Validation of a Formal Framework Model to Improve On-site Construction Productivity: Indian Scenario
Author(s) -
Saurav Dixit,
Choudhary Dhurva,
Singh Priyanka,
Krystyna Araszkiewicz
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.3311/ccc2020-008
Subject(s) - computer science , reliability (semiconductor) , structural equation modeling , productivity , data collection , data modeling , data mining , machine learning , software engineering , statistics , mathematics , economics , macroeconomics , power (physics) , physics , quantum mechanics
Validation can be carried out in many ways, as with most of the research work model validation is usually carried out in five main ways: retrospective project analysis, use of archival data, alternative data collection methods, replication of studies, and experimental implementation. Given the complexity of the data used to propose a framework model for on-site construction productivity, three separate validation methods have been used to verify accuracy and reliability. The validation of the framework model (structure equation model) and the hypothesis using statistical validation measures (quantitative experimental studies are ideal testing tools such as GOF, TLI, and CFI), secondly the validation of the model is by validating the seven main hypotheses using an expert panel of top management industry professionals from the Indian construction industry (using an expert panel of project managers from 13 different construction project in India). The results of the accuracy and effectiveness of the framework model were compared in both different validation processes and the findings of the study suggest that the framework model developed using the structural equation model is valid and that the model could be used by the Indian construction industry. © 2020 The Authors. Published by Budapest University of Technology and Economics & Diamond Congress Ltd Peer-review under responsibility of the Scientific Committee of the Creative Construction Conference 2020.
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