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A neuro-advertising property video recommendation system

Author

Listed:
  • Kaklauskas, A.
  • Zavadskas, E.K.
  • Banaitis, A.
  • Meidute-Kavaliauskiene, I.
  • Liberman, A.
  • Dzitac, S.
  • Ubarte, I.
  • Binkyte, A.
  • Cerkauskas, J.
  • Kuzminske, A.
  • Naumcik, A.

Abstract

Many factors influence the identification of the best real estate alternatives, such as supply and demand and the social, cultural, psychological and personal factors affecting buyer behavior and the emotional state of a buyer. What are the most effective ways of choosing a property, when the selection is so vast and complex? An aid is developed here to accomplish this, based on a new advertising format, an iterative method and the NEuro-Advertising Property Video Recommendation System (NEAR). A known methodology involves behavioral operational research and the emotions involved in decision-making. Three advanced research contributions are unique to the proposed method and NEAR, in contrast to innovative behavioral operational research. Firstly, data are compiled for a neuro decision matrix, based on housing attributes and the valence, arousal, emotional state and physiological parameters of a potential real estate buyer. Secondly, the performance of a multiple criteria neuroanalysis occurs as well as the selection of the most personalized and effective video clip ad variants drawn from many alternatives. Finally, NEAR is found to present the most effective video clips ads for real estate buyers for as long a period as possible, according to Multiple Resource Theory.

Suggested Citation

  • Kaklauskas, A. & Zavadskas, E.K. & Banaitis, A. & Meidute-Kavaliauskiene, I. & Liberman, A. & Dzitac, S. & Ubarte, I. & Binkyte, A. & Cerkauskas, J. & Kuzminske, A. & Naumcik, A., 2018. "A neuro-advertising property video recommendation system," Technological Forecasting and Social Change, Elsevier, vol. 131(C), pages 78-93.
    • Handle: RePEc:eee:tefoso:v:131:y:2018:i:c:p:78-93
    DOI: 10.1016/j.techfore.2017.07.011
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    Cited by:

    1. Arturas Kaklauskas & Edmundas Kazimieras Zavadskas & Bjoern Schuller & Natalija Lepkova & Gintautas Dzemyda & Jurate Sliogeriene & Olga Kurasova, 2020. "Customized ViNeRS Method for Video Neuro-Advertising of Green Housing," IJERPH, MDPI, vol. 17(7), pages 1-28, March.
    2. Carayannis, Elias G. & Ferreira, João J.M. & Jalali, Marjan S. & Ferreira, Fernando A.F., 2018. "MCDA in knowledge-based economies: Methodological developments and real world applications," Technological Forecasting and Social Change, Elsevier, vol. 131(C), pages 1-3.

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