Consumer decision-making in omnichannel retailing: Literature review and future research agenda

Omni-channel management in the new retailing era: A systematic review and future research agenda

This paper provides a literature review of freight transportation service procurement and investigates the challenges and opportunities regarding transportation organization and procurement mechanism design in the context of E-commerce. A total of 78 articles published in academic journals between 1998 and 2017 were reviewed. A framework comprising seven classification criteria is proposed to analyze the articles. The results reveal that new business environments challenge the efficiency and effectiveness of the current leading procurement mechanisms. This work also identifies the trends and gaps from the viewpoints of practitioners and researchers and describes future prospects in new freight transportation markets and organizations.

/pdf/freight-transportation-service-procurement-a-literature-11ekbq124k.pdf

Freight transportation service procurement: A literature review and future research opportunities in omnichannel E-commerce

Many retailers have recently implemented buy online and pick up in store (BOPS) by integrating their online and offline channels. In this paper, considering a retailer who sells products through both online and offline channels, we develop a theoretical model to study the effects of BOPS adoption. Using our model, we first analyze how adoption of BOPS affects a retailer’s optimal prices, total demand and profit under consistent and inconsistent pricing strategies where a retailer employs the same pricing strategy both before and after BOPS implementation. We then conduct a comparative analysis of the two pricing strategies, discussing which one is most profitable to the retailer. Subsequently, we analyze the scenario where a retailer uses consistent pricing before BOPS adoption and inconsistent pricing afterwards and the scenario where a retailer uses inconsistent pricing before BOPS adoption and consistent pricing afterwards. We conduct numerical studies to obtain insights on when BOPS is most advantageous and which pricing strategy is better to use. Our study results show that BOPS is not always beneficial to the retailer, depending on the unit operating cost and customer hassle cost in the BOPS channel and the cross-selling profit. We also identify under what conditions a retailer is better off under different scenarios. Moreover, we find that BOPS is more beneficial to the retailer under inconsistent pricing especially when the unit operating cost in the BOPS channel is lower.

The effects of BOPS implementation under different pricing strategies in omnichannel retailing

Optimal pricing decisions for an omni-channel supply chain with retail service

Shared Capacity Routing Problem − An omni-channel retail study

The presence of different distribution channels in omni-channel retail makes the fulfillment process challenging. When consumers can buy online and pick up their purchased goods at a store, the stores are often visited by a vehicle that supplies the pick-up points (PUPs) and by a vehicle that replenishes the store’s inventory. We study the benefit of exploiting any spare capacity in the vehicles replenishing store inventories to reduce online order fulfillment cost by transferring online orders to these vehicles at one or more of the stores visited. This involves choosing transfer locations and the set of stores whose online orders are transferred at these locations so as to minimize the online order fulfillment cost. We present a mixed integer linear programming model as well as an effective and efficient heuristic for solving this problem. An extensive computational study shows that significant benefits can be achieved by sharing capacity across the two channels.

Optimizing Omni-Channel Fulfillment with Store Transfers

More and more retailers allow customers to order goods online and then pick them up in a store. In this setting, these orders are typically served from a dedicated warehouse. This often means that the stores are visited by different vehicles to replenish the store inventory and to supply the pick-up points. Motivated by a collaboration with an omni-channel grocery retailer in the Netherlands, we study how to best share capacity between the routes associated with these different sales channels. As operational constraints prevent jointly planning the routes, we consider the replenishment routes as fi xed when planning the routes to serve the pick-up orders. An order can be transferred to the replenishment route, if capacity allows. We consider the problem of deciding which customer orders to transfer and which to deliver directly such that the total costs are minimized. We present an exact and heuristic approach to solve this problem. Computational experiments on both real-world and arti ficial instances show that substantial savings can be achieved by sharing vehicle capacity across different channels.

Shared Capacity Routing Problem - An Omni-channel Retail Study

More and more retailers allow customers to order goods online and then pick them up in a store. In this setting, these orders are typically served from a dedicated warehouse. This often means that the stores are visited by different vehicles to replenish the store inventory and to supply the pick-up points. Motivated by a collaboration with an omni- channel grocery retailer in the Netherlands, we study how to best share capacity between the routes associated with these different sales channels. As operational constraints prevent jointly planning the routes, we consider the replenishment routes as fixed when planning the routes to serve the pick-up orders. An order can be transferred to the replenishment route, if capacity allows. We consider the problem of deciding which customer orders to transfer and which to deliver directly such that the total costs are minimized. We present an exact and heuristic approach to solve this problem. Computational experiments on both real-world and artificial instances show that substantial savings can be achieved by sharing vehicle capacity across different channels.

/pdf/shared-capacity-routing-problem-an-omni-channel-retail-study-2ldjd939vp.pdf

Joydeep Paul

Papers

Shared Capacity Routing Problem − An omni-channel retail study

Optimizing Omni-Channel Fulfillment with Store Transfers

Shared Capacity Routing Problem - An Omni-channel Retail Study

Shared Capacity Routing Problem – An Omni-channel Retail Study