博碩士論文 107460001 詳細資訊




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姓名 黃韻芳(YunFang Huang)  查詢紙本館藏   畢業系所 會計研究所企業資源規劃會計碩士在職專班
論文名稱 以數據技術探討網路評價與購買行為之關聯-以美粧商品為例
(The relationship between online evaluation and purchase behaviors: case study of beauty products)
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摘要(中) 摘要
近年來網際網路硬體的提昇,上網的人口越來越普及化,帶動了電子商務的發展。由於網路購物網站能提供24小時全天候的便利服務,滿足不同時段的消費者,因此網路購物成了消費的管道之一。在美國尼爾森行銷公司的一份「全球網路消費者調查報告」中發現,消費者在從事網路購物時約有7成選擇相信網路購物中其他消費者在購物後對商品或服務所發表的評論或評價,而消費者在面對虛擬網路環境,無法確知商品品質、售後服務及退貨難易度的情況下,在購物的過程,消費者則參考商品本身的評價及商品收藏數的多寡,做為是否購買的參考依據。而網路商家也能透過網路評價,了解消費者對商品本身或服務的滿意程度,進而提升消費者的購買意願。
本研究網路購物網站的商品評價對消費者的購買行為和購買意願之間的關連性,透過搜集購物網站中的商品評價、商品購買量、商品收藏數,以獨立變數的統計方法分析後,得到下列結果:
1.購物網站中,網路商品評價對消費者購買行為的影響有顯著差異。
2.購物網站中,網路商品評價對消費者購買意願的影響有顯著差異。
3.購物網站中,商品的收藏數與商品的銷售量是正相關。
關鍵字:網路口碑、網路購物、知覺風險、購買意願
摘要(英) ABSTRACT
In recent years, the improvement of Internet hardware, the population of Internet access more and more popular, led to the development of e-commerce. Because online shopping sites can provide 24-hour convenience services to meet different time periods of consumers, so online shopping has become one of the channels of consumption. According to a "Global Online Consumer Survey" by Nielsen Marketing, about 70 percent of consumers who engage in online shopping choose to believe that other consumers in online shopping comment or comment on goods or services after shopping. And consumers in the face of the virtual network environment, can not be sure the quality of goods, after-sales service and return sasier, in the process of shopping, consumers refer to the evaluation of the goods themselves and the number of goods collected, as a reference for whether to buy. Online merchants can also through the network evaluation, to understand the consumer′s satisfaction with the goods themselves or services, and thus enhance the consumer′s willingness to buy. This study of the relationship between the product evaluation of online shopping websites and the consumer′s buying behavior and willingness to buy, By collecting the product evaluation, the quantity purchased and the collection of goods in the shopping website, the following results are obtained by analyzing the statistical method of independent variables:
1.In shopping websites, there are significant differences in the impact of online product evaluation on consumer buying behavior.
2.In shopping websites, there are significant differences in the impact of online product evaluation on consumers′ willingness to buy。
3.In the shopping website, the number of items Favorite is positively correlated with the sales volume of the items。
Keywords: Online word-of-mouth, Online shopping, Perceived risk, willingness to buy
關鍵字(中) ★ 網路口碑
★ 網路購物
★ 知覺風險
★ 購買意願
關鍵字(英) ★ Online word-of-mouth
★ Online shopping
★ Perceived risk
★ willingness to buy
論文目次 目錄
中文摘要 i
英文摘要 ii
誌謝 iii
目錄 iv
圖目錄 vi
表目錄 vii
一、 緒論 1
1.1 研究背景 1
1.2 研究動機 5
1.3 研究目的 7
1.4 研究流程 8
二、 文獻探討 10
2.1 口碑傳播 10
2.1.1 正向口碑和負向口碑 12
2.2 商品評價 13
2.2.1 評價數量 14
2.3 購買行為 15
2.4 購買意願 16
2.5 知覺風險 17
2.6 情感探勘 18
三、 研究方法 20
3.1 研究架構 20
3.2 研究假設 21
四、 數據分析 22
4.1 資料搜集 22
4.2 資料分析 23
4.3 敍述性統計分析 23
4.4 假設檢定 24
4.4.1 網路商品評價對商品銷售量之影響 24
4.4.2 網路商品評價對商品收藏數之影響 27
4.4.3 相關係數分析 30
五、 結論與未來研究方向 32
5.1 結論 32
5.1.1 商品評價對消費者購買行為之影響 32
5.1.2 商品評價對消費者購買意願之影響 33
5.2 未來研究方向 33
六、 參考文獻 35
參考文獻 參考文獻
[1] Amblee, N., & Bui, T. (2011). Harnessing the influence of social proof in online shopping: The effect of electronic word of mouth on sales of digital microproducts. International journal of electronic commerce, 16(2), 91-114.
[2] Baird, I. S., & Thomas, H. (1985). Toward a contingency model of strategic risk taking. Academy of management Review, 10(2), 230-243.
[3] Brown, J., Broderick, A. J., & Lee, N. (2007). Word of mouth communication within online communities: Conceptualizing the online social network. Journal of interactive marketing, 21(3), 2-20.
[4] Chatterjee, P. (2001). Online reviews: do consumers use them?
[5] Chen, Y., Fay, S., & Wang, Q. (2011). The role of marketing in social media: How online consumer reviews evolve. Journal of interactive marketing, 25(2), 85-94.
[6] Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews. Journal of marketing research, 43(3), 345-354.
[7] Collins, C., Hasan, S., & Ukkusuri, S. V. (2013). A novel transit rider satisfaction metric: Rider sentiments measured from online social media data. Journal of Public Transportation, 16(2), 2.
[8] Cox, D. F. (1967). Risk handling in consumer behavior: An intensive study of two cases. Risk taking and information handling in consumer behavior, 34-81.
[9] Dellarocas, C., Zhang, X. M., & Awad, N. F. (2007). Exploring the value of online product reviews in forecasting sales: The case of motion pictures. Journal of interactive marketing, 21(4), 23-45.
[10] Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers’ product evaluations. Journal of marketing research, 28(3), 307-319.
[11] Doh, S.-J., & Hwang, J.-S. (2009). How consumers evaluate eWOM (electronic word-of-mouth) messages. CyberPsychology & Behavior, 12(2), 193-197.
[12] Dowling, G. R., & Staelin, R. (1994). A model of perceived risk and intended risk-handling activity. Journal of consumer research, 21(1), 119-134.
[13] Erasmus, A. C., Boshoff, E., & Rousseau, G. (2001). Consumer decision-making models within the discipline of consumer science: a critical approach. Journal of Consumer Sciences, 29(1).
[14] Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research.
[15] Gelb, B., & Johnson, M. (1995). Word-of-mouth communication: Causes and consequences. Journal of health care marketing, 15, 54-54.
[16] Gelb, B. D., & Sundaram, S. (2002). Adapting to “word of mouse”. Business Horizons, 45(4), 21-25.
[17] Gershoff, A., Mukherjee, A., & Mukhopadhyay, A. (2003). Consumer acceptance of online agent advice: Extremity and positivity effects. Journal of Consumer Psychology, 13(1&2), 161-170.
[18] Harrison-Walker, L. J. (2001). The measurement of word-of-mouth communication and an investigation of service quality and customer commitment as potential antecedents. Journal of service research, 4(1), 60-75.
[19] Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic word-of-mouth via consumer-opinion platforms: what motivates consumers to articulate themselves on the internet? Journal of interactive marketing, 18(1), 38-52.
[20] Hennig-Thurau, T., Walsh, G., & Walsh, G. (2003). Electronic word-of-mouth: Motives for and consequences of reading customer articulations on the Internet. International journal of electronic commerce, 8(2), 51-74.
[21] Heung, V. C., & Gu, T. (2012). Influence of restaurant atmospherics on patron satisfaction and behavioral intentions. International Journal of Hospitality Management, 31(4), 1167-1177.
[22] Hu, N., Liu, L., & Sambamurthy, V. (2011). Fraud detection in online consumer reviews. Decision Support Systems, 50(3), 614-626.
[23] Kotler, P. (1997). Marketing management: analysis. Planning, Implementation, and Control, 9.
[24] Kotler, P., & Keller, K. L. (2009). Dirección de marketing: Pearson educación.
[25] Liu, B. (2012). Sentiment analysis and opinion mining. Synthesis lectures on human language technologies, 5(1), 1-167.
[26] Liu, Y. (2006). Word of mouth for movies: Its dynamics and impact on box office revenue. Journal of marketing, 70(3), 74-89.
[27] Mullet, G. M., & Karson, M. J. (1985). Analysis of purchase intent scales weighted by probability of actual purchase. Journal of marketing research, 22(1), 93-96.
[28] Pang, B., & Lee, L. (2004). A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts. Paper presented at the Proceedings of the 42nd annual meeting on Association for Computational Linguistics.
[29] Pantelidis, I. S. (2010). Electronic meal experience: A content analysis of online restaurant comments. Cornell Hospitality Quarterly, 51(4), 483-491.
[30] Park, C., & Lee, T. M. (2009). Information direction, website reputation and eWOM effect: A moderating role of product type. Journal of business research, 62(1), 61-67.
[31] Rezvani, S., Dehkordi, G. J., Rahman, M. S., Fouladivanda, F., Habibi, M., & Eghtebasi, S. (2012). A conceptual study on the country of origin effect on consumer purchase intention. Asian Social Science, 8(12), 205-215.
[32] Richins, M. L. (1983). Negative word-of-mouth by dissatisfied consumers: A pilot study. Journal of marketing, 47(1), 68-78.
[33] Sheth, J. N. (1971). Word-of-Mouth in Lov Risk lnnovations. Journal of Advertising, 15-18.
[34] Silverman, G. (2011). Secrets of word-of-mouth marketing: how to trigger exponential sales through runaway word of mouth: Amacom books.
[35] Tirunillai, S., & Tellis, G. J. (2014). Mining marketing meaning from online chatter: Strategic brand analysis of big data using latent dirichlet allocation. Journal of marketing research, 51(4), 463-479.
[36] Westbrook, R. A. (1987). Product/consumption-based affective responses and postpurchase processes. Journal of marketing research, 24(3), 258-270.
[37] Wilson, W. R., & Peterson, R. A. (1989). Some limits on the potency of word-of-mouth information. ACR North American Advances.
[38] 尼爾森(Nielsen)行銷公司. (2009). 2009年全球網路消費者調查報告. Retrieved from http://isaacleesheaven.blogspot.com/2009/08/7.html?m=0
[39] 尼爾森(Nielsen)行銷公司. (2016). 2015 年尼爾森虛擬購物行為研究報告. Retrieved from https://www.nielsen.com/wp-content/uploads/sites/3/2019/04/Taiwan-eCommerce-Report-2016ch.pdf
[40] 財團法人台灣網路資訊中心. (2018). 2018 台灣網路報告. Retrieved from https://report.twnic.tw/2018/
[41] 財團法人台灣網路資訊中心. (2019a). 2019年台灣網路報告. Retrieved from https://report.twnic.tw/2019/
[42] 財團法人台灣網路資訊中心. (2019b). 歷年個人及家庭上網行為. Retrieved from https://www.twnic.net.tw/doc/twrp/201912f.pdf
[43] 資策會產業情報研究所(MIC). (2019). 【網購調查系列一】網購消費占比達16.5% 愛用電商平台大排名. Retrieved from https://mic.iii.org.tw/news.aspx?id=516
指導教授 許秉瑜(Ping-Yu Hsu) 審核日期 2020-6-20
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