Attitudinal, personal, and job-related predictors of salesperson turnover

Brent M. Wren (Management and Marketing, University of Alabama in Huntsville, Huntsville, Alabama, USA)
David Berkowitz (Management and Marketing, University of Alabama in Huntsville, Huntsville, Alabama, USA)
E. Stephen Grant (Faculty of Business Administration, University of New Brunswick, Fredericton, New Brunswick, Canada)

Marketing Intelligence & Planning

ISSN: 0263-4503

Publication date: 28 January 2014

Abstract

Purpose

To contribute to the understanding of how to manage turnover, the purpose of this paper is to determine if sales managers have the ability to predict high levels of propensity to leave (PL) from variables readily available in personnel records, and on commonly used employee surveys.

Design/methodology/approach

The data used for the analysis of the study variables were collected from the sales forces of a total of ten firms across a variety of consumer and industrial product categories, resulting in a sample of 604 respondents. Data were analyzed via multiple discriminant analysis.

Findings

The analysis and test results demonstrate that discriminant sets of attitudinal variables, personal characteristics, and aspects of the job can be identified and used to establish meaningful classifications of a salesperson's PL. Organizational commitment, satisfaction with pay, family status, job involvement, level of education, and compensation plan were all found to be significant. Analysis fails to support the existence of several attitudinal variables generally thought to be predictors of PL.

Originality/value

The overarching implication to be drawn is that any effort to address salesperson turnover must be holistic, rather than limited to a narrow set of variables. These findings hold implications for sales management researchers and human resource/personnel managers.

Keywords

Citation

M. Wren, B., Berkowitz, D. and Stephen Grant, E. (2014), "Attitudinal, personal, and job-related predictors of salesperson turnover", Marketing Intelligence & Planning, Vol. 32 No. 1, pp. 107-123. https://doi.org/10.1108/MIP-04-2013-0061

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Publisher

:

Emerald Group Publishing Limited

Copyright © 2014, Emerald Group Publishing Limited

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