Document Type : Research Paper

Authors

1 Department of Technology Management, Faculty of Management, Islamic Azad University, South Tehran Branch, Tehran, Iran.

2 Assistant Professor, technology management Dept., Faculty of management, Islamic Azad University- south Tehran branch, Tehran, Iran. Corresponding Author:gh_abbaspour@azad.ac.ir

3 Assistant Professor, technology management Dept., Faculty of management, Islamic Azad University- south Tehran branch, Tehran, Iran.

https://doi.org/10.22054/IMS.2023.74392.2351

Abstract

Abstract
Nowadays, the development of science and technology parks and improving their performance depends on cooperation with industry and university and communication with the environment and related centers. Hence, it is important to identify cooperation network and networking indicators in science and technology parks. The purpose of this research is to identify the indicators of networking in science and technology parks. The method of the current research is qualitative and in it three methods of metacomposition, fuzzy Delphi and Dimetal were used. A search was made in Persian and English databases and 10 related studies were identified and analyzed. In order to verify the networking indicators extracted from the theoretical literature, 13 experts and managers of Pardis Technology Park were surveyed and the indicators were confirmed by the experts using the fuzzy Delphi method. In order to draw the causal model of the relationships between the indicators, DEMATEL method was used. The data was analyzed using Excel software. The results showed that networking in science and technology parks has 15 indicators, such as improving the level of products, information, increasing market share, goals and creating value. According to experts, the market share increase index is the first priority and organizational learning is the last. Drawing the causal model of networking showed that indicators such as management, organizational learning, information and knowledge are effective indicators. Indicators such as new product development, market opportunity creation, relationships and opportunity exploitation are also effective indicators in the networking of science and technology parks.

Introduction

Nowadays, the development of science and technology parks and improving their performance depends on cooperation with industry and universities and communication with the environment and related centers. Hence, it is important to identify cooperation network and networking indicators in science and technology parks. The ultimate mission of technology parks is to be able to coordinate the results obtained from academic research with the needs of the industry and thus fill the gap between the industry and the university, and this will ultimately lead to the commercialization of knowledge. One of the major influential factors in changing the approach of science and technology parks and creating new structures and mechanisms is the birth of new concepts such as networking in the field of business. The purpose of business networking is to increase competition, cooperation and organizational expansion. Considering the importance of these centers and the impact of networking on their performance, it is essential to identify the indicators of networking in science and technology parks. So far, many researchers have investigated the relationship between science and technology parks and other actors in the innovation ecosystem, but few researchers have focused only on the indicators of park networking. In this regard, this research aims to identify the factors influencing the networking of science and technology parks and to evaluate the cause-and-effect relationships between these factors by using the method of a systematic review of previous studies (super combination) and a survey of experts. This question should answer what are the indicators of networking in science and technology parks.

Literature Review

Paztto and Burin's research (2022) indicates that management control systems are effective in inter-organizational cooperation and identification of companies. This system promotes collaborative behaviors among companies related to science and technology parks. Networking and inter-organizational partnership ultimately lead to knowledge and information sharing, increasing flexibility, improving problem-solving strategies and limiting the use of power. The research of Glitova et al. (2022) showed that for cooperation and networking between industry, university and the public sector, attention should be paid to indicators such as knowledge creation by universities, research and development centers and businesses, technology transfer, creation of new businesses, industrial clusters, Business support services, customization, building the necessary infrastructure and equipment, and legal requirements at the local level are required. The research of Khan-Mirzaei et al. (2021) showed that networking and emphasizing cooperation and communication between science and technology parks and growth centers can lead to gaining a competitive advantage for the national economy. Communication with universities and research and development centers, cooperation with companies that have a similar field of work, access to the information flow and access to the information needed in the market, or in other words, the market situation, are among the factors that create a cooperation network between Science and technology, industry, university parks are important. In confirmation of this issue, Cadorin et al. (2019) stated that talent resources and the government play an important role in promoting cooperation between science and technology parks and universities. Managers of science and technology parks should strengthen their relationship with local universities and the student community (as sources of talent) and pay attention to their relations with government representatives to receive the necessary support for the development of the park.

Methodology

The method of the current research is qualitative and in it, three methods of Meta-synthesis, Fuzzy Delphi and DEMATEL were used. A search was conducted in Persian and English databases and 10 related studies were identified and analyzed. To verify the networking indicators extracted from the theoretical literature, 13 experts and managers of Pardis Technology Park were surveyed and the indicators were confirmed by the experts using the Fuzzy Delphi method. To draw the causal model of the relationships between the indicators, DEMATEL method was used. The data was analyzed using Excel software.

Results

In this research, a set of 62 codes and 15 indicators was obtained by extracting concepts effective on park networking from previous qualitative research. The main indicators include improving the level of products, and information, increasing market share, goals (park goals, socio-economic and environmental goals), creating value, exploiting the opportunities available in the park, optimizing resources, and developing new products, Knowledge includes the knowledge of the market-partners and co-creation of knowledge, the international and commercial performance of the park, creating opportunities through the market, management, the need for resources and operational resources, creating and developing relationships and organizational learning. According to experts, the market share increase index is the priority and organizational learning is the last. The indicators of relationships, value creation, resources, market opportunities, goals, management, knowledge, exploiting opportunities, resource optimization, performance, upgrading products, information and new product development are ranked second to fourteenth respectively. Indicators of management, organizational learning, information, knowledge, goals, resources, and upgrading of products are effective indicators. New product development, creating market opportunities, and relationships, exploiting opportunities, optimizing resources, creating value, and increasing market share and performance are also influential indicators in the networking of science and technology parks.

Conclusion

The review of the subject literature showed that paying attention to the indicators obtained in this research can lead to networking in science and technology parks. For example, the implementation of the indicators of improving the level of products, increasing market share, park goals, creating value, exploiting opportunities, knowledge, creating market opportunities, relations between actors, organizational learning and technical and human resources in Nihu Technology Park and Nankang Software Park in Taipei City. Networked. Researchers have pointed out various actors in the cooperation network of science and technology parks. The review of the texts in the meta-synthesis stage showed that each of the sources identified one to three actors based on their purpose. What was tried to be considered in this research was the gathering and consensus of all actors and their placement in the form of networking indicators such as increasing market share, resources and management. Among the new findings of this research, we can mention the type of causal relationships that are established between the indicators of networking in science and technology parks. Most researchers have not paid attention to these relationships and have focused more on the relationship between the park and variables such as innovation, performance, development, etc. However, the identification of networking behavior and the type of communication between the elements of this ecosystem can lead to the improvement of performance and optimization of activities and actions, and in this research, we tried to consider more and more comprehensive indicators in the cooperation network. be placed Finally, the purpose of the formation and development of science and technology parks is to increase the capacity of innovation and the growth of the knowledge-based economy through knowledge management (creation, sharing and access to knowledge and technology) among the members of the cooperation network of parks and to develop and commercialize the product, it becomes possible by them.
Keywords: Networking Indicators, Science and Technology Parks, Meta-synthesis, Fuzzy Delphi, DEMATEL.
 
 
 

Keywords

Main Subjects

آقازاده، هاشم؛ زارعی هنزکی، عباس؛ محمدی، مهدی؛ الهی، احمدرضا (1400). بررسی رابطه قابلیت شبکه­سازی پارک­های علم و فناوری بر نوآوری و عملکرد کسب‌وکار شرکت‌های عضو. مدیریت صنعتی، 13 (2)، 351-329.
حلاج یوسفی، محمدرضا؛ عالی، صمد؛ صنوبر، ناصر؛ نیکی اسفهلان، حکیمه (1400). طراحی الگوی قابلیت شبکه­سازی کارآفرینانه. توسعه کارآفرینی، 14 (2)، 260-241.
خزدوزی، لیلا؛ قاضی نوری، سید سپهر (1399). الگوی بلوغ پارک‌های فناوری بر اساس تکامل تاریخی؛ پارک‌های ایران کجا هستند؟. بهبود مدیریت،14(2)، 93-116.
رضائی صدرآبادی، مهدیه (1400). مروری بر وضعیت پارک‌های علم و فناوری و مراکز رشد در ایران. رشد فناوری، 17(66)، 62-53.
سخدری، کمال (1394). قابلیت شبکه‌سازی و عملکرد کارآفرینانه سازمانی: تبیین نقش گرایش‌های راهبردی سازمانی. توسعه کارآفرینی، 8 (1)، 174-159.
سهرابی، بابک، اعظمی، امیر، و یزدانی، حمیدرضا (1390). آسیب‌شناسی پژوهش‌های انجام‌شده در زمینه مدیریت اسلامی با رویکرد فرا ترکیب. چشم‌انداز مدیریت دولتی، 2(6)، 9-24.
 
شفقت، ابوطالب؛ رضائی، سیدجواد (1400). تحلیل ماتریس اهمیت- عملکرد شاخص­های نوآوری در مراکز علمی و پژوهشی. فصلنامه مدیریت نظامی، 21 (3)، 114-89.
عبادی، علی‌اصغر (1401). تجربیات نظام‌های نوآوری منطقه‌ای. تهران. پارک فناوری پردیس.
عباس‌پور اسفدن، قنبر (1393). کاربرد تئوری تصمیم‌گیری در مدیریت و مهندسی (کلاسیک و فازی با رویکرد پایان‌نامه‌نویسی). تهران: انتشارات اساتید برتر.
محمدی، مهدی؛ حمیدی، مهدی؛ محمودی، بهروز؛ جوادی، سپیده (1393). شناسایی، تحلیل و دسته­بندی عوامل مؤثر بر شکل­گیری شبکه­های نوآوری در شرکت­های دانش­بنیان (مطالعه موردی پارک علم و فناوری دانشگاه تهران). مدیریت نوآوری، 3 (4)، 24-1.
معاونت علمی و فناوری ریاست جمهوری (1395). در تکاپوی توسعه زیست‌بوم اقتصاد دانش‌بنیان. تهران. دانش‌بنیان فناور.
مقصودی گنجه، یاسر؛ خانی، ناصر؛ عالم تبریز، اکبر (1398). توانمندی شبکه­سازی، ساختار شبکه‌های کسب‌وکار و عملکرد تجاری­سازی در شرکت­های دانش­بنیان (مورد مطالعه: شرکت­های دانش­بنیان استان اصفهان). مدیریت توسعه فناوری، 7 (4)، 179-151.
نصر، علی؛ حاجی حسینی، حجت­اله (1396). نقش پارک­های علم و فناوری در توسعه نوآوری و فناوری. رهیافت، 27 (65)، 49-37.
 
References
Aarakit, S. M., & Kimbugwe, F. K. (2015). The Relationship between Social Networks and Firm Performance.
Aportela-Rodriguez, I. M., & Pacios, A. R. (2017). University libraries and science and technology parks: Reasons for collaboration. Libri, 67(3), 235-244.
Aslani, A., Eftekhari, H., Hamidi, M., & Nabavi, B. (2015). Commercialization methods of a new product/service in ICT industry: case of a science and technology park. Organizacija.
Bai, O., Wei, J. (2019), “Alliance Management Capability of Entrepreneurial Nonprofit Organizations and Cross-sector Alliance Performance: An fsQCA Approach”, IEEE International Symposium on Innovation and Entrepreneurship (TEMS-ISIE).
Berbegal-Mirabent, J., Alegre, I., & Guerrero, A. (2020). Mission statements and performance: An exploratory study of science parks. Long Range Planning, 53(5), 101932.
Cadorin, E., Klofsten, M., & Löfsten, H. (2021). Science Parks, talent attraction and stakeholder involvement: an international study. The Journal of Technology Transfer, 46(1), 1-28.
Chan, K. F., & Lau, T. (2005). Assessing technology incubator programs in the science park: the good, the bad and the ugly. Technovation, 25(10), 1215-1228.
Chen, M., Chang, Y., & Lee, C. (2015). Creative entrepreneurs’ guanxi networks and success: Information and resource. Journal of Business Research, 68(4), 900–905.
Chung, Y. S., Huang, S. J., Ho, M. H. C., & Liang, S. W. (2021). A 4D Analysis Framework of Competitive Advantages and Development Strategies of Urban Science and Technology Parks: The Examples of Taipei Neihu Technology Park and Nankang Software Park. Journal of Internet Technology, 22(6), 1313-1333.
Corsaro, D., & Cantù, C. (2015). Actors’ heterogeneity and the context of interaction in affecting innovation networks. Journal of Business & Industrial Marketing.
Corsaro, D., Ramos, C., Henneberg, S. C., & Naudé, P. (2012). The impact of network configurations on value constellations in business markets—The case of an innovation network. Industrial Marketing Management, 41(1), 54-67.
Glittová, K., & Šipikal, M. (2022, September). University Science Parks as an Innovative Tool for University-Business Cooperation. In European Conference on Innovation and Entrepreneurship (Vol. 17, No. 1, pp. 648-656).
Henriques, I. C., Sobreiro, V. A., & Kimura, H. (2018). Science and technology park: Future challenges. Technology in Society, 53, 144-160.
Jacobsen, A., Tanner, A. N., & Andersen, P. D. (2022). Foresight for science and technology parks in the context of smart specialisation. Technology Analysis & Strategic Management, 1-13.
Kang, B. J. (2014). Exploring governance models of science & research parks and related organizations. World Technopolis Review, 3(1), 39-54.
Khanmirzaee, S., Jafari, M., & Akhavan, P. (2022). Analyzing the competitive advantage’s criteria of science and technology parks and incubators using DEMATEL approach. Journal of the Knowledge Economy, 13(3), 2302-2318.
Mao, Z., Koksal, C. E., & Shroff, N. B. (2014). Optimal online scheduling with arbitrary hard deadlines in multihop communication networks. IEEE/ACM Transactions on Networking, 24(1), 177-189.
Parida, V., Patel, P. C., Wincent, J., & Kohtamäki, M. (2016). Network partner diversity, network capability, and sales growth in small firms. Journal of Business Research, 69(6), 2113-2117.
Pazetto, C. F., & Beuren, I. M. (2021). Control systems and interorganizational identification in technology parks cooperation. Revista Contabilidade & Finanças, 33, 13-28.
Phillimore, J. (1999). Beyond the linear view of innovation in science park evaluation An analysis of Western Australian Technology Park. Technovation, 19(11), 673-680.
Porter, M. E. (1998). Clusters and the new economics of competition. Harvard Business Review, 76(6), 77–90.
Ricardo, M. C. A., Pablo, R. P., & Francisco, J. S. M. (2011). A literature review of the effect of science and technology parks on firm performance: A new model of value creation through social capital. African Journal of Business Management, 5(30), 11999-12007.
Ruiz, M. S., da Costa, P. R., Kniess, C. T., & Ribeiro, A. P. (2017). Proposal of a theoretical model for the implementation and scalability of science parks: a case study. RAI Revista de Administração e Inovação, 14(1), 2-15.
Sadeghi, M. E., & Sadabadi, A. A. (2015). Evaluating science parks capacity to create competitive advantages: Comparison of Pardis Technology Park and Sheikh Bahaei Science and Technology Park in Iran. International journal of innovation and technology management, 12(06), 1550031.
Slotte–Kock, S., & Coviello, N. (2010). Entrepreneurship research on network processes: A review and ways forward. Entrepreneurship Theory and Practice, 34(1), 31-57.
Theeranattapong, T., Pickernell, D., & Simms, C. (2021). Systematic literature review paper: The regional innovation system-university-science park nexus. The Journal of Technology Transfer, 46(6), 2017-2050.
Walcott, S. M. (2002). Chinese industrial and science parks: Bridging the gap. The Professional Geographer, 54(3), 349-364.
 
References [In Persian]
Abbaspour Esfeden, Qanbar. (2013). The application of decision making theory in management and engineering (classical and fuzzy with thesis writing approach). Tehran. Asateed Bartar Publications. [In Persian]
AGHAZADE, HASHEM, Zareih Hanzaki, Abbas, MOHAMMADI, MEHDI, & Elahi, Ahmad Reza. (2021). The investigation of the Relationship between Capabilities of Networking of Science and Technology Parks in the Innovation and Business Performance of Park's Member Companies. JOURNAL OF INDUSTRIAL MANAGEMENT, 13(2), 329-351. SID. https://sid.ir/paper/964603 /en.  [In Persian]
Babak Sohrabi Yurtchi, Amir Aazami, Hamid Reza Yazdani, (2011). The Pathology of the Research of Islamic Management based on Meta Analysis, Journal of Public Administration Perspective, 2(6), 9. magiran.com/p947608. [In Persian]
Ebadi, Ali Asghar (1401). Experiences of regional innovation systems. Tehran. Pardis Technology Park. [In Persian]
Hallaj Yousefi, M. R., Aali, S., Sanoubar, N., & Nikki Esfahalan, H. (2021). Designing an entrepreneurial networking capability model. Journal of Entrepreneurship Development, 14(2), 241-260. doi: 10.22059/jed. 2021.311031.653470. [In Persian]
Khazdoozi, L., & Ghazinoory, S. (2020). Maturity Model of Tech-Parks based on Their Evolution; Where are Iran's parks?. Journal of Improvement Management, 14(2), 93-116. doi: 10.22034/jmi.2020. 112808. [In Persian]
Maghsoudi Ganjeh, Y., Khani, N., & Alem Tabriz, A. (2020). Networking Capability, Business Networks Structure, and Commercialization Performance in Knowledge-Based Companies (Case Study: Isfahan Province Knowledge-Based Companies). Journal of Technology Development Management, 7(4), 151-180. doi: 10.22104/jtdm.2020.3515.2218. [In Persian]
Mohammadi, M., Hamidi, M., Mahmoudi, B., & Javadi, S. (2015). Identifying, Analyzing and Categorizing Factors Affecting the Formation of Innovation Networks in Knowledge-Based Firms: A Case Study of the University of Tehran Science and Technology Park. Innovation Management Journal, 3(4), 1-24. [In Persian]
NASR, A., & HAJIHOSEINI, H.. (2017). SCIENCE AND TECHNOLOGY PARKS (STPS) ROLES IN INNOVATION AND TECHNOLOGY DEVELOPMENT. RAHYAFT, 27(65), 37-49. SID. https://sid.ir/paper/87778/en. [In Persian]
Presidency Science and Technology Vice President (2016). In the effort to develop the ecosystem of knowledge-based economy. Tehran. Danesh Bonyane Fanavar Publications. [In Persian]
Rezaeisadrabadi,Mahdieh. (2021).Science and Technology Parks and Incubators in Iran: Review. Roshd -e- Fanavari,66(17),53-62. [In Persian]
Sakhdari, K. (2015).. Journal of Entrepreneurship Development, 8(1), 159-174. doi: 10.22059/jed.2015.55473. [In Persian]
Shafaghat, A., & Rezaei, S. J. (2021). Analysis of the Importance-Performance Matrix of Innovation Indicators in Defence Scientific and Research Centres. MILITARY MANAGEMENT QUARTERLY, 21(83), 89-114. doi: 10.22034/iamu.2022.533049.2603. [In Persian]