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Smart users for smart technologies: Investigating the intention to adopt smart energy consumption behaviors

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  • Perri, Cecilia
  • Giglio, Carlo
  • Corvello, Vincenzo

Abstract

Smart grid technologies have the potential to overcome several environmental, social, and technical problems associated with the current electricity production and consumption modes. However, the adoption of smart grids requires a change in users’ behavior. This study investigates the individual-level motivational factors that affect the intention to adopt “smart consumption and production behaviors”. Understanding these factors is important for implementing effective behavioral change initiatives that would facilitate the diffusion of smart grids. Ajzen's theory of planned behavior is applied to explain the formation of such an adoption intention. With a questionnaire survey distributed to a random sample of consumers, an elicitation study is conducted to obtain salient modal beliefs. Data collected from the main survey are analyzed using structural equation modeling. Consistent with the theory, the results of the structural equation analysis reveals that attitude, subjective norm, and perceived behavioral control positively affect the adoption intention. Specifically, the study finds that the variable with the highest estimated loading factor perceived behavioral control, and the most important belief linked with attitude is energy savings. Further investigation indicates that the added exogenous variable, resistance to change, has a negative influence on intention. Results confirm the explanatory power of the theoretical model and provide valuable knowledge for individuals and institutions interested in facilitating the diffusion of smart grids via the implementation of behavioral change initiatives.

Suggested Citation

  • Perri, Cecilia & Giglio, Carlo & Corvello, Vincenzo, 2020. "Smart users for smart technologies: Investigating the intention to adopt smart energy consumption behaviors," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
  • Handle: RePEc:eee:tefoso:v:155:y:2020:i:c:s004016251930839x
    DOI: 10.1016/j.techfore.2020.119991
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