People, IT, and Structuration (PIS): An Integrative Theoretical Framework for Management Information Systems
Wei Huang, Xiaofang Cai, Qiaozhen Guo, Xiaosong Wu, Xin Tang
TLDR
The PIS framework unifies MIS theories by conceptualizing people, IT, and structure as mutually constitutive elements in ongoing structuration processes.
Key contributions
- Proposes the People-IT-Structuration (PIS) framework to unify fragmented MIS theories.
- Conceptualizes people, IT, and structure as mutually constitutive elements in ongoing structuration processes.
- Resolves long-standing MIS tensions, including technological vs. social determinism and micro vs. macro dynamics.
- Extends the framework to address contemporary phenomena like AI, algorithmic management, and human-AI collaboration.
Why it matters
This paper introduces the PIS framework, unifying fragmented MIS theories on people, IT, and structure. It resolves tensions and guides future research, especially in the AI era. This advances the discipline.
Original 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.
📬 Weekly AI Paper Digest
Get the top 10 AI/ML arXiv papers from the week — summarized, scored, and delivered to your inbox every Monday.