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The Role of Desires, Self‐Predictions, and Perceived Control in the Prediction of Training Session Attendance 1
Author(s) -
Fishbein Martin,
Stasson Mark
Publication year - 1990
Publication title -
journal of applied social psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.822
H-Index - 111
eISSN - 1559-1816
pISSN - 0021-9029
DOI - 10.1111/j.1559-1816.1990.tb00406.x
Subject(s) - psychology , attendance , theory of reasoned action , session (web analytics) , social psychology , normative , theory of planned behavior , control (management) , action (physics) , applied psychology , epistemology , philosophy , physics , management , quantum mechanics , world wide web , computer science , economics , economic growth
Employee attendance at a training session was examined using the theory of reasoned action (Fishbein & Ajzen, 1975). In addition, based on Audi (1973a, b) and Warshaw and Davis (1985), a distinction was made between desires (I want) and behavioral self‐predictions (I will), and as in Ajzen (1985, 1987), the role of perceived control as a determinant of these desires, self‐predictions, and attendance behavior, per se, was investigated. The results indicated that the best predictors of attendance at the training session were one's desire or motivation to attend the training session and the extent to which one perceived pressure from his or her supervisor to do so. Consistent with the theory of reasoned action, the motivation to attend training was predicted accurately from attitudes and subjective norms ( R = .76 , p < .001). Moreover, these attitudes and subjective norms were themselves predicted from a consideration of behavioral and normative beliefs, and key beliefs underlying one's desire to attend were identified. However, a consideration of perceived control did not improve the prediction of one's desire to attend training, and neither perceived control nor behavioral self‐predictions improved prediction of actual attendance. The discussion focused on the roles of perceived control and different measures of intention in behavioral prediction.