Omnichannel Retailing Research Articles

Evaluating omni channel retailing in the emergence of industry 5.0: A perspective of South Asian generation Z

This study investigates the influence of Omnichannel-Retailing (OCR) on customer-retention (CR) for Generation Z (Gen Z) in the nascent Industry 5.0 era. Employing a survey with South Asian respondents, the research explores their experiences with retailer-provided omnichannel services. A novel model examines the relationships between OCR, customer-satisfaction (CS), CR, and customer-engagement (CE). Additionally, the model investigates the moderating role of Man-Machine-Collaboration (MMC) on the OCR-CR association. Process macro analysis is employed to assess mediation and moderation effects. The findings reveal positive associations between OCR and both CR and CE. Interestingly, CS does not mediate the OCR-CR relationship, suggesting a more nuanced effect of OCR on retention. However, CE emerges as a significant mediator. Furthermore, the moderating role of MMC is confirmed. This research holds novelty by examining the early stages of Industry 5.0 and its potential disruption of marketing practices, particularly for CR strategies targeting Gen Z in South Asia.

Revolutionizing Retail: An Empirical Study on the Impact of Generative AI in Omnichannel Strategies

This article examines the transformative impact of Generative AI (Gen AI) on omnichannel retail, exploring its role in enhancing customer experiences and streamlining operations across digital and physical platforms. Through a comprehensive analysis of current literature, industry case studies, and empirical data, the study investigates six key applications of Gen AI in retail: personalization and dynamic content creation, virtual shopping assistants, inventory and fulfillment optimization, marketing content generation, customer insights and sentiment analysis, and immersive AR/VR experiences. The findings reveal that Gen AI significantly improves personalization, operational efficiency, and cross-channel integration in retail. However, the research also identifies challenges in implementation, including data privacy concerns and the need for seamless technology integration. This article contributes to the growing body of knowledge on AI in retail and provides practical insights for retailers seeking to leverage Gen AI in their omnichannel strategies. The paper concludes by discussing future research directions and the potential long-term implications of Gen AI on consumer behavior and global retail practices.

The Transformation of Retail Through Digitalization: Analyzing the Impact of Online-Offline Integration and Augmented Reality on Consumer Shopping Experience

The retail industry has especially changed in the last three decades by the effect of the technological change. This study examines the impact of two major innovations: two emerging issues, namely the omnichannel retailing and the augmented reality (AR). Omnichannel retailing combines online and offline selling pointers wherein consumers get a completely integrated purchasing experience whereas AR makes product differentiation easy and allows consumers to engage with products. The concern of this research is to examine how these technologies affect consumers behavior, satisfaction, and loyalty. Therefore, the study adopted a mixed research method, where data was gathered through online questionnaires, interviews and case studies of organizations such as Walmart, Nordstrom, IKEA, and Sephora. Based on the research, there is a suggestion that the synchronization of online and offline purchase touchpoints enhances the shopping convenience and customization; meanwhile, the application of AR enhances the interaction and the confidence of the purchase. Some of other issues that were realized include data privacy and consistent branding throughout the communication channels. This research establishes that these technologies use in strategic processes improves consumer shopping experiences, but more research is required to investigate long-term outcomes and new directions for the retail industry.

Inventory Decisions Considering Returns in Omni-channel Retailing

Omni-channel retail is a new model that is achieved by integrating online stores and offline physical stores. The inventory decision problem considering returns under omni-channel retail is studied in two cases: considering same-channel returns under omni-channel retail and considering cross-channel returns under omni-channel retail. Based on the consideration of consumer returns and resale of returned products, the newsboy model is used to construct inventory decision models with the goal of maximizing retailer profits and analyze the models. Numerical analysis shows that the online store return ratio and the cross-channel return ratio have a significant impact on the inventory and profit of the retailer's offline physical stores and online stores. In particular, when the cross-selling profit is large, the cross-channel return ratio increases, and the retailer's profit increases accordingly, but the retailer's profit may decrease with the increase of the online store return ratio.

Retail reimagined: pricing optimization in single channel, multi-channel and omni-channel retailing

Retail reimagined: pricing optimization in single channel, multi-channel and omni-channel retailing

Enhancing Environmental Awareness for Sustainable Retail: Analysis of the Buy-Online-and-Return-in-Store Policy Adoption Using Theory of Planned Behavior

This study explores the context of buy-online-and-return-in-store (BORS) policy from an environmental perspective and conducts a comprehensive analysis through the theory of planned behavior (TPB). Adding environmental awareness and awareness of consequences provides a new perspective on how sustainable practices can be enhanced through an omni-channel retail strategy. Survey responses from 405 participants were analyzed using structural equation modeling. Results show that attitudes, subjective norms, and perceived behavioral control are key determinants of practical BORS policy. The study found that environmental awareness significantly influenced BORS adoption directly and indirectly by enhancing perceived behavioral control, whereas consequence awareness primarily affected adoption by shaping consumer attitudes. Compared with consumers who choose to return online, consumers who prefer in-store returns show higher environmental awareness, highlighting the environmental advantages of BORS. In addition, the BORS policy improves overall shopping satisfaction by integrating the convenient process of online purchases and offline returns, allowing consumers to switch freely between different channels. These findings provide valuable insights for retailers and policymakers seeking to promote sustainable consumer behavior to effectively promote the importance of sustainable retail practices.

Due date-oriented picker routing, an efficient exact solution algorithm, and its application to pick-from-store omnichannel retailing

The advent of e-commerce and omnichannel retailing has sparked renewed interest in picker routing in warehouses. This paper presents two significant methodological advances in this well-established field. First, it is a well-known fact that the parallel-aisle layout of warehouses, as opposed to general graphs, allows for polynomial-time solutions of the Traveling Salesman Problem. We show that the parallel-aisle structure can also be exploited when pickers are tasked with visiting storage positions associated with specific due dates. We establish that picker routing in warehouses, subject to soft due date constraints, is a binary NP-hard problem. We also present an exact branch-and-bound algorithm with pseudo-polynomial time complexity. This algorithm effectively solves instances with up to 60 picking positions and five cross aisles within a few seconds while guaranteeing optimality. Second, for even larger pick lists, we demonstrate the successful integration of our algorithm into a real-time framework. This approach allows us to avoid extended solution times that would otherwise delay the picker’s departure, without compromising the quality of the solution. To illustrate the practical relevance of these two methodological innovations, we apply our routing algorithm to the context of pick-from-store omnichannel retailing. By assigning due dates to critical products, we significantly reduce stockout occurrences for online customers. These stockouts occur when the stock level, initially deemed sufficient to confirm an online order, is depleted by walk-in customers before the picker reaches the relevant shelf.

Physical stores versus physical showrooms: Channel structures of online retailers

To meet consumers’ expectations for experiential shopping, an increasing number of online retailers are expanding offline channels, with physical showrooms and physical showrooms emerging as the two most popular offline channel modes. Both channels can match consumers’ demand for on-site experiences. However, the two modes differ in terms of service cost, demand promotion efficiency, and channel differentiation generation. The article considers three channel structures: a single online channel, an online channel with physical stores, and an online channel with physical showrooms, as well as two scenarios: non-competitive and competitive. This study examines whether online retailers should integrate offline channels and which offline channel mode they should use by comparing the profit changes of themselves and rivals when three channel structures are adopted in two scenarios. It is found that: (i) If there is a significant difference between the online and physical store channels, providing physical stores help online retailer raise profits. If the physical showroom is highly effective at promoting demand, omnichannel retailers will dominate the entire online market, and expanding physical showrooms is always profitable; (ii) Whether in a competitive or non-competitive environment, online retailers should weigh channel differentiation and the efficiency of the offline channel modes in promoting demand to select the best channel mode; (iii) Due to channel differentiation, online retailers’ creation of physical stores, as well as increasing competition among physical stores, will have no impact on rival retailers. However, providing physical showrooms will result in lower sales volume and revenue for rival retailers.

Future Trends in Multichannel and Omni-Channel Retailing: Implications for Businesses and Consumers

Future Trends in Multichannel and Omni-Channel Retailing: Implications for Businesses and Consumers

What drives customer engagement in fresh food omnichannel retailing? The role of omnichannel integration, flow experience, and customer relationship quality

What drives customer engagement in fresh food omnichannel retailing? The role of omnichannel integration, flow experience, and customer relationship quality

Consumer perspectives on interventions to combat fraudulent product returns in omnichannel fashion retail

PurposeThe expansion of online shopping aligned with challenging economic conditions has contributed to increasing fraudulent retail product returns. Retailers employ numerous interventions typically determined by embedded perspectives within the company (supply side) rather than consumer-based assessments of their effectiveness (demand side). This study aims to understand how customers evaluate counter-fraud measures on opportunistic returns fraud in the UK. Based on the fraud triangle and the theory of planned behaviour, we develop an empirically informed framework to assist retail practice.Design/methodology/approachWe collected 485 valid survey responses about consumer attitudes regarding which interventions are effective against different types of returns fraud. First, a principal component section evaluates the policies' effectiveness to identify any policy grouping that could help prioritise specific sets of policies. Second, cluster analysis follows a two-stage approach, where cluster size is determined, and then survey respondents are partitioned into subgroups based on how similar their beliefs are regarding the effectiveness of anti-fraud policies.FindingsWe identify policies relating to perceived effectiveness of interventions and create customer profiles to assist retailers in conceptualising potential opportunistic fraudsters. Our product returns fraud framework adopts a consumer perspective to capture the perceived behavioural control of potential fraudsters. Results suggest effectiveness of different types of interventions vary between different types of consumers, which leads to the development of propositions to combat the fraud.Originality/valueThis study is unique in assessing the perceived effectiveness of a range of interventions based on data collection and advanced analytics to combat fraudulent product returns in omnichannel retail.

Mitigating Consumer Returns through Omnichannel Retail Operations: An EOQ Model under Stochastic Demand

Mitigating Consumer Returns through Omnichannel Retail Operations: An EOQ Model under Stochastic Demand

Determinants of customer buying behaviour in omnichannel retailing: a systematic literature review and future research directions

PurposeAdvances in digital technologies and the growing number of touch points have had a significant impact on the shopping behaviour of omnichannel customers. Several research papers have explored different facets of omnichannel, but only a few have thoroughly explored the literature on showrooming and webrooming simultaneously. This paper aims to identify the key groups of antecedents influencing customer buying behaviour in omnichannel, under the influence of digital technologies, with a particular focus on showrooming and webrooming.Design/methodology/approachOur study conducted a systematic literature review to identify the factors influencing customers’ buying behaviour in omnichannel, which have been the subject of academic discussion over the last decade. We finalized 149 articles for the thematic analysis and identified three groups of antecedents: channel-related, product-related and consumer-related with their subgroups.FindingsUnder channel-related antecedents, cost and perceived benefits, search convenience, need for interaction and situational circumstances have been identified as major attributes. The expressiveness of the product, product demonstration and search and experienced products have been identified under product-related antecedents, followed by price consciousness, past experiences, perceived risks and shopping motivations as leading attributes under consumer-related antecedents. The study revealed the multifaceted influence of digital technologies on omnichannel buying behaviour. Digital technologies are shaping the antecedents related to channels, products and consumers. Digital technologies simultaneously mediate between antecedents and the selection of a specific path within an omnichannel environment. Showrooming and webrooming should no longer be seen as general concepts. The rise of digital technologies has led to the development of new consumer journey patterns and the blurring of distinctions between showrooming and webrooming. A conceptual framework has been proposed to understand consumers' omnichannel behaviour, having considered the identified antecedents and the role of digital technologies.Practical implicationsThis study advances the academic understanding of consumer behaviour in omnichannel under the influence of digital technologies and provides important implications for omnichannel management. With the advancement of digital technologies such as augmented reality and virtual reality, retailers should implement channel integration strategies to bridge the gap between online and offline channels, providing a memorable shopping experience for omnichannel customers.Originality/valueThis study is unique because it identifies and analyses the antecedents of consumer behaviour in omnichannel settings under the influence of digital technologies. It also uncovers new potential combinations of showrooming and webrooming patterns. The proposed framework can help retailers in their future planning of omnichannel strategies.

Vehicle routing problem for omnichannel retailing including multiple types of time windows and products

This paper addresses the capacitated vehicle routing problem for omnichannel retailing with multiple types of time windows (hard time windows and soft time windows) and multiple types of products simultaneously. The problem aims to transfer multiple products from a central warehouse to stores and satellites, where split delivery is allowed since the demands of stores or satellites are large and the different product types have different volumes. Based on different characteristics of purchasing channels, the time window of a store is a hard constraint while the time window of a satellite is a soft one. This type of vehicle routing problem exists extensively in omnichannel retail distribution systems in the logistics industry of China, which considers multiple purchasing channels for customers. Since this type of vehicle routing problem is an NP-hard problem and more complicated than the conventional vehicle routing problem with time windows, we design an adaptive large neighborhood search (ALNS) method to solve it. Finally, numerical experiments are conducted to evaluate the effectiveness of the proposed algorithm and reveal some managerial insights. The numerical experiments show that the proposed algorithm can obtain a high-quality solution under a shorter computation time compared with the state-of-the-art MIP solver (Gurobi).

The Impact of Modern Lifestyles on Eating Habits and Food Shopping Behaviors: A Case Study of Omnichannel Retail Consumers Aged 25–40 in Athens

The Impact of Modern Lifestyles on Eating Habits and Food Shopping Behaviors: A Case Study of Omnichannel Retail Consumers Aged 25–40 in Athens

Optimizing omnichannel retailer inventory replenishment using vehicle capacity-sharing with demand uncertainties and service level requirements

This study explores an inventory replenishment problem for an omnichannel retailer selling a product with demand uncertainties and service level requirements in different channels through a capacity-sharing strategy. The omnichannel retailer allows customers to order products online and then pick them up in retail stores. The capacity-sharing strategy is considered to reduce travel costs when the omnichannel retailer delivers products in different channels. With the capacity-sharing strategy, some products can be transferred from the online delivery vehicle to the retail store delivery vehicle. The expectation and the bounds on the online route travel cost of the capacity-sharing strategy are determined, based on which the capacity-sharing rules are established. Optimization models and a solution procedure are developed to solve the omnichannel retailer inventory replenishment problem. To ensure adequate performance, service level requirements are considered when making delivery decisions. Numerical experiments using randomly generated and artificial instances are performed to verify the effectiveness and practicality of the proposed optimization models and the solution procedure. The results show that the proposed models and solution procedure can effectively reduce travel costs, and can provide effective schedule and delivery quantity decision support for omnichannel retailers.

Decoding Generation Z's habits: the augmented reality shift from gimmick to utility in omni-digital shopping

Purpose Building on technology acceptance and learning transfer theories, this study aims to evaluate the integration of mobile augmented reality (MAR) in omnichannel retailing touchpoints for Generation Z (or Gen Z)'s apparel shopping, assessing how habitual augmented reality (AR) use in nonretailing contexts impacts Gen Z's motivations, acceptance and use of MAR shopping apps. Design/methodology/approach A total of 562 participants downloaded a footwear MAR app and completed a survey. Data were analyzed using confirmatory factor analysis and multivariate regression to explore moderated mediation effects. Findings The study reveals a paradigm shift: Gen Z's habitual use of AR in social media (e.g. Snapchat and TikTok face filters) significantly influences their intent to use MAR in shopping, overshadowing hedonic motivations. This marks a transition from AR as a gimmick to a practical utility in omnichannel touchpoints, with performance expectancy emerging as a critical mediator in adopting MAR for utilitarian purposes. Research limitations/implications This study highlights how Gen Z consumers’ tech habits influence their pragmatic view of MAR, urging re-exploration of the main constructs of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model. Practical implications Findings suggest Gen Z values practicality over fun in MAR shopping apps, guiding marketers to emphasize tangible benefits for this demographic. Originality/value This research underscores the evolving perception of AR in retail among mobile natives, highlighting the shift from novelty to habitual utility. It offers strategic insights for integrating AR into omnichannel strategies, catering to the utilitarian expectations of Gen Z in the digital retail landscape.

An Analysis of Consumer Behaviour in Multichannel Retailing and Omnichannel Retailing

This paper investigates consumer behavior in multichannel and omnichannel retailing environments. With the evolution of technology and the increasing importance of the internet, consumer expectations and shopping behaviors have significantly transformed. Multichannel retailing, which involves using multiple channels for selling products, and omnichannel retailing, which ensures a seamless consumer experience across all channels, have emerged as critical strategies for businesses. This study aims to explore the differences in consumer behavior in these two retailing models, examining factors such as customer satisfaction, purchase frequency, and loyalty.

The Drivers of Omnichannel Shopping Intention: Assessing the Role of Gender as a Moderator in Apparel Industry

The purpose of this study is to explore the influence of the drivers of omnichannel retailing on omnichannel shopping intention and the role of gender as a moderator in the retailing apparel industry. The findings highlight the significance of customer perception of research shopping (including showrooming and webrooming) behaviors, compatibility, and risk to their intention towards omnichannel shopping, implying a profound understanding of designing an effective omnichannel retailing strategy. This study adopted the quantitative research method approach. The data were collected through a survey method using a close-ended questionnaire. The sample for this study were the individuals who have done shopping in three months period – from the last three months till the time of data collection, physically or virtually. The data were analyzed using Statistical Package for Social Sciences (SPSS) version 23 and Smart PLS. Regression techniques and correlation factor analysis and reliability test were the top priority in data analysis. The study expands the understanding of omnichannel shopping intention and its drivers while assessing gender as a moderator.

Optimisation of a multilevel logistics network for prepositioned warehouses under an omni-channel retail model

A new omni-channel retailing mode, prepositioned warehouses, which developed rapidly in China during the COVID-19 pandemic, was introduced, and a three-level logistics network optimisation model for agricultural products was presented. This study takes into account the characteristics of the omni-channel retail model, which combines the two delivery methods of vehicle delivery and consumer in-store purchase, adds the freshness penalty incurred by fresh agricultural products in the storage process of the prepositioned warehouse, and establishes a mathematical optimisation model of the three-stage logistics network of the prepositioned warehouse that meets the characteristics of omni-channel retailing on the basis of the classical EOQ inventory model. In this work, the shortest delivery time and the smallest total cost are set as the optimisation objectives, and the multi-objective problem is transformed into a single objective through normalisation and linear weighting methods to obtain a mixed-integer optimisation model. This paper solves the problems of site selection for prepositioned warehouses, merchandise replenishment strategies, and optimisation of delivery routes based on data from real cases. Additionally, through sensitivity analysis, the management inspiration of the enterprise is obtained.