博碩士論文 109421065 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:62 、訪客IP:18.191.135.193
姓名 張方馨(Fang-Hsin Chang)  查詢紙本館藏   畢業系所 企業管理學系
論文名稱 探討憤怒產品評論的幫助性和影響力---以價格、產品種類為調節變數
(The Effect of Anger Review on Helpfulness of Online Review and Persuasive---Price、Product Type as Moderators)
相關論文
★ 以第四方物流經營模式分析博連資訊科技股份有限公司★ 探討虛擬環境下隱性協調在新產品導入之作用--以電子組裝業為例
★ 動態能力機會擷取機制之研究-以A公司為例★ 探討以價值驅動之商業模式創新-以D公司為例
★ 物聯網行動支付之探討-以Apple Pay與支付寶錢包為例★ 企業資訊方案行銷歷程之探討-以MES為例
★ B2C網路黏著度之探討-以博客來為例★ 組織機制與吸收能力關係之研究-以新產品開發專案為例
★ Revisit the Concept of Exploration and Exploitation★ 臺灣遠距醫療照護系統之發展及營運模式探討
★ 資訊系統與人力資訊科技資源對供應鏈績效影響之研究-買方依賴性的干擾效果★ 資訊科技對知識創造影響之研究-探討社會鑲嵌的中介效果
★ 資訊科技對公司吸收能力影響之研究-以新產品開發專案為例★ 探討買賣雙方鑲嵌關係影響交易績效之機制 ─新產品開發專案為例
★ 資訊技術運用與協調能力和即興能力 對新產品開發績效之影響★ 團隊組成多元性影響任務衝突機制之研究─ 以新產品開發專案團隊為例
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   至系統瀏覽論文 (2024-8-31以後開放)
摘要(中) 隨著線上購物的普及,線上評論也越來越被重視並成功地發揮其功用。消費者也漸漸依賴線上評論來獲取資訊,來幫助降低網路購物上的風險,做出更好的購物決策。在 Anger in Consumer Reviews(Yin 2021)研究中將評論的幫助性與評論的影響力分開探討,提出即使消費者認為評論沒有幫助,但評論對消費者也會有影響。

此篇探討的主題非常新穎,故本研究以此篇延伸探討,了解不同價格和產品種類是否對評論幫助性和評論影響力會有不同的結果。本研究透過實驗設計來驗證憤怒網路評論、價格、產品種類對幫助性和影響力之關係,最後的研究結果也證實,價格和產品種類有顯著的調節效果,當消費者感知風險時,如:購買高單價產品或是經驗品,會產生歸因偏差以趨避風險,因此當有憤怒的產品評論出現時,會增加其幫助性並有負面的影響力。
摘要(英) With the popularity of online shopping, online reviews are increasingly valued and successfully used. Consumers are also increasingly relying on online reviews to obtain information to help reduce risks in online shopping and make better shopping decisions. In the Anger in Consumer Reviews (Yin 2021) study, the helpfulness of reviews and the influence of reviews are separately discussed and it proposed that even if consumers think that reviews are not helpful, reviews will have an impact on consumers.
The topic discussed in this article is very novel. Therefore, our study extends the discussion with this article and understand different prices and products whose impact on the review′s helpfulness and attitude. This study uses an experimental design to verify the relationship between angry online reviews, price, and product type on helpfulness and attitude. The final findings also confirm that price and product type have significant moderating effects. When consumers perceive risks, such as buying high-priced products or experiencing products will generate attribution bias to avoid risks, so when anger reviews appear, it will increase their helpfulness and have a negative impact.
關鍵字(中) ★ 網路評論
★ 負面偏誤
★ 情緒
★ 產品種類
★ 價格
關鍵字(英) ★ Online Reviews
★ negativity bias
★ Emotions
★ product type
★ price
論文目次 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 研究流程.......................................3
第二章 文獻探討.....................................4
2.1 網路評論、負面偏誤...............................4
2.2 憤怒網路評論之幫助性......................... ....5
2.3 網路評論之影響力.................................6
2.4 價格...........................................6
2.5 產品類別................................ .......7
第三章 研究方法......................................8
3.1 研究架構........................................8
3.2 研究假設........................................9
3.3 實驗設計..............................;.........13
3.4 憤怒評論操縱.....................................15
3.5 研究方法.........................................16
第四章 研究結果.......................................17
4.1 敘述型統計分析....................................17
4.2 共變數分析.......................................17
第五章 結論及建議.....................................23
5.1 研究結論.........................................23
5.2 研究貢獻與管理意涵.................................24
5.3 後續研究建議......................................25
參考文獻..............................................26
附錄一 網路評論表.......................................29
附錄二 實驗設計問題......................................31
參考文獻 1. Bae, S., & Lee, T. (2011). Product type and consumers ’ perception of online consumer reviews. Electron Markets, 255–266.
2. Chen, Z., & Lurie, N. H. (2013). Temporal Contiguity and Negativity Bias in the Impact of Online Word of Mouth. Journal of Marketing Research, L(August), 463–476.
3. Dellarocas, C. 2003. "The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms," Management Science (49:10), pp. 1407-1424.
4. Donald R. Lichtenstein, Nancy M. Ridgway and Richard G. Netemeyer.
Price Perceptions and Consumer Shopping Behavior: A Field Study. Journal of Marketing Research Vol. 30, No. 2 (May, 1993), pp. 234-245 (12 pages)
5. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
6. Fiske, Susan T. (1980), "Attention and Weight in Person Perception: The Impact of Negative and Extreme Behavior," Journal of Personality and Social Psychology, 38 (6), 889-906.
7. Gabriel Sperandio Milan1 ,Suélen Bebber2 , Deonir De Toni &LucieneEberle. Information Quality, Distrust and Perceived Risk as Antecedents of Purchase Intention in the Online Purchase Context. Journal of Management Information System & E-commerce . December 2015, Vol. 2, No. 2, pp. 111-129
8. Hao, Y., Ye, Q., Li, Y., & Cheng, Z. (2010). How does the valence of online consumer reviews matter in consumer decision making? Differences between
- 26 -
search goods and experience goods. Proceedings of the Annual Hawaii
International Conference on System Sciences, 1–10.
9. Kamalul Ariffin, S., Mohan, T. and Goh, Y.-N. (2018), "Influence of consumers’
perceived risk on consumers’ online purchase intention", Journal of Research in
Interactive Marketing, Vol. 12 No. 3, pp. 309-327.
10. Leahy, A. S. (2005). Search And Experience Goods: Evidence From The 1960’s
And 70’s. Journal of Applied Business Research (JABR), 21(1).
11. Lee, M., Jeong, M. and Lee, J. (2017), "Roles of negative emotions in customers’
perceived helpfulness of hotel reviews on a user-generated review website: A text mining approach", International Journal of Contemporary Hospitality Management, Vol. 29 No. 2, pp. 762-783.
12. Mudambi, S. M., & Schuff, D. (2010). What Makes a Helpful Online Review? A Study of Customer Reviews on Amazon.com. MIS Quarterly, 34(1), 185–200.
13. Park, Cheol & Lee, Thae Min, 2009. "Information direction, website reputation and eWOM effect: A moderating role of product type," Journal of Business Research, Elsevier, vol. 62(1), pages 61-67, January.
14. Petty, R. E., and Cacioppo, J. T. 1986. "The Elaboration Likelihood Model of Persuasion," in Communication and Persuasion: Central and Peripheral Routes to Attitude Change. New York, NY: Springer New York, pp. 1-24.
15. Philip Fei Wu, In Search of Negativity Bias: An Empirical Study of Perceived Helpfulness of Online Reviews , Psychology and Marketing, Vol. 30(11):971– 984 (November 2013)
16. Richard A. Spreng , Andrea L. Dixon, Richard W. Olshavsky . The Impact of Perceived Value on Consumer Satisfaction. Vol. 6 (1993) : The Journal of Consumer Satisfaction, Dissatisfaction and Complaining Behavior
- 27 -

17. Yin, D., Bond, S. D., & Zhang, H. (2014). Anxious or Angry? Effects of Discrete Emotions on the Perceived Helpfulness of Online Reviews. MIS Quarterly, 38(2), 539–560.
18. Yin, Dezhi and Bond, Samuel and Zhang, Han, Anger in Consumer Reviews: Unhelpful but Persuasive? (2020). MIS Quarterly, Forthcoming, Georgia Tech Scheller College of Business Research Paper No. 3588859, Available at SSRN: https://ssrn.com/abstract=3588859
指導教授 陳炫碩 審核日期 2022-8-1
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明