• Asia Marketing Journal
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• v.22 no.1
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• pp.41-60
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• 2020

The goal of the study is to understand the role of social norm in purchase decisions where demand is revealed in the form of multiple-discreteness. Consumers are socially engaged in various activities through the expectation from others in their community. Actions or decisions are likely to reflect this influence. This implicit or explicit social norm is revealed as the rules, regulations, and standards that are understood, shared, endorsed, and expected by group members. When consumers' decisions are in distance from the norm, they come to face discomfort such as shame, guilt, embarrassment, and anxiety. These pressure act as a constraint as opposed to utility in their decision making. In this study, the effect of social norms on consumer demand is captured via multiple constraint model where constraints are not only from budget equation but also from psychological burden induced by the deviation from the norm. The posterior distributions of model parameters were estimated via conjoint study allowing for heterogeneity via hierarchical Bayesian framework. Individual characteristics such as age, gender and work experience are also used as covariates for capturing the observed heterogeneity. The empirical results show the role of social norm as constraint in consumers' utility maximization. The proposed model accounting for social constraint outperforms the standard budget constraint-only model in terms of model fit. It is found that people with longer job experience tend to be more robust and resistant to the deviation from the norm. Incorporating social norm into the utility model allows for another means to disentangle the reason for no-purchase as 'not preferred' and 'not able to buy'.

• Asia Marketing Journal
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• v.18 no.4
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• pp.125-138
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• 2017

The goal of the study is to understand how consumers' constraint as opposed to utility structure gives rise to final decision when consumers purchase more than one variant of product at a time, i.e., horizontal variety seeking or multiple-discreteness. Purchase and consumption decision not only produces utility but also involves some sort of cognitive pressure. Past consumption or last purchase is likely to be linked to this burden we face such as concern for obesity, risk of harm, and guilt for mischief. In this research, the existence and the role of dynamic constraint are investigated through a microeconomic utility model with multiple dynamic constraint. The model is applied to the salty snacks data collected from field study where burden for spiciness serves as a constraint. The results are compared to the conventional multiple discreteness choice models of static constraints, and policy implications on price discounts is explored. The major findings are that first, one would underestimate the level of consumer preference for product offerings when ignoring the carry-over of the concern from the past consumption, and second, the impact of price promotion on demand would be properly evaluated when the model allows for the role of constraint as both multiple and dynamic. The current study is different from the existing studies in two ways. First, it captures the effect of 'mental constraint' on demand in formal economic model. Second, unlike the state dependence well documented in the literature, the study proposes the notion of state dependence in different way, via constraint rather than utility.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1074-1079
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• 2011

This paper describes the influence on the nonlinear critical speed results of a specific railway vehicle depending on various constraint conditions. In the roller-rig tests, proper constraints are inevitable to safely hold the test vehicles. Particularly, the test results using KRRI roller-rig are more sensitive to constraint conditions because it is a kind of semi-full car type. In this study, nonlinear critical speed of specific vehicle with regards to several constraint cases were predicted by computational analysis and these results were compared to find the suitable constraint conditions. And also the deviation of semi-full car model from actual full car model was investigated. According to the bifurcation analysis, the nonlinear critical speed are dependent with the constraint condition and car-body yaw motion should be free to achieve more accurate results. And the difference between semi-full and full car model was so small that KRRI's semi-full car model are valid as long as the stability is concerned.

• International Journal of CAD/CAM
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• v.6 no.1
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• pp.173-181
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• 2006

In this paper, an integration framework of Geometric Constraint Solving Engine and AutoCAD is presented, and a dynamic geometric constraint system is introduced. According to inherent orientation features of geometric entities and various Object Snap results of AutoCAD, the' proposed system can automatically construct an under-constrained geometric constraint model during interactive drawing. And then the directed constraint graph in a geometric constraint model is realtime modified in order to produce an optimal constraint solving sequence. Due to the open object-oriented characteristics of AutoCAD, a set of user-defined entities including basic geometric elements and graphics constraint relations are defined through derivation. And the custom-made Object Reactor and Command Reactor are also constructed. Several powerful characteristics are achieved based on these user-defined entities and reactors, including synchronously processing geometric constraint information while saving and opening DWG files, visual constraint relations, and full adaptability to Undo/Redo operations. These characteristics of the proposed system can help the designers more easily manage geometric entities and constraint relations between them.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.1
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• pp.81-95
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• 2009

The CDB(Constraint Database) model is a new paradigm for massive spatial data processing such as GIS(Geographic Information System). This paper will identify the limitation of the schema structure and query processing through prior spatial database research and suggest more efficient processing mechanism of constraint data model. We presented constraint model concept, presentation method, and the examples of query processing. Especially, we represented TIN (Triangulated Irregular Network) as a constraint data model which displays the height on a plane data and compared it with prior spatial data model. Finally, we identified that we were able to formalize spatial data in a simple and refined way through constraint data modeling.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.141-144
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• 2007

Given a number of training data, a traditional BPN is normally trained by minimizing the absolute difference between target outputs and approximate outputs. When BPN is used as a meta-model for inequality constraint function, approximate optimal solutions are sometimes actually infeasible in a case where they are active at the constraint boundary. The paper describes the development of the efficient BPN based meta-model that enhances the constraint feasibility of approximate optimal solution. The modified BPN based meta-model is obtained by including the decision condition between lower/upper bounds of a constraint and an approximate value. The proposed approach is verified through a simple mathematical function and a ten-bar planar truss problem.

• Journal of Information Processing Systems
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• v.2 no.1
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• pp.1-5
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• 2006

Finding a valid timing constraint is one of the most important issues in the real-time monitoring area. To get the valid timing constraint, a developer executes a real-time process and changes the constraint on a regular basis. This is an exhaustive and time-consuming process. To improve this approach, we propose a timing constraint search technique. This technique uses two load models and one condition proposed in this paper to support the developer in determining the valid timing constraint range in an easy and systematic manner.

• KIEAE Journal
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• v.2 no.4
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• pp.65-72
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• 2002

In this study, the evaluation of environmental performance of the building energy system of domestic commercial sector was carried out. Based on the theory of linear programming model, we established an evaluation model satisfying object functions and constraint conditions. Employing the model, the evaluation of building energy system was performed under the consideration of cost and environmental constraint conditions. As an evaluation tool, MARKAL (MARKet Allocation) known as a market distribution model was employed. We analyzed scenarios of Case I (Base Scenarios) through Case IX established by the combination of the components of building energy system such as glazing, building skin, core, and heat source system. According to the results of the evaluation, highest contribution on the useful energy demand was obtained from the building energy system combined with solar heat source system, when the total amounts of $CO_2$ exhaust as an environmental constraint condition is assumed to be the level of 1995.

• Journal of the Korean earth science society
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• v.30 no.7
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• pp.834-844
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• 2009

Two-dimensional magnetotelluric (MT) inversion algorithm using minimum support (MS) stabilizer functional was implemented in this study to enhance the contrast of inverted images. For this implementation, this study derived a formula in discrete form for creeping model updates in the least-squares linearized inversion. A spatially varying regularization parameter determination algorithm, which is known as ACB (Active Constraint Balancing), was also adopted to stabilize the inversion process when using MS stabilizer as a model constraint. Inversion experiments for a simple isolated body model show well the feature of MS stabilizer in concentrating the anomalous body compared with the second-order derivative model constraint. This study also compared MS stabilizer and the second-order derivative model constraints for a model having multiple anomalous bodies to show the applicability of the algorithm into field data.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.4
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• pp.45-56
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• 2010

This paper suggests constraint data modeling based on constraint data presentation techniques to perform complex spatial database operation naturally. We were able to identify the limitation of extendibility of dimension and non-equal framework via relevant research for former schema of spatial database and query processing. Therefore we described generalized tuple of spatial data and the definition of suggested constraint data modeling. Also we selected MLPQ/PReSTO tool among constraint database prototype and compare standard functionality of ARC/VIEW. Then we design scenario for spatial operation using MLPQ/PReSTO and we suggested application effect after query processing. Based on above explanation, we were able to identify that we can process spatial data naturally and effectively using simple constraint routine on same framework via constraint data modeling.