• Management & Information Systems Review
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• v.26
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• pp.27-60
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• 2008

Researches on the introduction of ERP system kept on examining the critical successful factors (CSFs) that focus on factors to achieve effectively successful projects, and trying to measuring the actual effectiveness of the introduction of ERP system. However, most of the preceding researches on the effectiveness of the introduction of ERP system that was searching devoted effects has been ceased, and actually even researches on the economical results have just done the basic cognitive evaluation of result indicators by many questionnaires instead of objective measuring values, because of the difficulty of measuring the evaluation of the result. Moreover, researches on positive effects of the introduction of ERP on enterprise results and researches that failed to give advantageous effects showed different results each other. And a part of researches reported that only a part of result indicators were partially affected. In this research, we investigated Korean large enterprises or middle-sized enterprises in manufacture industry that introduces SAP R/3 and Oracle package to compare their quantitative financial results after the introduction of ERP system, in order to measure the effects of the ERP system. First, we evaluated the difference of the quantitative financial results before and after the introduction of the ERP system. Second, we evaluated the opportunities shown by the effects after the introduction of the ERP system. Third, we removed the sample of the exchange crisis (IMF) and executed the additional analysis to reflect the average increasing and decreasing rate in the industry, so that pure evaluation can be achieved. Inherent limits of precedent researches are removed and practical effects of the pure introduction of the ERP system are evaluated, so the research of this research is significant. The result of this research is as follows. Because of the introduction of ERP, the rate of turnover of inventory property has increased and sales of preparation inventory property have decreased so that more effective inventory property management has been achieved. Moreover, preparation sales of labor costs and preparation sales of the number of employees have decreased to show the effect of the reduction of labor costs. However, it could no be concluded that we could increase the profit due to the introduction of ERP system. Due to the introduction of ERP, although we concluded that the return on assets (ROA) and the additional value of one-person employee statistically showed obvious differences and increased, the return on equity failed to show obvious differences after the process of introduction of ERP.

• Journal of Korean Academy of Nursing
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• v.29 no.4
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• pp.880-891
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• 1999

The purpose of this study was to describe nursing decision tasks, their characteristics, and problems associated with decision making. The subjects were 32 nurses who had at least one-year nursing experience and worked on medical-surgical units or intensive care units(ICU). They were asked to describe their decision making experiences in patient care situations and to identify the characteristics of each decisions. They were also asked to describe perceived problems associated with decision making in nursing. The responses on nursing decision tasks and problems were analyzed with content analysis and the decision characteristics were identified by statistical analysis of variance. It was found that there were 16 nursing decisions which are as follows : decisions related to interpreting and selecting appropriate strategies for pain management(6.6%) ; decisions related to providing emotional support (0.7%) ; decisions related to explaining the patient's condition and rationale for procedures(1.1%) ; decisions related to assisting patients to integrate the implications of illness and recovering into their lifestyles(2.9%) ; decisions related to detecting significant changes In patients and selecting appropriate intervention strategies (17.2%) ; decisions related to anticipating problems and selecting preventive measures(4.2%) ; decisions related to identifying emergency situations(0.4%) ; decisions related to effective management of patient crisis until physician assistance becomes available(2.8%) ; decisions related to starting and maintaining intravenous therapy(2.6%) ; decisions related to administering medications(8.1%) ; decisions related to combating the hazards of immobility(7.3%) : decisions related to treating wound management strategies(5.5%) ; decisions related to relieving patient discomfort(13.9) ; decisions related to selecting appropriate strategy according to the changing situation of the patient(18.2%) ; decisions related to selecting the best strategy for patient management(5.3%) ; and decisions related to coordinating, ordering, and meeting the various needs of the patient (3.1%). The nurses reported the fellowing problems in decision making : difficulties due to lack of knowledge and experience (18.6%) ; uncertainty and complexity of decision tasks(15.2%) ; lack of time to make decisions(2.9%) ; personal values which conflict with other staff(15.7%) ; lack of selection autonomy(30.0%) ; and organizational barriers(7.6%). Continuing education programs and decision support systems for frequent nursing decision tasks can be established on the basis of these results. Then decision ability in nurses will increase through the education programs and decision support systems, and then quality of nursing service will be better.

• Asia pacific journal of information systems
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• v.26 no.3
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• pp.367-384
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• 2016

Social networking services (SNS) have become a significant platform for Internet users to obtain knowledge and information. Users can share messages mutually via this platform. This kind of sharing enables users to exchange and gain useful information. However, in recent years, the crisis of stickiness has appeared in SNS, calling attention to the social network industry. Relevant professionals explain that the interest of users in sharing knowledge on SNS websites and applications may gradually decrease, eventually leading to users giving it because the platforms utilize simple and uninteresting methods to attract active participation from users. However, factors affecting the knowledge sharing on SNS websites and applications should be identified clearly through studies. Sina Weibo is one of the largest SNS platforms in the world, and studies on the factors affecting knowledge sharing of users could be valuable in addressing this issue. This paper establishes the theoretical analysis model of knowledge sharing in SNS sites and applications, analyzes the factors affecting knowledge sharing on these sites, and proposes the corresponding strategies to address the issues. Using questionnaire surveys on Sina Weibo users, this article will discuss the factors affecting knowledge sharing, and analyze these factors on SNS as well as improve the stickiness of users to achieve the aim of SNS platforms enabling the expansion of the range of users. The study will discuss theoretical foundations and the hypotheses that arise. The method of study will also be discussed. The study concludes with theoretical implications, practical implications, limitations, and future research opportunities. The results of this study could aid researchers in understanding the underlying reasons for social network activities as well as for SNS developers in improving SNS services.

• Information Systems Review
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• v.19 no.4
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• pp.171-182
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• 2017

Although economic growth has been retarded since the global economic crisis over recent decades, a large number of firms consider mergers and acquisitions (M and A) as a strategy to survive in a highly competitive market. In particular, an increasing number of firms pursue M and A with IT firms in recent years. In this study, we analyze the post-merger risks measured as ROA volatility for acquiring firms when they seek to acquire an IT firm. Our analysis suggests that a firm with prior experience in M and A acquires IT firms aggressively. Moreover, a substantial number of IT firms are relatively small and unlisted when they are acquired. We also show that an acquiring firm's post-merger risk (i.e., ROA volatility) increases after its acquisition of IT firms. However, an increase in post-merger risk is alleviated when relatedness exists between an acquiring firm and target.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.3
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• pp.170-179
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• 2016

In this paper we have tackled the outstanding inventory planning problems over new product launching period in a more holistic manner by addressing first the definition of efficient business rules to effectively control and reduce the inventory risks followed by the rigorous explanations on the implementation guide on suggested inventory planning rules. It is not unusual for many companies in the consumer electronics market to make a great effort to reduce the time to launch a new product because the ability to bring out higher performing products in such a short time period greatly increases the probability for them to remain competitive in the high tech market. Among so many newly developed products, those products with new features and technologies appeal to many potential customers while products which fail to win customers by design and prices rapidly disappear in the market. To adapt to this business environment, those companies have been trying to find the answer to minimize the inventory of old products so they can move to next generation products quickly with less obsolete material. In the experimental implementation of our rule-based inventory planning, Company 'S' reduced the inventory cost for the outgoing products as low as 49% of its peak level of its preceding product version in just 5 month after the adoption of rule-based inventory planning process and system. This paper concluded the subject with a suggestion that the best performance of rule-based inventory planning is guaranteed not from one-time campaign of process improvement along with system development but the decision maker's continuing support and attention even without seeing any upcoming business crisis.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.177-197
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• 2001

This paper is aimed at proposing a data mining-driven analysis to manage the customer defection rate in the bank. After 1997 IMF crisis, Korean banks were suffering from hard-pressed restructuring. At the heart of such restructuring effects, there was the need to manage the customer more effectively than ever. So far, many banks in Korea used to a poor management of customers without any highly-skillful techniques. In line with this argument, we propose several data mining techniques to determine more effective technique far managing customer deflection. We applied three data mining techniques such as logit model, neural network, and C5.0. Experiment data were collected from personal deposit account data of a specific bank in Korea. After experiments, we found that C5.0 showed more robust performance compared to other two techniques. On the basis of those experiment results, we proposed customer defection management policy.

• International journal of advanced smart convergence
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• v.6 no.1
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• pp.82-88
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• 2017

Emergency lights and exit signs are an indispensable part of safety precautions for effective evacuation in case of emergency in public buildings. These emergency sign indicates safe escape routes and emergency doors, using an internationally recognizable sign. However visibility of those signs drops drastically in case of emergency situations like fire smoke, etc. and loss of visibility causes serious problems for safety evacuation. This paper propose a novel emergency light and exit sign built-in with Bluetooth Low Energy (BLE) Beacon to assist the emergency self-guiding evacuation using devices for crisis and emergency management to avoid panic condition inside the buildings. In this approach, the emergency light and exit sign with the BLE beacons deployed in the indoor environments and the smart devices detect their indoor positions, direction to move, and next exit sign position from beacon messages and interact with map server in the Internet / Intranet over the available LTE and/or Wi-Fi network connectivity. The map server generate an optimal emergency exit path according to the nearest emergency exit based on a novel graph generation method for less route computation for each smart device. All emergency exit path data interfaces among three system components, the emergency exit signs, map server, and smart devices, have been defined for modular implementation of our emergency evacuation system. The proposed exit sign experimental system has been deployed and evaluated in real-time building environment thoroughly and gives a good evidence that the modular design of the proposed exit sign system and a novel approach to compute emergency exit path route based on the BLE beacon message, map server, and smart devices is competitive and viable.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.1-12
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• 2016

The current economic crisis is making new demands on manufacturing industry, in particular, in terms of the flexibility and efficiency of production processes. This requires production and administrative processes to be meshed with each other by means of IT systems to optimise the use and capacity utilisation of machines and lines but also to be able to respond rapidly to wrong developments in production and thus to minimise adverse impacts on the business. The future scenario of the "smart factory" represents the zenith of this development. The factory can be modified and expanded at will, combines all components from different manufacturers and enables them to take on context-related tasks autonomously. Integrated user interfaces will still be required at most for basic functionalities. The complex control operations will run wirelessly and ad hoc via mobile terminals such as PDAs or smartphones. The comnination of IoT, and Big Data optimisation is bringing about huge opportunities. these processes are not just limited to manufacturing, anywhere a supply chain environment exists can benefit from information provided by linked devices and access to big data to inform their decision support. Building a smart factory with smart assets at its core means reaching those desired new levels of productivity and efficiency. It means smart products that leverage advanced traceability, connectivity and intelligence. For businesses, it means being able to address the talent crunch through more autonomous. In a Smart Factory, machinery and equipment will have the ability to improve processes through self-optimization and autonomous decision-making.

• The Journal of Fisheries Business Administration
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• v.36 no.1 s.67
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• pp.139-153
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• 2005

Marine fish aquaculture has been introduced on the East sea since 1964. The production volume of the marine aquaculture has been increasing drastically since 1990 with the technological improvements and the introduction of new species. However, the increasing costs of feed, seedlings and medical supplies and the decreasing prices due to the increase in the imports and domestic production have decreased the profits in the aquaculture business. Futhermore, the damage from the natural disasters such as red tides and typhoons has accelerated the exit from the business. Even though managing abilities to overcome the business crisis caused by the above factors are required, business managers based on the small scale family businesses do not have enough managing abilities to deal with the difficulties in the business. On the other hand, advanced countries in the marine aquaculture such as Norway have reached the stage where the managing abilities of marine aquaculture are similar to those in the manufacturing industry. And the number of large scale aquaculture farms with developed technologies and advanced marketing strategies in those countries is increasing. Considering that the marine aquaculture in Japan under the similar fishery systems of Korea has developed the state-of-the-art management skills or lead to large scale management, it is difficult to expect the decrease in the production costs under the small scale family business in Korea and this will lead to the decreasing competitive advantage over the imported seafood. Therefore marine aquaculture in Korea needs to increase the economy of scale to acquire the competitive advantage. This study addresses the possibility of introducing the large scale aquaculture system in Korea by analysing the factors and process of leading to large scale businesses in the aquaculture in Japan.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.119-138
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• 2017

Recently, SNS has become an important channel for marketing as well as personal communication. However, cybercrime has also evolved with the development of information and communication technology, and illegal advertising is distributed to SNS in large quantity. As a result, personal information is lost and even monetary damages occur more frequently. In this study, we propose a method to analyze which sentences and documents, which have been sent to the SNS, are related to financial fraud. First of all, as a conceptual framework, we developed a matrix of conceptual characteristics of cybercriminality on SNS and emergency management. We also suggested emergency management process which consists of Pre-Cybercriminality (e.g. risk identification) and Post-Cybercriminality steps. Among those we focused on risk identification in this paper. The main process consists of data collection, preprocessing and analysis. First, we selected two words 'daechul(loan)' and 'sachae(private loan)' as seed words and collected data with this word from SNS such as twitter. The collected data are given to the two researchers to decide whether they are related to the cybercriminality, particularly financial fraud, or not. Then we selected some of them as keywords if the vocabularies are related to the nominals and symbols. With the selected keywords, we searched and collected data from web materials such as twitter, news, blog, and more than 820,000 articles collected. The collected articles were refined through preprocessing and made into learning data. The preprocessing process is divided into performing morphological analysis step, removing stop words step, and selecting valid part-of-speech step. In the morphological analysis step, a complex sentence is transformed into some morpheme units to enable mechanical analysis. In the removing stop words step, non-lexical elements such as numbers, punctuation marks, and double spaces are removed from the text. In the step of selecting valid part-of-speech, only two kinds of nouns and symbols are considered. Since nouns could refer to things, the intent of message is expressed better than the other part-of-speech. Moreover, the more illegal the text is, the more frequently symbols are used. The selected data is given 'legal' or 'illegal'. To make the selected data as learning data through the preprocessing process, it is necessary to classify whether each data is legitimate or not. The processed data is then converted into Corpus type and Document-Term Matrix. Finally, the two types of 'legal' and 'illegal' files were mixed and randomly divided into learning data set and test data set. In this study, we set the learning data as 70% and the test data as 30%. SVM was used as the discrimination algorithm. Since SVM requires gamma and cost values as the main parameters, we set gamma as 0.5 and cost as 10, based on the optimal value function. The cost is set higher than general cases. To show the feasibility of the idea proposed in this paper, we compared the proposed method with MLE (Maximum Likelihood Estimation), Term Frequency, and Collective Intelligence method. Overall accuracy and was used as the metric. As a result, the overall accuracy of the proposed method was 92.41% of illegal loan advertisement and 77.75% of illegal visit sales, which is apparently superior to that of the Term Frequency, MLE, etc. Hence, the result suggests that the proposed method is valid and usable practically. In this paper, we propose a framework for crisis management caused by abnormalities of unstructured data sources such as SNS. We hope this study will contribute to the academia by identifying what to consider when applying the SVM-like discrimination algorithm to text analysis. Moreover, the study will also contribute to the practitioners in the field of brand management and opinion mining.