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Managers of megaprojects face social risk management challenges throughout the various design, construction, and operation stages, owing to the various conflicts of interest among stakeholders, public skepticism, and opposition. However, most existing studies have not focused on the dynamic analysis of integrating social risks in these stages. This study developed a dynamic analysis approach to explore the dynamics of critical social risk factors and related stakeholders of megaprojects and built the managerial maps for various stakeholders.

Based on the social analysis network (SNA), a dynamic network analysis approach for understanding the dynamics of social risk and related stakeholders has been developed by literature and case analysis. The approach comprises the following steps: (1) generating social risk–stakeholder networks in different stages; (2) analysis of the critical stakeholders and social risk factors; (3) dynamic analysis of social risk factors; and (4) developing social risk management maps for various stakeholders. To verify the feasibility and effectiveness of the approach, 40 megaprojects from China were analyzed.

According to the results, the local government is a critical stakeholder during all stages, inadequate information promotion (IIP) and imperfect communication and coordination mechanism (ICCM) are key social risk sources throughout the megaproject life cycle. Furthermore, the management maps for government organizations, project implementation groups, and external stakeholders were constructed.

This research has three contributions. First, a dynamic analysis approach of stakeholder-associated social risks in megaprojects is developed, which enriches the social risk management theory of megaprojects and provides inspiration for future research focus. Second, the social risk–stakeholder networks and critical social risks in different stages are confirmed to provide a more valid and accurate picture of social risk management in megaprojects. Third, the social risk managerial maps for different stakeholders built in this research will be beneficial for governments, project implementation groups, and external stakeholders to optimize management strategies.

The study aims to explore the digital fashion trend within the Metaverse, characterized by non-fungible tokens (NFTs), across Twitter networks. Integrating theories of diffusion of innovation, two-step flow of communication and self-efficacy, the authors aimed to uncover the diffusion structure and the influencer's social roles undertaken by social entities in fostering communication and collaboration for the advancement of Metaverse fashion.

Social network analysis examined the critical graph metrics to profile, visualize, and cluster the unstructured network data. The authors used the NodeXL program to analyze two hashtag keyword networks, “#metaverse fashion” and “#metawear,” using Twitter API data. Cluster, semantic, and time series analyses were performed to visualize the contents and contexts of communication and collaboration in the diffusion of Metaverse fashion.

The results unraveled the “broadcast network” structure and the influencers' social roles of opinion leaders and market mavens within Twitter's “#metaverse fashion” diffusion. The roles of innovators and early adopters among influencers were comparable in collaborating within the competition venues, promoting awareness and participation in digital fashion diffusion during specific “fad” periods, particularly when digital fashion NFTs and cryptocurrencies became intertwined with the competition in the Metaverse.

The study contributed to theory building by integrating three theories, emphasizing effective communication and collaboration among influencers, organizations, and competition venues in broadcasting digital fashion within shared networks. The validation of multi-faceted Social Network Analysis was crucial for timely insights, highlighting the critical digital fashion equity in capturing consumers' attention and driving engagement and ownership of Metaverse fashion.

This paper aims to examine the relationship between being members of social media business networks and SME performance by comparing business performance between family-owned SMEs that are members and non-members of social media business networks.

The analysis empirically draws on cross-sectional data of 9,292 English and Welsh family-owned SMEs from the UK's Government Small Business Survey 2015. Propensity Score Matching (PSM) is applied to control for selection bias and differences in firm characteristics before comparing business performance, measured in terms of annual turnover, sales-growth intention and innovation between family-owned SMEs that are members and non-members of social media business networks.

The findings show that family-owned SMEs that are members of social media business networks are more likely to have higher prior turnover and to grow their sales than non-members. Also, they are more likely to report being innovative in products and processes than non-members. The empirical results acknowledge the importance of online business networks and digital social capital on enhanced family-owned business performance.

This paper is the first to explore the comparative analysis of business performance between family-owned SMEs that are members and non-members of social media business networks. This paper is important for the development of family business research by providing a comprehensive evidence-based analysis regarding the importance of online business networks to improve family-owned business performance, given the significant contribution of digital business activities to the UK economy.

This study aims to investigate the content of hotel brands’ mission statements (MSs) and their relationship with selected attributes of hotel brands.

Content analysis of hotel brands’ MSs was used to detect the MSs’ key words, which were further processed by methods of social network analysis, complemented by clustering techniques and correspondence analysis on the generalized aggregated lexical tables, a special type of correspondence analysis.

Hotel brands operating in luxurious markets more often emphasize experiences than those in midscale markets. Furthermore, hotel brands with longer traditions and those with a large number of controlled rooms communicate words in their MSs that represent a rather traditional approach to hospitality. Younger hotel brands with fewer controlled rooms chose words that indicate a more commercially oriented approach. Finally, cluster analysis revealed four dimensions of hotel brands’ MSs, instead of the nine most typically used in mission statement component models.

Understanding the frequencies and networks of keywords, and their relationship with hotel brand attributes, will help create more focussed MSs. This will strengthen hotel brands, raise their revenues and subsequently increase company performance.

The analysis provides valuable insight into MSs in the specific tourism context of hotel brands. The authors have achieved this with the use of a wide range of advanced network analytic methods. These insights can guide hotel brands to better position themselves in the competitive tourism accommodation market.

The significance of social media in our lives is manifold. The tourism sector closely interacts with existing and potential tourists through social media, and therefore, social media analytics (SMA) play a critical role in the uplift of the sector. Hence, this review focus on the role of SMA in tourism as discussed in different studies over a period of time. The purpose of this paper to present the state of the art on social media analytics in tourism.

The review focuses on identifying different SMA techniques to explore the trends and approaches adopted in the tourism sector. The review is based on 83 papers and discuss the studies related to different social media platforms, the travelers' reactions to a particular place and how the tourism experience is enriched by the way of SMA.

Findings indicate different sentiments associated with tourism and provides a review of tourists’ use of social media for choosing a travel destination. The various analytical approaches, areas such as social network analysis, content analysis, sentiment analysis and trend analysis were found most prevalent. The theoretical and practical implications of SMA are discussed. The paper made an effort to bridge the gap between different studies in the field of tourism and SMA.

SMA facilitate both tourists and tourism companies to understand the trends, sentiments and desires of tourists. The use of SMA offers value to companies for designing quick and adequate services to tourists.

Networks linking tourist attractions or organizations are a major focus of tourism research. Despite extensive research on tourism networks, academic research on the spatial structure and formation of wine tourism networks is limited. This study aims to investigate the spatial structure and factors influencing the development of a network among Ningxia wineries, an emerging wine tourism destination in China.

This study uses social network analysis to uncover “what” the spatial structure of wine tourism networks looks like. Sixteen in-depth interviews were conducted among key stakeholders to explain the “why” of such structural characteristics.

The results show that in an emerging wine tourism destination, popular tourist attractions enjoy high centrality and hold key positions in the wine tourism network. Small wineries exhibit high closeness centrality, and only one winery serves as a network broker. According to the stakeholders, the importance of network actors will increase as their economic and political importance increase, while small wineries that lack differentiation in the network may perish.

Local governments can implement the suggested measures for improving network connections, and wineries are advised to find suitable positions to improve the experiences of tourists.

This study pioneers the identification of the distinct structure and factors influencing the network of an emerging wine tourism destination, thus enriching the understanding of the interplay and roles of different actors.

This study aims to determine how the most sustainable brands in Italy and Spain developed communication and awareness-raising actions during the COVID-19 pandemic and whether these companies were truly involved in raising public awareness of the pandemic. The authors specifically focus on sustainable companies, as health communication is considered to be an important corporate social responsibility task.

To answer these questions, the authors have used data on the social media activity (Twitter and Instagram) of these brands in Spain and Italy, extracting the posts and associated hashtags that each of them has published throughout the pandemic to be processed using social network analysis and visualization techniques.

The detailed analysis of both the levels of activity and the content of the messages provides interesting insights into the communication models of the companies and the influence of factors such as time, country and the specific social media platform used.

The authors analyze the communication of the most sustainable businesses on social media during the pandemic, adopting a highly innovative approach. The particular originality of this study lies in the parallel analysis of two different countries that were simultaneously shaken by the pandemic in very similar circumstances. This study also presents a novel use of graphical representation tools in terms of companies’ behavior for health communication on social media.

El objetivo de esta investigación es determinar cómo las marcas reconocidas como las más sostenibles en Italia y España han desarrollado acciones de comunicación durante la pandemia del Covid-19 y si estas empresas se han involucrado realmente en la sensibilización pública de la pandemia. Nos centramos específicamente en las empresas sostenibles dado que la Comunicación en Salud se considera una tarea importante de responsabilidad social corporativa.

Para responder a estas preguntas, hemos utilizado datos de actividad en medios sociales (Twitter e Instagram) de estas marcas en España e Italia, extrayendo los posts y hashtags asociados que cada una ha publicado a lo largo de la pandemia para procesarlos usando técnicas de análisis y visualización de redes sociales.

El análisis detallado tanto de los niveles de actividad como del contenido de los mensajes permite obtener conclusiones interesantes sobre los modelos de comunicación de las empresas y la influencia de factores como el tiempo, el país y el medio social concreto utilizado.

Analizamos la comunicación realizada por las compañías más sostenibles en medios sociales durante la pandemia, adoptando un enfoque muy innovador. La particularidad de este estudio radica en el análisis paralelo de dos países diferentes que fueron sacudidos simultáneamente por la pandemia en circunstancias muy similares. Este estudio también conlleva un uso novedoso de herramientas de representación gráfica en términos del comportamiento de las empresas para Comunicación en Salud en medios sociales.

本研究的目的是确定在意大利和西班牙被认为是最可持续发展的品牌在Covid-19大流行期间是如何开展传播行动的, 以及这些公司是否真正参与了提高公众对该大流行病的认识。我们特别关注可持续发展的公司, 因为健康传播被认为是企业社会责任的一项重要任务。

为了回答这些问题, 我们使用了这些品牌在西班牙和意大利的社交媒体活动数据（Twitter和Instagram）, 提取了每个品牌在整个大流行期间发布的帖子和相关标签, 并使用社交网络分析和可视化技术进行处理。

通过对活动水平和信息内容的详细分析, 可以得出关于这些公司的传播模式以及诸如时间、国家和所使用的特定社交媒体等因素的影响的有趣结论。

我们分析了最可持续的公司在大流行期间在社交媒体上进行的传播, 采取了一种非常创新的方法。这项研究的特殊性在于对两个不同国家的平行分析, 这两个国家在非常相似的情况下同时受到大流行病的冲击。这项研究还包括在社交媒体上对公司健康传播行为的图形表示工具的新颖使用。

This study aims to provide a holistic review of social media influencers (SMIs) research based on a unique approach of bibliometric analysis and content analysis between 2011 and 2020. The review examines the main influential aspects, themes and research streams to identify research directions for the future.

The sample selection and data collection were done from the Scopus database. The sample dataset was refined based on the inclusion and exclusion criteria to determine the final dataset of 183 articles. The dataset was exported in the BibTeX format and then imported into the BiblioShiny app for bibliometric analysis. The content analysis was done following the theory-context-methodology framework.

The several findings of this study include (1) Co-word analysis of most used keywords; (2) Longitudinal thematic evolution; (3) The focus of the research papers as per the theory-context-methodology review protocol are persuasion knowledge model, fashion and beauty industries, Instagram and content analysis, respectively; and (4) The network analysis of the research studies is known as the co-citation analysis and depicts the intellectual structure in the domain. This analysis resulted in four clusters of the research streams from the literature and two emergent themes (Chen et al., 2010)

In general, the previous reviews in the area are either domain, method or theory-based. Thus, this study aims to complement and extend the existing literature by presenting the overall picture of the SMI research with the help of a unique combined approach and further highlighting the trends and future research directions based on the findings of this study.

Social risk management has recently come to the fore as a significant feature of project management. This prominence is particularly evident in urban construction projects that take place in cultural heritage and tourism historic sites. Accordingly, this study aims to adopt social network analysis (SNA) to investigate social risks in construction projects occurring in urban districts rife with historically and culturally significant tourism sites.

The present study analyzed a real case study in Iran as an emergent economy and a developing country. Primarily, the study reviewed previous literature on social risks and relevant stakeholders. Next, the judgments of experts through the content validity ratio analysis confirmed 12 social risks and 9 key stakeholders. Finally, SNA is used to determine the relations between the social risks and stakeholders as well as the significance of each risk.

The investigation demonstrated that the most important social risks in the construction projects of the case study are “Psychological disorders”, “Environmental pollution” and “Cultural conflicts”.

The findings could help policymakers, urban planners and project managers in developing countries with a rich cultural heritage to reduce social risks and improve the efficiency of their projects.

To the best of the authors’ knowledge, the present study is one of the first instances to investigate construction projects implemented in densely populated urban areas hosting cultural heritage and historic tourism sites.