Urban Planning
Hassan Mahmoudzadeh; Iraj Teimouri; Ali Amiri Varzqan
Abstract
Unreasonable urban sprawl has adverse effects on the natural and cultural environment of societies. Many efforts have been made to eliminate the negative effects of the scattered expansion of cities, the most important of which is the smart growth strategy. In fact, smart growth has emerged as a response ...
Read More
Unreasonable urban sprawl has adverse effects on the natural and cultural environment of societies. Many efforts have been made to eliminate the negative effects of the scattered expansion of cities, the most important of which is the smart growth strategy. In fact, smart growth has emerged as a response to the continuing problems of fragmented development and its negative results. The purpose of this research is to identify the physical capacities in order to develop intermediates by relying on the principles of smart growth in Qanbar Cheshmeh Marand neighborhood.The current research is applied-practical in terms of purpose and descriptive-analytical in terms of nature and method. The statistical population of the research consists of 200 dilapidated pieces of dilapidated buildings in Qanbar Cheshme neighborhood. In order to analyze the data, the weighted overlapping model (WLC) was used in the GIS environment.
By using ten indicators of smart urban growth, the rank of smart urban growth capacity was prioritized and mapped in the form of 5 sub-neighborhoods, and to prepare the final map, the highest rate of smart urban growth coefficient was calculated from the average of the ten ranks and the rank obtained as a percentage in GIS format. used. due to the current inefficiency of Baft, it cannot benefit from this increase in population. If 40% of the freed occupation area, which is an area of 15,476 square meters, is dedicated to green infrastructure, mixed uses, creating pedestrian-oriented communities and widening roads, the environmental quality of the worn-out area of Qanbar Cheshme will definitely increase. will find
Urban Planning
Yaser Gholizadeh; Iraj Teimouri; Rahim Heydari chianeh
Abstract
Smart tourism is a new applied term that describes the increasing dependence of tourism destinations, industries and different forms of tourists on new forms of information and communication technology that transform massive amounts of data into valuable propositions. Despite the growing importance of ...
Read More
Smart tourism is a new applied term that describes the increasing dependence of tourism destinations, industries and different forms of tourists on new forms of information and communication technology that transform massive amounts of data into valuable propositions. Despite the growing importance of smart tourism, as one of the most basic sources of income for societies, not so many studies (especially inside the country) have been conducted in this regard. Therefore, the purpose of this research was document analysis of authentic domestic articles about smart tourism in an analytical way. The current research is descriptive-analytical and its method is analysis. The statistical population of this research includes all scientific-research articles that have been published in scientific-research publications approved by the Ministry of Science, Research and Technology in the country, and due to the small number of them (12 cases), the full enumeration method was used. The results of the analysis show that from 2016 to now (2021) there are only 12 scientific research articles in the country, which indicates the lack of attention to research on smart tourism in Iran. Also, the results show that in terms of geographical distribution, Isfahan city is in the first place and the field of management, especially Market management, has played the most important role in the field of smart tourism in Iran. Also the superiority of the combined method over positivism or positivism is quite evident. Another finding of the research is that the method of collecting most the printed articles was documentary and combined (questionnaire and interview). Also the data analysis in most of the articles has been using the typical T-Tech test, structural equation model and composite model, and regarding the widely used software in the field of domestic smart tourism articles, we can mention SPSS software along with Smart PLS.
Geography and Urban Planning
Mohammad Nemati; Iraj Teimouri
Abstract
The aim of this research is to investigate the macroeconomic variables effect on housing prices and rents. The data are collected from reports and documents. Data is quarterly and is from 2008 to 2019. The ordinary least squares (OLS) regression model was used to analyze the data and the augmented Dickey-Fuller ...
Read More
The aim of this research is to investigate the macroeconomic variables effect on housing prices and rents. The data are collected from reports and documents. Data is quarterly and is from 2008 to 2019. The ordinary least squares (OLS) regression model was used to analyze the data and the augmented Dickey-Fuller test (ADF) was used to examine the unit root of the variables. Results show that predictor variables have a significant explanatory effect on the behavior of the dependent variable. Thus, for the housing price, the regression equation was significant with an R squared of 0.98 and an adjusted R squared of 0.975. Accordingly, this model predicts 97.5% of the variance in the housing price. Also, for the rental price, the regression equation was significant with an R squared of 0.986 and an adjusted R squared of 0.982. Accordingly, this model predicts 98.2% of the variance in the rental price. In housing prices, "informal exchange rate", "inflation rate" and "liquidity rate" have a direct and positive correlation with housing prices. "Unemployment rate", "coin price" and "bank interest rate" are also directly and negatively correlated. Also, the effect of the "consumer price index", "official exchange rate", "number of residential units built" and "Volume of the stock market" is not significant. In housing rent, the "informal exchange rate" and "inflation rate" have a direct and positive correlation with housing rent. "coin price", "bank interest rate", and"Unemployment rate" are also directly and negatively correlated. Also, the effect of the "consumer price index", "official exchange rate", "number of residential units built", "liquidity rate", and "Volume of the stock market" is not significant.
