10.5 Understanding the Role of Trust in Public Support for Weather (and Other) Drones: Results of a Nationally Representative U.S. Survey

Thursday, 11 January 2018: 11:30 AM
Ballroom F (ACC) (Austin, Texas)
Lisa PytlikZillig, Univ. of Nebraska Public Policy Center, Lincoln, NE; and A. Houston, J. Walther, J. Kawamoto, and C. Detweiler

Understanding the Role of Trust in Public Support for Weather (and Other) Drones: Results of a Nationally Representative U.S. Survey

Public trust is commonly referenced as an important factor influencing technology acceptance (Wu, Zhao, Zhu, Tan, & Zheng, 2011). Much of the research on trust, defined as a willingness to be vulnerable due to positive expectations (Rousseau, Sitkin, Burt, & Camerer, 1998), has focused on the bases of trust, such as the dispositions and perceptions that facilitate trust (Mayer, Davis, & Schoorman, 1995; PytlikZillig et al., 2017). However, little research has investigated the impact of different configurations of trust and distrust in specific actors within multi-actor contexts. Understanding public concerns and who or what the public needs to trust, before they will offer support for a new technology, can help to direct efforts to be more responsive to and better meet publics’ hopes and concerns.


New technologies such as unmanned aerial vehicles (i.e., UAVs or drones) designed for weather research may be trusted or distrusted to operate reliably and function without causing other harms. Separately, users of the drones may be trusted or distrusted to use the drones benevolently, competently, and with integrity; and regulators of the drones may be trusted or distrusted to competently set enforceable regulations that benefit the public’s interests and values. Because each of these entities (drones, users, and regulators) have an impact on how drones are used and integrated into society, we hypothesized public trust in each entity is likely to impact public support for the drones’ development and use.

However, there is a gap in the literature regarding the relative importance of trust in different entities. All potential trustees may not be equally important. Public acceptance of drones could hinge more or less on one trustee or another, and the importance of trust in different entities might vary across different public demographics. In addition, trust in or distrust of one entity may impact the importance of trust in another trustee.

Our team designed a national survey experiment capable of investigating the role of trust in support for new drone technologies and answering the following research questions:

  • Public attitudes: What are various publics’ most salient expectations and concerns when it comes to weather drones? Which publics are most supportive of drones for weather data collection?
  • Important trustees: Who or what is the most important trustee when it comes to support for weather drones? Does the importance of different trustees vary by drone purpose or characteristics of the publics that are surveyed?
  • Configurations of trust: How do levels of trust in specific different entities interact to impact public support for the use of weather drones?


In early 2017, the survey was administered to a nationally representative sample of 2100 U.S. adults recruited by Qualtrics Panels. Participants reported their demographics and general attitudes toward drones, prior to responding to a short drone use scenario. Within the scenario, we experimentally varied drone purpose (weather research, prescribed fires, delivery, movie making), actor using the drone (public or private), and location of use (rural or urban). Participants indicated their support for the development and use of drones in the scenario context, and rated how realistic they found the scenario, as well as their perceptions of the trustworthiness of drone users and regulators, and of the drone technology. At the end of the survey, to assess participant attentiveness and expectations, they reported their recollection of the features of the scenario they had viewed (i.e., who was using the drone, for what, and where).


This presentation will focus on a number of interesting results from the survey data. For example, descriptive and correlational results indicate white, educated, more liberal publics hold the most favorable attitudes toward weather drones, and weather drones garner significantly more support than other purposes examined. Participant ratings further indicated lower levels of concerns were provoked by weather uses than other uses. Meanwhile, participant ratings of scenario realism as well as their misrecollection of certain scenario features suggest public expectations that weather drones will be used by public entities and in rural areas.

Results from hierarchical regressions indicate the strongest trust-relevant driver of public support for drones is trust in the technology. Also, trust operates in an additive and compensatory manner. That is, trust in each entity significantly and independently contributes to public support for drones. However, significant negative interactions indicate that as trust in one entity increases, trust in another entity becomes less important. We also found evidence in line with our theoretical predictions that compulsory trust (i.e., requiring trust in multiple actors before offering support) emerged among publics with more negative attitudes toward drones overall.

Discussion and Conclusions

In line with this conference’s thematic emphasis on careful listening, understanding, and appropriate responding, data from our public survey suggest that different publics may need somewhat different responses to encourage their support of weather drones. Overall, public support for weather drones is relatively high and appears primarily to require drone design features and public communications that assure the public of the trustworthiness of the drone technology. However, more skeptical publics may also require regulations and trainings that further ensure and reassure responsible and safe use of weather drones.


Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. Academy of Management Review, 20, 709-734.

PytlikZillig, L. M., Kimbrough, C. D., Herian, M. N., Bornstein, B. H., Tomkins, A. J., Hamm, J. A., . . . Neal, T. M. (2017). A longitudinal and experimental study of the impact of knowledge on the bases of institutional trust. PLoS ONE, 12(4), e0175387. Retrieved from https://doi.org/10.1371/journal.pone.0175387

Rousseau, D. M., Sitkin, S. B., Burt, R. S., & Camerer, C. (1998). Not so different after all: a cross-discipline view of trust. Academy of Management Review, 23, 393-404.

Wu, K., Zhao, Y., Zhu, Q., Tan, X., & Zheng, H. (2011). A meta-analysis of the impact of trust on technology acceptance model: Investigation of moderating influence of subject and context type. International Journal of Information Management, 31(6), 572-581.

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