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Understanding trustworthiness: using response latencies from CATI surveys to learn about the “crucial” variable in trust research

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Abstract

Research on trustworthiness and trust behavior so far has followed different methodological approaches and has generated conflicting evidence regarding their interrelationships. While several authors follow the definition of trustworthiness as a belief or a formed expectancy by Person A about Person B to do X (usually to reward trust), different hypotheses can be derived regarding its formation, depending on whether one treats trustworthiness as incentive-based or as a propensity or disposition. Additionally, distinct measurement approaches for trustworthiness exist, depending on the mode of data collection. With theoretical claims that trustworthiness represents “the crucial variable” (Hardin in Trust, 2006) for understanding and explaining successful cooperation based on trust, the article proposes the use of para-data in the form of response latency measurement to enhance the understanding of the thought processes behind forming an assessment of trustworthiness. The study uses pooled data from two CATI surveys conducted in Germany in 2012 to test hypotheses on the underlying cognitive process of forming an expectation of trustworthiness by applying the techniques of both response latency measurement and Cox regression models. We find that the applied survey measures of trustworthiness generate inconsistent results regarding the underlying process of forming expectations. Consequences for future research are discussed.

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Notes

  1. This conceptualization of trustworthiness has led to an agreement within research on trust and trustworthiness that equates the expectation of trustworthiness with trust (Glaeser et al. 2000; although this may not be entirely warranted, see Hardin 2006, p. 32).

  2. Freitag and Traunmüller (2009, p. 9) distinguish dispositions from experiences to understand the logic of trust, but they differentiate with regards to the two facets of particularized and generalized trust. We will limit our study to the investigation of trustworthiness as we will not be able to account for trusting behavior during telephone interviews. We return to this point later.

  3. It appears obvious that the assumption that expected trustworthiness can be equated with trust is misguided, as it ignores the conditions of an action based on trust that is shaped by G and L as well p. Expectancies can be formed without trusting. We cannot elaborate on that further, see Hardin (2006) on these issues.

  4. We put the player in quotation marks as we did not perform any real experiments or trust games. The respondents in the survey were merely put in two situations resembling their role in games, although there did not exist any dyadic interactions. Respondents answered question from the perspective of “Player A” and “Player B”, or the trustor and the trustee of the traditional trust game, respectively. Details follow in the section on methods and data.

  5. Obviously, this relates well to the ideas of rational choice theory, where actions are explained by variation of conditions given a set of preferences, levels of information and assumptions about the rationality of actors (Opp 1999).

  6. Prior experiences are considered a crucial predictor to explain action based on trust (Fehr et al. 2002, p. 540).

  7. Scholars that appear to have replicated this finding do not speak about trustworthiness but rather about reciprocity, risk aversion or unconditional kindness (Altmann et al. 2008; Ashraf et al. 2006).

  8. Usually the amount sent is doubled or tripled and the trustee decides about the amount to be sent back. Ashraf, Bohnet, and Piankov (2006, p. 197) go so far to define trustworthiness by this measurement.

  9. To clarify, we do not accept the proposal “that trust is the expectation about other people’s behavior” and that “both the answers to the WVS-question and the sender’s expectation in a traditional trust game can be used as a measure” for trust (Sapienza et al. 2013, p. 1330). Trust represents an action based on an expectation.

  10. These efforts go beyond the usual practice of using response time measurement for pretests of questionnaires to detect mode effects or undesired response tendencies (for an overview see Yan and Tourangeau 2008; Dillman et al. 2009).

  11. See Neumann (2014) for additional validity checks of latency measures.

  12. We will document results for both valid and invalid measurements as an additional feature to our study.

  13. As RLD or RDD procedures are not feasible in Germany, the Gabler–Haeder design draws household numbers randomly from pre-generated blocks of entries. For more details, see Gabler and Häder (2002) for Germany and Häder (2012) for Europe.

  14. This has to be considered rather low with regards to average response rates for telephone interviews in Germany (Häder 2012, pp. 124–125), but Wang et al. (2014) report equally low response rates for the US.

  15. Three cases were dropped from the sample because of ineligibility due to age.

  16. Descriptive statistics for the Cox models are generated by applying the stset-command in Stata. These summary statistics can be provided upon request. Note that for all these models, the proportionality assumption holds.

  17. Cronbach’s \(\alpha \) for the trust index comes in at only 0.63, which has to be considered rather low. To circumvent the low reliability of the trust index, analyses were performed with single answers to the generalized trust item, but results did not change at all. Result can be provided upon request from the authors.

  18. These findings are not in line with the results in Mulligan et al. (2003, p. 297), who generate similar results for measurements with and without validity coding.

  19. With respect to the skewed distribution of the dependent variable, we also estimated two-tier regression models via the craggit-command in Stata (Cragg 1971; Burke 2009). Results do not differ in the sense that, for the first stage, answers with the highest level of behavioral trustworthiness were given fast and prior experience mattered, whereas generalized trust could not be considered as a relevant predictor. The coefficients for socio-demographic variables showed consistent results within the first stage model. Same holds for the part of the truncated regression model, although the latency scores lose their predictive power for the remaining levels or reported behavioral trustworthiness (measurements were validated, \(n=239\)). Results are not shown, but can be obtained upon request.

  20. The results could be criticized regarding the potential confounding effect of generalized trust on the dependent variable of expected trustworthiness. Both variables correlate at 0.22 \((p<0.05, n=569)\), which can be considered rather low. Dropping the generalized trust variable from the model yields the same results, with both indices for the response latencies as the only variables that explain the variation of the responses to the trustworthiness item T2. Results can be provided upon request.

  21. Notable exemptions exist: For instance, Przepiorka and Diekmann (2013, p. 3) test a model proposed by Posner (1998) by an experimental sequence where the signal of trustworthiness is sent by a trustee prior to the placement of trust by Player A, which conforms to the causal structure of a trust relationship.

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Acknowledgments

The author would like to thank participants of the RC45 and RC33 sessions of ISA World Congress 2014 in Yokohama, Japan, and the anonymous referees for helpful comments. The author is indebted to Lars Hiller for technical support.

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  1. Chair in Methods in Empirical Social Sciences, Technische Universität Dresden, Dresden, Germany

    Robert Neumann

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Appendix

Appendix

See Tables 6, 7 and 8.

Table 6 Summary statistics for respondent’s age, generalized trust and the two latency measures (pooled from two sub-samples)
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Table 7 Frequency statistics for the independent variables (pooled from two sub-samples)
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Table 8 Frequency statistics for the validation coding of the manual response time measurement for the items T1 (behavioral trustworthiness) and T2 (expected trustworthiness), pooled from two sub-samples
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Neumann, R. Understanding trustworthiness: using response latencies from CATI surveys to learn about the “crucial” variable in trust research. Qual Quant 50, 43–64 (2016). https://doi.org/10.1007/s11135-014-0136-2

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