College of Management Academic Studies

Multi-agent simulations are widely used to study complex social and ecological systems, where rich and often unexpected emergent behaviors arise from local interactions. A large body of prior work has focused on analyzing such emergent dynamics across domains. In this paper, we move beyond analyzing emergent behavior and introduce a learning-based mechanism for actively shaping it via social reward modeling. We introduce Multi-Agent Reward Prediction (MARP), a simple framework that extends preference-based reward modeling to multi-agent reinforcement learning. While the framework is designed to be applicable across multi-agent settings, the present empirical validation is limited to a single environment, and we therefore present MARP as a proof of concept within the studied domain. Rather than relying on handcrafted rewards, MARP learns a shared reward model from episode-level evaluations of collective outcomes, enabling decentralized agents to align their behavior with global social objectives. We study MARP in the Harvest Game, a canonical sequential social dilemma modeling common-pool resource management and related real-world challenges. Our results show that MARP can be tuned to produce behavior that is more closely aligned with target social metrics than standard reward-based baselines, while the learned reward model captures subtle environmental structure without explicit programming. Crucially, MARP supports multiple and composite social objectives within a single training regime. By modifying only the high-level evaluation metric, the same framework seamlessly aligns agent behavior with diverse goals, including sustainability, equality, and peace, as well as combinations of individual and group-level objectives. These findings demonstrate that emergent multi-agent behavior can be treated not only as a phenomenon to study, but as a target of principled, data-driven regulation.

Objective: This study examined therapists' retrospective experiences regarding self-disclosure in successful treatments. Previous research indicates that therapeutic alliance, empathy, and integrity are crucial for treatment success, with self-disclosure serving as an additional tool for fostering meaningful therapeutic relationships. Method: A qualitative approach was employed with nineteen clinical psychologists. Data were collected through semi-structured interviews and analyzed using thematic analysis. Results: Two contextual background themes emerged alongside two main findings. The contextual themes describe: (1) factors contributing to treatment success, including positive therapeutic alliance and patient characteristics such as high motivation; and (2) treatment outcomes, manifested in functional improvements and emotional changes. The main findings address: (1) considerations for employing self-disclosure, encompassing intuitive and emotion-based motives alongside structured therapeutic assessment, primarily aimed at normalizing and validating patient experiences; and (2) therapists' perceived impact on therapeutic dynamics, ranging from strengthened alliance and deepened emotional closeness to limited or unclear effects. Conclusions: Self-disclosure is a complex intervention that requires informed clinical judgment, a deep understanding of therapeutic dynamics, and careful adaptation to individual patient needs. The study underscores the need for balance between intuition and rational considerations. These findings contribute to a nuanced understanding of self-disclosure and its thoughtful application for improving treatment outcomes.

While hybridity has been extensively studied within bounded organizations, hybrid forms of organizing beyond formal organizational structures remain undertheorized. Hybrid organizationality, the concept introduced in this article, refers to a mode of organizing in which multiple institutional logics are sustained through coordinated action without crystallizing into a formal organization. The concept is developed through a qualitative case study of the Large-scale Agrifood Communal Trade Network (LACTN), a large-scale direct-to-consumer agricultural network linking farmers, volunteer-run distribution hubs, and consumers in Israel during successive periods of crisis. We show how LACTN loosely couples commercial and communal logics while preserving the autonomy of its constituent actors. Hybrid organizationality, we argue, becomes possible through the convergence of three conditions: the coexistence of autonomous commercial and communal actors, shared moral commitments that bridge these domains, and digitally mediated infrastructures that enable decentralized coordination at scale. The analysis further demonstrates how socio-economic sustainability may emerge in practice through large-scale, socially embedded market coordination, even in the absence of an explicit ideological sustainability agenda. By examining a network built largely upon conventional agricultural production and market logics, yet organized through volunteer mediation, communal coordination, and morally inflected exchange, the article complicates the conventional distinction between “alternative” and “conventional” food systems that has long structured scholarship on alternative agri-food networks. More broadly, the case illustrates how sustainability-oriented organizing can emerge through loosely coupled alignments among markets, communities, and digital infrastructures beyond the boundaries of formal organizations.

Andre Leo Rusavuk attempts to undermine Molinism by arguing that the doctrine of middle knowledge entails God’s subjection to circumstantial moral luck. According to Rusavuk, Molinism implies that God’s good actions and therefore the degree of His praiseworthiness depend upon the counterfactuals of creaturely freedom, which are not under His control. I critique this argument by showing that when properly defined, the praiseworthiness of God cannot depend on contingent actions or circumstances but only upon His morally perfect nature. If God’s praiseworthiness were to depend on His actions, the conclusion that God’s praiseworthiness varies from world to world would arguably follow even if Molinism were false, suggesting that the objection does not target Molinism specifically but rather a mistaken view of what divine praiseworthiness is and how it is grounded.

BACKGROUND:Understanding recovery variability in intensive psychiatric care is crucial, as variable-centered analyses often obscure individual differences. AIMS:This study aimed to identify distinct recovery trajectories among adults in intensive psychiatric care settings and assess whether treatment modality or patient characteristics could predict trajectory membership. METHODS:We used a KML3D machine-learning approach to analyze longitudinal data from 169 adults across three acute care settings: inpatient hospitalization, Soteria homes, and tech-assisted home care. Recovery was modeled across five outcome measures (symptomatology, functioning, quality of life), and a random forest model assessed predictors of trajectory membership. RESULTS:Two distinct trajectories were identified: "Persistent Challenges" (54.4%) and "Accelerated Recovery" (45.6%). The "Persistent Challenges" group had more severe baseline presentations and improved slowly, while the "Accelerated Recovery" group started with minor-to-moderate severity and improved faster. Treatment modality and other predictors showed no meaningful relationship with recovery trajectory membership (kappa = 0.17, AUC = 0.67). CONCLUSIONS:Higher multidimensional baseline severity predicted more challenging recovery courses. The lack of predictive power for treatment modality supports the viability of hospitalization alternatives and highlights the value of multidimensional assessment in intensive psychiatric care settings.