An Inventory Decision Model of BOPS Retailing Considering Cross-selling

Omnichannel retailing has been getting more and more attention as people’s buying habits become more diverse. BOPS (Buy-on-line, Pick-up-in store) is an important pattern of Omnichannel retailing which has significant impacts on a cross-selling effect and inventory decisions. This paper explores this implementation with cross-selling from a perspective of inventory management by developing and analyzing a mathematical model based on EOQ model. After series of numerical experiments, we found that firms in a perfectly competitive market have motivations to launch BOPS services in most cases, especially when the supply chain structure is centralized. Furthermore, in a decentralized supply chain, if the manufacturer bears the inventory costs generated in B&M stores according to the proportion of BOPS sales when the inventory capacity is not big enough, the retailer can shift a part of costs to the manufacturer by deliberately making biased inventory decisions, and this cost shifting may damage the manufacturer’s motivation to implement BOPS where the cross-selling effect is powerful enough

Omni-Channel Intensity and Shopping Value as Key Drivers of Customer Satisfaction and Loyalty

Omni-channel retailing consists of the complete alignment of the different channels and touchpoints that generate a seamless experience for consumers, allowing them to move freely through all channels. The consumer's perception of a seamless and consistent omni-channel experience is called intensity. This study reveals that this intensity in the shopping experience can offer value to consumers, and that intensity and shopping value also influence satisfaction and loyalty. We propose a relationship model that had been tested in a quantitative study with PLS, with a representative sample of buyers who had used the Click and Collect system. The main contribution of this study is to the literature on the analysis of omni-channels from the consumer experience perspective, through an in-depth analysis of the concepts of intensity and shopping value, as well as their relationship with satisfaction and loyalty. The results revealed the existence of a positive relationship between intensity and shopping value, and between these two variables and satisfaction and loyalty. Keywords: omni-channel; intensity; shopping value; satisfaction; loyalt

Omnichannel Management in a B2B context: concept, research agenda and bibliometric review

The COVID-19 pandemic has driven increases in the provision of services through digitalchannels, even by more traditional companies. An Omnichannel model of service provisionposes new management challenges for companies. This research reviews the literature onOmnichannel Management by companies whose clients are other companies (B2B) andclassifies the different areas of research to date. The principal finding is that, despite considerable academic interest in Omnichannel management, there have been few studies of Omnichannel in the B2B field. This emphasizes a significant research gap to address. We have also outlined the Research Agenda to highlight future lines of research

Challenges at the marketing–operations interface in omni-channel retail environments

To compete in today’s omni-channel business context, it is essential for firms to co-ordinate their activities across channels and across different stages of the customer journey and the product flow. This requires firms to adopt an integrative approach, addressing each omni-channel design decision from a dual demand-side (marketing) and supply-side (operations) perspective. However, both in practice and in academic research, such an integrative approach is still in an immature stage. In this article, a framework is developed with the following key decision areas: (i) assortment & inventory, (ii) distribution & delivery and (iii) returns. These affect both the customer journey and the product flow. As a consequence of the resulting interdependencies between the firm’s functions, addressing the issues that arise in the three decision areas requires an integrated marketing and operations perspective. For each of the areas, the key decisions that affect or involve both the customer journey and product flow are identified first. Next, for each decision, the marketing and operational goals and the tensions that arise when these goals are not perfectly aligned are described. The opportunities for relieving these tensions are also discussed and possible directions for future research aimed at addressing these tensions and opportunities are presented.info:eu-repo/semantics/publishedVersio

Using neural networks to examine trending keywords in Inventory Control

Inventory control is one of the key areas of research in logistics. Using the SCOPUS database, we have processed 9,829 articles on inventory control using triangulation of statistical methods and machine learning. We have proven the usefulness of the proposed statistical method and Graph Attention Network (GAT) architecture for determining trend-setting keywords in inventory control research. We have demonstrated the changes in the research conducted between 1950 and 2021 by presenting the evolution of keywords in articles. A novelty of our research is the applied approach to bibliometric analysis using unsupervised deep learning. It allows to identify the keywords that determined the high citation rate of the article. The theoretical framework for the intellectual structure of research proposed in the studies on inventory control is general and can be applied to any area of knowledge

On-demand last-mile distribution network design with omnichannel inventory

E-commerce delivery deadlines are getting increasingly tight, driven by a growing ‘I-want-it-now’ instant gratification mindset of consumers and the desire of online and omnichannel retailers to capitalize on the growth of on-demand e-commerce. On-demand deliveries with delivery deadlines as tight as one or two hours force companies to rethink their last-mile distribution network, since tight delivery deadlines require decentralization of order picking and inventory holding to ensure close proximity to consumers. This fundamentally changes the strategic design process of last-mile distribution networks. We study the impact of incorporating inventory order-up-to level decisions into the strategic design process of last-mile distribution networks with tight delivery deadlines. We develop an approximate inventory model by including an estimate of the cost of late delivery and additional transportation due to local stock-outs in a newsvendor formulation. Such local stock-outs require an order to be delivered from a more distant facility, which may lead to late delivery and additional transportation cost. We integrate our approximate inventory model and a location-allocation mixed-integer program that determines optimal facility locations, associated order-up-to inventory levels, and fleet composition, into a metamodel simulation-based optimization approach. Our numerical analyses demonstrate that pooling the additional online inventory with brick-and-mortar (B&M) inventories leads to cannibalization by the B&M network and higher B&M service levels. However, the pooling benefits to the online network outweigh the cost of inventory cannibalization. Furthermore, we show under which circumstances omnichannel retailers may have an incentive to consolidate online inventory in specific B&M facilities

Challenges at the marketing–operations interface in omni-channel retail environments

To compete in today’s omni-channel business context, it is essential for firms to co-ordinate their activities across channels and across different stages of the customer journey and the product flow. This requires firms to adopt an integrative approach, addressing each omni-channel design decision from a dual demand-side (marketing) and supply-side (operations) perspective. However, both in practice and in academic research, such an integrative approach is still in an immature stage. In this article, a framework is developed with the following key decision areas: (i) assortment and inventory, (ii) distribution and delivery and (iii) returns. These affect both the customer journey and the product flow. As a consequence of the resulting interdependencies between the firm’s functions, addressing the issues that arise in the three decision areas requires an integrated marketing and operations perspective. For each of the areas, the key decisions that affect or involve both the customer journey and product flow are identified first. Next, for each decision, the marketing and operational goals and the tensions that arise when these goals are not perfectly aligned are described. The opportunities for relieving these tensions are also discussed and possible directions for future research aimed at addressing these tensions and opportunities are presented

Wield the Power of Omni-channel Retailing Strategy: a Capability and Supply Chain Resilience Perspective

Omni-channel strategy can be a powerful mechanism through which successful implementing organisations achieve higher levels of resilience to better survive disruptions. However, such potential benefits have been overlooked in existing literature with limited discussions on how omni-channel strategy can be exploited for uncertain business environments. We conduct an in-depth case study on a leading UK-based fashion retailer, Next, to explore the role of omni-channel strategy in helping organisations respond to the challenging retail landscape. Our results reveal that Next’s ability to achieve vitality even during the COVID-19 pandemic is largely attributed to its well-executed omni-channel strategy which enhances its supply chain resilience (SCRES) by maintaining a dynamic fit between the internal information processing capacity and the changing information processing needs induced by external conditions. Our study contributes to the omni-channel and SCRES literature and provides practical insights on how omni-channel strategy can be wielded for both stable and turbulent environments

Managing physical inventory and return policies for omnichannel retailing

As the retail industry increasingly adopts an omnichannel strategy amidst the growth of e-commerce, this study explores the interplay between inventory and return policies in such a setting. Specifically, we focus on “return losses,” defined as the losses incurred by retailers due to customer product returns. We target how these return losses impact retailers’ profits and physical inventories. While previous research has mainly concentrated on cross-channel returns, little attention has been paid to how omnichannel return policies affect store inventory and profit. We posit that profit-maximizing retailers allow consumers to select their purchase channels based on utility but require returns to follow specific policies. In this paper, we model four return policies based on the channel of return: original purchasing channel return, offline return, online return, and cross-channel return. We use a newsvendor model to construct an optimal profit function that accounts for the additional profit from offline return, uncertainty demand, and inventory cost. Our analysis identifies the conditions under which certain return policies are beneficial or detrimental to omnichannel retailers. We discover that the retailer's product pricing, return losses, and consumer return hassle costs are the main factors influencing the best return policy and inventory policy decisions. Moreover, whether to increase or decrease store inventory and the relationship between physical inventory and return loss depend on the return policy, price, and return hassle cost. Numerical simulations support our findings, which offer practical guidance for omnichannel retailers aiming to optimize their inventory and return policies