• Industrial Engineering and Management Systems
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• v.14 no.3
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• pp.275-288
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• 2015

Purchase dependence is a frequent phenomenon in retail shops and is characterized by the purchase of certain items together due to their unknown interior associations. Although this concept has been significantly examined in the marketing field (e.g. market basket analysis), it has largely remained unaddressed in operations management. Since purchase dependence is an important factor in designing inventory replenishment policies, this paper demonstrates the means of applying it to the partial backordering inventory model. Through computational analyses, this paper compares the performance of inventory models that either consider or ignore purchase dependence; the results demonstrate that inventory models that ignore purchase dependence incur more average cost per unit time than the model that considers purchase dependence, and the impact of purchase dependence can increase in significance as the item set becomes more closely correlated with regard to order demand.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.3
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• pp.296-307
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• 2008

A semiconductor production system has sophisticated manufacturing operations and needs high capital investment for its expensive equipment, which warrants efficient real-time flow control for wafers. In the bay, we consider material handling equipment that can handle multiple carriers of wafers. The dispatching logic first determines the transportation time of each carrier to its destination by each unit of transportation equipment and uses this information to determine the destination machine and target carrier. When there is no available buffer space at the machine tool, the logic allows carriers to stay at the buffer of a machine tool and determine the delay time, which is used to determine the destination of carriers in URL. A simulation study shows this dispatching logic performs better than the procedure currently in use to reduce the mean flow time and average WIP of wafers and increase efficiency of material handling equipment.

• IE interfaces
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• v.21 no.2
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• pp.161-169
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• 2008

Normally, suppliers have to decide on what, how much, and when to replenish stocks of goods based on a data flow generated by a vendor managed inventory(VMI) system. But information from supply chain is often misleading. It is common for such data to be distorted by a lack of coordination and synchronization across several business entities managing different supply chain operations. This phenomenon is called the 'bullwhip effect(BwE)'. Many researchers, working over many years, have studied the reasons for the BwE. They have proposed various remedies, but this phenomenon persists. Though overlooked in previous research, this paper reveals that the 'lot size' of a supply chain of distribution is indeed the main cause of the BwE. In addition, some problems in the existing methods of measuring the BwE are identified and a revised much improved method of measurement is suggested.

• Journal of Distribution Science
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• v.13 no.3
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• pp.31-39
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• 2015

Purpose - Due to its potential to improve supply chain operations, supply chain collaboration has attracted significant attention from both academics and practitioners. This study focuses on VMI, in collaboration with consignment, and examines its impact on supply chain performance. Research design, data, and methodology - This study employs the analysis of mathematical models, formulated based on the proposed supply chain framework. Using numerical examples, it evaluates the performance of three supply chain systems: one including VMI and consignment, a consignment-only system, and a traditional system. Results - The combination of VMI and consignment produces greater supply chain benefits than the consignment-only and traditional systems. Whereas only the performance of the buyer improves with the consignment-only system, the system with VMI and consignment is beneficial to both the buyer and supplier. Conclusions - The results of this study reveal that the inclusion of the additional collaborative function of VMI makes consignment a better supply chain collaboration program. Future studies should examine issues regarding the testing of diverse collaboration programs and the building of a firm theoretical background.

• Management Science and Financial Engineering
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• v.12 no.2
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• pp.19-35
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• 2006

We use the hierarchical Bayesian approach to describe the transition probabilities of a binary nonhomogeneous Markov chain. The Markov chain is used for describing the transition behavior of emotionally disturbed children in a treatment program. The effects of covariates on transition probabilities are assessed using a logit link function. To describe the time evolution of transition probabilities, we consider two modeling strategies. The first strategy is based on the concept of exchangeabiligy, whereas the second one is based on a first order Markov property. The deviance information criterion (DIC) measure is used to compare models with two different time dependent structures. The inferences are made using the Markov chain Monte Carlo technique. The developed methodology is applied to some real data.

• Korean Management Science Review
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• v.32 no.3
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• pp.29-36
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• 2015

In this research, we analyze the sensitivity of the network density to the estimates for the Bass model parameters with both theoretical model and a simulation. Bass model describes the process that the non-adopters in the market potential adopt a new product or an innovation by the innovation effect and imitation effect. The imitation effect shows the word of mouth effect from the previous adopters to non-adopters. But it does not divide the underlying network structure from the strength of the influence over the network. With a network based Bass model, we found that the estimate for the imitation coefficient is highly sensitive to the network density and it is decreasing while the network density is decreasing. This finding implies that the interpersonal influence can be under-looked when the network density is low. It also implies that both of the network density and the interpersonal influence are important to facilitate the diffusion of an innovation.

• Korean Management Science Review
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• v.26 no.2
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• pp.19-35
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• 2009

This paper investigated performance of the Markowitz's portfolio selection model with applications to Korean stock market. We chose Samsung-Group-Funds and KOSPI index for performance comparison with the Markowitz's portfolio selection model. For the most recent one and a half year period between March 2007 and September 2008, KOSPI index almost remained the same with only 0.1% change, Samsung-Group-Funds showed 20.54% return, and Markowitz's model, which is composed of the same 17 Samsung group stocks, achieved 52% return. We performed sensitivity analysis on the duration of financial data and the frequency of portfolio change in order to maximize the return of portfolio. In conclusion, according to our empirical research results with Samsung-Group-Funds, investment by Markowitz's model, which periodically changes portfolio by using nonlinear programming with only financial data, outperformed investment by the fund managers who possess rich experiences on stock trading and actively change portfolio by the minute-by-minute market news and business information.

• Management Science and Financial Engineering
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• v.15 no.2
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• pp.101-118
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• 2009

In quantitative contexts, data mining is widely applied to the prediction of stock prices from financial time-series. However, few studies have examined the potential of data mining for shedding light on the qualitative problem-solving knowledge of experts who make stock price predictions. This paper presents a GA-based data mining approach to characterizing the qualitative knowledge of such experts, based on their observed predictions. This study is the first of its kind in the GA literature. The results indicate that this approach generates rules with higher accuracy and greater coverage than inductive learning methods or neural networks. They also indicate considerable agreement between the GA method and expert problem-solving approaches. Therefore, the proposed method offers a suitable tool for eliciting and representing expert decision rules, and thus constitutes an effective means of predicting the stock price index.

• Management Science and Financial Engineering
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• v.15 no.2
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• pp.69-100
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• 2009

In this paper, we consider a relatively new two-machine flow shop scheduling problem where the unit time WIP cost increases as a job passes through various stages in the production process, and the objective is to minimize the total WIP (work-in-process) cost. Specifically, we study three special cases of the problem. First, we consider the problem where processing times on machine 1 are identical. Second, the problem with identical processing times on machine 2 is examined. The recognition version of the both problems is unary NP-complete (or NP-complete in strong sense). For each problem, we suggest two simple and intuitive heuristics and find the worst case bound on relative error. Third, we consider the problem where the processing time of a job on each machine is proportional to a base processing time. For this problem, we show that a known heuristic finds an optimal schedule.

• Korean Management Science Review
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• v.25 no.3
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• pp.59-72
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• 2008

This paper proposes an R&D opportunity scan framework for information and telecommunications company in aging society. The framework consists of trend analysis, market-oriented search, technology-oriented search, and R&D Portfolio development. We identify technology themes in the market-oriented search by developing market scenarios and analyzing a new business model framework. And then we search prospective technologies in the technology-oriented recess by technology scanning and patent analysis. By matching technology themes with prospective technologies, generate an R&D portfolio. Finally, we evaluate the risk of the proposed R&D portfolio.