What explains differences in change of initial perceptions ......2nd IEAGHG Social Research Network Meeting, November 17-18, 2010, Yokohama City, Japan What explains differences in

2nd IEAGHG Social Research Network Meeting, November 17-18, 2010, Yokohama City, Japan

What explains differences in change of initial perceptions of CO2 Capture and

Storage?A structural equation modelling analysis of data from

representative surveys in Germany and Norway

Diana Schumann (IEK-STE, Germany)Sturle D. Tvedt (SINTEF, Norway)

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Institute of Energy and Climate Research November 17, 2010 Systems Analysis and Technology Evaluation (IEK-STE) Diana Schumann / 2

OutlinePoint of departureMeasuring change in initial perceptionsDifferences in change in initial perceptions in Germany and NorwayThe structural equation model (SEM)Preliminary results of testing the model with the German dataDiscussionNext steps for model application


Point of departure

It can be assumed that the majority of initial perceptions of CO2 capture and storage (CCS) are pseudo-opinionsPseudo-opinions are of low quality, i.e. inconsistent, unstable and people feel not confident about themPseudo-opinions can easily be changed by contextual information or slight changes in mood (cf. De Best-Waldhober et al. 2008)


Point of departure (II)

Results of representative surveys in Germany and Norway, carried out in 2009, also showed that initial perceptions of CCS are unstableHowever, the degree of change in initial perceptions of CCS systematically differ between German and Norwegian respondentsHow can these differences of changes in initial perceptions be explained?


Measuring change in initial perceptions of CCSTwo kinds of initial perceptions: 1) Regarding the use of CCS to address global

warming (general idea of CCS)2) Regarding the permission of a CCS demo plant

(concrete proposal of CCS)Both were surveyed before and after receiving information about CCS


Measuring change in initial perceptions of CCS (II)Calculating the absolute differences between pre-information and post-information perceptions regarding the general idea and a concrete proposal of CCSDirections of change: negative change/positive changeExtent of change: slight change/”extreme” change


Absolute differences in pre- and post-information perceptions in Germany and Norway regarding the general idea of CCS

Presenter

Presentation Notes

Explain all differences using this figure: Initial perceptions of Norwegian respondents are more stable Change of initial perceptions of Norwegian respondents is less “extreme” (however, small number of cases of respondents with extreme changes = 102) Initial perceptions of Norwegian respondents change more often in a positive direction All differences are statistically significant (ANOVA and Mann-Whitney-U Test)


Absolute differences in pre- and post-information perceptions in Germany and Norway regarding a concrete proposal of CCS

Presenter

Presentation Notes

Differences are statistically significant (ANOVA and Mann-Whitney-U Test)


Research questionsWhat are relevant factors for the change in initial perceptions?Do the factors which are relevant for the change in initial perceptions of CCS in Germany and Norway systematically differ?If yes, do these factors explain the differences in the change in initial perceptions between Germany and Norway?In order to investigate these questions structural equation modelling (SEM) is used


Why structural equation modelling?Structural equation modelling (SEM) incorporates and integrates various statistical techniques such as path analysis and factor analysisMost important advantage: SEM allows to model and test complex patterns of relationships, including a multitude of hypotheses simultaneously as a whole, including mean structure and group comparisons

Presenter

Presentation Notes

Further advantages of SEM are that it allows to make use of several indicator variables per construct simultaneously, to take measurement errors into account, both confirmatory and exploratory modelling, meaning SEM is suited to both hypotheses testing and hypotheses development However, on the other hand more effort is necessary until the greater complexity of SEM pays of Assumptions on the data may be higher and the process of interpreting the results is more complex compared to other methods of data analysis


Components of a structural equation modelA full structural equation model consists of three parts:

measurement model of latent exogenous variables,structural model, measurement model of latent endogenous variables


Measurement model of latent exogenous variables

Presenter

Presentation Notes

Validity and reliability of latent variables and measurement model have been tested with explanatory and confirmatory factor analysis


Structural model


Measurement model of the latent endogenous variables


Full model

Chi-square = 556,645Degrees of freedom = 239Probability level = .000Normed chi-square: 2.3CFI: .908RMSEA: .036

Presenter

Presentation Notes

Number of variables in the model: 60 Number of observed variables: 25 Number of unobserved variables: 35 Number of exogenous variables: 34 Number of endogenous variables: 26 Asymptotically Distribution-free Estimates Minimum was achieved after 13 iterations The Normed x2 (x2/df): according to Hanse and Engström (1999) values less than 1.0)=‘‘overidentified’’ models and values more than 2.0, or more liberally, more than 5.0 = and poorly fitted models; 2.3 = very acceptable fit CFI (comparative fit index): : values close to 1 indicate a very good model fit and Carlson and Mulaik (1993) argue that CFI values should be at least 0.95, however Homburg and Baumgartner (1996) argue that CFI values should be at least 0.90 RMSEA (root mean square error of approximation): : Browne and Cudeck (1996) argue that the value of RMSEA of about 0.05 or less would indicate a close fit of the model at the degrees of freedom; Hu and Bentler (1999) argue that RMSEA should be 0.06 or less the values of both fit indices indicate that the full model fits well to the German data


Preliminary results of testing the model with the German dataStandardized Regression Weights EstimateChange in initial perceptions of CCS <--- Pre-existing knowledge -,274***

Change in initial perceptions of CCS <--- Pre-existing attitudes towards renewables -,036

Change in initial perceptions of CCS <--- Pre-existing attitudes towards fossil fuels

and nuclear -,092

Change in initial perceptions of CCS <--- Trust in information from governments and

political parties ,138*

Change in initial perceptions of CCS <--- Trust in information from NGOs -,106

Change in initial perceptions of CCS <--- Preference for seeking information from

newspapers, TV or radio ,013

Change in initial perceptions of CCS <--- Preference for seeking information from the

Internet -,048

Change in initial perceptions of CCS <--- Perception of personal risks -,338***

Presenter

Presentation Notes

CFI: values close to 1 indicate a very good model fit and Carlson and Mulaik (1993) argue that CFI values should be at least 0.95, however Homburg and Baumgartner (1996) argue that CFI values should be at least 0.90 RMSEA: Browne and Cudeck (1996) argue that the value of RMSEA of about 0.05 or less would indicate a close fit of the model at the degrees of freedom; Hu and Bentler (1999) argue that RMSEA should be 0.06 or less the values of both fit indices indicate that the full model fits well to the German data


Preliminary results of testing the model with the German data (II)

Covariances Esti-mate S.E. C.R. P

Pre-existing knowledge <--> Perception of personal risks ,002 ,018 ,134 ,893

Pre-existing knowledge <--> Preference for seeking

information from the Internet ,206 ,042 4,889 ***

Pre-existing knowledge <-->

Preference for seeking information from newspapers, TV or radio

-,088 ,020 -4,451 ***

Pre-existing knowledge <--> Trust in information from NGOs ,076 ,019 3,962 ***

Pre-existing knowledge <--> Pre-existing attitudes towards

fossil fuels and nuclear -,150 ,028 -5,380 ***

Pre-existing knowledge <--> Trust in information from

governments and political parties -,031 ,019 -1,633 ,103

Pre-existing knowledge <--> Pre-existing attitudes towards

renewables ,039 ,014 2,769 ,006

Presenter

Presentation Notes



Preliminary results of testing the model with the German data (III)

Covariances Esti-mate S.E. C.R. P

Perception of personal risks <--> Pre-existing knowledge ,002 ,018 ,134 ,893

Perception of personal risks <--> Pre-existing attitudes

towards renewables -,033 ,018 -1,792 ,073

Perception of personal risks <-->

Pre-existing attitudes towards fossil fuels and nuclear

,151 ,034 4,404 ***


Trust in information from governments and political parties

,065 ,032 2,016 ,044

Perception of personal risks <--> Trust in information from

NGOs ,073 ,028 2,594 ,009


Preference for seeking information from newspapers, TV or radio

,063 ,033 1,916 ,055

Perception of personal risks <--> Preference for seeking

information from the Internet ,002 ,060 ,039 ,969

Presenter

Presentation Notes



Discussion

Preliminary results of testing the model with the German data indicate that knowledge as well as perceptions of personal risks can increase the stability of initial perceptions of CCSHowever, the results also indicates that knowledge and risk perceptions of CCS are not correlated (what is also known from other technologies)Risk perceptions of lay persons regarding CCS cannot easily be changed by increasing their knowledge

Presenter

Presentation Notes

The question of what explains the differences in initial perceptions cannot be answered yet For this purpose the following next steps for model application are necessary


Next steps for model application

Scrutinizing the plausibility of the model results in more detailCarrying out sensitivity analyses (e.g. variation of definition of constraints)Running the model with the Norwegian dataCarrying out multigroup analyses with the German and Norwegian data


Thank you very much for your attention!


Preliminary results of testing the model with the German data

Correlations Estimate

Pre-existing knowledge <--> Perception of personal risks ,006

Pre-existing knowledge <--> Preference for seeking information from the

Internet ,198***

Pre-existing knowledge <--> Preference for seeking information from

newspapers, TV or radio -,202***

Pre-existing knowledge <--> Trust in information from NGOs ,197***

Pre-existing knowledge <--> Pre-existing attitudes towards fossil fuels and

nuclear -,299***

Pre-existing knowledge <--> Trust in information from governments and

political parties -,060

Pre-existing knowledge <--> Pre-existing attitudes towards renewables ,158**

Presenter

Presentation Notes



Preliminary results of testing the model with the German data

Correlations Estimate

Perception of personal risks <--> Pre-existing knowledge ,006

Perception of personal risks <--> Pre-existing attitudes towards renewables -,076*

Perception of personal risks <--> Pre-existing attitudes towards fossil fuels

and nuclear ,170***

Perception of personal risks <--> Trust in information from governments and

political parties ,071**

Perception of personal risks <--> Trust in information from NGOs ,107***

Perception of personal risks <--> Preference for seeking information from

newspapers, TV or radio ,082*

Perception of personal risks <--> Preference for seeking information from the

Internet ,001

Presenter

Presentation Notes


Documents

What explains differences in change of initial perceptions ......2nd IEAGHG Social Research Network Meeting, November 17-18, 2010, Yokohama City, Japan What explains differences in