李东进;张宇东

• 1:南开大学 商学院，天津 300071

摘要(Abstract)：

量化自我是指消费者对自我数据进行收集并经由数据获得自我知识的过程。量化自我能增强消费者的自我精准管控和行为理性，驱动消费者行为方式的转变。数据驱动的量化自我时代正在来临，全新的商业逻辑正在被建立起来。消费者的行为正从非标准化向精准化转变。鉴于此，越来越多学者开始围绕量化自我展开研究，在清晰界定量化自我概念的基础上，分析量化自我的参与动机与阶段性过程，关注量化自我带来的消费者精准化消费方式转变。本文系统回顾了量化自我相关研究，阐释了量化自我的概念与本质，从量化自我的类型与效用、动机与过程等方面对相关研究进行了述评，整理提炼了量化自我在消费领域的应用现状，并在此基础上明确了量化自我研究尚需解决的问题和未来的研究方向。

关键词(KeyWords)： 量化自我;自我追踪;精准化;大数据

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目（71372099）；国家自然科学基金项目（71572107）

作者(Authors): 李东进;张宇东

参考文献(References)：

• [1] Almalki M, Gray K, Martin-Sanchez F. Activity theory as a theoretical framework for health self-quantification: A systematic review of empirical studies[J]. Journal of Medical Internet Research, 2016, 18(5): e131.
  [2] Ancker J S, Witteman H O, Hafeez B, et al. “You get reminded you're a sick person”: Personal data tracking and patients with multiple chronic conditions[J]. Journal of Medical Internet Research, 2015, 17(8): e202.
  [3] Azar B. QnAs with Davis Masten and Peter Zandan[J]. Proceedings of the National Academy of Sciences of the United States of America, 2014, 111(5): 1662-1663.
  [4] Barcena M B, Wueest C, Lau H. How safe is your quantified self[M]. Mountain View, CA: Symantech, 2014.
  [5] Beer D. The biopolitics of biometrics: An interview with Btihaj Ajana[J]. Theory Culture & Society, 2014, 31(7-8): 329-336.
  [6] Bloch M. Truth and sight: Generalizing without universalizing[J]. Journal of the Royal Anthropological Institute, 2008, 14(S1): S22-S32.
  [7] Bloem S, Stalpers J. Subjective experienced health as a driver of health care behavior[R]. Nyenrode Research Paper No. 12-01, 2012.
  [8] Buchanan K, Lockton D. Understanding human connectivity and the quantified self[R]. Working Paper of the Sustainable Society Network, 2015: 1-7.
  [9] Choe E K, Lee N B, Lee B, et al. Understanding quantified-selfers' practices in collecting and exploring personal data[A]. Proceedings of the SIGCHI conference on human factors in computing systems[C]. Toronto, Ontario, Canada: ACM, 2014: 1143-1152.
  [10] Choe Y, Fesenmaier D R. The quantified traveler: Implications for smart tourism development[A]. Xiang Z, Fesenmaier D R. Analytics in smart tourism design: Concepts and methods[C]. Cham: Springer, 2016: 65-71.
  [11] Clawson J, Pater J A, Miller A D, et al. No longer wearing: Investigating the abandonment of personal health-tracking technologies on craigslist[A]. Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing[C]. Osaka: ACM, 2015: 647-658.
  [12] Crawford K, Lingel J, Karppi T. Our metrics, ourselves: A hundred years of self-tracking from the weight scale to the wrist wearable device[J]. European Journal of Cultural Studies, 2015, 18(4-5): 479-496.
  [13] De Maeyer C, Jacobs A. Sleeping with technology-designing for personal health[A]. Proceedings of the 2013 medicine 2.0 conference[C]. Toronto: JMIR Publications, 2013: 11-16.
  [14] Elsden C, Kirk D, Selby M, et al. Beyond personal informatics: Designing for experiences with data[A]. Proceedings of the 33rd annual ACM conference extended abstracts on human factors in computing systems[C]. Seoul: ACM, 2015: 2341-2344.
  [15] Etkin J. The hidden cost of personal quantification[J]. Journal of Consumer Research, 2016, 42(6): 967-984.
  [16] Fawcett T. Mining the quantified self: Personal knowledge discovery as a challenge for data science[J]. Big Data, 2015, 3(4): 249-266.
  [17] Fogg B J. A behavior model for persuasive design[A]. Proceedings of the 4th international conference on persuasive technology[C]. Claremont, California: ACM, 2009: 1-7.
  [18] Guo L. Quantified-self 2.0: Using context-aware services for promoting gradual behaviour change[R]. Working Papers of Computers and Society, 2016: 1-18.
  [19] Haddadi H, Ofli F, Mejova Y, et al. 360-degree quantified self[A]. Proceedings of the 2015 international conference on healthcare informatics[C]. Texas: ACM, 2015: 587-592.
  [20] Hammarfelt B, de Rijcke S, Rushforth A D. Quantified academic selves: The gamification of research through social networking services[J]. Information Research, 2016, 21(2): 1-9.
  [21] Henning K J. Overview of syndromic surveillance: What is syndromic surveillance?[J]. MMWR Morbidity & Mortality Weekly Report, 2004, 53(S1): 5-11.
  [22] Ledger D, McCaffrey D. Inside wearables: How the science of human behavior change offers the secret to long-term engagement[M]. Endeavour Partners LLC, 2014: 1-17.
  [23] Li I, Dey A, Forlizzi J. A stage-based model of personal informatics systems[A]. Proceedings of the 28th annual ACM conference on human factors in computing systems[C]. Atlanta, Georgia: ACM, 2010: 557-566.
  [24] Li I. Personal informatics and context: Using context to reveal factors that affect behavior[J]. Journal of Ambient Intelligence and Smart Environments, 2012, 4(1): 71-72.
  [25] Lupton D. Quantifying the body: Monitoring and measuring health in the age of mHealth technologies[J]. Critical Public Health, 2013, 23(4): 393-403.
  [26] Lupton D. Self-tracking modes: Reflexive self-monitoring and data practices[J]. SSRN Electronic Journal, 2014a, 391(1): 547-551.
  [27] Lupton D. Self-tracking cultures: Towards a sociology of personal informatics[A]. Proceedings of the 26th Australian computer-human interaction conference on designing futures[C]. Sydney: ACM, 2014b: 77-86.
  [28] Marcengo A, Rapp A. Visualization of human behavior data: The quantified self[A]. Huang M L, Huang W D. Innovative approaches of data visualization and visual analytics[C]. Hershey: IGI Global, 2014, 1: 236-265.
  [29] Miltenberger R G. Behavior modification: Principles and procedures[M]. 5th ed. Belmont, CA: Wadsworth Cengage Learning, 2011.
  [30] Moore P, Robinson A. The quantified self: What counts in the neoliberal workplace[J]. New Media & Society, 2016, 18(11): 2774-2792.
  [31] Morschheuser B S, Rivera-Pelayo V, Mazarakis A, et al. Interaction and reflection with quantified self and gamification: An experimental study[J]. Journal of Literacy and Technology, 2014, 15(2): 136-156.
  [32] Orenga-Roglá S, Chalmeta R. Social customer relationship management: Taking advantage of Web 2.0 and big data technologies[J]. SpringerPlus, 2016, 5: 1462.
  [33] Pantzar M, Ruckenstein M. The heart of everyday analytics: Emotional, material and practical extensions in self-tracking market[J]. Consumption Markets & Culture, 2015, 18(1): 92-109.
  [34] Petersen R R, Lukas A, Wiil U K. QS Mapper: A transparent data aggregator for the quantified self: Freedom from particularity using two-way mappings[A]. Proceedings of the 10th international joint conference on software technologies[C]. Colmar: IEEE, 2015: 1-8.
  [35] Prochaska J O, Velicer W F. The transtheoretical model of health behavior change[J]. American Journal of Health Promotion, 1997, 12(1): 38-48.
  [36] Robertsson L. Quantified self: An overview & the development of a universal tracking application[D]. Sweden: Department of Computing Science, Umea University, 2014.
  [37] Rooksby J, Rost M, Morrison A, et al. Personal tracking as lived informatics[A]. Proceedings of the SIGCHI conference on human factors in computing systems[C]. Toronto: ACM, 2014: 1163-1172.
  [38] Ruckenstein M. Visualized and interacted life: Personal analytics and engagements with data doubles[J]. Societies, 2014, 4(1): 68-84.
  [39] Ruckenstein M, Pantzar M. Beyond the quantified self: Thematic exploration of a dataistic paradigm[J]. New Media & Society, 2017, 19(3): 401-418.
  [40] Sharon T, Zandbergen D. From data fetishism to quantifying selves: Self-tracking practices and the other values of data[J]. New Media & Society, 2017, 19(11): 1695-1709.
  [41] Shin D H, Biocca F. Health experience model of personal informatics: The case of a quantified self[J]. Computers in Human Behavior, 2017, 69: 62-74.
  [42] Shull P B, Jirattigalachote W, Hunt M A, et al. Quantified self and human movement: A review on the clinical impact of wearable sensing and feedback for gait analysis and intervention[J]. Gait & Posture, 2014, 40(1): 11-19.
  [43] Sjöklint M, Constantiou I D, Trier M. The complexities of self-tracking: An inquiry into user reactions and goal attainment[J]. Social Science Electronic Publishing, 2015, 13(6): 603-611.
  [44] Swan M. Emerging patient-driven health care models: An examination of health social networks, consumer personalized medicine and quantified self-tracking[J]. International Journal of Environmental Research and Public Health, 2009, 6(2): 492-525.
  [45] Swan M. Health 2050: The realization of personalized medicine through crowdsourcing, the quantified self, and the participatory biocitizen[J]. Journal of Personalized Medicine, 2012, 2(3): 93-118.
  [46] Swan M. The quantified self: Fundamental disruption in big data science and biological discovery[J]. Big Data, 2013, 1(2): 85-99.
  [47] Swan M. Connected car: Quantified self becomes quantified car[J]. Journal of Sensor and Actuator Networks, 2015, 4(1): 2-29.
  [48] Taylor S E. Asymmetrical effects of positive and negative events: The mobilization-minimization hypothesis[J]. Psychological Bulletin, 1991, 110(1): 67-85.
  [49] Thaler R H, Sunstein C R. Nudge: Improving decisions about health, wealth, and happiness[M]. New Haven: Yale University Press, 2008.
  [50] Till C. Exercise as labour: Quantified self and the transformation of exercise into labour[J]. Societies, 2014, 4(3): 446-462.
  [51] Trusov M, Ma L Y, Jamal Z. Crumbs of the cookie: User profiling in customer-base analysis and behavioral targeting[J]. Marketing Science, 2016, 35(3): 405-426.
  [52] Van Berkel N, Luo C, Ferreira D, et al. The curse of quantified-self: An endless quest for answers[A]. Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing[C]. Osaka: ACM, 2015: 973-978.
  [53] Verhoef P C, Venkatesan R, McAlister L, et al. CRM in data-rich multichannel retailing environments: A review and future research directions[J]. Journal of Interactive Marketing, 2010, 24(2): 121-137.
  [54] Whitson J. Gaming the quantified self[J]. Surveillance & Society, 2013, 11(1-2): 163-176.
  [55] Wolf G. Know thyself: Tracking every facet of life, from sleep to mood to pain, 24/7/365[R]. Wired Magazine, 2009.
  [56] Yang Y, Lee H, Gurrin C. Visualizing lifelog data for different interaction platforms[A]. Proceedings of the CHI 2013 extended abstracts on human factors in computing systems[C]. Paris: ACM, 2013: 1785-1790.