شناسایی و تحلیل عوامل مؤثر بر فرایند انتقال تکنولوژی در قوای محرکه خودرو (مورد مطالعه:گروه صنعتی ایران خودرو)
محورهای موضوعی : مدیریت صنعتیابراهیم دوست زاده 1 , عباس طلوعی اشلقی 2 , منوچهر منطقی 3 , رضا رادفر 4
1 - دانشجوی دکتری گروه مدیریت تکنولوژی ، واحد رودهن، دانشگاه آزاد اسلامی، رودهن ، ایران
2 - استاد گروه مدیریت صنعتی، واحد علوم تحقیقات، دانشگاه آزاد اسلامی، تهران ،ایران
3 - دانشیار گروه مهندسی صنایع، دانشگاه صنعتی مالک اشتر، تهران ، ایران
4 - استاد گروه مدیریت تکنولوژی، واحد علوم تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران
کلید واژه: انتقال تکنولوژی, تحقیق و توسعه , خلاقیت, نوآوری.,
چکیده مقاله :
شناسایی عوامل مؤثر بر فرایند انتقال تکنولوژی یکی از مهمترین پیش نیازهای این فرایند می باشد، فقدان انجام پژوهش در زمینه انتقال تکنولوژی در قوای محرکه خودرو، محقق را برآن داشت تا نسبت به انجام این تحقیق اهتمام ورزد. هدف از انجام این پژوهش شناسایی و تحلیل عوامل مؤثر بر فرایند انتقال تکنولوژی و تعیین شکاف های موجود در قوای محرکه خودرو در گروه صنعتی ایران خودرو بوده، جامعه آماری تحقیق برای بخش دلفی،10 نفر از خبرگان و برای بخش تحلیل اماری، 93 نفر از افراد صاحب نظر در قوای محرکه خودرو می باشند.در این پژوهش از ابزار مصاحبه و پرسشنامه باز بهره‌برداری شد. روش تحقیق دلفی بوده و تحلیل اماری با استفاده از نرم افزارSPSS به روش تحلیل عاملی اکتشافی انجام شده است، در این پژوهش، پس از شناسایی عوامل و شکاف بین وضعیت موجود و مطلوب، نسبت به تحلیل و تعیین ارتباط بین آنها اقدام شد. مقادیر ازمونKMO، بارتلت ،r و همچنین شاخص‌های اشتراک نشان از همبستگی بین متغیرها دارد و از درجه اعتبار کافی برخوردار می‌باشد. نتایج نشان داد اگر ایران‌خودرو بخواهد 19 شکاف شناسایی شده در قوای محرکه را مرتفع یا کاهش دهد می باید به 3 عامل مشارکت فراسازمانی، زیرساخت، آگاهی و دانش توجه ویژه نماید. 9 شکاف شناسایی شده با برنامه ریزی و توجه نمودن به عامل مشارکت فراسازمانی، 5 شکاف شناسایی شده با برنامه ریزی و توجه نمودن به عامل زیرساخت و 5 شکاف شناسایی شده دیگر نیز با برنامه ریزی و توجه نمودن به عامل آگاهی و دانش، قابل کاهش می باشند.
Identifying the key factors affecting the process of technology transfer is one of the most important prerequisites of this process. The lack of comprehensive research in the area of technology transfer within automotive powertrain sector mptivated the researchers to focus on this study. Hence, the purpose of this research was to identify and analyze the key factors affecting the technology transfer process and determine the existing gaps in the car powertrains in Iran Khodro Industrial Group. The statistical population of the study consisted of ten experts for the Delphi phase and 93 automotive powertrains specialists for the statistical analysis phase. This research utilized interviews and open-ended questionnaires as the data collection instruments. The research method was Delphi and the statistical analysis was conducted using SPSS software, specifically through exploratory factor analysis. In this research,after identifying the factors and the gap between the current and desired situations, the researchers analyzed and determined the relationship between them.The KMO, Bartlett, r test values as well as the sharing indices showed the correlation between the variables with a sufficient degree of validity.The results indicated that if Iran Khodro wants to reduce the 19 identified gaps,it should pay special attention to three key factors of trans-organizational participation, infrastructure, awareness and knowledge. Additionally, it was found that identified nine gaps can be reduced throiugh planning and focus on the trans-organizational participation factor, five gaps can be addressed by planning and prioritizing the infrastructure factor, and five other identified gaps can be mitigated by planning and emphasizing the awareness and knowledge factor. Key Words: technology transfer, invention, innovation, research and development 1.Introduction Iran's automotive industry has entered new challenges based on national macro policies by starting the process of self-sufficiency and technology transfer in different sectors. Thereby, the identification and analysis of factors affecting the process of technology transfer in the automotive industry is one of the most important needs of this industry. Due to the importance and unique role of technology in the design and construction of powertrains in the automotive industry, the identification and analysis of these factors seem to be necessary so that we can identify the factors affecting the technology transfer process and better examine the gap between the current and desired situation. In this regard, the present research was conducted with the aim of identifying and analyzing the factors affecting the technology transfer process and determining the existing gaps in the driving forces of the automobile in Iran Khodro Industrial Group. 2. Literature review As expected, technology is considered one of the most important elements of power and wealth (political economy) in today's world. For this purpose, Nouri et al. (2020), in seven selected countries, including Germany, Japan, China, South Korea, United Arab Emirates, India, and Turkey identified effective factors in technology transfer using qualitative content analysis. In addition, the role of the government in technology transfer was discussed and the experts and elites of the countries were introduced as the main trustees of technology transfer. In another research, Jung Suk Lee et al., (2023), examined the key enabling technologies for the smart factory in the automotive industry. In this paper, research was conducted on the cellular manufacturing system and five key technologies for smart manufacturing in the automobile industry were identified. Digital twins, additive manufacturing, artificial intelligence-based monitoring and inspection, human-robot collaboration, and advanced supply chain and logistics were selected and described with status and applications. In addition, a five-level framework for a smart car factory was proposed based on the essential keywords of each technology trend. 3. Methodology This research is practical regarding the result and exploratory and descriptive considering its goal because on the one hand, it determines the existence or non-existence of the phenomenon, and on the other hand, there is a need to describe and interpret the relationships between the phenomena. In terms of data collection procedure, it is a survey, that is, it depends on the opinions of the experts and specialists, and regarding the type of data, it is qualitative. The statistical population of the research for the Delphi section includes ten experts, comprising the current and former managers of the engine and gearbox units of the country's automotive industry with at least five years of useful work experience in vehicle propulsion, and for the analysis section using SPSS software, based on the recommendation of the mentioned ten experts, 93 specialists and experts in car powertrains were selected from Iran Khodro Industrial Group. In this research, the method used was descriptive and applied in which an open and Delphi questionnaire was used to identify the factors affecting the technology transfer process and to determine the technology gaps in the vehicle's powertrains. Since the number of factors and gaps was relatively large, the exploratory factor analysis was used based on the recommendation of two statisticions. Exploratory factor analysis is one of the data clustering methods in the field of data mining. In management studies, this technique is used to identify the underlying factors of a set of questions. Among the most important applications of this method is data reduction or structure identification. In addition, in exploratory factor analysis, the minimum number of factors is used to obtain the common variance between a set of parts. In the present research, since the number of factors and gaps identified was relatively large (16 factors and 20 gaps) and the examination of the relationship between them was also a complex matter, using the factor analysis method in order to reduce the data could be a suitable method to analyze the data. Finally, SPSS software and exploratory factor analysis method were employed to analyze the identified factors and determine gap between the current and desired situation in driving forces. 4. Result After holding a briefing meeting with ten experts of the country's automotive industry, 35 sub-factors were determined as the effective factors on the process of technology transfer in vehicle powertrains through interviews and considering the opinions of the mentioned experts. Also, the initial list of the gaps between the existing and desirable status in the driving forces of the car were prepared. Then, after conducting three rounds of Delphi with the mentioned experts, we achieved 16 factors and 20 identified gaps. Finally, the data collection and analysis of these factors were done using SPSS software. The first hidden factor of this part of the research was related to the variables such as political, economic, cultural and social; so, infrastructure is the best option to name the first hidden factor of this research. The second hidden factor was related to the variables such as research and development, business development and foreign investment, joint cooperation and creativity and innovation; so, extra-organizational participation is the most appropriate option to name the second hidden factor of this research. The third hidden factor of this part of the research was related to the variables such as mission and vision, short-term plans, medium-term plans and long-term plans; therefore, the mission and goals are the most suitable option for naming the third hidden factor of this research. The fourth hidden factor was related to the variables such as education, research, data analysis, creation and application of knowledge; so, awareness and knowledge is the most appropriate option to name the fourth hidden factor of this research. The first hidden factor of the identified gaps of the research is related to the variables such as not using car electrification technology, engine power, not using turbo charging technology, not using hybridization technology and not using direct fuel injection technology; so, the nature of the first hidden factor of this research is research type. The second hidden factor of this part of the research is related to variables such as engine durability, increase in fuel injection pressure, engine emissions, fuel consumption and torque loss when changing gears in the gearbox; therefore, the nature of the second hidden factor of this research is research and development type. The third hidden factor of this part of the research was related to the variables such as gearbox vibration, gearbox durability, axle durability, engine sound and gearbox sound; hence, the nature of the third hidden factor of this research is investment and economic. The fourth hidden factor of this part of the research was related to variables such as adjusting the road effect, reducing the turning circle, steering of the axle and proper power transmission of the axle; s,o the nature of the fourth hidden factor of this research is creative and innovative decisions. Gearbox leakage was the last variable out of 20 variables identified by the experts, which had nothing to do with the four hidden factors identified in this research. The experts acknowledged that the most influential factor in the occurrence of these problems is operator error, which can be studied in other researches. 5. Discussion The results of this research showed that 16 identified factors are related to hidden factors such as infrastructure, extra-organizational participation, mission and goals, awareness and knowledge, and that if Iran Khodro Company wants to eliminate or reduce nine identified gaps in the driving forces of the car including adjusting the road effect, reducing the curves of the roads, steering of the axle, proper power transmission of the axle, engine durability, increase in fuel injection pressure, engine emissions, fuel consumption and torque loss when changing gear in the gearbox, it should only focus on intra-organizational cooperation. Additionally, the reduction of five other gaps including gearbox vibration, gearbox durability, axle durability, engine noise and gearbox noise requires special attention to the infrastructure factor. Moreover, the other five gaps of this research include not using car electrification technology, engine power, non-use of Turbo charging technology, non-use of hybridization technology and non-use of direct fuel injection technology can be reduced by paying attention to the factor of awareness and knowledge. Since the correct determination of factors affecting the process of technology transfer in car powertrains is a very important and effective factor in the position of the country's automotive industry, it is recommended that this research be conducted at the national level. In addition, the aforementioned research can be implemented in all automotive groups. It can also be applied in light, heavy and motorcycle construction. Finally, as a suggestion for further research, we can refer to a more in-depth and specific analysis for each of the four hidden factors identified in this research and the formulation of guidelines for the standardization of this process.
Anzolin, G., & Andreoni, A. (2023), Robotising, but how? Evidence from the automotive sector in South Africa, Journal of Manufacturing Technology Management , 34(5), 820-837.
Amal F.Soliman,(2020), The effect of leadership empowerment on technology transfer effectiveness: A proposed model: An applied study on the telecommunication companies in one of the developing countries, The Journal of High Technology Management Research, Volume 31, Issue 1, May 2020, 100371. https://doi.org/10.1016/j.hitech.2020.100371
Ebrahimpour Azbari et al., (2018), Information Technology Capability and Supply Chain Integration Capability on New Product Development Performance, Technology Development Management Quarterly / Volume 6/Number 1, Summer 2018, (In Persian). doi:10.22104/jtdm.2018.2870.1970
Jafarnejad, A., Olfat, L., MOkhtarzadeh, N., Elyasi, M., Ahangari, S,S. (2018), Value Acquisition in Strategic Technological Alliances and Factors Affecting Its Different Dimensions in the Automotive Industry, Technology Development Management Quarterly/Volume 6(2),9-48. (In Persian),https://www.sid.ir/fa/journal/ViewPaper.aspx?id=495947
John D. Lee et al., (2012), Cognition, Technology & Work volume 14, pages39–49 (2012), https://link.springer.com/article/10.1007/s10111-011-0194-3
Jongsuk, L., Ping Chong, C., Lequn, C., Poh Huat, N. N., Yerim, K., Qiong, W., Sumin, J., Jihwan, J., Siheon, C., Seung, K. M. (2023), Key Enabling Technologies for Smart Factory in Automotive Industry: Status and Applications, Int. J. Precis. Eng. Manuf.-Smart Tech., 1(1), 93-105.
J Tidd, JR Bessant (2020), John Wiley & Sons, AP - Business & Economics, 1-624. http://www. books.google.com
Jupriyanto, S.IZ. et al., (2013). Indenasan Technology Transfer Successful Model with a Macroergonomics Framework. Journal Of Applied Sciences Research. Vol 9 (4), PP 2520-2525, http://www.aensiweb.com/old/jasr/jasr/2013/2520-2525.pdf
Khatami Firoozabadi, S. M., Tabatabaeian, S.H., Dashti, M.A. (2018), Key Success Factors in the Process of Implementing Advanced Production Technologies in Industrial Enterprises, Technology Development Management Quarterly / Volume 6 / Number 4, 89-126. (In Persian). doi:10.22104/jtdm.2019.3000.2013.
Majidpour and Mojiri, (2019), The Evolution of Concepts and Policies of International Technology Transfer, Comprehensive Special Issue of Science, Technology and Innovation Policy, 12(2), 425-437. (In Persian). https://www.sid.ir
Mehdi Nejati, Hossein Akbarifard, (2016), Evaluating the Effects of Export Technology Overflow on Total Productivity of Production Factors in the Industrial Sector: The Case of Iran, New Economy and Trade, Institute of Humanities and Cultural Studies, 13(1), 141-166. (In Persian). http://ensani.ir/fa/article/382723
Meybodi, Ahmad Hadi, (2017), Investigation of technology transfer barriers in cross-selling contract and assessment of technology transfer risk in Iran's new oil contract (IPC) by FMEA method, Iranian Energy Economics Research Journal, Year 6, Issue 22, Spring 2017, Page 1-43, (InPersian).https://www.sid.ir/fa/journal/ViewPaper.aspx?ID=355886
Moghasem, Y., saeidi, P., Moghassem, Y., Mehrabian, A. (2019), Development of small and medium manufacturing businesses based on the impact of performance and innovation in technology, Technology Development Management Quarterly, 7(1), 163-194. (In Persian). https://www.sid.ir › FileServer › 4039113980106-
Mohammad Naghizadeh, (2020), A Comprehensive Approach to Investigating the Role of Technology Transfer Rules in Foreign Joint Cooperation Contracts (Case Study of Amia Pars Company) Technology Development Management Quarterly, 8(2), 45-76. (In Persian). https://www.sid.ir
Mohsen Akbari et al., (2020), The Impact of Technology Transfer, Outsourcing, Organizational Capabilities on Innovative Performance, Quarterly Journal of Innovation Management in Defense Organizations, 3( 8), 42-76. (In Persian). https://www.sid.ir/fa/journal/ViewPaper.aspx?id= 555041
Safaei, B., Mosleh Shirazi, A.N., Mohamadi, A., Alimohammadlou, M. (2018), System Model of Commercial Soft Technology Dissemination in Iranian Oil Industry, Quarterly Journal of Technology Development Management, 6(3), 41-70. (In Persian). https://www.sid.ir/fa/Journal/ViewPaper.aspx?id=495974,
Nazeem Mustapha and Gerard Ralphs, (2021) Effectiveness of technology transfer in public research institutions in South Africa: A critical review of national indicators and implications for future measurement, African Journal of Science, Technology, Innovation and Development, 14(4), 863-875. d:10.1080/20421338.2021.1893467, 2021
Nejati and Akbarifard, (2018), Assessing the effects of technology overflow from exports on the productivity of total production factors in the industrial sector: the case of Iran, Institute of Humanities and Cultural Studies, 13(1), 141-166(In Persian). http://ensani.ir/fa/article/382723,
Nguyen, N., & Aoyama, A. (2013). Exploring Cultural Differences in Implementing International Technology Transfer In the Case of Japanese Manufacturing Subsidiaries in Vietnam. Contemporary Management Research, 9(1). doi:10.7903/cmr.10338
Nilforooshan, (2018), IEEE Internet Computing (Volume: 22, Issue: 1, Jan./Feb. 2018),https://civilica.com/doc/1189674/
N. Naghizadeh, (2018), Powder Technology, Volume 332, 1 June 2018, Pages 279-286,(In Persian). https://www.sid.ir/fa/Journal/ViewPaper.aspx? ID=555300.
Noori et al., International Political Economy Studies, 2020, Vol. 3, Issue. 2, pp. 473-509(In Persian).https://ipes.razi.ac.ir/article_1698.html?lang=en.
Taghva et al., (2014), Asian Journal of Research in Business Economics and Management, Year : 2014, Volume : 4, Issue : 9, First page : ( 57) Last page (75)(In Persian). Online ISSN : 2249-7307.
Taleghani et al., (2017), Determining the Most Effective Factor of Technology Transfer in the Development of Iranian Oil Fields Using Conditional Technology Transfer Effectiveness Model, Bi-Quarterly Journal of Industrial Technology Development, 15(29), 101-123. (In Persian). https://www.sid.ir/fa/journal/ViewPaper.aspx?ID=284792.
Scuotto, V & Beatrice, O & Valentina, C& Nicotra, M & Di Gioia, L & Farina Briamonte, M., (2020), Uncovering the micro-foundations of knowledge sharing in open innovation partnerships : An intention-based perspective of technology transfer , Technological Forecasting & Social Change 152(3), 119906, https://e-tarjome.com/storage/panel/ fileuploads/2020-02-05/1580905404_E14467-e-tarjome.pdf.
Vincenzo Carvello, et al., (2023), Start-up collaboration units as knowledge brokers in Corporate Innovation Ecosystems: A study in the automotive industry, Journal of Innovation & Knowledge Volume 8, Issue 1, January–March 2023, 100303.
Zeinali, et al., (2022), Explainig and Designing of the Technology Development Model of the Automotive Industry in Iran Based on Collaborative Management , Volume 16, Issue 2- Serial Number 56, September 2022, Pages 65-95.
