As China’s political and economic centre, the Beijing–Tianjin–Hebei (BTH) urban agglomeration experiences serious environmental challenges on particulate matter (PM) concentration, which results in fundamental or irreparable damages in various socioeconomic aspects. This study investigates the seasonal and spatial distribution characteristics of PM_2.5 concentration in the BTH urban agglomeration and their critical impact factors. Spatial interpolation are used to analyse the real-time monitoring of PM_2.5 data in BTH from December 2013 to May 2017, and partial least squares regression is applied to investigate the latest data of potential polluting variables in 2015. Several important findings are obtained: (1) Notable differences exist amongst PM_2.5 concentrations in different seasons; January (133.10 mg/m³) and December (120.19 mg/m³) are the most polluted months, whereas July (38.76 mg/m³) and August (41.31 mg/m³) are the least polluted months. PM_2.5 concentration shows a periodic U-shaped variation pattern with high pollution levels in autumn and winter and low levels in spring and summer. (2) In terms of spatial distribution characteristics, the most highly polluted areas are located south and east of the BTH urban agglomeration, and PM_2.5 concentration is significantly low in the north. (3) Empirical results demonstrate that the deterioration of PM_2.5 concentration in 2015 is closely related to a set of critical impact factors, including population density, urbanisation rate, road freight volume, secondary industry gross domestic product, overall energy consumption and industrial pollutants, such as steel production and volume of sulphur dioxide emission, which are ranked in terms of their contributing powers. The findings provide a basis for the causes and conditions of PM_2.5 pollution in the BTH regions. Viable policy recommendations are provided for effective air pollution treatment.

While there is a burgeoning trend to recognize leadership as an important enabler of new venture development and growth, scant research has explored the performance mechanisms of shared leadership in the entrepreneurial context. Based on the information processing perspective, we propose a moderated mediation model to examine how shared leadership in entrepreneurial teams advance new venture performance by identifying team reflexivity as a pivotal mediator and team boundary spanning as a crucial contingency. The data set from a cross-industry sample of 94 entrepreneurial teams indicated that shared leadership exerts a positive indirect influence on new venture performance via team reflexivity; and team boundary spanning moderates such indirect influence. Finally, how our findings contribute to the entrepreneurship, leadership, team research, and managerial practice are discussed.