In this dissertation I will present and test a model linking actual applicant-interviewer demographic, human capital, and cultural capital similarity to an interviewer??s recommendation to hire. Actual similarity is proposed to influence an interviewer??s perceptions of similarity with an applicant. These perceptions, in turn, lead to the interviewer??s perceptions of the applicant??s Person-Organization (PO) fit and the applicant??s Person-Job (PJ) fit. Two main mechanisms are proposed to mediate the relationship between an interviewer??s perceptions of similarity and an interviewer??s perceptions of an applicant??s fit: liking and negative behavioral expectations. Lastly, both an interviewer??s PO and PJ fit perceptions of an applicant are posited to influence the interviewer??s recommendation to hire. A total of 118 interviewer-applicant dyads contacted through the Career Center Office at a University located in the southwestern United States participated in the study. Results partially support the model. An interviewer??s perceptions of similarity with an applicant are positively related to an interviewer??s fit evaluations. An interviewer??s negative behavioral expectations of an applicant mediate this relationship. Furthermore, perceived similarity is positively related to an interviewer??s liking of an applicant. In turn, liking is positively related to an interviewer??s PO fit perceptions. However, liking does not function as a mediator between perceived similarity and fit evaluations. Finally, fit evaluations are positively related to hiring recommendations. I discuss the main implications of the study as well as strengths, limitations, and future research.
| Identifer | oai:union.ndltd.org:TEXASAandM/oai:repository.tamu.edu:1969.1/2787 |
| Date | 01 November 2005 |
| Creators | Garcia, Maria Fernanda |
| Contributors | Colella, Adrienne, DeNisi, Angelo, Murguía, Edward, Belliveau, Maura, Paetzold, Ramona |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Electronic Dissertation, text |
| Format | 630262 bytes, electronic, application/pdf, born digital |
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