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One of the most marginalized communities in India is the Lesbian, Gay, Bisexual and Transgender (LGBT) community which commonly experiences discrimination. Many studies have countered that the LGBT community faces high discrimination in the banking and financing industry. As a result, this study concentrates on this marginalized community and its acceptance and continuation habit regarding mobile wallets. Consequently, this study has considered continuance intentions as a response to confirm the progress of the mobile-wallet industry. Also, this study tried to study the relationship between behavioral intention (BI) and continuous intention (CI) which is seriously lacks in the library of literature. The research operationalized the stimulus–organism–response (SOR) framework for the conceptual model and surveyed 100 self-proclaimed members of the LGBT community in India. The analysis has been done using the partial least structure (PLS). The findings demonstrate that variables like perceived trust (PT) directly influence the BI. On the other hand, variables like perceived ease of use (PEoU), social influence (SI), and satisfaction (S) doesn’t influence BI of the LGBT Community. The main outcome was a favorable association between BI and CI. It will help the stakeholders to understand how important this new market avenue is and how it can be explored. To ensure safe and secure transactions, a group think tank composed of important parties (financial institutions, mobile-wallet providers, the government, security specialists, etc.) should make recommendations. Mobile-wallet providers will attain benefit from this study’s understanding of user categories and ability to tailor their service offers as per the community.

The main objective of this study is to examine the impact of the Theory of Planned Behavior (TPB) on the behavioral intentions of Fintech usage. The model incorporates perceived behavioral control, attitude, and subjective norms, and the researcher has also included perceived risk and perceived trust. This study involved 192 respondents who were Jordanian citizens. An online questionnaire was used as the survey instrument for data collection. The proposed hypotheses were statistically tested using SmartPLS and SPSS software after examining the data based on initial assumptions. The outcome of the data analysis supports several published hypotheses, with all hypotheses being supported. The significant value of this research lies in its examination of the TPB in the Jordanian context, incorporating perceived risk and perceived trust. To the best of the authors’ knowledge, no previous study has tested the TPB in the Jordanian setting by including perceived risk and trust to understand the behavioral expectations of Jordanian citizens regarding Fintech usage.

Chatbot technology is growing swiftly across the banking and finance industry. The study aims to explore the influence of Task-Technology Fit (TTF), system suitability, perceived usefulness, social influence and satisfaction on respondents’ continuance intention among the chatbot-users. A total of 250 responses were collected using a structured questionnaire via social media across India. The measurement model was proposed based on the system usability (SUS) and TTF model with other constructs, and the hypothesis was tested using a structural equation model. The findings of the study highlighted and confirmed the association among five constructs: TTF, SUS, perceived usefulness, social influence, on satisfaction and continuance intention in the context of chatbots usage in banking.

The advancement of technology and increased sales of service robots have led to discussions about their usage. Recently, the use of service robots in accommodation businesses has become a topic of examination. This study aims to explore the behavioural intentions of accommodation business managers towards using service robots from the perspective of the technology acceptance model. As part of this project-supported study, the ‘Sanbot Elf’ service robot was rented for 14 days and demonstrated in six accommodation businesses in Kastamonu. Semi-structured interviews were conducted with managers and unit supervisors after the demonstration, and the process was also monitored through participant observation. The data were analysed using content analysis and participant observation methods. It was determined that participants' opinions on service robots were generally positive. Participants stated that personalised service presentations could be provided with service robots and that these robots could be used in different departments and marketing processes. The study concluded that service robots could positively impact service quality, are an exciting technology for accommodation businesses and the use of service robots could increase in the future. Participants' attitudes towards using service robots in accommodation businesses were positive in this context.

The purpose of this research was to investigate at the influence of technology acceptance model (TAM) characteristics including perceived ease of use, perceived compatibility, and perceived security on the perceived utility and actual use of mobile banking among Yemeni academics. It also investigated the function of perceived utility as a moderator in the link between TAM variables and mobile banking adoption. The sample size was 251 respondents who worked at universities in Yemen and were chosen using stratified random selection. According to the findings, perceived compatibility and perceived security had a substantial positive influence on perceived usefulness and real mobile banking use; however perceived simplicity of use had no effect on mobile banking usage. According to the results, perceived usefulness slightly mediated the association between perceived ease of use and security and mobile banking use, whereas it completely mediated the relationship between perceived compatibility and mobile banking usage. Overall, the research proved the significance of TAM elements in academics’ use of mobile banking in Yemen, offering a credible empirical framework for studying mobile banking usage in this setting.

This study investigates the motivation among customers to be more loyal to online food delivery applications (OFDA) services even after the COVID-19 epidemic by using perceived service quality aspects in Sri Lanka. The data were gathered by physically distributing a self-administrated questionnaire to clients in Sri Lanka who continue to use OFDA services on platform to customer (P2C) service delivery platforms to buy food despite the COVID-19 outbreak. Multiple regression is employed to analyse 287 effective observations, and the data revealed the significant positive effect of interaction, environment, outcome, and food qualities on customer loyalty to OFDA services. In fact, there is no impact from the delivery quality on customer loyalty to OFDA services due to outsourced food delivery. The findings suggest regular improvements in attributes such as interaction, environment, outcome, and food qualities in this hyper-competitive business environment. Further, this study sets substantial facts for the interested parties to establish an exemplary delivery system and other technological advancements to have a sustainable competitive advantage and solid customer base in the long run.

This research sought to examine the differential effect of chatbot banking artificial intelligence (AI) on consumer experience in the banking industry. A positivist paradigm was adopted to sample 389 consumers who were previously exposed to chatbot banking in Zimbabwe. A causal research design was employed whilst a quantitative approach was followed. In analysing data, the research study applied the structural equation modelling (SEM) technique. The authors found that chatbot banking significantly improves customer experience (CX) in the banking industry. Reliability and responsiveness of the chatbot need to be enhanced for effective improvements in CX. A need was also identified to enhance CX through the development of an ease-to-use chatbot which is embedded in everyday messaging applications of consumers. A significant association was also found between perceived benefits of chatbot banking and CX. This study informs the development of competitive advantage by banks and other related companies through AI-based CX management strategies. In times of pandemics and beyond, chatbot banking can be very instrumental in improving CX.

This chapter provides an overview of the strategic implications of chatbot use and implementation, including potential applications in marketing, and factors affecting customer acceptance. After presenting a brief history and a classification of conversational artificial intelligence (AI) and chatbots, the authors provide an in-depth review at the crossroads between marketing, business, and human–computer interaction, to outline the main factors that drive users' perceptions and acceptance of chatbots. In particular, the authors describe technology-related factors and chatbot design characteristics, such as anthropomorphism, gender, identity, and emotional design; context-related factors, such as the product type, task orientation, and consumption contexts; and users-related factors such as sociodemographic and psychographic characteristics. Next, the authors detail the strategic importance of chatbots in the field of marketing and their impact on consumers' perceived service quality, satisfaction, trust, and loyalty. After discussing the ethical implications related to chatbots implementation, the authors conclude with an exploration of future opportunities and potential strategies related to new generative AI technologies, such as ChatGPT. Throughout the chapter, the authors offer theoretical insights and practical implications for incorporating conversational AI into marketing strategies.

Artificial Intelligence (AI) has revolutionised the tourism industry, offering personalised experiences and streamlining operations. AI provides customised recommendations for travellers through data analysis and machine learning, making their journeys more meaningful. It has also improved efficiency through automated processes, chatbots and enhanced security measures. AI's ability to analyse large volumes of data enables tourism organisations to make data-driven decisions and target their marketing strategies effectively. One of the most notable contributions of AI in tourism is its ability to offer personalised recommendations. By analysing vast travel history, preferences and online behaviour, AI systems can provide tailored suggestions for destinations, accommodations, activities and dining options. This level of customisation enhances the overall travel experience, making it more relevant and satisfying for individual travellers. AI has also greatly improved operational efficiency within the tourism sector. Chatbots, powered by natural language processing, are increasingly being deployed by hotels, airlines and travel agencies to provide instant customer support and assistance. These chatbots can answer queries, offer recommendations and handle booking processes, reducing waiting times and enhancing customer satisfaction. In addition, facial recognition technology allows for quick and accurate identity verification at airports, hotels and other travel-related facilities. This improves security and provides travellers with a seamless and efficient experience. As technology advances, we expect AI to play a more prominent role in augmented reality, voice recognition and virtual assistants, further enhancing the travel experience and facilitating seamless interactions. In conclusion, AI has transformed the tourism industry by providing personalised recommendations, improving operational efficiency, enhancing security measures and enabling data-driven destination management.

Social media has become an indispensable part of modern politics. Its rise in the political arena has coincided with the decline in trust toward mainstream media. Today, more than half of the population gets their political news and information through social media platforms like Twitter and Facebook. Social media offers a great marketing opportunity to politicians as they allow them to bypass traditional media and communicate directly with voters, engage citizens during campaign and noncampaign periods, and create a brand image. As social media's influence in politics grows, so has the research devoted to political marketing on social media. It is against this backdrop that this chapter is written, which provides readers with an overview of the academic domain and the current state of literature. The chapter highlights the various research areas that have been explored in the literature and the implications of social media for political marketing strategy, along with the domain's current limitations and possible avenues of further research.