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Record W2002430481 · doi:10.1108/14637150010345505

Management of environmental scanning processes in large companies in Thailand

2000· article· en· W2002430481 on OpenAlexaboutno aff
Chittipa Ngamkroeckjoti, Lalit M. Johri

Bibliographic record

VenueBusiness Process Management Journal · 2000
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCompetitive and Knowledge Intelligence
Canadian institutionsnot available
Fundersnot available
KeywordsScope (computer science)BusinessQuarter (Canadian coin)Order (exchange)Business environmentMarketingBusiness administrationFinanceGeographyComputer science

Abstract

fetched live from OpenAlex

A study of ABB, Shell and CP Group of companies in Thailand found that the scope and management of environmental scanning activities within organizations evolve continuously as a result of volatility of the environment and the diverse nature of businesses. In the case of ABB and Shell the respective regional head office along with global head quarter participate actively in the process of environmental scanning in order to make strategic choices and grant approvals for operating budgets and new investments. The regional head quarter, in the case of ABB and Shell, plays the intervening role as information and capital resource provider whereas the country offices collect specific information at the industry and market levels and use it for implementing specific programs. In the case the of CP Group, the president and several vice presidents at the head office in Thailand play the bulk of the role in environmental scanning. All companies use business performance indicators to review the scope and the management of their environmental scanning practices.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.000
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 head0.013
GPT teacher head0.237
Teacher spread0.224 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations29
Published2000
Admission routes1
Has abstractyes

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