Collaborate as a flock in the organization: how selection and synthesis influence knowledge convergence within a complex adaptive system

Abstract

Purpose: This study aims to investigate how two collaborative methods – selection and synthesis – influence knowledge convergence when people articulate a new strategic direction driving transformation within the organization. Design/methodology/approach: The study is based on a longitudinal field experiment developed in four organizations involving 82 employees over a three-month process. Inspired by dynamics governing flocks as complex adaptive systems, selection and synthesis have been separately used in two sets of companies. Primary and secondary data have been largely collected and analyzed throughout the whole process. Findings: This study describes how the two alternative methods differently influenced two kinds of knowledge convergence. While selection triggers a general and static knowledge convergence and the propagation of individual knowledge over time, synthesis fosters a local and dynamic knowledge convergence where individuals tend to propagate knowledge generated collectively. Research limitations/implications: This research offers insights into understanding the influence of alternative collaborative methods on the creation and propagation of knowledge when people are converging toward a new strategic direction. From a theoretical perspective, it contributes to complex adaptive system theory, highlighting the role of knowledge convergence and emergence through collaboration. Practical implications: This research offers insights to managers who deal with the complexity of the engagement of different stakeholders during collaborative processes, offering some actionable takeaways to foster knowledge convergence by alternatively employing selection and synthesis. Originality/value: This paper contributes to the management and social information processing literature emphasizing the role of knowledge convergence emerging from the complex interactions among multiple stakeholders.