Application of Structural Equation Model in Explaining the Role of Factors Affecting the Realization of Urban Development Plans (Case Study: Shiraz City)

Subject Areas :

Naser Rezaei ¹ , Hamid Majedi ² , Zahra Sadat Saeideh Zarabadi ³ , Hossein Zabihi ⁴

1 - Ph.D. Student, Department of Urban Development, Science and Research Branch, Islamic Azad University, Tehran, Iran.
2 - Professor, Department of Urban Planning, Science and Research Branch, Islamic Azad University, Tehran, Iran.
3 - Associate Professor, Department of Urban Development, Science and Research Branch, Islamic Azad University, Tehran, Iran.
4 - Associate Professor, Department of Urban Development, Science and Research Branch, Islamic Azad University, Tehran, Iran.

Received: 2019-05-08 Accepted : 2019-10-18 Published : 2020-10-22

Keywords: Land use change, Shiraz, Land Use, SEM, urban development plan,

Abstract :

Urban development plans are progressing towards becoming more effective in their evolutionary process, with the goal of serving human beings with a modeling of sustainable development components. One of the major goals of urban development plans is the provision of basic services and infrastructures for the full development of human settlements. In this regard, the main purpose of this paper is to explain the factors affecting the change of service landuses in the city of Shiraz and identify its reasons. This research is an exploratory research, which first studies the concepts related to land use change using document-library sources and then investigates the severity of the effect of the four factors (physical, activity, economic, accessibility) on land use change and their desirability. For this purpose, the second-order confirmatory factor analysis technique has been used to determine the severity of the effect of the four factors on land use change, through which a contributing framework for the effects of the four factors on land use change is obtained. Finally, the extent and direction of the factors affecting the realization of service land uses in the city of Shiraz are explained using the structural equation model (SEM). In order to achieve these goals, 50 variables affecting 600 plots in Shiraz city are extracted through field method. The variables are investigated and analyzed using GIS maps, Amos and SPSS software. The results of the research show that, in total, the selected four factors have a significant effect on the land use change. It is such that the standardized weights of regression for "the effect of the access factor on land use change", "the effect of the economic factor on land use change", "the effect of the activity factor on land use change", and "the effect of the physical factor on land use change" are 0.91, 0.78, 0.65, and 0.56, respectively. Extended Abstract Introduction:        As the rapid growth of population and the development of cities, especially metropolises have led to rapid changes in the land use patterns in and around cities, the majority of urban planners have emphasized the need to rethink the urban development plans, with particular emphasis on their feasibility, especially in land use, at a variety of time points. Although these urban development plans are costly and time consuming and have significant impacts on land use zoning and adherence to building regulations, they have not been feasible for some reason. One of the major goals of urban development projects in cities such as Shiraz metropolis is to provide essential services and human and urban infrastructure for the comprehensive development of human settlements. However, like many other big cities, Shiraz, which has been experiencing high population growth and poor physical development, has faced numerous challenges in realizing its urban development plans and goals, including the anticipated land uses and essential services and infrastructure. Since several factors influence the feasibility of urban development plans, the main question of this paper is to determine what factors and to what extent have influenced land use change in Shiraz for the past 20 years. The main purpose of this paper is to determine the factors that affect the implementation of urban development plans and land use changes in Shiraz and specify the complex relationships between these factors using structural equation modeling (SEM). Methodology:            In order to achieve the abovementioned goal, applying SEM structural equation modeling in analyzing the relationships of variables and achieving the optimal land planning model, the causal relationship as well as the hidden and explicit variables have been found at the level of complex equations. In this context, used documentary-library resources, the concepts related to the land use change have been studied first. Then, the impact of the quadripartite factors (physical, activity, economic, accessibility) on the land use change and the desirability of this impact have been investigated. To this end, second-order confirmatory factor analysis technique as one of the structural equation modeling techniques has been used to determine the severity of the effect of these quadripartite factors on the land use change, achieve an explanatory framework to specify this effect and finally, explain the extent and direction of the factors affecting the feasibility of service applications in Shiraz. In total, to achieve these goals, first, 50 variables affecting 600 sections have been field-sampled in Shiraz (their land use has been changed in Article Five Commission from 1994 to 2017) and analyzed using GIS maps as well as Amos and SPSS software to examine a set of bivariate correlations in a table called correlation matrix or covariance matrix, the most important of which are confirmatory factor analysis and structural equation modeling (SEM). RESULT AND DISCUSSION         Using SEM, it was found that the selected four factors (physical, activity, economic, accessibility) have a significant effect on the land use change. It is such that the standardized weights of regression for "the effect of the access factor on land use change", "the effect of the economic factor on land use change", "the effect of the activity factor on land use change", and "the effect of the physical factor on land use change" are 0.91, 0.78, 0.65, and 0.56, respectively. Moreover using SPSS software, more than 50 parameters were analyzed in about 600 plots having land use changed during 1994-2017 and the following results were determined: Most land use changes were in districts 1, 2, 7, 5, 3, 4, 10, 9, 6, and 11. 91% of the plates that had land use change during the years 1994 to 2017 had land use change in other plates within a range of around 500 meters radius. 95% of the plates that had land use change were outside the heritage zones and 50% of the plates that had land use change from 1994 to 2017 were far from natural zones and the other half was near the natural zones. More than 88% of the plates that had land use change from 1994 to 2017 were not on the development path of the city. Approximately 50% of the plates that had land use change from 1994 to 2017 had a good, high-quality landscape. Among the plates that had land use change from 1994 to 2017, 21.3% had a garden use in the detailed plan approved in 1994, 18.2% had a residential use, 15.1% were in the urban area, 13.6% had a park and green space use, and 11.4% had an educational use. The range of price changes of lands that had land use change varied from 500 to 10 million Tomans per meter, indicating that all urban lands with different economic positions are affected. In 73% of the land use change cases, the density predicted for land in the review plan is not proportional to the land economy. 61% of plates are within the scope of effective urban projects, 36% are not within the scope of effective urban projects, and 1.4% are negatively affected by urban projects. CONCLUSION:            Generally the results indicate that in an exploratory factor analysis process, the structural equation model (SEM) was used for the first time in order to clarify the relationship between criteria and indicators of the effectiveness of urban development plans. Also, the effect of new indicators was also explored in the research process which indicated that the model is a suitable tool for developing the hidden and obvious variables of the research subject as well as providing new indicators for feasibility studies in Iranian examples in international studies.

References:

1. Habibi, A. (2012). LISREL Applied Learning. Tehran: Second Edition: Summer.


2. Soltani, F. (1999). Preliminary research in the formulation of land theory for the realization of urban development plans. Proceedings of the Conference on Land and Urban Development.


3. Kalantari, K. (2009). Modeling of Structural Equations in Socio-Economic Research (Using LISREL and SIMPLES). Saba Farhang Publications.


4. Deputy of Shiraz Municipality Urban Planning. (2016). Statistical Yearbook of Shiraz,. Shiraz.


5. Azizi, M. M., & Dehghani. (2013). Measuring factors affecting land use changes in metropolitan expansion process (Case study: District 22 of Tehran City). Armanshahr Journal of Architecture and Urban , 343-359.


6. Taqizadeh, M. (2016). Comparison of urban land use change mechanisms (Case study: England, USA, India, Turkey, and Iran. Armanshahr Journal of Architecture and Urban Planning, 317-328.


7. Briasolis, H. (2010). Analytical Patterns of Land Use Change. (M. Rafieian, & M. Mahmoodi, Trans.) Tehran: Azarakhsh Publications.


8. Kafashi, M. (2011). Structural Equation Modeling of Educational Indicators Affecting the Social Confidence of Tehran Citizens in Islamic Azad University. Journal of New Thoughts in Educational Sciences, 6(2), 103-122.


9. Mahdizadeh, J. (2000). New Perspectives and Solutions in Land Use Planning. Proceedings of the Articles on Land and Urban Development. Tehran.


10. Fesharaki, M. (1977). Structural equation modeling and its application in psychological studies (Case study). Clinical and Personality Psychology Periodical, 16(1), 253-265.


11. Dadashpour, H., Kheiroddin, R., Yaghub Khani, M., & Chamani, B. (2013). Modeling of land use changes in Tehran metropolis using MOLAND model. Regional Planning Quarterly, 4(16), 49-64.


12. Akbari, M., & Rezaei, R. (1979). Evaluation of Land Use Changes in Isfahan Metropolis: District 3. Journal of Urban Research and Planning, 9(34), 93-104.


13. Zangi Aabadi, A., Abdolahi, M., Salek, G. R., & Qasemzade, B. (2014). Evaluation of factors affecting the implementation of urban master plans in Iran and its related challenges (Case study: Historical-cultural axis of District 6 of Tabriz). Journal of Urban Research and Planning, 5(18), 41-58.


14. Rezaei, N., Majedi, H., Zabihi, Z. S., & Zabihi, H. (2018). Explaining the role of factors affecting the implementation of urban development plans (Case study: Shiraz City). Journal of Urban Research and Planning, 9(34), 47-58.


15. Alterman, R. and Moris H. (1978): Implementation of Urban Land Use Plans, Journal of the American Institute of Pllaners. Vol 44, No. 3, pp. 274-285.


16. Batty, M. and P. M. Torrens (2001): Modeling complexity: the limits to prediction. CyberGeo 201.


17. Behn, R.D. (1980): Why Murphy Was Right?.Policy Analysis, 6, pp. 361-363.


18. Berke, P. Backhurst, M. Day, M. Ericksen, N. Laurian, L. Crawford, J. Dixon, J (2006): What makes plan implementation successful? An evaluation of local plans and implementation practices in New Zeland, Environment and Planning B: Planning & Design 33(4). 581-600.


19. 19.   Briamoh, A. K., Onishi, T. (2007): Spatial Determinants of Urban Land-Use Change in Lagos. Nigeria. Land Use Policy, (2)24, pp.502-515.


20. Browne, M. W., & Cudeck, R. (1993): Alternative ways of assessing model fit. In K. A. Bollen and J. S. Long (Eds.), Testing structural equation models (pp. 136-162). Newbury Park, CA.


21. Carmona, M. de Magalhães & Edwards, M.( 2001): The Value of Urban Design, London, CABE (Thomas Telford).


22. Cowan, R. (2005): The Dictionary of Urbanism, Streetwise Press, Tisbury.


23. Dalton, J. Elias, M. Wandersman, A. (2007): Community Psychology: Linking Individuals and Communities. (2nd Ed), Belmont, CA: Wadsworth.


24. Elmore, R. F. (1979): Backward Mapping: Implementation Research and Policy Decisions. Political Science Quarterly, 94, pp. 601-616.


25. Fixsen, D. L. Naoom, S. F. Blase, K. A., Friedman, R. M., Wallace, F. (2005): Implementation Research: A


26. Hoyle, R. H. (2012): Handbook of Structural Equation Modeling. 1 st ed.New York: The Guilford press.


27. Khoury, Z. B. (1996): Implementing the New Urban Agenda: The Case of Ismailia, Egypt. Environment &Urbanization, 8 (1). April.


28. Lang, J. (2005): Urban Design: A Typology of Procedures and Products. Oxford: Architectural Press.Decision Making Model.


29. Laurian, L. Day, M. Backhurst, M. Berke, P. Ericksen, N. Crawford, J. Dixon, J. Chapman, S. (2004): What drives plan implementation? Plans, planning agencies and developers, Journal of Environmental Planning and Management 47(4), pp. 555-77.


30. Long, H., Guoping, T., Xiubin, Li. & Gerhard, K. (2007): Socio-economic driving forces of land-use changes in Kunshan, the Yangtze River Delta economic area of China. Journal of Environmental Management, 83, pp. 351-364.


31. Luo, J., Wei, Y. (2009): Modeling Spatial Variations of Urban Growth Patterns in Chinese Cities: The Case of Nanjing [J]. Landscape and Urban Planning, 91(2), pp. 51-64.


32. MacCallum, R. C. Browne, Michael. W. Sugawara, Hazuki. M. (1996): Power Analysis and Determination of Sample Size for Covariance Structure Modeling. Psychological Methods. Vol, I, No. 2. Pp. 130-149.   


33. Moughtin, K. Cuesta, R. Sarris, C. Signoretta, P. (1999): Urban Design, Method and Techniques. Oxford: Architectural Press.


34. Norton, R.(2005): More and better local planning. A state-mandated local planning in Coastal North Carolina” Journal of the American Planning Association 71(1), pp. 55-71.


35. Nutt, P.C. 2007. Examining the Link between Plan Evaluation and Implementation, Technological Forecasting and Social Change. 74(8), pp. 1252-1271.


36. Oliveira, V. Pinho, P. (2008): Urban planning and regeneration in Oporto, 2004-2007” (submitted to Cities).


37. Parshall, S. & Pena, W. (2001): Problem Seeking: An Architectural Programming Primer. New York: John  Wiley & Sons.


38. Seto L. C., Woodcock C. E., Song C., Huang X., Lu J.& Kaufmann R. K. (2002): Monitoring land use change in the Pearl river delta using Landsat TM. International journal of remote sensing, 23 (10), pp. 989-1003.


39. Talen, E (1997): Success, failure and conformance: an alternative approach to planning evaluation, Environment and Planning B: Planning & Design 24(4), pp. 573-587.


40. Verburg, P. H., Schot, P. P., Dijst, M. J., Veldkamp, A. (2004): Land Use Modelling Current Practice and Research Priorities. GeoJournal, 61, pp. 309-324.