Group Decision and Negotiation. A Process-Oriented View

The benefice of a collective decisions process mainly rests upon the possibility for the participants to confront their respective points of views. To this end, they must have cognitive and technical tools that ease the sharing of the reasons that motivate their own preferences, while accounting for information and feelings they should keep for their own. The paper presents the basis of such a cooperative decision making methodology that allows sharing information by accurately distinguishing the components of a decision and the steps of its elaboration.

The precision engineering sector lies at the heart of the UK’s manufacturing capability. Successful precision engineering businesses are required to master process innovation and supply chain solutions. Companies operating in this sector support, amongst others, economy-driving industries such as aerospace, defence, motorsport, nuclear, off-highway equipment, oil and gas and renewable energy. The main companies that constitute this sector are SMEs (or small and medium-sized enterprises). In these types of business environment, the implementation of innovative, collaborative solutions has become a necessary strategy for enhancing SME decision-making processes as well as for improving overall business competitiveness. The aim of the research described in this paper is to present how, by implementing a web and onlinebased collaborative tool, precision engineering SME’s can benefit, and are able to enhance their performance, by improving their production planning processes collaboratively. The research is presented with the help of a description of case study undertaken in a precision engineering SME.

Very often Telecom operators and service providers need to procure multiple products and technologies to deliver services to their end users. Regulatory bodies might issue specific requirements for service delivery in specific areas where operators have no incentive to invest. This is typically the case in mobile communication’s industry where operators are forced by the license terms to provide services in low-revenue rural areas. They usually cooperate to build a shared network to reduce the cost of infrastructure while competing in major cities. Similar situation can be encountered in the Fiber to the Home (FTTH) service where the total cost of ownership is extremely high due to the high cost of civil works (e.g. trenching and pulling of fiber).Usually, Telecom authorities encourage operators to share the investment and develop partnerships to overcome the issue of business viability pertaining to high deployment cost. One way of achieving such goal is to deliver products and services under merger to benefit from economy of scale and scope and reduce marginal costs for the required products and services. In the same time, the merging firms are also competing on other standard products and services required by the buyer.

In this document we propose a model for multiple-unit procurement combining Merger and Budget Constraint under Cournot competition. Firms are requested to deliver two products A and B. We assume that the two firms have different marginal costs for product-A, subject to competition while product-B is delivered under merger between the two firms. The empirical part of the article shows that the buyer can comply with the budget constraint by setting a requirement on the minimum quantity of product-B to be delivered by the merger and in the same time optimize the total quantity of products A and B.

Winning bids in reverse auctions are efficient solutions (providing that fairly weak assumptions about the bidders are met). The auctions are efficient, under the assumption that the utilities of all participants are quasi-linear. Typically, this assumption is unrealistic. If that is the case, auctions are inefficient mechanisms. This paper outlines the limitations and impracticability of the quasi-linearity assumption and proposes augmenting reverse auctions with negotiations. It shows that when the efficient frontier is concave, then it is possible to improve the winning bid through negotiations that follow auctions.

Penny auction, an emerging popular auction mode, requires bidders to pay for each bid. Since its mechanism is different from traditional ones, the results of past studies may not be applied to this auction model. The goal of this study is to explore the drivers of engaging in penny auction. Perceived fairness and perceived value are the major cognitions we investigated. We inferred that certain mechanisms adopted by penny auctions may enhance perceived value and fairness of penny auction. An online experiment was implemented to examine the proposed hypotheses. The results confirmed most of our hypotheses – (1) intention to bid is a function of perceived hedonic value, transaction utility, and perceived price fairness and (2) bidding mechanisms have effects on bidders’ perceptions. Implications for researchers and practitioners are also provided.

In this paper, we propose a process for small to medium scale multi-assignment problems. In addition to biddings, agents can give motivations to explain their choices in order to help decision makers break ties in a founded way. A group decision support system, based on Logical Information Systems, allows decision makers to easily face both biddings and motivations. Furthermore, it guaranties that all the agents are treated equally. A successful case study about a small course assignment problem at a technical university is reported.

Knowledge-Based Decision Support Systems (KBDSS) have evolved greatly over the last few decades. The key technologies underpinning the development of KBDSS can be classified into two categories: technologies for knowledge modelling and representation, and the technologies for reasoning and inference. This paper provides a review on the recent advances in the two types of technologies, as well as the main application domains of KBDSS. Based on the examination of literature, future research directions are recommended for the development of KBDSS in general and in particular to support group decision making.

Cognitive science, as well as psychology, considers that individuals use internal representations of the external reality in order to interact with the world. These representations are called mental models and are considered as a cognitive structure at the basis of reasoning, decision making, and behavior.

This paper relies on a fieldwork realized as closely as possible from the respondents. We propose an approach based on graph theory in order to study the meanings given by several people to the same concept, and to identify those who give it the same meaning.

The use of tools from graph theory combined with the study of cognitive maps leaded us to highlight the importance of interaction notably within group decision making. This idea, as well as the limits of our approach, are discussed at the end of this paper.

Knowledge is the strength of an organisation. However, how much knowledge should be stored in the knowledge-base of a decision support system (DSS) has remained as a key question under investigation. Hence, a Lean-Knowledge Inventory Model (Lean-KIM) will be presented in this paper to optimise organisational knowledge inventory levels and knowledge flow for providing group decision makers with sufficient and high quality knowledge for decision making. This paper presents new contributions by integrating Lean Philosophy with nine knowledge activities to improve the knowledge management performance for group decision-making with respect to knowledge capture, creation, reposition, diffusion and application.

Multiple Criteria Decision Making (MCDM) models make preference decisions over multiple attributes’ alternatives available, which in most of the cases conflict among themselves. On the other hand, the classic MCDM model assumes that the decision maker has a pre-defined fixed set of criteria, when taking a decision, and is presented with a clear picture of all available alternatives. This classic view reduces the solution to computing the score of each alternative, producing a ranking, and choosing the one that maximizes this value. As most of the real-world decision making scenarios take place in dynamic environments, involving multiple alternatives which usually have conflicting attributes, classic MCDM models do not really satisfy their requirements, especially when we deal with multiple groups in the decision process. Dynamic MCDM models are more appropriate to solve real decision problems, since they cater for the impact of time within the decision making process. In this paper, we investigate an MCDM model for group decision making, by taking into consideration its dynamic perspective. A case-study about hotel ranking, involving multi-groups in the decision making process is sketched to illustrate the approach.

Pervasive computing allows a world full of electronic devices connected to each other, autonomous, context aware and with a certain level of intelligence. They are deployed in our environment to ease our life. However today users don’t control the traffic around their data. The use of mobile devices might increase this problem because the system is more complex and requests of personal data is transparent to users in order to reduce their cognitive load. The goal of Kapuer is to inform the user on requests about his privacy and help him protect his privacy by assisting him in the writing of authorization policies. But a risk remains, informing too much the user can drown him into a huge amount of information and could quit using the system. The idea around Kapuer is to make the user conscious of the situation without bothering him too much.

We consider a model of non-additive Choquet aggregation in group processes, with reference to the context of effort estimation in Project Management. The groups considered are formed by “experts” (people with specific technical competence) and “non-experts” (people with less specific technical competence, usually experts in related fields), so that the typically complementary biases of the two classes contribute to a more balanced estimate. We present two simple examples which illustrate how the Choquet aggregation results improve those of the classical weighted mean (additive case). Finally, we discuss the relation between the average Choquet weights of consensual coalitions of experts and non-experts and their individual Shapley values.

Urban and economic development is affected by the value of land. Therefore, land value appraisal methods are important to determine the significance of land segments. A significant number of these models do not apply geospatial analysis in their estimations. This paper presents a land valuation model based on spatial multi criteria decision analysis (SMCA) to assess land values in Abu Dhabi, UAE. Through this study, criteria maps were generated and combined to produce a final map ranking land segments based on their relative value.

Criteria weights are typically cognitively demanding to elicit and numeric precision is problematic since information in real-life multi-criteria decision making often is imprecise. One important class of methods rank the criteria and receive a criteria ordering which can be handled in various ways by, e.g., converting the resulting ranking into numerical weights, so called surrogate weights. In this article, we analyse the relevance of these methods and to what extent some validation processes are strongly dependent on the simulation assumptions. We also suggest more robust methods as candidates for modelling and analysing multi-criteria decision problems of this kind.

In this paper we study how do the decision makers proceed in analyzing the multiple criteria decision making (MCDM) problem. Based on the results of the questionnaire-based experiment, we investigate how do they define the reference points in the decision problem and specify their preferences. We also study what kind of problems do they encounter while analyzing such a multiple criteria decision making problem. Finally, we consider what MCDM methods could be used to fit the decision makers way of analyzing the preferences and conducting the decision process.

This paper considers group decision making problems (GDM) in bipolar context where actors provide their preferences over alternatives through positive and negative attributes. A soft consensus model based on distance between evaluations is proposed to narrow the differences between decision makers and to ensure convergence of individual preferences towards group preferences. A feedback mechanism defined by the identification and consensus phases is introduced to reach a consensus. For a group with interactive relationships, the potential reciprocal influence of decision makers is considered using concordance and discordance measures.

This work addresses the efficient multi-agent coordination problem based on negotiation which take into account the unpredictable behaviours and availabilities of the agents and the dynamic evolving of the tasks. To ensure and to adapt dynamically negotiations, we provide a new negotiation protocol based on the

recommendation

and on

alliance

principle. We also provide an experimental performance evaluation.

This work addresses the Interaction Protocols (IP) adaptation issue for negotiation in Opened Multi-Agents Systems (OMAS). By OMAS, we mean the agents evolve in a changeable and dynamic environment, and can be led to form dynamically partnerships which they can enter or leave any time, and in that play variable roles. The IP based negotiation is considered as an interesting aspect for coordination in OMAS since they structure and organize the negotiation between agents to reach a common decision on the considered negotiation object. Obviously, to ensure an efficient negotiation between agents, we need to adapt their interaction protocols if these are not perfectly suitable for them. More precisely, the paper defends that versioning technique is a good solution to deal with interaction protocols adaptation at build time (or a priori) in OMAS. First, it presents a Versioned Interaction protocol Meta-Model (VIP2M for short) for IP versions modeling. Then, it shows how we extend the VIP2M meta-model with the contextual dimension to facilitate the selection of an IP version among several. Finally, it gives a running example to better illustrate the use of IP versions.

The design of electronic negotiation systems should be sufficiently flexible to accommodate various types of mechanisms, as well as different roles of the participants. The current work relies on social interaction theory in order to propose design principles and a model for an ENS. The model is presented using a representational framework for IS meta-artifacts in the spirit of design science research. The features and functioning of the resulting system called PROSPER (a Platform Relying On Social Participation for E-market Realization) are presented.

In this paper we discuss the issue of evaluating the negotiation offers represented in a form of the complete packages and the negotiators’ consistency in scoring such packages. We analyze the results of an experiment, in which the negotiators were asked to build the ranking of fourteen negotiation offers and then compare it with two predefined rankings obtained by means of SAW method. We verify how do the negotiators evaluate these SAW-based rankings and how they correspond to the negotiators’ intrinsic ones. We discuss then both the negotiators’ consistency in defining their preferences and the applicability of some formal methods in supporting them in such a definition.

The starting point of modern social choice theory is the assumption that is the individuals are endowed with complete and transitive preference relations over the set of alternatives. Over the past 60 years a steady flow of experimental results has suggested that people tend to deviate from principles of choice stemming from the utility maximization theory. Especially in choices under risk, this behaviour is quite common. More importantly, this behaviour makes intuitive sense. The usual culprit, i.e. the source of this “deviant” behaviour, is most often found in the violation of transitivity or – under risk – of the monotonicity in prizes principle. We show that there are grounds for arguing that even the completeness principle as well as continuity of preferences may, quite plausibly, be violated.

Groups engaged in a mutual activity often need assistance in order to reach a joint decision. However, the group members’ personal preferences are often unknown and need to be collected. Querying for preferences can annoy the users. We suggest employing a voting mechanism that finds a winning item under incomplete settings. We present a practical method for eliciting the preferences, so that with a minimal amount of queries a winning item that certainly suits the group can be computed. The heuristic incorporates probabilistic assumptions on the users’ preferences and was evaluated on a real world datasets as well as on simulated data, showing a saving in queries to users.

In electronic negotiations, buyers and sellers are represented by negotiating agents and it becomes imperative for the negotiating agents to acquire user’s preferences to be able to negotiate better. In this paper we present the design of a web based engine to capture a buyer’s choices over time through a preference elicitation tool known as Time – Tradeoff sequence(TTO Sequence). Preferences thus elicited are used by buyer’s electronic agents to negotiate price and date of movie tickets with cineplex owners. Further, we illustrate with an example that negotiation outcome is affected by the time-preference of the buyer.

In the aim to decrease the user effort during the preference elicitation phase, we have studied the use of value ranges. We propose to allow the users to modify a reduced initial set of alternatives to easily report their preferences. We have investigated the consequences on the following steps of the decisional process. This is illustrated by examples taken in the search for common time slots for a meeting using an on-line group decision support system.

In any country or region undergoing social and economic advancement, coordinating the consumption of resources and environment with economic development inevitably becomes a major issue. Based on the combination of data envelopment analysis and grey system forecasting theory, this paper establishes a “grey model-data envelopment analysis” (GM-DEA)pre-evaluation model and extends the pre-evaluation ability of temporal sequence DEA. We take the resource, environment and economy system of Jiangsu Province as an example, then measure and analyze the coordination of the resource-environment-economy (REE) system of Jiangsu from 1997 to 2014 quantitatively. This paper introduces useful methods for optimizing the coordination among the REE system. The results show that the coordination declines at first and then rises slowly from 1997 to 2014 and there is a large fluctuation and weak stability. The evaluation results and related suggestions are provided in this paper.

Although some companies, such as Google, Best Buy and GE have generated and used prediction markets internally there has been limited investigation of real world use of prediction markets. Accordingly, the purpose of this paper is to investigate three issues associated with real world data derived from corporate use of prediction markets.

Strategic planning models and information provision for decision-making in complex strategic situations are frequent subjects for scientific research. This research deals with the problem of supporting strategic planning decision-making in public higher education (HE) institutions by designing a Decision Support System (DSS) to be used by HE decision makers in implementing their strategic planning process, considering that the DSS would be anchored in on all databases of the institution’s information systems. This paper adopts a model for the strategic planning process, advocates the incorporation of technologies of participation (ToP) and introduces a collaborative framework for the planning activities at the different institutional levels to develop the institution’s strategic plan using a bottom-up approach. Based on the strategic planning process model, a DSS framework is proposed and decision support methods are suggested for the different modules of the DSS. The DSS provides intelligent support (on the individual, group and organizational levels) to strategic planning decisions in all stages of the process. By utilizing this DSS, it is possible to create better conditions for implementing the objectives of the future-oriented activity of the institution.

This paper summarizes a research path in the area of Multicriteria Decision Aiding (MCDA) in order to propose, test and refine an implementation model of a decision support process that uses

VIP Analysis

Software (Variable Interdependent Parameters Analysis). This path followed an Action Research methodology, based on interventions in three organizations. The results of this research guide decision facilitators on how to use the system and the use of cognitive maps as problem structuring method.

Supply chain businesses are facing new challenges due to many events that recently took place in the Middle East Region that directly affects supply chain performance. Yet, managers lack insights in the development of effective performance measures and metrics needed to test and reveal the viability of strategies needed to make effective decisions before perils become more complicated. The main objective of this study is to have a network view to all factors causing vulnerabilities to the stakeholders in the entire chain. This can be done after identifying and prioritizing the critical factors and Key Performance Indicators in the Fast Moving Consumer Goods industry in the Middle East Region in order to proactively design and build resilience in supply chains. For this reason this study is considered as highly explorative. Therefore, the research methodology for this study comprises two purposeful components, namely; in-depth interviews combined with an analytic network process.

With the emergence of social networks, users show the willingness to use them to find and offer services. A problem arises when the number of available services is increasing and no means to distinguish between two or many providers offering the same service. To overcome this issue, we propose a trust measure defined as the combination of two dimensions namely

sociability

and

expertise

. This measure allows to discover trustworthy providers with good services satisfying the requester’s needs. The problem increases when no central control can be fixed due to the distributed nature of social networks. To address that, our work advocates a distributed agent-based service discovery approach where each user is represented by an agent that acts on behalf of him to achieve the service discovery task. The propagation process within the social network is ensured by means of a

referral system

wherein agents communicate and evaluate

referrals

based on a distributed knowledge and a decentralized decision-making.

Semantic Web technologies are intertwined with decision-making processes. In this paper the general objectives of the semantic web tools are reviewed and characterized, as well as the categories of decision support tools, in order to establish an intersection of utility and use. We also elaborate on actual and foreseen possibilities for a deeper integration, considering the actual implementation, opportunities and constraints in the decision-making context.