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In an empirical examination of the link between product involvement and brand loyalty, a convenience sample of 253 students were asked to complete a questionnaire relating to two products which had been found in preliminary qualitative research to be associated with contrasted levels of involvement. The factor structure of involvement was found to vary between the two product categories (sneakers and pens). Furthermore, the link between product involvement and brand loyalty was found to involve different aspects of product involvement for each of the products concerned. Hence, future researchers in the area should be mindful that product involvement and brand loyalty are not universal constructs: they should be examined within specific consumer and product parameters.

Gives an in depth view of the strategies pursued by the world’s leading chief executive officers in an attempt to provide guidance to new chief executives of today. Considers the marketing strategies employed, together with the organizational structures used and looks at the universal concepts that can be applied to any product. Uses anecdotal evidence to formulate a number of theories which can be used to compare your company with the best in the world. Presents initial survival strategies and then looks at ways companies can broaden their boundaries through manipulation and choice. Covers a huge variety of case studies and examples together with a substantial question and answer section.

Due to the popularity of mobile devices and the development of artificial intelligence (AI), AI-powered mobile fitness applications (MFAs) have entered people's daily lives. However, the extant literature lacks empirical investigations that explore users' continuance usage intentions regarding AI-powered MFAs. To fill this research gap, this paper employs goal-setting theory to establish a research model for exploring how AI-enabled features (i.e. intelligence and anthropomorphism) affect users' perceptions of goal difficulties and goal specificities, which in turn affect their MFA continuance usage intentions.

This paper uses a survey method to analyze the research model, and a total of 223 responses are collected. The partial least squares (PLS) technique is utilized for data analysis.

The results show that intelligence and anthropomorphism affect the continuance usage intention of MFA users through their goal difficulty and specificity. Both intelligence and anthropomorphism positively influence goal specificity, whereas they negatively affect goal difficulty. In addition, goal specificity increases users' MFA continuance usage intention, whereas goal difficulty decreases users' continuance usage intention. The findings of this study provide theoretical contributions for AI technology adoption research and offer practical strategies for firms to retain MFA users.

Based on goal-setting theory, this study reveals that as two primary AI features of contemporary mobile fitness apps, intelligence and anthropomorphism, can increase comprehension of users' perceptions regarding goal difficulty and specificity in the context of users' continuance usage intentions toward AI-powered MFAs.

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.

The rapid growth of technology, including artificial intelligence (AI), in the banking industry has played a disrupting role in traditional banking channels. This study aims to investigate factors that influence the attitudes and perceptions of digital natives pertaining to mobile banking and comfort interacting with AI-enabled mobile banking activities.

Data were collected from 218 digital natives. This paper uses multivariate regression and two separate multiple regression analyses to examine the differential effects of technology-based (i.e. attitudes toward AI, relative advantage, perceived trust and security in specific mobile banking activities) and non-technology based (i.e. need for service, quality of service) factors on mobile banking usage and AI-enabled mobile banking services.

This study identifies determining factors for mobile banking and AI-enabled mobile banking services. Results indicate a divide in how digital natives perceive relative advantage between our two dependent variables. Consistent with previous studies, the relative advantage construct has the most impact on mobile banking usage. However, relative advantage was not significant for AI-enabled mobile banking, suggesting an extra layer of complexity that goes beyond convenient fast banking.

A limitation of this study is that it does not incorporate age groups outside of digital natives. Further research is needed to test for differential effects between age groups. In addition, the discovery of no significant impact of relative advantage on AI mobile banking warrants more research on the similarities and differences between mobile banking and AI-enabled mobile banking.

To better appeal to digital natives, it is suggested that the banking industry emphasize mobile banking’s anywhere/anytime access to financial accounts, as this is important to college-age customers who may not live near their local banking institution. Moreover, the paper suggests that improvement to mobile banking features for one-on-one interpersonal contact with bank employees is needed.

This study addresses the gap in the understanding of how digital natives perceive mobile banking in comparison to AI-enabled mobile banking services.

The literature reports inconsistent findings about the effects of social media usage (SMU). Researchers distinguish between active and passive social media usage (ASMU and PSMU), which can generate different effects on users by social support and social comparison mechanisms, respectively. Drawing on social presence theory (SPT), this study integrates an implicit social presence mechanism with the above two mechanisms to explicate the links between SMU and seniors' loneliness.

Data were collected from a field study by interviewing seniors living in eight aging care communities in China. Loneliness, social media activities and experiences with social media in terms of online social support (OSS), upward social comparison (USC) and social presence (SP) were assessed. Factor-based structural equation modeling was used to analyze the data.

OSS can mediate the relationship between ASMU and seniors' loneliness. Moreover, SP mediates between ASMU, PSMU, and seniors' loneliness, and between OSS, USC and seniors' loneliness. OSS mediates the relationship between ASMU and SP, and USC mediates the relationship between PSMU and SP.

This study shows that social media can alleviate seniors' loneliness, which could help relieve the pressures faced by health and social care systems. Social presence features are suggested to help older users interact with social health technologies in socially meaningful ways.

This study not only demonstrates that SP can play a crucial role in the relationship between both ASMU and PSMU and loneliness, but also unravels the links between SP and OSS, as well as USC.

Undertakes a systems study, in the language of mathematics, of the concepts of “whole” and “part”. The concepts of linked systems, product systems, Cartesian product systems and inverse limit systems are used to study “wholeness”, and their factor systems are used and considered as “parts”. Discusses comparisons between models of “whole” and between “parts” and “whole”. Presents the application background and poses some open questions.

Human resource managers are adopting AI technology for conducting various tasks of human resource management, starting from manpower planning till employee exit. AI technology is prominently used for talent acquisition in organizations. This research investigates the adoption of AI technology for talent acquisition.

This study employs Technology-Organization-Environment (TOE) and Task-Technology-Fit (TTF) framework and proposes a model to explore the adoption of AI technology for talent acquisition. The survey was conducted among the 562 human resource managers and talent acquisition managers with a structured questionnaire. The analysis of data was completed using PLS-SEM.

This research reveals that cost-effectiveness, relative advantage, top management support, HR readiness, competitive pressure and support from AI vendors positively affect AI technology adoption for talent acquisition. Security and privacy issues negatively influence the adoption of AI technology. It is found that task and technology characteristics influence the task technology fit of AI technology for talent acquisition. Adoption and task technology fit of AI technology influence the actual usage of AI technology for talent acquisition. It is revealed that stickiness to traditional talent acquisition methods negatively moderates the association between adoption and actual usage of AI technology for talent acquisition. The proposed model was empirically validated and revealed the predictors of adoption and actual usage of AI technology for talent acquisition.

This paper provides the predictors of the adoption of AI technology for talent acquisition, which is emerging extensively in the human resource domain. It provides vital insights to the human resource managers to benchmark AI technology required for talent acquisition. Marketers can develop their marketing plan considering the factors of adoption. It would help designers to understand the factors of adoption and design the AI technology algorithms and applications for talent acquisition. It contributes to advance the literature of technology adoption by interweaving it with the human resource domain literature on talent acquisition.

This research uniquely validates the model for the adoption of AI technology for talent acquisition using the TOE and TTF framework. It reveals the factors influencing the adoption and actual usage of AI technology for talent acquisition.

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.