One of the central issues in choosing housing (buying or renting) is having a high degree of access to various types of urban transportation networks. Because the low-income groups of the society use public transportation more for traveling in and around the city, and this issue is so important in choosing a place of residence that it is one of the main local quality indicators and an effective factor to save the household budget, especially for the low-income sections of society. Therefore, the development of a score-based system and scoring of real-estate and housing based on access to the public transportation system is valuable.
Analysis of previous research shows that the importance and impact of transportation systems in property valuation, from the distant past to the present and, as in the past, has a decisive effect on property placement, especially in the selection of residential areas; In this regard (based on the summary of the researches - Table 1) can be categorized and proposed in several scenarios.
Scenario 1. Survey and ranking using socio-historical intelligence:
In the past, human memory and quotes from others about the tranquility of neighborhoods were questioned, and this method is still common among many traditional communities. This type of ranking is qualitative and the indexing is very low or the parameters have not been quantified yet. So that in no visible place has it been given a privilege except in the public mind. In this method, it is evaluated only based on the needs of the society and the demand of the people and the type of their behavior with the environment. Here, the desirability of the place is considered according to the social desirability and without the desirability of other parameters. And it is a kind of use of public trust in society.
Scenario 2. Review and rank the parameters based on the value from the customer's point of view:
Determine the value from the point of view of a particular person or group without considering the acceptance of the community. Customers who value the proximity to their place of business value the property more without the need for transportation services.
Scenario 3: Review and ranking with the characteristics of the type of building and local coordinates (local):
In such a case, the price evaluation is based on the characteristics of the neighborhood such as connection and density of streets, parking, garbage disposal, etc. Also, determining the price of a house is related to the type of building (apartment or villa), size and age of the building, number of rooms, water system, gas, swimming pool, heating services, cooling, etc.
Scenario 4: Review and ranking with purely economic parameters:
Based on the economic issues raised in the study community. This means that the value of the property is considered based on proximity to commercial real-estate or suitable job opportunities. On the other hand, the income and financial capacity of each person determine these types of values.
Scenario 5: Review and ranking with comfort-oriented parameters:
Here the value of the property is a function of other determining parameters, since the relaxation and comfort coefficient of each person is different, the criteria of comfort and relaxation, change over time and the value of the property will also be subject to these changes. For example, for one person with a student, proximity to school and educational services is a priority, and for another, distance from school and the resulting congestion is a parameter of comfort.
Scenario 6: Survey and ranking with the parameters of social welfare and quality of life (social life average):
One of the most important criteria for valuing property are human welfare factors, including proximity to the urban transportation system (Metro, Buses and BRT), education, health care, employment and leisure. Meanwhile, in densely populated cities, the urban transit system is an important factor in improving the quality of human life and easier access to amenities. Even the distance from the property to the transportation system will significantly determine the value of the property.
In this study, while reviewing examples of previous studies, their methods and results were specifically categorized in the above six scenarios, then by determining and classifying the indicators of each scenario, a new scenario called scoring and ranking with temporal and spatial variables (spatial effect of parameters and combination of previous scenarios) were presented. Also, the useful access radius of transportation stations was identified and verified based on the study of previous researches, consultation with specialized (academic) experts and local experts; then, using the fuzzy method, a mechanism for determining the characteristics, ranking and scoring was designed to create a hierarchical-scoring system with the algorithm of combining multidimensional real estate scores.
This ranking provides a quick and easy comparison of residential properties in multiple locations in the city in a reliable environment. The proposed system has three layers: data, logic and representation; In the coordinate data layer and descriptive and analytical information, the properties in the study area and metro, bus and BRT transport stations are recorded. In the logic layer, the fuzzy web service is used for fuzzy inference and the web server is used for the display layer to interact with the data layer. The results of the evaluation of the designed fuzzy scoring system, in comparison with the field evaluations and the results of other systems, confirm the efficiency of this system.
Scenario 7: Review and ranking with temporal and spatial variables (spatial effect of parameters and combination of previous scenarios):
The effect of parameters valuing property, based on the need that exists in a particular place or time. For example, for the needs of a customer, which is valuable only in a limited time and place, the use of public transport system, as a result of the spatial impact of such factors, depending on the time and place of customer needs, definition and specialized scoring (Non-public) is presented.
Sometimes a particular job situation requires a client to prefer a particular location only in certain seasons. Also, maybe the buyer or lessor of the property, each of them considers different and various parameters as value. As a result, for a person who is going to live in a place for a long time or a person who uses that place temporarily and for a short time, a series of short-term cross-sectional and long-term stable parameters will affect the value of the property. As a result, different results at different times and places provide maps for decision making.
Given the above, it is necessary to emphasize that the scenarios have integration and correlation and all of them have weaknesses, the structure and array of measurement, quantification and indexing systems, due to the lack of the same regional, urban and meta-indicators, their performance on different scales is somewhat problematic. On the other hand, the indexing system is largely conventional and varies from place to place and in each geographical area. Therefore, the system of these models cannot be the same everywhere unless we can change the indicators. Table 1 summarizes the articles of various researchers in this field with emphasis on access to the public transportation system.
Understanding the significant impact of the transportation system on property prices and its undeniable effects on the well-being and quality of life of people, designing a web-based system with dynamic and changeable information is important for public access. In our country, there is no comprehensive system that contains property price information with emphasis on access to the transportation system, so the development of a web-based system for rating residential real-estate based on transportation, as the goal of this study, is important.
Especially to design a system that maintains its dynamism and capabilities due to the dynamism of urban development plans and plans, diversity and multiplicity of laws, the existence and intervention of various decision makers in urban affairs and the sharp fluctuation of housing and property prices that do not make gross errors during the oscillation periods; Also, the designed system can have its unique features, the possibility of registering the property by users and the possibility of displaying it on the map and viewing transportation scores.