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Journal of Information and Optimization Sciences cover
Hybrid ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667

WoS  JIF 2026 : 0.4 (Q4)

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Monthly Journal: Publishes theoretical and applied research on topics in information and optimization sciences.

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Open Access Research Article

Evaluation of the intergenerational relationship of IoT awareness in businesses

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pp. 1753–1772Vol. 46Issue 5July 2025DOI: 10.47974/JIOS-1971XML
Received:
10 Dec 2024
Published Online:
09 Jul 2025
Article type:
Research Article
Language:
EN
Article no.:
JIOS-1971
Pages:
1753–1772

Abstract

This study aimed to examine the Internet of Things (IoT) awareness levels of generations with different demographic characteristics of society. In the research, sample selection was made from production, agriculture and service sectors. In the research, the relationship between IoT awareness was examined according to the demographic characteristics of the participants such as generation, gender, line of business, education level and social media usage intensity. The research was analysed using AMOS for path analysis for the model assumption and SPSS 24.0 for other analyses. Parametric and nonparametric hypothesis tests performed at the 0.05 significance level showed that there was no significant difference in IoT awareness levels depending on demographic characteristics. These results show that, despite the common belief that Generation Z is different from previous generations, there is no significant separation in IoT awareness compared to other generations. The research results support that the level of IoT awareness is not determined by the demographic characteristics examined and is generally widespread in society. These findings show that IoT technology is becoming increasingly widespread and reaching every segment of society.

Keywords

Subject Classifications

68-0268Q1194-0294A16

References

[1] Mohammad Soori, Arezoo B., and Reza Dastres, “Internet of Things and Cyber-Physical Systems,” Internet of Things and Cyber-Physical Systems, vol. 3, pp. 192–204 (2023).
[2] Carlo Tomazzoli, Silvia Scannapieco, and Michele Cristani, “Internet of Things and Artificial Intelligence Enable Energy Efficiency,” Journal of Ambient Intelligence and Humanized Computing, vol. 14, no. 5, pp. 4933–4954 (2023).
[3] Hamid Allioui and Yassine Mourdi, “Exploring the Full Potentials of IoT for Better Financial Growth and Stability: A Comprehensive Survey,” Sensors, vol. 23, no. 19, p. 8015 (2023).
[4] Anindya Chakraborty, Md. Islam, Fahim Shahriyar, S. Islam, H. U. Zaman, and Md. Hasan, “Smart Home System: A Comprehensive Review,” Journal of Electrical and Computer Engineering, vol. 2023, no. 1, Article ID 7616683 (2023).
[5] Mazin Al-Khafajiy, Tarek Baker, Chris Chalmers, Muhammad Asim, Hoshang Kolivand, M. Fahim, and A. Waraich, “Remote Health Monitoring of Elderly Through Wearable Sensors,” Multimedia Tools and Applications, vol. 78, no. 17, pp. 24681–24706 (2019).
[6] Kiran Meduri, G. S. Nadella, H. Gonaygunta, and S. S. Meduri, “Developing a Fog Computing-Based AI Framework for Real-Time Traffic Management and Optimization,” International Journal of Sustainable Development in Computing Science, vol. 5, no. 4, pp. 1–24 (2023).
[7] Naveen Vemuri, N. Thaneeru, and V. M. Tatikonda, “Smart Farming Revolution: Harnessing IoT for Enhanced Agricultural Yield and Sustainability,” Journal of Knowledge Learning and Science Technology, vol. 2, no. 2, pp. 143–148, ISSN: 2959-6386 (2023).
[8] Abid Haleem, M. Javaid, R. P. Singh, R. Suman, and S. Khan, “Management 4.0: Concept, Applications and Advancements,” Sustainable Operations and Computers, vol. 4, pp. 10–21 (2023).
[9] Arnab Hazra, P. Rana, M. Adhikari, and T. Amgoth, “Fog Computing for Next-Generation Internet of Things: Fundamental, State-of-the-Art and Research Challenges,” Computer Science Review, vol. 48, Article 100549 (2023).
[10] Bilal Gulzar, S. A. Sofi, and S. Sholla, “Exploring Personalized Internet of Things (PIoT), Social Connectivity, and Artificial Social Intelligence (ASI): A Survey,” High-Confidence Computing, Article 100242 (2024).
[11] Nikola Savić, Jovana Lazarević, Aleksandar Jeličić, and Filip Grujić, “Digital Economy and New Capitalism: Generation Z as Consumer,” Ekonomika preduzeća, vol. 72, no. 1–2, pp. 107–123 (2024).
[12] Lily Y. Rock, F. P. Tajudeen, and Y. W. Chung, “Usage and Impact of the Internet-of-Things-Based Smart Home Technology: A Quality-of-Life Perspective,” Universal Access in the Information Society, vol. 23, no. 1, pp. 345–364 (2024).
[13] Şükrü Mert Kaya, A. Erdem, and A. Güneş, “A Smart Data Pre-Processing Approach to Effective Management of Big Health Data in IoT Edge,” Smart Homecare Technology and TeleHealth, pp. 9–21 (2021). DOI: 10.2147/SHTT.S313666.
[14] Volkan Bayram and Şükrü Mert Kaya, İşletme Bilgi Sistemlerinde Nesnelerin İnterneti (IoT): Uygulama Alanları, in Stratejik Yönetimde İşletme ve Yönetim Bilgi Sistemleri, Nobel Bilimsel Eserler (2023).
[15] Peter B. Clarke, Din Sosyolojisi, Trans. İhsan Çapçıoğlu, Ankara, Turkey: İmge Kitabevi, [n.d.].
[16] Mehmet Özkan and Banu Solmaz, “Generation Z—The Global Market’s New Consumers—and Their Consumption Habits: Generation Z Consumption Scale,” European Journal of Multidisciplinary Studies, vol. 2, no. 5, pp. 222–229 (2017).
[17] Brenda R. Kupperschmidt, “Multigenerational Employees: Strategies for Effective Management,” The Health Care Manager, vol. 19, no. 1, pp. 65–76 (2000).
[18] Jean M. Twenge and W. Keith Campbell, “Birth Cohort Differences in the Monitoring the Future Dataset and Elsewhere: Further Evidence for Generation Me—Commentary on Trzesniewski & Donnellan (2010),” Perspectives on Psychological Science, vol. 5, no. 1, pp. 81–88 (2010).
[19] Rein De Cooman and Nicky Dries, “Attracting Generation Y: How Work Values Predict Organizational Attraction in Graduating Students in Belgium,” in Managing the New Workforce, pp. 42–63. Edward Elgar Publishing (2012).
[20] Ádám Nagy and András Kölcsey, “Az Alfa-Generáció Margójára: Marketing Vagy Tudomány?” pp. 1–11 (2016). [Online]. Available: https://real.mtak.hu/62421/
[21] Manickam Rajan Thomas and M. P. Shivani, “Customer Profiling of Alpha: The Next Generation Marketing,” Ushus Journal of Business Management, vol. 19, no. 1, pp. 75–86 (2020).
[22] Volkan Bayram and Şükrü Mert Kaya, “İşletmelerde Nesnelerin İnterneti (IoT) Farkındalık Ölçeği Geliştirme Çalışması,” İktisadi, İdari ve Siyasal Araştırmalar Dergisi, vol. 9, no. 24, pp. 447–465 (2024).
[23] Darren George and Paul Mallery, SPSS for Windows Step by Step: A Simple Study Guide and Reference, 17.0 Update (10/a). Pearson Education India (2010).
[24] Jos J. A. Moors, “The Meaning of Kurtosis: Darlington Reexamined,” The American Statistician, vol. 40, pp. 283–284 (1986). DOI: 10.1080/00031305.1986.10475415.
[25] Lawrence T. De Carlo, “On the Meaning and Use of Kurtosis,” Psychological Methods, vol. 2, no. 3, pp. 292–307 (1997). https://doi.org/10.1037/1082-989X.2.3.292.
[26] Kenneth D. Hopkins and David L. Weeks, “Tests for Normality and Measures of Skewness and Kurtosis: Their Place in Research Reporting,” Educational and Psychological Measurement, vol. 50, pp. 717–729 (1990). https://doi.org/10.1177/0013164490504001
[27] Richard A. Groeneveld and George Meeden, “Measuring Skewness and Kurtosis,” Journal of the Royal Statistical Society: Series D (The Statistician), vol. 33, no. 4, pp. 391–399 (1984). https://doi.org/10.2307/2987742.

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