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It’s all relative: how customer-perceived competitive advantage influences referral intentions

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Abstract

Better understanding the mechanisms that influence customer intentions to spread positive word-of-mouth (WOM) is crucial to both marketing scholars and managers. This multimethod research contributes to marketing knowledge by revealing how a firm’s customer-perceived competitive advantage (CPCA) influences positive WOM intentions. Analyses of (1) cross-sectional survey data on bank customers in Germany and (2) experimental data on customers of car insurance companies in the USA reveal two crucial insights. First, CPCA influences WOM intentions in both industries, over and above numerous established antecedents of customer loyalty (e.g., satisfaction, trust, and perceived value). Second, this research demonstrates a robust and pervasive CPCA-by-satisfaction interaction effect, such that the influence of CPCA on WOM intentions increases as customer satisfaction decreases. The results show that customer-perceived competitive advantage plays an important role in shaping WOM intentions, especially among less-satisfied customers. Theoretical and managerial implications of these findings are discussed.

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Notes

  1. Because not all survey questions were asked of every consumer (to keep the survey short), our analyses include 1,963 customers.

  2. We also conducted a factor analysis (principal component analysis with an oblique rotation) to explore the discriminant validity between the four CPCA items and the global satisfaction item. This analysis resulted in a two-factor solution. The two factors were moderately correlated (r = 0.37). The final rotated solution explained 66.91 % of the total variance in the items (CPCA accounted for 51.23 % and satisfaction for 15.68 % of the total variance). The factor loadings displayed a clean factor structure. The magnitude of factor loadings was satisfactory and meaningful, with loadings on the target factor (CPCA) ranging from 0.61 to 0.86. A similar analysis using the data from study 2 (four CPCA items and three satisfaction items) also extracted two factors and showed a clean factor structure and meaningful loadings. Taken together, these analyses suggest that satisfaction and CPCA represent distinct constructs and should be treated separately.

  3. We also examined the results when CPCA is omitted by running a restricted model (OLM without CPCA). Two insights emerged. First, eliminating CPCA results in a considerable drop in McKelvey and Zavoina’s R 2 in the equation. Second, in the absence of CPCA, satisfaction is statistically significant. However, when CPCA is controlled for, satisfaction is rendered nonsignificant. This finding suggests that the omission of CPCA fundamentally alters the conclusions about the relationships between satisfaction and WOM intentions. In an additional analysis, we explored a potential nonlinear effect by adding a satisfaction2 variable to the model. The coefficient for this satisfaction2 variable was nonsignificant (p > 0.17). Adding this variable did not alter the pattern of our hypothesized effects; the CPCA main effect remained significant (p < 0.01; H1), and the satisfaction-by-CPCA interaction term also remained significant (p < 0.05; H2).

  4. Because the wording of the value item included the word “satisfied” (see Appendix 1), we explored whether the value variable may have influenced our results. Therefore, we re-ran our analyses without the value variable. The corresponding results regarding our hypothesized effects were highly similar. That is, the main effect of CPCA on WOM intentions was still significant, and the CPCA-by-satisfaction interaction also remained significant (this is true for studies 1 and 2). In summary, even in the absence of value, the results support H1 and H2.

  5. We are grateful to one of the reviewers for suggesting an experimental study to demonstrate causality.

  6. “Number of relationships” was not included as a covariate because consumers work with only one car insurance company per vehicle (notably, this variable also had no significant effect in study 1; p > 0.85).

  7. These analyses controlled for all covariates displayed in Table 3; details are available on request.

  8. We are grateful to one of the reviewers for suggesting this avenue for further research.

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Acknowledgments

The authors are grateful to the editor and the two anonymous reviewers for the constructive and supportive feedback. Moreover, they thank Ruth Bolton, Mark Houston, Mike Hutt, and Maura Scott for helpful comments on earlier versions of this paper.

Author information

Authors and Affiliations

  1. Department of Marketing, College of Business, Florida State University, Tallahassee, FL, 32306-1110, USA

    Martin Mende

  2. Marketing Department, Terry College of Business, University of Georgia, Athens, GA, 30602, USA

    Scott A. Thompson

  3. Services Management, Zurich University of Applied Sciences, Zurich, Switzerland

    Christian Coenen

Authors
  1. Martin Mende
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  2. Scott A. Thompson
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  3. Christian Coenen
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Corresponding author

Correspondence to Scott A. Thompson.

Appendices

Appendix 1 Measurement of variables (study 1)

WOM intentiona

• Will you recommend ABC Bank to friends and family?

CPCAa, b

• Compared to its competitors, how do you assess ABC Bank’s products?b

• Compared to its competitors, how do you assess ABC Bank’s customer service?b

• Compared to its competitors, how do you assess ABC Bank’s fees and conditions?b

• Do you think ABC Bank provides you with more advantages than other financial service providers you would consider?a

Satisfactionc

• Thinking of all your experiences with ABC Bank, how satisfied are you with ABC Bank?

Customer valuec

• Comparing the total value you receive to the total price you pay, how satisfied are you with this “price-value-ratio” at ABC Bank?

Trustd

• I have great trust in the services and products of ABC Bank.

Affective bondd

• As a customer of ABC Bank, I feel like being part of a big family.

Brand reputationd

• ABC Bank is reputable.

Market screeningd

• To be able to compare, I always check conditions and terms of other banks.

Tenure

• How many years have you been a customer of ABC Bank?

Complaint

• During the last 12 months, have you had any reason to complain to ABC Bank? (Dummy coded)

Number of Bank Rel.

• How many banking relationships do you have in total (including ABC Bank)?

Demographics

• Gender, age, income (Dummy coded)

  1. For study 1, the collaborating market research firm worded the corresponding measures in line with the approach in all its surveys. Therefore, all variables in study 1 are coded such that lower scores suggest a more positive assessment by the consumer. The authors did not have any influence on the items or the measurement scales used and—consequently—some of the measures and their response categories are non-standard relative to prior scholarly marketing research. Importantly, however, study 2 uses measures from the academic marketing literature (e.g., seven-point Likert-type scales, coded from “strongly disagree” to “strongly agree”) and the results across studies 1 and 2 are highly consistent. Therefore, the nonstandard measurement of variables in study 1 does not reasonably explain the results of this study
  2. aVariable measured on a five-point Likert-type scale (1 = definitely, 5 = definitely not)
  3. bVariable measured on a five-point Likert-type scale (1 = far better, 5 = far worse)
  4. cVariable measured on a five-point scale (1 = completely satisfied, 5 = dissatisfied)
  5. dVariable measured on a four-point Likert-type scale (1 = completely agree, 4 = completely disagree)

Appendix 2 Measurement of variables (study 2)

Construct

Measure

Source

WOM intentiona

Coefficent alpha: 0.96

• How likely are you to tell others positive things about (company)?

• If your friends were looking for car insurance, how likely are you to tell them about (company)?

• If you were helping a colleague make a decision on what car insurance to get, how likely are you to recommend (company)?

Brown et al. (2005); Zeithaml et al. (1996)

CPCAb, c

(manipulation checks)

Coefficent alpha: 0.95

• The Consumer Reports study found (company) to be superior/comparable/inferior relative to its competitors.

• According to the Consumer Reports study, compared to its competitors, the products of (company) are superior / comparable / inferior

• According to the Consumer Reports study, compared to its competitors, the customer service of (company) is superior / comparable / inferior

• According to the Consumer Reports study, compared to its competitors, the prices, premiums, and fees of (company) are superior / comparable / inferior

 

Satisfactionb

Coefficent alpha: 0.93

• I am satisfied with (company); I am content with (company); I am happy with (company).

Thomson (2006)

Customer valueb

• Comparing the total value I receive from (company) to the total price I pay, I am satisfied with this price/value ratio.

Zeithaml (1988)

Trustb

Coefficent alpha: 0.85

• (Company) is trustworthy; (Company) keeps its promises; (Company) is truly concerned about my welfare.

Doney and Cannon (1997)

Affective bondb

Coefficent alpha: 0.86

• I feel a sense of belonging with (company); I feel attached to (company).

Gruen et al. (2000); Verhoef (2003)

Brand reputationb

• (Company) is reputable.

Selnes (1993)

Market screeningb

• To be able to compare, I always check conditions and terms of other car insurance companies.

 

Tenure

• Approximately, how many years have you been a customer of (company)?

 

Complaint

• During the last 12 months, have you had any reason to complain to (company)? (Dummy coded)

 

Demographics

• Gender, age, income (Dummy coded)

 

aVariable measured on a seven-point Likert-type scale (1 = very unlikely, 7 = very likely)

bVariable measured on a seven-point Likert-type scale (1 = strongly disagree; 7 = strongly agree)

cVariable measured on a seven-point Likert-type scale (1 = by far inferior to competitors; 7 = by far superior to competitors)

Appendix 3 Manipulation of CPCA (as used in study 2, “superior condition”)

At this point, you might be interested to learn about a new study on the competitiveness of car insurance companies published by Consumer Reports. This study revealed the three following findings regarding YOUR insurance company (i.e., insurance brand name was inserted here):

  • Finding 1: [Insurance brand] offers superior insurance products relative to its competitors.

  • Finding 2: [Insurance brand] offers superior customer service relative to its competitors.

  • Finding 3: [Insurance brand] offers superior prices, premiums, and fees relative to its competitors.

In sum: According to this study, [insurance brand] is superior relative to its competitors.

In the comparable and inferior conditions, the word “superior” was replaced by “comparable” and “inferior,” respectively. In the graphic, the three visual markers were placed accordingly below the center dot (comparable condition) and below the right dot (inferior condition).

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Mende, M., Thompson, S.A. & Coenen, C. It’s all relative: how customer-perceived competitive advantage influences referral intentions. Mark Lett 26, 661–678 (2015). https://doi.org/10.1007/s11002-014-9318-x

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