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題名 台灣消費者電子商務平台選擇與購物行為之實證研究—快思慢想的全面性決策分析
The Empirical Study of E-Commerce Platform Selection and Purchasing Behaviors of Taiwanese Consumers—The Comprehensive Decision Analysis of Thinking Fast and Slow作者 呂宜臻
呂宜臻Lu, I-Chen貢獻者 許牧彥
Hsu, Mu-Yen
呂宜臻
呂宜臻Lu, I-Chen關鍵詞 網路購物
消費者行為
行為經濟學
快思慢想
Online Shopping
Consumer Behavior
Behavioral Economics
Thinking Fast and Slow日期 2023 上傳時間 3-Oct-2023 10:43:56 (UTC+8) 摘要 隨著網路科技蓬勃發展與普及，網路購物已經成為大眾廣泛使用一種消費模式。電子商務市場的營收持續每年成長，同時在市場上同行間競爭也越來越激烈，各大電商應嘗試深入了解消費者的需求以及決策因素，除了為企業本身提供行銷策略的方向外，推出更符合消費者的優惠與服務，以提升顧客忠誠並做出差異化，強化自身在市場的地位。在過去在研究消費者網路購物行為中，鮮少以行為經濟學觀點來做問卷調查的消費者行為研究。而本研究將以行為經濟學中著名的「快思慢想」觀點出發，來探討消費者在網路購物時的網站平台選擇與購物決策的行為。本研究採問卷調查法，以網路問卷進行發放，最終回收378份問卷，剔除其中14份無效問卷，共有364份有效問卷。本研究的資料分析結果顯示消費者的決策型態傾向慢想，便會不容易固定使用某個購物網站；消費者的決策型態傾向快思，便會更加容易固著在同一個購物網站；損失規避與社會規範能夠作為快思的前置變數；理性決策能夠作為慢想的前置變數；年齡以及職業是否為學生在決策型態傾向快思或慢想上有顯著的差異；年紀越長的消費者在決策思維上會越傾向快思；對一個購物網站的採用與否，周遭其他使用者的使用經驗與口碑會比KOL或明星代言的廣告更有影響力。根據分析結果，本研究建議善用消費者的快思決策，善用促銷活動與推播通知、優惠券與紅利點數累積機制以及個人化的廣告與通知。針對傾向慢想決策的消費者則可以加強自身平台的服務內容，特別是在網站資訊安全的部分，吸引沒有固定使用購物網站的消費者。最後是善用口碑效應，當電商業者想觸及更多未使用族群時，可以善用社群的力量，搭配各式新用戶優惠活動帶動更多人一起使用。
With the flourishing development and widespread adoption of internet technology, online shopping has become a widely used consumption model among the general public. The revenue of the e-commerce market continues to grow annually, and the competition among major e-commerce players in the market has become increasingly fierce. It is crucial for these major e-commerce companies to deeply understand consumer needs and decision-making factors. Apart from providing marketing strategy direction for the businesses themselves, offering more consumer-oriented incentives and services is essential to enhance customer loyalty, create differentiation, and strengthen their market position.In the past, consumer behavior studies related to online shopping rarely approached from the perspective of behavioral economics through questionnaire surveys. This study takes its departure from the perspective of behavioral economics, particularly the well-known "Thinking Fast and Slow" framework, to explore consumer behavior in website platform selection and shopping decision-making during online shopping.This research employs a questionnaire survey method, distributed through online questionnaires. A total of 378 questionnaires were collected, with 14 invalid ones excluded, resulting in 364 valid questionnaires. The data analysis of this study reveals that consumers tend to exhibit slow-thinking decision-making patterns, making it less likely for them to consistently use a single shopping website. Conversely, consumers with a tendency for fast-thinking decision-making are more likely to stick to a single shopping website. Loss aversion and social norms act as antecedents for fast-thinking decisions, while rational decision-making serves as an antecedent for slow-thinking decisions. Age and occupation, specifically whether one is a student, show significant differences in fast-thinking or slow-thinking decision tendencies. Older consumers tend to lean more toward fast-thinking decision patterns. The adoption of a shopping website is more influenced by the usage experiences and word-of-mouth of other users in the vicinity compared to endorsements by key opinion leaders (KOLs) or celebrities.Based on the analysis results, this study recommends leveraging consumers` fast-thinking decisions through promotional activities, push notifications, coupon and loyalty point accumulation mechanisms, and personalized advertisements and notifications. For consumers inclined towards slow-thinking decisions, it`s advised to enhance service content on their platforms, particularly in terms of website information security, to attract consumers who do not have a fixed shopping website. Lastly, capitalizing on the power of word-of-mouth, e-commerce businesses aiming to reach untapped consumer segments can utilize the influence of communities, coupled with various new user incentive activities, to encourage more people to join in.參考文獻 一、中文部分資策會產業情報研究所(MIC)，2022年，零售電商消費者調查系列一，https://mic.iii.org.tw/news.aspx?id=621朱海城 (2019)。電子商務概論與前瞻(第二版)--跨境電商、行動商務、大數據。台北市：碁峰資訊股份有限公司。林琬玲 (2021)。台韓電子商務產業發展趨勢之比較研究（博碩士論文）。中國文化大學，台北市。電商讀書會，2022年，消費者數位洞察，2023電商必須關注的9大趨勢預測！，https://reurl.cc/8jNOxb游韻馨(譯) (2019)。解決所有煩惱的9種靈活思考，台北市：三采文化。(和田 秀樹,2018)張雅萍 (2013)。消費者網路購物滿意度與再購意願之研究-以某網路購物平台為例（博碩士論文）。吳鳳科技大學，嘉義縣。柯均儀 (2013)。母品牌態度、理性購買特質與聯合品牌態度之關係（博碩士論文）。中國文化大學，台北市。鄭尹惠 (2008)。服務創新類型對消費者捷思影響之研究（博碩士論文）。 國立雲林科技大學。雲林縣。沈建良 (2002)。影響網路購物行為的因素-從理性與非理性觀點探討（博碩士論文）。東吳大學，台北市。賴俊達 (2009)。理性與非理性因素對再購意圖影響之研究-以涉入程度為調節變數（博碩士論文）。銘傳大學，台北市。林敬堯(2008)。慣性對轉換意願影響之研究-以行動電話服務為例（博碩士論文）。銘傳大學，台北市。二、英文部分International Trade Administration (ITA).2020.eCommerce Sales & Size Forecast，https://www.trade.gov/ecommerce-sales-size-forecastJeffrey F. Rayport,& Bernard J. Jaworski (2001).Introduction to e-Commerce (1st Edition).New York：McGraw-Hill/Irwin.Kenneth C. Laudon,& Carol Guercio Traver (2017).E-commerce business. technology. society. (13th Edition).New Jersey：Pearson Education.Bernd W. Wirtz,& Nikolai Lihotzky (2003).Customer Retention Management in the B2C Electronic Business.Long Range Planning,Volume 36, Issue 6,517-532.Allan Afuah,& Christopher L. Tucci (2001).Internet Business Models and Strategies (2nd Edition).New York：McGraw-Hill/Irwin.Richard H. Thaler (2016).Misbehaving: The Making of Behavioural Economics.London,UK：Penguin Books.William Samuelson & Richard Zeckhauser (1988).Status quo bias in decision making.Journal of Risk and Uncertainty volume 1, 7–59.Jia Li, Minghui Liu, & Xuan Liu (2016).Why do employees resist knowledge management systems? An empirical study from the status quo bias and inertia perspectives.Computers in Human Behavior,Volume 65,189-200.Daniel Kahneman, & Amos Tversky (1979).Prospect Theory: An Analysis of Decision under Risk.Econometrica, Vol. 47, No. 2 , 263-292.Daniel Kahneman, Jack L. Knetsch, & Richard H. Thaler (1991).Anomalies: The Endowment Effect, Loss Aversion, and Status Quo Bias.The Journal of Economic Perspectives, Vol. 5, No. 1, 193-206.Hee-Woong Kim, & Atreyi Kankanhalli (2009).Investigating User Resistance to Information Systems Implementation: A Status Quo Bias Perspective.MIS Quarterly, Vol. 33, No. 3 , 567-582.Peter G. W. Keen (1981).Information Systems and Organizational Change,Communications of the ACM(24:1), 24-32.Martinko, M. J., Henry, J. W., & Zmud, R. W. (1996). An Attributional Explanation of Individual Resistance to the Introduction of Information Technologies in the Workplace, Behavior & Information Technology (15:5),313-330.James J. Jiang, W. Muhanna,& Gary Klein (2000). User Resistance and Strategies for Promoting Acceptance Across System Types, Information & Management (37:1), 25-36.William Samuelson & Richard Zeckhauser (1988) . Status Quo Bias in Decision Making , Journal of Risk and Uncertainty, vol.1, 7-59.Muzafer Sherif ( 1966 )。The Psychology of Social Norms (1st Edition).New York：Harper and Row.Viswanath Venkatesh, Michael G. Morris, Gordon B. Davis,& Fred D. Davis (2003).User Acceptance of Information Technology: Toward a Unified View,MIS Quarterly, Vol. 27, No. 3 ,425-478.Richard H. Thaler ,& Cass R. Sunstein (2009).Nudge: Improving Decisions About Health, Wealth, and Happiness . London,UK：Penguin Books.Icek Ajzen (1991).The theory of planned behavior,Organizational Behavior and Human Decision Processes,Volume 50, Issue 2,179-211.Teck-Hua Ho, Christopher S. Tang,&David R. Bell (1998).Rational Shopping Behavior and the Option Value of Variable Pricing,Management Science, Vol. 44, No. 12, Part 2 of 2,S145-S160.Kathleen D. Vohs (2006).Self-Regulatory Resources Power the Reflective System: Evidence From Five Domains,Journal of Consumer Psychology,Volume 16, Issue 3,217-223.Fritz Strack ,& Roland Deutsch (2004). Reflective and impulsive determinants of social behavior. , Personality and Social Psychology Review, 8(3), 220-247.Richard N. Cardozo (1965).An Experimental Study of Customer Effort, Expectation, and Satisfaction,Journal of Marketing Research, Vol. 2, No. 3,244-249.Howard, J.A. & Sheth, J.N. (1969) .The Theory of Buyer Behavior. New York：Wiley.Kim, H. W. (2011).The effects of switching costs on user resistance to enterprise systems implementation. IEEE Transactions on Engineering Management, 58(3), 471-482.Greta L. Polites ,& Elena Karahanna (2012).Shackled to the status quo: the inhibiting effects of incumbent system habit, switching costs, and inertia on new system acceptance. MIS quarterly, 21-42.Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425e478.Nunnally, J.C. (1978).Psychometric Theory, New York: McGraw-Hill.Daniel Kahneman (2011).Thinking, Fast and Slow，New York:Farrar, Straus and Giroux.Daniel Kahneman, Amos Tversky(1972).Subjective probability: A judgment of representativeness.Cognitive Psychology,Volume 3, Issue 3,430-454.Bass,F. M. (1969).A New Product Growth Model for Consumer Durables. Management Science, 15, 215-227.Müller-Lyer, FC (1889). "Optische Urteilstäuschungen". Archiv für Physiologie Suppl. 1889: 263–270.Assael, H. (1998). Consumer Behavior and Marketing Action, Cincinnati. OH: Southwestern College Publishing. 描述 碩士
國立政治大學
科技管理與智慧財產研究所
110364115資料來源 http://thesis.lib.nccu.edu.tw/record/#G0110364115 資料類型 thesis dc.contributor.advisor 許牧彥 zh_TW dc.contributor.advisor Hsu, Mu-Yen en_US dc.contributor.author (Authors) 呂宜臻 zh_TW dc.contributor.author (Authors) 呂宜臻Lu, I-Chen en_US dc.creator (作者) 呂宜臻 zh_TW dc.creator (作者) 呂宜臻Lu, I-Chen en_US dc.date (日期) 2023 en_US dc.date.accessioned 3-Oct-2023 10:43:56 (UTC+8) - dc.date.available 3-Oct-2023 10:43:56 (UTC+8) - dc.date.issued (上傳時間) 3-Oct-2023 10:43:56 (UTC+8) - dc.identifier (Other Identifiers) G0110364115 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/147732 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 科技管理與智慧財產研究所 zh_TW dc.description (描述) 110364115 zh_TW dc.description.abstract (摘要) 隨著網路科技蓬勃發展與普及，網路購物已經成為大眾廣泛使用一種消費模式。電子商務市場的營收持續每年成長，同時在市場上同行間競爭也越來越激烈，各大電商應嘗試深入了解消費者的需求以及決策因素，除了為企業本身提供行銷策略的方向外，推出更符合消費者的優惠與服務，以提升顧客忠誠並做出差異化，強化自身在市場的地位。在過去在研究消費者網路購物行為中，鮮少以行為經濟學觀點來做問卷調查的消費者行為研究。而本研究將以行為經濟學中著名的「快思慢想」觀點出發，來探討消費者在網路購物時的網站平台選擇與購物決策的行為。本研究採問卷調查法，以網路問卷進行發放，最終回收378份問卷，剔除其中14份無效問卷，共有364份有效問卷。本研究的資料分析結果顯示消費者的決策型態傾向慢想，便會不容易固定使用某個購物網站；消費者的決策型態傾向快思，便會更加容易固著在同一個購物網站；損失規避與社會規範能夠作為快思的前置變數；理性決策能夠作為慢想的前置變數；年齡以及職業是否為學生在決策型態傾向快思或慢想上有顯著的差異；年紀越長的消費者在決策思維上會越傾向快思；對一個購物網站的採用與否，周遭其他使用者的使用經驗與口碑會比KOL或明星代言的廣告更有影響力。根據分析結果，本研究建議善用消費者的快思決策，善用促銷活動與推播通知、優惠券與紅利點數累積機制以及個人化的廣告與通知。針對傾向慢想決策的消費者則可以加強自身平台的服務內容，特別是在網站資訊安全的部分，吸引沒有固定使用購物網站的消費者。最後是善用口碑效應，當電商業者想觸及更多未使用族群時，可以善用社群的力量，搭配各式新用戶優惠活動帶動更多人一起使用。 zh_TW dc.description.abstract (摘要) With the flourishing development and widespread adoption of internet technology, online shopping has become a widely used consumption model among the general public. The revenue of the e-commerce market continues to grow annually, and the competition among major e-commerce players in the market has become increasingly fierce. It is crucial for these major e-commerce companies to deeply understand consumer needs and decision-making factors. Apart from providing marketing strategy direction for the businesses themselves, offering more consumer-oriented incentives and services is essential to enhance customer loyalty, create differentiation, and strengthen their market position.In the past, consumer behavior studies related to online shopping rarely approached from the perspective of behavioral economics through questionnaire surveys. This study takes its departure from the perspective of behavioral economics, particularly the well-known "Thinking Fast and Slow" framework, to explore consumer behavior in website platform selection and shopping decision-making during online shopping.This research employs a questionnaire survey method, distributed through online questionnaires. A total of 378 questionnaires were collected, with 14 invalid ones excluded, resulting in 364 valid questionnaires. The data analysis of this study reveals that consumers tend to exhibit slow-thinking decision-making patterns, making it less likely for them to consistently use a single shopping website. Conversely, consumers with a tendency for fast-thinking decision-making are more likely to stick to a single shopping website. Loss aversion and social norms act as antecedents for fast-thinking decisions, while rational decision-making serves as an antecedent for slow-thinking decisions. Age and occupation, specifically whether one is a student, show significant differences in fast-thinking or slow-thinking decision tendencies. Older consumers tend to lean more toward fast-thinking decision patterns. The adoption of a shopping website is more influenced by the usage experiences and word-of-mouth of other users in the vicinity compared to endorsements by key opinion leaders (KOLs) or celebrities.Based on the analysis results, this study recommends leveraging consumers` fast-thinking decisions through promotional activities, push notifications, coupon and loyalty point accumulation mechanisms, and personalized advertisements and notifications. For consumers inclined towards slow-thinking decisions, it`s advised to enhance service content on their platforms, particularly in terms of website information security, to attract consumers who do not have a fixed shopping website. Lastly, capitalizing on the power of word-of-mouth, e-commerce businesses aiming to reach untapped consumer segments can utilize the influence of communities, coupled with various new user incentive activities, to encourage more people to join in. en_US dc.description.tableofcontents 第壹章 緒論 9第一節 研究背景與動機 9第二節 研究目的 11第三節 研究流程 11第貳章 文獻探討 13第一節 電子商務概要 13第二節 B2C電子商務 15第三節 傳統經濟學理論 18第四節 理性與非理性 19第五節 行為經濟學理論 20第六節 現狀偏誤 21第七節 輕推 23第八節 創新擴散 24第九節 小結 25第參章 研究方法 26第一節 研究架構與研究假說 26第二節 變數操作型定義與衡量 28第三節 問卷設計 35第四節 資料分析方法 36第肆章 資料分析 37第一節 敘述性統計 35第二節 信度分析 48第三節 邏輯迴歸分析 50第四節 多元迴歸分析 54第伍章 分析結果 61第一節 消費者的決策型態 61第二節 巴斯模型與快思慢想 63第三節 不同的消費族群與快思慢想 64第四節 小結 67第陸章 結論與建議 68第一節 研究結果 68第二節 學術意涵 70第三節 管理意涵 70第四節 研究限制 72參考文獻 74附錄：問卷 78 zh_TW dc.format.extent 16743024 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0110364115 en_US dc.subject (關鍵詞) 網路購物 zh_TW dc.subject (關鍵詞) 消費者行為 zh_TW dc.subject (關鍵詞) 行為經濟學 zh_TW dc.subject (關鍵詞) 快思慢想 zh_TW dc.subject (關鍵詞) Online Shopping en_US dc.subject (關鍵詞) Consumer Behavior en_US dc.subject (關鍵詞) Behavioral Economics en_US dc.subject (關鍵詞) Thinking Fast and Slow en_US dc.title (題名) 台灣消費者電子商務平台選擇與購物行為之實證研究—快思慢想的全面性決策分析 zh_TW dc.title (題名) The Empirical Study of E-Commerce Platform Selection and Purchasing Behaviors of Taiwanese Consumers—The Comprehensive Decision Analysis of Thinking Fast and Slow en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 一、中文部分資策會產業情報研究所(MIC)，2022年，零售電商消費者調查系列一，https://mic.iii.org.tw/news.aspx?id=621朱海城 (2019)。電子商務概論與前瞻(第二版)--跨境電商、行動商務、大數據。台北市：碁峰資訊股份有限公司。林琬玲 (2021)。台韓電子商務產業發展趨勢之比較研究（博碩士論文）。中國文化大學，台北市。電商讀書會，2022年，消費者數位洞察，2023電商必須關注的9大趨勢預測！，https://reurl.cc/8jNOxb游韻馨(譯) (2019)。解決所有煩惱的9種靈活思考，台北市：三采文化。(和田 秀樹,2018)張雅萍 (2013)。消費者網路購物滿意度與再購意願之研究-以某網路購物平台為例（博碩士論文）。吳鳳科技大學，嘉義縣。柯均儀 (2013)。母品牌態度、理性購買特質與聯合品牌態度之關係（博碩士論文）。中國文化大學，台北市。鄭尹惠 (2008)。服務創新類型對消費者捷思影響之研究（博碩士論文）。 國立雲林科技大學。雲林縣。沈建良 (2002)。影響網路購物行為的因素-從理性與非理性觀點探討（博碩士論文）。東吳大學，台北市。賴俊達 (2009)。理性與非理性因素對再購意圖影響之研究-以涉入程度為調節變數（博碩士論文）。銘傳大學，台北市。林敬堯(2008)。慣性對轉換意願影響之研究-以行動電話服務為例（博碩士論文）。銘傳大學，台北市。二、英文部分International Trade Administration (ITA).2020.eCommerce Sales & Size Forecast，https://www.trade.gov/ecommerce-sales-size-forecastJeffrey F. 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