Evaluation and measurement of indicators of quality of urban smart living in Tehran city

The current era with the passage of 50% of the world's urban population, the millennium of urbanization and therefore we are facing the second wave of urbanization due to the high volume and speed of urbanization and the emergence of new cities. Meanwhile, the growth of urbanization has taken place simultaneously with the rule of information technology in various fields of urban life and has taken a faster pace than in the past, which can perhaps be called the third wave of urbanization. This growing growth in recent centuries has led to numerous problems such as congestion, environmental pollution, food and energy crises, as well as difficult challenges for the government and issues related to development planning and operation of cities and urban management in the professional fields responsible to the city. Has created. The advent of information and communication technology has made the concept of intelligence have an undeniable impact on all human development processes. Cities use ICT to change urban infrastructure, public and private services, and government activities. One of the new concepts to meet the current challenges of cities in the field of urban planning is the development of smart cities, which has attracted much attention in recent years. Considering the efforts of thinkers as theorists and executives in order to improve the quality of life of urban people, the study and understanding of the effective factors in achieving this goal has been of the highest importance so that today with the advent of information and communication technology and its effects there are a hundred different factors. In this research, with descriptive-analytical approach, the dimensions and indicators affecting the quality of smart living were identified. Then, the importance of these factors was asked from the citizens' point of view using a questionnaire tool and the structural equation modeling method in SmrartPLS software was analyzed. By studying different sources and examining them, different dimensions of the study of the quality of urban smart living based on health, security, culture, education, cohesion and social participation, resource consumption and environmental protection, and finally physical and building development have been expressed.

The present study is of qualitative and quantitative type in which the necessary information is collected and the required dimensions and indicators in order to explain the relationships between them for survey-based analysis through structural equation modeling or SEM and partial least squares approach or PLS were identified.

. In this study, the dimensions and indicators of evaluating the quality of urban smart living have been extracted by studying various researches and in the next step by compiling a questionnaire based on Likert scale (ranking scale for measuring sequential data) and its distribution among city residents Tehran's opinions were collected in 3 regions: north, central and south.

By determining the measurement model, the relationships between observable variables (questionnaire questions) and dependent variables (dimensions and indicators) are considered and measured. In this method, it will be a homogeneous model where the absolute value of the factor load of each of the observable variables (questions) corresponding to the hidden variable of that model is at least 0.7. The result confirms this value. Cronbach's alpha coefficient and mean variance index or AVE were used to measure the two criteria, respectively, and the values obtained for Cronbach's alpha were higher than 0.7 and the mean extracted variance was above 0.5, which is higher than the minimum acceptable.

Finally, we used T-Value statistics and path coefficients to measure the significance and relationship between the indicators. The fit of the structural model using the T-value is such that the coefficients must be greater than 1.96 in order to confirm their significance at the 95% confidence level. Path Coefficient indicates the existence of a linear causal relationship and the intensity and direction of this relationship between the two latent variables. In fact, it is the same as the standard regression coefficient.

Discussion of Results

According to the information obtained in district one of Tehran, the index of electronic voting process intelligence has no significant relationship with social cohesion and participation, as well as the innovation of educational methods with public education. In the sixth district of Tehran, smartening index in the care and monitoring of patients' health status with the dimension of health, monitoring and control of public and private spaces with security, smartening to increase the level of study (electronics and mobile) in education and familiarity with tourist sites There is no significant relationship in cultural development and similarly in the nineteenth region, the index of receiving security services and analyzing data related to the occurrence of crime to prevent its further occurrence with security, intelligence in the direction of education and virtual assessment of education and cost. Construction in intelligent physical development, waste generation and innovation in its recycling has no significant relationship with the consumption of resources and the environment, while there is a significant relationship between other dimensions and indicators in creating an urban quality of smart living.

Accordingly, the dimensions of cohesion and social participation in region one, public education in region six, and resource consumption and environment in region nineteen of Tehran are of the highest importance in evaluating and improving the quality of smart living. Housing and buildings ranked seventh with the least importance. According to the information provided in the tables, the ranking of indicators can be checked. Finally, it should be noted that the development of information technology and its impact on the lives of societies is undeniable, but on the other hand, the emphasis on using this platform should not lead to the design of a single path for development. Understanding the opinions and demands of citizens in different cities is a key factor in targeting and determining urban development strategies using smart methods and equipment.