協同規劃預測分析機制之發展
─以唱片產業為例

林仁凱

doi:10.6840/cycu200700583

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協同規劃預測分析機制之發展 ─以唱片產業為例

Development of a Collaborative Planning and Forecasting Analysis Mechanism for Music Record Industry

林仁凱 , Masters　　Advisor：宮大川　　

繁體中文 DOI： 10.6840/cycu200700583

銷售預測；協同規劃預測補貨；創新性產品； sales forecasting ； innovation product ； CPFR

Abstract │ Reference (73) │ Times Cited (1) │ Altmetrics

Abstract 〈TOP〉

Parallel Abstract 〈TOP〉

Abstract
The vigorous development of the Information technology and Internet has led the
consumer market into the highly competitive environment. Facing the shortened
product cycle time and various choices of products, enterprise must develop the ability
of innovation to chime with the market environment and consumer preference. It’s now
an era of mutual-cooperation in the business model. Thus how to effectively integrate
the business collaboration of the members in the supply chain is the long last
competitive key point when dealing with this fiercely changeable market.
The purpose of this research is to design a collaborative planning and forecasting
analysis mechanism that based on the Collaborative Planning, Forecasting and
Replenishment (CPFR) business process model published by the Voluntary
Interindustry Commerce Standards (VICS) Association. The researching ranges are
mainly focusing in music record industry, the necessity of the collaboration between up
and downstream suppliers that must to quickly respond consumer and sharing business
information or the inaccuracy of the innovation product demand forecast, the frequency
of the demand changes, unable to control the demand information, high inventories and
loss sales on both supplier and retailer. And also the purpose of the research is to
proceed with analysis and study for the music record industries which had mentioned
above. Therefore, the collaborative planning and forecasting analysis mechanism
includes two issues. The first issue is to plan the music records industry business
process model in accordance with as-is operation process and CPFR business process,
which may lead the music company and retailer have the bidirectional communication.
The second issue is to design the sales forecasting and its adjustment model. The sales
forecasting model which considered the marketing mix factors, such as word-of-mouth,
sales trend, singer degree, the type of music record and holiday-effect provide themusic companies and retailer an advise sales forecasting value of new release music
record. Additionally the sales forecasting adjustment model consider the actuality sales
factory , including testing of the past and new released music record by using case
retrieval of Case-Based Reasoning (CBR)similarity factors, and estimations of the new
released music sales records by using the sales records from past released music
records that have similar topics. These are the reference bases for providing music
record enterprises to control accurately the uncertainly market and respond quickly to
the exception events.

Reference ( 73 ) 〈TOP〉

[6] 吳政達，「運用類神經網路估計新產品擴散模式係數之研究」，國立成功大學工業管理科學系碩士論文，2003。
連結：
[21] 黃郁仁，「整合案例式推理與類神經網路於新產品銷售預測--以圖書產品為例」，元智大學工業工程與管理學系研究所碩士論文，2003。
連結：
[23] 黃蘭禎，「CPFR流程下之銷售預測方法-混合預測模型」，國立政治大學資訊管理研究所碩士論文，2003。
連結：
[31] Barnett, H. G., Innovations: The basis of cultural change. New York: Mc Grew-Hill Book Company, Inc, 1953.
連結：
[33] Bass, F. M., A New Product Growth for Model Consumer Durables, Management Science,Vol.15, No.5, pp.215-227, 1969.
連結：

Times Cited (1) 〈TOP〉

李育修(2007)。協同訂單規劃與補貨機制之發展─以唱片產業為例。中原大學工業工程研究所學位論文。2007。1-106。

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