Title of assessment (Consumer Attitudes) – Research exercise
Perform a multiple regression analysis to explore how well the components of the Theory of Planned Behaviour (TPB) and other variables (socio-demographic and economics characteristics of respondents) contained in the ‘GM_Datset_2nd_Assignment.sav’ or ‘GM_Dataset_Assignment_02.csv’ datasets can predict purchasing. intentions for GM food products. Discuss your results commenting tables and or figures of your data analysis.
The ‘GM_Datset_2nd_Assignment.sav’ dataset contains the information necessary to perform the required statistical analysis. Furthermore, table 1 illustrates how questions related to TPB components were framed in the questionnaire and named in the ‘GM_Datset_2nd_Assignment.sav’ dataset.
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Overview and learning outcomes assessed :
You have to demonstrate your skills in analysing and summarising data on attitudes, and commenting results linked to the following learning outcomes:
• The strength of attitudes and the expectancy value principle (see learning outcomes of weeks 4 and 5)
• Predicting behaviour (see learning outcomes of week 6)
• Modelling consumer attitudes and behaviour (see learning outcomes of weeks 7-8)
• JASP/SPSS tutorials
Text has to be double spaced, character 12, between 1,000 and 1,200 words
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Variable Item
Attitudes (benefit and risks)
EV_PEST For me, reducing the use of pesticides and chemicals from the application of genetic engineering in food production is:
SP_PEST I think that reducing the use of pesticides and chemicals by using genetic engineering in food production is:
EV_FOOD For me, the development of foods with specific health benefits via the application of genetic engineering in food production is:
SP_FOOD I think that the development of foods with specific health benefits through the use of genetic engineering in food production is :
EV_LDCS For me, improvements in the nutritional situation of people in developing countries from the use of genetic engineering in food production are:
SP_LDCS I think that improvements in the nutritional situation of people in developing countries through the use of genetic engineering in food production are:
EV_BIOD For me, reduced biodiversity in ecological systems from the use of genetic engineering in food production is:
SP_BIOD I think that reduced biodiversity in ecological systems as a result of using genetic engineering in food production is:
EV_HEAL For me, health risks to myself and my family from the use of genetic engineering in food production are:
SP_HEAL I think health risks to myself and my family caused by genetic engineering in food production are:
EV_FUTG For me, negative health effects on future generations from use of genetic engineering in food production are:
SP_FUTG I think that negative health effects on future generations due to the use of genetic engineering in food production are:
Subjective norms and Perceived behaviour control
NB_SNOR For me, my family’s and my friends’ views of my purchasing genetically modified food items would be:
MC_SNOR I think the likelihood that my family’s and friends’ views will influence my intention to purchase or not to purchase genetically modified food items will be:
PC_PBCL For me, if genetically modified food products are introduced on the market, distinguishing them from food items produced without genetic engineering will be:
CB_PBCL I think that if food produced using genetic engineering is introduced on the market, the likelihood that I will have access to it in my usual shopping environment will be:
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Coding of variables for JASP users who import data from the CSV file.
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Variable Value names Label EV_PEST -3 Extremely undesirable -2 Very undesirable -1 Undesirable 0 Neutral 1 Desirable 2 Very desirable 3 Extremely desirable SP_PEST 1 Extremely unlikely 2 Very unlikely 3 Unlikely 4 Neither unlikely, nor likely 5 Likely 6 Very likely 7 Extremely likely EV_FOOD -3 Extremely undesirable -2 Very undesirable -1 Undesirable 0 Neutral 1 Desirable 2 Very desirable 3 Extremely desirable SP_FOOD 1 Extremely unlikely 2 Very unlikely 3 Unlikely 4 Neither unlikely, nor likely 5 Likely 6 Very likely 7 Extremely likely EV_LDCS -3 Extremely undesirable -2 Very undesirable -1 Undesirable 0 Neutral 1 Desirable 2 Very desirable 3 Extremely desirable SP_LDCS 1 Extremely unlikely 2 Very unlikely 3 Unlikely 4 Neither unlikely, nor likely 5 Likely 6 Very likely 7 Extremely likely EV_BIOD -3 Extremely undesirable -2 Very undesirable -1 Undesirable 0 Neutral 1 Desirable 2 Very desirable 3 Extremely desirable SP_BIOD 1 Extremely unlikely 2 Very unlikely 3 Unlikely 4 Neither unlikely, nor likely 5 Likely 6 Very likely 7 Extremely likely EV_HEAL -3 Extremely undesirable -2 Very undesirable -1 Undesirable 0 Neutral 1 Desirable 2 Very desirable 3 Extremely desirable SP_HEAL 1 Extremely unlikely 2 Very unlikely 3 Unlikely 4 Neither unlikely, nor likely 5 Likely 6 Very likely 7 Extremely likely EV_FUTG -3 Extremely undesirable -2 Very undesirable -1 Undesirable 0 Neutral 1 Desirable 2 Very desirable 3 Extremely desirable SB_FUTG 1 Extremely unlikely 2 Very unlikely 3 Unlikely 4 Neither unlikely, nor likely 5 Likely 6 Very likely 7 Extremely likely Subjective norms Variables names Values Labels NB_SNOR -3 Extremely negative -2 Very negative -1 Negative 0 Neutral 1 Positive 2 Very positive 3 Extremely positive MC_SNOR 1 Extremely low 2 Very low 3 Low 4 Neither low, nor high 5 High 6 Very high 7 Extremely high Perceived behavioural control PC_PBCL 1 Extremely difficult 2 Very difficult 3 Difficult 4 Neither difficult, nor easy 5 Easy 6 Very easy 7 Extremely easy CB_PBCL 1 Extremely low 2 Very low 3 Low 4 Neither low, nor high 5 High 6 Very high 7 Extremely high Other variables GENDER 0 Female 1 Male INCOME 1 Less than 1000 € 2 From 1000 to 1999 € 3 From 2000 to 2999 € 4 From 3000 to 3999 € 5 More than 4000 € COUNTRY 0 Italy 1 Germany ______________________________ Also, I have attached: * Assignment guide * Dataset on JASP Also Dataset on Excel And * Week 4 and 5 lectures * Week 6 lecture * Week 7 and 8 lectures |