Authors:
Sushanta Sengupta,Chinmoy Jana,DOI NO:
https://doi.org/10.26782/jmcms.2026.05.00007Keywords:
ANFIS,MSME,GDP,CRR,Repo Rate,CPI,Abstract
Over the past few decades, the Micro, Small, and Medium Enterprises (MSMEs) sector has emerged as a dynamic and vibrant component of the economy of India. A pivotal role is being played by MSMEs to generate noteworthy prospects in employment with relatively lower capital investment compared to large industries, while also contributing to the development of rural and underdeveloped areas. Macroeconomics plays a central role in understanding the dynamics of national and global economies by analyzing aggregate indicators such as GDP (Gross Domestic Product), inflation, unemployment, and interest rates. This research attempts to predict the MSME production based on the Macroeconomic fuzzy input variables using the ANFIS (Adaptive Neuro Fuzzy Inference) model. The time series data, such as GDP Per Capita (at constant price), Repo Rate, CRR (Cash Reserve Ratio), and CPI (Consumer Price Index), are considered as macroeconomic input variables, and the output variable is MSME Production (at constant price) for the last 20 years. The paper compares the actual value of MSME production with the ANFIS outcome and the prediction accuracy of the output variable between the same membership function (MF) usage for all the input variables and different MF usage of the input variables, with a linear output MF being observed. The prediction accuracy obtained in the latter case overcomes the prediction accuracy of the former. Accurate prediction of MSME production volume using macroeconomic variables helps policymakers envision industrial activity and design sensible fiscal and monetary measures to alleviate growth and support the MSME sector.Refference:
I. Behera M, Mishra S, Mohapatra N, Behera A R. “Covid-19 pandemic and Micro Small and Medium Enterprises (MSMEs): Policy response for revival.” Small enterprises development, Management and Extension Journal, vol. 47, no. 3, 2021, pp. 213-228. 10.1177/09708464211037485
II. Chukhrova N, Johansen A. “Fuzzy Regression Analysis: Systematic Review and bibliography.” Applied Soft Computing Journal, vol. 84, 2019 pp. 1-29. 10.1016/j.asoc.2019.105708
III. Gare D. “Performance of Micro Small and Medium Enterprises of India.” International Journal of Creative Research Thoughts, vol. 10, no. 10, 2022, pp. 1-8.
IV. Gibson T, Van der Vaart, H.J. “Defining SMEs: A less Imperfect Way of defining Small and Medium Enterprises in Developing Countries.” Brookings Global Economy and Development, 2008.
V. Jovic S, Milutinovic J S, Micic R, Markovic S, Rakic G. “Analyzing of Exchange Rate and Gross Domestic Product (GDP) by Adaptive Neuro Fuzzy Inference System (ANFIS).” vol. S0378, no. 4371, 2018, pp. 31133-31136. 10.1016/j.physa.2018.09.009
VI. Khanna R, Singh S P. “Status of MSMEs in India: A detailed Study.” Journal of Applied Management – Jidnyasa, vol. 10, no.2, 2018, pp. 1-14.
VII. Melin P, Soto J, Castillo O, Soria J. “A new approach for time series prediction using ensembles of ANFIS models.” Expert Systems with Applications, vol. 39, 2012, pp. 3494-3506. 10.1016/j.eswa.2011.09.040
VIII. Palaka S, Das S. “Growth and Elasticity of output of MSMEs in India.” Research Square, 2021, pp. 1-16. 10.21203/rs.3.rs-36142/v2
IX. Patel S K, Tripathy R. “Challenges of MSMEs in India.” Journal of Positive School Psychology, vol. 6, no. 6, 2022, pp. 1-23.
X. Petkovic J, Petrovic N, Dragovic I, Stanojevic K, Radakovic J A, Borojevic T, Borstnar M K. “Youth and forecasting of sustainable development pillars: An adaptive neuro-fuzzy inference system approach.” PLoS One, 2019, pp. 1-25. 10.1371/journal.pone.0218855
XI. Raharaja M A, Darmawan I D M B A, Nilakusumawati D P E, Supriana I W. “Analysis of Membership Function in implementation of adaptive neuro fuzzy inference system (ANFIS) method for inflation prediction.” Vol. 1722, no. 012005, 2021. 10.1088/1742-6596/1722/1/012005
XII. Rawat M. “Factors affecting the growth and development of MSME sector in India: An opinion survey of start-ups.” Mathematical Statistical and Engineering Applications, vol. 68, no. 1, 2019, pp. 230-236. 10.17762/msea.v68i1.2177
XIII. Reddy K, Sashidharan S. “Driving Small and Medium-Sized Enterprise participation in Global Value Chains: Evidences from India.” ADBI Working Paper series, vol. 1118, 2020, pp. 1-24.
XIV. Sahnewaz S. “The Contribution of MSMEs in India’s total export and GDP Growth: Evidence from cointegration and causality test.” Munich Personal RePEc Archive, 2028, pp. 1-15.
XV. Shetty M O, Bhatt G S. “A Performance analysis of Indian MSMEs.” International Journal of Applied Engineering and Management Letters, vol. 6, no. 2, 2022, pp. 1-19. 10.5281/zenodo.7112375
XVI. Shing J, Jang R. “ANFIS: Adaptive-Network-Based Fuzzy Inference System.” IEEE Transactions on Systems, MAN, and Cybernetics, vol. 23, no. 3, 1993, pp. 665-685. 10.1109/21.256541
XVII. Siva Sree H V, Vasavi P. “MSMEs in India – Growth and Challenges.” Journal of Scientific Computing, 2020, pp. 1-12.
XVIII. Tambunan T T H. “The Impact of the Economic Crisis on micros, small and medium enterprises and their crisis mitigation measures in Southeast Asia with reference to Indonesia.” Wiley Asia and Pacific policy studies, 2018, pp. 1-21. 10.1002/app5.264
XIX. Uwimana A. “Macroeconomics Dynamics through the lens of the Adaptive Neuro Fuzzy Inference Systems.” Intech Open, 2024, pp. 1-13. 10.5772/intechopen.1004041
XX. www.lendingkart.com/msme-1oan/what-is-msme/. Accessed 17 Oct 2025
XXI. www.rbi.org.in. Accessed 12 Oct 2025
XXII. www.msme.gov.in. Accessed 15 Oct 2025
XXIII. www.dcmsme.gov.in. Accessed 5 Nov 2025
XXIV. www.nsic.co.in. Accessed 6 Nov 2025
XXV. www.nimsme.org. Accessed 5 Nov 2025
XXVI. www.kvic.org.in. Accessed 17 Nov 2025
XXVII. www.coirboard.gov.in. Accessed 2 Nov 2025
XXVIII. www.mgiri.org. Accessed 12 Oct 2025
XXIX. www.nseindia.com. Accessed 14 Oct 2025
XXX. www.mospi.gov.in. Accessed 8 Nov 2025
View Download