• Asia pacific journal of information systems
• /
• v.23 no.2
• /
• pp.21-39
• /
• 2013

As the utilization of information technology and the turbulence of technological change increase in organizations, the adoption of IT outsourcing also grows to manage IT resource more effectively and efficiently. In this new way of IT management technique, service level management(SLM) process becomes critical to derive success from the outsourcing in the view of end users in organization. Even though much of the research on service level management or agreement have been done during last decades, the performance of the service level management process have not been evaluated in terms of final objectives of the management efforts or success from the view of end-users. This study explores the relationship between SLM maturity and IT outsourcing success from the users' point of view by a analytical case study in four client organizations under an IT outsourcing vendor, which is a member company of a major Korean conglomerate. For setting up a model for the analysis, previous researches on service level management process maturity and information systems success are reviewed. In particular, information systems success from users' point of view are reviewed based the DeLone and McLean's study, which is argued and accepted as a comprehensively tested model of information systems success currently. The model proposed in this study argues that SLM process maturity influences information systems success, which is evaluated in terms of information quality, systems quality, service quality, and net effect proposed by DeLone and McLean. SLM process maturity can be measured in planning process, implementation process and operation and evaluation process. Instruments for measuring the factors in the proposed constructs of information systems success and SL management process maturity were collected from previous researches and evaluated for securing reliability and validity, utilizing appropriate statistical methods and pilot tests before exploring the case study. Four cases from four different companies under one vendor company were utilized for the analysis. All of the cases had been contracted in SLA(Service Level Agreement) and had implemented ITIL(IT Infrastructure Library), Six Sigma and BSC(Balanced Scored Card) methods since last several years, which means that all the client organizations pursued concerted efforts to acquire quality services from IT outsourcing from the organization and users' point of view. For comparing the differences among the four organizations in IT out-sourcing sucess, T-test and non-parametric analysis have been applied on the data set collected from the organization using survey instruments. The process maturities of planning and implementation phases of SLM are found not to influence on any dimensions of information systems success from users' point of view. It was found that the SLM maturity in the phase of operations and evaluation could influence systems quality only from users' view. This result seems to be quite against the arguments in IT outsourcing practices in the fields, which emphasize usually the importance of planning and implementation processes upfront in IT outsourcing projects. According to after-the-fact observation by an expert in an organization participating in the study, their needs and motivations for outsourcing contracts had been quite familiar already to the vendors as long-term partners under a same conglomerate, so that the maturity in the phases of planning and implementation seems not to be differentiating factors for the success of IT outsourcing. This study will be the foundation for the future research in the area of IT outsourcing management and success, in particular in the service level management. And also, it could guide managers in practice in IT outsourcing management to focus on service level management process in operation and evaluation stage especially for long-term outsourcing contracts under very unique context like Korean IT outsourcing projects. This study has some limitations in generalization because the sample size is small and the context itself is confined in an unique environment. For future exploration, survey based research could be designed and implemented.

• Korean Journal of Heritage: History & Science
• /
• v.54 no.4
• /
• pp.152-173
• /
• 2021

The Large Banner was introduced during the Japanese Invasions of Korea with a new military system. It was a flag that controlled the movement of soldiers in military training. In addition, it was used in other ways, such as a symbol when receiving a king in a military camp, a flag raised on the front of a royal procession, at the reception and dispatch of envoys, and at a local official's procession. The Large Banner was recognized as a symbol of military dignity and training rites. The Large Banner was analyzed in the present study in the context of two different types of decorations. Type I includes chungdogi, gakgi and moongi. Type II includes grand, medium, and small obangi, geumgogi and pyomigi. Each type is decorated differently for each purpose. The size of the flag is estimated to be a square of over 4 ja long in length. Flame edges were attached to one side and run up and down The Large Banner used the Five Direction Colors based on the traditional principles of Yin-Yang and Five Elements. The pattern of the Large Banner is largely distinguished by four. The pattern of large obangi consists of divine beasts symbolizing the Five Directions and a Taoism amulet letter. The pattern of medium obangi features spiritual generals that escort the Five Directions. The pattern of small obangi has the Eight Trigrams. The pattern of moongi consists of a tiger with wings that keeps a tight watch on the army's doors. As for historical sources of coloring for Large Banner production, the color-written copy named Gije, from the collection of the Osaka Prefect Library, was confirmed as the style of the Yongho Camp in the mid to late 18th century, and it was also used for this essay and visualization work. We used Cloud-patterned Satin Damask as the background material for Large Banner production, to reveal the dignity of the military. The size of the 4 ja flag was determined to be 170 cm long and 145 cm wide, and the 5 ja flag was 200 cm long and 175 cm wide. The conversion formula used for this work was Youngjochuck (1 ja =30cm). In addition, the order of hierarchy in the Flag of the King was discovered within all flags of the late Joseon Dynasty. In the above historical study, the two types of Large Banner were visualized. The visualization considered the size of the flag, the decoration of the flagpole, and the patterns described in this essay to restore them to their original shape laid out the 18th century relics on the background. By presenting color, size, material patterns, and auxiliary items together, it was possible not only to produce 3D content, but also to produce real products.

• Journal of Intelligence and Information Systems
• /
• v.25 no.3
• /
• pp.179-200
• /
• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

• The Korean Journal of Archival Studies
• /
• no.44
• /
• pp.51-99
• /
• 2015

The purpose of the archival appraisal has gradually changed from the selection of records to the documentation of the society. In particular, the qualitative and quantitative developments of the current digital technology and web have become the driving force that enables semantic acquisition, rather than physical one. Under these circumstances, the concept of 'documentary heritage' has been re-established internationally, led by UNESCO. Library and Archives Canada (LAC) reflects this trend. LAC has been trying to develop a new appraisal model and an acquisition model at the same time to revive the spirit of total archives, which is the 'Whole-of-society approach'. Features of this approach can be summarized in three main points. First, it is for documentary heritage and the acquisition refers to semantic acquisition, not the physical one. And because the object of management is documentary heritage, the cooperation between documentary heritage institutions has to be a prerequisite condition. Lastly, it cannot only documenting what already happened, it can documenting what is happening in the current society. 'Whole-of-society approach', as an appraisal method, is a way to identify social components based on social theories. The approach, as an acquisition method, is targeting digital recording, which includes 'digitized' heritage and 'born-digital' heritage. And it makes possible to the semantic acquisition of documentary heritage based on the data linking by mapping identified social components as metadata component and establishing them into linked open data. This study pointed out that it is hard to realize documentation of the society based on domestic appraisal system since the purpose is limited to selection. To overcome this limitation, we suggest a guideline applied with 'Whole-of-society approach'.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
• /
• 2004.04a
• /
• pp.3-4
• /
• 2004

Results will be presented from two field studies that evaluated the in-situ treatment of chlorinated aliphatic hydrocarbons (CAHs) using aerobic cometabolism. In the first study, a cometabolic air sparging (CAS) demonstration was conducted at McClellan Air Force Base (AFB), California, to treat chlorinated aliphatic hydrocarbons (CAHs) in groundwater using propane as the cometabolic substrate. A propane-biostimulated zone was sparged with a propane/air mixture and a control zone was sparged with air alone. Propane-utilizers were effectively stimulated in the saturated zone with repeated intermediate sparging of propane and air. Propane delivery, however, was not uniform, with propane mainly observed in down-gradient observation wells. Trichloroethene (TCE), cis-1, 2-dichloroethene (c-DCE), and dissolved oxygen (DO) concentration levels decreased in proportion with propane usage, with c-DCE decreasing more rapidly than TCE. The more rapid removal of c-DCE indicated biotransformation and not just physical removal by stripping. Propane utilization rates and rates of CAH removal slowed after three to four months of repeated propane additions, which coincided with tile depletion of nitrogen (as nitrate). Ammonia was then added to the propane/air mixture as a nitrogen source. After a six-month period between propane additions, rapid propane-utilization was observed. Nitrate was present due to groundwater flow into the treatment zone and/or by the oxidation of tile previously injected ammonia. In the propane-stimulated zone, c-DCE concentrations decreased below tile detection limit (1 $\mu$g/L), and TCE concentrations ranged from less than 5 $\mu$g/L to 30 $\mu$g/L, representing removals of 90 to 97%. In the air sparged control zone, TCE was removed at only two monitoring locations nearest the sparge-well, to concentrations of 15 $\mu$g/L and 60 $\mu$g/L. The responses indicate that stripping as well as biological treatment were responsible for the removal of contaminants in the biostimulated zone, with biostimulation enhancing removals to lower contaminant levels. As part of that study bacterial population shifts that occurred in the groundwater during CAS and air sparging control were evaluated by length heterogeneity polymerase chain reaction (LH-PCR) fragment analysis. The results showed that an organism(5) that had a fragment size of 385 base pairs (385 bp) was positively correlated with propane removal rates. The 385 bp fragment consisted of up to 83% of the total fragments in the analysis when propane removal rates peaked. A 16S rRNA clone library made from the bacteria sampled in propane sparged groundwater included clones of a TM7 division bacterium that had a 385bp LH-PCR fragment; no other bacterial species with this fragment size were detected. Both propane removal rates and the 385bp LH-PCR fragment decreased as nitrate levels in the groundwater decreased. In the second study the potential for bioaugmentation of a butane culture was evaluated in a series of field tests conducted at the Moffett Field Air Station in California. A butane-utilizing mixed culture that was effective in transforming 1, 1-dichloroethene (1, 1-DCE), 1, 1, 1-trichloroethane (1, 1, 1-TCA), and 1, 1-dichloroethane (1, 1-DCA) was added to the saturated zone at the test site. This mixture of contaminants was evaluated since they are often present as together as the result of 1, 1, 1-TCA contamination and the abiotic and biotic transformation of 1, 1, 1-TCA to 1, 1-DCE and 1, 1-DCA. Model simulations were performed prior to the initiation of the field study. The simulations were performed with a transport code that included processes for in-situ cometabolism, including microbial growth and decay, substrate and oxygen utilization, and the cometabolism of dual contaminants (1, 1-DCE and 1, 1, 1-TCA). Based on the results of detailed kinetic studies with the culture, cometabolic transformation kinetics were incorporated that butane mixed-inhibition on 1, 1-DCE and 1, 1, 1-TCA transformation, and competitive inhibition of 1, 1-DCE and 1, 1, 1-TCA on butane utilization. A transformation capacity term was also included in the model formation that results in cell loss due to contaminant transformation. Parameters for the model simulations were determined independently in kinetic studies with the butane-utilizing culture and through batch microcosm tests with groundwater and aquifer solids from the field test zone with the butane-utilizing culture added. In microcosm tests, the model simulated well the repetitive utilization of butane and cometabolism of 1.1, 1-TCA and 1, 1-DCE, as well as the transformation of 1, 1-DCE as it was repeatedly transformed at increased aqueous concentrations. Model simulations were then performed under the transport conditions of the field test to explore the effects of the bioaugmentation dose and the response of the system to tile biostimulation with alternating pulses of dissolved butane and oxygen in the presence of 1, 1-DCE (50 $\mu$g/L) and 1, 1, 1-TCA (250 $\mu$g/L). A uniform aquifer bioaugmentation dose of 0.5 mg/L of cells resulted in complete utilization of the butane 2-meters downgradient of the injection well within 200-hrs of bioaugmentation and butane addition. 1, 1-DCE was much more rapidly transformed than 1, 1, 1-TCA, and efficient 1, 1, 1-TCA removal occurred only after 1, 1-DCE and butane were decreased in concentration. The simulations demonstrated the strong inhibition of both 1, 1-DCE and butane on 1, 1, 1-TCA transformation, and the more rapid 1, 1-DCE transformation kinetics. Results of tile field demonstration indicated that bioaugmentation was successfully implemented; however it was difficult to maintain effective treatment for long periods of time (50 days or more). The demonstration showed that the bioaugmented experimental leg effectively transformed 1, 1-DCE and 1, 1-DCA, and was somewhat effective in transforming 1, 1, 1-TCA. The indigenous experimental leg treated in the same way as the bioaugmented leg was much less effective in treating the contaminant mixture. The best operating performance was achieved in the bioaugmented leg with about over 90%, 80%, 60 % removal for 1, 1-DCE, 1, 1-DCA, and 1, 1, 1-TCA, respectively. Molecular methods were used to track and enumerate the bioaugmented culture in the test zone. Real Time PCR analysis was used to on enumerate the bioaugmented culture. The results show higher numbers of the bioaugmented microorganisms were present in the treatment zone groundwater when the contaminants were being effective transformed. A decrease in these numbers was associated with a reduction in treatment performance. The results of the field tests indicated that although bioaugmentation can be successfully implemented, competition for the growth substrate (butane) by the indigenous microorganisms likely lead to the decrease in long-term performance.

• Journal of Intelligence and Information Systems
• /
• v.20 no.4
• /
• pp.89-105
• /
• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Journal of Intelligence and Information Systems
• /
• v.24 no.1
• /
• pp.183-203
• /
• 2018

News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.