IDEAS home Printed from https://ideas.repec.org/p/ris/fcnwpa/2017_014.html
   My bibliography  Save this paper

Adoption and Cooperation Decisions in Sustainable Energy Infrastructure: Evidence from a Sequential Choice Experiment in Germany

Author

Listed:

Abstract

In this paper, we propose and apply the design of a sequential discrete choice experiment to examine homeowner preferences regarding the adoption of micro-generation systems and willingness to cooperate in sustainable energy infrastructure. Adoption and cooperation decisions of private households in the energy sector are complex, interlinked, and assumably sequential. A common design with single choice tasks reflecting both adoption and cooperation decisions is assumed as cognitively too burdensome for survey respondents. The objective of the proposed sequential choice task design is twofold. Firstly, reducing complexity for respondents. Secondly, reflecting a step-wise decision process as is appropriate for the studied decisions. Our application from the energy sector is motivated by the need for innovative business models for non-industrial prosumers providing flexibility services in (local) distribution grids, due to an increasing amount of volatile and decentrally generated electricity. Results indicate that respondents reveal more pronounced preferences when dealing with their decision in sequential steps and that the task design has a lasting effect on respondents’ choices. By estimating latent class logit models, five consumer classes are identified and labeled by their distinguished motivational foci: costs (1), climate protection (2), self-supply (3), local reference (4), and other (5).

Suggested Citation

  • Oberst, Christian & Harmsen - van Hout, Marjolein J. W., 2017. "Adoption and Cooperation Decisions in Sustainable Energy Infrastructure: Evidence from a Sequential Choice Experiment in Germany," FCN Working Papers 14/2017, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    • Handle: RePEc:ris:fcnwpa:2017_014
    as

    Download full text from publisher

    File URL: http://www.fcn.eonerc.rwth-aachen.de/global/show_document.asp?id=aaaaaaaaabdbzah
    File Function: Full text
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Oberst, Christian A. & Schmitz, Hendrik & Madlener, Reinhard, 2019. "Are Prosumer Households That Much Different? Evidence From Stated Residential Energy Consumption in Germany," Ecological Economics, Elsevier, vol. 158(C), pages 101-115.
    2. Scarpa, Riccardo & Willis, Ken, 2010. "Willingness-to-pay for renewable energy: Primary and discretionary choice of British households' for micro-generation technologies," Energy Economics, Elsevier, vol. 32(1), pages 129-136, January.
    3. Debby van Helvoort‐Postulart & Benedict G. C. Dellaert & Trudy van der Weijden & Maarten F. von Meyenfeldt & Carmen D. Dirksen, 2009. "Discrete choice experiments for complex health‐care decisions: does hierarchical information integration offer a solution?," Health Economics, John Wiley & Sons, Ltd., vol. 18(8), pages 903-920, August.
    4. Fredrik Carlsson & Peter Martinsson, 2008. "How Much is Too Much?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 40(2), pages 165-176, June.
    5. Achtnicht, Martin, 2011. "Do environmental benefits matter? Evidence from a choice experiment among house owners in Germany," Ecological Economics, Elsevier, vol. 70(11), pages 2191-2200, September.
    6. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    7. Hoyos, David, 2010. "The state of the art of environmental valuation with discrete choice experiments," Ecological Economics, Elsevier, vol. 69(8), pages 1595-1603, June.
    8. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    9. Kalkbrenner, Bernhard J. & Yonezawa, Koichi & Roosen, Jutta, 2017. "Consumer preferences for electricity tariffs: Does proximity matter?," Energy Policy, Elsevier, vol. 107(C), pages 413-424.
    10. Harmsen - van Hout, Marjolein & Ghosh, Gaurav & Madlener, Reinhard, 2013. "An Evaluation of Attribute Anchoring Bias in a Choice Experimental Setting," FCN Working Papers 6/2013, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    11. Christian A. Oberst & Reinhard Madlener, 2015. "Prosumer Preferences Regarding the Adoption of Micro†Generation Technologies: Empirical Evidence for German Homeowners," Working Papers 2015.07, International Network for Economic Research - INFER.
    12. Benedict G. C. Dellaert & Aloys W. J. Borgers & Jordan J. Louviere & Harry J. P. Timmermans, 2007. "Using Conjoint Choice Experiments to Model Consumer Choices of Product Component Packages," Springer Books, in: Anders Gustafsson & Andreas Herrmann & Frank Huber (ed.), Conjoint Measurement, edition 0, chapter 14, pages 273-293, Springer.
    13. Biegel, Benjamin & Hansen, Lars Henrik & Stoustrup, Jakob & Andersen, Palle & Harbo, Silas, 2014. "Value of flexible consumption in the electricity markets," Energy, Elsevier, vol. 66(C), pages 354-362.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Specht, Jan Martin & Madlener, Reinhard, 2018. "Business Models for Energy Suppliers Aggregating Flexible Distributed Assets and Policy Issues Raised," FCN Working Papers 7/2018, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    2. Pereira, Guillermo Ivan & Specht, Jan Martin & Silva, Patrícia Pereira & Madlener, Reinhard, 2018. "Technology, business model, and market design adaptation toward smart electricity distribution: Insights for policy making," Energy Policy, Elsevier, vol. 121(C), pages 426-440.
    3. Heesen, Florian & Madlener, Reinhard, 2021. "Revisiting heat energy consumption modeling: Household production theory applied to field experimental data," Energy Policy, Elsevier, vol. 158(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Meles, Tensay Hadush & Ryan, Lisa & Mukherjee, Sanghamitra C., 2022. "Heterogeneity in preferences for renewable home heating systems among Irish households," Applied Energy, Elsevier, vol. 307(C).
    2. Christian A. Oberst & Reinhard Madlener, 2015. "Prosumer Preferences Regarding the Adoption of Micro†Generation Technologies: Empirical Evidence for German Homeowners," Working Papers 2015.07, International Network for Economic Research - INFER.
    3. Stefania Troiano & Daniel Vecchiato & Francesco Marangon & Tiziano Tempesta & Federico Nassivera, 2019. "Households’ Preferences for a New ‘Climate-Friendly’ Heating System: Does Contribution to Reducing Greenhouse Gases Matter?," Energies, MDPI, vol. 12(13), pages 1-19, July.
    4. Alessandro Mengoni & Chiara Seghieri & Sabina Nuti, 2013. "The application of discrete choice experiments in health economics: a systematic review of the literature," Working Papers 201301, Scuola Superiore Sant'Anna of Pisa, Istituto di Management.
    5. Galassi, Veronica & Madlener, Reinhard, 2014. "Identifying Business Models for Photovoltaic Systems with Storage in the Italian Market: A Discrete Choice Experiment," FCN Working Papers 19/2014, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    6. de Ayala, Amaia & Hoyos, David & Mariel, Petr, 2015. "Suitability of discrete choice experiments for landscape management under the European Landscape Convention," Journal of Forest Economics, Elsevier, vol. 21(2), pages 79-96.
    7. Chiadmi, Ines & Traoré, Sidnoma Abdoul Aziz & Salles, Jean-Michel, 2020. "Asian tiger mosquito far from home: Assessing the impact of invasive mosquitoes on the French Mediterranean littoral," Ecological Economics, Elsevier, vol. 178(C).
    8. Laura Enthoven & Goedele Van den Broeck, 2021. "Promoting Food Safety in Local Value Chains: The Case of Vegetables in Vietnam," Sustainability, MDPI, vol. 13(12), pages 1-17, June.
    9. Schaak, Henning & Mußhoff, Oliver, 2019. "Public preferences for livestock presence in pasture landscape: A latent class analysis of a discrete choice experiment in Germany," DARE Discussion Papers 1901, Georg-August University of Göttingen, Department of Agricultural Economics and Rural Development (DARE).
    10. Chad M. Baum & Robert Weigelt, 2019. "How Where I Shop Influences What I Buy: The Importance of the Retail Format in Sustainable Tomato Consumption," Economic Complexity and Evolution, in: Andreas Chai & Chad M. Baum (ed.), Demand, Complexity, and Long-Run Economic Evolution, pages 141-169, Springer.
    11. Achtnicht, Martin & Madlener, Reinhard, 2014. "Factors influencing German house owners' preferences on energy retrofits," Energy Policy, Elsevier, vol. 68(C), pages 254-263.
    12. Ruokamo, Enni, 2016. "Household preferences of hybrid home heating systems – A choice experiment application," Energy Policy, Elsevier, vol. 95(C), pages 224-237.
    13. Oryani, Bahareh & Koo, Yoonmo & Shafiee, Afsaneh & Rezania, Shahabaldin & Jung, Jiyeon & Choi, Hyunhong & Khan, Muhammad Kamran, 2022. "Heterogeneous preferences for EVs: Evidence from Iran," Renewable Energy, Elsevier, vol. 181(C), pages 675-691.
    14. Ek, Kristina & Persson, Lars, 2014. "Wind farms — Where and how to place them? A choice experiment approach to measure consumer preferences for characteristics of wind farm establishments in Sweden," Ecological Economics, Elsevier, vol. 105(C), pages 193-203.
    15. Andersson, Henrik & Hole, Arne Risa & Svensson, Mikael, 2016. "Valuation of small and multiple health risks: A critical analysis of SP data applied to food and water safety," Journal of Environmental Economics and Management, Elsevier, vol. 75(C), pages 41-53.
    16. Daziano, Ricardo A. & Achtnicht, Martin, 2014. "Accounting for uncertainty in willingness to pay for environmental benefits," Energy Economics, Elsevier, vol. 44(C), pages 166-177.
    17. Girod, Bastien & Mayer, Sebastian & Nägele, Florian, 2017. "Economic versus belief-based models: Shedding light on the adoption of novel green technologies," Energy Policy, Elsevier, vol. 101(C), pages 415-426.
    18. Groh, Elke D., 2022. "Exposure to wind turbines, regional identity and the willingness to pay for regionally produced electricity," Resource and Energy Economics, Elsevier, vol. 70(C).
    19. Jihee Lee & HyungBin Moon & Jongsu Lee, 2021. "Consumers’ heterogeneous preferences toward the renewable portfolio standard policy: An evaluation of Korea’s energy transition policy," Energy & Environment, , vol. 32(4), pages 648-667, June.
    20. Schleich, Joachim & Tu, Gengyang & Faure, Corinne & Guetlein, Marie-Charlotte, 2021. "Would you prefer to rent rather than own your new heating system? Insights from a discrete choice experiment among owner-occupiers in the UK," Energy Policy, Elsevier, vol. 158(C).

    More about this item

    Keywords

    Choice Experiment; Micro-generation; Renewable Energy; Community Energy; Energy Transition;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ris:fcnwpa:2017_014. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Hendrik Schmitz (email available below). General contact details of provider: https://edirc.repec.org/data/fceonde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.