Analysis of Total Factor Productivity in Indonesia’s Large and Medium-Scale Industries in Response to Industry 4.0

Farhan Habibie; Rizalul Kalam

doi:10.55927/fjmr.v4i5.173

Authors

Farhan Habibie Universitas Padjadjaran
Rizalul Kalam Institut Sains dan Teknologi Nasional

DOI:

https://doi.org/10.55927/fjmr.v4i5.173

Keywords:

Total Factor Productivity, Industry 4.0, Stochastic Frontier Analysis, Technological Change

Abstract

This study examines the impact of Industry 4.0 on Total Factor Productivity (TFP) in Indonesia's large and medium-scale industries from 2010 to 2015. Utilizing the Stochastic Frontier Analysis (SFA) method with a translog production function, the research analyzes the relationship between inputs (capital, labor, and raw materials) and industrial output, while decomposing TFP growth into efficiency changes (EC), technological changes (TC), and scale effects (SC). The findings reveal that labor and raw materials significantly influence output, with labor exhibiting the highest elasticity (0.6389). The average TFP growth rate was 3.689%, primarily driven by technological advancements (6.996%), despite a decline in technical efficiency (-3.358%). The motor vehicle and food industries demonstrated the highest technical efficiency, while sectors like wood and furniture lagged. The study highlights Indonesia's reliance on foreign technology and underscores the need for domestic innovation to enhance Industry 4.0 readiness. Policy recommendations include fostering R&D collaboration and improving infrastructure to sustain productivity growth.

References

Agarwal, B. V., Lath, V., & Mancini, M. (2017). Confronting Indonesia’s Productivity Challenge. McKinsey & Company.

Angreani, L. S., Vijaya, A., & Wicaksono, H. (2020). Systematic Literature Review of Industry 4.0 Maturity Model for Manufacturing and Logistics Sectors. Procedia Manufacturing, 52(2019), 337–343. https://doi.org/10.1016/j.promfg.2020.11.056

Antara, N. T. et all. (2019a). Making Indonesia 4.0: Transformasi Industri Manufaktur Nasional ke Industri 4.0 (D. Prabantini (ed.); I). Penerbit ANDI.

Antara, N. T. et all. (2019b). Perjalanan Indonesia Menyongsong Revolusi Industri Keempat. BPPI.

Ayu Puspitasari, I. (2017). Analisis Efisiensi Industri Rokok di Indonesia dengan Menggunakan Metode Data Envelopment Analysis Tahun 2006 - 2008. Media Ekonomi; Vol 19, No 2 (2011)DO - 10.25105/Me.V19i2.830.

Badan Pusat Statistik. (2020). PDB Indonesia Triwulanan 2016-2020. 07130.2002, 98.

Banelienė, R. (2021). Industry impact on GDP growth in developed countries under R&D investment conditions. Journal of Small Business Strategy, 31(1), 66–80.

Battese, G. E. C. T. J. R. D. S. P. (2005). An introduction to efficiency and productivity analysis. In An Introduction to Efficiency and Productivity Analysis. https://doi.org/10.1007/b136381

de la Fuente-Mella, H., Rojas Fuentes, J. L., & Leiva, V. (2020). Econometric modeling of productivity and technical efficiency in the Chilean manufacturing industry. Computers and Industrial Engineering, 139(xxxx), 105793. https://doi.org/10.1016/j.cie.2019.04.006

Eskani, I. N. (2010). Total Factor Productivity (TFP) Industri Menengah Dan Besar Di Indonesia. Dinamika Kerajinan Dan Batik, 28, 17–24. https://doi.org/10.22322/dkb.v28i1.1133

Goel, H., & Noida, G. (2021). Exploring the Architecture of Fourth Industrial Revolution : Globalization 4 . 0. FOCUS: Journal of International Business, December 2020. https://doi.org/10.17492/jpi.focus.v7i2.722008

Ikhsan, M. (2007). Total Factor Productivity Growth in Indonesian Manufacturing: A Stochastic Frontier Approach. Global Economic Review, 36(4), 321–342. https://doi.org/10.1080/12265080701694488

Jia, F., Ma, X., Xu, X., & Xie, L. (2020). The differential role of manufacturing and non-manufacturing TFP growth in economic growth. Structural Change and Economic Dynamics, 52, 174–183. https://doi.org/10.1016/j.strueco.2019.10.006

Kementerian Perindustrian. (2020). Laporan Jumpa Pers Akhir Tahun 2020.

Kumbhakar, S. C., & Lovell, C. A. K. (2012). The Estimation of Efficiency Change and Productivity Change. In Stochastic Frontier Analysis. https://doi.org/10.1017/cbo9781139174411.009

Li, Y., Dai, J., & Cui, L. (2020). The impact of digital technologies on economic and environmental performance in the context of industry 4.0: A moderated mediation model. International Journal of Production Economics, 229(March), 107777. https://doi.org/10.1016/j.ijpe.2020.107777

Mahadevan, R. (2002). A DEA approach to understanding the productivity growth of Malaysia’s manufacturing industries. Asia Pacific Journal of Management, 19(4), 587–600. https://doi.org/10.1023/A:1020577811369

Mankiw, N. G. (2018). Principles of economics.

Margono, H., & Sharma, S. C. (2006). Efficiency and productivity analyses of Indonesian manufacturing industries. Journal of Asian Economics, 17(6), 979–995. https://doi.org/10.1016/j.asieco.2006.09.004

Pratiwi, A. M., Bendesa, I. K. G., & Yuliarmi, N. (2010). Analisis Efisiensi dan Produktivitas Industri Besar dan Sedang di Wilayah Provinsi Bali (Pendekatan Stochastic Frontier Analysis). Jurnal Ekonomi Kuantitatif Terapan.

Şeker, M., & Saliola, F. (2018). A cross-country analysis of total factor productivity using micro-level data. Central Bank Review, 18(1), 13–27. https://doi.org/10.1016/j.cbrev.2018.01.001

Shen, Y., Yue, S., Sun, S., & Guo, M. (2020). Sustainable total factor productivity growth: The case of China. Journal of Cleaner Production, 256, 120727. https://doi.org/10.1016/j.jclepro.2020.120727

Solomon, E. M., & Van Klyton, A. (2020). The impact of digital technology usage on economic growth in Africa. Utilities Policy, 67(July), 101104. https://doi.org/10.1016/j.jup.2020.101104

Surjaningsih, N., & Permono, B. P. (2014). Dinamika Total Factor Productivity Industri Besar Dan Sedang Indonesia. Buletin Ekonomi Moneter Dan Perbankan, 16(3), 277–308. https://doi.org/10.21098/bemp.v16i3.46