Prediction Markets as Web 2.0 Tools for Enterprise 2.0

In today’s fast-changing business environment, companies and stakeholders are confronted with a new range of businessdecisions. These decisions are constrained by events that are out of the scope of competencies of the decision makers. In thiscontext, prediction markets, which have demonstrated their efficiency in predicting the outcome of major elections, couldsupport companies in leveraging the knowledge and competencies of their collaborators. Using the power of Web 2.0 and theparticipative collaboration of the crowd, prediction markets are well designed to assess this new range of decisions. Thesimple buy and sell mechanism uses the crowd as proxy toward various information sources. Moreover, the decision task isdistributed between the traders, leaving them the tasks of framing the problem, setting the evaluation criteria and collectingthe supporting information, aggregating their results through the current market price.This paper presents the capabilities of prediction market as Web 2.0 decision making tool to increase the efficiency of thedecision making process in Enterprise 2.0 companies. It relies on many characteristics of these companies such as theenhanced collaboration between dispersed collaborators through social networks tools, the commitment of all collaborators inthe knowledge management process and the dedication of the organization toward open and participatory decision processes.It also have the ability to promptly leverage pieces of information scattered through the organization, without requesting asingle stakeholder knowing what to search for and where to search it. Moreover, due to the engagement of a large crowd inthe decision process, final decisions are subject to a broaden adhesion within the company.We conclude by making propositions regarding the deployment of this decision making tool. This involves numerousmanagerial issues, but also opens new perspectives to build upon the collective knowledge of the enterprise

Design of a New Data Structure to Support Non-Invasive Diagnostic on Heritage Metals

Conservation of heritage artifacts is a very sensitive task as conservators usually have very little information about the artifacts. Moreover, due to the uniqueness and the historic value of these artifacts, invasive analysis are not always possible. Therefore, without sampling options, conservators are required to use non-invasive diagnostic methods in order to identify the metal characteristics of the artifact. When confronted with an unknown artifact, conservators generate conceptual models of the corrosion forms. These models are based on formal representations of corrosion forms, but are not directly exploitable for drawing hypotheses regarding the underlying metal. This paper presents the design of a data structure generated from the conceptual models which supports the comparison and retrieval of corresponding artifacts. Integrated with a database of heritage artifacts, this data structure offers advanced decision support to conservators confronted with unknown artifacts

An Ontology to Support Non-Invasive Diagnosis of Heritage Metals

Metal conservators confronted with unknown artefacts rely on previous literature to develop treatment protocols. This search can be tedious given the dissemination of information across corpus of unstructured texts, mainly in the form of research papers and semi-structured databases of artefacts. In order to improve the search of artefacts sharing similar characteristics (metal composition and structure, conservation condition, etc.), this project proposes a hybrid search engine based on a domain ontology. Using a database populated with information resulting from comprehensive investigations of historic and archaeological artefacts, we extracted and selected key concepts and their relations through the use a various lexical analysis tools. Based on this corpus and frequency analysis, we were able to build an ontology of the domain, opening new perspective on information retrieval. Conservators are able to leverage the power of the hybrid search engine to compare their observations on a specific artefact with objects already stored in the database or with indexed research papers. Using keywords to describe corrosion forms they are confronted with, conservators can retrieve artefacts showing similar corrosion phenomena and assess the conservation condition of their artefacts, e.g. diagnosing the stability of metals or determining the location of the limit of the original surface in corrosion product crusts

MiCorr ::un outil d’aide au diagnostic et de partage de savoir sur les métaux archéologiques

L’application MiCorr vise à aider les professionnels de la conservation-restauration à réaliser le diagnostic le plus juste possible sur les métaux patrimoniaux qu’ils étudient. Sur la base d’observations visuelles et donc non invasives des formes de corrosion développées, retranscrites sous MiCorr à l’aide d’un outil de construction de structures stratigraphiques et enrichies de différents mots-clés propres aux métaux étudiés, l’utilisateur se voit proposer des modèles de corrosion équivalents ou proches. Au-delà de la simple consultation de la base de données de MiCorr, l’utilisateur peut insérer ses propres données, les partager et devenir ainsi un contributeur actif de ce site participatif

Influence of risks and privacy literacy on coping responses to privacy threats

L’adoption massive des smartphones et des applications qui leurs sont dédiées ouvre de nouvelles opportunités pour les éditeurs de logiciels tout en présentant des risques accrus pour les possesseurs de ces appareils. Afin de comprendre la réponse des utilisateurs f ace aux dangers pesant sur leur sphère privée, cette recherche prés ente une expérience nous permettant de mesurer l’influence de la connaissance des risques et de la sensibilité aux atteintes à la sphère privée sur la réponse à ces dangers. Les résultats nous permettent de montrer que la connaissance des risques est l’élément le plus important dans la mesure de l’intention d’installer une application potentiellement dangereuse. Ces résultats vont permettre de mieux cibler les actions visant à aider les utilisateurs à se protéger face à ces nouveaux risques.The mass adoption of s martphones and their dedicated applications opens new opportunities for software vendors while presenting increased risks for software users . In order to understand the reaction of users facing privacy risks, this research presents an experiment measuring the influence of risks and privacy literacy on coping responses to privacy threats. Results show that risks literacy has the largest influence on the intention to install a poten tially privacy - threatening application on a smartphone. These results could allow better target ing of actions developed to help users protect themselves against these new risks

Influence of users’ privacy risks literacy on the intention to install a mobile application

While users are increasingly embracing smartphones worldwide, these devices, storing our most personal information, are repeatedly found to be leaking users’ data. Despite various atte mpts to inform users of these privacy issues, they continue to adopt risky behaviors. In order to better protect users of these devices, we need to understand the antecedents of the decision to install potentially privacy-threatening applications on them. We ran a large experiment in order to determine the influence of privacy risks literacy on the intent to install a potentially privacy threatening application on a smartphone. Using partial least squares (PLS), we were able to find that more than the privacy risks literacy, it is the coping behavior literacy that influences the user’s decision to install a mobile application. These findings are relevant to help determine a course of action in order to increase the user’s privacy protection when using such devices

Comparison of Multicriteria and Prediction Market Approaches for Technology Foresight

Cet article présente et compare deux approches originales de veille technologique basées sur un paradigme antagoniste: une approche des sciences de la gestion (prise de décision multicritère) versus une approche participative (marché de prédictions). Elles sont toutes deux destinées à soutenir la gestion d'un portefeuille technologique ainsi que l'évaluation de nouvelles technologies dans le cadre d'une organisation active dans les technologies de l'information. Pour évaluer la pertinence de notre recherche, nous avons réalisé plusieurs expériences dans un environnement réel. Les résultats ont montré que la rigueur des sciences de la gestion combinée au côté participatif du Web 2.0 était un atout dans le cadre de la veille technologique. De plus, un cadre conceptuel a été établi pour comparer les deux approches