女性車主之購買行為研究

The study of purchase behavior of female car buyer

宋美玲(Mei-Ling Sung)

指導教授 ： 王如鈺

中原大學/商學院/企業管理研究所/碩士(2008年)

https://doi.org/10.6840/cycu200800075

摘要

近幾年來，由於我國經濟快速發展，國民所得大幅提升，汽車已由過去的奢侈品變成一種必需品、人們的代步工具。近年來，女性隨著教育普及，自主意識抬頭，女性工作人口因此增加，其可支配所得及購買力也隨之增加。且在汽車市場上女性消費者的比例逐年增加，因此本研究主要研究女性消費者之汽車購買行為研究，瞭解女性消費者在決定購買汽車時的影響因素。並藉由不同的市場區隔探討不同的消費群體間購買行為之差異，以供擬定行銷策略時的參考。

本研究針對女性車主採便利抽樣方法共回收498份有效樣本，分析結果如下：

1. 利用集群分析可將消費者區隔為四個集群，分別為：「未購車族」，「自我主義型」，「經濟務實型」，「社交享受型」；因此，以生活型態變數能將女性汽車消費者達成有效的市場區隔。
2. 根據女性消費者未來購車時各項屬性的重視程度，利用因素分析粹取出三項因素構面，此三項構面分別為：分為經濟性、功能性及舒適性。
3. 以生活型態為主要變數，將女性汽車消費者區隔成為幾個不同的群組，並針對人口統計變數、產品屬性偏好以及汽車購買及使用行為，進行不同生活型態消費者之差異分析。

關鍵字

產品屬性 ； 生活型態 ； 集群分析

並列摘要

In light of female work population increase, their disposable income and purchasing power are growing as well. The female car buyers have been increasing in the retail automotive market. More and more females are becoming active participants or the key decision makers in vehicle purchases.

The female car buyers have different perceptions, attitudes, and decision criteria and they can have different factors influencing their satisfaction and loyalty than the historically dominant male car buyers.

Following are some noteworthy trends via different life style groups regarding female car buyers.

The whole sample is classified into four groups. These four groups show significant difference after conducting Chi-Square test, ANOVA analysis, Regression analysis and discriminate analysis. After testing whether different variables of population statistics among different female groups will affect motivations of consumption needs, source of information, criterion of assessment, purchase behaviors, and service requirements, it is discovered that most of groups demonstrate significant difference.

The conclusion is：
1. Women with different educational level , occupation, and marriage show significant difference in different life style segment group
2. The purchase behavior in different life style segment group also display significant difference on transaction price and product life cycle.
3. Product preferences show significant difference in different life style segment group.
4. Different demographic reveals significant difference on different purchase behaviors.
5. Evaluation will defer when making decision to purchase.

Through step-wise regression and inputs from interviews, this study chooses “Age” and “Income” as independent factors for multi-regression forecast model. Both “Coefficient of Determination” (R2) and P Value are within acceptance level, proving adequacy of the model. Moreover, by step-wise regression, this study also selected key independent factors for multi-regression forecast model on different product preference groups. Both “Coefficient of Determination” (R2) and P Value are within acceptance level, proving adequacy of the model.

In addition, by way of discriminate analysis to classify the female consumers’ purchase behaviors correctly, forecast the potential consumers to assist in executing successful marketing program.

並列關鍵字

Cluster analysis ； Life style ； Product attributes

參考文獻

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