The Perception of Individuals’ Privacy Concerning the Adoption of Smart City Healthcare Services: A Generic Model Development
With the continuous efforts to implement several smart cities, several challenges face these initiatives at the global level, the most prominent of which is data privacy. There is a lack of research on the factors that affect the perception of individuals' privacy, such as the risk of privacy, data sensitivity, privacy Awareness. In addition, it is not clear what those factors are, and they could swing people's intention to adopt smart services. Concerns about data privacy are categorized based on data activities to unauthorized retrieval, unauthorized use, unauthorized access, unauthorized sharing, insecure storage, and insecure transmission. Each of these issues might lead to a personal data breach and expose the data to be compromised, especially in the case of healthcare data. Therefore, this study aims to identify factors that affect the adoption of smart city healthcare services and subsequently propose a generic adoption model to focus on data and information privacy in this model, especially in health care. This model is developed based on two ways to extract the factors. First: the theories used are the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), and Privacy calculus theory (PCT). Secondly: extract some factors from the literature review and studies related to this research. The model is expected will help to obtain the acceptance, adoption of smart city services and the extent of their impact on data and information privacy from the perspective of individuals and fill gaps. It also can be used in countries similar to Oman, such as in the Arabian Gulf countries.
Keywords: smart city, healthcare services, privacy, privacy concern, technology acceptance model.
LAM, P.T.I., and MA, R. Potential pitfalls in developing smart cities and mitigation measures: An exploratory study. Cities, 2017, 91(December): 146–156.
IEEE. Smart Cities, 2015.
SMART CITIES COUNCIL. Smart City Definitions and Overviews, 2014.
IHS TECHNOLOGY. Smart Cities to rising Fourfold in Number from 2013 to 2025, 2014.
YEH, H. The effects of successful ICT-based smart city services: From citizens’ perspectives. Government Information Quarterly, 2017, 34(3): 556–565.
GHARAIBEH, A. Smart cities: A survey on data management, security, and enabling technologies. IEEE Explore, 2017, 19(4): 2456–2501.
VAN ZOONEN, L. Privacy concerns in smart cities. Government Information Quarterly, 2016, 33(3): 472–480.
MCCLUSKEY, S., ECKHOFF, D., and WAGNER, I. Privacy in the Smart City - Applications, Technologies, Challenges, and Solutions. IEEE Explore, 2017, 19(1): 2456–2501.
ALEISA, N., and RENAUD, K. Privacy of the Internet of Things: A Systematic Literature Review. Proceedings of the 50th Hawaii International Conference on System Sciences, 2017: 1–10.
MARAKHIMOV, A., and JOO, J. Computers in Human Behavior Consumer adaptation and infusion of wearable devices for healthcare. Computers in Human Behavior, 2017, 76: 135–148.
MA, R., LAM, P.T.I., and LEUNG, C.K. Potential pitfalls of smart city development: A study on mobile parking applications (apps) in Hong Kong. Telematics and Informatics, 2018, 35(6): 1580–1592.
SOOKHAK, M., TANG, H., HE, Y., and YU, F.R. Security and Privacy of Smart Cities: A Survey, Research Issues, and Challenges. IEEE Communications Surveys & Tutorials, 2019, 21(2): 1718–1743.
SOOKHAK, M., TANG, H., and YU, F.R. Security and Privacy of Smart Cities: Issues and Challenge. Proceedings of the 20th IEEE International Conference on High-Performance Computing and Communications; 16th IEEE International Conference on Smart City; 4th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS, 2019: 1350–1357.
BRAUN, T., FUNG, B.C.M., IQBAL, F., and SHAH, B. Security and privacy challenges in smart cities. Sustainable Cities and Society, 2018, 39(August): 499–507.
SYMANTEC. Internet security threat report. Network Security, 2016, 21(2): 1–3.
PETERS, F., HANVEY, S., VELURU, S., MADY, A.E.D., BOUBEKEUR, M., and NUSEIBEH, B. Generating Privacy Zones in Smart Cities. The Fourth IEEE Annual International Smart Cities Conference (ISC2 2018), 2019: 1–8.
CUI, L., XIE, G., QU, Y., GAO, L., and YANG, Y. Security and privacy in smart cities: Challenges and opportunities. IEEE Access, 2018, 6(February): 46134–46145.
ATI, M., and BASMAJI, T. Framework for managing smart cities security and privacy applications. ISCAIE 2018 - 2018 IEEE Symposium on Computer Applications and Industrial Electronics, 2018: 191–194.
DING, D., CONTI, M., and SOLANAS, A. A smart health application and its related privacy issues. Proceedings 2016 Smart City Security and Privacy Workshop, 2016: 11–15.
ALGHANIM, A.A., RAHMAN, S.M.M., and HOSSAIN, M.A. Privacy Analysis of Smart City Healthcare Services. Proceedings of 2017 IEEE International Symposium on Multimedia, 2017, (January): 394–398.
DEEBAK, B.D., AL-TURJMAN, F., ALOQAILY, M., and ALFANDI, O. Special Section on Security and Privacy in Emerging Decentralized an Authentic-Based Privacy Preservation Protocol for Smart e-Healthcare Systems in IoT. IEEE Access, 2019, 7: 135632–135649.
LI, H., WU, J., GAO, Y., and SHI, Y. Examining individuals' adoption of healthcare wearable devices: An empirical study from a privacy calculus perspective. International Journal of Medical Informatics, 2016, 88(555): 8–17.
HATHALIYA, J.J., and TANWAR, S. An exhaustive survey on security and privacy issues in Healthcare 4.0. Computer Communications, 2020, 153(January): 311–335.
NATGUNANATHAN, I., MEHMOOD, A., XIANG, Y., and MEMBER, S. Location Privacy Protection in Smart Health Care System. IEEE Internet of Things Journal, 2019, 6(2): 3055–3069.
ZHANG, Y., ZHENG, D., and DENG, R.H. Security and Privacy in Smart Health: Efficient Access Control. IEEE Internet of Things Journal, 2018, 5(3): 2130–2145.
LIU, H., YAO, X., YANG, T., and NING, H. Cooperative Privacy Preservation for Wearable Devices in Hybrid Computing-Based Smart Health. IEEE Internet of Things Journal, 2019, 6(2): 1352–1362.
PARK, E. User acceptance of smart wearable devices: An expectation-confirmation model approach. Telematics and Informatics, 2020, 47(October).
GUNAWAN, H., and SMART, A. Identifying Factors Affecting Smart City Adoption Using the Unified Theory of Acceptance and Use of Technology Method. 2018 International Conference on Orange Technologies, 2019: 1–4.
SEPASGOZAR, S.M.E., HAWKEN, S., SARGOLZAEI, S., and FOROOZANFA, M. Implementing citizen-centric technology in developing smart cities: A model for predicting the acceptance of urban technologies. Technological Forecasting and Social Change, 2019, 142(December): 105–116.
MANFREDA, A., LJUBI, K., and GROZNIK, A. Autonomous vehicles in the smart city era: An empirical study of adoption factors important for millennials. The International Journal of Information Management, 2019, March: 102050.
SHUHAIBER, A., and MASHAL, I. Understanding users’ acceptance of smart homes. Technology in Society, 2019, 58(January): 101110.
BUYLE, R., VAN COMPERNOLLE, M., VLASSENROOT, E., VANLISHOUT, Z., MECHANT, P., and MANNENS, E. Technology readiness and acceptance model’ as a predictor for the use intention of data standards in smart cities. Media and Communication, 2018, 6(4): 127–139.
KIM, Y.B., JOO, H.C., and LEE, B.G. How to forecast behavioral effects on mobile advertising in the smart environment using the technology acceptance and web advertising effect models. KSII Transactions on Internet and Information Systems, 2016, 10(10): 4997–5013.
KIM, Y.B., JOO, H.C., and LEE, B.G. How to Forecast Behavioral Effects on Mobile Advertising in the Smart Environment using the Technology Acceptance Model and Web Advertising Effect Model. KSII Transactions on Internet and Information Systems, 2016, 10(10): 4997–5014.
BELANCHE-GRACIA, D., CASALÓ-ARIÑO, L.V., and PÉREZ-RUEDA, A. Determinants of multi-service smartcard success for smart cities development: A study based on citizens’ privacy and security perceptions. Government Information Quarterly, 2015, 32(2): 154–163.
BALAPOUR, A., NIKKHAH, H.R., and SABHERWAL, R. Mobile application security: Role of perceived privacy as the predictor of security perceptions. The International Journal of Information Management, 2020, November: 102063.
MOHAMMED, Z.A., and TEJAY, G.P. Examining privacy concerns and eCommerce adoption in developing countries: The impact of culture in shaping individuals' perceptions toward technology. Computers & Security, 2017, 67: 254–265.
FORTES, Z., and RITA, P. Privacy concerns and online purchasing behavior: Towards an integrated model. European Research on Management and Business Economics, 2016, 22(3): 167–176.
XU, F., MICHAEL, K., and CHEN, X. Factors affecting privacy disclosure on social network sites: an integrated model. Electronic Commerce Research, 2013: 151–168.
MORRIS, M.G., HALL, M., DAVIS, G.B., DAVIS, F.D., and WALTON, S.M. User Acceptance of Information Technology: Toward a Unified View. Institutions & Transition Economics: Microeconomic Issues eJournal, 2003, 27(3): 425–478.
MARCHEWKA, J.T., LIU, C., and KOSTIWA, K. An Application of the UTAUT Model for Understanding Student Perceptions Using Course Management Software. Communications of the IIMA, 2007, 7: 10.
VENKATESH, V., MORRIS, M.G., and DAVIS, F.D. User acceptance of information technology: Toward a unified view. MIS Quarterly, 2003, 27(3): 425-478.
LAUFER, R.S., and WOLFE, M. Privacy as a Concept and a Social Issue: A Multidimensional Developmental Theory. Journal of Social Issues, 1977, 33: 22-42.
DINEV, T., and HART, T.P. Privacy Concerns and Levels of Information Exchange: An Empirical Investigation of Intended e-Services Use. e-Service Journal, 2006, 4: 25-59.
PARASURAMAN, A. Technology Readiness Index (TRI) is a multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, 2000, 2(4).
- There are currently no refbacks.