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This study aims to understand why consumers continue to visit physical stores despite the rise in mobile shopping and online channels. Mobile shopping has changed how consumers shop, allowing them to easily switch between channels. However, physical stores continue to remain significant because some consumers still prefer them, challenging the belief that online markets always surpass offline markets. To serve their needs effectively, retailers must understand the motivations and behaviors of shoppers in both channels. Therefore, this study aims to explore why people cross the online channel to offline by examining their dissatisfaction with online shopping, using E-SERVQUAL variables.

This study uses a two-method approach that involves in-depth interviews to develop questions related to E-SERVQUAL variables and a survey to assess respondents’ likelihood of switching from online to offline. Data was collected from 203 participants.

The results indicate that dissatisfaction with the timeliness and condition of online shopping services is a significant factor driving consumers to switch to physical stores. This challenges the notion that online markets always surpass offline markets, emphasizing the continued significance of physical stores in the retail landscape.

This study recognizes the importance and relevance of physical stores in the retail environment while challenging the assumption that online markets always outperform brick-and-mortar markets. In terms of dissatisfaction and satisfaction, it is possible to identify under what circumstances dissatisfied consumers go from online to offline by considering the distribution channel migration phenomenon.

This paper aims to study how retailers moving from a multi- (in-store and online) to a single- (online) channel impacts consumers’ retailer and channel choices.

The authors conduct two scenario-based experimental studies to examine consumers’ in-store and online channel shopping preferences and behavioural intentions (i.e. channel and retailer choices) when their preferred focal retailer’s physical store closes.

The findings show that when a focal retailer removes its physical store location, consumers with a strong preference for shopping online have a greater likelihood of shopping online. Their loyalty towards the retailer explains this relationship but is conditional on low levels of reactance. When reactance is high, consumers with a strong preference for shopping online are more likely to switch to a competitor.

This research paper bridges the intersection between B2B and B2C literature to understand how retailers’ channel-related supply chain decisions affect downstream consumer shopping behaviour.

Perishable inventory management for the grocery sector has become more challenging with extended omnichannel activities and emerging consumer expectations. This paper aims to identify and formalize key performance measures of omnichannel perishable inventory management (OCPI) and explore the influence of operational and market-related factors on these measures.

The inductive approach of this research synthesizes three performance measures (product waste, lost sales and freshness) and four influencing factors (channel effect, demand variability, product perishability and shelf life visibility) for OCPI, through industry investigation, expert interviews and a systematic literature review. Treating OCPI as a complex adaptive system and considering its transaction costs, this paper formalizes the OCPI performance measures and their influencing factors in two statements and four propositions, which are then tested through numerical analysis with simulation.

Product waste, lost sales and freshness are identified as distinctive OCPI performance measures, which are influenced by product perishability, shelf life visibility, demand variability and channel effects. The OCPI sensitivity to those influencing factors is diverse, whereas those factors are found to moderate each other's effects.

To manage perishables more effectively, with less waste and lost sales for the business and fresher products for the consumer, omnichannel firms need to consider store and online channel requirements and strive to reduce demand variability, extend product shelf life and facilitate item-level shelf life visibility. While flexible logistics capacity and dynamic pricing can mitigate demand variability, the product shelf life extension needs modifications in product design, production, or storage conditions. OCPI executives can also increase the product shelf life visibility through advanced stock monitoring/tracking technologies (e.g. smart tags or more comprehensive barcodes), particularly for the online channel which demands fresher products.

This paper provides a novel theoretical view on perishables in omnichannel systems. It specifies the OCPI performance, beyond typical inventory policies for cost minimization, while discussing its sensitivity to operations and market factors.

Due to product value uncertainty, consumers do not know the product matching rate before they get the product, which is the probability of product fitness. Taking the consumers’ anticipated regret into account, this paper aims to develop a theoretical model to explore how the anticipated regret affects pricing and advertising decisions and profits of retailers in the online to offline (O2O) supply chain.

This paper considers an O2O supply chain consisting of an e-retailer and a brick-and-mortar retailer; both retailers cooperate to provide buying online and pick up in-store (BOPS) for consumers.

It shows three major findings. Retailers should decide whether to introduce BOPS channel according to the matching rate of the product when the BOPS channel is not very convenient for consumers. When the BOPS channel does not exist in the market, the profits of two retailers increase with the online regret of consumers, while the BOPS channel exists in the market and the matching rate of the product is low, the higher offline regret can enable both retailers to increase the profits; furthermore, when the matching rate is high, the higher degree of online regret can bring more profit to the O2O supply chain. Therefore, both retailers can take measures together to induce consumers’ regrets according to the different matching rates, which makes both retailers obtain more profits. Counterintuitively, consumer surplus will not always increase due to consideration of anticipated regret.

The model has some limitations that are worth further discussing. First, in practice, the O2O supply chain includes many forms except the BOPS channel, for example, order online and pick-up in-store (ROPS) channel; future research can discuss and consider the impact of consumers’ anticipated regret on ROPS. Second, the authors consider that O2O is a supply chain composed of two retailers. In reality, there is also a situation where an oligopoly retailer opens two channels to realize O2O supply chain, in the case the inventory decision-making of the product is worth studying. Finally, to highlight the impact of the anticipated regret on consumers’ decision-making, the return of the product is not considered. Future research can take the return of the product into account to assess the robustness of the results.

The contributions are in two main aspects. First, this paper considers an O2O supply chain with consumer value uncertainty, where there are duopoly retailers in the market and most of the existing literature focus on oligopoly retailer operates both online and offline channels; meanwhile, consumers’ value perceptions of the product is deterministic. Second, this paper explores how the consumer anticipated channel regret affects the pricing and advertising decisions of O2O supply chain, and the authors take behavioral theory into account when studying omnichannel operations, while most studies on anticipated regret consider traditional two-stage price reduction management, product innovation, etc.

The rapid development of the Internet has led to an increasingly significant role for E-commerce business. This study examines how the green supply chain (GSC) operates on the E-commerce online channel (resell mode and agency mode) and the traditional offline channel with information sharing under demand uncertainty.

This study builds a multistage game model that considers the manufacturer selling green products through different channels. On the traditional offline channel, the competing retailers decide whether to share demand signals. Regarding the resale mode of E-commerce online channel, just E-tailer 1 determines whether to share information and decides the retail price. In the agency mode, the manufacturer decides the retail price directly, and E-tailer 2 sets the platform rate.

This study reveals that information accuracy is conducive to information value and profits on both channels. Interestingly, the platform fee rate in agency mode will inhibit the effect of a positive demand signal. Information sharing will cause double marginal effects, and price competition behavior will mitigate such effects. Additionally, when the platform fee rate is low, the manufacturer will select the E-commerce online channel for operation, but the retailers' profit is the highest in the traditional channel.

This research explores the interplay between different channel structures and information sharing in a GSC, considering price competition and demand uncertainty. Besides, we also considered what behaviors and factors will amplify or transfer the effect of double marginalization.

An omni-channel is a retailing strategy that the behavior of companies adopts many retail channel types to combine and integrate cross-channel sales to meet the comprehensive needs of customers in shopping, entertainment and social networking both online and offline. This leads to several research questions of retailing omni-channel in this study. First, do channel brand trust (CBT) and store image (SI) affect re-patronage intentions through customer satisfaction (CS)? Second, regarding online rating (OR) and online involvement (OI), will CS be determined by consumer perception as well as the relevance of those attributes to the customer's re-patronage intentions? Third, do OR and OI have a role in exploring the moderating effect in the research model? Fourth, if there are positive effects from this relationship, it can generate a positive power return online. In addition, online-to-offline moves on a path for case firm omni-channel with customers' OR and OI with a reciprocal positive influence.

This study aims to investigate the relationship between CBT, SI, CS and re-patronize intention in an omni-channel. By using structural equation models (SEMs), this study aims to investigate offline-to-online and online-to-offline re-patronizing in the Taiwan Chunghwa Telecom (CHT) omni-channel (N = 1,642). Two moderated mediation models are investigated in this study.

This study first found that CBT and CS use SI to influence re-patronize intention in the omni-channel. SI plays a mediating role in this process; OR and OI influence the relationships of CBT, CS and re-patronize intention with two moderating roles.

This study first found that there is a reciprocal way with two paths in an omni-channel, starting with offline-to-online, in terms of confirming the relationship of CBT, CS and re-patronize intention in an omni-channel. There are positive effects from this relationship, and it can generate a positive power return online. In addition, we found that online-to-offline moves on a path that has a stronger influence of re-patronize intention for omni-channel with customers' OR and OI.

The pandemic impacted consumers' shopping processes, leading them to approach the online channel for grocery shopping for the first time. The paper contributes to the retailing literature by identifying different grocery shopper segments willing to switch online moved by heterogeneous motivations. Integrating the technology acceptance model 2 (TAM-2) and the protection motivation theory (PMT), this study identifies technology-related and Covid-related motivations jointly impacting channel switching.

A mixture regression model was estimated on the 370 valid questionnaires, filled out by Italian shoppers, delivering four internally consistent segments.

The results reveal the existence of four segments willing to switch towards the online channel for grocery shopping in the aftermath of the pandemic. Utilitarian shoppers would switch online as they consider the online channel useful and easy to use. Responsive shoppers will prefer the online channel driven by the fear of being infected in-store. Novel enthusiasts show interest in the online channel to not catch the virus and cope with emotional fear, although they consider online shopping as an enjoyable and useful activity as well. Smart shoppers consider online shopping as an easy-to-use alternative for their grocery purchases.

This paper identifies technology-related and Covid-related motivations jointly impacting shoppers' channel switching to online and presents a novel method – i.e. mixture regression – allowing for the identification of shopper segments motivated by different reasons, both emotional and utilitarian, to switch towards the online channel for their grocery shopping. Among other motivations, the fear of Covid-19 is identified as a relevant motivation to switch to online.

Motivated by the real-world practice that the boom of the online selling induces a higher product return as well, selecting which online channel mode indicates who takes ownership over the product and thus bears the loss of the product return. This paper aims to seek the optimal online channel modes for the two members in a platform supply chain in the presence of product returns.

This study aims to develop a platform supply chain that consists of one platform company and one supplier. Along with an offline distribution channel, the supplier can choose two alternative online selling modes (i.e. the reselling and agency modes) to sell its product through the online marketplace. This paper applies Stackelberg game to derive the equilibrium with different business scenarios and selects the optimal online channel modes for two parties, respectively. Moreover, this paper extends to a different supply chain with a reverse channel leadership and a different product return policy for testing the robustness.

Several interesting and important results are derived in this paper. Firstly, it is found that the relative pricing are largely relied on the costs of two channels. Secondly, the platform supply chain may benefit from a pure channel rather than the dual-channel when this channel enjoys a relatively low cost and/or a sufficiently high consumer preference. Then, the platform and the supplier act contradictorily when selecting their optimal online channel modes. To be specific, the platform motivates to choose the online reselling mode when both the commission rate and the slotting fee are relatively low, whereas the supplier is likely to select the online agency mode under this circumstance. Finally, a win-win situation in regards to the optimal online channel mode for two parties is achievable with numerical experiments.

Based on the analytical studies, the results derived in the authors’ work can provide managerial insights to assist the supplier and the platform company in determining the operational decision and selecting the optimal online channel mode to deal with consumer returns. In addition, appropriate commission rate along with slotting fee will make both parties achieve a win-win situation in determining their optimal online channel mode.

To the authors’ best knowledge, this paper makes the first move to determine the optimal online channel mode in the content of consumer returns and study how it is affected by different product return policies.

Enterprises' multichannel operations provide various avenues for customer interaction; however, existing literature investigating customer-to-customer interaction (CCI) mainly focuses on a single channel. The purpose of this paper is to investigate the spillover effect of CCI and potential underlying mediating mechanisms in different information channels.

Three between-subjects experiments with 946 participants were employed to empirically validate the proposed hypotheses in the context of an experiential product and a material product.

Results suggest the clear spillover effect of CCI, indicating that positive CCI improves focal customers' satisfaction and purchase intention, whereas negative CCI reduces focal customers' satisfaction and purchase intention. Moreover, CCI's spillover effect varies based on the CCI channel. Offline CCI has a stronger positive spillover effect than online CCI. Contrarily, online CCI has a stronger negative spillover effect than offline CCI. Customer experience and trust are demonstrated to have mediating roles in this process.

This study is the first to comprehensively understand and compare the CCI spillover effect of the two information channels. The findings add to the existing knowledge of information processing in the psychological mechanisms influencing the belief in addition to providing insights for companies engaged in multichannel operations management across different channels.

Newly established intersections between offline and online channels create room for enhancing inter-channel synergies. The nature and structure of emerging markets only further emphasize the need to expand existing knowledge. Consequently, this study investigates inter-channel synergy creation during offline–online retail integration in emerging markets.

Data collected from 97 companies in Serbia that incorporated online channels into their offline retailing businesses were analyzed using the structural equation modeling method.

The results show that retailers who have undergone click-to-brick integration in the emerging markets struggle to leverage physical presence for inter-channel synergy creation through digital channels. Essentially, retailers integrating clicks into bricks in emerging markets are less likely to achieve immediate omni-channel synergy, resorting to a multi-iterative transition process.

This research synthesizes knowledge on inter-channel synergy creation in an omni-channel context, as well as existing findings regarding inter-channel integration. This paper presents the first comprehensive study on inter-channel synergy creation during click-to-brick integration in emerging retail markets. Moreover, this study outlines challenges facing retailers seeking channel synergy during click-to-brick integration. The study results have theoretical and practical implications regarding inter-channel synergy creation in the multi-channel environment of emerging markets.