MétaCan
Menu
Back to cohort
Record W2971162245 · doi:10.5539/jms.v9n2p25

Methodological Redirections for an Evolutionary Approach of the External Business Environment

2019· article· en· W2971162245 on OpenAlexvenueno aff
Charis Vlados, Dimos Chatzinikolaou

Bibliographic record

VenueJournal of Management and Sustainability · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsnot available
FundersUniversity of the AegeanTrakya Üniversitesi
KeywordsContext (archaeology)Socioeconomic statusKnowledge managementManagement scienceSociologyBusinessComputer scienceEconomicsPopulationGeography

Abstract

fetched live from OpenAlex

The usual strategic analysis perceives the external business environment fragmentarily and without a coherent and unifying way. The three levels that a typical analysis of the external business environment involves are a) the macroenvironment and PEST analysis, b) mesoenvironment and “Porter’s diamond”, and c) industrial environment and “Porter’s five forces”. Contrary to the fragmentary analysis of the three levels, this article aims to counter-propose a restructured method of a unified and evolutionary analysis of the external business environment. After presenting the usual analytical handling of the external business environment in the three levels, we suggest that these are rather co-evolving than separate and autonomous spheres of analysis. Therefore, after introducing some elements of the evolutionary socioeconomic theory, we propose a systemic web that perceives the external environment of the socioeconomic organisations in dynamically unified and evolutionary terms. The systemic web conceptualises the approach of the external socioeconomic environment as an open and interactive system comprising three co-evolving spheres in the context of global dynamics: the institutional character of each spatially structured socioeconomic formation; the firm’s functions within the system; and the public-state intervention that contributes to the establishment and reproduction of the system. This conceptual redirection of the methodology of the external business environment can be useful for building an integrated strategic analysis that studies all “micro-meso-macro” components of the entire socioeconomic system.

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)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.353

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.053
GPT teacher head0.281
Teacher spread0.228 · 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

Citations17
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Management and SustainabilitySame topicInnovation and Knowledge ManagementFrench-language works237,207