PurposeThe purpose of this paper is to explore and provide empirical evidence for the combined effects of individual characteristics, training design factors as well as environmental factors (as pre-training factors) on training transfer.Design/methodology/approachPrimary data were collected from 235 managerial-level full-time employees in two phases with a temporal gap of two months. Both procedural and statistical measures were used to minimize the common method variance problem. Hierarchical regression analysis was conducted to analyze the data.FindingsThe results of this study clearly point out that all four predictor variables (voluntary participation, prior training information, training needs identification and training evaluation) positively and significantly influence training transfer.Research limitations/implicationsThe study contributes to the training transfer literature in three ways. One, the authors have shown the positive influence of pre-training factors (together as well as independently) on training transfer. The study is grounded in a strong theoretical framework, thus fulfilling the previous gap. This study brings more clarity to those variables (such as voluntary training) which are having contradicting views in the extant literature.Practical implicationsThe study has significant findings for the organizations operating in the current business scenario in their endeavor to enhance learning transfer, which is very low and a major cause of concern for every organization. If management is aware of the success factors of training transfer, they can ensure a better training transfer.Originality/valueThe training transfer literature showcases two significant gaps; first of all, it lacks in using appropriate motivational theories, and second, there is variability in the results. This paper bridges both the gaps and attempts to advance our understanding of training transfer grounded in the theoretical framework by focusing on the role of individual, motivational and situational factors of training transfer to understand better which predictor variables can improve training transfer.