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Reducing Perceived Risk in Purchase of Uncertified Used Cars: Contributory Factors.

By: Contributor(s): Material type: TextTextDescription: 7-24. pSubject(s): In: MURTHY, E N MARKETING MANAGEMENTSummary: A growing middle class, an upsurge in disposable income levels and satisfactory availability of financing options have contributed to the enormous demand for used cars in India. However, the used car market in India is highly unorganized, operating with a large number of uncertified used car dealers, which leads to a high level of perceived risk among prospects. It is an arduous task for a prospect to transmute into a customer unless he/she feels that the risk perception is low. This study tries to ascertain the various factors that are instrumental in facilitating the reduction of perceived risk while purchasing uncertified used cars. Adopting convenience sampling, data was collected from a sample of 419 respondents, using a self-administered questionnaire. The responses were analyzed using SPSS package 20.0, by adopting Principal Component Analysis, followed by Regression Analysis. The results portrayed prominent factors impacting risk perception. A significant correlation between the same and predictor variables was also revealed. [ABSTRACT FROM AUTHOR]
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A growing middle class, an upsurge in disposable income levels and satisfactory availability of financing options have contributed to the enormous demand for used cars in India. However, the used car market in India is highly unorganized, operating with a large number of uncertified used car dealers, which leads to a high level of perceived risk among prospects. It is an arduous task for a prospect to transmute into a customer unless he/she feels that the risk perception is low. This study tries to ascertain the various factors that are instrumental in facilitating the reduction of perceived risk while purchasing uncertified used cars. Adopting convenience sampling, data was collected from a sample of 419 respondents, using a self-administered questionnaire. The responses were analyzed using SPSS package 20.0, by adopting Principal Component Analysis, followed by Regression Analysis. The results portrayed prominent factors impacting risk perception. A significant correlation between the same and predictor variables was also revealed. [ABSTRACT FROM AUTHOR]

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