Spatial Analysis of the Relationship between Smart Cities and Urban Livability (Case Study: Neighborhoods of Isfahan)

Today, given the explosive growth of urban populations worldwide, urban planners seek new solutions to overcome these challenges. One of the approaches to addressing these issues in urban planning is the concept of smart cities, which has gained attention in recent years. In the current century, rapid advancements in information and communication technology, particularly in smart cities, have reduced the quality of life in environmental and socio-economic dimensions, i.e., the livability of cities, on a global scale. Therefore, this research aims to analyze the spatial relationship between smart city indicators and the livability of neighborhoods in the city of Isfahan. The required data and information were collected through both library and survey methods. After analysis in EXCEL software, the data were imported into GIS software and analyzed spatially using multivariate regression as a GWR (Geographically Weighted Regression) model. The statistical sample of the study consisted of 337 citizens of Isfahan. The results of the study revealed that the status of smart city indicators is unfavorable, with peripheral neighborhoods of the city being in worse condition. Additionally, the livability indicators in Isfahan are not in a desirable state, as most neighborhoods have an average score below 3. Furthermore, the results of the spatial analysis using the GWR model showed that, based on the R2 statistic, the relationship between the independent variable (city smartness) and the dependent variable (urban livability) is 76% and 67% for the economic and social indicators, respectively. Smart city indicators can have a significant impact on the livability of neighborhoods in Isfahan, especially in the eastern, southern, and southwestern regions of the city. The R2 statistic also indicated that the influence of smart city indicators on the physical and environmental dimensions of livability in Isfahan neighborhoods is at a moderate level of approximately 50%.
Extended Abstract
1-Introduction
The complex and extensive urban challenges can only be solved through a systematic approach. In other words, the intense density of cities has led to chaos and disorder, and in addition to disrupting the balance of cities, it has made it impossible to achieve sustainability with current methods of urban management and development. As a result, urban planners around the world are trying, in the directions mentioned above, to develop models for the development of 21st-century cities with an integrated view of all dimensions of urbanization to respond to the new demands and expectations of today's world. One of the solutions to overcome these problems in urban planning is the issue of smart cities, which has been considered in recent years. Smart cities have been proposed as the axis of change and development of the millennium, which means presenting new concepts in urban planning that combine the capabilities of the real and virtual worlds to solve urban problems. Urban smartification arises from this need for development from within that has been given importance. Therefore, considering the issues and problems raised, it is evident that smartification of cities in many countries has been a moderator of many of the problems of cities, so the main issue raised here is what is the status of the smart urban indicators of the Isfahan metropolis? What is the status of the livability of the neighborhoods of Isfahan? To what extent do smart city indicators affect the livability of Isfahan in the spatial dimension (neighborhoods)?
 2-Materials and Methods
The spatial scope of this research is the Isfahan metropolis in central Iran. According to the 2016 census, this city is the third most populous city in Iran, the capital of Isfahan province, and has an area of about 551.5 square kilometers, which has 15 districts. The present study is of applied type in terms of purpose and descriptive-correlational study in terms of nature and method, and the data collection method is documentary (library) and field (questionnaire). The statistical sample size includes citizens living in 15 regions of the Isfahan metropolis. The Cochran formula was used to determine the sample size of the regions randomly. Based on the d coefficient of 0.085, the sample size was 337 questionnaires, which were distributed according to the population of each region.
 3- Results and Discussion
One of the main goals of smart cities is to connect different systems and subsystems to enhance the quality of life, save energy, or reduce greenhouse gas emissions. In fact, making cities smart can bring investment in human and social capital and traditional (transport) and modern (ICT) infrastructure, sustainable economic growth, and high quality of life with wise management of natural resources through participatory governance.
Livability can be divided into three interrelated categories: economy, society, and environment. The economy provides jobs and income and is essential for people's health (their ability to provide food, clothing, and housing) and for meeting higher-level needs such as education, health, and recreation. At the same time, the economy must use the resources available in the environment in a way that ensures sufficient resources for present and future generations. However, social well-being depends on the social and spatial distribution of economic and environmental resources in a fair manner. Justice: Individual freedom and equal opportunities are important components of social well-being. The environment is the infrastructure that provides natural resources, waste disposal capacity, and the connection between humans and the natural environment. If the functioning of any of the three areas above is disrupted, human settlements can quickly collapse and lose their level of livability. According to the results of numerous studies, there is a significant and positive relationship with a moderate correlation between livability and urban smartness. This means that with the increase in the dimensions of a smart city such as (smart people, smart mobility, smart governance, smart living, and smart environment), the increase in the livability of citizens will follow, which is confirmed by the research of Shokri et al. (2019). Also, in the research of Shamai and Bigdali (2016), this relationship was positive and confirmed, as in this research. From the above discussions, it can be said that urban smartification as a new approach in government with its specific indicators has an effective role in the field of livability and causes citizens to be involved in various management fields, including decision-making, implementation, and evaluation, and by identifying problems, the necessary grounds for planning are provided; Therefore, to better prepare the ground for smartification and improve the livability of citizens in the studied area, it can be concluded that paying attention to smartification has been effective in promoting livability. These findings are consistent with the results of previous studies.
 
4- Conclusion
The conclusion of the research confirms these points; The situation of Isfahan neighborhoods in terms of independent variable indicators (smart city) is undesirable, so based on the final analysis of smart city indicators (smart environment, smart life, smart people, smart dynamics and smart governance), only a very limited number of neighborhoods in the central and southern regions have a suitable average of smart status. Also, most neighborhoods in Isfahan do not have a suitable environmental status, so in the eastern neighborhoods of the city due to the presence of various industrial factories and industrial estates and the central areas due to the dense and old texture, high traffic, the western neighborhoods have a very unsuitable environmental status from the perspective of citizens. Conclusion The spatial analysis of the GWR model showed that based on the R2 statistic, the relationship between the independent variable (smart city) and the dependent variable (urban livability) in two indicators; economic, social is 76% and 67% respectively, and smart indicators can have a high impact on the livability of Isfahan neighborhoods, especially in the eastern, southern and southwestern regions of the city. Also, the R2 statistic showed that the impact of smart city indicators on the physical and environmental dimensions of the livability variable of neighborhoods in Isfahan is at an average level of 50%.