Cecil Eng Huang Chua

The role of online trading communities in managing internet auction fraud

Internet auctions demonstrate that advances in information technologies can create more efficient venues of exchange between large numbers of traders. However, the growth of Internet auctions has been accompanied by a corresponding growth in Internet auction fraud. Much extant research on Carol Saunders was the accepting senior editor for this paper. Lucas Introna was the associate editor. Mike Chiasson and James Backhouse served as reviewers. Internet auction fraud in the information systems literature is conducted at the individual level of analysis, thereby limiting its focus to the choices of individual traders or trading dyads. The criminology literature, in contrast, recognizes that social and community factors are equally important influences on the perpetration and prevention of crime. We employ social disorganization theory as a lens to explain how online auction communities address auction fraud and how those communities interact with formal authorities. We show how communities may defy, coexist, or cooperate with the formal authority of auction houses. These observations are supported by a qualitative analysis of three cases of online anticrime communities operating in different auction product categories. Our analysis extends aspects of social disorganization theory to online communities. We conclude that community-based clan control may operate in concert with authority-based formal control to manage the problem of Internet auction fraud more effectively.

Fighting Internet auction fraud: an assessment and proposal

Online auctions constitute one of the most successful Internet business models. However, auction fraud has become far and away the largest component of all Internet fraud, posing a threat to the models future. Traditional government organizations such as the Federal Trade Commission and the Secret Service in the US, as well as new agencies such as Internet Fraud Watch and the Internet Fraud Complaint Center, have joined auction businesses in trying to develop new mechanisms to fight this problem. We propose empowering auction communities to integrate their work with that of governments and auction institutions. Our methodology leverages news reports and auction transactions.

Managing diverse stakeholders in enterprise systems projects: a control portfolio approach

While substantial research has examined the control of information systems (IS) projects, most studies in this area have only examined how one controller manages a single group of controllees. However, many IS projects, especially enterprise systems projects (often initiated by an organizations corporate headquarters, and involving business unit users and consultants), have multiple stakeholders. The corporate headquarters (the projects principal controller) must simultaneously ensure that the various stakeholders are aligned with the projects goals despite their diverse motivations, and that the stakeholders collaborate with each other to achieve project success. Behavior control theory argues that the controller enacts a control portfolio of formal and informal controls. However, the presence of multiple controllee groups increases the complexity of vertical controller–controllee relationships, the salience of controllee–controllee relationships, and the interaction between these vertical and horizontal relationships. We therefore examined the creation and evolution of the control portfolio in a multi-stakeholder project over a period of 14 months. We found that (1) the principal controller did enact separate controls for the user and consultant groups; (2) there was more than one controller – the principal controller co-existed with subordinate controllers; and (3) controls enacted by the subordinate controllers and other controllees that cut across stakeholder groups required the support of the principal controller.

Why Do Virtual Communities Regulate Speech

Virtual community research argues that regulations restricting the kinds of speech in a virtual community decrease the utility to members. However, many virtual communities enact regulations on speech within the virtual community. This research explores the contradiction through a cross-case analysis of virtual communities. It explains the contradiction between research and practice using the theory of collective identity. Communication is important for creating collective identity in virtual communities. However, multiple collective identities can arise. When one collective identity within a virtual community defines itself as adversarial to another, silencing speech emerges as adversarial collective identity creates enduring noise and flames. When the target collective identity creates formal regulations suppressing the adversarial collective identity, communication to foster the target collective identity emerges.

IS Bibliographic Repository (ISBIB): A Central Repository of Research Information for the IS Community

The IS Bibliographic Repository (ISBIB), a central repository of Information Systems citations and author information, is a shared resource for research and researcher assessment that can support multiple streams of research. The goal of the repository is to capture research citations and other valuable information from all sub-cultures and disciplines within the international IS community, thereby providing a balanced perspective on the state of art in IS research. This repository should lead to a better understanding on the scope and objectives of IS research in general. The repository also aims to be an unbiased data source for bibliometric research, and studies on IS research methods and processes. It currently holds systematic information about 92 journals. In the spirit of community development, the repository is available to the entire IS community, free of charge. This article describes the current state of the repository and invites readers to use it both for their own research and for bibliometric analysis. Because the repository is intended to be a reflection of the global IS community, the authors, who are also its maintainers, encourage IS researchers and journal editors to provide bibliographic information to extend the repository’s usefulness

An integrated data mining system to automate discovery of measures of association

Many data analysts require tools which can integrate their database management packages (e.g. Microsoft Access) with their data analysis ones (e.g. SAS, SPSS), and provide guidance for the selection of appropriate mining algorithms. In addition, the analysts need to extract and validate statistical results to facilitate data mining. In this paper, we describe an integrated data mining system called the Linear Correlation Discovery System (LCDS) that meets the above requirement. LCDS consists of four major sub-components, two of which, the selection assistant and the statistics coupler, we discussed in this paper. The former examines the scheme and instances to determine appropriate association measurement functions (e.g, chi-square, linear regression, ANOVA). The latter involves the appropriate statistical function on a sample data set, and extracts relevant statistical output such as /spl eta//sup 2/, and R/sup 2/ for effective mining of data. We also describe a new validation algorithm based on measuring the consistency of mining results applied to multiple test sets.

Deriving knowledge representation guidelines by analyzing knowledge engineer behavior

Knowledge engineering research has focused on proposing knowledge acquisition techniques, developing and evaluating knowledge representation schemes and engineering tools, and testing and debugging knowledge-based systems. Few formal studies have been conducted on understanding the behaviors and roles of knowledge engineers. Applying the theory of mental models, this paper describes a think aloud verbal protocol study to determine an empirical basis for understanding: (1) how knowledge engineers extract domain knowledge from textual sources; and (2) the cognitive mechanisms by which they engage various knowledge representation schemes to represent that knowledge acquired. The results suggest that knowledge representation is not simply a translation of acquired knowledge to a knowledge representation. Instead, it is an iterative process of selective querying of acquired knowledge, and continuous refinement of a model leveraging, not only on acquired knowledge from domain experts, but also from the knowledge engineer. From the findings of empirical studies, a set of guidelines is derived to support the training and development of better knowledge representation schemes, representation processes, and knowledge engineering tools.

Building Customized Search Engines: An Interoperability Architecture

Search engines are essential, ubiquitous tools for seeking information from the Internet. Prior research has also demonstrated that combining features of separate search engines often improves retrieval performance. However, such feature combination is often difficult, because developers don’t consider other developers when building their software. To facilitate the development of search engines, we propose a customized search engine approach to integrating appropriate components from multiple search engines. This article presents an interoperability architecture for building customized search engines. To achieve this, authors analyze existing search engines and decompose them into self-contained components that are classified into six categories. The Automated Software Development Environment for Information Retrieval (ASDEIR) was developed as the prototype of the proposed interoperability architecture to test its feasibility, robustness, and usefulness. ASDEIR incorporates intelligent features that detect and attempt to resolve conflicts between components.

A Smart Web Query Engine for Semantic Retrieval of Web Data and Its Application to E-Trading

Vast amounts of data are available on the World Wide Web. However, the extraction and use of this data is difficult, since web data does not conform to any data organization standard. Search engines provide only primitive data query capabilities, and require a detailed syntactic specification to retrieve relevant data. This research proposes a Smart Web Query (SWQ) approach for the semantic retrieval of web data. The approach uses context and domain information to specify and formulate appropriate web queries and formats to search. The SWQ approach relies on context ontologies to discover relevant web pages. Unlike traditional ontologies, SWQ ontologies are structured on a set-theoretic model, which makes them more flexible, adaptive, extensible, and rapidly deployable. An SWQ engine is being developed to test the approach.

Knowledge Representation: A Conceptual Modeling Approach

Substantial work in knowledge engineering has focused on eliciting knowledge and representing it in a computational form. However, before elicited knowledge can be represented, it must be integrated and transformed so the knowledge engineer can understand it. This research identifies the need to separate knowledge representation into human comprehension and computational reasoning and shows that this will lead to better knowledge representation. Modeling of human comprehension is called conceptual knowledge representation. The Conceptual Knowledge Representation Scheme is developed and validated by conducting a combined qualitative/quantitative repeated-measures experiment comparing the Conceptual Knowledge Representation Scheme to two computation-oriented ones. The results demonstrate that the Conceptual Knowledge Representation Scheme better facilitates human comprehension than existing representation schemes. Four principles of the Conceptual Knowledge Representation Scheme emerge that help to attain effective knowledge representation. These are: 1 a focus on human comprehension only, 2 design around natural language, 3 addition of constructs common in the domain, and 4 constructs for representing abstract versions of detailed concepts.