The present work investigated fundamental mediating mechanisms (i.e., flow experience, organizational identification, and trust), underlining the impact of authentic leadership on employee resilience during the turbulent COVID-19 pandemic. A total of 901 frontline employees working in a construction engineering company in China participated in this study. They were asked to respond to a battery of questionnaires comprising Trust Scale (affective-based, cognitive-based, and competence-based), Flow Proneness Questionnaire (FPQ), Organizational Identification Scale, Authentic Leadership Questionnaire, and Employee Resilience Scale. Results of structural equation modeling indicated that: (1) Authentic leadership positively predicted employee resilience in the COVID-19 pandemic, directly and indirectly. (2) As for the indirect relationship, two parallel mediation effects and one chain mediation were detected: employees’ flow at work and organizational identification respectively and dependently mediated the relationship between authentic leadership and employee resilience; trust and organizational identification played as a chain mediation role within authentic leadership-employee resilience association. The study provides empirical evidence for organizations’ resilience-building and leadership training programs. Findings also contribute to the literature by facilitating flow intervention, promoting organizational identification and trust to enhance the effect of authentic leadership in promoting positive psychological functioning of employee resilience. Limitations with respect to future research directions were also outlined.

Authentic leadership is essential for predicting employee resilience. However, despite fruitful findings, more adapted models of authentic leadership – employee resilience based on empirical findings can serve as a guide to understand the complex mediators and moderators in different industries such as in construction engineering project organizations during the turbulent pandemic. This study, therefore, based on the organizational identification theory and flow theory through the lens of positive organizational psychology, aims to disentangle the authentic leadership—employee resilience association by investigating their underlying mechanism and their boundary condition. To test our hypothetical model, we applied a cross-sectional design with data collected from a large sample of 884 employees from a big enterprise in China. Findings from confirmatory factor analysis, structural equation modeling analysis, and Hayes’s conditional process model indicated that: authentic leadership positively predicted employee resilience through the partial mediation effect of organizational identification, and such a mediation model was moderated by the experience of flow. In other words, flow moderated the relationships between authentic leadership, organizational identification, and employee resilience. Findings provide evidence for cultivating leaders’ authenticity in promoting their subordinates’ resilience; findings also highlight the significance of organizational identification in bridging authentic leadership and employee resilience and the essential role of flow experience in supporting the relationships mentioned above.

PurposeThis paper aims to examine the day-to-day within-person associations between employees' flow experience and organizational identification within the rarely studied context of construction engineering project organizations.Design/methodology/approachIn this daily diary design, the authors surveyed 204 (Mage = 28.3, SD = 5.69) employees of a state-owned construction engineering project organization in southwest China via the online questionnaires comprising flow and organizational identification scales once daily on each workday for three consecutive weeks, which yielded 3,060 data entries. The authors then tested the temporal directionality between flow and organizational identification with multilevel time-series cross-lagged path analysis using Mplus 8.3.FindingsDaily flow experience was linked positively with same-day organizational identification. Importantly, flow experience on the previous day predicted organizational identification on a subsequent day, but not vice versa.Practical implicationsThis study suggests that construction engineering project managers should implement interventions fostering the employees' flow experience to promote organizational identification, with important implications for organizations aiming at flourishing workforces by facilitating organizational identification through implementing flow strategies.Originality/valueThere is a dearth of diary studies on flow and organizational identification specific to construction engineering project employees. The authors’ findings provide concrete evidence of the fluctuant nature of daily flow experience and organizational identification as well as their dynamic predictive pathway relationship.

To evaluate different segmentation methods in analyzing Schlemm's canal (SC) and the trabecular meshwork (TM) in ultrasound biomicroscopy (UBM) images. Methods: Twenty-six healthy volunteers were recruited. The intraocular pressure (IOP) was measured while study subjects blew a trumpet. Images were obtained at different IOPs by 50-MHz UBM. ImageJ software and three segmentation methods-K-means, fuzzy C-means, and level set-were applied to segment the UBM images. The quantitative analysis of the TM-SC region was based on the segmentation results. The relative error and the interclass correlation coefficient (ICC) were used to quantify the accuracy and the repeatability of measurements. Pearson correlation analysis was conducted to evaluate the associations between the IOP and the TM and SC geometric measurements. Results: A total of 104 UBM images were obtained. Among them, 84 were adequately clear to be segmented. The level-set method results had a higher similarity to ImageJ results than the other two methods. The ICC values of the level-set method were 0.97, 0.95, 0.9, and 0.57, respectively. Pearson correlation coefficients for the IOP to the SC area, SC perimeter, SC length, and TM width were −0.91, −0.72, −0.66, and −0.61 (P < 0.0001), respectively. Conclusions: The level-set method showed better accuracy than the other two methods. Compared with manual methods, it can achieve similar precision, better repeatability, and greater efficiency. Therefore, the level-set method can be used for reliable UBM image segmentation. Translational Relevance: The level-set method can be used to analyze TM and SC region in UBM images semiautomatically.