ارائه پیشران های کلیدی آینده حکمروایی شهری هوشمند (مطالعه موردی: شهر رشت) (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
توسعه مستمر جمعیت شهری و نیازهای رو به افزایش آنها، شهرنشینی گسترده در کشورهای در حال توسعه، تغییرات جمعیت شناختی، چالش های محیط زیستی، معضلات اقتصادی، معضلات حمل و نقل شهری، پیشرفت های فناوری اطلاعات و ارتباطات و بوروکراسی، فرمولاسیون شهر هوشمند و حکمروایی شهری هوشمند را ضروری ساخته است. در خصوص شهر رشت می توان بیان نمود که شهر رشت نتوانسته آینده های پیشروی توسعه را متصور شود و پیشرفتی در زمینه حکمروایی شهری هوشمند داشته باشد. لذا هدف این پژوهش واکاوی پیشران های کلیدی حکمروایی شهری هوشمند با رویکرد آینده پژوهی است. پژوهش حاضر کاربردی و به لحاظ روش انجام توصیفی - تحلیلی و اکتشافی است. گردآوری داده ها به روش اسنادی و نیز به صورت پیمایشی مبتنی بر تکنیک دلفی می باشد. جامعه آماری کلیه متخصصان شهری شهر رشت در زمینه تحقیق می باشند. حجم نمونه با استفاده از قوانین راسکو، 45 نفر تعیین شد و شیوه نمون ه گیری به صورت گلوله برفی می باشد. 8 مؤلفه و 20 پیشران در خصوص حکمروایی شهری هوشمند تدوین شد و پرسشنامه ماتریس اثرات متقابل (وزن 0 تا 3) در اختیار متخصصان قرار گرفت و در نهایت با استفاده از نرم افزار میک مک پیشران های کلیدی استخراج شدند. نتایج حاصل از تحلیل حاکی از آن است که آموزش شهروندی و آگاهی رسانی، مشارکت شهروندان و تعهد مسئولان جزء 3 پیشران اول حکمروایی شهری هوشمند شهر رشت محسوب می شوند.Presenting the Key Driving Forces for the Future of Smart City Governance (Case study: Rasht city)
The continuous development of urban population and their growing needs, widespread urbanization in the developing countries, demographic changes, environmental challenges, economic problems, urban transportation problems, advances in information and communication technology, and bureaucracy have made the smart city formulation and smart city governance necessary. Regarding the city of Rasht, it can be said that this city has not been able to imagine the future of development and make progress in the field of smart urban governance. The present study aimed to investigate the key driving forces of smart governance with a futures research approach. The study was applied and descriptive-analytical and exploratory in terms of method. Data collection is documentary and survey based on Delphi technique. The statistical population included all the urban specialists in Rasht. From which 45 people were selected as the sample using Rasco's rules through snowball sampling method. 8 components and 20 driving forces regarding smart urban governance were compiled and the questionnaire of interaction effects matrix (weight 0 to 3) was provided to the specialists. Finally, key driving forces were extracted using MicMac software. The results of the analysis indicated that the education of citizenship and raising the awareness, citizen participation and commitment of officials are among the first three driving forces of smart city governance in Rasht. Extended Abstract Introduction Cities have faced many problems, such as huge social, economic and environmental problems, due to the lack of efficient planning and management. Today, urban management has become one of the most important challenges of the 21st century and the concept of smart city has been proposed as a possible solution. In fact, for responding to urban problems, we can mention the smart city approach. The smart city has emerged as a political idea and a planning act at the forefront of global urban policy debates. It should be noted that although the concept of smart city has a high potential, the related urban governance challenges have prevented it. It can be said that the governance methods, methods and policies can lead to a smart and sustainable urban future. Methodology The study was applied and descriptive-analytical and exploratory in terms of method. It has investigated the key driving forces of smart governance in Rasht. In this regard, first, smart governance driving forces were extracted from different sources (8 components and 20 driving forces) and their validity was confirmed by specialists (45 people) using the Delphi method. Then, the cross-effects matrix questionnaire was provided to the experts. The weightening of this questionnaire is measured by pairwise comparisons and and the degree of correlation of variables with numbers between zero and three. The influence of the driving forces on each other was determined by the opinion of the elites and specialists, and the effective and influential, key and strategic driving forces were compiled. Results and discussion Using direct classification of variables, the key variables were identified according to their influence and mutual impressibility based on system logic and by the output of MikMac software. Among the influential variables (because they are the most influential driving forces), risk variables (because they have a high capacity to become key agents of the system) and regulatory variables (which can be converted into risk variables and secondary objectives) were the most important factors. Variables that have a net negative impact score were removed from the list of key factors. A total of 9 key variables were identified, and the variable of citizenship education and awareness gained the first rank. Conclusion The results showed that the variables of citizenship education and awareness (effective variable) with a net impact score of 19 is in the first place, citizen participation in the implementation of smart technologies (impact variable) with a net score of 17, the commitment of city officials to implement smart urban projects (Influential variable) with a net impact score of 16, the organizational budget intended for intelligence (impact variable) with a net impact score of 16, access to information and communication technology (impact variable) with a net impact score of 15, access to open data (impact variable) with a net impact score of 11, private sector participation in investment in smart projects (impact variable) with a net score of 8 impact, municipal support Software and applications for establishing smart government (risk variable) with a net score of 8, establishing traffic security and protection of information and privacy (effective variable) with a net score of 4 were recognized as the key driving forces of smart governance in Rasht. In order to achieve smart governance in the city of Rasht, the desired drivers should be strengthened. Funding There is no funding support. Authors’ Contribution All of the authors approved the content of the manuscript and agreed on all aspects of the work. Conflict of Interest Authors declared no conflict of interest. Acknowledgments We are grateful to all the persons for scientific consulting in this paper.
تبلیغات
