A crucial theoretical outcome of CEO compensation research is that tying executive pay to long-term performance aligns CEO incentives with shareholders' objectives, thereby improving firm-level outcomes. This paper takes a different approach, shifting the analytical perspective from the CEO-shareholder relationship toward CEO and employee decision-making. We accomplish this by developing an Agent-Based Model built on the NK framework, extended to examine a hierarchical organisation. Employees aim to maximise their short-term performance outcomes, while we vary the CEO's decision-making horizon to capture different degrees of temporal (mis)alignment between employees and executives. Our results suggest that CEOs who align their decision-making process with the employees' short-term incentives increase firm performance substantially more than those pursuing medium- or long-term outcomes. This result is robust to variations in the task environment and the employees' turnover rate. Consequently, our results challenge the prevailing assumption of prior research regarding the benefits of tying CEO compensation to long-term performance. Instead, we argue that internal firm dynamics---the alignment between CEO and employee incentives---should be considered in the design of CEO compensation packages.

This study uses an agent-based model to investigate how workplace inequality emerges from the interaction between biased performance evaluations and homophily-driven informal networks. Simulations reveal that while informal communication improves overall organizational performance, it amplifies systemic inequality when combined with biased performance evaluations. This interaction structurally enforces a "glass ceiling" effect, trapping marginalized employees in lower capability deciles while advantaged groups dominate the top segments. Ultimately, organizations face a fundamental ethical dilemma: facilitating informal networks improves overall performance but, in the presence of biased performance evaluations, comes at the cost of equality.

While Organizational Psychology typically emphasizes job-level characteristics, a social simulation perspective suggests that integrating empirically validated micromechanisms via feedback loops can significantly reinforce process resilience at a granular level. This work introduces a prototypical process model that integrates psychological constructs with empirical data. By addressing shortcomings identified during the modelling phase, it proposes an interdisciplinary research agenda regarding optimal work process, focusing on task-level measurements, team-level constructs, and thus practical application of these findings. Beyond identifying mental health state as a key variable in operational resilience, the simulation results reveals significant potential for optimization by enhancing working conditions and reorganizing workflows to account for individual variability.

Industrial symbiosis (IS) networks can enhance circular resource efficiency, yet their governance is complicated by the dual tension of simultaneous re-source rivalry among cooperating firms and strategic ESG misrepresenta-tion. This study develops an agent-based model that couples multi-resource Leontief bottlenecks with endogenous strategy adaptation to explore how individual profit-seeking behavior influences collective network stability. Simulation sweeps suggest that monitoring and fines are complementary for suppressing greenwashing, while green premia face an “incentive–cost fron-tier”: increasing market rewards can expand true-green adoption when abatement costs are moderate, but may perversely amplify greenwashing when costs are high. Additional capacity-stress experiments show that tighter upstream constraints mainly reduce output and payoffs and push the system into a less efficient “degraded regime” rather than producing a single sharp collapse threshold. Crucially, we find that partial defection can act as a “safety valve” by relieving capacity pressure for remaining cooperators. This functions as a counter-intuitive built-in resilience mechanism that stabilizes network survival at the expense of overall circular performance, highlighting the complex trade-offs between system robustness and environmental efficiency.