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Record W2978629017 · doi:10.5267/j.msl.2019.9.016

A methodology for analysis and assessment of business processes of Ukrainian enterprises

2019· article· en· W2978629017 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueManagement Science Letters · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnterprise Management and Information Systems
Canadian institutionsnot available
Fundersnot available
KeywordsUkrainianBusinessProcess managementComputer science

Abstract

fetched live from OpenAlex

The article presents a methodological tool for analysis and evaluation of business processes of Ukrainian enterprises. The proposed methodology is provided for the identification of "problem" areas of certain business processes by calculating average weighted, integral and generic indicators of efficiency and effectiveness. It allows to evaluate the status of both certain business processes of enterprises and their totality, and to set the priorities of management actions for their improvements. The proposed methodology is examined on the example of a specific enterprise of the construction industry. In the framework of the proposed criteria (financialeconomic, resource-production, external integration, organizational), a list of indicators, taking into account the specifics of the enterprise are formed. Assessment of the efficiency and effectiveness of business processes by the specified criteria and indicators allows one to monitor the current activity of the enterprise and evaluate the effectiveness of its operations at every moment of time.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.040
GPT teacher head0.303
Teacher spread0.264 · 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