The influence of the work environment on the transfer of newly trained supervisory skills was examined. Participants were 505 supermarket managers from 52 stores. The work environment was operationalized in terms of transfer of training climate and continuouslearning culture. Climate and culture were hypothesized to have both direct and moderating effects on posttraining behaviors. Accounting for pretraining behaviors and knowledge gained in training, the results from a series of LISREL analyses showed that both climate and culture were directly related to posttraining behaviors. In particular, the social support system appeared to play a central role in the transfer of training. Moderating effects were not found. Implications for enhancing the transfer of training are discussed.

This study aims to gain insight into some of the factors that determine the transfer of training to the work context. The present research examined the relationship between three types of predictors on transfer of training, including training design, individual characteristics and work environment. Data was collected at two points in time from 182 employees in a large grocery organization. The results indicated that transfer design, performance self-efficacy, training retention and performance feedback were significantly related to transfer of training. Contrary to expectation, supervisory support was not significantly related to transfer of training. These results suggest that in order to enhance transfer of training, organizations should design training that gives trainees the ability to transfer learning, reinforces the trainee's beliefs in their ability to transfer, ensures the training content is retained over time and provides appropriate feedback regarding employee job performance following training activities.

Three general issues of dimensionality, validity, and content of ratings of managerial performance are examined in terms of "relevance to the ultimate criterion." It is argued that the multitrait-multimethod design yields the best evidence for investigating these issues. An analysis of variance model with computational formulas for the sums of squares and variance components based on the correlation matrix is proposed for the multitrait-multimethod situation. Using this model, data from two studies are examined and compared, relative to convergent and discriminant validity, method bias (halo), and error variance. It appears that this model and the indexes derived from it provide a more simplified and interpretable technique for analyzing and summarizing multitrait-multimethod data. In addition, a procedure to improve performance ratings based on partitioning the original matrix is illustrated with an example from the larger data set.

No abstract

No abstract