簡易檢索 / 詳目顯示

研究生: 吴宜婷
Claudia
論文名稱: 以需求滿足觀點瞭解使用者持續使用智慧型體能追蹤裝置
Understanding User Continuous Use Intention of Smart Fitness Tracker From a Needs - Satisfaction Perspective
指導教授: 朱宇倩
Yu-Qian Zhu
口試委員: 黃世禎
Sun-Jen Huang
魏小蘭
Hsiao-Lan Wei
學位類別: 碩士
Master
系所名稱: 管理學院 - 資訊管理系
Department of Information Management
論文出版年: 2021
畢業學年度: 109
語文別: 英文
論文頁數: 77
中文關鍵詞: 智慧⼿環健康動機⾺斯洛需求層次滿⾜實現持續使⽤意圖
外文關鍵詞: smart fitness tracker, health motivation, Abraham Maslow’s hierarchy needs, satisfaction, fulfillment, continuous use intention
相關次數: 點閱:243下載:21
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報

智慧⼿環⽇益受到歡迎,主要可歸因於其⾃⾝特點 – 透過追蹤功能達成設定 的⽬標,並潛移默化地改善⽣活的品質。隨著科技的發展,各類智慧⼿環如⾬後春 筍般出現,市場的競爭也逐漸加劇,造成其品牌與商品汰換率極⾼,⽽如何在這⽚ 紅海中留住使⽤者,成為⼀個重要且值得探討的議題。過往研究主要探討智慧⼿環 持續使⽤的意圖,⽽數個⽂獻皆⾔明這部分之⼼理因素動機尚不明確,應進⾏該部 分的深度探討與研究。⽽本研究企圖透過⼈類需求層次觀點,進⾏持續使⽤意圖之 探討。本研究模型以⾺斯洛⼈類需求五層次理論為基礎進⾏發展,並使⽤偏最⼩平 ⽅法結構⽅程模式進⾏數據分析,資料來源來⾃280個印度尼西亞智慧⼿環穿戴使⽤ 者。本研究證實智慧⼿環的使⽤滿⾜⼈類五層次需求中的三者(⽣理需求、安全需 求、⾃我實現),能增加滿意度並影響該設備的持續使⽤意圖。然⽽,尊重與歸屬 感並不能藉由配戴智慧⼿環得到。藉由本研究提出之觀點,可幫助智慧⼿環開發商 找出現存缺點加以改善,並以此制訂發展策略,增加使⽤者持續使⽤智慧⼿環之意 圖。


The increasing popularity of smart fitness tracker is largely attributed to their self – tracking ability that facilitates goal settings and potentially improving people’s quality of life. The evolving of the technology creates a competition that offers users to either upgrade or switch to other brands, making retaining users as an important issue to be explored. Extant research has examined the continuance intention to use of smart fitness tracker, however several researchers have called upon for a deeper exploration saying the psychology of motivation behind it is not clear. This study attempts to understand continuance use intention by seeing it from the perspective of human needs. Thereafter, a research model is developed based upon the Abraham Maslow’s hierarchy of needs and empirically tested using a partial least square structural equation modeling approach (PLS-SEM) on data obtained from 280 smart fitness tracker users in Indonesia. This study confirms that by using smart fitness tracker, three out of five human needs (physiological, safety security, and self-actualization needs) are fulfilled which creates satisfaction and leads to continuance use intention of the device. However, belonging and esteem needs found to be not fulfilled in the process of wearing smart fitness tracker. The insights provided by this study can help smart fitness tracker developers to mitigate the existing drawbacks and create better growth and development strategies with an aim to increase users’ continuous usage of smart fitness tracker.

Table of Contents 摘要 i ABSTRACT ii ACKNOWLEDGEMENT iii List of Figures vii List of Tables viii CHAPTER 1 1 INTRODUCTION 1 1.1. Background 1 1.2. Research Question 3 1.3. Research Purpose 3 1.4. Research Scope 4 1.5. Thesis Structure 4 CHAPTER 2 5 LITERATURE REVIEW 5 2.1. Wearable Technology – Smart Fitness Tracker 5 2.2. Prior research related to adoption and continuous use intention of smart fitness tracker 6 2.3. Abraham Maslow Hierarchy of Needs 13 2.3.1. Physiological Needs 13 2.3.2. Safety and Security Needs 13 2.3.3. Belonging and Love Needs 14 2.3.4. Esteem Needs 14 2.3.5. Self-Actualization Needs 14 2.4. Prior research using Abraham Maslow Hierarchy of Needs as theoretical background 15 2.5. Health Motivation 17 2.6. Social Influence 17 2.6. Privacy Concern 18 CHAPTER 3 19 RESEARCH FRAMEWORK AND HYPOTHESES 19 3.1. Research Framework 19 3.2. Hypotheses Formulation 21 3.2.1. Influence of health motivation to physiological needs fulfillment 21 3.2.2. Influence of health motivation to self-actualization needs fulfillment 21 3.2.3. Influence of social influence to esteem needs fulfillment 22 3.2.4. Influence of social influence to belonging needs fulfillment 22 3.2.5. Influence of privacy concern to esteem needs fulfillment 22 3.2.6. Influence of privacy concern to safety security needs fulfillment 23 3.2.7. Influence of Abraham Maslow hierarchy needs to satisfaction 23 3.2.8. Influence of satisfaction to continuance intention to use 24 CHAPTER 4 25 RESEARCH METHODOLOGY 25 4.1 Research Design 25 4.2 Questionnaire and Instrument Development 25 CHAPTER 5 30 DATA ANALYSIS AND RESULTS 30 5.1 Respondent Demographics 30 5.2. PLS-SEM Analysis 31 5.2.1. Data Handling 32 5.2.2 Measurement Model 32 5.2.4. Structural Model 37 5.2.5. Hypotheses Testing Result 38 5.2.6. Mediation Analysis 41 CHAPTER 6 44 DISCUSSION AND CONCLUSION 44 6.1. Discussion of Results 44 6.1.1. Influence of Health Motivation to Physiological Needs Fulfillment 44 6.1.2. Influence of Health Motivation to Self-Actualization Needs Fulfillment 44 6.1.3. Influence of Social Influence to Esteem Needs Fulfillment 44 6.1.4. Influence of Social Influence to Belonging Needs Fulfillment 45 6.1.5. Influence of Privacy Concern to Esteem Needs Fulfillment 45 6.1.6. Influence of Privacy Concern to Safety Security Needs Fulfillment 45 6.1.7. Influence of Abraham Maslow Hierarchy of Needs fulfillment to Satisfaction 45 6.1.8. Influence of Satisfaction to Continuous Use Intention 46 6.2. Theoretical contributions 46 6.3. Managerial implications 47 6.4. Limitation and Future Research 48 6.5. Conclusion 48 REFERENCES 50 APPENDIX 1 Original Questionnaire (English) 55 APPENDIX 2 Original Questionnaire (Indonesian) 61

REFERENCES

Abouzahra, M., & Ghasemaghaei, M. (2020). The antecedents and results of seniors’ use of activity tracking wearable devices. Health Policy and Technology, 9(2), 213–217. https://doi.org/10.1016/j.hlpt.2019.11.002
Abraham, C., & Sheeran, P. (2001). The health belief model. In Cambridge Handbook of Psychology, Health and Medicine (Issue June 2015, pp. 97–102). Cambridge University Press. https://doi.org/10.1017/CBO9780511543579.022
An, M., & Zhang, X. (2018). Identifying the Validity and Reliability of a Self-Report Motivation Instrument for Health-Promoting Lifestyles Among Emerging Adults. Frontiers in Psychology, 9. https://doi.org/10.3389/fpsyg.2018.01222
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423. https://doi.org/10.1037/0033-2909.103.3.411
Asimakopoulos, S., Asimakopoulos, G., & Spillers, F. (2017). Motivation and User Engagement in Fitness Tracking: Heuristics for Mobile Healthcare Wearables. Informatics, 4(1), 5. https://doi.org/10.3390/informatics4010005
Awad, & Krishnan. (2006). The Personalization Privacy Paradox: An Empirical Evaluation of Information Transparency and the Willingness to Be Profiled Online for Personalization. MIS Quarterly, 30(1), 13. https://doi.org/10.2307/25148715
Becker, M., Kolbeck, A., Matt, C., & Hess, T. (2017). Understanding the continuous use of fitness trackers: A thematic analysis. Proceedings Ot the 21st Pacific Asia Conference on Information Systems: “‘Societal Transformation Through IS/IT’”, PACIS 2017.
Benbunan-Fich, R. (2019). An affordance lens for wearable information systems. European Journal of Information Systems, 28(3), 256–271. https://doi.org/10.1080/0960085X.2018.1512945
Benson, S. G., & Dundis, S. P. (2003). Understanding and motivating health care employees: integrating Maslow’s hierarchy of needs, training and technology. Journal of Nursing Management, 11(5), 315–320. https://doi.org/10.1046/j.1365-2834.2003.00409.x
Bhattacherjee, A. (2001a). Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly, 25(3), 351. https://doi.org/10.2307/3250921
Bhattacherjee, A. (2001b). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32(2), 201–214. https://doi.org/10.1016/S0167-9236(01)00111-7
Brandyberry, A. A., Li, X., & Lin, L. (2010). Association for Information Systems Determinants of Perceived Usefulness and Perceived Ease of Use in Individual Adoption of Social Network Sites Recommended Citation "Determinants of Perceived Usefulness and Perceived Ease of Use in Individual Adoption o. Proceedings of the Sixteenth Americas Conference on Information Systems, August 12-(1). http://aisel.aisnet.org/amcis2010/544
Cao, H., Jiang, J., Oh, L. Bin, Li, H., Liao, X., & Chen, Z. (2013). A Maslow’s hierarchy of needs analysis of social networking services continuance. Journal of Service Management, 24(2), 170–190. https://doi.org/10.1108/09564231311323953
Chen, J., Ping, J. W., Xu, Y., & Tan, B. C. Y. (2015). Information privacy concern about peer disclosure in online social networks. IEEE Transactions on Engineering Management, 62(3), 311–324. https://doi.org/10.1109/TEM.2015.2432117
Chuah, S. H.-W. (2019). You inspire me and make my life better: Investigating a multiple sequential mediation model of smartwatch continuance intention. Telematics and Informatics, 43(June), 101245. https://doi.org/10.1016/j.tele.2019.101245
Chuah, S. H.-W., Rauschnabel, P. A., Krey, N., Nguyen, B., Ramayah, T., & Lade, S. (2016). Wearable technologies: The role of usefulness and visibility in smartwatch adoption. Computers in Human Behavior, 65(5–6), 276–284. https://doi.org/10.1016/j.chb.2016.07.047
Chuah, S. H. W. (2019). You inspire me and make my life better: Investigating a multiple sequential mediation model of smartwatch continuance intention. Telematics and Informatics, 43(June), 101245. https://doi.org/10.1016/j.tele.2019.101245
Dehghani, M. (2018). Exploring the motivational factors on continuous usage intention of smartwatches among actual users. Behaviour & Information Technology, 37(2), 145–158. https://doi.org/10.1080/0144929X.2018.1424246
Dehghani, M., Kim, K. J., & Dangelico, R. M. (2018). Will smartwatches last? factors contributing to intention to keep using smart wearable technology. Telematics and Informatics, 35(2), 480–490. https://doi.org/10.1016/j.tele.2018.01.007
Fereidooni, H., Frassetto, T., Miettinen, M., Sadeghi, A.-R., & Conti, M. (2017). Fitness Trackers: Fit for Health but Unfit for Security and Privacy. 2017 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), 19–24. https://doi.org/10.1109/CHASE.2017.54
Fraile, J. A., Bajo, J., Corchado, J. M., & Abraham, A. (2010). Applying wearable solutions in dependent environments. IEEE Transactions on Information Technology in Biomedicine, 14(6), 1459–1467. https://doi.org/10.1109/TITB.2010.2053849
Gulyas, J. (2014). Need Fulfillment. In Encyclopedia of Quality of Life and Well-Being Research (pp. 4291–4293). Springer Netherlands. https://doi.org/10.1007/978-94-007-0753-5_1918
Gupta, A., Dhiman, N., Yousaf, A., & Arora, N. (2020). Social comparison and continuance intention of smart fitness wearables: an extended expectation confirmation theory perspective. Behaviour & Information Technology, 0(0), 1–14. https://doi.org/10.1080/0144929X.2020.1748715
Hair, Joe F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. https://doi.org/10.2753/MTP1069-6679190202
Hair, Joseph F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
Hassan, L., Dias, A., & Hamari, J. (2019). How motivational feedback increases user’s benefits and continued use: A study on gamification, quantified-self and social networking. International Journal of Information Management, 46, 151–162. https://doi.org/10.1016/j.ijinfomgt.2018.12.004
Henriksen, A., Haugen Mikalsen, M., Woldaregay, A. Z., Muzny, M., Hartvigsen, G., Hopstock, L. A., & Grimsgaard, S. (2018). Using Fitness Trackers and Smartwatches to Measure Physical Activity in Research: Analysis of Consumer Wrist-Worn Wearables. Journal of Medical Internet Research, 20(3), e110. https://doi.org/10.2196/jmir.9157
Houghton, D., Pressey, A., & Istanbulluoglu, D. (2020). Who needs social networking? An empirical enquiry into the capability of Facebook to meet human needs and satisfaction with life. Computers in Human Behavior, 104(September 2019), 106153. https://doi.org/10.1016/j.chb.2019.09.029
Hsiao, K.-L. (2017). What drives smartwatch adoption intention? Comparing Apple and non-Apple watches. Library Hi Tech, 35(1), 186–206. https://doi.org/10.1108/LHT-09-2016-0105
Hsu, C.-L., & Lin, J. C.-C. (2016). An empirical examination of consumer adoption of Internet of Things services: Network externalities and concern for information privacy perspectives. Computers in Human Behavior, 62, 516–527. https://doi.org/10.1016/j.chb.2016.04.023
Jeong, S. C., Kim, S.-H., Park, J. Y., & Choi, B. (2017). Domain-specific innovativeness and new product adoption: A case of wearable devices. Telematics and Informatics, 34(5), 399–412. https://doi.org/10.1016/j.tele.2016.09.001
Karapanos, E., Gouveia, R., Hassenzahl, M., & Forlizzi, J. (2016). Wellbeing in the Making: Peoples’ Experiences with Wearable Activity Trackers. Psychology of Well-Being, 6(1), 4. https://doi.org/10.1186/s13612-016-0042-6
Kersten-van Dijk, E. T., Westerink, J. H. D. M., Beute, F., & IJsselsteijn, W. A. (2017). Personal Informatics, Self-Insight, and Behavior Change: A Critical Review of Current Literature. Human–Computer Interaction, 32(5–6), 268–296. https://doi.org/10.1080/07370024.2016.1276456
Kim, D., Park, K., Park, Y., & Ahn, J.-H. (2019). Willingness to provide personal information: Perspective of privacy calculus in IoT services. Computers in Human Behavior, 92, 273–281. https://doi.org/10.1016/j.chb.2018.11.022
Kim, H.-W., Chan, H. C., & Gupta, S. (2007). Value-based Adoption of Mobile Internet: An empirical investigation. Decision Support Systems, 43(1), 111–126. https://doi.org/10.1016/j.dss.2005.05.009
Kononova, A., Li, L., Kamp, K., Bowen, M., Rikard, R., Cotten, S., & Peng, W. (2019). The Use of Wearable Activity Trackers Among Older Adults: Focus Group Study of Tracker Perceptions, Motivators, and Barriers in the Maintenance Stage of Behavior Change. JMIR MHealth and UHealth, 7(4), e9832. https://doi.org/10.2196/mhealth.9832
Kothari, C. . (2004). Research Methodology (Second rev). New Age International Publishers.
Krey, N., Chuah, S. H.-W., Ramayah, T., & Rauschnabel, P. A. (2019). How functional and emotional ads drive smartwatch adoption. Internet Research, 29(3), 578–602. https://doi.org/10.1108/IntR-12-2017-0534
Lansu, T. A. M., Cillessen, A. H. N., & Karremans, J. C. (2015). The Effects of Social Status and Self-Esteem on Imitation and Choice of a Popular Peer. Journal of Relationships Research, 6(January), e14. https://doi.org/10.1017/jrr.2015.11
Li, Han, Gupta, A., Zhang, J., & Sarathy, R. (2014). Examining the decision to use standalone personal health record systems as a trust-enabled fair social contract. Decision Support Systems, 57, 376–386. https://doi.org/10.1016/j.dss.2012.10.043
Li, He, Wu, J., Gao, Y., & Shi, Y. (2016). Examining individuals’ adoption of healthcare wearable devices: An empirical study from privacy calculus perspective. International Journal of Medical Informatics, 88(555), 8–17. https://doi.org/10.1016/j.ijmedinf.2015.12.010
Lunney, A., Cunningham, N. R., & Eastin, M. S. (2016). Wearable fitness technology: A structural investigation into acceptance and perceived fitness outcomes. Computers in Human Behavior, 65, 114–120. https://doi.org/10.1016/j.chb.2016.08.007
Maddux, J. E. (1997). Habit, Health, and Happiness. Journal of Sport and Exercise Psychology, 19(4), 331–346. https://doi.org/10.1123/jsep.19.4.331
Maher, C., Ryan, J., Ambrosi, C., & Edney, S. (2017). Users’ experiences of wearable activity trackers: a cross-sectional study. BMC Public Health, 17(1), 880. https://doi.org/10.1186/s12889-017-4888-1
Martins, C., Oliveira, T., & Popovič, A. (2014). Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1–13. https://doi.org/10.1016/j.ijinfomgt.2013.06.002
Maslow, A. H. (1943). A Dynamic Theory of Human Motivation. In Understanding human motivation. (pp. 26–47). Howard Allen Publishers. https://doi.org/10.1037/11305-004
Moorman, C., & Matulich, E. (1993). A Model of Consumers’ Preventive Health Behaviors: The Role of Health Motivation and Health Ability. Journal of Consumer Research, 20(2), 208. https://doi.org/10.1086/209344
Motti, V. G., & Caine, K. (2015). Users’ privacy concerns about wearables: Impact of form factor, sensors and type of data collected. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8976(February), 231–244. https://doi.org/10.1007/978-3-662-48051-9_17
Naglis, M., & Bhatiasevi, V. (2019). Why do people use fitness tracking devices in Thailand? An integrated model approach. Technology in Society, 58, 101146. https://doi.org/10.1016/j.techsoc.2019.101146
Nascimento, B., Oliveira, T., & Tam, C. (2018). Wearable technology: What explains continuance intention in smartwatches? Journal of Retailing and Consumer Services, 43, 157–169. https://doi.org/10.1016/j.jretconser.2018.03.017
Pal, D., Funilkul, S., & Vanijja, V. (2020). The future of smartwatches: assessing the end-users’ continuous usage using an extended expectation-confirmation model. Universal Access in the Information Society, 19(2), 261–281. https://doi.org/10.1007/s10209-018-0639-z
Patel, M. S., Asch, D. A., & Volpp, K. G. (2015). Wearable Devices as Facilitators, Not Drivers, of Health Behavior Change. JAMA, 313(5), 459. https://doi.org/10.1001/jama.2014.14781
Peng, C., & Kim, Y. G. (2014). Application of the Stimuli-Organism-Response (S-O-R) Framework to Online Shopping Behavior. Journal of Internet Commerce, 13(3–4), 159–176. https://doi.org/10.1080/15332861.2014.944437
Reyes-Mercado, P. (2018). Adoption of fitness wearables. Journal of Systems and Information Technology, 20(1), 103–127. https://doi.org/10.1108/JSIT-04-2017-0025
Scherer, M. J. (2005). Assessing the benefits of using assistive technologies and other supports for thinking, remembering and learning. Disability and Rehabilitation, 27(13), 731–739. https://doi.org/10.1080/09638280400014816
Shaygan, A., Gungor, D. O., Kutgun, H., & Daneshi, A. (2017). Adoption Criteria Evaluation of Activity Tracking Wristbands for University Students. 2017 Portland International Conference on Management of Engineering and Technology (PICMET), 1–7. https://doi.org/10.23919/PICMET.2017.8125443
Shin, G., Jarrahi, M. H., Fei, Y., Karami, A., Gafinowitz, N., Byun, A., & Lu, X. (2019). Wearable activity trackers, accuracy, adoption, acceptance and health impact: A systematic literature review. Journal of Biomedical Informatics, 93(September), 103153. https://doi.org/10.1016/j.jbi.2019.103153
Soraya, S. I., Chiang, T.-H., Chan, G.-J., Su, Y.-J., Yi, C.-W., Tseng, Y.-C., & Ching, Y.-T. (2017). IoT/M2M wearable-based activity-calorie monitoring and analysis for elders. 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2390–2393. https://doi.org/10.1109/EMBC.2017.8037337
Sschwaig, S., Segars, A. H., & Fiedler, K. D. (2013). A Model of Consumers ’ Perceptions of the Invasion of Information Privacy. January. https://doi.org/10.1016/j.im.2012.11.002
Statista. (2020a). Global wrist worn wearable unit shipments worldwide 2019 - 2024. https://www.statista.com/statistics/296565/wearables-worldwide-shipments/
Statista. (2020b). Wearables - worldwide | Statista Market Forecast. https://www.statista.com/outlook/319/120/wearables/indonesia#market-globalRevenue
Ștefan, S. C., Popa, Ștefan C., & Albu, C. F. (2020). Implications of Maslow’s Hierarchy of Needs Theory on Healthcare Employees’ Performance. Transylvanian Review of Administrative Sciences, 16(59 E), 124–143. https://doi.org/10.24193/tras.59E.7
Suh, A. (2018). Sustaining the Use of Quantified-Self Technology : A Theoretical Extension and Empirical Test. Asia Pacific Journal of Information Systems, 28(2), 114–132. https://doi.org/10.14329/apjis.2018.28.2.114
Sun, S. Y., Ju, T., Chiu, C. M., & Hsu, M. H. (2005). A study on the factors influencing the intention of reusing an e-commerce website. Association for Information Systems - 11th Americas Conference on Information Systems, AMCIS 2005: A Conference on a Human Scale, 3, 1179–1187.
Taormina, & Gao. (2013). Maslow and the Motivation Hierarchy: Measuring Satisfaction of the Needs. The American Journal of Psychology, 126(2), 155. https://doi.org/10.5406/amerjpsyc.126.2.0155
Thielke, S., Harniss, M., Thompson, H., Patel, S., Demiris, G., & Johnson, K. (2012). Maslow’s Hierarchy of Human Needs and the Adoption of Health-Related Technologies for Older Adults. Ageing International, 37(4), 470–488. https://doi.org/10.1007/s12126-011-9121-4
Venkatesh, Morris, Davis, & Davis. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425. https://doi.org/10.2307/30036540
Windasari, N. A., Lin, F., & Kato-Lin, Y.-C. (2021). Continued use of wearable fitness technology: A value co-creation perspective. International Journal of Information Management, 57, 102292. https://doi.org/10.1016/j.ijinfomgt.2020.102292
Wu, J., Li, H., Lin, Z., & Zheng, H. (2017). Competition in wearable device market: the effect of network externality and product compatibility. Electronic Commerce Research, 17(3), 335–359. https://doi.org/10.1007/s10660-016-9227-6
Yang, H., Yu, J., Zo, H., & Choi, M. (2016). User acceptance of wearable devices: An extended perspective of perceived value. Telematics and Informatics, 33(2), 256–269. https://doi.org/10.1016/j.tele.2015.08.007
Zhou, T., & Li, H. (2014). Understanding mobile SNS continuance usage in China from the perspectives of social influence and privacy concern. Computers in Human Behavior, 37, 283–289. https://doi.org/10.1016/j.chb.2014.05.008
Zhu, Y., Dailey, S. L., Kreitzberg, D., & Bernhardt, J. (2017). “Social Networkout”: Connecting Social Features of Wearable Fitness Trackers with Physical Exercise. Journal of Health Communication, 22(12), 974–980. https://doi.org/10.1080/10810730.2017.1382617

QR CODE