Consumer trust and distrust: An issue of website design

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Abstract

Researchers have long speculated about the distinction between trust and distrust, yet the majority of studies on trust have treated them as essentially the same construct on opposite ends of a continuum. In order to resolve this ambiguity, we propose a theoretical framework to investigate the antecedents and influences of trust and distrust in the online shopping context, relying on the literature of website design and consumer trust, ambivalence theories, as well as emerging studies on distrust in the work place. Our findings indicate that trust and distrust are two separate concepts by reason of their distinct cognitions, different antecedents and different influences on consequent outcomes. In particular, the results show that specific website design attributes have distinct effects on shaping consumers’ trust and distrust. These findings suggest new ways in which website attributes can be fine-tuned by website designers and managers.

Research highlights

► Trust and distrust are two separate concepts by reason of their distinct cognition, different antecedents and different influence on consequent outcomes. ► Website design attributes have asymmetric impacts on shaping consumers' trust and distrust in the online shopping context. ► The influences of trust and distrust on buying intention are asymmetric in that distrust weighs more heavily in terms of lowering buying intention than trust does in terms of enhancing buying intention. ► A consumer's functional perception and motivating perception have asymmetric effects on a consumer's buying intention. ► Theoretical implications on ambivalence research and new insights about positive and negative manifestations have been emphasized.

Introduction

Consumer trust in the virtual environment has been extensively investigated in the past decade. However, little attention has been paid to trust’s counterpart, distrust. The lack of investigation is largely due to a commonly held assumption that trust and distrust are two sides of the same coin. Consequently, evidence of high trust has typically been regarded as equivalent to low distrust, and the antecedents and outcomes of trust have been treated as the converse of those of distrust. Recently, however, challenges to this assumption have emerged. Some scholars suggest that distrust is a qualitatively different construct from trust (Lewicki et al., 1998, McKnight et al., 2004). Consistently, neuroscience theories and functional neuron-imaging tools (Dimoka, et al., 2007) suggest that trust and distrust are connected to different cognitive parts of the brain: trust is associated with the caudate nucleus and the medial prefrontal cortex, while distrust is associated with the amygdala and the right insular cortex. These studies have suggested the possibility of the simultaneous coexistence of trust and distrust. In terms of their influences, distrust may have a more negative impact on consumers’ consumption decisions than what could be attributed to a simple degradation of trust. If distrust is distinct and has a significant effect, research that ignores distrust might yield a biased estimation of consumer behavior due to this important missing variable. However scholarly knowledge about how distrust is formed and how its consequences differ from those of trust is scarce.

In the context of website design and online purchasing behavior, the extant literature focuses on the effect of website design on trust building, but little research to date has modeled the impact of website design on the formation of distrust and its subsequent effect on consumers’ buying intention. This might have also biased the estimation of the role of website design in consumer behavior. For online consumers, it is easy to switch from one website to another. The complexity of the virtual world and online transactions with unseen and unknown e-vendors requires consumer trust, but also precipitates distrust.

If indeed distrust and trust can be treated separately, an investigation into how they form and co-exist in online consumers’ perception and behavior requires both theoretical and practical studies. Trust is regarded as a positive-valent belief that compels involved parties, such as online consumers in this research context, to take actions (such as buying) even with the exposure of risk; while distrust is a negative-valent belief that leads to protective actions to reduce risk (Luhmann, 1979). The combination of trust and distrust has the potential to simplify the process of consumer decisions and keep their perceptions functional. To motivate consumers to make online purchases, vendors need to carefully fine-tune their website attributes by nurturing trust and minimizing distrust, where a change in one may not lead to a corresponding change in the other. Consequently, determining whether trust and distrust are opposite ends of a continuum as is popularly viewed in many prior studies, or are actually two distinct constructs, has significant implications for website design and management. If they are found to be the same construct, then managing the same website attributes would be sufficient to simultaneously raise trust and lower distrust in a website. If however, they are different constructs, then different sets of website attributes may need to be managed in order to elevate trust, and to impede distrust.

Nevertheless, to the best of our knowledge, no research simultaneously links and empirically tests trust, distrust and the effects of website design in a single model. Grounded on ambivalence theories, especially Oliver’s (1997) three-factor framework, this study attempts to empirically test the distinction between trust and distrust, considering that they are induced by different website-design factors and have asymmetrical effects on buying intention in the online shopping context.

Following the introduction, we first explain ambivalence theories in order to understand the nature of the relationship between trust and distrust. Then we include various website-design factors as antecedents, and buying intention as the outcome in the framework of trust and distrust in Section 3. The methodology and data analysis are described in 4 Methodology, 5 Data analysis, respectively. We discuss the results in Section 6 and conclude this study in the final section.

Section snippets

Deliberating trust and distrust

Normatively, scholars generally consider trust to be “good” or “positive,” while distrust is “bad” or “negative.” In an organizational study, Lewicki et al.’s (1998) trust and distrust framework describes how trust in the work place could be characterized by hope, faith, assurance, confidence, and initiative, whereas distrust could be characterized by fear, skepticism, cynicism, wariness, and watchfulness. In an influential study investigating online consumers’ trust, scholars suggest

The framework of trust and distrust

The classical two-factor theory (Herzberg et al., 1967) and the generic three-factor framework (Oliver, 1997) serve as important anchors of this study where we investigate the antecedents of trust and distrust. We argue that consumer trust and distrust in the online shopping context are influenced by a number of distinct factors, consistent with the ambivalence theories. The theory of negativity bias and prospect theory further provide a basis to explore the distinct influences of trust and

Methodology

The survey method was used to validate the research model. The measures and the data collection procedures are detailed below.

Measurement model—reliability and validity

Given that our whole data pool came from participants’ evaluations of two different websites (i.e., Atriniti and BuyDig), we followed the method of previous studies (Koufaris and Hampton-Sosa, 2004, Pavlou and Gefen, 2005) to handle data sets from different markets and websites. First, in order to check whether the manipulation was successful (i.e., allowing for variance of constructs of interest to be adequately unveiled by asking the participants to browse two websites), we first conducted

Discussions

This study incorporates the construct of “distrust” into a model of e-commerce purchase intention. The mean of distrust from the sample is 3.62 and the mean of trust is 4.26 (see Table 4), suggesting that people’s attitudes toward a vending website generally tend to be more trusting than suspicious. However, distrust does exist! Table 6 indicates the coexistence of high and low trust/distrust. Notice that 19% of cases (62 out of 324) suggest the coexistence of high trust and high distrust and

Future research

For a balanced appreciation of the findings from this study, we must recognize several limitations. First, this study may have limited generalizability because a single-region student sample was used and the websites mainly vend electronic products. Prior research has indicated that the type of products may influence consumers’ purchase intention from the Internet (Phau and Poon, 2000). We also anticipate that consumers with different online purchase experience of electronic products may

Implications and conclusions

Despite these recognized limitations, this study yields a theoretically better understanding of trust and distrust. In response to the call for a greater understanding of distrust (McKnight et al., 2004; Ou and Sia, 2009), this study clarifies the different cognitions contained in trust and distrust, and empirically verifies that trust and distrust can simultaneously be present in individuals as positive and negative sentiments. Thus, distrust and trust are equally worthy of recognition.

Acknowledgements

The authors are indebted to the Associate Editor, Andrew Sears, and the review panel for their constructive feedback throughout the review process, which has dramatically improved this paper. The authors would also like to thank Robert Davison, Dov Te’eni, Hock Hai Teo, Kwok Kee Wei, and Ping Zhang for their insightful comments and suggestions on this paper at different stages. A practitioner-focused version of this research has been previously presented in Communications of the ACM.

The work

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