DEVELOPMENT OF SUCCESS MEASURES MODEL FOR MOBILE COMMERCE USING TEXT MINING AND MULTIGROUP SEM (STRUCTURAL EQUATION MODEL)

• Main Author: ABDUL HABIB KHOIRUL AMIN NIM: 23416082 , AHMAD
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/25155
• Institution: Institut Teknologi Bandung

The acceptance of the mobile commerce application system from customer perception is one of the driving factors for a successful mobile commerce implementation.The increasing number of companies that fail to implement mobile commerce applications is the driving forces behind the need to measure the success in implementing mobile commerce.The success measures of mobile commerce from customer perspective can be evaluated through the final feedback provided by the user about the performance of an information system. <br /> <br /> The development of technology allows customers to provide services feedback through online media without the limitation of time and place, for example using Twitter. Any tweet that contains comments or questions about a service is called a customer tweet. Customer tweets processed using text mining facilitate the company to get information about the success measures of a partcular services based on customer point of view. <br /> <br /> Based on previous literature studies, research on success measures of mobile commerce from the customer perspective is still in the early stages. Especially for topic about the development of success measures model for mobile commerce using text mining and multigroup SEM based on location. <br /> <br /> The finding of this study is that text mining can be used as preliminary study about the success measure model for mobile commerce application. Empirical study shows that variables of IT infrastrucuture service, system quality, service quality, process quality have significant influence to use, user satisfaction and net benefits. Other than that, there's evidence that there's difference in success measures model mobile commerce application based on customer in Bandung and Semarang. The diefferences happen on variable system quality, IT infrastucture services, service quality and use.