Mario José Valencia Salas

Dr. Mario José Valencia Salas


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
18 September 2026 in Preprints.org
Verified
Preprint
Open access
PDF file
FNFernando David Siles Nates
Fernando David Siles Nates
ACAugusto Cáceres-Núñez
Augusto Cáceres-Núñez
MSMario José Valencia Salas
Mario José Valencia Salas
MNMario Oswaldo Siles Neyra
Mario Oswaldo Siles Neyra
This comprehensive research article presents the empirical validation of a strategic maintenance engineering model through the systematic testing of 100 hypotheses (H1-H100) examining the complex interrelationships between external environmental factors, internal operational conditions, mediating results, and final organizational outcomes in physical asset maintenance management. The study employs a mixed-methods approach combining quantitative survey data from 124 organizations with qualitative inter-views, utilizing structural equation modeling and T-Student tests for hypothesis validation. The research investigates twelve dis-tinct relationship domains: (1) indirect external conditions and internal controls, (2) direct external conditions and internal controls, (3) internal mechanisms and controls, (4) indirect external conditions and mediating results, (5) direct external conditions and me-diating results, (6) internal conditions and mediating results, (7) mediating results between environment and internal, (8) mediating results and political management outcomes, (9) mediating results and operational outcomes, (10) political management and opera-tional outcomes, (11) final results, and (12) final results with control variables. The findings reveal that 78% of hypotheses were confirmed, demonstrating significant relationships between strategic maintenance management and organizational performance indicators including cost management, quality strategies, availability optimization, and overall productivity. The study proposes a five-stage strategic maintenance model: diagnostic analysis, strategic conditioning, implementation, evaluation, and strategic feedback. This research contributes to the theoretical development of maintenance engineering by integrating resource depen-dency theory, strategic management theory, and chaos theory into a unified framework for physical asset management. The im-plications extend to Industry 4.0 contexts, where IoT-based predictive maintenance and digital twin technologies are transforming traditional maintenance paradigms.