Abstract
Auto component industry is an interesting variant of business that is located in the context of dynamic value chain. While one end of the value chain is the sophisticated-oligopolistic original equipment manufacturers (OEMs), the other end has suppliers who are small and medium enterprises. In the whole length and breadth of this value chain, suppliers include small, medium, and large enterprises. Broadly, these enterprises are of two types: organised and unorganised. Unlike in the case of large multinational enterprises, auto component suppliers, in particular small and medium enterprises (SMEs), are not so well endowed to invest in research development and exhaustive capability building endeavours. However, as elucidated in the extant literature on SMEs, a prudent option for these enterprises is to build and foster absorptive capacities that synergise labour, information technology, and knowledge management. To gauge these themes, we analyse four types of data. First, we examine recent time series of select variables that delineate the basic dynamics of performance and resources of organised auto component industry in India. Second, we lay focus on cross-sectional enterprise data drawn from 2012 to 2013 Annual Survey of Industries. Third, we analyse 67th round, for the year 2009–2010, of National Sample Survey, to examine unorganised auto component industry in India. Fourth, we use field data, collected in 2016, to discuss multidimensional aspects of knowledge management, technology, learning, labour, and outcomes, based on a survey conducted in Pune, Maharashtra, India. We conclude that auto component manufacturers seem to rely more on labour, information technology, and attainments like ISO to perform well in the business. While automation appears to be a catching up trend in the value chain, use of information technology seems to be the game-changer as far as value added is concerned. Drawing cues from patterns and inferences presented in our paper, for enterprises in the auto component value chain, be they are in the organised and unorganised sector, whether they are small or medium, it is important to create synergies between human resources and information and communication technologies to scale up a sustained higher order performance.
This paper was presented in XI Annual Conference of Forum for Global Knowledge Sharing ‘Globalisation of Technology and Development’.
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Notes
- 1.
While scale effects emanate from strategic choices like expansions of scale, substitution effect tends to emerge from variations in factor/resource prices.
- 2.
‘An observation with an extreme value on a predictor variable is a point with high leverage. Leverage is a measure of how far an independent variable deviates from its mean. High leverage points can have a great amount of effect on the estimate of regression coefficients’. http://www.ats.ucla.edu/stat/stata/dae/rreg.htm.
- 3.
See Verardi and Croux (2009). Robust regression in Stata. The Stata Journal, 9(3), 439-453. http://www.stata-journal.com/article.html?article=st0173.
- 4.
Type of organisation also captures the scale of operation/employment. While public limited enterprises are larger units, the category of private limited captures medium to large. Other two types—proprietorship and partnership—are mainly formed by smaller enterprises.
- 5.
LNGVA = Natural Logarithm of GVA, LNLABOUR = Natural Logarithm of Employed Persons; LNCAPITAL = Natural Logarithm of Fixed Capital, LNSURPLUS = Natural Logarithm of Net Surplus, LNICT = Natural Logarithm of information, computer and telecommunications equipment, and LNPLANT = Natural Logarithm of Plant and Machinery.
- 6.
Phi correlation measures correlation between two nominal variables.
- 7.
Refer to Table 11.13.
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Bino Paul, G.D., Jaganth, G., Johnson Abhishek, M., Rahul, S. (2018). What Makes Enterprises in Auto Component Industry Perform? Emerging Role of Labour, Information Technology, and Knowledge Management . In: Siddharthan, N., Narayanan, K. (eds) Globalisation of Technology. India Studies in Business and Economics. Springer, Singapore. https://doi.org/10.1007/978-981-10-5424-2_11
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