Abstract
Bisbey et al. propose that emergent states (trust, cohesion, psychological safety) create “resource passageways” enabling teams to recognize, access, and integrate resources for resilience. Their model—emergent states → resilience capacity → performance—demonstrates that high-resilience teams maintain performance despite severe adversity while low-resilience teams suffer decrements. Yet three theoretical gaps limit the framework’s explanatory power: (1) coordination processes between “open passageways” and performance outcomes remain unexamined, (2) their unexpected psychological safety finding (predicting lower performance) challenges assumptions of uniform positive effects and demands contingency theorizing, and (3) treating resilience as capacity rather than process may misattribute performance to stable properties when it results from adaptive behaviors (Bisbey et al., 2025).
Opening the Coordination Black Box
Bisbey et al.’s pathway measures psychological context (emergent states) and outcomes (performance) while treating coordination as implicit. Between having open resource passageways and maintaining performance lie unexamined coordination processes. Teams with high resilience capacity maintain performance despite severe adversity (Figure 2: B = −0.02, p = .95) while low-resilience teams suffer decrements (B = −0.92, p = .008), but the model cannot explain what actually happens during those critical moments. Integration is fundamentally a coordination challenge—combining diverse inputs into unified action requires temporal sequencing, conflict resolution, and decision-making structures (Marks et al., 2001). Psychological safety may enable members to share resources, but something else determines whether those resources get integrated effectively or create cacophony.
Not theorizing coordination creates three costs. First, the model cannot explain which team processes mediate between context and outcomes (Kozlowski & Ilgen, 2006). Second, practitioners would focus exclusively on building psychological context without developing coordination protocols enabling resource deployment (Shuffler et al., 2018). Third, the theory cannot predict when resource passageways will be sufficient versus insufficient for resilience. Their Supplemental Table A reveals effect size variation across timepoints, suggesting coordination requirements shift with team development stage—early phases emphasizing relationship-building coordination, while late phases emphasize execution coordination—yet their static model cannot capture these dynamic demands.
Rethinking Psychological Safety and Emergent State Contingencies
Bisbey et al.’s most provocative finding receives insufficient theoretical attention: teams with higher psychological safety exhibited lower performance (Table 2: B = −0.91, SE = 0.43, p = .040). The authors briefly speculate about “overconfidence” or “relaxed climates,” suggesting “psychologically safe teams may have a more ‘relaxed’ climate where it feels safe to speak up even when it is inappropriate or counterproductive...These teams might be undeterred in speaking up yet engage in poor knowledge sharing behavior” (p. 25). This brief speculation inadequately addresses a finding that contradicts their framework, which positions psychological safety as uniformly enabling resource integration.
This paradox challenges the field’s assumption that psychological safety uniformly benefits teams (Edmondson & Bransby, 2023; Frazier et al., 2017). Three mechanisms could explain this effect. First, the deliberation trap: safety encourages voice, but voice without closure creates endless deliberation, sacrificing decisiveness for inclusivity. High-performing teams balance voice with decisive action through explicit decision protocols (Waller et al., 2004). Second, the conflict avoidance paradox: teams may feel “safe” precisely because they avoid difficult conversations, creating surface harmony that predicts poor performance. Third, the capability-context mismatch: safety enables speaking up, but performance requires coordinating those inputs effectively. Teams lacking structured communication protocols would experience safety’s voice-enabling benefits without integration advantages (Hackman, 2002).
By treating psychological safety as uniformly positive in their theoretical framework while finding it predicts lower performance, Bisbey et al. create a troubling disconnect. The focal model invites “more is better” interventions that may depress performance under some conditions. Organizations implementing their recommendations would invest in building psychological safety without understanding when safety helps versus harms. Their brief speculation acknowledges the paradox but provides no theoretical account of the mechanisms, leaving their resource passageway framework unable to explain this core finding.
The cohesion null finding provides additional evidence for contingency thinking. Despite theoretical predictions, between-team cohesion did not affect resilience capacity (B = 0.11, SE = 0.07, n.s.), whereas within-team upward fluctuations did (B = 0.20, p = .005). Emergent states’ resilience benefits are conditional rather than universal. Cohesion may matter for specific adversity types (interpersonal conflict requiring social support) but not others (client feedback requiring information integration). Bisbey et al.’s undifferentiated adversity measurement—defined as “anything that threatened getting work done” (Appendix) and aggregating social loafing to client feedback into a single severity score—masks these matching effects. Different adversities should require different resource configurations if emergent states enable different utilization functions as their framework proposes (LePine et al., 2005).
From Resilience Capacity to Resilience Processes
Bisbey et al. conceptualize resilience as a capacity—”a shared sense that the team can overcome its challenges” (p. 26)—adapting the Brief Resilience Scale (Smith et al., 2008) with items like “This team tends to bounce back quickly after hard times.” While methodologically sound (α = 0.92, ICC(2) = 0.89), the items resemble collective efficacy and potency constructs (Klein & Kozlowski, 2000). Compare to Guzzo et al.’s (1993) potency: “the collective belief...that it can be effective.” This overlap complicates interpreting their resilience capacity × adversity interaction (B = 0.67, p = .004). Does this represent recovery capability or general confidence?
Bisbey et al. acknowledge that “For teams that have only experienced low adversity, measurements...may be more reflective of collective efficacy” (p. 20). Their measure may capture different constructs depending on adversity history. More fundamentally, treating resilience as capacity (what teams have) rather than process (what teams do) may misattribute performance to stable properties when it results from adaptive behaviors (Fisher et al., 2023). This creates three costs: biased mechanism attribution to enduring properties versus specific responses like task redistribution; overly broad generalizations that cannot explain variation across time or adversity types (LePine et al., 2005); and mis-targeted interventions building enduring properties rather than behavioral capabilities (Shuffler et al., 2018).
If resilience is behavioral, capacity measures should assess behavioral repertoires rather than confidence (Hartwig et al., 2020). Open passageways may be necessary but insufficient—teams also need processual capabilities for deploying resources when adversity strikes. Within-team effects hint at this: higher emergent states than usual increased resilience capacity (cohesion B = 0.20, trust B = 0.26, safety B = 0.50, all p < .01), perhaps triggering compensatory coordination behaviors. This perspective suggests resilience operates differently across development stages: early phases require explicit coordination while late phases rely on implicit coordination via shared mental models (Mathieu et al., 2000).
Conclusion and Future Directions
Bisbey et al. demonstrate that resilience capacity protects against adversity effects. However, their resource passageway framework requires three extensions: explaining how teams coordinate resources under pressure, theorizing when emergent states help versus harm, and examining resilience as process rather than only capacity. These reconceptualizations sharpen their contributions while opening productive research directions—examining coordination behaviors mediating emergent states and performance, investigating psychological safety’s boundary conditions across adversity types, and developing behavioral resilience measures. Their rigorous design establishes that resilience matters most under severe conditions, their unexpected psychological safety finding reveals contingencies that “more is better” models miss, and within-team fluctuations hint at resilience’s dynamic nature. The field needs both what Bisbey et al. provide—rigorous empirical work on real teams facing actual adversity—and what their study provokes: theoretical precision about coordination mechanisms, contextual contingencies, and processual dynamics explaining when and how teams achieve resilient performance.
