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Record W2012874307 · doi:10.1016/j.jom.2011.04.001

Failure to deliver? Linking online order fulfillment glitches with future purchase behavior

2011· article· en· W2012874307 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Operations Management · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsTellabs (Canada)
Fundersnot available
KeywordsGlitchOrder (exchange)Order fulfillmentExpectancy theoryBusinessMarketingConsumer behaviourOrder bookPsychologyComputer scienceSocial psychologySupply chainTelecommunications

Abstract

fetched live from OpenAlex

Abstract This study investigates operations failures in online retailing. Specifically, it examines the relationship between an operations glitch (order fulfillment delay) and subsequent shopping behavior for previously loyal customers in an online retailing environment. Using archival data from a moderate‐sized online retailer of printed material, this study employs expectancy disconfirmation and distributive justice theories to empirically show that adverse post‐glitch reactions are seen in several dimensions of customer shopping behavior – order frequency and order size decrease, while customer anxiety level increases. The study thus demonstrates that online retailers need to deliver on order fulfillment promises, since a failure to live up to these promises can be detrimental. This study is unique in that, unlike previous studies on order fulfillment in online retailing investigating the tie between fulfillment success and future behavior, we examine the repercussions of order fulfillment failures upon future purchase behavior.

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.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.680
Threshold uncertainty score0.780

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.250
Teacher spread0.219 · 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