Applying Analytic Hierarchy Process Methodology in Determining Critical Challenges of Urban Big Data in a Developing City
The Case of Tehran
DOI:
https://doi.org/10.33568/rbs.6914Keywords:
AHP methodology, big data, urban development, IranAbstract
Although urban big data holds significant potential for transforming the way cities are managed, harnessing this potential requires overcoming major challenges, particularly in developing countries like Iran. Obstacles like policy gaps, legal barriers, limited resources for data management and infrastructure or even the low level of community engagement and the lack of technological capabilities could backward the development of becoming a real data-driven smart city. This study aims to address the understanding of this issue, by identifying and evaluating urban big data challenges critically, and to formulate policy-related support for governmental bodies in a country considered to be a developing information society. After thorough analysis of academic publications we identified 32 urban big data challenges in Iran, which then were systematically evaluated and ranked by Analytic Hierarchy Process (AHP) methodology based on expert surveys. Outcomes confirmed that although social, educational and financial challenges have been perceived, the most important ones are of political and governmental origin.
References
Abella, A., Ortiz-de-Urbina-Criado, M., & De-Pablos-Heredero, C. (2017). A model for the analysis of data-driven innovation and value generation in smart cities’ ecosystems. Cities, 64, 47–53. https://doi.org/10.1016/j.cities.2017.01.011
Albino, V., Berardi, U., & Dangelico, R. M. (2015). Smart Cities: Definitions, Dimensions, Performance, and Initiatives. Journal of Urban Technology, 22(1), 3–21. https://doi.org/10.1080/10630732.2014.942092
Alkin, M., & Christie, C. (2004). An Evaluation Theory Tree. In Alkin M. (Ed.), Evaluation Roots (pp. 13–65). SAGE Publications. https://doi.org/10.4135/9781412984157.n2
Bahrami, M., Abdolvand, N., & Rajaee Harandi, S. (2020). Developing a Solution for Intelligent Urban Transportation Management Using the Internet of Things. Scientia Iranica, 28(2), 709–720. https://doi.org/10.24200/sci.2020.51688.2316
Bibri, S. E. (2019). Big Data Science and Analytics for Smart Sustainable Urbanism: Unprecedented Paradigmatic Shifts and Practical Advancements. Springer International Publishing. https://doi.org/10.1007/978-3-030-17312-8
Bolici, R., & Mora. L. (2015). Urban Regeneration in the Digital Era: How to Develop Smart City Strategies in Large European Cities. TECHNE – Journal of Technology for Architecture and Environment. (10), 110–119. https://doi.org/10.13128/Techne-17507
Boyd, D. & Crawford, K. (2012). Critical Questions for Big Data: Provocations for a Cultural, Technological, and Scholarly Phenomenon. Information, Communication & Society, 15(5), 662–679. https://doi.org/10.1080/1369118X.2012.678878
Cardullo, P., & Kitchin, R. (2018). Being a ‘citizen’ in the smart city: up and down the scaffold of smart citizen participation in Dublin, Ireland. GeoJournal, 84(1), 1–13. https://doi.org/10.1007/s10708-018-9845-8
Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approach (4th ed). SAGE Publications.
Davarazar, P. & Lotfollahi, F. (2020). A Scientometric Study on the Analytical Hierarchy Process with Emphasis on Urban Affairs Management. Journal of Settlements and Spatial Planning, SI(6), 97–112. https://doi.org/10.24193/JSSPSI.2020.6.10
Davenport, T. H. (2014). Big Data at Work: Dispelling the Myths, Uncovering the Opportunities. Harvard Business Review Press.
De Mauro, A., Greco, M., & Grimaldi, M. (2015). What is big data? A consensual definition and a review of key research topics. AIP Conference Proceedings. 1644(1), 97–104. https://doi.org/10.1063/1.4907823
European Union Agency for Fundamental Rights (2018). Big Data, Discrimination and Fundamental Rights. Publications Office of the European Union. https://fra.europa.eu/en/publication/2018/big-data-discrimination
European Commission (2020). A European Strategy for Data. EC. https://digital-strategy.ec.europa.eu/en/policies/strategy-data
Govindan, K., Rajendran, S., Sarkis, J., & Murugesan, P. (2015). Multi criteria decision making approaches for green supplier evaluation and selection: a literature review. Journal of Cleaner Production, 98, 66–83. https://doi.org/10.1016/j.jclepro.2013.06.046
Han, W., Luan, H., & Liu, C. (2018). Assessment of Bolt Reinforcement Effect Based on Analytic Hierarchy Process. Geotechnical and Geological Engineering, 37, 803–812. https://doi.org/10.1007/s10706-018-0650-4
Lim, C., Kim, K.-J., & Maglio, P. P. (2018). Smart cities with big data: Reference models, challenges, and considerations. Cities, 82, 86–99. https://doi.org/10.1016/j.cities.2018.04.011
Janssen, M., Charalabidis, Y., & Zuiderwijk, A. (2012). Benefits, Adoption Barriers and Myths of Open Data and Open Government. Information Systems Management, 29(4), 258–268. https://doi.org/10.1080/10580530.2012.716740
Janssen, M., van der Voort, H., & Wahyudi, A (2017). Factors influencing big data decision-making quality. Journal of Business Research, 70, 338–345. https://doi.org/10.1016/j.jbusres.2016.08.007
Jiang, H., Geertman, S., & Witte, P. (2020). A Sociotechnical Framework for Smart Urban Governance. International Journal of E-Planning Research, 9(1), 1–19. https://doi.org/10.4018/ijepr.2020010101
Katzman, K. (2020). Iran Sanctions. Congressional Research Service. https://nsarchive.gwu.edu/document/27084-document-230-congressional-research-service-kenneth-katzman-iran-sanctions-november
Keyvanpour, M. R., & Moradi, S. S. (2014). A Perturbation Method Based on Singular Value Decomposition and Feature Selection for Privacy Preserving Data Mining. International Journal of Data Warehousing and Mining, 10(1), 55–76. https://doi.org/10.4018/ijdwm.2014010104
Kitchin, R. (2014). The real-time city? Big data and smart urbanism. GeoJournal, 79(1), 1–14. https://doi.org/10.1007/s10708-013-9516-8
Kitchin, Rob (2016). Getting Smarter about Smart Cities: Improving Data Privacy and Data Security. Data Protection Unit, Department of the Taoiseach.
Kitchin, R. & Lauriault, T. (2018) Towards critical data studies: Charting and unpacking data assemblages and their work. In Thatcher, J., Eckert, J. & Shears, A. (Eds.), Thinking Big Data in Geography (pp. 3–20). University of Nebraska Press.
McAfee, A., & Brynjolfsson, E. (2012). Big Data: The Management Revolution. Harvard Business Review, 90(10), 60–68.
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
Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hoagwood, K. (2015). Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Administration and Policy in Mental Health and Mental Health Services Research, 42(5), 533–544. https://doi.org/10.1007/s10488-013-0528-y
Rabari, C., & Storper, M. (2014). The digital skin of cities: urban theory and research in the age of the sensored and metered city, ubiquitous computing and big data. Cambridge Journal of Regions, Economy and Society, 8(1), 27–42. https://doi.org/10.1093/cjres/rsu021
Shadroo, S., & Rahmani, A. M. (2018). Systematic survey of big data and data mining in internet of things. Computer Networks, 139, 19–47. https://doi.org/10.1016/j.comnet.2018.04.001
Razavian, B., Hamed, S. M., Fayyaz, M., Ghasemi, P., Ozkul, S., & Tirkolaee, E. B. (2024). Addressing barriers to big data implementation in sustainable smart cities: Improved zero-sum grey game and grey best-worst method. Journal of Innovation & Knowledge, 9(4), 100593. https://doi.org/10.1016/j.jik.2024.100593
Selmi, M., Kormi, T., & Bel Hadj Ali, N. (2016). Comparison of multi-criteria decision methods through a ranking stability index. International Journal of Operational Research, 27(1/2), 165–183. https://doi.org/10.1504/IJOR.2016.078462
Supreme Council of Cyberspace (Iran) (2018). Strategic Plan for Development of Smart Cities in Iran. Tehran: SCC.
Thakuriah, P., Tilahun, N. & Zellner M. L. (Eds.) (2017) Seeing Cities Through Big Data. Springer Geography. Springer International Publishing. https://doi.org/10.1007/978-3-319-40902-3
Velasquez, M. & Hester, P. T. (2013) An Analysis of Multi-Criteria Decision-Making Methods. International Journal of Operations Research, 10(2), 56–66.
World Bank (2017). Digital Dividends – World Development Report 2016. https://www.worldbank.org/en/publication/wdr2016
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