Optimisation of cross-channel order fulfilment for click-and-collect practice in omnichannel retailing

Retailing business thrives on the implementation of click-and-collect service as one of the main options for the online orders. The primary concern in this service of omnichannel practice is the costly picking operations while at the same time it plays the major role in customer satisfaction. The...

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Bibliographic Details
Main Author: Fitri, Ulfa
Format: Dissertation (University of Nottingham only)
Language:English
Published: 2018
Subjects:
Online Access:https://eprints.nottingham.ac.uk/54692/
Description
Summary:Retailing business thrives on the implementation of click-and-collect service as one of the main options for the online orders. The primary concern in this service of omnichannel practice is the costly picking operations while at the same time it plays the major role in customer satisfaction. Therefore, the need to pursue an efficient picking configuration arises. To cope up with this issue, retailers convey the advantages of using the cross-channel fulfilment to serve the online demand. This study is oriented towards the formulation of a mathematical model to obtain the cost-optimal settings and configuration of picking operations for click-and-collect in omnichannel retailing. The Voronoi diagram approach is employed in the problem formulation to cluster the customer demand into hexagon region in a hierarchical facilities level. A suggestion regarding the degree of centralisation for picking activity has been made by incorporating three primary costs: picking cost, inbound transportation cost and the fixed cost for setting up picking and collection points. The result reveals the optimal order picking rate and order accumulation time in each level of centralisation for the picking facility with a predefined maximum tolerable distance for customers to collect the orders. Moreover, this output can be used to identify the attractive offers for customers which complement the needs of internal fulfilment operations. The result is further supported by the sensitivity analysis showing the pattern of behaviour changes on the optimal solution given various values of the model parameters. It is inferred that centralised picking configuration befits the operations when the maximum tolerable collection distance is low, the fixed cost is high, optimal picking rate is low and orders accumulation time is high. The study also highlights the comparison of fully decentralised, centralised and hybrid configuration which can be an insight for decision-making processes at the managerial level.