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Previous studies have rarely integrated the financing modes of a capital-constrained manufacturer with the choices of online sales strategies. To address this gap, the authors study how a manufacturer selects optimal financing modes under different sales strategies in three dual-channel supply chains.

This paper considers three sales strategies, namely, combining a traditional retailer channel with one of the direct selling, reselling and agency selling channels, and two common financing modes, namely, bank financing and retailer financing. The authors obtain equilibrium outcomes of the manufacturer and traditional retailer and then provide the conditions for them to select optimal financing modes under three sales strategies.

The results indicate that the manufacturer’s financing decisions rely on the initial capital and interest rates, and the manufacturer selects retailer financing only if the initial capital is relatively larger. In terms of financing mode options, the retailer financing mode is more beneficial for the manufacturer under the three sales strategies. From the perspective of sales strategies, the direct selling model is more beneficial. In addition, the higher the consumer acceptance of the online channel, the more profits the manufacturer obtains.

This paper provides suggestions on how the capital-constrained manufacturer chooses financing modes and sales strategies.

This paper integrates the financing mode and different sales strategies to investigate the manufacturer’s optimal operational decisions. These sales strategies allow us to investigate the manufacturer’s optimal financing modes in the presence of both different financing modes and sales strategies.

This paper aims to examine why retail firms seldom achieve full integration of online and offline channels as prescribed in omni-channel literature. It examines the intermediate process of channel integration from an internal, operational perspective.

This study is composed of two parts. In the first part, the authors interviewed informants from nine firms that were engaged in channel integration. In the second part, the authors conducted case studies with three firms from the cosmetics and skincare industry against the backdrop of the COVID-19 pandemic to find evidence to support or negate the propositions made in the first part.

The first part identified six operational challenges to channel integration. The authors categorized these challenges into two groups: inter-channel communication and inter-channel competition. Inter-channel competition carries more weight at the latter stage of integration. The authors also identified two antecedents that affect the seriousness of these challenges: heterogeneity among channels in business operation and external competitive pressure. In the second part, the authors found that both inter-channel communication and inter-channel competition were improved because of the external competitive pressure exerted by the COVID-19 pandemic. However, the heterogeneity of offline channels against online channels in business operation is a double-edged sword.

The study identifies the changing effects of the challenges of channel integration and their antecedents in the midst of integration. The positive influence of a specific dimension of channel heterogeneity against other channels increases and then decreases along channel integration. The identification of the changing effects lays the foundation for a finer stage model of channel integration.

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.

This paper investigates the buy online and pick up in-store cooperation (BOPSC) of online and offline retailers. Specifically, this study solves the following questions: (1) What is the impact of BOPSC on their optimal price and sales volume of products? (2) When should an online retailer and an offline retailer conduct the BOPSC strategy with each other?

The paper first establishes two game models to explore the equilibriums of online and offline retailers in non-BOPSC and BOPSC. Then the condition for online and offline retailers to implement BOPSC strategy are determined. Furthermore, the applicability of the BOPSC strategy is enhanced by incorporating numerical analysis.

The study’s findings reveal that BOPSC strategy will not always beneficial to online and offline retailers, which depends on the total cost of online shopping and the product valuation of consumers. BOPSC strategy leads to the increase of prices and online orders, and the demand of offline retailer is eroded. Moreover, BOPS cooperation between different retailers is easier to achieve than omni-channel integration strategy. When the convenience difference between offline shopping and BOPSC pick-up is moderate, the effectiveness of BOPSC strategy can be improved.

This study has the following two main contributions: Firstly, the authors investigate the effects of BOPSC strategy on the prices of online and offline retailers. The study results show that the BOPSC strategy alleviates price competition and promotes a win–win situation between online retailers and offline retailers. Secondly, this paper mainly studies the cooperative behavior between online and offline retailers and reveals the optimal conditions for online and offline retailers to adopt BOPSC strategy. It can help small- and medium-sized online and offline retailers to choose suitable products for BOPSC strategy, so as to achieve the purpose of increasing profit.

The paper attempts to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a two-part tariff coordination mechanism.

To deal with this pricing conflict problems of dual-channel supply chain consisting of dominant manufacturer and a retailer, considering the fact that online reviews and in-sale service are important factors on consumers’ purchase decisions, the authors establish some basic models and exploit them to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a profit-sharing coordination mechanism.

The results show that the optimal online direct selling price is positively correlated with product perceived quality obtained from online reviews and negatively correlated with the in-sale service. The traditional retail price is positively correlated with the in-sale service and weakly correlated with online reviews. For the manufacturer and retailer, whether decentralized decision or coordination contract, their profits increase with the increase of the in-sale service in a certain range and quality perceived from spontaneous online reviews. Online reviews and in-sale service are important factors on consumers’ purchase decisions. Positive in-sale services and online reviews can provide consumers with a better shopping experience, thereby promoting their enthusiasm for shopping and improving their quality of life. The two-part tariff coordination mechanism improves the profits of the manufacturer and the traditional retailer, respectively, through the transfer fee.

The proposed approach can well analyze the channel conflicts and pricing problems between retailers and manufacturers with respect to product offline price and online price. The analysis and results can inform decision-making for manufacturers and retailers.

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.