• The Journal of Asian Finance, Economics and Business
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• v.9 no.1
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• pp.121-132
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• 2022

The uncertainty regarding inventory may impart dynamic impacts on corporate-level financial decisions. Among others, a decision about capital investment is a crucial decision that requires overall financial stability. Following these theoretical notions, the current study aims to identify possible consequences of inventory volatility relating to corporate capital investment decisions. We employed ten years of data (2010-2019) of non-financial sector firms to achieve the objective. The Driscoll-Kraay model was used to quantify the regression. The statistical results imply that inventory volatility negatively influences capital investment decisions due to information asymmetry about the current financial position. Additionally, more volatility brings discrepancies in managers' investing decisions to fulfill the possible demand options of capital investment that require processing the inventory. However, based upon the statistical findings, it is suggested to corporate managers that they should consider the financial sensitivity of enterprises regarding inventory volatility. Thus, the current study introduces new thoughts regarding inventory volatility and its empirical role in determining capital investment.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.426-426
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• 1999

;There are many sources of uncertainty in a typical production and inventory system. There is uncertainty as to how many items customers will demand during the next day, week, month, or year. There is uncertainty about delivery times of the product. Uncertainty exacts a toll from management in a variety of ways. A spurt in a demand or a delay in production may lead to stockouts, with the potential for lost revenue and customer dissatisfaction. Firms typically hold inventory to provide protection against uncertainty. A cushion of inventory on hand allows management to face unexpected demands or delays in delivery with a reduced chance of incurring a stockout. The proposed strategies are used for the design of a probabilistic inventory system. In the traditional approach to the design of an inventory system, the goal is to find the best setting of various inventory control policy parameters such as the re-order level, review period, order quantity, etc. which would minimize the total inventory cost. The goals of the analysis need to be defined, so that robustness becomes an important design criterion. Moreover, one has to conceptualize and identify appropriate noise variables. There are two main goals for the inventory policy design. One is to minimize the average inventory cost and the stockouts. The other is to the variability for the average inventory cost and the stockouts The total average inventory cost is the sum of three components: the ordering cost, the holding cost, and the shortage costs. The shortage costs include the cost of the lost sales, cost of loss of goodwill, cost of customer dissatisfaction, etc. The noise factors for this design problem are identified to be: the mean demand rate and the mean lead time. Both the demand and the lead time are assumed to be normal random variables. Thus robustness for this inventory system is interpreted as insensitivity of the average inventory cost and the stockout to uncontrollable fluctuations in the mean demand rate and mean lead time. To make this inventory system for robustness, the concept of utility theory will be used. Utility theory is an analytical method for making a decision concerning an action to take, given a set of multiple criteria upon which the decision is to be based. Utility theory is appropriate for design having different scale such as demand rate and lead time since utility theory represents different scale across decision making attributes with zero to one ranks, higher preference modeled with a higher rank. Using utility theory, three design strategies, such as distance strategy, response strategy, and priority-based strategy. for the robust inventory system will be developed.loped.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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• pp.677-687
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• 1996

We study simultaneous decision making model for a monopolistic or competitive supplier to decide inventory and pricing policies under capacity constraint. Economic implications are obtained from the optimality conditions such as production lot sizes, pricing schedules and so on. Sensitivity analysis gives us the optimal relations among the critical economic quantities.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.201-204
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• 1997

This study is focussed on optimization problems which require allocating the restricted inventory to demand points and assignment of vehicles to routes in order to deliver goods for demand sites with optimal decision. This study investigated an integrated model using three step-by-step approach based on relationship that exists between the inventory allocation and vehicle routing with restricted amount of inventory and transportations. we developed several sub-models such as; first, an inventory-allocation model, second a vehicle-routing model based on clustering and a heuristic algorithms, and last a vehicle routing scheduling model, a TSP-solver, based on genetic algorithm. Also, for each sub-models we have developed computer programs and by a sample run it was known that the proposed model to be a very acceptable model for the inventory-allocation and vehicle routing problems.

• IE interfaces
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• v.21 no.4
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• pp.444-455
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• 2008

In the present manufacturing environment, the appropriate decision making strategy has a significance and it should count on the fast-changing demand of customers. This research derives the optimal levels of the decision variables affecting the inventory related performance in multi-stage supply chain by using simulation and genetic algorithm. Simulation model helps analyze the customer service level of the supply chain computationally and the genetic algorithm searches the optimal solutions by interaction with the simulation model. Our experiments show that the integration approach of the genetic algorithm with a simulation model is effective in finding the solutions that achieve predefined target service levels.

• Journal of Korean Society for Quality Management
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• v.38 no.3
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• pp.333-339
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• 2010

It is difficult to determine an optimal inventory level of aircraft engine and modules to achieve the target operational availability since F100-PW-200 & 229 engines of the F-16 & KF-16 aircraft are consisted of 5 modules with different failure rates and costs. This study presents a decision model, combining an integer programming problem and a regression metamodel. Data for the metamodel was attained from results of a simulation model, that represents operational and repair process of F-16 and KF-16. The objective function of an integer programming problem is maximizing the operational availability, representing pessimistic circumstances. Finally, an integer programming problem with a metamodel can make an optimal decision of the inventory level.

• The Journal of Information Systems
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• v.6 no.1
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• pp.223-256
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• 1997

Since the business scales of retailing companies become to be very large and the number of items dealt increases explosively, automation of inventory management becomes one of the most important issues to solve in retailing industry. In order to accomplish this automation of inventory management, there must be a great need to a method which can perform real-time decision making on inventory control in an automatic fashion, while communicating with inventory information systems like POS system and automatic warehousing system. But even in this circumstance, there are also many obstructions to such automation like varying demands, limited capacity of warehouse and exhibition room, need for strategic consideration on inventory control, etc., in a real sense. Due to these reasons, it seems very difficult that most large-scaled retailing companies get fully automated inventory management system. To overcome those difficulties and reflect them into inventory control, we propose a automated inventory control methodology for retailing industry based on neural network and policy model. Especially, policy model is devised to deal with dynamic varying demands and using this model, strategic goals on inventory can be considered into inventory control mechanism. Our proposed approach is implemented in workstation and its performance is also empirically verified also against to real case of one of the major retailing firm in Korea.

• Journal of Environmental Impact Assessment
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• v.19 no.6
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• pp.573-581
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• 2010

Natural ecosystem is an essential part to connect with the plan for biodiversity conservation in response strategy against climate change. For connecting biodiversity conservation with climate change strategy, Europe, America, Japan, and China are making an effort to discuss protection necessity through national biodiversity valuation but precedent studies lack in Korea. In this study, we made biodiversity maps representing biodiversity distribution range using species richness in National Forest Inventory (NFI) and Forest Description data. Using regression tree algorithm, we divided various classes by decision rule and constructed biodiversity maps, which has accuracy level of over 70%. Therefore, the biodiversity maps produced in this study can be used as base information for decision makers and plan for conservation of biodiversity & continuous management. Furthermore, this study can suggest a strategy for increasing efficiency of forest information in national level.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.904-913
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• 2005

This paper deals with an integrated problem of inventory control and dynamic pricing strategies for a commodity with price and sales-period dependent demand pattern, where a seller and customers have complete information of each other. The problem consists of two parts; one is each buyer's benefit problem which makes the best decision on price and time for buyer to purchase items, and the other one is a seller's profit problem which decides an optimal sales strategy concerned with inventory control and discount schedule. The seller's profit function consists of sales revenue and inventory holding cost functions. The two parts are closely related into each other with some related variables, so that any existing general solution methods can not be applied. Therefore, a simplified model with single seller and two customers in considered first, where demand for multiple units is allowed to each customer within a time limit. Therewith, the model is generalized for a n-customer-classes problem. To solve the proposed n-customer-set problem, a dynamic programming algorithm is derived. In the proposed dynamic programming algorithm, an intermediate profit function is used, which is computed in case of a fixed initial inventory level and then adjusted in searching for an optimal inventory level. This leads to an optimal sales strategy for a seller, which can derive an optimal decision on both an initial inventory level and a discount schedule, in $O(n^2)$ time. This result can be used for some extended problems with a small customer set and a short selling period, including sales strategy for department stores, Dutch auction for items with heavy holding cost, open tender of materials, quantity-limited sales, and cooperative buying in the on/off markets.

• The Journal of Fisheries Business Administration
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• v.25 no.2
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• pp.103-114
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• 1994

We consider the continous, deterministic, infinite horiton, perishable item inventory, within the setting of a retail sector, in which the price for an item is dependent on the lifetime of inventory. Replenishment cost is kept constant but the carrying cost per units is allowed to vary according to product lifetime. Tro possibilities of variation are considered : (1) Product lifetime is longer than cycletime and (2) Product lifetime is shorter than cycletime. We find the optimal policies and decision rules for perishable product.