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Record W4403799861 · doi:10.1002/mar.22150

Choice, Psychological Ownership, and Option Valuation

2024· article· en· W4403799861 on OpenAlexaff
Eugene Y. Chan

Bibliographic record

VenuePsychology and Marketing · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsValuation (finance)Actuarial scienceEconomicsBusinessPsychologyAccounting

Abstract

fetched live from OpenAlex

ABSTRACT In the past few decades, there have been concerns of a possible “choice overload effect” in that the provision of more (vs. less) choice might decrease choice satisfaction as it increases the difficulty of selecting an option among many. However, beyond choice satisfaction, there are other outcomes of offering more choices worth investigating. We examine another potential outcome of offering more choices. The results from four experiments suggest that offering more choice increases the chooser's valuation of the chosen option, relative to offering less choice. This is because offering choice increases the chooser's psychological ownership of the chosen option, a premise derived from prior conceptualizations of choice as fostering control. Thus, we extend theoretical understanding of the consequences of offering choice beyond satisfaction, while at the same time offer implications for marketers interested in understanding the benefits—in addition to the potential harms—of offering choice for consumers.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.147
GPT teacher head0.306
Teacher spread0.159 · 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 designObservational
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

Citations4
Published2024
Admission routes1
Has abstractyes

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