Willingness to pay for a domestic food waste diversion policy option in regional Queensland, Australia

Domestic food waste (DFW) is an important policy issue because it represents inefficiencies in supply chains and consumption behaviour, creates pressures on urban landfills, and causes downstream environmental impacts such as greenhouse gas (GHG) emissions and odour from landfills. However, the evaluation of proposals to minimise or treat food waste, such as through separate disposal streams, is difficult because those impacts are not registered through normal market price signals. This paper presents non-market valuations for a hypothetical kerbside DFW collection service from a survey of households in two local government areas in the Central Queensland region, Australia. Choice modelling (CM) and contingent valuation methods (CVM) were employed to elicit potential participation and estimate willingness to pay (WTP) of the community for a domestic food waste collection service. Latent class analysis results for the sub-groups supporting an improvement option revealed that cost, odour and fortnightly collection frequency limit both WTP for and participation in the potential kerbside collection program. While there was support because it would extend the lifespans of the local landfills, potential reduction of methane emissions was not a strong driver. No difference in support or willingness to pay could be identified between the two local government populations. While the CVM results showed a WTP of $30.42 and a 58% participation rate for the proposed option, the latent class models showed that potential participation and willingness to pay varied across negative, indifference and positive sub-samples. This study provides a useful example of how a new policy option to improve waste management at a local area level might be evaluated, where the willingness to pay estimates can be factored into a benefit cost analysis and the estimates of likely support or opposition can be inputted into a political economy framework. (C) 2020 Elsevier Ltd. All rights reserved.