سنجش تأثیرپذیری شهر از نماگرهای "شهر هوشمند"‏. مطالعه موردی: زنجان

نوع مقاله : مقاله علمی پژوهشی

نویسندگان

گروه جغرافیا و برنامه ریزی شهری، دانشکده ادبیات و علوم انسانی، دانشگاه محقق اردبیلی، ایران

چکیده

سنجش تأثیرپذیری شهر از نماگرهای "شهر هوشمند"‏
مطالعه موردی: زنجان

به دنبال تجدید ساختار اقتصادی و اجتماعی جهانی، تحولی در مفهوم توسعه‌ی شهری و پارادایم‌های آن به وجود آمده است؛ از آن جمله شهر هوشمند، پارادایمی برای توسعه‌ی شهرها در جامعه‌ی اطلاعاتی است. شهرهای هوشمند به عنوان آینده‌ی شهرهای انسانی، شهری فعال در زمینه‌ی فناوری، انعطاف‌پذیری، پایداری، خلاقیت و قابل زندگی در جهان پیش‌بینی شده‌اند و در حال تبدیل‌شدن به بخشی از چشم‌انداز دولت‌های ملی هستند چرا که با هدف افزایش کیفیت زندگی شهروندان ظهور یافته‌اند. این پژوهش با هدف تدقیق، بومی‌سازی و اولویت‌بندی و همچنین سنجش اثرات معیارهای شهر هوشمند در شهر زنجان انجام شده است. جامعه‌ی آماری تحقیق، کارشناسان آشنا با مفاهیم شهر هوشمند در شهر زنجان بوده و ابزار جمع‌آوری داده‌ها، پرسشنامه و مصاحبه است. تحلیل در دو بخش انجام یافته است؛ بخش اول توسط آزمون‌های آماری Spss انجام گرفته و در بخش دوم توسط نرم‌افزار میک‌مک انجام گرفته است. نتایج نشان داد معیارهای زیرساخت‌ فناوری، خدمات عمومی- اجتماعی و دسترسی به ترتیب با وزن‌های 01657/0، 01636/0 و 01619/0 در اولویت‌های اول تا سوم جهت هوشمندی شهر قرار دارند. همچنین نتایج تحلیل اثرات متقابل معیارها، نشان‌دهنده‌ی پراکنش نامنظم معیارها در پلان تاثیرگذاری و تاثیر‌پذیری است. تحلیل نشان داد که متغیرها در بخش تاثیرگذاری و تاثیرپذیری متوسط، دارای تراکم زیادی بوده و سیستم مورد مطالعه دارای ناپایداری است. در نهایت شش معیار راهبردی، کلیدی و استراتژیک سیستم شناسایی شدند که برای هوشمندی شهر زنجان بسیار مهم هستند، این معیارها عبارتند از؛ 1- زیرساخت‌های فناوری 2- توانمندی و صلاحیت شهروندان 3- حکمروایی شفاف 4- مشارکت شهروندان 5- امکانات فرهنگی 6- جاذبه‌های گردشگری.

کلید واژگان: شهر هوشمند، شاخص‌ها، اثرات متقابل، اولویت‌بندی، شهر زنجان.‏

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Measuring the effectiveness of the city from "smart city" indicators. Case Study: Zanjan

نویسندگان [English]

  • Jalil Mohammadi
  • Alireza Mohammadi
  • Ataa Ghafari
  • Mohammad Hassan Yazdani
Department of Geography and Urban Planning, Faculty of Humanities, University of Mohaghegh Ardabili, Ardabil, Iran
چکیده [English]

Introduction
Cities play a vital role in the lives of the vast majority of people, yet face great challenges beyond ‎regions, nations and continents, and most cities are the main drivers of change. Recent ‎technological developments have renewed belief in the positive impacts of ICT and other ‎innovative technologies in the city. The combination of smart solutions (active technology) to ‎address major social challenges and focus on the city as key drivers of change has led to the ‎concept of smart city. Finally, scientific studies on smart city development readiness are largely ‎limited to developed countries. And the literature on smart city readiness in developing countries ‎is at an early stage and needs more empirical support. The transformation of a city into a smart ‎city requires considerable efforts by political representatives, managers, residents, entrepreneurs, ‎as well as its various communities. The concept of smart city is evolving rapidly, and the ‎attention of the world as a promising response to the challenge of urban sustainability in large ‎and small cities. Given the different structure of Iranian cities, this study seeks to localize the ‎indicators and analyze their interactions for any planning and management.‎

‎ Methodology
The study of the components of smart city in Zanjan deals with 6 components, 30 benchmarks ‎and 100 standard indices designed in scientific societies around the world. By method, the ‎present study is a descriptive field type. In order to carry out the research, the research ‎components, criteria and indices were extracted from the theoretical foundations of the research ‎and then prioritized by in-depth experts. Library and field methods have been used to collect the ‎required information. Due to the lack of familiarity of most experts with the concepts of smart ‎city, only experts in the statistical population who were familiar with the concept of smart city ‎were included. The sampling method was theoretical saturation and by this method in 21 samples ‎we achieved our goals. In this study, first, the importance and impact of indicators on the ‎intelligence of cities were measured and analyzed by SPSS. Then, the extent of impact as well as ‎the interactions between the components, criteria and indices were measured and analyzed with ‎Micmac software. Because interviews and questionnaires have been used, the research is a ‎composite (sequential exploratory model). And the composition is in the concluding phase. Both ‎questionnaires were used by experts in this field.‎

Results and discussion
In the first part, after determining the components, criteria and indicators affecting the ‎intelligence of cities and in line with the main objectives of the research, determining the ‎importance and weight of each component, criteria and indicators. Finally, 30 criteria with 100 ‎indicators were finalized and these indicators were prioritized by experts. The data were ‎analyzed by SPSS software using Friedman test and the significance of each criterion and index ‎was determined and prioritized. The three components of smart mobility, smart governance, and ‎smart economy with weights of 0.01577,‎‏ ‏‎0.01394 and 0.01381 are the first to third priority, ‎respectively, and have the highest weight and importance in smart cities. The criteria for smart ‎mobility component include technology infrastructure, national, local access and sustainable ‎mobility, which are prioritized with weights 0.01657, 0.01619, 0.01609 and 0.01424, ‎respectively. Two criteria of smart governance components including public-social services and ‎transparent governance with weights of 0.01636 and 0.01153 were significant. Also the criteria ‎of smart economy component were international interactions, productivity, innovation, ‎entrepreneurship, economic image of the city and labor market flexibility with weights 0.01601, ‎‎0.01597, 0.01544, 0.01455, 0.01161 and 0.00928 respectively. In the analytical analysis of the ‎findings, the indicators of Internet penetration, municipality planning strategy and e-government ‎access have the weights of 0.01694, 0.01687 and 0.01684, respectively.‎
In the second part, we have used Micmac software to analyze the interaction of criteria. ‎In order to make the results more realistic and realistic, the analysis software was created in the ‎Micmac Matrix software and adjusted in 30 different criteria to 30 * 30 dimensions. Based on ‎the matrix output, the 10 criteria that had the most direct impact on the system in order of rating ‎are: 1- Technology infrastructure (677) 2- Citizens empowerment (655) 3- Transparent ‎governance (610) 4- Citizen participation (519) 5- Cultural facilities (440) 6- Sustainable and safe ‎transportation (440) 7- Lifelong learning (429) 8- Tourism attraction (406) 9- Educational ‎facilities (395) 10- National access (395). The 10 criteria that have a direct impact on city ‎intelligence are, respectively, priority and priority; 1- Citizen competence and competence (542) ‎‎2- City pollution level (508) 3- Urban productivity (497) 4- Entrepreneurship in the city (497) 5- ‎Transparent Governance (463) 6- City Tourism Attraction (440) 7- International Interaction (440) ‎‎8- Preservation of Environment (418) 9- Educational Facilities (384) 10- Citizen Participation ‎‎(384).‎

‎ Conclusion
The analysis of the results of the first section showed that the relevant components, criteria and ‎indices in the three prioritization of the rankings were almost identical. Thus, the component and ‎criterion that is ranked higher in the ranking also have more important indicators, while the ‎component and the criterion that is in the lower priorities have the least important ones. In the ‎second stage, the analysis of the interaction of criteria on the intelligence of the city is examined. ‎The results of the MicMac method in impact analysis indicate the irregular distribution of criteria ‎in the impact plan. The analysis of the plan and related diagrams show that the variables in the ‎medium of influence are high density and the studied system is unstable. Based on the results of ‎Structural Analysis and Micmac software, the direct and indirect effective criteria were ‎determined. Key variables and strategic indicators were also identified. What is important is that ‎improvement and improvement in each of the dimensions and components of the smart city will ‎be very influential in city intelligence because systematic reviews and evaluations of smart cities ‎do not consider growth in all dimensions. Therefore, any benchmark and component that can be ‎upgraded should be a priority.‎

کلیدواژه‌ها [English]

  • Keywords: Smart City
  • indicators
  • interactions
  • Prioritization
  • Zanjan City.‎

مقالات آماده انتشار، پذیرفته شده
انتشار آنلاین از تاریخ 11 اسفند 1398
  • تاریخ دریافت: 06 شهریور 1398
  • تاریخ بازنگری: 30 بهمن 1398
  • تاریخ پذیرش: 11 اسفند 1398