• Management Science and Financial Engineering
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• v.15 no.1
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• pp.1-31
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• 2009

This paper considers the value of warehousing contract under probabilistic demands. We consider a supply chain consisting of a supplier, a retailer and its third-party warehousing partner who provides the warehousing service to the retailer through an outsourcing contract. A typical contract is specified by initial space commitment and modification schedule. The retailer decides the order quantity for the supplier and space commitment for the outsourcing contract. Since there is close relationship between order quantity and space commitment to minimize the total cost including ordering cost, inventory carrying cost, shortage cost, and warehousing cost, we develop an analytical model under probabilistic demands, where the retailer can determine the optimal order size and space commitment level jointly. We found the closed-form optimum for a single-period case and the optimal conditions for a two-period case. To evaluate the value of contract flexibility for the two-period case, we compared the total cost under two policies; one with modification, under which the base commitment can be changed at the start of each period and the other without modification. From results of our numerical analysis, we showed that the modification policy is more cost-effective as the variability of demand increases.

• Journal of Korea Trade
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• v.27 no.2
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• pp.22-46
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• 2023

Purpose - study aims to investigate the relationships between global value chain (GVC)- and transportation-related determinants and economic performance. Also, moderating effects of COVID-19 on the relationships are theoretically and empirically discussed. A limitation of previous studies includes their over-reliance on the opportunities of GVC participation and larger transportation. This study represents the challenges associated with them. Also, it shows how GVC and logistics can be difficult in case of a market fluctuation such as COVID-19. Design/methodology - The sample for this study includes 828 observations from 138 countries. A semi-panel data set has been used. Six observations for each country are used to empirically test the hypotheses and a Two-way cluster model is conducted. Findings - It is confirmed that GVC forward participation contributes more than the backward participation to enhance performance. Transportation infrastructure is critical, but large scales of marine and air transportations are not positive in terms of economic performance. Stricter government response to COVID-19 negatively moderates economic performance by GVC backward participation and transportation infrastructure. Originality/value - The spread of COVID-19 is causing a severe collapse of GVC and transportation. This study empirically verifies the moderating effects of the government stringency on GVC and transportation. Previous studies usually discuss a positive impact of GVC and transportation size on economic performance. However, this study aims to show various challenges behind GVC participation and large scale transportation.

• Journal of Navigation and Port Research
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• v.29 no.8 s.104
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• pp.709-714
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• 2005

The purpose of this research is to verify the strategic fitness and relevance of the hub port strategy by SCM in Northeast Asia and to find a method to be a hub-port with a competitive edge. The fitness of the hub port development strategy is analysed by the structural equation model. The essential results of the research show that minimizing lead time from arrival of ship to inland transport and maximizing logistic services of each stage are important to provide optimal logistic service. And value-added port supply chain strategy is highly co-related with all the parts of port operation system, port transport system, distribution park and port information system. It shows that: various value added logistic service activity is more important than lowing cost; inland multimodal system should be rightly connected; distribution park should be connected to industry park to be a port cluster; and port information system should be developed.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.55-65
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• 2021

The purpose of this study is to explore whether entering the overseas market can be an opportunity in overcoming the limitations of the single profit structure in which the traditional performing arts industry relies on public support. To this end, we applied the concept of industrial value-chain and business model and divided the overseas market entry process into four stages-preparation, promotion, harvest, and follow-up. Based on three case-studies that actively pursued overseas market development with market-oriented thinking in the field of traditional music, the relevant entry model of overseas market for the Korean traditional performing arts industry was suggested. Although the overseas market is not yet a major source of revenue, the traditional performing arts teams searching for profit diversification can consider the overseas entry model derived from this study. Also as found in case studies, the Korean government should establish an institutional system to foster planning and distribution experts in charge of overseas markets for the traditional performing arts, and develop a long-term information provision program away from the one-time expense support.

• Management & Information Systems Review
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• v.31 no.2
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• pp.253-272
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• 2012

One of the fastest growing sectors in tourism industry is the use of applications from the MICE industry in various parts including business, politics, and cultural exchange due to globalization among the countries. The means-end chain theory suggests that convention participants perceive and judge convention destination as the means to achieving a desired end-state in a given destination selection situation. This study aims at establishing a convention destination's attributes, the benefits of consequences of using it, and the personal values it satisfies. A laddering interview was conducting in order to provide in-depth probing and to elicit responses from 96 visitors. This study presents the unique pyramid-structure of the means-end chain; a model linking perceived convention destination attributes to values. Understanding these concepts provides opportunities for convention destinations to target market segmentation and advertising based on the participants' desired end-states. In conclusion, the major correlations of attributions of the visitors, consequences, and the values are; informativeness(A), activity(A), tourist attraction(A) - sympathy(C), human relations(C) - self-development(V), and fellowship(V).

• International Commerce and Information Review
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• v.15 no.4
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• pp.509-532
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• 2013

This paper analyzed the functional global entry process of firms by real business cases. We reviewed the global firm Zara and Uniqlo's functional global entry process by Malnight (1995) four-step model which is composed of appendage, participation, contribution, integration stages. We found that both Zara and Uniqlo made successful internationalization using integrated global value chain. However, Zara maintained the home-initiated internationalization strategy on whole value chain, Uniqlo operated subsidiary-initiated functional strategy in specific value chain activities. This study suggests that internationalization occurs at the level of the function, rather than the firm. In addition, this study suggests practical implication to Korean fashion firms that global firms should maintain the functional global entry strategy basing on firm's internationalization steps.

• Journal of Distribution Science
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• v.11 no.4
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• pp.51-60
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• 2013

Purpose - The objective of this paper is to investigate the effect of asset specificity, the level of information sharing, the importance of information sharing, and an integrated collaborative environment on supply chain performance. Research design, data, and methodology - Data collection was implemented as follows: questionnaires were distributed to 250 companies that have business ties with Halla Climate Control Corporation. The empirical study to test our hypothesis was based on statistical analysis (using SPSS 18.0 and AMOS 18.0). The hypothesis of this paper is that the asset specificity variable has positive effects on the following variables: Level of information sharing, the importance of information sharing, and integrated collaborative environment. Moreover the variables, the level of information sharing, and the importance of information sharing are strongly influenced by the variable integrated collaborative environment, and these when combined, have an effect on the dependent variable, supply chain performance. We tested our hypothesized model utilizing path analysis with latent variables. Results - According to the results of our analysis, hypothesis H1, which tests whether there is a relationship between asset specificity and the integrated collaborative environment, is supported at the 0.01 level. Hypotheses H2 and H3 were also confirmed, and asset specificity had positive effects (+) on the level of information sharing variable. The importance of the information sharing variable was statistically significant at the 0.01 level. Hypotheses H4 and H5 posited that the integrated collaborative environment variable would have a positive effect on the level of information sharing; the importance of information sharing variable was strongly supported statistically, with a significant p-value below. Moreover, the level of information sharing (H6), and the importance of information sharing (H7) variables also had a statistically relevant influence on supply chain performance. As a result, existence of a collaborative system between companies would influence supply chain performance by strengthening real-time information access and information sharing. Thus, it is important to construct a collaborative environment where information sharing among companies and cooperation is possible. Conclusions - First, with rapid changes in the business environment, it becomes necessary for enterprises to acquire the right information in order to properly implement SCM. For successful SCM, firms should understand the importance of collaboration with supply chain partners and an internally built collaboration system, which in turn will better promote a partnership commitment with suppliers as well as collaborative integration with buyers. A collaborative system, as we suggest in this paper, facilitates the maintenance of a long-term relationship of trust, and can help reinforce information sharing. Second, it is necessary to increase information sharing over time via a collaborative system so that employees of the suppliers become aware of the system. The more proactive and positive attitudes are towards such a collaborative system by the managerial group, the higher the level of information sharing will be among the users. Successful SCM performance is achieved by information sharing through a collaborative environment rather than by investing only in setting up an information system.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.37-52
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• 2011

Supply chain management is a strategic thinking which enhances the value of supply chain and adapts more promptly for the changing environment. For the seamless partnership and value creation in supply chains, information and knowledge sharing and proper partner selection criteria must be applied. Thus, the partner selection criteria are critical to maintain product quality and reliability. Each part of a product is supplied by an appropriate supply partner. The criteria for selecting partners are technological capability, quality, price, consistency, etc. In reality, the criteria for partner selection may change according to the characteristics of the components. When the part is a core component, quality factor is the top priority compared to the price. For a standardized component, lower price has a higher priority. Sometimes, unexpected case occurs such as emergency order in which the preference may shift on the top. Thus, SCM partner selection criteria must be determined dynamically according to the characteristics of part and its context. The purpose of this research is to develop an OWL model for the supply chain partnership depending on its context and characteristics of the parts. The uncertainty of variable is tackled through fuzzy logic. The parts with preference of numerical value and context are represented using OWL. Part preference is converted into fuzzy membership function using fuzzy logic. For the ontology reasoning, SWRL (Semantic Web Rule Language) is applied. For the implementation of proposed model, starter motor of an automobile is adopted. After the fuzzy ontology is constructed, the process of selecting preference-based supply partner for each part is presented.

• Communications for Statistical Applications and Methods
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• v.30 no.2
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• pp.163-178
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• 2023

GARCH-X(1, 1) model specifies that conditional variance follows an AR(1) process and includes a past exogenous variable. This study proposes a new class from that model by allowing a more general (non-linear) variance function to follow an AR(1) process. The functions applied to the variance equation include exponential, Tukey's ladder, and Yeo-Johnson transformations. In the framework of normal and student-t distributions for return errors, the empirical analysis focuses on two stock indices data in developed countries (FTSE100 and SP500) over the daily period from January 2000 to December 2020. This study uses 10-minute realized volatility as the exogenous component. The parameters of considered models are estimated using the adaptive random walk metropolis method in the Monte Carlo Markov chain algorithm and implemented in the Matlab program. The 95% highest posterior density intervals show that the three transformations are significant for the GARCHX(1, 1) model. In general, based on the Akaike information criterion, the GARCH-X(1, 1) model that has return errors with student-t distribution and variance transformed by Tukey's ladder function provides the best data fit. In forecasting value-at-risk with the 95% confidence level, the Christoffersen's independence test suggest that non-linear models is the most suitable for modeling return data, especially model with the Tukey's ladder transformation.