• Journal of Korean Institute of Industrial Engineers
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• v.6 no.2
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• pp.21-29
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• 1980

This paper deals with the capital budgeting problem of a firm where investments are risky and interrelated. The established models might be classified into two categories; One is the chance-constrained programming model and the other is the expected utility maximization model. The former has a rather limited objective function and does not consider the risk in direct manner. The latter, on the other hand, might lead to a wrong decision because it uses an approximate value of expected utility. This paper attempts to extend the applicability of the chance-constrained programming model by modifying its objective function into a more general form. The capital budgeting problem is formulated as a nonlinear 0-1 integer programming problem first, and is formulated into a linear 0-1 integer programming problem for finding a lower-bound solution of the original problem. The optimal solution of the original problem is then obtained by branch & bound algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.3
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• pp.51-70
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• 2013

This paper develops a model to predict the adoption and level of usage of network technology in a two-level supply chain with buyer-supplier relationships. A firm's adoption of a new technology depends not only on its own beliefs of the new technology's costs and benefits, but also on the adoption decisions of other firms in the supply chain. A model first analyzes an individual supplier's decision about a new technology adoption considering with multiple suppliers and buyers. Individual suppliers' decisions are aggregated with a population model to project how new technology diffuses across the supply chain and examine the pattern of diffusion process. This study found that as more firms adopt in initial periods, the total amount of information to the potential adopters in the population increases, and then the number of firms persuaded by the information increases as the process moves up the distribution of adoption process. We consider three factors influencing the diffusion speed of the new technology in a supply chain network : mean benefits, cost sharing, and information provision. This study examines how such factors affect the reduction of threshold levels, which implies that reductions in threshold levels have an aggregate effect by accelerating the rate of adoption. In particular, we explore relationship factors available in practice in a buyer-supplier relationship and numerically examines how these relationship factors contribute to increase the diffusion speed of the technology in a two-level supply chain.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.59-77
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• 2012

This study focuses on predicting which firms will increase capital by issuing new stocks in the near future. Many stakeholders, including banks, credit rating agencies and investors, performs a variety of analyses for firms' growth, profitability, stability, activity, productivity, etc., and regularly report the firms' financial analysis indices. In the paper, we develop predictive models for rights issues using these financial analysis indices and data mining techniques. This study approaches to building the predictive models from the perspective of two different analyses. The first is the analysis period. We divide the analysis period into before and after the IMF financial crisis, and examine whether there is the difference between the two periods. The second is the prediction time. In order to predict when firms increase capital by issuing new stocks, the prediction time is categorized as one year, two years and three years later. Therefore Total six prediction models are developed and analyzed. In this paper, we employ the decision tree technique to build the prediction models for rights issues. The decision tree is the most widely used prediction method which builds decision trees to label or categorize cases into a set of known classes. In contrast to neural networks, logistic regression and SVM, decision tree techniques are well suited for high-dimensional applications and have strong explanation capabilities. There are well-known decision tree induction algorithms such as CHAID, CART, QUEST, C5.0, etc. Among them, we use C5.0 algorithm which is the most recently developed algorithm and yields performance better than other algorithms. We obtained data for the rights issue and financial analysis from TS2000 of Korea Listed Companies Association. A record of financial analysis data is consisted of 89 variables which include 9 growth indices, 30 profitability indices, 23 stability indices, 6 activity indices and 8 productivity indices. For the model building and test, we used 10,925 financial analysis data of total 658 listed firms. PASW Modeler 13 was used to build C5.0 decision trees for the six prediction models. Total 84 variables among financial analysis data are selected as the input variables of each model, and the rights issue status (issued or not issued) is defined as the output variable. To develop prediction models using C5.0 node (Node Options: Output type = Rule set, Use boosting = false, Cross-validate = false, Mode = Simple, Favor = Generality), we used 60% of data for model building and 40% of data for model test. The results of experimental analysis show that the prediction accuracies of data after the IMF financial crisis (59.04% to 60.43%) are about 10 percent higher than ones before IMF financial crisis (68.78% to 71.41%). These results indicate that since the IMF financial crisis, the reliability of financial analysis indices has increased and the firm intention of rights issue has been more obvious. The experiment results also show that the stability-related indices have a major impact on conducting rights issue in the case of short-term prediction. On the other hand, the long-term prediction of conducting rights issue is affected by financial analysis indices on profitability, stability, activity and productivity. All the prediction models include the industry code as one of significant variables. This means that companies in different types of industries show their different types of patterns for rights issue. We conclude that it is desirable for stakeholders to take into account stability-related indices and more various financial analysis indices for short-term prediction and long-term prediction, respectively. The current study has several limitations. First, we need to compare the differences in accuracy by using different data mining techniques such as neural networks, logistic regression and SVM. Second, we are required to develop and to evaluate new prediction models including variables which research in the theory of capital structure has mentioned about the relevance to rights issue.

• Journal of Korean Society for Quality Management
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• v.50 no.1
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• pp.153-167
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• 2022

Purpose: The purpose of this study is to guide the operation managers who plan daily production of large mass-processing facility that services multi-customers with multi-product, small-batch item characteristics by providing the practical best production quantity and the inventory allowed to build. Methods: Close observation of a subcontract paint-shop operator captured the daily decision process which was reflected in the subcontractor-unique mathematical model and the system dynamics simulation model. Multiple simulations were run to find the practical best production quantity and the maximum allowable stock level of inventory that did not undermine the profit from practical best daily production. Actual data and a few constant values were obtained from the firm under study. Results: While the inventory holding cost for the customer-owned material harms the total profit of the subcontractor, the running cost of the processing facility hinders production in small batches. This balances the maximum possible productions and results in practical best daily production which can be found through simulation runs with actual data. The maximum level of stocked inventory is deduced from the practical best daily production. Conclusion: To build a large volume that enables economy-of-scale production, operators should deal with multi-product small-batch items from multiple customers. When the planned schedule of the time and amount of material in-flow tend not to be reliable, operators can find it practical to execute level production across the planning horizon instead of adjusting to day-to-day in-flow fluctuations.

• Journal of Korea Port Economic Association
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• v.40 no.2
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• pp.65-78
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• 2024

This study investigates the correlation between financial constraints and investment activities in Korean logistics firms. A sample of 340 companies engaged in the transportation sector, as per the 2021 KSIC, was selected for analysis. Financial data obtained from the DART were used to compile a panel dataset spanning from 1996 to 2021, totaling 6,155 observations. The research model was validated, and tests for heteroscedasticity and autocorrelation in the error terms were conducted considering the panel data structure. The relationship between investment activities in the previous period and current investment activities was analyzed using panel Generalized Method of Moments(GMM). The validation results of the research indicate that Korean logistics firms tend to increase investment activities as their level of financial constraints improves. Specifically, a positive relationship between the level of financial constraints and investment activities was consistently observed across all models. These findings suggest that investment decision-making varies based on the financial constraints faced by companies, aligning with previous research indicating that investment activities of constrained firms are subdued. Moreover, while the results from the model examining whether investment activities in the previous period affect current investment activities indicated an influence of investment activities from the previous period on current investment activities, the investment activities from two periods ago did not show a significant relationship with current investment activities. Among the control variables, firm size and cash flow variables exhibited positive relationships, while debt size and asset diversification variables showed negative relationships. Thus, larger firm size and smoother cash flows were associated with more proactive investment activities, while high debt levels and extensive asset diversification appeared to constrain investment activities in logistics companies. These results interpret that under financial constraints, internal funding sources such as cash flows exhibit positive relationships, whereas external capital sources such as debt demonstrate negative relationships, consistent with empirical findings from previous research.

• KDI Journal of Economic Policy
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• v.28 no.1
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• pp.117-144
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• 2006

This study is to analyze the existence of the real buffer effect that reflects the effect of beginning-of-period inventory stocks effect on the demand for fixed investment, and the financial buffer effect indicates the substitution effect between end-of-period inventory stock and the source of financing for fixed investment. I use panel data of 361 Korean listed non-financial firms during 1990-2003. After the crisis, it also observed whether the relationship between inventory stocks and fixed investment has altered or not. I review the theoretical connection between inventory stock and fixed investment through the paper by Bo(2004) and estimate the investment model by the method of GMM-SYS. The results show negative relation between end-of-period inventory stock and fixed investment in the whole period and each period classified, also it confirms that the relation between fixed investment and end-of-period investment is significantly negative. It can be interpreted through two aspects that firms not only use inventory stock as a buffer in response to unexpectedly high demand, but also utilize inventory stock as a source of financing for fixed investment. The results imply that firm's decision-making is much correlated with production-and-inventory stock adjustment, decision-making about fixed investment, and decision-making about financial affairs.

• Korean Journal of Construction Engineering and Management
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• v.10 no.5
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• pp.135-147
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• 2009

The world has witnessed the dramatic expansion of international construction markets during the last decades, particularly around the developing economies and energy resource-rich countries. However, despite the booming markets, the risks of emerging regions have also increased under the rapidly changing environments confronting the global contractors. Most of all, success in overseas business mainly depends on selecting the right market to enter. Accordingly, the right market selection requires global firms to carefully carry out the scientific market entry decision by evaluating country risks, market prospects, firm's capability, level of competition, and among others. This study aims at developing a market entry model by the use of real option analysis (ROA) and scenario planning, which addresses the corporate strategic flexibility against the uncertainties encompassing the overseas construction markets. Based on the suggested approach, global contractors are expected to make a better decision rather than a typically static approach in pursuing, postponing, or abandoning a prospective market to their capacity with a concurrent consideration of uncertainties as well as its option value.

• Journal of Korea Technology Innovation Society
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• v.20 no.3
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• pp.732-753
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• 2017

Recently, when evaluating the technology values in the fields of biotechnology, pharmaceuticals and medicine, we have needed more to estimate those values in consideration of the period and cost for the commercialization to be put into in future. The existing discounted cash flow (DCF) method has limitations in that it can not consider consecutive investment or does not reflect the probabilistic property of commercialized input cost of technology-applied products. However, since the value of technology and investment should be considered as opportunity value and the information of decision-making for resource allocation should be taken into account, it is regarded desirable to apply the concept of real options, and in order to reflect the characteristics of business model for the target technology into the concept of volatility in terms of stock price which we usually apply to in evaluation of a firm's value, we need to consider 'the continuity of stock price (relatively minor change)' and 'positive condition'. Thus, as discussed in a lot of literature, it is necessary to investigate the relationship among volatility, underlying asset values, and cost of commercialization in the Black-Scholes model for estimating the technology value based on real options. This study is expected to provide more elaborated real options model, by mathematically deriving whether the ratio of the present value of the underlying asset to the present value of the commercialization cost, which reflects the uncertainty in the option pricing model (OPM), is divided into the "no action taken" (NAT) area under certain threshold conditions or not, and also presenting the estimation logic for option values according to the observation variables (or input values).

• KDI Journal of Economic Policy
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• v.12 no.1
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• pp.127-148
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• 1990

A Milgrom-Roberts style signalling model of limit pricing is developed to analyze the possibility and the scope of limit pricing in general, noncooperative oligopolies. The model contains multiple incumbent firms facing a potential entrant and assumes an information asymmetry between incombents and the potential entrant about the market demand. There are two periods in the model. In period 1, n incumbent firms simultaneously and noncooperatively choose quantities. At the end of period 1, the potential entrant observes the market price and makes an entry decision. In period 2, depending on the entry decision of the entrant, n' or (n+1) firms choose quantities again before the game terminates. Since the choice of incumbent firms in period 1 depends on their information about demand, the market price in period 1 conveys information about the market demand. Thus, there is a systematic link between the market price and the profitability of entry. Using Bayes-Nash equilibrium as the solution concept, we find that there exist some demand conditions under which incumbent firms will limit price. In symmetric equilibria, incumbent firms each produce an output that is greater than the Cournot output and induce a price that is below the Cournot price. In doing so, each incumbent firm refrains from maximizing short-run profit and supplies a public good that is entry deterrence. The reason that entry is deterred by such a reduced price is that it conveys information about the demand of the industry that is unfavorable to the entrant. This establishes the possibility of limit pricing by noncooperative oligopolists in a setting that is fully rational, and also generalizes the result of Milgrom and Roberts to general oligopolies, confirming Bain's intuition. Limit pricing by incumbents explained above can be interpreted as a form of credible collusion in which each firm voluntarily deviates from myopic optimization in order to deter entry using their superior information. This type of implicit collusion differs from Folk-theorem type collusions in many ways and suggests that a collusion can be a credible one even in finite games as long as there is information asymmetry. Another important result is that as the number of incumbent firms approaches infinity, or as the industry approaches a competitive one, the probability that limit pricing occurs converges to zero and the probability of entry converges to that under complete information. This limit result confirms the intuition that as the number of agents sharing the same private information increases, the value of the private information decreases, and the probability that the information gets revealed increases. This limit result also supports the conventional belief that there is no entry problem in a competitive market. Considering the fact that limit pricing is generally believed to occur at an early stage of an industry and the fact that many industries in Korea are oligopolies in their infant stages, the theoretical results of this paper suggest that we should pay attention to the possibility of implicit collusion by incumbent firms aimed at deterring new entry using superior information. The long-term loss to the Korean economy from limit pricing can be very large if the industry in question is a part of the world market and the domestic potential entrant whose entry is deterred could .have developed into a competitor in the world market. In this case, the long-term loss to the Korean economy should include the lost opportunity in the world market in addition to the domestic long-run welfare loss.

• Asia pacific journal of information systems
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• v.18 no.3
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• pp.91-121
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• 2008

Electronic commerce, commonly known as e-commerce or eCommerce, has become a major business trend in these days. The amount of trade conducted electronically has grown extraordinarily by developing the Internet technology. Most electronic commerce has being conducted between businesses to customers; therefore, the researches with respect to e-commerce are to find customer's needs, behaviors through statistical methods. However, the statistical researches, mostly based on a questionnaire, are the static researches, They can tell us the dynamic relationships between initial purchasing and repurchasing. Therefore, this study proposes dynamic research model for analyzing the cause of initial purchasing and repurchasing. This paper is based on the System-Dynamic theory, using the powerful simulation model with some restriction, The restrictions are based on the theory TAM(Technology Acceptance Model), PAM, and TPB(Theory of Planned Behavior). This article investigates not only the customer's purchasing and repurchasing behavior by passing of time but also the interactive effects to one another. This research model has six scenarios and three steps for analyzing customer behaviors. The first step is the research of purchasing situations. The second step is the research of repurchasing situations. Finally, the third step is to study the relationship between initial purchasing and repurchasing. The purpose of six scenarios is to find the customer's purchasing patterns according to the environmental changes. We set six variables in these scenarios by (1) changing the number of products; (2) changing the number of contents in on-line shopping malls; (3) having multimedia files or not in the shopping mall web sites; (4) grading on-line communities; (5) changing the qualities of products; (6) changing the customer's degree of confidence on products. First three variables are applied to study customer's purchasing behavior, and the other variables are applied to repurchasing behavior study. Through the simulation study, this paper presents some inter-relational result about customer purchasing behaviors, For example, Active community actions are not the increasing factor of purchasing but the increasing factor of word of mouth effect, Additionally. The higher products' quality, the more word of mouth effects increase. The number of products and contents on the web sites have same influence on people's buying behaviors. All simulation methods in this paper is not only display the result of each scenario but also find how to affect each other. Hence, electronic commerce firm can make more realistic marketing strategy about consumer behavior through this dynamic simulation research. Moreover, dynamic analysis method can predict the results which help the decision of marketing strategy by using the time-line graph. Consequently, this dynamic simulation analysis could be a useful research model to make firm's competitive advantage. However, this simulation model needs more further study. With respect to reality, this simulation model has some limitations. There are some missing factors which affect customer's buying behaviors in this model. The first missing factor is the customer's degree of recognition of brands. The second factor is the degree of customer satisfaction. The third factor is the power of word of mouth in the specific region. Generally, word of mouth affects significantly on a region's culture, even people's buying behaviors. The last missing factor is the user interface environment in the internet or other on-line shopping tools. In order to get more realistic result, these factors might be essential matters to make better research in the future studies.