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題名 行為變遷：以用途理論解讀惠普科技產品創新
Behavioral Shift: Analyzing Hewlett-Packard’s Product Innovation Using Deployment Theory作者 蔡宇晴
Tsai, Yu-Ching貢獻者 蕭瑞麟
Hsiao, Ruey-Lin
蔡宇晴
Tsai, Yu-Ching關鍵詞 行為變遷
環境趨勢
產品創新
創新調適
研發
behavioral shift
environmental trend
product innovation
innovation adaptation
research and development日期 2023 上傳時間 1-Sep-2023 14:51:12 (UTC+8) 摘要 受新冠肺炎疫情與技術進展等環境面的遷移，使用者行為會產生改變，比方說高度電腦使用、居家視訊會議以及各式線上活動逐漸增加。隨著數位化的趨勢，技術彷彿獲得至高無上的地位，以至於各家企業紛紛以技術為中心，展開產品技術創新，卻不知顧客對於產品設計的影響力。行為中藏有需求，然而現行理論的分析僅著重於短期的時間段，缺少對未來行為的探究，也因此難以預測長期的需求。本研究由行為變遷入手，分析環境變化下顧客行為的增減。本研究以惠普科技的三項筆記型電腦部件創新為例，分別闡釋視訊鏡頭、鍵盤以及筆電機殼研發背後的行為變遷、需求變化和創新回應。理論貢獻上，本研究提出行為分析的三項特性：前瞻性、調適性以及趨勢性。這可協助企業觀察用戶行為的變動，預測未來對產品的需求。以實務啟發而言，本研究釐清行為趨勢之於產品創新的重要性。分析行為的消長能辨識需求，為產品研發超前布局。分析行為的變遷能讓研發維持彈性，持續跟上趨勢而與時俱進，才不至於毫無因應之力。快速變動已成市場定局，若要保持競爭力，企業需掌握環境動態，瞭解用戶需求變遷，方能以創新立於不敗之地。
Affected by environmental changes, such as the COVID-19 epidemic and technological advancement, users would shift to new behaviors, such as increased computer use, home video conferencing, and various online activities. With the trend of digitalization, technology seems to have gained supremacy, so that companies have focused on product innovation. However, they rarely pay attention to the influence of consumer behavior on product design. Consumers’ needs are hidden in behavior, but the analysis of current theories majorly focuses on given time periods and explores less of future behavior. This is why it is rather difficult to predict long-term needs for product innovation. This study examines behavioral change and analyzes the increase and decrease of user behavior under environmental changes. This research selected HP`s three component innovations within notebook computer projects to explain the behavioral shifts, demand changes and innovation responses behind the development of video cameras, keyboards, and notebook casings. Theoretically, this study proposes three features of behavioral analysis with regards to prospective, adaptive and trending. The findings could help companies observe variations in usage behaviors and predict future demand for product innovation. In terms of practical implication, this study highlights the importance of behavioral trends analysis in product innovation. The inspection of addition and deduction of usage behavior could identify demand in advance, while preparing for product development. The analysis of behavioral shift allows R&D to maintain flexibility, keep up with market trends, and keep pace with the preference variations timely, so as to avoid ineffective coping. Rapid market changes have become new normal. To maintain competitiveness, enterprises need to become sensitive to environmental jolts and understand the changing needs of users in order to remain invincible through innovation.參考文獻 參考文獻Adner, R. 2017. Ecosystem as structure: An actionable construct for strategy. Journal of Management, 43(1): 39-58.Ajzen, I. 1991. The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2): 179-211.Ariely, D. 2008. Predictably irrational: The hidden forces that shape our decisions. New York: HarperCollins.Baldwin, C., & von Hippel, E. 2011. Modeling a paradigm shift: From producer innovation to user and open collaborative innovation. Organization Science, 22(6): 1399-1417.Beaudry, A., & Pinsonneault, A. 2005. Understanding user responses to information technology: A coping model of user adaption. MIS Quarterly, 29: 493-524.Beckman, S. L., & Barry, M. 2007. Innovation as a learning process: Embedding design thinking. California Management Review, 50(1): 25-56.Borner, K., Berends, H., Deken, F., & Feldberg, F. 2023. Another pathway to complementarity: How users and intermediaries identify and create new combinations in innovation ecosystems. Research Policy, 52(7): 104788.Brannen, M. Y. 2004. When Mickey loses face: Recontextualization, semantic fit, and the semiotics of foreignness. Academy of Management Review, 29(4): 593-616.Cantarella, M., Fraccaroli, N., & Volpe, R. 2023. Does fake news affect voting behaviour? Research Policy, 52(1): 104628.Christensen, C., Hall, T., Dillon, K., & Duncan, D. S. 2016. Competing against luck: The story of innovation and customer choice. HarperBusiness an imprint of HarperCollins Publishers.Claussen, J., Kretschmer, T., & Mayrhofer, P. 2012. The effects of rewarding user engagement: The case of Facebook apps. Information Systems Research, 24.de Jong, J. P. J., Rigtering, C., & Spaans, L. 2023. Heroes of diffusion: Making user innovations widely available. Research Policy, 52(8): 104840.George, J. M., & Bettenhausen, K. L. 1990. Understanding prosocial behavior, sales performance, and turnover: A group-level analysis in a service context. Journal of Applied Psychology, 75: 698-709.Grant, A. M., Dutton, J. E., & Rosso, B. D. 2008. Giving commitment: Employee support programs and the prosocial sensemaking process. Academy of Management Journal, 51(5): 898-918.Hartmann, M. R., & Hartmann, R. K. 2023. Hiding practices in employee-user innovation. Research Policy, 52(4): 104728.Hienerth, C., & Lettl, C. 2011. Exploring how peer communities enable lead user innovations to become standard equipment in the industry: Community pull effects. Journal of Product Innovation Management(1): 175-195.Hsiao, R.-L., Wu, S. W., & Hou, S. T. 2008. Sensitive cabbies: Ongoing sense-making within technology structuring. Information and Organization, 18(4): 251–279.Jaakkola, E., & Alexander, M. 2014. The role of customer engagement behavior in value co-creation: A service system perspective. Journal of Service Research, 17(3): 247-261.Jacobides, M. G., & Reeves, M. 2020. Adapt your business to the new reality. Harvard Business Review, 98(5): 74-81.Jasperson, J., Carter, P. E., & Zmud, R. W. 2005. A comprehensive conceptualization of post-adoptive behaviors associated with information technology enabled work systems. MIS Quarterly, 29(3): 525-557.Jena, S. D., Lodi, A., & Sole, C. 2021. On the estimation of discrete choice models to capture irrational customer behaviors. INFORMS J. Comput., 34: 1606-1625.Karahanna, E., Straub, D. W., & Chervany, N. L. 1999. Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2): 183-213.Koçak, Ö., Hannan, M. T., & Hsu, G. 2013. Emergence of market orders: Audience interaction and vanguard influence. Organization Studies, 35(5): 765-790.Kraatz, M. S., & Zajac, E. J. 2001. How organizational resources affect strategic change and performance in turbulent environments: Theory and evidence. Organization Science, 12(5): 632-657.Lee, K., & Malerba, F. 2017. Catch-up cycles and changes in industrial leadership:Windows of opportunity and responses of firms and countries in the evolution of sectoral systems. Research Policy, 46(2): 338-351.Lilien, G. L., Morrison, P. D., Searls, K., Sonnack, M., & von Hippel, E. 2002. Performance assessment of the lead user idea-generation process for new product development. Management Science, 48(8): 1042-1059.Mahr, D., & Lievens, A. 2012. Virtual lead user communities: Drivers of knowledge creation for innovation. Research Policy, 41(1): 167-177.Mathieson, K. 1991. Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3): 173-191.Moore, J. 1993. Predators and prey: A new ecology of competition. Harvard Business Review, 71(3): 75-86.Newman, M., & Noble, F. 1990. User involvement as an interaction process: A case study. Information Systems Research, 1(1): 89-113.Orlikowski, W. J. 1996. Improvising organizational transformation over time: A situated change perspective. Inf. Syst. Res., 7: 63-92.Powell, E. E., Hamann, R., Bitzer, V., & Baker, T. 2018. Bringing the elephant into the room? Enacting conflict in collective prosocial organizing. Journal of Business Venturing, 33(5): 623-642.Salunke, S., Weerawardena, J., & McColl-Kennedy, J. R. 2013. Competing through service innovation: The role of bricolage and entrepreneurship in project-oriented firms. Journal of Business Research, 66(8): 1085-1097.Siggelkow, N. 2002. Evolution toward fit. Administrative Science Quarterly, 47(1): 125-159.Sokol, M. B. 1994. Adaptation to difficult designs: Facilitating use of new technology. Journal of Business and Psychology, 8(3): 277-296.Thomke, S., & Hippel, E. 2002. Customers as innovators: A new way to create value. Harvard Business Review, 80.Tyre, M., & Orlikowski, W. 1994. Windows of opportunity: Temporal patterns of technological adaptation in organizations. Organization Science, 5(1): 98-118.von Hippel, C. D., & Cann, A. B. 2021. Behavioral innovation: Pilot study and new big data analysis approach in household sector user innovation. Research Policy, 50(8): 103992.von Hippel, E. 1986. Lead users: A source of novel product concepts. Management Science, 32(7): 791-805.von Hippel, E. 2001. Innovation by user communities: Learning from open-source software. Sloan Management Review, 42(4): 82-86.Wan, W. P., & Yiu, D. W. 2009. From crisis to opportunity: environmental jolt, corporate acquisitions, and firm performance. Strategic Management Journal, 30(7): 791-801.Witell, L., Gebauer, H., Jaakkola, E., Hammedi, W., Patricio, L., & Perks, H. 2017. A bricolage perspective on service innovation. Journal of Business Research, 79: 290-298.Yang, M., Ren, Y., & Adomavicius, G. 2019. Understanding user-generated content and customer engagement on Facebook Business Pages. Information Systems Research, 30(3): 839-855.Yu, J., & Zaheer, S. 2010. Building a process model of local adaptation of practices: A study of Six Sigma implementation in Korean and US firms. Journal of International Business Studies, 41(3): 475-499. 描述 碩士
國立政治大學
科技管理與智慧財產研究所
110364121資料來源 http://thesis.lib.nccu.edu.tw/record/#G0110364121 資料類型 thesis dc.contributor.advisor 蕭瑞麟 zh_TW dc.contributor.advisor Hsiao, Ruey-Lin en_US dc.contributor.author (Authors) 蔡宇晴 zh_TW dc.contributor.author (Authors) Tsai, Yu-Ching en_US dc.creator (作者) 蔡宇晴 zh_TW dc.creator (作者) Tsai, Yu-Ching en_US dc.date (日期) 2023 en_US dc.date.accessioned 1-Sep-2023 14:51:12 (UTC+8) - dc.date.available 1-Sep-2023 14:51:12 (UTC+8) - dc.date.issued (上傳時間) 1-Sep-2023 14:51:12 (UTC+8) - dc.identifier (Other Identifiers) G0110364121 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/146878 - 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) 110364121 zh_TW dc.description.abstract (摘要) 受新冠肺炎疫情與技術進展等環境面的遷移，使用者行為會產生改變，比方說高度電腦使用、居家視訊會議以及各式線上活動逐漸增加。隨著數位化的趨勢，技術彷彿獲得至高無上的地位，以至於各家企業紛紛以技術為中心，展開產品技術創新，卻不知顧客對於產品設計的影響力。行為中藏有需求，然而現行理論的分析僅著重於短期的時間段，缺少對未來行為的探究，也因此難以預測長期的需求。本研究由行為變遷入手，分析環境變化下顧客行為的增減。本研究以惠普科技的三項筆記型電腦部件創新為例，分別闡釋視訊鏡頭、鍵盤以及筆電機殼研發背後的行為變遷、需求變化和創新回應。理論貢獻上，本研究提出行為分析的三項特性：前瞻性、調適性以及趨勢性。這可協助企業觀察用戶行為的變動，預測未來對產品的需求。以實務啟發而言，本研究釐清行為趨勢之於產品創新的重要性。分析行為的消長能辨識需求，為產品研發超前布局。分析行為的變遷能讓研發維持彈性，持續跟上趨勢而與時俱進，才不至於毫無因應之力。快速變動已成市場定局，若要保持競爭力，企業需掌握環境動態，瞭解用戶需求變遷，方能以創新立於不敗之地。 zh_TW dc.description.abstract (摘要) Affected by environmental changes, such as the COVID-19 epidemic and technological advancement, users would shift to new behaviors, such as increased computer use, home video conferencing, and various online activities. With the trend of digitalization, technology seems to have gained supremacy, so that companies have focused on product innovation. However, they rarely pay attention to the influence of consumer behavior on product design. Consumers’ needs are hidden in behavior, but the analysis of current theories majorly focuses on given time periods and explores less of future behavior. This is why it is rather difficult to predict long-term needs for product innovation. This study examines behavioral change and analyzes the increase and decrease of user behavior under environmental changes. This research selected HP`s three component innovations within notebook computer projects to explain the behavioral shifts, demand changes and innovation responses behind the development of video cameras, keyboards, and notebook casings. Theoretically, this study proposes three features of behavioral analysis with regards to prospective, adaptive and trending. The findings could help companies observe variations in usage behaviors and predict future demand for product innovation. In terms of practical implication, this study highlights the importance of behavioral trends analysis in product innovation. The inspection of addition and deduction of usage behavior could identify demand in advance, while preparing for product development. The analysis of behavioral shift allows R&D to maintain flexibility, keep up with market trends, and keep pace with the preference variations timely, so as to avoid ineffective coping. Rapid market changes have become new normal. To maintain competitiveness, enterprises need to become sensitive to environmental jolts and understand the changing needs of users in order to remain invincible through innovation. en_US dc.description.tableofcontents 壹、緒論 1第一節 研究動機 1一、實務動機 1二、理論動機 2第二節 研究目的 4一、解讀環境趨勢形成 4二、分析顧客行為增減 4三、識別研發創新關鍵 5第三節 預期效益 5一、理論貢獻 5二、實務貢獻 5三、論文章節佈局 6貳、文獻回顧 8第一節 名詞定義 8一、使用者行為 8二、行為變遷 9三、文獻統整 9第二節 行為涉入觀點 11ㄧ、抗拒行為 11二、用戶參與 12三、同理心設計 13四、用戶共創 14五、不理性行為 15第三節 採納前後行為觀點 16一、採納前後行為 16二、因應調適行為 17三、依據時機的調適行為 18四、在地調適 18五、實踐性調適行為 19第四節 行為變遷觀點 19參、研究方法 21第一節 案例選擇 21一、市場特性快速變化 21二、多元產品技術應用 22三、創新導入長期有成 23第二節 分析架構 23一、分析架構發展 23二、資料分析步驟 24第三節 資料蒐集 26肆、研究發現 28第一節 個人電腦部件的創新 28第二節 鏡頭的創新機會 28一、環境與行為變遷 29（一） 視訊焦慮下的容貌修飾 29（二） 地盤心態下的環境遮蔽 30（三） 他人窺視時的隱私維護 31（四） 科技疑雲下的監視預防 31（五） 科技冷漠下的互動需求 32二、創新功能與用途 32（一） 美顏鏡頭：隱「惡」揚「善」的人性功能 32（二） 濾鏡功能：避免尷尬的遮羞防線 33（三） 智慧辨識：辨識使用者的專業守衛 33（四） 鏡頭遮斷：肉眼可視的貼心防護 34（五） 動作偵測：科技冷漠下的互動需求 35三、內外回饋與影響 36（一） 市場回饋 36（二） 內部影響 37第三節 鍵盤的創新機會 38一、環境與行為變遷 39（一） 輕便易使用的產品形式 39（二） 多工好上手的使用輔助 40（三） 美觀不趨同的外型設計 41（四） 舒適利識讀的視覺條件 41二、創新功能與用途 42（一） 剪刀腳鍵盤：輕薄精確的鍵盤技術 42（二） 多功能按鍵：統整功能的執行輔助 43（三） 彩色系鍵盤：亮眼特別的顏色設計 44（四） 高舒適配色：護眼清晰的對比選擇 45三、內外回饋與影響 45（一） 市場回饋 45（二） 內部影響 47第四節 機殼的創新機會 48一、環境與行為變遷 49（一） 美觀好炫耀的便攜產品 49（二） 強調保護時的美感建構 50（三） 損傷零容忍的品質要求 50（四） 電競潮流下的視覺偏好 51（五） 技術進益下的體驗渴望 52二、創新功能與用途 52（一） 多彩弧形金屬殼：現代時尚的精緻外型 52（二） 質感皮革式機殼：高保護力的溫潤質感 53（三） 軟質加高保險桿：內部損傷的預防方式 53（四） 科技感電競外殼：酷炫特別的全新設計 54（五） 機殼內彈性布局：降低干擾的應對手段 55三、內外回饋與影響 55（一） 市場回饋 55（二） 內部影響 56伍、討論 58第一節 學術貢獻 58一、行為前瞻性 58二、行為調適性 58三、行為趨勢性 59第二節 實務啟發 59一、顧客為企業之本 59二、變遷為創新之始 60三、彈性為市場之策 60第三節 研究限制與未來方向 61一、軟體層面的創新 61二、時空層面的擴增 61三、組織層面的深究 62陸、結論 63參考文獻 64 zh_TW dc.format.extent 2322126 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0110364121 en_US dc.subject (關鍵詞) 行為變遷 zh_TW dc.subject (關鍵詞) 環境趨勢 zh_TW dc.subject (關鍵詞) 產品創新 zh_TW dc.subject (關鍵詞) 創新調適 zh_TW dc.subject (關鍵詞) 研發 zh_TW dc.subject (關鍵詞) behavioral shift en_US dc.subject (關鍵詞) environmental trend en_US dc.subject (關鍵詞) product innovation en_US dc.subject (關鍵詞) innovation adaptation en_US dc.subject (關鍵詞) research and development en_US dc.title (題名) 行為變遷：以用途理論解讀惠普科技產品創新 zh_TW dc.title (題名) Behavioral Shift: Analyzing Hewlett-Packard’s Product Innovation Using Deployment Theory en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 參考文獻Adner, R. 2017. Ecosystem as structure: An actionable construct for strategy. Journal of Management, 43(1): 39-58.Ajzen, I. 1991. The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2): 179-211.Ariely, D. 2008. Predictably irrational: The hidden forces that shape our decisions. New York: HarperCollins.Baldwin, C., & von Hippel, E. 2011. Modeling a paradigm shift: From producer innovation to user and open collaborative innovation. Organization Science, 22(6): 1399-1417.Beaudry, A., & Pinsonneault, A. 2005. Understanding user responses to information technology: A coping model of user adaption. MIS Quarterly, 29: 493-524.Beckman, S. L., & Barry, M. 2007. Innovation as a learning process: Embedding design thinking. California Management Review, 50(1): 25-56.Borner, K., Berends, H., Deken, F., & Feldberg, F. 2023. Another pathway to complementarity: How users and intermediaries identify and create new combinations in innovation ecosystems. Research Policy, 52(7): 104788.Brannen, M. Y. 2004. When Mickey loses face: Recontextualization, semantic fit, and the semiotics of foreignness. Academy of Management Review, 29(4): 593-616.Cantarella, M., Fraccaroli, N., & Volpe, R. 2023. Does fake news affect voting behaviour? Research Policy, 52(1): 104628.Christensen, C., Hall, T., Dillon, K., & Duncan, D. S. 2016. Competing against luck: The story of innovation and customer choice. HarperBusiness an imprint of HarperCollins Publishers.Claussen, J., Kretschmer, T., & Mayrhofer, P. 2012. The effects of rewarding user engagement: The case of Facebook apps. Information Systems Research, 24.de Jong, J. P. J., Rigtering, C., & Spaans, L. 2023. Heroes of diffusion: Making user innovations widely available. Research Policy, 52(8): 104840.George, J. M., & Bettenhausen, K. L. 1990. Understanding prosocial behavior, sales performance, and turnover: A group-level analysis in a service context. 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