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This study aims to develop a building renovation duration prediction model incorporating both scope and non-scope factors.

The study used a questionnaire to obtain basic information relating to identified project scope factors as well as information relating to the impact of the non-scope factors on the duration of building renovation projects. The study retrieved 121 completed questionnaires from construction firms on tertiary education trust fund (TETFund) building renovation projects. Artificial neural network was then used to develop the model using 90% of the data, while mean absolute percentage error was used to validate the model using the remaining 10% of the data.

Two artificial neural network models were developed – a multilayer perceptron (MLP) and a radial basis function (RBF) model. The accuracy of the models was 86% and 80%, respectively. The developed models’ predictions were not statistically different from those of actual duration estimates with less than 20% error margin. Also, the study found that MLP models are more accurate than RBF models.

The developed models are only applicable to projects that suit the characteristics and nature of the data used to develop the models. Hence, models can only predict the duration of building renovation projects.

The developed models are expected to serve as a tool for realistic estimation of the duration of building renovation projects and thus, help construction project managers to effectively plan and manage it.

The developed models are expected to serve as a tool for realistic estimation of the duration of building renovation projects and thus, help construction project managers to effectively plan and manage it; it also helps clients to effectively benchmark projects duration and contractors to accurately estimate duration at tendering stage.

The study presents models that combine both scope and non-scope factors in predicting the duration of building renovation projects so as to ensure more realistic predictions.

Construction renovation projects have been noted to suffer from uncertainties. While recent efforts have studied uncertainties affecting the duration of other types of projects, these efforts have overlooked construction renovation projects. Therefore, this study aims to evaluate the uncertainty factors affecting the duration of construction renovation projects.

In total, 226 responses from construction professionals were collected via a questionnaire survey on the impact of uncertainty factors on the duration of construction renovation projects. The subjective responses of experts from the industry were categorised using principal component analysis (PCA) before being exposed to objective analysis, assessment and modelling using a soft computing technique called fuzzy synthetic evaluation (FSE).

In total, 25 uncertainty factors were grouped as critical factors and were modelled. The PCA of the 25 critical uncertainty factors produced an 8-factor solution that grouped the uncertainty factors into 8 categories. The FSE modelling indicated that all eight groups are critical, but with varying levels of criticality on the duration of construction renovation projects.

The study provides a basis for a cost-effective uncertainty management guideline to avoid time overruns in construction projects. It also offers a platform for choosing among renovation projects to decide whether or not a project will overrun its time or not.

The study identified and established critical uncertainties affecting the duration of construction renovation projects, thus providing the first empirical multi-attribute objective uncertainty evaluation for the duration of construction renovation projects.

This study aims to assess the extent of the impact of uncertainty factors on renovation project performance.

This study aims to adopt a quantitative approach, using structural equation modelling (SEM) to assess the extent of the impact of uncertainty variables on construction project performance based on data from 226 construction professionals sourced using a questionnaire.

The SEM result indicates four (4) principal uncertainty factors have a significant effect on renovation projects, while the remaining four (4) do not. Results of descriptive and inferential statistics showed that 25 out of 45 identified uncertainty factors have a critical impact on performance, thereby serving as the basis for exploratory factor analysis, which produced an eight-group factor solution.

The research is limited to specific locations, as uncertainty factors can be location-sensitive. Further research should be done to assess the Impact of these Uncertainty factors on a specific location and other project types.

The study aids practitioners in estimating project costs and durations by identifying uncertainty factors affecting renovation projects. It aids project managers in managing uncertainties to improve cost, quality and schedule and serves as a risk management tool for clients and project managers.

The study presents a path model that shows the impact of uncertainty factors on renovation project performance. The insights provided in this study are poised to assist project managers and other construction professionals in planning renovation projects more effectively and successfully.