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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.

Although buy-online-and-pick-up-in-store (BOPS) has been widely implemented by companies, scant attention has been paid to its effect on consumer experience and the concomitant outcomes. Using the psychological ownership theory, this study aims to examine whether and how the BOPS experience (vs online experience) can enhance consumer loyalty.

Study 1 investigated the consumer loyalty of shopping experience (self-pickup vs delivery) on actual consumer behavior through secondary data. Studies 2, 3 and 4 were controlled experiments to further investigate the mediating effect of product psychological ownership, and the moderating effects of product type and postdecision experience valence.

The authors found that BOPS shopping led to higher consumer loyalty (i.e. repeat purchase and repeat purchase frequency) compared with online shopping. Furthermore, the authors examined that this effect was mediated by product psychological ownership and moderated by product type and postdecision experience valence.

Theoretical speculations about how BOPS shopping affects consumer experience should be probed in future research.

Retailers with physical stores can offer in-store pickup options for their online consumers to increase their product psychological ownership and consumer loyalty. And the positive effects of the BOPS strategy relied on product type and postdecision experience valence.

This research offers theoretical contributions to research on the BOPS strategy, psychological ownership theory and consumer loyalty.

In an omnichannel environment, customers switch channels from product discovery to eventual purchase decision strategically. Hence, the biggest challenge for retailers nowadays is how to operate an effective omnichannel strategy. To improve inventory operational efficiency, this chapter investigates the influences of price setting and customers’ return probability on inventory forecasting. Subsequently, we explore how retailers participate in providing appropriate information delivery and product fulfillment. Specifically, a stylized newsvendor model, which incorporates customers’ showrooming behavior, is developed to address retailers’ inventory problem. Furthermore, we compare the benefits of buy-online-and-pick-up-in-store (BOPS) and showroom strategy which originates offline but is completed online. Three main findings are obtained as follows: (1)online and offline inventory order quantities augment with the ascending of pricing offline and online, respectively. Meanwhile, the inventory decisions increase when customers’ return probability declines; (2) the implementation of showroom helps retailers expand their pure online market coverage than BOPS, while it reduces the total inventory quantity if the proposition of unit online inventory cost accounting for product price exceeds physical store; and (3) showroom strategy is more profitable than BOPS option as long as unit online inventory cost is small enough. In addition, we find this boundary where showroom increases total profit expands with the attenuating of return probability.

As one of the omnichannel sales models, “buy online and pick up in store” (BOPS) not only is used in the commercial field but also has gradually attracted many scholars’ interests. However, although there are numerous research ideas, most of the current work is still limited to theoretical and empirical research, and few scholars study BOPS through models. This paper aims to discuss the best market conditions and opportunities for the implementation of BOPS against the backdrop of omnichannel by means of mathematical models and data simulations and discuss the optimal price–service strategies under different sales models.

First, from the perspective of different consumer shopping types, this paper separately divides consumers into different groups in traditional “dual channel” and BOPS models. Then, the authors analyze the impact of company market size, consumer service sensitivity and the scale of BOPS on companies’ strategies and the profit of the supply chain. Subsequently, they conduct an empirical analysis through specific values. Finally, the authors further expand the model on the basis of the original research, and discuss the retailer’s fairness concerns and unit compensation strategy to ensure that the research content is more rigorous.

It is observed that whether companies adopt BOPS depends on consumers’ service sensitivity degree and the scale of BOPS consumers and online retailers: when the sensitivity and the proportion of online consumers are high or the number of BOPS consumers is large, it is more advantageous for companies to implement BOPS. Moreover, companies should not only consider the market scale and production cost but also have a precise orientation of consumers’ experience sensitivity and willingness to engage in extra consumption when making price and service strategies. At the same time, the compensation strategy of companies and the peer-regarding fairness concern behavior of offline retailers will affect the optimal price and service strategy in the BOPS model.

These results provide managerial insights for companies preparing to implement BOPS and promote the development of relevant theories in the channel field.

At present, most of the research on BOPS is based on empirical reviews. However, this paper analyzes the applicability and feasibility of implementing BOPS by using specific models, and it will provide some reference for companies preparing to implement BOPS. In addition, this paper also discusses the unit compensation strategy and peer-regarding fairness concern behavior in the BOPS model, which have not been studied by relevant scholars.

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.

This study aims to investigate the moderating effects of brick-and-mortar (BM) store characteristics and customer satisfaction on the relationship between ship-to-store (STS) retailing and BM store performance in an emerging economy. The purpose is to explore how BM store characteristics and customer satisfaction influence online buying behaviour when customers visit the stores to pick up their products.

This study collected secondary longitudinal data from 615 BM stores from one of Brazil's largest retailers and performed a panel-data regression analysis using the following moderating variables: customer satisfaction with BM stores, BM store's size, convenience and inventory transparency.

Customer satisfaction with BM stores moderates the effect of STS transactions on the revenue per store. Results also show that BM store's convenience, size and inventory transparency moderate STS online customers' impact on BM store cross-sales.

The STS strategy can increase online and BM store performance. Some BM store characteristics and customer satisfaction influence online customers to buy more products when they visit BM stores to pick up their products, providing a more complex model for the relationship between STS strategy and BM store performance.

Companies in emerging economies can use the BM store more strategically in combination with the STS strategy to increase overall retailer performance. By managing some BM store characteristics, managers can improve retail sales.

This study demonstrates how new moderating factors expand the understanding of the relationship between online and physical retailing in emerging economies. Also, the panel data regression results control for extraneous variables and provide more robust evidence of the relationships observed.

Both online and brick and mortar retailers have invested heavily in developing omni-channel service offerings. Though seen as a competitive necessity, these omni-channel service offerings increase costs and complexities. The purpose of this study is to examine the effects of strategies involving bundles of omni-channel services related to order fulfillment and returns management on retailer performance.

Archival data were obtained for 152 retailers and analyzed using ordinary least squares regression. Robustness tests using an alternative dependent variable and a model-based classification strategy corroborate our findings.

Retailers offering full sets of high integration omni-channel services (buy online pick up in store, ship from store and in-store returns) have better performance (e.g. sales, growth and competitive position) and web sales than retailers that offer only a partial mix of these high integration services. Retailers offering a partial bundle of high integration services, in turn, have better performance and web sales than retailers that offer none of these services.

The research extends work that has examined the performance effects of omni-channel services on individual retailers. Our results indicate retailers benefit the most when offering a full set of high integration omni-channel services, suggesting retailers who have only adopted a subset of these services could improve performance through broader adoption of services. The results further indicate partial adoption of high integration services is better than no adoption.

Many e-commerce firms suffer from high returns because of inaccurate and incomplete product information. Omnichannel and bundling settings can help firms improve operational efficiency and lower returns costs. However, no studies have been conducted on omnichannel supply chains considering bundling strategies. The purpose of this study is to examine the comparison between test-in-store-and-buy-online (TSBO) and online retail, comparing manufacturers’ bundling with retailers’ bundling.

The supply chain discussed here consists of two competitive manufacturers and one retailer. The retailer sells both manufacturers' products online and displays one manufacturer's product in a showroom who bears the display cost. Stackelberg game theory is used to develop mathematical models that help manufacturers and retailers make the most effective decisions. Here, the manufacturer is the Stackelberg leader, while the retailer is the follower. Using the backward induction approach, the authors determined the optimal values for selling price, wholesale price and service effort level.

The results show that the total TSBO retailing profit under manufacturer bundling is highest when the second manufacturer integrates with the online retailer. The result additionally establishes that when the bundling cost exceeds a certain threshold (1.5), the total profit is higher for the non-integrated type of supply chain channel as compared to the integrated retailer bundling-based configuration.

The operations and logistics manager will likely undertake the TSBO omnichannel strategy during manufacturers bundling and retailer bundling under the integrated strategy.

The main contribution of the study is to examine the effect of TSBO retailing on supply chains profit and individual decision-making under different bundling strategies. The authors developed different mathematical models in the TSBO retailing and bundling context and extended the earlier work in the area of integration frame.

The authors analysed the operations of two synchronised channels by focusing on “buy online and return in store” (BORS) strategies in fast-fashion retail by investigating internal and external factors affecting this omnichannel strategy.

The authors apply a combination of techniques to identify the BORS factors. Firstly, a strengths, weaknesses, opportunities and threats (SWOT) analysis was used to define the operational factors of BORS adoption. The authors then apply analytic hierarchy process (AHP) to evaluate the factors under four SWOT categories for kids, male and female consumer groups. The factors of BORS were then ranked using the fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (fuzzy VIKOR) approach.

Combining the SWOT, AHP and fuzzy VIKOR techniques, the authors identified 21 factors in this study. The opportunity that BORS provides for trying in the fitting room for a better convenient shopping experience was ranked as the most important factor, followed by the opportunity to create a loyal customer profile with an easy and well-organised return process. Furthermore, the results reveal that the child consumer group is the most critical of the stated operations factors, followed by male and female consumers.

The authors described the operational factors and supported the decision-making system of BORS for each consumer group with a priority ranking to realise effective managerial management for fast-fashion retailers and practitioners.

The study contributes to the growing literature on the BORS omnichannel strategy, specifically for fast-fashion retail based on consumer needs.

This study conducts a systematic literature review of e-tail product returns research. E-tail product returns are essentially acquisition of products that have been sold through purely online or brick-and-click channels and then returned by consumer to business.

Using a systematic literature review protocol, we identified 75 peer-reviewed articles on e-tail product returns, conducted bibliometric analysis and content analysis of the articles and summarised our findings.

The findings reveal that the subject of e-tail returns is a new research area; academics have started to investigate several aspects of e-tail returns through different research methodologies and theoretical foundations. Further research is required in leading e-commerce countries and on key areas such as omni-channel returns management, customer satisfaction and service, the impact of resources such as people skills, the benefits of technology and IT systems in managing e-tail returns.

The study offers a summative account of current e-tail knowledge areas, which can serve as a reference guide for e-tailers to develop strategies for more efficient and competitive product returns.

This study contributes theoretically by developing clusters of key themes or knowledge areas about e-tail returns. It also provides a conceptual framework for e-tail returns management, which can be used as a springboard for further empirical research.