Factors influencing the use of knowledge management systems: a case study of the manufacturing sector and service sector in Thailand

Abstract

A growing interest in knowledge management systems has led to rapid change in using the knowledge management systems in organization. Knowledge management consists of three important compartments including users, management, and technology. Information technology plays a crucial role in a knowledge management system (KMS) both in production and service of business. The aims of this study were 1) to investigate the factors that influence the use of KMS in organizations especially in production and service, 2) to study the behavior of users who applied KMS in their organizations, and 3) to examine the results of applying Unified Theory of Acceptance and Use of Technology (UTAUT) in organizations. The population consisted of approximately 107,386 KMS users who are members of Thailand Productivity Institute. The randomized samples were 400 executive managers and employees. The research instruments included a survey questionnaire for collecting quantitative data and an interview for collecting qualitative data. The data from the questionnaire were collected from July to September 2016. Approximately 43 percent (172 out of 400 copies) of the questionnaire were returned. For qualitative data, users of KMS in both the production and service sections of four organizations were interviewed during November and December 2016. The four organizations were THAI Catering Department (Don Mueang), CAT Telecom Public Company Limited, TOT Public Company Limited, and Virtual Link Solutions Co, Ltd. (Vlink) The data were interpreted using the structural equation model (SEM). The partial least square (PLS) regression was used to assess relation, accuracy and reliability of the collected data and hypotheses. The results showed that 59.60 percent of effort expectancy affected KMS intention while 50.60 percent of usage behavior had an effect on KMS intention. Only 33.70 percent of the facility condition directly affected usage behavior. In conclusion, factors which influenced KMS usage were performance expectancy, effort expectancy, social influence, facility condition, behavioral intention and usage behavior. The facility condition and KMS intention which directly affected the behavior of users were the mediator of the model.