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研究生:康志瑋
研究生(外文):KANG CHIH WEI
論文名稱:涉入理論於網路商品行銷之應用
論文名稱(外文):Application of Involvement Theory to Online Product Marketing
指導教授:陳亭羽陳亭羽引用關係
指導教授(外文):Ting-Yu Chen, PH.D.
學位類別:碩士
校院名稱:長庚大學
系所名稱:企業管理研究所
學門:商業及管理學門
學類:企業管理學類
論文種類:學術論文
論文出版年:2001
畢業學年度:89
語文別:中文
中文關鍵詞:涉入理論個人涉入量表線上遊戲線上教學網路理財
外文關鍵詞:involvement theoryPersonal Involvement Inventoryon-line gamese-learningon-line trading
相關次數:
  • 被引用被引用:136
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  • 下載下載:395
  • 收藏至我的研究室書目清單書目收藏:19
涉入理論合理地解釋為何消費者並非總是以複雜且耗時耗力的決策程序進行購買決策。根據涉入理論,消費者處於低自我攸關/重要性情境時,將採行有限訊息處理模式;相反地,在高自我攸關情境時將改行廣泛訊息處理模式。涉入理論在行銷策略的應用相當廣泛,舉凡心理變數區隔(高/低涉入)、媒體策略、中央/週邊說服路徑、認知操弄等議題皆屬其涵蓋範圍。基於網際網路在商品訊息搜尋與評估活動上所帶來的廣泛利益,如何應用涉入理論於網路行銷上便成一值得探究的議題。因此,本研究運用涉入理論於網路商品,利用Zaichkowsky修正後的個人涉入量表,衡量消費者對網路商品的持久涉入程度,目的在探究網路商品涉入程度與消費行為之間的關聯性,並描繪高低涉入人口的族群特徵。
本研究以網路連線遊戲、線上教學課程與線上下單服務三項網路商品為涉入對象,透過電子郵件與市調網站進行三種商品的網路問卷實證調查。三項實證結果皆顯示高低涉入者在資訊蒐集、品牌偏好、產品使用上存在著泛的差異。與低涉入者相較,高涉入者有著較大的使用量、較頻繁的使用頻率與訊息蒐集行為、較高的品牌偏好認知。可知以涉入作為有效市場區隔的區隔基礎是恰當的。
實證結果指出網路商品的消費者可依其涉入程度進行市場區隔,而本研究也以人口統計、科技生活型態、上網動機等變數描繪高低涉入者的族群特徵。根據分析結果,網路連線遊戲高涉入族群以15歲-24歲經常上網從事休閒娛樂活動,具中高程度網路社會參與和科技嘗鮮傾向的男性高中生或工學院學生為主要組成份子。網路教學課程高涉入族群則具有高度網路社會參與傾向,且以充實專業知識、滿足工作需求為其主要上網動機。至於線上下單高涉入族群則具中高程度網路社會參與傾向,且以充實專業知識、滿足工作需求為其主要上網動機的商學人士為主要組成份子。論文最後討論如何應用涉入理論於網路商品行銷活動上,並做出具體的行銷建議,供學界及實務界人士參考。
The involvement theory reasonably explains why consumers do not always undertake a complex decision process requiring substantial amounts of time and energy while making a consumption decision. It proposes that consumers engage in limited information processing in situations of low importance or relevance to them and in extensive information processing in situations of high relevance. Involvement theory has numerous strategic applications for the marketer, such as psychological segmentation (low-involvement, high-involvement), media strategy, central or peripheral routes to persuasion, cognitive processing or passive processing paradigm, etc. With the widespread interest in using the Internet as a vehicle to seek product information and make initial product comparisons, the question then arises about the marketing implications of involvement theory to on-line retail shopping. Therefore, this study applied the revised, 10-item Zaichkowsky Personal Involvement Inventory to measure consumers’ enduring involvement with an on-line product. In addition, involvement theory and on-line consumer relevance was reexamined and low- and high-involvement consumers were profiled.
Through e-mail and Internet surveys, three empirical studies concerning on-line products were conducted, including on-line games, e-learning, and on-line trading. The findings of three studies revealed a wide variety of differences in information seeking, brand preference, and use-related factors between low- and high-involvement consumers. The more involved a consumer, the more the level of usage, rate of usage, information search, and degree of brand preference will be exhibited during on-line purchase processes. Thus, involvement can be an appropriate base for effective targeting of market segments.
The empirical studies indicated that on-line consumers could be segmented in terms of their levels of involvement. The characteristics of low- and high-involvement consumers are also profiled with several variables of demographic, techno-lifestyle, and motivation of Internet use. In terms of consumer characteristics, high-involvement segment in the on-line games category is male, 15-24 years old, beyond high school diploma, engineering-related professional, medially to highly involved in Internet communities, variety-novelty seeking in high technology, and using the Internet as a form of entertainment. As for the e-learning category, high-involvement segment is highly involved in Internet communities, and using the Internet as a social vehicle of professional achievements. In regard to the on-line trading category, high-involvement segment is business-related professional, medially to highly involved in Internet communities, and using the Internet as a social vehicle of professional achievements. Finally, the marketing implications of involvement theory were discussed and some valuable strategies were suggested for promoting on-line products.
目 錄
指導教授推薦書
口試委員會審定書
授權書iii
簽署人須知iv
中文摘要i
英文摘要i
誌謝i
第一章緒論    1
1.1研究背景與動機1
1.2研究目的2
1.3研究架構與方法2
1.4研究範圍與限制4
1.5研究內容與流程6
第二章涉入理論文獻探討6
2.1涉入的定義8
2.2涉入的分類10
2.3涉入的理論架構15
2.4涉入的衡量24
2.5小結 26
第三章研究方法29
3.1研究架構    29
3.2問卷設計    33
3.3問卷收集過程  42
3.4資料分析法   45
第四章資料分析 51
4.1科技生活形態量表因素分析51
4.2網路連線遊戲問卷統計分析54
4.2.1 樣本分佈敘述統計分析54
4.2.2 涉入程度分群57
4.2.3 檢測高低涉入集群與行為變數的關係59
4.2.4 涉入族群特徵描繪65
4.3線上教學課程問卷統計分析67
4.3.1 樣本分佈敘述統計分析67
4.3.2 涉入程度分群70
4.3.3 檢測高低涉入集群與行為變數的關係72
4.3.4 涉入族群特徵描繪77
4.4線上下單服務問卷統計分析79
4.4.1 樣本分佈敘述統計分析79
4.4.2 涉入程度分群82
4.4.3 檢測高低涉入集群與行為變數的關係84
4.4.4 涉入族群特徵描繪90
第五章結論與建議97
5.1結論     97
5.2建議     98
5.3後續研究建議103
參考文獻104
附 錄110
圖 目 錄
圖1.1研究分析架構4
圖1.2研究流程7
圖2.1四種不同本質的反應涉入13
圖2.2涉入的理論架15
圖3.1研究分析架29
圖3.2統計分析流50
表 目 錄
表2.1涉入相關文獻整理20
表2.2涉入量表相關文獻整理27
表3.1電子商店的商品型態33
表3.2衡量涉入水準之問項34
表3.3網路連線遊戲的消費行為問項35
表3.4線上下單服務的消費行為問項36
表3.5線上教學課程的消費行為問項37
表3.6科技生活形態量表問項38
表3.7上網動機問項40
表3.8人口統計變數問項41
表3.9各類商品問卷回收資料44
表4.1科技生活形態KMO與Bartlett檢定51
表4.2科技生活形態涉入量表因素分析結果52
表4.3網路連線遊戲樣本性別與年齡分佈情形54
表4.4網路連線遊戲樣本行業別分佈情形55
表4.5網路連線遊戲樣本教育背景分佈情形56
表4.6網路連線遊戲樣本每月收入分佈情形56
表4.7網路連線遊戲樣本主要上網動機分佈情形57
表4.8網路連線遊戲KMO與Bartlett檢定58
表4.9網路連線遊戲涉入量表因素分析結果58
表4.10網路連線遊戲涉入因素分數59
表4.11網路連線遊戲涉入分群結果59
表4.12涉入程度vs. 是否經常注意網路連線遊戲的廣告60
表4.13涉入程度 vs. 閱讀電玩雜誌的頻率61
表4.14涉入程度 vs. 上網搜尋電玩資訊的頻率.61
表4.15涉入程度 vs. 從電視上收看電玩節目的頻率62
表4.16涉入程度 vs. 有無訂閱以電玩遊戲為主題的電子報62
表4.17涉入程度 vs. 網路連線遊戲使用頻率63
表4.18涉入程度 vs. 網路連線遊戲每週使用小時數63
表4.19涉入程度 vs. 是否特別偏好某些軟體公司出產的網路連線遊戲64
表4.20涉入程度 vs. 感覺市面上同類型的網路連線遊戲差異不大64
表4.21網路連線遊戲高低涉入族群主要特徵66
表4.22線上教學課程樣本性別與年齡分佈情形67
表4.23線上教學課程樣本行業別分佈情形68
表4.24線上教學課程樣本教育背景分佈情形68
表4.25線上教學課程樣本每月收入分佈情69
表4.26線上教學課程樣本主要上網動機分佈情70
表4.27線上教學課程KMO與Bartlett檢定70
表4.28線上教學課程涉入量表因素分析結果71
表4.29線上教學課程涉入因素分數71
表4.30線上教學課程涉入分群結果72
表4.31涉入程度 vs. 經常注意線上教學課程的廣告72
表4.32涉入程度 vs. 經常閱讀報章雜誌上關於線上教學課程的新聞報導73
表4.33涉入程度 vs. 上網搜尋進修學習課程資訊的頻率73
表4.34涉入程度 vs. 有無訂閱以線上教學課程為主題的電子報74
表4.35涉入程度 vs. 曾報名過的線上教學課程數目74
表4.36涉入程度 vs. 瀏覽線上教學課程網站的頻率75
表4.37涉入程度 vs. 特別偏好某些老師或業者開設的線上教學課程75
表4.38涉入程度 vs. 認為線上教學課程比其他進修管道更能符合自己的需要76
表4.39涉入程度 vs. 感覺市面上同樣科目的線上教學課程彼此之間很相似.76
表4.40網路教學課程高低涉入族群主要特徵78
表4.41線上下單服務樣本性別與年齡分佈情形79
表4.42線上下單服務樣本行業別分佈情形80
表4.43線上下單服務樣本教育背景分佈情形80
表4.44線上下單服務樣本每月收入分佈情形81
表4.45線上下單服務樣本主要上網動機分佈情形82
表4.46線上下單服務KMO與Bartlett檢定83
表4.47線上下單服務涉入量表因素分析結果83
表4.48線上下單服務涉入因素分數84
表4.49線上下單服務涉入分群結果84
表4.50涉入程度 vs. 閱讀股市投資雜誌的頻率85
表4.51涉入程度 vs. 上網搜尋股市投資資訊的頻率85
表4.52涉入程度 vs. 從電視上收看股市投資節目的頻率86
表4.53涉入程度 vs. 閱讀報紙上財經新聞的頻率86
表4.54涉入程度 vs. 瀏覽網路券商網站的頻率87
表4.55涉入程度 vs. 有無訂閱以股市投資為主題的電子報87
表4.56涉入程度 vs. 經常注意線上下單服務的廣告88
表4.57涉入程度 vs. 有無使用過線上下單服務88
表4.58涉入程度 vs. 有無對特定券商提供的線上下單服務有特別偏好88
表4.59涉入程度 vs. 感覺市面各業者提供的線上下單服務彼此之間很相似88
表4.60涉入程度 vs. 是否認為線上下單比其它下單管道更符合自己的需要90
表4.61線上下單服務高低涉入族群主要特徵92
表4.62涉入與消費行為的關係94
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Zaichkowsky, J. L. (1986), “Conceptualizing Involvement, ” Journal of Advertising, Vol.15 (2), 4-14.
Zaichkowsky, J. L. (1994), “Research Notes: The Personal Involvement Inventory: Reduction, Revision and Application to Advertising, ” Journal of Advertising, Vol.23 (4): 58-70.
Zaichkowsky, J. L., and J. H. Sood (1988), “A Global Look at Consumer Involvement and Use of Products, ” International Marketing Review, Vol.6, 20-34.
三、網路文獻
潘明君(2001), 台灣網路潛在人口名列亞太地區前茅, http://www.fing.org.tw。
呂振誼(2001), 2000年底我國上網人口突破600萬大關-Cable Modem漸屈下風, ADSL脫穎而出, http://www.fing.org.tw。
資策會(1998), 「電子商業之應用概論」, http://www.ec.org.tw/co-3.asp。
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