The objective of this research was to explore factors affecting the selection of property plant and equipment revaluation influencing discretionary accruals of listed companies in real estate and construction sector in Stock Exchange of Thailand during the period of 2011 - 2013. Data were collected from 294 samples and analyzed by logistic regression analysis and t-test in order to test the hypothesis. The results revealed that debt and property investment ratios affected the selection of revaluation accounting policies. Furthermore the research revealed that sample firms selecting property plant and equipment revaluation had significantly higher discretionary accruals than those firms who applied cost method at 0.05 significant level of statistics.

The purpose of the study was to scrutinize patterns and levels of environmental accounting disclosure of listed companies in eight industries in the Stock Exchange of Thailand. The research applied documentary research methodology and descriptive statistics including percentage distribution and Correlation analysis using Chi – Square at Statistical significance at the 0.05 level. The results of the study showed that five among eight industries including agro- and food industry consumer goods industry industrial goods industry real estate and construction industry and resources industry disclosed their environmental accountings at level 2; specific but not quantitatively measurable. However each company paid the highest attention to the environmental management systems because of its prominent requirements. As for the other three industries which were finance industry service industry and technology industry disclosed their environmental accountings at level 0; no environmental accountings disclosure since they paid limited interest to the environmental accounting during 2009 and 2012. In terms of the relationship between the entrepreneur and the environmental accounting disclosure it was found that the entrepreneur’s five aspects such as the business operational period paid paid-up registered capital total assets total liabilities and total revenues were significantly related at the disclosed level of 0-3.

In this study pH physical and microbiological qualities of clear and opaque plastic bottled drinking water produced in Buriram Province Thailand were investigated. Samples of bottled drinking water (N=22) were 8 clear plastic bottles and 14 opaque plastic bottles. Results showed that pH value of all samples were in a range of 6.04 ± 0.03 to 7.61 ± 0.01 in which 7 samples were not acceptable according to the criteria for drinking water in sealed containers declared by the Ministry of Public Health of Thailand. Coliform bacteria in all tested samples were less than 1.8 MPN/100mL and none of E. coli was detected. Therefore consumers of bottled drinking water produced from Buriram province should be aware of health safety because some drinking water products were unacceptable in terms of pH value.

The purpose of this research was to construct the appropriate forecasting model for the export values of alcoholic beverages using three-time series analysis methods including Box-Jenkins method damped trend exponential smoothing method and combined forecasting method. Time series data from the website of Office of Agricultural Economics with total 199 months from January 1998 to July 2014 were used and divided into two series. The first 192- month data from January 1998 until December 2013 were used to build the forecasting models and the last 7-month data from January to July 2014 were used to compare the forecasting method accuracy via the criteria of the lowest mean absolute percentage error and root mean squared error. Research findings indicated that for all forecasting methods that had been studied combined forecasting method was the most accurate method and this model was when and represent the single forecasts at time t from Box-Jenkins method and damped trend exponential smoothing method respectively.

The objective of this research is to use a stochastic process for building a model using Bayesian parameter estimation. The model is applied to the of crash prices and future prices of rice in Thailand for 120 moths including monthly closing average price of white rice 5% non-glutinous paddy 15% and Hom Mali non-glutinous paddy 105. The data are time series data containing autocorrelation trend seasonality and outliers. The algorithms are turned into codes in OpenBugs and the performance of the model is evaluated using simulation in R. The model with a Weibull cumulative distribution function trend the model with an exponential cumulative distribution function trend and the exponential smoothing model are compared. The root mean squared error (RMSE) mean absolute percentage error (MAPE) and mean absolute error (MAE) are used as the criteria. The results show that the model with the model with an exponential cumulative distribution function trend gives smallest RMSE MAPE and MAE for the crash prices of non-glutinous paddy 15% and Hom Mali non-glutinous paddy 105 for both model fitting part and model validation part. The model with a Weibull cumulative distribution function trend gives the smallest RMSE MAPE and MAE for the closing average price of white rice 5% for both model fitting part and model validation part.