Databases and Information Systems Commons^™

Quantum Consensus, Jorden Seet, Paul Griffin

Research Collection School Of Computing and Information Systems

In this paper, we propose a novel consensus mechanism utilizing the quantum properties of qubits. This move from classical computing to quantum computing is shown to theoretically enhance the scalability and speed of distributed consensus as well as improve security and be a potential solution for the problem of blockchain interoperability. Using this method may circumvent the common problem known as the Blockchain Trilemma, enhancing scalability and speed without sacrificing de-centralization or byzantine fault tolerance. Consensus speed and scalability is shown by removing the need for multicast responses and exploiting quantum properties to ensure that only a single multicast is …

Optimal Design And Ownership Structures Of Innovative Retail Payment Systems, Zhiling Guo, Dan Ma

Research Collection School Of Computing and Information Systems

In response to the Fintech trend, an ongoing debate in the banking industry is how to design the new-generation interbank retail payment and settlement system. We propose a two-stage analytical model that takes into account the value-risk tradeoff in the new payment system design, as well as banks’ participation incentives and adoption timing decisions. We find that, as the system base value increases, banks tend to synchronize their investment and adoption decisions. When the system base value is low and banks are heterogeneous, bank association ownership maximizes social welfare. When both the system base value and bank heterogeneity are moderate, …

Automated Theme Search In Ico Whitepapers, Chuanjie Fu, Andrew Koh, Paul Griffin

Research Collection School Of Computing and Information Systems

The authors explore how topic modeling can be used to automate the categorization of initial coin offerings (ICOs) into different topics (e.g., finance, media, information, professional services, health and social, natural resources) based solely on the content within the whitepapers. This tool has been developed by fitting a latent Dirichlet allocation (LDA) model to the text extracted from the ICO whitepapers. After evaluating the automated categorization of whitepapers using statistical and human judgment methods, it is determined that there is enough evidence to conclude that the LDA model appropriately categorizes the ICO whitepapers. The results from a two-population proportion test …

Correlation-Sensitive Next-Basket Recommendation, Duc Trong Le, Hady Wirawan Lauw, Yuan Fang

Research Collection School Of Computing and Information Systems

Items adopted by a user over time are indicative ofthe underlying preferences. We are concerned withlearning such preferences from observed sequencesof adoptions for recommendation. As multipleitems are commonly adopted concurrently, e.g., abasket of grocery items or a sitting of media consumption, we deal with a sequence of baskets asinput, and seek to recommend the next basket. Intuitively, a basket tends to contain groups of relateditems that support particular needs. Instead of recommending items independently for the next basket, we hypothesize that incorporating informationon pairwise correlations among items would help toarrive at more coherent basket recommendations.Towards this objective, we develop a …

How To Derive Causal Insights For Digital Commerce In China? A Research Commentary On Computational Social Science Methods, David C.W. Phang, Kanliang Wang, Qiu-Hong Wang, Robert John Kauffman, Maurizio Naldi

Research Collection School Of Computing and Information Systems

The transformation of empirical research due to the arrival of big data analytics and data science, as well as the new availability of methods that emphasize causal inference, are moving forward at full speed. In this Research Commentary, we examine the extent to which this has the potential to influence how e-commerce research is conducted. China offers the ultimate in data-at-scale settings, and the construction of real-world natural experiments. Chinese e-commerce includes some of the largest firms involved in e-commerce, mobile commerce, social media and social networks. This article was written to encourage young faculty and doctoral students to engage …

Alpha Insurance: A Predictive Analytics Case To Analyze Automobile Insurance Fraud Using Sas Enterprise Miner (Tm), Richard Mccarthy, Wendy Ceccucci, Mary Mccarthy, Leila Halawi

Publications

Automobile Insurance fraud costs the insurance industry billions of dollars annually. This case study addresses claim fraud based on data extracted from Alpha Insurance’s automobile claim database. Students are provided the business problem and data sets. Initially, the students are required to develop their hypotheses and analyze the data. This includes identification of any missing or inaccurate data values and outliers as well as evaluation of the 22 variables. Next students will develop and optimize their predictive models using five techniques: regression, decision tree, neural network, gradient boosting, and ensemble. Then students will determine which model is the best fit …

Risk Pooling, Supply Chain Hierarchy, And Analysts' Forecasts, Nan Hu, Jian-Yu Ke, Ling Liu, Yue Zhang

Research Collection School Of Computing and Information Systems

We investigate whether a firm's risk pooling affects its analysts' forecasts, specifically in terms of forecast accuracy and their use of public vs. private information, and how risk pooling interacts with a firm's position in the supply chain to affect analysts' forecasts. We use a social network analysis method to operationalize risk pooling and supply chain hierarchy, and find that risk pooling significantly reduces analysts' forecast errors and increases (decreases) their use of public (private) information. We also find that the positive (negative) relationships between risk pooling and analyst forecast accuracy and analysts' use of public (private) information are more …

An Economic Analysis Of Consumer Learning On Entertainment Shopping Websites, Jin Li, Zhiling Guo, Geoffrey K.F. Tso

Research Collection School Of Computing and Information Systems

Online entertainment shopping, normally supported by the pay-to-bid auction mechanism, represents an innovative business model in e-commerce. Because the unique selling mechanism combines features of shopping and online auction, consumers expect both monetary return and entertainment value from their participation. We propose a dynamic structural model to analyze consumer behaviors on entertainment shopping websites. The model captures the consumer learning process, based both on individual participation experiences and also on observational learning of historical auction information. We estimate the model using a large data set from an online entertainment shopping website. Results show that consumers’ initial participation incentives mainly come …

Automated Trading Systems Statistical And Machine Learning Methods And Hardware Implementation: A Survey, Boming Huang, Yuziang Huan, Li Da Xu, Lirong Zheng, Zhuo Zou

Information Technology & Decision Sciences Faculty Publications

Automated trading, which is also known as algorithmic trading, is a method of using a predesigned computer program to submit a large number of trading orders to an exchange. It is substantially a real-time decision-making system which is under the scope of Enterprise Information System (EIS). With the rapid development of telecommunication and computer technology, the mechanisms underlying automated trading systems have become increasingly diversified. Considerable effort has been exerted by both academia and trading firms towards mining potential factors that may generate significantly higher profits. In this paper, we review studies on trading systems built using various methods and …

How Does Customer Service Offshoring Impact Customer Satisfaction?, Jonathan W. Whitaker, M. S. Krishnan, Claes Fornell, Forrest Morgeson

Management Faculty Publications

Information technology (IT) plays a vital role in customer relationship management (CRM), because CRM processes include the collection and analysis of customer information, firms use technology tools to interact with customers, and IT created the conditions under which firms can offshore CRM processes. Customers have negative perceptions toward offshoring, which suggests that firms might be reluctant to offshore IT-enabled CRM processes. However, firms have significantly increased offshoring for CRM processes, presenting a conundrum. Why would firms increase offshoring for CRM processes if there could be a risk to customer satisfaction?

This paper helps to resolve the conundrum by studying the …