• Fashion & Textile Research Journal
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• v.15 no.5
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• pp.753-762
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• 2013

This study identifies meaningful factors that influence relationship switching intention and multi-channel use intention for department store customers. Two types of commitment (affective and calculative commitment) are proposed as mediators between satisfaction and behavioral intention. A web-based survey collected fashion product data from consumers who had a relationship with a department store. A total of 150 responses were analyzed by frequency analysis and reliability analysis, CFA, and SEM analysis with SPSS 18.0 and AMOS 18.0. Department store attributes were composed of four factors (product, salespersons, facilities and place, and price and promotion). Department store satisfaction was specified as a second order latent construct which was reflected in the satisfaction with the four department store attributes. Department store satisfaction had a significant negative influence on calculative commitment and a positive effect on affective commitment. Calculative commitment affected switching intention and affective commitment determined multichannel use intention. This study has implications for retail marketers that target fashion consumers and academics who research consumer behavior in retail settings. The most important result is that the affective commitment and the calculative commitment serve different functions. Department store managers need to make an increased effort to instigate an affective customer commitment in order to reduce switching intention.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.2
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• pp.120-128
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• 2015

Quality function deployment (QFD) is a useful method in product design and development to maximize customer satisfaction. In the QFD, the technical attributes (TAs) affecting the product performance are identified, and product performance is improved to optimize customer requirements (CRs). For product development, determining the optimal levels of TAs is crucial during QFD optimization. Many optimization methods have been proposed to obtain the optimal levels of TAs in QFD. In these studies, the levels of TAs are assumed to be continuous while they are often taken as discrete in real world application. Another assumption in QFD optimization is that the requirements of the heterogeneous customers can be generalized and hence only one house of quality (HoQ) is used to connect with CRs. However, customers often have various requirements and preferences on a product. Therefore, a product market can be partitioned into several market segments, each of which contains a number of customers with homogeneous preferences. To overcome these problems, this paper proposes an optimization approach to find the optimal set of TAs under multi-segment market. Dynamic Programming (DP) methodology is developed to maximize the overall customer satisfaction for the market considering the weights of importance of different segments. Finally, a case study is provided for illustrating the proposed optimization approach.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.2
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• pp.177-186
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• 2022

A network QoS model for the joint integrated C4I structure was proposed for the integration of network infrastructure and network operations(NetOps) for NCOE. Detailed QoS requirements process of the joint integrated C4I systems are needs in the Multi-Domain Operation Environment(MDOE). A process is proposed for identifying QoS requirements and establishing in the MDOE using JMT(Joint Mission Thread) reference architecture and solution architecture. Mission analysis identify JCOAs(Joint Critical Operational Activities) and related activities based on JMT & System architecture's OVs, and Information analysis identify QoS attributes using System architecture's SVs. Identifying QoS attributes will be registered at PPS Registry by pre-regulated process, and will be set-up by NetOps. MDOE QoS requirement Process will support efficiently MUM-T and smart defense platform users under the future uncertain battlefield circumstances.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.176-181
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• 2011

A role of cost modeler is that of facilitating design process by the systematic application of cost factors so as to maintain sensible and economic relationships between cost, quantity, utility and appearance. These relationships help to achieve the client's requirements within an agreed budget. The purpose of this study is to develop a parametric cost estimating model for the early design stage by using the multi-dimensional system of OLAP (On-line Analytical Processing) based on the case of quantity data related to architectural design features. The parametric cost estimating models have been adopted to support decision making in the early design stage. These models typically use a similar instance or a pattern of historical case. In order to effectively use this type of data model, it is required to set data classification and prediction methods. One of the methods is to find the similar class in line with attribute selection measure in the multi-dimensional data model. Therefore, this research is to analyze the relevance attribute influenced by architectural design features with the subject of case-based quantity data used for the parametric cost estimating model. The relevance attributes can be analyzed by Analytical Characterization. It helps determine what attributes to be included in the OLAP multi-dimension.

• Journal of KIISE:Databases
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• v.35 no.2
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• pp.97-111
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• 2008

Commercial data mining tools basically support binary attributes only in mining association rules, that is, they can mine binary association rules only. In general, however. transaction databases contain not only binary attributes but also quantitative attributes. Thus, in this paper we propose a systematic approach to mine quantitative association rules---association rules which contain quantitative attributes---using commercial mining tools. To achieve this goal, we first propose an overall working framework that mines quantitative association rules based on commercial mining tools. The proposed framework consists of two steps: 1) a pre-processing step which converts quantitative attributes into binary attributes and 2) a post-processing step which reconverts binary association rules into quantitative association rules. As the pre-processing step, we present the concept of domain partition, and based on the domain partition, we formally redefine the previous bipartition and multi-partition techniques, which are mean-based or median-based techniques for bipartition, and are equi-width or equi-depth techniques for multi-partition. These previous partition techniques, however, have the problem of not considering distribution characteristics of attribute values. To solve this problem, in this paper we propose an intuitive partition technique, named standard deviation minimization. In our standard deviation minimization, adjacent attributes are included in the same partition if the change of their standard deviations is small, but they are divided into different partitions if the change is large. We also propose the post-processing step that integrates binary association rules and reconverts them into the corresponding quantitative rules. Through extensive experiments, we argue that our framework works correctly, and we show that our standard deviation minimization is superior to other partition techniques. According to these results, we believe that our framework is practically applicable for naive users to mine quantitative association rules using commercial data mining tools.

• Journal of KIISE:Software and Applications
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• v.31 no.3
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• pp.308-316
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• 2004

This paper proposed mediator agent system that guarantees reciprocity to attendances in bilateral negotiations for electronic commerce that is different from regular commercial transactions. The optimal agreement was supposed to provide the total maximum profits and the minimum difference in profits of both attendances in negotiations. In the mediator agent system, mediator agent conducted the negotiations considering multi attributes of product and Multi Attribute Utility Theory(MAUT) was applied to evaluate the profits of buyer and seller. 1'he negotiation model in mediator agent system was transformed into linear programming according to the information of bargain for attendances in negotiations. In order to compare with mediator agent system under the same conditions of reciprocity, another negotiation agent system was implemented using trade-off mechanism that is an algorithm for agent interactions in negotiation. The negotiation agent system using trade-off mechanism did not guarantee the optimal agreement, whereas mediator agent system provided attendances in negotiations with optimal agreement rapidly in comparison with trade-off mechanism.

• Journal of Korea Water Resources Association
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• v.46 no.10
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• pp.997-1004
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• 2013

There is imminent need to find a way to measure the recreational benefits of water so that appropriate actions can be taken to make a multi-purpose reservoir. Therefore, this study attempts to apply a choice experiment to quantifying the recreational benefits of a multi-purpose reservoir, using a specific case study of Sangkwan multi-purpose reservoir. We consider the trade-offs between price and attributes of recreational attributes for selecting a preferred alternative and derive the marginal willingness to pay (MWTP) estimate for each attribute. The results show that the MWTP for providing additional 10,000 ton of water is estimated to be 3 won per household per year. The MWTP for improving 1 level of water quality is computed to be 645.5 won per household per year. Moreover, the MWTP for providing recreation facilities is calculated to be 1,518.6 won per household per year. This study allows us to provide policy-makers with useful quantitative information that can reduce uncertainty in the decision-making process related to a multi-purpose reservoir construction projects.

• ETRI Journal
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• v.43 no.6
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• pp.1004-1012
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• 2021

The collaboration productively interacting between multi-agents has become an emerging issue in real-world applications. In reinforcement learning, multi-agent environments present challenges beyond tractable issues in single-agent settings. This collaborative environment has the following highly complex attributes: sparse rewards for task completion, limited communications between each other, and only partial observations. In particular, adjustments in an agent's action policy result in a nonstationary environment from the other agent's perspective, which causes high variance in the learned policies and prevents the direct use of reinforcement learning approaches. Unexpected social loafing caused by high dispersion makes it difficult for all agents to succeed in collaborative tasks. Therefore, we address a paradox caused by the social loafing to significantly reduce total returns after a certain timestep of multi-agent reinforcement learning. We further demonstrate that the collaborative paradox in multi-agent environments can be avoided by our proposed effective early stop method leveraging a metric for social loafing.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.63-68
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• 2022

Given the competition between different tourist destinations to attract domestic and international tourists it is absolutely vital to examine their website efficacy on specific attributes. This study employs one of the recently developed multi-criteria decision-making method the Best-Worst Method to assess the state government official tourism website across four Indian states known for their tourism potential- Himachal Pradesh, Uttrakhand, Uttar Pradesh and Rajasthan on specific attributes provided by the widely acknowledged WebQual instrument. Information Fit-to-Task and Trust emerged as the most important criterion. Relative advantage and Innovation the least important. The results of the study are easily interpretable and visual. They offer both an individual and comparative analysis of the perceived website efficacy on specific attributes to facilitate tourism stakeholders and website administrators to strategize and make their digital presence effective and competitive.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.225-234
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• 2015

This study focused on building the convergence framework of decision-making for camping site selection attributes. The first stage of study is to identify the camping motivations. The camping motivations are composed of 5 factors. The second stage is to identify the camping site selection attributes. They are composed of 4 factors. The relationships between camping site selection attributes and camping motivations are examined through the multi-regression analysis. The camping site selection attributes were significantly influenced by thr type of camping motivation. Lastly, the relationship between camping site selection attributes and camper's satisfaction and behavioral intention are testified. The implications are that camping site operators and developers need to understand the segmented camping motivations and site selection attributes. They could be the guideline of implementing the developing planning strategies of camping site.