| dc.description.abstract | This study aims to investigate if the adoption of employee proposals is affected by the characteristics of the proposers. By collecting the data of employee proposals from a medium-sized commercial bank in Taiwan (hereinafter referred to as Bank A) from 2017 to 2020, this study compares the empirical results of descriptive statistics with those of Logistic regression analysis, and then provides relevant management implications resulting from the analysis results.
The empirical results of this study show that: Based on the Logistic regression analysis, the adoption of employ proposals in Bank A is mainly affected by the ＂annual effect＂, which is very opposite to the results of descriptive statistics, as the latter indicate that “The proposals submitted by female senior managers are more likely to be adopted by the Bank A” and “If a proposer submits more than one proposal within a year, one of his/her proposals is more likely to be adopted”.
To sum up, in addition to analyze the descriptive statistics of Bank A′s employee proposal data, this study further employs a Logistic regression model to investigate whether characteristics of the proposer lead to his/her proposal to be adopted. This study concludes that, in Bank A, the determinants of employee’s proposal to be adopted may not be quantified and thus may not be captured by the Logistic regression results. By contract, the determinants of an adoption may be of a qualitative nature, such as the focus and content of the proposals required, how the management promotes the submission of proposals, the composition of the review committee, and/or the strategic aims of the managers, all of them differ every year. Therefore, the managerial implications of the conclusion of this study deserves being explored in more depth. | en_US |