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Title: A cloud-based responsive replenishment system in a franchise business model using a fuzzy logic approach
Authors: Lee, CKH 
Choy, KL 
Ho, GTS 
Lin, C 
Issue Date: Feb-2016
Source: Expert systems, Feb. 2016, v. 33, no. 1, p. 14-29
Abstract: In today's volatile markets, increasingly unpredictable customer demand is exerting great challenges to responsive replenishment. The complexity of responsive replenishment is higher when the business is global in which demand in both domestic and overseas markets has to be catered for. The emergence of cloud computing has eased the difficulties as it allows nearly real-time access to a universal platform for information sharing between franchisors and franchisees, creating huge opportunities for understanding global market needs for responsive replenishment. Considering the existence of uncertainties due to the fluctuating demands, fuzzy logic is useful in providing decision support for replenishment in uncertain environments. This paper presents a cloud-based responsive replenishment system to manage operation data of a franchise business using cloud computing, and for analysis using fuzzy logic in order to provide franchisors with the required inventory levels. To the best of our knowledge, this is the first study that applies cloud computing and artificial intelligence techniques in franchising. A pilot run of the system is conducted in an education company, which is considered to be a good representation of an industry operating with a franchise model. The results show that the system allows franchisors to formulate effective responsive replenishment strategies.
Keywords: Cloud computing
Customer relationship management
Franchise
Fuzzy logic
Replenishment
Publisher: Wiley-Blackwell Publishing Ltd.
Journal: Expert systems 
ISSN: 0266-4720
EISSN: 1468-0394
DOI: 10.1111/exsy.12117
Rights: © 2015 Wiley Publishing Ltd
This is the peer reviewed version of the following article: Lee, C. K. H., Choy, K. L., Ho, G. T. S., & Lin, C. (2016). A cloud-based responsive replenishment system in a franchise business model using a fuzzy logic approach. Expert Systems, 33(1), 14–29, which has been published in final form at https://doi.org/10.1111/exsy.12117. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.
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