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Record W2333289370 · doi:10.5539/ibr.v9n5p112

Creating Shared Value: the Fundamental Ontology of Establishing and Movement in Business

2016· article· en· W2333289370 on OpenAlexvenueno aff
Nishchapat Nittapaipapon, Thithit Atchattabhan

Bibliographic record

VenueInternational Business Research · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Strategies and Innovation
Canadian institutionsnot available
Fundersnot available
KeywordsAnticipation (artificial intelligence)Value (mathematics)Creating shared valueBusiness valueShareholderAdaptabilityShareholder valueCompetitive advantageValue creationBusiness transformationOntologyKnowledge managementBusiness modelProcess managementCorporate social responsibilityBusinessComputer scienceMarketingManagementElectronic businessPublic relationsBusiness relationship managementEpistemologyEconomicsPolitical scienceCorporate governanceMicroeconomics

Abstract

fetched live from OpenAlex

<p>The creation of CSV concept of Porter and Kramer (2011) has uncovered in empirical evidence to both of academic and business practical which a concept prominently manifested currently and future of business prospect. The anticipation and challenge manipulating have become meaningful and sophisticated hence; this article aims to explore a new aspect of CSV as the fundamental ontology of business creation and examine the movement in the business founded on the opportunity to create social value. The resulting proposes creating shared value (CSV) indeed defined as the fundamental of business procreation where business can express manifesting to establish the competitive advantage particularly the transformation changed reciprocated to social value. The three case studies enlighten the significant of focused strategy and the adaptability direction of business needed to engage shareholder anticipation which seems to be crucial for social value creation. In addition, manipulation of CSV-single value focused strategy deals with business operation and social value creation as a favorable arrangement.</p>

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)0.001
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 score0.436
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
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 head0.067
GPT teacher head0.333
Teacher spread0.266 · 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 designObservational
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

Citations0
Published2016
Admission routes1
Has abstractyes

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