The Future of Retail Operations

Retailing consists of all the activities associated with the selling of goods to the final consumer. In this article, we review the research on retail operations published in Manufacturing & Service Operations Research (M&SOM) since 1999. We then discuss the current retail landscape and the new research directions it offers, in which M&SOM can play a prominent role

Simulating an optimal continuous review inventory policy online retail

In the online channel of grocery retailers, customers typically define a specific date and time at which they want to receive their orders. This customer order time window provides additional flexibility, which can be used to improve the policy for optimizing inventory. This improvement allows to better adjust the ordering point and the ordering quantity, leading to a decrease in the total cost, which comprises the ordering, holding and stockout costs. This study is based on a previous thesis, where the (s, Q) inventory policy explicitly accounts for the ordering window. The policy considers that the customer demand as well as the customer ordering window are stochastic. In this thesis, we extend and refine the policy by exploring the multiple on order setting, which introduces more complex and extreme scenarios to the inventory system with ordering windows. The validations were performed using simulation for a variety of parameter configurations. The simulator was implemented in Excel, using VBA, and the policy was optimized via numerical optimization using MatLab. The revised policy proved to be appropriate both for single and multiple on order scenarios. There is an avenue of future research to be explored in this online retail setting, particularly in the exploration of inventory policies that account for the ordering window

Operational Strategies for On-demand Personal Shopper Services

Inspired by several recent startups, we study an on-demand delivery service that lets customers shop online for products from a number of brick and mortar stores. The customer orders are fulfilled by a fleet of personal shoppers who are responsible for both the shopping of orders at the stores and the delivery of these to customer locations. The operation of such a service requires to dynamically manage new requests, coordinate a fleet of shoppers, schedule shopping operations at stores, and execute deliveries to customers on time. Our work presents three operational strategies, each requiring different levels of shopper flexibility and implementation complexity. We quantify the performance of each strategy in a vast family of computational experiments. Also, the performance of this on-demand shopping service is compared to a setting in which customers travel to stores to shop themselves. Our numerical experiments show that there are significant savings in resources spent in shopping (up to 55.2%) when this activity is outsourced

Lp-Based Artificial Dependency for Probabilistic Etail Order Fulfillment

We consider an online multi-item retailer with multiple fulfillment facilities and finite inventory, with the objective of minimizing the expected shipping cost of fulfilling customer orders over a finite horizon. We approximate the stochastic dynamic programming formulation of the problem with an equivalent deterministic linear program, which we use to develop a probabilistic fulfillment heuristic that is provably optimal in the asymptotic sense. This first heuristic, however, relies on solving an LP that is exponential in the size of the input. Therefore, we subsequently provide another heuristic which solves an LP that is polynomial in the size of the input, and prove an upper bound on its asymptotic competitive ratio. This heuristic works by modifying the LP solution with artificial dependencies, with the resulting fractional variables used to probabilistically fulfill orders. A hardness result shows that asymptotically optimal policies that are computationally efficient cannot exist. Finally, we conduct numerical experiments that show that our heuristic's performance is very close to optimal for a range of parameters.http://deepblue.lib.umich.edu/bitstream/2027.42/108712/1/1250_ASinha.pd

On the Benefits of Flexible Customer-to-Depot Assignments in Attended Home Delivery

This paper investigates the value of flexibility in customer-to-depot assignments in last-mile distribution operations. In current practice, many companies use fixed delivery regions for their fulfillment warehouses. This allows a decomposition of delivery operations by ware- house, thereby simplifying the planning process. However, this approach foregoes some optimization potential, relative to a holistic planning of the delivery operations across the network. In this paper, we assess the value of this flexibility. We first identify and characterize two specific types of benefits, namely a routing benefit and a pooling benefit. We then proceed to quantify these benefits in an extensive numerical study. Our results disentangle how the benefits depend on key environmental parameters. They also show that a flexible customer-to-depot assignment can add significant value in various relevant conditions

Shipping Consolidation with Delivery Deadline and Expedited Shipment Options

Problem definition: Shipment consolidation is commonly used to take advantage of the economies of scale by avoiding some of the shipping costs. However, when pending current orders are consolidated with future orders it may require more expensive expedited shipment in order to meet shorter deadlines. In this paper, we study the optimal consolidation policy focusing on the trade-off between economies of scale and expedited shipping costs. Academic/Practical Relevance: Our work is motivated by the prevalence of consolidation in the supply chain industry and also by its potential application for online and omni-channel retailing, especially with the rise of, so-called, on-demand logistic services. In such situations, sellers, have the flexibility to take advantage of consolidation, by deciding from which warehouse to fulfill the orders and also when to ship the orders, as long as the orders deadlines are met. Methodology: We use Dynamic Programming to study the optimal policy and its structure. We also conduct intensive simulation tests to show the good performance of heuristics which we proposed based on structures of the optimal policy. Results: The optimal policies and their structures are characterized in settings with up to two warehouses, where the impact of expedited shipment on both shipping policy and order fulfillment policy are explored. Utilizing the insights of these structural properties, two easily implementable heuristics are proposed, which perform within 1-2% of the optimal in intensive numerical tests. Managerial Implications: Despite the complexity of the actual optimal consolidation policy, sellers can apply the two simple heuristic policies we proposed to get near-optimal performance in various cases.https://deepblue.lib.umich.edu/bitstream/2027.42/138942/1/1375_Jasin.pd

Dynamic Joint Pricing and Order Fulfillment for E-Commerce Retailers

We consider an e-commerce retailer (e-tailer) who sells a catalog of products to customers from different regions during a finite selling season and fulfills orders through multiple fulfillment centers. The e-tailer faces a Joint Pricing and Fulfillment (JPF) problem: At the beginning of each period, she needs to jointly decide the price for each product and how to fulfill an incoming order. The objective is to maximize the total expected profits defined as total expected revenues minus total expected shipping costs (all other costs are fixed in this problem). The exact optimal policy for JPF is difficult to solve; so, we propose two heuristics that have provably good performance compared to reasonable benchmarks. Our first heuristic directly uses the solution of a deterministic approximation of JPF as its control parameters whereas our second heuristic improves the first heuristic by adaptively adjusting the original control parameters at the beginning of every period. An important feature of the second heuristic is that it decouples the pricing and fulfillment decisions, making it easy to implement. We show theoretically and numerically that the second heuristic significantly outperforms the first heuristic and is very close to a benchmark that jointly re-optimizes the full deterministic problem at every period.http://deepblue.lib.umich.edu/bitstream/2027.42/117573/1/1310_Jasin.pd

Omni-Channel Supply Chain Management: Assessing the Impact of Retail Service Operations in the Retail Supply Chain

The traditional retail environment, which is characterized by a clear division between brick-and-mortar and non-brick-and-mortar retail channels, has been recently disrupted by developments in e-commerce and mobile technologies. The result has been the emergence of omni-channel retailing. Within the reality of this new retail environment, it has been proposed that retailers should develop the necessary capabilities to fulfill consumer demand from anywhere – the store, the distribution center, or via drop-shipping from a supplier – which leads to the emergence of new operational complexities and challenges in the retail supply chain. In light of the growing popularity of these new fulfillment capabilities, it is important to not only consider the financial returns they provide to retailers, but also the potential impacts on the upstream supply chain. Moreover, omni-channel operations will allow retailers to offer new fulfillment services to consumers, such as cross-channel returns or in-store pick-ups, ultimately resulting in new supply chain service outputs in the consumer market. Thus, the aim of this dissertation is to investigate and obtain a holistic understanding of the importance and impacts of omni-channel fulfillment operations for successful retail supply chain management. This will be done by considering three different echelons in the supply chain, (retailer, supplier, and consumer), and investigating how emerging strategies in omni-channel fulfillment impact all three. Using the theoretical underpinning of ambidexterity, Essay 1 investigates how retailers manage their investments and developments pertaining to existing and new fulfillment operations, and how that may lead to improvements in a retailer’s operational and financial performance. To address this research question a structured content analysis in combination with secondary financial data was conducted. To explore how retail omni-channel fulfillment operations impact upstream supply chain members a qualitative research approach was executed in Essay 2 using the case study methodology. Essay 3 employs a series of experimental studies to explore how retail omni-channel fulfillment operations can be used to recover from a stockout. Using equity theory, this essay investigates how, in the case of a stockout, different attributes of omni-channel service operations may impact consumer satisfaction and their evaluation of a retailer’s physical distribution service quality (PDSQ)