Ebook: Collaborative Decision Making: Perspectives and Challenges
This publication presents the latest innovations and achievements of academic communities on Decision Support Systems (DSS). These advances include theory systems, computer-aided methods, algorithms, techniques and applications related to supporting decision making. The aim is to develop approaches for applying information systems technology to increase the effectiveness of decision making in situations where the computer system can support and enhance human judgements in the performance of tasks that have elements which cannot be specified in advance. Also it is intended to improve ways of synthesizing and applying relevant work from resource disciplines to practical implementation of systems that enhance decision support capability. The resource disciplines include: information technology, artificial intelligence, cognitive psychology, decision theory, organizational theory, operations research and modeling. Researchers come from the Operational Research area but also from Decision Theory, Multicriteria Decision Making methodologies, Fuzzy sets and modeling tools. Based on the introduction of Information and Communication Technologies in organizations, the decisional process is evolving from a mono actor to a multi actor situation in which cooperation is a way to make the decision.
The Collaborative Decision Making Conference (CDM08) is a joined event. This conference has for objective to join two working groups on Decision Support Systems: the IFIP TC8/Working Group 8.3 and the Euro Working Group on Decision Support Systems.
The first IFIP TC8/Working Group 8.3 conference was organised in 1982 in Vienna (Austria). Since this year the IFIP conferences present the latest innovations and achievements of academic communities on Decision Support Systems (DSS). These advances include theory systems, computer aided methods, algorithms, techniques, and applications related to supporting decision making.
The development of approaches for applying information systems technology to increase the effectiveness of decision-making in situations where the computer system can support and enhance human judgements in the performance of tasks that have elements which cannot be specified in advance.
To improve ways of synthesizing and applying relevant work from resource disciplines to practical implementation of systems that enhance decision support capability. The resource disciplines include: information technology, artificial intelligence, cognitive psychology, decision theory, organisational theory, operations research and modelling.
The EWG on DSS was created in Madeira (Portugal) following the Euro Summer Institute on DSS, in May 1989. Researchers involved in this group meet each year in different countries through a workshop. Researches in this group come from Operational Research area but also from Decision Theory, Multicriteria Decision Making methodologies, Fuzzy sets and modelling tools.
Based on the introduction of Information and Communication Technologies in organisations, the decisional process is evolving from a mono actor to a multi actor situation in which cooperation is a way to make the decision.
For 2008, the objective was to create a synergy between the two groups around a specific focus: Collaborative Decision Making. Papers submitted to the conference have for main objectives to support Collaborative Decision Making but with several kinds of tools or models. 69 papers have been submitted coming from 24 countries. 34 full papers have been selected organised in 8 themes constituting the part I of this book. 9 short papers have been accepted as short papers organised in 3 themes constituting the part II. Nevertheless, a variety of topics are also presented through several papers coming reinforce the vivacity of researches conducted in Decision Support Systems.
The contributions are organised as follows:
Part I: Full Papers
Models for Collaborative Decision Making
Collaborative Decision Making for Supply Chain
Collaborative Decision Making for Medical Applications
Collaboration tools for Group Decision Making
Tools for Collaborative Decision Making
Collaborative Decision Making in ERP
Knowledge management for Collaborative Decision Making
Collaborative Decision Making Applications
Part II: Short Papers
Tools for Collaborative Decision Making
Collaborative Decision Making: Cases studies
Organisational Collaborative Decision Making
Hoping that joined projects could emerge from groups' members during and after the conference and hoping that new challenges could arise during the conference concerning Decision Support Systems researches. It is then our responsibility to maintain this domain an attractive and interesting investigating area. For the future, new conferences will be organised for both groups: the IFIP TC8/WG8.3 and the EWGDSS, hoping that this event, CDM08 2008, will stay the meeting point.
As editors of this book, it is our duty to conclude by expressing our gratitude to all contributors to these proceedings, to the members of the steering and program committees who helped us selecting the papers, making this conference as interesting as possible and preparing these proceedings.
Pascale Zaraté, CDM08 Chairperson
Jean Pierre Belaud, CDM08 Organisational Committee member
Guy Camilleri, CDM08 Organisational Committee member
Franck Ravat, CDM08 Organisational Committee member
This paper focuses on job shop scheduling problems in a cooperative environment. Unlike classical deterministic approaches, we assume that jobs are not known in advance but occur randomly during the production process, as orders appear. Therefore, the production schedule is adapted in a reactive manner all along the production process. These schedule adaptations are made according to a cooperative approach, that is the major originality of this paper. Each resource manages its own local schedule and the global schedule is obtained by point-to-point negotiations between the various machines. We also suppose that local schedules are flexible since several alternative job sequences are allowed on each machine. This flexibility is the key feature that allows each resource, on the one hand, to negotiate with the others and, on the other hand, to react to unexpected events. The cooperative approach aims at ensuring the coherence between the local schedules while keeping a given level of flexibility on each resource.
There is abundant evidence that the current business environment is pushing firms to invest increasing amounts of resources in sourcing state of the art IT capability. Some of this investment is directed towards developing the decision support capability of the firm and it is important to measure the extent to which this deployment of decision support is having a positive impact on the decision making of managers. Using existing theories, namely an adaptation of Humphreys' representation levels (Humphreys, 1989), to classify the type of support which managers can get from their decision support tools, we investigated the portfolio of decision related applications available to managers in 5 Irish firms. Our findings indicate that not all firms can achieve the development of decision support tools across all the categories of the framework. Managers need to be able to spell out the problems they are facing, but also need to be in a situation where they have clear incentives to make the efforts required in investigating high level problems, before firms can be observed to have a complete portfolio of decision support tools, not merely a collection of static reporting tools.
We describe how contextual graphs allow the analysis of oral corpus from person-to-person collaboration. The goal was to build a task model that would be closer to the effective task(s) than the prescribed task. Such a “contextualized prescribed task” is possible, thanks to a formalism allowing a uniform representation of elements of decision and of contexts. The collaborative process of answer building identified includes a phase of building of the shared context attached to the collaboration, shared context in which each participant introduces contextual elements from his/her individual context in order to build the answer with the other. Participants in the collaborative building process agree on the contextual elements in the shared context and organize, assemble and structure them in a proceduralized context to build the answer. The proceduralized-context building is an important key of the modeling of a collaborative decision making process.
In the context of supervisory control of one or several artificial agents by a human operator, the definition of the autonomy of an agent remains a major challenge. When the mission is critical and in a real-time environment, e.g. in the case of unmanned vehicles, errors are not permitted while performance must be as high as possible. Therefore, a trade-off must be found between manual control, usually ensuring good confidence in the system but putting a high workload on the operator, and full autonomy of the agents, often leading to less reliability in uncertain environments and lower performance. Having an operator in the decision loop does not always grant maximal performance and safety anyway, as human beings are fallible. Additionally, when an agent and a human decide and act simultaneously using the same resources, conflicts are likely to occur and coordination between entities is mandatory. We present the basic concepts of an approach aiming at dynamically adjusting the autonomy of an agent in a mission relatively to its operator, based on a formal modelling of mission ingredients.
Agents and multi-agent systems constitute nowadays a very active field of research. This field is very multidisciplinary since it is sustained by Artificial Intelligence, Distributed Systems, Software Engineering, etc. In most agent applications, the autonomous components need to interact. They need to communicate in order to solve differences of opinion and conflicts of interest. They also need to work together or simply inform each other. It is however important to note that a lot of existing works do not take into account the agents' preferences. In addition, individual decisions in the multi-agent domain are rarely sufficient for producing optimal plans which satisfy all the goals. Therefore, agents need to cooperate to generate the best multi-agent plan through sharing tentative solutions, exchanging sub goals, or having other agents' goals to satisfy. In this paper, we propose a new negotiation mechanism independent of the domain properties in order to handle real-time goals. The mechanism is based on the well-known Contract net Protocol. Integrated Station of Production agents will be equipped with a sufficient behavior to carry out practical operations and simultaneously react to the complex problems caused by the dynamic scheduling in real situations. These agents express their preferences by using ELECTRE III method in order to solve differences. The approach is tested through simple scenarios.
Dicodess is a model based distributed cooperative decision support system. It encapsulates the underlying model in a graphical user interface to shield users from the technical details of model configuration and optimization. However, a model usually evolves over time and therefore needs verification accordingly. Furthermore, users sometimes might want to have a better insight into the model to better understand a “strange” solution. Model views are a new concept for modeling language and domain independent model visualization. The focus is not on visualizing model input or model output but on the model's structure, the formalized knowledge. Modelers as well as domain experts are able to inspect a model visually in order to get a better understanding and to have a common base of discussion. The improvement of model understanding and communication among the people involved will lead to models of better quality. In this article we are proposing an integration of model views into Dicodess. This integration enables mutual benefit: Dicodess users get direct access to model visualization which through Dicodess' cooperative functionality can be done even in collaboration.
To improve the supply chains performance, taking into account the customer demand in the tactical planning process is essential. It is more and more difficult for the customers to insure a certain level of demand over a medium term period. Then it is necessary to develop methods and decision support systems to reconcile the order and book processes. In this context, this paper aims at introducing a collaboration support tool and methodology dedicated to a dyadic supply chain. This approach aims at evaluating in term of risks different demand management strategies within the supply chain using a simulation dedicated tool. The evaluation process is based on an exploitation of decision theory and game theory concepts and methods.
The slow progress to date regarding inter-organizational collaborative decision management within manufacturing supply chains is due to a lack of common understanding of this concept, and the difficulty of integrating external requirements of customers and suppliers into opaque internal decision control. In this paper, we focus on the production management of dynamic manufacturing networks that is characterized by non-centralized decision making. We set out to clarify internal decision collaboration concepts based on research and technology led on collaborative work and enterprise modeling techniques, and discuss how IT can support and improve business and managerial decision-making within supply chains. This paper begins with examining the Communication Driven Decision Support System (DSS) concept and its integration within a supply chain point of view. A framework for inter-organizational decision support is then discussed and linked to the traditional Decision Support Systems and the overall Information Management solutions. We conclude that the effectiveness of supply chain collaboration relies upon two factors: the level to which it integrates internal and external decisions at strategic, tactical and operational levels, and the level to which the efforts are aligned to the supply chain settings in terms of the geographical dispersion, the demand pattern, and the product characteristics.
ECLIPS is a European research project, partially funded by the European Commission in the context of its Research Framework Programme 6. Six partners participate in this research project: MÖBIUS (Belgium), EURODECISION (France), LoQutus (Belgium), the Technical University of RIGA (Latvia), Huntsman Advanced Materials (Germany), PLIVA-Lachema Diagnostika (Czech Republic). For more information about ECLIPS we recommend to visit the project web site www.eclipsproject.com. The overall goal of this project is to extend supply chain expertise to recent evolutions: globalisation, products diversification, and shortening of products life cycles. We consider that any life cycle can be divided into three phases: introduction, maturity and end-of-life. Three main issues are considered: Improve the statistical prediction of the demand at the beginning and at the end of a product life. Increase the profit during maturity phase by making cyclic the production at all levels of the process. From a pure mathematical point of view, Multi-Echelon Cyclic Planning induces an additional cost. However, simplification of production management and increase of the manufacturing efficiency should counterbalance this cost. More generally, to improve the whole life cycle management of products in supply chain, including switches between the three phases.
The paper addresses the general nature of a supply chain as a human artifact with potential for greatness and for failure like any other. The exact nature of the possible failures and successes are discussed, and the ethical issues identified. The hazards of adversarial supply chain management, especially the more vicious forms of it, are identified. Intra-chain brutality is rarely as profitable as mutual supportiveness if we think, as the world's first international lawyer said we should, prudently and well into the future. The paper concludes with one drastic example of what happens when we do not.
Effective decision making plays a paramount role for successful emergency management (EM). Decisions should include collaborating inputs and feedback from a wide range of relevant emergency stakeholders such as emergency agencies, government, experts and communities. Although this kind of collaborative decision making is ideal, the process can be lengthy and complex. While there has been substantial research in EM, there is a lack of integrated frameworks to structure these contributions. Without an integrated framework, the decision making process can be inefficient and suggestions of the stakeholders may be neglected or excluded inadvertently. This paper presents the “Integrated Framework for Comprehensive Collaborative Emergency Management” (IFCCEM). IFCCEM aims to provide a collaborative mechanism so that all agencies as well as communities can contribute in the decision making. IFCCEM is based on the ‘All Hazards Approach’ and can be used by all agencies. The developed framework is illustrated with an application for collaborative decision making.
While the important role of family as carer has been increasingly recognised in healthcare service provision, particularly for patients with acute or chronic illnesses, the carer's information and social needs have not been well understood and adequately supported. In order to provide continuous and home-based care for the patient, and to make informed decisions about the care, a family carer needs sufficient access to medical information in general, the patient's health information specifically, and supportive care services. Two key challenges are the carer's lack of medical knowledge and the many carers with non-English speaking and different cultural backgrounds. The informational and social needs of family carers are not yet well understood. This paper analyses the web-log of a husband-carer who provided support for his wife, who at the time of care was a lung cancer patient. It examines the decision-making journey of the carer and identifies the key issues faced in terms of informational and social practices surrounding care provision.
This paper addresses collaborative learning in the medical domain. In particular, it focuses on the evaluation of a component specially devised to promote collaborative learning using AMPLIA. AMPLIA is an intelligent multi-agent environment to support diagnostic reasoning and the modeling of diagnostic hypotheses in domains with complex, and uncertain knowledge, such as the medical domain. Recently, AMPLIA has been extended with a new component providing support in workgroup formation. Workgroups are proposed based on individual aspects of the students, such as learning style, performance, affective state, personality traits, and also on group aspects, such as acceptance and social skills. The paper also presents and discusses the results of an experiment evaluating the performance of workgroups composed according to suggestions provided by the system.
Research in psychology has found that subjects regularly exhibit a conjunction fallacy in probability judgment. Additional research has led to the finding of other fallacies in probability judgment, including disjunction and conditional fallacies. Such analyses of judgments are critical because of the substantial amount of probability judgment done in business and organizational settings. However, previous research has been conducted in the environment of a single decision maker. Since business and other organizational environments also employ groups, it is important to determine the impact of groups on such cognitive fallacies. This paper finds that groups substantially mitigate the impact of probability judgment fallacies among the sample of subjects investigated. A statistical analysis, based on a binomial distribution, suggests that groups investigated here did not use consensus. Instead, if any one member of the group has correct knowledge about the probability relationships, then the group uses that knowledge and does not exhibit fallacy in probability judgment. These results suggest that at least for this setting, groups have a willingness to collaborate and share and use knowledge from the group.
Information technology governance is the set of organizational structures that determine decision-making rights and responsibilities with regard to an organisation's information technology assets. Although an important sub-field of information technology, little research has been done on the issues relating to the governance of decision support systems. This paper argues that decision support systems are significantly different to other kinds of information technology, and that this means there is a need to consider issues specific to their governance. Orlikowski's  theory of the Structuration of Technology is used to highlight the fundamental differences between decision support systems and other kinds of information technology, and their respective relationships with organizational structures. Some preliminary recommendations and suggestions for further research into issues of decision support systems governance are made.
In today's global economy, and as a result of the complexity surrounding the working world, new ways of working are emerging. In particular, collaboration and networking gain increasing importance as they enable firms to face the new demands of a global economy. Within this context, it is necessary to understand how new ways of organising influence decision-making processes. This paper (i) explores the connection between networks and decision-making and (ii) tries to define how efficient networking can support reliable collaborative decision making .We argue that effective networking constitutes a fundamental support for decision-making. Our focus is on small and medium-sized companies where networking is particularly relevant because of their restricted means for action and resources. Our findings are based on seven semi-structured interviews, conducted within five French small and medium-sized companies. They confirm the allegation that enterprise decision-making is now embedded in network structures  and also offer a good basis for drawing guidelines, enabling effective networking and reliable decision-making.
In this study, we visualise and interpret the relationships between different types of social network (SN) structures (i.e., degree centrality, cut-points) and group behavior using political contribution dataset. We seek to identify whether investment behavior is network dependent using the political contribution dataset. By applying social networks analysis as a visualisation and interpretation technique, we find patterns of social network structures from the dataset, which explains the political contribution behavior (i.e., investment behavior) of political action committee (PAC). The following questions guide this study: Is there a correlation between SN structure and group behavior? Do we see patterns of different network structures for different types and categories of political contribution (i.e., support or oppose; level of contribution)? Is there a structural difference of networks between different types of support and oppose behavior? Do the group networks for support and oppose differ structurally on the basis of different types of political contribution patterns?
Companies are increasingly encouraging employees to work cooperatively, to coordinate their activities in order to reduce costs, increase production, and improve services or just to augment the robustness of the organization. This is particularly relevant in the software industry where the available time frames are quite tight. However, many software companies do not formally evaluate their team performance because the available methods are complex, expensive, slow to deliver the results or error-prone. In case of software companies that evaluate team performance, they have also to deal with team members feeling about the fairness of such evaluations. This paper presents a method intended to evaluate the software team and their members' performance in a simple and fast manner, involving also a low application cost. The method, called Team Evaluation Method (TEM), is supported by a software tool, which reduces the application effort. The proposal has been used to evaluate software development teams, and the obtained results are satisfactory.
Developing consensus is crucial to effective collaborative decision making and is particularly difficult in cases involving disruptive technologies, a new technology that unexpectedly displaces an established technology. Collaborative decision making often involves multiple criteria. Multicriteria decision making (MCDM) techniques, such as the analytical hierarchy process (AHP) and multiattribute utility theory (MUAT), rely on the accurate assignment of weights to the multiple measures of performance. Consensus weighting within MCDM can be difficult to achieve because of differences of opinion among experts and the presence of intangible, and often conflicting, measures of performance. The method presented in this paper can be used to develop a consensus weighting scheme within MCDM. This paper presents a statistically-based method for consensus building and illustrates its use in the evaluation of a capital project involving the purchase of mammography equipment as disruptive technology in healthcare management. An AHP architecture is proposed to evaluate the best decision from the proposed