Enterprise risk management and firm performance: developing risk management measurement in accounting practice
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The current extremely volatile business world requires firms to deal with a wide range of risks that pose threats to their organisations. The poor practices of risk management, based on Traditional Risk Management (TRM), was cited time and time again in the aftermath of the recent Global Crisis. Enterprise Risk Management (ERM) has been advocated as a solution to the problems of TRM. The aim is to centralise the management of risk within the organisation and ensure that the board deals with the risk. Hence strategic, external, internal, operational, compliance and reputational risk are dealt with jointly. In doing so, it is expected that ERM will bring value creation to firms. One of the main limitations facing researchers is the lack of a good standardised measurement of ERM implementation; therefore, it has not been possible to establish whether ERM does actually bring benefit to firms. In addition, many companies have set up ERM initiatives, but they lack a clear understanding of the factors that will lead to successful ERM implementation. The remaining unanswered problematic situation has led to two unanswered questions that will determine whether the solution to ERM implementation is avoiding potential pitfalls and improving business sustainability. Firstly, does ERM implementation have an impact on firm performance? And secondly, which is the firm-specific characteristic that leads to better ERM implementation level? This thesis answers the aforementioned questions by proposing a reliable ERM measurement method, and then testing whether firms that adopt ERM actually improve financial performance and determine the influential factor of ERM implementation. The proposed method for measuring ERM implementation is based on the components developed from the current ERM frameworks, where contribution scoring can be standardised to measure ERM implementation level. To demonstrate its viability, data was collected from publicly listed firms in Thailand and was then compared to three alternative methodologies: cluster analysis (CA), principal component analysis (PCA) and partial least squares (PLS). The results show that the proposed method did well compared to the alternatives, both statistically and in prediction performance. The relationship between the proposed ERM measurement and firm performance is then considered by taking appropriate control variables into account, such as the firm’s size and characteristics, industry effects, sales growth and the external environment: technology, market uncertainty, as well as economic factors. By using data from the Thailand Stock Exchange, it was found that implementing ERM could improve firm performance in term of Tobin's Q, ROE and ROA. The results show that ERM and firm performance are related. For the influential factor of ERM implementation, the empirical results show that a firm’s size and economic factors have a statistically positive relationship with a high level of ERM implementation, while lower ERM scores show more revenue volatility than those who have well-implemented ERMs. Furthermore, technology and growth are positively related to each ERM in the scoring system considered.