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Record W1993528649 · doi:10.5539/ass.v9n11p290

Barriers to Start-Up the Business among Students at Tertiary Level: A Case Study in Northern States of Peninsular Malaysia

2013· article· en· W1993528649 on OpenAlexvenueno aff
Azyyati Anuarq, Ida Normaya Mohd Nasir, Firdaus Abdul Rahman, Daing Maruak Sadek

Bibliographic record

VenueAsian Social Science · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsnot available
FundersUniversiti Teknologi MARA
KeywordsEntrepreneurshipGovernment (linguistics)PopulationClass (philosophy)Order (exchange)Tertiary levelStart upEconomic growthBusinessMarketingPublic relationsPolitical sciencePsychologySociologyMathematics educationEconomicsBusiness administrationComputer scienceFinance

Abstract

fetched live from OpenAlex

At university level, students are encouraged and expectant to create an entrepreneurial culture where they need to experience on how to operate the business inside the campus. This was also to aid the university in producing graduates who can help meet the government’s aspiration of turning Malaysia into a high-income country. Therefore, students are played a significant role as a novice entrepreneur in order to accomplish Vision of 2020. Generally, we have seen some of the research highlights the importance of entrepreneurship education, the effectiveness of entrepreneurship training and also seen the entrepreneurship has been taught in the class but unlikely, they do not fully utilized the given knowledge to practice it. The objectives of this paper is to identify the barriers faced by students for various departments to start-up the business at the IPTA’s in northern region that concise of three variables; personality traits, entrepreneurial skills and micro level. The target population of this study is all students in higher institutions in northern region including UiTM Kedah, UiTM Pulau Pinang, UiTM Perlis, UiTM Perak, USM, UNIMAP and UUM. The expected outcome is to expose a student on how to start-up the business and experiencing the challenges of entrepreneurial environment.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.261
Teacher spread0.245 · 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 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

Citations12
Published2013
Admission routes1
Has abstractyes

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