What is it about?

Many real-world systems involve competition over shared resources, such as transportation networks, energy systems, cloud computing platforms, and digital marketplaces. In these systems, organizations make strategic decisions while anticipating how users will respond, and those responses are often influenced by congestion and resource availability. Most existing models focus only on direct interactions between decision-makers and their customers. However, they often overlook two important realities. First, competing organizations may have different roles, capabilities, and decision horizons. Second, individuals who are not directly involved in a market can still influence its outcomes by contributing to and responding to congestion in shared resources. This work introduces a new game-theoretic framework that captures both of these features. The framework models heterogeneous decision-makers, strategic users, and non-follower agents who do not participate in market competition but still influence system-wide outcomes. Using electric vehicle (EV) charging networks as an example, we show how charging providers, EV drivers, and non-EV drivers interact through shared road infrastructure. By explicitly accounting for these interactions, the framework provides a more realistic representation of strategic behaviour in congestion-coupled systems and can be applied to a wide range of transportation, energy, and digital service applications.

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Why is it important?

Many important planning and investment decisions rely on models that predict how people and organizations will respond to incentives. If these models oversimplify reality by assuming that all competitors behave in the same way or by ignoring users who indirectly affect the system, the resulting predictions may be inaccurate and lead to poor decisions. This research demonstrates that agents who are not direct participants in a market can still significantly influence strategic outcomes through their impact on shared resources such as transportation networks. It also highlights the importance of accounting for differences between competing organizations, particularly when they operate under different constraints or make decisions over different timescales. By providing a more realistic representation of strategic interactions, the proposed framework can support better infrastructure planning, pricing strategies, and policy design. Although motivated by electric vehicle charging networks, the approach is broadly applicable to a wide range of congestion-coupled systems, including transportation networks, smart energy systems, cloud computing services, communication networks, and digital platforms. In all of these settings, strategic decisions made by organisations interact with the behaviour of multiple user groups through shared resources. Capturing these interactions more accurately can lead to better investment decisions, fairer competition, and more efficient use of critical infrastructure.

Perspectives

The motivation behind this work came from observing that many real-world systems are more complex than the simplified assumptions often used to model them. Decision-makers do not always have the same goals, capabilities, or time horizons, and individuals who are not directly involved in a specific market can still influence its outcomes. I was particularly interested in understanding these hidden interactions: how long-term and short-term decisions in competitive environments, and the behavior of indirectly involved agents combine to shape the final outcome. Electric vehicle (EV) charging networks are a good example of this. EV and non-EV drivers share the same roads and contribute to traffic congestion, even though non-EV drivers do not use charging stations or participate in the charging market. However, the routes chosen by non-EV drivers can affect where EV drivers decide to travel and charge, while EV drivers’ routing and charging choices can also change congestion patterns experienced by non-EV drivers. Through this research, I hope to contribute towards more realistic models that capture these two-way interactions between different decision-makers and user groups, supporting smarter decisions for future transportation, energy, and other shared-resource environments.

Niloofar Aminikalibar
Aston University

One of the challenges that has always interested me is how organisations make strategic decisions when they operate in competitive environments and must anticipate the reactions of both their competitors and their users. In many real-world systems, some decisions are long-term and difficult to reverse, such as infrastructure investments, while others are short-term and can be adjusted frequently, such as pricing or resource allocation. Understanding how these decisions interact is essential for designing efficient and sustainable systems. This work was motivated by the need to model these interactions within a unified framework. We study a setting where resource providers make decisions across multiple timescales while anticipating both competitive responses and changes in user behaviour. This naturally leads to a hierarchical three-stage game, where long-term strategic decisions influence short-term competition, and both ultimately shape how users respond. A key aspect of this work is the effort to move towards a more realistic representation of strategic systems. Rather than assuming that all competitors are identical or treating other users of shared resources as fixed background conditions, the framework allows decision-makers to differ in their capabilities and decision horizons while explicitly accounting for the impact of other agents whose behaviour influences congestion and demand. Although these details may seem subtle, they can significantly alter the incentives and outcomes predicted by the model. While electric vehicle charging networks provide a timely and practical application, the underlying challenge is much broader. Similar multi-level strategic interactions arise in transportation, energy systems, communication networks, cloud computing, and digital platforms. I hope this work contributes to a better understanding of how complex resource-sharing systems can be designed and managed when infrastructure decisions, competition, user behaviour, and shared resources are all tightly interconnected.

Farzaneh Farhadi
Aston University

Read the Original

This page is a summary of: Strategic Interactions in Multi-Level Stackelberg Games with Non-Follower Agents and Heterogeneous Leaders, International Foundation for Autonomous Agents and Multiagent Systems,
DOI: 10.65109/kxdz6376.
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