• The Journal of Industrial Distribution & Business
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• v.10 no.2
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• pp.39-49
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• 2019

Purpose - Customer loyalty and citizenship behavior are key success factors of franchise system. They make the management of franchisee more effective and efficient. Prior studies, however, mainly dealt with only acquisition utility of customer, such as perceived product/service quality and brand reputation to explain customer loyalty and citizenship behavior, which explains only on one side. We tried to investigate the effect of exchange utility of customer, such as relationship strength and psychological obligation together with the acquisition utility. In addition, we tried to investigate the relationship between customer loyalty and citizenship behavior in franchise context. Research design, data, and methodology - This study used data collected from the dining franchisee managers of 342 franchisors in South Korea. The franchisors consist of more than ten franchisees, the majority of which participated directly in the transaction with franchisor and have worked for more than six months. To test the hypotheses, the study used structural equation model analysis. Results - H1-1, 1-2, 1-3 predicted that acquisition utility would increase customer loyalty to franchisee. In support of H1-1, 1-2, 1-3, the results indicated that acquisition utilities such as perceived product value, perceived service value, and franchise brand reputation had positive effects on customer loyalty. H2-1, 2-2 predicted that exchange utility would increase customer loyalty to franchisee. In support of H2-2, the result indicated that psychological obligation had positive effects on customer loyalty like other acquisition utilities. However, H2-1 was not supported. Relationship strength had no significant effect on customer loyalty. H3 predicted that customer loyalty would increase customer citizenship behavior. In support of H3, the results indicated that customer loyalty had positive effect on customer citizenship behavior. Overall, the evidences generally supported the hypotheses. Conclusion - The results of the study show that not only acquisition utility but also exchange utility increases customer loyalty to franchisee and also show that customer loyalty increases customer citizenship behavior. Interestingly, however, relationship strength has no significant effect on customer loyalty. These results have two implications. The one is that increasing exchange utility can improve customer loyalty as acquisition utility can. The other one is that both of customer utilities can improve customer citizenship via customer loyalty.

• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.51-58
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• 2016

The unprecedented power of cloud computing (CC) that enables free sharing of confidential data records for further analysis and mining has prompted various security threats. Thus, supreme cyberspace security and mitigation against adversaries attack during data mining became inevitable. So, privacy preserving data mining is emerged as a precise and efficient solution, where various algorithms are developed to anonymize the data to be mined. Despite the wide use of generalized K-anonymizing approach its protection and truthfulness potency remains limited to tiny output space with unacceptable utility loss. By combining L-diversity and (${\alpha}$,k)-anonymity, we proposed a hybrid K-anonymity data relocation algorithm to surmount such limitation. The data relocation being a tradeoff between trustfulness and utility acted as a control input parameter. The performance of each K-anonymity's iteration is measured for data relocation. Data rows are changed into small groups of indistinguishable tuples to create anonymizations of finer granularity with assured privacy standard. Experimental results demonstrated considerable utility enhancement for relatively small number of group relocations.

• Journal of The Korea Institute of Healthcare Architecture
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• v.23 no.4
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• pp.77-84
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• 2017

Purpose: In terms of the flexibility in hospital architecture, there are fixed elements of hospital architecture: mechanical, electrical, aeration rooms and shafts, which are the main utility spaces. Thus, it is necessary to recognize the utility space as a system that helps internal functions and flexible internal changes. This study analyzes the notion of the main utility space in hospital architecture and the architectural planning features of the main utility spaces as the system in the design process of the recently built hospitals. Methods: The design factors are extracted comparing two hospitals' plans in each stage and the systematic characteristics of utility spaces are analyzed accordingly. The opinions gathered from interviews of practitioners, architects and facility planning experts directly involved in the architecture design process are analyzed and reflected in the results. Results: Planning for utility spaces should be accompanied by the architectural plan from the basic design process, and proceeded with recognizing utility spaces as a system, which is a fixed element. Utility spaces are highly organically connected. Horizontal and vertical distribution of air chambers can reduce the length and number of ducts, and thus save story height, and reduce the number of shafts, the vertical connection passage. This is advantageous in securing the variable area, which is the ultimate objective of the system-centered hospital architecture plan. Implications: Thereby aims to provide fundamental data on systematic utility space planning in the hospital architecture planning.

• Journal of Korea Multimedia Society
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• v.16 no.5
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• pp.657-666
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• 2013

Today, many aspects of our lives are characterized by the rapid influx of large amounts of data from various application domains. The applications that produce this massive of data span a large spectrum, from social media to business intelligence or biology. This massive influx of data necessitates large scale parallelism for efficiently supporting a large class of analysis tasks. Recently, there have been extensive studies in using MapReduce framework to support large parallelism. While this technique has produced impressive results in diverse applications, the same can not be said for multimedia applications where most of users are interested in a small number of results having high or low score. Thus, in this paper, we develop the data partitioning algorithm which is able to efficiently process large data set having different data utility. The experiment results show that the proposed technique provides significant execution time gains over the existing solution.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.53-59
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• 2016

Recently, huge stream data have been generated in real time from various applications such as wireless sensor networks, Internet of Things services, and social network services. For this reason, to develop an efficient method have become one of significant issues in order to discover useful information from such data by processing and analyzing them and employing the information for better decision making. Since stream data are generated continuously and rapidly, there is a need to deal with them through the minimum access. In addition, an appropriate method is required to analyze stream data in resource limited environments where fast processing with low power consumption is necessary. To address this issue, the sliding window model has been proposed and researched. Meanwhile, one of data mining techniques for finding meaningful information from huge data, pattern mining extracts such information in pattern forms. Frequency-based traditional pattern mining can process only binary databases and treats items in the databases with the same importance. As a result, frequent pattern mining has a disadvantage that cannot reflect characteristics of real databases although it has played an essential role in the data mining field. From this aspect, high utility pattern mining has suggested for discovering more meaningful information from non-binary databases with the consideration of the characteristics and relative importance of items. General high utility pattern mining methods for static databases, however, are not suitable for handling stream data. To address this issue, sliding window based high utility pattern mining has been proposed for finding significant information from stream data in resource limited environments by considering their characteristics and processing them efficiently. In this paper, we conduct various experiments with datasets for performance evaluation of sliding window based high utility pattern mining algorithms and analyze experimental results, through which we study their characteristics and direction of improvement.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.481-486
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• 2021

Machine learning algorithms adopt criterion function as a key component to measure the quality of their model derived from data. Cluster analysis also uses this function to rate the clustering result. All the criterion functions have in general certain types of favoritism in producing high quality clusters. These clusters are then described by attributes and their values. Category utility and partition utility play an important role in cluster analysis. These are fully analyzed in this research particularly in terms of how they are related to the favoritism in the final results. In this research, several data sets are selected and analyzed to show how different results are induced from these criterion functions.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.6
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• pp.1128-1141
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• 2022

Due to increased interest in safety in sports, leisure, industries, and daily life; the demand for products that protect the head is increasing. As a preparatory study for the development of head protection for head injury prevention, this study analyzed patents and utility models related to head protection products such as industrial safety helmets, vehicle helmets, and sports protection gear. For this study, 368 patents and utility models for head protection products searched through WipsOn were selected and analyzed by application year, function, application, protection area, main material, and subject. From the analytic results of this study, the quantitative and qualitative flow and characteristics of developing technology related to head protection products were identified. Through the trend of current technology, it provided data to seek the development direction in the future. The significance of this study is to secure objective data to establish a road map for creating new Intellectual Property for head protection products.

• Journal of KIISE:Databases
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• v.37 no.5
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• pp.221-227
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• 2010

Web access sequence mining can discover the frequently accessed web pages pursued by users. Utility-based web access sequence mining handles non-binary occurrences of web pages and extracts more useful knowledge from web logs. However, the existing utility-based web access sequence mining approach considers web access sequences from the very beginning of web logs and therefore it is not suitable for mining data streams where the volume of data is huge and unbounded. At the same time, it cannot find the recent change of knowledge in data streams adaptively. The existing approach has many other limitations such as considering only forward references of web access sequences, suffers in the level-wise candidate generation-and-test methodology, needs several database scans, etc. In this paper, we propose a new approach for high utility web access sequence mining over data streams with a sliding window method. Our approach can not only handle large-scale data but also efficiently discover the recently generated information from data streams. Moreover, it can solve the other limitations of the existing algorithm over data streams. Extensive performance analyses show that our approach is very efficient and outperforms the existing algorithm.

• Journal of Distribution Science
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• v.16 no.12
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• pp.57-68
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• 2018

Purpose - The development of technologies lead the volume of sale on online market increase but an off-line shopping center is still a core component in the omni-channel strategy. It is generally thought that high-level retailtainment on brick and mortar store affects purchase intentions positively, but some previous studies dispute that and have reported that retailtainment does not affect purchase intentions. So we have studied the additional factors' effect - the nature of purchase and utility - with retailtainment. Research design, data, and methodology - There are 8 treatment groups which were assigned by the method of retailtainment (high vs. low), nature of purchase (essential vs. non-essential), and utility (acquisition vs. transaction). A total of 240 subjects (office workers = 163, 68%; undergraduates = 77, 32%; average age = 30s; female = 39%) were divided into groups and exposed to one of the eight scenarios. Participant's purchase intention was the dependent, and ANOVA and L-matrix were used to analyze for main and interactive effects between factors. Results - First, the main effect and interactive effect between retailtainment and the nature of purchase are significant. We also found that the contrast between essential and non-essential at low-level retailtainment is higher than that of high-level retailtainment. Second, in the case of retailtainment and utility, transaction utility under high-level retailtainment affects purchase intentions positively. Third, between the nature of the purchase and utility, the main effect of the nature of purchase and the interactive effect is significant, but the main effect of utility is not significant. In the case of non-essential goods, the purchase intention was high when transaction utility was provided but in the case of essential goods, acquisition utility increased purchase intentions. Finally, when transaction utility is given, purchase intentions of essential goods increase under low retailtainment, and the purchase intentions of non-essential goods increase under high retailtainment. Conclusions - When customers buy essential goods, discounts decrease purchase intentions. During the season for bargain sales, purchase intentions increase when retailtainment of essential goods is low, and retailtainment of non-essential goods is high.

• Journal of the Korean Institute of Landscape Architecture
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• v.27 no.4
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• pp.137-142
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• 1999

The purpose of this study is to develope a CAD-based tool for rasterization of polygonal vector map in AutoCAD. To identity the layer property of polygonal entity with user-defined coordinates as topology, algorithm in processing entity data of selection set that intersected with scan line was used, and the layers were extracted sequentially by sorted intersecting points in data-list. In addition to the functions for querying and modifying topology, two options for mapping were set up to construct plan projection type and to change meshes' properties in existing DTM data. In case of plan projection type, user-defined cell size of 3DFACE mesh is available for more detailed edge, and topological draping on landform can be executed in case of referring DTM data as an AutoCAD's drawing. The concept of algorithm was simple and clear, but some unexpectable errors were found in detecting intersected coordinates that were AutoCAD's error, not the utility's. Also, the routines to check these errors were included in algorithmic processing. Developed utility named MESHMAP was written in entity data control functions of AutoLISP language and dialog control language(DCL) for the purpose of user-oriented interactive usage. MESHMAP was proved to be more effective in data handling and time comparing with GRIDMAP module in LANDCADD which has similar function.