Characterization of investments profiles on the energy transition for european citizens

Resumo

<strong>Name</strong>: Characterization of investments profiles on the energy transition for european citizens <strong>Summary</strong>: The dataset contains: (1) surveyee consent form for the study, (2) different scenarios about the energy transition, (3) determinant factors about those scenarios, (4) socioeconomic description of the surveyee, (5) investment decisions, (6) and household characterization/description. <strong>License</strong>: cc-BY-SA <strong>Acknowledge</strong>: These data have been collected in the framework of the WHY project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 891943. <strong>Disclaimer</strong>: The sole responsibility for the content of this publication lies with the authors. It does not necessarily reflect the opinion of the Executive Agency for Small and Medium-sized Enterprises (EASME) or the European commission (Ec). EASME or the Ec are not responsible for any use that may be made of the information contained therein. <strong>Collection Date</strong>: 22/07/2022 <strong>Publication Date</strong>: 15/10/2023 <strong>DOI</strong>: 10.5281/zenodo.4455198 <strong>Other repositories:</strong> <strong>Author</strong>: University of Deusto <strong>Objective of collection</strong>: This data was originally collected to analyze quantitatively the decisions of everyday people in relation to their energy consumption and their reactions to specific political interventions. <strong>Description:</strong> The dataset contains a CSV file file containing data collected from a survey about energy consumption investments. The fields that can be found for each entry are (1) Different scenarios about the energy transition and reactions to those scenarios, (money spent on energy investments, decisions about scenarios, actions taken under a blackout, etc.) (2) Determinant factors about the chosen scenarios in the previous question, which include different choices that could affect your decision about a scenario (3) socioeconomic information about the user (age, country of residence, studies), (4) estimation of the prices of various technologies related to the energy transition and (5) descriptive statistics about the household living situation (gender of user, people living in household, yearly rent, average savings per month, type of house, size of house) and also includes questions about climate change expertise. Next you can found a description of each field in the dataset <strong>Section 1 - Scenarios for energy transition.</strong> <strong>ID90.</strong> Rank in order of priority, from top to bottom, in which scenario you will be willing to live or to contribute/invest to make it possible. <strong>ID36, ID38, ID43, ID44, ID72. </strong>Percentage of money people are willing to spend/save out of their income per scenario <strong>ID191, ID192</strong>.. Amount of money people would spend based on an assumed case. <strong>ID191, ID192. </strong>Priority service provision in case of Intermittent energy service. Rating energy services from 0 to 10 stars, where 0 stars means it is extremely low priority for you and 10 stars means it is absolutely necessary for you. <strong>[ID325, ID326, ID327, ID328, ID329, ID330, ID331, ID332, ID333, ID334, ID335, ID336, ID337, ID338, ID339, ID340, ID341, ID133, ID242]</strong>. Priority service provision in case of <em>Intermittent energy service</em>. Rating energy services from 0 to 10 stars, where 0 stars means it is extremely low priority and 10 stars means it is absolutely necessary. [<strong>ID251, ID256, ID257, ID292, ID293, ID294, ID295, ID296, ID297, ID298, ID299, ID301, ID302, ID303, ID304, ID305, ID306, ID250, ID251</strong>]. Priority service provision in case of <em>full </em><em>black-outs</em>. Rating energy services from 0 to 10 stars, where 0 stars means it is extremely low priority and 10 stars means it is absolutely necessary. [<strong>ID141, ID5, ID147</strong>]. Used for statements that best represent survey responder <strong>Section 2 - Determinants (factors).</strong> Questions used to rate (from 0 to 100) factors that may influence the decision-making process contributing to make an ideal scenario possible. <strong>ID100</strong> Risk profile <strong>ID101</strong> Added value <strong>ID102</strong> Self-Satisfaction <strong>ID103</strong> Technical Fit <strong>ID104</strong> Own competence <strong>ID105</strong> Knowledge <strong>ID106</strong> Cost-Efficiency <strong>ID107</strong> Safety <strong>ID108</strong> Trust <strong>ID109</strong> Autarky <strong>ID110</strong> Legal <strong>ID111</strong> Climate Protection <strong>ID112</strong> Wellbeing <strong>ID113</strong> Coziness <strong>ID114</strong> Rights and Duties <strong>ID115</strong> Peer-Pressure <strong>ID116</strong> Socialising <strong>ID117</strong> Support <strong>ID118</strong> Agreement <strong>ID119</strong> Brag <strong>ID120</strong> Fun <strong>ID121</strong> Novelty <strong>ID122</strong> Trends <strong>ID123</strong> Authority <strong>ID124</strong> Own Significance <strong>ID125</strong> Poseur <strong>ID2</strong> Frugality <strong>ID3</strong> Environmental concerns <strong>ID31</strong> Adherence <strong>ID52</strong> Commitment <strong>ID97</strong> Profits <strong>ID99</strong> Credit Score <strong>Section 3 - “Socio-economic” description. </strong>Questions about the socio-economic information of the survey respondents for data stratification. The indentation represents the dependency of questions and whether this data was asked <strong>ID164</strong> Understanding of questions <strong>ID300</strong> Country of residence <strong>ID137</strong> Age <strong>ID178</strong> Highest level of education <strong>ID136</strong> Willingness to provide data on the investment decision (respond apply for -Investment decision section) <strong>Section 4 - Investment decision</strong>. Questions about specific prices of potential purchases-decisions related to four scenarios (respondent's lifestyle) Appliances <strong>ID42</strong> Affordable cost of a Regular refrigerator <strong>ID45</strong> Energy efficient refrigerator costs <strong>ID50</strong> Willingness to purchase an energy efficient refrigerator <strong>ID65</strong> Why no <strong>ID66</strong> affordable cost of an energy efficient option <strong>ID67</strong> Years to amortize an efficient option Insulation <strong>ID47</strong> Affordable cost of updating to a state of the art insulation on the facade <strong>ID56</strong> Willingness for paying/invest <strong>ID74</strong> Why no? <strong>ID20</strong> affordable cost of an energy efficient option <strong>ID34</strong> Years to amortize an energy efficient option Energy Generation <strong>ID68</strong> Affordable cost of a solar photovoltaic system <strong>ID76</strong> Willingness for paying/invest <strong>ID84</strong> Why no? <strong>ID132</strong> Affordable cost of a photovoltaic system <strong>ID138</strong> Years that amortize a photovoltaic system Energy Storage <strong>ID142</strong> Affordable cost of an energy storage system <strong>ID146</strong> Willingness for paying/invest <strong>ID181</strong> Why no? <strong>ID182</strong> Affordable cost of an energy storage system <strong>ID183</strong> Years that amortize an energy storage systems Heating <strong>ID140</strong> Affordable cost of a gas boiler <strong>ID209</strong> Affordable cost of an energy efficient heating system <strong>ID217</strong> Willingness for paying/invest <strong>ID238</strong> Why no? <strong>ID239</strong> Affordable cost of a energy efficient option <strong>ID241</strong> Years that amortize a heat pumps Mobility <strong>ID41</strong> Average kilometers traveled a typical day <strong>ID51</strong> Usual travel option <strong>ID264</strong> Affordable cost of a diesel or gasoline mid-range brand new car <strong>ID265</strong> Affordable cost of a mid-range brand new electric car <strong>ID281</strong> Willingness to buy an electric car <strong>ID289</strong> Why no? <strong>ID290</strong> Affordable price of an electric car <strong>ID291</strong> Years that amortize an electric car <strong>Section 5 - Household characterization</strong> <strong>ID127</strong> Selecting an asked value <strong>ID189</strong> Type of living area <strong>ID202</strong> Gender identity <strong>ID1</strong> Those living in the house <strong>ID32</strong> Number of inhabitants <strong>ID220</strong> Average neat yearly income <strong>ID229</strong> Average monthly saving <strong>ID240</strong> Type of housing <strong>ID249</strong> Owner / co-owner <strong>ID255</strong> Usable area of the property (m²) <strong>ID263</strong> Insulation level <strong>ID270</strong> Climate zone <strong>ID86</strong> Level of self-awareness about climate change. On scale of 0-10, where 0 is “climate change does not exist” and 10 is “I am a climate change expert/activist” <strong>ID87</strong> Level of awareness of climate change among your peers or relatives, On a scale of 0-10, where 0 is “climate change does not exist” and 10 is “They are climate change experts/activists” <strong>ID88</strong> Level of self-awareness about energy transition. On a scale of 0-10, where 0 is “It is the first time I hear about it” and 10 is “I am an expert or activist” <strong>ID89</strong> Level of awareness of energy transition among your peers or relatives On a scale of 0-10, where 0 is “It is the first time they hear about it” and 10 is “They are experts or activists” <strong>ID190</strong> feedback about survey <strong>5 star</strong>: ⭐⭐⭐ <strong>Preprocessing steps:</strong> anonymization, data fusion, imputation of gaps. <strong>Reuse:</strong> NA <strong>Update policy:</strong> No more updates are planned <strong>Ethics and legal aspects:</strong> Spanish electric cooperative data contains the CUPS (Meter Point Administration Number), which is personal data. A pre-processing step has been carried out to substitute the CUPS by a random value hash. <strong>Technical aspects</strong>: <strong>Other:</strong>