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Article
Publication date: 7 September 2021

Christian Nnaemeka Egwim, Hafiz Alaka, Luqman Olalekan Toriola-Coker, Habeeb Balogun, Saheed Ajayi and Raphael Oseghale

This paper aims to establish the most underlying factors causing construction projects delay from the most applicable.

Abstract

Purpose

This paper aims to establish the most underlying factors causing construction projects delay from the most applicable.

Design/methodology/approach

The paper conducted survey of experts using systematic review of vast body of literature which revealed 23 common factors affecting construction delay. Consequently, this study carried out reliability analysis, ranking using the significance index measurement of delay parameters (SIDP), correlation analysis and factor analysis. From the result of factor analysis, this study grouped a specific underlying factor into three of the six applicable factors that correlated strongly with construction project delay.

Findings

The paper finds all factors from the reliability test to be consistent. It suggests project quality control, project schedule/program of work, contractors’ financial difficulties, political influence, site conditions and price fluctuation to be the six most applicable factors for construction project delay, which are in the top 25% according to the SIDP score and at the same time are strongly associated with construction project delay.

Research limitations/implications

This paper is recommending that prospective research should use a qualitative and inductive approach to investigate whether any new, not previously identified, underlying factors that impact construction projects delay can be discovered as it followed an inductive research approach.

Practical implications

The paper includes implications for the policymakers in the construction industry in Nigeria to focus on measuring the key suppliers’ delivery performance as late delivery of materials by supplier can result in rescheduling of work activities and extra time or waiting time for construction workers as well as for the management team at site. Also, construction stakeholders in Nigeria are encouraged to leverage the amount of data produced from backlog of project schedules, as-built drawings and models, computer-aided designs (CAD), costs, invoices and employee details, among many others through the aid of state-of-the-art data driven technologies such as artificial intelligence or machine learning to make key business decisions that will help drive further profitability. Furthermore, this study suggests that these stakeholders use climatological data that can be obtained from weather observations to minimize impact of bad weather during construction.

Originality/value

This paper establishes the three underlying factors (late delivery of materials by supplier, poor decision-making and Inclement or bad weather) causing construction projects delay from the most applicable.

Details

Journal of Engineering, Design and Technology , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1726-0531

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Article
Publication date: 6 September 2021

Luqman Toriola-Coker, Hakeem Owolabi, Hafiz Alaka, Wasiu Adeniran Bello and Chaminda Pathirage

This study aims to investigate two public private partnership (PPP) road projects in Nigeria for exploring factors that can motivate end-user stakeholders for contributing…

Abstract

Purpose

This study aims to investigate two public private partnership (PPP) road projects in Nigeria for exploring factors that can motivate end-user stakeholders for contributing towards sustaining a PPP project in the long-term.

Design/methodology/approach

Using a case study methodology approach, this study adopts two-way data collection strategies via in-depth interviews with PPP experts and end-user stakeholders in Nigeria host communities and a questionnaire survey to relevant stakeholders.

Findings

The study identifies an eight-factor structure indicating critical success factors for ensuring end-user stakeholders support PPP projects on a long-term basis in their host communities.

Originality/value

Results of the study have huge implications for policymakers and project companies by encouraging the early integration of far-sighted measures that will promote long-term support and sustainability for PPP projects amongst the end-user stakeholders.

Details

Journal of Engineering, Design and Technology , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1726-0531

Keywords

Content available
Article
Publication date: 12 March 2018

Hafiz A. Alaka, Lukumon O. Oyedele, Hakeem A. Owolabi, Muhammad Bilal, Saheed O. Ajayi and Olugbenga O. Akinade

This study explored use of big data analytics (BDA) to analyse data of a large number of construction firms to develop a construction business failure prediction model…

Abstract

This study explored use of big data analytics (BDA) to analyse data of a large number of construction firms to develop a construction business failure prediction model (CB-FPM). Careful analysis of literature revealed financial ratios as the best form of variable for this problem. Because of MapReduce’s unsuitability for iteration problems involved in developing CB-FPMs, various BDA initiatives for iteration problems were identified. A BDA framework for developing CB-FPM was proposed. It was validated by using 150,000 datacells of 30,000 construction firms, artificial neural network, Amazon Elastic Compute Cloud, Apache Spark and the R software. The BDA CB-FPM was developed in eight seconds while the same process without BDA was aborted after nine hours without success. This shows the issue of not wanting to use large dataset to develop CB-FPM due to tedious duration is resolvable by applying BDA technique. The BDA CB-FPM largely outperformed an ordinary CB-FPM developed with a dataset of 200 construction firms, proving that use of larger sample size with the aid of BDA, leads to better performing CB-FPMs. The high financial and social cost associated with misclassifications (i.e. model error) thus makes adoption of BDA CB-FPMs very important for, among others, financiers, clients and policy makers.

Details

Applied Computing and Informatics, vol. 16 no. 1/2
Type: Research Article
ISSN: 2634-1964

Keywords

Content available
Article
Publication date: 13 August 2021

Habeeb Balogun, Hafiz Alaka and Christian Nnaemeka Egwim

This paper seeks to assess the performance levels of BA-GS-LSSVM compared to popular standalone algorithms used to build NO2 prediction models. The purpose of this paper…

Abstract

Purpose

This paper seeks to assess the performance levels of BA-GS-LSSVM compared to popular standalone algorithms used to build NO2 prediction models. The purpose of this paper is to pre-process a relatively large data of NO2 from Internet of Thing (IoT) sensors with time-corresponding weather and traffic data and to use the data to develop NO2 prediction models using BA-GS-LSSVM and popular standalone algorithms to allow for a fair comparison.

Design/methodology/approach

This research installed and used data from 14 IoT emission sensors to develop machine learning predictive models for NO2 pollution concentration. The authors used big data analytics infrastructure to retrieve the large volume of data collected in tens of seconds for over 5 months. Weather data from the UK meteorology department and traffic data from the department for transport were collected and merged for the corresponding time and location where the pollution sensors exist.

Findings

The results show that the hybrid BA-GS-LSSVM outperforms all other standalone machine learning predictive Model for NO2 pollution.

Practical implications

This paper's hybrid model provides a basis for giving an informed decision on the NO2 pollutant avoidance system.

Originality/value

This research installed and used data from 14 IoT emission sensors to develop machine learning predictive models for NO2 pollution concentration.

Details

Applied Computing and Informatics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2634-1964

Keywords

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Article
Publication date: 6 December 2019

Hakeem Owolabi, Lukumon Oyedele, Hafiz Alaka, Saheed Ajayi, Muhammad Bilal and Olugbenga Akinade

Earlier studies on risk evaluation in private finance initiative and public private partnerships (PFI/PPP) projects have focussed more on quantitative approaches despite…

Abstract

Purpose

Earlier studies on risk evaluation in private finance initiative and public private partnerships (PFI/PPP) projects have focussed more on quantitative approaches despite increasing call for contextual understanding of the bankability of risks. The purpose of this paper is to explore the perspectives of UK PFI financiers’ regarding the bankability of four critical risks (construction and completion risk, operations, supply and offtake risk) in PPP projects.

Design/methodology/approach

Multiple case study strategy was adopted to investigate the phenomenon within real-life context of PFI/PPP projects in UK. Using purposive sampling approach, the study examined school and road PFI/PPP projects through interviews, documentations and focus group discussions.

Findings

Results from the study unravelled 36 suitable bankability criteria and some mitigation strategies for evaluating the four critical risks in PFI/PPP during due diligence appraisal. Further evidences from the study also show that, financiers’ bankability criteria, when paired along with corresponding risks and mitigation strategies within with a single framework, provides a quick and effective view of bankability of risks in PFI/PPP funding application.

Research limitations/implications

In order to ensure generalisability of findings, only projects with similar nature were selected from just two sectors of the UK economy (road and education sectors). The context of the study is also based on UK’s PFI/PPP and Construction Industry, as such, other geographical regions in Europe and beyond have not been contextualised in this study. Due to the significance of finance in PFI/PPP contracts, only the perspective of project financiers have been explored in this study.

Practical implications

This study provides a less complicated but useful understanding of how risks in PFI/PPP projects may be packaged in a bankable manner to secure the confidence of project financiers. By presenting a qualitative framework, the study addresses concerns of over quantification of risk analysis in PFI/PPP appraisals and provides a relatable approach useful for non-finance oriented PPP practitioners.

Social implications

This study addresses the social concerns of too much complexity and ambiguity in PFI/PPP structuring especially regarding factors that could make a project acceptable to lenders.

Originality/value

The study proposes a “Bankability and Risk Qualitative Framework”, which presents bankability information on critical risks in clear manner and represents critical parameters for winning financiers’ funding approvals for PFI/PPP projects.

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Article
Publication date: 1 October 2018

Hakeem Adedayo Owolabi, Lukumon Oyedele, Hafiz Alaka, Obas John Ebohon, Saheed Ajayi, Olugbenga Akinade, Muhammad Bilal and Oladimeji Olawale

A major challenge for foreign lenders in financing public private partnerships (PPP) infrastructure projects in an emerging market (EM) is the bankability of…

Abstract

Purpose

A major challenge for foreign lenders in financing public private partnerships (PPP) infrastructure projects in an emerging market (EM) is the bankability of country-related risks. Despite existing studies on country risks in international project financing, perspectives of foreign lenders on bankability of country-specific risks in an EM is yet to be explored. Hence, using a mixed methodology approach, three private finance initiatives/PPP projects in Sub Saharan Africa (Nigeria) were used to investigate political risk, sponsor, concession and legal risks in PPP loan applications. The paper aims to discuss these issues.

Design/methodology/approach

The study adopted mixed methodological approach comprising focus group discussions and analysis of loan documents obtained from foreign project lenders, in addition to the questionnaire survey distributed to local and international project financiers with experiences in PPPs within Nigeria.

Findings

Results identified seven topmost bankability criteria for evaluating country-related risks (political risk, sponsor, concession and legal risks) in EM PPPs. In addition, a “Risk and Bankability Framework Model” was developed from the study presenting critical parameters for gaining foreign funding approval for EM’s PPP loan applications.

Research limitations/implications

Since the study only explored bankability of PPPs in Sub Saharan Africa with the exclusion of other geographical regions, the proposed framework model should be taken in context of EMs as a mind-map for foreign lenders and local private investors seeking to finance PPPs in an EM.

Practical implications

Results from the study represent critical parameters for winning foreign loan approval for PPP infrastructure projects within an EM context.

Originality/value

Study proposed “Risk and Bankability Framework Model” relevant for evaluating PPP loan applications at the pre-approval stage for EM PPPs.

Details

World Journal of Science, Technology and Sustainable Development, vol. 16 no. 3
Type: Research Article
ISSN: 2042-5945

Keywords

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Article
Publication date: 14 June 2019

Hakeem Owolabi, Lukumon Oyedele, Hafiz Alaka, Muhammad Bilal, Saheed Ajayi, Olugbenga Akinade and Alirat Agboola

Although the UK Guarantee Scheme for Infrastructures (UKGSI) was introduced in 2012 to address the huge financing gap for critical infrastructures, PFI sponsors have so…

Abstract

Purpose

Although the UK Guarantee Scheme for Infrastructures (UKGSI) was introduced in 2012 to address the huge financing gap for critical infrastructures, PFI sponsors have so far guaranteed only few projects. Many stakeholders in the project finance industry have blamed this situation on lack of general understanding of strategies for harnessing the benefits of the government guarantee scheme. The purpose of this paper is to investigate the perspectives of UK’s PFI/PPP stakeholders on critical factors influencing approval for government guarantees using the UKGSI as a focal point.

Design/methodology/approach

Using a mixed methodology approach, this study identified 26 important criteria used in evaluating government guarantee applications through focus group discussions with PFI stakeholders. The identified criteria were then put in questionnaire survey to 195 respondents within the UK PFI/PPP industry.

Findings

Through factor analysis, five critical factors determining successful government guarantee application were unravelled. These include: compliance with UK National Infrastructure Plan; demonstration of project bankability and risk management; value for money; proof of projects’ dependence on government guarantee; and certainty of planning commission’s approval.

Originality/value

Results of this study will facilitate an in-depth understanding of critical factors necessary for accessing government guarantee scheme for PFI/PPPs, while also improving the bankability of potential PFI projects.

Details

World Journal of Entrepreneurship, Management and Sustainable Development, vol. 15 no. 3
Type: Research Article
ISSN: 2042-5961

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Article
Publication date: 8 July 2021

Saheed O. Ajayi, Farouq Oyebiyi and Hafiz A. Alaka

To foster effective implementation of building information modelling (BIM), it is guided by standards and protocols that require files naming in a format, containing a…

Abstract

Purpose

To foster effective implementation of building information modelling (BIM), it is guided by standards and protocols that require files naming in a format, containing a string of letters and digits in a tightly defined manner, which is perceived to be time-consuming, error-prone and serves as a barrier to BIM adoption. This paper aims to present a BIM-based plug-in solution (Auto-BIMName) that facilitates automated naming in compliance with BIM standards.

Design/methodology/approach

The Auto-BIMName portal has an information management system (IMS) for generating a master information delivery plan (MIDP), which serves as pre-requisites to effective file naming. Once the naming schema is implemented through text input controls for a project name, volume, level and number, the Revit plugin communicates with its IMS to fetch the name string or concatenate the string in line with the ISO 19650 convention, where the IMS is unused. The system was validated through a simulated collaborative project.

Findings

System testing and evaluation confirmed that the Auto-BIMName will ease the process of file naming, thereby facilitating collaboration efficiency, naming consistency across project teams and lifecycle stages, ease of file naming, time-saving and inducement for BIM implementation, etc. By linking information from MIDP in the BIM execution plan, the platform enhanced information management processes and improved coordination across project teams and lifecycle stages.

Originality/value

Apart from demonstrating how the automated naming platform enhances project performance, information management and coordination, the paper provides a practical demonstration of how the construction industry will benefit from enhanced digitalisation and process automation.

Details

Journal of Engineering, Design and Technology , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1726-0531

Keywords

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Article
Publication date: 18 July 2016

Saheed O Ajayi, Lukumon O. Oyedele, Kabir O Kadiri, Olugbenga O Akinade, Muhammad Bilal, Hakeem A Owolabi and Hafiz A Alaka

Competency-based measure is increasingly evident as an effective approach to tailoring training and development for organisational change and development. With design…

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Abstract

Purpose

Competency-based measure is increasingly evident as an effective approach to tailoring training and development for organisational change and development. With design stage widely reckoned as being decisive for construction waste minimisation, the purpose of this paper is to identify designers’ competencies for designing out waste.

Design/methodology/approach

Due to paucity of research into competency for construction waste mitigation, this study corroborates verbal protocol analyses (VPA) with phenomenological research.

Findings

Combining findings from the two methodological approaches, competencies for designing out waste are grouped into five categories, three of which are largely task related and two being contextual competencies. The study suggests that design task proficiency, low waste design skills and construction-related knowledge are indispensable task competencies, while behavioural competence and inter-professional collaborative abilities are requisite contextual competencies for designing out waste. In concurrence with task-contextual theory of job performance, personality variables and cognitive abilities are found to influence one another. This suggests that both task and contextual competencies are not only important, they are less mutually exclusive with respect to designing out waste.

Practical implications

This study implies that apart from commitment and dedication of designers to waste minimisation, design and firm practices are expected to be adapted to the industry’s standard.

Originality/value

Basis for training needs of design professionals as well as redeployment criterion are further elaborated in the paper. By enhancing competencies identified in this study, construction waste would not only be significantly designed out, adequate cost saving could be made as a result of waste reduction.

Details

Engineering, Construction and Architectural Management, vol. 23 no. 4
Type: Research Article
ISSN: 0969-9988

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Article
Publication date: 16 May 2019

Mohamed Marzouk and Mohamed Enaba

The purpose of this paper is to expand the benefits of building information modeling (BIM) to include data analytics to analyze construction project performance. BIM is a…

Abstract

Purpose

The purpose of this paper is to expand the benefits of building information modeling (BIM) to include data analytics to analyze construction project performance. BIM is a great tool which improves communication and information flow between construction project parties. This research aims to integrate different types of data within the BIM environment, then, to perform descriptive data analytics. Data analytics helps in identifying hidden patterns and detecting relationships between different attributes in the database.

Design/methodology/approach

This research is considered to be an inductive research that starts with an observation of integrating BIM and descriptive data analytics. Thus, the project’s correspondence, daily progress reports and inspection requests are integrated within the project 5D BIM model. Subsequently, data mining comprising association analysis, clustering and trend analysis is performed. The research hypothesis is that descriptive data analytics and BIM have a great leverage to analyze construction project performance. Finally, a case study for a construction project is carried out to test the research hypothesis.

Findings

The research finds that integrating BIM and descriptive data analytics helps in improving project communication performance, in terms of integrating project data in a structured format, efficiently retrieving useful information from project raw data and visualizing analytics results within the BIM environment.

Originality/value

The research develops a dynamic model that helps in detecting hidden patterns and different progress attributes from construction project raw data.

Details

Built Environment Project and Asset Management, vol. 9 no. 4
Type: Research Article
ISSN: 2044-124X

Keywords

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