Digitalization and artificial intelligence (AI) have infiltrated most sectors of the economy, including the energy sector, where they have been extensively investigated. The aim of the study is primarily to assess the awareness of AI in facility management, and to identify the prospects and challenges of the adoption of AI in the energy sector. The study adopted the quantitative methodology approach, using a structured questionnaire to a sample size of 384 respondents. The questionnaire was administered to professionals such as mechanical, civil, electrical, computer, and mechatronics engineers, and project managers within the North-central geopolitical zone of Nigeria. Data gathered was analysed using descriptive analysis (mean value, weighted total, and relative importance index). The study based on findings concludes that there exists high awareness level about the concept of AI in the energy sector. However, regarding the awareness about some selected AI technologies, machine & deep learning, robotics, and speech recognition had high awareness level. The study also concludes that improved energy management, efficiency and transparency, remote reading of energy meters, and improved planning, operation & control of power systems were prevalent prospects of AI adoption. The major challenging factors to the adoption of AI in the Nigerian energy sector are outdated power system infrastructure, cellular technologies, lack of qualified experts and data science skills, and growing threat from cyber-attacks. The study recommends improved awareness and technical know-how of energy sector personnel, and provision of adequate power system infrastructure to provide stable power supply.
In recent times, the preference for expatriates in the contractual process in Nigeria has become an issue of controversy and general public interest. As a result, the high presence of these foreign expatriates has raised competitiveness in the construction sector, which is partly caused by indigenous enterprises' incapacity to meet the demands placed on them in terms of construction project delivery. This paper, therefore, investigates the factors influencing clients’ choice of contractor, examines the performance index of both expatriate and indigenous construction firms (ICFs), and analyzes the key performance indicators (KPI) for ICFs to increase their competitive advantage. The methodology involved the administration of structured questionnaires to a paper population of 384 construction experts comprising engineers, architects, quantity surveyors, builders, and project managers in Nigeria. With a response rate of 69%, frequencies/percentages, mean values, relative importance index (RII), and regression model were employed for the analysis. The findings revealed that the most important factors influencing clients’ choice are past performance and experience, equipment capabilities, and quality specification/standards. Additionally, this paper used six (6) KPIs (human resource management, financial management practices client-based strategy, organizational culture practices, smart work methods, and quality management practices) to model the performances of ICFs to increase their competitive advantage in Nigeria. This paper concluded that there is a higher performance of foreign expatriates in terms of time, cost, scope, quality, and satisfaction over their indigenous counterparts. This paper recommended that there is a need for ICFs to increase their equipment capacity and ability to undertake mega projects, develop an effective funding strategy to execute projects and collaborate with international partners to boost their level of competitiveness.
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