The role of social user and social feature on recommendation acceptance in instagram in Indonesia

Muhammad Aldi Yusron, Putu W. Handayani, Qorib Munajat

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

This study aims to identify the effect of social features and social users on recommendations acceptance on shopping activities in Instagram. This study uses quantitative approach to process 654 data collected using online questionnaire. The data were analyzed using CB-SEM method and AMOS 21 tools. The results of this study showed that social features and social users give moderating effect on the relationship between social recommendation, cognitive appraisal and affective appraisal. Meanwhile, affective and cognitive appraisal was found to affect purchase intention. The finding shows that the user giving recommendation and the features used to make recommendation can influence the level of recommendation acceptance.

Original languageEnglish
Title of host publicationProceedings - 2018 5th International Conference on Electrical Engineering Computer Science and Informatics, EECSI 2018
EditorsDeris Stiawan, Imam Much Ibnu Subroto, Munawar A. Riyadi, Christian Sri Kusuma Aditya, Zulfatman Has, Anton Yudhana, Agus Eko Minarno
PublisherInstitute of Advanced Engineering and Science (IAES)
Pages90-96
Number of pages7
ISBN (Electronic)9781538684023
DOIs
Publication statusPublished - 1 Oct 2018
Event5th International Conference on Electrical Engineering Computer Science and Informatics, EECSI 2018 - Malang, Indonesia
Duration: 16 Oct 201818 Oct 2018

Publication series

NameInternational Conference on Electrical Engineering, Computer Science and Informatics (EECSI)
Volume2018-October
ISSN (Print)2407-439X

Conference

Conference5th International Conference on Electrical Engineering Computer Science and Informatics, EECSI 2018
Country/TerritoryIndonesia
CityMalang
Period16/10/1818/10/18

Keywords

  • E-commerce
  • Purchase Intention
  • Social Feature
  • Social Recommendation
  • Social User

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