To or Not to Cooperate with Third-Party E-commerce Platform: The Influence of Commission Fee and Service Level

The third-party e-commerce platform is now widely adopted by small and medium sized retailers. For the retailer, commission fee and service level provided by the platform are two key factors influencing the pricing strategy and sales profit. However, these two factors are rarely considered in previous operations models. Taking both factors into consideration, we formulate the decision-making problem of third-party e-commerce as a Stackelberg game where the platform is the leader and the retailer is the follower. Given the platform’ s commission fee, we derive optimal sales price for the retailer and optimal service level for the platform. Our result shows that the platform’s service level must be high enough to guarantee a positive profit and the effect of commission fee is dependent. Precisely, when the commission fee is small (or large) enough, the retailer and the platform can reach a consensus to increase (or to decrease) it. When it is moderate, they will bargain with each other, i.e., the retailer wants to decrease commission fee but the platform wants to increase it. Based on these observations, retailers are able to choose sales channel with more profit by comparing online store and offline shop

E-fulfilment and distribution in omni-channel retailing: a systematic literature review

Purpose – Given the progressive growth of e-commerce sales and the rising interest in omni-channel (OC) retailing amongst academics and practitioners, the purpose of this paper is to provide an up-to-date literature review on the logistics involved when moving towards OC retailing. Specifically, we have examined the main issues relating to e-fulfilment and distribution, highlighting how the topic has been developed over time, and identifying the most promising research streams for the near future. Design/methodology/approach – A systematic literature review methodology is adopted. The review is based on 58 papers published from 2002 to 2017 in 34 international journals. The papers were analysed and categorised according to their defining characteristics, methodologies adopted and themes addressed. Findings – This paper provides an overview of the main issues relating to e-fulfilment and distribution experienced by companies shifting towards OC, mapped along three dimensions: distribution network design, inventory and capacity management, delivery planning and execution. Despite the growing interest in OC retailing, many key topics are still under-represented, including the evolution of retail distribution networks, assortment planning over multiple channels, the logistics role played by stores in the delivery process and the interplay between different logistics aspects. Originality/value – The paper offers insights into the main logistics issues in MC and OC retailing, as well as highlights potential fields for further investigation. From a managerial perspective, this paper is useful for retailers adopting an OC approach to guide their future efforts concerning their business logistics model

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

Best Performance Frontiers for Buy-Online-Pickup-in-Store order fulfilment

With the proliferation of omni-channel retailing, Buy-Online-Pickup-in-Store (BOPS) retail services have gained increasing popularity as they have benefits for both customers and retailers. However, using conventional retail stores to fulfil orders received online whilst also serving walk-in customers is challenging for retailers, particularly when a high customer service level is promised to online customers (e.g., order by a certain time and pick up in store after a specific time later the same day). This paper examines store picking operations for same day BOPS services. Specifically, we derive Best Performance Frontiers (BPFs) for single wave and multi-wave order picking. New relationships, propositions, and results are presented to determine the minimum picking rate needed in stores to guarantee a target service level, the number of picking waves a retailer should launch in an ordering cycle, and the timing of picking waves. We also examine demand surge scenarios with different order arrival rates in an ordering cycle. Insights and implications of the results are discussed for retailers that seek to benchmark their current BOPS performances and understand how to schedule and improve the picking of online orders in conventional retail stores and the picking rates needed to guarantee a desired service level for online customers

An optimisation approach for the e-grocery order picking and delivery problem

[EN] Traditional supermarket chains that are adopting an omni-channel approach must now carry out the order picking and delivery processes to serve online orders, previously done by the customer. The complexity of the logistics processes has increased, therefore modelling and optimising e-grocery operations becomes definitely important. Since there are few studies modelling order picking and delivery processes, we propose an approach that simultaneously optimises the decision variables of different functions which have traditionally been treated separately. In this study, we present a linear programming model for store-based e-fulfilment strategies with multiple picking locations. The proposed model optimises the allocation of online orders to stores, based on the e-fulfilment costs. As well as minimising the picking and delivery costs, the proposed approach consolidates workloads in order to avoid idle times and reduce the amount of resources required. A weighted sum method is applied to compute the solution, integrating parameters that represent different store features such as the product range, sales mode and physical store activities. The proposed model has been tested on one of the largest grocery sellers, showing that substantial savings can be achieved by reallocating orders to different stores, time windows and delivery vehicles. By focusing on optimising e-fulfilment resources, this approach serves as a guide for traditional grocery sellers to redesign their supply chains and to facilitate decision-making at a managerial level.Funding was provided by Universidade de Vigo.Vazquez-Noguerol, M.; Comesaña-Benavides, J.; Poler, R.; Prado-Prado, JC. (2022). An optimisation approach for the e-grocery order picking and delivery problem. Central European Journal of Operations Research. 30(3):961-990. https://doi.org/10.1007/s10100-020-00710-9S96199030

Deep learning with long short-term memory networks and random forests for demand forecasting in multi-channel retail

This paper proposes a novel forecasting method that combines the deep learning method - long short-term memory (LSTM) networks and random forest (RF). The proposed method can model complex relationships of both temporal and regression type which gives it an edge in accuracy over other forecasting methods. We evaluated the new method on a real-world multivariate dataset from a multi-channel retailer. We benchmark the forecasting performance of the new proposition against neural networks, multiple regression, ARIMAX, LSTM networks, and RF. We employed forecasting performance metrics to measure bias, accuracy, and variance, and the empirical evidence suggests that the new proposition is (statistically) significantly better. Furthermore, our method ranks the explanatory variables in terms of their relative importance. The empirical evaluations are replicated for longer forecasting horizons, and online and offline channels and the same conclusions hold; thus, advocating for the robustness of our forecasting proposition as well as the suitability in multi-channel retail demand forecasting

Should offline retailers expand online under consumer showrooming based on the effects of intershowrooming and intrashowrooming?

This study aims to find a way to alleviate or eliminate the negative impact of showrooming on brick-and-mortar retailers. Therefore, under careful consideration of the effects of intershowrooming and intrashowrooming, this study explores whether retailers can effectively solve the negative impact of showrooming by opening online channels. Conduct a comparative study on the decision-making of dual/multi-channel supply chain members before and after the retailer opens an online channel and analyze the influence. In addition, we also explored the impact of factors such as the market scale expansion effect and internet market power structure. Research has found that regardless of the market scale expansion effect generated, it is effective for the retailer to increase profits by opening an online channel. The impact of market scale expansion is not entirely beneficial to the retailer. Under the intrashowrooming, the effect of market scale expansion may benefit the manufacturer. But what is more noteworthy is that for the manufacturer, the impact of intrashowrooming is not necessarily the greater, the better, and the manufacturer's profit may decrease as this effect increases

Digitalization in B2B Marketing. Omnichannel Management from a PLS-SEM approach.

Purpose: The purpose of this paper is to establish a reference model that will allow us to understand the factors that influence the omnichannel management of an organization in a business-to-business (B2B) context. Design/methodology/approach: In building the model, a partial least squares structural equation modeling approach was followed. More than 1,000 executives with a C-level profile (chief executive officer, chief marketing officer or chief digital officer), from manufacturers and wholesalers, in various industries worldwide were contacted. The final sample consisted of 124 C-level executives in multinational B2B companies from 35 countries worldwide. Findings: The principal finding is that optimal omnichannel management must involve a customer-centric proposition forming the basis for individualized marketing that tailors the company's portfolio of solutions to suit each client. To ensure this, customer knowledge at each touchpoint is essential. The results show that the main predictor of B2B omnichannel management is sales and marketing, even above channels. The principal conclusions are that the model shows that good omnichannel performance is measured by the performance of the industrial buyer. Loyalty and experience are primary measures of this customer's performance. Originality/value: Research into omnichannel management in the B2B field is scarce, especially concerning the creation of models for decision-making

Model and management indicators in industrial omnichannel (B2B)

The COVID-19 pandemic has driven increases in the provision of services through digital channels, even by more traditional companies. An Omnichannel model of service provision poses new management challenges for companies. This research reviews the literature on Omnichannel Management by companies whose clients are other companies (B2B) and classifies 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