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Abdul Shukor, S (2013) A geometrical-based approach to recognise structure of complex interiors, Unpublished PhD Thesis, Warwick Manufacturing Group, University of Warwick.
Attwell, D N (1989) Bayesian models for sequential bidding and related theoretical topics, Unpublished PhD Thesis, Department of Statistics, University of Warwick.
Bastien, A N (2002) Successful organisational and human practices in the UK construction industry: proposing the CONSTRUCT framework of good practice, Unpublished PhD Thesis, Warwick Manufacturing Group, University of Warwick.
Burrows, B G (1989) Organisation and quality of falsework construction: A socio-economic study of the organisational structure of the construction industry with respect to the falsework production process and the quality of workmanship attained, Unpublished PhD Thesis, Department of Engineering, University of Warwick.
Craig, D (2002) A model for customer-focused culture change in the speculative house-building industry: Executive summary, Unpublished PhD Thesis, Department of Engineering, University of Warwick.
Davies, R J (2003) Formulating competitive strategy in the UK housebuilding industry: Executive summary, Unpublished PhD Thesis, Department of Engineering, University of Warwick.
Druker, J (1980) One big union? Structural change in building trade unionism, Unpublished PhD Thesis, School of Industrial and Business Studies, University of Warwick.
Korczynski, M (1993) Capital, labour and economic performance in the engineering construction industry: 1960-1990, Unpublished PhD Thesis, Department of Industrial Relations and Organisational Behaviour, University of Warwick.
Mahdad, S (2015) Achieving design quality in building projects: An evolving understanding of critical success factors and stakeholder attributes, Unpublished PhD Thesis, Warwick Manufacturing Group, University of Warwick.
Nikolov, A (2022) Exploring pathways for improving the supply chain integration of infrastructure projects, Unpublished PhD Thesis, , University of Warwick.
Wu, H-C (2007) Business failure prediction model for the construction industry using financial ratios and entropy measures with discriminant analysis, Unpublished PhD Thesis, Warwick Manufacturing Group, University of Warwick.
- Type: Thesis
- Keywords: business failure; construction companies; financial ratio; prequalification; stress; Taiwan
- ISBN/ISSN:
- URL: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.487367
- Abstract:
The purpose of this research is to examine empirically the effectiveness of entropy measures derived from information theory combined with discnminant analysis in the prediction ofconstruction business failure. The research will use data derived from the construction industry as business failure is an extremely disruptive force, and a key factor in the prequalification appraisal of contractors in the construction industry (Kangari, Farid et al. 1992; Russell 1992; Yang 1997). The study has used Taiwan construction industry data for empirical analysis. In this research, the model is based on a financial distress definition of business failure. Previous research has shown that the decomposition measure for financial statements has the power to discriminate with respect to failed and non-failed firms. However, the predictive ability is weaker than with just financial ratios (Hamer 1980). This work I explores the transformation of financial ratios to information decomposition measures using information theory. The transformation can' adjust the data to be naturally dynamic. The accumulative dynamic information measures offinancial ratios ar{, then compared with a static financial ratios model in terms oftheir failure prediction ability. It appears that researchers have never utilized information measures of financial ratio to analyse whether this can improve predictive ability. Thus, this new work modifies discriminant analysis with the information measures offinancial ratios. Therefore, this study attempts to bridge this gap in earlier studies. The method devised contributes to measuring the risk (financial distress) of companies in the construction industry or contractors on tender lists. Financial data was gathered for 15 failures and 30 non-failure examples from Taiwanese construction companies between 1997 and 2002.The research uses statistical methodology to test the most important hypotheses 'The predictive ability using dynamic information measures and discriminant analysis is not more accurate than usingjinancial ratios and discriminant analysis'. In conclusion, the author provides evidence to reject the hypotheses. The results reflect a remarkable effect ofthe model using dynamic infonnation measures on perfonnance in the three different models (prediction Model with Financial Ratios, Prediction Model with Static Infonnation Measures, and Prediction Model with Dynamic Infonnation Measures). In the research, the SAS (Business Intelligence software) is used to develop the discriminant models for the study. In future research, the author suggests the combining of the agent technology concept and the tool to extend a real time dynamic prediction model. An agent as an early warning system may be the key to the constant monitoring ofthe financial condition of a company.