(Georgia Institute of Technology, 2008-09)
Abraham, Vinoj; Joseph, K. J.
It may be paradoxical that a developing country like India, while having only a negligible
share in world trade, has been able to record remarkable export performance, mostly at
the instance of domestic firms, in a knowledge intensive sector like IT software and
services. and that has attracted world attention. While this achievement is highly
laudable, the real return from a General Purpose Technology (GPT) like ICT is accrued
when it is harnessed for enhancing the productivity and competitiveness of different
sectors of the economy and welfare gains for different sections of the society. In the
current era of globalization and intense international competition the ability to reap such
returns could help ensure the survival of the developing countries and their catch up. The
relevant question in case of India is its success with respect to harnessing the new
technology for addressing various development problems. While, there are a number of
studies on the use of ICT in agriculture and other service sectors including e-governance,
the issue of IT diffusion in India’s manufacturing sector has not yet attracted the attention
of researchers that it deserves. In this context the present study is an attempt at
addressing this issue by making use of a unique dataset on the IT investment in India’s
manufacturing sector furnished by the Annual Survey of Industries. Conventional approach towards analyzing the diffusion process involves estimation of
diffusion curves which considers diffusion process analogous to the occurrence of an
‘epidemic disease’ within a population (Rogers 1962). Such analyses, cast mostly in the
neoclassical framework involves analysis of the time path of the technology adoption
process by estimating the sigmoid or S shaped curve. Most of the studies in this tradition
(see Karshenhas and Stoneman 1995 for a survey) also indicate that inter-firm diffusion
differs across industries and technologies and has highlighted a number of technology
specific, adopter-specific and other factors like the environment in which the adopter
operates that influence the diffusion process. Apart from the greater focus on demand
side factors at the cost of supply side factors influencing diffusion process, it is also
assumed that technology remain the same during the diffusion process. More importantly,
these traditional analytical models fail to take care of the changes that take place in the
environment wherein the diffusion process and those that occur at the original innovation
itself (Freeman, 2003). In the evolutionary theory, that forms the theoretical foundation
for the innovation systems approach, approach Nelson and Winter (1982) rejects the
models that assume full information and classical rationality and instead postulates
limited information and bounded rationality. They sustain that both the course and the
rhythm of the diffusion process are not easily given, and are intertwined with a
combination of elements such as: organizational routines, profitability expected by firms
of the sector; consumers’ preferences and existing regulatory devices, as well as the
imitation process. This paper follows the innovation system perspective to address the
issue at hand.