Climbing the causality ladder to understand the energy demand on the residential sector

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Published December 1, 2022 | Version 1
Dataset Open

Characterization of investments profiles on the energy transition for european citizens

Creators

  • 1. University of Deusto

Contributors

  • 1. Norwegian University of Science and Technology
  • 2. JOANNEUM RESEARCH Forschungsgesellschaft mbh
  • 3. 4wardenergy
  • 4. GoiEner

Description

  • Name: Characterization of investments profiles on the energy transition for european citizens
  • Summary: 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. 
  • License: cc-BY-SA
  • Acknowledge: 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.
  • Disclaimer: 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.
  • Collection Date: 22/07/2022
  • Publication Date: 15/10/2023
  • DOI: 10.5281/zenodo.4455198
  • Other repositories:
  • Author: University of Deusto
  • Objective of collection: 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.
  • Description: The dataset contains a ODS spreadsheet 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
    • Section 1 - Scenarios for energy transition.
      • ID90. 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. 
      • ID36, ID38, ID43, ID44, ID72. Percentage of money people are willing to spend/save out of their income per scenario
      • ID191, ID192.. Amount of money people would spend based on an assumed case.
      • ID191, ID192. 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.
      • [ID325, ID326, ID327, ID328, ID329, ID330, ID331, ID332, ID333, ID334, ID335, ID336, ID337, ID338, ID339, ID340, ID341, ID133, ID242]. 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 and 10 stars means it is absolutely necessary.
      • [ID251, ID256, ID257, ID292, ID293, ID294, ID295, ID296, ID297, ID298, ID299, ID301, ID302, ID303, ID304, ID305, ID306, ID250, ID251]. Priority service provision in case of full black-outs. 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.
      • [ID141, ID5, ID147]. Used for statements that best represent survey responder
    • Section 2 - Determinants (factors). Questions used to rate (from 0 to 100) factors that may influence the decision-making process contributing to make an ideal scenario possible.
      • ID100 Risk profile
      • ID101 Added value
      • ID102 Self-Satisfaction
      • ID103 Technical Fit
      • ID104 Own competence
      • ID105 Knowledge
      • ID106 cost-Efficiency
      • ID107 Safety
      • ID108 Trust
      • ID109 Autarky
      • ID110 Legal
      • ID111 climate protection
      • ID112 Wellbeing
      • ID113 Coziness
      • ID114 Rights and Duties
      • ID115 Peer-Pressure
      • ID116 Socialising
      • ID117 Support
      • ID118 Agreement
      • ID119 Brag
      • ID120 Fun
      • ID121 Novelty
      • ID122 Trends
      • ID123 Authority
      • ID124 Own Significance
      • ID125 Poseur
      • ID2 Frugality
      • ID3 Environmental concerns
      • ID31 Adherence
      • ID52 Commitment
      • ID97 Profits
      • ID99 Credit Score
    • Section 3 - “Socio-economic” description. 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
      • ID164 Understanding of questions
      • ID300 Country of residence
      • ID137 Age
      • ID178 Highest level of education
      • ID136 Willingness to provide data on the investment decision (respond apply for -Investment decision section)
    • Section 4 - Investment decision. Questions about specific prices of potential purchases-decisions related to four scenarios (respondent's lifestyle)
      • Appliances
        • ID42 Affordable cost of a Regular refrigerator
        • ID45 Energy efficient refrigerator costs
        • ID50 Willingness to purchase an energy efficient refrigerator
          • ID65 Why no
          • ID66 affordable cost of an energy efficient option
          • ID67 Years to amortize an efficient option
      • Insulation
        • ID47 Affordable cost of updating to a state of the art insulation on the facade
        • ID56 Willingness for paying/invest
          • ID74 Why no?
          • ID20 affordable cost of an energy efficient option
          • ID34 Years to amortize an energy efficient option
      • Energy Generation
        • ID68 Affordable cost of a solar photovoltaic system
        • ID76 Willingness for paying/invest
          • ID84 Why no?
          • ID132 Affordable cost of a photovoltaic system
          • ID138 Years that amortize a  photovoltaic system
      • Energy Storage
        • ID142 Affordable cost of an energy storage system
        • ID146 Willingness for paying/invest
          • ID181 Why no? 
          • ID182 Affordable cost of an energy storage system 
          • ID183 Years that amortize an energy storage systems
      • Heating
        • ID140 Affordable cost of a gas boiler
        • ID209 Affordable cost of an energy efficient heating system
        • ID217 Willingness for paying/invest
          • ID238 Why no?
          • ID239 Affordable cost of a energy efficient option
          • ID241 Years that amortize a heat pumps
      • Mobility
        • ID41 Average kilometers traveled a typical day
        • ID51 Usual travel option
        • ID264 Affordable cost of a diesel or gasoline mid-range brand new car
        • ID265 Affordable cost of a mid-range brand new electric car
        • ID281 Willingness to buy an electric car
          • ID289 Why no?
          • ID290 Affordable price of an electric car
          • ID291 Years that amortize an electric car
    • Section 5 - Household characterization
      • ID127 Selecting an asked value
      • ID189 Type of living area
      • ID202 Gender identity
      • ID1 Those living in the house
      • ID32 Number of inhabitants
      • ID220 Average neat yearly income
      • ID229 Average monthly saving
      • ID240 Type of housing
      • ID249 Owner / co-owner
      • ID255 Usable area of the property (m²)
      • ID263 Insulation level
      • ID270 Climate zone
      • ID86 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”
      • ID87 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”
      • ID88 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”
      • ID89 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”
      • ID190 feedback about survey
  • 5 star: ⭐⭐⭐
  • Preprocessing steps: anonymization, data fusion, imputation of gaps.
  • Reuse: NA
  • Update policy: No more updates are planned
  • Ethics and legal aspects: 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.
  • Technical aspects: 
  • Other:

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Additional details

Funding

WHY – Climbing the causality ladder to understand and project the energy demand of the residential sector 891943
European Commission