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Record W2143376044 · doi:10.1080/10580531003685204

An E-Business Audit Service Model in the B2B Context

2010· article· en· W2143376044 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

VenueInformation Systems Management · 2010
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsAuditBusinessService (business)New business developmentBusiness processElectronic businessBusiness service providerProcess managementKnowledge managementBusiness modelAccountingService designService delivery frameworkComputer scienceMarketing

Abstract

fetched live from OpenAlex

This research studies E-business audit as a specialized service rendered in an information technology intensive environment. A service model is used to research the E-business audit context. Here auditing is viewed as a specialized technical service conducted in the context of E-business technologies, business processes, and people involved in E-business transactions. The specialized audit service is provided to the E-Business transacting firms that in most cases involve transactions between customers and suppliers. A field study of information technology auditors showed that both knowledge of the business processes and of the technologies were critical for them to render reliable and accurate E-business audit findings. The results showed the need for higher training levels in advanced IT methods and tools for technology auditors in rendering IT audit judgments for the business-to-business (B2B) context. Thus, these results provided support for the service model that calls for the appropriate knowledge and use of technologies, business processes, and people in providing service.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.744
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.069
GPT teacher head0.344
Teacher spread0.275 · 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