Araştırma Makalesi
BibTex RIS Kaynak Göster

Akıllı Şehir Uygulamaları Farkındalık Ölçeği Geliştirme ve Uygulama Çalışması

Yıl 2025, Cilt: 25 Sayı: 4, 372 - 391, 29.12.2025
https://doi.org/10.18037/ausbd.1712489

Öz

Bu çalışmanın amacı, akıllı şehir uygulamalarına yönelik olarak şehirde yaşayan farklı demografik özelliklere sahip bireylerin algılarını ölçmek amacıyla Akıllı Şehir Uygulamaları Ölçeği’nin geliştirilmesi ve akıllı şehir uygulamalarına ilişkin algının demografik değişkenlere göre farklılık gösterip göstermediğinin belirlenmesidir. Ölçeğin geliştirilmesi sürecinde, Açımlayıcı Faktör Analizi (AFA) için 259 yetişkin bireyden oluşan birinci çalışma grubu, Doğrulayıcı Faktör Analizi (DFA) için ise 580 yetişkin bireyden oluşan ikinci çalışma grubu olmak üzere toplamda 839 katılımcıdan oluşan bir örneklem grubu oluşturulmuştur. Verilerin analizi JASP programı aracılığıyla gerçekleştirilmiştir. Araştırmada, ölçeğin yapı geçerliliğini değerlendirmek amacıyla AFA ve DFA uygulanmıştır. AFA, ölçeğin faktör yapısını belirlemek ve maddelerin hangi alt boyutlarla ilişkili olduğunu tespit etmek için kullanılmıştır. Elde edilen faktör yapısının doğrulanması amacıyla DFA gerçekleştirilmiş ve modelin uyum indeksleri değerlendirilmiştir. KMO değeri 0 ile 1 arasında değişmekte olup, 0,90 ve üzeri değerlerin "mükemmel" kabul edilmesi nedeniyle elde edilen sonuçlar analiz bulgularının güvenilirliğini desteklemektedir. Bartlett Küresellik Testi sonucunda (~χ² = 6542,77, sd = 377, p = .001) korelasyon matrisinin birim matris olmadığı ve değişkenler arasında anlamlı ilişkiler bulunduğu belirlenmiştir. Ölçeğin tek boyutlu ve 29 maddeden oluştuğu tespit edilmiştir. Güvenilirlik analizleri sonucunda McDonald’s ω (omega) katsayısı 0,97 ve Cronbach Alfa katsayısı 0,97 olarak hesaplanmıştır. Bu bulgular, geliştirilen ölçeğin yüksek düzeyde güvenilir ve geçerli bir ölçüm aracı olduğunu göstermektedir.

Kaynakça

  • Abadía, J. J. P., Walther, C., Osman, A., & Smarsly, K. (2022). A systematic survey of internet of things frameworks for smart city applications. Sustainable Cities and Society, 83, 103949. https://doi.org/10.1016/j.scs.2022.103949
  • Avcı, E. (2024). Akıllı şehirler için üretken yapay zekâ kavramsal çerçevesi. Kent Akademisi, 17(5), 1654-1675. https://doi.org/10.35674/kent.1490925
  • Bartlett, M. S. (1954). A note on the multiplying factors for various chi-squared approximations. Journal of the Royal Statistical Society, 16(2), 296-298.
  • Brosnan, S. F. (1998). Psychology of computers and technology. Routledge.
  • Carvalho, L., Costa, A., & Dias, J. (2013). Smart cities and the internet of things: A survey. Proceedings of the 6th International Conference on Information and Communication Technologies for Sustainability (ICT4S), 45-56.
  • Calzada, I., & Cobo, C. (2015). Unplugging: Deconstructing the smart city. Journal of Urban Technology, 22(1), 23-43. https://doi.org/10.1080/10630732.2014.971535
  • 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
  • Chourabi, H., Nam, T., Walker, S., Gil-Garcia, J. R., Mellouli, S., Nahon, K., ... & Scholl, H. J. (2012). Understanding smart cities: An integrative framework. In 2012 45th Hawaii International Conference on System Sciences (pp. 2289-2297). IEEE. https://doi.org/10.1109/HICSS.2012.615
  • Cohen, S. (2004). Social relationships and health. American Psychologist, 59(8), 676-684. https://doi.org/10.1037/0003-066X.59.8.676
  • Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334.
  • Dameri, R. P. (2017). Smart city implementation. Progress in IS. Springer.
  • Diener, E., Emmons, R. A., Larsen, R. J., & Griffin, S. (1999). The satisfaction with life scale. Journal of Personality Assessment, 49(1), 71-75. https://doi.org/10.1207/s15327752jpa4901_13
  • Eremia, M., Toma, L., & Sanduleac, M. (2017). The smart city concept in the 21st century. Procedia Engineering, 181, 12-19. https://doi.org/10.1016/j.proeng.2017.02.357
  • Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). Sage Publications.
  • Falconer, G., & Mitchell, S. (2012). Smart city framework. Cisco Internet Business Solutions Group (IBSG), 12(9), 2-10.
  • Guo, Q., & Zhong, J. (2022). The effect of urban innovation performance of smart city construction policies: Evaluate by using a multiple period difference-in-differences model. Technological Forecasting and Social Change, 184, 122003. https://doi.org/10.1016/j.techfore.2022.122003
  • Guo, Q., Wang, Y., & Dong, X. (2022). Effects of smart city construction on energy saving and CO2 emission reduction: Evidence from China. Applied Energy, 313, 118879. https://doi.org/10.1016/j.apenergy.2022.118879
  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Pearson.
  • 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
  • Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1-55. https://doi.org/10.1080/10705519909540118
  • Jarrahi, M. H., Sawyer, S., & Erickson, I. (2022). Digital assemblages, information infrastructures, and mobile knowledge work. Journal of Information Technology, 37(3), 230-249. https://doi.org/10.1177/0268396221105094
  • Jebaraj, L., Khang, A., Chandrasekar, V., Pravin, A. R., & Sriram, K. (2023). Smart city: Concepts, models, technologies and applications. In smart cities (pp. 1-20). CRC Press.
  • Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31-36.
  • Kaluarachchi, Y. (2022). Implementing data-driven smart city applications for future cities. Smart Cities, 5(2), 455-474.
  • Kayahan- Yüksel, D. (2020). Değişen dünyada ayrımcılığa karşı kapsayıcı eğitim. M. Kanak & M. Ersoy (Ed.), Değişen dünyada çocuk içinde (s. 161-177). Eğiten Yayıncılık.
  • Khazael, B., Asl, M. V., & Malazi, H. T. (2023). Geospatial complex event processing in smart city applications. Simulation Modelling Practice and Theory, 122, 102675. https://doi.org/10.1016/j.simpat.2022.102675
  • Leung, L. (2015). Social media connectivity in China: The role of interactivity and social presence in mobile social networking. Computers in Human Behavior, 46, 272-283.
  • Lv, Z., Chen, D., & Lv, H. (2022). Smart city construction and management by digital twins and BIM big data in COVID-19 scenario. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 18(2s), 1-21. https://doi.org/10.1145/3529395
  • Mehta, S., Bhushan, B., & Kumar, R. (2022). Machine learning approaches for smart city applications: Emergence, challenges and opportunities. In Recent Advances in Internet of Things and Machine Learning: Real-World Applications (pp. 147-163).
  • Mokhtar, S. S., Sulaiman, N., & Hassan, M. R. (2012). Public service delivery and smart city concepts: A framework for service innovation in Malaysia. Procedia - Social and Behavioral Sciences, 62, 1239-1243.
  • Nam, T., & Pardo, T. A. (2011). Smart city as urban innovation: Focusing on management, policy, and context. In Proceedings of the 5th International Conference on Theory and Practice of Electronic Governance (ICEGOV2011). https://doi.org/10.1145/2072069.2072100
  • Neirotti, P., De Marco, A., Cagliano, A. C., Mangano, G., & Scorrano, F. (2014). Current trends in smart city initiatives: Some stylised facts. Cities, 38, 25-36. https://doi.org/10.1016/j.cities.2013.12.010
  • Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9(5), 1-6.
  • Shelton, T., Zook, M., & Wiig, A. (2015). The ‘actually existing smart city’. Cambridge Journal of Regions, Economy and Society, 8(1), 13-25. https://doi.org/10.1093/cjres/rsu026
  • Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). Allyn & Bacon.
  • Tyagi, N., & Bhushan, B. (2023). Demystifying the role of natural language processing (NLP) in smart city applications: Background, motivation, recent advances, and future research directions. Wireless Personal Communications, 130(2), 857-908.
  • Urhan, O., & Güllü, K. (2023). Veriye dayalı akıllı şehir oluşturmada teknoloji trendleri. Şura Akademi, (2), 19-25.
  • Venkatesh, V., & Morris, M. G. (2000). Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 115-139. https://doi.org/10.2307/3250981
  • Van Deursen, A. J., & Van Dijk, J. A. (2014). Digital skills: Unlocking the potential of a digital world. Springer.
  • Van Dijk, J. A. (2006). The network society: Social aspects of new media. Sage Publications.
  • Xia, X., Yu, R., & Zhang, S. (2023). Evaluating the impact of smart city policy on carbon emission efficiency. Land, 12(7), 1292. https://doi.org/10.3390/land12071292
  • Zubizarreta, I., Seravalli, A., & Arrizabalaga, S. (2016). Smart city concept: What it is and what it should be. Journal of Urban Planning and Development, 142(1), 04015005. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000282

Smart City Applications Awareness Scale Development and Implementation Study

Yıl 2025, Cilt: 25 Sayı: 4, 372 - 391, 29.12.2025
https://doi.org/10.18037/ausbd.1712489

Öz

The aim of this study is to develop the Smart City Applications Scale to measure the perceptions of individuals with different demographic characteristics living in the city regarding smart city applications, and to determine whether the perception of smart city applications differs according to demographic variables. During the scale development process, the first study group for Exploratory Factor Analysis (EFA) consisted of 259 adult individuals, while the second study group for Confirmatory Factor Analysis (CFA) consisted of 580 adult individuals, making a total sample size of 839 participants. Data analysis was conducted using the JASP program. In the study, EFA and CFA were applied to evaluate the construct validity of the scale. EFA was used to identify the factor structure of the scale and to determine which subdimensions the items were associated with. To confirm the obtained factor structure, CFA was conducted, and the model fit indices were evaluated. The KMO value, ranging from 0 to 1, supports the reliability of the analysis findings, as values above 0.90 are considered "excellent." The Bartlett’s Test of Sphericity (~χ² = 6542.77, sd = 377, p = .001) indicated that the correlation matrix was not an identity matrix, and significant relationships between the variables were found. It was determined that the scale is unidimensional and consists of 29 items. Reliability analyses revealed a McDonald’s ω (omega) coefficient of 0.97 and a Cronbach’s Alpha coefficient of 0.97. These findings demonstrate that the developed scale is a highly reliable and valid measurement tool.

Kaynakça

  • Abadía, J. J. P., Walther, C., Osman, A., & Smarsly, K. (2022). A systematic survey of internet of things frameworks for smart city applications. Sustainable Cities and Society, 83, 103949. https://doi.org/10.1016/j.scs.2022.103949
  • Avcı, E. (2024). Akıllı şehirler için üretken yapay zekâ kavramsal çerçevesi. Kent Akademisi, 17(5), 1654-1675. https://doi.org/10.35674/kent.1490925
  • Bartlett, M. S. (1954). A note on the multiplying factors for various chi-squared approximations. Journal of the Royal Statistical Society, 16(2), 296-298.
  • Brosnan, S. F. (1998). Psychology of computers and technology. Routledge.
  • Carvalho, L., Costa, A., & Dias, J. (2013). Smart cities and the internet of things: A survey. Proceedings of the 6th International Conference on Information and Communication Technologies for Sustainability (ICT4S), 45-56.
  • Calzada, I., & Cobo, C. (2015). Unplugging: Deconstructing the smart city. Journal of Urban Technology, 22(1), 23-43. https://doi.org/10.1080/10630732.2014.971535
  • 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
  • Chourabi, H., Nam, T., Walker, S., Gil-Garcia, J. R., Mellouli, S., Nahon, K., ... & Scholl, H. J. (2012). Understanding smart cities: An integrative framework. In 2012 45th Hawaii International Conference on System Sciences (pp. 2289-2297). IEEE. https://doi.org/10.1109/HICSS.2012.615
  • Cohen, S. (2004). Social relationships and health. American Psychologist, 59(8), 676-684. https://doi.org/10.1037/0003-066X.59.8.676
  • Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334.
  • Dameri, R. P. (2017). Smart city implementation. Progress in IS. Springer.
  • Diener, E., Emmons, R. A., Larsen, R. J., & Griffin, S. (1999). The satisfaction with life scale. Journal of Personality Assessment, 49(1), 71-75. https://doi.org/10.1207/s15327752jpa4901_13
  • Eremia, M., Toma, L., & Sanduleac, M. (2017). The smart city concept in the 21st century. Procedia Engineering, 181, 12-19. https://doi.org/10.1016/j.proeng.2017.02.357
  • Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). Sage Publications.
  • Falconer, G., & Mitchell, S. (2012). Smart city framework. Cisco Internet Business Solutions Group (IBSG), 12(9), 2-10.
  • Guo, Q., & Zhong, J. (2022). The effect of urban innovation performance of smart city construction policies: Evaluate by using a multiple period difference-in-differences model. Technological Forecasting and Social Change, 184, 122003. https://doi.org/10.1016/j.techfore.2022.122003
  • Guo, Q., Wang, Y., & Dong, X. (2022). Effects of smart city construction on energy saving and CO2 emission reduction: Evidence from China. Applied Energy, 313, 118879. https://doi.org/10.1016/j.apenergy.2022.118879
  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Pearson.
  • 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
  • Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1-55. https://doi.org/10.1080/10705519909540118
  • Jarrahi, M. H., Sawyer, S., & Erickson, I. (2022). Digital assemblages, information infrastructures, and mobile knowledge work. Journal of Information Technology, 37(3), 230-249. https://doi.org/10.1177/0268396221105094
  • Jebaraj, L., Khang, A., Chandrasekar, V., Pravin, A. R., & Sriram, K. (2023). Smart city: Concepts, models, technologies and applications. In smart cities (pp. 1-20). CRC Press.
  • Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31-36.
  • Kaluarachchi, Y. (2022). Implementing data-driven smart city applications for future cities. Smart Cities, 5(2), 455-474.
  • Kayahan- Yüksel, D. (2020). Değişen dünyada ayrımcılığa karşı kapsayıcı eğitim. M. Kanak & M. Ersoy (Ed.), Değişen dünyada çocuk içinde (s. 161-177). Eğiten Yayıncılık.
  • Khazael, B., Asl, M. V., & Malazi, H. T. (2023). Geospatial complex event processing in smart city applications. Simulation Modelling Practice and Theory, 122, 102675. https://doi.org/10.1016/j.simpat.2022.102675
  • Leung, L. (2015). Social media connectivity in China: The role of interactivity and social presence in mobile social networking. Computers in Human Behavior, 46, 272-283.
  • Lv, Z., Chen, D., & Lv, H. (2022). Smart city construction and management by digital twins and BIM big data in COVID-19 scenario. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 18(2s), 1-21. https://doi.org/10.1145/3529395
  • Mehta, S., Bhushan, B., & Kumar, R. (2022). Machine learning approaches for smart city applications: Emergence, challenges and opportunities. In Recent Advances in Internet of Things and Machine Learning: Real-World Applications (pp. 147-163).
  • Mokhtar, S. S., Sulaiman, N., & Hassan, M. R. (2012). Public service delivery and smart city concepts: A framework for service innovation in Malaysia. Procedia - Social and Behavioral Sciences, 62, 1239-1243.
  • Nam, T., & Pardo, T. A. (2011). Smart city as urban innovation: Focusing on management, policy, and context. In Proceedings of the 5th International Conference on Theory and Practice of Electronic Governance (ICEGOV2011). https://doi.org/10.1145/2072069.2072100
  • Neirotti, P., De Marco, A., Cagliano, A. C., Mangano, G., & Scorrano, F. (2014). Current trends in smart city initiatives: Some stylised facts. Cities, 38, 25-36. https://doi.org/10.1016/j.cities.2013.12.010
  • Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9(5), 1-6.
  • Shelton, T., Zook, M., & Wiig, A. (2015). The ‘actually existing smart city’. Cambridge Journal of Regions, Economy and Society, 8(1), 13-25. https://doi.org/10.1093/cjres/rsu026
  • Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). Allyn & Bacon.
  • Tyagi, N., & Bhushan, B. (2023). Demystifying the role of natural language processing (NLP) in smart city applications: Background, motivation, recent advances, and future research directions. Wireless Personal Communications, 130(2), 857-908.
  • Urhan, O., & Güllü, K. (2023). Veriye dayalı akıllı şehir oluşturmada teknoloji trendleri. Şura Akademi, (2), 19-25.
  • Venkatesh, V., & Morris, M. G. (2000). Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 115-139. https://doi.org/10.2307/3250981
  • Van Deursen, A. J., & Van Dijk, J. A. (2014). Digital skills: Unlocking the potential of a digital world. Springer.
  • Van Dijk, J. A. (2006). The network society: Social aspects of new media. Sage Publications.
  • Xia, X., Yu, R., & Zhang, S. (2023). Evaluating the impact of smart city policy on carbon emission efficiency. Land, 12(7), 1292. https://doi.org/10.3390/land12071292
  • Zubizarreta, I., Seravalli, A., & Arrizabalaga, S. (2016). Smart city concept: What it is and what it should be. Journal of Urban Planning and Development, 142(1), 04015005. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000282
Toplam 42 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Erişilebilir Bilgi İşlem
Bölüm Araştırma Makalesi
Yazarlar

Aysel Arslan 0000-0002-8775-1119

Mehmet Biçer 0009-0008-1043-6939

Fatıma Firdevs Adam 0000-0003-1765-6287

Gönderilme Tarihi 2 Haziran 2025
Kabul Tarihi 3 Aralık 2025
Yayımlanma Tarihi 29 Aralık 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 25 Sayı: 4

Kaynak Göster

APA Arslan, A., Biçer, M., & Adam, F. F. (2025). Akıllı Şehir Uygulamaları Farkındalık Ölçeği Geliştirme ve Uygulama Çalışması. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 25(4), 372-391. https://doi.org/10.18037/ausbd.1712489