• Korean Management Science Review
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• v.33 no.3
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• pp.65-87
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• 2016

Being the FinTech technologies rapidly developed, the non face-to-face private loan market is also growing dramatically. While the real-world interests in this market are keen, the empirical studies on the issue are few compared to its prospective impact on credit loan market. This paper suggests a credit scoring model for the non face-to-face private loan employing the ratings approach (the absolute measurement method) of AHP. Analyzing a sample of data consisting of 460,000 transaction records over an 8-year period in the United States, we develop a scoring model for the non face-to-face private loan screening, and validate the model for the practical usage. Conducting sensitivity analysis, we suggest customized cut-off points for the loan execution to suit each individual loan institution's need.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.3
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• pp.1-19
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• 2002

Recently, increasing attention has been paid to building a successful software process in Information System(IS) implementation. This study establishes software process model as a key predictor of organizational performance. We propose a theoretical framework for capability maturity model derived from the Software Engineering Institute(SEI). This paper identify the process-related variables, financial performance and non-financial performance from the relevant literature and clarify the concept of software process by distinguishing between its component and determinants. We then examine the impact of software process on organizational performance. Hypotheses on software process were tested for 36 enterprises including 118 organizational units. Results indicate that software process capability may serve as a key predictor of organizational performance. Software process maturity found to be positively influenced on the financial and non-financial performance, while investment of information technology as a mediating variable not significantly affected to the performance.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.3
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• pp.59-74
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• 2016

Electricity sales are directly measured from individual consumers, which could minimize the time gap between data collection and public announcement. Furthermore, industrial electricity sales are highly linked with production and output. Therefore, industrial electricity consumption can be used to track production and output in real time. By using the high-frequency data of industrial electricity sales, this study develops the daily electricity business index (DEBI) to capture the daily economic status. The steps used to formulate DEBI are as follows: (1)selection of the explanatory variables and period, (2) amendment of the seasonal adjustment to eliminate daily temperature and effective day effects, (3) estimation of the weighted value via variables by using PCA, (4) calculation of DEBI and commencement of validation tests. Our empirical analysis and the Hodrick-Prescott filter analysis show that DEBI is highly related to existing economic indices.

• Journal of Distribution Science
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• v.11 no.3
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• pp.5-11
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• 2013

Purpose - Going concern is one of fundamental concepts in accounting and auditing and sometimes the assessment of a company's going concern status that is a tough process. Various going concern prediction models' based on statistical and data mining methods help auditors and stakeholders suggested in the previous literature. Research design - This paper employs a data mining approach to prediction of going concern status of Iranian firms listed in Tehran Stock Exchange using Particle Swarm Optimization. To reach this goal, at the first step, we used the stepwise discriminant analysis it is selected the final variables from among of 42 variables and in the second stage; we applied a grid-search technique using 10-fold cross-validation to find out the optimal model. Results - The empirical tests show that the particle swarm optimization (PSO) model reached 99.92% and 99.28% accuracy rates for training and holdout data. Conclusions - The authors conclude that PSO model is applicable for prediction going concern of Iranian listed companies.

• Bulletin of the Korean Chemical Society
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• v.29 no.10
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• pp.2009-2016
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• 2008

The relationship between thermal decomposition temperature and structure of a new data set of eighty monomers of different polymers were studied by multiple linear regression (MLR). The stepwise method was used in order to variable selection. The best descriptors were selected from over 1400 descriptors including; topological, geometrical, electronic and hybrid descriptors. The effect of number of descriptors on the correlation coefficient (R) and F-ratio were considered. Two models were suggested, one model having four descriptors ($R^2$ = 0.894, $Q^2_{cv}$ = 0.900, F = 172.1) and other model involving 13 descriptors ($R^2$ = 0.956, $Q^2_{cv}$ = 0.956, F = 125.4).

• Journal of Information Technology Applications and Management
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• v.16 no.4
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• pp.185-203
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• 2009

The literature reveals that service quality is critical determinants affecting customer satisfaction in the retail industry. Recent online B2C studies also show that service quality significantly influences online customer satisfaction. However, research on analyzing antecedents to determine the service quality level of online shopping has not been sufficiently reported. Moreover, the offline synergy effect on the Internet shopping mall has been presented mostly at a conceptual level. The purpose of this study is to investigate key managerial variables exploiting offline synergy, including pure online attributes, that impact on service quality of the click and mortar Internet shopping mall. A survey was conducted for empirical validation of the hypotheses. The results indicate that core offline synergy factors significantly enhance the perceived service quality level of the Internet shopping mall. Implications, limitations, and future research directions are also discussed.

• Journal of Environmental Science International
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• v.14 no.10
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• pp.911-917
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• 2005

A comparison between the estimated chlorophyll a from OSMI, the SeaWiFS and the chlorophyll a measured from the research cruises of National Fisheries Research and Development Institute was made. The updated empirical algorithm for calibrating and validating of the estimated chlorophyll a in the East China Sea was formulated by relationship between the estimated chlorophyll a and the field one. The relationship between the chlorophyll a and the band ratio(nLw490/555) was still highest in the OSMI data after launching of KOMPSAT satellite. The distributions of OSMI chlorophyll a were compared with those of sea surface temperature, zooplankton biomass, and catch amounts of the Pacific mackerel in the East China Sea. In case of the relationships in specially winter seasons of 2002 and 2004, the zooplankton and the fish were totally depended on the distributions of SST than those of chlorophyll a.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2009.04a
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• pp.269-270
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• 2009

This study builds a sediment rating curve using the measured sediment yield and the simulated soil erosion by a GIS-embedded empirical model. Then the structured sediment rating curve is used to determine the SDR on a basin scale in southern Korea. The whole data(year of 2002-2008) are divided into two groups and the first group(year of 2002-2005) is used for calibration, while the other is used for validation. Two cases(rainfall amount and rainfall intensity) are analyzed to consider the rainfall runoff erosivity factor in simulating soil erosion. The results show the derived SDR provides reasonable accuracy and rainfall intensity gives better performance in calculating soil erosion than rainfall amount.

• Asia pacific journal of information systems
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• v.26 no.1
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• pp.124-142
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• 2016

Companies operating in social network platforms continue to improve and expand their marketing techniques. This study examines the practice of "gating", which involves virtual barriers between social network users and company content. Gates demand mandatory user endorsements, in the form of a Facebook "Likes", Twitter "retweets" etc., to gain access to company content, such as coupons and rewards,. Gating practices demand a mandatory endorsement before any content consumption takes place. Thus, while user endorsements are assumed to arise voluntarily from trusted known sources, gating practices would appear to violate this assumption. However, whether this violation lessens the effectiveness of gating practices still requires empirical validation. We investigate this question through the use of a unique panel data set that includes data on "like" endorsements obtained from a number of real-world Facebook business pages. Results of the study show that gating practices are effective for endorsement solicitation; however, gates may interfere with more traditional marketing activities.

• Journal of computational fluids engineering
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• v.18 no.2
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• pp.93-98
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• 2013

In this paper, we reported the verification of numerical simulation approach for sedimentation of the multi-size particles in a container. The comparison between experimentally measured values and numerically evaluated values on settle down process of fully mixed mixture is carried out. In an attempt to represent the natural particle size distribution, various diameters of single particles are simulated and the results are compared with the outcome of the multi-size computation. When the empirical formula for mean particle size estimation is adopted to define the sediment diameter, computation and comparison are conducted.