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Record W4379260383 · doi:10.5267/j.dsl.2023.4.002

Determinants of woodcraft family business success

2023· article· en· W4379260383 on OpenAlexvenueno aff
Putu Yudy Wijaya, Ni Nyoman Reni Suasih

Bibliographic record

VenueDecision Science Letters · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsnot available
Fundersnot available
KeywordsFamily businessSuccessor cardinalTourismCraftMarketingBusinessBusiness modelBusiness analysisNew business developmentElectronic businessIndustrial organizationPolitical science

Abstract

fetched live from OpenAlex

The woodcraft industry has been developing in Bali for more than half a century in the form of family business (SMEs) which is currently managed by the third generation or the transition from the second to the third generation, where this phase is the climax of the family business. Apart from contributing to tourism, this craft business also has cultural values. Moreover, the tourism situation and macroeconomic shocks have had an impact on business conditions. This research aims to analyze the performance of a woodcraft family business based on a family and financial approach, through a two by two matrix analysis as well as to analyze the determining factors of willingness to succession of woodcraft family business in Bali, with MICMAC analysis. The results show that the performance of the family business in this case is high emotional but low financial capital. There are 18 identified factors related to the willingness to succeed in the woodcraft family business, and the most influential factor (existing and forecasting) is the participative leadership style, while the most dependent is personal interest which is the involvement of the successor from an early age in family business activities.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.242
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.010
Science and technology studies0.0000.001
Scholarly communication0.0000.005
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.029
GPT teacher head0.285
Teacher spread0.257 · 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.

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

Citations1
Published2023
Admission routes1
Has abstractyes

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