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題名：以多層次潛在類別模式分析網路使用行為類型
作者：謝翠娟
校院名稱：國立交通大學
系所名稱：資訊管理研究所
指導教授：楊千
學位類別：博士
出版日期：2011
主題關鍵詞：網際網路使用行為模式；區域差異；性別差異；多層次潛在類別分析；online behavior patterns；regional differences；gender difference；Multilevel Latent Class Analysis
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本研究證實網路的行為取決於個人特質和其居住環境。本研究應用了多層次潛在類別分析，考慮台灣25個不同縣市環境的影響，並分析共計10,909位居民常見的七種網際網路應用行為，探討及歸納網路應用的使用類型。研究結果顯示，在考慮使用者居住區域影響的情形下，網際網路使用模式確實具存在居住地和性別的差異。例如，在大都會區有較高比例的成員相對善於應用網際網路服務，而非都會地區則有相對較多屬於不常使用網際網路服務的成員。有趣的是，網路購物及網路學習都是非都會區的用戶使用比率較高。除此之外，研究發現使用者的個人特質也會影響使用者分群。例如，女性使用網路購物服務的機率高於男性，年輕人普遍擅長各種網際網路應用，且較其他年齡的使用者更常使用部落格與即時信息服務。研究建議，服務提供者可以規劃網路購物並適當搭配網路金融及遞送服務，以吸引非都會區的用戶購買。如果服務供應者的目標客戶是大都會區的使用者，則應該強化安全性訴求，並搭配互動與行動服務，以利推廣行銷。考量21-40歲的使用者是網際網路服務的核心用戶，所以建議網站服務規劃，可以參考研究所整理該年齡層行為特質，提供適當客制化服務與折扣，以吸引他們使用。本研究應用豐富的調查數據，有效驗證網際網路使用行為模式確實存在城鄉區域和性別差異，研究結果將有助於網際網路服務供應商參考發展服務策略，提高用戶需求的契合度，並進一步提升使用者滿意度。
This research confirms that online behaviors are dictated by both personal characteristics and areas of people reside. This study has applied the MLCA model to investigate Internet usage patterns from seven online applications among 10,909 Taiwan residents who live in one of 25 different regions. The results showed that online behavior patterns do exhibit regional and gender differences, as the regional segments are dictated by the individual segments of different use patterns. For instance, the urban area segment comprised a higher proportion of members who are good at using the Internet. The rural area segment made up a higher proportion of members who occasionally use the Internet. Interestingly, non-metropolitan area users went online more often than those in metropolitan area users when using e-learning or online shopping. Service providers can offer an appropriate collocation of online shopping, online financing and delivery services to attract purchases from non-metropolitan area residents. If a service provider is trying to target metropolitan area residents, then it should enhance security and could use pre-introduction or a trial together with a promotion on an interactive and mobile service.
On the other hand, the individual segments are dictated by users’ personal characteristics. For instance, younger people were good at various online services, as they had more employing blog and instant message services than others. Gender difference depends on various/heterogeneity application. Females used the Internet more often for online shopping application than males. People aged 21-40 were the major users of online applications, and websites could offer these users appropriate discounts of customization to attract their purchases. By using a massive amount of survey data to show regional and gender differences in online behavior patterns, the findings herein will help Internet service providers to form an applicable guideline for developing service strategies of higher service satisfaction between products and users’ needs.
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