How do online green motivations prompt green travel? A hybrid fsQCA–ANN investigation

Since promoting individual green travel has been regarded as an effective way to reduce carbon emissions, we are curious to know how online green motivations prompt green travel. Contrary to traditional symmetrical logic and linear causal analyses, this study adopted a configurational perspective, fuzzy set qualitative comparative analysis (fsQCA) and 203 survey data to investigate the synergistic influence of three online motivations and demographic characteristics on green travel. The results uncovered four heterogeneous pathways that equally prompt high green travel, which differ in the matching of three online motivations (goals) and demographic characteristics (gender, income): normative goal constitutes a universal core condition across all pathways, while hedonic goal and gain goal, together with gender and income, form unique peripheral conditions distinguishing each solution. This research revealed that varied configurations of normative, gain and hedonic goals interact with demographic characteristics to facilitate green travel. Further, the artificial neural network (ANN) analysis was performed to rank the causal conditions in terms of their importance, indicating normative goal was the most relevant antecedent in triggering green travel, supporting the robustness of fsQCA findings. This research employed a novel perspective and innovatively hybrid methods to enrich understanding of mechanisms through which online green motivations prompt green travel.