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1. Innovative technologies, such as DS, can engage different human senses and play an important role in enhancing the store atmosphere.

2. The majority of DS networks feature content that is generic and is rarely tailored to the audience passing by the screens. As a result, digital displays are often ignored.

3. DS coupled with sensors and Artificial Intelligence allow for more relevant and personalized experiences.

4. Relevance through personalization can help retailers overcome display blindness, but challenges in terms of legal restrictions and ethical concerns exist to unlock its potential.

5. Nontouch interaction technologies, such as voice assistants, gesture controls, facial recognition, and augmented reality, present new ways of interacting with digital screens.

Innovative technologies, such as DS, can engage different human senses and play an important role in enhancing the store atmosphere.

The majority of DS networks feature content that is generic and is rarely tailored to the audience passing by the screens. As a result, digital displays are often ignored.

DS coupled with sensors and Artificial Intelligence allow for more relevant and personalized experiences.

Relevance through personalization can help retailers overcome display blindness, but challenges in terms of legal restrictions and ethical concerns exist to unlock its potential.

Nontouch interaction technologies, such as voice assistants, gesture controls, facial recognition, and augmented reality, present new ways of interacting with digital screens.

This chapter provides an overview of technology management to support retailing, before and during the COVID-19 pandemic. Specifically, it focuses on the technologies developed and in use before the pandemic, the ones further developed as response to the pandemic, while the final part of the chapter proposes a new technology implementation process (cycle) to support retailers in introducing new technology. In particular, the process in based on seven main activities: (1) Technology need recognition; (2) Technology screening; (3) Initial development and testing; (4) Business analysis; (5) Technology development; (6) Market acceptance testing; and (7) Technology adoption, while monitoring and learning actions should occur constantly throughout the process to evaluate the benefit of the technology at each stage (or to discard for further investment).

This study aims to explore the influence of perceived value, enjoyment and novelty of fast-food chains’ smart retailing technology (SRT) on Filipino consumers’ attitude and loyalty.

Purposive sampling was used in identifying the respondents (N = 343). The participants were composed of consumers of the leading fast-food chains in the Philippines, where SRT using self-service ordering kiosks is being implemented. The hypotheses were explored using partial least squares path modeling, and predictive-causal was the study’s research design.

The results reveal that, among the factors, perceived enjoyment substantially contributes to the formation of favorable consumers’ attitude toward SRT. Moreover, perceived value was found to have a moderate effect on attitude while perceived novelty showed small impact. In terms of consumers’ attitude and loyalty, the two variables were found to have large positive and significant relationship. The moderation analysis shows that consumers’ attitude toward SRT has medium indirect effect on the relationship between perceived enjoyment and loyalty, while there is small indirect influence on the links between perceived value and loyalty, and between perceived novelty and loyalty.

As more and more fast-food establishments are adopting the use of SRT via self-ordering kiosks, the present study is the only study in the Philippine context that explores how perceived value, enjoyment and novelty affect consumers’ attitude and loyalty.

The adoption of augmented reality (AR) settings represents an extraordinary opportunity to enrich the value of the omni-customer brand experience, especially in fashion retail. AR enhances the brand of extra-contents, both informational and sensorial, amplifies its significance toward consumers and inflects its commercial and emotional charm through new dimensions in the store. In this light, the purpose of this paper is to verify whether AR affects customer behavior toward brands in the retailing system.

By means of a qualitative approach, a preliminary research question linking technological settings of the store/brand and customer informational eagerness has been analyzed in a fashion retailing chain store. To frame the research question, the omni-customer segment perspective has been assumed, taking into consideration two main dimensions as follows: implementation of in-store AR settings; and affective/cognitive/functional structure of the experiential brand value.

Preliminary findings suggest that AR can create extra brand value by simplifying the decision-making process and engaging customers. In the sum four “realms” in terms of augmented brand experience can emerge and be managed by retailers.

Even though the contribution of AR is easily understood in selling activities from a marketing perspective, very few retail applied studies can be found to-date. The present analysis aims to narrow this gap. It also contributes to brand management, stimulating the integration of the AR dimension as an additional facet of a brand tool kit in the “project” for value co-creation.

This paper aims to understand the impact of modern technologies such as artificial intelligence on impulse buying behaviour of Indian shoppers specifically in fashion retail outlets.

The empirical study on the effect of artificial intelligence on impulse purchase decisions was conducted through an e-survey of the Indian shoppers. The data collected was analysed using factor analysis and multiple regression analysis.

The impact of modern technologies which are used by the retailers to enhance sale and consumer engagement was studied. The relationship between use of artificial intelligence parameters such as the purchase duration, recommended products, product information and human interaction and its impact on Impulse Purchase was studied and the results revealed that all these factors except product information had a significant impact on the impulse purchase decision of the buyer.

This study will be useful to the fashion retailers to gauge the effect of incorporating artificial intelligence and its impact on driving sales by attracting shoppers to their outlets.

This study specifically focusses on the impact of modern technologies on impulse purchase of Indian shoppers in fashion retail outlets. Other research works have focussed on impact of visual merchandising, store layouts, store environment and promotional activities on impulse purchases. This is one of the few studies which deals with the impact of artificial intelligence on impulse buying behaviour of Indian shoppers specifically in the fashion retail segment.

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.

This paper aims to explore factors affecting young consumers’ purchasing of new smart products under the influence of social media.

Twenty semi-structured, face-to-face, in-depth interviews were conducted with young consumers who used new media, and five extended interviews were conducted with popular smartwatch retailers in Macau.

The findings reveal that they tend to garner product information from multiple channels of communication. Social media exert the greatest influence. Reliable information, strong branding and interactions with vendors are also influential, although new product pre-announcements may be boring and difficult to understand.

This study presents new insights into diffusion of innovation theory and provides retailers launching smart products with a better understanding of their target young customers’ purchasing behavior.

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.

Identifying the patterns of retail institutional change has piqued the interest of retail academics for nearly a century. The Big Middle hypothesis is one of the most recent and hybridized versions of similar theories. According to it, retailers seeking a dominant position in retailing can migrate into the Big Middle, the largest market segment, by specializing in a large market with a broad product assortment or by focusing on a specific product category and simultaneously catering for multiple segments at the same time. This study provides empirical evidence for the latter proposition by employing fuzzy-set qualitative comparative analysis (fsQCA) on the case of UNIQLO, a Japanese clothing specialist retailing giant.

The authors devised a survey to assess (1) consumers' perceptions of UNIQLO's store attributes and (2) their perceived distance between the UNIQLO and potential competitors. The authors used fsQCA procedures to identify multiple confluences of causal conditions that led to a high level of consumer patronage for UNIQLO from various market segments.

The findings show that UNIQLO's dominance in the Big Middle stems not only from capturing a sizable homogeneous market but from aggregating multiple heterogeneous market segments with disparities of various types. This finding explains how a specialty store retailer achieves its Big Middle position.

The findings gleaned from fsQCA are not statistically generalisable. It, therefore, is essential to ensure whether similar phenomena are observed under different spatiotemporal settings. Concerning the scope of the research, this study's finding is pertinent to only one part of the Big Middle hypothesis. Future studies are required to cover other dimensions of the Big Middle, including the generalist retailer's cases of the Big Middle.

The results of this study may present a valuable tool to deepen retailers' understandings on; (1) the multiple causal recipes of customer patronages to their retail offerings, (2) who the pure fans of their stores are, (3) who their principal rivals are in the mind space of the consumers, and (4) their overall market position upon aiming to realise the Big Middle. It will give retail managers an insight into how to design, implement, and churn an efficient and effective RBM.

The study's originality is in empirically scrutinizing and elaborating a part of the mechanism of retail change heralded by the Big Middle hypothesis.