Attribute exclusion strategies in airline choice : accounting for exogenous information on decision maker processing strategies in models of discrete choice

We examine the impact of individual-specific information processing strategies (IPSs) on the inclusion/exclusion of attributes on the parameter estimates and behavioural outputs of models of discrete choice. Current practice assumes that individuals employ a homogenous IPS with regards to how they process attributes of stated choice (SC) experiments. We show how information collected exogenous of the SC experiment on whether respondents either ignored or considered each attribute may be used in the estimation process, and how such information provides outputs that are IPS segment specific. We contend that accounting the inclusion/exclusion of attributes will result in behaviourally richer population parameter estimates.

Determinants and consequences of information sharing with key suppliers

The economic environment of today can be characterized as highly dynamic and competitive if not being in a constant flux. Globalization and the Information Technology (IT) revolution are perhaps the main contributing factors to this observation. While companies have to some extent adapted to the current business environment, new pressures such as the recent increase in environmental awareness and its likely effects on regulations are underway. Hence, in the light of market and competitive pressures, companies must constantly evaluate and if necessary update their strategies to sustain and increase the value they create for shareholders (Hunt and Morgan, 1995; Christopher and Towill, 2002). One way to create greater value is to become more efficient in producing and delivering goods and services to customers, which can lead to a strategy known as cost leadership (Porter, 1980). Even though Porter (1996) notes that in the long run cost leadership may not be a sufficient strategy for competitive advantage, operational efficiency is certainly necessary and should therefore be on the agenda of every company. ----- ----- ----- Better workflow management, technology, and resource utilization can lead to greater internal operational efficiency, which explains why, for example, many companies have recently adopted Enterprise Resource Planning (ERP) Systems: integrated softwares that streamline business processes. However, as today more and more companies are approaching internal operational excellence, the focus for finding inefficiencies and cost saving opportunities is moving beyond the boundaries of the firm. Today many firms in the supply chain are engaging in collaborative relationships with customers, suppliers, and third parties (services) in an attempt to cut down on costs related to for example, inventory, production, as well as to facilitate synergies. Thus, recent years have witnessed fluidity and blurring regarding organizational boundaries (Coad and Cullen, 2006). ----- ----- ----- The Information Technology (IT) revolution of the late 1990’s has played an important role in bringing organizations closer together. In their efforts to become more efficient, companies first integrated their information systems to speed up transactions such as ordering and billing. Later collaboration on a multidimensional scale including logistics, production, and Research & Development became evident as companies expected substantial benefits from collaboration. However, one could also argue that the recent popularity of the concepts falling under Supply Chain Management (SCM) such as Vendor Managed Inventory, Collaborative Planning, Replenishment, and Forecasting owe to the marketing efforts of software vendors and consultants who provide these solutions. Nevertheless, reports from professional organizations as well as academia indicate that the trend towards interorganizational collaboration is gaining wider ground. For example, the ARC Advisory Group, a research organization on supply chain solutions, estimated that the market for SCM, which includes various kinds of collaboration tools and related services, is going to grow at an annual rate of 7.4% during the years 2004-2008, reaching to $7.4 billion in 2008 (Engineeringtalk 2004).

Social Impact of Mining Survey : Aggregate Results Queensland Communities

This is the final report from a study into the social impact of mining in Queensland.

Ontology-based specific and exhaustive user profiles for constraint information fusion for multi-agents

Intelligent agents are an advanced technology utilized in Web Intelligence. When searching information from a distributed Web environment, information is retrieved by multi-agents on the client site and fused on the broker site. The current information fusion techniques rely on cooperation of agents to provide statistics. Such techniques are computationally expensive and unrealistic in the real world. In this paper, we introduce a model that uses a world ontology constructed from the Dewey Decimal Classification to acquire user profiles. By search using specific and exhaustive user profiles, information fusion techniques no longer rely on the statistics provided by agents. The model has been successfully evaluated using the large INEX data set simulating the distributed Web environment.

Selected new training documents to update user profile

Relevance Feedback (RF) has been proven very effective for improving retrieval accuracy. Adaptive information filtering (AIF) technology has benefited from the improvements achieved in all the tasks involved over the last decades. A difficult problem in AIF has been how to update the system with new feedback efficiently and effectively. In current feedback methods, the updating processes focus on updating system parameters. In this paper, we developed a new approach, the Adaptive Relevance Features Discovery (ARFD). It automatically updates the system's knowledge based on a sliding window over positive and negative feedback to solve a nonmonotonic problem efficiently. Some of the new training documents will be selected using the knowledge that the system currently obtained. Then, specific features will be extracted from selected training documents. Different methods have been used to merge and revise the weights of features in a vector space. The new model is designed for Relevance Features Discovery (RFD), a pattern mining based approach, which uses negative relevance feedback to improve the quality of extracted features from positive feedback. Learning algorithms are also proposed to implement this approach on Reuters Corpus Volume 1 and TREC topics. Experiments show that the proposed approach can work efficiently and achieves the encouragement performance.

Sharing with care : an information accountability perspective

Health information sharing has become a vital part of modern healthcare delivery. E-health technologies provide efficient and effective ways of sharing medical information, but give rise to issues that neither the medical professional nor the consumers have control over. Information security and patient privacy are key impediments that hinder sharing information as sensitive as health information. Health information interoperability is another issue which hinders the adoption of available e health technologies. In this paper we propose a solution for these problems in terms of information accountability, the HL7 interoperability standard and social networks for manipulating personal health records.

Security analysis and enhancement of one-way hash based low-cost authentication protocol (OHLCAP)

Choi et al. recently proposed an efficient RFID authentication protocol for a ubiquitous computing environment, OHLCAP(One-Way Hash based Low-Cost Authentication Protocol). However, this paper reveals that the protocol has several security weaknesses : 1) traceability based on the leakage of counter information, 2) vulnerability to an impersonation attack by maliciously updating a random number, and 3) traceability based on a physically-attacked tag. Finally, a security enhanced group-based authentication protocol is presented.

Information accountability for online healthcare social networks

Online social networking has become one of the most popular Internet applications in the modern era. They have given the Internet users, access to information that other Internet based applications are unable to. Although many of the popular online social networking web sites are focused towards entertainment purposes, sharing information can benefit the healthcare industry in terms of both efficiency and effectiveness. But the capability to share personal information; the factor which has made online social networks so popular, is itself a major obstacle when considering information security and privacy aspects. Healthcare can benefit from online social networking if they are implemented such that sensitive patient information can be safeguarded from ill exposure. But in an industry such as healthcare where the availability of information is crucial for better decision making, information must be made available to the appropriate parties when they require it. Hence the traditional mechanisms for information security and privacy protection may not be suitable for healthcare. In this paper we propose a solution to privacy enhancement in online healthcare social networks through the use of an information accountability mechanism.

A systematic, tool-supported method for conducting literature reviews in information systems

While the importance of literature studies in the IS discipline is well recognized, little attention has been paid to the underlying structure and method of conducting effective literature reviews. Despite the fact that literature is often used to refine the research context and direct the pathways for successful research outcomes, there is very little evidence of the use of resource management tools to support the literature review process. In this paper we want to contribute to advancing the way in which literature studies in Information Systems are conducted, by proposing a systematic, pre-defined and tool-supported method to extract, analyse and report literature. This paper presents how to best identify relevant IS papers to review within a feasible and justifiable scope, how to extract relevant content from identified papers, how to synthesise and analyse the findings of a literature review and what are ways to effectively write and present the results of a literature review. The paper is specifically targeted towards novice IS researchers, who would seek to conduct a systematic detailed literature review in a focused domain. Specific contributions of our method are extensive tool support, the identification of appropriate papers including primary and secondary paper sets and a pre-codification scheme. We use a literature study on shared services as an illustrative example to present the proposed approach.

Privacy by information accountability for e-health systems

Privacy has become one of the main impediments for e-health in its advancement to providing better services to its consumers. Even though many security protocols are being developed to protect information from being compromised, privacy is still a major issue in healthcare where privacy protection is very important. When consumers are confident that their sensitive information is safe from being compromised, their trust in these services will be higher and would lead to better adoption of these systems. In this paper we propose a solution to the problem of patient privacy in e-health through an information accountability framework could enhance consumer trust in e-health services and would lead to the success of e-health services.

Open content licensing of public sector information and the risk of tortious liability for Australian Governments

There has been an increasing interest by governments worldwide in the potential benefits of open access to public sector information (PSI). However, an important question remains: can a government incur tortious liability for incorrect information released online under an open content licence? This paper argues that the release of PSI online for free under an open content licence, specifically a Creative Commons licence, is within the bounds of an acceptable level of risk to government, especially where users are informed of the limitations of the data and appropriate information management policies and principles are in place to ensure accountability for data quality and accuracy.

A Personalized Ontology Model for Web Information Gathering

As a model for knowledge description and formalization, ontologies are widely used to represent user profiles in personalized web information gathering. However, when representing user profiles, many models have utilized only knowledge from either a global knowledge base or a user local information. In this paper, a personalized ontology model is proposed for knowledge representation and reasoning over user profiles. This model learns ontological user profiles from both a world knowledge base and user local instance repositories. The ontology model is evaluated by comparing it against benchmark models in web information gathering. The results show that this ontology model is successful.