Development of a measurement tool for transfer of training and its validation in the public sector insurance corporation of Pakistan
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2022
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230 leaves
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b214887
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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Khan, Kehar (2022). Development of a measurement tool for transfer of training and its validation in the public sector insurance corporation of Pakistan. Retrieved from: https://repository.nida.ac.th/handle/662723737/6170.
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Development of a measurement tool for transfer of training and its validation in the public sector insurance corporation of Pakistan
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Abstract
The present study was aimed at developing a valid and reliable measurement tool for transfer of training under the Pakistani context and validating the tool among the sales representatives of State Life Insurance Corporation of Pakistan (SLIC). To achieve this, the study was conducted in which data was obtained from the sample of 589 employees from SLIC. 500 sample size was finally used after data cleaning process.
This research was conducted in two stages: Developing a measurement tool and validating the measurement tool. In the development stage, the measurement tool was developed through synthesizing the literature, performing content validity by panel of experts, pilot study, conducting factor analysis, and reliability analysis. Additionally, a qualitative study was also conducted to see if any further factors are discovered which have not yet been explored by the literature. The development process ended with the identification of 14 subfactors and 43 items of the measurement tool for transfer of training, with factor loadings of over 0.45 and internal consistency with over 0.70 (Cronbach’s alpha).
The validation phase consisted of two phases. In the first phase, the validation of the measurement tool for transfer of training was done through performing CFA. Results of the CFA showed strong correlation between the 14 subfactors of the measurement tool. The CFA model showed a good fit (CMIN/DF= 2.358, GFI= 0.854, AGFI= 0.819, TLI= 0.917, CFI=.929, RMSEA= .052). Moreover, composite reliability, convergent and discriminant validity were also found significant.
In the second phase of validation, the measurement tool was validation by examining the factors affecting the transfer of training among the sales presentative of the SLIC. Multiple hierarchical regression was applied for the validation. Separate hypotheses and sub hypotheses were developed for each dependent variable (declarative knowledge and perceived performance). Five models were developed to investigate the predictive power on each dependent variable.
The results of the hierarchical regression of declarative knowledge as independent variable showed that out of twelve variables, eight variables were found statistically significant. However, the results did not support five hypotheses H1b, H1c, H1e, H1f, and H1g. Out of those five, three variable, transfer design, motivation to learn, and principles of learning were negatively significant, while no evidence was found regarding statistical significance of the two subfactor ability to learn, and sequencing.
For perceived performance as the dependent variable, the hierarchical regression results showed that out of 12 independent variables, eight variables positively and significantly predicted perceived performance, and four variables did not exhibit positive significance on perceived performance. Out of these four variables, training contents (H2d) was non-significant, while the three variables, ability to learn(H2b), sequencing (H2e), and principles of learning (h2f) exhibited negative significance.
This research adds value to the existing body of knowledge in several ways. The study adds value by developing a new and extended measurement tool, which is unified in nature, by developing a new and comprehensive definition of the transfer of training, and by providing empirical evidence by examining the factors affecting the transfer of training in the State Life Insurance Corporation of Pakistan.
The present study will be helpful for Insurance companies in Pakistan in evaluating and improving transfer of training. The measurement tool may help the management of insurance companies to view and evaluate training programs from a different perspective.
Future studies can be conducted by extending the validity of the measurement tool by performing Structural Equation Modeling (SEM). The future research can also be done by studying private insurance companies in the country to examine difference between public sector and private insurance companies. Moreover, future studies can also be carried out to test and use the measurement tool in the sectors and industries other than insurance industry in Pakistan or in other countries located in Asia, given the assumption that Asian culture and context has some similarities across most countries. Lastly, future study can also be conducted to refine and extend the scope of the unified measurement tool to make the measure as a diagnostic tool for organizational diagnosis.
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Thesis (Ph.D. (Human Resource and Organization Development))--National Institute of Development Administration, 2022