• Industrial Engineering and Management Systems
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• v.12 no.3
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• pp.224-233
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• 2013

In supply chain management, the supply contract can induce collaboration and coordination among the supply chain members in order to optimize supply chain performance. Numerous supply contracts have been examined; however, some difficulties related to the application of these contracts still occur. One of the solutions is to apply the composite supply contract which can assist in the supply chain coordination. This research examines the composite contract of the revenue sharing and quantity flexibility contracts in a two-stage supply chain, which comprises a retailer and a supplier. In this research, a mathematical model of the composite contract is developed; then, the applicability of the proposed composite contract is examined by investigating its capability in terms of supply chain coordination and profit allocation. In the numerical experiments, the composite revenue sharing-quantity flexibility contract showed that it is superior to both component contracts in terms of supply chain coordination and profit allocation among supply chain members.

• Journal of Distribution Science
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• v.15 no.2
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• pp.91-100
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• 2017

Purpose - Domestic franchise market has been grown steadily, reaching 50 trillion won in sales and 3,360 franchise headquarters in 2014. A franchise system is an effective business system for the franchisees to lower the failure rate due to the fact that the inexperienced entrepreneurs are supported by their headquarters through the franchisee contract. However, there are also conflicts between franchiser and franchisee behind the quantitative growth of domestic franchise industry. Therefore, it is very important to structure the causes of conflicts and to examine the effect of factors on the relationship commitment and performances. Research design, data, and methodology - In this study, the author divides the composite incompatibility between the franchise and the franchisee into goal incongruity, domain dissensus, and perceptual differences, and examines each dimension to the relationship with commitment and performances. To verify the proposed research model and test hypotheses, the author selected 200 franchise responses in food and beverage industry. The data were analyzed using SPSS 18.0 and AMOS structural equation modeling program. Results - The empirical findings provide goal incongruity and perceptual differences have a negative effect on the affective commitment, but not the calculative commitment. In addition, affective commitment and calculative commitment are found to have a positive effect on re-contractual intention and extended brand shop running intention, respectively. Affective commitment have a stronger effect on re-contractual intention than calculative commitment. Conclusions - First of all, the fact that goal incongruity and perceptual differences negatively affect the affective commitment, but it does not affect the calculative commitment. It means the relationship commitment in distribution channel are multi-dimensional concept that may be attributed to emotional or affective dimensions but may exist in terms of necessity or power-dependence. Second, the level of relationship commitment such as affective and calculative commitment to franchise headquarters positively affects the re-contractual intention and franchiser's extend brand shop running intention suggest that franchiser should encourage and support existing franchisee's commitment. Third, the fact that affective commitment has a greater effect on relationship performance than calculative commitment means to induce franchisee's affective commitment and to prevent the inconsistency between goals and perceptual differences.

• Journal of Mechanical Science and Technology
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• v.15 no.7
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• pp.876-888
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• 2001

For a large scaled optimization based on response surface methods, an efficient quadratic approximation method is presented in the context of the trust region model management strategy. If the number of design variables is η, the proposed method requires only 2η+1 design points for one approximation, which are a center point and tow additional axial points within a systematically adjusted trust region. These design points are used to uniquely determine the main effect terms such as the linear and quadratic regression coefficients. A quasi-Newton formula then uses these linear and quadratic coefficients to progressively update the two-factor interaction effect terms as the sequential approximate optimization progresses. In order to show the numerical performance of the proposed method, a typical unconstrained optimization problem and two dynamic response optimization problems with multiple objective are solved. Finally, their optimization results compared with those of the central composite designs (CCD) or the over-determined D-optimality criterion show that the proposed method gives more efficient results than others.

• Smart Media Journal
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• v.11 no.3
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• pp.62-73
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• 2022

Researches on the prediction of domestic apartment sales price have been continuously conducted, but it is not easy to accurately predict apartment prices because various characteristics are compounded. Prior to predicting apartment sales price, the analysis of major factors, influencing on sale prices, is of paramount importance to improve the accuracy of sales price. Therefore, this study aims to analyze what are the factors that affect the apartment sales price in Gwangju, which is currently showing a steady increase rate. With 6 years of Gwangju apartment transaction price and various social factor data, several maching learning techniques such as multiple regression analysis, random forest, and deep artificial neural network algorithms are applied to identify major factors in each model. The performances of each model are compared with RMSE (Root Mean Squared Error), MAE (Mean Absolute Error) and R² (coefficient of determination). The experiment shows that several factors such as 'contract year', 'applicable area', 'certificate of deposit', 'mortgage rate', 'leading index', 'producer price index', 'coincident composite index' are analyzed as main factors, affecting the sales price.