Understanding Trust in Financial Services

Abstract

Although the financial crisis has elevated the interest for factors such as consumer financial healthiness, broad-scope trust, financial knowledge, and consumer relationship satisfaction, no existing model describes how these factors may influence consumer financial relationship trust. This research extends prior research by developing a conceptual framework explaining how these constructs affect consumers' trust in their financial service provider. Based on two surveys comprising 764 pension consumers and 892 mortgage consumers, respectively, the results of this study indicate that financial healthiness, broad-scope trust, knowledge, and satisfaction positively affect narrow-scope trust in financial services. Furthermore, it is found that broad-scope trust negatively moderates the relationships between financial healthiness and narrow-scope trust and between satisfaction and narrow-scope trust, respectively. In addition, the results marginally indicate that broad-scope trust negatively moderates the relationship between consumer financial knowledge and narrow-scope trust. This study encourages public policy makers, consumer organizations, and financial service providers to continue, improve, and/or develop consumer financial education programs and also encourages consumers to participate in such programs. This is especially important when broad-scope trust is low. Also, when broad-scope trust is low, financial service providers should consider devoting additional resources in satisfying their customers and/or in improving their financial healthiness.

Keywords

financial services financial healthiness broad-scope trust financial knowledge satisfaction narrow-scope trust

As one of its many serious outcomes, the global financial crisis has led many to believe that the relationships between customers and financial service providers have become badly damaged. For instance, recent research and commentaries have suggested that “financial services providers are struggling to maintain consumer trust” (Costa 2010) and that “the economic crisis of 2008 led to a loss in confidence in financial institutions” (Uslaner 2010, p. 110). In this article, we argue that consumers' financial knowledge, financial healthiness, trust in the financial services industry as a whole, and satisfaction with their financial service provider are key concepts for explaining consumers' trust in a financial service provider. However, even though researchers have long acknowledged the importance of such factors for the understanding of consumer financial service behavior (e.g., Grayson, Johnson, and Chen 2008; Hogarth and Hilgert 2002; Howlett, Kees, and Kemp 2008; Joo and Grable 2004; Perry and Morris 2005; Xiao, Tang, and Shim 2009), no existing model describes how these factors may influence consumer financial relationship trust. This is unfortunate since a better understanding of the relationships between such factors and consumers' trust in their financial service provider may assist financial service providers in managing their financial services and may also assist financial authorities and public policy makers in facilitating well-functioning financial markets.

Trust is believed to be among the most critical variables for developing and maintaining well-functioning customer–seller relationships (Eisingerich and Bell 2007; Johnson and Selnes 2004; Morgan and Hunt 1994; Selnes and Sallis 2003). However, although past research (e.g., Driscoll 1978; Scott 1980) suggests that trust not only relates to consumer trust in individual companies but also relates to the broader business context in which consumers may plan and carry out their financial behavior; only one previous study (i.e., Grayson, Johnson, and Chen 2008) has empirically considered this distinction in a marketing context. In the present study, two kinds of trust are specified: narrow-scope trust and broad-scope trust. Following Sirdeshmukh, Singh, and Sabol (2002), narrow-scope trust can be defined as “the expectation held by the customer that the service provider [i.e., the specific financial institution] is dependable and can be relied on to deliver on its promises” (p. 17). Based on this definition, we define broad-scope trust as the expectation held by the consumer that companies within a certain business type are generally dependable and can be relied on to deliver on their promises.

No research has yet examined how broad-scope trust relates with consumer financial knowledge, financial healthiness, and satisfaction in influencing narrow-scope trust. This is an important shortcoming. An understanding of how broad-scope trust may influence narrow-scope trust and how broad-scope trust may moderate relationships between other key constructs and narrow-scope trust is highly beneficial to financial service providers. If moderating effects occur it means that financial services managers should not only consider their own behavior and trustworthiness when seeking to develop trustful relationships with their customers but also that the successfulness of such attempts may be influenced by the trustworthiness of other service providers.

The present research contributes to the service marketing literature by addressing these important shortcomings. Specifically, we find support for the premise that financial knowledge, financial healthiness, broad-scope trust, and satisfaction with their financial service provider significantly influence consumers' trust in a financial service provider. Also, we demonstrate that trustful customer–seller relationships derives not only from the interaction between the two parties, as is typically modeled (Danaher, Conroy, and McColl-Kennedy 2008; Morgan and Hunt 1994) but also from the trustworthiness of the financial context (i.e., broad-scope trust) in which they develop.

Our study is based on two surveys. Survey 1 comprises 764 pension consumers, whereas Survey 2 comprises 892 mortgage consumers. Trust is likely to be especially important in consumer financial behavior because financial service providers have an implicit responsibility for the management of their consumers' funds and the nature of financial advice supplied (Harrison 2003). The remainder of the article is organized as follows. First, the theoretical framework and hypotheses are introduced followed by a review of the methods used to test the hypotheses. Next, the results are presented. Finally, the implications of the findings are discussed and suggestions for future research are provided.

Theoretical Framework and Research Hypotheses

Our theoretical framework is shown in Figure 1. The specification of the hypothesized relationships in the theoretical framework draws primarily on attribution theory (Fiske and Taylor 1991; Tomlinson and Mayer 2009; Weiner 1986, 2000), institutional theory (DiMaggio and Powell 1983; Meyer and Brian 1977; Scott 2004), and consumer choice theory (Jayanti and Burns 1998; Shafir and Tversky 1992; Shiu et al. 2011).

Figure 1.

Conceptual model.

Because there is no comprehensive theory dealing with how financial healthiness, broad-scope trust, knowledge, and satisfaction may affect narrow-scope trust in financial services, we combine several theories to form a more complete picture of how these factors can be expected to influence trust. Specifically, the multitheoretical approach taken in this study recognizes that our framework contains a multifaceted range of variables, including evaluative and personal outcomes such as satisfaction and financial healthiness (i.e., attribution theory is particularly devoted to explaining consumers' evaluation of the causality of outcomes), knowledge (i.e., consumer choice theory may explain how consumers act upon their knowledge), and different levels of trust (i.e., institutional theory).

Although it is acknowledged that also other contextual, relationship, and/or individual constructs (e.g., culture, general economic welfare of the society, relationship communication, consumers' financial expectations, consumers' trust in their own financial behavior, and the like) may potentially influence narrow-scope trust, the constructs included in our framework were selected (a) based on theories suggesting that they can be regarded as key concepts for developing trust in financial service providers, (b) in response to the financial crisis, which has elevated the importance of consumer trust in both individual financial service providers and in financial institutions for the well-functioning of financial markets, (c) because the range of choice available to financial consumers has increased dramatically in recent years (Brennan and Coppack 2008) emphasizing the potential importance of consumer financial knowledge for developing well-functioning customer–seller relationships, and (d) because the financial crisis has evoked an increased focus on the financial healthiness of financial services customers and on their satisfaction with their financial service provider. Financial healthiness is also important since it contributes to financial satisfaction, which ultimately contributes to life satisfaction (Xiao, Tang, and Shim 2009).

Construct Definitions

Consumers' financial healthiness refers to consumers' financial status and the degree to which they have financial adequacy (Xiao, Sorhaindo, and Garman 2006). Financial healthiness can be related to objective circumstances such as income and assets, subjective phenomena such as financial satisfaction or happiness, and/or outcomes such as whether consumers exhibit positive and desirable financial behaviors (Xiao, Tang, and Shim 2009). In line with Joo and Grable (2004) and Perry and Morris (2005), we take an outcome approach and conceptualize financial healthiness as the extent to which the consumer exhibits positive financial behaviors, such as avoiding financial troubles caused by not having enough money and paying credit card bills in full each month. A number of studies have focused on how financial healthiness relates to financial customer–seller relationships. For instance, it has been considered how financial healthiness may guide relationship segmentation and communication, influence customers' need for relationship information and advice, and use of relationship technology (Cameron, Cornish, and Nelson 2006; Hogarth and Anguelov 2004; Lee and Cho 2005). However, no studies known to us have previously considered the relationship between financial healthiness and trust in financial service providers.

While marketing relationship trust (i.e., narrow-scope trust) has been extensively investigated within the relationship marketing literature (e.g., Morgan and Hunt 1994; Sharma and Patterson 2000), broad-scope trust is clearly underresearched. Broad-scope trust can be regarded as “formal” or “informal.” Formal broad-scope trust is the belief that proper impersonal structures are in place to enable one to anticipate a successful future endeavor (McKnight, Cummings, and Chervany 1998). Formal broad-scope trust is also referred to as “system trust,” thereby underlining that it relates to the consumer’s views regarding the formalized regulation of a particular activity system (Grayson, Johnson, and Chen 2008). Informal trust (also referred to as generalized trust; Humphrey and Schmitz 1996) concerns whether the entities in a system can be trusted, regardless of sector or context.

In the theoretical framework, informal trust is considered. This is because informal trust is more directly related to the behavior of companies than formal trust, which also concerns trust in legal rules and public authorities. We conceptualize (informal) broad-scope trust as the expectation held by the consumer that companies within a certain business type are generally dependable and can be relied on to deliver on their promises. This definition is consistent with previous research suggesting that broad-scope trust (or generalized trust) is a generalized expectancy that the promise of a group can be relied upon (Rotter 1980; Siegrist, Gutscher, and Earle 2005).

Narrow-scope trust is being regarded as one of the most critical variables for developing and maintaining well-functioning relationships (Morgan and Hunt 1994; Sharma and Patterson 2000). While a large body of research exists within the concept of narrow-scope trust, with different points of view being advocated, we adapt the often-cited definition proposed by Sirdeshmukh, Singh, and Sabol (2002) and conceptualize narrow-scope trust as “the expectation held by the consumer that the service provider [i.e., the specific financial institution] is dependable and can be relied on to deliver on its promises” (p. 17).

Consumer financial knowledge refers to the body of facts and principles (i.e., information and understanding) accumulated by a consumer (i.e., stored in memory) about a financial domain (Page and Uncles 2004). A distinction can be made between domain-general knowledge (i.e., general knowledge about financial services) and domain-specific knowledge (i.e., knowledge about a specific financial service or range of related financial services; Duncan 2007). This study focuses on domain-specific knowledge. This is because financial services are a very broad term covering a range of different service offerings (i.e., short term/long term, simple/complex, etc.). Hence, by focusing on domain-specific knowledge, we consider the implications of consumers' knowledge for their evaluation of narrow-scope trust, and of other constructs included in this study, given the particular characteristics of services. A distinction can also be made between subjective knowledge which refers to individuals' perceptions of their own knowledge, and objective knowledge which refers to absolute knowledge measured against objective standards (Alba and Hutchinson 2000). In the present research, we focus on subjective (domain-specific) knowledge. This is consistent with past research, which suggests that subjective consumer knowledge is a stronger customer-related motivation than objective knowledge, and which has shown a tendency to prefer subjective knowledge measures (Flynn and Goldsmith 1999).

Satisfaction may be conceptualized as a facet (attribute-specific) or as an overall (aggregate) characteristic. Also, the characteristic can be viewed as transaction-specific (encounter satisfaction) or as cumulative (satisfaction over time). Similar to past relationship and service-related research (Dimitriades 2006; Levesque and McDougall 1996), satisfaction is in the present study conceptualized as an overall, cumulative consumer evaluation of her or his relationship with a financial service provider. Cumulative relationship satisfaction recognizes that customers may rely on their entire experience with a financial service provider when evaluating its performance (Dimitriades 2006).

Hypotheses

We argue that institutional theory can explain how broad-scope trust influences narrow-scope trust. Institutional theory suggests that the processes and structures that are established within a society, or a community, act as authoritative guidelines for social behavior. Social behavior needs to be legitimized by the rules and norms that exist in the social environment (Scott 2004). In a similar vein, Meyer and Brian (1977) argue that institutional rules function as myths, which organizations incorporate in order to gain legitimacy, stability, and enhanced survival prospects. Also, DiMaggio and Powell (1983) suggest that organizations that operate outside of accepted norms in the organizational field face isomorphic pressures. According to DiMaggio and Powell, organizational legitimacy is therefore closely linked with survival. Thus, if trust is common within a business type, it encourages the development of trust in customer–seller relationships suggesting the existence of a positive relationship between broad-scope trust and narrow-scope trust.

The few studies dealing with the relationship between broad-scope trust and narrow-scope trust suggest the empirical validity of institutional theory. Although Kenning (2008) found no significant correlation between general trust and specific trust, Grayson, Johnson, and Chen (2008) found that broad-scope trust positively affected narrow-scope trust. Consistent with this finding, Pennington, Wilcox, and Grover (2003) found that system trust positively influenced perceived trust in a vendor. On the basis of our theoretical reasoning and empirical evidence, we hypothesize as follows.

Hypothesis 1: Broad-scope trust has a positive influence on narrow-scope trust.

Our arguments concerning the relationships between financial healthiness and narrow-scope trust, between financial healthiness and broad-scope trust, and between financial healthiness and satisfaction, respectively, build primarily upon attribution theory. Attribution theory describes consumers' evaluation of causality in a postbehavior context on the basis of different situational contexts (Fiske and Taylor 1991; Tomlinson and Mayer 2009; Weiner 1986). As stated by Weiner (1991), attributions are considered answers to why questions regarding outcome occurrences. In general, attribution research indicates that consumers tend to attribute their failures to variables outside themselves (Gotlieb 2009). Such “defensive attributions” help consumers to establish mental justification in relation to their outcome experiences and to maintain self-confidence and avoiding cognitive dissonance (Gotlieb 2009; Todd and Gigerenzer 2003). In other words, when outcomes are unfavorable, there is a tendency to assign external blame (Blount 1995), which suggests that narrow-scope trust, broad-scope trust, and relationship satisfaction would be negatively affected by a decrease in financial healthiness.

In line herewith, we also expect that narrow-scope trust, broad-scope trust, and relationship satisfaction would be positively affected by an increase in financial healthiness. This expectation is consistent with marketing relationship theory suggesting that customers who perceive value or benefits, which (wholly or partially) can be attributed to their relationship with an exchange partner, are likely to increase their willingness to develop relational bonds (Palmatier et al. 2006). Moreover, past research suggests that people experiencing positive outcomes and that “everything is under control” are more likely than other people to develop “interpersonel trust,” which is the “generalized expectancy that the promise of an individual or a group can be relied upon” (Couch and Jones 1997; Rotter 1980). While attribution theory especially focuses on the explanation-seeking process, individuals engage in when they are surprised or threatened by unexpected or negative events (Fiske and Taylor 1991), the “New Look” model states that mental imbalance is aroused whenever outcomes are inconsistent with perceived societal normative standards for competent or moral behavior (Maertz, Hassan, and Magnusson 2009). In this regard, Abelson and Rosenberg’s theory of Symbolic Psycho-Logic (Abelson and Rosenberg 1958; Rosenberg and Abelson 1960) posits that a person experiencing mental imbalance will try to redress the cognitive state by altering the relations, modifying the elements, or avoiding the issue altogether. Hence, in incidents where the consumer is financially healthy, it provides a reason to positively evaluate her or his financial surroundings in order to achieve cognitive consistency. The following hypotheses cover our reasoning.

Hypothesis 2: Financial healthiness has a positive influence on narrow-scope trust.

Hypothesis 3: Financial healthiness has a positive influence on broad-scope trust.

Hypothesis 4: Financial healthiness has a positive influence on satisfaction.

We argue that attribution theory can also explain how broad-scope trust moderates the relationships between financial healthiness and narrow-scope trust and between satisfaction and narrow-scope trust, respectively. Weiner (1986) suggests that the causes of all outcomes can be decomposed into a set of points on three orthogonal continua, or causal dimensions. These continua are (a) locus—the prior outcome’s causal agent relative to the decision maker; (b) stability, stable to unstable—the likelihood that a prior outcome’s causal agent will persist in the future; and (c) controllability, controllable to uncontrollable—the decision maker’s degree of influence over the causal agent. Locus of causality relates to the location attributed to the cause of an outcome. It could be an internal position (the cause is located in the consumer herself/himself or in one of her or his decisions), external (located in the company that offers the service), or situational (located in environmental effects; Oliver 1993). In that respect, consumers will distinguish between causes that are internal, external, and situational. Locus of causality is in particular relevant in the present study because it explicitly distinguishes between situational causes (i.e., broad-scope trust) and causes (i.e., narrow-scope trust) that are more directly related to the individual seller that offers the service. Attribution theory predicts that consumers are more likely to evaluate a supplier positively when they make higher external attributions and lower situational attributions toward a positive experience (Weiner 1986).

Several insightful studies have investigated trust using an attribution theory approach. As an overall conclusion, these studies indicate that trust in a relationship (i.e., narrow-scope trust) is enhanced to the extent that the other’s trustworthiness can be ascribed to factors that are internal to the trustee, rather than situationally driven (e.g., Malhotra and Murnighan 2002; Tomlinson and Mayer 2009). Drawing on such insights, it is predicted that in an environment where broad-scope trust is low, consumers should be expected to be more likely to attribute negative outcomes to situational causes and less likely to attribute negative experiences to external causes (i.e., poor and untrustworthy advices from their financial service provider) compared with environments where broad-scope trust is high. In a similar vein, when broad-scope trust is low consumers should be expected to be less likely to attribute positive outcomes to situational causes and more likely to attribute positive experiences to external causes (i.e., good and trustworthy advices from their financial service provider) compared with environments where broad-scope trust is high. Specifically, in trying to assess the causes for their satisfaction and their financial healthiness, consumers may evaluate their experiences in the light of the perceived trustworthiness of available alternative financial service providers. In incidents where broad-scope trust is high, attribution theory suggests that consumers would be more inclined to attribute negative outcomes to their current financial service provider, and vice versa when broad scope trust is low. Thus, it is expected that broad-scope trust would negatively moderate the relationships between financial healthiness and narrow-scope trust and between satisfaction and narrow-scope trust, respectively. In sum, the following hypotheses are proposed.

Hypothesis 5: The influence of financial healthiness on narrow-scope trust is negatively moderated by broad-scope trust, such that financial healthiness has a greater positive effect on narrow-scope trust when broad-scope trust is low compared to high.

Hypothesis 6: The influence of satisfaction on narrow-scope trust is negatively moderated by broad-scope trust, such that satisfaction has a greater positive effect on narrow-scope trust when broad-scope trust is low compared to high.

We expect that knowledgeable consumers will be more trustful than less knowledgeable consumers. Past research suggests that knowledge facilitates the learning of new information and that knowledgeable consumers acquire and retain more information than less knowledgeable consumers (Brucks 1985; Jayanti and Burns 1998). Also, as noted by Brucks (1985) knowledge may allow consumers to formulate more questions. Hence, financial knowledge is likely to make consumers more aware of what is possible for a financial service provider and may facilitate consumers' possibility to make reliable predictions about the future behavior of a financial service provider, which in turn may be an important information source of trust (Pučėtaitė and Lämsä 2008). Also, knowledgeable consumers may feel more in control and more comfortable in their evaluation of a financial service provider (Walczuch and Lundgren 2004). Although it could also be argued that increased knowledge could backfire because knowledgeable consumers may be more able to detect the limitations of a financial service provider, thus decreasing trust, several studies from other areas suggest a positive relationship between individuals' knowledge and trust. For instance, it has been found that public’s trust in a government is positively related to its knowledge (Cook, Jacobs, and Kim 2010) and that consumer knowledge is positively related to trust toward food product categories (Puspa and Kühl 2006). The following hypotheses cover our reasoning.

Hypothesis 7: Financial knowledge has a positive influence on narrow-scope trust.

Hypothesis 8: Financial knowledge has a positive influence on broad-scope trust.

We expect financial knowledge to positively influence both narrow-scope trust and broad-scope trust. This is because previous studies indicate that individuals' domain specific-knowledge and domain-general knowledge are interrelated and that domain-specific knowledge is likely to influence their domain-general reasoning (Duncan 2007).

We also suggest that higher financial knowledge should lead to greater relationship satisfaction among financial consumers. Knowledgeable consumers enjoy an increased ability to evaluate information and to conduct more effective search, are likely to make better decisions about which service provider to choose, and are likely to form more realistic relationship expectations (Morgeson et al. 2011; Tam 2006) than less knowledgeable consumers, and thus should be more satisfied with the service provider finally selected. Also, less knowledgeable consumers may feel more insecure in the customer–seller relationship, which is likely to be associated with a reduction in satisfaction (Wilkens and Nermerich 2011). On the basis of such reasoning, the following hypothesis is proposed.

Hypothesis 9: Financial knowledge has a positive influence on satisfaction.

The evolving dynamism and complexity of modern financial markets makes the challenges for consumers to maintain knowledge structures suitable for financial decision making increasingly higher (Brennan and Coppack 2008; Organization for Economic Co-operation and Development [OECD] 2006; Towers Perrin 2008). Research suggests that when the complexity of the information provided exceeds consumers' knowledge and information processing capacity, the quality of the latter’s financial decisions will be affected negatively in a considerable manner (Howlett, Kees, and Kemp 2008; Oehler and Kohlert 2009), which may reduce their financial healthiness. On a similar note, Hogarth and Hilgert (2002) and Hilgert, Hogarth, and Beverly (2003) found in a series of studies that financially knowledgeable consumers are more likely to behave in financially responsible ways. The survey results obtained by Perry and Morris (2005) support this notion. Hence, we hypothesize as follows.

Hypothesis 10: Financial knowledge has a positive influence on financial healthiness.

When broad-scope trust is low, it means that consumers cannot just rely on any service provider to reduce the complexity and uncertainty they are faced with. Hence, the consumer risks that her or his interests will not be properly served. When faced with such circumstances, consumer choice theory indicates that a consumer will tend to more thoroughly evaluate the trustworthiness of various service providers (e.g., Shafir and Tversky 1992; Shiu et al. 2011). That is, when broad-scope trust is low even higher demands are put on consumers' knowledge and cognitive skills (Jayanti and Burns 1998). On a similar note, high broad-scope trust should be expected to facilitate consumers' evaluation of the trustworthiness of service providers without having extensive knowledge (Hall et al. 2002). Moreover, even when people possess knowledge and information, they may ignore it if they feel that their decision-environment can be trusted (Rotfeld 2007). In summary, we expect that when broad-scope trust is low consumers will rely more on their financial knowledge in determining the trustworthiness of their financial service provider than when broad-scope trust is high. We hypothesize as follows.

Hypothesis 11: The influence of financial knowledge on narrow-scope trust is negatively moderated by broad-scope trust, such that financial knowledge has a greater positive effect on narrow-scope trust when broad-scope trust is low compared to high.

Although previous research results are mixed concerning the relationship between satisfaction and narrow-scope trust (e.g., Grayson, Johnson, and Chen 2008) found that narrow-scope trust positively influenced consumer relationship satisfaction), we expect relationship satisfaction to positively influence narrow-scope trust. Our expectation is based on past research suggesting that satisfaction antecedes trust (Ouyang 2010; Zboja and Voorhees 2006), that satisfaction develops in the initial stages of marketing relationships and trust develops in the intermediate stages (Geyskens, Steenkamp, and Kumar 1999; Leisen and Hyman 2004) and that satisfaction positively influences narrow-scope trust because it increases consumers' confidence that they will be treated fairly and that the seller cares about their interests (Ganesan 1994). In sum, we hypothesize as follows.

Hypothesis 12: Satisfaction has a positive influence on narrow-scope trust.

Methodology

Data Collection

Two financial service industries were selected for our study: pension and mortgage companies. The use of multiple service industries provides a robust test of model relationships by allowing greater variability in study constructs (Sirdeshmukh, Singh, and Sabol 2002). For each industry, a two-step procedure was utilized to sample respondents from Capacent Epinion’s online panel of approximately 30,000 Danish consumers. In the first step, a stratified random sample of 4,820 respondents aged 18+ was drawn from the online panel, reflecting the distribution of gender, age, and educational level in the population (aged 18+) as a whole. In the second step, these 4,820 respondents were contacted by e-mail, and asked to respond to the screening question: “Have you recently been in contact with your current (main) pension/mortgage company?” (Yes/No/Not currently engaged with a pension/mortgage company) to ensure that only ongoing relationships were included in the sample.

In the final samples (pension sample, n = 764; mortgage sample, n = 892), 52.3% (pension sample) and 52.5% (mortgage sample), respectively, were women and average age was 46.5 years (pension sample) and 49.1 years (mortgage sample), respectively, with ranges between 18 and 85 years (pension sample) and 20–87 (mortgage sample), respectively. It was investigated whether the profiles of the study samples deviated from the country population aged 18–85 and 20–87, respectively, on gender and educational level. χ² tests of difference between samples and population frequencies on each of these criteria produced p values >.11 for both samples, indicating that our samples reflected the demographic profile of the studied country population.

Measurements

Our measurement items were based on prior research, modified to fit the financial service context of this study where relevant. The final items for each construct are summarized in Appendix A. Financial healthiness was measured using 6 items adapted from Joo and Grable (2004). Narrow-scope trust was measured by 3 items adapted from the trust in the Organization scale developed by Tax, Brown, and Chandrashekaran (1998). A 3-item scale adapted from De Wulf, Odekerken-Schröder, and Iacobucci (2001) measured satisfaction, whereas 3 items based on Tax, Brown, and Chandrashekaran (1998) measured broad-scope trust. Knowledge was measured using the 3-item Subjective Knowledge scale provided by Mukherjee and Hoyer (2001). In the questionnaire, the items used to measure the study constructs were presented in random order.

Results

Validation of Measurements

Confirmatory factor analysis (CFA) was conducted on the five latent factors, with each indicator specified to load on its hypothesized latent factor. Raw data were used as input for the maximum likelihood (ML) estimation procedure using the pooled sample of respondents. Table 1 summarizes the CFA results.

Table 1.

Confirmatory Factor Analysis Results

Construct/Indicator	Standardized Factor Loading^a	Critical Ratio	Composite Reliability	Extracted Variance
Financial healthiness			.86	.51
X1	.74	—
X2	.71	15.25
X3	.81	16.40
X4	.64	14.30
X5	.70	16.35
X6	.69	15.08
Broad-scope trust			.83	.62
X7	.71	—
X8	.77	18.91
X9	.87	20.04
Narrow-scope trust			.77	.53
X10	.62	—
X11	.81	19.23
X12	.74	17.78
Knowledge			.79	.56
X13	.69	—
X14	.80	13.11
X15	.75	13.15
Satisfaction			.80	.58
X16	.82	—
X17	.59	16.74
X18	.84	25.83

Note. ^aOne item for each construct was set to 1.

CFA = confirmatory factor analysis; CFI = comparative fit index; NFI = normed fit index; RMSEA = root mean square error of approximation.

CFA analysis (pooled sample): Model fit: χ² = 475.82 (df = 125, p < .01); CFI = .95; NFI = .94; RMSEA = .057; Hoelter(.05) = 278.

The items for each construct are summarized in the Appendix A.

Table 2.

Correlations and Descriptive Statistics

	1	2	3	4	5
1. Financial healthiness	1.00
2. Broad-scope trust	.29^a	1.00
3. Narrow-scope trust	.25^a	.58^a	1.00
4. Knowledge	.29^a	.44^a	.41^>a	1.00
5. Satisfaction	.26^a	.62^a	.66^a	.38^a	1.00
Mean	5.37	4.04	5.61	5.28	5.71
SD	1.41	1.23	1.16	1.17	1.22

Note. ^a p < .01.

Averaged scale means are reported; all items were measured on 7-point Likert-type scales (1 = strongly disagree; 7 = strongly agree).

The measurement model yields a chi-square of 475.82 (df = 125, p < .01). However, the Hoelter (0.05; Hoelter 1983) estimate (n = 278) suggests that the lack of absolute fit can be explained by sample size. Thus, since the chi-squared test is highly sensitive to sample size other fit measures are given greater prominence in evaluating model fit (e.g., Ye, Marinova, and Singh 2007). The root mean square error of approximation (RMSEA = .057), the comparative fit index (CFI = .95), and the normed fit index (NFI = .94) suggest that the measurement model fits the data reasonably well (Bagozzi and Yi 1988). Composite reliabilities were close to or greater than .80, indicating good reliability of measured constructs (Bagozzi and Yi 1988). Finally, extracted variance was greater than .5 for all latent constructs, which satisfies the threshold value recommended by Fornell and Larcker (1981).

Discriminant validity is assessed in two ways. First, the method proposed by Fornell and Larcker (1981) was applied. According to this method, the extracted variance for each individual construct should be greater than the squared correlation (i.e., shared variance) between constructs. An examination of Tables 1 and 2 shows that the extracted variance for each of the constructs exceeded the squared correlation.

Second, the baseline measurement model was compared to alternative models where covariances between pairs of constructs were constrained to unity (Anderson and Gerbing 1988). In every case, the restricted model had a significant ( p < .05) poorer fit than the unrestricted model suggesting sufficient discriminant validity.

Model and Hypotheses Testing

The moderating effects were formed using the product indicator formatting procedure (i.e., matching indicators by reliability) proposed by Jackman, Leite, and Cochrane (2011) and applying the residual-centering (i.e., orthogonalizing), two-step procedure recommended by Little, Bovaird, and Widaman (2006). First, each of the specified interactions was regressed onto the first-order effect indicators of the two constructs under consideration. Second, for each of these regressions, the residuals were saved and used as indicators of the interaction construct. This method, which is facilitated by the relatively large sample sizes of this study, is regarded superior to more common path models, because it incorporates measurement error (Kaplan 2009). Both the main effects and the hypothesized interaction effects were estimated in the model.

The use of product indicators renders nonnormality, which violates the distributional assumptions of the standard ML estimator and can lead to underestimation of standard errors (Kaplan 2009). Hence, the model estimations reported below were initially estimated using the bootstrapping resampling procedure (2000 samples; Efron and Tibshirani 1993) to produce distributionally appropriate standard errors and chi-squared statistics. Next, the models were reestimated using ML. A comparison of the parameter estimates produced by bootstrapping and ML suggested similar significance levels for all estimated structural equation modeling (SEM) paths. This result is consistent with the suggestion put forward by Little, Bovaird, and Widaman (2006) that when utilizing the residual-centering procedure “the standard maximum likelihood estimator likely provides a reasonably robust estimate of standard errors and significance” (p. 512). In the following, the results based on ML estimates are reported.

Initially, an estimation of the model for each of the two samples separately showed reasonable model fit in both incidents (pension services: χ² = 871.99, df = 300; CFI = .94; NFI = .91; RMSEA = .047; mortgage services: χ² = 844.93, df = 300; CFI = .93; NFI = .91; RMSEA = .049). The hypothesized model was then fitted simultaneously to the pension and mortgage services samples using multiple-group latent variable SEM analysis. Initially, a fully restricted model was estimated holding all paths invariant across the two data sets. Next, using a chi-squared difference test, we investigated whether paths with significant test statistics varied across subsamples. All of the released paths failed to enhance model fit suggesting that the investigated path coefficients did not differ significantly across the two subsamples; therefore, the fully restricted model was used to represent the data sets. The model chi-squared statistic was 1756.86 (df = 678, p < .01), indicating that the model fails to fit in an absolute sense. However, the more robust fit indexes (CFI = .94; NFI = .92; RMSEA = .031) indicated an acceptable model fit. In addition, the NNFI, which is thought to be sensitive to both explanation and parsimony, equals .91, suggesting that the model shows an appropriate balance between these competing goals.

To test the improvement in fit due to the hypothesized interaction effects, a competing model omitting these interactions, but retaining all other relationships, was estimated. Compared with the proposed model the results suggest that the competing model had inferior fit statistics: χ² = 1229.40, df = 297, p < .01; CFI = .92; NFI = .91; RMSEA = .044; NNFI = .90. To conclude, the hypothesized model is a reasonable fit to the data. Table 3 displays the estimated coefficients from the multiple-group SEM analysis.

Table 3.

Estimated Standardized Coefficients

	Pension Services								Mortgage Services
	Dependent Constructs								Dependent Constructs
	Narrow-Scope trust		Financial Healthiness		Broad-Scope Trust		Satisfaction		Narrow-Scope Trust		Financial Healthiness		Broad-Scope Trust		Satisfaction
Independent Constructs	β (SE)	t Value	β (SE)	t Value	β (SE)	t Value	β (SE)	t Value	β (SE)	t Value	β (SE)	t Value	β (SE)	t Value	β (SE)	t Value
Direct effects
Financial healthiness	.09 (.02)	3.22^a	—	—	.16 (.04)	3.99^a	.15 (.04)	3.80^a	.08 (.02)	2.82^a	—	—	.16 (.04)	3.76^a	.14 (.04)	3.17^a
Broad-scope trust (BST)	.38 (.03)	10.35^a	—	—	—	—	—	—	.40 (.03)	10.10^a	—	—	—	—
Knowledge	.10 (.03)	2.74^a	.29 (.07)	6.13^a	.46 (.07)	8.70^a	.42 (.07)	8.37^a	.12 (.04)	3.14^a	.25 (.07)	5.18^a	.44 (.08)	8.06^a	.40 (.07)	7.64^a
Satisfaction	.56 (.04)	14.52^a	—	—	—	—	—	—	.58 (.04)	15.52^a	—	—	—	—	—	—
Moderating effects
FH × BST	−.09 (.03)	−3.15^a	—	—	—	—	—	—	−.08 (.03)	−2.92^a	—	—	—	—	—	—
Knowledge × BST	−.06 (.03)	−1.69^b	—	—	—	—	—	—	−.07 (.03)	−1.84^b	—	—	—	—	—	—
Satisfaction × BST	−.11 (.03)	−3.81^a	—	—	—	—	—	—	−.11 (.03)	−3.70^a	—	—	—	—	—	—

Note. CFI = comparative fit index; NFI = normed fit index; RMSEA = root mean square error of approximation.

^aSignificant on the 1% level; ^bSignificant on the 10% level.

Model fit: χ² = 1756.86 (df = 678, p < .01); CFI = .94; NFI = .92; RMSEA = .031; NNFI = .91.

Unconstrained standardized coefficients are reported.

In forming the interaction constructs, product indicators were created by multiplying the three most reliable indicators of each scale according to the procedure proposed by Jackman, Leite, and Cochrane (2011).

R ²: (pension services: narrow-scope trust = .52, financial healthiness = .08, broad-scope trust = .28, satisfaction = .23; mortgage services: narrow-scope trust = .51, financial healthiness = .07, broad-scope trust = .25, satisfaction = .20).

Eleven of the proposed relationships included in our theoretical framework were supported and one relationship (Hypothesis 11) was marginally supported. Broad-scope trust positively influenced narrow-scope trust (pension services: β = .38, p < .01; mortgage services: β = .40, p < .01). Thus, Hypothesis 1 was supported. The SEM relationships pertaining to Hypotheses 2–4 (pension services: financial healthiness → narrow-scope trust β = .09, p < .01, financial healthiness → broad-scope trust β = .16, p < .01, financial healthiness → satisfaction β = .15, p < .01; mortgage services: financial healthiness → narrow-scope trust β = .08, p < .01, financial healthiness → broad-scope trust β = .16, p < .01, financial healthiness → satisfaction β = .14, p < .01) support these three hypotheses.

The influence of financial healthiness on narrow-scope trust was negatively moderated by broad-scope trust (pension services: β = −.09, p < .01; mortgage services: β = −.08, p < .01). Thus, Hypothesis 5 was supported. Broad-trust also negatively moderated the influence of satisfaction on narrow-scope trust (pension services: β = −.11, p < .01; mortgage services: β = −.11, p < .01). This provides support to Hypothesis 6.

Hypotheses 7 and 8 were also supported since knowledge positively influenced narrow-scope trust and broad-scope trust, respectively (pension services: knowledge → narrow-scope trust β = .10, p < .01, knowledge --> broad-scope trust β = .46, p < .01; mortgage services: knowledge → narrow-scope trust β = .12, p < .01, knowledge → broad-scope trust β = .44, p < .01). Supporting Hypotheses 9 and 10, knowledge also positively influenced satisfaction and financial healthiness, respectively (pension services: knowledge → satisfaction β = .42, p < .01, knowledge → financial healthiness β = .29, p < .01; mortgage services: knowledge → satisfaction β = .40, p < .01, knowledge → financial healthiness β = .25, p < .01).

The results marginally suggest that broad-scope trust negatively moderated the relationship between knowledge and narrow-scope trust (pension services: β = −.06, p < .10; mortgage services: β = −.07, p < .10). Thus, Hypothesis 11 was marginally supported in the study.

As expected from previous research, satisfaction had a positive influence on narrow-scope trust (pension services: β = .56, p < .01; mortgage services: β = .58, p < .01). Hence, Hypothesis 12 was supported.

Common Method Variance

In order to assess the effects of common-method variance, we reestimated the structural model by adding a same-source factor (all 18 main construct items loading on it) to the model in Figure 1 (Netemeyer et al. 1997). Common method variance is a known limitation when using self-report measures. Comparing an unconstrained model in which all indicators are related to a common factor to one in which these paths are constrained to zero represents a significance test of the effects of the same-source factor.

For the pension services sample, the fit of the constrained model was χ² = 843.00 (df = 299), CFI = .94; NFI = .92; RMSEA = .046; NNFI = .91. For the unconstrained model, the fit was χ² = 820.12 (df = 282), CFI = .94; NFI = .92; RMSEA = .047; NNFI = .91. The fit of the unconstrained model did not differ from that of the constrained model (Δχ² = 22.88, Δdf = 17, p = .15) and the results for all the hypotheses tests were identical to the results reported above suggesting that the results are robust with respect to common method variance.

For the mortgage services sample, the fit of the constrained model was χ² = 815.01 (df = 299), CFI = .94; NFI = .91; RMSEA = .048; NNFI = .90. For the unconstrained model, the fit was χ² = 789.19 (df = 282), CFI = .94; NFI = .91; RMSEA = .049; NNFI = .90. The fit of the unconstrained model did not differ from that of the constrained model (Δχ² = 25.82, Δdf = 17, p = .08) and all significant path loadings reported above remained significant.

Hence, in both samples all of the paths that were significant when the common method factor was not controlled remained significant when the effects of common method variance were controlled. Based on the results of the conducted tests, we conclude that common method variance does not appear a problem in our study.

Results Summary

Consistent with institutional theory, our research shows that broad-scope trust can improve narrow-scope trust. Drawing on attribution theory, we found that financial healthiness positively influenced narrow-scope trust, broad-scope trust, and satisfaction, respectively. Guided by consumer choice theory, the results also show that consumer knowledge positively influenced narrow-scope trust, broad-scope trust, financial healthiness, and satisfaction, respectively. Consistent with past relationship research, this study also demonstrates the beneficial effect of relationship satisfaction for increasing narrow-scope trust. We also found that broad-scope trust negatively moderates the relationships between financial healthiness and narrow-scope trust and between satisfaction and narrow-scope trust, respectively. In addition, the results marginally indicate that broad-scope trust negatively moderates the relationship between consumer financial knowledge and narrow-scope trust.

Discussion

Theoretical Implications

This study has several implications for marketing relationship theory, which has heavily focused on the role of narrow-scope trust in developing close relationships with consumers. Although a large number of conceptualizations of “relationship marketing” have been proposed, marketing researchers seem to agree that (a) relationship marketing focuses on the individual customer–seller relationship; (b) both parties in a relationship must benefit for the relation to continue; (c) the relationship is often longitudinal in nature; (d) the focus of relationship marketing is to retain customers (Hunt, Arnett, and Madhavaram 2006; Peterson 1995). These perspectives have resulted in a strong focus on variables such as satisfaction, trust, cooperation, understanding, and fulfillment of promises within the relationship marketing approach. In that respect, our results strongly suggest that the investigation of customer–seller relationships should not be limited to focusing on the interaction between the two parties, as is typically modeled (Danaher, Conroy, and McColl-Kennedy 2008; Morgan and Hunt 1994), but should expand into a broader perspective, which also includes consumer personal constructs (such as financial healthiness and knowledge) and contextual variables (such as broad-scope trust). Specifically, we highlight three important theoretical implications.

First, this study provides further evidence for the usefulness of the distinction between narrow-scope trust and broad-scope trust. This is because the trustworthiness of other service providers, even if they may not be considered direct competitors, may (a) influence narrow-scope trust and (b) moderate the development of specific financial customer–seller relationships. Second, we demonstrate that our understanding of narrow-scope trust may substantially benefit from taking into account personal characteristics. Specifically, by showing that financial healthiness and knowledge positively influence narrow-scope trust, this study establishes these personal characteristics as key constructs in understanding consumer financial relationship behavior. Third, it is generally believed that broad-scope trust may arise from the law and/or from company culture (Carlin, Dorobantu, and Viswanathan 2009). Hence, by proposing and showing that personal financial healthiness and knowledge positively influence broad-scope trust this study (a) extends prior theoretical considerations concerning the development of broad-scope trust and (b) demonstrates the importance of taking personal characteristics into account when studying the functioning of financial markets.

In addition to these implications, previous theorizing suggests that early in a relationship narrow-scope trust is most likely based primarily on general trust, but as the relationship continues, a divergence is more likely between broad-scope trust and narrow-scope trust (Gutek et al. 1999). This is because as individual relationships develop, the personalization that occurs may boost the level of narrow-scope trust. Notably, our study results support this suggestion. A comparison of broad-scope trust with narrow-scope trust shows that narrow-scope trust is more than one third higher on average than broad-scope trust (5.61 vs. 4.04, p < .01; Table 2).

Finally, the finding that broad-scope trust positively influences narrow-scope trust supports institutional theory at the expense of functionalist theory. These two theories represent competing views on the relationship between broad-scope trust and narrow-scope trust. In contrast to institutional theory, functionalist theory (Luhmann 1979; Parsons 1967) holds that narrow-scope trust is only formed where it is needed. In incidents where broad-scope is insufficient (i.e., at a low level), economic parties may therefore compensate for this by developing narrow-scope trust suggesting the existence of a negative relationship between broad-scope trust and narrow-scope trust.

Implications for Marketing Practice, Consumers, and Public Policy

Financial education programs have now been established in many countries (e.g., Gaurav, Cole, and Tobacman 2011) and also the OECD prioritizes this issue (OECD 2006). Our finding that increased knowledge may improve financial healthiness encourages public policy makers, financial authorities, and consumer organizations to continue and even further develop consumer financial education programs. Also, it encourages consumers to participate in such programs. As important additional effects of such initiatives increasing consumer financial knowledge is also likely to improve broad-scope trust and narrow-scope trust. The positive relationship between knowledge and financial healthiness is also of interest to financial managers. Since financial companies are dependent on customers to pay their loans and bills they have a greater interest in developing relationships with financially healthy consumers than with the opposite. Our results further underline this interest by showing that financial healthiness positively affects narrow-scope trust and relationship satisfaction.

In addition to improving consumers' knowledge about financial topics and concepts, our results suggest that financial education programs should be concerned with enabling consumers to assess the trustworthiness of their individual service provider. This is especially important when broad-scope trust is low. It is well-known that some consumers face particular difficulties and are often categorized as vulnerable, excluded, or susceptible (Brennan and Coppack 2008). Vulnerable consumers can be characterized as consumers who are disadvantaged due to factors that are largely beyond their direct control, such as lack of knowledge, the young, and members of ethnic minorities (Andreasen and Manning 1990). Our results suggest that when broad-scope trust is low, consumers rely more on the evaluation of relationship satisfaction and (to a marginal degree) knowledge in assessing narrow-scope trust. Hence, when broad-scope trust is low even higher burdens are put on cognitive skills, which in turn may reduce the ability of vulnerable consumers to confidently determine the trustworthiness of their individual service provider. However, while general consumer financial knowledge and capability can hardly be strongly improved in the short-term vulnerable consumers may be even more difficult to educate by financial programs (Brennan and Coppack 2008). Our study thus suggests that in the after-crisis era, public policy makers and legal authorities should increasingly consider complementing educational programs with financial services consumer protection initiatives in order to ease the cognitive burdens put on vulnerable consumers. Because satisfaction is positively related to narrow-scope trust facilitating consumers' evaluation of relationship satisfaction is also in the interest of financial managers. Hence, when broad-scope trust is low, financial service managers should, in particular, consider collaborating with public authorities in increasing consumer knowledge and/or developing their own educational programs.

Because broad-scope trust is associated with financial service providers as a whole, the detected positive relationship between broad-scope trust and narrow-scope trust holds true even for service providers who have not actively participated in improving broad-scope trust. However, because of market competition and scarce resources some managers may feel tempted only to focus on developing narrow-scope trust (Carlin, Dorobantu, and Viswanathan 2009; Williamson 1993). Since it is in the interest of societies that their citizens have trust in financial institutions this underlines the importance of developing well-functioning financial regulations, which ensures that the development of broad-scope trust is not left to the financial industry alone. On top of this, the financial services industry may consider improving self-regulatory mechanisms to facilitate the development of a trustful company culture.

As expected from attribution theory, the results indicate that broad-scope trust has a negative moderating influence on the relationship between satisfaction and narrow-scope trust and a negative moderating influence on the relationship between financial healthiness and narrow-scope trust. These results have important implications for financial service managers.

While managers should be concerned that a low level of broad-scope trust may have a direct negative influence on narrow-scope trust, they should also pay attention when broad-scope trust level is high or on the increase since broad-scope trust negatively moderates the relationships between customer satisfaction and narrow-scope trust and between financial healthiness and narrow-scope trust, respectively. On the other hand, with higher levels of broad-scope trust managers may benefit from an improved relationship between broad-scope trust and narrow-scope trust. Hence, when considering how to approach their customers and the amount of resources (staff resources, market campaigns, etc.) needed in order to develop trustful relationships with consumers financial services managers should take into account the trustworthiness of other service providers as detailed in the following.

When broad-scope trust is low, financial service providers will gain a higher amount of narrow-scope trust from satisfying their customers than when broad-scope trust is high. Hence, as a direct managerial implication, financial service managers should consider investing additional resources in satisfying customers when broad-scope trust is low or on the decrease. In addition, financial healthiness is a more important antecedent of narrow-scope trust when broad-scope trust is low compared to high. When broad-scope trust is low, managers will therefore benefit from increasing their financial counseling effort and should, as an additional effort, consider developing services (e.g., favorable savings accounts, financial budgeting services, and the like) specifically aimed at improving and/or preserving customers' financial healthiness. When broad-scope trust is high, the positive influence of consumer satisfaction and financial healthiness on narrow-scope trust decreases. However, this may be compensated by the positive relationship between broad-scope trust and narrow-scope trust. Since financial healthiness and satisfaction are less important determinants of narrow-scope trust when broad-scope trust is high, financial service managers may instead wish to direct a larger amount of their resources at (a) attracting new customers (because broad-scope trust is high, consumers should be expected to be less skeptical when exposed to financial market campaigns from alternate service providers) and (b) providing existing customers with favorable offerings in order to make them more reluctant to market communication and offers from competing financial service providers.

Limitations and Directions for Future Research

This study drew on various theories and concepts in order to develop a theoretical understanding of how financial healthiness, broad-scope trust, knowledge, and satisfaction affect narrow-scope trust. In relation hereto, future research could collect longitudinal data to assess the long-term relationships between the proposed antecedents and narrow-scope trust. Longitudinal studies would help understand whether the nature of the effects obtained in this study is indeed long term. Also, while this research demonstrates the importance of one contextual variable (i.e., broad-scope trust), one evaluative variable (i.e., satisfaction) and two personal characteristics (i.e., knowledge and financial healthiness) for the development of narrow-scope trust future research may wish to include additional explaining personal, evaluative and/or situational characteristics. For example, it is known that consumer financial knowledge and healthiness can vary with education, income, gender, and age (e.g., Garmaise 2010) and that satisfaction and narrow-scope trust (and perhaps also broad-scope trust) may be affected by service providers' communication effort (Selnes 1998). Also, while broad-scope trust is known to be positively correlated with economic growth (Zak and Knack 2001), it might also be interesting to investigate how the perceived general economic welfare of a society may complement broad-scope trust in affecting narrow-scope trust and in moderating the relationships between satisfaction, knowledge, and financial healthiness, respectively, and narrow-scope trust.

Although the present research concentrated on investigating consumers' trust in their financial service providers, our theoretical framework may also be applicable to research dealing with other business and services areas, such as for instance food retailing and medical services. Food might cause health risks and both individual food retailers and the food industry as a whole are often dealing with lack of consumer trust, for instance caused by mad-cow-disease, food poisoning, or when risks of genetically manipulated food are discussed (Kenning 2008). Also, it is well known that individuals are likely to distinguish between trust in their individual medical service provider and trust in the medical service industry as a whole and also that individuals may differ according to their personal healthiness, knowledge of health issues, and relationship satisfaction with their medical service provider (Hall et al. 2002).

There are several other limitations of this study that should be acknowledged. Consumers were approached via online surveys; they may behave differently when engaging in specific relationship settings. Also, this study concentrated on analyzing the consumer population of one society and in two industries. Although the investigated financial industry types are present in most societies and even though their service offerings are most likely guided by similar financial and economic principles, this could mean that the results may suffer from a lack of generalizability when other countries and/or industries are considered. Future research is called upon to take into account cultural characteristics such as, for example, the degree of consumer uncertainty avoidance, among others (Hofstede 2001). Since trust may decrease uncertainty, financial consumers within uncertainty avoiding societies may put higher emphasis on broad-scope trust and narrow-scope trust when compared to less uncertainty avoiding societies. Also, recent research suggests that the trust-building process may differ across cultures (Schumann et al. 2010). Future research could also manipulate some of our antecedent variables in an experimental setting. Such an experimental study would replicate the present cross-sectional survey results, and thus provide stronger evidence for the direction of causality in the proposed research model.

Conclusion

Drawing on institutional theory, attribution theory, and consumer choice theory, this study demonstrated that financial healthiness, broad-scope trust, knowledge, and satisfaction affect narrow-scope trust in financial services. Because consumer knowledge was found to positively influence financial healthiness, broad-scope trust and narrow-scope trust, respectively, this study encourages public policy makers, financial authorities, and financial service providers to continue, improve, and/or develop consumer financial education programs. This study also indicated, however, that when broad-scope trust is low even higher burdens are put on cognitive skills, which in turn may reduce the ability of vulnerable consumers to confidently determine the trustworthiness of their individual service provider. Thus, when broad-scope trust is low, financial education programs become even more important. In addition, we showed that financial service providers may benefit from an increased broad-scope trust since it positively influences narrow-scope trust. However, when broad-scope trust is low, financial service providers will gain a higher amount of narrow-scope trust from investing additional resources in satisfying their customers and/or from improving customers' financial healthiness than when broad-scope trust is high.

Footnotes

Appendix A

Items used to measure the constructs in the study
Financial healthiness (financial behavior over the last year) X1. I set money aside for savings X2. I reached the maximum limit on a credit card^* X3. I spent more money than I had^* X4. I had to cut living expenses^* X5. I had to buy on credit^* X6. I had financial troubles because I did not have enough money^* Broad-scope trust X7. In general, I believe that financial companies cannot be relied on to keep their promises^* X8. In general, I believe that financial companies are trustworthy X9. Overall, I believe financial companies are honest Narrow-scope trust X10. I believe that my [financial service provider] cannot be relied upon to keep its promises^* X11. I believe that my [financial service provider] is trustworthy X12. Overall, I believe my [financial service provider] is honest Knowledge X13. In general, how knowledgeable are you about different types of [the service in question] in the market? X14. In general, how much experience do you have with different types of [the service in question] in the market? X15. Compared to others you know, how knowledgeable are you about the features of different [the service in question] in the market? Satisfaction X16. I am satisfied with the relationship I have with my [financial service provider] X17. As a regular customer, I have a high quality relationship with my [financial service provider] X18. I am happy with the effort my [financial service provider] is making towards regular customers like me

Items used to measure the constructs in the study

Financial healthiness (financial behavior over the last year)
X1. I set money aside for savings
X2. I reached the maximum limit on a credit card^*
X3. I spent more money than I had^*
X4. I had to cut living expenses^*
X5. I had to buy on credit^*
X6. I had financial troubles because I did not have enough money^*
Broad-scope trust
X7. In general, I believe that financial companies cannot be relied on to keep their promises^*
X8. In general, I believe that financial companies are trustworthy
X9. Overall, I believe financial companies are honest
Narrow-scope trust
X10. I believe that my [financial service provider] cannot be relied upon to keep its promises^*
X11. I believe that my [financial service provider] is trustworthy
X12. Overall, I believe my [financial service provider] is honest
Knowledge
X13. In general, how knowledgeable are you about different types of [the service in question] in the market?
X14. In general, how much experience do you have with different types of [the service in question] in the market?
X15. Compared to others you know, how knowledgeable are you about the features of different [the service in question] in the market?
Satisfaction
X16. I am satisfied with the relationship I have with my [financial service provider]
X17. As a regular customer, I have a high quality relationship with my [financial service provider]
X18. I am happy with the effort my [financial service provider] is making towards regular customers like me

^*Item reverse coded.

Acknowledgments

The data for this study were collected in collaboration with the Danish Money and Pension Panel.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

Abelson

Robert P.

Rosenberg

Milton J.

(1958), “Symbolic Psycho-Logic: A Model of Attitudinal Cognition,” Behavioral Science, 3 (1), 1–13.

Alba

Joseph W.

Hutchinson

John W.

(2000), “Knowledge Calibration: What Consumers Know and What They Think They Know,” Journal of Consumer Research, 27 (September), 123–156.

Anderson

James C.

Gerbing

David W.

(1988), “Structural Equation Modelling in Practice: A Review and Recommended Two-Step Approach,” Psychological Bulletin, 103 (November), 411–423.

Andreasen

Alan R.

Manning

Jean

(1990), “The Dissatisfaction and Complaining Behavior of Vulnerable Consumers,” Journal of Consumer Satisfaction, Dissatisfaction and Complaining Behavior, 3, 12–20.

Bagozzi

Richard P.

Youjae

(1988), “On the Evaluation of Structural Equation Models,” Journal of the Academy of Marketing Science, 16 (1), 74–94.

Blount

Sally

(1995), “When Social Outcomes Aren’t Fair: The Effect of Causal Attributions on Preferences,” Organizational Behavior and Human Decision Processes, 62 (2), 131–144.

Brennan

Carol

Coppack

Martin

(2008), “Consumer empowerment: Global Context, UK Strategies and Vulnerable Consumers,” International Journal of Consumer Studies, 32 (4), 306–313.

Brucks

Merrie

(1985), “The Effects of Product Class Knowledge on Information Search Behavior,” Journal of Consumer Research, 12 (June), 1–16.

Cameron

Fiona

Cornish

Charlotte

Nelson

William

(2006), “FSS2: A New Methodology for Segmenting Consumers for Financial Services,” Journal of Financial Services Marketing, 10 (3), 260–271.

10.

Carlin

Bruce Ian

Dorobantu

Florin

Viswanathan

(2009), “Public Trust, the Law, and Financial Investment,” Journal of Financial Economics, 92 (3), 321–341.

11.

Cook

Fay Lomax

Jacobs

Lawrence R.

Kim

Dukhong

(2010), “Trusting What You Know: Information, Knowledge, and Confidence in Social Security,” Journal of Politics, 72 (2), 397–412.

12.

Costa

MaryLou

(2010), “Why Shattered Reputations are Ripe for Repair,” Marketing Week, July 22 (accessed January 10, 2012), [available at http://www.marketingweek.co.uk/trends/why-shattered-reputations-areripe-for-repair/3016057.article].

13.

Couch

Laurie L.

Jones

Warren H.

(1997), “Measuring Levels of Trust,” Journal of Research in Personality, 31 (September), 319–336.

14.

Danaher

Peter J.

Conroy

Denise M.

McColl-Kennedy

Janet R.

(2008), “Who Wants a Relationship Anyway? Conditions When Consumers Expect a Relationship With Their Service Provider,” Journal of Service Research, 11 (1), 43–62.

15.

Wulf

Kristof

Gaby Odekerken-Schröder

Iacobucci

Dawn

(2001), “Investments in Consumer Relationships: A Cross-Country and Cross-Industry Exploration,” Journal of Marketing, 65 (October), 33–50.

16.

DiMaggio

Paul J.

Powell

Walter W.

(1983), “The Iron Cage Revisited: Institutional Isomorphism and Collective Rationality in Organizational Fields,” American Sociological Review, 48 (2), 147–160.

17.

Dimitriades

Zoe S.

(2006), “Customer Satisfaction, Loyalty and Commitment in Service Organizations,” Management Research News, 29 (12), 782–800.

18.

Driscoll

James W.

(1978). “Trust and Participation in Organizational Decision Making as Predictors of Satisfaction,” Academy of Management Journal, 21 (March), 44–56.

19.

Duncan

Ravit Golan

(2007), “The Role of Domain-Specific Knowledge in Generative Reasoning About Complicated Multileveled Phenomena,” Cognition and Instruction, 25 (4), 271–336.

20.

Eisingerich

Andreas B.

Bell

Simon J.

(2007), “Maintaining Customer Relationships in High Credence Services,” Journal of Services Marketing, 21 (4), 253–262.

21.

Efron

Bradley

Tibshirani

Robert J.

(1993), An Introduction to the Bootstrap. London: Chapman & Hall.

22.

Fiske

Susan T.

Taylor

Shelley E.

(1991), Social Cognition, 2nd ed. New York, NY: McGraw-Hill.

23.

Flynn

Leisa Reinecke

Goldsmith

Ronald E.

(1999), “A Short Reliable Measure of Subjective Knowledge,” Journal of Business Research, 46 (1), 57–66.

24.

Fornell

Claes

Larcker

David F.

(1981), “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error,” Journal of Marketing Research, 18 (1), 39–50.

25.

Ganesan

Shankar

(1994), “Determinants of Long-Term Orientation in Buyer–Seller Relationships,” Journal of Marketing, 58 (April), 1–19.

26.

Garmaise

Ena

(2010), “Patterns of Financial Well-Being and Their Implications for Financial Advice,” Journal of Financial Service Professionals, 64 (3), 68–76.

27.

Gaurav

Sarthak

Cole

Shawn

Tobacman

Jeremy

(2011), “Marketing Complex Financial Products in Emerging Markets: Evidence from Rainfall Insurance in India,” Journal of Marketing Research, XLVII (Special Issue), 150–162.

28.

Geyskens

Inge

Steenkamp

Jan-Benedict E. M.

Kumar

Nirmalya

(1999), “A Meta-Analysis of Satisfaction in Marketing Channel Relationships,” Journal of Marketing Research, 36 (May), 223–238.

29.

Gotlieb

Jerry

(2009), “Justice in the Classroom and Students' Evaluations of Marketing Professors' Teaching Effectiveness: An Extension of Prior Research Using Attribution Theory,” Marketing Education Review, 19 (2), 1–14.

30.

Grayson

Kent

Johnson

Devon

Chen

Der-Fa Robert

(2008), “Is Firm Trust Essential in a Trusted Environment? How Trust in the Business Context Influences Customers,” Journal of Marketing Research, XLV (April), 241–256.

31.

Gutek

Barbara A

Bhappu

Anita D.

Liao-Troth

Matthew A.

Cherry

Bennett

(1999), “Distinguishing between Service Relationship and Encounters,” Journal of Applied Psychology, 84 (2), 218–233.

32.

Hall

Mark A.

Camacho

Fabian

Dugan

Elizabeth

Balkrishnan

Rajesh

(2002), “Trust in the Medical Profession: Conceptual and Measurement Issues,” Health Services Research, 37 (5), 1419–39.

33.

Harrison

Tina

(2003), “Why Trust is Important in Customer Relationships and How to Achieve it,” Journal of Financial Services Marketing, 7 (3), 206–209.

34.

Hilgert

Marianne A.

Hogarth

Jeanne M.

Beverly

Sondra

(2003), “Household Financial Management: The Connection between Knowledge and Behavior,” Federal Reserve Bulletin, 89 (7), 309–322.

35.

Hoelter Jon

(1983), “The Analysis of Covariance Structures: Goodness-of-Fit Indices,” Sociological Methods and Research, 11 (3), 325–344.

36.

Hofstede

Geert

(2001), Culture’s Consequences. London, England: SAGE.

37.

Hogarth

Jeanne M.

Anguelov

Christoslav E.

(2004), “Are Families Who Use E-Banking Better Financial Managers?,” Financial Counseling and Planning, 15 (2), 61–77.

38.

Hogarth

Jeanne M.

Hilgert

Marianne A.

(2002), “Financial Knowledge, Experience and Learning Preferences: Preliminary Results from a New Survey on Financial Literacy,” Consumer Interests Annual, 48 (1), 1–7.

39.

Howlett

Elizabeth

Kees

Jeremy

Kemp

Elyria

(2008), “The Role of Self-Regulation, Future Orientation, and Financial Knowledge in Long-term Financial Decisions,” Journal of Consumer Affairs, 42 (2), 223–242.

40.

Humphrey

John

Schmitz

Hubert

(1996), “Trust and Economic Development,” IDS discussion paper 355. Brighton, England: Institute of Development Studies, University of Sussex.

41.

Hunt

Shelby D.

Arnett

Dennis B.

Madhavaram

Sreedhar

(2006), “The Explanatory Foundations of Relationship Marketing Theory,” Journal of Business & Industrial Marketing, 21 (2), 72–87.

42.

Jackman

Grace-Anne

Walter L. Leite

Cochrane

David J.

(2011), “Estimating Latent Variable Interactions with the Unconstrained Approach: A Comparison of Methods to Form Product Indicators for Large, Unequal Numbers of Items,” Structural Equation Modeling, 18 (2), 274–288.

43.

Jayanti

Rama K.

Burns

Alvin C.

(1998), “The Antecedents of Preventive Health Care Behavior: An Empirical Study,” Academy of Marketing Science, 26 (1), 9–15.

44.

Johnson

Michael D.

Selnes

Fred

(2004), “Customer Portfolio Management: Toward a Dynamic Theory of Exchange Relationships,” Journal of Marketing, 68 (April), 1–17.

45.

Joo

So-Hyun

Grable

John E.

(2004), “An Exploratory Framework of the Determinants of Financial Satisfaction,” Journal of Family and Economic Issues, 25 (1), 25–50.

46.

Kaplan

David

(2009), Structural Equation Modeling–Foundations and Extension, Advance Quantitative Techniques in the Social Sciences Series, Vol. 10, 2nd ed. Thousand Oaks, CA: SAGE.

47.

Kenning

Peter

(2008), “The Influence of General Specific Trust on Buying,” International Journal of Retail & Distribution Management, 36 (6), 461–76.

48.

Lee

Jinkook

Cho

Jinsook

(2005), “Consumers' Use of Information Intermediaries and the Impact on Their Information Search Behavior in the Financial Market,” Journal of Consumer Affairs, 39 (1), 95–120.

49.

Leisen

Birgit

Hyman

Michael R.

(2004), “Antecedents and Consequences of Trust in a Service Provider: The Case of Primary Care Physicians,” Journal of Business Research, 57 (9), 990–999.

50.

Levesque

Terrence

McDougall

Gordon H. G.

(1996), “Determinants of Customer Satisfaction in Retail Banking,” International Journal of Bank Marketing, 14 (7), 12–20.

51.

Little

Todd D.

Bovaird

James A.

Widaman

Keith F.

(2006), “On the Merits of Orthogonalizing Powered and Interaction Terms: Implications for Modeling Interactions among Latent Variables,” Structural Equation Modeling: A Multidisciplinary Journal, 13 (4), 497–519.

52.

Luhmann

Niklas

(1979). Trust and Power, Chichester, NY: John Wiley.

53.

Maertz

Carl P.

Hassan

Ahmad

Magnusson

Peter

(2009), “When Learning is not Enough: A Process Model of Expatriate Adjustment as Cultural Cognitive Dissonance Reduction,” Organizational Behavior and Human Decision Processes, 108 (1), 66–78.

54.

Malhotra

Deepak

Keith Murnighan

(2002), “The Effects of Contracts on Interpersonal Trust,” Administrative Science Quarterly, 47 (3), 534–559.

55.

McKnight

Harrison D.

Cummings

Larry L.

Chervany

Norman L.

(1998), “Initial Trust Formation in new Organizational Relationships,” Academy of Management Review, 23 (3), 473–490.

56.

Meyer

John W.

Brian

Rowan B.

(1977), “Institutionalized Organizations: Formal Structure as Myth and Ceremonyl,” American Journal of Sociology, 83 (2), 340–363.

57.

Morgan

Robert M.

Hunt

Shelby D.

(1994), “The Commitment-trust Theory of Relationship Marketing,” Journal of Marketing, 58 (3), 20–38.

58.

Morgeson

III

Forrest

Mithas

Sunil

Keiningham

Timothy L.

Aksoy

Lerzan

(2011), “An Investigation of the Cross-National Determinants of Customer Satisfaction,” Journal of the Academy of Marketing Science, 39 (2), 198–215.

59.

Mukherjee

Ashesh

Hoyer

Wayne D.

(2001), “The Effect of Novel Attributes on Product Evaluation,” Journal of Consumer Research, 28 (December), 462–472.

60.

Netemeyer

Richard G.

Boles

James S.

McKee

Daryl O.

McMurrian

Robert C.

(1997), “An Investigation into the Antecedents of Organizational Citizenship Behaviors in a Personal Selling Context,” Journal of Marketing, 61 (July), 85–98.

61.

OECD (Organization for Economic Co-operation and Development) (2006), “The Importance of Financial Education,” Policy Brief, (July), 1–8.

62.

Oehler

Andreas

Kohlert

Daniel

(2009), “Financial Advice Giving and Taking—Where are the Market’s Self-healing Powers and a Functioning Legal Framework When We Need Them?,” Journal of Consumer Policy, 32 (2), 91–116.

63.

Oliver

Richard L.

(1993), “Cognitive, Affective and Attribute Bases of the Satisfaction Response,” Journal of Consumer Research, 20 (January), 418–430.

64.

Ouyang

Yenhui

(2010), “A Relationship between the Financial Consultants' Service Quality and Customer Trust after Financial Tsunami,” International Research Journal of Finance and Economics, 36, 75–86.

65.

Page

Kelly

Uncles

Mark

(2004), “Consumer Knowledge of the World Wide Web: Conceptualization and Measurement,” Psychology & Marketing, 21 (8), 573–591.

66.

Palmatier

Robert W.

Dant

Rajiv P.

Grewal

Dhruv

Evans

Kenneth R.

(2006), “Factors Influencing the Effectiveness of Relationship Marketing: A Meta-Analysis,” Journal of Marketing, 70 (4), 136–153.

67.

Parsons

Talcott

(1967), Sociological Theory and Modern Society. New York, NY: Free Press.

68.

Pennington

Robin

Dixon Wilcox

Grover

Varun

(2003), “The Role of System Trust in Business-to Consumer Transactions,” Journal of Management Information Systems, 20 (3), 197–226.

69.

Perry

Vanessa G.

Morris

Marlene D.

(2005), “Who Is in Control? The Role of Self Perception, Knowledge, and Income in Explaining Consumer Financial Behavior,” Journal of Consumer Affairs, 39 (2), 299–313.

70.

Peterson

Robert A.

(1995), “Relationship Marketing and the Consumer,” Journal of the Academy of Marketing Science, 23 (4), 278–281.

71.

Pučėtaitė

Raminta

Lämsä

Anna-Maija

(2008), “Advancing Organizational Trust in a Post-Structuralist Context: Role of Ethics Management Tools,” Economics and Management, 13, 381–388.

72.

Puspa

Jofi

Kühl

Rainer

(2006), “Building Consumer’s Trust through Persuasive Interpersonal Communication in a Saturated Market: The Role of Market Mavens,” 99th EAAE Seminar “Trust and Risk in Business Networks,” February, 210–221, Bonn, Germany.

73.

Rosenberg

Milton J.

Abelson

Robert P.

(1960), “An Analysis of Cognitive Balancing,” In Attitude Organization and Change: An Analysis of Consistency Among Attitude Components, Rosenberg

M. J.

Hovland

C. I.

McGuire

W. J.

Abelson

R. P.

Brehm

J. W.

, eds. New Haven, CT: Yale University Press, 112–163.

74.

Rotfeld

Herbert Jack

. (2007), “Depending on the Kindness of Strangers,” Journal of Consumer Affairs, 40 (Winter), 407–409.

75.

Rotter

Julian B.

(1980), “Interpersonal Trust, Trustworthiness, and Gullibility,” American Psychologist, 35 (1), 1–7.

76.

Scott

Cuthbert L.

(1980), “Interpersonal Trust: A Comparison of Attitudinal and Situational Factors,” Human Relations, 33 (11), 805–812.

77.

Scott

Richard W.

(2004), “Institutional Theory”, In: Encyclopedia of Social Theory, Ritzer

George

, ed. Thousand Oaks, CA: SAGE, 408–414.

78.

Schumann

Jan H.

Florian

v.Wangenheim

Stringfellow

Anne

Yang

Zhilin

Praxmarer

Sandra

Jiménez

Fernando R.

Blazevic

Vera

Shannon

Randall M.

Shainesh

Komor

Marcin

(2010), “Drivers of Trust in Relational Service Exchange: Understanding the Importance of Cross-Cultural Differences,” Journal of Service Research, 13 (4), 453–468.

79.

Selnes

Fred

(1998), “Antecedents and Consequences of Trust and Satisfaction in Buyer-Seller Relationships,” European Journal of Marketing, 32 (3/4), 305–322.

80.

Selnes

Fred

Sallis

James

(2003), “Promoting Relationship Learning,” Journal of Marketing, 67 (July), 80–95.

81.

Shafir

Eldar

Tversky

Amos

(1992), “Thinking through uncertainty: Nonconsequential Reasoning and Choice,” Cognitive Psychology, 24 (4), 449–474.

82.

Sharma

Neeru

Patterson

Paul G.

(2000), “Switching Costs, Alternative Attractiveness and Experience as Moderators of Relationship Commitment in Professional, Consumer Services,” International Journal of Service Industry Management, 11 (5), 470–490.

83.

Shiu

Edward M. K.

Walsh

Gianfranco

Hassan

Louise M.

Shaw

Deirdre

(2011), “Consumer Uncertainty, Revisited,” Psychology & Marketing, 28 (6), 584–607.

84.

Siegrist

Michael

Gutscher

Heinz

Earle

Timothy C.

(2005), “Perception of Risk: The Influence of General Trust, and General Confidence,” Journal of Risk Research, 8 (2), 145–156.

85.

Sirdeshmukh

Deepak

Singh

Jagdip

Sabol

Barry

(2002), “Consumer Trust, Value and Loyalty in Relational Exchanges,” Journal of Marketing, 66 (1), 15–37.

86.

Tam

Jackie L. M.

(2006), “Managing Customer Expectations in Financial Services: Opportunities and Challenges,” Journal of Financial Services Marketing, 11 (4), 281–289.

87.

Tax

Stephen S.

Brown

Stephen W.

Chandrashekaran

Deborah

(1998), “Customer Evaluations of Service Complaint Experiences: Implications for Relationship Marketing,” Journal of Marketing, 62 (April), 60–76.

88.

Todd

Peter M.

Gigerenzer

Gerd

(2003), “Bounded Rationality to the World,” Journal of Economic Psychology, 24 (2), 143–165.

89.

Tomlinson

Edward C.

Mayer

Roger C.

(2009), “The Role of Causal Attribution Dimensions in Trust Repair,” Academy of Management Review, 34 (1), 85–104.

90.

Perrin

Towers

(2008), “Financial Literacy and Transparency Initiatives and Tools in Life and Pensions,” DIA Report, 6, 115.

91.

Uslaner

Eric M.

(2010), “Trust and the Economic Crisis of 2008,” Corporate Reputation Review, 13 (2), 110–123.

92.

Walczuch

Rita

Lundgren

Henriette

(2004), “Psychological Antecedents of Institution based Consumer Trust in E-retailing,” Information & Management, 42 (1), 159–177.

93.

Weiner

Bernard

(2000), “Attributional Thoughts about Consumer Behavior,” Journal of Consumer Research, 27 (December), 382–387.

94.

Weiner

Bernard

(1991), “Metaphors in Motivation and Attribution,” American Psychologist, 46 (9), 921–30.

95.

Weiner

Bernard

(1986), An Attributional Model of Motivation and Emotion. New York, NY: Springer-Verlag.

96.

Wilkens

Uta

Nermerich

Daniel

(2011), “Love it, Change it, or Leave it–Understanding Highly-Skilled Flexible Workers' Job Satisfaction from a Psychological Contract Perspective,” Management Revue , 22 (1), 65–83.

97.

Williamson

Oliver

(1993), “Calculativeness, Trust, and Economic Organization,” Journal of Law and Economics, 36 (1), 453–486.

98.

Xiao

Jing Jian

Tang

Chuanyi

Shim

Soyeon

(2009), “Acting for Happiness: Financial Behavior and Life Satisfaction of College Students,” Social Indicators Research, 92 (1), 53–68.

99.

Xiao

Jing Jian

Sorhaindo

Benoit

Thomas Garman

(2006), “Financial Behaviours of Consumers in Credit Counselling,” International Journal of Consumer Studies, 30 (2), 108–121.

100.

Jun

Marinova

Detelina

Singh

Jagdip

(2007), “Strategic Change Implementation and Performance Loss in the Front Lines,” Journal of Marketing, 71 (4), 156–171.

101.

Zak

Paul

Knack

Stephen

(2001), “Trust and growth,” Economic Journal, 111 (April), 295–321.

102.

Zboja

James J.

Voorhees

Clay M.

(2006), “The Impact of Brand Trust and Satisfaction on Retailer Repurchase Intentions,” Journal of Services Marketing, 20 (5), 381–390.

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