TY - GEN
T1 - Continuance usage intention and intention to recommend on information based mobile application
T2 - 9th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2017
AU - Setyawan, Nurlina
AU - Shihab, Muhammad Rifki
AU - Hidayanto, Achmad Nizar
AU - Pinem, Ave Adriana
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - The purpose of this research is to understand the antecedents of continuance usage intention and intention to recommend of information based mobile application. The underlying research model was developed from technological as well as user experience perspectives, intertwined with the expectation-confirmation model. A total of 176 respondents participated in this study, whom were avid users of a respected information based mobile application in Indonesia. Data was analyzed using Structural Equational Modeling, aided by WarpPLS 4.0. The results revealed a number of factors that influence intention to reuse and intention to recommend, which include system quality, information quality, perceived usefulness, perceived enjoyment, confirmation, and satisfaction. Perceived usefulness and satisfaction were factors that directly affect continuance usage intention. Intention to recommend, on the other hand, was only directly influenced by satisfaction. Confirmation affected both user experience factors of perceived usefulness and perceived enjoyment, as well as satisfaction. Finally, perceived usefulness was affected by information quality and perceived enjoyment was affected by system quality.
AB - The purpose of this research is to understand the antecedents of continuance usage intention and intention to recommend of information based mobile application. The underlying research model was developed from technological as well as user experience perspectives, intertwined with the expectation-confirmation model. A total of 176 respondents participated in this study, whom were avid users of a respected information based mobile application in Indonesia. Data was analyzed using Structural Equational Modeling, aided by WarpPLS 4.0. The results revealed a number of factors that influence intention to reuse and intention to recommend, which include system quality, information quality, perceived usefulness, perceived enjoyment, confirmation, and satisfaction. Perceived usefulness and satisfaction were factors that directly affect continuance usage intention. Intention to recommend, on the other hand, was only directly influenced by satisfaction. Confirmation affected both user experience factors of perceived usefulness and perceived enjoyment, as well as satisfaction. Finally, perceived usefulness was affected by information quality and perceived enjoyment was affected by system quality.
KW - PLS
KW - SEM
KW - continuance intention
KW - intention to recommend
KW - mobile application
UR - http://www.scopus.com/inward/record.url?scp=85050945759&partnerID=8YFLogxK
U2 - 10.1109/ICACSIS.2017.8355031
DO - 10.1109/ICACSIS.2017.8355031
M3 - Conference contribution
AN - SCOPUS:85050945759
T3 - 2017 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2017
SP - 184
EP - 189
BT - 2017 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2017
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 28 October 2017 through 29 October 2017
ER -