فصلنامه علمی راهبرد

فصلنامه علمی راهبرد

تبیین نظریه جمعیتِ نوآور مبتنی بر تجارب جهان و پیشنهادهایی برای ایران

نوع مقاله : مقاله پژوهشی

نویسندگان
1 استادیار دانشگاه جامع امام حسین(ع)، تهران، ایران
2 استادیار دانشگاه جامع امام حسین(ع)، تهران، ایران.
3 دانشجوی کارشناسی ارشد دانشگاه امام حسین(ع)، تهران ایران
چکیده
جمعیت یکی از چالش‌های عمده جهان امروز است که بر الگوهای رشد اقتصادی پایدار تأثیرگذار است. پدیده اقتصادی که در این مطالعه توضیح داده می‌شود، بررسی رابطه بین جمعیت و خروجی‌های نوآورانه است. هدف این پژوهش ارائه نظریه جمعیت نوآور است. تمرکز نظریه جمعیت نوآور، بر تحلیل دامنه نرخ رشد جمعیت مناسب برای حمایت از خروجی‌های نوآورانه سطح بالا، است. این پژوهش به صورت مطالعات تطبیقی در آمار تولیدات نوآورانه کشورها و نرخ جمعیت آن‌ها و مبتنی بر روش حداقل مربعات است. یافته‌های این مطالعه نشان می‌دهد که جهان غرب در مستندات علمی خود تلاش دارد که رابطه بین نرخ رشد جمعیت و نوآوری را طوری مدیریت کند که کشورهای دارای سطح متوسطی از جمعیت را در دستیابی به نوآوری نشان دهد؛ حال آنکه تجارب جهانی بیانگر وجود یک رابطه مستقیم بین تعداد جمعیت ملل و توفیق آن کشور در دستیابی به نوآوری‌های نوظهور است. یافته‌ها نشان می‌دهد وجود روابطی خلاف این اصل در برخی کشورها، حاصل وضع و اعمال قواعد ضدجمعیتی است. ‌ نتایج این پژوهش پیامدهای سیاست عمومی منتج از این دو نگاه در نسبت به نرخ جمعیت و تولید نوآوری باعث خواهد شد که یک کشور با بحران همزمان نسلی و کم شدن توان نوآورانه مواجه شود یا خیزش مناسب برای تولید نوآوری‌های مورد نیاز خود را از طریق نیروی جوان تضمین نماید. لذا، کشورهایی که در صدد تمدن‌سازی هستند، ناگزیر باید به سمت تولید نسل بیشتر حرکت کنند، در غیر این صورت، همواره به عنوان یک کشور پیرو و غیر خلاق شناسایی خواهند شد.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Exploring the Dimensions of the Innovative Population Theory through Global Experiences: Policy Recommendations for Iran

نویسندگان English

khalil noruzi 1
mohammad abbasi 2
mohammad faraji 3
1 Assistant Professor, Imam Hussein University, Tehran, Iran
2 Assistant Professor, Imam Hussein University, Tehran, Iran.
3 MA Student, Imam Hussein University, Tehran, Iran.
چکیده English

Population dynamics have emerged as a critical global issue with direct implications for sustainable economic development. This study examines the correlation between population size and innovative output among member states of the Organisation for Economic Co-operation and Development (OECD), introducing a new conceptual framework entitled the Highly Innovative Population Theory (HIPT). HIPT investigates the optimal range of population growth conducive to fostering high levels of innovation. Employing a comparative approach and utilizing least squares regression analysis, the study analyzes innovation metrics in relation to population data across selected countries. The findings reveal that while Western scientific discourse often emphasizes moderate population levels as ideal for innovation, global empirical evidence suggests a more straightforward positive correlation: countries with larger populations tend to demonstrate greater capacity for breakthrough innovation. Exceptions to this trend are frequently associated with the implementation of restrictive population policies. The study concludes that national public policies reflecting either perspective will significantly influence a country's future innovation potential. Nations that limit generational growth risk facing simultaneous demographic decline and diminished innovation capabilities. Conversely, those that strategically invest in population expansion, particularly youth development, are more likely to achieve innovation-led growth. For countries aspiring to civilizational advancement, fostering a growing and dynamic population is not merely advantageous but essential.
 

کلیدواژه‌ها English

Innovative population
innovation
population
generation
  • Ahadi, M. R., & Eyvazi, M. R. (2020). Population aging: A challenge to the national security of the Islamic Republic of Iran in the next two decades. Rahbord (Strategy), 29(96), 63–102.
  • Austin, A. L., & Brewer, J. W. (1971). World population growth and related technical problems. Technological Forecasting and Social Change, 3, 23–49.
  • Australian Bureau of Statistics. (2021). Population estimates and projections.
  • Barros, A. J. D., & Victora, C. G. (2019). The impact of health services on maternal and child health in Brazil. The Lancet, 394(10196), 1386–1396.
  • Boserup, E. (1981). Population and technology (Vol. 255). Oxford: Blackwell.
  • Boserup, E. (2014). The conditions of agricultural growth: The economics of agrarian change under population pressure. Routledge.
  • Brynjolfsson, E., & McAfee, A. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W. W. Norton & Company.
  • Christensen, C. M. (1997). The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail. Harvard Business Review Press.
  • Coccia, M. (2007). Macchine, lavoro e accrescimento della ricchezza... CNR-IRCrES Research Institute, Italy.
  • Diamond, J. (1993). Ten thousand years of solitude. DISCOVER-NEW YORK-, 14, 48–48.
  • (2020). Family policies in Greece: Challenges and opportunities.
  • Fagerberg, J. (2005). Innovation: A Guide to the Literature. In The Oxford Handbook of Innovation (pp. 1–26). Oxford University Press.
  • Gonzalez, M. (2019). Education and social inequality in Mexico. Journal of Latin American Studies, 51(3), 485–511.
  • Government of Canada. (2020). Maternity and parental benefits.
  • Grossman, G. M., & Helpman, E. (1993). Innovation and growth in the global economy. MIT Press.
  • Hempel, C. G. (1965). Aspects of scientific explanation. New York: Free Press.
  • Hirano, K. (2019). Japan’s family policy and its impact on fertility. Journal of Family Issues, 40(6), 762–784.
  • Huebner, J. (2005). A possible declining trend for worldwide innovation. Technological Forecasting and Social Change, 72(8), 980–986.
  • Huebner, J. (2005). Discussion of Huebner article – Comments by John Smart, Response by Jonathan Huebner. Technological Forecasting and Social Change, 72(8), 995–1000.
  • Hunt, J. (2011). Which immigrants are most innovative and entrepreneurial? Journal of Labor Economics, 29(3), 417–457.
  • Hunt, J., & Gauthier-Loiselle, M. (2010). How much does immigration boost innovation? American Economic Journal: Macroeconomics, 2(2), 31–56.
  • Instituto Nacional de Estadística (INE). (2020). Demographic indicators in Spain.
  • Istituto Nazionale di Statistica (ISTAT). (2021). Population and social conditions.
  • Jones, C. I. (1995). R & D-based models of economic growth. Journal of Political Economy, 103(4), 759–784.
  • Kallio, K. (2019). Family policies in Finland: A historical perspective. Journal of Family Research, 31(2), 152–173.
  • Kato, T., & Kato, H. (2018). Japan’s declining birth rate: Causes and solutions. Asian Economic Policy Review, 13(1), 94–110.
  • Kealey, T. (1996). The economic laws of scientific research. London, New York.
  • Kerr, W. R., & Lincoln, W. F. (2010). The supply side of innovation: H-1B visa reforms and US ethnic invention. Journal of Labor Economics, 28(3), 473–508.
  • Kremer, M. (1993). Population growth and technological change: One million BC to 1990. The Quarterly Journal of Economics, 108(3), 681–716.
  • Kreyenfeld, M. (2017). Fertility in East and West Germany: A comparison. Demographic Research, 37, 1351–1380.
  • Kuznets, S. (1960). Population change and aggregate output. In Demographic and economic change in developed countries (pp. 324–351). Columbia University Press.
  • LePoire, D. J. (2010). Long-term population, productivity, and energy use trends in the sequence of leading capitalist nations. Technological Forecasting and Social Change, 77(8), 1303–1310.
  • Malkova, T., & Sinyavskaya, O. (2017). Demographic trends in Russia. Russian Journal of Economics, 3(4), 385–404.
  • Mansfield, E. (1991). Technological change and the management of the innovation process. Research Policy, 20(5), 439–455.
  • Modis, T. (2005). Discussion of Huebner article.
  • National Academies of Sciences, Engineering, and Medicine. (2020). The future of the U.S. workforce.
  • National Women’s Law Center. (2020). The importance of paid family leave.
  • (2020). Family database.
  • Porter, M. E., & Stern, S. (2001). National innovative capacity. In The Global Competitiveness Report 2001–2002 (pp. 102–120). Oxford University Press.
  • Rogers, E. M. (2003). Diffusion of Innovations (5th ed.). Free Press.
  • Sadeghi, S. H., & Eskandari, M. (2025). Identifying dimensions and components effective in designing the emerging technology acquisition system for the armed forces. Rahbord (Strategy), 33(2), 1–40.
  • Schumpeter, J. A. (1934). The Theory of Economic Development: An Inquiry into Profits, Capital, Credit, Interest, and the Business Cycle. Harvard University Press.
  • Sheffield, J. (1998). World population growth and the role of annual energy use per capita. Technological Forecasting and Social Change, 59(1), 55–87.
  • Simon, J. L. (2019). The economics of population growth (Vol. 5403). Princeton University Press.
  • Smart, J. (2005). Measuring innovation in an accelerating world: Review of “A possible declining trend for worldwide innovation”, Jonathan Huebner. Technological Forecasting and Social Change, 72, 988–995.
  • Strulik, H. (2005). The role of human capital and population growth in R&D‐based models of economic growth. Review of International Economics, 13(1), 129–145.
  • Thagard, P. (2018). Computational models in science and philosophy. Introduction to Formal Philosophy, 457–467.
  • Tushman, M. L., & Anderson, P. (1986). Technological Discontinuities and Organizational Environments. Administrative Science Quarterly, 31(3), 439–465.
  • United Nations. (2022). World population prospects 2022. United Nations Department of Economic and Social Affairs, Population Division.
  • Valli, V., & Saccone, D. (2011). Economic development and population growth: An inverted-U shaped curve. Working Paper Series, Departments of Economics Torino, Working Paper No. 5/2011.
  • Verhoeven, M. (2018). Parental education and child development in the Netherlands. Child Development Perspectives, 12(2), 117–121.
  • World Health Organization. (2021). World health statistics 2021.
  • Young, A. (1993). Invention and bounded learning by doing. Journal of Political Economy, 101(3), 443–472.
  • Young, H. P. (2009). Innovation diffusion in heterogeneous populations: Contagion, social influence, and social learning. American Economic Review, 99(5), 1899–1924.

 

  • تاریخ دریافت 22 دی 1403
  • تاریخ بازنگری 01 اردیبهشت 1404
  • تاریخ پذیرش 03 اردیبهشت 1404