隨著都市化所帶來的各項挑戰日益嚴峻，智慧城市已成為許多國家積極發展的解決方案，台灣亦在發展智慧城市的行列之中。本研究旨在探討影響民眾對智慧城市服務使用意圖的因素，並將智慧城市定義為一個以「資訊與通訊技術基礎設施」作為發展的基礎，創造一個「獨特的協作生態系統」，以提升民眾的「生活品質」的城市。本研究從台灣電信業者提供的智慧城市服務中，篩選出智慧醫療及智慧家庭兩項智慧城市服務作為研究主體，並在整合科技接受模型(Unified Theory of Acceptance and Use of Technology, UTAUT)的基礎上進行模型的擴展，加入了對企業的信任、對科技的信任以及自我效能三個變項，構成整體研究架構。
本研究採用問卷調查法，透過社群媒體發放問卷以收集民眾對智慧城市服務的看法。最終獲得284份有效問卷，而結構方程模型分析的結果顯示，績效預期和社群影響是影響民眾使用智慧城市服務意圖最為關鍵的變項，結果亦顯示，不同的服務會使結果具有差異：對企業的信任在智慧醫療中無顯著影響，而在智慧家庭時則具顯著影響。最後，本研究針對研究結果進行討論，闡述本研究之理論和實務意涵，並提出未來研究建議。

With the growing challenges brought by urbanization, smart cities have become a key solution actively promoted by many countries, including Taiwan. This study aims to examine the factors influencing citizens’ intention to use smart city services. In this research, a smart city is defined as one that is built upon information and communication technology infrastructure to create a unique collaborative ecosystem aimed at enhancing the quality of life for its citizens. This research focuses on two services provided by Taiwanese telecom operators—smart healthcare and smart home. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT), the research model was extended by incorporating trust in businesses, trust in technology, and self-efficacy.
Data were collected through a survey distributed via social media, yielding 284 valid responses. Structural equation modeling results indicate that performance expectancy and social influence are the most significant determinants of citizens’ usage intention. Moreover, service type differences were observed: trust in businesses shows no significant effect in smart healthcare but has a significant effect in smart home. This study discusses both theoretical and practical implications of the findings and provides suggestions for future research.

一、中文文獻
May.（2024）。智慧管家進駐就是這麼簡單TWM Smarter Home開啟跨系統服務新體驗。幸福空間。https://hhh.com.tw/HHH_NEW/columns_detail/7974.php
內政部戶政司（2025）。人口數按性別。全國人口資料庫統計地圖。 https://gis.ris.gov.tw/dashboard.html?key=B01
中華電信（2024）。中華電信榮獲智慧城市卓越貢獻獎 以創新科技賦能智慧城市。中華電信官網。https://www.cht.com.tw/zh-tw/home/cht/messages/2024/0815-1640
中華電信（n.d.）。智慧醫療。中華電信官網。https://www.chttl.com.tw/rd_iot-medical.html
台灣大哥大（n.d.-a）。智慧醫療。台灣大哥大官網。https://www.twmsolution.com/5G/Smart_HealthCare/
台灣大哥大（n.d.-b）。智慧家庭。台灣大哥大官網。https://smarterhome.taiwanmobile.net/
台灣大哥大（n.d.-c）。［智慧家庭之示意圖］［圖片］。台灣大哥大官網。https://smarterhome.taiwanmobile.net/
台灣大哥大（2021）。台灣大哥大智慧家庭｜打造Smarter Home，讓智慧接軌無縫（智慧家庭）［影片］。YouTube。https://www.youtube.com/watch?v=sHvE14au0CM
台灣大哥大（2024）。台灣大智慧城市展聚焦四大領域　「從行動到移動」打開智慧生活台灣大聚焦5G智慧交通 首度展出MyCharge三倍速充電樁　引領5G車聯網產業鏈發展 台灣大展示一站式車聯網解決方案。台灣大哥大官網。https://corp.taiwanmobile.com/press-release/news/press_20240319_860497.html
朱正庭、張為竣（2023）。智慧城市展登場　遠傳元宇宙數位治理場景吸睛。遠東人月刊。https://magazine.feg.com.tw/magazine/tw/magazine_detail.aspx?id=13930
菲利浦．科特勒、陳就學、伊萬．塞提亞宛（2023）。幾年出生是Z世代？Z世代現在幾歲？。商業周刊。https://www.businessweekly.com.tw/management/blog/3014164
遠傳電信（n.d.-a）。5G遠距診療平台。遠傳電信官網。https://enterprise.fetnet.net/content/ebu/tw/solution/5g-innovation/innovation/5g-telemedicine.html
遠傳電信（n.d.-b）。［智慧醫療之示意圖］［圖片］。遠傳電信官網。https://www.fetnet.net/content/cbu/tw/network/index/what-is-5G.html
遠傳電信（2024）。5G遠距診療2.0－在宅急症照護方案［影片］。YouTube。https://www.youtube.com/watch?v=QoWtTdcoIzM
鄭怡君、蔡俊傑（2016）。Bootstrap中介效果結構方程模式分析。體育學系學刊，15，102–114。https://doi.org/10.29793/NTUSPE.201608_(15).0008
二、英文文獻
Ahmed, W., Sheikh, M. H., Sentosa, I., Akter, H., Yafi, E., & Ali, J. (2020). Predicting IoT Service Adoption towards Smart Mobility in Malaysia: SEM-Neural Hybrid Pilot Study. International Journal of Advanced Computer Science and Applications, 11(1). https://doi.org/10.14569/IJACSA.2020.0110165
Al-Saedi, K., Al-Emran, M., Ramayah, T., & Abusham, E. (2020). Developing a general extended UTAUT model for M-payment adoption. Technology in Society, 62, 101293. https://doi.org/10.1016/j.techsoc.2020.101293
Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99–110. https://doi.org/10.1016/j.ijinfomgt.2017.01.002
Albino, V., Berardi, U., & Dangelico, R. M. (2015). Smart cities: Definitions, dimensions, performance, and initiatives. Journal of Urban Technology, 22(1), 3–21. http://dx.doi.org/10.1080/10630732.2014.942092
Alhalafi, N., & Veeraraghavan, P. (2023). Exploring the challenges and issues in adopting Cybersecurity in Saudi Smart cities: Conceptualization of the Cybersecurity-based UTAUT Model. Smart Cities, 6(3), 1523–1544. https://doi.org/10.3390/smartcities6030072
Appio, F. P., Lima, M., & Paroutis, S. (2019). Understanding Smart Cities: Innovation ecosystems, technological advancements, and societal challenges. Technological Forecasting and Social Change, 142, 1–14. https://doi.org/10.1016/j.techfore.2018.12.018
Babin, B. J., & Svensson, G. (2012). Structural equation modeling in social science research: Issues of validity and reliability in the research process. European Business Review, 24(4), 320–330. https://doi.org/10.1108/09555341211242132
Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122. https://doi.org/10.1037/0003-066X.37.2.122
Barrionuevo, J. M., Berrone, P., & Ricart, J. E. (2012). Smart cities, sustainable progress. IESE Insight, 14(14), 50–57. https://doi.org/10.15581/002.ART-2152
Baudier, P., Ammi, C., & Deboeuf-Rouchon, M. (2020). Smart home: Highly-educated students' acceptance. Technological Forecasting and Social Change, 153, 119355. https://doi.org/10.1016/j.techfore.2018.06.043
Bervell, B. B., Kumar, J. A., Arkorful, V., Agyapong, E. M., & Osman, S. (2022). Remodelling the role of facilitating conditions for Google Classroom acceptance: A revision of UTAUT2. Australasian Journal of Educational Technology, 38(1), 115-135. https://doi.org/10.14742/ajet.7178
Braun, T., Fung, B. C., Iqbal, F., & Shah, B. (2018). Security and privacy challenges in smart cities. Sustainable Cities and Society, 39, 499–507. https://doi.org/10.1016/j.scs.2018.02.039
Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81. https://doi.org/10.1037/h0046016
Caragliu, A., Del Bo, C., & Nijkamp, P. (2011). Smart cities in Europe. Journal of Urban Technology, 18(2), 65–82. https://doi.org/10.1080/10630732.2011.601117
Chan, F. K., Thong, J. Y., Venkatesh, V., Brown, S. A., Hu, P. J., & Tam, K. Y. (2010). Modeling citizen satisfaction with mandatory adoption of an e-government technology. Journal of the Association for Information Systems, 11(10), 519–549. https://doi.org/10.17705/1jais.00239
Chang, V., Wang, Y., & Wills, G. (2020). Research investigations on the use or non-use of hearing aids in the smart cities. Technological Forecasting and Social Change, 153, 119231. https://doi.org/10.1016/j.techfore.2018.03.002
Chen, C. W. (2022). Can smart cities bring happiness to promote sustainable development? Contexts and clues of subjective well-being and urban livability. Developments in the Built Environment 13, 100108. https://doi.org/10.1016/j.dibe.2022.100108
Chen, T. M. (2010). Editor's note: smart grids, smart cities need better networks. IEEE Network: The Magazine of Global Internetworking, 24(2), 2–3. https://doi.org/10.1109/MNET.2010.5430136
Chen, Z., & Chan, I. C. C. (2023). Smart cities and quality of life: a quantitative analysis of citizens' support for smart city development. Information Technology & People, 36(1), 263–285. https://doi.org/10.1108/ITP-07-2021-0577
Cheung, G. W., & Lau, R. S. (2008). Testing mediation and suppression effects of latent variables: Bootstrapping with structural equation models. Organizational Research Methods, 11(2), 296–325. https://doi.org/10.1177/1094428107300343
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295–336. http://www.researchgate.net/publication/232569511
Chiu, C. M., & Wang, E. T. (2008). Understanding Web-based learning continuance intention: The role of subjective task value. Information & Management, 45(3), 194–201. https://doi.org/10.1016/j.im.2008.02.003
Dashkevych, O., & Portnov, B. A. (2023). Human-centric, sustainability-driven approach to ranking smart cities worldwide. Technology in Society, 74, 102296. https://doi.org/10.1016/j.techsoc.2023.102296
Duong, C. D., Vu, T. N., & Ngo, T. V. N. (2023). Applying a modified technology acceptance model to explain higher education students’ usage of ChatGPT: A serial multiple mediation model with knowledge sharing as a moderator. The International Journal of Management Education, 21(3), 100883. https://doi.org/10.1016/j.ijme.2023.100883
Dustdar, S., Nastić, S., & Šćekić, O. (2017). Smart cities. The Internet of Things, People and Systems. https://doi.org/10.1007/978-3-319-60030-7
European Commission. (2023). Shaping Europe’s Digital Future: Smart Cities and Communities. European Commission. https://interoperable-europe.ec.europa.eu/collection/einclusion/news/smart-cities-and-communities
Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272. https://doi.org/10.1037/1082-989X.4.3.272
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312
Giffinger, R., & Gudrun, H. (2010). Smart cities ranking: an effective instrument for the positioning of the cities?. ACE- Architecture, City and Environment, 4(12), 7–26. https://doi.org/10.5821/ace.v4i12.2483
Gimpel, H., Graf, V., & Graf-Drasch, V. (2020). A comprehensive model for individuals’ acceptance of smart energy technology-A meta-analysis. Energy Policy, 138, 111196. https://doi.org/10.1016/j.enpol.2019.111196
Gracias, J. S., Parnell, G. S., Specking, E., Pohl, E. A., & Buchanan, R. (2023). Smart cities—a structured literature review. Smart Cities, 6(4), 1719-1743. https://doi.org/10.3390/smartcities6040080
Habib, A., Alsmadi, D., & Prybutok, V. R. (2023). Factors that determine residents' acceptance of smart city technologies. In Smart Cities at Play: Technology and Emerging Forms of Playfulness (pp. 4–17). CRC Press. https://doi.org/10.1080/0144929X.2019.1693629
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (1998). Multivariate Data Analysis (Vol. 5, Issue 3).
Hakeem, M. J., & Sulphey, M. M. (2025). An evaluation of factors affecting the acceptance of smart city ICT services in India. Public Administration and Policy. https://doi.org/10.1108/PAP-07-2024-0114
Hamamurad, Q. H., Jusoh, N. M., & Ujang, U. (2022). Factors affecting stakeholder acceptance of a Malaysian Smart City. Smart Cities, 5(4), 1508–1535. https://doi.org/10.3390/smartcities5040077
Han, M. J. N., & Kim, M. J. (2024). A systematic review of smart city research from an urban context perspective. Cities, 150, 105027. https://doi.org/10.1016/j.cities.2024.105027
Haque, A. B., Bhushan, B., & Dhiman, G. (2022). Conceptualizing smart city applications: Requirements, architecture, security issues, and emerging trends. Expert Systems, 39(5), e12753. https://doi.org/10.1111/exsy.12753
Harrison, C., Eckman, B., Hamilton, R., Hartswick, P., Kalagnanam, J., Paraszczak, J., & Williams, P. (2010). Foundations for smarter cities. IBM Journal of Research and Development, 54(4), 1–16. https://doi.org/10.1147/JRD.2010.2048257
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43, 115–135. https://doi.org/10.1007/s11747-014-0403-8
Hollands, R. G. (2020). Will the real smart city please stand up?: Intelligent, progressive or entrepreneurial?. In The Routledge Companion to Smart Cities (pp. 179–199). Routledge. https://doi.org/10.1080/13604810802479126
Hou, J., Arpan, L., Wu, Y., Feiock, R., Ozguven, E., & Arghandeh, R. (2020). The road toward smart cities: A study of citizens’ acceptance of mobile applications for city services. Energies, 13(10), 2496. https://doi.org/10.3390/en13102496
Hou, J., & Wang, H. (2025). Analysis of Corporate Acceptance of Hydrogen Energy Technology Based on the Extended Technology Acceptance Model. Energies, 18(4), 1013. https://doi.org/10.3390/en18041013
Hu, L. T., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3(4), 424. https://doi.org/10.1037/1082-989X.3.4.424
Huang, C. C., Wang, Y. M., Wu, T. W., & Wang, P. A. (2013). An empirical analysis of the antecedents and performance consequences of using the moodle platform. International Journal of Information and Education Technology, 3(2), 217. https://doi.org/10.7763/IJIET.2013.V3.267
Ji, T., Chen, J. H., Wei, H. H., & Su, Y. C. (2021). Towards people-centric smart city development: Investigating the citizens’ preferences and perceptions about smart-city services in Taiwan. Sustainable Cities and Society, 67, 102691. https://doi.org/10.1016/j.scs.2020.102691
Kaiser, Z. A., & Deb, A. (2025). Sustainable smart city and Sustainable Development Goals (SDGs): a review. Regional Sustainability, 6(1), 100193. https://doi.org/10.1016/j.regsus.2025.100193
Kelloway, E. K. (1998). Using LISREL for structural equation modeling: A researcher's guide. Sage.
Lean, O. K., Zailani, S., Ramayah, T., & Fernando, Y. (2009). Factors influencing intention to use e-government services among citizens in Malaysia. International Journal of Information Management, 29(6), 458–475. https://doi.org/10.1016/j.ijinfomgt.2009.03.012
Lee, J., & Lee, H. (2014). Developing and validating a citizen-centric typology for smart city services. Government Information Quarterly, 31, S93–S105. https://doi.org/10.1016/j.giq.2014.01.010
Lin, C., Zhao, G., Yu, C., & Wu, Y. J. (2019). Smart city development and residents’ well-being. Sustainability, 11(3), 676. https://doi.org/10.3390/su11030676
Lin, Y. (2018). A comparison of selected Western and Chinese smart governance: The application of ICT in governmental management, participation and collaboration. Telecommunications Policy, 42(10), 800–809. https://doi.org/10.1016/j.telpol.2018.07.003
Macke, J., Casagrande, R. M., Sarate, J. A. R., & Silva, K. A. (2018). Smart city and quality of life: Citizens’ perception in a Brazilian case study. Journal of Cleaner Production, 182, 717–726. https://doi.org/10.1016/j.jclepro.2018.02.078
Macke, J., Sarate, J. A. R., & de Atayde Moschen, S. (2019). Smart sustainable cities evaluation and sense of community. Journal of Cleaner Production, 239, 118103. https://doi.org/10.1016/j.jclepro.2019.118103
Maillet, É., Mathieu, L., & Sicotte, C. (2015). Modeling factors explaining the acceptance, actual use and satisfaction of nurses using an Electronic Patient Record in acute care settings: An extension of the UTAUT. International Journal of Medical Informatics, 84(1), 36–47. https://doi.org/10.1016/j.ijmedinf.2014.09.004
Manfreda, A., Ljubi, K., & Groznik, A. (2021). Autonomous vehicles in the smart city era: An empirical study of adoption factors important for millennials. International Journal of Information Management, 58, 102050. https://doi.org/10.1016/j.ijinfomgt.2019.102050
Marsal-Llacuna, M. L., Colomer-Llinàs, J., & Meléndez-Frigola, J. (2015). Lessons in urban monitoring taken from sustainable and livable cities to better address the Smart Cities initiative. Technological Forecasting and Social Change, 90, 611–622. https://doi.org/10.1016/j.techfore.2014.01.012
Microsoft. (2023). What Are Smart Cities? Microsoft. https://www.microsoft.com/en-us/industry/government/resources/smart-cities
Nayak, M. S. D. P., & Narayan, K. A. (2019). Strengths and weaknesses of online surveys. Technology, 6(7), 0837-2405053138. https://doi.org/10.9790/0837-2405053138
Nunnally, J. C. (1994). Psychometric Theory (3rd ed.). McGraw-Hill.
Oliveira, T., Faria, M., Thomas, M. A., & Popovič, A. (2014). Extending the understanding of mobile banking adoption: When UTAUT meets TTF and ITM. International Journal of Information Management, 34(5), 689–703. https://doi.org/10.1016/j.ijinfomgt.2014.06.004
Pal, D., Funilkul, S., Charoenkitkarn, N., & Kanthamanon, P. (2018). Internet-of-things and smart homes for elderly healthcare: An end user perspective. IEEE Access, 6, 10483–10496. https://doi.org/10.1109/ACCESS.2018.2808472.
Papa, A., Mital, M., Pisano, P., & Del Giudice, M. (2020). E-health and wellbeing monitoring using smart healthcare devices: An empirical investigation. Technological Forecasting and Social Change, 153, 119226. https://doi.org/10.1016/j.techfore.2018.02.018
Park, J., Hong, E., & Le, H. T. (2021). Adopting autonomous vehicles: The moderating effects of demographic variables. Journal of Retailing and Consumer Services, 63, 102687. https://doi.org/10.1016/j.jretconser.2021.102687
Peng, G. C. A., Nunes, M. B., & Zheng, L. (2017). Impacts of low citizen awareness and usage in smart city services: The case of London’s smart parking system. Information Systems and e-Business Management, 15, 845–876. https://doi.org/10.1007/s10257-016-0333-8
Popova, Y., & Zagulova, D. (2022). UTAUT model for smart city concept implementation: use of web applications by residents for everyday operations. In Informatics (Vol. 9, No. 1, p. 27). MDPI. https://doi.org/10.3390/informatics9010027
Rahi, S., Othman Mansour, M. M., Alghizzawi, M., & Alnaser, F. M. (2019). Integration of UTAUT model in internet banking adoption context: The mediating role of performance expectancy and effort expectancy. Journal of Research in Interactive Marketing, 13(3), 411–435. https://doi.org/10.1108/JRIM-02-2018-0032
Rana, N. P., Luthra, S., Mangla, S. K., Islam, R., Roderick, S., & Dwivedi, Y. K. (2019). Barriers to the development of smart cities in Indian context. Information Systems Frontiers, 21, 503–525. https://doi.org/10.1007/s10796-018-9873-4
Schaffers, H., Komninos, N., Pallot, M., Trousse, B., Nilsson, M., & Oliveira, A. (2011). Smart cities and the future internet: Towards cooperation frameworks for open innovation. In The Future Internet Assembly (pp. 431–446). Berlin, Heidelberg: Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-20898-0_31
Sepasgozar, S. M., Hawken, S., Sargolzaei, S., & Foroozanfa, M. (2019). Implementing citizen centric technology in developing smart cities: A model for predicting the acceptance of urban technologies. Technological Forecasting and Social Change, 142, 105–116. https://doi.org/10.1016/j.techfore.2018.09.012
Sukhu, A., Zhang, T., & Bilgihan, A. (2015). Factors influencing information-sharing behaviors in social networking sites. Services Marketing Quarterly, 36(4), 317–334. https://doi.org/10.1080/15332969.2015.1076697
Tang, W., Chaiyasoonthorn, W., & Chaveesuk, S. (2024). Understanding the Impact of Self-efficacy, Personal Innovativeness and Content Quality on Mobile Learning Usage in Higher Vocational Colleges. Espacio Tiempo y Educacion, 11(1). http://dx.doi.org/10.14516/ete.11110
Teli, M., Bordin, S., Blanco, M. M., Orabona, G., & De Angeli, A. (2015). Public design of digital commons in urban places: A case study. International Journal of Human-Computer Studies, 81, 17–30. https://doi.org/10.1016/j.ijhcs.2015.02.003
Teng, Q., Bai, X., & Apuke, O. D. (2024). Modelling The Factors That Affect the Intention to Adopt Emerging Digital Technologies for a Sustainable Smart World City. Technology in Society, 102603. https://doi.org/10.1016/j.techsoc.2024.102603
United Nations. (2018, May 16). 68% of the world population projected to live in urban areas by 2050, says UN. United Nations, Department of Economic and Social Affairs. https://www.un.org/development/desa/en/news/population/2018-revision-of-world-urbanization-prospects.html
Utomo, P., Kurniasari, F., & Purnamaningsih, P. (2021). The effects of performance expectancy, effort expectancy, facilitating condition, and habit on behavior intention in using mobile healthcare application. International Journal of Community Service & Engagement, 2(4), 183–197. https://doi.org/10.47747/ijcse.v2i4.529
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 425–478. https://doi.org/10.2307/30036540
Wang, H., Zhang, M., & Zhong, M. (2019). Opportunities and challenges for the construction of a smart city geo-spatial framework in a small urban area in central China. Smart Cities, 2(2), 245-258. https://doi.org/10.3390/smartcities2020016
Wang, Y. C., & Papastathopoulos, A. (2024). Cross-segment validation of customer support for AI-based service robots at luxury, fine-dining, casual, and quick-service restaurants. International Journal of Contemporary Hospitality Management, 36(6), 1744-1765. https://doi.org/10.1108/IJCHM-11-2022-1448
Wu, W., Wu, Y. J., & Wang, H. (2021). Perceived city smartness level and technical information transparency: The acceptance intention of health information technology during a lockdown. Computers in Human Behavior, 122, 106840. https://doi.org/10.1016/j.chb.2021.106840
Xu, L., & Wang, S. (2012). Empirical research on construct of chain store logistics capability system. Ibusiness, 4(1), 10-17. https://doi.org/10.4236/ib.2012.41002
Yang, H., & Lee, H. (2023). Smart city and remote services: The case of South Korea’s national pilot smart cities. Telematics and Informatics, 79, 101957. https://doi.org/10.1016/j.tele.2023.101957
Yeh, H. (2017). The effects of successful ICT-based smart city services: From citizens' perspectives. Government Information Quarterly, 34(3), 556–565. https://doi.org/10.1016/j.giq.2017.05.001
Yigitcanlar, T., Kamruzzaman, M., Foth, M., Sabatini-Marques, J., Da Costa, E., & Ioppolo, G. (2019). Can cities become smart without being sustainable? A systematic review of the literature. Sustainable Cities and Society, 45, 348-365. https://doi.org/10.1016/j.scs.2018.11.033
Zhuhadar, L., Thrasher, E., Marklin, S., & de Pablos, P. O. (2017). The next wave of innovation—Review of smart cities intelligent operation systems. Computers in Human Behavior, 66, 273–281. https://doi.org/10.1016/j.chb.2016.09.030
Zygiaris, S. (2013). Smart city reference model: Assisting planners to conceptualize the building of smart city innovation ecosystems. Journal of the Knowledge Economy, 4, 217–231. https://doi.org/10.1007/s13132-012-0089-4