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Record W4285137993 · doi:10.5267/j.jpm.2022.5.001

Critical success factors for international development projects in Afghanistan: An exploratory factor analysis

2022· article· en· W4285137993 on OpenAlexvenueno aff
Nasir Ahmad Shafiei, K. Puttanna

Bibliographic record

VenueJournal of Project Management · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain Resilience and Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsCritical success factorExploratory factor analysisRanking (information retrieval)Exploratory researchKnowledge managementPopulationProcess managementPsychologyOperations managementBusinessEngineeringMarketingComputer scienceMedicineEnvironmental healthSociology

Abstract

fetched live from OpenAlex

This study aims to identify and evaluate the critical success factors (CSFs) for international development projects (IDPs) from the perspective of key IDP stakeholders in Afghanistan. The study adopts a quantitative cross-sectional survey research design. Thirty-one success factors were identified and shortlisted through literature reviews and validated by experts and IDP management practitioners. The study's target population is the IPD senior management, IDP team members, and the general public. Amongst 500 questionnaires distributed, a total of 217 were returned and considered for analysis. The result of Exploratory Factor Analysis (EFA) revealed five key CSFs, namely: project cycle management, effective recruitment, continuous learning and adapting, project management method, and clear project goals and objectives. Besides, one-way ANOVA results revealed no statistically significant differences in the ranking of CSFs by the three groups of respondents. However, the post hoc test result indicated that the CSF 'continuous learning and adapting' was relatively rated lower by the general public. The findings of the study would assist the international community, their implementing partners, and IDP management practitioners in better management and successful implementation of IDPs in developing countries. It will also contribute to the CSFs theories and IDPM body of knowledge. The research is the first of its kind to examine the CSFs for IDPs in Afghanistan.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score0.915

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.045
GPT teacher head0.314
Teacher spread0.269 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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