Ana Rita Gonçalves, Diego Costa Pinto, Saleh Shuqair, Anna Mattila and Anel Imanbay
This paper aims to bridge the extended reality framework and the luxury hospitality literature by providing insights into how immersive technologies using artificial intelligence…
Abstract
Purpose
This paper aims to bridge the extended reality framework and the luxury hospitality literature by providing insights into how immersive technologies using artificial intelligence (AI) can shape luxury value and consumer differentiation.
Design/methodology/approach
The authors conducted three experimental studies comparing immersive AI versus traditional hospitality across luxury contexts (hotels, restaurants and spas). Study 1 investigates the effect of immersive AI (vs traditional hospitality) on customers’ behavioral intentions and the need for differentiation using virtual-assisted reality. Study 2 tests the underlying mechanism of the need for differentiation and luxury value in an augmented reality context. Study 3 provides additional support for the proposed underlying mechanism using virtual-assisted reality in luxury hospitality.
Findings
The findings reveal that immersive AI (vs traditional) luxury hospitality reduces customers’ behavioral intentions of using such services and perceived luxury value. Moreover, the findings indicate that the intention to use immersive AI (vs traditional) luxury hospitality services is contingent upon customers’ need for differentiation.
Originality/value
The findings have important theoretical and managerial implications for immersive technologies in luxury hospitality. They shed light on the dynamics between integrating immersive AI into luxury hospitality and its impact on customers’ differentiation motives and perceived luxury value. The findings reveal the detrimental effect of using immersive AI (vs traditional hospitality) within this context.
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Márcia Maurer Herter, Saleh Shuqair, Diego Costa Pinto, Anna S. Mattila and Paola Zandonai Pontin
This paper aims to examine how the relationship norms established between customers and brands influence customer perceptions of crowdsourcing (vs firm-generated) cues.
Abstract
Purpose
This paper aims to examine how the relationship norms established between customers and brands influence customer perceptions of crowdsourcing (vs firm-generated) cues.
Design/methodology/approach
Four studies (N = 851) examine the moderating role of relationship norms on product labeling cues (crowdsourcing vs firm-generated) effects on brand engagement, and the underlying mechanism of self-brand connection.
Findings
The findings suggest that crowdsourcing (vs firm-generated) cues lead to higher brand engagement (Studies 1A–1B), mediated by self-brand connection (Studies 2–3). In addition, relationship norms moderate the effects (Study 3), such that under exchange brand relationships crowdsourcing (vs firm-generated) cues yield higher brand engagement, whereas communal brand relationships reverse such effects.
Practical implications
The findings provide valuable managerial implications by highlighting the importance of using relationship norms as diagnostic cues to successfully implement crowdsourcing initiatives.
Originality/value
This research adds to the customer-brand relationship literature by revealing an accessibility-diagnosticity perspective of consumers’ reactions to crowdsourcing (vs firm-generated) cues.
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Ana Rita Gonçalves, Amanda Breda Meira, Saleh Shuqair and Diego Costa Pinto
The digital revolution has changed consumer–service provider interaction, spawning a new generation of FinTech. This paper analyzes consumers' reactions to artificial intelligence…
Abstract
Purpose
The digital revolution has changed consumer–service provider interaction, spawning a new generation of FinTech. This paper analyzes consumers' reactions to artificial intelligence (AI) (vs human) decisions.
Design/methodology/approach
The authors tested their predictions by conducting two experimental studies with FinTech consumers (n = 503).
Findings
The results reveal that consumers' responses to AI (vs human) credit decisions depend on the type of credit product. For personal loans, the rejection by an AI provider triggers higher levels of satisfaction compared to a credit analyst. This effect is explained via the perceived role congruity. In addition, the findings reveal that consumers’ rejection sensitivity determines how they perceive financial services role congruity.
Originality/value
To the best of the authors' knowledge, this research is the first to jointly examine AI (vs human) credit decisions in FinTech and role congruity, extending prior research in the field.
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Salman Khan, Shafaqat Mehmood and Safeer Ullah Khan
Generative artificial intelligence (GenAI) is one of the most diffused AI technologies, capable of generating manifold forms of content, including music, text, images and…
Abstract
Purpose
Generative artificial intelligence (GenAI) is one of the most diffused AI technologies, capable of generating manifold forms of content, including music, text, images and synthetic data. The purpose of this study is to analyze the determinants that affect GenAI acceptance and its outcomes on both the explorative and exploitative forms of innovation.
Design/methodology/approach
The study employs a conceptual framework based on the technology-organization-environment (TOE) paradigm. Through Smart-PLS analysis, it examines empirical data retrieved from an online survey where 302 manufacturing companies took part.
Findings
It is found that GenAI has the potential to facilitate both exploratory and exploitative innovation, particularly via the moderating effect of environmental dynamism. Hence the adoption of GenAI has potential to improve organizational performance.
Originality/value
The study is the first empirical project to investigate factors that influence manufacturing firms' adoption of GenAI. As the first project to have integrated the TOE paradigm when examining the impact of environmental dynamism on exploratory and exploitative innovation, the study emphasizes the double innovation potential of GenAI in organizational performance improvement.