• Journal of Service Research and Studies
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• v.13 no.2
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• pp.130-145
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• 2023

The digital transformation of finance is accelerating, and digital banking has already become a major banking channel. Banks have traditionally placed importance on CRM(Customer Relationship Management) and have tried to retain their loyal customers, who contribute significantly to the bank, such as long-term transactions, holding accounts with a certain balance or more, and holding loans. In this situation, this study exploratorily analyzed the consumer behavior of digital banking deposits in a major bank of Korea(1,145 samples). Statistical analysis was performed using SPSS. The main findings of the study are summarized as follows. It was found that there were differences of consumer behavior in digital banking deposits by generation, and the MZ generation used digital banking more on holidays than other generations. As a result of analyzing the behavior of existing loyal customers and regular customers of digital banking deposit, there was a significant difference in both the amount and period of the deposit. It was confirmed that the existing loyal customers of the bank also engage in consumer behavior that contributes to the bank in digital banking. In addition, the interaction between the customer type and the date of sign up for the deposit period, which is the goal setting of financial consumers, it was found that there was a significant effect. This study empirically analyzed the consumer behavior of digital banking in a situation where decrease of bank branches and encounters with digital banking. The major concepts of the consumer behavior theory are Loyal Customer, Goal Pursuit, and Habit, which were confirmed in an example of digital banking. The results of this study can suggest practical implications for existing banks and Internet-only banks, including the importance of customer management in digital banking.

• Journal of Navigation and Port Research
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• v.47 no.3
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• pp.147-154
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• 2023

This study aims to determine the necessity, role, utilization, and operation and management plan in relation to the underwater space platform where humans can newly reside. It provides a comprehensive opinion on the need for creating undersea space and operation plans based on opinions of industry-university-affiliated organizations involved in the R&D project of the Ministry of Maritime Affairs and Fisheries for the utilization of undersea space and external experts participating in marine technology development. In this study, a survey was conducted on researchers participating in the construction of a Korean submarine space platform. FGI was conducted on marine technology development experts. Results were then derived. As a result of the analysis, the need for subsea space construction was found to be high. As for the role of subsea space, the most common opinion was to develop technology for utilizing subsea space and to secure marine science research functions. It was found that the creation of subsea space would have a positive impact on the domestic industry, especially the deep-sea development industry and the shipbuilding/offshore structure industry. In terms of utilization, after the end of the seabed space test bed, the response to utilization as a marine observation base and marine ecosystem research had the highest proportion. As for expected inconvenience, discomfort in the psychological environment was the highest. Experts suggest that securing a continuous budget is most important for stable operation in the future and that securing a manpower budget is essential for itemized budgets. In addition, it was judged that it would be appropriate to establish a prior agreement from the time of the prior agreement and prepare a countermeasure before proceeding with the project in order to ensure ownership issues, consignment management issues, and cost issues when using the project after the end of the project.

• Korean Journal of Cognitive Science
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• v.34 no.3
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• pp.153-180
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• 2023

Previous research on the action effect had shown how simple action towards a stimulus can enhance the processing of that stimulus in subsequent visual search task (Buttaccio & Hahn, 2011; Weidler & Abrams, 2014). In four experiments, we investigated whether semantic representation of action word can induce the same attentional boost towards that stimulus and whether the type of action performed can modulate the action effect. In experiment 1, we replicated the same experimental paradigm displayed in previous studies. Participants were first shown an action word cue - "go" or "no". When the action cue was "go", participants were to press a designated key, but not to when the action cue was "no". Next, participants performed a visual search task, in which they reported the orientation of a tilted bar. The target could appear on top of the previously shown prime object (valid), or not (invalid). Reaction times (RTs) to the search task were measure for analysis and comparison, and the action effect had been replicated. In experiment 2, participants were instructed to respond with the keyboard for the action task, and to respond with the joystick for the visual search task. In experiment 3, participants were instructed not to press any key on the onset of prime, and then perform the visual search task to isolate the effect of semantic representation. Lastly, in experiment 4, participants were instructed to press separate keys for "go" and "no" on the onset of prime, and then perform the visual search task. Results indicate that semantic representation alone did not modulate the action effect, regardless of type of action and medium of action.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.13 no.1
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• pp.1-14
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• 2008

Eight comprehensive oceanographic cruises on a squared $30{\times}30\;km$ area have been made to investigate the short and long-term impacts on the water qualities due to the sand mining operations at Exclusive Economic Zone (EEZ) in the central Yellow Sea from 2004 to 2007. The area was categorized to 'Sand Mining Zone', 'Potentially Affected Zone', and 'Reference Zone'. The investigation covered suspended solids, nutrients (nitrate, nitrite, ammonium, phosphate), and chlorophyll-a in seawater and several parameters such as water temperature, salinity, pH, and ORP. Additionally, several intensive water collections were made to trace the suspended solids and other parameters along the turbid water by sand mining activities. The comprehensive investigation showed that suspended solids, nitrate, chlorophyll-a and ORP be sensitively responding parameters of seawater by sand mining operations. The intensive collection of seawater near the sand mining operation revealed that each parameter show different distribution pattern: suspended solids showed an oval-shaped distribution of the north-south direction of 8 km wide and the east-west direction of 5 km wide at the surface and bottom layers. On the other hand, phosphate showed so narrow distribution not to traceable. Also ammonium showed a limited distribution, but its boundary was connected to the high nitrate and chlorophyll-a concentrations with high N/P ratios. From the last 4 years of the comprehensive and intensive investigations, we found that suspended solids, ammonium, nitrate, chlorophyll-a, and ORP revealed the sensitive parameters of water quality for tracing the sand mining operations in seawater. Especially suspended solids and ORP would be useful tracers for monitoring the water qualities of remote area like EEZ in Yellow Sea.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.17-35
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• 2015

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1565-1576
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• 2023

An atmospheric correction algorithm based on the radiative transfer model is required to obtain remote-sensing reflectance (R_rs) from the Geostationary Ocean Color Imager-II (GOCI-II) observed at the top-of-atmosphere. This R_rs derived from the atmospheric correction is utilized to estimate various marine environmental parameters such as chlorophyll-a concentration, total suspended materials concentration, and absorption of dissolved organic matter. Therefore, an atmospheric correction is a fundamental algorithm as it significantly impacts the reliability of all other color products. However, in clear waters, for example, atmospheric path radiance exceeds more than ten times higher than the water-leaving radiance in the blue wavelengths. This implies atmospheric correction is a highly error-sensitive process with a 1% error in estimating atmospheric radiance in the atmospheric correction process can cause more than 10% errors. Therefore, the quality assessment of R_rs after the atmospheric correction is essential for ensuring reliable ocean environment analysis using ocean color satellite data. In this study, a Quality Assurance (QA) algorithm based on in-situ R_rs data, which has been archived into a database using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Archive and Storage System (SeaBASS), was applied and modified to consider the different spectral characteristics of GOCI-II. This method is officially employed in the National Oceanic and Atmospheric Administration (NOAA)'s ocean color satellite data processing system. It provides quality analysis scores for R_rs ranging from 0 to 1 and classifies the water types into 23 categories. When the QA algorithm is applied to the initial phase of GOCI-II data with less calibration, it shows the highest frequency at a relatively low score of 0.625. However, when the algorithm is applied to the improved GOCI-II atmospheric correction results with updated calibrations, it shows the highest frequency at a higher score of 0.875 compared to the previous results. The water types analysis using the QA algorithm indicated that parts of the East Sea, South Sea, and the Northwest Pacific Ocean are primarily characterized as relatively clear case-I waters, while the coastal areas of the Yellow Sea and the East China Sea are mainly classified as highly turbid case-II waters. We expect that the QA algorithm will support GOCI-II users in terms of not only statistically identifying R_rs resulted with significant errors but also more reliable calibration with quality assured data. The algorithm will be included in the level-2 flag data provided with GOCI-II atmospheric correction.