فراترکیب پیشران های اجتماعی تأثیرگذار در توسعه هاب های نوآوری و دانش بنیان شهری (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
پیشران های اجتماعی، زمینه را برای جذب نخبگان و تحقق پذیری شهر دانش بنیان به عنوان یکی از پارادایم های مهم شهر آینده فراهم می آورد. هدف پژوهش حاضر، سنتز ادبیات گسترده پیشران های اجتماعی تأثیرگذار در توسعه هاب های نوآوری و دانش بنیان شهری جهت ارایه مدل مفهومی یکپارچه و جامع آن است. پژوهش حاضر از لحاظ هدف توسعه ای و روش آن کیفی است. جامعه آماری شامل پژوهش های منتشره در بازه زمانی دهه 1990 تا سال 2022 به تعداد 1223 مأخذ است. ابتدا 892 منبع با بررسی عنوان و 156 منبع با بررسی چکیده حذف، سپس محتوای 175 منبع به طور کامل بررسی و تحلیل و 43 مقاله جهت تجزیه وتحلیل نهایی انتخاب گردید. برای سنجش میزان پایایی از ضریب کاپای کوهن استفاده شد و نتایج آن معادل 733/0 با سطح معناداری 000/0 بوده که بیانگر پایایی مناسب پژوهش است. بر اساس نتایج پژوهش، پیشران های اجتماعی هاب های نوآوری و دانش بنیان شهری دارای پنج مقوله متمایز و درهم تنیده متشکل از حس مکانی، سرمایه اجتماع، یکپارچگی اجتماعی، رفاه اجتماعی و توسعه اجتماعی-فرهنگی می باشد. نوآوری و دانش بنیان شهری دارای 10 بعد (مشتمل بر احساس تعلق به اجتماع، ساختار اجتماعی، زیرساخت کارکنان دانش، رفاه، ساختار اجتماع، سرمایه انسانی اشتراک مبنا، شکل، تصویر، کارکرد و محیط) و 31 مؤلفه است. همچنین در مجموع، هاب های نوآوری و دانش بنیان شهری دارای 115 شاخص است. مقوله یکپارچگی اجتماعی، 24 درصد مجموع شاخص ها را در برمی گیرد. سایر مقوله ها متشکل از حس مکانی، سرمایه اجتماع، توسعه اجتماعی-فرهنگی و رفاه انسانی به ترتیب 33، 20 درصد، 12 درصد و 11 درصد مجموع شاخص ها را شامل می شوند.Meta-Synthesis of Influential Social Drivers in the Development of Urban Innovation and Knowledge-Based Hubs
Social drivers provide the ground for the attraction of elites and the realization of the knowledge-based city as one of the important paradigms of the future city. The purpose of the present research is to synthesize the extensive literature regarding the influential social drivers in the development of urban innovation and knowledge-based hubs. The current research is a review in terms of its purpose, and its method is qualitative. The statistical community includes all the studies from the 1990s to 2022 (1223 sources). First, 892 sources were removed by reviewing the title, and 156 sources by reviewing the abstract. Then, the content of 175 sources was fully reviewed and analyzed, and finally, 43 articles were selected for final analysis. Cohen's kappa coefficient was equal to 0.733 with a significance level of 0.000, indicating the research's appropriate reliability. The research results show that the social drivers of innovation and knowledge-based hubs have five distinct consisting of sense of place, social capital, social integration, social well-being and socio-cultural development. Also, social drivers have 10 dimensions (including a sense of belonging to the community, social structure, infrastructure of knowledge workers, well-being, community structure, human capital, shared basis, form, image, function, and environment) and 31 components. In total, innovation and knowledge-based hubs have 115 indicators. The category of social integration includes 24% of all indicators. Other categories of sense of place, community capital, socio-cultural development, and human well-being comprise 33%, 20%, 12%, and 11% of the total indicators, respectively.
Extended Abstract
Introduction
Today, knowledge-based urban development is at the center of policymaking in various cities that are looking for increased productivity and competitiveness. Also, a knowledge-based urban development strategy is used to deal with spatial, environmental, economic, and social challenges. As a result, a new typology of knowledge environments has emerged in the form of knowledge and innovation spaces. Knowledge-based urban development, as a sustainable socio-spatial strategy, first appeared in the best global examples such as Silicon Valley, Cambridge Science Park, and Sophia Antipolis, and then accepted by leading cities in Europe, North America, Australia, and Asia, including Austin, Barcelona, Boston, Delft, Manchester, Melbourne, Singapore, and Toronto. These cities have planned digital infrastructure, green technologies, and other infrastructure requirements of their knowledge-based urban development as ways to revive stagnant urban environments, provide economic opportunities, and strengthen their global competitiveness. Therefore, the results of studies clearly indicate that for the successful development of urban innovation and knowledge-based spaces, it is necessary to pursue economic, political, physical, and social development in a balanced and comprehensive manner. Despite this, most studies have emphasized the spatial, economic, and institutional aspects and have neglected to pay attention to the social dimension. The present research aims to synthesize the extensive literature regarding social drivers influencing the development of urban innovation and knowledge-based hubs to provide a comprehensive and integrated conceptual model in relation to it.
Methodology
The current research is qualitative in terms of its fundamental purpose and method. Considering that the purpose of the current research is to extract the social components of urban knowledge-based hubs, it is considered as a review goal. Its method is qualitative and exploratory. The meta-synthesis method was used to answer the research questions. In the current research, the seven-step model of Sandelowski and Barroso (2007) was used for meta-synthesis. The statistical community includes all the studies published from the 1990s to 2022. It was searched using keywords as knowledge-based development, knowledge-intensive activities, knowledge cities, knowledge-based urban development, knowledge-based clusters, hubs of Knowledge, knowledge communities, knowledge locations, Knowledge and innovation spaces, innovation ecosystem, innovation districts, innovation clusters, social innovation in different databases including Google Scholar, Science Direct, Emerald, Springer a Scopus, Proquest, Sage Wiley, Taylor & Francis. In the initial search, 1223 sources were obtained. The critical assessment skills program tool was used to evaluate the quality of the studies that were conducted. The logic of selecting the articles was based on ten indicators, including research objectives, logic of the method, research design, sampling method, data collection, reflectivity, ethical considerations, accuracy of data analysis, clear statement of findings, and value of research. First, 892 sources were removed by reviewing the title, and 156 sources by reviewing the abstract. Then, the content of 175 sources was fully reviewed and analyzed, and finally, 43 articles were selected for final analysis. Cohen's kappa coefficient was used to measure reliability, and its results were equal to 0.733 with a significance level of 0.000, indicating the appropriate research reliability.
Results and discussion
The present research results show that studies related to the knowledge-based city have experienced many changes over time. Thus, the studies of the knowledge-based city can be divided into three time periods. The first period was between 2005 and 2012, which mostly emphasized the multi-dimensional dimensions of the knowledge-based city and extracted its conceptual framework consisting of economic, spatial, sociocultural, and institutional development. In this regard, fundamental features such as the necessity of policy-making, policy-making, and knowledge-based planning in cities have been emphasized, which leads to the promotion of human capital, the formation of the economy and knowledge-based management, and finally, the improvement of the environmental quality of cities. At the same time, the realization of this importance requires the existence of knowledge infrastructures, information and communication technology infrastructures in cities, and the ease of sharing knowledge and innovation. The second period is equal to the period from 2013 to 2015, where a special emphasis has been placed on defining the methodology for measuring and quantifying the indicators of the knowledge-based city and, in this regard, measuring the status of different cities. Knowledge-based indicators have been used to find out how much they have. Also, paying attention to the physical-spatial structure of the knowledge-based city and the need to pay attention to the unique urban planning elements for them, such as the expansion of comfort and recreational facilities such as parks, restaurants, and cafes, promotion of transportation environmentally friendly transfer of cultural assets (museums and art galleries), etc. have been carried out. In this regard, innovation and knowledge-based hubs have been emphasized by attracting diverse actors and gathering them in a geographical location, forming different clusters, and forming an innovation platform. The third period is equal to the period from 2016 to 2022, which is focused on the spatial quality of innovation hubs with the aim of streamlining to attract skilled and talented people. In this regard, the necessity of continuous innovation, attention to creativity, attracting the creative class, and bringing professional talents together has been emphasized. In the meantime, attention has been paid to social characteristics and emphasis on components such as social cohesion, social infrastructure, transparency, participation, and social tolerance in order to attract the creative class.
Conclusion
According to the results of this research, the influential social drivers in the development of innovation hubs and urban base knowledge consist of five categories, 10 dimensions, 31 components, and 115 indicators. About 24 percent of the indicators belong to the first category, sense of place. About 20 percent of the indicators are related to social capital. The category of social welfare includes about 11% of the extracted indicators. About 33% of the indicators belong to the category of social integration. In addition, about 12% of the extracted indicators are related to the socio-cultural development category.
Funding
There is no funding support.
Authors’ Contribution
Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.
Conflict of Interest
Authors declared no conflict of interest.
Acknowledgments
We are grateful to all the scientific consultants of this paper.
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