Pub Date : 2023-11-14DOI: 10.1108/jedt-06-2023-0268
Benson Rugalema Mwemezi, Geraldine John Kikwasi, Sarah Phoya
Purpose Although there are several established frameworks for health and safety in construction, there are inadequate health and safety conditions at informal construction sites, and no framework has been designed to address this problem. The purpose of this paper is to develop a validated framework for health and safety risk management (HSRM) in informal construction sites with the aim of supporting Sustainable Development Goals 3, 8 and 11 of the 2030 Agenda, which are to ensure everyone enjoys a healthy life and to create inclusive, secure, robust and sustainable cities and human settlements, respectively. Design/methodology/approach The study is based on HSRM questionnaire survey and interviews with construction workers working on informal construction sites in Tanzania. A total of 13 health and safety specialists in construction were specifically chosen to validate the proposed framework for HSRM in informal construction to determine its applicability, efficacy and adaptation. Findings The validation results demonstrated that all of the suggested metrics within the framework for HSRM in informal construction scored higher than the test value, proving the framework’s feasibility Originality/value This research adds to the body of knowledge on the issue in a never-before-seen setting. To the best of the authors’ knowledge, this study is the first empirical study in Tanzania to develop and validate a framework for HSRM in informal construction.
{"title":"Development and validation of a framework for improving health and safety risk management at informal construction sites in Tanzania","authors":"Benson Rugalema Mwemezi, Geraldine John Kikwasi, Sarah Phoya","doi":"10.1108/jedt-06-2023-0268","DOIUrl":"https://doi.org/10.1108/jedt-06-2023-0268","url":null,"abstract":"Purpose Although there are several established frameworks for health and safety in construction, there are inadequate health and safety conditions at informal construction sites, and no framework has been designed to address this problem. The purpose of this paper is to develop a validated framework for health and safety risk management (HSRM) in informal construction sites with the aim of supporting Sustainable Development Goals 3, 8 and 11 of the 2030 Agenda, which are to ensure everyone enjoys a healthy life and to create inclusive, secure, robust and sustainable cities and human settlements, respectively. Design/methodology/approach The study is based on HSRM questionnaire survey and interviews with construction workers working on informal construction sites in Tanzania. A total of 13 health and safety specialists in construction were specifically chosen to validate the proposed framework for HSRM in informal construction to determine its applicability, efficacy and adaptation. Findings The validation results demonstrated that all of the suggested metrics within the framework for HSRM in informal construction scored higher than the test value, proving the framework’s feasibility Originality/value This research adds to the body of knowledge on the issue in a never-before-seen setting. To the best of the authors’ knowledge, this study is the first empirical study in Tanzania to develop and validate a framework for HSRM in informal construction.","PeriodicalId":46533,"journal":{"name":"Journal of Engineering Design and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134953969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-10DOI: 10.1108/jedt-07-2023-0304
Bamidele Temitope Arijeloye
Purpose This paper aims to help understand how adopting risk allocation criteria impacts the delivery of public–private partnership (PPP) mass housing in Nigeria with the view of promoting the adoption of PPP housing scheme in Nigeria. Design/methodology/approach The research design adopts the census sampling approach by using well-structured questionnaires distributed to stakeholders involved in PPP-procured mass housing projects, i.e. consultants, in-house professionals, contractors and the organized private sector, registered with PPP departments in the Federal Capital Territory Development Authority, Abuja, Nigeria. Sixty-three risk factors, nine risk allocation criteria and nine project delivery indices were submitted for the respondents to rank on a Likert scale of 7. Two hypotheses were formulated to test whether the risk allocation criteria impacted PPP mass housing delivery or otherwise. The study adopts partial least square-structural equation modeling to model the effect of risk on risk allocation criteria on project delivery indices and risk severity. Findings The finding shows that project risk allocation criteria have less effect on project delivery indices than on risk severity. The study concludes that risk allocation principles do not directly affect the delivery of PPP-procured mass housing projects. This is evident by the path coefficient of 0.724 values, which is not statistically significant at a 5% alpha protection value. The study concludes that allocating critical risk factors influences the performance of PPP-procured mass housing projects, as the path coefficient of 0.360 is also not significantly far from 0 and at a 5% alpha protection value. Originality/value The study is one of the recent studies conducted in PPP-procured mass housing projects in Nigeria owing to the novelty of procurement option in the sector. It highlights the risk factors that can jeopardize the PPP-procured mass housing project objectives. The study is of immense value to PPP actors in the sector by providing the necessary information required to formulate risk response methods to minimize the impact of the risk factors in PPP mass housing projects.
{"title":"Impact of project risk allocation on PPP housing project delivery in Nigeria: partial least square structural equation modeling approach","authors":"Bamidele Temitope Arijeloye","doi":"10.1108/jedt-07-2023-0304","DOIUrl":"https://doi.org/10.1108/jedt-07-2023-0304","url":null,"abstract":"Purpose This paper aims to help understand how adopting risk allocation criteria impacts the delivery of public–private partnership (PPP) mass housing in Nigeria with the view of promoting the adoption of PPP housing scheme in Nigeria. Design/methodology/approach The research design adopts the census sampling approach by using well-structured questionnaires distributed to stakeholders involved in PPP-procured mass housing projects, i.e. consultants, in-house professionals, contractors and the organized private sector, registered with PPP departments in the Federal Capital Territory Development Authority, Abuja, Nigeria. Sixty-three risk factors, nine risk allocation criteria and nine project delivery indices were submitted for the respondents to rank on a Likert scale of 7. Two hypotheses were formulated to test whether the risk allocation criteria impacted PPP mass housing delivery or otherwise. The study adopts partial least square-structural equation modeling to model the effect of risk on risk allocation criteria on project delivery indices and risk severity. Findings The finding shows that project risk allocation criteria have less effect on project delivery indices than on risk severity. The study concludes that risk allocation principles do not directly affect the delivery of PPP-procured mass housing projects. This is evident by the path coefficient of 0.724 values, which is not statistically significant at a 5% alpha protection value. The study concludes that allocating critical risk factors influences the performance of PPP-procured mass housing projects, as the path coefficient of 0.360 is also not significantly far from 0 and at a 5% alpha protection value. Originality/value The study is one of the recent studies conducted in PPP-procured mass housing projects in Nigeria owing to the novelty of procurement option in the sector. It highlights the risk factors that can jeopardize the PPP-procured mass housing project objectives. The study is of immense value to PPP actors in the sector by providing the necessary information required to formulate risk response methods to minimize the impact of the risk factors in PPP mass housing projects.","PeriodicalId":46533,"journal":{"name":"Journal of Engineering Design and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135091703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-07DOI: 10.1108/jedt-07-2022-0379
Christian Nnaemeka Egwim, Hafiz Alaka, Youlu Pan, Habeeb Balogun, Saheed Ajayi, Abdul Hye, Oluwapelumi Oluwaseun Egunjobi
Purpose The study aims to develop a multilayer high-effective ensemble of ensembles predictive model (stacking ensemble) using several hyperparameter optimized ensemble machine learning (ML) methods (bagging and boosting ensembles) trained with high-volume data points retrieved from Internet of Things (IoT) emission sensors, time-corresponding meteorology and traffic data. Design/methodology/approach For a start, the study experimented big data hypothesis theory by developing sample ensemble predictive models on different data sample sizes and compared their results. Second, it developed a standalone model and several bagging and boosting ensemble models and compared their results. Finally, it used the best performing bagging and boosting predictive models as input estimators to develop a novel multilayer high-effective stacking ensemble predictive model. Findings Results proved data size to be one of the main determinants to ensemble ML predictive power. Second, it proved that, as compared to using a single algorithm, the cumulative result from ensemble ML algorithms is usually always better in terms of predicted accuracy. Finally, it proved stacking ensemble to be a better model for predicting PM 2.5 concentration level than bagging and boosting ensemble models. Research limitations/implications A limitation of this study is the trade-off between performance of this novel model and the computational time required to train it. Whether this gap can be closed remains an open research question. As a result, future research should attempt to close this gap. Also, future studies can integrate this novel model to a personal air quality messaging system to inform public of pollution levels and improve public access to air quality forecast. Practical implications The outcome of this study will aid the public to proactively identify highly polluted areas thus potentially reducing pollution-associated/ triggered COVID-19 (and other lung diseases) deaths/ complications/ transmission by encouraging avoidance behavior and support informed decision to lock down by government bodies when integrated into an air pollution monitoring system Originality/value This study fills a gap in literature by providing a justification for selecting appropriate ensemble ML algorithms for PM 2.5 concentration level predictive modeling. Second, it contributes to the big data hypothesis theory, which suggests that data size is one of the most important factors of ML predictive capability. Third, it supports the premise that when using ensemble ML algorithms, the cumulative output is usually always better in terms of predicted accuracy than using a single algorithm. Finally developing a novel multilayer high-performant hyperparameter optimized ensemble of ensembles predictive model that can accurately predict PM 2.5 concentration levels with improved model interpretability and enhanced generalizability, as well as the provision of a novel databank of historic pollution data from
{"title":"Ensemble of ensembles for fine particulate matter pollution prediction using big data analytics and IoT emission sensors","authors":"Christian Nnaemeka Egwim, Hafiz Alaka, Youlu Pan, Habeeb Balogun, Saheed Ajayi, Abdul Hye, Oluwapelumi Oluwaseun Egunjobi","doi":"10.1108/jedt-07-2022-0379","DOIUrl":"https://doi.org/10.1108/jedt-07-2022-0379","url":null,"abstract":"Purpose The study aims to develop a multilayer high-effective ensemble of ensembles predictive model (stacking ensemble) using several hyperparameter optimized ensemble machine learning (ML) methods (bagging and boosting ensembles) trained with high-volume data points retrieved from Internet of Things (IoT) emission sensors, time-corresponding meteorology and traffic data. Design/methodology/approach For a start, the study experimented big data hypothesis theory by developing sample ensemble predictive models on different data sample sizes and compared their results. Second, it developed a standalone model and several bagging and boosting ensemble models and compared their results. Finally, it used the best performing bagging and boosting predictive models as input estimators to develop a novel multilayer high-effective stacking ensemble predictive model. Findings Results proved data size to be one of the main determinants to ensemble ML predictive power. Second, it proved that, as compared to using a single algorithm, the cumulative result from ensemble ML algorithms is usually always better in terms of predicted accuracy. Finally, it proved stacking ensemble to be a better model for predicting PM 2.5 concentration level than bagging and boosting ensemble models. Research limitations/implications A limitation of this study is the trade-off between performance of this novel model and the computational time required to train it. Whether this gap can be closed remains an open research question. As a result, future research should attempt to close this gap. Also, future studies can integrate this novel model to a personal air quality messaging system to inform public of pollution levels and improve public access to air quality forecast. Practical implications The outcome of this study will aid the public to proactively identify highly polluted areas thus potentially reducing pollution-associated/ triggered COVID-19 (and other lung diseases) deaths/ complications/ transmission by encouraging avoidance behavior and support informed decision to lock down by government bodies when integrated into an air pollution monitoring system Originality/value This study fills a gap in literature by providing a justification for selecting appropriate ensemble ML algorithms for PM 2.5 concentration level predictive modeling. Second, it contributes to the big data hypothesis theory, which suggests that data size is one of the most important factors of ML predictive capability. Third, it supports the premise that when using ensemble ML algorithms, the cumulative output is usually always better in terms of predicted accuracy than using a single algorithm. Finally developing a novel multilayer high-performant hyperparameter optimized ensemble of ensembles predictive model that can accurately predict PM 2.5 concentration levels with improved model interpretability and enhanced generalizability, as well as the provision of a novel databank of historic pollution data from ","PeriodicalId":46533,"journal":{"name":"Journal of Engineering Design and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135431370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-06DOI: 10.1108/jedt-05-2023-0200
Love Opeyemi David, Nnamdi Ikechi Nwulu, Clinton Ohis Aigbavboa, Omoseni Oyindamola Adepoju
Purpose This paper aims to examine the role of technological Innovation in ensuring resource sustainability in the water, energy and food (WEF) nexus, as there exists a shortage of statistical research on the extent of the influence of technological Innovation on the WEF nexus. Design/methodology/approach The study used a quantitative research method, using a well-structured questionnaire to collect data from management staff in the WEF departments in South Africa. The collected data were analyzed by using mean score ranking, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) for structural equation modelling (SEM). Findings The findings show that the technological process of technological innovation is significant for resource sustainability. The result also showed that technological innovations directly and statistically significantly affect WEF nexus. The EFA resulted in three components of WEF nexus product innovation, WEF nexus process innovation and WEF nexus novel innovations. Furthermore, the CFA and SEM analysis reveals that six technological innovation indicators influence the sustainability of the nexus: smart water metering technology, smart metering technology, food quality monitoring technology, agricultural technology solutions, new technological design and eco-friendly WEF products. Originality/value The sustainability of these three inevitable resources for man’s survival is dependent on technological innovations, and this study has shown the major categories of innovations needed, thus establishing a pathway for engineering design.
{"title":"Resource sustainability in the water, energy and food nexus: role of technological innovation","authors":"Love Opeyemi David, Nnamdi Ikechi Nwulu, Clinton Ohis Aigbavboa, Omoseni Oyindamola Adepoju","doi":"10.1108/jedt-05-2023-0200","DOIUrl":"https://doi.org/10.1108/jedt-05-2023-0200","url":null,"abstract":"Purpose This paper aims to examine the role of technological Innovation in ensuring resource sustainability in the water, energy and food (WEF) nexus, as there exists a shortage of statistical research on the extent of the influence of technological Innovation on the WEF nexus. Design/methodology/approach The study used a quantitative research method, using a well-structured questionnaire to collect data from management staff in the WEF departments in South Africa. The collected data were analyzed by using mean score ranking, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) for structural equation modelling (SEM). Findings The findings show that the technological process of technological innovation is significant for resource sustainability. The result also showed that technological innovations directly and statistically significantly affect WEF nexus. The EFA resulted in three components of WEF nexus product innovation, WEF nexus process innovation and WEF nexus novel innovations. Furthermore, the CFA and SEM analysis reveals that six technological innovation indicators influence the sustainability of the nexus: smart water metering technology, smart metering technology, food quality monitoring technology, agricultural technology solutions, new technological design and eco-friendly WEF products. Originality/value The sustainability of these three inevitable resources for man’s survival is dependent on technological innovations, and this study has shown the major categories of innovations needed, thus establishing a pathway for engineering design.","PeriodicalId":46533,"journal":{"name":"Journal of Engineering Design and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135584217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose One of the most contested and anticipated research issues is the acceptability of using recycled aggregates instead of fresh aggregates. This study aims to look at the possibility of replacing fresh aggregates with 15%, 30%, 60% and 100% recycled aggregates. Design/methodology/approach The research is divided into two stages. The compressive, split tensile, flexural and bond strength of the various mixes were examined in the first phase using untreated recycled concrete aggregates (RCA). The second phase entails chemically treating RCA with a 10% 0.1 M sodium metasilicate solution to evaluate differences in strength, indicating the success of the treatment performed. Microstructural experiments such as scanning electron microscopy and X-ray diffraction were also conducted to evaluate the formation of interfacial transition zone (ITZ) in treated and untreated RCA specimens. Findings The observed findings reveal a decrease in concrete strength with increasing RCA concentration; however, when treated RCA was used, the strengths increased significantly when compared to untreated samples. The findings also include curves indicating the correlation between compressive strength and other mechanical strength parameters for an optimum mix of concrete prepared with 30% RCA replacement. Originality/value The study through its novel approach, demonstrates the effect of pretreatment of RCA in the absence of any standardized chemical treatment methodology and presents significant potential in minimizing reliance on fresh aggregates used in concrete, lowering building costs and promoting the use of waste materials in construction.
{"title":"Mechanical and microstructural characteristics of structural concrete containing RCA treated with sodium metasilicate","authors":"Shubham Bansal, Lokesh Choudhary, Megha Kalra, Niragi Dave, Anil Kumar Sharma","doi":"10.1108/jedt-03-2023-0109","DOIUrl":"https://doi.org/10.1108/jedt-03-2023-0109","url":null,"abstract":"Purpose One of the most contested and anticipated research issues is the acceptability of using recycled aggregates instead of fresh aggregates. This study aims to look at the possibility of replacing fresh aggregates with 15%, 30%, 60% and 100% recycled aggregates. Design/methodology/approach The research is divided into two stages. The compressive, split tensile, flexural and bond strength of the various mixes were examined in the first phase using untreated recycled concrete aggregates (RCA). The second phase entails chemically treating RCA with a 10% 0.1 M sodium metasilicate solution to evaluate differences in strength, indicating the success of the treatment performed. Microstructural experiments such as scanning electron microscopy and X-ray diffraction were also conducted to evaluate the formation of interfacial transition zone (ITZ) in treated and untreated RCA specimens. Findings The observed findings reveal a decrease in concrete strength with increasing RCA concentration; however, when treated RCA was used, the strengths increased significantly when compared to untreated samples. The findings also include curves indicating the correlation between compressive strength and other mechanical strength parameters for an optimum mix of concrete prepared with 30% RCA replacement. Originality/value The study through its novel approach, demonstrates the effect of pretreatment of RCA in the absence of any standardized chemical treatment methodology and presents significant potential in minimizing reliance on fresh aggregates used in concrete, lowering building costs and promoting the use of waste materials in construction.","PeriodicalId":46533,"journal":{"name":"Journal of Engineering Design and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135777409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-02DOI: 10.1108/jedt-08-2023-0340
Hung Duy Nguyen, Tuan Anh Nguyen, Vi Vu Doan, Chau Ngoc Dang
Purpose Public–private partnership (PPP) projects play a pivotal role in fostering infrastructure development in developing countries. This study aims to identify major barriers and critical success factors (CSFs) for PPP projects in Vietnam. Design/methodology/approach The study initially conducted an extensive literature review and interviewed industry experts to compile a comprehensive list of barriers and success factors. Subsequently, a survey involving 250 construction professionals was conducted to assess these identified factors. The research used both ANOVA test and hierarchical regression analysis to explore the relationship between participants’ characteristics and assessments. Findings The results could provide a valuable reference for practitioners by assessing barriers and CSFs in PPP projects. Specifically, the ANOVA analysis indicated a positive correlation between barrier assessment and participants’ experience, while the influence of participants’ sector on the evaluation was minor. Furthermore, the hierarchical regression analysis demonstrated that participants’ sector did not moderate the relationship between barrier assessment and industry experience. Originality/value This research contributes to the existing literature by offering empirical insights into barriers and CSFs specific to PPP projects in a developing country context. The findings highlight the crucial role of experienced professionals in ensuring PPP project success. Moreover, the study provides construction practitioners with a better understanding of the essential factors and supports the development of effective management strategies for future PPP projects.
{"title":"Assessing critical barriers and success factors of PPP projects in emerging economies: a case of Vietnam","authors":"Hung Duy Nguyen, Tuan Anh Nguyen, Vi Vu Doan, Chau Ngoc Dang","doi":"10.1108/jedt-08-2023-0340","DOIUrl":"https://doi.org/10.1108/jedt-08-2023-0340","url":null,"abstract":"Purpose Public–private partnership (PPP) projects play a pivotal role in fostering infrastructure development in developing countries. This study aims to identify major barriers and critical success factors (CSFs) for PPP projects in Vietnam. Design/methodology/approach The study initially conducted an extensive literature review and interviewed industry experts to compile a comprehensive list of barriers and success factors. Subsequently, a survey involving 250 construction professionals was conducted to assess these identified factors. The research used both ANOVA test and hierarchical regression analysis to explore the relationship between participants’ characteristics and assessments. Findings The results could provide a valuable reference for practitioners by assessing barriers and CSFs in PPP projects. Specifically, the ANOVA analysis indicated a positive correlation between barrier assessment and participants’ experience, while the influence of participants’ sector on the evaluation was minor. Furthermore, the hierarchical regression analysis demonstrated that participants’ sector did not moderate the relationship between barrier assessment and industry experience. Originality/value This research contributes to the existing literature by offering empirical insights into barriers and CSFs specific to PPP projects in a developing country context. The findings highlight the crucial role of experienced professionals in ensuring PPP project success. Moreover, the study provides construction practitioners with a better understanding of the essential factors and supports the development of effective management strategies for future PPP projects.","PeriodicalId":46533,"journal":{"name":"Journal of Engineering Design and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135875958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-01DOI: 10.1108/jedt-05-2023-0202
Suhaib Arogundade, Mohammed Dulaimi, Saheed Ajayi, Abdullahi Saka, Olusegun Ilori
Purpose Extant studies have discussed numerous carbon reduction drivers, but there is a dearth of holistic review and understanding of the dynamic interrelationships between the drivers from a system perspective. Thus, this study aims to bridge that gap. Design/methodology/approach The study conducted a review using Preferred Reporting Items for Systematic Reviews and Meta-Analyses and adopted interpretive structural modelling (ISM) to analyse and prioritise the drivers. Findings Eighteen drivers were identified and grouped into five, namely, policy instruments, bid-related, cost and risk, education and training, and reward and penalty drivers. The ISM revealed two hierarchical levels of the drivers with only higher cost of electricity/fuel on the higher level, making it the most important driver that could influence others. Practical implications The study presents an overview of decarbonisation drivers in the literature and would be of benefit to the government and stakeholders towards achieving net zero emissions in the construction industry. Originality/value The findings of the study present drivers of carbon reduction and prioritise and categorise them for tailored interventions within the construction sector. Also, it could serve as foundational knowledge for further study in the construction process decarbonisation research area.
{"title":"Decarbonization of construction projects: a review and interpretive structural modelling of carbon reduction drivers","authors":"Suhaib Arogundade, Mohammed Dulaimi, Saheed Ajayi, Abdullahi Saka, Olusegun Ilori","doi":"10.1108/jedt-05-2023-0202","DOIUrl":"https://doi.org/10.1108/jedt-05-2023-0202","url":null,"abstract":"Purpose Extant studies have discussed numerous carbon reduction drivers, but there is a dearth of holistic review and understanding of the dynamic interrelationships between the drivers from a system perspective. Thus, this study aims to bridge that gap. Design/methodology/approach The study conducted a review using Preferred Reporting Items for Systematic Reviews and Meta-Analyses and adopted interpretive structural modelling (ISM) to analyse and prioritise the drivers. Findings Eighteen drivers were identified and grouped into five, namely, policy instruments, bid-related, cost and risk, education and training, and reward and penalty drivers. The ISM revealed two hierarchical levels of the drivers with only higher cost of electricity/fuel on the higher level, making it the most important driver that could influence others. Practical implications The study presents an overview of decarbonisation drivers in the literature and would be of benefit to the government and stakeholders towards achieving net zero emissions in the construction industry. Originality/value The findings of the study present drivers of carbon reduction and prioritise and categorise them for tailored interventions within the construction sector. Also, it could serve as foundational knowledge for further study in the construction process decarbonisation research area.","PeriodicalId":46533,"journal":{"name":"Journal of Engineering Design and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135217448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-31DOI: 10.1108/jedt-06-2023-0235
Chukwuka Christian Ohueri, San Chuin Liew, Jibril Adewale Bamgbade, Wallace Imoudu Enegbuma
Purpose The efficient application of building information modeling (BIM) methodology in the sustainable building design process, known as green BIM, provides ideal leverage to significantly enhance multidiscipline team collaboration. However, the practical execution of green BIM is characterized by issues such as duplication of work, information silos and poor cross-party coordination. Besides, there are limited studies on the specific components that are critical to driving green BIM collaborative design. This study aims to establish the critical components of green BIM collaborative design to enable the multidiscipline team to effectively use diverse software to collaboratively exchange accurate information, thus ensuring informed decision-making in the sustainable building design process. Design/methodology/approach Data were obtained by using a questionnaire to survey 360 respondents comprising mainly architects and engineers (civil, mechanical and electrical) in Malaysia. Subsequently, data were analyzed via confirmatory factor analysis. Afterward, a measurement model was established and used to test the 11 hypotheses of this study. Findings A covariance-based structural equation model of the critical components for successful BIM-based sustainable building design collaboration was established. Practical implications The research findings will guide the multidisciplinary team to collaboratively exchange accurate information in green BIM practices. Originality/value To the best of the authors’ knowledge, this research is the first attempt in the literature to provide a pragmatic approach for practitioners to combine the established critical components of green BIM to collaboratively exchange heterogeneous sustainability criteria and efficiently design buildings with high sustainability performance, particularly in emerging countries like Malaysia.
{"title":"Critical components for successful BIM-based sustainable building design collaboration: structural equation model analysis","authors":"Chukwuka Christian Ohueri, San Chuin Liew, Jibril Adewale Bamgbade, Wallace Imoudu Enegbuma","doi":"10.1108/jedt-06-2023-0235","DOIUrl":"https://doi.org/10.1108/jedt-06-2023-0235","url":null,"abstract":"Purpose The efficient application of building information modeling (BIM) methodology in the sustainable building design process, known as green BIM, provides ideal leverage to significantly enhance multidiscipline team collaboration. However, the practical execution of green BIM is characterized by issues such as duplication of work, information silos and poor cross-party coordination. Besides, there are limited studies on the specific components that are critical to driving green BIM collaborative design. This study aims to establish the critical components of green BIM collaborative design to enable the multidiscipline team to effectively use diverse software to collaboratively exchange accurate information, thus ensuring informed decision-making in the sustainable building design process. Design/methodology/approach Data were obtained by using a questionnaire to survey 360 respondents comprising mainly architects and engineers (civil, mechanical and electrical) in Malaysia. Subsequently, data were analyzed via confirmatory factor analysis. Afterward, a measurement model was established and used to test the 11 hypotheses of this study. Findings A covariance-based structural equation model of the critical components for successful BIM-based sustainable building design collaboration was established. Practical implications The research findings will guide the multidisciplinary team to collaboratively exchange accurate information in green BIM practices. Originality/value To the best of the authors’ knowledge, this research is the first attempt in the literature to provide a pragmatic approach for practitioners to combine the established critical components of green BIM to collaboratively exchange heterogeneous sustainability criteria and efficiently design buildings with high sustainability performance, particularly in emerging countries like Malaysia.","PeriodicalId":46533,"journal":{"name":"Journal of Engineering Design and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135808752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-30DOI: 10.1108/jedt-04-2023-0164
Oluseyi Julius Adebowale, Justus Ngala Agumba
Purpose The United Nations has demonstrated a commitment to preserving the ecosystem through its 2030 sustainable development goals agenda. One crucial objective of these goals is to promote a healthy ecosystem and discourage practices that harm it. Building materials production significantly contributes to the emissions of greenhouse gases. This poses a threat to the ecosystem and prompts a growing demand for sustainable building materials (SBMs). The purpose of this study is to investigate SBMs to determine their utilization in construction operations and the potential impact their application could have on construction productivity. Design/methodology/approach A systematic review of the existing literature in the field of SBMs was conducted for the study. The search strings used were “sustainable” AND (“building” OR “construction”) AND “materials” AND “productivity”. A total of 146 articles were obtained from the Scopus database and reviewed. Findings Bio-based, cementitious and phase change materials were the main categories of SBMs. Materials in these categories have the potential to substantially contribute to sustainability in the construction sector. However, challenges such as availability, cost, expertise, awareness, social acceptance and resistance to innovation must be addressed to promote the increased utilization of SBMs and enhance construction productivity. Originality/value Many studies have explored SBMs, but there is a dearth of studies that address productivity in the context of SBMs, which leaves a gap in understanding. This study addresses this gap by drawing on existing studies to determine the potential implications that using SBMs could have on construction productivity.
{"title":"Sustainable building materials utilization in the construction sector and the implications on labour productivity","authors":"Oluseyi Julius Adebowale, Justus Ngala Agumba","doi":"10.1108/jedt-04-2023-0164","DOIUrl":"https://doi.org/10.1108/jedt-04-2023-0164","url":null,"abstract":"Purpose The United Nations has demonstrated a commitment to preserving the ecosystem through its 2030 sustainable development goals agenda. One crucial objective of these goals is to promote a healthy ecosystem and discourage practices that harm it. Building materials production significantly contributes to the emissions of greenhouse gases. This poses a threat to the ecosystem and prompts a growing demand for sustainable building materials (SBMs). The purpose of this study is to investigate SBMs to determine their utilization in construction operations and the potential impact their application could have on construction productivity. Design/methodology/approach A systematic review of the existing literature in the field of SBMs was conducted for the study. The search strings used were “sustainable” AND (“building” OR “construction”) AND “materials” AND “productivity”. A total of 146 articles were obtained from the Scopus database and reviewed. Findings Bio-based, cementitious and phase change materials were the main categories of SBMs. Materials in these categories have the potential to substantially contribute to sustainability in the construction sector. However, challenges such as availability, cost, expertise, awareness, social acceptance and resistance to innovation must be addressed to promote the increased utilization of SBMs and enhance construction productivity. Originality/value Many studies have explored SBMs, but there is a dearth of studies that address productivity in the context of SBMs, which leaves a gap in understanding. This study addresses this gap by drawing on existing studies to determine the potential implications that using SBMs could have on construction productivity.","PeriodicalId":46533,"journal":{"name":"Journal of Engineering Design and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136018903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-23DOI: 10.1108/jedt-01-2023-0021
Mallikarjun S. Bhandiwad, B.M. Dodamani, Deepak M.D.
Purpose The present work involves analytical and experimental investigation of sloshing in a two-dimensional rectangular tank including the effect of porous baffles to control and/or reduce the wave motion in the sloshing tank. The purpose of this study is to assess the analytical solutions of the drag coefficient effect on porous baffles performance to track free surface motion variation in the sloshing tank by comparison with experimental shake table tests under a range of sway excitation. Design/methodology/approach The linear second-order ordinary differential equations for liquid sloshing in the rectangular tank were solved using Newmark’s beta method and obtained the analytical solutions for liquid sloshing with dual vertical porous baffles of full submergence depths in a sway-oscillated rectangular tank following the methodology similar to Warnitchai and Pinkaew (1998) and Tait (2008). Findings The porous baffles significantly reduce wave elevation in the varying filled levels of the tank compared to the baffle-free tank under the range of excitation frequencies. It is observed that the Reynolds number-dependent drag coefficient for porous baffles in the tank can significantly reduce the sloshing elevations and is found to be effective to achieve higher damping compared to the porosity-dependent drag coefficient for porous baffles in the sloshing tank. The analytical model’s response to free surface elevation variations in the sloshing tank was compared with the experiment’s test results. The analytical results matched with shake table test results with a quantitative difference near the first resonant frequency. Research limitations/implications The scope of the study is limited to porous baffles performance under range sway motion and three different filling levels in the tank. The porous baffle performance includes Reynolds number dependent drag coefficient to explore the damping effect in the sloshing tank. Originality/value The porous baffles with low-level porosities in the sloshing tank have many engineering applications where the first resonant mode of sloshing in the tank is more important. The porous baffle drag coefficient is an important parameter to study the baffle’s damping effect in sloshing tanks. Hence, obtained analytical solution for liquid sloshing in the rectangular tank with Reynolds number as well as porosity-dependent drag coefficient (model 1) and porosity-dependent drag coefficient porous baffles (model 2) performance is discussed. The model’s test results were validated using a series of shake table sloshing experiments for three fill levels in the tank with sway motion at various excitation frequencies covering the first four sloshing resonant modes.
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