Abstract
The purpose of this research is to provide a model of factors affecting smart governance in the country. The research method is applicable in terms of purpose, and mixed (qualitative-quantitative) in terms of its implementation, and descriptive-survey type in terms of data collection. The statistical population in the qualitative section includes 28 university experts familiar with the subject, who were selected in a non-probability and judgmental manner. The statistical population in the quantitative part includes all the managers and experts working in South Khorasan governorate and Birjand city governorate of planning administration equal to 420 people, and the sample number was selected using Cochran's formula of 200 people. The sampling method in this section was done in a random stratified manner. A semi-structured interview and a researcher-made questionnaire taken from the qualitative section were used to collect information. In the qualitative part, the fuzzy Delphi method was used, and the data from the interviews were coded and analyzed in the three main stages of open coding; axial coding; and selective coding, and SmartPLS 3 software was used in the quantitative part of factor analysis, and SPSS 22 software was used for analysis. The results of the research in the qualitative part showed that three categories of background factors (equipment and infrastructure, required resources, information and communication technology, statistics and intelligent information, and formation platform), content (cyber security, strategy formulation, intelligent management and intelligent planning) and Structural (smart readiness, smart architecture, and smart administration) are effective on the formation of smart governance in the country. The results of the quantitative section showed that the model is of good quality.
Extended Abstract
Introduction
The evolution of human knowledge shows that along with the change in the nature and form of the problems facing mankind, the knowledge packages suitable for the management of such problems have also undergone evolution. One of the important human knowledge that plays an important role in the survival and health of societies is the knowledge of governance and management of public affairs. Therefore, political systems should choose their appropriate style of governance according to the social, political, economic and cultural environment governing the society (Hoseini et al, 2022). One of the most important opportunities that information technology presents to statesmen and managers is increasing accessibility, strengthening efficiency and re-engineering the architecture of the government and the possibility of making it more responsive. The use of information technology in the governance process has led to the emergence of a reality called "smart governance" which is a prerequisite for governing information societies (Mohammadi et al, 2021). Smart governance is about relationships between private, public, economic and social stakeholders and focuses on citizen participation (Lopes & Oliveira, 2017). This style of governance is based on a transparent management system that allows citizens to participate in the planning and decision-making process in terms of the development of their communities, and ensure free access to information (Penaska & Velas, 2019). Smart governance uses information and communication technology to improve democratic processes and public services (e-government), support and facilitate planning and decision-making (Camero & Alba, 2019).
Based on this, the researcher of the present study intends to answer the main question: what model of effective factors is suitable for smart governance in the country?
Theoretical framework
Smart governance
Smart governance refers to the intelligent use of information and communication technology to improve decision-making through better collaboration between different stakeholders, including government and citizens. In this case, tools based on information and communication technology, such as social media and the openness of the political space, can be factors that increase citizen interaction and support the development of new governance models for the smart government. Smart governance may also play an important role in smart city initiatives that require complex interactions between governments, citizens, and other stakeholders (Nasri & Tabarzad, 2020). Smart governance is a style of management that is formed based on the intelligent participation of citizens through information and communication technology. This new form of governance transforms citizens from passive consumers of city services to active actors who can comment on the type of services they need (Mohammadi Dehchshme & Moradi, 2021). In other words, this type of governance is based on a transparent management system. This should allow citizens to participate in the planning and decision-making process in terms of city development and ensure free access to information (Penaska & Velas, 2019).
Research background
Chegni & Koshtar Haranki (2022), examined "smart (knowledge-based) governance relying on the development model (functions of thinker boards)", to explain the concept of thinker board as a strategic and influential institution on the country's decision-making and policy making process and drawing and presenting a local and ecologically compatible model of governance in Iran from this strategic institution. The findings of this research showed that the Islamic Republic's thinker boards at the macro level can help to make the country's governance system smarter and knowledge-based, and in addition to the common functions; it can have functions such as the governing body, guiding and directing the country's macro policies, protection and supervision, explaining the basics, concepts and theoretical frameworks, discourse maker, observation and production of thought, strength of the internal structure of power, socialization and grounding of modern Islamic civilization, use of popular participation and mobilization in the matter of political research and decision making and consultation and problem solving.
Hamghadam et al, (2022) investigated "presenting future scenarios of smart urban governance (case study: Rasht city)". The results of the analysis showed that the appropriate foundation scenarios in the field of citizenship education and raising awareness, popular participation and citizenship and private sector participation, making arrangements to increase the budget in the field of smartness, and municipal support of the smart government have the most adaptive value in the future of smart urban governance of the city of Rasht.
Research methodology
The current research is applicable in terms of purpose, and mixed (qualitative-quantitative) in terms of its implementation, and descriptive-survey type in terms of data collection. The statistical population in the quantitative part includes all the managers and experts working in South Khorasan Governorate and Birjand City Governorate of planning administration, which was identified as 420 people based on internal statistics. Also, the sampling method in this section was done in a random stratified manner. The number of samples was obtained using Cochran's formula considering that the number of people in the studied society was 200. The statistical population in the qualitative section includes 28 university experts familiar with the subject, who were selected in a non-probability and judgmental manner. In this research, the research strategy is of a mixed type (qualitative-quantitative) that after defining the topic and conducting preliminary exploratory and library studies and semi-structured interviews, the relevant factors and components are determined through the Delphi method, which is considered a qualitative research method, by a researcher-made questionnaire (including the answers of the five-choice Likert range and an open question to add possible new components) according to academic and professional experts familiar with the subject, And after receiving their qualitative and quantitative corrective opinions (prioritization of factors) based on the statistical methods of analysis, and finally, through three rounds of going back and forth of the fit of the model, components, and combination of factors reached the consensus of the elites. Research data collection tools are a) library studies (foreign and domestic books and publications, databases, internet sites, etc.); b) semi-structured interviews with academic experts and specialists in the field of governance and information technology; c) a questionnaire. In the qualitative part, the data obtained from the interviews were analyzed in the first stage using three stages of open, central and selective coding; and in the quantitative part, the required data were collected through a questionnaire with closed questions, and in order to analyze them, confirmatory factor analysis test was used in SmartPLS 3 software environment. Also, SPSS 22 software environment was used to analyze the data collected in the descriptive statistics section and determine Cronbach's alpha to check the reliability of the data collection tool.
 
 Discussion and results:
SPSS 22 statistical software was used for descriptive data analysis. And the structural equation test was used using SMART PLS 3 software to answer the research questions. Factor loadings are calculated by calculating the correlation value of the indicators of a structure with that structure. If this value is equal to or greater than 0.4, it confirms that the variance between the structure and its indicators is greater than the variance of the size error of that structure, and the reliability of that measurement model is acceptable. The results of the factor analysis show the desired components, since the factor loading of all the items is more than 0.4, and also the value of t statistic is more than 1.96, so the model has good validity.
Conclusion:
The construction of the concept of intelligent governance has played an important role in shaping the existing electronic goals in the world's information society, followed by the progress and development of different societies. Therefore, the current research was conducted with the aim of providing a model of factors affecting smart governance in the country so that by knowing smart governance and the factors affecting it, future strategies and plans can be adopted in line with the effective establishment and development of this type of governance in the country. Therefore, according to the studies conducted in this field and also, based on the analytical logic of the open system and taking into account the opinion of experts, the factors affecting smart governance were finally categorized in the form of 3 dimensions and 12 components, which in terms of prioritizing the components of the three factors, were ranked respectively; in the contextual factors section: the formation platform, equipment and infrastructure, statistics and intelligent information, information and communication technology, and required resources; in content factors section: cyber security, smart management, strategy formulation and smart planning; and in the structural factors section: smart architecture, smart administration and smart preparation.
Contextual factors such as needs assessment and capacity producing, along with causal factors, provide a suitable platform for the establishment of smart governance in the country. The contextual factor of needs assessment in this research included equipment and infrastructure, required resources, information and communication technology, cyber security, statistics and intelligent information. In other words, equipment and infrastructure such as hardware, software, high-speed and secure internet, user-friendly designed websites and portals, resources such as sufficient financial and human resources, and most importantly securing this virtual space through the creation of functional ID, network security, design and the development of security laws, and finally the creation of mechanized databases in various fields and the formation of electronic statistics and information units in government organizations can help to provide a suitable platform for the establishment of smart governance in the country as effectively as possible.