No abstract

Disruptive digital innovation (DDI) often creates hypercompetitive market environment that forces firms to be agile to survive and remain competitive. Whereas most studies have focused on larger firms' effort to be agile, few have looked at how small-and medium-sized enterprises (SMEs) respond to DDI. The study attempts to answer the research question of how SMEs achieve agility to respond to DDI. Drawing on a case study of an innovative SME, our study develops a framework on agility based on the processes of mitigating organizational rigidity, developing innovative capabilities, and balancing the tension of organizational ambidexterity.Specifically, our findings show that for SMEs, mitigating organizational rigidity is enabled by the mechanism of achieving boundary openness while developing innovative capability is enabled by the mechanism of achieving organizational adaptability. At the same time, given the inherent challenges of resource constraints, SMEs also need to balance the tension of organizational ambidexterity.

Sepsis is a leading cause of death in hospitals. Early prediction and diagnosis of sepsis, which is critical in reducing mortality, is challenging as many of its signs and symptoms are similar to other less critical conditions. We develop an artificial intelligence algorithm, SERA algorithm, which uses both structured data and unstructured clinical notes to predict and diagnose sepsis. We test this algorithm with independent, clinical notes and achieve high predictive accuracy 12 hours before the onset of sepsis (AUC 0.94, sensitivity 0.87 and specificity 0.87). We compare the SERA algorithm against physician predictions and show the algorithm’s potential to increase the early detection of sepsis by up to 32% and reduce false positives by up to 17%. Mining unstructured clinical notes is shown to improve the algorithm’s accuracy compared to using only clinical measures for early warning 12 to 48 hours before the onset of sepsis.

We add to the theory of entrepreneurial fi rm growth by inductively theorizing the processes through which new high-growth fi rms utilize their partnering portfolios to pursue distinctive approaches to growth. We extend the strategic perspective on entrepreneurial networks by identifying three mechanisms linking partnering portfolios to differences in fi rm growth: confi guring partnering portfolios to pursue distinctive logics for sourcing external resources, aligning resource-sourcing and resource-linking logics in new product development, and embarking on different growth trajectories, which contribute to different performance patterns. These theoretical insights contribute to current understanding of the external and internal sources of heterogeneity in the performance of entrepreneurial fi rms.

No abstract