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Record W2886415636 · doi:10.1108/ejm-11-2017-0848

Reversing the endowment effect by empowering buyers and sellers

2018· article· en· W2886415636 on OpenAlexaff
Eugene Y. Chan, Najam U. Saqib

Bibliographic record

VenueEuropean Journal of Marketing · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicPsychology of Social Influence
Canadian institutionsLaurentian University
Fundersnot available
KeywordsEndowment effectValue (mathematics)EconomicsMarketingModerationMicroeconomicsFeelingEndowmentValuation (finance)WarrantDatabase transactionBusinessPsychologySocial psychologyFinancial economics

Abstract

fetched live from OpenAlex

Purpose The endowment effect is well-established in economics, psychology and marketing where sellers place a higher value on a good than buyers. One potential moderator, namely, power is explored. The authors predicted that feeling powerful can reverse the effect, making buyers place a higher value on a good than sellers. Design/methodology/approach The authors manipulated power to assess the effects on the valuation of three different products (keychain, gift card and iPhone case). They also assessed participants’ focus on parting with the good (money), which is a loss, and receiving money (the good), which is a gain, for sellers (buyers). Findings Feelings of power reduced sellers’ prices but they increased buyers’. Crucially, the authors observed the endowment effect, but only under conditions of low power. When participants had high power, the effect reversed, with buyers placing a higher value on the good under transaction than sellers. Process data indicated that powerful buyers and sellers focused on what they gained and less on what they lost, compared to powerless buyers and sellers. Research limitations/implications The authors link the construct of power with the endowment effect, showing that the former can moderate the latter. Certainly, the endowment effect is well-established, but there are moderators and boundary conditions that warrant consideration. Practical implications The results suggest a case where the market may clear, where buyers value a consumer product more than sellers, and thus buyers would likely accept the offer made by sellers. Originality/value The authors are the first to link the power literature with the endowment effect. They also show a possible moderator for the well-established endowment effect.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.023
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.674
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.306
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2018
Admission routes1
Has abstractyes

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