Empirical Research on Users' Continuous Use Intention of Live Broadcast Platform in the Context of Digital Societ

Pengyu Zhu, Shimin Shao

2022

Abstract

With the rapid development of live broadcast industry, the competition between live broadcast platforms is becoming more and more fierce. It is very important for live broadcast platform to retain users and enhance their continuous use intention. In this paper, we construct the model of live broadcast platform users' continuous use intention, collect data through the way of questionnaire investigation, analyze and process the data by using SPSS software, draw conclusions and put forward relevant suggestions, which will provide reference for enhancing the user stickiness and competitiveness of live broadcast platform.

Paper Citation

in Harvard Style

Zhu P. and Shao S. (2022). Empirical Research on Users' Continuous Use Intention of Live Broadcast Platform in the Context of Digital Societ. In Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI; ISBN 978-989-758-620-0, SciTePress, pages 185-190. DOI: 10.5220/0011732700003607

in Bibtex Style

@conference{icpdi22,
author={Pengyu Zhu and Shimin Shao},
title={Empirical Research on Users' Continuous Use Intention of Live Broadcast Platform in the Context of Digital Societ},
booktitle={Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI},
year={2022},
pages={185-190},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011732700003607},
isbn={978-989-758-620-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI
TI - Empirical Research on Users' Continuous Use Intention of Live Broadcast Platform in the Context of Digital Societ
SN - 978-989-758-620-0
AU - Zhu P.
AU - Shao S.
PY - 2022
SP - 185
EP - 190
DO - 10.5220/0011732700003607
PB - SciTePress