نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار، دانشکده معماری و شهرسازی، دانشگاه علم و صنعت ایران، تهران، ایران.

2 دکتری شهرسازی، دانشکده معماری و شهرسازی، دانشگاه هنر تهران، تهران، ایران.

چکیده

توسعه شهری دانش ­بنیان را می­ توان فرم، رهیافت و پارادایم جدیدی برای پایداری شهرها و توسعه در دوره ­ی دانش دانست که هدف نهایی آن ایجاد شهر دانش است. در این الگوی توسعه، تقویت اعتماد و مشارکت ذینفعان برای حرکت به سوی توسعه شهری دانش ­بنیان اهمیت بسزایی دارد. از سویی، با توجه به این­که خوشه­ های دانش­ بنیان (شامل مکان­ های دانش و تکنوپل) بر این فرض استوارند که همجواری فعالیت­ های دانش­ بنیان و نوآورانه، موجب استحکام زنجیره ارزش و تعامل دانشگران و نوآوران و تسهیل به اشتراک­ گذاری دانش و تجربه و هم ­افزایی توانمندی برای توسعه خود و شهر می ­شود، لازم است پیش از انجام اقدامات مبتنی بر رویکرد خوشه­ ای، مطلوبیت این رویکرد برای توسعه شهری دانش بنیان اصفهان مورد آزمون قرار گیرد. این پژوهش برآنست تا با تحلیل شبکه ­های ارتباط، اعتماد و مشارکت ذینفعان کلیدی توسعه شهری دانش بنیان اصفهان به­ عنوان زمینه ­ساز انتقال و تبادل دانش، مطلوبیت رویکرد خوشه ­ای در توسعه شهری دانش ­بنیان اصفهان را به آزمون بگذارد. پژوهش حاضر با رویکردی کمی و هدف عملیاتیِ توصیفی- اکتشافی و در چارچوب مطالعه موردی انجام شده است. و از روش تحلیل شبکه اجتماعی و شاخص QAP استفاده شده است. یافته ­های پژوهش حاضر نشان می ­دهد که افزایش ارتباط بین ذینفعان منجر به افزایش چشم­گیر و قابل توجه مشارکت یا افزایش قابل توجه اعتماد بین آنها نمی­ شود. در واقع، در صورت وجود پیوند ارتباط بین دو ذینفع، احتمال اعتماد و همچنین مشارکت بین این دو ذینفع، کمتر از ۵۰ درصد است. بنابر این، تولید دانش بنیان لزوما نیازمند وجود مکان­ های خاص فناورانه مانند پارک­ های علم و فناوری نیست بلکه می­ تواند در فضاهای عمومی شهر و مکان­ های غیررسمی نیز اتفاق بیفتد. در واقع، دانش لازم برای توسعه شهری را نباید به معنای محدود فناورانه تلقی نمود و فضایی خاص در شهر را به آن اختصاص داد.

کلیدواژه‌ها

عنوان مقاله [English]

Appropriateness Analysis of the Cluster Approach in Knowledge-Based Urban Development of Isfahan

نویسندگان [English]

  • Ahmad Khalili 1
  • Mostafa Dehghani 2

1 Assistant Professor, School of Architecture and Urban Planning, Iran University of Science and Technology, Tehran, Iran.

2 Ph.D in Urban and Regional Planning, Faculty of Architecture and Urban Planning, University of Art, Tehran, Iran.

چکیده [English]

Extended Abstract
Background and Objectives: Knowledge-Based Urban Development (KUBD) can be considered a new form, approach, or paradigm of sustainable urban development in the knowledge age. Knowledge-based clusters (e.g., knowledge locations and technopoles) assume that the proximity of knowledge-based and innovative activities reinforces the value chain, establishes knowledge worker-innovator interaction, facilitates knowledge and experience sharing, and leads to a synergistic ability for the development of self and the city. Therefore, the purpose of this study is to test the use of the cluster approach in KBUD in Isfahan before adopting measures based on the cluster approach by analyzing the communication, trust, and participation networks of the key stakeholders of KUBD in Isfahan that provide the basis for knowledge transfer.
Method: This study was carried out in two steps by adopting a quantitative approach with the purpose of descriptive-exploratory operations in a case study framework. In the first step, the key stakeholders are identified through theoretical and non-probability sampling (i.e., snowball), and referring to KBUD experts in Isfahan, using the fuzzy screening method and power-interest matrix model. In this step, 14 key stakeholders were identified. The second step involves analyzing the structure of stakeholder relationships network using the "social network analysis (SNA)" method. The purpose of this study is to examine correlations rather than to analyze the internal patterns of three separate networks, namely communication, trust, and participation. Therefore, the Quadratic Assignment Procedure (QAP) index was used. The sample population in this step consisted of 157 members of the main KBUD stakeholders. Network data were collected through a questionnaire and analyzed using UCINET6.
Findings: The results of the linear regression relationship between the three networks of communication, trust, and participation of Isfahan KUBD stakeholders based on the QAP index indicate a significant positive correlation between communication, trust, and participation networks. The trust-participation link has a high correlation coefficient (0.74), indicating that trust is where knowledge-based interactions start and lays the groundwork for stakeholder participation. Nevertheless, the trust-relationship link and the relationship-partnership link have a fairly low correlation coefficient (<0.5). That is, simply increasing the relationship between stakeholders does significantly increase participation or mutual trust. Consequently, despite the high correlation between trust and participation networks, simply increasing the relationship between stakeholders does not significantly increase participation or mutual trust. Hence, it defies the theory of clustering businesses and knowledge-based centers toward realizing KBUD. This is because the mere buildup of such activities and their working relationships does not build mutual trust. It also does not result in their widespread involvement in producing, sharing, and applying knowledge toward urban development.
Conclusions: It is vital to promote stakeholder trust and participation in moving towards KBUD. The findings of this study are consistent with those of Story and Teters (1998) on questioning the role of clusters in technology transfer, Wested and Story (1995) on considering the importance of the actual links between universities and companies situated in science parks as exaggerated, and Messi et al. (1992) on the unavailability of significant evidence confirming the effects of geographical proximity of universities and science parks on promoting technology transfer and synergistic production support. Accordingly, a consensus can be reached with critics of the cluster theory at founding KBUD that knowledge cities should act as places for intellectual development, environmental sensitivity, social inclusion and cohesion, and participatory and transparent governance. This consensus can also be on the fact that knowledge and innovation clusters can succeed by providing a range of high-quality, attractive, and diverse places to live and work. Hence, knowledge-based production does not necessarily require constructing special technological places, e.g., science parks, but it can also occur in public urban spaces and informal places. Indeed, the knowledge required for urban development should not be regarded as technologically limited to which a specific urban space is allocated. Instead, the stage must be set to produce, share, and apply local tacit knowledge all over the city. Citizens' local tacit knowledge can be exploited to facilitate their participation in the development process.

کلیدواژه‌ها [English]

  • Knowledge-based Urban Development
  • Cluster Approach
  • Knowledge Places
  • social network analysis
  • Isfahan
داداش­پور، هاشم (1390)، نظریه­ ها و مدل ­های تازه توسعه­ منطقه­ ای خوشه ­وار، مجله اطلاعات سیاسی- اقتصادی، 26 (285)، 272-285.
رحیمی، حسین، نیک­سیرت، مسعود (1391)، مکانیابی خوشه­ های علم و فناوری به روش تحلیل سلسله ­مراتبی و با استفاده از سیستم اطلاعات مکانی، فصلنامه تخصصی پارک ها و مراکز رشد، 9 (33)، 63-70.
فرهنگی، مرجان (1392)، تبیین اصول و ویژگی­ های فضایی توسعه شهری دانش ­مبنا؛ مطالعه موردی شهر اصفهان، رساله دکتری شهرسازی به راهنمایی اسفندیار زبردست، دانشگاه تهران.
فیلد، جان (1388)، سرمایه اجتماعی،  ترجمه غلامرضا غفاری و حسین رمضانی، انتشارات کویر، چاپ دوم، تهران.
محمودپور، ئسرین (1394)، چارچوب انگاشتی برنامه ­ریزی شهری دانش ­پایه در شهر تهران، رساله دکتری برنامه ­ریزی شهری و منطقه ­ای به راهنمایی زهره عبدی دانشپور، دانشگاه شهید بهشتی.
نیکینا، آنا ، پیکه، جوزپ، سنز، لوئیس (1398)، نواحی نوآوری در عرصه جهانی؛ مفهوم و کاربرد، ترجمه هاشم آقازاده، انتشارات دانشگاه تهران، تهران.
Bond, M., and N. Harrigan. (2011), Political Dimensions of Corporate Connections. Pp.198–209 in The SAGE Handbook of Social Network Analysis, edited by John Scott and Peter J Carrington. SAGE Publications.
Borgatti, S. P., (2005), Centrality and network flow. Social Networks 27 (1), 55ـ71.
Brandes, U., Kruse, R., Spiliopoulou, M. (2009), Community Analysis in Dynamic Social Networks, Magdeburg University Press.
Carlaw, K., Oxley, L., Walker, P., Thoms, D. and Nuth, M. (2006), Beyond the Hype: Intellectual Property and the Knowledge Society, Journal of Economic Surveys, 20 (4), 633-658.
Carrillo, F. J. (2006), Knowledge Cities: Approaches, Experiences and Perspectives. Amsterdam, Boston, HeIdelberg, London, New York, Oxford, Paris, SanFrancisco, San Diego, Singapore, Sydney, Tokyo: Elsevier.
Carrillo, J., Yigitcanlar, T., Garcia, B., Lonnqvist, A. (2014), Knowledge and the city: concepts, applications and trends of knowledge-based urban development, Routledge, Washington, DC.
Carvalho, L., & Winden, W. V. (2017), Planned knowledge locations in cities: Studying emergence and change. International Journal of Knowledge-Based Development, 8(1), 47-67.‏
Casanueva, C., Castro, I., & Galán, J. L. (2013), Informational networks and innovation in mature industrial clusters. Journal of business research, 66(5), 603-613.‏
Castells, M. and Hall, P. (1994), Technopoles of the World: The Making of the 21st Century Industrial Complexes.London and New York: Routledge.
Christopherson, S., & Clark, J. (2007), Power in firm networks: What it means for regional innovation. Regional Studies, 41(9), 1223-1236.‏
Davies, J. (2012), Network Governance Theory: A Gramscian Critique, Environment and Planning A, 44(11), 2687 – 2704.
Friedman, A.L. and Miles, S. (2006), Stakeholders: Theory and Practice, Oxford University Press.
Dvir, R. and Pasher, E. (2004), Innovation Engines for Knowledge Cities: An Innovation Ecology Perspective.
Ergazakis, K., Metaxiotis, k. and Psarras, J. (2004), Towards Knowledge City: Conceptual Analysis and Success Stories, Journal of Knowledge Management, 8 (5), 5-15.
Gnyawali, D. R., & Srivastava, M. K. (2013), Complementary effects of clusters and networks on firm innovation: A conceptual model. Journal of Technology Management, 30(1),1-20.‏
Hermans, L., Kwakkel, J., Thissen, W., Koppenjan, J., & Bots, P. (2010), Policy analysis of multi-actor systems. The Hague: Lemma.
Hoen, A. R. (2002), Identifying linkages with a cluster-based methodology. Economic Systems Research, 14(2), 131-146.‏
Jacobson, A. (2012), A Cohesive Downtown from a Knowledge City Perspective - A Study in Urban Planning, Final phd Thesis Essay, the School of Engineering in Jönköping in the subject area of Building Projects with Architectural Technology.
Jepsen A. L. Eskerod P. (2009), Stakeholder analysis in projects: Challenges in using current guidelines in the real world, International Journal of Project Management, NO.27, 335–343.
Jessop, B. (2011), Metagovernance. In Mark Bevir, the SAGE Handbook of Governance. SAGE Publications Ltd, chapter 8, 106-123.
Knight, R. (2008), Knowledge-Based Development: The Challenge for Cities, in Yigitcanlar, T.(ed), Knowledge-Based Urban Development: Planning and Applications in the Information Era. Hershey and New York: Infonnation Science Reference.
Lai, Y. L., Hsu, M. S., Lin, F. J., Chen, Y. M., & Lin, Y. H. (2014), The effects of industry cluster knowledge management on innovation performance. Journal of Business Research, 67(5), 734-739.‏
Lopez-Saez, P., Navas-Lopez, J. E., Martín-de-Castro, G., & Cruz-Gonzalez, J. (2010), External knowledge acquisition processes in knowledge-intensive clusters. Journal of Knowledge Management, 14(5), 690-707.‏
Luthe T, Wyss R, Schuckert M (2012), Network governance and regional resilience to climate change: empirical evidence from mountain tourism communities in the Swiss Gotthard region. Regional Environmental Change. 12 (4), 839–854.
Massey, D. (1992), A place called home. New formations, 17(3), 3-15.‏
Miles, I. and Keenan M. (2003), Organising a Technology Foresight Exercise, Technology Foresight for Organizers, Ankara, Turkey.
Olsson, a.r. (2009), Relational rewards and communicative planning: understanding actor motivation. Journal of Planning Theory, 8(3), 263–281.
Reed, M. S., Graves, A., Dandy, N., Posthumus, H., Hubacek, K., Morris, J., & Stringer, L. C. (2009), Who’s in and why? A typology of stakeholder analysis methods for natural resource management.Journal of environmental management, 90 (5), 1933-1949.
Richardson, C. (2013), Knowledge-sharing through social interaction in a policy-driven industrial cluster. Journal ­of Public­Policy.‏
Richardson, T. (2002): Freedom and Control in Planning: Using Discourse in the Pursuit of Reflexive Praxis. In: Planning Theory & Practice, 3 (3), 353-361.
Roose, A. and Lepik, K-L. (2015), Assessment of knowledge-based urban development in the cross-border twin-city: a Tallinn-Helsinki case study, Int. J. Knowledge-Based Development, 6 (4), 299–313.
Science Reference.
Srećković, M., & Windsperger, J. (2011), Organization of knowledge transfer in clusters: a knowledge-based view. In New Developments in the Theory of Networks (pp. 299-315). Physica, Heidelberg.‏
Srećković, M., & Windsperger, J. (2013), The impact of trust on the choice of knowledge transfer mechanisms in clusters. In Network Governance (73-85). Physica, Berlin, Heidelberg.‏
Stacke, A., Emil Hoffmann, V., & Araujo Costa, H. (2012), Knowledge transfer among clustered firms: a study of Brazil. Anatolia, 23(1), 90-106.‏
Storey, D. J., & Tether, B. S. (1998), New technology-based firms in the European Union: an introduction. Research policy, 26(9), 933-946.‏
Turina, M., Confessore, G., Barbante, I., Buzzi, O., & Turina, S. (2016), Hub agribusiness in the Center Italy: Simulation of the growth of a new “industrial cluster” through logistic functions. Agriculture and agricultural science procedia, 8, 353-371.‏
van den Berg, L., Pol, P. M. 1., Winden, W. and Woets, P. (2005), European Cities in theKnowledge Economy: The Caseof Amsterdam, Dortmund, Eindhoven, Helsinki, Manchester, Munich, Munster, Rutterdam and Zaragoza.Hants, England:Ashgate.
Wang, X. (2009), Knowledge-based urban development in China, Final phd Thesis Essay, Newcastle University, the School of Geography, Politics, and Sociology.
Westhead, P., & Storey, D. J. (1995), Links between higher education institutions and high technology firms. Omega, 23(4), 345-360.‏
Wilson, L. O. U., & Spoehr, J. (2010), Labour relations and the transfer of knowledge in industrial clusters: Why do skilled workers share knowledge with colleagues in other firms?. Geographical Research, 48(1), 42-51.‏
Work Foundation. (2005), Ideopolis: Knowledge Cities. London: the work foundation.
Work Foundation. (2006), Creating and Ideopolis: Case Study of Manchester. London.
Yigitcanlar, T. (2011), Position paper: Redefining knowledge-based urban development. International Journal of KnowledgeBased Development, 2(4), 340–356.
Yigitcanlar, T., & Bulu, M. (2015), Dubaization of Istanbul: insights from the knowledgebased urban development journey of an emerging local economy, Environment and Planning A, 47(1), 89-107.
Yigitcanlar, T., & Inkinen, T. (2019), Benchmarking City Performance. In Geographies of Disruption (pp. 159-197). Springer, Cham.‏
Yigitcanlar, T., Guaralda, M., Taboada, M., & Pancholi, S. (2016), Place making for knowledge generation and innovation: Planning and branding Brisbane’s knowledge community precincts. Journal of Urban Technology, 23(1), 115-146.
Yigitcanlar, T., Velibeyoglu, K. and Baum, S. (2008), Knowledge-Based Urban Development: Planning and Applications in the Information Era. Hershey and New York: Information Science Reference.
Zhang, Y. (2005), The Science Park Phenomenon: Development, Evaluation and Typology, International Journal of Entrepreneurship & Innovation Management 5 (112), 138-154