The primary objective of this study is to compare three approaches traditionally used to explain employee reactions to work: the person-environment fit approach, the fairness approach, and the job characteristics approach. The person-environment fit point of view suggests that compatibility between an employee and the work environment is a determinant of work-related attitudes and behaviors. The fairness perspective proposes that perceptions of fair treatment influence motivational and emotional responses to work. The job characteristics research suggests that there are certain task characteristics which influence levels of motivation, performance, and job satisfaction. Although these frameworks are used to explain overlapping sets of variables, they diverge considerably in focus and in recommended strategies for improving person-organization relationships. This research investigates the separate, combined, and relative power of these approaches to predict two specific reactions to work, affective responses and energy level. A model incorporating all three approaches is developed. The model is evaluated with data from 2,822 federal government employees. Estimation of the coefficients of the variables is done with the use of maximum likelihood estimation procedures. Eight models representing various combinations of the three sets of predictor variables are reviewed in terms of their ability to predict affective responses to work and energy level for work. The results suggest person-environment fit was unrelated to both affective responses and energy level, although there is reason to believe that this finding may be a function of an imprecise measure of fit. Fairness was related only to feelings of affect and job challenge was related to both affective responses and energy level. These findings suggest that both fairness and job design considerations are important to an understanding of emotional and motivational responses to work. Interventions designed to enhance these responses should consider the importance of both job and fairness variables.Ph.D.Occupational psychologyUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/160713/1/8520967.pd
