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Introduction: Artificial intelligence (AI) and digitisation offer substantial human potential and profit margins, making them promising retail solutions. Retail leaders have successfully integrated comprehensive uses into their daily operations, while competitors heavily invest in new projects. The Indian retail sector is undergoing a significant transformation, which can be attributed to factors such as growing income, demographic characteristics, and enhanced consumerism, as well as the rapid development of new technologies such as digitisation and AI, which is changing both consumers’ and retailers’ buying behaviour.

Purpose: This study aims to determine the influence of AI on elements that drive digitisation in the retailing sector, as well as the factors that lead to organised retailers adopting digitisation and its impact on their business.

Methodology: The study employs a standardised questionnaire distributed to organised stores via an online link, and the data are analysed with SmartPLS software 3.0.

Finding: The retail sector is driven by elements that promote digitalisation in food and groceries retailing, such as simplicity of operation, adoption of digital payment, quicker internet connection, retailer consumer interface, and the involvement of AI.

Research implication: AI has significant consequences for retailing, which serves as the interface between marketers and customers.

Theoretical implication: The study’s findings reflect the perspectives of retailers, store managers, and entrepreneurs on how digitalisation and AI are crucial for the creation and growth of long-term competitive advantages in retail.

This study explores the present state of research related to omnichannel retail, investigates retail's different sub-areas and suggests future research directions.

The subdomains of omnichannel retail have been identified using a keyword co-occurrence network (KCN) map and content analysis. The 5W1H method assisted in finding the bibliographies of 258 SCOPUS-indexed and ABDC-ranked journal articles and showcasing the omnichannel retail landscape.

Most research on omnichannel retail is concentrated on five subdomains: customer behaviour, channel integration, technological innovation, supply chain and operations and strategy. The study's conceptual framework illustrates the omnichannel retailing environment and the variables that must be considered whilst establishing an omnichannel strategic vision. Besides, future researchers have been urged to concentrate on interdisciplinary research, as a seamless experience is unachievable if focussed on a single subdomain.

There is a slight probability of missing out on some good articles as this study considered only those articles that have been published in SCOPUS and ranked by the ABDC quality list.

This study emphasises that for businesses to capitalise on the omnichannel model, the businesses must undergo a transformation involving technology convergence, customer-centricity and internal process reorganisation that integrates consumer feedback to co-create value. When a business adopts an omnichannel model, the business's priorities shift. Rather than depending solely on technology, faster delivery and channel integration, an omnichannel strategy requires strong leadership, a clear vision, training for all stakeholders and an understanding of customer pain points to reach the full potential.

The illustration of the omnichannel retail landscape using the 5W1H methodology and antecedents-decisions-outcomes (ADO) framework.

Digital technology plays a vital role in empowering omnichannel integration. Research on digital technology has recently attracted attention and rapidly developed. However, a comprehensive assessment of the research status and potential gaps is yet to be conducted. Thus, this study investigated the current research status of digital technology-empowered omnichannel integration, and future research directions are proposed.

A three-stage bibliometric analysis was conducted on 764 articles published from 2000 to 2023, cited in the Web of Science database. Furthermore, performance and thematic analyses were performed.

The most productive contributors and influential articles in this field were identified, and four themes of focus were discovered: service quality, o2o commerce, omnichannel retailing, and digital transformation.

To the best of our knowledge, this work is the first attempt to enable researchers to understand the vast body of published scholarship on digital technology-empowered omnichannel integration.

This study aims to investigate the intention of adopting a technological service innovation that is a mix-mode consumer shopping service in the retailing context.

A modified extended Unified Theory of Acceptance and Use of Technology (UTAUT2) model is tested by using data on a real example named “Mkolay” which is a new mix-mode consumer shopping service. Data are collected from 217 participants and analyzed by using Partial Least Squares Structural Equation Modeling (PLS-SEM).

Research findings show that the customers' intention to use the new mix-mode consumer shopping service is particularly influenced by performance expectations, effort expectations, social influence and personal innovativeness.

In designing a mix-mode consumer shopping service, keeping the design as simple and easy to use as possible seems to increase the intention of adoption. Additionally, collaborating with reference figures or influencers could be instrumental to spread the new service to a wider audience hence increase the likelihood of adoption. Practitioners should also use new technologies in different ways to attract and surprise customers, especially taking into account the technological profile of potential users.

This study contributes to the literature of technological service innovation adoption by revealing the factors affecting the intention of adoption of mix-mode consumer shopping service in the retailing context with a modified UTAUT2 model.

This study considers the potential of logistics 4.0 for supply chain (SC) optimization in French retail. The authors investigate the implementation of Industry 4.0 technologies to optimize SC performance in the retail sector and SC's role in the digital transformation in supply chain management (SCM).

The authors first carry out a comprehensive bibliographic taxonomy to highlight the different existing digital tools. Based on this, the authors posed three research questions (RQs) and hypotheses to examine the contribution of logistics 4.0 in improving the performance of retail logistics. Then, the authors considered a case study of retail in France based on qualitative and quantitative analysis to answer all the RQs and examine the hypotheses.

The results showed that digital tools such as Cyber Security Systems (CSS), Big Data Analytics (BDA) and Blockchain (BC) technology are the most effective and appropriate tools to optimize the SC performance in retail.

This research work showed that the implementation of these tools in retail can offer several benefits such as improved productivity, optimized delivery times, improved inventory management and secure real-time communication, which leads to improved profitability of the SC.

The study opens a door to develop practical roadmaps for companies that enable smart deliveries based on logistics 4.0.

Consumer behavior has evolved because of technological development. Nowadays, consumers carry out the different stages of the decision-making process by combining multiple devices which has been defined as multi, cross and omnichannel behavior. These behaviors have attracted the attention of academics and become a hot topic in literature. As a result, vast amounts of studies on the subject need to be revised and clarified. Thus, the aim of this chapter is to synthetize the primary academic literature that analyzes multi, cross and omnichannel behavior from the consumer point of view. To do that, first, the main concepts (multi, cross and omnichannel) and their differences are clarified. Second, the major findings of channel mix literature regarding the topics, channel scope and theories are exposed and described. Third, the opportunities and future lines of research are presented. This chapter contributes to the literature by clarifying the conceptualization of multi, cross and omnichannel behaviors; offering a complete picture of the main topics, channel approaches and theories addressed in channel mix literature; and presenting future research opportunities and open research questions in a channel mix context that could serve as a starting point to build further research.

This paper aims to explore the factors influencing the behavioural intention of Gen Y consumers to avail omnichannel service and to identify the relative influence of predictors in explaining the behavioural intention of Gen Y consumers to use omnichannel service.

Data collected through surveys from 287 Gen Y consumers has been analysed through structural equation modelling to examine direct and mediated relationships between the constructs influencing behavioural intention to use omnichannel service.

Findings indicate that perceived ease of use, social influence, perceived trust, and personal innovativeness positively affect behavioural intention to use omnichannel service, with the result accounting for 48% of the variance. We also demonstrate that perceived value and perceived ease of use mediate the association between personal innovativeness and behavioural intention to use omnichannel service.

The study provides valuable insights into adopting technology-based offerings for Gen Y customers. The presented model can be extended for analysing consumers' behavioural intentions by considering additional variables, such as consumer personality traits and diverse cultural settings. The study may help managers and policymakers formulate a consumer-focussed strategy to win over modern retail consumers.

This study explores the behavioural intention of Gen Y consumers in availing omnichannel services. Further, the study contributes to the technology acceptance model (TAM), unified theory of acceptance and use of technology (UTAUT) or UTAUT2 theories that may need to be extended in the omnichannel shopping context.

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 objective of this research is to evaluate and rank the factors influencing omnichannel (OC) logistics, while also investigating the significant impact of big data analytics in improving these drivers of OC logistics.

Using exploratory sequential mixed method design, an in-person interview survey was conducted to identify and stratifies the enablers of OC retailing. These interviews were supplemented with a case study in an apparel firm to prioritise the enablers of OC logistics. Further, a survey was conducted to understand the role of big data analytics in improving drivers of OC logistics as well as the role of Individual capability and organisational capability in big data usage for omnichannel retailing.

Findings represent that information management is the most important driver followed by inventory management and network design for improving OC logistics. Further, significant relationship between big data analytics and drivers of omnichannel logistics has been reported.

This study identifies and classifies the drivers of OC retailing relating to their level of criticality in OC logistics which will assists practitioners to prioritise their tasks for the successful development of OC logistics. The study will also help practitioners to use BDA for developing the drivers of OC.

The study substantiates and adds to the BDA literature by emphasising the positive role of BDA in development of OC driver and highlighting the significant role of drivers of BDA in its usage.

Acknowledging previous scholarly focus on functional attributes in understanding technology acceptance behaviour, the current study aims to offer a novel perspective by integrating eight different dimensions of utilitarian and hedonic attributes to examine their influence in delivering a holistic web-based retail shopping experience.

The research model was tested and validated through data collected from 370 online shoppers across both hedonic and utilitarian product ranges. Hypotheses were tested using covariance-based structural equation modelling with multi-group analysis to examine the moderation effect.

The findings strongly support the model confirming eight new utilitarian and hedonic dimensions that influence web-based retail shopping behaviour. The findings also confirm that hedonic attributes remain important even for utilitarian product purchasing.

The key managerial implication is the demonstrated need to balance utilitarian and hedonic attributes in web-based retail platforms, where previously, there has been an overemphasis on functional features. Web-based retailers should consider the optimal blend of utilitarian (e.g. information quality) and hedonic (e.g. aesthetic) attributes in the design of a retail shopping site, irrespective of the product category.

This study integrates multiple dimensions of utilitarian and hedonic attributes into a single model and highlights the interplay of these attributes, thus extending the technology acceptance model. This paper also advances scholarship through its identification of attribute impact across different product categories.