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Record W3185882883 · doi:10.33476/j.e.b.a.v6i1.1923

Analisis Pengaruh Dinamisme Lingkungan dan Faktor Manajerial Terhadap Perencanaan Strategis dalam Upaya Meningkatkan Kinerja Organisasi Non-Profit dengan Pendekatan Balanced Scorecard

2021· article· en· W3185882883 on OpenAlex
Siti Khusnul Rifani, Tengku Ezni Balqiah

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJEBA (Journal of Economics and Business Aseanomics) · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior and Marketing Influence
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsDynamismBalanced scorecardBusinessProcess managementStrategic planningBusiness administrationProfit (economics)Business environmentStrategy mapKnowledge managementMarketingComputer scienceEconomics

Abstract

fetched live from OpenAlex

External environment changes and managerial factors are important to be considered in the preparation of strategic planning. Strategic planning is very important for the organization, not only for profit organizations but also for nonprofit organizations because a formal strategic planning can guide them to assess how far their goals have been achieved and how to achieve them. This study discusses how the dynamism of the external environment and managerial factors influence strategic planning and its implications for WWF Indonesia's performance using the Balanced Scorecard approach. The research method used is to use a survey of employees at WWF Indonesia and processed with SmartPLS 3.0. The results show that external business environment dynamism and managerial factors can influence strategic planning which ultimately affects the improvement of WWF Indonesia's performance.

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), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.000
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 head0.017
GPT teacher head0.216
Teacher spread0.198 · 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