Understanding technology-driven work arrangements from a complexity perspective: a systematic literature review and an agenda for future research

Abstract

Organizations are increasingly introducing new work arrangements triggered by fast-paced knowledge acquisition, exponential technological growth, and demographic changes. Even though many studies have provided an in-depth understanding of how technology changed individual forms of modern work (e.g. virtual teams, shared leadership, remote work), the field needs a broader view of what constitutes technology-driven work arrangements and why they are implemented in organizations. The purpose of our paper is to systematically review, structure, and integrate the empirical evidence on current research on technology-driven work arrangements and to identify blind spots, which will serve as a springboard for the further development of the field. Based on our understanding of technology-driven work arrangements as flexible approaches to work within and beyond organizational boundaries that result from technology-driven transformation processes characterized by intensified spread, speed, and depth, we identify 191 studies that meet our inclusion criteria and organize them into six thematic clusters. We integrate our findings into an overarching framework based on complexity theory. We argue that three thematic clusters identified in our systematic literature review (organizational architectures across boundaries, knowledge integration processes across boundaries, and flexible employment relations across organizational boundaries) address an organization’s need for external flexibility. In contrast, three other clusters (virtual teams within organizations, virtual communication processes within organizations, and enhancement of self-responsibility of organizational actors) address internal flexibility needs, reflecting the overall goal of technology-driven work arrangements to achieve internal and external flexibility via coordinated and consistent patterns of action across all clusters. We additionally highlight underexplored research opportunities and provide promising avenues for future research.