博碩士論文 etd-0725105-145308 詳細資訊


[回到前頁查詢結果 | 重新搜尋]

姓名 吳金山(Chin-Shan Wu) 電子郵件信箱 E-mail 資料不公開
畢業系所 資訊管理學系研究所(Information Management)
畢業學位 博士(Ph.D.) 畢業時期 93學年第2學期
論文名稱(中) 框架效應與定錨效應對電子商務採購行為意圖與估價結果影響之研究
論文名稱(英) The study of framing and anchoring effect on Internet buyers' purchasing intention and price estimates
檔案
  • etd-0725105-145308.pdf
  • 本電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
    請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。
    論文使用權限

    電子論文:校內校外均不公開

    論文語文/頁數 中文/136
    統計 本論文已被瀏覽 5640 次,被下載 0 次
    摘要(中) 隨著網際網路的開放,已使其成為新興的大眾媒體。而網路時代的消費者除了開始在網際網路上蒐集產品資訊外,亦逐漸從實體環境轉移至電子商務平台進行交易。在此一環境下,產品資訊及廣告的呈現方式如何影響消費者的購買意願及其對產品價格的估計便成為一個重要的議題。本研究採用實驗法,針對兩種因資訊呈現方式而可能導致的決策偏誤(bias)進行探討,並分別在這兩個決策偏誤的議題下,各進行兩個實驗。第一個議題是探討決策理論中不同框架效應(framing effect)對消費者購買產品行為意圖的影響。第二個議題則探討網頁中所呈現的錨點對消費者產品價格估計之影響,稱為定錨效應(anchoring effect)。
    在框架效應的實驗中,探討的框架效應包括屬性框架效應、目標框架效應及風險選擇框架效應,三種框架分別配合正負面兩種資訊表述方式,形成不同的框架訊息內容。此外,本研究依據受測者與實驗標的物的本質自我相關程度,將其分為高低程度兩組,以瞭解本質自我相關程度是否在框架效應中扮演調節變數的角色。
    在定錨效應的實驗中,除了考慮高�低錨點值對受測者價格估計判斷之影響,同時亦探討錨點運作方式(雙向�單向)、錨點強化作用(強化�一般)、以及錨點訊息與估計標的物之間的語意相關性(相關�不相關)等三個變數,是否會扮演錨點類型對決策者估計影響之調節角色。
    研究結果發現,屬性框架效應是很穩定的框架效應,且不會受本質自我相關程度之影響;至於目標及風險選擇框架效應,則會因受測者與研究議題之本質自我相關程度而有所差異。其中,本質自我相關程度較高者,較不會受到框架訊息的影響而發生框架效應;相反地,大部份自我相關程度較低的受測者,會因為框架訊息的操弄而有不同的購買意願或選擇,而呈現框架效應的現象。
    此外,本研究驗證了定錨效應的穩健性。無論是以單向或雙向作業方式運作,高低錨點組受測者的價格估計皆有顯著差異。本研究亦發現,錨點訊息與估計標的物之相關性會調節定錨效應,只有在錨點訊息具有相關性時,才會發生定錨效應。至於錨點強化作用對定錨效應之調節作用,則視錨點運作方式而有所差異。亦即,當錨點以雙向作業方式運作時,無論錨點是否強化,皆會發生定錨效應,而只有在錨點以單向作業方式運作時,錨點強化作用才會調節定錨效應,且只有在錨點重覆出現的情況下,定錨效應才會發生。
    本研究的結果不僅可作為後續學術研究上的參考,在實務上亦有一定程度的貢獻。
    摘要(英) Internet has become a new form of mass media since its commercialization in early 1990’s. While the transaction platform moves from bricks-and-motar to Internet, potential factors that influence consumers’ purchase decisions changed. Because they cannot touch the product and interact with sales person, Internet buyers can only make decisions based on information presented on web pages. Under this circumstance, how the presentation of information such as advertisement and product description influence consumers’ buying decision is an important issue.
    When the information is presented in different ways, people might make biased decisions. This study conducts four laboratory experiments which aim to investigate two decision biases in e-commerce context: framing effect and ancoring effect. The first two experiments focus on the framing effect and the last two experiments focus on the anchoring effect. Framing effect refers to the situation in which people’s buying intention is influenced by different framing messages. Anchoring effect center on the situation in which people’s price estimates are influenced by different anchor points presented in web pages.
    Three different kinds of framing messages which are formed by combining the attribute framing, goal framing and risky choice framing message and positive and negative presentation are considered in the first two experiments. Moreover, the subjects were assigned into two groups in different level of intrinsic self-relevence to understand whether it plays the moderating role in framing effect.
    In anchoring effect, in addition to the influence of high and low anchor points on subjects’ price estimates, we also consider the moderating role of the operation of anchor points (one-way/two way), the reinforcement of anchor points (normal/intensified), and the relevancy between anchor and target (relevant/unrelevant).
    The results indicated that attribute framing effect is stable and is not influenced by subjects’ level of intrinsic self-relevance, whereas the occurrence of goal framing effect and risky choice framing effect depends on the participants’ level of intrinsic self-relevance. For subjects low in intrinsic self-relevance are more influenced by framing message and thus results in different buying intention or choices than those high in intrinsic self-relevance.
    This study also test and verify the robustness of anchoring effect. Estimaes made by participants in high and low anchor conditions is significantly different no matter the anchor is manipulated in one-way or two-way. In addition, the result of anchoring experiment supports the argument that the relevancy between anchor and target is important for the occurrence of anchoring effect. The moderating effect of anchor reinceforcement depends on the anchor was operated in one-way or two way condition. Anchoring effect is stable despite that the anchor is manipulated in normal or intensified condition when the anchor is manipulated in two-way. On the other hand, when the anchoring effect is manipulated in one-way condition, the anchor reinceforcement plays the role the moderator. Anchoring effect can be observed only when the anchor point is reinforced by appearing for three times.
    This study serves as a foundation for future study in e-commerce area. The procedures and experimental designs in this study can be either replicated or modified with a different sample to gather further evidence for the results discovered. Further, it can benefit practitioners in improving the design of e-commerce interfaces in real world applications.
    關鍵字(中)
  • 電子商務
  • 實驗法
  • 行為決策
  • 框架效應
  • 定錨效應
  • 關鍵字(英)
  • experiment
  • anchoring effect
  • e-commerce
  • decision making
  • framing effect
  • 論文目次 摘要 I
    Abstract III
    誌謝 V
    第一章 緒論 1
    第一節 研究背景 1
    第二節 研究動機與目的 6
    第三節 論文架構 8
    第二章 文獻探討 9
    第一節 框架效應 12
    第二節 影響框架效應發生之因素 18
    第三節 定錨效應 22
    第四節 影響定錨效應之因素 27
    第五節 定錨研究中的價格估計問題 32
    第六節 電子商務相關研究 33
    第七節 網路廣告對消費者決策之影響 37
    第三章 研究設計 39
    第一節 實驗一 41
    第二節 實驗二 48
    第三節 實驗三 52
    第四節 實驗四 62
    第四章 資料分析 66
    第一節 實驗一 66
    第二節 實驗二 69
    第三節 框架效應小結 72
    第四節 實驗三 77
    第五節 實驗四 90
    第六節 定錨效應小結 98
    第五章 結論 102
    第一節 結論 102
    第二節 實務及學術貢獻 105
    第三節 研究限制 107
    參考文獻 108
    參考文獻 1. Abelson, R.P. and A. Levi (1985), “Decision Making and Decision Theory,” in G. Lindzey and E. Aronson (Eds.), Handbook of Social Psychology, NY: Random House.
    2. Agarwal, R. and V. Venkatesh (2002), “Assessing a Firm’s Web Presence: A Heuristic Evaluation Procedure for the Measurement of Usability,” Information Systems Research, Vol. 13, No. 2, pp. 168-186.
    3. Alba, J., J. Lynch, B. Weitz, C. Janiszewski, R. Lutz, A. Sawyer, and S. Wood (1997), “Interactive Home Shopping: Consumer, Retailer, and Manufacturer Incentives to Participate in Electronic Marketplaces,” Journal of Marketing, Vol. 61, July, pp. 38-53.
    4. Anderson, N. H. (1968), A Simple Model for Information Integration, in R.P. Abelson, E. Aronson, W.J. McGuire, T.M. Newcomb, M.J. Rosenberg and P.H. Tannenbaum (Eds.), Theories of Cognitive Consistency: A Sourcebook, Chicago, Illinois: Rand McNally.
    5. Ba, S. (2002), “Evidence of the Effect of Trust Building Technology in Electronic Markets: Price Premiums and Buyer Behavior,” MIS Quarterly, Vol. 26, No. 3, pp. 245-268.
    6. Bar-Hillel, M. (1973), “On the Subjective Probability of Compound Events,” Organizational Behavior and Human Decision Processes, Vol. 9, pp.396-406.
    7. Beam, C. and A. Segev (1996), “Electronic Catalogs and Negotiation,” CITM 96-WP-1016, Fisher Center for Information Technology Management, University of California at Berkeley, August. http://haas.berkeley.edu/~citm/wp-1016-summary.html
    8. Berkeley, D. and P. Humphreys (1982), Structuring Decision Problems and the Bias Heuristic, Acta Psychology, Vol. 50, pp. 201-252.
    9. Bhatnagar, A. and P. Papatla (2001), “Identifying Locations for Targeted Advertising on the Internet,’ International Journal of Electronic Commerce, Vol. 5, No. 3, pp.23-44.
    10. Brewer, M.B. and R.M. Kramer (1986), “Choice Behavior in Social Dilemmas: Effects of Social Identity, Group Size, and Decision Framing,” Journal of Personality and Social Psychology, Vol.50, pp. 543-549.
    11. Brewer, T. and G. B. Chapman (2002), “The Fragile Basic Anchoring Effect,” Journal of Behavioral Decision Making, Vol. 15, pp.65-77.
    12. Burgoon, M. (1989). The Effects of Message Variables on Opinion and Attitude Change, in J. Bradac (ed.), Messages in Communication Sciences: Contemporary Approaches to the Study of Effects, Newbury Park, CA: Sage, pp. 129-164.
    13. Busemeyer, J. R. and W.M. Goldstein (1992), “Linking Together Different Measures of Preference: a Dynamic Model of Matching Derived from Decision Field Theory,” Organizational Behavior and Human Decision Processes, Vol. 52, pp. 370-396.
    14. Cervone, D. and P. K. Peake (1986), “Anchoring, Efficacy, and Action: the Influence of Judgmental Heuristics and Self-Efficacy Judgments and Behavior,” Journal of Personality and Social Psychology, Vol. 50, pp. 492 – 501.
    15. Chaiken, S. (1980), “Heuristic versus Systematic Information Processing and the Use of Source versus Message Cues in Persuasion,” Journal of Personality and Social Psychology, Vol. 39, pp.752-766.
    16. Chaiken, S. (1987), “The Heuristic Model of Persuasion,” Social Influence: The Ontario symposium, Vol. 5, pp. 3-39, Hillsdale, NJ: Lawrence Erlbaum.
    17. Chapman G.B. and E.J. Johnson (2000), “Incorporating the Irrelevant: Anchors in Judgments of Belief and Value,” in Gilovich, T., Griffin, D.W. and Kahneman D. (Eds), The Psychology of Intuitive Judgment: Heuristics and Biases, NY: Cambridge University Press.
    18. Chapman, G. B. and B. H. Bornstein (1996), “The More You Ask For, The More You Get: Anchoring in Personal Injury Verdicts,” Applied Cognitive Psychology, Vol. 10, pp. 519-540.
    19. Chapman, G. B. and E. J. Johnson (1994), “The Limits of Anchoring,” Journal of Behavioral Decision Making, Vol. 7, pp. 223-242.
    20. Chapman, G. B. and E. J. Johnson (1999), “Anchoring, Cctivation and the Construction of Values,” Organizational Behaviors and Human Decision Processes, Vol. 79, No. 2, pp.115-153.
    21. Danaher, P.J. and G.W. Mullarkey (2003), “Factors Affecting Online Advertising Recall: A Study of Students,” Journal of Advertising Research, September, pp.252-267.
    22. Davis, H. L., S. J. Hoch, and E. E. Ragsdale (1986), “An Anchoring and Adjustment Model of Spousal Predictions,” Journal of Consumer Research, Vol. 13, pp. 25-37.
    23. Dunegan, K.J. (1993), “Framing, Cognitive Modes, and Image Theory: Toward an Understanding of a Glass Half Full,” Journal of Applied Psychology, Vol. 78, pp. 79-86.
    24. Dunegan, K.J. (1996), “Fines, Frames and Images: Examining Formulation Effects on Punishment Decisions,” Organizational Behavior and Human Decision Processes, Vol. 68, pp. 58-67.
    25. Dunegan, K.J., D. Duchon, and D. Ashmos (1995) “Image Compatibility and the Use of Problem Space Information in Resource Allocation Decisions: Testing a Moderating Effects Model,” Organizational Behavior and Human Decision Processes, Vol. 64, pp. 31-37.
    26. Dworman, G.O., S.O. Kimbrough, and J.D. Laing (1995), “On Automated Discovery of Models Using Genetic Programming: Bargaining in a Three Agent Coalition Game,” Journal of Management Information Systems, Vol. 12, No. 3, pp. 97-125.
    27. Edwards, W. (1954), “The Theory of Decision Making,” Psychological Bulletin, Vol. 51, pp. 380-417.
    28. Engel, J.F. and R.D. Blackwell (1982), Consumer Behavior, 4th Edition, NY: The Dryden Press.
    29. Fagley, N.S. and P.M. Miller (1990), “The Effect of Framing on Choice: Interactions with Risk-Taking Propensity, Cognitive Style, and Sex,” Personality and Social Psychology Bulletin, Vol. 16, pp. 496-510.
    30. Festinger, L. (1954), “A Theory of Social Comparision Processes,” Human Relations, Vol. 7, pp.117-140.
    31. Fischhoff, B. (1975), “Hindsight ≠ Foresight: The Effect of Outcome Knowledge on Judgment under Uncertainty,” Journal of Experimental Psychology: Human Perception and Performance, Vol. 1, pp. 288 – 299.
    32. Fleischman, J.A. (1988), “The Effects of Decision Framing and Others’ Behavior on Cooperation in a Social Dilemma,” Journal of Conflict Resolution, Vol. 32, pp. 162-180.
    33. Friedlander, M. L. and S. J. Stockman (1983), “Anchoring and Publicity Effects in Clinical Judgment,” Journal of Clinical Psychology, Vol. 39, pp. 637–643.
    34. Ganzach, Y. and N. Karsahi (1995), “Message Framing and Buying Behavior: A Field Experiment,” Journal of Business Research, Vol. 32, pp. 11–17.
    35. Gilbert, D. T. (1991), “How Mental Systems Believe,” The American Psychologist, Vol. 46, pp. 107-119.
    36. Gilovich, T. (1991), How We Know What Isn’t So, NY: Free Press.
    37. Glazer, R. (1991), “Marketing in an Information-Intensive Environment: Strategic Implications of Knowledge as an Asset,” Journal of Marketing, Vol. 55, October, pp. 1-19.
    38. Grewal, D., J. Gotlieb, and H. Marmorstein (1994), “The Moderating Effects of Message Framing and Source Credibility on the Price-Perceived Risk Relationship,” Journal of Consumer Research, Vol. 21, pp. 145-153.
    39. Hair, J., R. Anderson, R. Tatham and W. Black (1998), Multivariate Data Analysis, NJ: Prentice Hall.
    40. Helson, H. (1964), Adaptation Level Theory: An Experimental and Systemantic Approach to Behavior, NY: Harper.
    41. Herr, P. M. (1989), “Priming Price: Prior Knowledge and Context Effects,” Journal of Consumer Research, Vol. 16, June, pp.67-75.
    42. Highhouse, S. and P. Yuce (1996), “Perspectives, Perceptions, and Risk-Taking Behavior,” Organizational Behavior and Human Decision Processes, Vol. 65, pp. 159-167.
    43. Highhouse, S. and P.W. Pease (1996), “Problem Domain and Prospect Frame: Choice under Opportunity versus Threat,” Personality and Social Psychology Bulletin, Vol. 22, pp.124-132.
    44. Hinsz, V. B., L. R. Kalnbach, and N. R. Lorentz (1997), “Using Judgmental Anchors to Establish Challenging Self-set Goals without Jeopardizing Commitment,” Organizational Behavior and Human Decision Processes, Vol. 71, pp. 287 – 308.
    45. Hoffman, D. and T. Novak (2000), “Advertising Pricing Models for the World Wide Web,” in Hurley, D. Kahn, B. and Varian, H. Eds., Internet Publishing and Beyond: The Economics of Digital Information and Intellectual Property, Cambridge, MA: MIT Press.
    46. Hoffman, D.L. and T.P. Novak (1996), “Marketing in Hypermedia Computer-Mediated Environments: Conceptual Foundations,” Journal of Marketing, Vol. 60, July, pp.50-68.
    47. Hogarth, R. M. (1987), Judgment and Choice: The Psychology of Decision, 2nd Edition, Wiley-Interscience Publication.
    48. Homer, P. M. and S.G. Yoon (1992), “Message Framing and the Interrelationships among Ad-Based Feelings, Affect, and Cognition,” Journal of Advertising, Vol. XXI, pp. 19-32.
    49. Huang, M. H. (2000), “Information Load: its Relationship to Online Exploratory and Shopping Behavior,” International Journal of Information Management, Vol. 20, pp. 337-347.
    50. Irwin, F. W. (1953), "Stated Expectations as Functions of Probability and Desirability of Outcomes," Journal of Personality, Vol. 21, pp. 329-335.
    51. Jacowitz, K.E. and D. Kahneman (1995), “Measures of Anchoring in Estimation Tasks,” Personality and Social Psychology Bulletin, Vol. 21, pp. 1161-1166.
    52. Johnson, B. T. and A. H. Eagly (1989), “Effects of Involvement on Persuasion: A Meta-Analysis,” Psychological Bulletin, Vol. 2, pp. 290-314.
    53. Johnson, R. D. (1987), “Making Judgments when Information is Missing: Inferences, Biases, and Framing Effects,” Acta Psychologica, Vol. 66, pp. 69-82.
    54. Joyce, E. and G. Biddle (1981), “Anchoring and Adjustment in Probabilistic Inference in Auditing,” Journal of Accounting Research, Vol. 19, pp. 120-145.
    55. Jupiter Media Metrix (2002), http://www.newsbytes.com/cgi-bin/udt/im.display.printable?client.id=newsbtytes&story.id=175015/.
    56. Kahneman, D. and A. Tversky (1973), “On the Psychology of Prediction,” Psychological Review, Vol. 80, pp. 237.
    57. Kahneman, D. and A. Tversky (1979), “Prospect Theory: An Analysis of Decision under Risk,” Econometrica, Vol. 47, pp. 263–291.
    58. Kahneman, D. and A. Tversky (1990), Prospect Theory: An Analysis of Decision under Risk, in Moser, P.K. Eds., Rationality in Action: Contemporary Approaches, NY: Cambridge University Press, pp.140-170.
    59. Kahneman, D. and A. Tversky, (1972), "Subjective Probability: A Judgment of Representativeness," Cognitive Psychology, Vol. 3, pp. 430-454.
    60. Kahneman, D. and D. T. Miller (1986), “Norm Theory: Comparing Reality to Its Alternatives,” Psychological Review, Vol. 93, pp.136-153.
    61. Kahneman, D. and J. Knetsch (1993), Strong Influences and Schallow Inferences: An Analysis of Some Anchoring Effects, Unpublished Manuscript, University of California, Berkeley.
    62. Kahnemen, D. and A. Tversky (2000), Choices, Values, and Frames, Cambridge: Cambridge University Press.
    63. Kang, J.Y. and E. S. Lee (1998), “A Negotiation Model in Electronic Commerce to Reflect Multiple Transaction Factors and Learning”, IEEE, pp.275-278.
    64. Kanouse, D. E. (1984), “Explaining Negativity Biases in Evaluation and Choice Behavior: Theory and Research,” Advances in Consumer Research, Vol. 11, pp. 703-708.
    65. Kramer, R. M. (1989), “Windows of Vulnerability or Cognitive Illusions? Cognitive Processes and the Nuclear Arms Race,” Journal of Experimental Social Psychology, Vol. 25, pp. 79-100.
    66. Krishnamurthy, P., P. Carter, and E. Blair (2001), “Attribute Framing and Goal Framing Effects in Health Decisions,” Organizational Behavior and Human Decision Processes, Vol. 85, No.2, pp. 382–399.
    67. Kristensen, H. and T. G
    口試委員
  • 陳鴻基 - 召集委員
  • 劉書助 - 委員
  • 吳仁和 - 委員
  • 郭峰淵 - 委員
  • 林信惠 - 指導教授
  • 口試日期 2005-07-08 繳交日期 2005-07-25

    [回到前頁查詢結果 | 重新搜尋]


    如有任何問題請與論文審查小組聯繫