评估在尼日利亚建筑部门实施自动化技术的驱动因素

IF 1.9 Q3 ENGINEERING, CIVIL
Ayodeji Emmanuel Oke, John Aliu, Patricia Fadamiro, Feyisetan Leo-Olagbaye, Paramjit Singh Jamir Singh, Mohamad Shaharudin Samsurijan
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引用次数: 0

摘要

全球建筑行业的研究已经显著地探索了自动化技术的影响,揭示了它们的变革潜力。然而,在具体的地方背景下,特别是在尼日利亚这样的发展中国家,关于它们的应用的研究很少。尼日利亚呈现出独特的背景,其挑战包括熟练劳动力短缺、安全问题和成本效率。因此,调查自动化技术在尼日利亚建筑行业的实施对于应对这些挑战,带来变革性的进步,并为自动化采用的更平衡的全球话语做出贡献至关重要。本研究旨在填补这一重大研究空白。设计/方法/方法采用了一种混合的研究方法,将定性和定量数据收集和分析相结合。由23位来自业界和学术机构的专家(定性)进行的两次焦点小组讨论产生了17个驱动因素,用于编制结构良好的问卷(定量),并分发给建筑专业人员。收集到的数据通过各种统计技术进行分析,包括百分比、频率、平均项目得分和探索性因素分析。主成分分析(PCA)得出四个驱动因素集群,即:(1)与绩效相关的驱动因素,(2)与可视化和效率相关的驱动因素,(3)与技术和人为相关的驱动因素,(4)与经济相关的驱动因素。该研究提供了经验见解,可以帮助利益相关者,决策者,政策制定者和政府制定战略,以促进尼日利亚建筑行业及其他行业的自动化技术。本研究的独创性在于探索了尼日利亚建筑行业自动化技术尚未开发的潜力,为这些技术如何解决熟练劳动力短缺、安全问题和成本效率等具体挑战提供了新颖的视角,从而为该行业的变革进步铺平了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating the drivers for the implementation of automation techniques in the Nigerian construction sector
Purpose Global construction sector studies have significantly explored the impact of automation techniques, revealing their transformative potential. However, research on their application within specific local contexts, especially in developing countries like Nigeria, is sparse. Nigeria presents a unique context marked by challenges such as skilled labor shortage, safety concerns and cost efficiency. Therefore, investigating the implementation of automation techniques in the Nigerian construction industry is crucial to address these challenges, bring transformative advancements and contribute to a more balanced global discourse on automation adoption. This study aims to fill this significant research gap. Design/methodology/approach A mixed research method was deployed which combined both qualitative and quantitative data collection and analysis. Two focus group discussions conducted with 23 experts from both industry and academic institutions (qualitative) yielded 17 drivers which were used to formulate a well-structured questionnaire (quantitative), which was disseminated to construction professionals. Collected data underwent analysis through various statistical techniques, including percentages, frequencies, mean item scores and exploratory factor analysis. Findings Principal component analysis (PCA) yielded four driver clusters namely: (1) performance-related drivers, (2) visualization and efficiency-related drivers, (3) technological and human-related drivers and (4) economic-related drivers. Practical implications The study provides empirical insights that can aid stakeholders, decision-makers, policymakers and the government in formulating strategies to promote automation techniques in the Nigerian construction industry and beyond. Originality/value This study's originality lies in its exploration of the untapped potential of automation techniques in the Nigerian construction industry, offering novel perspectives on how these technologies can address specific challenges such as skilled labor shortage, safety concerns and cost efficiency, thereby paving the way for transformative advancements in the sector.
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来源期刊
CiteScore
4.30
自引率
9.10%
发文量
41
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