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Building on social media and destination brand-related literature, this study aims to explore World Heritage Sites’ (WHSs) brand diffusion and formation process from long-term and short-term perspectives, which includes brand diffusion, user-generated content (UGC), opinion leaders and brand events’ impact.

This study uses a mixed-method including text mining, keyword analysis and social network analysis to explore the brand formation process of four popular WHSs in Beijing, namely, the Palace Museum, Great Wall, Summer Palace and Temple of Heaven and more than 10,000,000 users’ data on Sina Weibo has been implemented to uncover the underlying social media branding mechanism.

The results show that the number of postings keeps in a stable range in most months, but, in general, there are no common rules for changing trends among the four WHSs; long-term high-frequency keywords related to history and culture account for a higher percentage; different kinds of accounts have varying impacts on information diffusion, in which media accounts lead to a bigger influence. However, more followers do not necessarily mean more interactions and most of the interaction ratio is much lower than 0.01000; brand events facilitate brand dissemination and have an impact on the creation of UGC.

This study is valuable for destination marketers to deeper understand brand diffusion and formation and provides valuable insights for developing effective destination marketing strategies.

Unlike previous studies that only concern a few parts of destination brand formation via social media (e.g. brand diffusion, brand events or opinion leaders’ impact), this study takes a more comprehensive perspective by systematically analyzing the brand formation process of WHSs on social media. By considering both long-term diffusion and short-term representative events, this study provides a more holistic understanding of the branding mechanism.

This study aims to investigate the mechanism of the misinformation spread based on the elaboration likelihood model and the effects of four factors – emotion, topic, authority and richness – on the depth, breadth and structural virality of misinformation spread.

The authors collected 2,514 misinformation microblogs and 142,006 reposts from Weibo, used deep learning methods to identify the emotions and topics of misinformation and extracted the structural characteristics of the spreading network using the network analysis method.

Results show that misinformation has a smaller spread size and breadth than true news but has a similar spread depth and structural virality. The differential influence of emotions on the structural characteristics of misinformation propagation was found: sadness can promote the breadth of misinformation spread, anger can promote depth and disgust can promote depth and structural virality. In addition, the international topic, the number of followers, images and videos can significantly and positively influence the misinformation's spread size, depth, breadth and structural virality.

The influencing factors of the structural characteristics of misinformation propagation are clarified, which is helpful for the detection and management of misinformation.

The aim of this paper is to present the first diffusion analysis of ISO/IEC 27001, the fourth most popular ISO certification at global level and the most important standard for information security.

To achieve the purposes, the authors applied Grey Models (GM) – Even GM (1,1), Even GM (1,1,α,θ), Discrete GM (1,1), Discrete GM (1,1,α) – complemented by the relative growth rate and the doubling time indexes on the six most important countries in terms of issued certificates.

Results show that a growing trend is likely to be expected in the years to come and that China will lead at country level.

The study contributes to the scientific debate by presenting the first diffusive analysis of ISO/IEC 27001 and by proposing a forecasting approach that to date has found little application in the field of international standards.

This study aims to use organizational fashion to underscore a novel phenomenon in which products, services and practices fade in and out of the tourism/hospitality setting within a specific time frame. Drawing from the fashion theoretical strands in organization research, this paper studies how fashion has been conceptualized, operationalized and then diffused among tourism/hospitality enterprises.

A qualitative case design was used. A total of 37 semistructured in-depth interviews with executives of innovative tourism/hospitality companies (e.g. restaurants, hotels, theme parks and travel agencies) were conducted. This paper focuses on the organizational fashion phenomenon in which organizational trendsetters with creative, “hot” products/services have emerged prominently in the marketplace.

This inquiry illustrates a social phenomenon concerning the organizational fashion setting process by integrating existing production practices among different organizational suppliers in the hospitality sector. Different cases in the study show that fashion consists of a series of hybrid, paradoxical processes. These include conceptualization (conventionalization vs novelty, and personalization vs conformity), operationalization (bundling vs unbundling, and learning vs relearning) and diffusion (framing vs co-framing, and adaptation vs alteration).

Throughout the three continuous processes, service design and identity development for consumption, as well as value creation and knowledge transformation for production, are carried out according to the decision of what is “hot” and what is “out” at a particular time. In essence, fashion helps to explain why hospitality institutions imitate specific innovations to take advantage of popular trends in the consumer market, as well as how such trends vanish eventually.

This research contributes the insight that organizations use fashion as a managerial initiative to translate their organizational goals and improvise nascent products and services. The fashion processes can be triggered by microlevel individual organizations and are spread through a series of social interactions to become macrolevel phenomena in a recurring manner.

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.

With the increasing number of mobile applications, efficiently recommending mobile applications to users has become a challenging problem. Although existing mobile application recommendation approaches based on user attributes and behaviors have achieved notable effectiveness, they overlook the diffusion patterns and interdependencies of topic-specific mobile applications among user groups. mobile applications among user groups. This paper aims to capture the diffusion patterns and interdependencies of mobile applications among user groups. To achieve this, a topic-aware neural network-based mobile application recommendation method, referred to as TN-MR, is proposed.

In this method, first, the user representations are enhanced by introducing a topic-aware attention layer, which captures both the topic context and the diffusion history context. Second, it exploits a time-decay mechanism to simulate changes in user interest. Multitopic user representations are aggregated by the time decay module to output the user representations of cascading representations under multiple topics. Finally, user scores that are likely to download the mobile application are predicted and ranked.

Experimental comparisons and analyses were conducted on the actual 360App data set, and the results demonstrate that the effectiveness of mobile application recommendations can be significantly improved by using TN-MR.

In this paper, the authors propose a mobile application recommendation method based on topic-aware attention networks. By capturing the diffusion patterns and dependencies of mobile applications, it effectively assists users in selecting their applications of interest from thousands of options, significantly improving the accuracy of mobile application recommendations.

Drawing on social network and information diffusion theories, the authors study the impact of the structural characteristics of a seller’s local social network on her promotion effectiveness in social commerce.

The authors define a local social network as one formed by a focal seller, her directly connected users and all links among these users. Using data from a large social commerce website in China, the authors build econometric models to investigate how the density, grouping and centralization of local social networks affect the number of likes received by products posted by sellers.

Local social networks with low density, grouping and centralization are associated with more likes on sellers’ posted products. The negative effects of grouping and centralization are reduced when density is high.

The paper deepens the understanding of the determinants of social commerce success from a network structure perspective. In particular, it draws attention to the role of sellers’ local social networks, forming a foundation for future research on social commerce.

Crowdfunding (CF) has become an increasingly popular means of financing for entrepreneurs and has attracted significant attention from both researchers and practitioners in recent years. The purpose of this study is to investigate the core content and knowledge diffusion paths in the CF field. Specifically, we aim to identify the main topics and themes that have emerged in this field and to trace the evolution of CF knowledge over time.

This study employs co-word clustering and main path analysis (MPA) to examine the historical development of CF research based on 1,528 journal articles retrieved from the Web of Science Core Collection database.

The results of the analysis reveal that CF research focuses on seven themes: sustainability, entrepreneurial finance, entrepreneurship, fintech, social entrepreneurship, social capital, and microcredits. The analysis of the four main paths reveals that equity CF has been the dominant topic in the past years. Recently, CF research has tended to focus on topics such as fintech, the COVID-19 pandemic, competition, Brexit, and policy response.

To the authors' best knowledge, this is the first attempt to explore knowledge diffusion dynamics in the CF field. Overall, the study offers a structure for analyzing the paths through which knowledge is diffused, enabling scholars to effectively manage a large volume of research papers and gain a deeper understanding of the historical, current, and future trends in the development of CF.

This study aims to examine the diffusion and implementation of trust-based management (TBM) in Scandinavian countries (Denmark, Norway and Sweden). TBM is a novel “anti-New Public Management (NPM)” innovation within the realm of New Public Governance (NPG), which asserts that leadership and control in public sector organizations should be practiced and designed based on the assumption that civil servants and employees in general are trustworthy. The research questions are as follows: How has TBM been diffused and implemented in Scandinavia? To what extent can the institutional logics framework increase understanding of similarities and differences between the Scandinavian countries (Denmark, Norway and Sweden)?

The authors designed and submitted surveys to the municipal directors of the three Scandinavian municipal populations, thereby producing a unique cross-country dataset on TBM diffusion and implementation in Scandinavia (Denmark, Norway and Sweden).

The authors' study shows that TBM has diffused widely among Scandinavian municipalities and has developed into a municipal-level concept across policy fields and sectors. While Denmark stands out as an earlier and more decisive TBM reformer, the results show that similarities in the diffusion and implementation of TBM in Scandinavian countries are more apparent than the differences.

This study contributes to the public management literature and research on anti-NPM and NPG concepts by being the first wide-scale empirical study of TBM diffusion and implementation in the Scandinavian municipal sectors.

The current paper is a comment on goalkeepers in football. This paper aims to explore the skillset of the contemporary goalkeeper and whether these can be reliably measured. This paper advocates the recognition of the goalkeeper as the most important member of the football team.

This paper draws on the work of Bourdieu (1995) to examine the impact of calculative practice on the art of goalkeeping. This reveals the diffusion of calculations to goalkeeping but challenges whether these statistics are robust. This study used the Internet (Jeacle, 2021) to explore the multiple dimensions of this study.

The comment argues a case for the goalkeeper as the principal actor in the football team. From an accountability perspective, the impact of the goalkeeper can be profound, the more so because of rule changes. Whilst calculative practice has entered the world of the goalkeeper, the practice is questionable if contemporary metrics are not robust and more sophisticated performance indicators are required. Increasing transfer costs highlight the need for objective measures of goalkeeping performance.

This paper is novel in that the paper attempts to broaden the scope of accounting scholarship into a new domain of football in popular culture.