Prior Product Knowledge Bias about NGP Goods Affects Post-Purchase Surveys
Olivier Mesly
Journal of Economic Issues, 2025, vol. 59, issue 2, 619-637
Abstract:
This study delves into the economic consequences of prior product knowledge in post-purchase satisfaction surveys, focusing on the used car and real estate sectors as case examples, for so-called NGP goods. I resort to the five-step purchasing model and focus on the link between the step of information gathering and the post-purchase step, whereby market agents are seen or act with dubious motives. This research seeks to provide these embryonic yet valuable insights through linear regressions and path analysis. My study introduces my novel concept of the NGP framework, which refers to the interplay between consumer needs (N), objectives/goals (G), and preferences (P) in relation to products of high economic and/or emotional value, thereby enriching the current understanding of buying behavior and economic theory about unique kinds of products, such as Veblen and Giffen goods. I offer practical recommendations for businesses aiming to minimize the prior product-knowledge bias-related impacts. The findings can guide companies in designing more effective survey instruments and making informed economic decisions based on accurate assessment of customer feedback.
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/00213624.2025.2493587 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:mes:jeciss:v:59:y:2025:i:2:p:619-637
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/MJEI20
DOI: 10.1080/00213624.2025.2493587
Access Statistics for this article
More articles in Journal of Economic Issues from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().