Foreseeing the dynamics of strategy : an anticipatory systems perspective

The paper explores firms as complex anticipatory systems which construct dynamic strategic configurations based on anticipation of their future possible states within the competitive environment. We argue that firm’s performance depends on (a) its strategy making process based on anticipation, and (b) its managerial capabilities which effectuate the anticipatory process in the following four stages: search across anticipated “what-if” resource configurations, the articulation and conversion of their meaning, and the finding and evolution of strategic patterns and courses of action for environmental fit. We performed an in-depth exploratory study with a group of senior managers in a pharmaceutical firm to uncover diverse anticipatory capabilities. The study was based on the development and re-assessment of a product market strategy for a new drug launch without and with the use of a simulation-based learning environment. The results show the existence of heterogeneous anticipatory process, which we name search-articulate-find-evolve of alternative resource configuration sets, determining the managerial dynamic capabilities related particularly to managerial cognition and decision making. We propose anticipation enhanced by modelling and simulation can improve managers’ mental processes and help them to overcome cognitive limitations when dealing with real-world complexities

Enhancing the theoretical framework behind the integration of system dynamics and agent based modelling for use in pharmaceutical systems

A novel view for an integrative SD and AB modelling framework for use in pharmaceutical systems is proposed. This is centred around the key concepts of resources, agents and information imperfection and is supported by the theoretical perspectives of resource-dependence theory and resource based view, behavioural decision theory, information economics theory and anticipatory systems theory. Each of the above theoretical perspectives provides different knowledge and explanations of socio-economic phenomena and integrating them provides a more holistic view for critically exploring and interpreting market resource and agent interrelated behaviour. Conceptualizing the pharmaceutical market as an anticipatory adaptive socio-economic system emerging out of agents heuristic rules and forward-looking behaviour, competing for limited resources within an informationally imperfect market environment, would further complement the general systems and complex adaptive systems theoretical frameworks underpinning the practical integration of SD and AB modelling approaches. The proposed theoretical framework will be illustrated in the context of the External Reference Pricing regulation on the pharmaceutical market in EU. The analysis focuses on the relevant market agents and market resources involved, the main information imperfections and related phenomena that could lead to market imperfections and market failure from the public healthcare perspective of providing equitable and timely access to affordable medicinal products The resource/agent/information integrated framework proposed here contributes to the ongoing efforts of the modelling and simulation community to develop an enhanced epistemological paradigm in support of the integration of SD and AB methodological approaches. Another practical contribution is to the call of the European Council for a systemic evaluation of the pharmaceutical regulation in EU and associated pharmaceutical market system effects

Managing complex adaptive systems : a resource/agent modelling perspective

Complex adaptive systems are systems where those managing the system, the agents, interact with other competing agents and key resources available to the system. The behaviour of the agents and the resources are constantly changing over time thus resulting in complex systems of evolving problem configurations. Managing such a system can be very challenging, particularly when attempting to manage rather than simplify complexity. One particular problem is the need to take a comprehensive perspective of the complex system in order to manage it effectively. Resource structure and agent behaviour are interdependent and both interconnected components need to be considered in order to support optimal decision making. Due to the lack of an appropriate technique in the literature to achieve a comprehensive qualitative appreciation of resource/agent complex adaptive system behaviour, we have developed a novel qualitative modelling tool, a Resource/Agent Map, that aims to map and analyse both resources and agents interactive behaviour. We show how this modelling tool can help achieve a holistic appreciation of the resource/agent perspectives and generate scenario alternatives to inform policy decision making in respect to system management and regulation. A pharmaceutical example is used to demonstrate the modelling tool

Conceptual System Dynamics and Agent-Based Modelling Simulation of Interorganisational Fairness in Food Value Chains: Research Agenda and Case Studies

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/)System dynamics and agent-based simulation modelling approaches have a potential as tools to evaluate the impact of policy related decision making in food value chains. The context is that a food value chain involves flows of multiple products, financial flows and decision making among the food value chain players. Each decision may be viewed from the level of independent actors, each with their own motivations and agenda, but responding to externalities and to the behaviours of other actors. The focus is to show how simulation modelling can be applied to problems such as fairness and power asymmetries in European food value chains by evaluating the outcome of interventions in terms of relevant operational indicators of interorganisational fairness (e.g., profit distribution, market power, bargaining power). The main concepts of system dynamics and agent-based modelling are introduced and the applicability of a hybrid of these methods to food value chains is justified. This approach is outlined as a research agenda, and it is demonstrated how cognitive maps can help in the initial conceptual model building when implemented for specific food value chains studied in the EU Horizon 2020 VALUMICS project. The French wheat to bread chain has many characteristics of food value chains in general and is applied as an example to formulate a model that can be extended to capture the functioning of European FVCs. This work is to be further progressed in a subsequent stream of research for the other food value chain case studies with different governance modes and market organisation, in particular, farmed salmon to fillet, dairy cows to milk and raw tomato to processed tomato.Peer reviewedFinal Published versio

Evaluating pharmaceutical external reference pricing regulation in EU : a hybrid resource / agent modelling and simulation approach

The aim of this research is to evaluate the impact of the pharmaceutical pricing regulation in the EU in relation to drugs access, affordability and availability. It aligns with the call of the Council of the European Union (2016) and corresponds also to the call regarding the need for use of dynamic simulation methods for the analysis of healthcare system interventions (Roberts 2015). The methodological approach of my research is related to application of a hybrid qualitative and quantitative system dynamics and agent-based simulation modelling. This approach is employed for the evaluation of the External Reference Pricing (ERP) regulation effect on equitable access, availability, and affordability of drugs on the cardiovascular pharmaceutical market in EU. The research is nested in a rich theoretical paradigm, capable of supporting the hybrid simulation modelling approach. This paradigm integrates the Resource-dependence Theory and Resource-based Theory, Behavioural Decision Theory, and Anticipatory Systems Theory. It fills practical, methodological and theoretical gaps in relation to the research topic. My PhD’s main contribution is connected to both methodological and practical aspects of developing a novel problem structuring method, Resource Agent Maps (RAM), and using that method for qualitative analysis and as a conceptual validation and hybridization procedure for designing a hybrid simulation evaluation of the ERP regulation effects. The ERP analysis demonstrates that applying a RAM approach can enable a comprehensive evaluation (taking account of both resource-feedback and agent-based perspectives) of the ERP effect on drug equitable access, affordability and availability. In addition, the analysis extends previous research on the ERP, helping to overcome previous limitations (Toumi et al., 2014, Vogler et al. 2015). Main insights from the ERP regulation evaluation are that the ERP alone has no effect on drug access delay (access criterion). On the contrary, it provides an attractive route for propagation of the highest price at the first country of launch to other referencing countries. Other factors like mandatory official price discounts can have effects on delays in local markets, which could interfere with the ERP tool set of rules. Also, ERP alone has no price decrease (affordability criterion) effect for on patent drugs or any drug in a monopolistic market. Price decrease is an effect mainly from local price competition intensity, which the ERP regulation transfers to other reference basket countries, depending on reference price calculation formula and reference country basket composition. ERP can have effect on drug market exits (availability criterion) for off patent innovative and generic medicines, depending on pharmaceutical firms’ pricing strategies and on the indirect effects of price competition, local prescribing regulation and parallel trade.The aim of this research is to evaluate the impact of the pharmaceutical pricing regulation in the EU in relation to drugs access, affordability and availability. It aligns with the call of the Council of the European Union (2016) and corresponds also to the call regarding the need for use of dynamic simulation methods for the analysis of healthcare system interventions (Roberts 2015). The methodological approach of my research is related to application of a hybrid qualitative and quantitative system dynamics and agent-based simulation modelling. This approach is employed for the evaluation of the External Reference Pricing (ERP) regulation effect on equitable access, availability, and affordability of drugs on the cardiovascular pharmaceutical market in EU. The research is nested in a rich theoretical paradigm, capable of supporting the hybrid simulation modelling approach. This paradigm integrates the Resource-dependence Theory and Resource-based Theory, Behavioural Decision Theory, and Anticipatory Systems Theory. It fills practical, methodological and theoretical gaps in relation to the research topic. My PhD’s main contribution is connected to both methodological and practical aspects of developing a novel problem structuring method, Resource Agent Maps (RAM), and using that method for qualitative analysis and as a conceptual validation and hybridization procedure for designing a hybrid simulation evaluation of the ERP regulation effects. The ERP analysis demonstrates that applying a RAM approach can enable a comprehensive evaluation (taking account of both resource-feedback and agent-based perspectives) of the ERP effect on drug equitable access, affordability and availability. In addition, the analysis extends previous research on the ERP, helping to overcome previous limitations (Toumi et al., 2014, Vogler et al. 2015). Main insights from the ERP regulation evaluation are that the ERP alone has no effect on drug access delay (access criterion). On the contrary, it provides an attractive route for propagation of the highest price at the first country of launch to other referencing countries. Other factors like mandatory official price discounts can have effects on delays in local markets, which could interfere with the ERP tool set of rules. Also, ERP alone has no price decrease (affordability criterion) effect for on patent drugs or any drug in a monopolistic market. Price decrease is an effect mainly from local price competition intensity, which the ERP regulation transfers to other reference basket countries, depending on reference price calculation formula and reference country basket composition. ERP can have effect on drug market exits (availability criterion) for off patent innovative and generic medicines, depending on pharmaceutical firms’ pricing strategies and on the indirect effects of price competition, local prescribing regulation and parallel trade

Managing complex adaptive systems : a resource/agent qualitative modelling perspective

Complex adaptive systems are systems where those managing the system, the agents, interact with other competing agents and key resources available to the system. The behaviour of the agents and the resources are constantly changing over time thus resulting in complex systems of evolving problem configurations. Managing such a system can be very challenging, particularly when attempting to manage rather than simplify complexity. One particular problem is the need to take a comprehensive perspective of the complex system in order to manage it effectively. Resource structure and agent behaviour are interdependent and both interconnected components need to be considered in order to support optimal decision making. Due to the lack of an appropriate technique in the literature to achieve a comprehensive qualitative appreciation of resource/agent complex adaptive system behaviour, this paper describes the development of a novel qualitative modelling tool, a Resource/Agent Map, that aims to map and analyse both resources and agents interactive behaviour. We show how this modelling tool can help achieve a holistic appreciation of the resource/agent perspectives and generate scenario alternatives to inform policy decision making in respect to system management and regulation. A pharmaceutical example is used to demonstrate the modelling tool

Conceptual System Dynamics and Agent-Based Modelling Simulation of Interorganisational Fairness in Food Value Chains: Research Agenda and Case Studies

System dynamics and agent-based simulation modelling approaches have a potential as tools to evaluate the impact of policy related decision making in food value chains. The context is that a food value chain involves flows of multiple products, financial flows and decision making among the food value chain players. Each decision may be viewed from the level of independent actors, each with their own motivations and agenda, but responding to externalities and to the behaviours of other actors. The focus is to show how simulation modelling can be applied to problems such as fairness and power asymmetries in European food value chains by evaluating the outcome of interventions in terms of relevant operational indicators of interorganisational fairness (e.g., profit distribution, market power, bargaining power). The main concepts of system dynamics and agent-based modelling are introduced and the applicability of a hybrid of these methods to food value chains is justified. This approach is outlined as a research agenda, and it is demonstrated how cognitive maps can help in the initial conceptual model building when implemented for specific food value chains studied in the EU Horizon 2020 VALUMICS project. The French wheat to bread chain has many characteristics of food value chains in general and is applied as an example to formulate a model that can be extended to capture the functioning of European FVCs. This work is to be further progressed in a subsequent stream of research for the other food value chain case studies with different governance modes and market organisation, in particular, farmed salmon to fillet, dairy cows to milk and raw tomato to processed tomato.European Commission Horizon 202

Combining SD & ABM : frameworks, benefits, challenges, and future research directions

System Dynamics (SD) and Agent-Based modelling (ABM) are two commonly used simulation methods with different characteristics and benefits. When tackling a complex problem, the use of one of these methods may be insufficient and, instead, a combination of the two methods in a hybrid simulation may be required. To support modellers in the development of SD-ABM hybrid simulations, this chapter provides a comprehensive overview of methodological and practical considerations. Frameworks are presented to facilitate the implementation of hybrid SDABM models including the development of a conceptual SD-ABM hybrid model. The chapter then presents key benefits associated with SD-ABM hybrid modelling, which include being able to model an appropriate level of complexity, facilitate communication of the model design, enhance confidence building and reduce compute intensity. Two case studies are used to illustrate these benefits. Although there are many benefits, there are also key challenges associated with the development of a SD-ABM hybrid model and these are discussed. The chapter concludes with a discussion of opportunities and areas for future research

Combining SD & ABM: Frameworks, benefits, challenges, and future re-search directions

System Dynamics (SD) and Agent-Based modelling (ABM) are two commonly used simulation methods with different characteristics and benefits. When tackling a complex problem, the use of one of these methods may be insuffi-cient and, instead, a combination of the two methods in a hybrid simulation may be required. To support modellers in the development of SD-ABM hybrid simulations, this chapter provides a comprehensive overview of methodological and practical considerations. Frameworks are presented to facilitate the implementation of hybrid SD-ABM models including the devel-opment of a conceptual SD-ABM hybrid model. The chapter then presents key benefits associated with SD-ABM hybrid modelling, which include being able to model an appropriate level of complexity, facilitate communication of the model design, enhance confidence building and reduce compute intensity. Two case studies are used to illustrate these benefits. Although there are many benefits, there are also key challenges associated with the development of a SD-ABM hybrid model and these are discussed. The chapter concludes with a discussion of opportunities and areas for future research