Multi-Stakeholder Consensus Decision-Making Framework Based on Trust and Risk

Indiana University-Purdue University Indianapolis (IUPUI)This thesis combines human and machine intelligence for consensus decision-making, and it contains four interrelated research areas. Before presenting the four research areas, this thesis presents a literature review on decision-making using two criteria: trust and risk. The analysis involves studying the individual and the multi-stakeholder decision-making. Also, it explores the relationship between trust and risk to provide insight on how to apply them when making any decision. This thesis presents a grouping procedure of the existing trust-based multi-stakeholder decision-making schemes by considering the group decision-making process and models. In the first research area, this thesis presents the foundation of building multi-stakeholder consensus decision-making (MSCDM). This thesis describes trust-based multi-stakeholder decision-making for water allocation to help the participants select a solution that comes from the best model. Several criteria are involved when deciding on a solution such as trust, damage, and benefit. This thesis considers Jain's fairness index as an indicator of reaching balance or equality for the stakeholder's needs. The preferred scenario is when having a high trust, low damages and high benefits. The worst scenario involves having low trust, high damage, and low benefit. The model is dynamic by adapting to the changes over time. The decision to select is the solution that is fair for almost everyone. In the second research area, this thesis presents a MSCDM, which is a generic framework that coordinates the decision-making rounds among stakeholders based on their influence toward each other, as represented by the trust relationship among them. This thesis describes the MSCDM framework that helps to find a decision the stakeholders can agree upon. Reaching a consensus decision might require several rounds where stakeholders negotiate by rating each other. This thesis presents the results of implementing MSCDM and evaluates the effect of trust on the consensus achievement and the reduction in the number of rounds needed to reach the final decision. This thesis presents Rating Convergence in the implemented MSCDM framework, and such convergence is a result of changes in the stakeholders' rating behavior in each round. This thesis evaluates the effect of trust on the rating changes by measuring the distance of the choices made by the stakeholders. Trust is useful in decreasing the distances. In the third research area, this thesis presents Rating Convergence in the implemented MSCDM framework, and such convergence is a result of changes in stakeholders' rating behavior in each round. This thesis evaluates the effect of trust on the rating changes by measuring the perturbation in the rating matrix. Trust is useful in increasing the rating matrix perturbation. Such perturbation helps to decrease the number of rounds. Therefore, trust helps to increase the speed of agreeing upon the same decision through the influence. In the fourth research area, this thesis presents Rating Aggregation operators in the implemented MSCDM framework. This thesis addresses the need for aggregating the stakeholders' ratings while they negotiate on the round of decisions to compute the consensus achievement. This thesis presents four aggregation operators: weighted sum (WS), weighted product (WP), weighted product similarity measure (WPSM), and weighted exponent similarity measure (WESM). This thesis studies the performance of those aggregation operators in terms of consensus achievement and the number of rounds needed. The consensus threshold controls the performance of these operators. The contribution of this thesis lays the foundation for developing a framework for MSCDM that facilitates reaching the consensus decision by accounting for the stakeholders' influences toward one another. Trust represents the influence

Мультиагентний підхід до аналізу ефективності ланцюга поставок

У статті розглядається проблема оцінювання ефективності ланцюга поставок. Запропоновано критерій ефективності, заснований на сумарному дефіциті в розподільчій системі. Оцінювання зміни значення критерію виконано за допомогою метарегресійної моделі, яка побудована за статистикою, що була отримана за результатами прогонів авторської мультиагентної моделі «виробник – розподільчий центр – кінцевий споживач».В статье рассматривается проблема оценивания эффективности цепочки поставок. Предложен критерий эффективности, основанный на суммарном дефиците в распределительной системе. Оценка изменения значения критерия проведена с помощью метарегрессионной модели, которая построена по статистике, полученной по результатам прогонов авторской мультиагентной модели вида «производитель – распределительный центр – конечный потребитель».There is discussed the problem of supply chain efficiency in the article. The criteria of efficiency based on a total deficit in a distribution system is off ered. Estimation of criterion variation is done by metaregression model that was constructed according to data generated by the оriginal multi - agent model «manufacturer – distribution center – сonsumer

Adaptive tension, self-organization and emergence : A complex system perspective of supply chain disruptions

The purpose of this thesis was to explore how microstate human interactions produce macro level self-organization and emergence in a supply disruption scenario, as well as discover factors and typical human behaviour that bring about disruptions. This study argues that the complex adaptive system’s view of complexity is most suited scholarly foundation for this research enquiry. Drawing on the dissipative structure based explanation of emergence and self-organization in a complex adaptive system, this thesis further argues that an energy gradient between the ongoing and designed system conditions, known as adaptive tension, causes supply chains to self-organize and emerge. This study adopts a critical realist ontology operationalized by a qualitative case research and grounded theory based analysis. The data was collected using repertory grid interviews of 22 supply chain executives from 21 firms. In all 167 cases of supply disruptions were investigated. Findings illustrate that agent behaviours like loss of trust, over ambitious pursuit, use of power and privilege, conspiring against best practices and heedless performance were contributing to disruption. Impacted by these behaviours, supply chains demonstrated impaired disruption management capabilities and increased disruption probability. It was also discovered that some of these system patterns and microstate agent behaviours pushed the supply chains to a zone of emergent complexity where these networks self-organized and emerged into new structures or embraced changes in prevailing processes or goals. A conceptual model was developed to explain the transition from micro agent behaviour to system level self-organization and emergence. The model described alternate pathways of a supply chain under adaptive tension. The research makes three primary research contributions. Firstly, based upon the theoretical model, this research presents a conceptualization of supply chain emergence and self-organization from dissipative structures and adaptive tension based view of complexity. Secondly, it formally introduces and validates the role of behavioural and cognitive element of human actions in a supply chain scenario. Lastly, it affirms the complex adaptive system based conceptualization of supply chain networks. These contributions succeed in providing organizations with an explanation for observed deviations in their operations performance using a behavioural aspect of human agents

Resilience in projects: definition, dimensions, antecedents and consequences

Disruptions can cause projects to fail. Within the project management literature, approaches to managing disruptions consist of uncertainty, risk, opportunity, change, and crisis management. These approaches focus on developing strategies to manage perceived threats and also work towards predicting risk, therefore, reducing vulnerability. This vulnerability-reduction only focus is limiting because it takes the focus away from the development of a general capacity for readiness and for responding to uncertain situations. A resiliency approach enables a simultaneous focus on vulnerability reduction, readiness and response and thus ensures recovery. Given the context and discipline specific nature of the resilience concept, and the little or no attention in projects, this thesis conceptualises resilience in projects. This conceptualisation is to enable the identification of factors to consider and indicators to ensure overall project recovery, through the identification of dimensions and antecedents of resilience respectively. The aim of this study therefore, is to develop a framework to conceptualise resilience in projects. To achieve this aim, three case studies, namely; building, civil engineering and engineering construction projects were investigated. Within each case study, the critical incident technique was employed to identify disruptions and their management through direct observations of human activities, narration of critical incidents and review of documents on disruption. Following this, a comparative analysis and synthesis of the case studies was carried out and findings revealed definition, dimensions, antecedents and consequences of resilience in projects. Specifically, resilience in projects is defined as; the capability of a project to respond to, prepare for and reduce the impact of disruption caused by the drifting environment and project complexity. The dimensions of resilience are; proactivity, coping ability, flexibility and persistence. Proactivity can be defined as an anticipatory capability that the project takes to influence their endeavours whilst coping ability can be defined as the capability to manage and deal with stress caused by disruptions within the projects. Furthermore, flexibility can be defined as the capability of a project to manage disruption by allowing change but ultimately making sure that the aim is maintained and persistence is the capability to continue despite difficult situations. Several antecedents of these dimensions of resilience are identified. For proactivity these include contract, training, monitoring, contingency and experience. For coping ability these include the contract, training, contingency and experience. For flexibility these include open-mindedness, planning, continual monitoring and continual identification of ideas and for persistence these include continual monitoring, planning and negotiation. Also, the consequence of resilience in projects is recovery through response, readiness and vulnerability reduction. This conceptualisation of resilience is then synthesised into a validated framework for resilience in projects. Theoretically, this research provides definition, dimensions, antecedents and consequence for resilience in projects and a theoretical starting point for the concept of resilience in projects. The significance of this research to practice is the identification and development of a more holistic perspective of managing disruptions in projects through the identified dimensions, antecedents and consequences. These dimensions, antecedents and consequences provide clarity for the roles of project managers and team members in managing disruptions and thus, expand the eleventh knowledge area; project risk management, of the Project Management Book of Knowledge (PMBOK). In addition, the dimensions, antecedents and consequences of resilience in projects contribute to the curriculum development in project management and thus, provide factors and indicators that project managers require in managing disruptions

Cyclic blackout mitigation and prevention

Severe and long-lasting power shortages plague many countries, resulting in cyclic blackouts affecting the life of millions of people. This research focuses on the design, development and evolution of a computer-controlled system for chronic cyclic blackouts mitigation based on the use of an agent-based distributed power management system integrating Supply Demand Matching (SDM) with the dynamic management of Heat, Ventilation, and Air Conditioning (HVAC) appliances. The principle is supported through interlocking different types of HVAC appliances within an adaptive cluster, the composition of which is dynamically updated according to the level of power secured from aggregating the surplus power from underutilised standby generation which is assumed to be changing throughout the day. The surplus power aggregation provides a dynamically changing flow, used to power a basic set of appliances and one HVAC per household. The proposed solution has two modes, cyclic blackout mitigation and prevention modes, selecting either one depends on the size of the power shortage. If the power shortage is severe, the system works in its cyclic blackout mitigation mode during the power OFF periods of a cyclic blackout. The system changes the composition of the HVAC cluster so that its demand added to the demand of basic household appliances matches the amount of secured supply. The system provides the best possible air conditioning/cooling service and distributes the usage right and duration of each type of HVAC appliance either equally among all houses or according to house temperature. However if the power shortage is limited and centred around the peak, the system works in its prevention mode, in such case, the system trades a minimum number of operational air conditioners (ACs) with air cooling counterparts in so doing reducing the overall demand. The solution assumes the use of a new breed of smart meters, suggested in this research, capable of dynamically rationing power provided to each household through a centrally specified power allocation for each family. This smart meter dynamically monitors each customer’s demand and ensures their allocation is never exceeded. The system implementation is evaluated utilising input power usage patterns collected through a field survey conducted in a residential quarter in Basra City, Iraq. The results of the mapping formed the foundation for a residential demand generator integrated in a custom platform (DDSM-IDEA) built as the development environment dedicated for implementing and evaluating the power management strategies. Simulation results show that the proposed solution provides an equitably distributed, comfortable quality of life level during cyclic blackout periods.Severe and long-lasting power shortages plague many countries, resulting in cyclic blackouts affecting the life of millions of people. This research focuses on the design, development and evolution of a computer-controlled system for chronic cyclic blackouts mitigation based on the use of an agent-based distributed power management system integrating Supply Demand Matching (SDM) with the dynamic management of Heat, Ventilation, and Air Conditioning (HVAC) appliances. The principle is supported through interlocking different types of HVAC appliances within an adaptive cluster, the composition of which is dynamically updated according to the level of power secured from aggregating the surplus power from underutilised standby generation which is assumed to be changing throughout the day. The surplus power aggregation provides a dynamically changing flow, used to power a basic set of appliances and one HVAC per household. The proposed solution has two modes, cyclic blackout mitigation and prevention modes, selecting either one depends on the size of the power shortage. If the power shortage is severe, the system works in its cyclic blackout mitigation mode during the power OFF periods of a cyclic blackout. The system changes the composition of the HVAC cluster so that its demand added to the demand of basic household appliances matches the amount of secured supply. The system provides the best possible air conditioning/cooling service and distributes the usage right and duration of each type of HVAC appliance either equally among all houses or according to house temperature. However if the power shortage is limited and centred around the peak, the system works in its prevention mode, in such case, the system trades a minimum number of operational air conditioners (ACs) with air cooling counterparts in so doing reducing the overall demand. The solution assumes the use of a new breed of smart meters, suggested in this research, capable of dynamically rationing power provided to each household through a centrally specified power allocation for each family. This smart meter dynamically monitors each customer’s demand and ensures their allocation is never exceeded. The system implementation is evaluated utilising input power usage patterns collected through a field survey conducted in a residential quarter in Basra City, Iraq. The results of the mapping formed the foundation for a residential demand generator integrated in a custom platform (DDSM-IDEA) built as the development environment dedicated for implementing and evaluating the power management strategies. Simulation results show that the proposed solution provides an equitably distributed, comfortable quality of life level during cyclic blackout periods

Sustainability of systems interoperability in dynamic business networks

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de ComputadoresCollaborative networked environments emerged with the spread of the internet, contributing to overcome past communication barriers, and identifying interoperability as an essential property to support businesses development. When achieved seamlessly, efficiency is increased in the entire product life cycle support. However, due to the different sources of knowledge, models and semantics, enterprise organisations are experiencing difficulties exchanging critical information, even when they operate in the same business environments. To solve this issue, most of them try to attain interoperability by establishing peer-to-peer mappings with different business partners, or use neutral data and product standards as the core for information sharing, in optimized networks. In current industrial practice, the model mappings that regulate enterprise communications are only defined once, and most of them are hardcoded in the information systems. This solution has been effective and sufficient for static environments, where enterprise and product models are valid for decades. However, more and more enterprise systems are becoming dynamic, adapting and looking forward to meet further requirements; a trend that is causing new interoperability disturbances and efficiency reduction on existing partnerships. Enterprise Interoperability (EI) is a well established area of applied research, studying these problems, and proposing novel approaches and solutions. This PhD work contributes to that research considering enterprises as complex and adaptive systems, swayed to factors that are making interoperability difficult to sustain over time. The analysis of complexity as a neighbouring scientific domain, in which features of interoperability can be identified and evaluated as a benchmark for developing a new foundation of EI, is here proposed. This approach envisages at drawing concepts from complexity science to analyse dynamic enterprise networks and proposes a framework for sustaining systems interoperability, enabling different organisations to evolve at their own pace, answering the upcoming requirements but minimizing the negative impact these changes can have on their business environment

A systematic methodology to analyse the performance and design configurations of business interoperability in cooperative industrial networks

This thesis proposes a methodology for modelling business interoperability in a context of cooperative industrial networks. The purpose is to develop a methodology that enables the design of cooperative industrial network platforms that are able to deliver business interoperability and the analysis of its impact on the performance of these platforms. To achieve the proposed objective, two modelling tools have been employed: the Axiomatic Design Theory for the design of interoperable platforms; and Agent-Based Simulation for the analysis of the impact of business interoperability. The sequence of the application of the two modelling tools depends on the scenario under analysis, i.e. whether the cooperative industrial network platform exists or not. If the cooperative industrial network platform does not exist, the methodology suggests first the application of the Axiomatic Design Theory to design different configurations of interoperable cooperative industrial network platforms, and then the use of Agent-Based Simulation to analyse or predict the business interoperability and operational performance of the designed configurations. Otherwise, one should start by analysing the performance of the existing platform and based on the achieved results, decide whether it is necessary to redesign it or not. If the redesign is needed, simulation is once again used to predict the performance of the redesigned platform. To explain how those two modelling tools can be applied in practice, a theoretical modelling framework, a theoretical Axiomatic Design model and a theoretical Agent-Based Simulation model are proposed. To demonstrate the applicability of the proposed methodology and/or to validate the proposed theoretical models, a case study regarding a Portuguese Reverse Logistics cooperative network (Valorpneu network) and a case study regarding a Portuguese construction project (Dam Baixo Sabor network) are presented. The findings of the application of the proposed methodology to these two case studies suggest that indeed the Axiomatic Design Theory can effectively contribute in the design of interoperable cooperative industrial network platforms and that Agent-Based Simulation provides an effective set of tools for analysing the impact of business interoperability on the performance of those platforms. However, these conclusions cannot be generalised as only two case studies have been carried out. In terms of relevance to theory, this is the first time that the network effect is addressed in the analysis of the impact of business interoperability on the performance of networked companies and also the first time that a holistic approach is proposed to design interoperable cooperative industrial network platforms. Regarding the practical implications, the proposed methodology is intended to provide industrial managers a management tool that can guide them easily, and in practical and systematic way, in the design of configurations of interoperable cooperative industrial network platforms and/or in the analysis of the impact of business interoperability on the performance of their companies and the networks where their companies operate