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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.

Since the advent of augmented reality (AR) technology, “Smart Retailing” has become the dominant business model in the retail sector. Therefore, comprehending the dynamics of AR adoption is essential if retailers are to successfully encourage customers to embrace this extremely innovative form of technology. As a result, the authors propose and evaluate a more comprehensive model, consisting of the task-technology fit (TTF) and unified theory of acceptance and use of technology (UTUAT2) models, for use in low-income countries.

The present research uses variance-based partial least squares structural equation modeling (PLS-SEM) using WarpPLS.7 to examine 398 responses from Egyptian retail consumers.

TTF, performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating condition (FC), hedonic motivation (HM) and customer innovativeness (CI) positively affect shoppers' behavioral intentions (BI) to adopt AR Apps in retail, while perceived risk (PR) negatively affects BI.

The current study is the first to investigate the determinants of shoppers' BI toward AR Apps adoption in the retail context using UTAUT2 and TTF models.

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.

The growing complexity of consumer engagement (CE) due to the impact of Internet of things (IoT) has been attracting significant attention from both academics and industry practitioners especially in recent times. Hence, understanding this phenomenon remains very crucial to the body of knowledge. This study conducted a systematic review on IoT and CE with the aim of proposing future research opportunities using the TCCM model.

Extant literature studies were systematically examined by sourcing high ranking ABS journals from EBSCO, ScienceDirect and Emerald. A total of 58 articles were included in the final analysis of this research.

The analysis established the need to conduct more research on CE due to the impact of new technological implementation in retail. The results further suggest the need for extensive research across African countries and emerging markets to enable broader empirical generalizations of research outcomes. Using the TCCM framework, the authors indicated directions for future empirical research.

This study exposes the current trends in CE and IoT. The results and analysis are both compelling and verifiable, hence, establishing a firm base of reference for future research in related fields.

As the size of the population is growing and the capacity of the planet Earth is limited, human beings are searching for sustainable and technology-enabled solutions to support society, ecology and economy. One of the solutions has been developing smart sustainable cities. Smart sustainable cities are cities as systems, where their infrastructure, different subsystems and different functional domains are virtually connected to the information and communication technologies (ICT) and internet via sensors and devices and the Internet of Things (IoT), to collect and process real-time Big Data and make efficient, effective and sustainable solutions for a democratic and liveable city for its various stakeholders. This chapter explores the concepts and practices of sustainable smart cities across the globe and explores the use of technologies such as IoT, Blockchain technology and Cloud computing, etc. their challenges and then presents a view on business models for sustainable smart cities.

The purpose of this study is to examine how phygital luxury experiences can be generated from mobile-mediated service activities while enabling luxury apparel shoppers to attain status goals and hedonic goals. Phygital luxury experiences are defined in this context as shopping experiences that blend the participative and immersive components of mobile and ubiquitous media with physical luxury servicescapes.

This conceptual research draws on activity theory from the field of human-computer interaction to produce an activity-centric model of phygital luxury experiences. By drawing on activity theory, the authors develop research propositions and build a conceptual model. The conceptual model probes how phygital luxury experiences can be generated from mobile-mediated service activities that enable luxury apparel shoppers to attain status goals and hedonic goals. In turn, service activities are proposed to meld with luxury shopping goals when mobile devices allow luxury apparel shoppers to participate in community-, rules-, and labor-based service activities.

First, the conceptual model demonstrates that social validation and personalization are status and hedonic drivers for community-based service activities (e.g. content-sharing and multiplatform storytelling). Second, special privileges and new comforts are status and hedonic drivers for rules-based service activities (e.g. engaging in pseudo-webrooming, pseudo-showrooming, and seamless and on-demand resources). Third, know-how and domination are status and hedonic drivers for labor-based service activities (e.g. adopting self-service technologies and smart or intelligent displays).

This conceptual model contributes to the well-documented need for research on interactive luxury strategies and luxury retail innovation. Overall, these service activities provide luxury brands and shoppers new opportunities for building elite communities, bending store rules, and altering the division of labor within physical stores. At the same time, this model shows that exclusivity and allure of luxury consumption can be reproduced through luxury apparel shoppers' embodied interactions with salespeople and relevant audiences in connected store environments.

Long sales periods (i.e. Christmas time, Black Friday, etc.) and the risk of contagion while shopping (i.e. during pandemics like COVID-19) showed the extent to which crowded shopping environments have negative effects on consumers’ behavior. Hence, using terror management theory (TMT) and stimulus–organism–response (S–O–R) approach, the authors aims to develop a new model to investigate the effect of crowd-checking technology on shopping anxiety, the perceived value of shopping experience and willingness to pay.

Using a cross-sectional research design and with a help of an independent research company, the authors collected 1,000 valid responses from individuals residing in the UK.

Results showed that crowd-checking technology cues reduce shopping anxiety, improve value perceptions and increase willingness to pay. In addition, the efficacy of technology in reducing shopping anxiety is moderated by customers’ shopping orientation.

To the best of the authors’ knowledge, this research is the first one investigating crowd monitoring systems used at the initial stage of consumers’ journey to show the number of consumers in-store in real-time. It contributes to the literature on technology applications in retailing by providing evidence that technology cues reduce shopping anxiety, which in turn enhances customer-perceived value from the shopping experience and increases the willingness to pay in stores with embedded crowd-checker technology. The study also extends the application of TMT in a new context.

Los largos periodos de rebajas (ej. Navidades, Black Friday, etc.) y el riesgo de contagio durante las compras (ej. durante pandemias como la COVID-19) mostraron hasta qué punto los entornos de compras abarrotados tienen efectos negativos en el comportamiento de los consumidores. Utilizando la Teoría de la Gestión del Terror (TMT) y el enfoque Estímulo-Organismo-Respuesta (S-O-R), desarrollamos un nuevo modelo para investigar el efecto de la tecnología de control de multitudes sobre la ansiedad en las compras, el valor percibido de la experiencia de compra y la disposición a pagar.

Utilizando un diseño de investigación transversal y con la ayuda de una empresa de investigación independiente, recogimos 1.000 respuestas válidas de personas residentes en el Reino Unido.

Los resultados mostraron que las señales de la tecnología de comprobación de multitudes reducen la ansiedad en las compras, mejoran la percepción del valor y aumentan la disposición a pagar. Además, la eficacia de la tecnología en la reducción de la ansiedad de compra está moderada por la orientación de compra de los clientes.

Esta investigación es la primera que estudia los sistemas de seguimiento de multitudes utilizados en la fase inicial del viaje de los consumidores para mostrar el número de consumidores en la tienda en tiempo real. Contribuye a la literatura sobre aplicaciones tecnológicas en el comercio minorista aportando pruebas de que las señales tecnológicas reducen la ansiedad de compra, lo que a su vez mejora el valor percibido por el cliente de la experiencia de compra y aumenta la disposición a pagar en tiendas con tecnología de control de multitudes integrada. El estudio también amplía la aplicación de la Teoría de la Gestión del Terror en un nuevo contexto.

漫长的销售期（即圣诞节时间、黑色星期五等）和购物时的传染风险（即在COVID-19等大流行病期间）显示了拥挤的购物环境对消费者行为的负面影响程度。 因此, 利用恐怖管理理论（TMT）和刺激-组织-反应（S-O-R）方法, 我们建立了一个新的模型来研究人群检查技术对购物焦虑、购物体验的感知价值和支付意愿的影响。

在一家独立研究公司的帮助下, 我们采用横断面研究设计, 从居住在英国的个人中收集了1000份有效的答复。

结果显示, 人群检查技术提示减少了购物焦虑, 改善了价值认知, 并提高了支付意愿。此外, 技术在减少购物焦虑方面的功效受到顾客购物取向的调节。

这项研究是第一个调查在消费者旅程的初始阶段使用的人群监测系统, 以实时显示店内消费者的数量。它为零售业技术应用的文献做出了贡献, 提供了技术线索减少购物焦虑的证据, 这反过来又提高了顾客从购物体验中感知到的价值, 并增加了在有嵌入式人群检查器技术的商店中的支付意愿。该研究还扩展了恐怖管理理论在新环境中的应用。

The aim of this study is to investigate the psychographic factors of shopping enjoyment, market mavenism and consumer innovativeness and their influence on hedonic and utilitarian values, attitudes and patronage intentions of the small concept luxury department (SCLD) store.

The researchers utilized a quantitative method. An online survey was created and distributed over a three-week period to a representative sample of US luxury consumers. Structural equation modeling (SEM) was used to test the hypothesized relationships among variables.

The theory of reasoned action (TRA) theoretical framework provided an effective model to investigate the perspectives and behaviors of luxury consumers within the SCLD. The findings of this study suggest the SCLD is an effective store format for consumers who are characterized as market mavens, are considered innovative and enjoy shopping.

The findings from this research are beneficial to luxury department store retailers looking to invest resources into a new experiential format to appeal to their consumer base.

The research extends the literature in a rapidly evolving area of retail formats and consumer perception by exploring psychographic factors, including shopping enjoyment, market mavenism and consumer innovativeness, and their impact on the beliefs regarding retail formats' hedonic and utilitarian value.

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.

This research aims to propose the development of a model that identifies, in essential services, the determining factors affecting the technological advances offered by different smart technologies in supermarket retail channels that influence citizens' quality of life, amidst the coronavirus disease 2019 (COVID-19) pandemic.

The data were collected using a cross-sectional questionnaire survey (n = 469). The authors applied the structural equation modeling (SEM) technique to test the hypotheses, along with the partial least squares (PLS) method for estimating latent variables and combining with the necessary condition analysis (NCA) method.

According to the results of the NCA method, the results were adequate, and more attention should be paid to the quality of life construct after finding the bottleneck point of 50%. In this sense, adaptive resilience was characterized as the main necessary predictor construct for quality of life. In addition, Generation Z and Millennials have the highest frequency of use in all smart technologies, with “assisted purchase” being the most widely used.

Finally, the effect of the pandemic changed the consumption routine with supermarkets, not being a mere option but a necessity in the context of a smart city.

As a result, the proposed model was consistent, showing that all direct and indirect SEM paths were validated, highlighting data security and privacy and resilience issues. In addition, the NCA method complemented the procedures performed in the SEM phase.