Xin Li

City University of Hong Kong | CityU · Department of Information Systems

Knowledge management is essential to modern organizations. Due to the information overload problem, managers are facing critical challenges in utilizing the data in organizations. Although several automated tools have been applied, previous applications often deem knowledge items independent and use solely contents, which may limit their analysis a...

Online product reviews are arguably one of the most easily accessible sources of marketing data for online retailers. It is possible to build machine learning tools to learn consumers' opinions from online word of mouth (WOM). Menu costs are practically trivial for online retailers, and it is not difficult to program automatic price changes based o...

Online health communities (OHCs) play an important role in enabling patients to exchange information and obtain social support from each other. However, do OHC interactions always benefit patients? In this research, we investigate different mechanisms by which OHC content may affect patients’ emotions. Specifically, we notice users can read not onl...

Natural disasters can have devastating economic and financial consequences for those affected. This research note explores the potential of artificial intelligence (AI) in disaster relief through lending services. By collaborating with a credit-scoring company, we investigate how AI-empowered lenders can effectively reduce delinquency rates for bor...

Swift and unexpected shifts of financial regulations can have profound implications for the general population. This is evidenced by China’s abrupt transition in its stance on P2P lending in 2018. Initially embracing these platforms, the abrupt regulatory pivot to widespread shutdowns. Our empirical research, drawing upon credit application data, d...

BACKGROUND The assessment of medical service quality is difficult, due to the information asymmetry between patients and doctors. With the development of online healthcare platforms, patients nowadays have more channels to reach medical service and assess others reviews as a quality indicator. However, what aspects in online reviews we should care...

In e-commerce, product photos are a major component of product presentations that aid consumers' understanding of products. In this study, we investigate the impact of the background of product photos on consumers' interest. Drawing upon the attention theories of visual perception, we propose a contrast-composition-distraction framework to understa...

Natural disasters wreak economic havoc and cause financial distress for victims. Commercial loans provided by lending firms play a key role in helping victims recover from disasters. This research note studies whether lenders' use of AI in the lending process can, through reducing delinquency, benefit borrowers who experience natural disasters. Col...

Purpose Drawing on social network and information diffusion theories, the authors study the impact of the structural characteristics of a seller’s local social network on her promotion effectiveness in social commerce. Design/methodology/approach The authors define a local social network as one formed by a focal seller, her directly connected user...

Model-based systems engineering (MBSE) is a leading paradigm for the analyses and development of complex systems. However, the development of modeling and simulation infrastructure supporting MBSE is lacking, which limits the application of MBSE. To address this problem, this paper proposes an SES-X methodology that integrates system modeling (foll...

Purpose Leveraging information technology (IT) to improve the treatment and support of patients is a widely studied topic in healthcare. For chronic diseases, such as diabetes, the use of information technology is even more important since its effect extends from a clinic environment to patients’ daily life. The purpose of this paper is to investig...

Gene/protein interactions provide critical information for a thorough understanding of cellular processes. Recently, considerable interest and effort has been focused on the construction and analysis of genome-wide gene networks. The large body of biomedical literature is an important source of gene/protein interaction information. Recent advances...

Predicting gene functions is a challenge for biologists in the post genomic era. Interactions among genes and their products compose networks that can be used to infer gene functions. Most previous studies adopt a linkage assumption, i.e., they assume that gene interactions indicate functional similarities between connected genes. In this study, we...

Purpose: We model group advertising decisions, which are the collective decisions of every single advertiser within the set of advertisers who are competing in the same auction or vertical industry, and examine resulting market outcomes, via a proposed simulation framework named EXP-SEA (Experimental Platform for Search Engine Advertising) supporti...

Photos play a critical role in online shopping. To examine their impact on consumers, most previous studies rely on human assessments to develop measures for photos. Such an approach limits the number of dimensions and samples that can be investigated in one study. This study exploits image-processing techniques to tackle this challenge. We develop...

Public news provides rich information about firm operations and market dynamics. Learning about firm interactions from news is commonly done by human investors but has not been realized by automatic methods, leading to a research opportunity in market signaling via dynamic firm relations. This study proposes a new text-mining approach to extract co...

Section identification is an important task for library science, especially knowledge management. Identifying the sections of a paper would help filter noise in entity and relation extraction. In this research, we studied the paper section identification problem in the context of Chinese medical literature analysis, where the subjects, methods, and...

Hospital readmissions consume large amounts of medical resources and negatively impact the healthcare system. Predicting the readmission rate early one can alleviate the financial and medical consequences. Most related studies only select the patient’s structural features or text features for modeling analysis, which offer an incomplete picture of...

Multiplayer Online Battle Arena (MOBA) game is a popular and major sector in the online gaming business these years. The major revenue source of this type of games is from the selling of skins. In this study, we investigate how the social influence, i.e., impressions from others' skin use, may affect one's skin purchase decision. Due to unique cont...

As a result of the information asymmetry on product quality, there is a risk of unethical suppliers defrauding buyers in a supply chain. Buyers often conduct quality inspection on shipments and frame supply contracts to punish quality fraud. Due to cost concerns, buyers need to estimate the suppliers’ fraud possibilities and choose appropriate test...

The Chinese medical literature contains a large amount of knowledge. Reducing the effort needed by medical scholars to extract this knowledge requires a literature analysis to identify the key information in each paper. We argue that identifying the sections of a paper would help us filter noise from the paper and increase the accuracy of extractin...

Purpose We model group advertising decisions, which are the collective decisions of every single advertiser within the set of advertisers who are competing in the same auction or vertical industry, and examine resulting market outcomes, via a proposed simulation framework named EXP-SEA (Experimental Platform for Search Engine Advertising) supporti...

Quality inspection, a widely adopted practice in supply chains, measures whether delivered products conform to prespecified quality requirements. Due to potential economic benefits, suppliers may deliberately manipulate products to falsify test results. However, unqualified products could cause severe problems in supply chains or even tragedies, su...

It is well documented in management literature that characteristics of collaboration processes strongly influence team performance in a business environment. However, little work has been done on how specific collaboration process patterns affect teamwork performance, leading to an open issue in collaboration management. To address this research ga...

This study draws from strategic choice theory, management fashion theory, and trust research to investigate organizational transformation toward cloud service. Considering organizations’ substantive rationality, this study proposes that SMEs’ entrepreneurial orientation and the institutional pressures received from the marketplace provide motives f...

Drug interactions represent adverse effects when employing two or multiple drugs together in treatments. Adverse effects are critical and may be deadly in medical practice. However, our understanding of drug interactions is far from complete. In the medical study on drug interaction, the prediction of potential drug interactions will help reducing...

Chinese medicine is increasingly being used with Western medicine in practice, especially for treatment of chronic diseases. In this integrative medicine process, it is necessary to understand the interactions between Chinese and Western medicine to reduce adverse events. However, compared to Western medicine, there are limited studies that summari...

With the rapid development of the mobile app market, understanding the determinants of mobile app success has become vital to researchers and mobile app developers. Extant research on mobile applications primarily focused on the numerical and textual attributes of apps. Minimal attention has been provided to how the visual attributes of apps affect...

Cryptocurrencies, such as Bitcoin, have ignited intense discussions. Despite receiving extensive public attention, theoretical understanding is limited regarding the value of blockchain-based cryptocurrencies, as expressed in their exchange rates against traditional currencies. In this paper, we conduct a theory-driven empirical study of the Bitcoi...

Recommender systems are widely used for suggesting books, education materials, and products to users by exploring their behaviors. In reality, users' preferences often change over time, leading to studies on time-dependent recommender systems. However, most existing approaches that deal with time information remain primitive. In this paper, we exte...

Social media is a major platform for opinion sharing. In order to better understand and exploit opinions on social media, we aim to classify users with opposite opinions on a topic for decision support. Rather than mining text content, we introduce a link-based classification model, named global consistency maximization (GCM) that partitions a soci...

Market surveillance systems (MSSs) are increasingly used to monitor trading activities in financial markets to maintain market integrity. Existing MSSs primarily focus on statistical analysis of market activity data and largely ignore textual market information, including, but not limited to, news reports and various social media. As suggested by b...

Chinese medicine research documents a significant amount of knowledge. However, compared to Western medicine, there are limited studies that take advantage of and summarize findings based on the Chinese medicine literature. This paper builds a literature analysis system based on information extraction and visualization technologies, which allow use...

Recommender systems have been widely used to provide personal and convenient services for users. As one of successful recommendation methods, collaborative filtering explores users' interests from item consumptions. However, it suffers from the data sparsity problem that most users have interacted with a small number of items. Particularly, data sp...

With the rapid adoption of smartphones, developing mobile apps has become an attractive arena for entrepreneurs. Many factors drive the sales of mobile apps, one of which is online word of mouth (eWOM). This research examines the effect of textual consumer reviews on the sales of mobile apps. Noting the inconsistent findings on the effect of textua...

his paper presents a case study on 100Credit, an Internet credit service provider in China. 100Credit began as an IT company specializing in e-commerce recommendation before getting into the credit rating business. The company makes use of Big Data on multiple aspects of individuals’ online activities to infer their potential credit risk. Based on...

Purpose – Although big data analytics has reaped great business rewards, big data system design and integration still face challenges resulting from the demanding environment, including challenges involving variety, uncertainty, and complexity. These characteristics in big data systems demand flexible and agile integration architectures. Furthermor...

Community detection is a fundamental task in network analysis. Applications on massive dynamic networks require more efficient solutions and lead to incremental community detection, which revises the community assignments of new or changed vertices during network updates. In this paper, we propose to use machine learning classifiers to predict the...

Market surveillance systems have increasingly gained in usage for monitoring trading activities in stock markets to maintain market integrity. Existing systems primarily focus on the numerical analysis of market activity data and generally ignore textual information. To fulfil the requirements of information-based surveillance, a multi-agent-based...

This column examines the cognitive load of prediction markets from four steps of user's decision process (that is, timing, pricing, revisiting, and benefit) and discusses how a prediction market mechanism could have a low cognitive load. In the column, the authors propose that fixed-odds betting can be used as a prediction market mechanism with car...

Market surveillance systems (MSSs) are information systems that monitor financial markets to combat market abuses. Existing MSSs focus mainly on analyzing trading activities and are often developed through a trial-and-error approach by screening data mining algorithms and features. The void of theoretical direction limits the effectiveness of MSSs...

We propose a rewiring algorithm that changes the community structure from overlapping to non-overlapping while maintaining the degree distribution of the network.•We simulate the susceptible-infected-susceptible (SIS) epidemic process on both synthetic scale-free networks and real-world networks.•Experiments show that epidemics spread faster on net...

Prediction markets provide a promising approach for future event prediction. Most existing prediction markets are built upon auction mechanisms. Although powerful and flexible in some contexts to capture signals of events, these mechanisms 1) mix opinions from experts and amateurs; 2) require continuous attention from the participants and limit pos...

This paper proposes a model to calculate the average speed of transmission of intervehicle communication (IVC) messages in a general traffic stream on highways in the early stage of deploying distributed traffic information systems (DTIS). The model helps explain the relationship between average IVC message speed and traffic parameters such as equi...

Determinants of online consumer's purchase decisions are of long-term interest to researchers and practitioners. Since product photos directly aid consumers' understanding of products, retailers often put a lot of effort into polishing them. However, there is limited research on the impact of product photos on purchase decisions. Most previous stud...

Please refer to the journal version: Li, Xin; Wang, Chong Alex / The Technology and Economic Determinants of Cryptocurrency Exchange Rates: The Case of Bitcoin. 2017; In: Decision Support Systems. Vol. 95, pp. 49-60

This paper presents a hybrid approach to automatic incident detection (AID) in transportation systems. It combines time series analysis (TSA) and machine learning (ML) techniques in light of the fault diagnosis theory. In this approach, the time series component is to forecast the normal traffic for the current time point based on prior (normal) tr...

Recommender systems have demonstrated commercial success in multiple industries. In digital libraries they have the potential to be used as a support tool for traditional information retrieval functions. Among the major recommendation algorithms, the successful collaborative filtering (CF) methods explore the use of user-item interactions to infer...

Many organizations adopt information technologies to make intelligent decisions during operations. Time-series data plays a crucial role in supporting such decision making processes. Though current studies on time-series based decision making provide reasonably well results, the anomaly detection essence underling most of the scenarios and the plen...

Traditional recommender system research often explores customer, product, and transaction information in providing recommendations. Social relationships in social networks are related to individuals' preferences. This study investigates the product recommendation problem based solely on people's social network information. Taking a kernel-based app...

The wisdom of crowds has been recognized as an effective decision making mechanism by aggregating information from different individuals to derive an overall decision. However, in this information aggregation process, individuals may be influenced by various factors and provide biased claims (or individual level decisions), especially when such cla...

Previous research on collaboration posits collaboration process as a key factor for team performance. However, it is not fully understood which characteristics of a process make collaboration more efficient. In this research, we investigate the effect of collaboration process patterns on teamwork efficiency (e.g. time cost) in the software developm...

Enabled by Web 2.0 technologies, social media provide an unparalleled platform for consumers to share their product experiences and opinions through word-of-mouth (WOM) or consumer reviews. It has become increasingly important to understand how WOM content and metrics influence consumer purchases and product sales. By integrating marketing theories...

Traditional recommender system research often explores customer demographics, product characteristics, and transactions in providing recommendations. This study investigates the recommendation problem based on social network information. In light of the social network theories on the formation of a social network and its impact on human behavior, w...

Cloud Computing Service (CCS) paradigm is changing IT strategy of organizations in the digital world. CCS that requires few upfront investments and uses lease-based pricing is especially relevant to the Small and Medium Enterprises (SMEs), which have limited resources and may not know their true valuation for the IT prior to adoption. Thus, this re...

Fixed odds betting is a popular mechanism in sports game betting. In this paper, we aim to decipher actual group belief on contingent future events from the dynamics of fixed odds betting. Different from previous studies, we adopt the prospect theory rather than the expected utility (EU) theory to model bettor behaviors. Thus, we do not need to mak...