• Journal of Intelligence and Information Systems
• /
• v.21 no.2
• /
• pp.19-47
• /
• 2015

In this era of knowledge economy, a variety of virtual communities are proliferating for the purpose of knowledge creation and utilization. Since the voluntary contributions of members are the essential source of knowledge, member turnover can have significant implications on the survival and success of virtual communities. However, there is a dearth of research on the effect of membership turnover and even the method of measurement for membership turnover is left unclear in virtual communities. In a traditional context, membership turnover is calculated as the ratio of the number of departing members to the average number of members for a given time period. In virtual communities, while the influx of newcomers can be clearly measured, the magnitude of departure is elusive since explicit withdrawals are seldom executed. In addition, there doesn't exist a common way to determine the average number of community members who return and contribute intermittently at will. This study initially examines the limitations in applying the concept of traditional turnover to virtual communities, and proposes five membership fluidity measures based on a preliminary analysis of editing behaviors of 2,978 featured articles in English Wikipedia. Subsequently, this work investigates the relationships between three selected membership fluidity measures and group collaboration performance, reflecting a moderating effect dependent on work characteristic. We obtained the following results: First, membership turnover relates to collaboration efficiency in a right-shortened U-shaped manner, with a moderating effect from work characteristic; given the same turnover rate, the promotion likelihood for a more professional task is lower than that for a less professional task, and the likelihood difference diminishes as the turnover rate increases. Second, contribution period relates to collaboration efficiency in a left-shortened U-shaped manner, with a moderating effect from work characteristic; the marginal performance change per unit change of contribution period is greater for a less professional task. Third, the number of new participants per month relates to collaboration efficiency in a left-shortened reversed U-shaped manner, for which the moderating effect from work characteristic appears to be insignificant.

• Journal of Intelligence and Information Systems
• /
• v.17 no.4
• /
• pp.193-212
• /
• 2011

Mobile instant messaging service is surfacing to an important keyword in the mobile market together with popularization of Smart phones. Mobile instant messaging service in Korea has become popular to the degree of 87.9% usages from total Smartphone holders, and it is expected that using populations will be more enlarged afterwards if considering a fact that its populations of Smartphone is continuously being increased after exceeding 10 million persons (Trend Monitor, June 2011). In the instant messaging market where competitions have been deepened day by day, raising customer's royalties will be the key for company's business survivals and goals of corporate marketing strategies. It could be said that understanding on which factors affect to customer retentions and royalties is very important. Specially, as changing status is being progressed very quickly in case of innovative mobile services like the instant messaging service, research necessities on how many do consumers use the services after accepting them, how much do consumers use them variously, and whether does it connect to long-term relations have been increased, but studies on such matters are in insufficient situations actually. Therefore, this study examined on which effects were affected to use-diffusion and loyalty factors from perceived customer vales' factors having been occurred after accepting the mobile instant messaging service, namely 'functional value', 'monetary value', 'emotional value', and 'social value'. Also, the study looked into what kind of roles do the service usage and using variety play to service's continued using intents as a loyalty index, recommending intents to others, and brand switching intents. And then the study laid the main purpose in trying to provide implications for enhancing customer securities and royalties on the mobile instant messaging service through research's results. The research hypotheses are as follows; H1: Perceived values will affect influences to royalties. H2: Use-Diffusion will affect influences to loyalty. H3: Perceived value will affect influences to loyalty. H4: The use-diffusion will play intermediating roles between perceived values and loyalty. Total 276 cases among collected 284 ones were used for the statistical analysis by SPSS ver. 15 package. Reliability, Factor analysis, regression were done. As the result of research, 'monetary value' and 'emotional value' affected to 'usage' among perceived value factors, and 'emotional value' was appeared as affecting the largest influence. Besides, the usage affected to constant-using intents and recommending intents to others, and using varieties were displayed as affecting to recommending intents to others. On the other hand, 'Using' and 'Using diversity' were appeared as not affecting to 'brand switching intentions'. Meanwhile, as the result of recognizing about effects of perceived values on the loyalty, it was appeared such like 'continued using intents' affected to'functional value', 'monetary value', and 'social value' first, and also 'monetary value', 'emotional value', and 'social value' affected to 'recommending intents to others'. On the other hand, it was shown such like only 'social value' affected influences to 'brand switching intents', and thus contrary results with the factor 'constant-using intents' were displayed. So, it seems that there are many applications to service provides who are worrying about marketing strategies for making consumer retains (constant-using) and new consumer's inductions (brand-switching intents). Finally, as a result of looking into intermediating roles of the use-diffusion factor in relations between conceived values and royalties at hypothesis 4, 'using' and 'using diversity' were displayed as affecting significant influences all together. Regarding to research result's implications, for expanding and promoting continued uses of the mobile instant messaging service by service providers: First, encouraging recognitions on the perceived value connected to users' service usage are necessary. Second, setting up user's use-diffusion strategies are required so as to enhance the loyalty after understanding a fact that use-diffusion patterns affecting to the service's loyalty are different. Finally, methods of raising customer loyalties and making constant relationships have to be grouped by analyzing on what are the customer value's factors that can satisfy users in competitive alterations.

• Korean journal of communication and information
• /
• v.81
• /
• pp.153-186
• /
• 2017

The purpose of this study was to identify the characteristics of village community media in Jeju by looking at the value that it's participants have experienced in the production process. Therefore, this study focused on the creation and production process of village community media, the specific value reflected in this process as well as how to activate and operate it sustainably through in-depth interviews with 12 media participants in Jeju community. As a result of the analysis, firstly, we were able to see that the migrants who are not the indigenous became the center of village community media creation in Jeju and they felt very personal 'fun', 'enthusiasm' and 'satisfaction'. It was also completely open to access and participate in village community media and its contents were filled with stories of everyday life of village residents and hidden stories of old people in the village that were not recorded. The characteristic of the production process of village community media was the horizontal communication and it reflected well the opinions of individual media participants even if it had a joint meeting. Second, as a result of examining the values applied to the production process by village community media participants, they regarded the connection of communication by voluntary participation and restoration of communities through activation of communication in functionalism as an important value. Finally, as a result of examining the challenges and development plans for sustainable management of community media in Jeju, it was required the active participation of village residents, ensuring space for village community media, providing insufficient broadcasting equipment, and the budget support from local governments, etc. It was once again confirmed that the provision of a support system for the stable activities of local governments is an urgent task for sustainable village community media.

• Journal of the Korean earth science society
• /
• v.31 no.4
• /
• pp.392-402
• /
• 2010

The purpose of this study is to analyze and evaluate the self-directed learning contents of Earth science area in the basic course of the 7th grade. For this purpose, we applied the 'Cyber Home Study Content Quality Control Tool' presented in 'Elementary Secondary Education e-Learning Quality Management Guidelines (Ver.2.0)' of Korea Education & Research Information Service (2008). The results of contents analysis are as follow: First, it was presented that the study guide introduced the contents which should be studied for one class, properly. And it was not analyzed that the diagnosis assesment was not completed in the initiative study; Second, it was possible to study choosing the contents fitting the learner's level of learning in the main study, it was comprised of about 15 minutes. Third, it was performed without feedback for incorrect answers in the learning assessment, just the number of wrong questions. And the learning arrangement present the important contents learned in that class, summarizing and arranging again. The results of content evaluation are as follows: First, a big difference was not showed against the needs analysis, instructional design, interaction in each class. And the evaluation of the ethics was not included a word or sentence not suitable. The evaluation of copyright, it was analyzed that Work within the content display in compliance with international copyright Second, the evaluation of instructional design presented mainly the description of a simple picture based, the visible resources like flash card were poor. And in the evaluation of Supporting System, it was presented that the contents were installed so that it was freely available for learners. But it was analyzed that there was no memo-function learners were able to jot down something during the studying contents. And in the evaluation for evaluation, the clear valuation basis about the described content was not presented. So there were slightly differences for each class. Third, in the evaluation and analysis for learning content, it was presented that there were some big differences for each class because it was not composed of the latest information, not corrected and complementary.

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

• Journal of the Society of Disaster Information
• /
• v.16 no.1
• /
• pp.178-191
• /
• 2020

Purpose: This paper proposes a performance evaluation method for state-of-the-art facility inspection/diagnostic equipment through a trend survey of equipment and standardization systems of US, Japan, and Korea. This paper also suggests the priority of developing a performance evaluation method through expert interviews and surveys. Method: In this study, report for the last 5 years of FMS, state-of-the-art equipment of facility maintenance companies/safety diagnosis specialist agencies and papers/research reports/patents of NTIS were analyzed to identify recent trends of facility inspection/diagnostic equipment usages. standardization system of US, Japan, and Korea were analyzed to figure out a suitable form of a performance evaluation method for the domestic situation. And expert interview and survey were conducted to identify the priority of developing a performance evaluation method. Result: The performance evaluation method must be developed by the shape that only evaluates performance, regardless of types of equipment, on inspection item level for creative technology development. The priority of developing the performance evaluation method was identified as crack detection of concrete for durability evaluation and displacement/deformation/fatigue detection of concrete and steel for stability evaluation. Conclusion: The performance evaluation method will be developed firstly for the crack detection of concrete for durability evaluation and displacement/deformation/fatigue detection of concrete/steel for stability evaluation. In order to promote creative technology development, the performance evaluation method should be developed in a form that provides standardized specimens or testbeds and can be applied regardless of types of technologies.

• Journal of Intelligence and Information Systems
• /
• v.19 no.4
• /
• pp.97-121
• /
• 2013

With the growing importance of knowledge for sustainable competitive advantages and innovation in a volatile environment, many researches on knowledge sharing have been conducted. However, previous researches have mostly relied on the questionnaire survey which has inherent perceptive errors of respondents. The current research has drawn the relationship among primary participant behaviors towards the participation level in knowledge sharing, basically from online user behaviors on Wikipedia, a representative community for online knowledge collaboration. Without users' participation in knowledge sharing, knowledge collaboration for creating knowledge cannot be successful. By the way, the editing patterns of Wikipedia users are diverse, resulting in different revisiting periods for the same number of edits, and thus varying results of shared knowledge. Therefore, we illuminated the participation level of knowledge sharing from two different angles of number of edits and revisiting period. The behavioral dimensions affecting the level of participation in knowledge sharing includes the article talk for public discussion and user talk for private messaging, and community registration, which are observable on Wiki platform. Public discussion is being progressed on article talk pages arranged for exchanging ideas about each article topic. An article talk page is often divided into several sections which mainly address specific type of issues raised during the article development procedure. From the diverse opinions about the relatively trivial things such as what text, link, or images should be added or removed and how they should be restructured to the profound professional insights are shared, negotiated, and improved over the course of discussion. Wikipedia also provides personal user talk pages as a private messaging tool. On these pages, diverse personal messages such as casual greetings, stories about activities on Wikipedia, and ordinary affairs of life are exchanged. If anyone wants to communicate with another person, he or she visits the person's user talk page and leaves a message. Wikipedia articles are assessed according to seven quality grades, of which the featured article level is the highest. The dataset includes participants' behavioral data related with 2,978 articles, which have reached the featured article level, with editing histories of articles, their article talk histories, and user talk histories extracted from user talk pages for each article. The time period for analysis is from the initiation of articles until their promotion to the featured article level. The number of edits represents the total number of participation in the editing of an article, and the revisiting period is the time difference between the first and last edits. At first, the participation levels of each user category classified according to behavioral dimensions have been analyzed and compared. And then, robust regressions have been conducted on the relationships among independent variables reflecting the degree of behavioral characteristics and the dependent variable representing the participation level. Especially, through adopting a motivational theory adequate for online environment in setting up research hypotheses, this work suggests a theoretical framework for the participation level of online knowledge sharing. Consequently, this work reached the following practical behavioral results besides some theoretical implications. First, both public discussion and private messaging positively affect the participation level in knowledge sharing. Second, public discussion exerts greater influence than private messaging on the participation level. Third, a synergy effect of public discussion and private messaging on the number of edits was found, whereas a pretty weak negative interaction effect of them on the revisiting period was observed. Fourth, community registration has a significant impact on the revisiting period, whereas being insignificant on the number of edits. Fifth, when it comes to the relation generated from private messaging, the frequency or depth of relation is shown to be more critical than the scope of relation for the participation level.

• Journal of Intelligence and Information Systems
• /
• v.21 no.1
• /
• pp.29-45
• /
• 2015

Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.