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Consumers' perceptions of product intelligence affect their willingness to accept smart offerings. This paper explores how people perceive various smart products based on their smartness profiles, composed of five distinct smartness facets. Additionally, the study investigates how these perceptions of product intelligence impact consumers' evaluation of factors that either promote or impede the adoption of smart products. These factors are examined as potential mediators in the adoption process. This paper aims to determine if the value-based adoption model can be applied to a broad range of smart service systems.

Consumers assessed one of 28 smart products in a scenario-based quantitative study. Multilevel structural equation modeling (SEM) is used to test the conceptual model, taking the nested data structure into account.

The findings show that product smartness essentially enhances usage intention via adoption drivers (enjoyment and usefulness) and reduces usage intention via adoption barriers (intrusiveness). In particular, the ability to interact in a humanlike manner increases the benefits consumers perceive, which in turn increases consumer acceptance. Only the smartness characteristic of awareness impairs usage intention, mediated by the perceived benefits of enjoyment and usefulness.

In contrast to previous research, which usually focuses on single smart products, this work examines a variety of different products, which allows for better transferability of the results to other smart offerings. Furthermore, prior research has mainly focused on single facets of product smartness or researched smartness on an aggregated level. By considering the consumer perception of each smartness facet, the authors gain deeper insights into the perceptual differences regarding product smartness and how this affects technology adoption via conflicting key acceptance drivers and barriers.

Considering the growth of the at-home smart technology industry and the increasing power of social media influencers, this study aims to examine how influencer endorsements affect individuals’ attitudes and trial intentions toward smart technology products.

An online experiment was conducted to investigate the impact of follower number and expertise domain of influencers and the trust propensity of individuals on their attitudinal and behavioral responses to influencer endorsements of smart technology products. The moderated mediation effect of perceived credibility was further examined.

The results demonstrated that individuals with lower trust propensity responded more positively to a microinfluencer with fewer followers and a specific area of expertise, which led to favorable attitudes and increased intention to try a smart technology product. However, the expertise domain was not a significant factor for the megainfluencer condition with a more extensive follower base. Interestingly, the interaction effects were not observed for individuals with higher trust propensity.

The results of this research provide practical implications for marketers who look for effective strategies for influencer marketing by demonstrating the significant impact of source-related cues, including follower number and expertise domain.

Based on the modality, agency, interactivity and navigability; source credibility; and persuasion knowledge models, this research explains how source-related cues of influencers affect credibility judgment, attitude formation and trial intentions for new technology products and how trust propensity as a personal dispositional factor varies the relationship.

As a smart service, location-based advertising (LBA) integrates advanced technologies to deliver personalized messages based on a user’s real-time geographic location and needs. However, research has shown that privacy concerns threaten the diffusion of LBA. This research investigates how privacy-related factors (i.e. LBA type, privacy self-efficacy (PSE) and consumer generation) impact consumers’ value-in-use and their intention to use LBA.

This study developed and examined an LBA value-in-use framework that integrates the role of LBA type, consumers’ PSE and consumer generation into the technology acceptance model (TAM). Data were collected through two experiments in the field with a total of 374 consumers. The proposed relationships were tested using PROCESS modeling.

The results reveal that pull (vs push) LBA causes higher value-in-use in terms of perceived usefulness and perceived ease of use, leading to greater usage intention. Further, the differences in the mediated relationship between pull- and push-LBA are larger among consumers of low PSE (vs high PSE) and Generation Z (vs other generations). The findings suggest that the consumer value-in-use brought about by LBA diminishes when using push-LBA for low PSE and Generation Z consumers.

This research is the first to integrate the privacy-related interactions of LBA type and consumer characteristics into TAM to develop a TAM-based LBA value-in-use framework. This study contributes to the literature on service value-in-use, smart services and LBA by clarifying the boundary conditions that determine the effectiveness of LBA in enhancing consumers’ value-in-use.

Industry 4.0 has put forward a smart perspective on managing supply chain networks and their operations. The current manufacturing system is primarily data-driven. Industries are deploying new emerging technologies in their operations to build a competitive edge in the business environment; however, the true potential of smart manufacturing has not yet been fully unveiled. This research aims to extensively analyse emerging technologies and their interconnection with smart manufacturing in developing smarter supply chains.

This research endeavours to establish a conceptual framework for a smart supply chain. A real case study on a smart factory is conducted to demonstrate the validity of this framework for building smarter supply chains. A comparative analysis is carried out between conventional and smart supply chains to ascertain the advantages of smart supply chains. In addition, a thorough investigation of the several factors needed to transition from smart to smarter supply chains is undertaken.

The integration of smart technology exemplifies the ability to improve the efficiency of supply chain operations. Research findings indicate that transitioning to a smart factory radically enhances productivity, quality assurance, data privacy and labour efficiency. The outcomes of this research will help academic and industrial sectors critically comprehend technological breakthroughs and their applications in smart supply chains.

This study highlights the implications of incorporating smart technologies into supply chain operations, specifically in smart purchasing, smart factory operations, smart warehousing and smart customer performance. A paradigm transition from conventional, smart to smarter supply chains offers a comprehensive perspective on the evolving dynamics in automation, optimisation and manufacturing technology domains, ultimately leading to the emergence of Industry 5.0.

Generation Z will be the leading consumer group in the future. Using convenience stores, the study provides an in-depth analysis on Gen Z’s current experience and future expectations from retail stores. The study further highlights the differences between Gen Z’s perception of convenience stores across three different regions – the USA, South Korea and Japan.

This study conducted a series of in-depth, semi-structured interviews with 36 Gen Z participants from the USA (12), South Korea (11) and Japan (13). All interviews were first coded based on a preselected list of themes and were further coded with new themes that emerged from exploratory coding.

Each regional cohort varied in terms of how they experienced and what they expected from convenience stores. US participants showed negative or utilitarian attitudes toward convenience stores, whereas South Korean participants had a positive, personal attachment to them. In comparison, Japanese participants had a relatively neutral attitude. However, all three groups showed a common preference for smart technology and health concerns surrounding convenience store foods.

Convenience store chains should consider the cultural nuances when designing future services. The chains should further strive to remove the health concerns about the foods provided at the stores and design smart technologies that enhance user experience.

The present study broadens the knowledge in this budding consumer segment where current research is limited. It further sheds light on the variance among Gen Zers across different cultural contexts.

Digitalization is revolutionizing the retail sector as today's consumers prefer a seamlessly integrated, fluid and irritation-free shopping experience enhanced with artificial intelligence (AI)-powered technologies. Literature highlights gaps in the understanding of the shopping experience in an omnichannel context, involving aesthetic, cognitive and affective experience dimensions. This research highlights the direct effects and the mechanism triggered in the presence of such device.

A sample of 259 consumers was interviewed at the point of sale. Data have been collected after a shopping experience in two concept stores belonging to the same fashion brand: (1) not equipped with AI-powered technology and (2) equipped with these tools. The measurement scales were validated through ANCOVA analysis and causal relationship analysis with structural equation modeling.

The results show that the presence of an in-store AI-powered technologies in a connected store generates a higher aesthetic reaction when visiting the store, a higher absorption when shopping through the flow and a higher intent to purchase. The authors further investigate the underlying mechanism triggered by the presence of this technology, which enables the authors to outline their consequences regarding purchase intention.

The study, conducted within an actual connected store in France, explores the impact of AI technology in connected retail environments on consumer responses. It is an early research in this field, shedding light on a rarely explored area. The authors’ research addresses a significant gap, providing insights into AI-driven retail experiences.

This study delves into the psychological processes underlying sport fans' post-purchase innovativeness behaviour. This exploratory research aims to establish a theoretical framework that elucidates the formation of sport fans' word-of-mouth (WOM) behaviours, particularly emphasising the structural relationship between motivated consumer innovativeness and satisfaction in using AR live-streaming services.

Utilising an online survey and convenience sampling, the study garnered a total of 243 usable responses from three online baseball fan communities in South Korea. Confirmatory factor analysis was employed to assess the psychometric properties of the constructs. Subsequently, a structural equation model was used to probe the influence of motivated consumer innovativeness on WOM, with a particular focus on the mediating role of satisfaction.

Three dimensions of motivated sport fans innovativeness – functional, hedonic and cognitive – showed a positive association with WOM, partly mediated by satisfaction. In contrast, socially motivated sport fans innovativeness did not directly lead to WOM but influenced it solely through satisfaction. The full mediating role of satisfaction in the relationship between socially motivated fans innovativeness and WOM was found.

This research stands out as one of the scant studies exploring motivated sport fans innovativeness in the context of AR live sport streaming. The findings not only corroborate but also augment the extant literature by empirically confirming that three dimensions of motivated fans innovativeness, coupled with satisfaction, are pivotal antecedents to WOM intention.

The primary purpose of this study is to examine the relationship between conumers' emotional attachment towards fashion apps and positive behavioral outcomes, such as e-WoM and repurchase intention. The study also aims to explore how e-servicescape, customer experience and perceived value of online shopping influence this relationships.

The study has used quantitative research methods to collect data from a sample of 484 consumers who had previous experience of purchasing using fashion apps. Data were collected from university students enrolled in university in Gujarat, India using an online self-administered questionnaire. The data are analyzed using structure equation modeling to determine the relationships between the variables under investigation.

The results demonstrate relationships between e-servicescape, customer experience and perceived value of online shopping, emotional attachment and the two consumer outcomes: repurchase intention and e-WoM. The study found support for hypotheses 1, 2 and 3, highlighting the influence of e-servicescape, customer experience and perceived value of online shopping in developing emotional attachment with fashion apps. The study also confirmed hypotheses 5 and 6, which suggest that consumers who have a stronger emotional attachment to fashion apps are more likely to intend to repurchase fashion products and engage in positive electronic word-of-mouth behavior for fashion brands.

In today's digital age, fashion apps are vital for fashion retailers to remain competitive and offer their customers a smooth and immersive shopping experience . Given the potential impact of fashion apps on the customer behavior, it is essential to investigate the relationship relationships between e-servicescape, customer experience and perceived value of online shopping, emotional attachment and the two consumer outcomes: repurchase intention and e-WoM in the context of fashion apps. The findings of the study are expected to contribute to the understanding of consumer behavior in the context of fashion apps and e-commerce more broadly. The results may also provide insights into how fashion retailers can improve their online presence and customer experiences to increase emotional attachment and positive behavioral outcomes.

The results of this study have several implications for online retail managers and fashion app developers. The study provides strong support for the idea that the extent to which online customers feel emotionally attached to fashion apps is strongly related to their e-WoM and repurchase intention. Moreover, the results of the study suggest that online retailers who are looking to cultivate emotional connections with consumers through fashion apps should prioritize three key areas: e-servicescape, customer experience and perceived value of online shopping.

The study’s objective is to measure the importance consumers attach to AI-based attributes, namely, chatbots, face recognition, virtual fitting room, smart parking and cashier-free station in retail stores. The study also examines the specific purpose of using these attributes for shopping.

A conjoint experiment was conducted using fractional factorial design. Consumers were given 14 profiles (AI attributes and its levels) to rank according to their visiting preferences.

The results revealed that the retail chatbot was considered the most important attribute, followed by face recognition, virtual fitting room, smart parking system and cashier-free station. Moreover, consumers prefer to use chatbots for in-store shopping assistance over alerts and updates, customer support and feedback. Similarly, consumers wish a face recognition facility for greetings while entering the store over other services. In addition, cluster analyses revealed that customer groups significantly differ in their preferences for AI-based attributes.

The study guides retail managers to invest in AI technologies to provide consumers with a technology-oriented shopping experience.

Our results provide an insight into the receptivity of AI technologies that consumers would like to experience in their favorite retail stores. The present study contributes to the literature by investigating consumer preferences for various AI technologies and their specific uses for shopping.