GREEN WHEELS TURNING?Willingness to pay and participants' views on green initiatives at the Cape Argus Pick 'n Pay cycle tour

Paper prepared for the IATE 2013 International Conference, 1-4 July 2013, University of Ljubljana, Slovenia.

By

Waldo Krugell & Melville Saayman

1) Introduction

• Tourism and the environment – some key stats…• Tourists are starting to demand “green” facilities and

experiences and are often willing to pay for it.• This paper examines the characteristics of the people

who are willing to pay and focusses on a major sports event – the Cape Argus Pick ‘n Pay Cycle Tour in Cape Town, South Africa.

• Specifically, we asked them about their attitudes towards the initiatives in place to ensure a greener cycle tour.

2) Why would they pay? • The environment as a common pool resource:

• Is commonly owned by everyone and utilised by all.• It suffers the effects of the pollution that occurs during all our

production and consumption activities.• The market fails to account for the social costs.

• Getting people to pay: cooperation or coercion?• Mitigation will require a combination of voluntary

contributions and compulsory taxes.

2) How can we determine WTP ?• Since no formal market exists a sustainable tourism

experience or a green event, researchers have to use indirect ways to determine willingness to pay.

• TCM, HPM, CVM…• Contingent Valuation Method has key elements:

• The scenario presented to the respondents in the survey.• This matters because…

• The way in which the willingness to pay question is asked.• The "cheap talk" problem.

2) Who are willing to pay? • Demographic variables are used to distinguish the

character of the survey samples.• The common explanatory variables used in the studies

surveyed include measures of:• Environmental engagement,• Environmental attitudes / beliefs,• Education level,• Perceived efficacy of policy / strategy,• Political views,• Level of certainty of climate change and policy outcomes,• Expected future temperature / precipitation levels, and• Perceptions of others’ efforts.

Description of the survey data• More about the survey…• Elements of the CVM: knowledge, cooperation, mitigation.• Description of the data:

• 180 completed questionnaires.• 72% male.• Average age 41 years.• 54% English speaking.• 37% diploma/degree, 29% post-grad qualification.• 37% professional positions, 20% in management.• 29% local residents.

• Our WTP question: “Would you be willing to pay R20 ($3) extra, that will be donated to Trees of Africa, as an offset for your carbon footprint?” (yes/no)

Description of the survey data• Willingness to pay:

• 111 would pay, 39 would not, 30 skipped WTP question.

• Cross-tabs of WTP and demographic variables show:• A greater proportion of women were willing to pay.• The age groups 18 to 30 years (68.9%) and 51 to 60 years (71.4%)

had the biggest share of those who said they are willing to pay.• There is little variation in willingness to pay between the differences

in marital status and different language groups.• WTP per level of education were: 55% for Grade 12 only, 64% for

those with diploma/degree, 65% for those with post-grad qualification.

• The average of total spending of those who said they are willing to pay was R5’317, and for those who said they were not willing to pay, it was R3’420.

PCA of the green views• We also asked cyclists about their opinions on initiatives

that could ensure a greener cycle tour. • Principle component analysis of these views was used to

characterise a type of cyclist.• Exploratory factor analysis was used with principle components

extraction and varimax rotation. • Anderson-Rubin method was used to obtain standard normal factor

scores. • The KMO measure of sampling adequacy was 0.880.• In total four factors were identified with Eigen values greater than

one and they explain 73 per cent of the variance of the data.

• The following table shows the type of cyclists by their green views.

Green money Green products Re-“cyclers” Do your bit Providing

opportunity to buy carbon credits

Providing opportunity to financially support other green initiatives at the race

Providing info of carbon footprint at the cycle tour

Opportunity to be part of Ride for Nature with WWF-SA

Recognition of clubs or teams that support a greener cycle tour

Providing info regarding current recycling activities

Providing info regarding recycling methods for cyclists

Use of local products and produce by food vendors

Environmentally friendly packaging of food

Use of energy saving lights at the expo

Cycle Tour supporting a particular conservation organisation

Providing opportunity to buy bio-degradable products at the expo

Marketing material printed on recycled paper

Recycling bins at the expo

Recycling bins along the route

Visible signage for bins along the route

Recycling of paper, bottles, cans before, during and after the race

Stronger awareness of stash your trash initiative

Cyclists retaining their own litter, disposing after race

Predictors of WTP• To determine how these green views are related to WTP

a binary logistic regression model was estimated.

Willing to pay

Not willing to pay

Willing to pay82 4 95.3

Not willing to pay 31 3 8.8

70.8

Observed

Predicted

Step 1 WTP, 1=yes, 2=no

Overall Percentage

Exp(B) S.E. Sig.

Green views: Do-your-bit .074

Green views: Green money .300 .599 .044

Green views: Green products .220 .718 .035

Green views: Re-cyclers .685 .590 .522

Total spending 1.000 .000 .072

Constant .568 .286 .048

Predictors of WTP• Why we did not add the demographic variables…

Conclusions and recommendations• The key finding is that specific types of green views were

positively and significantly associated with stated willingness to pay.

• What are the recommendations for practitioners and researchers?• Tourism service providers or event organisers who want to make

their offerings more environmentally friendly and get people to pay for it, will need to target their initiatives. They need to identify their green-minded consumers and developing them.

• Further research in this field needs to examine the range of explanatory variables of willingness to pay, such as perceived efficacy of interventions, or the role of perceptions of others’ efforts.