• Journal of Hospice and Palliative Care
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• v.24 no.3
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• pp.184-193
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• 2021

Purpose: This study attempted to develop clinical guidelines to help patients use hospice and palliative care (HPC) at an appropriate time after writing physician orders for life-sustaining treatment (POLST) by identifying the characteristics of HPC use of patients with terminal cancer. Methods: This retrospective study was conducted to understand the characteristics of HPC use of patients with terminal cancer through decision tree analysis. The participants were 394 terminal cancer patients who were hospitalized at a cancer-specialized hospital in Seoul, South Korea and wrote POLST from January 1, 2019 to March 31, 2021. Results: The predictive model for the characteristics of HPC use showed three main nodes (living together, pain control, and period to death after writing POLST). The decision tree analysis of HPC use by terminal cancer patients showed that the most likely group to use HPC use was terminal cancer patients who had a cohabitant, received pain control, and died 2 months or more after writing a POLST. The probability of HPC usage rate in this group was 87.5%. The next most likely group to use HPC had a cohabitant and received pain control; 64.8% of this group used HPC. Finally, 55.1% of participants who had a cohabitant used HPC, which was a significantly higher proportion than that of participants who did not have a cohabitant (1.7%). Conclusion: This study provides meaningful clinical evidence to help make decisions on HPC use more easily at an appropriate time.

• Health Policy and Management
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• v.9 no.2
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• pp.77-94
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• 1999

The purpose of this study is to establish strategy by subdividing consumer market according to the lifestyle which influences the use of medical facilities. The subject of this study were 700 adults who were over 20 years of age and residing in Suwon and its vicinity. To collect data trained staff conducted person-to-person interviews with the assistance of structured questionnaires. The questionnaires cover the areas of life style pattern study. the characteristics of demographic sociology, decision-making process related to the use of medical service. The influencing factors were analyzed and as a result total 18 factors were singled out. Cluster analysis was performed to differentiate similar responses. Each group was named as 'health-unconcern type' 'passive health-concern type' 'regular health-concern type' and 'active health-concern type' according to the characteristics. Each group showed statistically significant difference in the characteristics of demographic sociology. Decision-making process regarding the use of medical service according to lifestyle was analyzed. As a result following items showed significant difference:whether the information was utilized, what was the criteria in selecting medical facilities for serious illness or complicated examination. who was the decision maker in selection medical facilities, and with whom one discussed in selecting medical facilities. The result of this study has its limitation in that it can not be applied directly to market subdivision. However, this will help medical facilities understand customers' lifestyle. which will eventually provide medical facilities with marketing tools in establishing effective PR strategy. In order to apply the lifestyle as a marketing tool of medical facilities, following tasks are to be carried out: the development of the questionnaire which can better analyze consumers' lifestyle related to the use of medical service. the examination of precise characteristics of subdivided market according to lifestyle. and the continuing study on the relationship between lifestyle and the process in selecting medical facilities.

• The Research Journal of the Costume Culture
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• v.10 no.4
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• pp.336-349
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• 2002

The purpose of this paper is to examine the characteristics of consumption vision related to the apparel buying decision-making. They propose that consumers form mental images of future consumption situations and that these consumption visions influence their decision-making. Consumers can imagine themselves consuming apparel products and experiencing the consequences of this consumption. By imagining the likely outcomes, they are able to identify the salient characteristics of each alternative and develop beliefs about their outcomes. Also, they can experience affective reactions to the outcomes they imagines. In this way, they form the cognitive and affective basis for their preferences and construct several consumption visions in the apparel buying decision-making. A consumption vision is "a visual image of certain product-related behaviors and their consequences....(they consisted of concrete and vivid mental images that enable consumers to vicariously experience the self-relevant consequences of product use"(Walker & Olson, 1994). We conducted unstructured, depth interviews with 9 groups participating 48 students at universities located in Busan, based on the results of previous studies. The results show that consumption visions related to the apparel buying decision-making are characterized as self-image, reactions of others, affection and mood, visual imagine, and self-satisfaction. By constructing consumption visions based on the various perspectives, consumers are influenced in the apparel buying decision-making. Many subjects reported experiencing positive affect when imagining positive outcomes of product use. Other subjects mentioned using consumption visions for purely hedonic reasons. With no intention of purchasing apparel products, consumers may evoke consumption visions to escape from the daily life, to fantasize and daydream about pleasurable consumption situations, and to enhance the mood. That is, the consumption vision related to the apparel buying decision-making helps consumers anticipate an uncertain future and make the purchase of apparel products.

• Journal of Labour Economics
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• v.37 no.3
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• pp.101-122
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• 2014

This paper empirically estimates the decision of aged workers related to the retirement decision. Using the supplemental survey for aged people of the Korean panel data set, the paper analyses the correlation between the retirement decision of middle-aged people (aged 50 years or older) and personal characteristics and job characteristics of main jobs that aged people had worked, particularly focusing on the mandatory job retirement regulation and its regulation of retirement ages. The empirical results show that the regulated retirement age is more important than the existence of mandatory retirement system in related to the workers' retirement decision.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.8
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• pp.1199-1203
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• 2012

H.264 adopted many compression tools to increase image data compression efficiency such as B frame bi-directional predictions, the direct mode coding and so on. Despite its high compression efficiency, H.264 can suffer from its long coding time due to the complicated tools of H.264. To realize a high performance H.264, several fast algorithms were proposed. One of them is adaptive fast direct mode decision algorithm using mode and Lagrangian cost prediction for B frame in H.264/AVC (MLP) algorithm which can determine the direct coding mode for macroblocks without a complex mode decision process. However, in this algorithm, macroblocks not satisfying the conditions of the MLP algorithm are required to process the complex mode decision calculation, yet suffering a long coding time. To overcome the problem, this paper proposes a fast direct mode prediction algorithm. Simulation results show that the proposed algorithm can determine the direct mode coding without a complex mode decision process for 42% more macroblocks and, this algorithm can reduce coding time by up to 23%, compared with Jin's algorithm. This enables to encode B frames fast with a less quality degradation.

• Asia-Pacific Journal of Business
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• v.14 no.1
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• pp.411-426
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• 2023

Purpose - The purpose of this study was to explore and diagnose the characteristics and behavioural patterns of rural tourists after COVID-19 using decision tree analysis to classify and identify key segmentation groups. Design/methodology/approach - The CHAID algorithm was used as the analysis technique for the decision tree. The explanatory variables used in the analysis of each decision tree model were demographic variables and rural tourism usage behaviour and perception variables, and the target variables were the preferences of rural tourists' activities after COVID-19. From the Rural Tourism 2020 survey data, 614 samples with rural tourism experience were extracted and used in the analysis. Findings - The variables that significantly explained the preference for each type of rural tourism activity after COVID-19 were rural tourism safety perception, repeated visits to the region, rural tourism priority activity, rural tourism accommodation experience, gender, age group, marital status, occupation, and education level. Among them, rural tourism safety perception was the most important explanatory variable in each analysis model. Research implications or Originality - Overall, to promote rural tourism, it is necessary to enhance the safety image of rural tourism, strengthen loyalty programs for repeat visitors, and develop customized products that reflect the preferred trends of rural tourism.

• Journal of Home Health Care Nursing
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• v.31 no.1
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• pp.56-65
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• 2024

Purpose: This study aimed to explore the association between demographic characteristics, hospitalization-related characteristics, and the severity of long-term hospitalization in a high-level general hospital, and to analyze the factors influencing decisions of all patients. Methods: General and clinical characteristics of the participants were analyzed using frequency, percentage, mean, and standard deviation. Differences in these characteristics, contingent upon whether a power source was requested, were analyzed using independent t-Test and Chi-squared tests. Logistic regression analysis was used to identify the factors related to the presence or absence of power requests. Results: The factors impacting the decision to refer a dependent variable include medical treatment (neurosurgery) (B=2.118, SE=0.960, p-value=.027, OR=8.314, 95% CI=1.267-54.551), infection isolation (CRE) (B=1.336, SE=0.666, p-value=.045, OR=3.804, 95% CI=1.032-14.021), and the utilization of tertiary antibiotics (B=3.076, SE=1.362, p-value= .024, OR=21.663, 95% CI=1.502-312.530). Conclusion: This study found a significant association between medical treatment (neurosurgery), infection isolation (CRE), and the use of tertiary antibiotics as dependent variables. These findings indicate that continuous monitoring can contribute to a reduction in long-term financial burdens.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11
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• pp.2863-2874
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• 1999

Apartment auction is a system that is used for the citizens to get a house. This paper deals with the implementation of a web-based intelligent decision support system using OLAP technique and data mining technique for auction decision support. The implemented decision support system is working on a real auction database and is mainly composed of OLAP Knowledge Extractor based on data warehouse and Auction Data Miner based on data mining methodology. OLAP Knowledge Extractor extracts required knowledge and visualizes it from auction database. The OLAP technique uses fact, dimension, and hierarchies to provide the result of data analysis by menas of roll-up, drill-down, slicing, dicing, and pivoting. Auction Data Miner predicts a successful bid price by means of applying classification to auction database. The Miner is based on the lazy model-based classification algorithm and applies the concepts such as decision fields, dynamic domain information, and field weighted function to this algorithm and applies the concepts such as decision fields, dynamic domain information, and field weighted function to this algorithm to reflect the characteristics of auction database.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.339-344
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• 2007

In the cut-throat competitive environment of business, large-scale IS investment is becoming inevitable strategic necessity for gaining competitive advantage. However. it bears great deal of risk over all the associated processes so that the investment decisions need to be taken in a greatly careful manner. Nonetheless, Korean organizations are prominently showing risk taking behaviors regarding major is investment, in terms of system downsizing. Although decision theory argues decision makers' rational choice of options through the assessment of risk and benefit, the notable trend toward system downsizing in Korea defies common understandings on IS project risk. Furthermore, it encourages us to investigate many impenetrable characteristics underlying organizational risk taking decisions with IS investment. We found out that there is Significant effect of IS decision makers' risk propensity when they make system downsizing decisions. Moreover. we Identified that IS decision makers do not get a strong pressure of cost savings and have tendencies to mimic competitor's decisions.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.336-342
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• 2001

One of the most important problems on rule induction methods is that they cannot extract rules, which plausibly represent experts decision processes. On one hand, rule induction methods induce probabilistic rules, the description length of which is too short, compared with the experts rules. On the other hand, construction of Bayesian networks generates too lengthy rules. In this paper, the characteristics of experts rules are closely examined and a new approach to extract plausible rules is introduced, which consists of the following three procedures. First, the characterization of decision attributes (given classes) is extracted from databases and the classes are classified into several groups with respect to the characterization. Then, two kinds of sub-rules, characterization rules for each group and discrimination rules for each class in the group are induced. Finally, those two parts are integrated into one rule for each decision attribute. The proposed method was evaluated on a medical database, the experimental results of which show that induced rules correctly represent experts decision processes.