Significance of Trait Inferences on Applicant Attraction: A Study of the Indian Information Technology Sector

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dc.contributor.author Kavitha, M
dc.contributor.author Srinivasan, P. T.
dc.date.accessioned 2018-10-11T07:02:42Z
dc.date.available 2018-10-11T07:02:42Z
dc.date.issued 2012-06
dc.identifier.issn 1800-363X
dc.identifier.uri http://220.247.247.85:8081/handle/123456789/7695
dc.description.abstract All the business units are in a tussle to build a competitive brand not only to increase the market share but also to capture the potential applicants. It is believed that customers assign certain qualities to each and every brand they know. Similarly, potential applicants attach specific traits to the organizations, which in turn influence their attitude towards the organization. The present study attempts to examine the perception of external audience towards symbolic traits and employer attractiveness in the Indian Information Technology (IT) Sector. Two samples of prospective applicants were drawn (Students = 351, IT Employees = 234) from the applicant population. Respondents were randomly assigned to respond about two leading IT companies, chosen for the study. Results of multiple regressions reveal that the symbolic attributes significantly predict the level of attractiveness of an organization, with dimensions like competence and sophistication playing an important role as major predictors for both the samples. Students, being a naïve job seeker, considered excitement as another key predictor for attractiveness. Based on the results implications for practice are discussed. en_US
dc.language.iso en en_US
dc.publisher Faculty of Management & Finance, University of Colombo en_US
dc.relation.ispartofseries Vol. 03 , No. 01;
dc.subject Trait Inferences en_US
dc.subject Symbolic Attributes en_US
dc.subject Organizational Attractiveness en_US
dc.subject Information Technology Sector en_US
dc.title Significance of Trait Inferences on Applicant Attraction: A Study of the Indian Information Technology Sector en_US
dc.type Article en_US
dc.identifier.accno 16213 en_US


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