MétaCan
Menu
Back to cohort
Record W4285520647 · doi:10.21272/1817-9215.2021.2-26

DEVELOPMENT OF INDUSTRIAL ENTERPRISE MANAGEMENT STRATEGY ON THE BASIS OF A BALANCED SYSTEM INDICATORS

2021· article· en· W4285520647 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueVìsnik Sumsʹkogo deržavnogo unìversitetu · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Issues in Ukraine
Canadian institutionsnot available
Fundersnot available
KeywordsBalanced scorecardStrategy mapBusinessProcess managementStrategic managementPerformance indicatorPerformance managementAgency (philosophy)Marketing

Abstract

fetched live from OpenAlex

This article is devoted to the study of the peculiarities of developing a management strategy for an industrial enterprise. Analysis of the main indicators of enterprise activity is a prerequisite for making effective management decisions and determining strategic directions of development in general. An urgent task for modern business entities is the formation of a balanced scorecard in order to implement it in the management strategy of the enterprise. Obstacles to the introduction of a balanced scorecard at Ukrainian enterprises have been identified. At the same time, among the foreign companies that have integrated the balanced scorecard are representatives of both the private and public sectors: Volkswagen, Ford Motor Company, Wells Fargo, Citibank, TD Canada Trust, Apple, Microsoft Latin America, Veriz, Veolia Water, Philips Electronics, City of Charlotte, Defense Logistics Agency, Federal Bureau of Investigations (FBI), University of Virginia. The system of balanced indicators contributes to the formalization and justification of strategic guidelines in accordance with the company's mission in quantitative and qualitative parameters, as well as specifies the actions and efforts of employees, consolidating their responsibility in achieving certain strategic results in staff motivation. This makes it possible to link the remuneration of staff with the achievement of the company's performance, which they have a direct impact on. The article systematizes the algorithm for developing a management strategy, the stages of forming a balanced scorecard. The key objectives that are necessary to achieve the set performance indicators according to the established blocks of analysis are identified: customers, business processes, training and career growth and finance. The relevance and importance of the chain of causation, which affects all components of a balanced system of indicators on the vertical vector. A balanced system of industrial enterprise development indicators is presented in general.

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 categoriesMeta-epidemiology (narrow)
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 score0.893
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.042
GPT teacher head0.210
Teacher spread0.168 · 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