Search for: All records

This research examines how team members’ passion for innovation compiles to contribute to team innovation. We argue that team mean passion influences team innovation by affecting team reflexivity, which is a key team process for members to collectively reflect on and adjust their efforts toward achieving innovation goals. The indirect effect of mean passion on team innovation via team reflexivity depends on the nature of passion—harmonious passion (HP) versus obsessive passion (OP)—and the diversity of the corresponding type of passion. Results from a two‐wave field study of 131 teams and a three‐wave field study of 155 teams support the differential effects of compiled HP and OP. Moreover, the effect of mean HP on team reflexivity and its indirect effect on team innovation via reflexivity were less positive when HP diversity was higher rather than lower, while the effect of mean OP on team reflexivity and its indirect effect on team innovation via reflexivity were less negative when OP diversity was higher rather than lower. This research offers important theoretical and practical implications for literatures on passion, teams, and team innovation.

 

Abstract Soil moisture heterogeneity can induce mesoscale circulations due to differential heating between dry and wet surfaces, which can, in turn, trigger precipitation. In this work, we conduct cloud-permitting simulations over a 100 km × 25 km idealized land surface, with the domain split equally between a wet region and a dry region, each with homogeneous soil moisture. In contrast to previous studies that prescribed initial atmospheric profiles, each simulation is run with fixed soil moisture for 100 days to allow the atmosphere to equilibrate to the given land surface rather than prescribing the initial atmospheric profile. It is then run for one additional day, allowing the soil moisture to freely vary. Soil moisture controls the resulting precipitation over the dry region through three different mechanisms: as the dry domain gets drier, (i) the mesoscale circulation strengthens, increasing water vapor convergence over the dry domain, (ii) surface evaporation declines over the dry domain, decreasing water vapor convergence over the dry domain, and (iii) precipitation efficiency declines due to increased reevaporation, meaning proportionally less water vapor over the dry domain becomes surface precipitation. We find that the third mechanism dominates when soil moisture is small in the dry domain: drier soils ultimately lead to less precipitation in the dry domain due to its impact on precipitation efficiency. This work highlights an important new mechanism by which soil moisture controls precipitation, through its impact on precipitation reevaporation and efficiency. 

Incentives are explored in the sharing economy to inspire users for better resource allocation. Previous works build a budget-feasible incentive mechanism to learn users' cost distribution. However, they only consider a special case that all tasks are considered as the same. The general problem asks for finding a solution when the cost for different tasks varies. In this paper, we investigate this general problem by considering a system with k levels of difficulty. We present two incentivizing strategies for offline and online implementation, and formally derive the ratio of utility between them in different scenarios. We propose a regret-minimizing mechanism to decide incentives by dynamically adjusting budget assignment and learning from users' cost distributions. Our experiment demonstrates utility improvement about 7 times and time saving of 54% to meet a utility objective compared to the previous works.