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Heather A. Triezenberg & Shawn J. Riley Michigan State University, Fisheries & Wildlife

Trust-space continuum: A spatial analysis of stakeholders’ trust and confidence in a state wildlife agency. Heather A. Triezenberg & Shawn J. Riley Michigan State University, Fisheries & Wildlife Sarah L. Hession & Wenjuan Ma

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Heather A. Triezenberg & Shawn J. Riley Michigan State University, Fisheries & Wildlife

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  1. Trust-space continuum: A spatial analysis of stakeholders’ trust and confidence in a state wildlife agency Heather A. Triezenberg & Shawn J. Riley Michigan State University, Fisheries & Wildlife Sarah L. Hession & Wenjuan Ma Michigan State University, Center for Statistical Training & Consulting

  2. Acknowledgements • Michigan Department of Natural Resources’ Wildlife Division • Federal Aid in Wildlife Restoration • Graduate School at Michigan State University • Dr. Julie Brockman MSU School of Human Resources & Labor Relations • Charlotte Powers & Stanton Mack MSU Department of Organizational Psychology • Respondents to our questionnaires

  3. Latent Factor Model of Trust and Confidence in the MiDNR Wildlife Division • Direct effects, standardized path coefficient, z-statistic in parenthesis, *=p<.01 for straight line; covariance, z-statistic in parenthesis, * = p<.01 for curved line • (X2 = 153, df = 38, X2/df = 4.03, p=.00, CFI=.99, RMSEA = .04, 90% RMSEA confidence interval .03 – .04

  4. Wildlife Division Administrative Regions

  5. Trust and Space • Common Belief: Residents from Michigan’s Upper Peninsula have different beliefs than the rest of the state • Tobler’s first law: everything is related, but nearer things are more related than distant things

  6. Objectives • Determine the scale for testing spatial relationships of trust/confidence in MiDNR WD • Test the influence of spatial relations on variables • Identify variables that predict trust/confidence in MiDNR WD • Identify the spatial scale of nearest neighbor clustering for respondents with similar levels of trust/confidence in a SWA

  7. Methods • n = 6,825 Resident hunting license (any) buyers for 2012 season; >18 years; Stratified for MiDNR WD regions • Modified tailored design method • Administered February – May 2013 • Non-respondent telephone survey May – June 2013 • MSU IRB approval #x12-1201e • SPSS v19; Stata v12 & v13; Mplus 7.01, ArcGIS 10.1, GeoDa1.4.1

  8. Methods • Single imputation of missing data with random draw • Weighted data according to proportion of respondents being represented by proportion of license buyers/region • Computed factor score for each latent factor • Geocoding and Moran’s I conducted in ArcGIS • Weights matrices created and spatial analysis in GeoDa • Spatial Lag Model • Spatial Error Model • OLS Regression

  9. Results • 39% usable response rate (n = 2,691) • Respondents were more critical of WD than non-respondents • I believe that the WD as a whole is effective at managing Michigan’s wildlife resources: respondents (M= 3.00, SD=.99) vs. non-respondents (M=3.39, SD=1.20); t(df) = -4.02(170), p=.00). • 91% male • Age M=54 years; SD = 14.31

  10. Residence Direct effects, standardized path coefficient, z-statistic in parenthesis, *=p<.01 for straight line; covariance, z-statistic in parenthesis, * = p<.01 for curved line

  11. Interests Direct effects, standardized path coefficient, z-statistic in parenthesis, *=p<.01 for straight line; covariance, z-statistic in parenthesis, * = p<.01 for curved line

  12. Geocoding of Survey Respondents n= 2,691 point locations

  13. Clustering 25 km Moran’s I = 0.022 10 km Moran’s I = 0.007 5 km Moran’s I = 0.016

  14. Results So what? Use OLS regression, with direct effects if needed

  15. Predictor Variables & Coefficients Procedural Fairness 0.48** Technical Competence 0.11** Dependent Variable Moral Agreement -0.06** Beliefs about Government 0.02 Trust/Confidence in MiDNR Wildlife Division Value Congruence 0.48** Interaction with MiDNR WD -0.04* Age -0.001 Gender -0.02 *<0.05, **<0.01

  16. Predictor Variables & Coefficients Controlling for Region of Residence Procedural Fairness 0.48** Procedural Fairness 0.48** Dependent Variable Tech. Competence 0.11** Tech. Competence 0.11** Moral Agreement -0.06** Moral Agreement -0.06** Beliefs about Government 0.02 Beliefs about Government 0.02 Trust/Confidence in MiDNR Wildlife Division Value Congruence 0.48** Value Congruence 0.48** Controlling for Region of Recreational Interest Interaction with MiDNR WD -0.03* Interaction with MiDNR WD -0.03* Age -0.001 Age -0.001 Gender -0.01 Gender -0.01 I_NLP 0.04* R_NLP 0.04 R_SWL0.05* I_SWL0.04 I_SEL0.07** R_SEL0.08** *<0.05, **<0.01

  17. Cluster Analysis at 25km Neighbors within 25km have similar levels of high trust in WD Neighbor points within 25 km have similar levels of low levels of trust in WD

  18. A Few More Thoughts • Theoretical model relatively stable across space • More heterogeneity in trust/confidence in Southern Michigan than other areas • Trust/confidence may be managed in the extent to which there address: • procedural fairness • value congruence

  19. Thank You Heather A. Triezenberg vanden64@msu.edu www.fw.msu.edu/~vanden64

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