透過您的圖書館登入
IP:3.145.183.137
  • 期刊

Understanding Customer Innovativeness: A Soft Computing Approach in the Database Marketing Context

資料庫行銷環境下以柔性計算方法瞭解顧客對創新產品的採用傾向

摘要


創新是當代企業的重點策略,雖然產品和服務的創新能帶給顧客新的價值,利益和便利,然而卻有可能在創新擴散及採用的過程中無法順利跨越“創新採用鴻溝”而告失敗。原因是這些創新產品只吸引了市場內的先進顧客群而無法成功地滲透到全面市場。因此,瞭解顧客對創新的回應以及打量不同區隔顧客們的創新採用傾向,然後開發並提供有魅力的產品,乃成爲產品商業化成功的緊要工作。公司既有的顧客資料庫可用以掌握顧客的行爲,並萃取對各個區隔的顧客知識。但是,市場區隔作業的品質也是重要之事,做好區隔才能確認目標顧客。本研究的主要目的在於提供一個新穎的方法論,以柔性計算方法決定區隔作業的品質,並以最佳的區隔結果得知顧客的創新採用傾向。最後用業界實際收集來的數據驗證本方法論的實用性。

並列摘要


Although innovation is the focus of business strategy nowadays, products/services innovation that deliver values, benefits, and convenience to customers may fail to cross the chasm in the process of innovation diffusion and adoption. This is because substantiation of market penetration never comes into being as the products/services attract merely customers of innovator segment in the market instead of those who are in the overall market. Therefore, understanding customer response to innovation, measuring customer innovativeness-the propensity of customers in different segments to adopt innovative products/services-and developing the attractive deliverables to them are crucial tasks for the success in commercialization. For a company, the customer database already in place enables the firm to capture customers' behavior and extract knowledge about customer innovativeness in different segments. However, the quality of segmentation task is also critical to empower the company to target the right customers. This paper makes a contribution toward the extant body of literature by presenting a novel methodology which firstly uses soft computing methods to determine the quality of segmentation task and then articulates customer innovativeness based on the best segmentation outcome. Data collected from an industry level case study is used for justification.

參考文獻


Alexander, D. L.、John, G. L. ,Jr.、Wang, Q.(2008)。As times go by: do cold feet follow warm intentions for really new versus incrementally new products?。Journal of Marketing Research。45(3),307-319。
Bigné, E.,Aldas-Manzano, J.,Kuster, I.,Vila, N.(2010).Mature market segmentation: a comparison of artificial neural networks and traditional methods.Neural Computing and Applications.19(1),1-11.
Castano, R.,Sujan, M.,Kacker, M.,Sujan, H.(2008).Managing consumer uncertainty in the adoption of new products: temporal distance and mental simulation.Journal of Marketing Research.45(3),320-336.
Chan, C. C. H.(2008).Intelligent value-based customer segmentation method for campaign management: a case study of automobile retailer.Expert Systems with Applications.34(4),2754-2762.
Chiu, C. Y.,Chen, Y. F.,Kuo, I. T.,Ku, H. C.(2009).An intelligent market segmentation system using K-means and particle swarm optimization.Expert Systems with Applications.36(3),4558-4565.

延伸閱讀