Abstract
Companies offer ethics codes and training to increase employees’ ethical conduct. These programs can also enhance individual work attitudes because ethical organizations are typically valued. Socially responsible companies are likely viewed as ethical organizations and should therefore prompt similar employee job responses. Using survey information collected from 313 business professionals, this exploratory study proposed that perceived corporate social responsibility would mediate the positive relationships between ethics codes/training and job satisfaction. Results indicated that corporate social responsibility fully or partially mediated the positive associations between four ethics program variables and individual job satisfaction, suggesting that companies might better manage employees’ ethical perceptions and work attitudes with multiple policies, an approach endorsed in the ethics literature.
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Sean Valentine (D.B.A., Louisiana Tech University) is an Associate Professor of Management in the college of Business at the University of Wyoming. His teaching and research interests include business ethics, organizational behavior, and human resource management. He has published in journals such as Behavioral Research in Accounting, Journal of Business Research, Journal of Personal Selling & Sales Management, and Journal of Business Ethics.
Gary Fleischman (Ph.D., Texas Tech University) is an Associate Professor and is the McGee Hearne and Paiz Faculty Scholar in Accounting at the University of Wyoming. His teaching expertise is in accounting and entrepreneurship and his research interests are in business ethics and behavioral business research. He has published in journals such as Behavioral Research in Accounting, The International Journal of Accounting and Journal of Business Ethics.
Appendix: Explanation of Key Statistical Terms
Appendix: Explanation of Key Statistical Terms
The authors recommend the following statistics reference textbook (Hair et al., 1998) that we find to be helpful regarding statistics-oriented questions related to behavioral ethics research. The statistical-tool descriptions provided below are taken from this text:
Hair, J. F., R. E. Anderson, R. L. Tatham, and W. C. Black: 1998, Multivariate Data Analysis (Prentice Hall Publishers, Upper Saddle River, New Jersey).
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a.
ANOVA: Stands for “Analysis of Variance”. Generally, this method assesses, “on the basis of one dependent variable, whether samples are from populations with equal means” (Hair et al., 1998, p. 3) or not.
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b.
Coefficient alpha: This “alpha” is referring to a measure called “Cronbach’s alpha,” which is a “measure of reliability that ranges from 0 to 1” (Hair et al., 1998, p. 88). Generally, the lower level of tolerance for this statistic is .60.
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Eigenvalues: The eigenvalue “represents the amount of variance accounted for by a factor” (Hair et al., 1998, p. 89).
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Exploratory Factor Analysis: Factor analysis “is a statistical approach that can be used to analyze interrelationships among a large number of variables and to explain these variables in terms of their common underlying dimensions (factors)” (Hair et al., 1998, p. 14). In other words, it shows whether or not there are several factors (CSR and Job satisfaction variables in this paper) that account for significant variance.
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Factor loading: This represents the “correlation between the original variables and the factors,” which facilitates comprehension of the factors (Hair et al., 1998, p. 89).
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Rotated component matrix: Rotation specifically refers to the “process where the reference axes of the factors are turned about the origin until some other position has been reached,” which moves variance to different factors so that a more parsimonious factor pattern can be obtained (Hair et al., 1998, p. 106-107).
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Mediated regression (Mediated Framework): Mediated regression analysis is a procedure that examines the presence of mediation among a set of variables (see Baron and Kenny, 1986 for discussion). This procedure requires the specification of three different regression equations: 1) independent variable → mediator variable, 2) independent variable → dependent variable, 3) independent variable and mediator variable → dependent variable. The relationships must be significant is the first two equations, as well as the relationship between the mediator variable and dependent variable in the third equations. If the independent and mediation variables are both related to the dependent variable in the third equation, then partial mediation is present if there is a noteworthy reduction in effect in the independent variable. If the independent and dependent variables are not related in the presence of the mediator variable, then full mediation exists.
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Social desirability bias: This bias can negatively affect ethics research. As such, the measure employed in this study is utilized as a “control” variable to investigate socially acceptable responses.
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Two-factor solution: This refers to the fact that just two factors were identified, which was based on an assessment of the most explained variance (Hair et al., 1998, p. 103).
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Valentine, S., Fleischman, G. Ethics Programs, Perceived Corporate Social Responsibility and Job Satisfaction. J Bus Ethics 77, 159–172 (2008). https://doi.org/10.1007/s10551-006-9306-z
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DOI: https://doi.org/10.1007/s10551-006-9306-z