2013
DOI: 10.1177/2158244013492782
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Consumer Trust in Information Sources

Abstract: Trust is essential to understanding public reaction to innovative issues. This research focuses on trust in information sources by explicating the construct of trust and testing a comprehensive model on several information sources about genetically modified foods. Results from a survey of 369 participants reveal the significance of projecting competence and the role of the environment in which a target public receives information. Perceptions of regulatory, social, business, and technical environments affect h… Show more

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Cited by 13 publications
(5 citation statements)
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“…Receiving information can affect the public's knowledge about perceived risk, thereby influencing their decisions to adopt protective measures [31,32]. However, public response to communication efforts may be shaped less by explanations of uncertainty than by trust in the parties involved [25,33]. It is, therefore, important to understand how the public perceives the situation and to what degree they trust different agents that inform them about uncertainty resulting from the COVID-19 pandemic [31,34].…”
Section: Introductionmentioning
confidence: 99%
“…Receiving information can affect the public's knowledge about perceived risk, thereby influencing their decisions to adopt protective measures [31,32]. However, public response to communication efforts may be shaped less by explanations of uncertainty than by trust in the parties involved [25,33]. It is, therefore, important to understand how the public perceives the situation and to what degree they trust different agents that inform them about uncertainty resulting from the COVID-19 pandemic [31,34].…”
Section: Introductionmentioning
confidence: 99%
“…Trust can be defined as "the willingness of a party to be vulnerable to the actions of another party based on the expectation that the other will perform a particular action important to the trustor, irrespective of the ability to monitor or control that other party" (Mayer el al., 1995). Scientists divide trust into four conceptual categories (McKnight and Chervany, 2001;Tsai et al, 2010;Love et al, 2013;Lam et al, 2018;Bachmann and Inkpen, 2011;Benson et al, 2019): (1) trust belief, (2) trust intention, (3) institutional based trust, (4) general trust. The survey which results are presented in this paper was conducted in Poland in January 2020.…”
Section: Discussionmentioning
confidence: 99%
“…Scientists divide trust into four conceptual categories (McKnight and Chervany, 2001; Tsai et al. , 2010; Love et al. , 2013; Lam et al.…”
Section: Discussionmentioning
confidence: 99%
“…Approaches to solving the problems resulting from multiparadigm or multidisciplinary big data rely on the assumption that different theories can have a multiparadigmatic or multidiscipline perspective. At least for multidiscipline perspectives, such theories can be found in social research, notably an interdisciplinary theory of coordination (Malone and Crowston 1991), an interdisciplinary model of school absenteeism (Kearney 2008), an interdisciplinary model of consumer trust (Love, Mackert, and Silk 2013), and an interdisciplinary privacy and communication model (Bräunlich et al 2021). Such theories could be used as models to develop interdisciplinary theories based on big data.…”
Section: Big Data and Standards For Evaluating Theoriesmentioning
confidence: 99%