Trust Based Consensus Model for Social Network in an Incomplete Linguistic Information Context

A theoretical framework to consensus building within a networked social group is put forward. This article investigates a trust based estimation and aggregation methods as part of a visual consensus model for multiple criteria group decision making with incomplete linguistic information. A novel trust propagation method is proposed to derive trust relationship from an incomplete connected trust network and the trust score induced order weighted averaging operator is presented to aggregate the orthopairs of trust/distrust values obtained from different trust paths. Then, the concept of relative trust score is defined, whose use is twofold: (1) to estimate the unknown preference values and (2) as a reliable source to determine experts' weights. A visual feedback process is developed to provide experts with graphical representations of their consensus status within the group as well as to identify the alternatives and preference values that should be reconsidered for changing in the subsequent consensus round. The feedback process also includes a recommendation mechanism to provide advice to those experts that are identified as contributing less to consensus on how to change their identified preference values. It is proved that the implementation of the visual feedback mechanism guarantees the convergence of the consensus reaching process

A graph model with minimum cost to support conflict resolution and mediation in technology transfer of new product co-development.

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Successful new product development advocate for collaboration among different institutions in which technology transfer dispute widely exists. Although several studies have discussed conflict modelling and resolution in technology transfer dispute, scant research attempted to model third-party (or mediator) mediation, let alone develop effective approaches to minimize cost in the conflict resolution process. This study uses a graph model and minimum cost to investigate the conflict resolution and mediation in technology transfer dispute of new product collaborative development. On the one hand, the conflict in technology transfer of new product collaborative development is modelled using the graph model theory, in which the stakeholders (or decision-makers), their options, the feasible states, and the preferences of decision-makers are analyzed. On the other hand, an inverse graph model with minimum cost is designed to tackle the problem of specifying which decision-makers’ preferences lead to a desired solution, thereby making it easier for a mediator or other third party to influence the course of the conflict. In the inverse graph model with minimum cost, two 0-1 mixed linear approaches are constructed to judge the Nash and General Merataionality stabilities within the graph model, and several optimization-based models that minimize mediation cost are designed for the mediator to guide the technology transfer conflict resolution process to achieve the desired solution. Finally, the proposed methodology is applied to a technology transfer dispute case study

Multicriteria Model for the Choice of Best Battery Provider

The choice of suppliers is a matter of great importance in organizations. The cost, quality and delivery time provided to customers may depend to a large extent on this decision. This paper, therefore, describes a model applicable to a real organization, using multicriteria decision techniques to choose the best supplier of batteries. In order to establish concordance and discordance thresholds the values provided by the decision-maker of the company will be compared with those obtained by the fuzzy Analytic Hierarchy Process. Both valuations of the thresholds will be applied in the ELECTRE II technique

Network Analysis, Creative System Modelling and Decision Support: The NetSyMoD Approach

This paper presents the NetSyMoD approach – where NetSyMod stands for Network Analysis – Creative System Modelling – Decision Support. It represents the outcome of several years of research at FEEM in the field of natural resources management, environmental evaluation and decision-making, within the Natural Resources Management Research Programme. NetSyMoD is a flexible and comprehensive methodological framework, which uses a suite of support tools, aimed at facilitating the involvement of stakeholders or experts in decision-making processes. The main phases envisaged for the process are: (i) the identification of relevant actors, (ii) the analysis of social networks, (iii) the creative system modelling and modelling of the reality being considered (i.e. the local socio-economic and environmental system), and (iv) the analysis of alternative options available for the management of the specific case (e.g. alternative projects, plans, strategies). The strategies for participation are necessarily context-dependent, and thus not all the NetSyMod phases may be needed in every application. Furthermore, the practical solutions for their implementation may significantly differ from one case to another, depending not only on the context, but also on the available resources (human and financial). The various applications of NetSyMoD have nonetheless in common the same approach for problem analysis and communication within a group of actors, based upon the use of creative thinking techniques, the formalisation of human-environment relationships through the DPSIR framework, and the use of multi-criteria analysis through the mDSS software.Social Network, Integrated Analysis, Participatory Modelling, Decision Support

Pairwise comparison matrix in multiple criteria decision making

The measurement scales, consistency index, inconsistency issues, missing judgment estimation and priority derivation methods have been extensively studied in the pairwise comparison matrix (PCM). Various approaches have been proposed to handle these problems, and made great contributions to the decision making. This paper reviews the literature of the main developments of the PCM. There are plenty of literature related to these issues, thus we mainly focus on the literature published in 37 peer reviewed international journals from 2010 to 2015 (searched via ISI Web of science). We attempt to analyze and classify these literatures so as to find the current hot research topics and research techniques in the PCM, and point out the future directions on the PCM. It is hoped that this paper will provide a comprehensive literature review on PCM, and act as informative summary of the main developments of the PCM for the researchers for their future research. First published online: 02 Sep 201

Preference Similarity Network Structural Equivalence Clustering based Consensus Model

Open access articleSocial network analysis (SNA) methods have been developed to analyse social structures and patterns of network relationships, although they have been least explored and/or exploited purposely for decision-making processes. In this study, we bridge a gap between SNA and consensus-based decision making by defining undirected weighted preference network from the similarity of expert preferences using the concept of ‘structural equivalence’. Structurally equivalent experts are represented using the agglomerative hierarchical clustering algorithm with complete link function, thus intra-clusters’ experts are high in density and inter-clusters’ experts are rich in sparsity. We derive cluster consensus based on internal and external cohesions, while group consensus is obtained by identifying the highest level consensus at optimal level of clustering. Thus, the clustering based approach to consensus measure contributes to present homogeneity of experts preferences as a whole. In the event of insufficient group consensus state, we construct a feedback mechanism procedure based on clustering that consists of three main phases: (1) identification of experts that contribute less to consensus; (2) identification of a leader in the network; and (3) advice generation. We make use of the centrality concept in SNA as a way of determining the most important person in a network, who is presented as a leader to provide advices in the feedback process. It is proved that the implementation of the proposed feedback mechanism increases consensus and, because of the bounded condition of consensus measure, convergence to sufficient group agreement is guaranteed. The centrality concept is also applied in the construction of a new aggregation operator, namely as cent-IOWA operator, that is used to derive the collective preference relation from which the feasible alternative of consensus solution, based on the concept of dominance, is achieved according to a majority of the central experts in the network, which is represented in this paper by the linguistic quantifier ‘most of.’ For validation purposes, an existing literature study is used to perform a comparative analysis from which conclusions are drawn and explained

Preference Uncertainty and Trust in Decision Making

A fuzzy approach for handling uncertain preferences is developed within the paradigm of the Graph Model for Conflict Resolution and new advances in trust modeling and assessment are put forward for permitting decision makers (DMs) to decide with whom to cooperate and trust in order to move from a potential resolution to a more preferred one that is not attainable on an individual basis. The applicability and the usefulness of the fuzzy preference and trust research for giving an enhanced strategic understanding about a dispute and its possible resolution are demonstrated by employing a realworld environmental conflict as well as two generic games that represent a wide range of real life encounters dealing with trust and cooperation dilemmas. The introduction of the uncertain preference representation extends the applicability of the Graph Model for Conflict Resolution to handle conflicts with missing or incomplete preference information. Assessing the presence of trust will help to compensate for the missing information and bridge the gap between a desired outcome and a feared betrayal. These advances in the areas of uncertain preferences and trust have potential applications in engineering decision making, electronic commerce, multiagent systems, international trade and many other areas where conflict is present. In order to model a conflict, it is assumed that the decision makers, options, and the preferences of the decision makers over possible states are known. However, it is often the case that the preferences are not known for certain. This could be due to lack of information, impreciseness, or misinformation intentionally supplied by a competitor. Fuzzy logic is applied to handle this type of information. In particular, it allows a decision maker to express preferences using linguistic terms rather than exact values. It also makes use of data intervals rather than crisp values which could accommodate minor shifts in values without drastically changing the overall results. The four solution concepts of Nash, general metarationality, symmetric metarationality, and sequential stability for determining stability and potential resolutions to a conflict, are extended to accommodate the new fuzzy preference representation. The newly proposed solution concepts are designed to work for two and more than two decision maker cases. Hypothetical and real life conflicts are used to demonstrate the applicability of this newly proposed procedure. Upon reaching a conflict resolution, it might be in the best interests of some of the decision makers to cooperate and form a coalition to move from the current resolution to a better one that is not achievable on an individual basis. This may require moving to an intermediate state or states which may be less preferred by some of the coalition members while being more preferred by others compared to the original or the final state. When the move is irreversible, which is the case in most real life situations, this requires the existence of a minimum level of trust to remove any fears of betrayal. The development of trust modeling and assessment techniques, allows decision makers to decide with whom to cooperate and trust. Illustrative examples are developed to show how this modeling works in practice. The new theoretical developments presented in this research enhance the applicability of the Graph Model for Conflict Resolution. The proposed trust modeling allows a reasonable way of analyzing and predicting the formation of coalitions in conflict analysis and cooperative game theory. It also opens doors for further research and developments in trust modeling in areas such as electronic commerce and multiagent systems