On Developing an Inter-Agency Trust Scale for Assessing Governance Networks in the Public Sector

ABSTRACT

This article presents the development and validation of a psychometric scale for assessing public sector inter-agency trust. The instrument is grounded in contemporary trust theory and methodologically adapted from a measure developed for private sector alliances. Tested using four discrete studies of governance networks, each addressing transboundary environmental issues such as climate change and fisheries, the scale exhibits reasonably valid psychometric properties while also enabling visualized analysis of networked trust distributions. Based on this work, we outline further research needs with a view to stimulating greater trust research in governance networks and facilitating more collaborative and innovative policy outcomes in the public sector.

ACKNOWLEDGMENTS

The authors thank the anonymous survey participants who generously donated their valuable time, experience, and knowledge to the study. Gratitude is also expressed to colleagues and agency staff who provided advice on the design of the scale.

Notes

The number of cases used for the analysis in each data set is different than the number of completed survey responses for two reasons. First, in a small number, respondents chose answers that brought the survey to logical completion but without the trust-related questions being posed. Second, some respondents failing to complete the survey nevertheless answered the portions related to inter-organizational trust. In the latter case, the trust data (from both complete and incomplete responses) were utilized.

The model we tested was not specifically a second-order factor model. With only six items, we did not have enough degrees of freedom to fully estimate such a model. Nevertheless, the SEM results present evidence that such a model would be viable.

The chi-square goodness-of-fit test was not used, since it is particularly sensitive to sample sizes (that is, it tends to produce less valid approximation when the sample size is not sufficiently large). To alleviate this issue, we opted to use the other goodness-of-fit measures which are easier to read and interpret.

The goodness-of-fit measures for the British Columbia and New York data are not as good as we would have liked, yet the models border on the traditional acceptable values (RMSEA < .10, CFI  > .95). After careful inspection of the items, we explored the possibility of a different structure. The observed item HabA appears to relate to both Relational Comfort and Fair Play. We estimated a structural model that includes HabA as a measure of both latent constructs for both the British Columbia and the New York data. While the model did not converge for the New York dataset, the results for the British Columbia data increased the model fit as expected (RMSEA = .071, CFI =.960). These results suggest that our scale might have more complexities that emerge in different settings. Exploring the specific changes case by case is beyond the scope of this article, but signals that, when using this scale, we must keep each specific context in mind.

Scores for RC and FP between jurisdictions were calculated using the following procedure: (1) the RC and FP data of a respondent for each of the target agencies he/she indicated to be in professional contact were grouped according to the jurisdiction to which the agencies belong. The RC and FP scores that fall within each jurisdiction were then averaged so that each respondent has a RC and FP score assigned to them for each target jurisdiction; (2) these respondent-specific scores on each target jurisdiction were next categorized by the home jurisdiction of the respondent and averaged—this step produced trust scores (RC and FP) to and from each jurisdiction; (3) finally, they were standardized to −1 to 1 scale.

Additional information

Funding

This work was supported by the Social Sciences and Humanities Research Council of Canada (grant number 430-2011-0644; 435-2014-0970) and the IBM Center for the Business of Government, Washington DC, USA.

Notes on contributors

Andrew M. Song

Andrew M. Song ([email protected]) was a postdoctoral fellow in the Department of Natural Resource Sciences at McGill University when this study was conducted. He is currently a research fellow at the Australian Research Council Centre of Excellence for Coral Reef Studies, James Cook University, Australia, exploring the issue of multi-scalar, transboundary fisheries governance in the Asia-Pacific region. Also affiliated with WorldFish, his work has appeared in journals such as Marine Policy, Society & Natural Resources, Political Geography, and Current Opinion in Environmental Sustainability.

Angel Saavedra Cisneros

Angel Saavedra Cisneros ([email protected]) is an assistant professor of political science at St. Norbert College. He specializes in minority political psychology, measurement and campaigns in both the USA and Mexico. His recent book is titled Latino Identity and Political Attitudes: Why are Latinos Not Republican.

Owen Temby

Owen Temby ([email protected]) is an assistant professor of political science at the University of Texas Rio Grande Valley. Previously, he worked as a postdoctoral fellow at McGill University and Carleton University. He is the author of numerous articles in respected journals and co-editor of the forthcoming book, Towards Continental Environmental Policy? North American Transnational Networks and Governance (SUNY Press). Presently, Dr. Temby serves as co-editor of Urban History Review/Revue d’Histoire Urbaine and environmental policy book review editor of Review of Policy Research.

Jean Sandall

Jean Sandall ([email protected]) is the Director of Customer Research and Insights at the Department of Transport and Main Roads, Queensland. She contributed to this program of research while undertaking a postdoctoral fellowship in the Department of Natural Resource Sciences at McGill University. Her research interests reflect her aspiration to build the capacity of government to address complex social and environmental issues by harnessing science and collaborative leadership across agency boundaries.

Ray W. Cooksey

Ray Cooksey ([email protected]) is Emeritus Professor in the UNE Business School at the University of New England and is a Fellow of the Australian and New Zealand Academy of Management. His research areas include managerial and educational decision making, complexity theory, systems theorizing, psychometrics and statistics, and research methods. He is the author of Judgment Analysis: Theory, Methods & Applications (Academic Press), several other books on social research methods and statistics, and more than 70 refereed publications.

Gordon M. Hickey

Gordon M. Hickey ([email protected]) is an Associate Professor and William Dawson Scholar in the Department of Natural Resource Sciences at McGill University, Canada. His international research applies mixed-method techniques to explore the institutional processes affecting sustainable natural resource-related policymaking and implementation, with a particular focus on innovation. His work has appeared in journals such as Organization & Environment, Social Studies of Science, Science and Public Policy, International Journal of Forecasting, Food Policy, Land Use Policy, and World Development.