• Management & Information Systems Review
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• v.32 no.1
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• pp.63-85
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• 2013

This study tries to investigate the fundamental implications inherent in inventory asset information(specifically, unexpected inventory investment) by analyzing how the relationship between unexpected inventory investment and future operating performance. And we study how is the response of the stock market participants to the fundamental implications inherent in inventory asset information. Prior papers often assume the efficient market and they view the significant relation between stock prices and financial indicators as evidence of the contribution of such indicators to future earnings. Leading indicators are attracting the market's attention for equity valuation. We study whether one leading indicator (unexpected Inventories) forecasts future earnings, and whether market participants fully reflect the predictive ability when they sets share prices(Mishkin test, 1983). Our empirical results of the study are summarized as follows. Current unexpected inventory investment is negatively associated with future operating performance. Also, our evidence is that the stock market participants overprice the contribution of unexpected inventory investment when predicting future earnings. Furthermore, a hedge strategy that uses the overpricing gives significant future abnormal returns. The overall results help the users of financial reports, researchers of accounting, and the accounting principle setting body.

• Korean Journal of Construction Engineering and Management
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• v.9 no.1
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• pp.187-198
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• 2008

There are usually plenty of material inventories in a construction site. More inventories can meet unexpected demands, and also they may have an economical advantage by avoiding a probable escalation of raw material costs. On the other hand, these inventories also cause negative aspects to increase costs for storing redundant inventory as well as decreasing construction productivity. Therefore, a proper method of deciding an optimal level of material inventories while considering dynamic variations of resources under uncertainty is very crucial for the economical efficiency of construction projects. This research presents a stochastic modelling method for construction operations, particularly targeting a work process involving on-site fabrication of raw materials like iron-rebar process (delivery, cut and assembly, and placement). To develop the model, we apply the concept of factory physics to depict the overall components of a system. Then, an optimal inventory management model is devised to support purchase decisions where users can make timely actions on how much to order and when to buy raw materials. Also, optimal time lag, which minimizes the storage time for pre-assembled materials, is obtained. To verify this method, a real case is applied to elicit an optimal amount of inventory and time lag. It is found that average values as well as variability of inventory level decreased significantly so as to minimize economic costs related to inventory management under uncertain project condition.