مقاله انگلیسی رایگان در مورد رفتار اجتناب از اطلاعات در سایت های شبکه های اجتماعی – الزویر 2020

1- Introduction

2- Theoretical background

3- Research model and hypothesis

4- Research methodology

5- Discussions and implications

6- Conclusions and limitations

References

Abstract

Drawing on the stressor-strain-outcome framework, this study investigates how information irrelevance and overload induce social network fatigue, and the relationship of these variables to users’ information avoidance behavior. It also examines the conditions under which social network fatigue is more likely to be translated into information avoidance behavior. The analysis of data collected from 341 users of WeChat Moments suggests that information irrelevance directly leads to information avoidance behavior, and social media fatigue as a mediator partially mediates the impact of information overload on information avoidance behavior and fully mediates the impact of social overload on information avoidance behavior. Furthermore, time pressure strengthens the effect of social network fatigue on information avoidance behavior. This study fulfills the identified need for an in-depth investigation of actual discontinuous behavior in social network services (SNSs) by investigating information avoidance behavior and its antecedents. The findings provide SNSs providers with guidelines on how to manage users’ behavior so that they remain active users of the SNSs.

Introduction

Recently, social network services (SNSs) have become ubiquitous in our lives and have received much attention from academics (Alalwan, Rana, Dwivedi, & Algharabat, 2017; Shiau, Dwivedi, & Yang, 2017; Zhang, Zhao, Lu, & Yang, 2016). Currently, after a period of flourishing growth, users’ enthusiasm for SNSs has begun to wane, and passive usage behaviors, such as consciously ignoring some messages or avoiding some friends via technical means due to lack of time, energy, knowledge, or personal interest, are becoming increasingly common. For instance, there has been a substantial decrease in the number of active users on many popular SNSs such as Facebook, Twitter, and Myspace. WeChat Moments, the largest SNS provider in China, is facing the same issue. Recently, many WeChat Moment users have expressed negative feelings about SNSs due to boredom and weariness with the large amounts of irrelevant information and excessive demands from friends for “forwards,” “thumbs up,” and “help do the bargaining.” According to the China Internet Network Information Center (CNNIC, 2019), after six years of growth, WeChat Moments experienced a decrease in the use rate from 87.3 % in December 2017 to 83.4 % in December 2018. SNSs providers have tried to develop various functions and content to retain users, but none have been as effective as hoped. In studies of this phenomenon, some scholars have investigated what they call the passive use of SNSs (Chen, Tran, & Nguyen, 2019; Han & Myers, 2018; Luqman, Cao, Ali, Masood, & Yu, 2017; Maier, Laumer, Eckhardt, & Weitzel, 2015; Maier, Laumer, Weinert, & Weitzel, 2015; Nisar, Prabhakar, Ilavarasan, & Baabdullah, 2019; Turel, 2016). Other studies refer to discontinuous intention, which is conceptualized as the opposite of continuous use. SNSs are tools for connecting with others (Alalwan et al., 2017; Shiau et al., 2017), and it is not easy for users to stop using them. In fact, more and more users are exhibiting compulsive use habits and are fearful of missing out on important interactions on SNSs (Dhir, Yossatorn, Kaur, & Chen, 2018). Therefore, as it can be difficult for users to check each message on a social network, they may skim or skip irrelevant information or even avoid some information. That means users typically exhibit ignoring and avoidance behaviors before they stop using an SNS or switch to an alternative network. Zhang et al. (2016) suggested that although behavioral intention is usually regarded as an effective predictor of actual behavior, in-depth investigation is needed to understand actual discontinuous behavior. This study answers this call by focusing on users’ information avoidance behavior and the antecedents of this behavior.