TY - GEN
T1 - Social media user acceptance on instagram health information recommendation
T2 - 5th International Conference on Informatics and Computing, ICIC 2020
AU - Rafizal Adnan, Hafizh
AU - Nizar Hidayanto, Achmad
AU - Vithasa Immanuel Kassan, Christie
AU - Christian Bagun, Albert
AU - Pamungkas Nasution, Ilham
AU - Samuel,
AU - Cofryanti, Ervi
N1 - Funding Information:
ACKNOWLEDGMENT This work was supported by the PUTI grant from the University of Indonesia with contract number: NKB-755/UN2.RST/HKP.05.00/2020.
Publisher Copyright:
© 2020 IEEE.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2020/11/3
Y1 - 2020/11/3
N2 - Social media revolutionize to exchange of health information. People can easily share and seek information to help them in diagnosing and curing disease. Many scholars have also explored the health information exchange. However, little research focuses on what drives people to adopt health information or recommendation on social media, specifically Instagram. This research explores the phenomenon by utilizing a transactive memory system (TMS) as the primary theoretical lenses. A quantitative survey and analysis were conducted to test several hypotheses developed regarding the phenomenon. The findings showed that social media user acceptance of health information/recommendation was mostly influenced by the communication quality and the credibility of the information. This study also found that communication quality was influenced by two TMS components: specialization and credibility. Furthermore, formal communication was also found to be more influential as the input of TMS compared to informal communication. The implication of the findings is also discussed.
AB - Social media revolutionize to exchange of health information. People can easily share and seek information to help them in diagnosing and curing disease. Many scholars have also explored the health information exchange. However, little research focuses on what drives people to adopt health information or recommendation on social media, specifically Instagram. This research explores the phenomenon by utilizing a transactive memory system (TMS) as the primary theoretical lenses. A quantitative survey and analysis were conducted to test several hypotheses developed regarding the phenomenon. The findings showed that social media user acceptance of health information/recommendation was mostly influenced by the communication quality and the credibility of the information. This study also found that communication quality was influenced by two TMS components: specialization and credibility. Furthermore, formal communication was also found to be more influential as the input of TMS compared to informal communication. The implication of the findings is also discussed.
KW - Health information sharing
KW - Partial least squares
KW - Transactive memory
UR - http://www.scopus.com/inward/record.url?scp=85099315612&partnerID=8YFLogxK
U2 - 10.1109/ICIC50835.2020.9288529
DO - 10.1109/ICIC50835.2020.9288529
M3 - Conference contribution
AN - SCOPUS:85099315612
T3 - 2020 5th International Conference on Informatics and Computing, ICIC 2020
BT - 2020 5th International Conference on Informatics and Computing, ICIC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 3 November 2020 through 4 November 2020
ER -