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Record W2795055140 · doi:10.3968/10138

Measuring Capital Structure Determinants of Small and Medium Enterprises (SMEs): An Assessment of Construct Reliability and Validity of a Proposed Questionnaire

2018· article· en· W2795055140 on OpenAlexvenueno aff
Hafizah Mat Nawi

Bibliographic record

VenueCanadian social science · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCronbach's alphaReliability (semiconductor)Construct validityConstruct (python library)PsychologyScale (ratio)Dimension (graph theory)Exploratory factor analysisReplication (statistics)Social capitalKnowledge managementCapital (architecture)Applied psychologyBusinessSocial psychologyComputer scienceSociologyStatisticsPsychometricsMathematicsClinical psychologyGeography

Abstract

fetched live from OpenAlex

This paper presents the assessment of reliability and validity of a proposed questionnaire of the capital structure determinants. The questionnaire is developed based on the existing measurement scales from the literature, interviews and focus groups discussions with the SMEs’ owners from the East-Coast region of Malaysia. The study analysed a total of 384 questionnaires. This study analyses data using SPSS 24.0. A purification process involves scale reliability and Exploratory Factor Analysis. A total of 11 constructs and 40 out of the initial 52 items represent the theoretical model. Items assigned to each dimension consistently exhibited high loadings on their constructs. In addition, results showed a relatively high internal consistency, with a Cronbach alpha greater than 0.7 for all constructs, except for three of the constructs (i.e. commercial goals, social welfare goals, and external environment). This study contributes to theory extension and testing, verification of the conceptualisation and operationalisation of constructs, and replication of the previous studies. The findings help in introducing a research framework to be as a standard measurement for SMEs’ capital structure determinants.

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)0.000
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 score0.048
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.020
GPT teacher head0.262
Teacher spread0.243 · 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

Citations5
Published2018
Admission routes1
Has abstractyes

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