Jha, K N and Chockalingam, C T (2011) Prediction of schedule performance of Indian construction projects using an artificial neural network. Construction Management and Economics, 29(9), pp. 901-911. ISSN 1466433X
Abstract
Approximately 42% of Indian government-funded construction projects are facing time overruns. With a number of challenging projects around the corner, there is a definite need to overcome these delays. In an earlier study conducted by one of the authors, 55 project performance attributes were identified based on expert opinions and literature surveys, which were subsequently reduced to 20 factors (11 success and nine failure factors) using factor analysis. A second-stage questionnaire survey based on these factors was used to identify the significant schedule performance factors. The analysis of the survey responses led us to conclude that factors such as: a project manager's competence; monitoring and feedback by project participants; commitment of all project participants; owner's competence; interaction between external project participants; and good coordination between project participants significantly affect schedule performance. The survey also provided the basis for the development of a schedule performance prediction model. For this, an artificial neural network (ANN) method was used to construct the model, and the best was determined to be a 6-3-1 feed-forward neural network based on a back-propagation algorithm with a mean absolute percentage deviation (MAPD) of 11%. This enables project team members to understand the factors they must monitor closely in order to complete the projects on schedule and to predict performance throughout the course of the project.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | construction schedule; India; neural networks; predictions; project management |
| Index terms: | schedule performance, failure factor, commitment, neural network, survey, artificial neural network, prediction model, construction project, competence, questionnaire, project manager, time overrun, owner, deviation, propagation, monitoring, project performance, factor analysis, interaction, India, project management, project team, coordination |
| Subjects: | project controls, sociology, behavioral psychology, statistical analysis, management, production management, Geography, personnel development, project management theory and practice, psychology, modelling and simulation, artificial intelligence, project delivery, financial and cost management, prediction and forecasting, data collection methods, profession, risk assessment, engineering process, control systems |
| Topics: | Engineering Principles, Research Practice, Project Management, Geographical Context, Cost Management, Risk Management, Roles and Professions, Stakeholder Management, Human Resources, Digital Applications, Time Control, Organizational Design, Site Management |
| Descriptive scope: | 4 PCEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here