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Record W4220990557 · doi:10.33423/jabe.v24i1.5046

Digital Transformation as a Business Sustainability Instrument

2022· article· en· W4220990557 on OpenAlexvenueno aff

Bibliographic record

VenueJournal of Applied Business and Economics · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBusiness, Innovation, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsBusiness transformationSustainabilityDigital transformationBusinessSustainable businessCompetitive advantageNew business developmentBusiness modelProcess managementDigital RevolutionProcess (computing)Sustainable developmentBusiness processStrategic managementBusiness environmentBusiness analysisElectronic businessIndustrial organizationBusiness relationship managementMarketingComputer scienceTelecommunicationsWork in processBusiness administration

Abstract

fetched live from OpenAlex

In recent years, companies' contribution to achieving the sustainable development of countries has been significant, especially in an environment of dizzying and unpredictable business changes in most business sectors. A business environment where companies need to continuously improve their ability to develop and maintain a competitive advantage. To face these environments and be sustainable over time facing new forms of business management, it is essential to join the digital revolution through a digital transformation which is a process that aims to optimize a company by promoting changes in its characteristics by combining information technologies, automation, communication and connectivity with priority in a strategic and aligned way according to the evolution in tastes and preferences of us individuals. The objective of this paper is to share a review of both concepts aligned with each other: Digital transformation and sustainability as a basis in their current relationship to raise from the business vision the new competitiveness consolidated in technology to adapt to business challenges and the dynamics of changes in business preferences.

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.

How this classification was reachedexpand

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.427
Threshold uncertainty score0.947

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.013
GPT teacher head0.179
Teacher spread0.166 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

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