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Record W4410871355 · doi:10.5267/j.jpm.2025.5.003

The impact of technological innovation on project management performance: The mediating roles of sustainability culture and top management support

2025· article· en· W4410871355 on OpenAlexvenueno aff
Abdulaziz Alhammadi

Bibliographic record

VenueJournal of Project Management · 2025
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityInnovation managementBusinessKnowledge managementOrganizational cultureProcess managementManagementMarketingComputer scienceEcologyEconomics

Abstract

fetched live from OpenAlex

This study investigates the influence of technological innovation, sustainability culture, and top management support on project management performance in Saudi Arabia's manufacturing sector. Employing a cross-sectional quantitative research design, data was collected from 293 employees using a convenience sampling technique. Structural Equation Modeling (SEM) with SmartPLS software was utilized for data analysis to examine the proposed relationships between the constructs. The findings indicate that technological innovation has a significant positive effect on both sustainability culture and top management support. Furthermore, both sustainability culture and top management support were found to positively influence project management performance. The results underscore the critical role of technological advancements in fostering a culture of sustainability and obtaining strong leadership support, which in turn contributes to enhanced project outcomes. This study offers important insights for the manufacturing sector in Saudi Arabia, particularly as it aligns with the country’s Vision 2030 objectives, aiming to diversify its economy through innovation, sustainability, and enhanced project performance.

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)0.007
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 score0.708
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.044
GPT teacher head0.415
Teacher spread0.371 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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