Pioneering tomorrow's playgrounds: illuminating the path through research

Our relentless research drives the heart of Sentience, shaping gaming innovation that resonates with our vision and mission – creating games that respect and engage the community.

Research

Effectiveness on Public Advertisement Interaction of Advertiser Awareness, Advertisement Appeal and Customer Involvement and Need for Cognition

This research investigates the interaction effects of factors, namely, advertiser awareness, advertisement appeal, and customer involvement and need for cognition, selected from the parties involved in public service advertisement. Manipulating the participant’s involvement, attitude toward the advertisement and the advertiser and intention to donate according to 2 (awareness) X 2 (cognitive/affective appeal) factors were surveyed. In result, participants with high involvement were relatively less affected by advertiser awareness. Also, high need for cognition indicated less effect of advertiser awareness on intention to donate. Moreover, when cognitive appeal is used, advertiser awareness affected less on consumers’ attitude toward the advertisement and the advertiser and intention to donate. Further issues on changing customers’ attitudes and behaviors are discussed.

Effectiveness on Public Advertisement Interaction of Advertiser Awareness, Advertisement Appeal and Customer Involvement and Need for Cognition

This research investigates the interaction effects of factors, namely, advertiser awareness, advertisement appeal, and customer involvement and need for cognition, selected from the parties involved in public service advertisement. Manipulating the participant’s involvement, attitude toward the advertisement and the advertiser and intention to donate according to 2 (awareness) X 2 (cognitive/affective appeal) factors were surveyed. In result, participants with high involvement were relatively less affected by advertiser awareness. Also, high need for cognition indicated less effect of advertiser awareness on intention to donate. Moreover, when cognitive appeal is used, advertiser awareness affected less on consumers’ attitude toward the advertisement and the advertiser and intention to donate. Further issues on changing customers’ attitudes and behaviors are discussed.

Effect of Self-Monitoring on Long-Term Patient Engagement with Mobile Health Applications

Despite the growing adoption of the mobile health (mHealth) applications (apps), few studies address concerns with low retention rates. This study aimed to investigate how the usage patterns of mHealth app functions affect user retention. We collected individual usage logs for 1,439 users of single tethered personal health record app, which spanned an 18-months period from August 2011 to January 2013. The user logs contained timestamps whenever an individual uses each function, which enables us to identify the usage patterns based on the intensity of using a particular function in the app. We then estimated how these patterns were related to 1) the app usage over time (using the random effect model) and 2) the probability of stopping the use of the application (using the Cox proportional hazard model). The analyses suggested that the users utilize the app most at the time of the adoption and gradually reduce their usage over time. The average duration of use after starting the app was 25.62 weeks (SD: 18.41). The degree of the usage  eduction, however, decreases as the self-monitoring function is more frequently used (coefficient = 0.002, P = 0.013); none of the other functions has this effect. Moreover, engaging with the self-monitoring function frequently (coefficient = −0.18, P = 0.003) and regularly (coefficient = 0.10, P = 0.001) significantly also reduces the probability of abandoning the application. Specifically, the estimated survival rate indicates that, after 40 weeks since the adoption, the probability of the regular users of self-monitoring to stay in use was about 80% while that of non-user was about 60%. This study provides the empirical evidence that sustained use of mHealth app is closely linked to the regular usage on self-monitoring function. The implications can be extended to the education of users and physicians to produce better outcomes as well as application development for effective user interfaces.

A Discovery of Emergent Behavior Pattern in Trading of Unknown Goods

Society sometimes suffers from the erroneous valuation of very large scale, like the Enron incident. Since any individual reasonable risk evaluation or existence of greedy arbitragers should have prevented such long-term, large scale valuation errors, such events are often considered as a matter of errors of the valuation system. This study suggests a computational model that describes interactions such as emergence and feedback, between individual valuation behavior and group behavior, which discovered a clear and distinctive pattern that the group's valuation may seem to converge into a consensus, even if it is not real. The model is a relatively new approach in explaining valuation behavior, linking individual decision and group behavior with a feedback mechanism. Implications from the analysis can be helpful to managers who handle complex and uncertain goods.

A Discovery of Emergent Behavior Pattern in Trading of Unknown Goods

Society sometimes suffers from the erroneous valuation of very large scale, like the Enron incident. Since any individual reasonable risk evaluation or existence of greedy arbitragers should have prevented such long-term, large scale valuation errors, such events are often considered as a matter of errors of the valuation system. This study suggests a computational model that describes interactions such as emergence and feedback, between individual valuation behavior and group behavior, which discovered a clear and distinctive pattern that the group's valuation may seem to converge into a consensus, even if it is not real. The model is a relatively new approach in explaining valuation behavior, linking individual decision and group behavior with a feedback mechanism. Implications from the analysis can be helpful to managers who handle complex and uncertain goods.

A Discovery of Emergent Behavior Pattern in Trading of Unknown Goods

Society sometimes suffers from the erroneous valuation of very large scale, like the Enron incident. Since any individual reasonable risk evaluation or existence of greedy arbitragers should have prevented such long-term, large scale valuation errors, such events are often considered as a matter of errors of the valuation system. This study suggests a computational model that describes interactions such as emergence and feedback, between individual valuation behavior and group behavior, which discovered a clear and distinctive pattern that the group's valuation may seem to converge into a consensus, even if it is not real. The model is a relatively new approach in explaining valuation behavior, linking individual decision and group behavior with a feedback mechanism. Implications from the analysis can be helpful to managers who handle complex and uncertain goods.

Research partners

Chul Kim
Assistant Professor, Baruch College, City University of New York (CUNY)
Chul Kim is an Assistant Professor in Marketing at Baruch College, City University of New York (CUNY). His research priority is to provide counterfactual insights regarding social media and digital marketing by utilizing Bayesian methods and dynamic structural models. His current studies explore the dynamics of crowd-fundraising and the Billboard Effect of online travel agencies. He received his Ph.D. in Management Engineering from KAIST Business School with a focus on Marketing. He was a postdoctoral research fellow and lecturer in Marketing at the University of Maryland. He also has a professional experience as a Data Scientist at Samsung. He was responsible for developing Samsung’s proprietary global demand forecasting models for smartphones.
Sunghan Ryu
Associate Professor, USC-SJTU Institute of Cultural Creative Industry, Shanghai Jiao Tong University (SJTU)
Sunghan Ryu is an Associate Professor at the USC-SJTU Institute of Cultural and Creative Industry in Shanghai Jiao Tong University. He is also the founding director of the Center for Digital Creative Enterprise Research, where he is a renowned expert in digital innovations across the media and entertainment industries.

Ryu has served as a visiting professor at several prestigious universities worldwide, and his research focuses on the impact of crowdfunding on innovation, digital marketing practices, coworking space values, and the digital entertainment consumption behaviors of young generations. His extensive contributions include academic publications, prestigious conference presentations, and recognition with awards such as the HICSS Best Paper Award, SAGE Business Cases Editors’ Choice Award, and more.
Hyunkyung Lee
Ph.D Candidate in Information Systems & Operations Management, Emory University
Hyunkyung is a PhD Candidate in Information Systems and Operations Management at Goizueta Business School of Emory University. She holds a Master's degree in Management Engineering from KAIST and a Bachelor's degree in Industrial Engineering from Yonsei University. Prior to joining the program, she co-founded a tech start-up company that offers user behavioral analytics. She is interested in the areas related to online advertising, online consumer behavior, digital economy, and cloud computing. Her dissertation focuses on understanding the antecedents and consequences of ad-blocking technologies, an important emerging technological trend in the digital advertising ecosystem and the Internet economy.

Patents

US | 11376507

Apparatus for data preprocessing for classifying the psychology of a game user and an operation thereof

US | 11263338

Data security maintenance method for data analysis application

US | 11642597

Apparatus for recommending game contents based on the psychology of a game user and an operation thereof

KR | 10-1978379

Data security maintenance method for data analysis application

KR | 10-2469355

Apparatus for generating standardized table for classifying the psychology of a game user and an operation thereof

KR | 10-2297795

Apparatus for data preprocessing for classifying the psychology of a game user and an operation thereof

KR | 10-2304756

Apparatus for recommending game contents based on the psychology of a game user and an operation thereof

KR | 10-2236351

Apparatus for proving information about marketing performance contribution and method of assessing marketing performance by multi-channel encounter