Customer Value Creation for Risky Products: The Role of Brand Trust and Trusting Beliefs

Abstract

Consumers often perceive products and services as risky. As a result, they might perceive the same products as less valuable. While past research has investigated numerous ways of reducing the negative effect of perceived product risk on customers’ perceived value, surprisingly, the role of brand trust has not been taken into account. This article aims to fill this gap by investigating how consumers’ trust in a brand, as well as their trusting beliefs about the brand’s competence, benevolence and integrity, may moderate the relationship between consumers’ perceived product risk and consumers’ perceived value. By means of two empirical studies based on a panel of smartphone users, the authors propose and demonstrate that the trust customers have for a brand can mitigate the negative effect of perceived product risk on perceived value of products with the same brand name. Importantly, findings also show that the various beliefs underlying trust have differential downstream effects. More specifically, while benevolence and integrity beliefs about a brand mitigate the negative effect of perceived product risk on customers’ perceived value, competence beliefs were found irrelevant to the effect of risk on value. These findings inform and guide marketing practitioners’ efforts to cultivate specific, rather than generic, trusting beliefs to ultimately create and maximize value for their customers who otherwise view these products as risky.

Keywords

Perceived value perceived product risk trust benevolence integrity competence

Introduction

In recent years, safety-related product recalls have grown in frequency and scale across a variety of product categories, ranging from pharmaceutical drugs and children’s toys, to home appliances and automobile parts (e.g., Paulssen, Roulet & Wilke, 2014). While many of these recalls have gained publicity around the world, undoubtedly the recall of Samsung smartphone due to exploding batteries has received the most attention. After a series of overheating and explosion incidents in September 2016, Samsung suspended the sales of its newly released Galaxy Note 7 smartphone and issued a general recall for its sold products (Sczcepanski, 2016). Initially, as expected, this widely publicized recall hurt Samsung’s sales, including the company’s worldwide smartphone sales during the holiday shopping season, affecting the brand’s stock prices and market value (Luces, 2016; Pressman, 2017). However, following the initial shocks, recent studies and consumer surveys have provided better and surprising news for Samsung suggesting that many consumers are still likely to purchase a Samsung smartphone in the future (Siegel, 2017). While product recalls are only one way in which consumers become more uncertain about a brand and the value of its products, a better understanding of how consumers continue to see value in such risky products and what conditions might positively influence their willingness to purchase may have important implications for brands facing similar challenges.

Consumers may view products as risky for a number of reasons. For example, a consumer may be uncertain regarding whether or not a product will perform as expected, which poses financial, functional and even physical risk (e.g., Dowling & Staelin, 1994). As another example, consumers may be uncertain of whether or not using a product would trigger the desired social response (i.e., social risk). Regardless of the source of uncertainty, it has been empirically shown that perceived product risk negatively affects consumers’ perceived product value and thus lowers purchase likelihood (Agarwal & Teas, 2001; Chang & Hsiao, 2008; Snoj, Korda & Mumel, 2004). This is not particularly surprising as perceived risk is one of the key factors among the non-monetary costs which consumers carefully consider when making their purchase decisions (e.g., Kumar & Grisaffe, 2004; Pappas, 2016). On these premises, various studies have investigated ways to reduce risk perceptions by increasing brand familiarity (Morgan-Thomas & Velotsou, 2013) or product knowledge (Nepomuceno, Laroche & Richard, 2014), as well as by providing quality assurance (Yeung, Yee & Morris, 2010). Such remedies have helped offset, at least in part, the negative effects of perceived risk on perceived customer value and purchase intentions. However, they have failed to account for the positive role of brand trust in mitigating uncertainty while enhancing product assessment and purchase intentions (Beneke, Flynn, Greig & Mukaiwa, 2013; Pappas, 2016), as well as the overall confidence in the consumer-brand relationships (Kim, Donald & Rao, 2008; Li, Jiang & Wu, 2014).

In this article, we seek to address this gap by investigating the role of brand trust in the relationship between customers’ perceived product risk and their perceived product value. Importantly, to effectively guide the marketing strategy of risky products, we not only investigate brand trust as a unitary concept but also explore whether and how specific trusting beliefs (i.e., benevolence, integrity and competence; McKnight, Choudhury & Kacmar, 2002) may differentially impact the relationship between perceived risk and perceived value. Two studies provide empirical evidence suggesting that (a) the trust customers have for a brand can in fact mitigate the negative effects of perceived product risk on perceived product value, but (b) only two of the three trusting beliefs identified in prior literature (benevolence and integrity) have a positive impact on perceived value of risky products. Contributing to theory, the latter finding suggests that trusting beliefs differ not only in their antecedents but also in their substantive implications. Informing marketing strategy, these findings also provide managers with guidance on specific trusting beliefs that ought to be cultivated to create value for their customers when those customers perceive high level of product risk.

In the sections that follow, we first review the relevant research and develop our research hypotheses. Then, we report two empirical studies that utilize an online survey method to test the hypotheses using a sample of randomly selected smartphone users from a larger national sample. Last, we discuss the theoretical and managerial implications of our findings, noting the limitations of the research and identifying future research opportunities.

Perceived Risk and Customer Value

Perceived product risk can be defined as a subjective expectation of loss (Nepomuceno et al., 2014; Peter & Ryan, 1976) and various studies have shown that it is central to consumers’ evaluation and purchasing behaviour (e.g., Pippas, 2016). For example, when perceived product risk is high, consumers are more likely to compare alternatives and ask friends and relatives for advice before purchasing a product (Boze, 1987). Perceived product risk has been conceptualized as having two dimensions, namely, uncertainty and negative consequences (Cunningham, 1967), both associated with product performance below consumer expectations (Biswas & Burman, 2009; Wang, 2015).

Various studies have investigated the effects of perceived risk on perceived customer value. The latter has been defined as the customers’ overall assessment of a product or a service based on their perception of what is received and what is given (Boksberger & Melsen, 2011; Holbrook, 1999). While many conceptualizations of perceived product value exist (Kumar & Reinartz, 2016; Ozdilek, 2016), one commonly agreed upon conceptualization is the net trade-off received from all relevant benefits and costs or sacrifices delivered by a product or service and its use (e.g., Smith & Colgate, 2007; Zeithaml, Berry & Parasuraman, 1996). Such value assessment is essentially weighing of the quality and benefits that customers receive against the associated sacrifices and costs (Lepak, Smith & Taylor, 2007; Mencarelli & Riviere, 2015; Zeithaml, 1988). When negative outcomes are likely or when uncertainty is high, perceptions of risk increase, influencing consumers’ assessment of sacrifices and costs and subsequently, leading to deterioration of perceived product value. In line with this reasoning, product risk can be viewed as subjective anticipation of loss, to some extent, as well as the expectation that the product may not offer all of its anticipated benefits, or even have negative and harmful consequences (Sweeney, Soutar & Johnson, 1999).

In light of the importance of risk perceptions for customer assessment of value and purchase intention, a number of risk reduction strategies have been identified in the literature. For example, Yeung and Yee (2003) distinguished a total of 17 risk-reducing strategies including brand loyalty, store image, money back guarantee and the like. Similarly, Yeung et al. (2010) suggest that offering information and quality assurance may reduce risk perceptions. In recent years, brand-related factors, such as increasing brand knowledge and familiarity (Morgan-Thomas & Veloutsou, 2013; Nepomuceno et al., 2014), have also been identified as effective risk-reducing strategies (Yeung et al., 2010), because of their positive effect on customers’ perceived value and purchase intentions. Surprisingly, however, and to the best of our knowledge, one important factor has not been investigated in this context—that is, brand trust. To address this gap, we next discuss the role of brand trust in the perceived risk–value relationship and develop our hypotheses.

The Role of Brand Trust

Service research has long since acknowledged that ‘effective service marketing depends on the management of trust because customers typically must buy a service before experiencing it’ (Berry & Parasuraman, 1991, p. 144). Similarly, in retailing, trust has been the basis for loyalty (Zeithaml et al., 1993). Given its importance for creating long-term relationships with customers, especially for high-risk/uncertainty cases (Kim et al., 2008), we can reasonably anticipate that the trust customers have in brands may have the potential to help those brands reduce the risk perception for their products. However, to our best knowledge, there is no systematic investigation of how to effectively mitigate the negative consequences of perceived product risk through brand trust.

Trust is one of the most important components of relationship marketing (Morgan & Hunt, 1994). It is defined as willingness to rely on an exchange partner in whom one has confidence (Kim et al., 2008; Moorman, Deshpande & Zaltman, 1993). It implies accepting the vulnerability on the grounds of positive expectations about the intentions or behaviour of a partner in a situation characterized by interdependence and risk (Moorman et al., 1993). Many researchers have argued that trust is a crucial enabling factor, especially in relations where there is uncertainty, information asymmetry and fear of opportunism (Buttner & Goritz, 2008; McKnight et al., 2002). By decreasing uncertainty, trust is indeed seen as a control mechanism that facilitates exchange relationships characterized by uncertainty, risk and vulnerability (Hong & Cha, 2011; Li et al., 2014; Morgan & Hunt, 1994). On these premises, we propose that brand trust can be used by customers as an important cue to reduce perceived risk and thus attenuate its negative effects on perceived value.

Particularly, when perceived product risk is high, individuals with limited information and/or taxed cognitive resources seek to reduce perceived risk and uncertainty by applying mental shortcuts (Grabner-Kraeuter, 2002; Li et al., 2014). We suggest that one such mental shortcut is brand trust, which serves to reduce uncertainty and expectations of negative consequences created by perceived risk (Kabadayi, 2016). By decreasing perceived product risk, trust positively affects consumers’ attitudes which subsequently influence behavioural intentions (Pappas, 2016; Pavlou, 2003; Yousafzai, Pallister & Foxall, 2005, 2009). Indeed, individuals with high levels of brand trust tend to assume that the trusted brand will do its best to reduce any negative and harmful consequences that may be created by the same factors which initially caused the brand to be perceived as highly risky. In other words, trust may provide assurance to individuals about future interactions with the same brand despite having problems with its products. Such assurance reduces the uncertainty related to using otherwise high-risk products, and thus, the presence of trust weakens the negative effect of product risk on perceived value of the same products. Formally, we hypothesize:

HYPOTHESIS 1: Customers’ trust in a brand weakens the negative relationship between perceived product risk and the perceived value of that brand’s product.

The Individual Effects of Trusting Beliefs

Although trust was treated as a unitary concept in earlier literature, later researchers have come to an agreement that trust is a multidimensional construct with two inter-related components—trusting beliefs (i.e., perceptions of trustworthiness of a partner) and trusting behaviour—that is, one’s willingness to depend upon and make oneself vulnerable to a partner (Mayer, Davis & Schoorman, 1995; McKnight et al., 2002; Rousseau, Sitkin, Burt & Camerer, 1998). Trusting beliefs are the trustor’s cognitive beliefs that result from observing the trustee’s actions, and attributing the causes of the behaviour to the trustee’s internal trust-related characteristics (Komiak & Benbasat, 2004; McKnight & Chervany, 2001); they are the trustor’s perception that the trustee possesses characteristics and attributes that are beneficial to the trustor (McKnight & Chervany, 2001). Thus, trusting beliefs collectively represent a sentiment or expectation about an exchange partner’s trustworthiness (Moorman et al., 1993). While various trusting beliefs have been identified in the literature, general agreement has been reached on the three focal underlying beliefs: benevolence, integrity and competence (McKnight et al., 2002). These three trusting beliefs are related, yet distinct. Each belief captures some unique elements of trustworthiness. Therefore, taken together, competence, benevolence and integrity appear to largely explain trustworthiness while maintaining parsimony (Mayer et al., 1995). For example, in a smartphone setting, an individual may believe that a brand cares about its customers and intends to deliver a high-quality product (i.e., the brand is benevolent), but they may also believe that it lacks the skills and ability to do so (i.e., the brand is not competent) (Schlosser, White & Lloyd, 2006). Therefore, it is possible for a consumer to have mixed trusting beliefs with respect to the same brand, such that, for example, a brand is believed to be low on benevolence and high on integrity and competence. If instead all three trusting beliefs are consistently strong, a smartphone brand is deemed quite trustworthy. However, trustworthiness should be thought of as a continuum, rather than the trustee being either trustworthy or not trustworthy.

Benevolence beliefs imply that the trusted party will not act opportunistically against the trustor, even when given the opportunity. As such, they represent the extent to which one party is genuinely interested in the other partner’s welfare and is motivated to seek joint gain rather than maximizing his own profit (Doney & Cannon, 1997, p. 36). In the smartphone context, benevolence beliefs reflect the confidence that a brand has a positive orientation towards its customers beyond an egocentric profit motive (Mayer et al., 1995). This belief translates into a perception that beyond pursuing profitability, the brand cares about its customers and their well-being. Therefore, a benevolent brand would not be perceived to act opportunistically by taking advantage of its customers (Kabadayi, 2016; McKnight & Chervany, 2001). Such benevolent beliefs assure consumers that the brand would not do anything knowingly to harm them, and that even in the presence of risky products, the same brand would do whatever it takes to protect them. Consumers with benevolence beliefs also believe that, despite the past problem with their smart phones, if another problem arose, the brand would go out of its way to help them and would not let them suffer even at a loss for the brand. Finally, because of such benevolent beliefs, consumers feel assured that the brand would make sure that the reasons for high-risk perception would be eliminated to avoid similar problems and risky products in the future. Thus, benevolence beliefs provide a peace of mind about future transactions with the same smartphone brand even in the presence of high-risk products. By doing so, they mitigate the negative effect of perceived risk on customers’ perceived value. Therefore, we hypothesize:

HYPOTHESIS 2: Customers’ benevolence belief about a brand weakens the negative relationship between perceived product risk and the perceived value of that brand’s product.

Integrity beliefs embody the notion that one partner adheres to a set of moral principles or professional standards that guide his interactions with his partners. In the smartphone context, they imply that a brand acts in accordance with widely accepted standards of honesty or a set of accepted principles to guide its overall business practices, to fulfil promises and to provide accurate information (Mayer et al., 1995). If customers believe that a smartphone brand follows socially accepted principles, such as not telling a lie or deceiving its customers, then these integrity beliefs reassure the customer that the brand would provide correct information even if a problem occurred with one of its products (i.e., smartphones). Similarly, customers, who hold integrity beliefs about a brand, trust that the brand would not hide the truth or lie about potential problems with using their smartphones or any related security hazard. They also believe that the brand would share information with them without hesitation and that it would not try to deceive them. Because of their integrity beliefs, therefore, customers are convinced that even in the presence of high-risk products, the brand would take any necessary steps using ethical guidelines to provide solutions to those affected by such products. Furthermore, they believe that the brand would share the truth about the status of its products and would not consider selling the same products without resolving the problem that created the risk in the first place. Therefore, when consumers make value assessment for products of brands they trust with integrity, the weight of their original risk perception on such assessment diminishes. Thus, our next hypothesis is:

HYPOTHESIS 3: Customers’ integrity belief about a brand weakens the negative relationship between perceived product risk and the perceived value of that brand’s product.

Competence beliefs are based on one party’s confidence that another party has the ability or power to do the job (Mayer et al., 1995). In the smartphone context, they would refer to individuals’ convictions that their smartphone brand has the necessary skills, resources and technical capabilities to create and deliver high-quality products in a satisfactory way. As a result of their competence beliefs, consumers are convinced that even though a brand has some high-risk products, it still has the ability and resources to deliver quality products with no faults or risks. They may perceive the presence of such high-risk products as a one-time anomaly, rather than a standard case for that brand (Kabadayi, 2016). Therefore, because of such competence beliefs, they may discount the effect of such high-risk products on their overall value assessment with the conviction that the brand will continue to offer high-quality products in the future as it has the required resources and capabilities to do so. In other words, this belief should lessen the negative effects of perceived risk on perceived value. Therefore, our final hypothesis is:

HYPOTHESIS 4: Customers’ competence belief about a brand will effectively weaken the negative relationship between perceived product risk and the perceived value of that brand’s product.

Study 1

The purpose of Study 1 was to test H1, that is, whether or not customers’ trust in a brand mitigates the otherwise negative effect of perceived product risk on perceived product value in the context of cellular phones. Once again, cellular phones were chosen due to recent recalls in this product category and, thus, greater perceived risk is associated with cellular devices.

Participants and Procedure

Totally, 178 individuals participated in this online study using MTurk online survey service. Given the technical problems and massive product recalls that Samsung Galaxy smartphones have had in recent years, we chose the smartphone as the setting for our studies. Participants were first asked whether they owned a smartphone or not to ensure that they qualified to answer the survey questions. Ninety-seven per cent of the respondents confirmed that they indeed owned a smartphone and thus 173 participants were included in our study. The sample was 51.2 per cent female with an average age of 37.5, which is reflective of the US population per the US Census. Almost 46 per cent of the sample owned an Apple I-Phone while 43 per cent owned a Samsung phone, and the remainder owned other brands, such as LG or Motorola.

Measures

This study adopted existing scales to measure the participants’ perceived product risk, perceived value and brand trust (see Table 1 for scale items, reliabilities and respective loadings). All items were measured using 5-point Likert scales with (1) being ‘strongly disagree’ and (5) being ‘strongly agree’. Three control variables were also included: frequency of smartphone usage, perceived difficulty to switch to another smartphone brand and length of participants’ relationship with their current smartphone brands in terms of years. Finally, questions were asked pertaining to participants’ demographic profile.

Table 1.

Scale Items, Reliabilities and Item Loadings

	Factor Loadings
Items and Cronbach Alphas	1st study	2nd study
Perceived Product Risk (a = 0.90, 0.89)*
I think using a smartphone can be risky.	0.89	0.88
Using a smartphone may have a bad effect on my health.	0.91	0.87
I am aware of smartphone’s safety risks.	0.90	0.89
Smartphones may cause me physical harm.	0.87	0.86
Using a smartphone may not be safe for me.	0.91	0.90
Perceived Smartphone Value (a = 0.86, 0.87)
My smartphone provides a valuable service to its users.	0.85	0.86
My smartphone provides a better value for money for its users compared to other phones.	0.87	0.89
My smartphone provides services that I need.	0.84	0.85
My smartphone provides a good value given the price I paid for it.	0.88	0.88
Trust in Smartphone Brand (a = 0.88, 0.90)
I trust my smartphone brand.	0.87	0.91
My smartphone brand is trustworthy.	0.88	0.90
My smartphone brand is reliable.	0.89	0.88
My smartphone brand can be trusted at all times.	0.88	0.90
Benevolence Beliefs (a = 0.85)
My smartphone brand seems concerned about its customers’ welfare.		0.83
My smartphone brand would not knowingly do anything to hurt its customers.		0.84
My smartphone brand appears to go out of its way to help its customers.		0.85
I believe that my smartphone brand would act in its customers’ interests.		0.85
My smartphone brand is not only interested in its own well-being.		0.83
Integrity Beliefs about Banks (a = 0.86)
My smartphone brand seems to have a strong sense of justice.		0.87
My smartphone brand appears to be fair in dealing with its customers.		0.86
Sound principles seem to guide my smartphone brand’s actions.		0.86
I would characterize my smartphone brand as honest.		0.87
My smartphone brand seems to keep its commitments.		0.84
Competence Beliefs about Banks (a = 0.87)
My smartphone brand seems very capable of serving its customers.		0.86
My smartphone brand seems to have necessary knowledge and resources to fulfil its customers’ needs.		0.95
I feel very confident about my smartphone brand’s skills to serve its customers.		0.88
My smartphone brand seems to be competent and effective.		0.88
My smartphone brand performs its role very well.		0.86

Source: Authors’ own.

Note: * First number denotes Study 1; second number denotes Study 2.

The measurement properties of the constructs were evaluated in a confirmatory factor analysis using LISREL 9.1. The model fit was assessed using a series of indices suggested by Gerbing and Anderson (1992) and Hu and Bentler (1999), including a goodness of fit index (GFI), a comparative fit index (CFI) and the root-mean-square error of approximation (RMSEA). The results showed that all indexes met or exceeded the critical values for acceptable fit (c2 = 237.59, df = 142, p < 0.01, CFI = 0.94, GFI = 0.95, RMSEA = 0.06), suggesting a satisfactory fit for the measurement model tested (Table 2).

All the factor loadings were highly significant ( p < 0.001), which showed unidimensionality of the measures (Gerbing & Anderson, 1992). A reliability test was performed for each construct to see if all the measures demonstrated satisfactory coefficient of reliability. All Cronbach alphas of the constructs were above 0.70. Thus, the measures demonstrated adequate convergent validity and reliability.

Table 2.

Correlations and Descriptive Statistics (Study 1)

	1	2	3
1. Perceived product risk	1.00
2. Perceived smartphone value	-0.27*	1.00
3. Trust in smartphone brand	-0.11	0.31*	1.00
Mean	3.47	3.86	4.03
Standard deviation	1.05	0.92	0.75
Average variance extracted	0.59	0.61	0.63
Highest shared variance	0.11	0.13	0.10

Source: Authors’ own.

Note: * Significant at 0.01 level.

Analysis and Results

In order to test the first hypothesis, a hierarchical moderated regression (HMR) was performed where perceived customer value was the dependent variable. Following Aiken and West (1991), all the variables were mean centred to minimize the threat of multi-collinearity between the interaction terms and their components in equations where we included the interaction terms. A possible multi-collinearity among the variables was tested by calculating the variance inflation factor (VIF) for each of the regression coefficients. The VIF values (lowest = 1.92; highest = 5.46) were well below the cut off of ten.

In Step 1, only the three control variables were entered into the regression model. In Step 2, the main effects of individuals’ perceived product risk and their overall trust in their smartphone brands were entered along with the control variables. Finally, in Step 3, the interaction effect between perceived risk and their brand trust was entered along with the control variables and the main effects. Evidence of the interaction effect would exist if the interaction term accounted for a significant incremental variance in explaining consumers’ perceived product value, either individually, as manifested by beta values, or collectively, as revealed by the values of the incremental F-statistic.

As shown in Step 1 (Table 3), both length of the relationship with their smartphone and the frequency of smartphone usage had significant relationships with the dependent variable, while the other control variable had no such significant relationship. Next, Step 2 provided a significant increase in variance explained over Step 1 (ΔR² = 0.132, p < 0.01). Perceived product risk ( β = -0.20, t = -2.419) had a significant negative relationship with customers’ perceived value of their smartphones. In other words, the higher the risk perceived the lower the product value perceptions. This finding provided further empirical support for the existing literature. In addition, trust in the smart phone brand ( β = 0.17, t = 1.803, p < 0.01) was found to be positively and significantly related to participants’ perceived value of smartphones.

Table 3.

Hierarchical Moderated Regression Analysis Results (Study 1) (Dependent Variable: Perceived Smartphone Value)

	Step 1		Step 2		Step 3
Variables	b	t-value	b	t-value	b	t-value
Controls
Frequency of smartphone usage	0.118	1.101**	0.094	0.934	0.088	0.872
Difficulty of switching to another smartphone	-0.081	-0.797	-0.073	-0.719	-0.059	-0.601
Length of using the same smartphone/years (log-transformed)	0.101	1.037**	0.096	0.955	0.082	0.806
Main Effects
Perceived Product Risk (1)			-0.231	-2.409*	-0.182	-1. 843*
Trust in Smartphone Brand (2)			0.173	1.803*	0.148	1.407*
Interactions
1 x 2					-0.196	-2.004*
R2		0.074		0.206		0.387
F		0.776		19.846*		38.435*
D R2				0.132		0.181

Source: Authors’ own.

Note: * Significant at <0.01 level and ** Significant at <0.05 level.

The two-way interaction hypothesis (H1) was tested by examining the incremental variance explained by Step 3 over Step 2. As shown in Table 3, the addition of the two-way interaction of perceived risk and brand trust increased R² by 18.1 per cent in Step 3 over Step 2. More specifically, the interaction (β = -0.20, t = -2.004, p < 0.01) was negatively and significantly related to consumers’ perceived value of smartphones.

Study 1 findings, thus, provide support for our first hypothesis. Particularly, we show that while customers are likely to perceive lower value when the product risk is high, their overall trust in the brand moderates this relationship. However, the first study, like many others, treats trust as a unitary concept. As discussed earlier, more recent studies suggest that trust, in fact, has multiple dimensions, or trusting beliefs, and interestingly, different trusting beliefs have been shown to have differential effects on outcome variables in different contexts (Kabadayi, 2016; Kabadayi & Kachersky, 2012). Therefore, in Study 2, we examine the individual effects of such trusting beliefs on the relationship between customers’ perceived risk and their value perceptions created by those high-risk products.

Study 2

Building on Study 1 findings, the purpose of Study 2 is to test our predictions regarding the individual moderating effects of the three brand-specific trusting beliefs—benevolence, integrity and competence—on the negative relationship between perceived product risk and product value (H2–H4).

Participants and Procedure

Similar to the first study, a sample of 258 smartphone users participated in the second online study using MTurk. The sample was 52 per cent female, with an average age of 38.3. The same scales used in Study 1 were used in this study to measure the participants’ perceived product risk and value of their smartphones. In addition to the items included in Study 1, individuals’ benevolence, integrity and competence beliefs about brands were measured using the existing items adopted from similar studies (e.g., Kabadayi & Kachersky, 2012). For all items, 5-point Likert scales were used with (1) being ‘strongly disagree’ and (5) ‘strongly agree’.

The results of confirmatory factor analysis suggested a satisfactory fit for the measurement model. All indices met or exceeded the critical values (c2 = 416.87, df = 212, p < 0.01, CFI = 0.94, GFI = 0.96, RMSEA = 0.07). The factor loadings were highly significant, showing unidimensionality of the measures (Gerbing & Anderson, 1984). Also, the path coefficients (loadings) for each latent factor to its manifest indicators pointed to the convergent and discriminant validity of the measures. A reliability test revealed satisfactory coefficient of reliability; all Cronbach alphas of the constructs were above 0.70. Thus, the measures in this study demonstrated adequate convergent validity and reliability as well (Table 4).

Table 4.

Correlations and Descriptive Statistics (Study 2)

	1	2	3	4	5
1. Perceived product risk	1.00
2. Perceived smartphone value	−0.24*	1.00
3. Benevolence beliefs about smartphone brand	−0.09	0.21*	1.00
4. Integrity beliefs about smartphone brand	−0.08	0.23*	0.39*	1.00
5. Competence beliefs about smartphone brand	−0.04	0.12**	0.27*	0.28*	1.00
Mean	3.39	3.89	3.90	4.05	4.02
Standard deviation	1.32	1.10	0.97	0.89	0.91
Average variance extracted	0.51	0.55	0.62	0.59	0.57
Highest shared variance	0.10	0.09	0.10	0.12	0.10

Source: Authors’ own.

Note: * Significant at 0.01 level and ** Significant at 0.05 level.

Analysis and Results

An HMR analysis was conducted to test the individual moderating effects of three trusting beliefs. All the variables were mean centred to minimize the problem of multi-collinearity between the interaction terms and their components in equations where we included the interaction terms. The VIF values (lowest = 2.43; highest = 5.37) were well below the cut off of ten.

Table 5 shows the findings of the HMR analysis with individuals’ perceived value of their smartphones as the dependent variable. The same procedure as in Study 1 was repeated. This time, in Step 3, the two-way interaction effects between three trusting beliefs and perceived product risk were entered along with the control variables and the main effects.

Table 5.

Hierarchical Moderated Regression Analysis Results (Study 2) (Dependent Variable: Perceived Smartphone Value)

	Step 1		Step 2		Step 3
Variables	b	t-value	b	t-value	b	t-value
Controls
Frequency of smartphone usage.	0.112	1.093**	0.090	0.902	0.083	0.787
Difficulty of switching to another smartphone.	-0.083	-0.829	-0.079	-0.801	-0.072	-0.697
Length of using the same smartphone/years (log-transformed).	0.106	1.076**	0.094	0.941	0.089	0.891
Main Effects
Perceived product risk (1)			-0.186	-1.932*	-0.143	-1.408*
Benevolence beliefs about smartphone brand (2)			0.146	1.439*	0.083	0.827
Integrity beliefs about smartphone brand (3)			0.162	1.611*	0.090	0.905
Competence beliefs about smartphone brand (4)			0.094	0.953	0.069	0.701
Interactions
1 x 2					-0.185	-1.843*
1 x 3					-0.203	2.015*
1 x 4					-0.087	0.911
R2		0.081		0.234		0.429
F		0.904		24.107*		41.781*
D R2				0.153		0.195

Source: Authors’ own.

Note: * Significant at <0.01 level and ** Significant at <0.05 level.

The results showed that Step 2 provided a significant increase in variance explained over Step 1 by 15.3 per cent (p < 0.01). Consistent with Study 1, perceived product risk had a significant negative relationship with perceived value of smartphones ( β = -0.19, t = -1.932, p < 0.01), providing further support for findings reported in the literature. In terms of the main effects of individuals’ three trusting beliefs about their smartphone brands, the findings indicate that both benevolence beliefs ( β = 0.15, t = 1.439) and integrity beliefs ( β = 0.16, t = 1.611) had significant positive relationships, while competence beliefs did not have such a significant relationship ( β = 0.09, t = 0.953).

The two-way interactions were tested by observing the incremental variance explained by Step 3 over Step 2. As shown in Table 5, the addition of the two-way interactions between competence, integrity and benevolence beliefs and perceived product risk increased R² by 19.5 per cent in Step 3 over Step 2 (p < 0.01). More specifically, the interaction between benevolence belief and perceived risk ( β = -0.19, t = -1.843, p < 0.01) and the interaction between integrity belief and perceived risk ( β = -0.20, t = -2.015, p < 0.01) were both negatively and significantly related to customers’ perceived value of their smartphones, thus confirming H2 and H3, respectively. However, contrary to H4, the interaction between competence belief and perceived risk did not have a significant relationship with the dependent variable ( β = -0.09, t = -0.911, n.s.).

Our findings offer a partially unexpected, but an interesting insight, which extends theory and has important implications to marketers. The results suggest that while benevolence and integrity beliefs participants hold about their smartphone brand lessen the negative effect of perceived product risk on perceived value of the smartphones, competence beliefs have no such significant effect. In other words, the extent to which consumers believed that the brand would not act opportunistically against them, or that it adhered to a set of moral principles or professional standards, significantly impacted the effect of product risk on product value perceptions. However, the extent to which consumers were confident in the brand’s ability and competences did not impact the relationship between perceived risk and value.

Discussion and Theoretical Implications

This research investigates the relationship between consumers’ perceived product risk, value perceptions and trust towards the brand. Across two studies, we show that while perceived product risk may be detrimental to consumers’ perceptions of value, brand trust may lessen the negative effect of risk on value created by those products. Furthermore, our findings suggest that the various beliefs underlying trust have differential effects. Particularly, while competence beliefs were found irrelevant to the effects of risk on value, brand-specific beliefs of benevolence and of integrity effectively mitigated the otherwise negative influence of perceived product risk on its value. Although not directly tested in the present research, a possible explanation for why competence beliefs did not significantly impact the effect of product risk on value perceptions might be primarily related to the very nature of competence beliefs and of the product category (technology). In the smartphone context, competence beliefs refer to individuals’ convictions that their smartphone brand has the necessary skills, resources and technical capabilities to create and deliver high-quality products in a satisfactory way. Recent research suggests that such beliefs have a stronger influence on purchase decisions as compared to beliefs in a brand’s integrity and benevolence and instead matter less on post-purchase perceptions (i.e., satisfaction; Xu, Cenfetelli & Aquino, 2016). This should be particularly true in the context of smartphones where the technological and complex nature of the product requires relatively high levels of trust in the brand’s competence for a purchase decision to be made. Thus, competence beliefs may carry a stronger weight on purchase decisions and, as a result, they might be strongly held for them to significantly vary and thus impact post-purchase (value) perceptions, despite the effects of risk. In addition, even if competence beliefs were to vary in the post-purchase phase, consumers may be more willing to tolerate brands for their incompetence than for their lack of integrity or benevolence for products which are infrequently purchased (Xu, Cenfetelli & Aquino, 2016). In fact, violations of integrity or of benevolence, such as misrepresentations of product features, or failing to keep a promise, not only cause consumers to experience negative emotions (Tranfinow, Bromgard, Finlay & Ketelaar, 2005), they also are much harder to tolerate, because of the perceived intentional nature of such violations (Xu, Cenfetelli & Aquino, 2016), even more so when perceived risk is high. The distinct effects of competence beliefs are also consistent with McKnight et al.’s argument (2002) that competence beliefs appear as the most unique of the three trusting beliefs.

By shedding light on the relationship among perceived risk, perceived value and brand trust, this article makes several contributions. First, we contribute to the consumer behaviour literature by turning a simple, main effect of perceived risk on perceived value into a more insightful, conditional relationship (Featherman & Fuller, 2003). More specifically, while a number of studies have investigated risk-remediating strategies (e.g., providing quality assurance, increasing brand familiarity or product knowledge; Morgan-Thomas & Velotsou, 2013; Nepomuceno et al., 2014; Yeung et al., 2010), they have not accounted for important boundary conditions to the effects of perceived risk on perceived value, such as consumers’ brand trust. Not only does trust directly impact consumers’ overall evaluations and purchase intentions (Beneke et al., 2013; Pappas, 2016), it is also a crucial component of long-term customer relationships. This is particularly true for relationships characterized by uncertainty and/or risk (Kim et al., 2008; Li et al., 2014), thus making it especially worthy of investigating.

Second, we contribute to research on value creation by investigating the role of the various components of trust, and by showing that a deeper understanding of the relationship between risk and value is possible when consumers’ trusting beliefs of benevolence and integrity (but not competence) are accounted for. Hence, we demonstrate that the three trusting beliefs have differential roles in the product risk–value perception relationship, providing empirical support for the position that trusting beliefs should be considered separately (McKnight et al., 2002). Last, marketing researchers have highlighted a variety of contexts in which trust plays a fundamental role, from facilitating monetary transactions (Kim, Ferrin & Rao, 2009), to creating and maintaining successful consumer–brand relationships. Yet, to the best of our knowledge, we are the first to assess its role in the relationship between product performance risk and value perception.

Managerial Implications

Given the important role of consumers’ brand trust in mitigating the negative effects of risk on value perceptions, our findings suggest that managers ought to adopt more proactive strategies to build and manage trust perceptions. Particularly, our results indicate that if high risk of unsatisfactory product performance is perceived, consumers’ brand-related beliefs of integrity and of benevolence may lessen the negative impact of risk on value perception; thus, managers should strive to instil these specific beliefs. Cultivating and protecting a brand’s integrity and benevolence might be a multifaceted process, incorporating a variety of different practices. We suggest that these practices fall into one of the two groups, either focused on the product and brand, or focused on the organization as a whole.

As part of the first group of implications, to enhance the project brand integrity, we recommend managers engaging in a number of activities centred on delivering products that are in line with the brand’s core value. For example, Nestlé recently decided to remove artificial flavours and certified colours such as Red #40 from more than 250 products (e.g., Butterfinger, Crunch), thus significantly altering the composition of its flagship brands in the name of integrity. Engaging in activities that reflect a brand’s core value of integrity, and keeping the public informed on a regular basis through relevant communication channels may be of particular value when the brand faces a crisis due to high-risk perceptions and possible product recalls. To inspire benevolence beliefs, which suggest that the brand adheres to a set of moral principles or professional standards, managers will have to primarily cultivate the brand’s image and reputation, including its ethical standards and social responsibility. For example, credible communication pointing to a ‘sincere’ brand personality (Aaker, 1995) might contribute to shaping benevolent brand-related beliefs. This is important as our findings indicate that in the case of high-risk products, consumers’ benevolence beliefs weaken the perception of high risk on their value assessment for that brand’s products. In fact, Chernev and Blair (2015) show that knowing that a company has behaved ethically can cause customers to perceive that the company’s products also perform better and, in general, to experience the product in a different, more positive way. Therefore, even when hit by-product recalls and/or high-risk perceptions about its products, brands can still benefit from the positive value assessment for their products due to the brand-related benevolence beliefs.

As part of the second group of practices (i.e., those focused on the organization as a whole), to inspire integrity, managers should pursue consistency across the company’s practices and communications. Thus, all products should be managed consistently with the firm’s core value in focus. For example, Dove’s core brand value ‘Be your beautiful self’ is consistent with a number of activities the company runs such as helping millions of teenagers build their self-esteem. Similarly, in 2014, CVS company decided to interrupt the (US $2 billion annual) sales of harmful tobacco products as this was inconsistent with its goal of being a trusted health provider (Hall, 2015). These types of initiatives, indeed, strengthen the integrity beliefs thus weakening potential negative effects of risk on perceived product value. As part of other organization-focused practices to inspire benevolence, managers might have to be particularly open and honest in their communications with consumers. For example, consider AT&T’s response to recent complaints about its high-speed wireless coverage in the USA. Following some issues with its network’s ability to handle calls in heavily populated areas such as New York, AT&T admitted these limitations to the public and pointed to its efforts and plans to ensure an improved service in the future, thus undermining its competence in favour of both its integrity and benevolence. So, while the initial coverage issue might have created some heightened risk for some users, companies’ efforts to create trusting beliefs prevent its customers from developing negative value perceptions. Such actions should bolster consumers’ trust in the brand. Finally, as benevolence is more difficult to attain, managers should place a greater emphasis on hiring contact personnel that consider and are sensitive to the needs and interests of consumers, so that firms can increase value perceptions, especially in cases where product risk is high.

Future Research

While this article makes some interesting and relevant contributions, it also has limitations that future studies can address. First, given the nature of the product, that is, smartphones, we use exchange-value conceptualization of customer value. While we believe that our results may hold for value-in-use conceptualization as well, future studies may want to empirically test this assumption, especially in the context of high-risk services.

Second, in our studies, we use perceived value as the main dependent variable of interest and essentially focus on the product evaluation phase of the consumer decision process. Future researchers may also want to investigate which trusting beliefs matter most across other phases of the decision-making process. For example, when searching for information, beliefs of competence might be particularly important for consumers weighing the information they are exposed to.

Finally, while we have shown that competence beliefs do not matter as much as those of benevolence and of integrity in moderating the effects of performance risk on value perception, future research might explore whether these effects are further moderated by the presence (versus absence) of another type of risk (i.e., social risk).

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