Purpose

The purpose of this study is to explore the effects of recommendation algorithm, product reputation, new product novelty, privacy concern and privacy protection behavior on users’ satisfaction and continuance intention to use short-form video application (APP).

Design/methodology/approach

Based on the existing theories, the research model of this study was developed and 445 valid data were collected through a questionnaire survey. The partial least squares structural equation modeling (PLS-SEM) was employed for data analysis to test the research model and hypotheses.

Findings

The results reveal that the recommendation algorithm has a significant positive effect on user satisfaction, new product novelty and privacy concern. The influence of recommendation algorithm on privacy concern is negatively moderated by product reputation. Privacy concern has a significant and positive impact on privacy protection behavior, and privacy protection behavior has a significant and positive impact on user satisfaction. New product novelty also has significant impact on user satisfaction.

Originality/value

This study is one of the earliest studies to incorporate recommendation algorithm as a construct into the college students’ continuance intention to use short-form video APP. The influence of reputation as a moderator variable on the relationship between algorithm and privacy concerns is also investigated.

中文翻译：

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大学生短视频APP持续使用意愿影响因素分析

目的

本研究的目的是探讨推荐算法、产品声誉、新产品新颖性、隐私关注和隐私保护行为对用户使用短视频应用（APP）的满意度和持续意愿的影响。

设计/方法/方法

在现有理论的基础上，建立了本研究的研究模型，通过问卷调查收集到445份有效数据。采用偏最小二乘结构方程模型（PLS-SEM）进行数据分析以检验研究模型和假设。

发现

结果表明，推荐算法对用户满意度、新产品新颖性和隐私关注具有显着的正向影响。推荐算法对隐私问题的影响受到产品声誉的负面影响。隐私关注对隐私保护行为具有显着正向影响，隐私保护行为对用户满意度具有显着正向影响。新产品的新颖性对用户满意度也有显着影响。

原创性/价值

本研究是最早将推荐算法作为构建体纳入大学生使用短视频APP的持续意愿的研究之一。还研究了作为调节变量的声誉对算法和隐私问题之间关系的影响。