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Disruptive technologies are accelerating global growth. Artificial intelligence (AI) has the potential to transform the idea of delivering value to end users. On the other hand, the growth of Industry 5.0 has given rise to the concept of humanizing technology, and AI is a promising technology with the potential to contribute to business success. Nevertheless, the idea of value creation in the field of AI is novel, so it is necessary to define the meaning of value by understanding the context of AI applicability in different environments and industries. In this chapter, the author uses the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) procedure to conduct an SLR that provides interesting insights into the focus, industries, and methodologies and approaches used in existing research. Following the initial literature review on the state of the art of AI and value creation, the author also offers a reflection on the strategic implications of AI in the field of marketing, postulating a macrovalue creation framework that addresses the existence of implications on three different levels: emerging markets, Sustainable Development Goals, and adoption issues. Therefore, this chapter examines the value creation perspectives of AI to understand the current research focus and future directions.

The purpose of this paper is to investigate the factors influencing Palestinian consumer attitudes toward artificial intelligence (AI)-powered online banking, focusing on performance expectancy, effort expectancy, social influence and facilitating conditions while considering the moderating role of trust in financial institutions.

To test the hypotheses, an empirical study with a questionnaire was carried out. The study was completed by 362 Palestinian customers who use online banking services.

The findings of this paper show that performance expectancy, effort expectancy, social influence and facilitating conditions significantly influence consumer attitudes toward AI-powered online banking. Furthermore, trust in financial institutions as a moderating variable strengthens the impact of performance expectancy, effort expectancy, social influence and facilitating conditions on consumer attitudes toward AI-powered online banking. Therefore, more studies should focus on certain fields and cultural contexts to get a more thorough grasp of the variables influencing adoption and acceptability.

The study's findings may be specific to the Palestinian context, limiting generalizability. The reliance on self-reported data and a cross-sectional design may constrain the establishment of causal relationships and the exploration of dynamic attitudes over time. In addition, external factors and technological advancements not captured in the study could influence Palestinian consumer attitudes toward AI-powered online banking.

Financial institutions can leverage the insights from this research to tailor their strategies for promoting AI-powered online banking, emphasizing factors like perceived security and ease of use. Efforts to build and maintain trust in financial institutions are crucial for fostering positive consumer attitudes toward AI technologies. Policymakers can use these findings to inform regulations and initiatives that support the responsible adoption of AI in the financial sector, ensuring a more widespread and effective implementation of these technologies.

This research delves into Palestinian consumer attitudes toward AI-powered online banking, focusing on trust in financial institutions. It aims to enrich literature by exploring this under-explored area with meticulous examination, robust methodology and insightful analysis. The study embarks on a novel journey into uncharted terrain, seeking to unearth unique insights that enrich the existing literature landscape. Its findings offer valuable insights for academia and practitioners, enhancing understanding of AI adoption in Palestine and guiding strategic decisions for financial institutions operating in the region.

This study explores how predictor variables (value congruence and customer–AI-assisted exchanges) lead tourism businesses to meet customer needs through contactless technology and enhance their willingness to pay more.

The research model was designed from the perspective of consumer-brand relationships and acceptance of AI device use. This study collected and analyzed 647 valid questionnaires using the structural equation modeling (SEM) approach.

The findings indicate that value congruence and customer-AI-assisted exchanges (CAIX) affect intimacy. Intimacy affects satisfaction and the willingness to pay more for contactless technological services. Moreover, brand trust and sensory brand experience play a role in moderating contactless technological services.

Effective interactions between customers and AI-assisted services significantly contribute to overall satisfaction. When AI systems can understand and respond appropriately to customer queries, needs, and preferences, they enhance customer experience and satisfaction levels, increasing overall customer satisfaction with AI services.

Conceptual and empirical research over the past 20 years has moved the social media (SM) literature beyond the embryotic stage to a well-developed academic discipline. As the lead article in the special issue in the Journal of Research in Interactive Marketing on Cutting-Edge Research in Social Media and Interactive Marketing, this review and agenda article has two key goals: (1) to review key SM and interactive marketing research over the past three years and (2) to identify the next wave of high priority challenges and research opportunities.

Given the “cutting-edge” research focus of the special issue, this review and research agenda paper focused on articles published in 25 key marketing journals between January 2021 and March 2024. Initially, the search request was for articles with “social media, social selling, social commerce” located in the article title, author-selected key words and journal-selected keywords. Later, we conducted searches based on terminology from articles presented in the final review. In total, over 1,000 articles were reviewed across the 25 journals, plus additional ones that were cited in those journals that were not on the initial list.

Our review uncovered eight key content areas: (1) data sources, methodology and scale development; (2) emergent SM technologies; (3) artificial intelligence; (4) virtual reality; (5) sales and sales management; (6) consumer welfare; (7) influencer marketing; and (8) social commerce. Table I provides a summer of key articles and research findings for each of the content areas.

As a literature review and research agenda article, this paper is one of the most extensive to date on SM marketing, and particularly with regard to emergent research over the past three years. Recommendations for future research are integrated through the paper and summarized in Figure 2.

Consumer welfare is one of the eight emergent content areas uncovered in the literature review. Specific focus is on SM privacy, misinformation, mental health and misbehavior.

The study investigates the consumer’s attitude to using artificial intelligence (AI) devices in hospitality service settings considering social influence, hedonic motivation, anthropomorphism, effort expectancy, performance expectancy and emotions.

This study employed a quantitative methodology to collect data from Bangladeshi consumers who utilized AI-enabled technologies in the hospitality sector. A total of 343 data were collected using a purposive sampling method. The SmartPLS 4.0 software was used to determine the constructs' internal consistency, reliability and validity. This study also applied the partial least squares structural equation modeling (PLS-SEM) to test the research model and hypotheses.

The finding shows that consumer attitude toward AI is influenced by social influence, hedonic motivation, anthropomorphism, performance and effort expectancy and emotions. Specifically, hedonic motivation, social influence and anthropomorphism affect performance and effort expectations, affecting consumer emotion. Moreover, emotions ultimately influenced the perceptions of hotel customers' willingness to use AI devices.

This study provides a practical understanding of issues when adopting more stringent AI-enabled devices in the hospitality sector. Managers, practitioners and decision-makers will get helpful information discussed in this article.

This study investigates the perceptions of guests' attitudes toward the use of AI devices in hospitality services. This study emphasizes the cultural context of the hospitality industry in Bangladesh, but its findings may be reflected in other areas and regions.

The purpose of this study is to analyze state-of-the-art knowledge of artificial intelligence (AI) research in hospitality.

This study adopts the theory-context-methods framework to systematically review 100 AI-related articles recently published (i.e. from 2021 to April 2023) in three top-tier hospitality journals, namely, the International Journal of Contemporary Hospitality Management, International Journal of Hospitality Management and Journal of Hospitality Marketing and Management.

Findings suggest that studies of AI applications in hospitality are mostly theory-driven, whereas most AI methods research adopts a data-driven approach. State-of-the-art AI applications research exhibits the most interest in service robots. In AI methods research, little attention was paid to the amid-service/experience.

This study reveals inadequacies in theory, context and methods in contemporary AI research. More research from hospitality suppliers’ perspectives and research on generative AI applications are advocated in response to the unveiled research gaps and recent AI developments.

This study classifies the most recent AI research in hospitality into two main streams – AI applications research and AI methods research – and discusses the gaps in each research stream and latest AI developments. The paper then suggests future research directions to guide researchers in advancing AI research in hospitality.

Artificial intelligence (AI) has become a pivotal technology in both marketing and daily life. Despite extensive research on the benefits of AI, its adverse effects on customers have received limited attention.

We employed meta-analysis to synthesise effect sizes from 45 studies encompassing 50 independent samples (N = 19,503) to illuminate the negative facets of AI's impact on customer responses.

Adverse effects of AI, including privacy concern, perceived risks, customer alienation, and uniqueness neglect, have a negative and significant effect on customers' cognitive (perceived benefit, trust), affective (attitude and satisfaction) and behavioural responses (purchase, loyalty, well-being). Additionally, moderators in AI (online versus offline), customer (age, male vs. female), product (hedonic vs. utilitarian, high vs. low involvement), and firm level (service vs. manufacturing) and national level (individualism, power distance, masculinity, uncertainty avoidance, long-term orientation) moderate these relationships.

Our findings inform marketing managers about the drawbacks of utilising AI as part of their value proposition and provide recommendations on how to minimise these effects in different contexts. Additionally, policymakers need to consider the dark side of AI, especially among the vulnerable groups.

This paper is among the first research studies that synthesise previous research on the dark side of AI, providing a comprehensive view of its diminishing impact on customer responses.

This study investigates the influence of artificial intelligence (AI) stimuli on customer stickiness (CS), the mediation effects of social presence (SP) and the moderating impacts of customer traits in this influencing process.

Drawing on the arousal theory and social response theory, a conceptual model was established and tested by a data set of 268 customers in the catering industry.

The results indicate that AI stimuli, such as perceived personalization and perceived interactivity, positively affect CS. SP partially mediates the influence of AI stimuli on CS. Customer traits such as customers' need for interaction (NFI) and novelty seeking (NS) actively moderate the mediating effects of SP.

This study advances the interactive marketing literature from three aspects. Firstly, instead of focusing on the functional aspects of AI stimuli, it extends our understanding of AI-enabled interactive marketing by examining the effects of social and emotional aspects of AI stimuli on customer response. Secondly, it extends our understanding of social response by illuminating the mediating effects of SP between AI stimuli and CS. Finally, it provides new insights and empirical evidence for the research focus on customer traits in AI-enabled interactive marketing.

This study examines the link between the knowledge creation process, ambidextrous innovation, and competitive advantage. Further, this study also tested the moderating role of organizational agility on the relationship between the knowledge creation process and ambidextrous innovation.

The empirical study’s data were collected by surveying 306 respondents employed in 140 Pakistani Small and Medium Enterprises (SMEs). The questionnaire was designed according to the study’s requirements and was based on theoretical knowledge and findings from previous research on the knowledge-creation process, ambidextrous innovation, and competitive advantage. All hypotheses were tested using a structured regression method.

The study indicates that the knowledge creation process significantly impacts a firm’s competitive advantage. Additionally, this study demonstrates that ambidextrous innovation can moderate the relationship between the knowledge-creation process and competitive advantage.

Future studies should examine mediating factors, such as organizational culture, leadership style, and industry characteristics, as well as moderating variables, such as environmental turbulence.

This study guides SME leaders on the importance of knowledge creation and ambidextrous innovation in achieving operational success and gaining a competitive advantage.

This study explores how the knowledge creation process directly and indirectly, enhances organizational capacity for competitive advantage through the mediating roles of ambidextrous innovation and the moderating role of organizational agility.

This study aims to identify, review and synthesize existing literature on key theories, drivers and barriers affecting consumer adoption or resistance to artificial intelligence (AI) in the hospitality sector.

This study aims to conduct a complete literature review of the accrued knowledge generated so far on AI in the hospitality sector. To attain the overall objectives of this study, we used the systematic literature review (SLR) method. This method systematically handles the diversity of knowledge in a specific topic to answer precise research questions. It also generates new visions through a synthesis of the literature, to identify the knowledge gaps, set the new directions for the future researcher and provide sufficient guidance to inform the policy and practice.

The findings of this study are presented in three sections, as follows: descriptive analysis, content analysis and synthesized framework. The findings highlighted the state-of-the-art mapping of the existing research in terms of publication frequency over time and across publication outlets, key theories, methods and geographies. In addition, literature on consumer adoption (or resistance) of AI in hospitality is content analyzed to highlight key drivers and barriers. Moreover, this review critically evaluates extant literature and sets future agendas by postulating specific research questions for further knowledge development in this field of study.

The SLR focused on consumer adoption or resistance to use AI in hospitality literature. The future researcher may include additional streams to get better results.

The study findings will help multiple stakeholders to understand the underlying causes of customer resistance or barriers to the intention to use/adopt AI services in the hotel sector. Furthermore, study results will allow them to better analyze the relationship between customer barriers, intents or consumer decision behaviors.

First, this study provides a comprehensive synthesis of the literature on the consumer adoption or resistance of AI in hospitality. This study categorizes the existing diversified literature in two main themes – drivers and barriers – to present a simplistic picture of the existing literature. Second, the review highlights the gaps and limitations in existing research and provides guidance for future scholars. Third, the key contribution of this review is the development of a unified framework on the consumer adoption or resistance of AI in the hospitality sector. That is, this study puts forward the behavioral reasoning theory framework and suggests that future research using this lens will immensely contribute to existing literature. Finally, this study facilitates the practitioners to understand the key motivating and hindering factors affecting the adoption and resistance behavior.