The determinants affecting the implementation of target costing in startup firms
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.
Bibliographic record
Abstract
The research investigated the dynamics affecting the implementation of target costing in startups in Thailand. Startups face turbulent and competitive environments, lack of market demand and regulatory hurdles, which require effective cost management strategies. The study used quantitative methodology to evaluate the effect of various factors - perceived environmental uncertainty, competitor influence, product diversity, firm revenue, and business strategy for the adoption of target costing. Primary data from a sample of 314 respondents were used. The constructs validity and reliability were analyzed using Confirmatory Factor Analysis while Multiple regression analysis was used to evaluate the study hypotheses. The findings indicated that adoption of target costing was positively and significantly influenced by perceived environmental uncertainty, competitor influence, firm revenue, and business strategy, while product diversity has an insignificant influence. The study recommended that startup managers should consider using complex cost management techniques, as a means of acquiring competitive market advantage, strategic alignment of cost management and using competitors as a benchmark to evaluate their market competitiveness.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it