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      Interactive effects of advising strength and brand familiarity on users' trust and distrust in online recommendation agents

      , , , ,
      Information Technology & People
      Emerald

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          Abstract

          Purpose

          This paper investigates the effects of advising strength of a recommendation agent on users' trust and distrust beliefs and how the effects are moderated by perceived brand familiarity.

          Design/methodology/approach

          A research model is evaluated using a laboratory experiment with 149 participants.

          Findings

          Results reveal that a strong advising tone leads to higher trust in terms of users' credibility and benevolence beliefs and lower distrust in terms of their discredibility beliefs (the trustor's concerns regarding the trustee's dishonesty and competence in engaging in harmful behavior) when perceived brand familiarity is high. By contrast, when brand familiarity is low, strong advising tone results in low trust in terms of users' credibility belief and high distrust in terms of their beliefs in discredibility and malevolence (concerns regarding the trustee's conduct in terms of a malicious intention that can hurt the trustor's welfare).

          Originality/value

          This paper contributes to the trust and distrust literature by studying how each of the dimensions of trust and distrust can be affected by an RA's design feature. It extends the attribution theory to the RA context by studying the moderating role of brand familiarity in determining the effects of the advising strength of an RA. It provides actionable guidelines for practitioners regarding the adoption of an RA's appropriate advising strength to promote different types of products.

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          Most cited references104

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          One possible reason for the continued neglect of statistical power analysis in research in the behavioral sciences is the inaccessibility of or difficulty with the standard material. A convenient, although not comprehensive, presentation of required sample sizes is provided here. Effect-size indexes and conventional values for these are given for operationally defined small, medium, and large effects. The sample sizes necessary for .80 power to detect effects at these levels are tabled for eight standard statistical tests: (a) the difference between independent means, (b) the significance of a product-moment correlation, (c) the difference between independent rs, (d) the sign test, (e) the difference between independent proportions, (f) chi-square tests for goodness of fit and contingency tables, (g) one-way analysis of variance, and (h) the significance of a multiple or multiple partial correlation.
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            An Integrative Model of Organizational Trust

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              Structural Equation Modeling and Regression: Guidelines for Research Practice

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                Author and article information

                Contributors
                Journal
                Information Technology & People
                ITP
                Emerald
                0959-3845
                May 24 2021
                November 18 2021
                May 24 2021
                November 18 2021
                : 34
                : 7
                : 1920-1948
                Article
                10.1108/ITP-08-2019-0448
                6ec43b17-a20a-462a-b6e1-31b54654f26f
                © 2021

                https://www.emerald.com/insight/site-policies

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