Abstract
In this study, data mining is applied to the use of an Enterprise Resource Planning (ERP) database to explore the core value of business operations by revising the RFM model into an RFGP model through “customer value analysis”. This model is used as a tool by enterprises to make proper adjustment to business strategies in a timely manner. By using an RFM model to “analyze dependence on suppliers”, enterprises can properly plan to reduce internal procurement costs and suppliers can properly manage their risks. With this two-prong focus on “profit maximization” and “cost reduction”, enterprises can maximize their profits. The findings of this study indicate that high-value customers are stable customers and accounted for 31 % of total customers. The statistics also show that customers of LED backlight modules constituted 18 % of the total and were the primary source of profit for the enterprises. However, there remains much uncertainty in the LED lighting market and the rate of return was low. With limited operational resources, enterprises should explore technologies related to backlight products, purchase automation equipment, train professionals in related disciplines and seek to enhance their overall competitive power. Suppliers of key materials are suppliers of high dependence, accounting for 11 % of the total and including suppliers of heavy reliance and exclusive suppliers. Enterprises are strongly advised to establish new sources of supplies to ensure a proper procurement balance and reduce materials supply related risks. In addition, enterprises should take the top 10 key materials suppliers as targets for price reductions in order to cut costs and maximize profits. Enterprises are also strongly advised to invest in the suppliers of key materials. The recycled use of enterprise resources could feedback to the enterprises themselves and helps to maximize enterprise profits.
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Kao, JH., Lai, F., Liaw, HT., Hsieh, Ph. (2015). Study of Customer Value and Supplier Dependence with the RFM Model. In: Park, J., Pan, Y., Chao, HC., Yi, G. (eds) Ubiquitous Computing Application and Wireless Sensor. Lecture Notes in Electrical Engineering, vol 331. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9618-7_27
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DOI: https://doi.org/10.1007/978-94-017-9618-7_27
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