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• Explain what a smart consumer is through Generation Z views

• Understanding the nature of decision-making process with the use of smart technologies

Explain what a smart consumer is through Generation Z views

Understanding the nature of decision-making process with the use of smart technologies

This study aims to examine the influence of the derived attributes of embedded artificial intelligence-mobile smart speech recognition (AI-MSSR) technology, namely perceived usefulness, perceived ease of use (PEOU) and perceived enjoyment (PE) on consumer purchase intention (PI) through the chain relationships of attitudes to AI and consumer smart experience, with the moderating effect of consumer innovativeness and Generation (Gen) X and Gen Y in fashion retail.

The study employed a quantitative survey strategy, drawing a sample of 836 respondents from Sri Lanka and India representing Gen X and Gen Y. The data analysis was carried out using smart partial least squares structural equation modelling (PLS-SEM).

The findings show a positive relationship between the perceived attributes of MSSR and consumer PI via attitudes towards AI (AAI) and smart consumer experiences. In addition, consumer innovativeness and Generations X and Y have a moderating impact on the aforementioned relationship. The theoretical and managerial implications of the study are discussed with a note on the research limitations and further research directions.

To multiply the effects of embedded AI-MSSR and consumer PI in fashion retail marketing, managers can develop strategies that strengthen the links between awareness, knowledge of the derived attributes of embedded AI-MSSR and PI by encouraging innovative consumers, especially Gen Y consumers, to engage with embedded AI-MSSR.

This study advances the literature on embedded AI-MSSR and consumer PI in fashion retail marketing by providing an integrated view of the technology acceptance model (TAM), the diffusion of innovation (DOI) theory and the generational cohort perspective in predicting PI.

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.

The purpose of this study is to explore consumers’ profiles for and purchase intentions towards smart environmental objects. It segments consumers according to two apparently contradictory dimensions of smart environmental objects: environment (i.e. environmental concern and environmental beliefs) and technology (i.e. materialistic values and technological beliefs).

A cluster analysis was conducted among 658 French consumers based on their environmental concern, environmental beliefs, materialistic values, perceived usefulness and perceived ease of use. A regression analysis identifies the variables with the greatest influence on purchase intentions.

Four segments result from the analysis: unconcerned, retro eco-friendly, non-materialistic converted and converted. The converted consumer segment had the highest purchase intentions and exhibited high levels of both environmental beliefs and perceived usefulness compared with the other segments. Both environmental and technological beliefs and environmental concern influence purchase intentions more broadly.

A combined consideration of both environmental and technological beliefs is necessary to influence purchase intentions towards smart environmental objects. This study challenges some previous research that assumes a clear opposition between materialism and environmentalism.

This study proposes tailored managerial recommendations for each of the four consumer segments in the context of smart environmental objects.

This study provides novel insights into consumers’ concerns, beliefs and values in the rapidly expanding context of smart environmental objects.

The purpose of this study is to gain a better conceptualization and measurement of smart shopping. The specific objectives are to: investigate consumers' perceptions of the term smart shopping; develop a measure of smart shopping; and validate the measure of smart shopping.

The research includes a comprehensive literature review, focus group interviews, and in‐depth interviews for initial item generation and instrument development. Scale development consists of a pilot test (n=100), a pretest (n=237), and main study (n=1,474).

The findings indicate that smart shopping includes consumers seeking to minimize the expenditure of time, money, or energy to gain hedonic or utilitarian value from the experience.

In‐store shopping was examined based on shopping for clothing, grocery, or electronics; therefore caution must be used when applying the smart shopping scale to other shopping contexts or product categories.

Gaining a better understanding of the smart shopper will enable retailers to more accurately target this consumer group. Focus could be placed on saving time or saving energy in addition to the traditional emphasis on saving money. Retailers could also provide a combination of utilitarian and hedonic experiences for consumers.

This study conceptualizes and tests the term smart shopping from a broader perspective than previous studies that primarily focused on monetary savings in the grocery shopping context. Smart shopping includes the desire for efficient shopping but emphases on the components of an efficient trip may differ from traditional theories.

This study develops the idea of smart retailing, exemplified in innovative, technology-enriched retail services as part of service-oriented strategies. In particular, the purpose of this paper is to provide a new integrated framework to understand the emerging retail scenario based on the smart usage of technologies to improve retail service and develop innovation management strategies. This framework will provide a comprehensive understanding the basic forms of smart retailing as the current competitive scenario.

As a viewpoint, this paper employs an interdisciplinary approach, drawing upon the actual challenges in retailing, to propose a new perspective, the smart retailing one, to describe the new competitive scenario and formulates an emerging research agenda.

The present paper contributes to research on innovation and technology management for retailing by examining the key dimensions of smart retailing, which aims to enhancing retail service quality and retailers’ performance.

The paper clearly explains how current retailing is moving to a smart perspective, and how retail management should be adapted to successfully perform in the current service-dominant logic scenario, as consequence of the increasing consumer involvement in service co-production and the rapid growth of digital technologies.

This study aims to examine the effects of perceived product–brand fit and brand type on consumer evaluations of wearable smart masks’ technological, aesthetic and social attributes and how these affect consumers’ attitudes and intentions to use.

Through an experimental approach, a total of 240 US consumers’ evaluations of smart masks are compared according to perceived product–brand fit (high vs low) and brand type (electronics vs fashion).

The results showed that high perceived product–brand fit increases consumers’ evaluations, while brand type did not significantly affect consumers’ evaluations. Among various attributes, social acceptability had the greatest influence on consumers’ attitude and intention to use. Perceived ease of use, however, positively influenced attitude but negatively influenced intention to use.

As consumers’ interest in smart health-care wearables increases and air pollution is a serious issue across countries, research on wearable smart masks is being facilitated. Smart masks refer to the digitalized, reusable wearable masks that provide protection and health-care functions. However, their market penetration is still limited. To close this gap between smart mask technology and the market, this study examines how perceived fit and brand type can be used to enhance consumer evaluations.

The purpose of this study is to examine the effects of brand and message framing on consumers’ evaluations and purchase intentions of smart health-care clothing. The study also examines the mediating effect of consumers’ evaluations on the effects of the brand and message framing on purchase intentions.

Through an experimental approach, a total of 240 US consumers’ evaluation of smart health-care clothing is compared according to the existence of a well-known brand (vs. none) and message framing (technology-focused vs. fashion-focused).

The results show that consumer evaluation of smart health-care clothing is higher when the product is from a well-known brand, where consumers’ fashion consciousness and health consciousness positively influence such an evaluation as covariates. Message framing, however, did not have an influence that revealed any significant difference between technology-focused and fashion-focused messages. The consumer’s evaluation of smart health-care clothing eventually increased their purchase intentions and mediated the effects of brand on purchase intentions.

Smart health-care clothing refers to clothing that measures, records and manages the user’s activity and health status through conductive fibers or sensors that are woven in the clothes. Despite its benefits, smart health-care clothing is still not widely adopted among consumers, except for a few successful examples. Closing this gap, the results of this study provide implications regarding whether and how brand and message framing maximize consumers’ evaluations toward smart health-care clothing, which the developers and marketers of such products can use to increase the product’s market penetration.

Consumers are increasingly connected to, and make use of, a multitude of technologies in their daily lives. The exponential growth in the use of Internet of Things (IoT)-based services is ushering in a new era of e-services, in which the service experience is becoming autonomous (intelligence), devices are intercommunicating (connectivity) and consumers can access the service anytime, anywhere and using any device (ubiquity). However, a number of challenges have arisen. The purpose of this paper is to investigate factors that reduce consumer resistance to smart services (factors against resistance) and factors that promote this resistance (factors for resistance), by means of a dual-factor approach.

To test this theoretical model, the authors developed a Web-based survey and used structural equation modeling.

Results show that consumer-lifestyle factors (individual “mobiquity” and self-image congruence) reduce consumer resistance to smart services (factors against resistance). Conversely, innovation-related factors (perceived security, perceived complexity) and ecosystem-related factors (perceived government surveillance and general skepticism toward IoT) promote consumer resistance to smart services (factors for resistance). In addition, general skepticism toward IoT has a significant positive effect on perceived complexity, perceived security risk and perceived government surveillance.

This research investigates consumer resistance to smart services using a dual-factor perspective (Cenfetelli, 2004; Claudy et al., 2015): factors reducing resistance versus factors promoting resistance. This paper provides evidence for the importance of consumer lifestyle-related factors, innovation-related factors and ecosystem-related factors in explaining consumer resistance to smart services. This work enriches previous studies of consumer resistance to innovation (Ram and Sheth, 1989; Ram, 1987) by studying original variables (individual mobiquity, technological innovativeness, government surveillance).

This research clarifies the connotations and dimensions of artificial intelligence (AI) technology stimulation and establishes a stimulus scale to explain the relationship between AI technology stimuli and smart customer experience.

This is an empirical study that uses SPSS 24.0 software to perform hypothesis testing on the path relationships between model elements.

Two dimensions of AI technology stimuli (i.e. passion and usability) have a significant, positive impact on smart customer experience; the moderating effects of contrasting dimensions of technology readiness (i.e. optimism and discomfort) are significantly different; smart customer experience has a significant, positive impact on the word-of-mouth (WOM) intentions of consumers.

There are several limitations. Most importantly, the data collected in this study are only from consumers who use intelligent customer service robots in the catering industry. Future research can consider exploring relevant AI technologies in other sectors.

This study has several implications that guide catering companies to develop various positioning and strategies for remaining competitive effectively.

Based on arousal theory, customer experience theory and WOM marketing theory, this is the first novel research project that empirically discusses the dimensions of AI technology stimuli, smart customer experience and WOM intentions with regard to the moderating effect of the technology readiness of consumers toward AI technology.