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Record W2008516933 · doi:10.1287/mnsc.1120.1533

Large-Scale Service Marketplaces: The Role of the Moderating Firm

2012· article· en· W2008516933 on OpenAlex
Gad Allon, Achal Bassamboo, Eren B. Çil

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

VenueManagement Science · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain and Inventory Management
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsBusinessOperational efficiencyService (business)Scale (ratio)Service providerMarketingIndustrial organization

Abstract

fetched live from OpenAlex

Recently, large-scale, Web-based service marketplaces, where many small service providers compete among themselves in catering to customers with diverse needs, have emerged. Customers who frequent these marketplaces seek quick resolutions and thus are usually willing to trade prices with waiting times. The main goal of this paper is to discuss the role of the moderating firm in facilitating information gathering, operational efficiency, and communication among agents in service marketplaces. Surprisingly, we show that operational efficiency may be detrimental to the overall efficiency of the marketplace. Furthermore, we establish that to reap the “expected” gains of operational efficiency, the moderating firm may need to complement the operational efficiency by enabling communication among its agents. The study emphasizes the scale of such marketplaces and the impact it has on the outcomes. This paper was accepted by Yossi Aviv, operations management.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.710
Threshold uncertainty score0.774

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0020.002
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 head0.012
GPT teacher head0.210
Teacher spread0.198 · 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