Presentation on theme: "Application of choice and choice behaviour to the community choices among option for the development of the Moranbah township John Rolfe and Galina Ivanova."— Presentation transcript:
Application of choice and choice behaviour to the community choices among option for the development of the Moranbah township John Rolfe and Galina Ivanova
Outline of this presentation Case study: Mining town Methods of assessing community preferences Survey outline Results Pooling CM and CB data Discussion
Background: Issues for Mining Town Mining has been through cyclical patterns of decline and boom Increased use of workcamps and ‘fly-in/fly- out’ Town development is limited by high housing costs and low levels of local spending Other key issues are provision of services (water) and future proximity of mining Limited knowledge what are the priorities in the community regarding town development
Moranbah Coal mining town in northern Bowen Basin Population of approx. 7,000 Up to 4,000 non-permanent workforce also ‘cycling’ through the town Substantial pressure from local council to locate more workforce in the town –Council refuses to allow more workcamps to be built –Issues about future development of reserves close to township
Case study: Moranbah Funded by the State Government Objectives of the Study –Assess views of residents regarding development options Use 2 techniques: Choice Modelling (CM) and Contingent Behaviour (CB) –focuses attention on the key issues or attributes of importance, –provides some quantitative feedback about the relative importance of those issues and attributes (tradeoffs). CB vs CM –CB does not use $ –CB provides insights on how behaviour might change –CB provides more flexibility with choices
Survey A literature review and extended stakeholder analysis were used to design a CM / CB survey Choice Modelling survey –3 choice sets /respondent –3 profiles / choice set describing the alternatives on offer –One of the profiles described a status quo option –The other profiles varied Contingent Behaviour survey –Reference point – intention to stay in Moranbah (years) –3 profiles describing the alternatives on offer Same profiles as from the CM experiment –Respondent identified the length of residence for each scenario
Question 2: Carefully consider each of the following three options. Suppose options A, B and C were the only options available, which would you choose? Additional annual costs to your household Housing and rental prices Level of water restrictions Buffer for mine impacts close to town Growth in population of 5,000 people I would choose Potential Condition in 5 years time (Options A,B and C) Option A(Expected outcome under current policy pressures) $0 No changeSome for households, town parks and gardens are drier than now Moderate impacts from noise, vibration and dust 1,000 in housing, 4,000 in workcamps Option B $250 ($21/month) No changeNone for households, town parks and gardens are drier than now Slight impacts from noise, vibration and dust 4,000 in housing, 1,000 in workcamps Option C $1,000 ($83/month) 25% increase None for households, town parks and gardens are greener than now Slight impacts from noise, vibration and dust 1,000 in housing, 4,000 in workcamps Figure 1. Example choice set used in survey
Performance of the survey November 2006 - Combined phone and mail-out. –Both CM and CB contained in mail-out –Split sample used to test order effect Random sample of households in Moranbah community Each respondent completed three choice sets The response rate was 41% (131). CM data analysed with logistic regression models CB data analysed with multiple regression models
Results of the Choice Modelling Experiment Coefficient Standard Error Constant-0.5990.937 Cost-0.001***0.000 Housing and Rentals0.284**0.119 Water Restrictions0.218*0.114 Buffer for Mine Impacts0.248**0.118 Population in Work Camps1.583**0.144 Female1.243***0.259 Number of Children0.261***0.098 Income0.000**0.000 Age0.037**0.015 Length of residence-0.100*0.053 Enjoy living in Moranbah0.212*0.125 Spending in Moranbah-0.010**0.005 Improved services less travel0.025***0.007 Number of observations420 Log likelihood function-316.4385 R-sqrd.31 *** = significant at the 1% level, ** = significant at the 5% level, * = significant at the 10% level.
Results of the Choice Modelling Experiment Part worth, expected Confidence intervals for Part worth lower CIHigher CI Constant -$582-$2,691$1,300 Housing and Rentals$276$51$601 Water Restrictions$212-$6$483 Buffer for Mine Impacts$241$12$541 Population in Work Camps$1,540$1,048$2,636
Example of Choice Behaviour survey Question 2. If the scenario below summarised the key changes in Moranbah in the next five years, would it change how long you think you would live in Moranbah? Option 1 Housing and rental prices No change Level of water restrictions Some for households, town parks and gardens are drier Buffer for mine impacts close to town Slight impacts from noise, vibration and dust Growth in population of 5,000 people 4,000 in housing, 1,000 in workcamps Please circle how many years from now you think you will live in Moranbah if this is how it develops (Remember your answer in Question 1) less than one year1 1 - 2 years2 2 - 3 years3 3 - 4 years4 4 - 5 years5 6 - 10 years 6 10 - 15 years 7 over 15 years 8 unsure9
Conducting the CB analysis Calculated a dependent variable from the responses –Change in intention to stay –Difference between ‘Planned years of stay’ and ‘Years of stay’ for each profile –Variable indicates the level of behaviour response to each profile Used as dependent variable in regression
Model 1Model 2 Coefficient Constant5.845***10.451*** CB Housing and Rentals-0.294-0.644 CB Water Restrictions0.1230.029 CB Buffer for Mine Impacts-0.501*-0.701* CB Population in workcamps-1.198***-1.335*** Female-1.268* Younger than Primary School kids -0.293 Primary school kids-0.365 Secondary school kids0.481* Age-0.048 Adjusted R Square0.0450.070
Choice Modelling vs. Contingent Behavior Results are similar but not identical –Priority of the variables is similar –Relative weighting of variables is more extreme with CB data Results suggest that responses may vary to some extent between CM and CB formats Potential reasons –Different formats (closed vs open-ended) –Categorical responses in CB –Brevity of the response format ?
Testing for order effects Tested CM models to identify if coming before or after CB sets affected values No significant effect on CM models
Pooling the data Exploratory test to combine data sets Converted CB data to binary format –Assumed that respondents implicitly considered a status quo option relative to each CB choice on offer –Set the status quo option and the choice alternative –Stacked CB data with CM dataset
Discussion Choice modelling: –Promising tool for prioritising development options –different benefits can be compared to costs of implementation Contingent Behaviour: –Largely supportive of the CM results –Different format to engage people in choice exercises Pooled data set –Difficult to add value from pooling exercise
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