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Engineering systems, characterized by their high technical complexity and societal intricacies, require a strategic design approach to navigate multifaceted challenges. Understanding the circumstances that affect strategic action in these systems is crucial for managing complex real-world challenges. These challenges go beyond localized coordination issues and encompass intricate dynamics, requiring a deep understanding of the underlying structures impacting strategic behaviors, the interactions between subsystems, and the conflicting needs and expectations of diverse actors. Traditional optimization and game-theoretic approaches to guide individual and collective decisions need adaptation to capture the complexities of these design ecosystems, particularly in the face of increasing numbers of decision-makers and various interconnections between them. This paper presents a framework for studying strategic decision-making processes in collective systems. It tackles the combinatorial complexity and interdependencies inherent in large-scale systems by representing strategic decision-making processes as binary normal-form games, then dissects and reinterprets them in terms of multiple compact games characterized by two real-numbered structural factors and classifies them across four strategy dynamical domains associated with different stability conditions. We provide a mathematical characterization and visual representation of emergent strategy dynamics in games with three or more actors intended to facilitate its implementation by researchers and practitioners and elicit new perspectives on design and management for optimizing systems-of-systems performance. We conclude this paper with a discussion of the opportunities and challenges of adopting this framework within and beyond the context of engineering systems. 

Abstract Robust designs protect system utility in the presence of uncertainty in technical and operational outcomes. Systems-of-systems, which lack centralized managerial control, are vulnerable to strategic uncertainty from coordination failures between partially or completely independent system actors. This work assesses the suitability of a game-theoretic equilibrium selection criterion to measure system robustness to strategic uncertainty and investigates the effect of strategically robust designs on collaborative behavior. The work models interactions between agents in a thematic representation of a mobile computing technology transition using an evolutionary game theory framework. Strategic robustness and collaborative solutions are assessed over a range of conditions by varying agent payoffs. Models are constructed on small world, preferential attachment and random graph topologies and executed in batch simulations. Results demonstrate that systems designed to reduce the impacts of coordination failure stemming from strategic uncertainty also increase the stability of the collaborative strategy by increasing the probability of collaboration by partners; a form of robustness by environment shaping that has not been previously investigated in design literature. The work also demonstrates that strategy selection follows the risk dominance equilibrium selection criterion and that changes in robustness to coordination failure can be measured with this criterion. 

Strategy dynamics are hypothesized to be a fundamental factor that influences interactive decision-making activities among autonomous design actors. The objective of this research is to understand how strategy dynamics in characteristic engineering design problems influence cooperative behaviors and collective efficiency for pairs of design actors. Using a bi-level model of collective decision processes based on design optimization and strategy selection, we formulate a series of two-actor parameter design tasks that exhibit four strategy dynamics (harmony, coexistence, bistability, and defection), associated with low and high levels of structural fear and greed. In these tasks, actors work collectively to maximize their individual values while managing the trade-offs between aligning with or deviating from a cooperative collective strategy. Results from a human-subject design experiment indicate cognizant actors generally follow normative predictions for some strategy dynamics (harmony and coexistence) but not strictly for others (bistability and defection). Cumulative link model regression analysis shows a greed factor contributing to strategy dynamics has a stronger effect on collective efficiency and equality of individual outcomes compared to a fear factor. Results of this study establish a foundation for future work to study strategic decision-making in engineering design problems and enable new methods and processes to mitigate potential unfavorable effects of their underlying strategy dynamics through social constructs or mechanism design. 

Collaborative systems design is a human-centered activity dependent on individual decision-making processes. Personality traits have been found to influence individual behaviors and tendencies to compete or cooperate. This paper investigates the effects of Big Five and Locus of Control personality traits on negotiated outcomes of a simplified collaborative engineering design task. Secondary data includes results from short-form personality inventories and outcomes of pair design tasks. The data includes ten sessions of four participants each, where each participant completes a sequence of 12 pair tasks involving design space exploration and negotiation. Regression analysis shows a statistically-significant relationship between Big Five and Locus of Control and total individual value accumulated across the 12 design tasks. Results show the Big Five, aggregating extraversion, agreeableness, conscientiousness, neuroticism, and intellect/imagination to a single factor, negatively affects individual value and internal Locus of Control positively affects individual value. Future work should consider a dedicated experiment to refine understanding of how personality traits influence collaborative systems design and propose interventions to improve collaborative design processes. 

This work presents a conceptual model of collective decision-making processes in engineering systems design to understand the tradeoffs, risks, and dynamics between autonomous but interacting design actors. The proposed approach combines value-driven design, game theory, and simulation experimentation to study how technical and social factors of a design decision-making process facilitate or inhibit collective action. The collective systems design model considers two levels of decision-making: 1) lower-level design value exploration; and 2) upper-level design strategy selection. At the first level, the actors concurrently explore two strategy-specific value spaces with coupled design decision variables. Each collective decision is mapped to an individual scalar measure of preference (design value) that each actor seeks to maximize. At the second level, each of the actor’s design values from the two lower-level design exploration tasks is assigned to one diagonal entry of a normalform game, with off-diagonal elements calculated in function of the “sucker’s” and “temptation-to-defect” payoffs in a classical strategy game scenario. The model helps generate synthetic design problems with specific strategy dynamics between autonomous actors. Results from a preliminary multi-agent simulation study assess the validity of proposed design spaces and generate hypotheses for subsequent studies using human subjects.