An agent-based model of competition and collaboration in supply chains

This paper proposes an agent-based simulation model to study how competition and collaboration affect supply chains by looking at the problem at a market level. A theory-driven approach is applied to the modelling. The model reflects customers, manufacturers, and suppliers competing and collaborating in a supply chain strategic space. Preliminary results show that the market structure is determined primarily by bounded-rational behaviours of the supply chains and not by demand. This study is expected to provide a new perspective for understanding the implications of firms’ behaviour as supply chains to the market. It is also intended to act as a building block to study more complex and real supply chains, and encourage academics, business managers, and market regulators to invest time in studying the impact of competition and collaboration strategies in supply chains

An Agent-based Simulation of a QoS-oriented Supply Chain

With adaptive customer-orientation the efficiency of supply chain management is improved substantially. By the introduction of service quality-based decision-making into supply chain management the quality of service (QoS) within supply chains is expected to improve autonomously and continuously up- and downstream. In the paper the main characteristics of quality of service oriented supply chain management are outlined. The quality of service criterion, introduced into the adaptive supply chain model, provides market regulators and managements with the needed information and feedback to their increasingly informed decisions. By an experiment comprising several typical scenarios on our agent-based simulation model it was possible to empirically verify the expected impact of quality of service-based reasoning on generic adaptive supply chains.</p

An agent-based model of supply chain collaboration: Investigating manufacturer loyalty

Collaboration is considered to be a key driver to supply chain success. However, the ideal collaboration practice is difficult to achieve. Firms’ strategy and behaviour in supply chain collaborations are identified as the main reasons for supply chain failure. To study this problem, we use an agent-based model which represents two-stage supply chains, consisting of customers, manufacturers, and suppliers. The firms exist in a two-dimension supply chain strategic space defined by efficiency and responsiveness. In this paper, we examine the effect of manufacturer loyalty on supply chains’ performance in an innovative products market from system perspective. Measuring the supply chains fill rate and number of surviving supply chains in the market, the results indicate that manufacturer loyalty at intermediate levels does not seem to guarantee supply chain success in a market of innovative products, unless it is very high or does not exist at all

How to Make the Most Productive Intervention in a Complex Economic System

Information about supply and demand propagates through supply chains in a queueing network with people and computers as batch information processors. As each batch processor delays propagation of information whilst pursuing optimal local decisions, the effect is delay and distortion of the information that is used to commit resources to actions in the supply chain. This thesis investigates the effect of delay and imperfect information as a source of error, to establish the case for change in research focus from optimal exploitation of physical constraints to optimal exploitation of information. In the context of real world supply chains, the thesis asks "How does one make the most productive intervention in a complex economic system?" and pursues a meta-intervention which perpetually minimises the discovered error-term. Evidence from literature indicates that agent-based modelling permits real-time peer-to-peer communication and distributed optimisation. Based on the literature the research project designs and develops an agent-based model which operates in real-time without batch-processes and can perform incremental multi-objective optimisation under realistic (chronologically progressive) conditions for decision making. The agent based model is then used to investigate two real-world supply chains, as case studies, which reveals a significant improvement of profitability and order-fulfilment. The thesis concludes that agent-based modelling is a very promising direction for "making the most productive intervention" as it reduces delay to a minimum. Finally it recommends that continuous improvement of decision making methods is a role better suited for humans, rather than operational decision making where computers cope much better with the high amount of detailed information

Duration of collaboration from a market perspective: An agent-based modeling approach

Maintaining a long-term partnership with a supplier is considered an effective strategy to achieve collaboration success in supply chain management (SCM). However, individual companies find that this approach does not always improve business performance. In this paper, an agent-based model (ABM) is developed to investigate the effect of duration of collaboration on supply chains from a market perspective. The model represents two-stage supply chains of an innovative product market, involving suppliers and manufacturers. The model outputs are measured by the rate of demand fulfilment and the number of supply chains which can survive in the market. The results show that duration of collaboration has no significant impact on both demand fulfilment and survivability of supply chains. This finding contradicts the common belief held in the literature about the benefits of long-term collaboration, but it corroborates examples encountered in practice. This study provides new insights to the practice of supply chain collaboration by taking a market perspective. The results show that a longer duration of collaboration does not provide a significant improvement to the supply chain's competitiveness from a market point of view, in terms of demand fulfilment and supply chain's ability to survive over the long-term. The implications of this finding to practice are discussed in the paper

Modeling dynamic interactions in supply chains using agentbased simulations

In this work, we present preliminary results of our research on the construction of an agent-based simulation framework suitable to support the analysis of complex supply chain interactions as the one required for the performance assessment in collaborative supply chains. In particular we focus in the modeling of dynamic interactions through agent-to-agent message communication avoiding predefined supply chain network structures. For defining the internal structure of agents we explore the application of the SCOR reference model to bring a business process perspective and adopt the requirement of making explicit separation of the execution and control and decision making processes.Sociedad Argentina de Informática e Investigación Operativ

Modeling dynamic interactions in supply chains using agentbased simulations

In this work, we present preliminary results of our research on the construction of an agent-based simulation framework suitable to support the analysis of complex supply chain interactions as the one required for the performance assessment in collaborative supply chains. In particular we focus in the modeling of dynamic interactions through agent-to-agent message communication avoiding predefined supply chain network structures. For defining the internal structure of agents we explore the application of the SCOR reference model to bring a business process perspective and adopt the requirement of making explicit separation of the execution and control and decision making processes.Sociedad Argentina de Informática e Investigación Operativ

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

Agent Based Modeling and Simulation Framework for Supply Chain Risk Management

This research develops a flexible agent-based modeling and simulation (ABMS) framework for supply chain risk management with significant enhancements to standard ABMS methods and supply chain risk modeling. Our framework starts with the use of software agents to gather and process input data for use in our simulation model. For our simulation model, we extend an existing mathematical framework for discrete event simulation (DES) to ABMS and then implement the concepts of variable resolution modeling from the DES domain to ABMS and provide further guidelines for aggregation and disaggregation of supply chain models. Existing supply chain risk management research focuses on consumable item supply chains. Since the Air Force supply chain contains many reparable items, we fill this gap with our risk metrics framework designed for reparable item supply chains, which have greater complexity than consumable item supply chains. We present new metrics, along with existing metrics, in a framework for reparable item supply chain risk management and discuss aggregation and disaggregation of metrics for use with our variable resolution modeling

A Multiagent Approach for Modelling SME Mechatronic Supply Chains

International audienceThis paper presents the application of the multiagent system for modelling supply chains involving Small and Medium Enterprises (SMEs) in the mechatronic industry. This work is a combination of two research scopes. The first one deals with the identification of the different concepts able to model the particular manufacturing systems and production context in Savoie - France. The second one outlines the development process based on an agent modelling approach, which offers an easy and reusable modelling of supply chain concepts