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With the recent development of science and technology, research on information diffusion has become increasingly important.

To analyze the process of information diffusion, researchers have proposed a framework with graphical evolutionary game theory (EGT) according to the theory of biological evolution.

Through this method, one can study and even predict information diffusion.

This paper summarizes three existing works using graphical EGT to discuss how to obtain the static state and the dynamics of information diffusion in social network.

This study explores the emergence of discrimination based on observable characteristics. In many instances, agents presume differences arising from traits such as race or gender, even when these parameters are irrelevant to the situation at hand. This paper intends to reveal an emergent behavior and a persistent culture of discrimination caused by miscategorization in strategic interactions.

We assume that agents occasionally engage in conflicts modeled as asymmetric hawk and dove games, where boundedly rational agents may categorize their opponents based on observable traits to make effective decisions. Three categorization strategies are considered: fine-grained, regular, and coarse-grained. Subsequently, an evolutionary agent-based model is employed to examine the performance of these strategies in a dynamic environment.

The results demonstrate that fine-grained categorization provides an advantage when the cost of fighting is low, while coarse-grained categorizers exhibit more peaceful behavior, gaining an advantage when the cost of conflict is high. Our primary finding indicates the emergence of discrimination based on non-relevant traits, manifested through consistent aggressive behavior towards individuals possessing these traits.

This paper is the first to investigate the emergence of discrimination without assuming prior differences between groups. Previous studies have assumed either an initial population difference or a homophily-based approach. In contrast, we demonstrate that discrimination can emerge even in the absence of such assumptions. Discrimination between two groups may arise as long as there are agents who label these categories.

The purpose of this paper is to analyze the supply chain's resilience in crowd networks from both static and dynamic perspectives.

This paper first defines the supply chain’s resilience, then proposes a graphical and game-theoretic framework to evaluate the resilience.

In this framework, an equilibrium with high resilience will be achieved after the iterated prisoner's dilemma in the supply chain. The two-stage update mechanism contributes to higher profits, higher stability and stronger risk resistance capability. The reputation-based tit-for-tat strategy in the second stage helps to realize society cooperation.

This work pays more attention to the dynamic evolution of interactions between organizations in the supply chain. It provides an important theoretical basis for future work such as how to effectively control and guide the evolution of events in the intelligence network and how to stand sudden changes and avoid collapse.

The promotion of autonomous vehicles introduces privacy and security risks, underscoring the pressing need for responsible innovation implementation. To more effectively address the societal risks posed by autonomous vehicles, considering collaborative engagement of key stakeholders is essential. This study aims to provide insights into the governance of potential privacy and security issues in the innovation of autonomous driving technology by analyzing the micro-level decision-making processes of various stakeholders.

For this study, the authors use a nuanced approach, integrating key stakeholder theory, perceived value theory and prospect theory. The study constructs a model based on evolutionary game for the privacy and security governance mechanism of autonomous vehicles, involving enterprises, governments and consumers.

The governance of privacy and security in autonomous driving technology is influenced by key stakeholders’ decision-making behaviors and pivotal factors such as perceived value factors. The study finds that the governmental is influenced to a lesser extent by the decisions of other stakeholders, and factors such as risk preference coefficient, which contribute to perceived value, have a more significant influence than appearance factors like participation costs.

This study lacks an investigation into the risk sensitivity of various stakeholders in different scenarios.

The study delineates the roles and behaviors of key stakeholders and contributes valuable insights toward addressing pertinent risk concerns within the governance of autonomous vehicles. Through the study, the practical application of Responsible Innovation theory has been enriched, addressing the shortcomings in the analysis of micro-level processes within the framework of evolutionary game.

How can managers reduce information asymmetry in dyadic manager-external stakeholder relationships in a complex and evolving environment? Addressing this question has significant implications for firm survival, growth, and competitive advantage.

We have adopted a multiparadigm approach to theory building, known as metatriangulation. We integrate the dynamic capabilities, sensemaking, and evolutionary theory literatures to theorize how managers can relate to stakeholders in a complex and evolving environment.

We propose, via a conceptual framework and three propositions, “evolutionary sensemaking” as the managerial metacognitive dynamic capability that helps managers hone their understanding based on the evolutionary changes in the stakeholder’s interpretations of information quality preferences. The framework unfolds across three evolutionary stages: sensing preferences' variation of the stakeholder, seizing preferences, and transforming for complexity alignment and retention. The propositions focus on managing complexity in stakeholder information quality preference, employing cognitive capabilities to simplify, interpret, and align interpretations for effective information asymmetry reduction.

To develop the metacognitive dynamic capability of evolutionary sensemaking, managers need to train for and foster the underlying complex cognitive capabilities by enhancing their (1) perception and attention skills, (2) problem-solving and reasoning skills, and (3) language, communication, and social cognition skills, focusing specifically on reducing the complexity embedded in stakeholder cognition and diverse stakeholder preferences for information quality. Contrary to the current advice to “keep things simple” and provide “more” information to the stakeholders for opportunism reduction, trust-building, and superior governance, our framework suggests that managers hone their cognitive capabilities by learning to deal with the underlying complexity.

The proposed framework and propositions address research gaps in reducing information asymmetry. It enriches the dynamic capabilities literature by recognizing complexity (as opposed to opportunism) as an alternative source of information asymmetry, which needs to be addressed in this stream of research. It extends the sensemaking literature by identifying the complexity sources – i.e. stakeholder preferences for diverse information quality attributes and the associated cognitive preference interpretation processes. The article enhances evolutionary theory by delving into microprocesses related to information asymmetry reduction, which the existing literature does not thoroughly investigate.