Dynamic Analysis of Store-to-Store Delivery Service through Fuzzy Cognitive Map

Abstract:

The Internet enables many companies to use the Web to allow customers to configure specific order options tailored to the tastes and preferences of the customers. Hence, logistics management exposes the formerly latent logistics system in the economic activities and reveals the inner connections between parts of logistics activities. Store-to-store delivery service is one of the most important delivery systems in Taiwan. The authors establish an evaluation model to analyze and describe the store-to-store delivery using sensitivity model and fuzzy cognitive map. The results obtained can be used to help the manager formulate strategies and reduce risks as well.

• Periodical: Applied Mechanics and Materials (Volumes 253-255)
• Pages: 1558-1562
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.253-255.1558
• Online since: December 2012
• Authors: Cheng Chi Chung, Yu Kai Huang
• Keywords: Fuzzy Cognitive Map, Multimedia Kiosk, Sensitivity Model, Store-to-Store Delivery

References

[1] Huang, Y. K., Feng, C. M., Why Customers Stay: An Analysis of Service Quality and Switching Cost on Choice Behavior by Catastrophe Model, Services Operations and Informatics [J], 2009, PP: 107-122.

DOI: 10.1109/soli.2006.237153

[2] Kok, K. The potential of Fuzzy Cognitive Maps for semi-quantitative scenario development, with an example from Brazil, Global Environmental Change [J], 2009, PP: 122-133.

DOI: 10.1016/j.gloenvcha.2008.08.003

[3] Lee, S., Ahn, H. Fuzzy cognitive map based on structural equation modeling for the design of controls in business-to-consumer e-commerce web-based systems, Expert Systems with Application [J], 2009, PP: 10447-10460.

DOI: 10.1016/j.eswa.2009.01.070

[4] Peter P. Groumpos, Chrysostomos D. Stylios. Modelling supervisory control systems using fuzzy cognitive maps, Chaos, Soltions and Frachals [J], 2000, PP: 329-336.

DOI: 10.1016/s0960-0779(98)00303-8

[5] Stylios, C. D., Georgopoulos, V. C., Malandraki, G. A., Chouliara, S. Fuzzy cognitive map architectures for medical decision support systems, Applied Soft Computing [J], PP: 1243-1251.

DOI: 10.1016/j.asoc.2007.02.022

[6] Kang, I., Lee. S., Choi, J. Using fuzzy cognitive map for the relationship management in airline service, Expert Systems with Application [J], 2004, PP: 545-555.

DOI: 10.1016/j.eswa.2003.10.012

[7] Tsadiras, A. H. Comparing the inference capabilities of binary, trivalent and sigmoid fuzzy cognitive maps, Information Science [J], 2008, P: 3880-3894.

DOI: 10.1016/j.ins.2008.05.015

[8] Bueno, S., Salmeron, J. L. Fuzzy modeling Enterprise Resource Planning tool selection, Computer Standards & Interfaces [J], 2008, PP: 137-147.

DOI: 10.1016/j.csi.2007.08.001

[9] Kosko, B. Fuzzy cognitive maps, Man-Machine Studies [J], 1986, PP: 65-75.

[10] Lee, K. C., Kim, H. S. A Fuzzy Cognitive Map-Based Bi-Directional Inference Mechanism: An Application to Stock Investment Analysis, Intelligence Systems in Accounting, Finance and Management [J], 1997, PP: 41-57.

DOI: 10.1002/(sici)1099-1174(199703)6:1<41::aid-isaf119>3.0.co;2-j