台灣筆記型電腦擴散情形及消費者偏好之研究

The Study of Evolutional Diffusion and the Preference of Consumer for the Notebook in Taiwan

張志煌(Chih-Huang Chang)

指導教授 ： 王福琨 ； 田方治

國立臺北科技大學/管理學院/工業工程與管理系所/碩士(2005年)

摘要

隨著消費者消費能力提昇，以往傳統創新產品已不能滿足消費者需求，創新科技產品不斷地被開發出來，產品生命週期越來越短，正確地對產品市場銷售量進行預測在現代管理上更顯得重要。而擴散模型最主要目的在於探究產品之生命週期，並預測需求量。因此，本研究是以Bass擴散模型（Diffusion Model）為基礎，加入價格作為影響產品銷售量之變數，應用於筆記型電腦來驗證此模型於市場銷售預測能力；研究分析資料由1994年至2003年之筆記型電腦各季出貨量。最後以聯合分析法（Conjoint Analysis）分析消費者對筆記型電腦之使用偏好及選擇重點。
研究結果發現，本預測模型加入價格變數後，對台灣地區筆記型電腦銷售情形，不但具有良好之配適能力，在預測方面，也有相當不錯之預測能力。且不論在配適情形或預測能力上，都優於Bass擴散模型，而筆記型電腦銷售量與價格呈現反向關係，即筆記型電腦銷售價格降低時，其銷售量則向上成長。至於筆記型電腦選購喜好部分，消費者重視因素依序為：重量、功能，而品牌則居於最末端。

關鍵字

擴散模型 ； 聯合分析法 ； 基因演算法

並列摘要

With the arising of consuming capability, traditional innovative products are not able to meet the demand of consumers. Instead, the innovative technology products are constantly developed to shorten the product life cycles. Therefore, a correct sales forecast is more and more importance in the modern management. The main purpose of diffusion model is to investigate the product life cycle, and to forecast demand. Thus, the primary purpose of this study is to suggest a modified Bass model, adding the variable of product price, and use notebook to prove its better ability in sales forecast. The quarterly unit sales data of notebook, for the 40 periods from January 1994 to December 2003, are used. Finally, we utilize conjoint analysis to analyze the preference of consumers to notebook.
The results reveals that after adding the variable of product price, the forecasting model has better ability in sales forecast than Bass model. The relationship between price and sales is negative, which means sales will increase when price is decrease. In the aspect of purchasing preference in notebook, the rank of factors is weight, function, and then the brand in order.

並列關鍵字

Diffusion Model ； Conjoint Analysis ； Genetic Algorithm

參考文獻

[7] 邱凌志，「新產品銷售成長，最佳廣告支出與訂價策略—M.K.K.模型之推廣」，國立交通大學管理科學研究所，碩士論文，民國77年。

[19] Bass F. M., 1969, A New Product Growth Model for Consumer Durable. Management Science, 15(5), 215-227.

[20] Bayus B. L., 1987, Forecasting Sales of New Contingent Products: An Application to the Compact Disc Market, Journal of Product Innovation Management, 4(4), 243-255.

[21] Carmone J. D., Green P. E. and Jain A. K., 1978, Robustness of Conjoint Analysis: Some Monte Carlo Result, Journal of Marketing Research, 15(2), 300-303.

[22] Fourt L. A., and Woodlock J. W., 1960, Early Prediction of Market Success for Grocery Products. Journal of Marketing, 25(2), 31-38.