several worldwide industries. The aim of this research is to evaluate the current and future trends in DT specifically focusing in construction industry.

This study adopts a qualitative analysis approach grounded on descriptive and bibliometric analyses. In total, 283 papers from Scopus between January 2015 and April 2023 were retrieved in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) review methodology. This study examines the publishing trends, most productive nation, university, publications and authors. Keyword co-occurrence analysis and thematic evolution were analyzed through Vosviewer and Biblioshiny.

The results illustrate a growing desire to use digital technologies in the construction industry, which shows the topic's power and expanding popularity. This research reveals various emerging themes based on technology usage in construction sector. Out of 14 themes, occupational health and safety, mass customization, virtual reality and artificial intelligence were identified as isolated themes. Further, this study elaborates the difficulties encountered by the construction industry while employing digital technologies and examines the interrelationships among various keywords in DT and reveals the paradoxes and hotspots.

This research adds to the body of literature as it identifies the research areas and gaps in the existing DT domain in construction industry. The integration of technology in this sector has an intense positive future vision as various subareas have immense potential for technology application.

The COVID-19 pandemic severely impacted tourism, and the hotel and restaurant industry was the most affected sector, which faced issues related to business uncertainty and unemployment during the crisis. The analysis of recovery time and the influence factors is significant to support policymakers in developing an effective response and mitigating the risks associated with the tourism crisis. This study aims to investigate numerous factors affecting the recovery time of the hotel and restaurant sector after the COVID-19 crisis by using survival analysis.

This study uses the quarterly value added with the observation time from quarter 1 in 2020 to quarter 1 in 2023 to measure the recovery status. The recovery time refers to the number of quarters needed for the hotel and restaurant sector to get value added equal to or exceed the value added before the crisis. This study applies survival models, including lognormal regression, Weibull regression, and Cox regression, to investigate the effect of numerous factors on the hazard ratio of recovery time of hotels and restaurants after the COVID-19 crisis. This model accommodates all cases, including “recovered” and “not recovered yet” areas.

The empirical findings represented that the Cox regression model stratified by the area type fit the data well. The priority tourism areas had a longer recovery time than the non-priority areas, but they had a higher probability of recovery from a crisis of the same magnitude. The size of the regional gross domestic product, decentralization funds, multiplier effect, recovery time of transportation, and recovery time of the service sector had a significant impact on the probability of recovery.

This study contributes to the literature by examining the recovery time of the hotel and restaurant sector across Indonesian provinces after the COVID-19 crisis. Employing survival analysis, this study identifies the pivotal factors affecting the probability of recovery. Moreover, this study stands as a pioneer in investigating the multiplier effect of the regional tourism and its impact on the speed of recovery.