ارائه مدل حکمرانی هوشمند با تمرکز بر توسعه و آموزش منابع انسانی در بخش دولتی (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
پژوهش حاضر با هدف ارائه مدل حکمرانی هوشمند با تمرکز بر توسعه و آموزش منابع انسانی در بخش دولتی می باشد. روش پژوهش برحسب هدف کاربردی و برحسب نوع داده ها آمیخته (کیفی- کمی) است. جامعه آماری در بخشی کیفی پژوهش شامل 15 نفر از خبرگان دانشگاهی و کارشناسان متخصص در زمینه فناوری اطلاعات و ارتباطات در وزارت کشور و مدیران استانداری خراسان جنوبی آشنا با موضوع بود که به صورت غیر احتمالی و قضاوتی انتخاب و با روش تحلیل مضمون اطلاعات مورد نیاز از ایشان جمع آوری شد.جامعه آماری در بخش کمی پژوهش شامل مدیران و کارشناسان شاغل در بخش مدیریت و برنامه ریزی اتوماسیون اداری برنامه ریزی به تعداد 246 نفر که با استفاده از فرمول کوکران تعداد 150 نفر به عنوان نمونه انتخاب گردید. در ادامه در راستای اعتباریابی مدل پژوهش پرسشنامه پژوهش طراحی و در بین 150 نفر از مدیران و کارشناسان شاغل در بخش مدیریت و برنامه ریزی اتوماسیون اداری برنامه ریزی که به روش تصادفی طبقه ای توزیع گردید. به منظور تجزیه وتحلیل داده ها از نرم افزار Smart PLS 2 استفاده شد. نتایج نشان داد که تمامی مولفه های حکمرانی هوشمند در بخش دولتی شناسایی واز بعد معناداری در پژوهش مورد تایید قرار گرفتند و با بررسی مضامین، مفاهیم و تحقیقات کمی و کیفی الگوی حکمرانی هوشمند با تمرکز بر توسعه و آموزش منابع انسانی در بخش دولتی تبیین گردید.Providing a smart governance model with a focus on the development and training of human resources in the public sector
The current research aims to provide a smart governance model with a focus on the development and training of human resources in the public sector. The research method is applicable according to the purpose, and mixed (qualitative-quantitative) according to the type of data. The statistical population in the qualitative part of the research consisted of 15 academic experts and experts in the field of information and communication technology in the Ministry of Interior and managers of the South Khorasan Governorate who were familiar with the subject, which was selected in a non-probabilistic and judgmental way, and the required information was collected from them with the method of content analyzing. The statistical community in the quantitative part of the research includes managers and experts working in the management and planning department of administrative automation planning in the number of 246 people, of which 150 people were selected as a sample using Cochran's formula. Further, in line with the validation of the research model, a research questionnaire was designed and distributed in a stratified random method among 150 managers and experts working in the management and planning department of administrative automation. Smart PLS 2 software was used in order to analyze the data. The results showed that all the components of smart governance in the public sector were identified and their significance was confirmed in the research; and by examining themes, concepts and quantitative and qualitative research; the smart governance model was explained with a focus on the development and training of human resources in the public sector. ExtendedIntroduction The speed of developments and changes in communication and information technology has envisioned an unpredictable world even for the near future and has even changed the concept of governance in such a way that "smart governance" is the only way forward for governments and rules (Fuller & Crawford, 2022). The meaning of smart governance is to provide a platform for the integrated management of city affairs. This platform should provide services and interactions between the parts of the city in order to achieve an effective and efficient city (Moreno & Paez, 2022). The most important effective tool in this field is the use of FAVA (including communication infrastructure, hardware and software), the use of intelligent processes and information-based decision-making (Holzer et al, 2022). The interaction and participation of all private, government and city governance factors is one of the requirements to achieve smart governance. The development of the dimension of smart governance, due to its fundamental nature in the building of a smart city, becomes the basis for the development of other dimensions of smartness as well (Azkuna, 2022). Smart government is a platform for proper urban management. All the services provided in a smart city should be offered to the people through the channel of smart governance. In the intelligent governance of democracy, the foundation of a government is ideal and perfect. But the existence of corruption, unfair policies and mismanagement of the government causes people to lose their trust in governments (Alvahdei, 2016). The development and application of information technology in various fields is the result of the capabilities of information technology, which is facing great success today (Karegar.rt.al.2015). One of the most important opportunities that new technologies provide to government men and managers is increasing accessibility, strengthening efficiency and re-engineering the government's architecture and making it more responsive. The use of the re-engineering of government architecture and other mentioned facilities in the governance process has led to the emergence of a reality called the intelligent government, which is the prerequisite of government over information societies. Smart government is the use of information and communication technology to improve public sector management and has gained increasing popularity. Smart government is a powerful tool that provides better public services, reduces waiting time and improves cost-effectiveness, increases productivity and improves transparency and accountability, and improves the government's ability to perform key activities (Moghimi, 2017).Therefore, the main question of the research is, what is the smart governance model with the approach of focusing on the development and training of human resources in the public sector? Theoretical Framework Literature Smart rule The meaning of smart governance is to provide a platform for the integrated management of urban affairs. This platform should provide services and interactions between the parts of the city in order to achieve an effective and efficient city. The most important effective tool in this field is the use of FAVA (including communication infrastructure, hardware and software), the use of intelligent processes and information-based decision making. The interaction and participation of all private, government and city governance factors is one of the requirements for achieving smart governance. The development of smart governance, due to its fundamental nature in building a smart city, also lays the foundation for the development of other dimensions of smartness. Smart governance includes political and active participation, citizen services and smart use of e-government. In addition, smart governance refers to the use of new communication channels, such as electronic government or "electronic democracy" (Ghorbanzadeh, 2015). The main elements of smart governance Smart governance : means public investment in ICT to promote transparency and accountability among public institutions at the local and national levels and improve their performance. This element is usually related to public management reform programs and government modernization (Ghorbanzadeh, 2015). Providing intelligent services: Public investment in ICT is to improve the efficiency and transparency of public institutions in providing public services in all sectors. This element is related to the reform programs of public management, local governance and access to justice (Ghorbanzadeh, 2015). Smart participation : Public investment in ICT is aimed at promoting interaction between public institutions and citizens in order to improve policy making and provide public services and activities. This element includes three levels of providing information to citizens, consultation with citizens, and dialogue between the government and citizens. This element is usually related to public accountability programs, strengthening of civil society and strengthening of parliamentary system and parliament (Ghorbanzadeh, 2015). There have been numerous articles on the explanation of smart governance models, but the explanation of a comprehensive and complete model with the approach of human resource development and training has been done less. Hosseini et al. (2022) in an article investigated the antecedents and consequences of smart good governance with a fuzzy Delphi approach. The research method is among mixed researches in the deductive-inductive approach. The statistical population of the research consists of all governance activists, 26 of whom were selected based on the principle of theoretical adequacy and using the purposeful sampling method. In the qualitative part, the data obtained from the interview were analyzed using the Atlas.ti software and the identification method was analyzed. The results of the research indicate that among the antecedents, respectively, technology and smart data, electronic and intelligent interaction, governance Law, competent and committed brokers, cyber and smart security had the highest priority (Hoseini.et.al, 2022).Paighan et al. (2022) in an article identified and prioritized factors affecting good governance with a sustainable development approach in the government organizations of Sistan and Baluchistan province. The research method is applicable in terms of purpose, and mixed (qualitative-quantitative) with an exploratory approach according to the type of data; in this way, 54 articles in the field of good governance were analyzed and research indicators were identified using meta-composite method. The identified factors and components were weighed with the opinion of experts and after receiving their corrective opinions, they were analyzed based on relevant statistical methods, and finally the fit of the model, components, and the combination of factors was reached by their consensus. The statistical population in the qualitative part of the research included 11 academic and professional experts familiar with the subject, who were selected in a non-probabilistic and judgmental manner, and the required information was collected from them using the Delphi method. Further, in line with the validation of the research model, a research questionnaire was designed and distributed among 216 sample members, including managers and experts of the governorate, governorate and academic staff members of the university in Sistan and Baluchistan province, which was randomly distributed by stratified method. In order to analyze the data, Smart PLS software was used. Finally, the findings of the research showed that the indicators of commenting and accountability, quality of laws, corruption control, rule of law, transparency, vision and planning, effectiveness and efficiency, ethics, responsibility, trust, justice, poverty alleviation, Economic growth, participation, institutional development, meritocracy, trust-oriented, political stability, and anger are respectively the most important components of good governance with a sustainable development approach (Peghan.et.al.2022). Methodology The research method is applicable according to the purpose, and mixed (qualitative-quantitative) according to the type of data. The statistical population in the qualitative part of the research consisted of 15 academic experts and specialists in the field of information and communication technology in the Ministry of Interior and managers of the South Khorasan Governorate who were familiar with the subject, which was selected in a non-probabilistic and judgmental way, and the required information was collected from them with the method of content analyzing. The statistical population in the quantitative part of the research includes managers and experts working in the management and planning department of administrative automation planning in the number of 246 people, 150 of whom were selected as a sample using the Cochran formula. used. Discussion and results: SPSS 26 statistical software is used for descriptive data analysis, and the Kolmogorov-Smirnov test for the normality of the data, and the structural equation test using SMART PLS 2 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 measurement 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 items is greater than 0.4, and the value of the t statistic is greater than 1.96, so the model has good validity. Conclusion : This research was conducted with the aim of investigating the components of smart governance with a focus on the development and training of human resources in the public sector. For this purpose, data was collected through in-depth and semi-structured interviews with 15 experts, including university faculty members and experts in the field of information and communication technology in the Ministry of Interior and managers of South Khorasan Governorate who were selected by theoretical sampling. In the quantitative phase of the research, a researcher-made questionnaire based on the extracted components was prepared and provided to 150 managers and experts working in the management and planning department of administrative automation. Then, using the coding method of qualitative content analysis based on interviews with elites and using thematic analysis method, the components of smart governance with a focus on the development and training of human resources in the public sector were identified and extracted, and the effectiveness weights were obtained using the structural model. SPSS 26 and PLS 2 software were used for statistical analysis of the research. To check the fit of the measurement models, convergent validity was used, and the results showed that the AVE values for all variables are greater than 0.5, so the convergent validity of the constructs is acceptable. Also, the results of the factor analysis of the desired components were confirmed, considering that the factor loading of all items is greater than 0.4, and the value of the t statistic is greater than 1.96, so the final model of the research was determined to have good validity. The results of this research are in agreement with Hoseini.et.al, (2022), Peghan.et.al., (2022), Rostaei.et.al, 2(018), Faraji (2022), Meijer et al., (2018), and Washburn et al., (2018).
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