Workforce in Indian Information Technology (IT) Industry: Exploring NSS Employment and Unemployment Survey
The present paper examines the situation of software workers in India wherein the paper focuses on the disparities across sub-population distinguished socio-economic and regional characteristics and also attempt is made find the determinants of IT workforce within the household level characteristics.
Competition, Regulation and Strategy
The IT industry (both software and hardware) is characterised by 'vast consumer side scale and scope economies' which are incomparably larger than in other industries with supply side network economies like pipelines or electricity distribution. In IT the supply side economies are also incomparably larger because the marginal cost of an additional unit of the software or hardware especially the former is very small. But its uniqueness arises on the demand side. The interaction of these two economies, in a situation of heightened technological dynamism, imposes a greater degree of contingency, and hence path dependency in the developments in the industry as a whole. It makes possible giants like Microsoft and CISCO. Even as they extract a significant part of the scale economies in the form of large profits, such firms are competitive in the more relevant dynamic sense. In this respect these industries are therefore distinguished from nearly all other prior industries. Traditional anti-trust like regulation or price regulation is entirely outmoded for the development of these industries. Strategies with the most potential would involve promoting inter-firm linkages, promoting industries with the least need to be in contact with other firms, in fresh clusters. The costs of disassociation are too large even for large countries attempting to have a role in the evolution of IT industries, so that closed-door approaches are almost entirely unworkable.
RDF Keyword Search based on Keywords-To-SPARQL Translation
In this paper, we present a summary of our work on RDF keyword search. Given a set of keywords, our method automatically generates a set of candidate SPARQL queries, and their natural language description, to be evaluated on the RDF data graph. We discuss our approach, highlighting current and future directions.