EMPIRICAL VALIDATION OF DEVELOPMENT PATTERNS IN RAILWAY MANUFACTURING ENTERPRISES: DERIVED DEMAND, LEARNING EFFECTS IN SERIAL PRODUCTION, AND CUSTOMER DEPENDENCE
DOI:
https://doi.org/10.5281/zenodo.23467099Abstract
This article proposes a methodological framework for empirically testing the development patterns of enterprises engaged in railway rolling stock manufacturing and overhaul. Five hypotheses concerning the distinction between nominal growth and actual economic development, the existence of derived demand, the amplification of demand fluctuations through the ordering system, learning effects in serial production, and customer dependence are formulated as testable propositions with explicitly defined decision criteria. The proposed framework incorporates an order volatility amplification coefficient, a two-factor unit cost model that distinguishes learning effects from the allocation of fixed costs, and a threshold panel regression specification. The framework is illustrated using simulated time series for three hypothetical enterprises operating under different ordering regimes. The simulation results indicate that differences in ordering arrangements, rather than final demand alone, can influence order volatility, the realization of learning effects, and the responsiveness of profitability to changes in operating conditions.Keywords
railway engineering, rolling stock overhaul, derived demand, bullwhip effect, volatility amplification coefficient, learning curve, cost elasticity, customer dependence, threshold effectReferences
1. Argote, L., & Epple, D. (1990). Learning Curves in Manufacturing. Science, 247(4945), 920–924.
2. Arrow, K. J. (1962). The Economic Implications of Learning by Doing. The Review of Economic Studies, 29(3), 155–173.
3. Diewert, W. E. (2008). Index Numbers. The New Palgrave Dictionary of Economics, 190–211.
4. Forrester, J. W. (1961). Industrial Dynamics / J. W. Forrester. MIT Press.
5. Hansen, B. E. (1999). Threshold Effects in Non-Dynamic Panels: Estimation, Testing, and Inference. Journal of Econometrics, 93(2), 345–368.
6. Lapidus, B. M., & Macheret, D. A. (2014). Makroekonomicheskaya rol zheleznodorozhnogo transporta [The Macroeconomic Role of Railway Transport] / B. M. Lapidus, D. A. Macheret. KRASAND.
7. Lee, H. L., Padmanabhan, V., & Whang, S. (1997). Information Distortion in a Supply Chain: The Bullwhip Effect. Management Science, 43(4), 546–558.
8. Marshall, A. (1920). Principles of Economics / A. Marshall. Macmillan.
9. Newey, W. K., & West, K. D. (1987). A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix. Econometrica, 55(3), 703–708.
10. Schumpeter, J. A. (1934). The Theory of Economic Development / J. A. Schumpeter. Harvard University Press.
11. Sterman, J. D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World / J. D. Sterman. Irwin/McGraw-Hill.
12. Teryoshina, N. P., Levitskaya, L. P., & Shkurina, L. V. (2012). (eds.). Ekonomika zheleznodorozhnogo transporta [Economics of Railway Transport]. UMTs ZhDT.
13. Williamson, O. E. (1985). The Economic Institutions of Capitalism / O. E. Williamson. Free Press.
14. Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data / J. M. Wooldridge. MIT Press.
15. Wright, T. P. (1936). Factors Affecting the Cost of Airplanes. Journal of the Aeronautical Sciences, 3(4), 122–128.
Downloads
Published
How to Cite
Issue
Section
