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The Role of Application Rank in the Extended Mobile Application Download
Bang, Youngsok,Lee, Dong-Joo The Korea Society of Management Information System 2015 Asia Pacific Journal of Information Systems Vol.25 No.3
The growing popularity of mobile application has led to researchers and practitioners needing to understand users' mobile application download behaviors. Using large-scale transaction data obtained from a leading Korean telecommunications company, we empirically explore how application download rank, which appears to users when they decide to download a new application, affects their extended mobile application download. This terminology refers to downloading an additional application in the same category as those that they have already downloaded. We also consider IT characteristics, user characteristics, and application type that might be associated with the extended application download. The analysis generates the following result. Overall, a higher rank of a new application encourages the extended application download, but the linear relationship between the rank and the extended application download disappears when critical rank points are incorporated into the model. Further, no quadratic effect of rank is found in the extended application download. Based on the results, we suggest theoretical and managerial implications.
Jialu Liu,Youngsok Bang 한국경영정보학회 2021 한국경영정보학회 학술대회논문집 Vol.2021 No.11
Do people with a high credit default risk visit different locations in a city, compared to where people with a low credit default risk visit? We propose that geosimilarity risk and the geolocation network size of people comprise a critical classifier that predicts their credit default. Two people are defined as geosimilarity network (GSN) neighbors to each other if they share a visited location during a specific period. Based on the consumer-location and loan-repayment data from a leading FinTech company in Hong Kong, we found that the GSN neighbors of a person who defaulted on a loan are approximately three times more likely to default compared to the average default rate and are approximately 4.5 times more likely to default compared to the GSN neighbors of a person who has not defaulted. The geosimilarity risk and geolocation network size significantly explain credit defaults after controlling for traditional factors such as demographics, financial ability measures, and loan characteristics. In addition, incorporating these measures into the traditional model improves the prediction accuracy of credit default by approximately 9%.
The Spillover Effects of Health Information Technology Implementation on Healthcare Quality
Yongjin Park,Youngsok Bang,Juhee Kwon 한국경영정보학회 2018 한국경영정보학회 학술대회논문집 Vol.2018 No.11
U.S. government subsidies under the HITECH Act of 2009 have boosted hospitals’ IT investments, which are expected to improve the quality of care as well as the effectiveness of healthcare management. Given the rush to adopt health information technology (HIT) throughout the continuum of care across healthcare providers, this study tries to identify the spillover effects of HIT adoption on quality of care. Using 1,965 U.S. hospital data in 232 health referral regions (HRRs), we examine how a hospital’s and its neighboring hospitals’ HIT adoptions interact with each other and how they impact readmission rates. We find that a hospital’s readmission rate is reduced by both its own and neighbors’ HIT adoption. Such effects become greater along with the focal hospital’s own adoption. We further investigate how spillover effects vary with HRRs’ different market structures and hospitals’ meaningful-use status. Our findings offer theoretical and managerial insights for both healthcare researchers and practitioners.
E-market consumers’ heterogeneity in responding to sales promotion : A case of Korean e-marketplace
Yiying Zhang,Youngsok Bang,Sangwon Kim 한국경영정보학회 2019 한국경영정보학회 학술대회논문집 Vol.2019 No.11
We empirically examine e-market consumers’ heterogeneity in responding to sales promotion. As e-market users are exposed to frequent seller discounts online, they might become less attracted to such discounts. We find that there are two different types of consumers on the e-market, those who are strongly motivated by temporal seller discounts to buy their products (H_Sens group), and those who are less motivated by such discounts (L_Sens group). Platform-level promotions may work for H_Sens group to enhance their purchase intention, but not for L_Sens group. We also find that contemporaneous platform-level and seller-level promotions have a synergy effect on increase in sales. This might be because the platform promotion brings H_Sens consumers into the market, which is positively related to the effectiveness of seller promotion. Such synergy, however, depends on product categories, where search goods have a higher synergetic effect than experience goods.