How do two facets of social media interaction shape waste sorting behaviour? Empirical evidence from Beijing, China

IF 12.9 1区 管理学 Q1 BUSINESS Technological Forecasting and Social Change Pub Date : 2024-10-31 DOI:10.1016/j.techfore.2024.123850
Myat Su Han , Yiwen Zhang , Cinnie Liu
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Abstract

In the ever-changing digital era, social media has become a powerful tool for shaping public environmental awareness and pro-environmental behaviour. However, no existing studies have addressed the double-edged role of social media interaction in the context of household waste sorting, particularly in a rapidly developing country with considerable waste management challenges. Against this background, our study aims to investigate the positive and negative impacts of two facets of social media interaction (i.e. online peer influence and perceived information overload) on household waste sorting behaviour in China. Moreover, we investigate the mechanisms behind these impacts by analysing the moderating roles of psychological enablers (i.e. green self-efficacy) and barriers (i.e. environmental apathy). Drawing upon social learning theory, we develop a conceptual model that is empirically tested using 1200 online survey responses from Beijing, one of the most populous cities in China. We then employ a two-stage data analysis technique comprising confirmatory factor analysis and moderated multiple regression analysis to examine the proposed hypotheses. The findings of this pioneering study can assist policymakers and environmentalists in designing successful social intervention strategies that may encourage household waste sorting in large metropolitan regions, such as Beijing.
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社交媒体互动的两个方面如何影响垃圾分类行为?来自中国北京的经验证据
在日新月异的数字时代,社交媒体已成为塑造公众环境意识和环保行为的有力工具。然而,目前还没有研究探讨过社交媒体互动在家庭垃圾分类中的双刃作用,尤其是在一个面临巨大垃圾管理挑战的快速发展国家。在此背景下,我们的研究旨在调查社交媒体互动的两个方面(即网络同伴影响和感知信息超载)对中国家庭垃圾分类行为的积极和消极影响。此外,我们还通过分析心理促进因素(即绿色自我效能感)和障碍因素(即环境冷漠)的调节作用,研究了这些影响背后的机制。借鉴社会学习理论,我们建立了一个概念模型,并利用来自北京(中国人口最多的城市之一)的 1200 份在线调查问卷对该模型进行了实证检验。然后,我们采用两阶段数据分析技术,包括确证因子分析和调节多元回归分析,对提出的假设进行检验。这项开创性研究的结果可以帮助政策制定者和环保人士设计成功的社会干预策略,从而鼓励像北京这样的大都市地区进行家庭垃圾分类。
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来源期刊
CiteScore
21.30
自引率
10.80%
发文量
813
期刊介绍: Technological Forecasting and Social Change is a prominent platform for individuals engaged in the methodology and application of technological forecasting and future studies as planning tools, exploring the interconnectedness of social, environmental, and technological factors. In addition to serving as a key forum for these discussions, we offer numerous benefits for authors, including complimentary PDFs, a generous copyright policy, exclusive discounts on Elsevier publications, and more.
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