Journal
TOURISM MANAGEMENT
Volume 53, Issue -, Pages 197-206Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.tourman.2015.10.001
Keywords
Location selection; Data mining; Rough set theory
Funding
- Ministry of Science and Technology, Taiwan, R.O.C. [NSC 102-2410-H-030-071-MY3]
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Location selection plays a crucial role in the retail and service industries. A comprehensive location selection model and appropriate analytical technique can improve the quality of location decisions, attracting more customers and substantially impacting market share and profitability. This study developed a data mining framework based on rough set theory (RST) to support location selection decisions. The proposed framework consists of four stages: (1) problem definition and data collection; (2) RST analysis; (3) rule validation; and (4) knowledge extraction and usage. An empirical study focused on a restaurant chain to demonstrate the validity of the proposed approach. Twenty location variables relevant to five location aspects were examined, and the results indicated that latent knowledge can be identified to support location selection decisions. (C) 2015 Elsevier Ltd. All rights reserved.
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