European waste legislation has been encouraging for years the incorporation of selective collection systems for the biowaste fraction. European countries are therefore incorporating it into their current municipal solid waste management (MSWM) systems. However, this incorporation involves changes in the current waste management habits of households. In this paper, the attitude of the public towards the incorporation of selective collection of biowaste into an existing MSWM system in a Spanish municipality is analysed. A semi-structured telephone interview was used to obtain information regarding aspects such as: level of participation in current waste collection systems, willingness to participate in selective collection of biowaste, reasons and barriers that affect participation, willingness to pay for the incorporation of the selective collection of biowaste and the socioeconomic characteristics of citizens who are willing to participate and pay for selective collection of biowaste. The results showed that approximately 81% of the respondents were willing to participate in selective collection of biowaste. This percentage would increase until 89% if the Town Council provided specific waste bins and bags, since the main barrier to participate in the new selective collection system is the need to use specific waste bin and bags for the separation of biowaste. A logit response model was applied to estimate the average willingness to pay, obtaining an estimated mean of 7.5% on top of the current waste management annual tax. The relationship of willingness to participate and willingness to pay for the implementation of this new selective collection with the socioeconomic variables (age, gender, size of the household, work, education and income) was analysed. Chi-square independence tests and binary logistic regression was used for willingness to participate, not being obtained any significant relationship. Chi-square independence tests, ordinal logistic regression and ordinary linear regression was applied for willingness to pay, obtaining statistically significant relationship for most of the socioeconomic variables.