Visual analytics for supply network management: system design and evaluation

We propose a visual analytic system to augment and enhance decision-making processes of supply chain managers. Several design requirements drive the development of our integrated architecture and lead to three primary capabilities of our system prototype. First, a visual analytic system must integrate various relevant views and perspectives that highlight different structural aspects of a supply network. Second, the system must deliver required information on-demand and update the visual representation via user-initiated interactions. Third, the system must provide both descriptive and predictive analytic functions for managers to gain contingency intelligence. Based on these capabilities we implement an interactive web-based visual analytic system. Our system enables managers to interactively apply visual encodings based on different node and edge attributes to facilitate mental map matching between abstract attributes and visual elements. Grounded in cognitive fit theory, we demonstrate that an interactive visual system that dynamically adjusts visual representations to the decision environment can significantly enhance decision-making processes in a supply network setting. We conduct multi-stage evaluation sessions with prototypical users that collectively confirm the value of our system. Our results indicate a positive reaction to our system. We conclude with implications and future research opportunities.The authors would like to thank the participants of the 2015 Businessvis Workshop at IEEE VIS, Prof. Benoit Montreuil, and Dr. Driss Hakimi for their valuable feedback on an earlier version of the software; Prof. Manpreet Hora for assisting with and Georgia Tech graduate students for participating in the evaluation sessions; and the two anonymous reviewers for their detailed comments and suggestions. The study was in part supported by the Tennenbaum Institute at Georgia Tech Award # K9305. (K9305 - Tennenbaum Institute at Georgia Tech Award)Accepted manuscrip

Managing Knowledge in a Distributed Decision Making Context

This paper considers the role of electronic communication in the creation and distribution of knowledge, and in particular, the creation and sharing of personalised knowledge. Personalised knowledge or "intellectual capital" is perhaps a least understood but most important asset of modern organisations. This paper reveals the creation and sharing of personalised knowledge in a network organisation. The network organisation investigated in this paper relies on electronic communication in a distributed decision making context to leverage the skills and intellect of its key professionals. This paper investigates electronic group meetings that take place on this electronic social space to analyse key processes of knowledge creation. Implications for managing distributed personalised knowledge are discussed and conclusions drawn with respect to the key decision support systems functionalities required for managing knowledge in situations where decision making is distributed and takes place on an electronic social space.Personalised Knowledge;c entrality;communication infrastructure;distributed decision support;electronic social space;prestige

An Integrated Assessment Framework for Water Resources Management: A DSS Tool and a Pilot Study Application

Decision making for the management of water resources is a complex and difficult task. This is due to the complex socio-economic system that involves a large number of interest groups pursuing multiple and conflicting objectives, within an often intricate legislative framework. Several Decision Support Systems have been developed but very few have indeed proved to be effective and truly operational. MULINO (Multisectoral, Integrated and Operational Decision Support System for Sustainable Use of Water Resources at the Catchment Scale) is a project funded under the Fifth Framework Programme of the European Research and the key action line dedicated to operational management schemes and decision support system for sustainable use of water resources. The MULINO DSS (mDSS) integrates hydrological models with multi-criteria decision methods and adopts the DPSIR (Driving Force – Pressure – State – Impact – Response) framework developed by the European Environment Agency. The DPSIR was converted from a static reporting scheme into a dynamic framework for integrated assessment modelling (IAM) and multi-criteria evaluation procedures. This paper presents the methodological framework and the intermediate results of the mDSS tool through its application in a pilot study area located in the Watershed of the Lagoon of Venice.Integrated water resources management, Spatial decision-making, Decision support system, Catchment, Environmental modelling

Decision support systems for large dam planning and operation in Africa

Decision support systems/ Dams/ Planning/ Operations/ Social impact/ Environmental effects

A Conceptual Framework for Mobile Learning

Several technology projects have been launched to explore the opportunities that mobile technologies bring about when tackling issues of democratic participation and social inclusion through mobile learning. Mobile devices are cheaper than for instance a PC, and their affordance, usability and accessibility are such that they can potentially complement or even replace traditional computer technology. The importance of communication and collaboration features of mobile technologies has been stressed in the framework of ICT-mediated learning. In this paper, a theoretical framework for mobile learning and e-inclusion is developed for people outside the conventional education system. The framework draws upon the fields of pedagogy (constructivist learning in particular), mobile learning objects and sociology.Mobile Learning, Digital Divide, Constructivist Pedagogy, Forms Of Capital

CBR and MBR techniques: review for an application in the emergencies domain

The purpose of this document is to provide an in-depth analysis of current reasoning engine practice and the integration strategies of Case Based Reasoning and Model Based Reasoning that will be used in the design and development of the RIMSAT system. RIMSAT (Remote Intelligent Management Support and Training) is a European Commission funded project designed to: a.. Provide an innovative, 'intelligent', knowledge based solution aimed at improving the quality of critical decisions b.. Enhance the competencies and responsiveness of individuals and organisations involved in highly complex, safety critical incidents - irrespective of their location. In other words, RIMSAT aims to design and implement a decision support system that using Case Base Reasoning as well as Model Base Reasoning technology is applied in the management of emergency situations. This document is part of a deliverable for RIMSAT project, and although it has been done in close contact with the requirements of the project, it provides an overview wide enough for providing a state of the art in integration strategies between CBR and MBR technologies.Postprint (published version

Information techniques for irrigation systems: Selected proceedings of the Second International Network Meeting on Information Techniques for Irrigation Systems held in Lahore/Bahawalnagar, Pakistan, 5-8 December 1994

Irrigation management / Irrigation systems / Decision support tools / Decision making / Information systems / Computer techniques / Models / Water management / Malaysia / Pakistan / Sri Lanka

Potentials and Limits of Bayesian Networks to Deal with Uncertainty in the Assessment of Climate Change Adaptation Policies

Bayesian networks (BNs) have been increasingly applied to support management and decision-making processes under conditions of environmental variability and uncertainty, providing logical and holistic reasoning in complex systems since they succinctly and effectively translate causal assertions between variables into patterns of probabilistic dependence. Through a theoretical assessment of the features and the statistical rationale of BNs, and a review of specific applications to ecological modelling, natural resource management, and climate change policy issues, the present paper analyses the effectiveness of the BN model as a synthesis framework, which would allow the user to manage the uncertainty characterising the definition and implementation of climate change adaptation policies. The review will let emerge the potentials of the model to characterise, incorporate and communicate the uncertainty, with the aim to provide an efficient support to an informed and transparent decision making process. The possible drawbacks arising from the implementation of BNs are also analysed, providing potential solutions to overcome them.Adaptation to Climate Change, Bayesian Network, Uncertainty