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Flexible customer willingness to pay for bundled smart home energy products and services

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  • Daziano, Ricardo A.

Abstract

Energy markets are rapidly changing with smarter, connected, more reliable infrastructure and cleaner generation on the supply side, and more choice, greater control and enhanced flexibility for customers. This paper examines willingness to pay for bundled smart home energy products and information services, using data from a set of two discrete choice experiments that were part of a survey by the regional energy provider of upstate New York. To let the data reveal how preferences are distributed in the population, a logit-mixed logit model in willingness-to-pay space and a combination of observed and unobserved preference heterogeneity was specified and fitted. Results show that residents of Tompkins County are willing to pay more than in other counties for residential storage, and that for home energy management there is an important generational divide with millennials being much more likely to perceive the economic value in the smart energy technologies. The flexible logit-mixed logit estimates provide evidence of important heterogeneity in preferences: whereas most of the population has a positive—albeit rather low—valuation of smart energy products and services, there is a considerable percentage of customers with negative perceptions.

Suggested Citation

  • Daziano, Ricardo A., 2020. "Flexible customer willingness to pay for bundled smart home energy products and services," Resource and Energy Economics, Elsevier, vol. 61(C).
    • Handle: RePEc:eee:resene:v:61:y:2020:i:c:s0928765519303227
    DOI: 10.1016/j.reseneeco.2020.101175
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    Cited by:

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    4. Ciarreta, Aitor & Espinosa, Maria Paz & Pizarro-Irizar, Cristina, 2023. "Pricing policies for efficient demand side management in liberalized electricity markets," Economic Modelling, Elsevier, vol. 121(C).

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    More about this item

    Keywords

    Discrete choice; Seminonparametrics; Willingness to pay; Logit-mixed logit; Smart energy packages; New energy markets;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design

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