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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.

Service research offering a view of both the dark and bright sides of smart technology remains scarce. This paper embraces a critical perspective and examines the conflicting outcomes of smart services on the customer experience (CX), with a specific focus on chatbots.

This study uses empirical research methods to examine a single case study where an online retail service provider implemented a chatbot for customer service. Using discourse analysis, we analysed 7,167 conversations between customers and the chatbot over a two-year period.

The analysis identifies seven general themes related to the effects of the chatbot on CX: interaction quality, information gathering, procedure literacy, task achievement, digital trust, shopping stress and shopping journey. We illuminate both positive (i.e. having a pleasant interaction, providing information, knowing procedures, improving tasks, increasing trust, reducing stress and completing the journey) and negative outcomes (i.e. having an unpleasant interaction, increasing confusion, ignoring procedures, worsening tasks, reducing trust, increasing stress and abandoning the journey).

The paper develops a comprehensive framework to offer a clearer view of chatbots as smart services in customer care. It delves into the conflicting effects of chatbots on CX by examining them through relational, cognitive, affective and behavioural dimensions.

This paper aims to understand Chinese tourists’ changing shopping experience in Macao. In scrutinizing reviews posted in the pre-COVID and during COVID eras, the study has identified changing patterns in Chinese tourists’ shopping experiences, including increased leisure components while shopping, decreased luxury pursuits and an improved overall leisure and shopping experience because of decreased prices in accommodation and a less crowded retail and leisure environment. An emergent opportunity to provide “retail-tainment” experience is discussed.

Understanding the effect of assortment composition on attentional levels is an essential topic for academic researchers and practitioners. This work has important implications when analyzing the influence of shopping frame time and search effort on the relationship between the reaction to assortment composition and visual attention to stock-keeping units (SKUs) pricing.

Two experimental studies through gauze behavior analysis technology (using eye-tracking equipment) analyze the variable's large assortment, visual attention to SKU pricing, search effort and shopping frame time.

The results suggest that, although it increases the search effort, a large assortment decreases the visual attention to SKU pricing. Further, our results indicate a moderating effect associated with mitigating the negative effect by medium-low levels of search effort and a moderating impact of time in this relation.

Marketing professionals can carefully optimize the in-store experience by managing the assortment and variety and by influencing consumers' visual attention to SKU pricing along the journey as part of the experience. Assortment and SKU pricing strategies need to be aligned with consumer journey design.

Our findings contribute to assortment theory and management by detailing the relationship between consumers' reactions to assortment perception and visual attention to SKU pricing in time flow. We reinforce the importance of considering assortment strategies from the consumer perspective and giving reliable information about in-store behavior.

This study aims to investigate customers' personal innovativeness (PI) as an influencing factor of omni-channel customer experience throughout pre-purchase, purchase and post–purchase stages of the customer journey, and their subsequent influences on customers' reuse intention.

Data were collected from customers who had experience with omni-channel shopping in South Korea through a questionnaire made with Naver Forms, both online and offline from 15 June to 15 July 2022. Out of the received responses, only valid and consistent questionnaires were considered for statistical analysis. In total, 272 valid samples were utilised for the final analysis. Analyses included reliability, validity, path, structural equation modelling and mediation effects, using SPSS and AMOS software.

The results revealed a significant influence of personal innovativeness on the omni-channel customer experience across all purchase stages. Personal innovativeness was found to influence the customer experience in the pre- and post–purchase stages, thus affecting reuse intention. However, it did not have the same effect in the purchase stage. The omni-channel experience customer experience also played an indirect mediating role in the relationship between personal innovativeness and reuse intention.

First, personal innovativeness in the IT domain may be very prominent in studies examining innovative behaviours related to computing technology. Second, this study provides further understanding of customers' intentions to reuse omni-channel shopping. Third, the path analysis showed that personal innovativeness significantly affects customer experience at all pre-purchase, purchase and post–purchase stages of the customer journey. However, except for the purchase experience, both pre- and post–purchase experiences significantly impact customers' intention to reuse omni-channels and play a mediating role.

First, omni-channel retailers should launch new products, innovative promotional activities and explore new channels or new service modes to stimulate the need recognition of customers with high personal innovativeness. Second, omni-channel retailers should pay attention to the users' reviews of each channel because they play a key role in potential customers' purchase decisions. Third, offering customers a seamless shopping experience is essential as a marketing strategy for omni-channel retailing.

This study elucidates the causal relationship between personal characteristics and behaviour by dividing the omni-channel customer journey. In particular, personal innovativeness is identified as an important predictor of the intention to reuse omni-channels during the pre- and post–purchase stages. This suggests that omni-channel retailers need to strategically manage these stages to boost customers' reuse intention.

The objective of this research is to analyze how omnichannel consumer journey design (OCJD) influences the online customer experience (OCE) and e-satisfaction in consumers' multirooming behavior (searching for information in online and offline channels and purchasing the product online).

The problem-solving theory and experiential marketing perspective are the theoretical background that enables the establishment of five hypotheses. A survey is conducted on multiroomers who had purchased a product online, following an online and offline research journey.

The results showed that OCJD directly and indirectly (through online consumer experience) influences e-satisfaction. Females and younger individuals exhibited higher levels of e-satisfaction.

First, this research analyzes consumers' multichannel search strategies. Second, the consumer journey is incorporated into the study of multichannel retailing. Third, an emergent typology of cross-channel free-riding behavior is analyzed: multirooming.

This study considers perceived enjoyment and attitude consistency as internal states of consumers in an omni-channel environment. This study aims to investigate the mediating role of perceived enjoyment and attitude consistency to reveal how omni-channel environment factors of interaction fluency, convenience, price advantage and personalization contribute to omni-channel shopping intention.

Consumers who had shopped at Uniqlo's online and offline stores were surveyed through an online questionnaire, and 566 data were collected for analysis through partial least squares structural equation modeling (PLS-SEM).

The results find that interaction fluency, price advantage and personalization positively affect perceived enjoyment, interaction fluency and convenience positively affect attitude consistency and perceived enjoyment and attitude consistency in turn facilitate omni-channel shopping intention. The mediating role of perceived enjoyment and attitude consistency was confirmed.

The original finding of this study is that factors such as interaction fluency, convenience, price advantage and personalization in omni-channel retailing require momentary and continuous affective states of consumers to facilitate omni-channel shopping intention, respectively. Therefore, this study considers the necessity of capturing different affective states of consumers in omni-channel shopping.

The study aims to delve into the “phygital customer journey” (PCJ), which merges physical and digital interactions in customer experiences, using a practice-based lens to reveal the underlying dynamics of these blended encounters.

Feedback from 60 individuals established the groundwork for a qualitative analysis. They chronicled customer journeys through diaries and used UXPressia software for journey mapping. This strategy enabled a detailed exploration of the PCJ, focusing on customers’ lived experiences and perceptions.

The study presents an integrative framework for the PCJ, identifying four key elements: hybrid artefacts (the melding of digital and physical tools/interfaces), blended contexts (the seamless integration of digital and physical spaces), circular actions (the non-linear paths of customer engagement) and intertwined emotions (the complex emotional responses to phygital experiences). These elements underscore the intricate and interconnected nature of the PCJ.

This study advances the field by applying a practice-based approach to unravel the complexities of the PCJ, illuminating the nuanced interplay between digital and physical realms. This innovative lens foregrounds the significance of practices in consumer experiences, thereby contributing to a deeper academic and practical understanding of phygital integration.

This study delves into the complex realm of consumer behavior by exploring the impact of distinct shopping motives, encompassing status, value and gratification, on store satisfaction within the domain of organic food retail. Moreover, it seeks to decipher the influence of perceptual disparities between male and female patrons on the intricate nexus between shopping experience and consumer loyalty within organic food stores.

A comprehensive dataset comprising responses from 400 participants was gathered and subjected to confirmatory analysis and structural equation modeling. These analytical tools were employed to dissect the data, validate the underlying research framework and unveil critical insights.

The empirical analysis, facilitated by structural equation modeling, substantiates that organic food stores prioritize the organic attribute, primarily centered on healthiness, often to the detriment of broader conceptual and social aspects. This validates the interplay between shopping experience dimensions, customer contentment, loyalty and the intent to revisit. Gender, as a moderator, exerts a discernible influence on these relationships, highlighting distinct shopping behaviors among male and female consumers when gauging the influence of shopping experience dimensions within organic food retail establishments.

The implications of this research resonate deeply within the organic food retail landscape. The insights garnered provide valuable guidance to organic food retailers aiming to enhance their store ambiance and allure, thereby fostering sustained customer satisfaction. This, in turn, augments the propensity for customer loyalty and repeat patronage, a particularly pressing concern in today's fiercely competitive retail milieu. Furthermore, the study carries significant ramifications for organic food producers and governmental entities, outlining a framework for augmenting the value proposition of organic foods in alignment with customer experiential paradigms.

In a milieu characterized by the emergence of novel product categories and industry entrants, the study fills a critical void by investigating customer satisfaction within the broader retail food sector, with specific focus on organic food stores. Moreover, the research embarks on a pioneering exploration of the prospective trajectory of organic food stores in the Indian context, employing a marketing lens and grounded in the theory of needs satisfaction.

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.