The objectives of this study were to investigate inventory management with logistics systems affecting balanced scorecard (BSC) and to study the balanced scorecard (BSC) affecting organizational sustainability. The population used in this study was under the supervision of the Thai Auto Parts Manufacturers Association. A questionnaire was used as a research instrument for collecting data from accounting executives accounting staff and other related line staff. Data were analyzed using descriptive statistics such as mean standard deviation and percentage and inferential statistics including Pearsons Correlation Coefficient and Multiple Regression Analysis. The major findings indicated that 1) Inventory management with a logistic system positively effected operating results. 2) The performance of the organization had a positive effect on the sustainability of the organization. The study showed that agencies or organizations that rely on inventory storage manage their warehouses better when the logistics system plays a role in managing various systems within the warehouse. Organizations do not have to store excess inventory resulting in liquidity. Reduced Inventory costs also result in lower total costs. The selling price can be set lower than the competitors. Businesses earn more profits which positively affects the balanced scorecard (BSC) in all four organization perspectives. When the balanced scorecard (BSC) continues to improve the organization will grow sustainably.

The objectives of this research were to select the most appropriate forecasting model for uncertain demand of hot-rolled steel and to find the purchase amount and the reorder point of some raw materials in order to minimize the total cost of production in an iron and steel production planning. The three forecasting models which were exponential model ARIMS model and the proposed Bayesian model were studied. An iron and steel factory in Samutprakarn province was a prototype for this study. Because of their uncertain high demand the Steel H-Beam Steel plate steel round bar and black steel round bar with various sizes were selected and their parameters including demand rate inventory cost back order cost and setup cost were collected. The study found that the proposed Bayesian forecasting model is the most appropriate. The predicted demand and all parameter values were used to find the purchase amounts and the reorder points of the raw materials under the (rQ) policy of the stochastic inventory model.