ABSTRACT This study evaluates five accounting‐based bankruptcy prediction models—Altman Z′′ (1998), Pascale (1988), Springate (1978), Zmijewski (1984) and CA‐Score (Legault, 1987)—in Ecuador's corporate sector during the postpandemic period 2021–2024, using an Ecuadorian administrative firm‐year panel ( n = 324,252; 110,404 firms). The design departs from prior validation work in the following five ways: continuous winsorised scores replace dichotomised flags, with thresholds re‐estimated via Youden's J per model and size stratum; performance is reported through prevalence‐adjusted metrics (Matthews correlation, F1, Bayesian PPV and decision‐curve net benefit) better suited to the sample's 1:42 class imbalance; results are tested across three definitions of legal failure; a lag‐aware robustness check accounts for the 2‐ to‐3‐year administrative dissolution lag under Article 20 of the Companies Law; and an XGBoost benchmark (70/30 stratified split) bounds the out‐of‐sample gap. Our results suggest that model validity is size‐conditional: Altman rises monotonically (AUC 0.553 → 0.657; z = +3.84), Springate declines (0.623 → 0.489; z = −5.14) and Pascale falls below random among large firms (0.464). Continuous‐score evaluation reorders the field: Springate (0.624) > Pascale (0.594) > CA‐Score (0.588) > Altman (0.562) > Zmijewski (0.553). Even at recalibrated thresholds, Bayesian PPV stays below 5.5%, reframing these flags as portfolio‐level tools rather than firm‐level verdicts. The Institutional Friction Index reveals a 7 × −73 × wedge between predicted distress and legal liquidation, decomposed into real‐recovery (~10%), administrative‐lag (~50%) and panel‐composition (~40%) components. XGBoost reaches out‐of‐sample AUC 0.796 (vs. 0.694 for the five scores), showing traditional models leave roughly one‐third of attainable performance untapped. The findings support a segmented, decision‐calibrated, lag‐aware early‐warning regime over single‐threshold gatekeeping.
ABSTRACT As environmental, social, and governance (ESG) considerations become increasingly pivotal to investment decisions, regulatory agendas, and corporate strategies, the diffusion of sustainable practices across firms has emerged as a critical concern. Auditors who serve multiple clients may act as conduits for the cross‐firm transmission of ESG knowledge and norms. Drawing on social network theory and organizational learning theory, this study examines whether sharing signing auditors with high‐ESG peers enhances corporate ESG performance. Using a comprehensive sample of Chinese A‐share listed firms from 2009 to 2025, we document that firms sharing signing auditors with high‐ESG peers exhibit significantly better ESG outcomes, consistent with a “hand‐in‐hand” convergence effect rather than an “out‐of‐step” divergence. This finding remains robust to a series of endogeneity and robustness tests. Moderation analyses show that the positive effect is amplified when executives have environmental backgrounds but attenuated by greater institutional investor attention, underscoring the roles of managerial receptivity and external governance substitution in shaping the diffusion process. Further analyses reveal that the ESG improvements resulting from shared signing auditors translate into enhanced stock returns and stronger sustainable development capacity. This study advances research on ESG determinants and auditor networks by identifying shared signing auditors as interorganizational knowledge brokers that facilitate the diffusion of sustainability‐related knowledge and practices, offering practical implications for firms, audit professionals, and regulators.
ABSTRACT This paper studies cooperation and defection in teams when workers differ in talent and tasks vary in their degree of substitutability. We consider an organizational environment in which workers receive equal shares of team output, the principal allocates workers to teams, and a minimum effort standard is enforced through monitoring. Using a CES production technology, we characterize the equilibrium effort profiles that emerge under different combinations of task technology, talent heterogeneity, and effort standards. Mutual cooperation is most likely when workers have similar talent levels and tasks are complementary, whereas mutual defection becomes more prevalent as substitutability increases. Most importantly, asymmetric effort equilibria arise only when talent heterogeneity interacts with a production technology that departs from the Cobb–Douglas benchmark. Under substitutability, the more talented worker tends to cooperate while the less talented worker defects; under complementarity, the opposite pattern may emerge. The paper contributes by identifying a technological condition for asymmetric effort allocation in teams. More broadly, the results show that free riding may emerge as an equilibrium response to task technology and team composition rather than as a simple consequence of weak incentives. From the principal's perspective, profits depend more on team composition and task technology than on the strictness of effort standards, and asymmetric effort allocation may represent a stable and profitable organizational outcome.
Why do rational co-founders repeatedly select overconfident partners? We develop a formal model in which founder overconfidence carries both a benefit and a cost for the venture team. The benefit operates through effort: a founder who overestimates project value works harder, and because efforts are strategic complements it induces higher effort from a rational co-founder, partially solving the team moral hazard problem. The cost operates through decisions: overconfidence distorts resource allocation and delays exit from failing courses of action. The co-founder's partner-selection problem trades off these forces, and its solution constitutes a form of delegated commitment: like an owner who commits to aggressive competition by hiring a manager with distorted incentives, the co-founder commits the team to a high-effort equilibrium by partnering with a founder whose beliefs make high effort a best response. We establish five results: (1) Both agents' efforts strictly increase with founder bias. (2) The co-founder's payoff is uniquely maximized at a strictly positive, interior bias level, so perfectly rational founders are suboptimal partners, and this preference survives when candidate founders vary jointly in quality and bias and when equity is negotiated. (3) Total team surplus peaks at a lower bias level than the co-founder's private optimum, because the co-founder externalizes both the founder's overwork and part of the distortion cost. (4) Optimal bias increases with project quality: quality and founder confidence are complements in team production. (5) Welfare gains from optimal bias selection are superlinear in project quality, and we show that this superlinearity is generated entirely by effort complementarity: absent complementarity, percentage gains are independent of quality. These results reframe overconfidence from an individual-level cognitive error to a costly but strategically selected feature of entrepreneurial team formation, with implications for co-founder selection, venture capital assessment, and the design of entrepreneurial teams.
This paper considers a supply chain consisting of a supplier and a platform, focusing on the platform's information technology (IT) investment and the supplier's pricing strategies under uncertain demand and supply disruption. Two models are developed. The no-IT investment model is formulated as a nonsmooth stochastic optimization problem and solved using slack variables and quasi-Monte Carlo approximation. The IT investment model is formulated as a deterministic optimization problem solvable by standard optimization methods. Sensitivity analysis provides several managerial insights. First, IT investment by the platform is often essential and may lead to oversupply conditions that improve profitability for both parties. Additionally, IT investment can significantly reduce losses caused by inventory shortages and supply-demand mismatches, which is particularly beneficial to the supplier. Second, the supplier's optimal pricing increases with the accuracy of demand information enabled by IT. Third, IT investment does not always benefit the supplier. Under moderate supply disruption and when demand exceeds supply, IT investment mainly benefits the platform while potentially harming the supplier. The analysis is further extended in two directions. One extension introduces a model in which demand information accuracy depends on the IT investment level. The results show that when information accuracy increases with the level of IT investment, the investment becomes consistently beneficial to the supplier. Another extension analyzes dual-supplier competition under an agency model. Using the Gauss-Seidel iteration to compute the Nash equilibrium, the results indicate that high information-sharing costs can justify IT investment and that such investment improves profits as cross-price sensitivity increases.
