• Journal of Distribution Science
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• v.9 no.4
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• pp.63-73
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• 2011

The relationship between buyers and sellers is changing into a long-term relationship. A number of distribution channel researchers have determined that the behavior of distribution channel members can be characterized by relational exchanges. The members of relational distribution channels may be perceived as strategic partners; however, even within these arrangements, member asymmetries may exist, which can create unequal distributions of power and dependence. Thus, as all distribution channel members may not be equal in power, it is possible that a less-dependent channel leader may emerge. Therefore, leadership in distribution channels is a very important variable. Distribution channel leadership can be defined as the activities undertaken by the distribution channel leader to influence the marketing programs and strategies of channel members. A distribution channel's performance is influenced by the leadership style of the channel leader. Although research on channel leadership styles can be broadly categorized, many researchers have dealt with analyzing distribution channel leadership by using the power-influence approach, which includes looking at variables, such as power, power base, and influence strategies. Moreover, they have examined the direct relationship between leadership styles and performance. Many distribution channel scholars have attempted to justify the application of leadership styles identified in alternative leadership theories to the inter-organizational context of distribution channels. They have made suggestions regarding how great the usefulness of leadership style as a strategy is to secure the compliance of distribution channel members and have conceptually and empirically linked it to channel-related phenomena, such as manifest conflict, cooperation, channel efficiency, and effectiveness. However, as few empirical studies have examined the antecedents and consequences of leadership styles, research on leadership style can be considered nascent. Thus, it is required to investigate the antecedents and consequences of the leadership style of a distribution channel leader. This study aims to empirically identify whether there are influences of the antecedents of leadership on two different leadership styles, and to reveal whether these leadership styles induce any consequences. The research subjects were 220 franchisees. Research findings are as follows: First, the results show a positive effect of technological capability on transformational relationships. However, it does not have a significant effect on transactional leadership. Second, innovation-oriented organizational culture has negatively influenced both leaderships. However, task-oriented organizational culture positively and significantly influenced both forms of leadership. Third, the ethics of leaders has influenced both leadership styles positively and significantly. Fourth, regarding consequences, transformational leadership strengthens financial performances, whereas it weakens relational citizenship behaviors. However, transactional leadership positively influences relational citizenship behavior whilst negatively affecting financial performance.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.1-18
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• 2015

Collaborative filtering(CF) algorithm has been popularly used for recommender systems in both academic and practical applications. A general CF system compares users based on how similar they are, and creates recommendation results with the items favored by other people with similar tastes. Thus, it is very important for CF to measure the similarities between users because the recommendation quality depends on it. In most cases, users' explicit numeric ratings of items(i.e. quantitative information) have only been used to calculate the similarities between users in CF. However, several studies indicated that qualitative information such as user's reviews on the items may contribute to measure these similarities more accurately. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's reviews can be regarded as the informative source for identifying user's preference with accuracy. Under this background, this study proposes a new hybrid recommender system that combines with users' review mining. Our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and his/her text reviews on the items when calculating similarities between users. In specific, our system creates not only user-item rating matrix, but also user-item review term matrix. Then, it calculates rating similarity and review similarity from each matrix, and calculates the final user-to-user similarity based on these two similarities(i.e. rating and review similarities). As the methods for calculating review similarity between users, we proposed two alternatives - one is to use the frequency of the commonly used terms, and the other one is to use the sum of the importance weights of the commonly used terms in users' review. In the case of the importance weights of terms, we proposed the use of average TF-IDF(Term Frequency - Inverse Document Frequency) weights. To validate the applicability of the proposed system, we applied it to the implementation of a recommender system for smartphone applications (hereafter, app). At present, over a million apps are offered in each app stores operated by Google and Apple. Due to this information overload, users have difficulty in selecting proper apps that they really want. Furthermore, app store operators like Google and Apple have cumulated huge amount of users' reviews on apps until now. Thus, we chose smartphone app stores as the application domain of our system. In order to collect the experimental data set, we built and operated a Web-based data collection system for about two weeks. As a result, we could obtain 1,246 valid responses(ratings and reviews) from 78 users. The experimental system was implemented using Microsoft Visual Basic for Applications(VBA) and SAS Text Miner. And, to avoid distortion due to human intervention, we did not adopt any refining works by human during the user's review mining process. To examine the effectiveness of the proposed system, we compared its performance to the performance of conventional CF system. The performances of recommender systems were evaluated by using average MAE(mean absolute error). The experimental results showed that our proposed system(MAE = 0.7867 ~ 0.7881) slightly outperformed a conventional CF system(MAE = 0.7939). Also, they showed that the calculation of review similarity between users based on the TF-IDF weights(MAE = 0.7867) leaded to better recommendation accuracy than the calculation based on the frequency of the commonly used terms in reviews(MAE = 0.7881). The results from paired samples t-test presented that our proposed system with review similarity calculation using the frequency of the commonly used terms outperformed conventional CF system with 10% statistical significance level. Our study sheds a light on the application of users' review information for facilitating electronic commerce by recommending proper items to users.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.417-428
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• 2005

Today, IT organizations perform projects with vision related to marketing and financial profit. The objective of realizing the vision is to improve the project performing ability in terms of QCD. Organizations have made a lot of efforts to achieve this objective through process improvement. Large companies such as IBM, Ford, and GE have made over $80\%$ of success through business process re-engineering using information technology instead of business improvement effect by computers. It is important to collect, analyze and manage the data on performed projects to achieve the objective, but quantitative measurement is difficult as software is invisible and the effect and efficiency caused by process change are not visibly identified. Therefore, it is not easy to extract the strategy of improvement. This paper measures and analyzes the project performance, focusing on organizations' external effectiveness and internal efficiency (Qualify, Delivery, Cycle time, and Waste). Based on the measured project performance scores, an OT (Opportunity Tree) model was designed for optimizing the project performance. The process of design is as follows. First, meta data are derived from projects and analyzed by quantitative GQM(Goal-Question-Metric) questionnaire. Then, the project performance model is designed with the data obtained from the quantitative GQM questionnaire and organization's performance score for each area is calculated. The value is revised by integrating the measured scores by area vision weights from all stakeholders (CEO, middle-class managers, developer, investor, and custom). Through this, routes for improvement are presented and an optimized improvement method is suggested. Existing methods to improve software process have been highly effective in division of processes' but somewhat unsatisfactory in structural function to develop and systemically manage strategies by applying the processes to Projects. The proposed OT model provides a solution to this problem. The OT model is useful to provide an optimal improvement method in line with organization's goals and can reduce risks which may occur in the course of improving process if it is applied with proposed methods. In addition, satisfaction about the improvement strategy can be improved by obtaining input about vision weight from all stakeholders through the qualitative questionnaire and by reflecting it to the calculation. The OT is also useful to optimize the expansion of market and financial performance by controlling the ability of Quality, Delivery, Cycle time, and Waste.

• Journal of Oral Medicine and Pain
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• v.33 no.1
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• pp.41-48
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• 2008

The focus of this study is to analyze the effect of stress on the health of bruxism patients using the MBTI system. The most common personality type will be identified among the bruxism patients and by understanding their personality & their handling of stress, more comprehesive and effective treatment plan can be constructed. The study will also conclude that the type of personality has big effect on the cause of bruxism, and that this will be considered in the treatment plan in this hospital. The result of the study is as follow. First, more bruxism patients were type I than type E. It can be suggested that this result is due to the introversive people maintaining their energy how within themselves, and private are less to likely to release there stress than the expressive people. Second, among the bruxism patients significantly more type T were found compared to type F. This implies the bruxism tend to follow principals, scientific and analysing during decision making rather than basing their decision an meanings, emotions and influences. Thirdly, more bruxism patients clarified into ST in comparison to non-bruxism patients. This is thought to be due to probable increased stress and anxiety following ST people's tendency to more strict and realistic thinking according to effectiveness, evidence-based and productivity. Fourth, the type IJ was the most of the bruxism patients. We can come to the conclusion that decision-oriented introversion people who have hard to change, a thoroughgoing preparation characters are likely to grind their teeth by their detailed characters. Fifth, the type IT was the most of the bruxism patients. Bruxism patients are usually influenced by spirit, easily hearted, awed of relationship and attention. So, their intensity of stress is much bigger because of their personality. The last, Type IS was the most of the bruxism patients. It means that introvert sensitive types who have characters of calm, passive but defence to other's emotion, also neutral, keep moderation, and have cold-heartedness are likely to grind their teeth frequently. In conclusion it is evident that bruxism patients have particular personality types. Precisive, analysing and introversive bruxism patients are expected to have higher sensitivities to stress.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.117-137
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• 2009

Recently, intelligent traffic information systems have enabled people to forecast traffic conditions before hitting the road. These convenient systems operate on the basis of data reflecting current road and traffic conditions as well as distance-based data between locations. Thanks to the rapid development of ubiquitous computing, tremendous context data have become readily available making vehicle route planning easier than ever. Previous research in relation to optimization of vehicle route planning merely focused on finding the optimal distance between locations. Contexts reflecting the road and traffic conditions were then not seriously treated as a way to resolve the optimal routing problems based on distance-based route planning, because this kind of information does not have much significant impact on traffic routing until a a complex traffic situation arises. Further, it was also not easy to take into full account the traffic contexts for resolving optimal routing problems because predicting the dynamic traffic situations was regarded a daunting task. However, with rapid increase in traffic complexity the importance of developing contexts reflecting data related to moving costs has emerged. Hence, this research proposes a framework designed to resolve an optimal route planning problem by taking full account of additional moving cost such as road traffic cost and weather cost, among others. Recent technological development particularly in the ubiquitous computing environment has facilitated the collection of such data. This framework is based on the contexts of time, traffic, and environment, which addresses the following issues. First, we clarify and classify the diverse contexts that affect a vehicle's velocity and estimates the optimization of moving cost based on dynamic programming that accounts for the context cost according to the variance of contexts. Second, the velocity reduction rate is applied to find the optimal route (shortest path) using the context data on the current traffic condition. The velocity reduction rate infers to the degree of possible velocity including moving vehicles' considerable road and traffic contexts, indicating the statistical or experimental data. Knowledge generated in this papercan be referenced by several organizations which deal with road and traffic data. Third, in experimentation, we evaluate the effectiveness of the proposed context-based optimal route (shortest path) between locations by comparing it to the previously used distance-based shortest path. A vehicles' optimal route might change due to its diverse velocity caused by unexpected but potential dynamic situations depending on the road condition. This study includes such context variables as 'road congestion', 'work', 'accident', and 'weather' which can alter the traffic condition. The contexts can affect moving vehicle's velocity on the road. Since these context variables except for 'weather' are related to road conditions, relevant data were provided by the Korea Expressway Corporation. The 'weather'-related data were attained from the Korea Meteorological Administration. The aware contexts are classified contexts causing reduction of vehicles' velocity which determines the velocity reduction rate. To find the optimal route (shortest path), we introduced the velocity reduction rate in the context for calculating a vehicle's velocity reflecting composite contexts when one event synchronizes with another. We then proposed a context-based optimal route (shortest path) algorithm based on the dynamic programming. The algorithm is composed of three steps. In the first initialization step, departure and destination locations are given, and the path step is initialized as 0. In the second step, moving costs including composite contexts into account between locations on path are estimated using the velocity reduction rate by context as increasing path steps. In the third step, the optimal route (shortest path) is retrieved through back-tracking. In the provided research model, we designed a framework to account for context awareness, moving cost estimation (taking both composite and single contexts into account), and optimal route (shortest path) algorithm (based on dynamic programming). Through illustrative experimentation using the Wilcoxon signed rank test, we proved that context-based route planning is much more effective than distance-based route planning., In addition, we found that the optimal solution (shortest paths) through the distance-based route planning might not be optimized in real situation because road condition is very dynamic and unpredictable while affecting most vehicles' moving costs. For further study, while more information is needed for a more accurate estimation of moving vehicles' costs, this study still stands viable in the applications to reduce moving costs by effective route planning. For instance, it could be applied to deliverers' decision making to enhance their decision satisfaction when they meet unpredictable dynamic situations in moving vehicles on the road. Overall, we conclude that taking into account the contexts as a part of costs is a meaningful and sensible approach to in resolving the optimal route problem.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.39-58
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• 2014

As the importance of big data and related technologies continues to grow in the industry, it has become highlighted to visualize results of processing and analyzing big data. Visualization of data delivers people effectiveness and clarity for understanding the result of analyzing. By the way, visualization has a role as the GUI (Graphical User Interface) that supports communications between people and analysis systems. Usually to make development and maintenance easier, these GUI parts should be loosely coupled from the parts of processing and analyzing data. And also to implement a loosely coupled architecture, it is necessary to adopt design patterns such as MVC (Model-View-Controller) which is designed for minimizing coupling between UI part and data processing part. On the other hand, big data can be classified as structured data and unstructured data. The visualization of structured data is relatively easy to unstructured data. For all that, as it has been spread out that the people utilize and analyze unstructured data, they usually develop the visualization system only for each project to overcome the limitation traditional visualization system for structured data. Furthermore, for text data which covers a huge part of unstructured data, visualization of data is more difficult. It results from the complexity of technology for analyzing text data as like linguistic analysis, text mining, social network analysis, and so on. And also those technologies are not standardized. This situation makes it more difficult to reuse the visualization system of a project to other projects. We assume that the reason is lack of commonality design of visualization system considering to expanse it to other system. In our research, we suggest a common information model for visualizing text data and propose a comprehensive and reusable framework, TexVizu, for visualizing text data. At first, we survey representative researches in text visualization era. And also we identify common elements for text visualization and common patterns among various cases of its. And then we review and analyze elements and patterns with three different viewpoints as structural viewpoint, interactive viewpoint, and semantic viewpoint. And then we design an integrated model of text data which represent elements for visualization. The structural viewpoint is for identifying structural element from various text documents as like title, author, body, and so on. The interactive viewpoint is for identifying the types of relations and interactions between text documents as like post, comment, reply and so on. The semantic viewpoint is for identifying semantic elements which extracted from analyzing text data linguistically and are represented as tags for classifying types of entity as like people, place or location, time, event and so on. After then we extract and choose common requirements for visualizing text data. The requirements are categorized as four types which are structure information, content information, relation information, trend information. Each type of requirements comprised with required visualization techniques, data and goal (what to know). These requirements are common and key requirement for design a framework which keep that a visualization system are loosely coupled from data processing or analyzing system. Finally we designed a common text visualization framework, TexVizu which is reusable and expansible for various visualization projects by collaborating with various Text Data Loader and Analytical Text Data Visualizer via common interfaces as like ITextDataLoader and IATDProvider. And also TexVisu is comprised with Analytical Text Data Model, Analytical Text Data Storage and Analytical Text Data Controller. In this framework, external components are the specifications of required interfaces for collaborating with this framework. As an experiment, we also adopt this framework into two text visualization systems as like a social opinion mining system and an online news analysis system.

• Archives of design research
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• v.18 no.3 s.61
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• pp.129-138
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• 2005

It has been assumed that the clarification of a message is a necessary element for successful communication. However, in the today's complicated and changing environment of business marketing media, it is shown that the clarification of the message of advertisement may inhibit the effectiveness of communication. This study was to examine what was effective communication in advertisement when the company, provoking the people's negative emotional response, needs to establish new identities such as the goals and the special fields of business. In particular, the study was to investigate what effect the advertising strategy of strategically emitting ambiguous messages makes on the consumer's recognition, emotional attitude, reliability, and attitude towards the company. It was hypothesized that an ambiguous message in an advertisement has an effect on the consumer's recognition, emotional attitude, reliability, and attitude towards the company. Three texts from the 'Imagination Praises' campaign of KT&G which has been in process since 2003 were systematically sampled and the survey was performed by the means of questionnaires made on the sample The results showed that the ambiguous message of advertising texts gained better responses on the consumer's attention, good impression, affirmation, memory, sympathy than the dear message and that the ambiguous message had an effect on the consumer's attitude towards the advertisement itself. Thus, it could be tentatively concluded that the ambiguous message could be more effective in recognition and recall to promote the changes of identities of the company having the people's unfavorable emotion. But there wasn't any evidence that an ambiguous message in an advertisement was more effective in terms of the consumer's emotional response, reliability, and attitude towards the company. From this, it could be inferred that the receiver had an uncomfortable, doubtful and negative attitude about the implicit expressive code contained in the message. In the future deeper qualitative studies can compensate for the limited explanation of this empirical study focused on statistical analyses.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.121-145
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• 2010

University timetabling depending on the educational environments of universities is an NP-hard problem that the amount of computation required to find solutions increases exponentially with the problem size. For many years, there have been lots of studies on university timetabling from the necessity of automatic timetable generation for students' convenience and effective lesson, and for the effective allocation of subjects, lecturers, and classrooms. Timetables are classified into a course timetable and an examination timetable. This study focuses on the former. In general, a course timetable for liberal arts is scheduled by the office of academic affairs and a course timetable for major subjects is scheduled by each department of a university. We found several problems from the analysis of current course timetabling in departments. First, it is time-consuming and inefficient for each department to do the routine and repetitive timetabling work manually. Second, many classes are concentrated into several time slots in a timetable. This tendency decreases the effectiveness of students' classes. Third, several major subjects might overlap some required subjects in liberal arts at the same time slots in the timetable. In this case, it is required that students should choose only one from the overlapped subjects. Fourth, many subjects are lectured by same lecturers every year and most of lecturers prefer the same time slots for the subjects compared with last year. This means that it will be helpful if departments reuse the previous timetables. To solve such problems and support the effective course timetabling in each department, this study proposes a university timetabling support system based on two phases. In the first phase, each department generates a timetable template from the most similar timetable case, which is based on case-based reasoning. In the second phase, the department schedules a timetable with the help of interactive user interface under the timetabling criteria, which is based on rule-based approach. This study provides the illustrations of Hanshin University. We classified timetabling criteria into intrinsic and extrinsic criteria. In intrinsic criteria, there are three criteria related to lecturer, class, and classroom which are all hard constraints. In extrinsic criteria, there are four criteria related to 'the numbers of lesson hours' by the lecturer, 'prohibition of lecture allocation to specific day-hours' for committee members, 'the number of subjects in the same day-hour,' and 'the use of common classrooms.' In 'the numbers of lesson hours' by the lecturer, there are three kinds of criteria : 'minimum number of lesson hours per week,' 'maximum number of lesson hours per week,' 'maximum number of lesson hours per day.' Extrinsic criteria are also all hard constraints except for 'minimum number of lesson hours per week' considered as a soft constraint. In addition, we proposed two indices for measuring similarities between subjects of current semester and subjects of the previous timetables, and for evaluating distribution degrees of a scheduled timetable. Similarity is measured by comparison of two attributes-subject name and its lecturer-between current semester and a previous semester. The index of distribution degree, based on information entropy, indicates a distribution of subjects in the timetable. To show this study's viability, we implemented a prototype system and performed experiments with the real data of Hanshin University. Average similarity from the most similar cases of all departments was estimated as 41.72%. It means that a timetable template generated from the most similar case will be helpful. Through sensitivity analysis, the result shows that distribution degree will increase if we set 'the number of subjects in the same day-hour' to more than 90%.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.33-53
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• 2021

In the crossroads of social change caused by the spread of the Fourth Industrial Revolution and the prolonged COVID-19, the Korean government announced the Digital New Deal policy on July 14, 2020. The Digital New Deal policy's primary goal is to create new businesses by accelerating digital transformation in the public sector and industries around data, networks, and artificial intelligence technologies. However, in a rapidly changing social environment, information asymmetry of the future benefits of technology can cause differences in the public's ability to analyze the direction and effectiveness of policies, resulting in uncertainty about the practical effects of policies. On the other hand, the media leads the formation of discourse through communicators' role to disseminate government policies to the public and provides knowledge about specific issues through the news. In other words, as the media coverage of a particular policy increases, the issue concentration increases, which also affects public decision-making. Therefore, the purpose of this study is to verify the dynamic relationship between the media coverage and the stock market on the Korean government's digital New Deal policy using Granger causality, impulse response functions, and variance decomposition analysis. To this end, the daily stock turnover ratio, daily price-earnings ratio, and EWMA volatility of digital technology-based companies related to the digital new deal policy among KOSDAQ listed companies were set as variables. As a result, keyword search volume, daily stock turnover ratio, EWMA volatility have a bi-directional Granger causal relationship with media coverage. And an increase in media coverage has a high impact on keyword search volume on digital new deal policies. Also, the impulse response analysis on media coverage showed a sharp drop in EWMA volatility. The influence gradually increased over time and played a role in mitigating stock market volatility. Based on this study's findings, the amount of media coverage of digital new deals policy has a significant dynamic relationship with the stock market.

• The Korean Journal of Air & Space Law and Policy
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• v.34 no.1
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• pp.3-38
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• 2019

In 1984, Congress enacted a new measure of administrative sanctions which is a civil money penalty program for violations of Aviation Act and its implementing regulations. This civil money penalty system has been in operations in lieu of suspending or revoking certificates issued by Korean government, Ministry of Land, Infrastructure, and Transport. According to the rules of Aviation Business Act or Aviation Safety Act, where the Minister of Land, Infrastructure and Transport should order an air carrier to suspend operation because of her violation under certain rules, in which case the suspension of operation is likely to cause serious inconvenience to consumers of air transport services or to harm public interest, the Minister of the department may impose an administrative monetary penalty in lieu of the suspension of operation. In this regard, airline related civil money penalties are somewhat different from those of fair trade, which is the origin of the money penalties system in Korea. Civil money penalties in the field of fair trade are imposed on executive duty violations that undermine the value of the market economy order, and focus on reimbursement of profits due to violations and compensation for unfair spending by consumers. However, in the aviation sector, breach of duty by a business operator does not simply cause the property loss of the public, but it has a direct impact on life or property of the public. In this respect, aviation penalties are more likely to be administrative sanctions or punitive measures than refunds of unfair benefits, compared to penalties in the field of fair trade. In general, civil money penalties have been highly preferred as administrative sanctions because they are subject to investigations by administrative experts and thus, efficiency can be ensured and execution is quicker than judicial procedures. Moreover, in Korea, because punitive civil damages cannot awarded by the courts, the imposition of civil money penalties is recognized as a means of realizing social justice by recognizing the legal feelings of the people. However, civil money penalties are administrative sanctions, and in terms of effectiveness, they are similar to criminal fines, which are a form of punishment. Inadequate legislation and operation of penalties imposition may cause damage to the value of Constitution. Under the above recognition, this paper has been described for the purpose of identifying the present status of the civil money penalties imposition system and operating status in the area of air transport under the laws and regulations in Korea. Especially, this paper was focused on exploring the problem and improvement direction of Korean system through the comparative study with foreign laws and regulations.