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Despite the severe impact of the COVID-19, Maldives was one of the top destinations which witnessed decent tourist arrival amid the pandemic. This study aims to analyze luxury hospitality experiences of guests amid COVID-19 pandemic.

This study is exploratory in nature. This study analyses 4,302 real-time customer reviews using sentiment and thematic analysis with the help of NVIVO 12 plus and Leximancer.

The findings suggest travel products as well as services associated with luxury resorts needs to be revisited. Staff needs to be more professional and must be proactive while redesigning services specially in situations like pandemic. While redesigning services in situations like pandemic, staff needs to be proactive, professional and must follow all protocols. Major negative experiences included long waiting time to avail frill services, privacy intrusion by bloggers and influencers, service quality issues. We recommend enhancing service quality followed by investing more in training and development, increasing the number of foreign languages spoken by staff and disseminating localized culinary experiences will enhance the experience quality with guests.

This study has several limitations: first, this study limited itself to 15 luxury resorts of Maldives, which may not serve as a true representation of all luxury resorts of Maldives. The next limitation of this study is that the authors have collected customer reviews from TripAdvisor only, and the reviews were only in English language.

The findings of the research can be beneficial for the policymakers, hospitality practitioners and academicians who study luxury tourism industry to carve appropriate strategies for enhancing the customers’ luxury experience like leveraging customization in all areas and enhancing service quality, food quality, training and development of employees.

Maldives has become one of the most expensive traveler destinations and is home to world’s most expensive resorts. This study is original in nature and has a forward-looking approach which studies the disruptive effect of pandemic, intangible nature of luxury as a concept can be used by hospitality industry to redesign the luxury customer experience which can improve marketing strategies aiming to potentiate this niche. In addition, to the best of the authors’ knowledge, this study will be the first one to capture the real customer experiences of luxury resorts of Maldives.

This study, a conceptual paper, analyses the growth of curation in tourism and hospitality and the curator role in selecting and framing products and experiences. It considers the growth of expert, algorithmic, social and co-creative curation modes and their effects.

Narrative and integrative reviews of literature on curation and tourism and hospitality are used to develop a typology of curation and identify different curation modes.

Curational techniques are increasingly used to organise experience supply and distribution in mainstream fields, including media, retailing and fashion. In tourism and hospitality, curated tourism, curated hospitality brands and food offerings and place curation by destination marketing organisations are growing. Curation is undertaken by experts, algorithms and social groups and involves many of destination-related actors, producing a trend towards “hybrid curation” of places.

Research is needed on different forms of curation, their differential effects and the power roles of different curational modes.

Curation is a widespread intermediary function in tourism and hospitality, supporting better consumer choice. New curators influence experience supply and the distribution of consumer attention, shaping markets and co-creative activities. Increased curatorial activity should stimulate aesthetic and stylistic innovation and provide the basis for storytelling and narrative in tourism and hospitality.

This is the first study of curational strategies in tourism and hospitality, providing a definition and typology of curation, and linking micro and macro levels of analysis. It suggests the growth of choice-based logic alongside service-dominant logic in tourism and hospitality.

Fake news stories have become a central element of crises that corporate public relations practitioners have confronted. Whether such stories are rumors, outright lies or deliberate attempts to discredit corporations, they have the same impact and require specific strategies for public relations practitioners to effectively respond. The purpose of this study is to uncover strategies to manage crises that arise from fake news and if and how these strategies differ for other corporate crises.

In this multi-method study of 21 in-depth interviews and a 8-person focus group with senior-level corporate public relations practitioners, authors explored decision-making strategies for responding to fake news crises. Transcripts of interviews and the focus group were thematically analyzed.

Results reveal insights regarding how public relations practitioners determine if and when to respond to fake news crises in corporations; what response strategies public relations practitioners have the autonomy to employ for fake news crises in corporations, and how public relations practitioners control media narratives during fake news crises in corporations.

The findings guide public relations practitioners to craft an autonomous decision-making process and effective online listening strategies—establishing a watchful waiting approach—and determine if the fake news issue is a passing moment or movement swirling into a crisis.

Few studies have examined the perspectives of crisis communication experts about minimizing and managing fake news crises. The study identifies opportunities for future research focused on crises originating from fake news and disinformation.

Communities representing groups of agents with similar interests or functions are one of the essential features of complex networks. Finding communities in real-world networks is critical for analyzing complex systems in various areas ranging from collaborative information to political systems. Given the different characteristics of networks and the capability of community detection in handling a plethora of societal problems, community detection methods represent an emerging area of research. Contributing to this field, the authors propose a new community detection algorithm based on the hybridization of node and link granulation.

The proposed algorithm utilizes a rough set-theoretic concept called closure on networks. Initial sets are constructed by using neighborhood topology around the nodes as well as links and represented as two different categories of granules. Subsequently, the authors iteratively obtain the constrained closure of these sets. The authors use node mutuality and link mutuality as merging criteria for node and link granules, respectively, during the iterations. Finally, the constrained closure subsets of nodes and links are combined and refined using the Jaccard similarity coefficient and a local density function to obtain communities in a binary network.

Extensive experiments conducted on twelve real-world networks followed by a comparison with state-of-the-art methods demonstrate the viability and effectiveness of the proposed algorithm.

The study also contributes to the ongoing effort related to the application of soft computing techniques to model complex systems. The extant literature has integrated a rough set-theoretic approach with a fuzzy granular model (Kundu and Pal, 2015) and spectral clustering (Huang and Xiao, 2012) for node-centric community detection in complex networks. In contributing to this stream of work, the proposed algorithm leverages the unexplored synergy between rough set theory, node granulation and link granulation in the context of complex networks. Combined with experiments of network datasets from various domains, the results indicate that the proposed algorithm can effectively reveal co-occurring disjoint, overlapping and nested communities without necessarily assigning each node to a community.

This study carries important practical implications for complex adaptive systems in business and management sciences, in which entities are increasingly getting organized into communities (Jacucci et al., 2006). The proposed community detection method can be used for network-based fraud detection by enabling experts to understand the formation and development of fraudulent setups with an active exchange of information and resources between the firms (Van Vlasselaer et al., 2017). Products and services are getting connected and mapped in every walk of life due to the emergence of a variety of interconnected devices, social networks and software applications.

The proposed algorithm could be extended for community detection on customer trajectory patterns and design recommendation systems for online products and services (Ghose et al., 2019; Liu and Wang, 2017). In line with prior research, the proposed algorithm can aid companies in investigating the characteristics of implicit communities of bloggers or social media users for their services and products so as to identify peer influencers and conduct targeted marketing (Chau and Xu, 2012; De Matos et al., 2014; Zhang et al., 2016). The proposed algorithm can be used to understand the behavior of each group and the appropriate communication strategy for that group. For instance, a group using a specific language or following a specific account might benefit more from a particular piece of content than another group. The proposed algorithm can thus help in exploring the factors defining communities and confronting many real-life challenges.

This work is based on a theoretical argument that communities in networks are not only based on compatibility among nodes but also on the compatibility among links. Building up on the aforementioned argument, the authors propose a community detection method that considers the relationship among both the entities in a network (nodes and links) as opposed to traditional methods, which are predominantly based on relationships among nodes only.

Digital influencers, besides being a personal branding phenomenon, constitute, nowadays, important partners for brands in the digital environment. Despite the benefits for both parties, the brand and the endorser, there is a risk when the individuals or the brand take part in some scandal or questionable activity, which causes a loss of credibility and reputation. The contagious effect of personal or corporate brand crisis with the partners is well reported in the literature. However, there are no studies about such occurrence in the digital environment, considering that the phenomenon of digital influence has some particularities differing from traditional celebrity endorsement. This chapter focuses on the research of the consequences of a change in the credibility of influencers or brands, after the occurrence of a negative situation, and the way in which this change affects the two parties involved, the brand and the influencer. We conducted a netnographic study of the social media pages of three digital influencers and the social media pages of a recognized fast fashion brand recognized in the digital world. We analyzed 1500 social media comments from their audiences and found that influencers suffer from a loss in sympathy and credibility by scandals while crisis communication strategies in corporate brands can prevent such damages. Strategic implications for brand managers and digital influencers managing their endorsements are addressed in the discussion.

This research paper aims to investigate the critical factors influencing the live commerce industry and their implications for Key Opinion Leaders (KOLs) and brands.

The study comprehensively reviews previous research, develops relevant hypotheses and utilizes personal information from 66 anchors, along with data from 23,000 product links obtained from the backends of live commerce platforms.

The study emphasizes that KOLs with higher traffic significantly influence Gross Merchandise Volume (GMV). Intriguingly, KOLs with lower traffic levels exhibit a more pronounced effect on Return on Investment (ROI), highlighting their significance in driving profitability. Furthermore, the study explores the correlation between KOL hashtags and GMV/ROI and the intricate relationship between product types and KOL hashtags.

The findings significantly enhance the understanding of live shopping behavior and provide valuable insights for business management strategies. Practitioners can leverage this empirical evidence to make informed decisions, utilizing extensive data samples of KOLs and brands.

This research contributes unique insights into the live-streaming commerce industry using backend data from Live Streaming E-commerce platforms. The findings are more accurate based on market data than previous studies that relied on platform reviews or questionnaires. Additionally, this paper investigates the impact of KOLs on the performance of live e-commerce from three perspectives: GMV, ROI and hot-selling products.

The purpose of this study is to examine the impact of fashion influencer measures on consumers' purchase intentions and the mediation of attitudes to understand the phenomenon of influencer marketing in the backdrop of the fashion industry.

The present study employs a conceptual model based on extended theory of planned behaviour (TPB) with added perceived trust. Data were collected from 341 participants from different regions of the country and analysed using direct path analysis and mediation technique.

The study found that attitudes toward fashion influencers are positively influenced by perceived trust, subjective norms and perceived behavioural control. However, perceived behavioural control is not directly related to purchasing intents in the research model. The results confirmed that attitudes have a positive association with purchase intentions both directly and indirectly (partially mediation).

The study advocates market practitioners and advertisers to acknowledge the increasing importance of influencer marketing and the promotion of their fashion offerings in the setting of emerging fashion industry.

The present study adds crucial value to enhance the understanding of fashion influencer marketing in the Indian context. This research offers several insights into the continually growing knowledge domain of influencer marketing by predicting the direct relationships with purchase intents and the mediation of attitudes.

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.

The focus of this study is on how online-only retailers, known as pure-play e-retailers, leverage e-commerce platforms to identify and pursue market opportunities. Through the perspective of entrepreneurial marketing, this study aims to explore the influence of e-commerce technologies on the decision-making process of entrepreneurial marketing. This exploration is conducted via a case study of pure-play e-retailers based in China.

This study utilised a qualitative case study methodology to examine the complex processes of entrepreneurial marketing in an online environment. The study gathered detailed insights from both owner-managers and staff members of eight pure-play e-retail businesses. Additionally, the research involved a careful review of the firms' webpages and social media pages. This holistic approach facilitated a comprehensive understanding of their marketing strategies and practices.

The case study findings indicate that while many core aspects of entrepreneurial marketing remain important, there are distinct factors influencing the entrepreneurial marketing decision-making in the online marketplace. The online EM framework can be visualised as follows: (1) trend-orientated as well as innovative-orientated (2) data-orientated and entrepreneur-orientated (3) innovative-driven customer stimulation (4) orientated towards both platforms and proactiveness.

The paper provides an initial understanding of how digitalisation is enabling and transforming entrepreneurship in companies with high level digitalisation but low level digital development. Building on current entrepreneurial marketing literature, this paper develops an online entrepreneurial marketing framework to enhance understanding of the interaction between e-commerce technology and entrepreneurial marketing decision making.

Based on the “S-O-R” and attachment theories, this paper constructs a research model of the platform attribute factors of sports short video live e-commerce on consumers' psychological conditions, and explores how platform attributes affect consumer behavior through consumer attachment.

The study carried out questionnaire survey through the “snowball” method, and a total of 422 valid questionnaires were collected. The paper uses SPSS 26.0 and AMOS 26.0 to adapt the data and model, and adopts the method of structural equation modeling for analysis.

The research results show that the interactivity, identity, personalization and entertainment of live sports e-commerce platforms can actively stimulate consumer attachment, and directly drive their consumption behavior through their attachment.

Examining the platform attributes and system functions of short video live broadcast e-commerce from the perspective of consumer attachment can help sports e-commerce understand consumers' needs and satisfaction with the functions provided by the platform. Through timely optimization and improvement of system functions, the platform will make the connection between consumers and e-commerce closer, thereby increasing consumer stickiness and promoting the vigorous development of sports e-commerce.

This study identified and defined the platform attributes contained in the sports live broadcast e-commerce platform, combined the S-O-R model with the attachment theory, expanded the analytical framework of the S-O-R theory and made contributions to the extension of the attachment theory.