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| Title: | 從ELM理論看WeChat與Weibo之資訊流廣告效果
A research of news feed ads effect between WeChat and Weibo: based on Elaboration Likelihood Model |
| Authors: | 陳奕杭
Chen, Yihang |
| Contributors: | 張郁敏
Chang, Yuhmiin
陳奕杭
Chen, Yihang |
| Keywords: | 社群媒體
資訊流廣告
訊息涉入度
訊息可信度
感知按讃數量
Social Media
News Feed Ad
Message Involvement
Message Credibility
Perceived Number of Likes |
| Date: | 2017 |
| Issue Date: | 2017-04-05 15:43:28 (UTC+8) |
| Abstract: | 行動時代的到來為社群媒體帶來了發展的春天，原生廣告也隨之應運而生，成為備受社群媒體青睞的新興廣告形式。而在中國市場，WeChat與Weibo這兩大社群媒體自2012年起相繼推出了資訊流廣告服務，並不斷試水新的技術和表現形式。兩者的資訊流廣告在運作機制和表現形式上雖有所雷同，但仍各有特點，其中最主要的差異體現在廣告訊息的按讃者和按讃數量上。
因此，本研究以WeChat和Weibo為研究對象，援引推敲可能性模式理論，希望探究消費者在觀看WeChat和Weibo資訊流廣告時，是否會因為廣告訊息按讚者或按讚數量的不同，在品牌態度和購買意願上產生差異。
本研究採用實驗室實驗法，招募60名國立政治大學非傳播相關科系的大陸籍學生進行實驗。研究結果發現WeChat和Weibo的資訊流廣告訊息接收者在品牌態度和購買意願的形塑歷程上確實存在差異：就WeChat而言，廣告訊息可信度更能正向影響消費者的品牌態度和購買意願；就Weibo而言，感知按讃數量更能正向影響消費者的購買意願，但對品牌態度不構成顯著影響。
Native advertising has emerged both as an exciting new way for digital marketers to engage with the consumer, and as a new source of advertising revenue for social media. In the China market, news feed ad, a major type of native advertising, has been very popular in WeChat and Weibo since 2012. Visually the native advertisement in these two social media seem pretty similar, but they have enough differences to make them different, particularly in the differences of likers and the number of likes on advertisement.
Using the Elaboration Likelihood Model (ELM) adopted by Harkins and Petty, this study focus on WeChat and Weibo and try to clarify the differences of consumer’s information processing, brand attitude and purchase intention between these two social media, which has various social tie strength. Adopting an laboratory experimentation, a total of 60 samples, participated in this study during January, 2017.
Finding of this study show the differences of brand attitude and purchase intention towards news feed ad when subjects are exposed to WeChat between Weibo. In WeChat, message credibility indicate more significant influence on the brand attitude and purchase intention towards native advertisement rather than perceived number of likes. Oppositely perceived number of likes positively influence on purchase intention towards native advertisement in Weibo. |
| Reference: | 一、中文書目
白明勝（1995）。《投入程度、認知需求對廣告說服效果之影響》。台北：國立政治大學國際貿易研究所碩士論文。
吳統雄（1984）。《電話調查：理論與方法》。台北市：聯經出版事業公司。
張郁敏（2008）。〈單一與多重媒體重複策略之傳播效果比較〉，《中華傳播學刊》，14：231-265。
張維仁（2015）。〈原生廣告5大型態〉，《動腦雜誌》，467：60-65。
陳又瑈（2015）。《Facebook與Instagram之跨訊息綜效比較》。台北：國立政治大學廣告學系碩士論文。
陳歆平（2016）。《探討原生廣告和橫幅廣告與網頁一致性差異對使用者經驗與廣告效果的影響》。高雄：國立中山大學資訊管理學系碩士論文。
陳維謙（2016）。《原生廣告位置及內容一致性對廣告效果之影響—以產品及內容涉入程度為干擾變數》。台北：國立政治大學商學院企業管理學系碩士論文。
陳建州（2009）。《線上社會網絡連結強度之衡量》。台北：國立台灣大學管理學院資訊管理學研究所碩士論文。
黃俊寧、李奇勳、陳俊銘（2014）。〈傳遞者專業度、訊息數量與聯繫強度對口碑接受度和購買意圖之影響〉，《輔仁管理評論》，21（1）：33-60。
程新雨（2001）。《產品屬性，產品知識，認知需求對消費者反遞移律決策行為之影響》。台北：國立台灣大學商學研究所碩士論文。
戴軒廷、馬恆、張紹勳（2004）。〈影響網路廣告效果之相關因素〉，《中華管理評論》，7（2）：1-29。
二、英文書目
Arndt, J. (1967). Role of product-related conversations in the diffusion of a new product. Journal of marketing Research, 4(1), 291-295.
Appelman, A., & Sundar, S. S. (2015). Measuring Message Credibility Construction and Validation of an Exclusive Scale. Journalism & Mass Communication Quarterly, 93(1), 59-79.
boyd, Danah M. & Nicole, B. Ellison (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1), 210-230.
Brown, J. J., & Reingen, P. H. (1987). Social ties and word-of-mouth referral behavior. Journal of Consumer research, 14(3), 350-362.
Cacioppo, J. T., Petty, R. E., Kao, C. F., & Rodriguez, R. (1986). Central and peripheral routes to persuasion: An individual difference perspective. Journal of Personality and Social Psychology, 51(5), 1032-1043.
Chang, Y., & Thorson, E. (2004). Television and web advertising synergies. Journal of Advertising, 33(2), 75-84.
Cheung, M. Y., Luo, C., Sia, C. L., & Chen, H. (2009). Credibility of electronic word-of-mouth: Informational and normative determinants of on-line consumer recommendations. International Journal of Electronic Commerce, 13(4), 9-38.
Chu, S. C., & Kim, Y. (2011). Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites. International Journal of Advertising, 30(1), 47-75.
Clancy, K. J., & Kweskin, D. M. (1971). TV commercial recall correlates. Journal of Advertising Research, 2, 18-20.
De Bruyn, A., & Lilien, G. L. (2008). A multi-stage model of word-of-mouth influence through viral marketing. International Journal of Research in Marketing, 25(3), 151-163.
Duhan, D. F., Johnson, S. D., Wilcox, J. B., & Harrell, G. D. (1997). Influences on consumer use of word-of-mouth recommendation sources. Journal of the Academy of Marketing Science, 25(4), 283-295.
Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends”: Social capital and college students’ use of online social network sites. Journal of Computer‐Mediated Communication, 12(4), 1143-1168.
Ellison, N. B., Vitak, J., Gray, R., & Lampe, C. (2014). Cultivating social resources on social network sites: Facebook relationship maintenance behaviors and their role in social capital processes. Journal of Computer-Mediated Communication,19(4), 855-870.
Erickson, B.H., Nosanchuk, T.A., Mostacci, L. and Dalrymple, C.F. (1978). The flow of crisis information as a probe of work relations. Canadian Journal of Sociology, 3(1), 71-87.
Frenzen, J., & Nakamoto, K. (1993). Structure, cooperation, and the flow of market information. Journal of Consumer Research, 20(3), 360-375.
Gaziano, C., & McGrath, K. (1986). Measuring the concept of credibility. Journalism and Mass Communication Quarterly, 63(3), 451.
Gilbert, E., & Karahalios, K. (2009, April). Predicting tie strength with social media. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 211-220). New York, NY: ACM.
Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360-1380.
Haythornthwaite, C. (2002). Strong, weak, and latent ties and the impact of new media. The Information Society, 18(5), 385-401.
Harkins, S. G., & Petty, R. E. (1981). The multiple source effect in persuasion: The effects of distraction. Personality and Social Psychology Bulletin, 7(4), 627-635.
Harkins, S. G., & Petty, R. E. (1981). Effects of source magnification of cognitive effort on attitudes: An information-processing view. Journal of Personality and Social Psychology, 40(3), 401-413.
Harkins, S. G., & Petty, R. E. (1987). Information utility and the multiple source effect. Journal of Personality and Social Psychology, 52(2), 260.
He, Y., Zhang, C., & Ji, Y. (2012, October). Principle features for tie strength estimation in micro-blog social network. In Computer and Information Technology (CIT), 2012 IEEE 12th International Conference on (pp. 359-367). IEEE.
Houghton, D.J. and Joinson, A.N. (2010). Privacy, social network sites, and social relations. Journal of Technology in Human Services, 28(1), 74-94.
Hovland, C. I., & Weiss, W. (1951). The influence of source credibility on communication effectiveness. Public opinion quarterly, 15(4), 635-650.
Hu, Y., & Sundar, S. S. (2009). Effects of online health sources on credibility and behavioral intentions. Communication Research, 37, 105-132.
Keller, K. L. (1993). Conceptualizing, measuring, and managing customer-based brand equity. The Journal of Marketing, 1-22.
Koo, D. M. (2016). Impact of tie strength and experience on the effectiveness of online service recommendations. Electronic Commerce Research and Applications, 15, 38-51.
Lee, Y. H. (2000). Manipulating ad message involvement through information expectancy: Effects on attitude evaluation and confidence. Journal of Advertising, 29(2), 29-43.
Lee, K. T., & Koo, D. M. (2015). Evaluating right versus just evaluating online consumer reviews. Computers in Human Behavior, 45, 316-327.
Lin, N., Vaughn, J. C., & Ensel, W. M. (1981). Social resources and occupational status attainment. Social forces, 59(4), 1163-1181.
Lin, C. P., & Bhattacherjee, A. (2008). Elucidating individual intention to use interactive information technologies: The role of network externalities. International Journal of Electronic Commerce, 13(1), 85-108.
Luarn, P., & Chiu, Y. P. (2015). Key variables to predict tie strength on social network sites. Internet Research, 25(2), 218-238.
Marks, L. J., & Olson, J. C. (1981). Toward a cognitive structure conceptualization of product familiarity. NA-Advances in Consumer Research, 8, 145-150.
Marsden, P. V. & Campbell, K. E. (1984). Measuring tie strength. Social Forces, 63(2), 482–501.
Marsden, P. V. (1990). Network data and measurement. Annual Review of Sociology, 16(1), 435–463.
Martin, B.A.S., Lee, C.K.C, and Yang, F. (2004). The influence of ad model ethnicity and self-referencing on attitudes. Journal of Advertising, 33(4), 27-37.
Mathews, K. M., White, M. C., Long, R. G., Soper, B., & Von Bergen, C. W. (1998). Association of indicators and predictors of tie strength. Psychological Reports, 83, 1459-1469.
McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce: An integrative typology. Information Systems Research, 13(3), 334-359.
McCroskey, J. C., & Teven, J. J. (1999). Goodwill: A reexamination of the construct and its measurement. Communications Monographs, 66(1), 90-103.
Metzger, M. J., Flanagin, A. J., Eyal, K., Lemus, D. R., & McCann, R. M. (2003). Credibility for the 21st century: Integrating perspectives on source, message, and media credibility in the contemporary media environment.Annals of the International Communication Association, 27(1), 293-335.
Moore, D. J., & Reardon, R. (1987). Source magnification: The role of multiple sources in the processing of advertising appeals. Journal of Marketing Research, 24(4), 412-417.
Moore, D. J., Mowen, J. C., & Reardon, R. (1994). Multiple sources in advertising appeals: When product endorsers are paid by the advertising sponsor. Journal of the Academy of Marketing Science, 22(3), 234-243.
Park, D. H., & Kim, S. (2009). The effects of consumer knowledge on message processing of electronic word-of-mouth via online consumer reviews. Electronic Commerce Research and Applications, 7(4), 399-410.
Petróczi, A., Nepusz, T., & Bazsó, F. (2007). Measuring tie-strength in virtual social networks. Connections, 27(2), 39-52.
Singh, S. N., Lessig, V. P., Kim, D., Gupta, R., & Hocutt, M. A. (2000). Does your ad have too many pictures? Journal of Advertising Research, 40(1-2), 11-27.
Sundar, S. S. (1999). Exploring receivers’ criteria for perception of print and online news. Journalism & Mass Communication Quarterly, 76, 373-386.
Tavassoli, N., Shultz, C. J., & Fitzsimons, G. J. (1995). Program involvement：Are moderate levels best for ad memory and attitude toward the ad? Journal of Advertising Research, 61.
Van Hoye, G. & F. Lievens. (2007). Social Influences on organizational attractiveness: Investigating if and when word of mouth matters. Journal of Applied Social Psychology, 37(9), 2024-2047.
Wang, J. C., & Chang, C. H. (2013). How online social ties and product-related risks influence purchase intentions: A Facebook experiment. Electronic Commerce Research and Applications, 12(5), 337-346.
Wellman, B., & Wortley, S. (1990). Different strokes from different folks: Community ties and social support. American journal of Sociology, 558-588.
Wen, C., Tan, B. C., & Chang, K. T. T. (2009). Advertising effectiveness on social network sites: an investigation of tie strength, endorser expertise and product type on consumer purchase intention. ICIS 2009 Proceedings, 151.
Xiang, R., Neville, J., and Rogati, M. (2010). Modeling relationship strength in online social networks. In Proceedings of the 19th International Conference on World Wide Web (pp. 981-990). New York, NY: ACM.
Zaichkowsky, J. L. (1985). Measuring the involvement construct. Journal of Consumer Research, 12(3), 341-352.
Zaichkowsky, J. L. (1994). The personal involvement inventory: Reduction, revision, and application to advertising. Journal of Advertising, 23(4), 59-70.
Zhang, Y., & Buda, R. (1999). Moderating effects of need for cognition on responses to positively versus negatively framed advertising messages. Journal of Advertising, 28(2), 1-15.
三、網路資料
199IT（2016）。〈2015年中國移動廣告支出首次超過PC〉。上網日期：2016年3月10日，取自http://www.199it.com/archives/437023.html
BJQ智商謀略（2013）。〈調查：News Feed植入式廣告成新寵〉。上網日期：2016年4月2日，取自
http://www.bqjournal.com/survey-news-feed-cloned-into-advertising-sandoval
DCCI互聯網數據中心（2015）。〈2015年中國數字營銷趨勢報告〉。上網日期：2016年3月10日，取自http://www.199it.com/archives/358413.html
Farmarketing（無日期）。〈原生廣告能否成功逼宮BANNER〉。上網日期：2016年4月2日，取自http://www.yeahmobi.com/cn_newsshow-36-630-1.html
Greenberg, Dan & Navin, James (2013). Where You Can Go Right, and Wrong, with Native Ads. Retrieved from https://techcrunch.com/2013/02/17/the-native-ad-movement-and-the-opportunity-for-web-publishers/
iResearch艾瑞咨詢（2015）。〈2015年中國移動應用廣告平台市場研究報告〉。上網日期：2016年3月10日，取自http://www.iresearch.com.cn/report/2329.html
iResearch艾瑞咨詢（2016）。〈2015年中國網路廣告市場規模突破2000億〉。上網日期：2016年6月10日，取自
http://report.iresearch.cn/content/2016/04/259999.shtml
iResearch艾瑞咨詢（2016）。〈2016年中國網絡廣告行業年度監測報告〉。上網日期：2016年12月15日，取自http://report.iresearch.cn/report/201604/2566.shtml
IAB (2013). Native Advertising Playbook. Retrieved from http://www.iab.net/media/file/IAB-Native-Advertising-Playbook2.pdf
Lazauskas, Joe (2014). Study: Sponsored Content Has a Trust Problem. Retrieved from https://contently.com/strategist/2014/07/09/study-sponsored-content-has-a-
trust-problem-2/
Manic, Marius (2014). The rise of native advertising, Bulletin of the Transilvania University of Brasov. Retrieved from https://www.researchgate.net/publication/290062102_The_Rise_of_Native_Advertising
Sebastian, Michael (2014). The Year in Native Ads. Retrieved from http://adage.com/article/media/year-content-marketing-native-ads/296436/
Sharethrough (n. d.).Native ads vs Banner ads. Retrieved from http://www.sharethrough.com/resources/in-feed-ads-vs-banner-ads/
Titan（2014）。〈低頭族一天看手機 150 次，行動原生廣告將崛起〉。上網日期：2016年4月2日，取自
http://www.inside.com.tw/2014/08/18/yahoo-taiwan-is-going-to-push-native-ads-on-mobile-platforms#fnref:3
每經網（2015）。〈微信朋友圈又發廣告，這次是凱迪拉克〉。上網日期：2016年12月5日，取自http://www.nbd.com.cn/articles/2015-02-02/895101_2.html
城市畫報、騰訊問卷（2016）。〈2016年中國青年生活型態調查報告〉。上網日期：2016年12月17日，取自http://cdc.tencent.com/2016/03/02/2015%E5%B9%
B4%E4%B8%AD%E5%9B%BD%E9%9D%92%E5%B9%B4%E7%94%9F%E6%B4%BB%E5%BD%A2%E6%80%81%E8%B0%83%E6%9F%A5%E6%8A%A5%E5%91%8A/
新浪科技（2016）。〈魅族試水微博資訊流視頻廣告 單日播放近3000萬〉。上網日期：2015年12月5日，取自http://tech.sina.com.cn/i/2016-02-23/doc-ifxprucs6406298.shtml
新浪微博數據中心（2015）。〈2015微博用戶發展報告〉。上網日期：2016年2月5日，取自http://www.useit.com.cn/thread-10921-1-1.html
新華網（2015）。〈2015年度食品品牌口碑報告〉。上網日期：2016年6月10日，取自http://news.xinhuanet.com/food/2016-03/24/c_1118433550.htm
騰訊企鵝智酷（2015）。〈2015年微信平台資料研究報告〉。上網日期：2016年1月17日，取自http://www.199it.com/archives/324845.html
騰訊企鵝智酷（2015）。〈2015年微信生活白皮書〉。上網日期：2016年1月17日，取自http://www.199it.com/archives/396766.html
騰訊（2016）。〈2015年報〉。上網日期：2016年2月5日，取自http://www.tencent.com/zh-cn/content/ir/rp/2015/attachments/201502.pdf |
| Description: | 碩士
國立政治大學
傳播學院傳播碩士學位學程
103464079 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0103464079 |
| Data Type: | thesis |
| Appears in Collections: | [傳播學院傳播碩士學位學程] 學位論文
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