اقتصاد اسلامی

اقتصاد اسلامی

اقتصاد علم و تئوری انگیزش؛ دلالت‌هایی برای مطالعات اقتصاد مقاومتی

نوع مقاله : مقاله پژوهشی

نویسندگان
سعید فراهانی فرد 1
حمید رضا مقصودی 2
رسول غلامزاده 3
علی اکبر ابراهیمی نژاد رفسنجانی 4
1 استاد تمام گروه اقتصاد اسلامی دانشگاه قم
2 استادیارگروه اقتصاد اسلامی دانشگاه قم
3 مربی، گروه مدیریت بازرگانی و IT، دانشگاه پیام نور، تهران، ایران
4 دانشجوی دکتری اقتصاد اسلامی دانشگاه قم
10.22034/iec.2024.2026593.2741
چکیده
نظام انگیزشی و مکانیسم تصمیم‌گیری انسان، محور بسیاری از توسعه‌های مهم دانش اقتصاد است. تئوری نظام انگیزش در دانش اقتصاد با کنارگذاشتن فروض محدودکننده نئوکلاسیک در حال ارائه تحلیل­های کامل­تری از نظام انگیزشی و نحوه رفتار انسان­ها در شرایط واقعی اقتصادی است. این پیشرفت در تئوری انگیزش، «اقتصاد علم» را نیز تحت تأثیر قرار داد و اقتصاددانان را واداشت اثرگذاری انگیزه­های غیر مالی بر عملکرد تولیدکنندگان علم را نیز بررسی کنند. در پژوهش حاضر ضمن احصای انواع انگیزه­ها و مشوق­های تأثیرگذار بر انگیزش دانشمندان و تولیدکنندگان علم، با بهره­گیری از روش حداقل مربعات جزئی (PLS) داده­های تکمیل‌شده توسط 65 عضو هیئت علمی (33 استاد تمام، 32 استادیار و دانشیار) از 19 دانشگاه سراسر کشور در نرم‌افزار SMART PLS4 مورد بررسی و تحلیل قرارگرفته و تأثیرگذاری انگیزه درونی، دینی، شغلی و مشوق مالی بر نظام انگیزش دانشمندان بررسی شده­ است. ضریب تعیین یک برای مدل نشان می‌دهد ابعاد تعریف‌شده به صورت کامل سازه مرکزی را پوشش داده و تبیین می‌کنند. یافته­های تحقیق نشان می­دهد انگیزه درونی، دینی، شغلی و مشوق مالی به‌ترتیب با 38/0، 45/0، 24/0 و 33/0 اثرات مثبتی بر نظام انگیزش دانشمند دارند. همچنین بر اساس ماتریس اهمیت-عملکرد، انگیزه دینی، انگیزه درونی و مشوق مالی به‌ترتیب بیشترین اهمیت را در نظام انگیزش دانشمند دارند که از نظر عملکرد نیز انگیزه دینی دارای بالاترین عملکرد است. این یافته­ها می­توانند مطالعات سیاست‌گذاری علم و فناوری با رویکرد اقتصاد مقاومتی و اقتصاد اسلامی را تحت تأثیر قرار دهند.
کلیدواژه‌ها
حداقل مربعات جزئی
اقتصاد مقاومتی
اقتصاد علم
انگیزش دانشمندان

عنوان مقاله English

Economics of science and theory of motivation; Implications for resistance economy studies

نویسندگان English

saeed farahanifard 1
HamidReza Maghsoodi 2
Rasoul Gholamzade 3
Ali Akbar Ebrahimi Nejad Rafsanjani 4
1 Professor of the Islamic Economics Department of Qom University
2 Assistant Professor, Department of Islamic Economics, University of Qom
3 Instructor, Department of Business Administration & IT, Payame Noor University, Tehran, Iran.
4 PhD student of Islamic Economics, University of Qom
چکیده English

The motivational system and human decision-making mechanism are the focus of many important developments in economic knowledge. The theory of motivational system in the science of economics, by abandoning the restrictive neoclassical assumptions, is presenting a more complete analysis of the motivational system and the way people behave in real economic conditions. This progress in the theory of motivation also affected the "economy of science" and made economists to examine the effect of internal motivations and non-financial motivations on the performance of science producers. In the current research, while counting the types of motivations and incentives that influence the motivation of scientists and science producers, using the partial least squares (PLS) method, the data completed by 65 faculty members (33 full professors, 32 assistant professors and associate professor) from 19 universities all over the country were investigated and analyzed in SMART PLS4 software, and the influence of Intrinsic motivation, religious motivation, career rewards and financial rewards endives on the motivation system of scientists was investigated. A determination coefficient of one for the model shows that the defined dimensions completely cover and explain the central structure. The findings of the research show that internal, religious, occupational and financial incentives have positive effects on the scientist's motivation system with 0.38, 0.45, 0.24 and 0.33 respectively. Also, based on the importance-performance matrix, religious motivation, internal motivation, and financial incentive are respectively the most important in the scientist's motivation system, and in terms of performance, religious motivation has the highest performance. These findings can influence science and technology policy-making studies with the approach of resistance economy and Islamic economy.

کلیدواژه‌ها English

economics of science
resistance economy
scientists' motivations
partial least squares (PLS) method
  1. آخوند خراسانی، محمدکاظم بن حسین (1409ق). کفایة الاصول. قم: انتشارات اسلامی.
  2. آذر، عادل، غلامزاده، رسول (1395). مدلسازی معادلات ساختاری کمترین مربعات جزئی. تهران: انتشارات نگاه دانش.
  3. آذر، عادل، غلامزاده، رسول، قنواتی، مهدی (1391). مدلسازی مسیری-ساختاری در مدیریت. انتشارات نگاه دانش.
  4. حر عاملی، شیخ محمدحسن (1409ق). وسائل الشیعه. 30 جلد، قم: مؤسسه آل البیت:.
  5. ری شهری، محمد (1389). منتخب میزان الحکمه. تلخیص حمید حسینی، ترجمه حمیدرضا شیخی، قم: دار الحدیث.
  6. شعبانی، اولیاء (1389) نقش نیت در فعل و هدف اخلاقی. راه تربیت، 5 (11).
  7. طوسی، محمد بن حسن (1365). تهذیب الاحکام. تهران: دار الکتب الإسلامیه.
  8. کلینی، محمد بن یعقوب (1369). اصول کافی. ترجمه و شرح سیدجواد مصطفوی، 4 جلد، تهران: کتاب فروشى علمیه اسلامیه‏.
  9. مجلسى، محمدباقربن‌محمدتقى (1403ق). بحارالأنوار. بیروت: دار إحیاء التراث العربی.
  10. مرکز اطلاعات و مدارک اسلامی (1389). فرهنگ‌نامه اصول فقه. قم: پژوهشگاه علوم و فرهنگ اسلامی.
  11. منسوب به جعفربن‌محمد7 (1360). مصباح الشریعة و مفتاح الحقیقة. ترجمه حسن مصطفوى، 1جلد، تهران: انجمن اسلامى حکمت و فلسفه ایران.
  12. نورث، داگلاس (1379). ساختار و دگرگونی در تاریخ اقتصادی. ترجمه غلامرضا آزاد (ارمکی)، تهران: نشر نی.
  13. هاشمی شاهرودی، سیدمحمود (1382). فرهنگ فقه مطابق مذهب اهل بیت. 5 جلد، قم: مؤسسه دایرةالمعارف فقه اسلامی.
  14. Kopytova, A. (2017). Pattern of the rational worker incentive system. International Science Conference SPbWOSCE-2016 “SMART City”, 106, 2017.
  15. Adams, Julia (1996). Principals and Agents, Colonialists and Company Men: The Decay of Colonial Control in the Dutch East Indies. American Sociological Review, 61 (1), 12–28.
  16. Agner, Erik (2021). A course in Behavioral Economics (3rd Ed.). Red Globe Press, 2–4.
  17. Arthur Diamond, Jr. (2008). economics of Science. The New Palgrave Dictionary of Economics, 2nd Edition, Basingstoke and New York: Palgrave Macmillan.
  18. Bahaa Ibrahim (2020). The role of Egyptian State Awards in changing researchers’ performance in the science and technology sector. Research Evaluation, 29, Issue 2, April 2020, Pages 171–190, https://doi.org/10.1093/reseval/rvz038.
  19. Barroso, C., Carrion, G. C., & Roldan, J. L. (2010). Applying maximum likelihood and PLS on different sample sizes: studies on SERVQUAL model and employee behavior model. In V. Esposito Vinzi, W. Chin, J. Henseler, & H. Wang (Eds.), Handbook Partial Least Squares, Berlin: Springer.
  20. Becker, J.-M., Ringle, C.M., Sarstedt, M. and Völckner, F. (2015). How collinearity affects mixture regression results. Marketing Letters, 26 (4), 643-659.
  21. Bhattacharya, J., & Packalen, M. (2020). Stagnation and scientific incentives(No. w26752). National Bureau of Economic Research.‏
  22. Bruno Frey & Susanne Neckermann (2008). Academics Appreciate Awards. A New Aspect of Incentives in Research, IEW - Working Papers 400, Institute for Empirical Research in Economics - University of Zurich.
  23. Bruno Frey, & Susanne Neckermann. Academics Appreciate Awards. A New Aspect of Incentives in Research. IEW - Working Papers 400, Institute for Empirical Research in Economics - University of Zurich.
  24. Chin, W. W. (1998). The partial least squares approach to structural equation modelling. In G. A. Marcoulides (Ed.), Modern methods for business research, New Jersey: Lawrence Erlbaum.
  25. Chin, W. W. (2010). How toWrite Up and Report PLS Analyses. In: V. Esposito Vinzi, W. Chin, J. Hensler, and H. Wold (Eds.,) Handbook of partial least squares.
  26. Coase, Robert (1974). The Light house in Economics. Journal of Law and Economics. 17, 357–376.
  27. Coase, Ronald H. (1960). The Problem of Social Cost. Journal of Law and Economics. 3 (1), 1–44. doi:10.1086/466560. S2CID 222331226.
  28. Coase, Ronald H. (1973). The Nature of the Firm. Economica, 4 (16), 386–405. doi:10.1111/j.1468-0335.1937.tb00002.x.
  29. Colman, Andrew (2006). A Dictionary of Psychology. New York: Oxford University Press. ISBN 978-0-19-861035-9.
  30. Diamantopoulos, A., Sarstedt, M., Fuchs, C., Wilczynski, P., & Kaiser, S. (2012). Guidelines for choosing between multi-item and single-item scales for construct measurement: A predictive validity perspective. Journal of the Academy of Marketing Science, 40 (3), 434–449.
  31. Drolet, A. L. and Morrison, D. G. (2001). Do we really need multiple-item measures in service research. Journal of Service Research, 3 (3), 196-204.
  32. Efron, B., & Tibshirani, R. J. (1993). An introduction to the bootstrap. New York: Chapman and Hall.
  33. Eisenhardt, M. (1989). Agency Theory: An Assessment and Review. The Academy of Management Review, 14 (1), 57–74.
  34. Fornell, C., & Bookstein, F. L. (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing Research, 19, 440–452.
  35. Frey, & Gallus, J. (2014). The Power of Awards. The Economists. Voice, 11(1), 1-5. https://doi.org/10.1515/ev-2014-0002.
  36. Frey, S. (1992a). Tertium datur: pricing, regulating and intrinsic motivation. Kyklos. 45 (2), 161-184.
  37. Frey, S. (2001). Inspiring Economics: Human Motivation in Political Economy. Ed- ward Elgar, Cheltenham, UK .
  38. Frey, S. and Gallus, J. (2016). Awards as non-monetary incentives. Evidence-based HRM, 4 (1), 81-91. https://doi.org/10.1108/EBHRM-05-2015-0016
  39. Frey, S. (1990). L’effet de transfert de motivation. Journal des Economistes et des Etudes Humaines. 1 (3) 225–252.
  40. Frey, Bruno S. (1997). Not just for the money. An economic theory of personal motivation. E. Elgar,
  41. Gleeson, F., & Hargaden, V. (2015(. Improving knowledge worker efficiency. In 2015 IEEE International Symposium on Technology and Society (ISTAS), 1-8, IEEE.
  42. Gleeson, F., & Hargaden, V. (2015). Improving knowledge worker efficiency. In 2015 IEEE International Symposium on Technology and Society (ISTAS), 1-8, IEEE.
  43. Gleeson, , & Hargaden, V. (2015). Improving knowledge worker efficiency. In 2015 IEEE International Symposium on Technology and Society (ISTAS), 1-8. IEEE.
  44. Haenlein, M., & Kaplan, A. M. (2004). A beginner’s guide to partial least squares analysis. Understanding Statistics, 3 (4), 283–297.
  45. Hair, J. F., Hult, G. T. M., Ringle, C. M. and Sarstedt, M. (2017a). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage, Thousand Oaks, CA.
  46. Hair, J. F., Ringle, C. M. and Sarstedt, M. (2011). PLS-SEM: indeed a silver bullet. Journal of Marketing Theory and Practice, 19 (2), 139-151.
  47. Hair, J. F., Ringle, C. M., Sarstedt, M. (2011). PLS-SEM: Indeed a Silver Bullet. Journal of Marketing Theory and Practice, 19 (2), 139–151.
  48. Hair, J. F., Sarstedt, M. and Ringle, C. M. (2019). Rethinking some of the rethinking of partial least squares. European Journal of Marketing, Forthcoming.
  49. Hall, B. H. and J. van Reenen (2000) How Effective Are Fiscal Incentives for R&D? A Review of the Evidence. Research Policy, 449-469.
  50. Harré, Rom (1979). Social Being. Oxford: Basil Blackwell.
  51. Henseler, J., Ringle, C. M. and Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43 (1), 115-135.
  52. Henseler, J., Ringle, C. M. and Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. in Sinkovics, R. R. and Ghauri, P. N. (Eds). Advances in International Marketing, Emerald: Bingley.
  53. Jöreskog, K. G. (1971). Simultaneous factor analysis in several populations. Psychometrika, 36 (4), 409–426.
  54. kahneman, Daniel & Tversky, Amos (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, Econometric Society, 47 (2). 
  55. Laffont, J.-J., & Martimort, D. (2002). The Theory of Incentives: The Principal-Agent Model. Princeton University Press. https://doi.org/10.2307/j.ctv7h0rwr
  56. Laffont, J. J. and D. Martimort (2002). The Theory of Incentives: The Principal-Agent Model. Princeton University Press.
  57. Lam, Alice (2011). What motivates academic scientists to engage in research commercialization: gold, ribbon or puzzle?. MPRA Paper 30849, Germany: University Library of Munich.
  58. Le, A. T. T., Tran, T. V., Tran, T. M., & Phan, T. H. (2024). Intrinsic and Extrinsic Factors as Motivation Roles in Scientific Research Activities of Professors at Several Vietnamese Universities. Sage Open, 14 (1). https://doi.org/10.1177/21582440241230838
  59. Maskin, (1999). Nash Equilibrium and Welfare Optimality. Reveiw of Economic Studies, 23.
  60. Mason, C. H. and Perreault, W. D. (1991). Collinearity, power, and interpretation of multiple regression analysis. Journal of Marketing Research, 28 (3), 268-280.
  61. Mirowski, , & Sent, E. M. (2008). The commercialization of science and the response of STS.‏
  62. Romaniuc, R. (2016). Intrinsic motivation in economics: A history. Journal of Behavioral and Experimental Economics.
  63. Romaniuc, R. (2016). intrinsic motivation in economics: A history. Journal of Behavioral and Experimental Economics. http://dx.doi.org/10.1016/j.socec.2016.10.002.
  64. Rabin, (1998). Psychology and economics. J. Econ. Lit. 36 (1), 11–46.
  65. Raithel, S., Sarstedt, M., Scharf, S. and Schwaiger, M. (2012). On the value relevance of customer satisfaction. Multiple drivers and multiple markets. Journal of the Academy of Marketing Science, 40 (4), 509-525.
  66. Reinartz, W., Haenlein, M., Henseler, J. (2009). An empirical comparison of the efficacy of covariance-based and variance-based SEM. J. of Research in Marketing, 26, 332–344.
  67. Romer, David (2012). Advanced macroeconomics. 4th Ed, McGrow-hill.
  68. Ryan, C. (2004) An examination of the role of scientists. motivations and the influence of the organizationalenvironment on scientific research effectiveness. PhD Dissertation, Dublin City University, Dublin.
  69. Saul Lach & Mark Schankerman, (2006). Incentives and Invention in Universities. CEP Discussion Papers dp0729, Centre for Economic Performance, LSE.
  70. Scitovsky, (1976). The joyless economy: An inquiry into human satisfaction and consumer dissatisfaction. New York: Oxford University Press.
  71. Scitovsky, (1976). The Joyless Economy: An Inquiry into Human Satisfaction and Dissatisfaction. Oxford: Oxford University Press.
  72. Shmueli, G., Ray, S., Velasquez Estrada, J.M. and Shatla, S. B. (2016). The elephant in the room: evaluating the predictive performance of PLS models. Journal of Business Research, 69 (10), 4552-4564.
  73. Shmueli, G., Sarstedt, M., Hair, J.F., Cheah, J.-H., Ting, H., Vaithilingam, S. and Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: guidelines for using PLSpredict. Working Paper.
  74. Simon, Herbert A. (1947). Administrative Behavior: a Study of Decision-Making Processes in Administrative Organization (1st ed.). New York: Macmillan. OCLC 356505.
  75. Simon, Herbert A. (1956). Rational Choice and the Structure of the Environment (PDF). Psychological Review. 63 (2), 129–138.
  76. Simon, Herbert A. (1979). Rational decision making in business organizations. The American Economic Review. 69 (4), 493–513.
  77. Simpson, John (2007). Share the Fruits of State Funded Research, Consumer Watchdog, August 11.
  78. Tenenhaus, M. (2008). Component-based Structural Equation Modelling. Total Quality Management & Business Excellence, 19, Issue 7-8, 871-886.
  79. Tenenhaus, M., Vinzi, V. E., Chatelinc, Y. M. and Lauro, C. (2005). PLS path modeling. Computational Statistics & Data Analysis, 48, 159-205.
  80. Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness.Yale University Press.
  81. Thang, Nguyen, Lan, Nguyen, Scott, Bryant & Hieu, Nguyen (2020). What Motivates Scientists in Emerging Economies to Become Entrepreneurs? Evidence from Vietnam. Sustainability, MDPI, Open Access Journal, 12 (3), 1-18, February.
  82. Titmuss, (1970). the Gift Relationship: From Human Blood to Social Policy. Reprinted by the New Press, ISBN 1-56584-403-3 (reissued with new chapters 1997, John Ashton & Ann Oakley, LSE Books).
  83. Voorhees, C. M., Brady, M. K., Calantone, R. and Ramirez, E. (2016). Discriminant validity testing in marketing: an analysis, causes for concern, and proposed remedies. Journal of the Academy of Marketing Science, 44 (1), 119-134.
  84. Wetzels, M., Odekerken-Schroder, G., van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: guidelines and empirical illustration. MIS Quarterly 33 (1), 177-195.
  85. Wilson, Bradley, & Henseler, Jörg (2007). Modeling reflective higher-order constructs using three approaches with PLS path modeling: a Monte Carlo comparison. Australian and New Zealand Marketing Academy Conference, Otago, Australia, December 3-5.
  86. Wold, H. (1982). Soft modeling: The basic design and some extensions. In K. G. Joreskog & H. Wold (Eds.), Systems under indirect observations: Part II. Amsterdam: North-Holland.
اقتصاد اسلامی
دوره 24، شماره 93
بهار 1403
صفحه 101-139