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Willingness to pay and nuanced cultural cues: Evidence from Hong Kong's license-plate auction market

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  • Woo, Chi-Keung
  • Horowitz, Ira
  • Luk, Stephen
  • Lai, Aaron

Abstract

We estimate a hedonic price model of willingness to pay (WTP) for superstition. The model explains WTP measured by winning bids in Hong Kong license-plate auctions through numeric and alpha-numeric sequences catering to culturally-sensitive superstitions, tempered by self-expression, economic and auction-specific considerations. The paper adds to the extant literature on three dimensions. First, we focus on a commodity that is a necessary accessory with no intrinsic value, known to be available in unlimited supply at a production cost substantially less than the buyer's WTP. Second, we show differentiated responses by consumers to nuanced cues that exploit well-known local cultural sensitivities. Finally, we incorporate macroeconomic and auction-specific variables to elicit their impact on consumer preferences and behavior within our culturally-sensitive context. Our results suggest quantifiable differences in consumer responses to psychologically-nuanced cultural cues, which management can exploit to its competitive advantage. This evidence is relevant and timely, given the rising corporate interest in serving the vast and growing consumer market in China.

Suggested Citation

  • Woo, Chi-Keung & Horowitz, Ira & Luk, Stephen & Lai, Aaron, 2008. "Willingness to pay and nuanced cultural cues: Evidence from Hong Kong's license-plate auction market," Journal of Economic Psychology, Elsevier, vol. 29(1), pages 35-53, February.
  • Handle: RePEc:eee:joepsy:v:29:y:2008:i:1:p:35-53
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    2. Vinci Chow, 2019. "Predicting Auction Price of Vehicle License Plate with Deep Residual Learning," Papers 1910.04879, arXiv.org.
    3. Chui, Peter M.W. & Fong, Lawrence Hoc Nang & Ren, Jinjuan & Tam, Lewis H.K., 2022. "Anchoring effects in repeated auctions of homogeneous objects: Evidence from Macao," Journal of Economic Psychology, Elsevier, vol. 90(C).
    4. Shum, Matthew & Sun, Wei & Ye, Guangliang, 2014. "Superstition and “lucky” apartments: Evidence from transaction-level data," Journal of Comparative Economics, Elsevier, vol. 42(1), pages 109-117.
    5. Han, SeungOh, 2024. "Price clustering on cryptocurrency order books at a US-based exchange," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(C).
    6. Brad R. Humphreys & Adam Nowak & Yang Zhou, 2017. "Chinese Superstition and Real Estate Prices: Transaction-level Evidence from the US Housing Market," Working Papers 17-18, Department of Economics, West Virginia University.
    7. Maria De Paola & Francesca Gioia & Vincenzo Scoppa, 2013. "Overconfidence, Omens And Emotions: Results From A Field Experiment," Framed Field Experiments 00395, The Field Experiments Website.
    8. Nicole M. Fortin & Andrew J. Hill & Jeff Huang, 2014. "Superstition In The Housing Market," Economic Inquiry, Western Economic Association International, vol. 52(3), pages 974-993, July.
    9. Ng, Travis & Chong, Terence & Du, Xin, 2010. "The value of superstitions," Journal of Economic Psychology, Elsevier, vol. 31(3), pages 293-309, June.
    10. Brad R. Humphreys & Adam Nowak & Yang Zhou, 2016. "Cultural Superstitions and Residential Real Estate Prices: Transaction-level Evidence from the US Housing Market," Working Papers 16-27, Department of Economics, West Virginia University.
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    14. Vinci Chow, 2017. "Predicting Auction Price of Vehicle License Plate with Deep Recurrent Neural Network," Papers 1701.08711, arXiv.org, revised Oct 2019.
    15. De Paola, Maria & Gioia, Francesca & Scoppa, Vincenzo, 2014. "Overconfidence, omens and gender heterogeneity: Results from a field experiment," Journal of Economic Psychology, Elsevier, vol. 45(C), pages 237-252.
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