Search

Purpose: This paper seeks to examine whether the primary factors motivating the career plans of high-achieving Indian adolescents vary between academic specializations. Particular attention is to be paid to differences between science and business students. Design/methodology/approach: The study surveyed approximately 2,700 secondary school students in South India regarding their academic and career plans and their perceptions of business compared with science. Survey results were analyzed using both descriptive techniques and multinomial logistic regression. Findings: Students perceive business to be comparable with, but not superior to, science and engineering. The proportion of students choosing business over science increased among males and in some more economically developed cities. Engineering students were most likely to cite parents as a major influence, while business students more often pointed to salary and career prospects. Research limitations/implications: The study's scope was limited to South India. Greater geographic coverage could broaden the generalizability of the results. Practical implications: The increasing desirability of formal business education can give rise to a stronger entrepreneurial base and greater business development in India. Furthermore, improved management skills in the Indian workforce can attract higher value-added offshore work from multinational corporations. Originality/value: The existing literature contains little empirical research directly comparing business students with their peers in science and engineering, with no such study previously conducted in India. The results shed light on what attracts students to each track and can inform policy aimed at encouraging further enrollment in specific fields. (Contains 6 tables and 1 figure.)

Copyright of World Medical & Health Policy is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: Slums pose a significant challenge for urban planning and policy as they provide shelter to a third of urban residents. UN-Habitat reports that, in 2001, approximately 924 million people lived in slums or informal settlements across the world (UN-Habitat, 2003). However, varying definitions of what constitutes a slum result in different slum population estimates. Most definitions treat a slum as a community of several households, rarely recognizing that housing conditions differ for each individual household within the area. Moreover, definitions of slums usually take a dichotomous approach whereby a place is either a slum or not. Little attempt is made to go beyond this slum/non-slum dichotomy. This paper moves beyond the traditional ways of defining a slum by proposing a new household level enumeration of slums and developing Slum Severity Index (SSI), which measures the level of deprivation on a continuous scale based on the UN-Habitat's slum definition. We apply this new approach of analyzing slums to a household survey dataset to estimate the total number of slum households in Mumbai and Kolkata, two megacities in India. To contrast our approach, we compare these estimates with the Census of India's. The comparison highlights stark differences in the two estimates and the slum/non-slum household classifications. The estimates by the Census are considerably smaller than those based on the UN-Habitat definition in both cities. By applying the SSI, we also demonstrate intra-urban variability in housing conditions within our study cities. The analysis highlights differences in slum profiles measured in terms of both housing deprivation levels and housing deprivation types in both cities. The main objective of this study is to demonstrate the usefulness of the household level analysis of slums in drawing implications for designing and implementing slum policies. [Copyright &y& Elsevier]