Motivation for applying to join the military via online channels : A case study of military units at the Artiliery Center (for Bhumibol), Lopburi Province

Abstract

          The objectives of this study are to 1) study the motivational factors for applying to join the military via online channels, 2) study the demand factors influencing applications submitted through online channels to present guidelines to enhance military recruitment through online platforms within military units at the Artillery Center (Bhumibol Camp), Lopburi Province. This study employed quantitative research approaches. Questionnaires were used as research tools to collect data from 92 samples who had applied to become soldiers via online channels for military recruitment at the Artillery Center (Bhumibol Camp), Lopburi Province, selected using Taro Yamane’s formula. The statistical methods used in this study include percentage, mean, standard deviation, and descriptive data synthesis to provide an overall analysis. The results showed that 1) the motivational factors for applying to join the military via online channels include salary, career advancement opportunities, future career growth potential, and job security. And 2) the demand factors influencing applicants involve the need for security and safety, the desire for love and social belonging, the need for recognition and respect, and the aspiration for success in life. Therefore, to enhance recruitment motivation, several strategies are recommended. These include increasing public relations efforts to promote the military’s image as honorable and prestigious to gain public trust, expanding recruitment information dissemination using more personnel, and improving the quality of life for recruits by enhancing welfare benefits, salaries, educational opportunities, vocational training, and other aspects, more effectively. Furthermore, a five-step selection process should be implemented to ensure the recruitment of qualified candidates, ultimately developing the system towards a volunteer-based recruitment model in the future.