Data analyses
We applied the Cronbach’s alpha coefficient to test the reliability and internal consistency of responses across items in the questionnaire (acceptable value= 0.80 > α > 0.70). We characterized each visitor’s perception and attitude according to their sociodemographic backgrounds (e.g., gender, group, age, educational attainment). To test for the significant difference in categorical responses based on their sociodemographic backgrounds, we used Pearson’s chi-squared test of independence (ꭓ2). A Cramer’sV was then applied to measure strength of association between variables (V values: weak < .10, low < .10> .30, and moderate < .30> .50).
We performed separate generalised linear regression (GLMs) to determine variables that predict tourists’conservation willingness in the (i) pre-visit and (ii) post-visit. We pooled the responses “Not sure” with “No” and coded as “Not willing” and “Yes” as “Willing” (e.g., Carson et al. 1995; Mulema et al. 2020) to fit with the binary modelling following Aziz et al. (2017). We used the values obtained from mean scores of each indicator in pre-visit and post-visit variables (Supplementary data 1) and sociodemographic profiles as covariates and factors in the binomial logistic model. The (a) prior experience and recognition, (b) knowledge and understanding about Philippine bats, and (c) and prior knowledge of ecosystem services were used as predicting variables for pre-visit conservation willingness. Next, we used: (a) learning and aesthetic satisfaction, (b) perceptions about conservation importance, (c) enhanced knowledge of ecosystem services of bats and (d) prior knowledge about ecosystem services as predicting variables for post-visit conservation willingness. We choose the best model based on the lowest of Akaike’s Information Criteria (AIC) values.
Consequently, to determine the effectiveness of short-term enhancement of knowledge about bat ecosystem services and conservation willingness, we applied the non-parametric Wilcoxon rank test to assess the significant relationship between visits. All reliability and statistical tests were performed using the open-source program Jamovi version 1.2.6 (The Jamovi Project 2020). We set our statistical significance atp = .05.