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- Analytical modeling (1)
- Causality (1)
- Computational Social Science (1)
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- Data analytics (1)
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- Sales forecasting (1)
- Self-selection biases (1)
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- Social Trust (1)
Articles 1 - 7 of 7
Full-Text Articles in Physical Sciences and Mathematics
Combining Machine-Based And Econometrics Methods For Policy Analytics Insights, Robert J. Kauffman, Kwansoo Kim, Sang-Yong Tom Lee, Ai Phuong Hoang, Jing Ren
Combining Machine-Based And Econometrics Methods For Policy Analytics Insights, Robert J. Kauffman, Kwansoo Kim, Sang-Yong Tom Lee, Ai Phuong Hoang, Jing Ren
Research Collection School Of Computing and Information Systems
Computational Social Science (CSS) has become a mainstream approach in the empirical study of policy analytics issues in various domains of e-commerce research. This article is intended to represent recent advances that have been made for the discovery of new policy-related insights in business, consumer, and social settings. The approach discussed is fusion analytics, which combines machine-based methods from Computer Science (CS) and explanatory empiricism involving advanced Econometrics and Statistics. It explores several efforts to conduct research inquiry in different functional areas of Electronic Commerce and Information Systems (IS), with applications that represent different functional areas of business, as well …
How To Enable Future Faster Payments? An Evaluation Of A Hybrid Payments Settlement Mechanism, Zhiling Guo, Yuanzhi Huang
How To Enable Future Faster Payments? An Evaluation Of A Hybrid Payments Settlement Mechanism, Zhiling Guo, Yuanzhi Huang
Research Collection School Of Computing and Information Systems
In the era of Fintech innovation and e-commerce, faster settlement of massive retail transactions is crucial for business growth and financial system stability. However, speeding up payments settlement can create periodic liquidity shortfalls to banks which would incur high cost of funds in the settlement process. We propose a new hybrid settlement mechanism design that integrates features of real-time gross settlement, deferred net settlement, and central queue management structure. The hybrid mechanism is managed by an intermediary and is particularly suitable to settle large volume of small-value retail payments. We evaluate the mechanism using computer experiments and simulation. We find …
On Self-Selection Biases In Online Product Reviews, Nan Hu, Paul A. Pavlou, Jie Zhang
On Self-Selection Biases In Online Product Reviews, Nan Hu, Paul A. Pavlou, Jie Zhang
Research Collection School Of Computing and Information Systems
Online product reviews help consumers infer product quality, and the mean (average) rating is often used as a proxy for product quality. However, two self-selection biases, acquisition bias (mostly consumers with a favorable predisposition acquire a product and hence write a product review) and underreporting bias (consumers with extreme, either positive or negative, ratings are more likely to write reviews than consumers with moderate product ratings), render the mean rating a biased estimator of product quality, and they result in the well-known J-shaped (positively skewed, asymmetric, bimodal) distribution of online product reviews. To better understand the nature and consequences of …
Online Advertising, Retail Platform Openness, And Long Tail Sellers, Jianqing Chen, Zhiling Guo
Online Advertising, Retail Platform Openness, And Long Tail Sellers, Jianqing Chen, Zhiling Guo
Research Collection School Of Computing and Information Systems
It becomes increasingly popular that some large online retailers such as Amazon open their platforms to allow third-party retail competitors to sell on their own platforms. We develop an analytical model to examine this retailer market place model and its business impact. We assume that a leading retailer has both valuation advantage that may come from its reputation and information advantage that may come from its brand awarenewss. We find that the availability of relatively low-cost advertising through social media or search engine can effectively reduce the leading retailer's information advantage, and thus be an important driving force for its …
Factored Similarity Models With Social Trust For Top-N Item Recommendation, Guibing Guo, Jie Zhang, Feida Zhu, Xingwei Wang
Factored Similarity Models With Social Trust For Top-N Item Recommendation, Guibing Guo, Jie Zhang, Feida Zhu, Xingwei Wang
Research Collection School of Computing and Information Systems
Trust-aware recommender systems have attracted much attention recently due to the prevalence of social networks. However, most existing trust-based approaches are designed for the recommendation task of rating prediction. Only few trust-aware methods have attempted to recommend users an ordered list of interesting items, i.e., item recommendation. In this article, we propose three factored similarity models with the incorporation of social trust for item recommendation based on implicit user feedback. Specifically, we introduce a matrix factorization technique to recover user preferences between rated items and unrated ones in the light of both user-user and item-item similarities. In addition, we claim …
Inferring User Consumption Preferences From Social Media, Yang Li, Jing Jiang, Ting Liu
Inferring User Consumption Preferences From Social Media, Yang Li, Jing Jiang, Ting Liu
Research Collection School Of Computing and Information Systems
Social Media has already become a new arena of our lives and involved different aspects of our social presence. Users' personal information and activities on social media presumably reveal their personal interests, which offer great opportunities for many e-commerce applications. In this paper, we propose a principled latent variable model to infer user consumption preferences at the category level (e.g. inferring what categories of products a user would like to buy). Our model naturally links users' published content and following relations on microblogs with their consumption behaviors on e-commerce websites. Experimental results show our model outperforms the state-of-the-art methods significantly …
They All Seem Good, But Which One Fits Me? Reducing Fit Uncertainty For Digital Entertainment Goods, Ai Phuong Hoang
They All Seem Good, But Which One Fits Me? Reducing Fit Uncertainty For Digital Entertainment Goods, Ai Phuong Hoang
Research Collection School Of Computing and Information Systems
Faster Internet connections and advanced streaming technologies have boosted the consumption of digital entertainment content. Nonetheless, many content providers are still struggling to differentiate their services and sell their offerings in the market, due to the large number of options available and customers’ uncertainty about the specific attributes of individual information goods. The providers employ different strategies to communicate information on the quality and fit of their products. In this research, I examine the effectiveness of sampling-based seller strategy on the marketing of digital entertainment goods. Using a large dataset on series drama on-demand, I show that content sampling plays …