Faculty Publications

Now showing 1 - 3 of 3

Dimensions for improvement of construction management practice in Ethiopian construction industry
(Emerald Group Holdings Ltd., 2020) Mengistu, D.G.; Mahesh, G.
Purpose: The state of the different practices in construction industry determines its performance level. Hence, improving performance of construction industry needs assessing state of the practices in the industry and devising improvement intervention. The purpose of this paper is to measure improvement requirement level of different construction management practice areas and to identify the underlying improvement dimensions in Ethiopian construction industry. Design/methodology/approach: Questionnaire survey was developed for data collection based on a thorough literature review which yielded 28 construction management practice areas. Purposive sampling method was used to select respondents for the survey. Mean score was used to identify the required improvement level, and one sample T-test was carried out to identify significance of improvement requirement. Factor analysis was conducted to identify the underlying dimensions of the construction management practice areas. Findings: Findings indicate 27 areas need significant improvement. This shows the low level of adoption of good construction management practices in Ethiopian construction industry. Factor analysis resulted in the areas being grouped to four broad improvement dimensions, namely, project management, organization management, knowledge and risk management and project development and contract management. Originality/value: The findings provide information for appropriate action by the stakeholders to raise standards of adopted construction management practices. It also show areas of construction management which require more focused research in the context of Ethiopian construction industry. Considering the similarity of nature of construction industry problems in developing countries, the findings can be extended to similar countries. © 2019, Emerald Publishing Limited.
Identifying the performance areas affecting the project performance for Indian construction projects
(Emerald Group Holdings Ltd., 2021) Ingle, P.V.; Mahesh, G.; Deepak, D.
Purpose: The construction industry is facing challenges because of performance shortfalls. Construction projects are highly complex, distinctive, fragmented and do not have well-established performance assessment models to evaluate their project success. The purpose of this paper is to assess the direction through determination of performance areas that would affect project performance in Indian construction projects. Design/methodology/approach: A survey instrument was developed to gather data on the perception of industry professionals on these identified areas. Purposive sampling method was used to select respondents for the survey. These performance areas are ranked using relative importance index to ascertain a level of importance among the group. Factor analysis (FA) was conducted to identify the significant performance areas project performance. Further to identify the most influence performance areas on Indian construction projects, multiple regression analysis was carried out. Findings: Findings indicated 28 significant performance areas. This shows the low level of adoption of good construction management practices in Indian construction projects. FA resulted in the areas being grouped to nine broad significant performance areas with 59.49% of the total variance, namely, quality, schedule, environment and stakeholder satisfactions, cost, productivity, safety, communication management, customer relations and finance. Multiple regression analysis revealed two pivotal factors “customer relations” and “schedule” that significantly influence project performance in Indian construction industry. Originality/value: The outcome of the study will guide project stakeholders, who desire to improve project performance on construction projects, to prioritize their efforts. It also highlights performance areas of project management which required more focussed research in the context of Indian construction projects. The findings can be extended to the developing countries. © 2020, Emerald Publishing Limited.
A hybrid machine learning approach for early cost estimation of pile foundations
(Emerald Publishing, 2025) Deepa, G.; Niranjana, A.J.; Balu, A.S.
Purpose: This study aims at proposing a hybrid model for early cost prediction of a construction project. Early cost prediction for a construction project is the basic approach to procure a project within a predefined budget. However, most of the projects routinely face the impact of cost overruns. Furthermore, conventional and manual cost computing techniques are hectic, time-consuming and error-prone. To deal with such challenges, soft computing techniques such as artificial neural networks (ANNs), fuzzy logic and genetic algorithms are applied in construction management. Each technique has its own constraints not only in terms of efficiency but also in terms of feasibility, practicability, reliability and environmental impacts. However, appropriate combination of the techniques improves the model owing to their inherent nature. Design/methodology/approach: This paper proposes a hybrid model by combining machine learning (ML) techniques with ANN to accurately predict the cost of pile foundations. The parameters contributing toward the cost of pile foundations were collected from five different projects in India. Out of 180 collected data entries, 176 entries were finally used after data cleaning. About 70% of the final data were used for building the model and the remaining 30% were used for validation. Findings: The proposed model is capable of predicting the pile foundation costs with an accuracy of 97.42%. Originality/value: Although various cost estimation techniques are available, appropriate use and combination of various ML techniques aid in improving the prediction accuracy. The proposed model will be a value addition to cost estimation of pile foundations. © 2023, Emerald Publishing Limited.

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