• Information Systems Review
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• v.17 no.2
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• pp.77-100
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• 2015

This study examined the factors that influence the smartphone user's decision to accept the personalized mobile advertisement. As a theoretical basis, we applied the privacy calculus model (PCM) that illustrates how consumers are engaged in a dynamic adjustment process in which privacy risks are weighted against benefits of information disclosure. In particular, we investigated how smartphone users make a risk-benefit assessment under which personalized service as benefit-side factor and information privacy risks as a risk-side factor accompanying their acceptance of advertisements. Further, we extend the current PCM by considering advertisement fatigue as a new factor that may influence the user's acceptance. The research model with five (5) hypotheses was tested using data gathered from 215 respondents through a quasi-experimental survey method. During the survey, each participant was asked to navigate the website where the experimental simulation of a mobile advertisement service was provided. The results showed that three (3) out of five (5) hypotheses were supported. First, we found that the intention to accept advertisements is positively and significantly influenced by the perceived value of personalization. Second, perceived advertisement fatigue was also found to be a strong predictor of the intention to accept advertisements. However, we did not find any evidence of direct influence of privacy risks. Finally, we found that the significant moderating effect between the perceived value of personalization and advertisement fatigue. This suggests that the firms should provide effective tailored advertisement that can increase the perceived value of personalization to mitigate the negative impacts of advertisement fatigue.

• The Journal of Fisheries Business Administration
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• v.22 no.2
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• pp.75-99
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• 1991

A quantitative analysis was carried out to monitor the commercial yield level of walleye pollock Theragra chalcogramma in the east coast of Korea, based on available data on catch and fishing effort, catch per unit of effort including fish prices from 1911 to 1988, using a traditional yield model. The results from the quantitative assessment were based to estimate maximum economic yield (MEY) and optimal fishing effort (E-opt) at MEY. On the other hand, interaction aspects between danish seine fishery and trawl fishery mainly targeting walleye pollock in the east coast of Korea were studied to predict optimal situation in fishing effort level from economic point of view which gives the most benefits to the two fisheries. Total production of walleye pollock in 1911 when its catch record was begun for the first time was about 12, 000 metric tons(M/T), and then the catch trend maintained nearly at the level of 50, 000 M/T per annum, showing a decreasing trend until 1930. The highest production from historical data base on walleye pollock fishery statistics was from the years in 1939 and 1940, about 270, 000 M/T and 26, 000 M/T, respectively. No production of the fish species was recorded during the years from 1943 to 1947, and from 1949 to 1951. From 1952 onwards annual production was only available from the southern part of 38$^{\circ}$N in the east coast. During two decades from 1952 to 1970, the production had sustained about less than 30, 000 M/T every year. Annual production showed an increasing trend from 1971, reaching a maximum level of approximately 162, 000 M/T in 1981. Afterwards, it has deceased sharply year after year and amounted to 180, 000 M/T in 1988. The catch composition of walleye pollock for different fishery segments during 1970~1988 showed that more than 70% of the total catch was from danish seine fishery until 1977 but from 1978 onwards, the catch proportion did not differ from one another, accounting for the nearly same proportion. Catch per unit of effort (CPUE) for both danish seine fishery and trawl fishery maintained a decline tendency after 1977 when the values of CPUE were at level of 800 kg/haul for the former fishery and 1, 300 kg/haul for the latter fishery, respectively. CPUEs of gillnet fishery during 1980~1983 increased to about 3.5 times as high value as in the years, 1970~1979 and during 1987~1988 it decreased again to the level of the years, 1970~1978. The bottom longline fishery's CPUE wa at a very low level (20 kg/basket) through the whole study years, with exception of the value (60 kg/basket) in 1980. Fishing grounds of walleye pollock in the east coast of Korea showed a very limited distribution range. Danish seine fishery concentrated fishing around the coastal areas of Sokcho and Jumunjin during January~February and October~December. Distributions of fishing grounds of trawl fishery were the areas along the coastal regions in the central part of the east coast. Gillnet and bottom longline fisheries fished walleye pollock mainly in the areas of around Sokcho and Jumunjin during January~February and December. Relationship between CPUEs' values from danish seine fishery and trawl fishery was used to standardize fishing effort to apply to surplus production model for estimating maximum sustainable yield (MSY) and optimum fish effort (F-opt) at MSY. The results suggested a MSY of 114, 000 M/T with an estimated F-opt of 173, 000 hauls per year. Based on the estimates of MSY and F-opt, MEY was estimated to be about 94, 000 M/T with a range of 81, 000 to 103, 000 M/T and E-opt 100, 000 hauls per year with a range of 80, 000 to 120, 000 hauls. The estimated values of MEY and E-opt corresponded to 82% of MSY and 58% of F-opt, respectively. An optimal situation in the fishing effort level, which can envisage either simultaneously maximum yield or maximum benefit for both danish seine fishery and trawl fishery, was determined from relationship between revenue and cost of running the fleet : the optimal fishing effort of danish seine fishery was about 52, 000 hauls per year, corresponding to 50 danish seiners and 27, 000 hauls per year which is equal nearly to 36 trawlers, respectively. It was anticipated that the net income from sustainable yield estimated from the respective optimal fishing effort of the two fisheries will be about 3, 800 million won for danish seine fishery and 1, 000 million won for trawl fishery.

• Journal of Hospice and Palliative Care
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• v.19 no.1
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• pp.61-69
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• 2016

Purpose: It is important to alleviate care burden for terminal cancer patients and their families. This study investigated the factors associated with care burden among family caregivers (FCs) of terminally ill cancer patients. Methods: We analyzed data from 289 FCs of terminal cancer patients who were admitted to palliative care units of seven medical centers in Korea. Care burden was assessed using the Korean version of Caregiver Reaction Assessment (CRA) scale which comprises five domains. A multivariate logistic regression model with stepwise variable selection was used to identify factors associated with care burden. Results: Diverse associating factors were identified in each CRA domain. Emotional factors had broad influence on care burden. FCs with emotional distress were more likely to experience changes to their daily routine (adjusted odds ratio (aOR), 2.54; 95% confidence interval (CI), 1.29~5.02), lack of family support (aOR, 2.27; 95% CI, 1.04~4.97) and health issues (aOR, 5.44; 2.50~11.88). Family functionality clearly reflected a lack of support, and severe family dysfunction was linked to financial issues as well. FCs without religion or comorbid conditions felt more burdened. The caregiving duration and daily caregiving hours significantly predicted FCs' lifestyle changes and physical burden. FCs who were employed, had weak social support or could not visit frequently, had a low self-esteem. Conclusion: This study indicates that it is helpful to understand FCs' emotional status and family functions to assess their care burden. Thus, efforts are needed to lessen their financial burden through social support systems.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.4
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• pp.377-392
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• 2017

A set of BFM (Brute Force Method) simulations with the CMAQ (Community Multiscale Air Quality) model were conducted in order to estimate self-contributions and conversion rates of PPM (Primary $PM_{2.5}$), $NO_x$, $SO_2$, $NH_3$, and VOC emissions to $PM_{2.5}$ concentrations over the SMA (Seoul Metropolitan Area). CAPSS (Clean Air Policy Support System) 2013 EI (emissions inventory) from the NIER (National Institute of Environmental Research) was used for the base and sensitivity simulations. SCCs (Source Classification Codes) in the EI were utilized to group the emissions into area, mobile, and point source categories. PPM and $PM_{2.5}$ precursor emissions from each source category were reduced by 50%. In turn, air quality was simulated with CMAQ during January, April, July, and October in 2014 for the BFM runs. In this study, seasonal variations of SMA $PM_{2.5}$ self-sensitivities to PPM, $SO_2$, and $NH_3$ emissions can be observed even when the seasonal emission rates are almost identical. For example, when the mobile PPM emissions from the SMA were 634 TPM (Tons Per Month) and 603 TPM in January and July, self-contributions of the emissions to monthly mean $PM_{2.5}$ were $2.7{\mu}g/m^3$ and $1.3{\mu}g/m^3$ for the months, respectively. Similarly, while $NH_3$ emissions from area sources were 4,169 TPM and 3,951 TPM in January and July, the self-contributions to monthly mean $PM_{2.5}$ for the months were $2.0{\mu}g/m^3$ and $4.4{\mu}g/m^3$, respectively. Meanwhile, emission-to-$PM_{2.5}$ conversion rates of precursors vary among source categories. For instance, the annual mean conversion rates of the SMA mobile, area, and point sources were 19.3, 10.8, and $6.6{\mu}g/m^3/10^6TPY$ for $SO_2$ emissions while those rates for PPM emissions were 268.6, 207.7, and 181.5 (${\mu}g/m^3/10^6TPY$), respectively, over the region. The results demonstrate that SMA $PM_{2.5}$ responses to the same amount of reduction in precursor emissions differ for source categories and in time (e.g. seasons), which is important when the cost-benefit analysis is conducted during air quality improvement planning. On the other hand, annual mean $PM_{2.5}$ sensitivities to the SMA $NO_x$ emissions remains still negative even after a 50% reduction in emission category which implies that more aggressive $NO_x$ reductions are required for the SMA to overcome '$NO_x$ disbenefit' under the base condition.

• Journal of dental hygiene science
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• v.18 no.6
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• pp.327-339
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• 2018

This study aimed to provide basic data for establishing the clinical basis for dental hygienist-led dental hygiene process of care by identifying multiple risk factors for self-support program participants in Gangneung city; we also compared oral health status and behavioral changes through customized oral health care. Four dental hygienists who were evaluated for degree of conformity provided dental hygiene process of care to eight self-support program participants who were selected as having an oral health risk among people in the self-support center. The clinical indicators measured during dental hygiene assessment and evaluation and behavioral changes due to dental hygiene intervention were compared and analyzed. With respect to clinical indicators, at the time of probe, the retention rate of patients with gingival bleeding decreased from 61.4% to 14.7% after intervention (p=0.004). Furthermore, the retention rate of patients with a periodontal pocket >4 mm decreased from 15.6% to 5.8% (p=0.001). The average modified O'Leary index of the patients improved from 23 to 40 (p=0.002). Previously, all eight subjects used the vertical or horizontal method of brushing; after dental hygiene care interventions regarding method and frequency of toothbrushing, use of oral care products, and individual interventions, they started using the rolling or Bass method of toothbrushing. Four of eight subjects reported using interdental toothbrushes after intervention. As a result of applying the change model to the transtheoretical behavior change of the subject, the result of strengthening the health behavior was confirmed. For promotion of oral health by the prevention-centered incremental oral health care system, dental hygienist-led dental hygiene management and maintenance is essential. It is thought that continuous research, such as for feasibility evaluation, cost benefit analysis, and preparation of legal systems, is needed to establish and activate dental hygiene management.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.