Accounting for the importance of psychological distance in assessing public preferences for air quality improvement policies: an application of the integrated choice and latent variable model.

Assessing public preferences for air pollution control is essential to achieving effective air quality improvement, but the internal psychological factors affecting public preferences, especially psychological distance (PD), have only received limited attention. Therefore, this paper explores the role of PD in assessing public preferences for air quality improvement policies. Compared with previous studies that consider psychological factors in the choice model, this study incorporates PD into the choice model as a latent variable by considering both individual responses to measurement questions and socio-economic characteristics in the integrated choice and latent variable model. The results of this study clearly show that PD significantly affects public preferences for air quality improvement policies. Respondents with close PD had obvious preferences for air quality improvement, while those with distant PD were satisfied with the current situation and reluctant to improve it. After considering PD in the analysis, respondents' willingness to pay for one-unit level change of attributes "heavily polluted days," "good air days," "mortality," and "policy postponement" were respectively 10.3791CNY, 10.9005CNY, 11.0427CNY, 28.3412CNY per year. In addition, the paper also found men and respondents with lower levels of education and higher monthly incomes tended to view air pollution as psychologically distant and thus less willing to improve air quality. It is suggested that policy makers should reduce the PD of air pollution among these people by increasing publicity about the hazards of air pollution. This study not only contributes to the literature on the importance of PD in assessing individual preferences, but also provides constructive guidance for policy makers to assess the public's acceptability of air quality improvement.

Can respondent uncertainty be ignored when exploring heterogeneity in public preferences for air pollution treatment policies? Comparative results from choice experiment analysis.

Based on choice experiment (CE), evaluating the public's heterogeneous preferences and willingness to pay (WTP) for air pollution treatment policies can provide useful social views for the reasonable formulation of treatment schemes. However, the application of CE contains an implicit assumption that respondents understand their real preferences and can make choices with complete certainty. In reality, for a variety of reasons, not all respondents are absolutely certain about their responses, this assumption distinctly is hard to be consistent with reality. To explore the impact of respondent uncertainty on the public's WTP and heterogeneous preferences for air pollution treatment policies, this study introduces the critical point and exponential weighting methods to deal with this uncertainty in the context of CE and conducts comparative analysis based on the random parameters logit (RPL) and latent classes models (LCM). The results show that, ignoring uncertainty leads to distortions in the public's WTP and preference characteristics. In the RPL models, on average, the WTP for attributes is overstated by 32.10%. Our results also reveal that, whether to consider uncertainty does not affect the ranking of the implicit prices of these attributes. After incorporating uncertainty into the analysis, respondents were divided into two potential groups with different preferences, namely the environment-focused group (79.44%) and the price-focused group (20.56%), which is quite distinct from research results of ignoring the uncertainty. Contribution of this study is not only to provide theoretical insights for exploring the effects of uncertainty on public preferences based on CE, but also to provide valuable guidance for policy makers to formulate more accurate and effective treatment measures.