• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.12 s.159
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• pp.1697-1707
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• 2006

Relentless advances in information technology are constantly transforming market dynamics of the retail industry. RFID is an emerging innovative technology that can reduce labor costs, improve inventory control and increase sales by effective business processes. Apparel retailers need to recognize the benefits of RFID and identify critical success factors. By focusing on apparel retailers, this study attempts (1) to identify the reality of RFID associated with benefits; and (2) to prospect the implementation of RFID in apparel retailing. We conducted a focus group interview with selected six panels who were experts of retail industry in the United States to obtain data regarding RFID attributes. Content analysis was used to generate related excerpts and classify 31 attributes of RFID benefits from the meaningful 173 responses. For experience of RFID, retailers were familiar with RFID technology and expressed the belief that RFID basically would support an existing retail system for speed to markets. However, retailers addressed the level of experience with RFID technology that they were still in the early adoption stage among few innovative companies. The content analysis identified five dimensions of RFID benefits for apparel retailing: Visibility and Velocity, Revenue Enhancement, Customer Service, Security, and Employee Productivity. This result lends support to the belief that RFID has a significant potential to streamline supply chain management, store operation and customer service for apparel retailing. This study provides intellectual and managerial implications far practitioners and researchers by postulating the effective use of RFID in the apparel retail industry.

• Journal of Food Hygiene and Safety
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• v.16 no.1
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• pp.66-75
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• 2001

A survey was conducted to investigate consumers'attitudes toward the foods developed by gene recombination techniques from December, 1999 to April, 2000. The questionnaires were mailed to 1,500 people, and the 1,101 people responded. The consumers were asked about knowledge, acceptance, intention of purchasing, and labeling information. Although the portion of the consumers (88.8%) knowing the genetically modified floods (GMF) was lower than that of the flood expert group (98.7%), many consumers had some knowledge on the GMF, which may be influenced by news released from mass media. Seventy-nine percent of the consumers responded that gene recombination technology is necessary in food production, which is similar to the findings on the survey of the expert group. The portion of the consumers responding that these foods are potentially hazard was 88.1%, which is a little higher than the data (80.9%) from the expert group. The consumers having greater knowledge less worried about a potential hazard of the gene recombinant foods (p<0.01). Although 62.9% of the consumers responded to be willing to purchase those foods, only 16.2% of them responded to purchase the foods with no conditions, which is lower to that from the expert group (23.5%). There was no statistically significant relationship between the knowledge and the intention of purchasing. The ninety point three percent of the consumers wanted the information on gene recombination to be labeled on the foods. The data from this survey suggest that knowledge of the consumers on the GMF are not accurate, so proper strategy for consumer education may need to be developed. In addition, it is necessary to improve safety assessment system and analytical techniques for genetically modified foods (GMF) and to build pre- and post-market surveillance system fur efficient implementation of the GMF labeling.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• 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.

• Management & Information Systems Review
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• v.33 no.5
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• pp.185-212
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• 2014

This study investigated the base of marine leisure facilities and studied the future vision for development of marine industry by conducting a systematic analysis on the category of marine leisure products for development of design and specialization of southeast area of Korea. If the age of $20,000 of per capita national income is called 'the age of my car', $20,000 of per capita national income is called 'the age of my boat'. According to the report of UK-based Marine South East, the scale of world's small boat and personal waterborne equipment reached 277 trillion won in 2010 and domestic market scale is expected to be 11 trillion won. Marine leisure facilities are the new growth engine industry that the government should promote as a nation's strategic and core industry, and the government is pushing ahead with promotion of marine industry actively by announcing Marine Leisure Equipment Industry Activation Plan(June 2009, Ministry of Knowledge Economy), Marine Leisure Activation Plan(July 2010, Ministry of Land, Infrastructure and Transport), The 1st General Plan for Marina Port(January 2010, Ministry of Land, Infrastructure and Transport) etc. The purpose of marine design lies in seeking the status of the country and qualitative value in human life through functional, artistic, industrial and cultural development of design elements for all marine activities made around the sea. Related to all activities made in the ocean and cost, marine design is a sphere of design that includes special conditions centering around water. Considering the condition that 3 sides of land are facing the sea, this study systematically analyzed present condition of equipment possessed by each area, type of facilities, operational status, current status of sectoral use of marine leisure facilities and future prospect of marine leisure products that become the basis of value to raise the statue as an advanced marine power in 2010s through development of the qualitative level of the people, establishment of the direction of national strategy, convergence of industry and culture and specialization of area focusing on the actual condition survey of marine leisure facilities. Especially, this study will be predicting the basis of strategy for strengthening marketability and competitiveness by suggesting role and process of design in developing a promising marine leisure product through an actual condition survey of marine leisure products of southeast area.

• Management & Information Systems Review
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• v.37 no.1
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• pp.103-122
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• 2018

This paper expands the results of previous studies indicating that manager's ability positively affects business performance to analyze whether the degree to which the role of manager's ability improves business performance appears differently according to the characteristics of enterprises. As for the characteristics of enterprises, whether enterprises correspond to enterprises with high levels of funding constraints or late movers in the market is considered. Enterprises with high levels of funding constraints greatly require managers' roles not only for efficient use of funds but also for smooth financing. Late movers require more judgments of professional managers to overcome insufficient resources held and low profitability. In the case of enterprises with corporate characteristics with high dependency on the manager, the business performance is expected to greatly vary with the ability of the manager. The empirical analysis was conducted with listed companies from 2010 to 2014, manager's ability was measured by first measuring the efficiency of the entire enterprise through data envelopment analysis (DEA) using the methodology of Demerjian et al.(2012) and removing enterprise characteristics factors thereafter. Business performance was measured by the return on industrial fixed assets. The results of the empirical analysis indicated that the degree to which manager's ability improves business performance was higher in managerial competence enhances managerial performance in enterprises with high levels of funding constraints and late movers. Business performance is considered to have been improved further in cases where manager's ability is high because investments were made more efficiently through smooth funding. In addition, in the case of late movers in relatively poor environments, business performance was improved further because high manager's ability induced efficient decision making. In this paper, we extend the precedent study that the manager's ability improves the management performance, and confirm that the manager's ability to improve the managerial performance can be different according to the situation of the company. In addition, it is meaningful to analyze empirically whether a company's managerial ability is more important. This paper expanded the results of previous studies indicating that manager's ability improves performance to identify that the degree to which manager's ability improves business performance may appear differently according to situations in which enterprises are placed. In addition, this paper is meaningful in that it empirically analyzed what enterprises require manager's ability more importantly.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.2
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• pp.201-219
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• 2014

The Republic of Korea in the real economy to a knowledge economy, and a center of creativity and imagination in the creative economy is changing the paradigm. As the core of creating economic, creative industries with the technology and information play an important role in the industry individuals. In order to solve the problem of the polarization of the economy and high youth unemployment rate of Korea, to recognize the role of the creative industries, as objection part, dimensions pan-national and one creative companies in industries of Mobile Apps various policies that support has been promoted. Support these policies to be able to contribute to the establishment of the success of mobile apps one-person creating company, we performed this study targeting one-person company that creates mobile apps area, we conducted a demonstration study of success factors, and thus more effective and efficient in an attempt to seek out support measures. In this study, we derive a research 4 hypothesis about the success factors of one creative enterprise through literature discussion, a study was made on the basis of empirical data of one-person company that creates mobile apps. The results of the analysis, first, if the development rate of the mobile application technology is fast and a new competition associated product is appeared, it was possible to find a tendency to be higher at the performance quantitative companies. Second, if the founder is a founding for the benefit and rewarding work and come to terms with the risk, it was possible to discover tends to be higher achievement quantitative. Third, if one-person company select a target market with capture intensively, it was possible to find a tendency for higher qualitative results. Fourth, it could be found that the reliability of the contact frequency of the network related performance business environment these characteristics enterprise management strategy and act as a significant modulatory effect. Provision of information relating to management and entrepreneurship education to be one creative enterprise is required, these results suggest that there is a provision continuing need for the opportunity to be able to meet and network and reliable variety have. In this study, to take advantage to promote the elimination measures that can increase the likelihood of success of the company of institutions to support one company that creates knowledge-based, such as in the field of mobile application.

• Management & Information Systems Review
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• v.31 no.2
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• pp.143-172
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• 2012

While e-commerce market(B2C) grows rapidly, many experts argue that EC(B2C) transactions have not reached its full potential. A notable difference between online and offline consumer markets that is suppressing the growth of EC(B2C) is the decreased presence of human and social elements in the online shopping environments. Generally online shopping lacks human warmth and sociability. In this study, social presence in online shopping mall was proposed as a substitute for face-to-face social interaction in the traditional commerce and author explored what variables affect social presence(human warmth and sociability) on online shopping malls and how human warmth and sociability can influence on online store loyalty. To achieve research objectives, we reviewed literatures related with marketing, psychology and communication research areas. Based on literature review, we proposed a research model on the online shopping mall. To examine the proposed research model, we gathered data by using a self-report questionnaire. Respondents consists of online shoppers with at least five or more times of purchase experience in online shopping malls. Because social presence is a feeling which needs frequent contacts with malls to experience, respondents must have enough purchase experiences. The empirical results are as follows : First, shopping mall's customization efforts influence perceived social presence on the mall significantly. Second, shopping mall's responsiveness influences perceived social presence significantly. Third, perceived activity of community of online shopping mall influences perceived social presence significantly. Mall managers have to activate their customer community to reinforce social presence, resulting in trust building. Finally, perceived social presence influences trust and enjoyment on the mall significantly. And then trust and enjoyment on the mall affect store loyalty significantly. From these findings it can be inferred that perceived social presence appears determinant which is critical to the formation of core variables(trust and loyalty) in existing online shopping papers.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.95-105
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• 2013

Recently, SME's Collaboration activities have become one of a vital factor for sustaining competitive edge. This is because of the rapidly changing and competitive market environment, and also to leverage performance by overcoming obstacles of having limited internal resources. Discussing about the effects and relationships of the firm's collaboration activities and its outputs are not new. However, as ICT and various technologies have been diffused into the traditional industries, boundaries and practice capabilities within the industries are becoming ambiguous. Thus contents of the products/services and their development methods are also go and come over the industries. Although many researchers suggested the relations of SME's collaboration activities and innovation performances, most of the previous literatures are focusing on broad perspectives of firm's environmental factors rather than considering various SME's idiosyncrasy factors such as their major product and customer types at once. Therefore, the purpose of this paper is to analyze how SME(Small Medium Enterprise)'s external collaboration activities by their idiosyncrasy act as an input to types of innovation performance. In order to analyze collaboration effects in detail, we defined factors that can represent the SME's business environment - Perceived importance of using external resources, Perceived importance of external partnership, Collaboration and Collaboration levels of Major Product types, Customer types and lastly the Firm Sizes. We have also specifically divided the performance of innovation types as product innovation and process innovation based on existing research. In this study, the empirical analysis is based on Probit Regression Model to observe the correlations with the impact of each SME's business environment and their activities. For the empirical data, 497 samples were collected which, this sample data was extracted from the 'Korean Open Innovation Survey' performed by ETRI(Korean Electronics Telecommunications Research Institute) in 2010. As a result, empirical test results indicated that the impact of collaboration varies depend on the innovation types (Product and Process Innovation). The Impact of the collaboration level for the product innovation tend to be more effective when SMEs are developing for a final product, targeting on for individual customers (B2C). But on the other hand, the analysis result of the Process innovation tend to be higher than the product innovation, when SMEs are developing raw materials for their partners or to other firms targeting on for manufacturing industries(B2B). Also perceived importance of using external resources has effected to both product and process innovation performance. But Perceived importance of external partnership was statistically insignificant. Interesting finding was that the service product has negative effects on for the process innovation performance. And Relationship between size of the firms and their external collaboration activities with their performance of the innovations indicated that the bigger firms(over 100 of employees) tend to have better for both product and process innovations. Finally, implications of the results can be suggested as performance of innovation can be varied depends on firm's unique business idiosyncrasy as well as levels of external collaboration activities. The Implication of this research can be considered for firms in selecting an appropriate strategy as well as for policy makers.