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Development of a Performance Reference Model (PRM) for Ubiquitous City Operations (U-City 전략 성과 참조모델로서의 운영성과 측정 지표체계 개발에 대한 연구)

  • Park, Dong-Wan;Lee, Jung-Hoon;Kim, Jae-Min
    • The Journal of Society for e-Business Studies
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    • v.15 no.3
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    • pp.25-44
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    • 2010
  • In recent years, Ubiquitous City (u-City), the integrated and convergence of ubiquitous services, infrastructure, technologies and city management of the new future development city, is being initiated by the Korean government and local authorities as their new national growth engine. However, a performance measurement system for evaluating and monitoring the impacts of U-City implementation is yet to be established. This paper aims to develop an integrated performance management system (PMS) and extensively used as a tool for managing performance activities to support the visions and goals of the u-City operations. Based on current reviews on the literature and interviews with experts drew Critical Success Factors (CSF) and Key Performance Indicators (KPI) by four different measurement domains including U-City services, infrastructure, technologies, management and developed into an integrated performance measurement system based on the Balanced Scored Card (BSC) perspective. The system also provides number of examples of 'u-City Strategy Map' which illustrates a causal relationship between CSFs to execute u-City visions and goals.

A Study on the Effect of Brand Familiarity and Brand image on Intending Purchase and Revisiting by Coupon Property. -Focused on Chicken Speciality Store- (쿠폰특성에 따른 브랜드 친숙도와 브랜드 이미지가 구매 의도와 재 방문 의도에 관한 연구 - 국내 치킨 산업을 중심으로 -)

  • Shin, Gun-Chu;Jang, Jae-Nam
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.1
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    • pp.295-306
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    • 2010
  • The company have get the most out of coupon that is very useful to draw on consumer with sensitive the price, low the br loyalty to induct the direct buying intention. The effect of the coupon is a hard fact to an aid of working out successful strategy by the results that many scholar studied for long time. But the results of research was centered upon examining to influence br image company's sales, gains for guessing exchange action of coupon. Antecedent researches of our country is a lot of coupon combination discount card for drawing on revisiting making new consumer. The purpose of the study is to identify how to influence br familiarity br image into intending purchase revisiting by coupon property. In this study, collage man, worker located in Seoul Kyunggi province were sampled by convenience sampling. As a result, Br familiarity br image affect affirmatively intending purchase revisiting by coupon property.

Satisfaction about Internet Shopping Mall and Purchasing Intention of Fashion Goods - Difference of Department of Fashion Design and Non Fashion Design - (인터넷쇼핑몰에 대(對)한 만족도(滿足度)와 의류제품구매의도(衣類製品購買意圖)의 차이(差異) - 의상전공(衣裳專攻)과 비전공(非專攻) 대학생(大學生)의 비교(比較) -)

  • Park, Hea-Ryung;Kim, Si-Wuel
    • Journal of Fashion Business
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    • v.5 no.3
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    • pp.19-34
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    • 2001
  • The purpose of this study was to investigate the differences of the general characteristics of subjects, the utilizing realities and the degree of satisfaction in the shopping mall and purchasing intention between group I that specializes in fashion design and group II that doesn't specialize in it. The results are summarized as the following six aspects. First, as a result of the general characteristics of subjects and the utilizing realities, the most different variables were the visiting frequency and the goods purchasing frequency. The result indicated that group II took more interests than group I. Second, as a result of the degree of satisfaction according to the factors of the general characteristics of subjects and the utilizing realities in the shopping mall, both group I and group II showed high degree of satisfaction in factor 1 (variety of event) whereas both groups showed relatively low degree of satisfaction in factor 3 (variety of goods). Third, as a result of the degree of satisfaction according to the general characteristics of subjects and the utilizing realities, group I showed significant differences in the degree of satisfaction according to a monthly allowance of pocket money and goods purchasing frequency and group II showed significant differences in the degree of satisfaction according to grade, the utilizing reason, goods purchasing frequency. Fourth, as a result of purchasing intention of fashion goods according to the general characteristics of subjects and the utilizing realities, group I showed the higher purchasing intention of fashion goods in group that the terms of payment was on-line payment than group that they was credit card. On the other hand, group II showed a significant difference in grade, which showed that group that was above third grade had the higher purchasing intention of fashion goods than group that was under third grade. Fifth, as a result of purchasing intention of fashion goods according to the degree of satisfaction, group I showed significant differences in factor 1 and factor 3 among the degree of satisfaction. In other words, group that had high degree of satisfaction in factor 1 showed the higher purchasing intention of fashion goods than other groups and group that had medium degree of satisfaction in factor 3 showed the higher purchasing intention of fashion goods than other groups. In group II, on the other hands, group that had high total degree of satisfaction showed the higher purchasing intention of fashion goods than other groups. Sixth, as a result of relative influencing power of independent variable with respect to purchasing intention of fashion goods in group I, the higher degree of satisfaction in factor 1 and the lower degree of satisfaction in factor 3 showed, the higher purchasing intention of fashion goods showed. As a result of relative influencing power of independent variable in group II, however, the higher grade and the higher degree of satisfaction in factor 1 showed, the higher purchasing intention of fashion goods showed.

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Implementation of payment settlement system through Cyber Bank for Electronic Commerce (전자상거래용 사이버뱅크의 지불결제시스템 구축)

  • Kim, Moon-Shik;Lee, Eun-Seok
    • The KIPS Transactions:PartD
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    • v.15D no.1
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    • pp.121-130
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    • 2008
  • In line with the enhanced weight and variety of electronic commerce in business activities, new type of payment settlement and banking system which will enable to store, create and transfer values from the existing method of payment settlement is highly required. Cyber Banking system draws strong attention being the solution of there requirements. The existing Cyber Banking system has the difficulty of operation, administration, in addition to the problem of initial facility investment of big amount, resulted from the usage of the current business process. As the existing Cyber Bank system is unable to carry out the function of storing, creating, and transferring values due to the adoption conventional credit card system instead of the application of non-stop payment system between the seller and buyer. As a result, current Cyber Bank system still imply the deficiency of non-performing cash payment function on internet. This paper describes (1) an integrated application process, One Process One Input (OPOI) which is essential for software development of the Cyber Bank, (2) an application process of payment settlement system to be applied to the electronic commerce in Internet. And then, with these for a basis, (3) design and implementation of payment settlement system through CyberBank for Electronic Commerce. Consequently, by means of this suggested process, we could attempt to solve the problem of existing Cyber Bank system and further to explore the possibility of advanced Cyber Banking being the non-stop payment settlement system. The effectiveness of this suggested system has been practically confirmed.

Artificial Intelligence Techniques for Predicting Online Peer-to-Peer(P2P) Loan Default (인공지능기법을 이용한 온라인 P2P 대출거래의 채무불이행 예측에 관한 실증연구)

  • Bae, Jae Kwon;Lee, Seung Yeon;Seo, Hee Jin
    • The Journal of Society for e-Business Studies
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    • v.23 no.3
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    • pp.207-224
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    • 2018
  • In this article, an empirical study was conducted by using public dataset from Lending Club Corporation, the largest online peer-to-peer (P2P) lending in the world. We explore significant predictor variables related to P2P lending default that housing situation, length of employment, average current balance, debt-to-income ratio, loan amount, loan purpose, interest rate, public records, number of finance trades, total credit/credit limit, number of delinquent accounts, number of mortgage accounts, and number of bank card accounts are significant factors to loan funded successful on Lending Club platform. We developed online P2P lending default prediction models using discriminant analysis, logistic regression, neural networks, and decision trees (i.e., CART and C5.0) in order to predict P2P loan default. To verify the feasibility and effectiveness of P2P lending default prediction models, borrower loan data and credit data used in this study. Empirical results indicated that neural networks outperforms other classifiers such as discriminant analysis, logistic regression, CART, and C5.0. Neural networks always outperforms other classifiers in P2P loan default prediction.

Quantitative Estimation Method for ML Model Performance Change, Due to Concept Drift (Concept Drift에 의한 ML 모델 성능 변화의 정량적 추정 방법)

  • Soon-Hong An;Hoon-Suk Lee;Seung-Hoon Kim
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.6
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    • pp.259-266
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    • 2023
  • It is very difficult to measure the performance of the machine learning model in the business service stage. Therefore, managing the performance of the model through the operational department is not done effectively. Academically, various studies have been conducted on the concept drift detection method to determine whether the model status is appropriate. The operational department wants to know quantitatively the performance of the operating model, but concept drift can only detect the state of the model in relation to the data, it cannot estimate the quantitative performance of the model. In this study, we propose a performance prediction model (PPM) that quantitatively estimates precision through the statistics of concept drift. The proposed model induces artificial drift in the sampling data extracted from the training data, measures the precision of the sampling data, creates a dataset of drift and precision, and learns it. Then, the difference between the actual precision and the predicted precision is compared through the test data to correct the error of the performance prediction model. The proposed PPM was applied to two models, a loan underwriting model and a credit card fraud detection model that can be used in real business. It was confirmed that the precision was effectively predicted.

Factors Affecting Consumers' Acceptance of e-Commerce Consumer Credit Service: Multiple Group Path Analysis by Naver Shopping and Coupang (이커머스 후불결제(BNPL) 수용에 영향을 미치는 요인: 네이버쇼핑과 쿠팡 간 다중집단 비교)

  • Kim, Su Jin;Mo, Jeonghoon
    • The Journal of Society for e-Business Studies
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    • v.27 no.2
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    • pp.105-135
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    • 2022
  • As COVID-19 has led to a surge in e-commerce Buy Now Pay Later(BNPL) has become preferred choice among millennials. In Korea Coupang followed by Naver Pay offers a deferred payment, aiming to create customer lock-in effect, save credit card processing fee and lay the groundwork for entering into new financial services. However the literature related to the influential factors of customers' usage intention toward a deferred payment is scarce. For the study, a multi-group analysis was carried out to find differences between Naver shopping and Coupang. The results revealed that the important factors that affect a deferred payment adoption were compatibility, impulsive buying tendency in Naver shopping, whereas compatibility, relative advantage, additional value in Coupang(listed in order of most important). In addition, impulsive buying tendency had a positive effect on adoption intention in Naver shopping and on perceived risk in Coupang. The results imply that Naver shopping need to focus on managing delinquency while Coupang should provide sufficient information on how late fees and credit rating downgrade work and try not to make a deferred payment option stand out. In order to increase adoption rate it is recommendable to narrow down target segment of a deferred payment and expand it to a specialized vertical such as travel.

A Big Data Analysis Methodology for Examining Emerging Trend Zones Identified by SNS Users: Focusing on the Spatial Analysis Using Instagram Data (SNS 사용자에 의해 형성된 트렌드 중심지 도출을 위한 빅 데이터 분석 방법론 연구: 인스타그램 데이터 활용 공간분석을 중심으로)

  • Il Sup Lee;Kyung Kyu Kim;Ae Ri Lee
    • Information Systems Review
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    • v.20 no.2
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    • pp.63-85
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    • 2018
  • Emerging hotspot and trendy areas are formed into alleys and blocks with the help of viral effects among social network services (SNS) users called "Golmogleo." These users search for every corner of the alleys to share and promote their own favorite places through SNS. An analysis of hot places is limited if it is only based on macroeconomic indicators such as commercial area data published by national organizations, large-scale visiting facilities, and commuter figures. Careful analyses based on consumers' actual activities are needed. This study develops a "social big data analysis methodology" using Instagram data, which is one of the most popular SNSs suitable to identify recent consumer trends. We build a spatial analysis model using Local Moran's I. Results show that our model identifies new trend zones on the basis of posting data in Instagram, which are not included in the commercial information prepared by national organizations. The proposed analysis methodology enables better identification of the latest trend areas formulated by SNS user activities. It also provides practical information for start-ups, small business owners, and alley merchants for marketing purposes. This analytical methodology can be applied to future studies on social big data analysis.

Risk Analysis of Household Debt in Korea: Using Micro CB Data (개인CB 자료를 이용한 우리나라 가계의 부채상환위험 분석)

  • Hahm, Joon-Ho;Kim, Jung In;Lee, Young Sook
    • KDI Journal of Economic Policy
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    • v.32 no.4
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    • pp.1-34
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    • 2010
  • We conduct a comprehensive risk analysis of household debt in Korea for the first time using the whole sample credit bureau (CB) data of 2.2 million individual debtors. After analysing debt service capacity profiles of debtor groups classified by the borrower characteristics such as income, age, occupation, credit scoring, and the type of creditor business companies, we investigate the impact of interest rate and income changes on debt service-to-income ratios (DTIs) and default rates of respective debtor groups. Empirical results indicate that debt service burdens are relatively high for low income wage earners, high income self-employed, low income capital and card loan holders, and high income mutual savings loan holders. We also find that debtors from multiple financial companies are particularly weak in their debt service capacity. The scenario analysis indicates that financial companies, with the current level of capital buffers, may be able to absorb negative consequences arising from the increase in DTIs and loan default rates if the interest rate and income changes remain modest. However, the negative consequences may fall disproportionately on non-bank financial companies such as capital, credit card, and mutual savings banks, whose debtors' DTIs are already high. We also find that the refinancing risk of household debt is relatively high in Korea as more than half of household mortgage debts are bullet loans. As the DTIs of mortgage loan holders are already high, under the current DTI regulation, mortgage loans may not be readily refinanced especially when the interest rate rises. Disruptions in mortgage loan refinancing may put downward pressure on housing prices, which may in turn magnify refinancing risk under the current loan-to-value (LTV) regulation. Overall our analysis suggests that, for more effective monitoring of household debt risk, it is necessary to combine existing surveillance schemes based on macro aggregate indicators with more comprehensive and detailed risk analyses based on micro individual data.

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The Mediating Role of Perceived Risk in the Relationships Between Enduring Product Involvement and Trust Expectation (지속적 제품관여도와 소비자 요구신뢰수준 간의 영향관계: 인지된 위험의 매개 역할에 대한 실증분석을 중심으로)

  • Hong, Ilyoo B.;Kim, Taeha;Cha, Hoon S.
    • Asia pacific journal of information systems
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    • v.23 no.4
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    • pp.103-128
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    • 2013
  • When a consumer needs a product or service and multiple sellers are available online, the process of selecting a seller to buy online from is complex since the process involves many behavioral dimensions that have to be taken into account. As a part of this selection process, consumers may set minimum trust expectation that can be used to screen out less trustworthy sellers. In the previous research, the level of consumers' trust expectation has been anchored on two important factors: product involvement and perceived risk. Product involvement refers to the extent to which a consumer perceives a specific product important. Thus, the higher product involvement may result in the higher trust expectation in sellers. On the other hand, other related studies found that when consumers perceived a higher level of risk (e.g., credit card fraud risk), they set higher trust expectation as well. While abundant research exists addressing the relationship between product involvement and perceived risk, little attention has been paid to the integrative view of the link between the two constructs and their impacts on the trust expectation. The present paper is a step toward filling this research gap. The purpose of this paper is to understand the process by which a consumer chooses an online merchant by examining the relationships among product involvement, perceived risk, trust expectation, and intention to buy from an e-tailer. We specifically focus on the mediating role of perceived risk in the relationships between enduring product involvement and the trust expectation. That is, we question whether product involvement affects the trust expectation directly without mediation or indirectly mediated by perceived risk. The research model with four hypotheses was initially tested using data gathered from 635 respondents through an online survey method. The structural equation modeling technique with partial least square was used to validate the instrument and the proposed model. The results showed that three out of the four hypotheses formulated were supported. First, we found that the intention to buy from a digital storefront is positively and significantly influenced by the trust expectation, providing support for H4 (trust expectation ${\rightarrow}$ purchase intention). Second, perceived risk was found to be a strong predictor of trust expectation, supporting H2 as well (perceived risk ${\rightarrow}$ trust expectation). Third, we did not find any evidence of direct influence of product involvement, which caused H3 to be rejected (product involvement ${\rightarrow}$ trust expectation). Finally, we found significant positive relationship between product involvement and perceived risk (H1: product involvement ${\rightarrow}$ perceived risk), which suggests that the possibility of complete mediation of perceived risk in the relationship between enduring product involvement and the trust expectation. As a result, we conducted an additional test for the mediation effect by comparing the original model with the revised model without the mediator variable of perceived risk. Indeed, we found that there exists a strong influence of product involvement on the trust expectation (by intentionally eliminating the variable of perceived risk) that was suppressed (i.e., mediated) by the perceived risk in the original model. The Sobel test statistically confirmed the complete mediation effect. Results of this study offer the following key findings. First, enduring product involvement is positively related to perceived risk, implying that the higher a consumer is enduringly involved with a given product, the greater risk he or she is likely to perceive with regards to the online purchase of the product. Second, perceived risk is positively related to trust expectation. A consumer with great risk perceptions concerning the online purchase is likely to buy from a highly trustworthy online merchant, thereby mitigating potential risks. Finally, product involvement was found to have no direct influence on trust expectation, but the relationship between the two constructs was indirect and mediated by the perceived risk. This is perhaps an important theoretical integration of two separate streams of literature on product involvement and perceived risk. The present research also provides useful implications for practitioners as well as academicians. First, one implication for practicing managers in online retail stores is that they should invest in reducing the perceived risk of consumers in order to lower down the trust expectation and thus increasing the consumer's intention to purchase products or services. Second, an academic implication is that perceived risk mediates the relationship between enduring product involvement and trust expectation. Further research is needed to elaborate the theoretical relationships among the constructs under consideration.