Accurate prognosis of battery remaining useful life is essential for evaluating reliability and optimizing the utilization of energy storage systems. To address the challenge of multicollinearity among degradation features, we propose a Bayesian adaptive elastic net method that improves prediction accuracy while providing comprehensive uncertainty quantification. The proposed approach implements adaptive shrinkage, applying separate penalty parameters to each regression coefficient to shrink the non-significant variables while preserving the effects of important predictors. By representing Laplace priors as Gaussian-exponential mixtures through data augmentation techniques and approximating the normalizing constant numerically, we develop an efficient Metropolis-Hastings-within-Gibbs sampling framework for posterior inference. Validation using numerical simulations and battery cycle life data demonstrates that the proposed method delivers superior prediction accuracy and robust uncertainty quantification, even under severe multicollinearity, providing an effective solution for battery lifetime prediction.

Purpose: Flexibility and efficiency are dual attributes of the organizational structure that are crucial for project-driven enterprises to achieve sustainable development in a dynamic environment. However, there is a lack of research on the patterns by which the dual attributes of a project-driven enterprise’s organizational structure affect business model innovation. Employing organizational theory, this study aims to assess the mediating mechanisms and dynamic capabilities through which the dual attributes of the organizational structure influence business model innovation in project-driven enterprises. Design/methodology/approach: Data were collected from 242 employees from four project-driven companies across 26 cities (e.g. Beijing, Tianjin, Guangzhou and Shenzhen) in China. Structural equation modeling revealed the relationship between organizational structure’s dual attributes and business model innovation. Findings: The findings show that the dual attributes (flexibility and efficiency) of the organizational structure have positive impacts on business model innovation. Moreover, dynamic capabilities mediate the relationship between the dual attributes and business model innovation in project-driven enterprises. Originality/value: This study provides contributions to innovation research in the context of project-driven enterprises by revealing the influence of organizational structure on business model innovation through the firms’ dynamic capabilities. Such knowledge can enable managers of project-driven enterprises to develop effective interventions to promote business model innovation.