by Pornthip Manodamrongsat

Year 2019


ABSTRACT

This research aimed to identify factors considered as pre-warning signs of problem firms in the Stock Exchange of Thailand (SET), and to explore successful turnaround strategies of problem firms.

The study employed a mixed-methods research methodology, including both quantitative and qualitative research. Potential factors used in this study were adopted from both previous studies and this present study, which covered two main areas, namely corporate governance mechanisms and financial ratios. The data collection used a matched pairs sample totalling 220 problem and non-problem firms during 2013-2018. For the qualitative research including documentary research, in-depth interview, and focus group interview were used as data collection tools. Statistical method for data analysis employed binary logistic regression to analyze quantitative data, while qualitative research adopted content analysis and used NVivo, which is designed for analyzing the qualitative data.

The quantitative research showed that at a significance level of 0.05, the financial ratios including current ratio, debt ratio, and return on assets could predict problem firms. However, corporate governance mechanisms were less likely to predict problem firms. The prediction accuracy rate of the 3-year prediction model equals 74.5 Percent, 75.9 Percent in the 2-year, and 78.2 Percent in the 1-year before being marked as problem firms. Besides, the qualitative research suggested that the successful turnaround strategies could be prioritized investments in other businesses, finding a new capital group, negotiating with creditors for debt-to-equity conversion scheme, and reducing costs and expenses. The study results benefit regulators, investors, creditors, the board of directors, and executives in the area of early warning signs of financial distress, while successful turnaround strategies are recommended for problem firms.


Download : Early Warning Signs of Problem Firms and Their Turnaround Strategies