Organizational Determinants and Project Performance: Mediating Roles of AI and Environmental Responsiveness in Malaysia’s Oil & Gas

George anak Budit; Mohd Zainal Munshid Harun; Rahmat Aidil Djubair

doi:10.56427/jcbd.v4i3.788

Penulis

George anak Budit University of Technology Sarawak
Mohd Zainal Munshid Harun University of Technology Sarawak
Rahmat Aidil Djubair University of Technology Sarawak

DOI:

https://doi.org/10.56427/jcbd.v4i3.788

Kata Kunci:

Project Performance, Artificial Intelligence Adoption, Environmental Responsiveness, Organizational Factors, Oil and Gas Industry

Abstrak

Project performance remains a persistent challenge in Malaysia’s oil and gas industry, where cost overruns, schedule delays, and operational inefficiencies continue to occur despite extensive prior research. Although earlier studies have examined organizational, technological, and environmental determinants, limited attention has been given to how these dimensions interact to influence project outcomes. This conceptual paper addresses this gap by proposing a dual-mediation framework in which Artificial Intelligence (AI) adoption and environmental responsiveness function as mechanisms through which organizational factors enhance project performance. Drawing on the Technology–Organization–Environment (TOE) framework, the Resource-Based View (RBV), and Diffusion of Innovations (DOI) theory, the study reconceptualizes five organizational factors—top management support, organizational culture, communication, change management, and training—as strategic resources that facilitate digital transformation. AI adoption is theorized as an internal capability that translates managerial commitment and cultural readiness into improved efficiency, accuracy, and project timeliness. In parallel, environmental responsiveness reflects the organization’s adaptive capacity to meet regulatory requirements, sustainability expectations, and evolving stakeholder pressures. The integration of these mediating mechanisms produces a comprehensive model that explains how internal competencies and external pressures jointly shape performance in a high-risk, capital-intensive sector. The paper contributes theoretically by extending the TOE framework through a dual-mediation perspective and offers practical implications for managers seeking to leverage AI and adaptive capabilities to achieve sustainable improvements in project performance.

Unduhan

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