Zhang, Lina
(2020)
Models for omni-channel retailing.
PhD thesis, University of Nottingham.
Abstract
Though many retailers have embarked on the omni-channel journey, most of them are grappling with the difficulties of order fulfilment and delivery in an omni-channel environment. As customers have become more demanding regarding delivery flexibility and more intolerant of long delivery waiting times, it is imperative for retailers to revise their supply chains and operational systems to embrace omni-channel and guarantee high customer service levels. The main objective in this thesis is to explore key supply chain management (SCM) decisions faced by retailers in transition to omni-channel and to use quantitative methods to examine some of these decisions. Based on extensive review from both academic studies and the business literature, we present a conceptual map pinpointing critical supply chain and operations decisions. The conceptual map encapsulates the main contextual factors including retailer characteristics, demand characteristics, order characteristics and supplier characteristics.
In light of the conceptual map, we examine three research questions. The first research question investigates the operational decisions for fulfilling same day ‘Buy-Online-Pickup-in-Store’ (BOPS) orders from retail stores. Given the order cut-off time and the deadline (i.e., the earliest collection time promised to customers), analytical models are developed to find the Best Performance Frontiers (BPFs), along which the best combination of the time to commence picking and the minimum picking rate needed can be found for each stipulated service level. Two scenarios have been examined, i.e., when the retailer picks a single wave per cycle and when the retailer organises multiple picking waves per cycle. We also conduct sensitivity analyses to explore the impact of the timing and the magnitudes of demand rate flunctuations on the picking rate required. Our model results and analyses can assist retailers with the decisions on scheduling order picking and setting the picking rate in stores for BOPS fulfilment to achieve a specific service level.
The second research question studies the decisions on the ordering window for BOPS services and the corresponding fulfilment operations. Given a deadline, a longer ordering window leads to a shorter window for order processing and transportation, which requires higher processing rate and/or more late deliveries. However, a longer ordering window can be convenient to customers and retailers can capture last minute shoppers. The strategic decision on the optimal ordering window for BOPS services is clearly a problem at the marketing-operations interface. We develop cost minimisation models to jointly optimise BOPS service offerings (i.e., the order receipt window length) and BOPS fulfilment operations (i.e., the time to start picking and the picking rate needed). We consider different retail scenarios when BOPS orders are fulfilled from local stores with zero transportation window and when BOPS orders are fulfilled from more central facilities (e.g., warehouses) before being shipped to the collection stores. We apply our model results to analyse and explain the current service offerings of five major UK-based retailers. Accordingly, we provide insights into the key trade-offs for the centralisation level of BOPS fulfilment operations and present two frameworks to delineate the impact of product characteristics and retailer characteristics on BOPS collection speed to be offered, i.e., same- or next-day or over two days.
The third research question examines the strategic decision on from where to fulfil online orders. We first provide a typology of commonly used fulfilment network configurations, as retailers from different product sectors use different combinations of online fulfilment options. We then focus our study on the online groceries fulfilment network and present analytical models to determine how to best fulfil online orders. In our research setting, online demand is further divided into BOPS demand and home delivery (HD) demand. The total cost in the proposed analytical model is expressed as a function of the centralisation level of online picking, which allows the derivation of clear insights into the number of online fulfilment facilities needed. Numerical experiments have been conducted to investigate the impact of different problem parameters, such as the demand density and the maximum travel distance allowable for BOPS collection, on the configuration of the optimal online fulfilment network. The analytical expression of the total cost provide further insights. For example, the size of the retailer’ service region plays no role in determining the centralisation level of online fulfilment, as it only affects the magnitude of cost savings from such decisions.
| Item Type: |
Thesis (University of Nottingham only)
(PhD)
|
| Supervisors: |
MacCarthy, Bart
Muyldermans, Luc |
| Keywords: |
Omni-channel retailing; Buy-Online-Pickup-in-Store (BOPS); Home delivery (HD); ordering receipt window; the picking rate; online order fulfilment |
| Subjects: |
H Social sciences > HF Commerce |
| Faculties/Schools: |
UK Campuses > Faculty of Social Sciences, Law and Education > Nottingham University Business School |
| Item ID: |
61414 |
| Depositing User: |
Zhang, Lina
|
| Date Deposited: |
11 Dec 2020 04:40 |
| Last Modified: |
11 Dec 2022 04:30 |
| URI: |
https://eprints.nottingham.ac.uk/id/eprint/61414 |
Actions (Archive Staff Only)
 |
Edit View |
Tools
Tools
![[img]](/style/images/fileicons/application_pdf.png)