توسعه های کالبدی مختلف و عوامل موثر بر رفتار سفر در سه محله کلان شهر تهران (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
هدف پژوهش حاضر شناسایی معیارهایی است که به دلیل تفاوت های توسعه های مختلف کالبدی بر رفتار سفر تأثیر می گذارند. جهت دستیابی به این مهم، ۲۷۱ پرسشنامه از سه محله منیریه، کوی بیمه و کوی گلستان به عنوان محدوده های موردمطالعه در بافت قدیم، میانی و جدید در شهر تهران جمع آوری شد. عوامل موثر بر رفتار سفر با استفاده از روش کمی ِتحلیل عاملی اکتشافی استخراج و در تحلیل رگرسیون جهت یافتن عوامل موثر بر رفتار سفر به تفکیک مدهای سفر، استفاده شد. از آزمونِ ANOVA یک طرفه جهت تحلیل تفاوت معناداریِ میان توسعه های کالبدی مختلف ازلحاظ رفتار سفر و عوامل موثر بر آن و آزمونِ Dunnett’s T3 برای مشخص کردن اینکه کدام محدوده متفاوت از دیگر محدوده های مطالعاتی است، استفاده شد. درنهایت با مقایسه نتایج تحلیل رگرسیون و آزمون ANOVA، پنج عامل وابستگی و دوستدار اتومبیل شخصی، تنوع و تراکم خرده فروشی ها، تراکم و دسترسی به واحدهای آموزشی و پارک، دسترسی به مراکز درمانی و خدماتی، مالکیت خودرو به عنوان عوامل موثر بر رفتار سفر که به دلیل تفاوت در توسعه های کالبدی بر رفتار سفر تأثیر می گذارند و عوامل نزدیکی به ایستگاه حمل ونقل عمومی، ترجیحات قابلیت دسترسی در انتخاب محل سکونت، دوستدار مدهای غیر اتومبیل شخصی، دارای گواهینامه، تعداد فرزندان زیر 5 سال و سن به عنوان معیارهایی که فارغ از نوع توسعه کالبدی با رفتار سفر ارتباط دارند در سه محله با توسعه های کالبدی متفاوت مشخص شد. تمایز میان این دو دسته در برنامه ریزی و طراحی توسعه های کالبدی (محلات) برای کاهش مد سفر با اتومبیل شخصی و افزایش دیگر مدهای سفر نقش بسزایی داردDifferent Physical Patterns and Travel Behavior Factors in Three Neighborhoods in the Tehran Metropolis
Despite a wide range of components and criteria affecting travel behavior presented through empirical research, the results of these studies are inconclusive, which could be due to the difference between these components and criteria in the study areas. Therefore, this research presented a method to determine which factors in different physical developments affect travel behavior due to the differences in various physical developments. The required information was collected through 271 questionnaires at the level of three neighborhoods of Monirieh, Koye Bimeh, and Koye Golestan in Tehran, Iran, as the old, conventional, and new neighborhoods, respectively. ANOVA test was exerted to analyze the significant difference between different development patterns in three neighborhoods. Dunnett's T3 was applied to determine which neighborhood caused the difference between groups. Also, the factors affecting travel behavior were obtained based on exploratory factor analysis indicators. Finally, by comparing the results of the ANOVA test and regression analysis, it was discovered that factors such as car ownership, dependence and pro-liking for private cars, density and access to educational centers and parks, access to medical and service centers, and variety and density of retail stores had been introduced as the factors affecting travel behavior due to the differences in development patterns. However, proximity to the public transportation station, accessibility preferences in choosing a residence, dependence, and pro-liking for other than a private car, having a license, number of children under five years old, and age have influenced travel behavior regardless of the variation between neighborhoods.
Extended
Introduction
Finding factors affecting travel behavior has been one of the main concerns of transportation planners. However, in the last two decades, the importance of the influence of the features of the built environment, including land use, along with demographic-economic characteristics, travel behavior, and attitudes of people, has been raised by urban planners. Studies seek to find factors affecting travel behavior, especially land use characteristics. Despite presenting a wide range of components and criteria affecting travel behavior, the results of the studies are inconclusive, which could be due to the difference between these components and criteria in the study areas. Therefore, this research presented a method to determine which factors in different physical developments affect travel behavior due to the differences in various physical developments. In order to do this, it must first be determined whether the study areas/different development patterns have a significant difference in terms of travel behavior or not. In case of a positive answer to the previous question, the following question is which study areas caused this difference. The next question arises:
-Which physical and non-physical characteristics affect travel behavior due to distinctions between different development patterns?
Methodology
The present research method is analytical and experimental based on quantitative methods. This research chose the frequency of travel by private car, public transportation, and walking as the travel behavior. According to the research's purpose, indicators and criteria affecting travel behavior were extracted after reviewing the theoretical and experimental literature. Then, the required information was collected through 271 questionnaires at the level of three neighborhoods of Monirieh, Koye Bimeh, and Koye Golestan as the old, conventional, and new neighborhoods, respectively. The questionnaire was compiled as a Likert scale in five parts of travel information, demographic-economic characteristics, perceptual characteristics of land use, travel habits, and access preferences of people in choosing their residence. ANOVA test was used to analyze the significant difference between different groups of a characteristic (here, different development patterns or the three case studies). Dunnett T3 was exerted to determine which neighborhood caused the difference between groups. Also, the factors affecting travel behavior were obtained based on exploratory factor analysis indicators. Finally, by comparing the results of the ANOVA test and regression analysis, it was discovered which factors affecting travel behavior were due to the differences in study areas and which factors affect travel behavior regardless of development patterns.
Results and discussion
This research aims to identify the factors affecting travel behavior due to the differences in development patterns. In this regard, the findings in line with the first research question show that the frequency of three modes of travel, by private car, transportation, and pedestrian, differ significantly in the three neighborhoods. Furthermore, ANOVA test results depict that there is a significant difference between these three neighborhoods in terms of factors affecting travel behavior, such as perceptually environmental characteristics of the neighborhood, dependence and pro-liking for personal cars, variety and density of retail stores, density and access to educational units and parks, access to medical and service centers, and car ownership. Finally, by comparing the results of the ANOVA test with the regression analysis assessing the relationship between physical and non-physical factors (the same indicators in the same study areas) with travel behavior, the factors affecting travel behavior owing to different development patterns were identified. Factors such as car ownership, dependence and pro-liking for private cars, density and access to educational units and parks, access to medical and service centers, and variety and density of retail stores have been introduced as the factors affecting travel behavior due to the differences in development patterns. However, proximity to the public transportation station, accessibility preferences in choosing a place of residence, dependence, and pro-liking for other than a private car, having a certificate, number of children under five years old, and age have influenced on travel behavior regardless of the variation between neighborhoods (different physical development patterns).
Conclusion
In In order to discover the factors affecting travel behavior due to the differences in patterns of physical development, this research has provided a more detailed analysis of the factors affecting travel behavior. It has achieved more accurate components than previous studies in this regard. Detailed analysis of studies related to travel behavior and finding the main components affecting it, considering the extent of variables and data, can pave the way for professionals in transportation planning and urban planning, in addition to providing detailed methods and criteria in the related literature.
Funding
There is no funding support.
Authors’ Contribution
Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.
Conflict of Interest
Authors declared no conflict of interest.
Acknowledgments
We are grateful to all the scientific consultants of this paper.
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