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1 – 10 of 251Disruptive 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…
Abstract
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.
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Kamrul Hasan Bhuiyan, Selim Ahmed and Israt Jahan
The study investigates the consumer’s attitude to using artificial intelligence (AI) devices in hospitality service settings considering social influence, hedonic motivation…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Practical implications
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.
Originality/value
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.
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Gang Li, Zhihuang Zhao, Lan Li, Yuanbo Li, Mengjiao Zhu and Yongxin Jiao
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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Hafiz Muhammad Wasif Rasheed, He Yuanqiong, Hafiz Muhammad Usman Khizar and Junaid Khalid
This study aims to identify, review and synthesize existing literature on key theories, drivers and barriers affecting consumer adoption or resistance to artificial intelligence…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Practical implications
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.
Originality/value
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.
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The purpose of this study is to provide insights and guidance for practitioners in terms of ensuring rigorous ethical and moral conduct in artificial intelligence (AI) hiring and…
Abstract
Purpose
The purpose of this study is to provide insights and guidance for practitioners in terms of ensuring rigorous ethical and moral conduct in artificial intelligence (AI) hiring and implementation.
Design/methodology/approach
The research employed two experimental designs and one pilot study to investigate the ethical and moral implications of different levels of AI implementation in the hospitality industry, the intersection of self-congruency and ethical considerations when AI replaces human service providers and the impact of psychological distance associated with AI on individuals' ethical and moral considerations. These research methods included surveys and experimental manipulations to gather and analyze relevant data.
Findings
Findings provide valuable insights into the ethical and moral dimensions of AI implementation, the influence of self-congruency on ethical considerations and the role of psychological distance in individuals’ ethical evaluations. They contribute to the development of guidelines and practices for the responsible and ethical implementation of AI in various industries, including the hospitality sector.
Practical implications
The study highlights the importance of exercising rigorous ethical-moral AI hiring and implementation practices to ensure AI principles and enforcement operations in the restaurant industry. It provides practitioners with useful insights into how AI-robotization can improve ethical and moral standards.
Originality/value
The study contributes to the literature by providing insights into the ethical and moral implications of AI service robots in the hospitality industry. Additionally, the study explores the relationship between psychological distance and acceptance of AI-intervened service, which has not been extensively studied in the literature.
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Maosheng Yang, Lei Feng, Honghong Zhou, Shih-Chih Chen, Ming K. Lim and Ming-Lang Tseng
This study aims to empirically analyse the influence mechanism of perceived interactivity in real estate APP which affects consumers' psychological well-being. With the growing…
Abstract
Purpose
This study aims to empirically analyse the influence mechanism of perceived interactivity in real estate APP which affects consumers' psychological well-being. With the growing application of human–machine interaction in real estate APP, it is crucial to utilize human–machine interaction to stimulate perceived interactivity between humans and machines to positively impact consumers' psychological well-being and sustainable development of real estate APP. However, it is unclear whether perceived interactivity improves consumers' psychological well-being.
Design/methodology/approach
This study proposes and examines a theoretical model grounded in the perceived interactivity theory, considers the relationship between perceived interactivity and consumers' psychological well-being and explores the mediating effect of perceived value and the moderating role of privacy concerns. It takes real estate APP as the research object, analyses the data of 568 consumer samples collected through questionnaires and then employs structural equation modelling to explore and examine the proposed theoretical model of this study.
Findings
The findings are that perceived interactivity (i.e. human–human interaction and human–information interaction) positively influences perceived value, which in turn affects psychological well-being, and that perceived value partially mediates the effect of perceived interaction on psychological well-being. More important findings are that privacy concerns not only negatively moderate human–information interaction on perceived value, but also negatively moderate the indirect effects of human–information interaction on users' psychological well-being through perceived value.
Originality/value
This study expands the context on perceived interaction and psychological well-being in the field of real estate APP, validating the mediating role and boundary conditions of perceived interactivity created by human–machine interaction on consumers' psychological well-being, and suggesting positive implications for practitioners exploring human–machine interaction technologies to improve the perceived interaction between humans and machines and thus enhance consumer psychological well-being and span sustainable development of real estate APP.
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Hamood Mohammed Al-Hattami, Nabil Ahmed Mareai Senan, Mohammed A. Al-Hakimi and Syed Azharuddin
This study aims to empirically examine accounting information system (AIS) success at the organizational level during COVID-19 era.
Abstract
Purpose
This study aims to empirically examine accounting information system (AIS) success at the organizational level during COVID-19 era.
Design/methodology/approach
Based on the information system success model, this paper developed its model and proposed a total of nine hypotheses. This paper gathered the required data via a questionnaire from Yemeni small and medium enterprises (SMEs) owners and managers. To test the proposed research model paths, SmartPLS software, which is known as partial least squares structural equation modeling, was used.
Findings
The results showed that the quality dimensions (information quality and system quality) positively affected the use of AIS and satisfaction; user satisfaction positively affected the use of AIS. Management support positively affected the AIS users' usage and satisfaction. Finally, the use dimensions (user satisfaction and usage) positively impacted the net benefits in terms of gaining a competitive advantage, productivity enhancement and saving time and cost. In all, this research has succeeded in providing support for DeLone and McLean's IS success model at the organizational level during the COVID-19 era.
Practical implications
AIS is becoming increasingly important for SMEs in low-income countries like Yemen, particularly in the present pandemic conditions (COVID-19 era). By using AIS, users can access the enterprise's data and conduct transactions without being limited by distance. Indeed, AIS proved its ability in enhancing the net benefits at the organizational level in the COVID-19 era in terms of gaining a competitive advantage, productivity enhancement and saving time and cost. However, AIS can only be considered useful to the enterprise if it is effective/successful.
Originality/value
This study is one of the first to have assessed the impact of AIS success at the organizational level in the era of COVID-19 pandemic, the context of Yemeni SMEs.
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Jennifer Huh, Hye-Young Kim and Garim Lee
This study examines how the locus of agency of brands' artificial intelligence (AI)–powered voice assistants (VAs) could lead to brand loyalty through perceived control, flow and…
Abstract
Purpose
This study examines how the locus of agency of brands' artificial intelligence (AI)–powered voice assistants (VAs) could lead to brand loyalty through perceived control, flow and consumer happiness under the moderating influences of brand image and voice congruity.
Design/methodology/approach
This study conducted a 2 (locus of agency: high vs. low) by 2 (brand image-voice congruity: congruent vs. incongruent) between-subjects experimental design. MANOVA, ANOVA and structural equation modeling (SEM) were conducted to test the hypothesized model.
Findings
ANOVA results revealed that human-centric (vs. machine-centric) agency led to higher perceived control. The interaction effect was significant, indicating the importance of congruency between brand image and VAs' voices. SEM results confirmed that perceived control predicted brand loyalty fully mediated by flow experience and consumer happiness.
Originality/value
This study provides evidence that the positive technology paradigm could carve out a new path in existing literature on AI-powered devices by showing the potential of a smart device as a tool for improving consumer–brand relationships and enriching consumers' well-being.
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Qian Chen, Yaobin Lu, Yeming Gong and Jie Xiong
This study investigates whether and how the service quality of artificial intelligence (AI) chatbots affects customer loyalty to an organization.
Abstract
Purpose
This study investigates whether and how the service quality of artificial intelligence (AI) chatbots affects customer loyalty to an organization.
Design/methodology/approach
Based on the sequential chain model of service quality loyalty, this study first classifies AI chatbot service quality into nine attributes and then develops a research model to explore the internal mechanism of how AI chatbot service quality affects customer loyalty. The analysis of survey data from 459 respondents provided insights into the interrelationships among AI chatbot service quality attributes, perceived value, cognitive and affective trust, satisfaction and customer loyalty.
Findings
The results show that AI chatbot service quality positively affects customer loyalty through perceived value, cognitive trust, affective trust and satisfaction.
Originality/value
This study captures the attributes of the service quality of AI chatbots and reveals the significant influence of service quality on customer loyalty. This study develops research on service quality in the information system (IS) field and extends the sequential chain model of quality loyalty to the context of AI services. The findings not only help an organization find a way to improve customers' perceived value, trust, satisfaction and loyalty but also provide guidance in the development, adoption, and post-adoption stages of AI chatbots.
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Rongxin Chen and Tianxing Zhang
In the global context, artificial intelligence (AI) technology and environmental, social and governance (ESG) have emerged as central drivers facilitating corporate transformation…
Abstract
Purpose
In the global context, artificial intelligence (AI) technology and environmental, social and governance (ESG) have emerged as central drivers facilitating corporate transformation and the business model revolution. This paper aims to investigate whether and how the application of AI enhances the ESG performance of enterprises.
Design/methodology/approach
This study uses panel data from Chinese A-share listed companies spanning the period from 2012 to 2022. Through a multivariate regression analysis, it examines the impact of AI on the ESG performance of enterprises.
Findings
The findings suggest that the application of AI in enterprises has a positive impact on ESG performance. Internal control systems within the organization and external information environments act as mediators in the relationship between AI and corporate ESG performance. Furthermore, corporate compliance plays a moderating role in the connection between AI and corporate ESG performance.
Originality/value
This paper underscores the pivotal role played by AI in enhancing corporate ESG performance. It explores the pathways to improving corporate ESG behavior from the perspectives of internal control and information environments. This discussion holds significant implications for advancing the application of AI in enterprises and enhancing their sustainable governance capabilities.
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