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The purpose of this paper is to identify and examine the important factors that could affect consumers' behavioural intention and use behaviour towards mobile payment services during COVID-19.

The proposed model extends meta-Unified Theory of Acceptance and Use of Technology (meta-UTAUT) model with perceived severity and self-efficacy factors affecting consumers' behavioural intention and use behaviour towards mobile payment services. A convenient sampling technique has been utilized to gather data from a self-administered questionnaire. The data collection was restricted to the online mode to avoid any physical contact considering the COVID-19 situation.

The findings revealed that performance expectancy, effort expectancy and perceived severity have a significant positive impact on consumers' attitude; facilitating conditions has a significant positive impact on effort expectancy; self-efficacy has a significant positive impact on effort expectancy; attitude has a significant positive impact on behavioural intention; and behavioural intention has a significant positive impact on use behaviour. Social influence did not confirm any significant relationship.

The current research study has utilized a non-probability convenient sampling technique to gather data through a self-administered questionnaire. The data collection was restricted to the online mode to avoid any physical contact considering the COVID-19 situation. The respondents were adopters of mobile payment services. The scope of the study is the COVID-19 context or related chronic diseases context where major preventive mechanisms such as social distancing and avoidance of physical contacts are vital.

This study has extended the meta-UTAUT model with the COVID-19 context-specific constructs and relationships. The undertaken work has strengthened the explanability of the model. The inclusion of context relevant variables such as perceived severity and self-efficacy and their association with the existing meta-UTAUT framework have enriched the context of the study. The current study offers a holistic understanding of significant factors influencing Indian consumers’ adoption of mobile payment services in the COVID-19 context.

Purpose: Nowadays, many terms like computer vision, deep learning, and machine learning have all been made possible by recent artificial intelligence (AI) advances. As new types of employment have risen significantly, there has been significant growth in adopting AI technology in enterprises. Despite the anticipated benefits of AI adoption, many businesses are still struggling to make progress. This research article focuses on the influence of elements affecting the acceptance procedure of AI in organisations.

Design/Methodology/Approach: To achieve this objective, propose a hierarchical paradigm for the same by developing an Interpretive Structural Modelling (ISM). This paper reveals the barriers obstructing AI adoption in organisations and reflects the contextual association and interaction amongst those barriers by emerging a categorised model using the ISM approach. In the next step, cross-impact matrix multiplication is applied for classification analysis to find dependent, independent and linkages.

Findings: As India is now focusing on the implementation of AI adoption, therefore, it is essential to identify these barriers to AI to conceptualise it systematically. These findings can play a significant role in identifying essential points that affect AI adoption in organisations. Results show that low regulations are the most critical factor and functional as the root cause and further lack of IT infrastructure is the barrier. These two factors require the most attention by the government of India to improve AI adoption.

Implications: This study may be utilised by organisations, academic institutions, Universities, and research scholars to fill the academic gap and faster implementation of AI.

In this chapter, to explore the past and understand the present scenario in financial market, a comprehensive literature review (LR) is performed, in which 809 articles from the database of Scopus for the last 10 years are extracted and analyzed using VOSviewer software for bibliometric analysis. Citation analysis of the popular identified factors is highlighted that will help the future researchers to focus on the identified popular factors for research in the financial market. The chapter also presents a conceptual model of financial market, to uncover the future of financial markets.

This study aims to explore the consumers’ choices of mobile payments (m-payments) using a comprehensive unified model. The financial technology for digital m-payment has been increasingly introduced in the market, yet their acceptance has remained low.

This study uses the unified theory of acceptance and use of technology (UTAUT) with additional constructs of social influence, trust, anxiety, personal innovativeness and grievance redressal (GR). Structural equation modeling is used to evaluate the predictive model of attitudes toward m-payment. Individuals’ responses to questions regarding their attitude and intention to accept m-payment were gathered and examined through the lens of extended UTAUT model.

While the model supports TAM classical role, empirical examination of the model revealed that users’ attitudes and intentions are influenced by trust, personal innovativeness and social influence. Moreover, intention to use and GR are significant positive predictors of m-payment usage behavior.

M-payment provides customers with new digital payment platforms while providing businesses and marketing agents with more alternatives for online marketing. However, there is not much reported about m-payment adoption in Pakistan. This research introduces and evaluates new constructs that were not included in the original model. In Pakistan, to the best of the authors’ knowledge, this is a first of its kind of research which is purely based on the customers’ perspective of m-payment adoption.

The paper intends to review academic research on peer to peer (P2P) accommodation sharing, notably Airbnb, for 2010–2022 and to identify the knowledge gaps for future research directions.

Numerous databases were searched using keywords. Based on the central theme of the research papers, the papers were divided into eight segments—consumer behavior, host behavior, host–guest relationship (HGR), trust in Airbnb, dominant theories in Airbnb, Airbnb regulation, Airbnb and hotels and macro impacts of Airbnb. In-depth content analysis resulted in the final 101 papers for inclusion.

The review advances comprehension of the Airbnb phenomenon by enriching the literature with new and most recent studies. Most existing Airbnb research has been conducted in Europe, USA/Canada, followed by Asian countries like China, Singapore, S. Korea and India. Future studies should include South America, Africa and other developing nations. More cross-cultural studies are required to understand consumer and host behavior in different cultural settings. Numerous proposals to fulfill the research gaps identified by the paper are discussed.

The study will give better insights into the spiraling P2P accommodation economy. The study will be useful to researchers, scholars, Airbnb, the hotel industry, vacation rental players and destination marketing organizations by relating the study findings to practical competition analysis. The study provides deeper insights into the decision-making process of both guests and hosts by examining the relevant motivators and constraints. It will also assist the Airbnb platform in identifying its strength over the traditional hotel industry and other vacation rentals. The findings will also assist policymakers in better controlling the Airbnb phenomena by providing a comprehensive view of the micro and macro environment.

The paper includes the most recent studies from Asian countries like India, Singapore, China, Korea and Taiwan, not covered by earlier reviews. Prior studies mainly focused on European and American countries. Also, the paper tried to cover the macro impacts of Airbnb in-depth and the effects of COVID-19.

The purpose of this paper is to propose a model that examines the relationships among the five dimensions of the unified theory of acceptance and use of technology (UTAUT) toward the overall behavioral intentions (BIs); to use cashless payment systems in Thailand, which are practically based on the basic models and theories of consumer behavior such as the theory of reasoned action (TRA), theory of planned behavior (TPB) and technology acceptance model (TAM); and to explain the indirect effects between UTAUT and BIs to use cashless payment systems mediating by perceived risk and trust.

A total of 708 respondents, who have had an experience with a cashless payment system in Thailand, were selected using a stage sampling method. The data obtained from the participants were analyzed using a structural equation modelling approach.

The results of this paper reveal that UTAUT model, perceived risk and trust have all significant influences on BIs to use a cashless payment system. This suggests that consumers in Thailand adopt to specific financial technological innovation if they perceive that the risk is low and they can trust the system, especially if it is associated with a reliable online banking network.

The basic understanding of the UTAUT model that influences BIs to use cashless payment systems has been the focus of this current paper. This paper empirically examined the overall direct and indirect influences of UTAUT model and perceived risk, trust and BI to use. This current paper also expands the UTAUT theory by exploring several dimensions (i.e. performance expectancy, effort expectancy and social influence). Research findings reveal that effort expectancy can reduce perceived risk and increase trust in Thailand's cashless payment systems. This can generate more customer interest and engagement, as well as provide insights into customers' intentions in using a cashless payment system.

This study aims to investigate the influence of environmental factors on individual personality traits associated with mobile paymens (MP) adoption using the technological personal environment (TPE) theory as a framework for the proposed theoretical model.

A total of 736 feedback from respondents was used to validate the proposed model using structural equation modeling. The model comprises Trust and Self-efficacy to explain MP adoption from a personal trait perspective. Meanwhile, environmental aspects are represented by social influence, vendor regulations and network externalities.

The result indicates that self-efficacy has the most significant direct effect on user intention to use MP, followed in decreasing order of significance by social influence, trust, vendor regulations and network externalities. Furthermore, social influence is the most contributing aspect from the environmental area that influences user intention directly and indirectly through trust and self-efficacy as mediators. Meanwhile, the moderating effect analysis also found that gender moderates the effect of user self-efficacy on MP adoption.

This study fills the gap by comparing trust and self-efficacy and exploring how those factors are developed and affected by the environmental aspect of MP usage. It was discovered that self-efficacy was the most influential construct influencing the adoption of MP. Social influence was identified as the primary environmental factor that directly impacts user intention regarding MP usage. Furthermore, gender was shown as a moderator, as males place a higher value on self-efficacy as a factor affecting their intention to embrace MP in comparison to females.

This research empirically studies consumers' continued intention to use mobile food delivery applications (apps) during the post-pandemic era in Saudi Arabia.

Using the unified theory of adoption and use of technology 2 (UTAUT2) as a theoretical model, this study collected data from a survey of 304 Saudi Arabian consumers. Structural equation modelling (SEM) was used to examine the proposed model and its hypotheses.

Social influence and performance expectancy (PE) had the strongest effects on the intention to continue using mobile food delivery apps in the post-pandemic era. In addition, effort expectancy (EE) significantly influenced PE regarding the adoption of food delivery apps. Meanwhile, EE was not an important predictor of the continued intention to use mobile food delivery apps in Saudi Arabia.

This study enriches the literature on consumers' continued intention to use food delivery apps in the post-pandemic era, a subject that has rarely been studied. In addition, this study expands the theoretical potential of the UTAUT2 model by examining the role of trust in continued intention and the effect of PE on EE in the adoption of food delivery apps during the post-pandemic era in Saudi Arabia.