• Journal of applied mathematics & informatics
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• v.13 no.1_2
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• pp.125-138
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• 2003

Some Riccati type difference inequalities are established for the second-order nonlinear difference equations with negative neutral term $\Delta$(a(n)$\Delta$(x(n) - px(n-$\tau$))) + f(n, x($\sigma$(n))) = 0 using these inequalities we obtain some oscillation criteria for the above equation.

• The Korean Journal of Health Service Management
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• v.10 no.2
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• pp.155-166
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• 2016

Objectives : This study confirmed the limitation of long-term care insurance by analyzing media contents. Methods : Articles and reviews were searched with the article searching system (KINDS) from July 2008 to December, 2015. Results : Among the 155 articles examined, 61.1% highlighted the faults of suppliers, and 25.2% indicated the responsibility of the insurer. As for their purpose, 56.8% reported on accidents, and 32.3% provided information. Furthermore, 74.2% reported on negative contents and only 25.8% on neutral contents. The negative contents consisted of requesting false insurance benefits, amending the range and price indicating the very low salaries of the care givers, limitations on the care grade assessment, and problems related with assistive devices. The majority of neutral articles is for providing information. Conclusions : There were many problems starting from the early stage of the insurance. We must pay attention to these problems. Moreover, we should try to handle and prevent these problems with supportive responses from authorities.

• Bulletin of the Korean Mathematical Society
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• v.45 no.1
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• pp.23-31
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• 2008

In this paper, we investigate nonoscillatory solutions of a class of higher order neutral nonlinear difference equations with positive and negative coefficients $\Delta^m(x(n)+p(n)x(\tau(n)))+f_1(n,x(\sigma_1(n)))-f_2(n,x(\sigma_2(n)))=0,\;n{\geq}n_0$. Some sufficient conditions for the existence of nonoscillatory solutions are obtained.

• Journal of Korea Trade
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• v.27 no.1
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• pp.60-78
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• 2023

Purpose - The study analyzed 90 online firms worldwise and observed them for ten years to investigate their investments and firm performance variabilities. This study attemped to verify the existence of agency problems in online firms. Through this, the paper intends to expand the scope of research in the fields of investment and firm value both empirically and in theory. This study also attempted to supplement the insufficient logic of previous studies by analyzing the relationship between investment and profitability. Design/methodology - In this study, the investment is subdivided into over-, under-, and neutral investments, and an empirical analysis of the firm performance was conducted. As investment generally has long-term effects, the impact of a firm's investment on future firm performance and variabilities in firm performance was considered over the short-and medium-term period. Findings - It was found that there was a negative relationship between firms with an overinvestment and future firm performance. Underinvestment has no clear statistically significant results on firm performance. This implies that overinvestment causes more reduction in future firm performance than underinvestment. It was also found that underinvestment and overinvestment significantly increased the variability of firm performance. A positive significance was found between under- and over- investment with a variability of 3 years and overinvestment with a variability of 4 years in the future. A negative relationship was found between neutral investment propensity and future performance variabilities. Neutral investment has less effect on the future performance variability of a firm than a firm's overinvestment and underinvestment. For online firms, underinvestment and overinvestment have a greater effect on the firm's future performance variability than neutral investment. Originality/value - The agency theory predicts that information asymmetry and adverse selection problems exacerbate conflicts of interest among stakeholders, thus firm performance. The study contributed to accumulating research on online firms that are currently underexplored by analyzing the investment behavior of major firms in the online industry.

• Korean Journal of Child Studies
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• v.36 no.5
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• pp.75-94
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• 2015

This study examined short-term longitudinal reciprocal relationships between maternal parenting behavior and preschoolers' compliance/noncompliance, as well as stability in both maternal parenting behavior and preschoolers' compliance/noncompliance over time. The sample which was used for this study was taken from a two-wave (one year apart) longitudinal study of preschool-aged children and their mothers (N = 53 dyads). At both times, mothers and their children were invited to a laboratory and engaged in 25 minutes of play involving three episodes of mother-child interaction. Maternal parenting behavior and preschoolers' compliance/noncompliance during play were coded using the Dyadic Parent-Child Interaction Coding System-III (DPICS-III). Maternal codes included positive, neutral, and negative parenting behaviors and child codes were comprised of compliance and noncompliance. The results revealed that during the play session, maternal neutral and negative parenting behavior and preschoolers' compliance were stable over time. In addition, T1 maternal negative parenting behavior was significantly related to T2 child compliance/noncompliance. However, T1 child compliance/noncompliance were not significantly associated with T2 maternal parenting behavior. These findings suggest that during the preschool period, there are unidirectional effects from mothers to children.

• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.495-501
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• 2004

HJM representation of the term structure of interest rates sometimes produces the negative interest rates with positive probability. This paper shows that the condition of positive interest rates can be derived from the jump diffusion process, if a proper positive martingale process with the compensated jump process is chosen. As in Flesaker and Hughston, the condition is incorporated into the bond price process.

• Journal of the Korea Convergence Society
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• v.9 no.8
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• pp.319-330
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• 2018

The aim of this study was to identify the relationship of caregiving appraisal and family function among senile dementia patients' families using in-home services for the Long-Term Care Insurance(LTCI). The participants were 121 family caregivers of senile dementia patients using in-home services for the LTCI. The participants' mean age was $53.80{\pm}10.86years$, all middle-aged women(75.2%). When negative cognition's burden and neutral one's demand in their caregiving appraisal were low and positive cognition's satisfaction and mastery in their caregiving appraisal were high, emotional function in their family function was high. There is a need to develop nursing interventions for strengthening positive cognition's satisfaction and decreasing neutral one's demand in their caregiving appraisal to improve emotional function and communication of senile dementia patients' families.

• Information Systems Review
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• v.21 no.1
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• pp.91-111
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• 2019

Around the end of 2017, the investment fever for cryptocurrencies-especially Bitcoin-has started all over the world. Especially, South Korea has been at the center of this phenomenon. Sinceit was difficult to find the profitable investment opportunities, people have started to see the cryptocurrency markets as an alternative investment objects. However, the cryptocurrency fever inSouth Korea is mostly based on psychological phenomenon due to expectation of short-term profits and social atmosphere rather than intrinsic value of the assets. Therefore, this study aimed to analyze influence of people's social sentiment on price movement of cryptocurrency. The data was collected for 181 days from Nov 1st, 2017 to Apr 30th, 2018, especially focusing on Bitcoin-related post in Twitter along with price of Bitcoin in Bithumb/UPbit. After the collected data was refined into neutral, positive and negative words through sentiment analysis, the refined neutral, positive, and negative words were put into regression model in order to find out the impacts of social sentiments on Bitcoin price. After examining the relationship by the regression analyses and Granger Causality tests, we found that the positive sentiments had a positive relationship with Bitcoin price, while the negative words had a negative relation with it. Also, the causality test results show that there exist two-way causalities between social sentiment and Bitcoin price movement. Therefore, we were able to conclude that the Bitcoin investors'behaviors are affected by the changes of social sentiments.

• Journal of Information Technology Applications and Management
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• v.26 no.4
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• pp.51-69
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• 2019

One of the most considerate phenomena of the era of the Fourth Industrial Revolution is the use of digital devices. Digitalization is rapidly advancing through all areas of industry and life. Customer journey with digitalization is looking totally different from previous customer journey. The research targets were users of fashion, automobiles, cosmetics and online shopping malls. We analyzed 300 people for each valid questionnaire. The results of the study are as follows. First, it has been proven that digital experience affects positive (+) impact on purchasing intention and positive (+) impact on recommending intention and negative impact (-) on switching intent and subsequently affects positive impact (+) to purchase and incase of switching intent, negative impact (-) to purchase. Unlike traditional methods such as SPC(Service Profit Chain), the Digital experience to Purchase process Chain (DPC) has been identified to be suitable in the digital age. Second, the digital satisfied group (5 score-very satisfaction) has shown same result as above. However the digital neutral group (even though 4 score- satisfaction in five-point scale), specially in a highly competitive industry, has different from the satisfied group and 3 score-normal is same as dissatisfied group. It means that this group is that If there is a high level of attractiveness of substitute goods, there is a high possibility of switching them. It has supported Jones and Sasser [1995] that there have been two types of loyalty of true long-term loyalty and what we call false loyalty in the highly competitive industry zone which is commoditization or low differentiation, many substitutes, low cost of switching. Identifying true loyalty and false loyalty is crucial to establishing a customer experience strategy. it is necessary to actively utilize long-term digital experiences strategy to increase the total satisfaction of digital experience through all of customer purchasing journey in order to enhance the digital customer experience. It is difficult to see the effect as a one-time event. It should be scaled over the entire customer purchase process over a long period of time, which can positively affect purchase intention, recommendation intention, and conversion intention. This is also why it is difficult for second-runners to overtake first-runners in a short period.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.129-142
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• 2016

Customer product reviews have become one of the important factors for purchase decision makings. Customers believe that reviews written by others who have already had an experience with the product offer more reliable information than that provided by sellers. However, there are too many products and reviews, the advantage of e-commerce can be overwhelmed by increasing search costs. Reading all of the reviews to find out the pros and cons of a certain product can be exhausting. To help users find the most useful information about products without much difficulty, e-commerce companies try to provide various ways for customers to write and rate product reviews. To assist potential customers, online stores have devised various ways to provide useful customer reviews. Different methods have been developed to classify and recommend useful reviews to customers, primarily using feedback provided by customers about the helpfulness of reviews. Most shopping websites provide customer reviews and offer the following information: the average preference of a product, the number of customers who have participated in preference voting, and preference distribution. Most information on the helpfulness of product reviews is collected through a voting system. Amazon.com asks customers whether a review on a certain product is helpful, and it places the most helpful favorable and the most helpful critical review at the top of the list of product reviews. Some companies also predict the usefulness of a review based on certain attributes including length, author(s), and the words used, publishing only reviews that are likely to be useful. Text mining approaches have been used for classifying useful reviews in advance. To apply a text mining approach based on all reviews for a product, we need to build a term-document matrix. We have to extract all words from reviews and build a matrix with the number of occurrences of a term in a review. Since there are many reviews, the size of term-document matrix is so large. It caused difficulties to apply text mining algorithms with the large term-document matrix. Thus, researchers need to delete some terms in terms of sparsity since sparse words have little effects on classifications or predictions. The purpose of this study is to suggest a better way of building term-document matrix by deleting useless terms for review classification. In this study, we propose neutrality index to select words to be deleted. Many words still appear in both classifications - useful and not useful - and these words have little or negative effects on classification performances. Thus, we defined these words as neutral terms and deleted neutral terms which are appeared in both classifications similarly. After deleting sparse words, we selected words to be deleted in terms of neutrality. We tested our approach with Amazon.com's review data from five different product categories: Cellphones & Accessories, Movies & TV program, Automotive, CDs & Vinyl, Clothing, Shoes & Jewelry. We used reviews which got greater than four votes by users and 60% of the ratio of useful votes among total votes is the threshold to classify useful and not-useful reviews. We randomly selected 1,500 useful reviews and 1,500 not-useful reviews for each product category. And then we applied Information Gain and Support Vector Machine algorithms to classify the reviews and compared the classification performances in terms of precision, recall, and F-measure. Though the performances vary according to product categories and data sets, deleting terms with sparsity and neutrality showed the best performances in terms of F-measure for the two classification algorithms. However, deleting terms with sparsity only showed the best performances in terms of Recall for Information Gain and using all terms showed the best performances in terms of precision for SVM. Thus, it needs to be careful for selecting term deleting methods and classification algorithms based on data sets.