Factors affecting the intention to adopt artificial intelligence in the construction supply chain management in West Bank: using technology-organization-environment framework

业务 结构方程建模 弹性(材料科学) 西岸 供应链 供应链管理 风险管理 施工管理 巴勒斯坦 营销 建筑业 项目管理 知识管理 心理弹性 计划行为理论 过程管理 数据收集 风险感知 培训(气象学) 概念模型 信息技术 政治 公共部门 制造业 产业组织 概念框架 竞争优势
作者
Walaa Shams,Suhail Sultan,Luay Jum’a
出处
期刊:The International Journal of Logistics Management [Emerald Publishing Limited]
卷期号:36 (6): 1956-1983
标识
DOI:10.1108/ijlm-01-2025-0054
摘要

Purpose The construction sector is one of the most vital industries in Palestine, contributing significantly to employment and economic growth. However, it remains highly fragmented, under-digitized and vulnerable to political and economic instability. These challenges have hindered the adoption of innovative technologies, such as artificial intelligence (AI), which, globally, has demonstrated potential to improve productivity, coordination and project performance. This study aims to investigate the factors influencing the intention of construction organizations in the West Bank to adopt AI, applying the technology-organization-environment (TOE) framework and introducing perceived risk as a moderating variable. Design/methodology/approach A quantitative, deductive approach was employed, with data collected through online questionnaires distributed among engineers, managers and project stakeholders in the West Bank construction sector. Partial least squares structural equation modeling (PLS-SEM) was applied to analyze 230 valid responses. Findings The results indicate that four constructs, namely top management support, relative advantage, competitive pressure and technology resources, significantly influence the intention to adopt AI in the construction sector in the West Bank region. Additionally, perceived risk was found to moderate the relationship between the regulatory environment and adoption intention of AI in the construction sector. Research limitations/implications The study focuses only on the West Bank, given the ongoing conflict in Gaza, and uses non-probability sampling, which may limit generalizability. Nonetheless, it provides crucial insights for policymakers and industry stakeholders in Palestine to design strategies, policies and capacity-building programs that encourage AI adoption, enhance sectoral resilience and support post-conflict reconstruction. Originality/value This study is needed because the Palestinian construction sector, though economically vital, faces persistent delays, poor performance and low technology adoption. Unlike prior research in developed economies, no studies have systematically examined AI adoption in this context. By focusing on the West Bank and introducing perceived risk as a moderator in the TOE framework, the study fills this gap and offers both theoretical insights and practical guidance for stakeholders in developing and conflict-affected settings.
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