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This paper aims to systematically find the main research differences and similarities between social media and social networks in marketing research using the bibliometric perspective and provides suggestions for firms to improve their marketing strategies effectively.

The methods of co-word analysis and network analysis have been used to analyze the two research fields of social media and social networks. Specifically, this study selects 2,424 articles from 27 marketing academic journals present in the database Web of Science, ranging from January 1, 1996 to August 8, 2020.

The results show that social networks and social media are both research hotspots within the discipline of marketing research. The different intimacy nodes of social networks are more complex than social media. Additionally, the research scope of social networks is broader than social media in marketing research as shown by the keyword co-occurrence analysis. The overlap between social media and social networks in marketing research is reflected in the strong focus on their mixed mutual effects.

This paper explores the differences and similarities between social networks and social media in marketing research from the bibliometric perspective and provides a developing trend of their research hotspots in social media and social networks marketing research by keyword co-occurrence analysis and cluster analysis. Additionally, this paper provides some suggestions for firms looking to improve the efficiency of their marketing strategies from social and economic perspectives.

This paper aims to provide a review of hotel performance within the hospitality and tourism research domain. The authors use network analysis to examine two research questions. The first relates to ascertaining general trends within the hotel performance literature, and the second focuses on identifying the salient streams and sub-topics.

Articles were selected according to three criteria: keywords, journals and year of publication. The analysis embraces 20 years (1996-2015). These choices assure a wide coverage of the literature. Using these three criteria, the sample includes 1,155 papers. For the analysis, the authors created a network of papers designated as nodes, and the citations among the papers as links. A network approach recognizes the internal structure of the network by identifying groups of nodes (papers) that are more densely connected between themselves than to other nodes within the network (modules, clusters or communities).

The authors found 761 papers that were “connected” studies within the network. By contrast, 34 per cent of the sample (394 papers) consists of “unconnected” studies. Excluding outliers, the net sample was 734 articles. The authors identify 14 clusters, which they break down into several sub-topics. The authors conclude by providing some conclusions regarding trends and future research directions. With regards to salient topics, cross-citation and network analysis provide a detailed picture of where the literature comes from and where it currently stands. Conclusions are articulated at the theoretical and empirical levels.

Compared with previous hotel performance reviews, the approach followed by this study enables the discovery of an analytical research map, which is able to identify both clusters and sub-topics populating each segment. Researchers are able to position their work and identify issues that are in growth and decline.

The purpose of this paper is to conduct a structured literature review using advanced bibliometric tools to understand the existing knowledge base, understand the trends in omni-channel (OC) research and identify emerging research topics.

More than 500 articles selected through a keyword combination search from reputed databases of peer-reviewed academic sources from period 2009–19 are analyzed for the purposes of this study. The study first presents an exploratory analysis to determine influential authors, sources and regions, among other key aspects. Second, several network analyses including co-citation and dynamic co-citation network analyses are conducted to identify themes. These allow identifying research clusters and emerging research topics algorithmically. Both centrality and modularity-based clustering are employed. A content analysis of the most influential groups within OC literature for each cluster is included.

The findings of this paper make unique contributions by using advanced tools from network analysis along with the standard bibliometric analysis tools to explore the current status of OC research, identify existing themes and the guidance for potential areas of future research interest in OC.

This research provides a comprehensive view of the range of topics of importance that have been discussed in the literature of OC management. These research trends can serve as a quick guide to researchers and practitioners to improve decision making and also develop strategies.

The paper employs advanced tools for the first time to review the literature of OC retailing. The sophisticated tools include co-citation and dynamic co-citation network analysis.

This paper systematically evaluates the existing literature of innovations in freight transport, including all modes, to uncover the key research themes and methodologies employed by researchers to study innovations and their implications in this industry. It analyses the role of transport and the impact of innovations during crises, such as COVID-19.

Qualitative and quantitative analysis of the innovations in freight transport unravels the pre-requisites of such endeavours in achieving a resilient and sustainable transport network that effectively and efficiently operates during a crisis. The authors performed keyword co-occurrence network (KCON) analysis and research focus parallelship network (RFPN) analysis using BibExcel and Gephi to determine the major resulting research streams in freight transport.

The RFPN identified five emerging themes: transport operations, technological innovation, transport economics, transport policy and resilience and disaster management. Optimisation and simulation techniques, and more recently, artificial intelligence and machine learning (ML) approaches, have been used to model and solve freight transport problems. Automation innovations have also penetrated freight and supply chains. Information and communication technology (ICT)-based innovations have also been found to be effective in building resilient supply chains.

Given the growth of e-commerce during COVID-19 and the resulting logistics demand, along with the need for transporting food and medical emergency products, the role of automation, optimisation, monitoring systems and risk management in the transport industry has become more salient. Transport companies need to improve their operational efficiency using innovative technologies and data science for informed decision-making.

This paper advises researchers and practitioners involved in freight transport and innovation about main directions and gaps in the field through an integrated approach for evaluating research undertaken in the area. This paper also highlights the role of crisis, e.g. COVID-19, and its impacts on freight transport. Major contributions of this paper are as follows: (1) a qualitative and quantitative, systematic and effective assessment of the literature on freight transport through a network analysis of keywords supplemented by a review of the text of 148 papers; (2) unravelling major research areas; (3) identifying innovations in freight transport and their classification as technological and non-technological and (4) investigating the impact of crises and disruptions in freight transport.

This study research contributes in fulfilling the gap by carrying out a systematic literature review (SLR) of contemporary research studies in closed-loop supply chain (CLSC). To the best of the author’s knowledge, an SLR rooted in bibliometric analysis has not been carried focusing on advent developments in CLSC. SLR employs scientific methodologies to select papers from standard databases. The SLR using advanced bibliometric and network analysis enables unveiling the key features of the contemporary literature.

The author has analyzed over 333 documents published from 2008 and onward. Using the contemporary tools from bibliometric analysis tools, the author presented an exploratory analysis. A network analysis is utilized to visualize literature and create clusters for the cocited research studies, keywords and publication sources. A detailed multivariate analysis of most influential works published based top 100 articles via a cocitation matrix is done. The multivariate analysis used k-means clustering in which optimal number of clusters are estimated. The analysis is further extended by using a factor analysis, which enables determining the most influential clusters in the k-means clustering analysis.

The SLR using a bibliometric and network analysis enables unveiling the key features of the contemporary literature in CLSC. The author examined published research for influential authors, sources, region, among other key aspects. Network analysis enabled visualizing the clusters of cocited research studies, cowords and publication sources. Cluster analysis of cocited research studies is further explored using k-means clustering. Factor analysis extends findings by identifying most contributing grouping of research areas within CLSC research. Each clustering technique disclosed a unique grouping structure.

CLSC has received considerable attention, and its core areas start with focusing on reverse logistics concepts relating reuse, recycling, remanufacturing, among others. Contemporarily, the studies have enhanced reverse logistics core functionalities interfaced with the other interesting avenues related to CO₂ emission reduction, greening and environmental protection, sustainability, product design and governmental policies. Earlier studies have presented a literature review of CLSC; however, these reviews are commonly conducted in the traditional manner where the authors select papers based on their area of expertise, interest and experience. As such these reviews fall short in utilizing the advanced tools from bibliometric analysis.

Misinformation (i.e. information identified as false) spreads widely and quickly on social media – a space where crowds of ordinary citizens can become leading voices – during a crisis when information is in short supply. Using the theoretical lenses of socially curated flow and networked gatekeeping frameworks, we address the following three aims: First, we identify emergent opinion leaders in misinformation-related conversations on social media. Second, we explore distinct groups that contribute to online discourses about misinformation. Lastly, we investigate the actual dominance of misinformation within disparate groups in the early phases of mass shooting crises.

This paper used network and cluster analyses of Twitter data that focused on the four most prevalent misinformation themes surrounding the El Paso mass shooting.

A total of seven clusters of users emerged, which were classified into five categories: (1) boundary-spanning hubs, (2) broadly popular individuals, (3) reputation-building hubs, (4) locally popular individuals and (5) non-opinion leaders. Additionally, a content analysis of 128 tweets in six clusters, excluding the cluster of non-opinion leaders, further demonstrated that the opinion leaders heavily focused on reiterating and propagating misinformation (102 out of 128 tweets) and collectively made zero corrective tweets.

These findings expand the intellectual understanding of how various types of opinion leaders can shape the flow of (mis)information in a crisis. Importantly, this study provides new insights into the role of trans-boundary opinion leaders in creating an echo chamber of misinformation by serving as bridges between otherwise fragmented discourses.

This paper aims to present a systematic review of the literature concerning major aspects of innovation performance and compare the research hotspots of innovation performance in the twenty-first century with three primary purposes: first, to view the trend of Chinese and English literature on innovation performance research; second, to summarize the research streams in innovation performance; and third, to predict possible directions for future innovation performance research.

The authors first introduce a framework of innovation performance research developments. Then they construct a representative data set of bibliographic records, obtaining 1,768 articles in the SSCI citation index database and 1,431 articles in the CSSCI database. The authors then make a comparative analysis from two aspects: research themes and development of academic communities. The research objects are keywords and references so that co-word and co-cited reference networks are established. Finally, the authors combine the direction of research streams about “innovation performance” to summarize 28 questions in three research fields that can be studied in the future.

The momentum of the literature in English on innovation performance is increasing, whereas the Chinese literature has declined in recent years. The direction of research streams in Chinese and English literature is the same: they are the “innovation system/elements” research stream, the “innovation activity/ability” research stream and the “innovation network/social capital” research stream. Although the directions are the same, the specific contents of the research are different. The direction of future development of innovation performance research can be undertaken in three aspects: follow research into expanding hot topics, mine the research of typical academic circles and develop research into exploring more fields. Combined with the direction of research streams, 28 questions in three research fields are summarized.

Based on the background of “mass entrepreneurship and innovation” in China, the research on enterprise “innovation performance” is becoming more and more important. The findings help us summarize the research streams related to innovation performance research, better understand the themes that point to directions for future development of innovation performance research and summarize 28 questions.

Time analysis and institution analysis as well as journal analysis allow the study to show literature distribution in this research area. Research hotspots and trending among different times are revealed by network-structural properties and network-temporal property. The study aims to shed light on international cluster research progress on strategic niche management (SNM).

Using searched literature data on SNM from 1991 to 2018 from the database of Web of Science (WOS), the article maps the citation network and completes the citation analysis based on bibliometric citation analysis.

These eight research streams reveal the development of SNM from theoretical description to target-oriented study and finally diversification analysis.

The paper identifies eight continuous research streams in SNM: sustainable transition, dynamical diversity, complexity, social-technical system, social innovation, social-cognitive evolution, emerging market and policy mix.

The purpose of this paper is to present an integrated model of the determinants of innovation in clusters. In the understanding, internal, external and relational dimensions must be considered to make up a complete picture of the innovation processes. The authors propose that the exploration capacity of the firm, as well as its networking intensity and the external resources provided by supporting organizations are relevant in this context.

The empirical study has drawn on the population of the firms belonging to the Valencian textile industrial cluster in Spain and was carried out in two different phases. In the first step the authors applied the social network analysis technique to study the relational structure of the participating companies, followed by a second analysis aimed at performing a more detailed analysis of the companies that answered the roster by means of face-to-face interviews.

Results suggest that firms in clusters must develop individual capacities parallel to the systemic resources in order to improve their innovation performance. These systemic resources are provided by the position in the knowledge network and the relations with Knowledge Intensive Business Services (KIBS), as agents that connect the cluster with external networks.

In spite of diverse contributions, previous research only provides a partial explanation of the issue and others underestimate one of the elements (internal or external to the firm) where the sources of innovation are generated. The originality of this study lies in the fact that it presents a complete perspective of the innovation process in clustered firms and clarifies key questions in cluster studies through network analysis techniques.

Little is known, about the role played by start-ups in open innovation networks. Start-ups – due to their nature of new and emerging companies – can largely benefit from the knowledge that can flow intentionally or unintentionally from external partners during open innovation practices. When open innovation networks are not set among peers on both sides the authors expect to have more unintended knowledge flows. Such knowledge “leaks” – as the authors named them – in open innovation networks are totally unexplored in literature. Hence, the purpose of this paper is to focus “whether and how knowledge leaks occur in open innovation networks with start-ups”.

The research design of this study relies on social network analysis methods and techniques to disentangle the role of start-ups in open innovation networks – in a major Italian aerospace cluster – vis-à-vis the three types of knowledge considered in this study. Then the authors confirmed knowledge leaks to occur through a multiplexity analysis. In the second stage of the research, the authors decided to strengthen the results, making them more vivid and thorough, relying on four case studies.

The paper sheds light on a totally unexplored phenomenon, theorizing on the role of start-ups in open innovation networks and suggesting intriguing implications both for theory and managers on whether and how knowledge leaks occur.

The main limitations arise from the specific research context, in fact the study has been conducted in an aerospace cluster. So future studies might consider to explore knowledge leaks in non-cluster settings and in low tech industries.

The results have practical implications both for policy makers and for managers. First of all, the research confirms how open innovation often originates from a combination of different knowledge types acquired through the collaboration with heterogeneous players, start-ups included. Hence, managers may design open innovation strategies balancing their portfolio of collaborations to maximize the absorption of relevant knowledge and start-uppers may consider to engage in open innovation practices to accelerate knowledge absorption. Nevertheless, the study warns managers against the risk of knowledge leaks, especially in cases like start-ups where the eagerness to participate or the prestige associated with participating in open innovation networks with key players may hamper the control over knowledge leaks.

This opens up for possible interventions for policy makers too. First of all, policy makers may consider incorporating the concept of knowledge leaks in their campaign in favour of open innovation. Second, the study may help policy makers in designing programmes for knowledge transfer partnerships amongst the various players of a cluster in a more conscious way, especially warning new to business companies, like start-ups, about possible leaks. Finally, there is also the need of developing professional figures like consultants capable of supporting start-ups in their open innovation practices.

Findings reported in the paper confirm multiplexity and heteromorphism in knowledge exchanges and shed the light on a completely unexplored field (i.e. open innovation and start-ups), focussing on knowledge leaks. Relevant implications for policy makers and managers are included in the study.