Modeling of individual customer delivery satisfaction: an AutoML and multi-agent system approach
Industrial Management & Data Systems
ISSN: 0263-5577
Article publication date: 29 November 2018
Issue publication date: 1 May 2019
Abstract
Purpose
The purpose of this paper is to propose an automated machine learning (AutoML) and multi-agent system approach to improve overall product delivery satisfaction under limited resources.
Design/methodology/approach
An AutoML method is purposed to model delivery satisfaction of individual customer, and a heuristic method and multi-agent system are proposed to improve overall satisfaction under limited processing capability. A series of simulation experiments have been conducted to illustrate the effectiveness of the proposed methodology.
Findings
The simulated results show that the proposed method can effectively improve overall delivery satisfaction, especially when the demand of customer orders is highly fluctuating and when the customer satisfaction models are highly diversified.
Practical implications
The proposed framework provides a more dynamic and continuously improving way to model delivery satisfaction of individual customer, thereby supports companies to provide personalized services and develop scalable and flexible business at a lower cost, and ultimately improves the overall quality, efficiency and effectiveness of delivery services.
Originality/value
The proposed methodology utilizes AutoML and multi-agent system to model individual customer delivery satisfaction and improve the overall satisfaction. It can cooperate with the existing delivery resource planning methods to further improve customer delivery satisfaction. The authors propose an AutoML approach to model individual customer delivery satisfaction, which enables continuous update and improvements. The authors propose multi-agent system and a heuristic method to improve overall delivery satisfaction. The numerical results show that the proposed method can improve overall delivery satisfaction with limited processing capability.
Keywords
Acknowledgements
This work was supported by the National Natural Science Foundation of China under Grant No. 51405089; the Science and Technology Planning Project of Guangdong Province under Grant Nos 2015B010131008 and 2015B090921007; China Postdoctoral Science Foundation under Grant Nos 2018M630928 and 2018M633008; and Natural Science Foundation of Guangdong Province under Grant No. 2018A0303130035.
Citation
Wang, W.M., Wang, J.W., Barenji, A.V., Li, Z. and Tsui, E. (2019), "Modeling of individual customer delivery satisfaction: an AutoML and multi-agent system approach", Industrial Management & Data Systems, Vol. 119 No. 4, pp. 840-866. https://doi.org/10.1108/IMDS-07-2018-0279
Publisher
:Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited