A A Performance Improvement of Kasikorn Bank Employees in the Northeastern Area 2 Business Network.
Keywords:
Performance improvement Model, Kasikorn bank employees, Business NetworkAbstract
The purposes of this study were 1. to study factors influencing performance of Kasikorn bank employees in the Northeastern Area 2 business network 2. to design a model to improve performance of Kasikorn bank employees; and 3. to carry out a trial run and assess the performance improvement model to Kasikorn bank employees. The research used Mixed Methods. The data were collected through questionnaires. The sample consisted of 220 Kasikorn bank employees and were analyzed by the structural equation model (SEM) in the LISREL program, the researcher gathered 20 stakeholders into a focus group and brainstorming sessions. The purpose of these gatherings was then assessed by three specialists to check the model was appropriate before a trial run. The performance improvement model was carried out to 30 Kasikorn bank employees in Roi-et province. The researcher analyzed the pre-and-posttest of the performance improvement model using repeated measure MANOVA (α=0.05) The results were as follows: 1. The factors influencing performance of Kasikorn bank employees (α=0.05) were role recognition (β=0.42), being a good membership of the organization (β=0.19), leadership (β=0.16), motivation (β=0.14), and teamwork (β=0.13), respectively : 2. A model to improve performance of Kasikorn bank employees consisted of 11 activities, 2.1 roles and duties training activities, 2.2 knowledge about leadership, 2.3 leadership development, 2.4 Joe Hari ' s Window method, 2.5 puzzle image game, 2.6 team collaboration, 2.7 role playing activity, 2.8 good corporate membership, 2.9 good membership behavior, 2.10 encouragement, and 2.11 learning about individual and team development : 3. The result of the performance improvement model on Kasikorn bank employees showed that there were statistically significant differences at the level of 0.05 between the pre-and-posttest of the model, the posttest better than the pretest.