Document Type : Research Paper
Authors
1 Esmal nasiri hendehkhalel associat professor at geography and urban planning in payame nor university tehran–iran
2 Master of Urban Planning, Payame Noor University, Tehran, Iran
Abstract
Introduction
The city is a cultural-physical complex that is formed based on the needs, activities and behaviors of its inhabitants (Pour Mohammadi et al., 2015: 30). Urban spaces are one of the areas of manifestation of human behavior (Bardi Anna Moradnejad and Makran 20: 1398). Attention is paid to the links between spatial changes in the city and people's behavioral patterns (Abdolhahi Turkmani et al., 2012: 211). It also includes any activity or action that a living being performs, such as "a reflection or set of values based on a person's situation." D (Saeidian, 1382: 52) During the process of socialization, behavior is influenced by culture and by this process; language, customs and traditions, values and expectations are taught (Namazian, 1: 1397) Bahraini states that activities Humans rely on culture, culture creates a pattern of behavior, and this "behavioral pattern determines and expresses how people use spaces" (Bahraini, 2011: 43) Environment of artificial, natural and Their composition is composed. (Farhang Doostfard, 2000, 1997).
Data and Method
In order to have a normal data distribution, the Kolmogorov-Smirnov test was used. Independent variables of this study include indicators of diversity, flexibility, permeability, visual fitness, readability, sensory richness and variable and behavioral patterns of citizens. . The selection of these variables was done to measure based on theoretical literature and the sources of existing research, as well as interviews with experts in the field of urban planning. In order to measure the questions related to the effect of physical-environmental components on the behavioral pattern of citizens, the Cronbach's alpha obtained is 0.76 and since this value is higher than 0.7, it indicates that the questions related to the variables have a good reliability. The statistical population of this study is the beneficiaries of the use of the space of 30 Tir Street, who have been present at the place of residence from 10:00 AM to 10:00 PM. The sampling method was also random, using cluster sampling with a simple random sampling of 384 people. In order to measure the reliability of the questionnaire, a prototype included 30 over-tested questionnaires. Then, using Cronbach's alpha method, its reliability was checked. This figure was obtained for independent variables of 0.787 and for 0.77 variables, which indicates the necessary reliability of the questionnaire.
Results and Discussion
The Pearson coefficients correlation matrix between the components of physical components with behavioral patterns can be observed. The results show that there was the highest correlation coefficient between the dimensions of physical components with the behavioral patterns of citizens between permeability (P <0.01, r = 0.0579) and the lowest correlation coefficient between sensory richness and behavioral patterns. . (P <0.01, p = 0.142) In this study, multiple regression analysis between the components of physical components was used as a predictor variable and behavioral patterns were used as a criterion variable by simultaneous method. The results of multiple correlation coefficients indicate that in general, there is a direct relationship between the components of physical components with the behavioral patterns of citizens and significant statistical continuity. (599R =, 01 / 0sig =). In addition, the correlation coefficient shows that by changing the status of physical components, the behavioral patterns of their citizens also increase. 0) and visual fit (0.187) is clearly evident, but in terms of the impact of sensory richness in the study area, this impact on citizens' behavioral patterns has been largely indirect. The value of F is equal to 984.764 and its significance is equal to 0.000 and since it is less than 0.05, its significance is obvious and shows that the dimensions of the independent variables in this study can change the dependent variable. Express. Therefore, considering the calculated value for F at the 99% confidence level, it can be said that the linear composition of the independent variables in this study are also significant and as a result, they are able to predict the variable changes
Conclusion
The Pearson coefficients correlation matrix between the components of physical components with behavioral patterns can be observed. The results show that there was the highest correlation coefficient between the dimensions of physical components with the behavioral patterns of citizens between permeability (P <0.01, r = 0.0579) and the lowest correlation coefficient between sensory richness and behavioral patterns. . (P <0.01, p = 0.142) In this study, multiple regression analysis between the components of physical components was used as a predictor variable and behavioral patterns were used as a criterion variable by simultaneous method. The results of multiple correlation coefficients indicate that in general, there is a direct relationship between the components of physical components with the behavioral patterns of citizens and significant statistical continuity. (599R =, 01 / 0sig =). In addition, the correlation coefficient shows that by changing the status of physical components, the behavioral patterns of their citizens also increase. 0) and visual fit (0.187) is clearly evident, but in terms of the impact of sensory richness in the study area, this impact on citizens' behavioral patterns has been largely indirect. The value of F is equal to 984.764 and its significance is equal to 0.000 and since it is less than 0.05, its significance is obvious and shows that the dimensions of the independent variables in this study can change the dependent variable. Express. Therefore, considering the calculated value for F at the 99% confidence level, it can be said that the linear composition of the independent variables in this study are also significant and as a result, they are able to predict the variable changes.
Keywords
Main Subjects
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