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Record W2039386689 · doi:10.1287/mnsc.1070.0777

Service-Level Agreements in Call Centers: Perils and Prescriptions

2008· article· en· W2039386689 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

VenueManagement Science · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAdvanced Queuing Theory Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCenter (category theory)Variance (accounting)BusinessPercentilePerspective (graphical)Service (business)Contract managementCustomer satisfactionComputer scienceCall centreMarketingMicroeconomicsEconomicsMathematicsTelecommunicationsStatisticsAccounting

Abstract

fetched live from OpenAlex

Acall center with both contract and noncontract customers was giving priority to the contract customers only in off-peak hours, precisely when having priority was least important. In this paper, we investigate whether this is rational behavior on the part of the call center and what the implications are for customers. In particular, we show that under contracts on the percentile of delay, which are commonly used in the call center industry, this is rational behavior, at least under the approximating asymptotic regime considered in this paper. We then suggest other contracts that do not result in this type of undesirable behavior from a contract customer's perspective. We compare the performance of the different contracts in terms of mean, variance, and outer percentiles of delay for both customer types using both numerical and asymptotic heavy-traffic analyses. We argue that including terms reflecting the second moment of delay in a contract would be beneficial to contract customers and, in a sense, fairer.

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)0.001
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 score0.321
Threshold uncertainty score0.597

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.001
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 head0.039
GPT teacher head0.245
Teacher spread0.206 · 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