The Effect of Perceived Threats and Response Efficacy on Adaptation to Smog: An Instrumental Variables Design

Abstract

Threats and response efficacyperceptions are core conceptsof the protection motivationtheory, and recent years have witnessed a considerable growth of research on the effect of thesefactors on adaptation to air pollution. However, few studies use appropriate designs to deal with endogeneity issues, a situation that raises serious questions on the validity of their findings. To overcome this problem, this study uses the instrumental variables method to test the effect of perceived threats and response efficacy on adaptation to smog episodes. The results of this study show that the conjunction of a moderate to high perception of threats with a high perception of response efficacy is positively associated with the adoption of the recommended behavior. The increase of perceived threats does not seem to have an effect on the behavior of individuals with low response efficacy perception. Moreover, change in perceived response efficacy does not lead to any change in the behavior of individuals with low threat perceptions. Concerning policy implications, this study suggests that smog warnings and health communication campaigns could be more effective if they provide accurate information simultaneously on air pollution level, its adverse effects, and advice on how to mitigate these effects.

Knowledge of climate change and adaptation by smallholder farmers: evidence from southern Ethiopia

“…However, this cross-sectional survey-based empirical research work focused on the measured factors with a biased causal effect on the given outcome variables ( Wooldridge, 2016 ; Wuepper et al., 2018 ). The present study employed the Heckprobit model to correct selectivity bias ( Mehiriz and Gosseln, 2021 ; Sojons, 202). Adaptation to climate change and variability follows two-step process that involves perceiving that climate is changing and then in the second step, preparation to take adaptation measures through CSA adoptions ( Morton 2007 ; Deressa et al., 2011 ).…”

Do perception factors affect adaptation behaviours against air pollution among vulnerable occupation groups? evidence from chittagong and dehradun

“…There have been a few studies exploring into determinants of protective and/or adaptive behavior in relation to air pollution exposure. These studies have tested the effects of perceived threats and response efficacy on adaptation to smog episodes and have found positive relationships (Johnson 2012, Lin and Bautista 2016, D'Antoni et al 2017, Covey et al 2019, Mehiriz and Gosselin 2022. In some studies, self-efficacy was found to be statistically significant factor in predicting adaptive or protective behavior (Hansstein andEchegaray 2018, Sahrir 2019).…”

Protective consumption behavior under smog: using a data-driven dynamic Bayesian network

“…With smog crisis, unlike some natural hazards (e.g., earthquakes, flood), the public have some time to prepare, given that smog is a gradual risk and evolves regularly over time (Mehiriz & Gosselin, 2022 ). The other avoiding behavior and alternative mitigation options are allowed because individuals can gather enough information and afford some time cost.…”

“…Second, this paper uses a data-driven approach to obtain the network structure and relationships among protective consumption behaviors and their influencing factors, which avoids the possible subjective limitations of previous subjective diagnosis based on the expert knowledge (Yang et al, 2021 ). Third, existing studies generally focus on considering one aspect that influences protective consumption behavior, such as marketing strategies from a firm-side perspective (Stanciu et al, 2020 ; Untaru & Han, 2021 ), risk perception on the public side (Mehiriz & Gosselin, 2022 ), but the protective consumption behavior of the public in the real world is influenced by multiple factors (Awan & Raza, 2012 ), which are not independent of each other. Certain limitations in the survey data and statistical approach exist in identifying complex relationships between multidimensional factors and target variables (Simsekler & Qazi, 2020 ).…”