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Social customer relationship management (SCRM) is an evolving strategy gaining prominence in the hotel industry by cultivating new, improved relationships through engaging customers on social media (SM) platforms. Accordingly, this study aims to assess the effect of SCRM on customer service and customer loyalty (CL) in the hotel industry. This study also explores the moderating effect of COVID-19 (EC) on the relationship between (customer engagement [CE] and improved customer service [ICS]) and (CE and trust [TR]).

This study develops and tests the SCRM model using structural equation modelling on a sample size of 214 responses. The questionnaire was administered online to the customers of five preselected global hotel chains. The criteria for selecting the participants were that they must have tweeted from their Twitter handle by using # (hashtag) hotel name to resolve any customer service issues.

Results denote that CE significantly impacts ICS. CE was also found to exert a substantial effect on TR. The moderating EC was also found to be significant, but the effect was weak. Although the customers were extensively impacted by the pandemic and were initially hesitant to visit hotels, SCRM proved to be a powerful tool to gain back customer trust (CT) and develop CL by upsurging the shadows of COVID-19.

This study suggests that viable enforcement of the SCRM system can assist in real-time monitoring and tracking of customers' activities. This can develop a more profound connection with customers through CE which can boost the co-innovation process.

This study denotes a pioneer attempt to investigate the relationships between SCRM, CE, CT, ICS, CL and COVID-19 in the same framework in a SM context.

This paper aims to explore the role of blockchain (BCT) and Artificial Intelligence (AI) technologies in enhancing and incentivizing environmentally responsible, socially inclusive and economically viable tourism practices within the hospitality and tourism (H&T) industry.

This study is based on a critical reflection research approach that enables a synthesis of information derived from existing literature's insights and the authors' experiences and observations. By examining frameworks and theories in the literature, critical reflection also helps develop a more comprehensive understanding of the topic.

This study portrays how BCT could be used to track the sustainability credentials of tourism providers and how AI can optimize energy usage in hotels. This study depicts how adopting technology-driven sustainable practices in the H&T industry can increase profitability, improve reputation, compliance with regulations, efficiency and a better guest experience.

The study suggests targeted actions and policy frameworks that can be tailored to different stakeholder groups (hospitality businesses, policymakers and tourists) to overcome barriers and maximize the positive societal and environmental impacts of adopting BCT and AI for sustainable tourism.

The originality of this study lies in its ability to offer new perspectives and novel recommendations on the diverse uses of AI and BCT in the context of sustainable tourism. Furthermore, the study provides strategic and policy elements (Targeted actions and policy frameworks) for stakeholders to integrate sustainable tourism practices using BCT and AI successfully. This study differs from earlier review studies that primarily focused on adopting emerging technologies and ignoring the sustainability angle in the use of technology.

Research on food tourism has a significant impact on destination attractiveness. However, components interfacing food experiences and memory are under-researched topics in food tourism literature. Therefore, this study aims to present a framework based on the components of rememberable food experiences while travelling through the lens of the diffusion of sensory stimulation.

This study adopted a qualitative application of “Memory-Work”, a social constructionist archetype suggested for food tourism-related research. A survey was conducted, and the respondents were asked an open-ended question.

The analysis found the components instigating these food experiences: Peculiar food and drink experience, setting/geographical location, companions and social interactions, celebrating occasions and touristic components (e.g. serendipitous travel experience and food nostalgic memory). Predominantly, rememberable food tourism experiences are more explicit than memorable tourism experiences.

The components mentioned in this framework illustrate that various food-related experiences should be involved in destination marketing. Service providers could use these components to create unique destination stories.

This study is the first to present a newly developed framework for food tourism service providers that incorporates sensory impressions with food memories to explore the connection between food memories associated with a destination.

The hospitality industry experienced an unanticipated challenge from the COVID-19 pandemic. However, research in this area is scarce. Accordingly, this study aims to unfold a three-angled research agenda to intensify the knowledge advancement in the hospitality sector. It proposes a theoretical framework by extending the protection motivation theory (PMT) to explain the guest’s intent to adopt artificial intelligence (AI) and robotics as a protective measure in reaction to COVID-19.

The research is centered on outlining the pertinent literature on hospitality management practices and the guest’s transformed behavior during the current crisis. This study intends to identify a research agenda based on investigating hospitality service trends in today’s changing times.

The study sets out a research agenda that includes three dimensions as follows: AI and robotics, cleanliness and sanitation and health care and wellness. This study’s findings suggest that AI and robotics may bring out definite research directions at the connection of health crisis and hospitality management, taking into account the COVID-19 crisis.

The suggested research areas are anticipated to propel the knowledge base and help the hospitality industry retrieve the COVID-19 crisis through digital transformation. AI and robotics are at the cusp of invaluable advancement that can revive the hotels while re-establish guests’ confidence in safe hotel practices. The proposed research areas are likely to impart pragmatic lessons to the hospitality industry to fight against disruptive situations.

This study stands out to be pioneer research that incorporated AI and robotics to expand the PMT and highlights how behavioral choices during emergencies can bring technological revolution.

The purpose of this paper is to investigate a distinct set of characteristics that influence Muslim customers’ intentions to purchase Ar-Rahnu Islamic financing contract in Malaysia.

The study studied the impact of perceived value, perceived quality, perceived financial advantages, religious commitment and product knowledge on the purchase intention Ar-Rahnu Islamic financing contract using a quantitative research approach. A Google Form-based online survey was created and distributed through Twitter, Facebook and Instagram, among others. The survey data were analysed using structural equation modelling with a partial-least-square estimation property (PLS-SEM).

The study results suggested that Muslim customers in Malaysia had a greater propensity to buy Ar-Rahnu Islamic financing contract. Analysis of the data revealed that perceived value, perceived quality, perceived financial benefits and religious commitment had direct effects on the desire to buy Ar-Rahnu Islamic financing contract in Malaysia. In addition, the results reveal that religious commitment, perceived quality and perceived financial benefit are the top three important factors in explaining Ar-Rahnu Islamic financing contract buying intentions in this country.

Muslim customers may use Ar-Rahnu Islamic financing contract as a short-term credit alternative to enhance their financial standing. Ar-Rahnu Islamic financing contract generates a substantial quantity of credit demand and supply, which not only allows Muslim customers to adhere to Islamic standards but also contributes to the expansion of the economy. The result would aid and advise Ar-Rahnu finance resources and legislators in measuring the efficacy of the program in Malaysia, especially among Muslim customers.

Ar-Rahnu Islamic financing contract as a financing alternative has been explored extensively, but this study takes a whole new approach to the subject by looking at dimensions of perceived value, perceived quality and perceived financial benefit along with individual product knowledge and religious commitment. Consequently, this study will contribute to the understanding of how Muslim customers will respond to the Ar-Rahnu Islamic financing contract and will assist financial institutions in increasing the possibility that Muslim consumers would acquire Ar-Rahnu Islamic financing contract.

This paper aims to discover and analyze the challenges hampering blockchain technology’s (BT’s) implementation in the Indian health-care sector. A total of 18 challenges have been prioritized and modeled based on an extensive literature search and professional views.

An integrated multi-criteria decision-making approach has been used in two phases. Best worst method (BWM) is used in the first phase to prioritize the challenges with sensitivity analysis to validate the findings and eliminate a few challenges. In the second phase, interpretive structural modeling is applied to the remaining 15 challenges to obtain relative relationships among them with cross-impact matrix multiplication applied to classification analysis for their categorization.

The study’s results reveal that limited knowledge and expertise, cost and risk involved, technical issues, lack of clear regulations, resistance to change and lack of top management support are the top-ranked or high-intensity challenges according to the BWM. Interpretive structural modelling findings suggest that the lack of government initiatives has been driving other challenges with the highest driving power.

This work has been conducted in the Indian context, so careful generalization of the results is needed.

This work will give health-care stakeholders a better perspective regarding blockchain’s adoption. It will help health-care stakeholders, service providers, researchers and policymakers get a glimpse of the strategies for eradicating mentioned challenges. The analysis will help reduce the challenges’ impact on blockchain’s adoption in the Indian health-care sector.

The adoption of BT is a novel concept, especially in developing countries such as India. This is one of the few works addressing the challenges to BT adoption in the Indian health-care sector.