English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113318/144297 (79%)
Visitors : 51024149      Online Users : 905
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/136687


    Title: 我國醫療諮詢平台設計與營運之影響因素探討-以醫聯網為例
    Exploring the Influencing Factors of Online Medical Consulting Platform Strategies and Operation in Taiwan—the Case of MED-NET
    Authors: 許睿哲
    Hsu, Jui-Che
    Contributors: 吳豐祥
    Wu, Feng-Shang
    許睿哲
    Hsu, Jui-Che
    Keywords: 醫療諮詢平台
    平台
    雙邊市場
    網路效應
    關鍵考量因素
    諮詢服務品質
    知識管理策略
    平台績效
    Medical consulting platform
    Platform business model
    Two-sided markets
    Network effect
    Key considerations
    Quality of consultation
    Knowledge management strategies
    Platform performance
    Date: 2021
    Issue Date: 2021-08-04 16:27:28 (UTC+8)
    Abstract: 2019年新冠肺炎(COVID-19)爆發,病毒高度的傳染力,使各國開始封城或者限制人民的活動以避免群聚感染,也因此大幅改變人們的行為模式,更催生了各種「零接觸」的需求。而在醫療領域,「遠距醫療」成為疫情期間民眾接觸醫療資源的重要途徑,以減少不必要的外出以及風險,其中醫療諮詢平台打破地理及時間的限制,透過平台模式讓民眾及專業的醫療人員可以直接互動,幫助民眾在就診前後對自己的健康狀況更加了解。然而醫療服務與一般服務具有諸多不同的地方,包括政府高度管制、高度資訊不對稱、治療的不確定性等,使得平台經營者在設計醫療平台時需有不同的考量因素。本研究的主要目的即是探討醫療諮詢平台的設計與營運之重要考量因素。
    本研究以國內一間規模最大的醫療諮詢平台做為研究對象,透過質性個案研究的方式,深入訪談平台經營者以及在平台上服務的醫師,以實際瞭解醫療諮詢平台在擬定策略與營運活動時,特別考量的因素,以及其作為對於平台績效的影響。本研究最後所得到的主要結論如下:
    (1)醫療諮詢平台啟動營運時,會先考量與既有的醫療服務連結,並透過供給端(醫師)與需求端(消費者)的共同演化,來突破「雞生蛋、蛋生雞」的挑戰。
    (2)醫療諮詢平台的主要補貼方會是醫師及「一般」諮詢者,尤其著重於前者。而付費方則為「指定」諮詢者,平台在相關的定價上會尊重醫師自行專業判斷的價值而定。
    (3)醫療諮詢平台會因服務需求者的目的性,而更加聚焦於專業知識的提供以及與詢問者的互動,以期達到良好的醫病關係。
    (4)醫療諮詢平台的知識管理策略,在考量醫療知識複雜性及醫療不確定性等因素之下,會以個人化策略為主,整理化策略為輔。其中前者會強調外部供需媒合的精準度,而後者則會著重於民眾重複問題的探索與歸類。
    (5)醫療諮詢平台會透過大量資料的匯聚與學習循環,來創造資訊的網路外部性,並發揮知識管理策略的互補性之效益。
    (6)醫療諮詢平台考量到民眾問題的明確度對醫師回覆意願的影響,因而會引導民眾釋放更多的信息,除了提高醫師回覆意願之外,也可以降低醫師診療的不確定性,並提升諮詢服務的品質。
    (7)醫療諮詢平台會透過跨域性的運作,來提升醫師科別多樣性、醫師數量及服務品質,並使其成為吸引消費者的關鍵因素。也會透過不同資訊豐富度的諮詢方式之提供,來滿足不同發問者的需求。
    (8)醫療諮詢平台的詢問者之問題流量與問題品質以及平台的合法性會是吸引醫師的關鍵因素,而醫師也會藉此營運來滿足其自身的好奇心、公益心、以及建立品牌的企圖心。此外,考量到醫療服務品質對平台口碑的影響,平台也會透過對醫師用戶的過濾機制,來維持平台整體的諮詢品質,並藉由醫師服務的口碑帶動民眾對平台的信任,以增進跨邊的網路效應。
    (9)醫療諮詢平台營運的網路效應,除了會受到使用者用戶數的影響之外,也會受到服務品質的影響,因而使得平台經營者會同時重視用戶數、科別多樣性、功能多樣性、回覆速度,以及諮詢品質等兼具質與量的營運考量因素。

    本研究最後並提出學術上與實務上的貢獻,以及對後續研究者的建議。
    In 2019, the outbreak of the coronavirus(COVID-19)which is highly contagious cause countries to lock down cities and restrict people’s activities to avoid cluster infection. This has also greatly changed people’s behavior and the business of "zero-contact". In the medical field, “telemedicine” that allow people to reduce unnecessary contact has become an important way for people to access medical resources during the epidemic. Among telemedicine, medical consulting platform could break geographical and time constraints, and provide public and professional service providers to interact directly for helping people better understand their health conditions before or after seeing a doctor. However, there are many differences between medical services and general services, including high government regulation, high information asymmetry, and uncertainty in treatment, which make platform operators have different considerations when designing a medical platform. The main purpose of this research is to explore the key factors when designing and operating the medical consulting platform.
    This study selected one of the largest domestic medical consulting platforms as the research subject, and interviewed with platform operators and doctors in order to understand the factors that the medical consulting platform took into consideration when developing strategies and operating activities. The main conclusions obtained at the end of this study are as follows:
    (1)During the launch period of medical consulting platform, it will consider to connect with existing medical services first, and make the co-evolution of the supply side (physicians) and the demand side(consumers)to break through the challenge of "chickens and eggs" problem.
    (2)The main subsidies of the medical consulting platform will be physicians and "general" consultants, with emphasis on the former. The paying party is the consultee who choose the doctor by designation, and the platform’s consultation pricing will respect doctor’s judgement of their own value.
    (3)The medical consulting platform will focus on the provision of professional knowledge and the interaction between doctors and service demanders who usually have some purpose, in order to achieve a good medical-patient relationship.
    (4)The knowledge management strategy of the medical consulting platform will be based on personalization strategy, and supplemented by codification strategy by taking into account the complexity of medical knowledge and medical uncertainty. The former will emphasize the accuracy of every matching, while the latter will focus on the exploration and classification of repeated problem among the people.
    (5)The medical consulting platform will create network externalities of information to leverage the complementary benefits of knowledge management strategies through the aggregation of a large amount of data and learning cycles.
    (6)The medical consulting platform takes into account the impact of the clarity of the public’s questions on the doctor’s willingness to respond, and will guide the public to release more information, which can reduce the uncertainty of the doctor’s diagnosis and can improve the service quality of consultation.
    (7)The medical consulting platform will improve the diversity of physician’s divisions, the number of physicians, and the quality of services through cross-domain operation, and make it a key factor in attracting consumers. It will also meet the needs of different questioners through the provision of different consultation methods
    (8)The key factors to attract doctors will be the amount and quality of users’ question and the legitimacy of the platform. Its way of operating will also satisfy doctors’ curiosity, public-spiritedness, and ambition to build a brand. In addition, considering the impact of the quality of medical services on the brand equity of the platform, the filtering mechanism of doctor users will also be used to maintain the overall consulting quality of the platform. The brand equity of the doctor`s services will drive the public`s trust in the platform to enhance the positive cross network effect.
    (9)The network effect of consulting platform operation is not only influenced by the number of users, but also by the quality of service. These may make the operator to optimize the number of users, various divisions, various functions, waiting time, and quality of consultation, which considering both quality and quantity.
    At last but not least, this study provides both academic and practical contribution, as well as suggestions for follow-up researchers.
    Reference: 英文文獻
    Almathami, H. K. Y., Win, K. T., & Vlahu-Gjorgievska, E.(2020). Barriers and facilitators that influence telemedicine-based, real-time, online consultation at patients’ homes: systematic literature review. Journal of Medical Internet Research, 22(2), e16407.

    Babbie, E. R.(2020). The Practice of Social Research. Cengage learning.

    Beckman, T.(1997). Implementing the knowledge organization in government. Paper and Presentation, 10th National Conference on Federal Quality,

    Berry, L. L., & Bendapudi, N.(2007). Health care: a fertile field for service research. Journal of Service Research, 10(2), 111-122.

    Bonchek, M., & Choudary, S. P.(2013). Three elements of a successful platform strategy. Harvard Business Review, 92(1-2).

    Choudary, S. P., Parker, G. G., & Van Alstyne, M.(2015). Platform Scale: How an Emerging Business Model Helps Startups Build Large Empires with Minimum Investment. Platform Thinking Labs.

    Contractor, F. J., & Ra, W.(2002). How knowledge attributes influence alliance governance choices: a theory development note. Journal of International Management, 8(1), 11-27.

    Cusumano, M.(2010). Technology strategy and management.The evolution of platform thinking. Commun. ACM, 53(1), 32–34. https://doi.org/10.1145/1629175.1629189

    Cusumano, M. A., & Gawer, A.(2002). The elements of platform leadership. MIT Sloan Management Review, 43(3), 51.

    Cusumano, M. A., Gawer, A., & Yoffie, D. B.(2019). The Business of Platforms: Strategy in the Age of Digital Competition, Innovation, and Power. . Harper Business.

    Davenport, T. H., & Prusak, L.(1998). Working Knowledge: How Organizations Manage What They Know. Harvard Business Press.

    Eisenmann, T., Parker, G., & Van Alstyne, M.(2011). Platform envelopment. Strategic Management Journal, 32(12), 1270-1285.

    Eisenmann, T., Parker, G., & Van Alstyne, M. W.(2006). Strategies for two-sided markets. Harvard Business Review, 84(10), 92.

    Eisenmann, T. R.(2006). Platform-mediated networks: definitions and core concepts.

    Evans, D. S.(2009). How catalysts ignite: the economics of platform-based start-ups. Platforms, Markets and innovation, 416.

    Evans, D. S., & Schmalensee, R.(2005). The industrial organization of markets with two-sided platforms.

    Evans, D. S., & Schmalensee, R.(2016). Matchmakers: The new economics of multisided platforms. Harvard Business Review Press.

    Fitzsimmons, J. A., Fitzsimmons, M. J., & Bordoloi, S.(2008). Service Management: Operations, Strategy, and Information Technology. McGraw-Hill New York.

    Fu, W., Wang, Q., & Zhao, X.(2018). Platform-based service innovation and system design: a literature review. Industrial Management & Data Systems.

    Gawer, A., & Cusumano, M. A.(2014). Industry platforms and ecosystem innovation. Journal of Product Innovation Management, 31(3), 417-433. https://doi.org/10.1111/jpim.12105

    Hagiu, A.(2015). Strategic decisions for multisided platforms. Top, 10, 4-13.

    Hagiu, A., & Rothman, S.(2016). Network effects aren’t enough. Harvard Business Review, 94(4), 64-71.

    Hagiu, A., & Wright, J.(2015). Multi-sided platforms. International Journal of Industrial Organization, 43, 162-174.

    Hansen, M. T., Nohria, N., & Tierney, T.(1999). What’s your strategy for managing knowledge. The Knowledge Management Yearbook 2000–2001, 77(2), 106-116.

    Harper, F. M., Raban, D., Rafaeli, S., & Konstan, J. A.(2008). Predictors of answer quality in online Q&A sites. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems,

    Katz, M. L., & Shapiro, C.(1985). Network externalities, competition, and compatibility. The American Economic Review, 75(3), 424-440.

    Katz, M. L., & Shapiro, C.(1986). Technology adoption in the presence of network externalities. Journal of Political Economy, 94(4), 822-841.

    Korhonen, H. M., Still, K., Seppänen, M., Kumpulainen, M., Suominen, A., & Valkokari, K.(2017). The core interaction of platforms: How startups connect users and producers. Technology Innovation Management Review, 7(9), 17-29.

    McIntyre, D. P., & Chintakananda, A.(2014). Competing in network markets: Can the winner take all? Business Horizons, 57(1), 117-125.

    Meyer, M. H., & Lehnerd, A. P.(1997). The Power of Product Platforms. Simon and Schuster.

    Nonaka, I., & Takeuchi, H.(1995). The Knowledge-Creating Company: How Japanese Companies Create The Dynamics Of Innovation. Oxford university press.

    Nonaka, I., & Takeuchi, H.(2007). The knowledge-creating company. Harvard Business Review, 85(7/8), 162.

    Parker, G. G., Van Alstyne, M. W., & Choudary, S. P.(2016). Platform Revolution: How Networked Markets are Transforming the Economy and How to Make Them Work for You. WW Norton & Company.

    Polanyi, M.(1966). The logic of tacit inference. Philosophy, 41(155), 1-18.

    Polanyi, M.(2009). The Tacit Dimension. University of Chicago press.

    Rochet, J.-C., & Tirole, J.(2003). Platform competition in two-sided markets. Journal of the European Economic Association, 1(4), 990-1029.

    Rochet, J.-C., & Tirole, J.(2004a). Defining two-sided markets.

    Rochet, J.-C., & Tirole, J.(2004b). Two-sided markets: an overview. Institut d’Economie Industrielle Working Paper.

    Rochet, J. C., & Tirole, J.(2006). Two‐sided markets: a progress report. The RAND Journal of Economics, 37(3), 645-667.

    Scheepers, R., Venkitachalam, K., & Gibbs, M. R.(2004). Knowledge strategy in organizations: refining the model of Hansen, Nohria and Tierney. The Journal of Strategic Information Systems, 13(3), 201-222.

    Schilling, M. A.(2002). Technology success and failure in winner-take-all markets: The impact of learning orientation, timing, and network externalities. Academy of Management Journal, 45(2), 387-398.

    Sumant Ugalmugale, R. S.(2020). Telemedicine Market Share Report | Global 2020-2026 Industry Data. https://www.gminsights.com/industry-analysis/telemedicine-market

    Szasz, T. S., & Hollender, M. H.(1956). A contribution to the philosophy of medicine: the basic models of the doctor-patient relationship. AMA Archives of Internal Medicine, 97(5), 585-592.

    Van Alstyne, M. W., Parker, G. G., & Choudary, S. P.(2016). Pipelines, platforms, and the new rules of strategy. Harvard Business Review, 94(4), 54-62.

    WHO.(2010). Telemedicine: opportunities and developments in Member States: report on the second global survey on eHealth 2009.

    Wu, H., & Lu, N.(2017). Online written consultation, telephone consultation and offline appointment: An examination of the channel effect in online health communities. International Journal of Medical Informatics, 107, 107-119.

    Yin, R. K.(1994). Case study research: Design and methods, applied social research. Methods Series, 5.

    Zack, M. H.(1999). Developing a knowledge strategy. California Management Review, 41(3), 125-145.

    Zhang, Y.(2010). Contextualizing consumer health information searching: an analysis of questions in a social Q&A community. Proceedings of the 1st ACM international health informatics symposium,

    中文文獻
    王節祥、蔡寧(2018)。平台研究的流派,趨勢與理論框架——基於文獻計量和內容分析方法的詮釋。商業經濟與管理,38(3),20-35。

    成令方(2002)。醫 「用」關係的知識與權力。台灣社會學,3,11-71。

    余峻瑜、鄭佩怡(2016)。服務創新與設計之健康照護服務設計規劃模式:以遠距照護為例。臺大管理論叢,27(1),225-254。

    吳仁和(2010)。醫療資訊管理 Healthcare Information Management。台北市:智勝文化

    林東清(2009)。知識管理(三版)。台北:智勝文化。

    林信亨(2020)。疫情之下的遠距醫療應用分析。台北市:資策會產業情報研究所(MIC)

    張苙雲(1998)。「逛醫師」的邏輯:求醫歷程的分析。臺灣社會學刊(21), 59-87。

    郭峰淵、柯秀佳、黃莉君、許瓊文(2007)。醫師對參與網路線上諮詢之態度。台灣公共衛生雜誌,26(2),89-98。

    陳威如、王詩一(2016)。決勝平台時代:第一本平台化轉型實戰攻略 Platform Transformation。台北:城邦商業周刊出版。

    陳威如、余卓軒(2013)。平台革命:席捲全球社交、購物、遊戲、媒體的商業模式創新(初版)台北:商周出版。


    廖士程、李明濱、謝博生、李源德(2005)。醫病關係與醫療滿意度之全國性普查。醫學教育,9(2),149-161。

    劉文良(2008)。知識管理(初版)。台北:碁峰資訊。

    鍾燕宜、劉孟基(2009)。行動通信即時視訊對遠距醫療諮詢成功關鍵因素之探討。醫護科技期刊,11(3),171-185。

    藍新堯(2020)。圖解醫療行銷3.0(二版)台北:五南。

    譚大純(2001)。知識管理文獻之回顧與前瞻-以知識作業及知識管理策略為分類基礎。管理評論, 20(4),93-135。

    卡莎馬諾、高耳、友菲(2019)。平台策略:在數位競爭、創新與影響力掛帥的時代勝出(陳琇玲,譯)。台北:商周出版。

    網路文獻
    巫芝岳,高科技外衣之下!? 遠距醫療發展的關鍵商模。環球生技。上網日期110年05月11日,檢自:https://news.gbimonthly.com/tw/magazine/article_show.php?num=38207&page=1&range=news


    巫芝岳,高科技外衣之下!?之二:政府領頭推開了遠距醫療大門。環球生技。上網日期110年05月11日,檢自:https://news.gbimonthly.com/tw/magazine/article_show.php?num=38205&page=1&menu=1056

    譚建民(2003)。「網路醫療諮詢」在「臨床診治」扮演角色探討及研究。KingNet國家網路醫藥。上網日期110年05月25日,檢自: https://www.kingnet.com.tw/news/single?newId=8896

    曾淑芬、張良銘(1998)。另類醫療行為模式:醫療諮詢網站的發展與應用。中央研究院。上網日期110年05月21日,檢自:https://www.ios.sinica.edu.tw/events/seminar/infotec2/info2-10.htm
    Description: 碩士
    國立政治大學
    科技管理與智慧財產研究所
    108364116
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0108364116
    Data Type: thesis
    DOI: 10.6814/NCCU202100950
    Appears in Collections:[科技管理與智慧財產研究所] 學位論文

    Files in This Item:

    File Description SizeFormat
    411601.pdf4575KbAdobe PDF2101View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback