Dual-channel Retailer Research Articles

Fulfillment Center Location and Network Design in Dual-Channel Retailing

Fulfillment Center Location and Network Design in Dual-Channel Retailing

Does outsourcing enhance consumer services and profitability of a dual-channel retailing?

In the era of digital commerce, the concept of dual-channel retailing has attracted increased attention. Dual-channel retailing increases the importance of outsourcing for an imperfect production process to enhance customer satisfaction. This study explores a sustainable dual-channel retailing strategies for an imperfect production process under a flexible production system. The manufacturer runs a production process prone to defects utilizes both offline and online channels for product sales. The manufacturer contemplates green investments to enhance the production efficiency and reduce waste and carbon emissions, alongside the possibility of outsourcing a portion of production to a partner. A mathematical model is developed to accounts for these factors and analyzes the optimal allocation of products between channels, pricing strategies, production rates, and investments amount to reduce carbon emissions. The model incorporates demand sensitiveness to green practices and channel's selling price. Results of this research are directed towards offering significant perspectives for organizations that aspire to attain a harmonious equilibrium among financial profitability, ecological sustainability, and addressing deficiencies in their manufacturing procedures in a dual-channel retail setting through subcontracting. Numerical illustrations exhibit that partial outsourcing enhances system's profit by 2.03%, whereas investments to reduce carbon emissions enhance the profit by 4.95%. Flexibility in the production process helps to increase the profit by 13.50%, and channel coordination helps to enhance the profit by 38.54%.

A strategic analysis of timing of wholesale pricing and information sharing strategy in dual-channel retailing

A strategic analysis of timing of wholesale pricing and information sharing strategy in dual-channel retailing

Embracing the power of AI in retail platform operations: Considering the showrooming effect and consumer returns

This study examines a duopoly market comprising an online retail platform and a physical store, both of them selling experience-based products to consumers who are unaware of the products’ fitness. The platform could introduce artificial intelligence (AI) technology into retail operations to address consumers’ fitness uncertainty and then gain market share, while the physical store could exert a service effort to recapture the market, potentially facilitating showrooming behavior. Operational decisions including pricing, AI application, and service effort exertion are investigated in the cases where consumers are allowed and unallowed to return unsuitable products. We first develop a theoretical model of dual-channel retailing to determine the equilibrium operational decisions for the supply chain members, and then examine the interactions between these operational decisions and consumers’ showrooming behaviors. Subsequently, we perform numerical simulations to verify the robustness of the theoretical findings. Results indicate that both AI application and service efforts exertion will strengthen consumers’ showrooming effect, especially when the cost of AI application is relatively low. Moreover, regardless of whether the store implements the service effort or not, the platform prefers to apply AI technology when consumers are allowed to return products. Furthermore, the physical store will always exert a service effort, and with the service effort, the application of AI technology in the retail platform operation could effectively mitigate the impact of consumer return on supply chain members.

Perils and Merits of Cross-Channel Returns

In this article, we study the impact of cross-channel returns on a bricks-and-clicks dual-channel retailer's overall profit, individual channel prices, and individual channel demand under two scenarios: 1) exogenous returns and 2) refund-dependent returns. Our study reveals a number of interesting results. For example, when channel substitutability is high, accepting online purchased returns in the bricks-and-mortar store is likely to drive the in-store price up, despite a drop in the offline demand due to the cannibalization effect. In general, firms should allow cross-channel returns when channel substitutability is high, return handling cost is low, and self-channel returns are not hefty. Unlike the extant literature, we also see that bricks-and-mortar returns impact a multiple-channel retailer's optimal return policy. We are also able to verify that our main findings are fairly consistent under both exogenous and refund-dependent returns scenarios.

Optimal pricing for dual-channel retailing with stochastic attraction demand model

In dual-channel supply chains, where retailers sell their goods both online and in physical stores, determining the optimal pricing strategy while considering customer behavior is a critical challenge. This study introduces and investigates a dual-channel pricing model that accounts for customer channel choice behavior. Drawing inspiration from market-share models, we incorporate a demand model that reflects the attraction between online and physical stores. Our approach includes stochastic assumptions for potential market demand and price-based interactions between the two channels. In particular, we model the channel’s stochastic demand as a non-linear function of prices and we allow for different customer reactions when the physical store runs out of stock. This paper makes two key contributions. First, we highlight the analytical complexity involved in verifying the joint concavity of the retailer’s expected profit function with respect to selling prices. To address this challenge, we introduce a novel approach to establish the existence of optimal global prices in the context of non-linear demand and a non-linear, non-concave objective function. Secondly, our study offers practical insights by applying the model to various operational scenarios. We provide guidance on the best pricing strategy when physical store capacity is limited. Depending on customer channel preferences, prioritizing the showroom may lead to higher profits. However, optimizing for profit could result in a reduced market share. In a showroom configuration, the retailer’s choice may shift between exclusive physical and exclusive online retailing to maximize profit.

The impact of sales effort on a dual-channel dynamical system under a price-sensitive stochastic demand

Sales efforts play a crucial role in dynamic retail management and can have a significant impact on the overall success of a retail business. The primary goal of sales efforts is to generate revenue. By effectively promoting and selling products or services, sales teams can drive sales and increase the company's revenue. Demand of products play a critical role for retailing sector and demand cannot be predicted perfectly in reality. Owing to this situation, a dynamical system with dynamic sales effort and price-sensitive stochastic demand is proposed in this study. A dual-channel (online & offline) is considered in this study to provide the best consumer experience. Contradictory to the existing literature, geometric Brownian motion under a fuzzy environment is utilized to handle the dynamic price situations, which is solved through the Black-Scholes equations. The effect of preseason cost on the optimal results is analyzed. To validate the study, a numerical analysis of the dual-channel retailing system is presented with optimal selling price, sales effort, and profit under stochastic demand. Sales efforts have a profound impact on dynamic retail management. They drive revenue generation, customer acquisition and retention, inform inventory management decisions, provide market insights, contribute to competitive advantage, align with marketing strategies, and enable performance measurement and improvement. From the findings, it is clear that sales effort can provide 0.02% higher profit per cycle in a dual-channel retailing.

The impact of adopting customization policy and sustainability for improving consumer service in a dual-channel retailing

In recent decades sustainability and dual-route retailing have been adopted by many big industries. Companies are now bound to maintain such strategies that fulfill the sustainable goals developed by the United Nations. Industries face a huge penalty if carbon emissions exceed a certain boundary. Moreover, factories should maintain sufficient flow in retail chains and product quality. This paper demonstrates 3-pillar sustainability in dual channel retailing, empowering firms to integrate the financial-economic pillar with the non-financial (environmental, social, and ethical) pillar. The core product is made available through the traditional channel and customized products are through online channels. The model is enabling the customers with customization provisions where they can influence the products. Thus, as a novel approach, the article incorporates a presumed threshold limit on the product's (standard and customized) selling price difference. Due to customization, a new product is developed which needs extensive quality checks. The study introduces an investment in checking the quality of the customized product which reduces the probability of customization defects exponentially. Additionally, current research adapts the carbon emission cost, penalties charged to a firm for overshooting the limit, and social costs in a smart supply chain. It also exemplifies that production is directly proportional to financial investments in meeting sustainability objectives. The numerical analysis reflects that as production increases, penalty costs decrease at a significant rate but after reaching optimal production penalty cost again starts to increase. It is observed that the downfall of penalty is 20% more for the single-channel than dual. Adaptation of the customization policy makes the retailing strategy more cost-effective. The model exemplifies that it is more economical to adopt dual-channel retailing compared to single-channel as there is approximately a 14.0625% reduction in total cost in dual-channel retailing. Moreover, an 80% improved quality is observed with a financial investment, which improves consumer satisfaction.

Dual-channel retailing strategy vs. omni-channel buy-online-and-pick-up-in-store behaviors with reference freshness effect

When the freshness of the firm's food is not observable, consumers may experience psychological feelings of elation or disappointment when the perceived actual freshness exceeds or falls short of their initial expectations. This paper investigates the firm's optimal selling strategies considering the consumer reference freshness effect in a fresh food supply chain. We consider two selling modes: the dual-channel retailing strategy (DCRS) mode in which the retailer sells food to consumers from store and online, and the omni-channel buy-online-and-pick-up-in-store (BOPS) mode in which the retailer additionally provides the BOPS option to consumers. Furthermore, the case of two competing suppliers is also considered. We show that on the one hand, the reference effect positively affects price strategies at a low reference freshness, and negatively affects goodwill and freshness-keeping effort in both the DCRS and BOPS modes. The BOPS mode helps to mitigate the negative effects and improve them. On the other hand, the differences found between the two modes indicate that BOPS mode is not always better than DCRS mode. Prices are higher in BOPS mode than in DCRS mode at a high reference freshness, otherwise the prices in DCRS mode are higher at a low reference freshness and with large BOPS channel size. Although BOPS mode helps to alleviate the anchoring effect, it creates higher requirements in terms of the firm's freshness-keeping efforts. If consumer perceptions of freshness as high/low are only dependent on a high/low goodwill, then the firm's profit in DCRS mode is more likely to be higher than in BOPS mode.

The impact of information sharing and bullwhip effects on improving consumer services in dual-channel retailing

Data sharing among the supply chain players can be an exceptionally significant factor for the retailing industry. In this consideration, an improved retailing methodology for a dual-channel supply chain with a single retailer and manufacturer is built under the bullwhip effect and asymmetric data sharing. Retailer provides asymmetric information to the manufacturer regarding demand to increase their profit. In this scenario, measuring the bullwhip effect is essential in retailing strategy. By adopting an online-to-offline retailing strategy, industries can earn more profit and increase the satisfaction level of customers. The present study focuses on dual-channel retailing, where the demand for the product in both channels varies with the selling price. Keeping in mind the goal of sustainable development, an advanced transportation strategy is utilized in this study, along with some carbon emission costs. Autonomated inspection is utilized to identify defective products. Finally, centralized and decentralized profit functions are formulated for this study. Several cases and numerical examples are provided to validate this study. It is clear from the numerical findings that information sharing within the players provides 1.26% more profit compared to a decentralized case. Due to asymmetric information, which leads to the bullwhip effect, the retailing system faces loss. Thus, information sharing is 0.19% beneficial for dual-channel retailing. Sensitivity analysis for key parameters ensures the findings' applicability in the real world.

Optimal pricing and ordering strategies for dual-channel retailing with different shipping policies

<p style='text-indent:20px;'>In this paper, considering dual-channel retailing (online channel and offline channel), we study the pricing and ordering problem under different shipping policies. In this research, we mainly consider three shipping policies: without shipping price (OSP), with shipping price (WSP) and conditional free shipping (CFP). Based on the principle of maximum utility, we firstly obtain the probability of demand for the online and offline channels and further model the pricing and ordering problem under the three shipping policies. Further, avoiding the curse of dimensionality, the deep deterministic policy gradient (DDPG) method is employed to solve the problem to obtain the optimal pricing and ordering policy. Finally, we conduct some numerical experiments to compare the optimal pricing and ordering quantity under the three different shipping policies and reveal some managerial insights. The results show that the conditional free shipping policy is better than the other two policies, and stimulates the increase of demand to gain more profit.</p>

Retailing and servicing strategies for an imperfect production with variable lead time and backorder under online-to-offline environment

<p style='text-indent:20px;'>Online-to-offline (O2O) retailing strategy is one of the trending topics in the business industry. The current study focuses on an advanced retailing strategy for a single item for a retailer and a manufacturer. Reminding the revolution in the internet world, a dual-channel retailing system is developed in this current study. The retailer offers their item through online and offline mode, though the producer prefers only offline mode. Besides, manufacturer provide different services to their clients through the product's life cycle to keep the company's brand image. The product's demand depends on the selling price and its service for both channels (offline and online) to their customers. To upgrade the services, some investments are implied to decrease the lead time. In expansion, to increase the demand and optimize the system benefit, the manufacturer gives their customers different services (unpaid, partially paid, full paid). The supply chain's benefit is optimized beside the ideal esteem of the decision variables. {Application of different service strategies in O2O retailing are near about <inline-formula><tex-math id="M1">\begin{document}$ 71\% $\end{document}</tex-math></inline-formula> beneficial compared to traditional supply chain. Numerical experiment proved that full-paid services are near about <inline-formula><tex-math id="M2">\begin{document}$ 79\% $\end{document}</tex-math></inline-formula> beneficial compare to partially paid service; however, partially paid services are recommended for industrial benefit.} Different numerical examples, exceptional cases, and sensitivity analyses were performed to prove the model's applicability along with graphical representations.</p>

Dynamic pricing and sales effort in dual-channel retailing for seasonal products

<p style='text-indent:20px;'>This paper studies the joint strategies of dynamic pricing and sales effort involving a seller and a third-party e-commerce platform (TPECP). The seller sells seasonal products through both offline and online channels, and the latter is opened on the TPECP. Considering a dual-channel setting, this paper fills a gap in the studies of joint strategies of dynamic pricing and sales effort. This paper formulates dynamic decision models and investigates them under both centralized and decentralized decision-making cases. Furthermore, a revenue-cost sharing contract is proposed to coordinate the two parties' decisions in the decentralized case, and it is validated theoretically and numerically. The key findings are as follows: For a given selling slot, the optimal online price decreases and the optimal sales effort level increases in the centralized case as the inventory level increases and remains below a threshold; however, when the inventory level exceeds the threshold, both the optimal online price and sales effort level remain fixed as the the inventory level increases in both cases. In addition, for a given inventory level below the threshold, the optimal online price decreases and the optimal sales effort level increases over time in both cases; however, when the inventory level exceeds the threshold, over time, the optimal online price increases and the optimal sales effort level decreases in the centralized case, and both the optimal online price and sales effort level increase in the decentralized case. Finally, a numerical experiment and some management implications are provided.</p>

Dual-Channel Retailer’s Multi-Period Inventory and Pricing Policy with the Quantity-Sales Mode

This paper investigates a dual-channel retailer’s inventory and pricing integrated decision-making problem over multiple periods. The quantity-sales mode is adopted in the online channel while the unit-sales mode is used offline. The customer demand of each sales channel is stochastic, and depends on visit costs, customer return costs, sales modes and pricing levels. To achieve the long-term profit maximization, the dual-channel retailer needs to optimize the pricing levels of both channels and the ordering quantity. For this problem, we first formulate a stochastic dynamic programming model, and then prove the joint concavity and the supermodularity of the objective function. With these properties, the optimality of the base-stock policy is proved, and the optimum price policy is characterized. Specifically, if the retailer’s optimum stock is neither too low nor too high, both sales channels need to be operated simultaneously, otherwise, only operating one channel is optimal. The online price is invariant with the retailer’s stock level while the offline price is decreasing in the retailer’s stock level. Finally, numerical results show that the quantity-sales mode, dual-channel sales model, and the multi-period dynamic decisions could benefit the dual-channel retailer. In addition, influences of cost parameters on the total profit are verified numerically.

Service Decisions in a Two-Echelon Retailing System with Customer Returns

Many manufacturers and retailers have already opened online stores to sell their products. Thus, manufacturers are competing as sellers, and retailers are transforming into dual-channel retailers (DCRs). Such an expansion in business scope and the wide spread of lenient return policies trigger tremendous return volume that requires great deal of logistical efforts. The service levels offered within online stores greatly affect channels’ demand. However, they also influence the channel choice of return for online customers, if applicable, when their purchases are unsatisfactory. Therefore, this paper studies the optimal service level for a centralized DCR. In addition, it examines the optimal levels for a decentralized two-echelon system through the implementation of Nash and Stackelberg theoretical frameworks. Important properties of optimal solutions and vital managerial insights have been devised through analytical and sensitivity analysis. It is found that a DCR may have the following tradeoff: decrease service level to increase the reward from the physical store or increase service level to enhance competitiveness of the online store. The optimal decision depends greatly on how sensitive the customers’ return behavior is to service level. In addition, as the exogenous price increases, the change in the retailer’s offered level depends significantly on the different rates of return.

A smart production system with an autonomation technology and dual channel retailing

Smart products can be sold through online or offline with different price range. For this, the production management has to take care about the price in both channel. A smart single-stage production model with an autonomation inspection technology is considered to develop this prevailing study. Different quality products are sold in different channels with different price (i.e., online and offline). Due to different quality and channel, the price is also varies based on quality or channel. Owing to this situation, the total demand depends on the price of a different quality product. The imperfect products are produced in the out-of-control situation, which causes the backordered. The generation of defective items lead to generation of wastes, and wastes generation create a bad impact for the industry both economically and environmentally. The imperfect or defective items are detected through a smart autonomation inspection technology and sent back for remanufacturing in the same production cycle. The decision-making variables are obtained through a classical optimization technique. A lemma has been proved to finalize the global optimum solution of the decision-making variables. Numerical experiments prove that the manufacturing system provides 0.3% better result, when the defective rate follows a Triangular distribution, whereas the production increases the profit up to 35% due to use of online-to-offline retailing system, and reduces waste up to 50.84% due to use of autonomation inspection. Moreover, the impact of critical parameters on the total system profit is presented through the sensitivity analysis and graphical representations.

Optimal Channel Strategy for Dual-Channel Retailers: The Bright Side of Introducing Agency Channels

Driven by the prosperity of the online retail market and the success of the agency selling format, dual-channel retailers have engaged extensively in online retailing. However, whether dual-channel retailers act as intermediaries to introduce agency channels for third-party sellers in their online stores has not yet received sufficient attention. To address this problem, we perform game-theoretic analysis of the optimal channel strategy of a dual-channel retailer under three channel structures: No-agency mode, manufacturer-agency mode, and e-tailer-agency mode. Under each structure, the price competition model is studied, with the manufacturer as the Stackelberg leader and the retailer or authorized e-tailer as the follower. We analyze the optimal prices and profits of different structures and study the influence of agency channels. Our analysis shows that when the commission rate is higher than a certain threshold, the dual-channel retailer will introduce an agency channel for the third-party seller, and when the commission rate is high, the dual-channel retailer prefers to introduce an agency channel for the manufacturer rather than an authorized e-tailer. However, higher offline operating cost reduces the willingness of the dual-channel retailer to introduce an agency channel. Furthermore, the manufacturer will always benefit from the agency channel and, because of the mitigation of double marginalization, the manufacturer is most profitable in the manufacturer-agency mode. Finally, introducing an agency channel for the third-party seller can create a “win-win” outcome for the manufacturer and the dual-channel retailer, while the e-tailer-agency mode can increase the dual-channel retailer’s relative channel power under certain conditions.

Dual-Channel Supply Chain Pricing Decisions under Discounted Advertising Value

Retailers advertise on different sales channels. When consumers buy online, the effectiveness of advertising is discounted because they cannot feel the product. Observing this phenomenon, this paper studies the advertising strategy of a dual-channel retailer. In this paper, we build stylized game models for the retailer’s price and advertising levels on online and offline channels, respectively. Our contribution is to provide prescriptions for how dual-channel retailers make price and advertise decisions and determine which channel is more profitable for retailers. We find that advertising discounts are not always harming the retailer’s profits. The level of advertising discounts causes retailers to increase the selling price when consumers engage in online shopping. Also, we derive that retailers can choose the sales channels based on the level of consumers’ channel preference of consumers. Interestingly, an increase in the level of advertising discounts will contribute to the growth of the retailer’s profit. Finally, by numerical analysis, we demonstrate the robustness of the results.

Decisions and Coordination of Dual-Channel Supply Chain considering Retailers’ Bidirectional Fairness Concerns under Carbon Tax Policy

Climate change has caused huge negative impacts on the ecosystem. Carbon tax policy is an important regulatory means to reduce carbon emissions and mitigate climate change. Based on the carbon tax policy, this study discusses a dual-channel supply chain consisting of one manufacturer, one online retailer, and one offline retailer. Considering retailers’ bidirectional fairness concerns, the optimal carbon emission reduction strategy and the optimal pricing strategy of centralized and decentralized decision-making are discussed under consumers’ channel preference, respectively. On this basis, a coordination contract is proposed to realize the Pareto improvement of the dual-channel supply chain. We find that dual-channel retailers’ profits and prices are negatively correlated with the horizontal fairness concern coefficient and positively correlated with the vertical fairness concern coefficient. The profit of the manufacturer, the carbon emission reduction, and the bargaining power of consumers are all positively correlated with the horizontal fairness concern coefficient and negatively correlated with the vertical fairness concern coefficient. Maintaining an appropriate service level can maximize the profits of enterprises and positively affect the development of enterprises. Through the coordination contract, the supply chain can be promoted to form a win-win mode of complementary advantages.

Sale through dual channel retailing system— A mathematical approach

This paper deals with a dual channel inventory model where capacity of the market of a particular product is uncertain. The demand rates of the traditional consumers and the online consumers are segregated from total capacity of the market. The trust vale and acceptance rate of the product by the online consumers and utility functions comprising of value of the product, trust value of the online purchasing and some costs associated with risk, traffic, opportunities, etc., determine the demand rates of the products in offline and online channel. In this model, one retailer has offline and online options to sale the products. The objective of the retailer is to find out optimal pricing, order lot size and reorder point for maximizing jointly the average expected profit from offline and online channel. A mathematical model is analyzed to find out the optimal values of variables. Finally, a numerical example is illustrated to justify the proposed model.