Predicting production-output performance within a complex business environment: from singular to multi-dimensional observations in evaluation

Abstract

Performance evaluation (also measurement) provides a mechanism to ensure that organisations thrive in today’s complex and dynamic business environment. Performance evaluation is widely used for not only interpreting present performance but also for examining the future production output. An understanding of the ‘future’ is reliant on ‘prediction’, which should consider potential uncertainties as a result of the change of time or the variations between organisations, sectors or regions. However, the development of the epistemology of prediction has been overlooked within the context of performance evaluation. This paper develops and expands an existing paradigm of prediction by addressing the multi-dimensional observation for predicting an organisation’s production performance under the auspices of evaluation and specifically in the context of a construction organisation that delivers infrastructure projects, which are acknowledged as being dynamic, uncertain and complex. Three advanced econometric models are applied by using the production-related data provided by a construction organisation to test the developed paradigm. The managerial implications of the research are discussed to ensure their relevance to practice. The empirical study presented in this paper provides a significant contribution to improving the practice of performance evaluation, which is essential for construction organisations to ensure positive business outcomes can be achieved.

KEYWORDS:

• Production output
• prediction
• performance evaluation
• infrastructure projects
• multi-dimensional observations

Acknowledgments

The authors would like to acknowledge the financial support provided by the Australian Research Council (DP160102882).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 ‘Ontology’ is defined as the philosophical study of existence. Accordingly, the ontology here is referred to as the existence of the significance of cross-sectional heterogeneities in performance evaluation (e.g. variations of business functions in construction companies, which are attributed to the nature of the business rather than the changes of time).

Additional information

Funding

The authors would like to acknowledge the financial support provided by the Australian Research Council (DP160102882).

Notes on contributors

Henry J. Liu

Henry J. Liu, Dr Henry Liu is an Assistant Professor in Building & Construction Management at the School of Design and the Built Environment, University of Canberra, Australia. He holds a PhD in Civil Engineering, Master of Construction Management (by research), Master of Science (MSc) in Management and Bachelor of Law (1st Hons). Dr Liu's research interests include Public-Private Partnerships (PPPs), performance measurement, forecasting of construction production output and transport infrastructure resilience. His research has been published in leading scholarly journals, such as Production Planning & Control, Transportation Research Part D: Transport and Environment, Cities, Environment and Planning C: Politics and Space, Journal of Construction Engineering and Management, Journal of Management in Engineering and International Journal of Project Management.

Peter E.D. Love

Peter E. D. Love, Peter is a John Curtin Distinguished Professor in the School of Civil and Mechanical Engineering at Curtin University. He holds a Higher Doctorate of Science for his contributions in the field of civil and construction engineering and a PhD in Operations Management. His research interests include operations and production management, resilience engineering, infrastructure development and digitization in construction. He has published over 400 scholarly journal papers which have appeared in leading journals such as the European Journal of Operations Research, Journal of Management Studies, IEEE Transactions in Engineering Management, International Journal of Operations and Production Management and Transportation Research A: Policy and Practice. He tweets at: drpedl.

Le Ma

Le Ma, Dr Le Ma is a Sessional Lecturer in Property at the Deakin Business School, Deakin University, Australia. He was awarded a PhD in Property Economics from Deakin University. Dr Ma also holds a Master of Finance and a Bachelor of Applied Mathematics and Statistics, which is conferred by RMIT University, Melbourne and Qingdao University, China, respectively. His research interests include construction economics and productivity, econometric modelling and spatial analysis.

Michael C.P. Sing

Michael C. P. Sing, Dr Michael Sing is an Associate Professor at the School of Architecture and Built Environment, University of Newcastle, Australia. He obtained his BSc in Building Surveying with Arup’s Best Student award and a PhD with a full scholarship from Curtin University in Australia. Dr Sing has more than 9 year’s industrial experience in the field of building surveying and project management. His research interests involve project performance evaluation, modelling and simulation, sustainability in construction and asset management.