People, IT, and Structuration (PIS): An Integrative Theoretical Framework for Management Information Systems

TL;DR

The paper introduces the PIS framework, unifying various MIS theories by conceptualizing people, technology, and structure as mutually constitutive elements engaged in ongoing processes.

Contribution

It synthesizes existing MIS theories into a unified framework based on Giddens' structuration theory, addressing unresolved tensions and extending to AI-related phenomena.

Findings

PIS resolves tensions between social and technological determinism.

It formalizes mechanisms of co-evolution among P, I, and S.

Extends framework to include AI, algorithms, and human-AI collaboration.

Abstract

The Management Information Systems (MIS) discipline has long grappled with how to theorize the complex, mutually constitutive relationships among people, information technology, and organizational structures. Decades of research have produced influential but fragmented theoretical streams from socio-technical systems theory to technology acceptance models, from adaptive structuration theory to sociomateriality, and each illuminating important facets while leaving integrative questions unresolved. This paper proposes the People - IT - Structuration (PIS) framework as a unifying theoretical lens that synthesizes these streams. Drawing on Giddens' structuration theory, we conceptualize People (P), Information Technology (I), and Structure (S) not as independent variables but as mutually constitutive elements engaged in ongoing structuration processes. We trace the intellectual history of MIS theorizing to demonstrate how PIS resolves persistent tensions in the field,e.g. between technological and social determinism, between variance and process approaches, and between micro-level interaction and macro-level institutional dynamics. We develop a set of formal propositions articulating the mechanisms through which P, I, and S co-evolve, and extend the framework to address contemporary phenomena including artificial intelligence, algorithmic management, and human-AI collaboration. The PIS framework offers both a retrospective lens for understanding the discipline's theoretical evolution and a prospective tool for guiding research in the AI era.