تدوین مدل جامع ارزیابی عملکرد نظامهای نوآوری منطقه‌ای(مطالعه موردی: منطقه ویژه علم و فناوری استان یزد)

فصلنامه علمی برنامه ریزی منطقه ای

دوره 13، شماره 51، آذر 1402، صفحه 91-106   

نوع مقاله: مقاله پژوهشی

شناسه دیجیتال (DOI): 10.30495/jzpm.2021.28081.3899

نویسندگان

علی اصغر سعدآبادی^{* 1}؛ زهره رحیمی راد²؛ کیارش فرتاش¹

¹اســتادیار پژوهشکده مطالعات بنیادین علــم و فنــاوری، دانشــگاه شــهید بهشــتی، تهــران، ایــران.

²دانش آموخته دکتـری سیاسـتگذاری علـم و فنـاوری، دانشـگاه مازنـدران، مازنـدران، ایران.

تاریخ دریافت: 03 خرداد 1400،  تاریخ بازنگری: 02 مهر 1400،  تاریخ پذیرش: 04 مهر 1400 

چکیده

طبق شواهد، میان مناطق مختلف جغرافیایی توزیع نامتوازنی در سطح و نوع رفتار نوآورانه دارند. نظام نوآوری منطقه‌ای، بعنوان یکی از نظریه‌های مطرح در این حوزه، نوآوری را به عنوان فرآیندی حاصل از عوامل مختلف درون و بیرون از بنگاه‌ها در نظر می‌گیرد. پژوهشگران و سازمان‌های دولتی برای پایش نظام‌های نوآوری منطقه‌ای خود، مدلهای فراوانی را باتوجه به ویژگی‌های خاص هر منطقه‌ ارائه نموده‌اند. در این پژوهش نیز تلاش شده است تا مدلی بر اساس بافت و شرایط مناطق در کشور ایران جهت رصد نظام‌های نوآوری منطقه‌ای ارائه ‌شود. ابتدا پس از مرور ادبیات و مصاحبه با خبرگان، داده‌های حاصله مورد تحلیل مضمون قرار گرفته و ابعاد، مولفه‌ها و شاخصهای اولیه شناسایی شدند. سپس در ادامه، پس از استخراج و اصلاح شاخص‌های موردنظر با بکارگیری تکنیک دلفی فازی ، مدلی جامع در 5 بعد، 20 شاخص و 180 زیر شاخص جهت ارزیابی نظام نوآوری منطقه‌ای شناسایی شد. مدل نهایی متشکل از ابعاد ویژگی‌ های مکانی، فرآورده‌ های نوآورانه، سرمایه انسانی، اقتصاد، و رفتار بنگاه‌ها و تعاملات منطقه‌ای است که هر بعد، شاخصها و زیرشاخص های خود را داراست. در انتها نیز نظام نوآوری منطقه ای استان یزد بعنوان یک منطقه ویژه علم و فناوری با استفاده از این مدل مورد ارزیابی قرار گرفت. نتایج ارزیابی نشان داد ابعاد ویژگیهای مکانی و رفتار بنگاهها و تعاملات منطقه‌ای در وضعیت بهتری نسبت به سایر ابعاد قرار دارند گرچه میزان پیشبرد تمام ابعاد کمتر از 50 درصد است. همچنین طبق این نتایج ابعاد فراورده های نوآورانه و اقتصادی کمترین میزان پیشبرد را دارد.

کلیدواژه‌ها

نوآوری؛ نظام نوآوری منطقه‌ای؛ مدل ارزیابی؛ استان یزد

عنوان مقاله [English]

Develop a comprehensive model for evaluating the performance of regional innovation systems (Case study: Science and Technology Special Region of Yazd)

نویسندگان [English]

ali asghar sadabadi¹؛ zohreh rahimi rad²؛ kiarash fartash¹

¹Assistant Professor, Institute for Science and Technology Studies, Shahid Beheshti University, Tehran, Iran.

²Ph.D. of Science and Technology Policy, University of Mazandaran, Mazandaran, Iran.

چکیده [English]

According to the evidence, there are unbalanced distributions in different geographical areas in terms of level and type of innovative behavior. Regional innovation system, as one of the theories in this field, considers innovation as a process resulting from various factors inside and outside companies. Researchers and government agencies have provided many models for monitoring their regional innovation systems, taking into account the specific characteristics of each region. In this research, by a comprehensive overview of the regional innovation model, has been tried to provide a model based on the context and conditions of the regions in Iran for monitoring of regional innovation systems. In the first stage, after reviewing the literature, interviewing the experts and then thematic analyzing the content of the obtained data, initial Dimensions and indicators were identified Then, a Fuzzy Delphi technique and a seven-scale questionnaire were used to test the results and expert opinion. Finally, after the extraction and correction of the indicators to evaluate the regional innovation systems, a comprehensive model was identified in 5 dimensions, 20 indicators and 180 sub-indicators. The proposed regional innovation system assessment model consists of firms' behavior and regional interactions, economy, Human Capital, Innovative outputs, Locational Features, that each dimension has its own indicators and sub-indicators, each one is discussed in the paper.
Finally, the regional innovation system of Yazd province as a special science and technology region was evaluated using this model. The evaluation results showed that the Locational Features and firms' behavior and regional interactions are in a better position than other dimensions, although the progress rate of all dimensions is less than 50%. Also, according to these results, the dimensions of innovative outputs and economy have the least amount of progress.
Extended Abstract
 
Introduction
Innovation is a key factor in economic development and growth; This fact has long been agreed upon by researchers, entrepreneurs, and economic and technological policy makers. Evidence shows that there is an unbalanced distribution between different geographical regions in the level and type of innovative behavior. Especially in our country, where the conditions and characteristics and as a result the development requirements of different regions of the country are very different, so that sometimes even in one province, several regions can be identified in terms of development. Therefore, one of the important tasks of planners is to evaluate and recognize the development potential and capacities of geographical areas, so that using this knowledge can provide the grounds for the development of regions. In Iran, the establishment of science and technology special regions with the aim of achieving a knowledge-based economy from the Fourth Development Plan onwards and also in order to achieve the goals outlined in the Twenty-Year Vision Document has been considered. Also, the emphasis of the Sixth Development Plan on issues such as the formation of entrepreneurial universities, knowledge-based economy, science and technology parks and entrepreneurial training centers, etc. have been manifestations of attention to such areas in recent years. In this regard, the plan of Yazd province science and technology special regions along with several other provinces since 2006 with the approval of the cabinet, is on the agenda of the senior management of this province, despite policymakers' attention to the development of regions in the country. It is not given much attention and faces problems such as lack of regional data. This study seeks to answer the following two questions:1. What are the dimensions, components and evaluation indicators of regional innovation systems? 2. According to the identified model, what is the situation of the special science and technology zone of Yazd province?
 
Methodology
This research is exploratory-descriptive in terms of orientation in which the model and description of the results are presented. Also, this research is applied in terms of purpose and its nature is quantitative-qualitative (mixed) and thematic analysis and fuzzy delphi methods are used. The present research is done in 2 stages: 1- Identifying and extracting the evaluation model of regional innovation system 2- Evaluating a regional innovation system as a case study. In first step, the researcher seeks to identify the dimensions, components and evaluation indicators of the regional innovation system to determine the performance of this system. To achieve this goal, first the theoretical foundations of regional innovation systems were studied and regional-based innovation models were comprehensively reviewed. Thus, while understanding the main concepts in the regional innovation system, the main aspects and dimensions of each of the proposed models were identified to be used in presenting the indigenous model of our country. Then, by collecting the opinions of experts in the field of science and technology policy, the dimensions, components and indicators appropriate to the context of our country, which were neglected in previous models, were identified and refined, and other dimensions of the model were completed. Then, after extracting the initial framework, in order to finalize and ensure the dimensions, components and indicators extracted and for validating it in 4 stages, Ishikawa fuzzy Delphi technique and questionnaire tools were used. In second step, the regional innovation system of Yazd province was monitored by a survey of scientific and executive experts of this province.
 
 Results and discussion
After extracting and modifying the final indicators, a comprehensive model in 5 dimensions, 16 indicators and 176 sub-indicators were identified to evaluate the regional innovation system. The final model consists of the dimensions of spatial features, innovative products, human capital, economics, and firm behavior and regional interactions. Finally, the regional innovation system of Yazd province as a science and technology special regions was evaluated using this model. According to the results of experts, the scores of dimensions of spatial characteristics, innovative products, human capital, economy and firm behavior and regional interactions are 0.44, 0.36, 0.43, 0.36 and 0.44, respectively. The evaluation results showed that the dimensions of spatial features and behavior of firms and regional interactions are in a better position than other dimensions, although the rate of advancement of all dimensions is less than 50%. Also, according to these results, the dimensions of innovative products and economy have the least amount of progress. According to the results of the survey, the regulatory and legal features of this province are inappropriate. Appropriate rules can play an incentive, motivating and facilitating role in innovation and business. Also, although the research publication is in good condition, but the patent is weak in this province. Also, according to experts, the human capital, like other dimensions, is in a lower than average position. The incomeand investment of enterprises in this province is also low. The behavior of firms and regional interactions, which include indicators such as firms having skilled and trained employees, which are known as the flourishing factors of innovation and entrepreneurship of firms, need to be further strengthened and the application of different strategies at different levels.
 
 Conclusion
The regional innovation system can be considered as the result of the interaction of regional inputs such as formal and informal governmental and non-governmental organizations, enterprises and institutions, which in the vicinity of each other leads to the creation, application and distribution of knowledge and ultimately increases innovation and competitiveness in the region. In this study, a model of the dimensions and indicators affecting the regional innovation system was extracted. One of the limitations of this research is the quality of a small number of research indicators such as risk aversion. It is suggested that in future research, a set of indicators extracted in several other selected regions of Iran (such as Yazd, which was studied in this study) be implemented to identify both strengths and weaknesses and its efficiency, as well as the innovation system of these regions. Measure and compare. In addition, the weighting of the indicators used in the model presented based on different weighting methods such as AHP will be helpful in completing this research.
 

کلیدواژه‌ها [English]

Innovation, regional innovation system, evaluation model, Yazd province

مراجع

• Asheim, B. T. & Isaksen, A. )1997(. Location, agglomeration and innovation: Towards regional innovation systems in Norway. European Planning Studies, 5(3), 299–330.
• Braun, V., & Clarke, V. )2006(. Using thematic analysis in psychology. Qualitative research in psychology, 3(2), 77-101.
• Cooke, P. (2004). Evolution of Regional Innovation Systems – Emergence, Theory, Challenge for Action. Cooke P. (Ed.). Regional Innovation Systems, 2nd, 1-18 London, UK: Routledge.
• Cooke, P. Gomez Uranga, M. Etxebarria, G. )1997(. Regional innovation systems: Institutional and organisational dimensions. Research Policy, 26, 475-491
• Dadashpoor, H., Zahedpour, S. (2013). An analysis of patterns of regional specialization and spatial concentration of industries in Iran. Regional Planning, 3(11), 1-18. [In Persian]
• Diez, M. A., & Esteban, M. S. )2000(. The evaluation of regional innovation and cluster policies: looking for new approaches. 4. EES Konferansında Sunulan Tebliğ, 12-14.
• Doloreux, D. )2004(. Regional innovation systems in Canada: a comparative study. Regional studies, 38(5), 479-492.
• Florida R. (1995). Toward the learning region. Futures. 27(5):527–36.
• Guba, E. L., & Lincoln, Y. (1994). Competing paradigms in qualitative research. Handbook of cualitative research. California: Sage, 105-117.
• Iammarino, S., Mc Cann, P. (2006). The Structure and Evolution of Industrial Clusters: Transactions, Technology and Knowledge Spillovers. Research Policy, 35(7), 1018-1036.
• Khosravaninezhad, S., Alizadeh, A., Noghsan Mohamadi, M., Akbari, R. (2020). Science and Technology Special Regions; New Approach in Sustainable Development (Case: Science and Technology Special Region of Yazd). Town and Country Planning, 12(1), 225-252. [In Persian]
• Krätke, S. (2002). Network analysis of production clusters: the Potsdam/Babelsberg film industry as an example. European Planning Studies, 10(1), 27-54.
• Maillat, D. (1998).  From  the  Industrial  District  to  the  Innovative  Milieu:  Contribution  to  an Analysis   Territorialized   Production      Discussion   Paper,   Université   de Neutchatel.
• Malmberg, A., Maskell, P. (2002). The Elusive Concept of Localization Economies: Towards a Knowledge-Based Theory of Spatial Clustering. Environment and Planning, 34(3), 429-449.
• Mohammadi, Y., moghbel, A., Bagheri Moghaddam, N. (2019). Functional Analysis Framework of Regional Innovation System in Developing Countries. Journal of Technology Development Management, 7(2), 43-87. [In Persian]
• Morgan, K. (1997). The learning region: institutions, innovation and regional renewal, Regional Studies, 31, 491–504.
• Naghizadeh, R., Elahi, S., Manteghi, M., Ghazinoory, S. (2015). The Meta-Synthesis of Regional Innovation Models: A Review of 1990–2013. Innovation Management Journal, 3(4), 25-56. [In Persian]
• Pakzad, M, Sadabadi, A, Kazemi, M, Azimi, A, Hosseini, SA. (2017). Regional Innovation System: Concepts and evaluation models. First Edition. Tehran: National Research Institute For Science Policy. [In Persian]
• Parizad, Taher., Asadi, Saleh., Molai-Gholichi, Mohammad & Sheikhi, Hojat. (2012). "Investigation and Analysis of Relative Capabilities of Regional Development in Ports of Northern Iran Using Integration of TOPSIS and ELECTRE Techniques". Regional Planning, 2(6), 15-29. [In Persian]
• Razavi, SM, Akbari, M. (2010). Innovation system. First Edition. Tehran: Tehran University Press [In Persian]
• Scott A. J. (1988). New Industrial Spaces, London, UK: Pion.
• Stejskal, J., Kuvíková, H., & Meričková, B. M. (2018). Regional Innovation Systems Analysis and Evaluation: The Case of the Czech Republic. In Knowledge Spillovers in Regional Innovation Systems (pp. 81-113). Springer, Cham.
• Wolfe, D. (2003). Clusters old and new: The Transition to a Knowledge Economy in Canada’s Regions. Kingston: Queen’s School of Policy Studies.
• Yin, R., K. (2014). Case Study Research: design and Methods. Sage Publication.
• Zali, N., Sajjadi asl, S., abizadeh, S. (2020). Application of analytical models in the formulation of balanced regional development strategies Case Study: Kohgiluyeh and Boyer-Ahmad Province. Regional Planning, 9(36), 49-66. [In Persian]