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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.

The purpose of this paper is to give an overview of artificial intelligence (AI) and other AI-enabled technologies and to describe how COVID-19 affects various industries such as health care, manufacturing, retail, food services, education, media and entertainment, banking and insurance, travel and tourism. Furthermore, the authors discuss the tactics in which information technology is used to implement business strategies to transform businesses and to incentivise the implementation of these technologies in current or future emergency situations.

The review provides the rapidly growing literature on the use of smart technology during the current COVID-19 pandemic.

The 127 empirical articles the authors have identified suggest that 39 forms of smart technologies have been used, ranging from artificial intelligence to computer vision technology. Eight different industries have been identified that are using these technologies, primarily food services and manufacturing. Further, the authors list 40 generalised types of activities that are involved including providing health services, data analysis and communication. To prevent the spread of illness, robots with artificial intelligence are being used to examine patients and give drugs to them. The online execution of teaching practices and simulators have replaced the classroom mode of teaching due to the epidemic. The AI-based Blue-dot algorithm aids in the detection of early warning indications. The AI model detects a patient in respiratory distress based on face detection, face recognition, facial action unit detection, expression recognition, posture, extremity movement analysis, visitation frequency detection, sound pressure detection and light level detection. The above and various other applications are listed throughout the paper.

Research is largely delimited to the area of COVID-19-related studies. Also, bias of selective assessment may be present. In Indian context, advanced technology is yet to be harnessed to its full extent. Also, educational system is yet to be upgraded to add these technologies potential benefits on wider basis.

First, leveraging of insights across various industry sectors to battle the global threat, and smart technology is one of the key takeaways in this field. Second, an integrated framework is recommended for policy making in this area. Lastly, the authors recommend that an internet-based repository should be developed, keeping all the ideas, databases, best practices, dashboard and real-time statistical data.

As the COVID-19 is a relatively recent phenomenon, such a comprehensive review does not exist in the extant literature to the best of the authors’ knowledge. The review is rapidly emerging literature on smart technology use during the current COVID-19 pandemic.

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.

Despite the enormous benefits, smart homes (SHs) are still not widely adopted by residents in China. Furthermore, research on the intention to use SHs has overlooked the role of family factors. Thus, this study aims to propose a new research model to examine the impact of family factors on the usage intention (UI) of SHs.

This study collected 265 valid data from potential users of SHs in China using a convenience sampling method. The PLS-SEM method was applied to test the research model and related hypotheses.

The empirical results confirm the mediating role of optimism (OP) in perceived family support (PFS)/perceived family trust (PFT) and attitude (AT). Unsurprisingly, the results validated the relationship between perceived usefulness (PU), attitude (AT) and UI of SHs through TAM theory. Besides, this study also identified the moderating effect of perceived risk (PR) between AT and UI.

To improve SH adoption, practitioners should focus on family factors and utilize family influence to promote the spread of smart home reputation. Besides, SH practitioners should enhance user trust and reduce perceived risks through technological upgrades and security measures.

Based on the Social Impact Theory and Technology Acceptance Model (TAM), this study is an empirical attempt to explore the impact of family factors on the intention to use SHs, expanding the research on smart home adoption.

To influence consumer pre-purchase decision-making processes, such as brand selection and perceived brand experience, brands are interested in adopting hyperconnected technological stimuli, such as artificial intelligence, augmented reality (AR), virtual reality, social media and tech devices. However, the understanding of different hyperconnected touchpoints remained shallow and results mixed in previous literature, despite the fact that these touchpoints span different technological interfaces/devices and may influence consumer brand selection. This paper aims to solidify the conceptual underpinnings of the role of online hyperconnected stimuli, which may influence consumer psychological reactions in terms of brand selection and experience.

This paper is conceptual and presents a discussion based on extant literature from various international publishers.

The authors revealed different technological stimuli in the online hyperconnected environment that may influence consumer online hyperconnected brand selection (OHBS), perceived online hyperconnected brand experience (OHBE), perceived well-being and behavioral intention.

The conceptual understanding of OHBS and perceived OHBE was mixed and inconsistent in previous studies. This paper brings together extant literature to establish the conceptual understanding of antecedents and outcomes of OHBS, i.e. perceived OHBE, perceived well-being and behavioral intention, and presents a cohesive conceptual framework.

This research investigates apparel consumers' psychological and behavioral responses to omnichannel (OC) integration. Specifically, the study applies the cognitive–affective–conative (CAC) model to reveal consumers' decision-making process under the impact of channel integration quality (CIQ), perceived fluency (PF) and cognitive and affective trust (AT).

Primary data were collected through an online survey. In total, 657 eligible responses were received. This study applied partial least square structural equation modeling for data analysis.

The findings demonstrate that the extrinsic cognitive factor, CIQ, substantially affects consumers' intrinsic cognition (cognitive trust [CT] and PF), which consequently fosters consumers' AT and shopping intentions. Specifically, integrated promotion and transaction information positively affects CT, while integrated product and price and information access negatively impact CT. All the dimensions of CIQ, except integrated promotion (IP), significantly affect PF. CT and AT exhibit mediation effects in the CAC model.

Apparel brands and retailers may apply the findings to effectively design their retail channels and implement channel integration to boost consumers' shopping intentions and trust.

This study is one of the pioneering studies applying the CAC model to empirically examine OC consumers' decision-making process. It is also among the first to determine that cognitive and AT have theoretical distinctions in the OC retailing setting.

The purpose of this study is to identify segments in the Gen Z population (born between 1996 and 2010) in Europe, the USA and Australia, based on brand- and lifestyle-related variables and perceptions about their online activities. This study explores how these segments differ and provide insights into cross-country similarities and differences.

An online survey was conducted with 4,304 participants, and cluster analysis and analysis of variance were used to identify and profile Gen Z segments in each of three geographical areas.

Five segments in Europe and four segments in the USA and in Australia were identified. Segments differ in terms of the importance they attach to exclusivity, inclusivity and sustainability of brands, how Gen Z members perceive money issues and stand in life and how they perceive their online activities. Similar segments are found in the three geographical areas.

This study proposes a conceptual and analytical approach for exploring intra-cohort diversity. Future research can apply this approach to different generational cohorts and use it to study intra-cohort diversity in other parts of the world.

This study provides input for marketing practitioners to create better focused and more effective campaigns.

Cross-country generational cohort research is scarce, and especially intra-cohort diversity is under-researched. This study offers a deep and fine-grained insight into the diversity of the Gen Z cohort across three geographical areas, based on representative samples in these areas.

Managing the growing word-of-mouth (WOM) of brand fans has become a new challenge for companies in the fan economy era. The purpose of this paper is to examine the effect of language intensity of brand fan WOM on customers' willingness to adopt WOM based on psychological resistance theory and to reveal the underlying mechanism of this process.

A research model was developed to test the proposed hypotheses. Two experiments were conducted on an online platform using data from 708 participants. The independent samples t-test and analysis of variance were used to analyze the data.

The results show that, in the context of WOM among brand fans, high-intensity language leads to a lower willingness to adopt than low-intensity language and threats to freedom mediate this effect. Moreover, the restoration postscript moderates the effect of language intensity on threats to freedom and customers' willingness to adopt WOM.

Unlike previous studies that focused on electronic word-of-mouth (eWOM) language content, this paper focuses on language intensity to reveal the psychological process of customers' willingness to adopt brand fan WOM. The findings not only enrich the research related to the language effect in eWOM, but also deepen the understanding of the influence effect on brand fan WOM, providing effective guidance for brands to manage fan WOM.

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.

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.