The Theory Map That Keeps Growing

It started as one page. I wrote the names of five IS theories on sticky notes, arranged them in a rough circle on my desk, and drew arrows between the ones that seemed related. That was four months ago. The page is now a wall. The sticky notes have migrated to a large whiteboard. The arrows have multiplied, turned into dashed lines and solid lines and colored paths that I add to whenever I read something that rearranges my understanding. I did not plan for this to happen. It just did, because the more I studied each theory on its own, the more I saw that none of them sat still.

The first connection I drew was between the Resource-Based View and dynamic capabilities theory. I had studied them in separate weeks, separate readings, separate mental boxes. RBV, taught first, felt complete. Barney (1991) gave us the VRIN criteria: valuable, rare, inimitable, non-substitutable. A resource that has those four things can produce sustained competitive advantage. The logic is clean, almost elegant. I remember closing the book and thinking I understood IT business value. Then I read Teece et al. (1997) the following week, and the clean picture got messier.

Dynamic capabilities theory asks a different question. Not what resources give you advantage, but how you change your resources when the environment shifts. Sensing, seizing, transforming. The two theories are not competing explanations of the same thing. They operate at different analytical levels. RBV answers a static question: at this point in time, does this resource bundle have VRIN characteristics? Dynamic capabilities answer a dynamic question: can this organization reconfigure its resource bundle when conditions change? The wall now shows those two theories connected by a thick arrow labeled "level of analysis." They need each other. A firm can have VRIN resources today and lose everything tomorrow if it lacks the capability to reconfigure them.

The second connection took me longer to see. I was studying affordance theory and structuration theory in the same week, and at first they looked like rivals. Both deal with the relationship between technology and people using it in organizations. Orlikowski (1992) applied structuration to technology by arguing that technology is both a product of human action and a medium of it. People build systems, and those systems then shape how people work, which shapes the next wave of systems, in a recursive loop. Affordance theory, as Markus and Silver (2008) formulated it, says something different: technology creates action possibilities, but only for specific actors with specific goals. A feature is not an affordance until you name who is using it and what they are trying to do.

I spent two weeks thinking these were competing accounts. I even wrote a paragraph starting with "structuration says X while affordance theory says Y, and Y is right." Then I realized I had the relationship backwards. Structuration explains the ongoing recursive co-evolution of technology and organizational practice. Affordance theory explains the specific action possibilities that exist at a given moment for a given actor. They are not answering the same question. Structuration asks how technology and practice shape each other over time. Affordance asks what a technology makes possible for a specific person right now. They are different mechanisms for different parts of the same process, and a complete answer needs both.

The third connection became obvious only after I failed to answer a practice question cleanly. The question asked about organizational technology adoption, and I started listing theories, but the answer came out flat because every theory I named was trying to explain a different phase. Institutional theory, as DiMaggio and Powell (1983) showed, explains why organizations adopt technologies. Organizations converge on similar tools because of coercive regulatory pressure, mimetic imitation under uncertainty, and normative professional standards. But institutional theory stops at adoption. It explains why a university adopts a learning management system, not what happens after faculty start using it or not using it.

That is where affordance theory and structuration step in. Institutional theory gets the organization to the starting line. It explains the decision. The post-adoption reality, whether the technology actually changes work or sits unused, is a different phenomenon explained by a different set of mechanisms. Isomorphism may explain why every hospital bought the same electronic health record, but it does not explain why some departments use it to improve care coordination while others keep printing the records and typing notes by hand. For that you need structuration, which explains how the tool reshapes practice and practice reshapes how the tool is used. Or you need affordance theory, which asks what the system actually enables for a specific physician with a specific patient load on a specific shift.

I started drawing these connections with colored pens. Blue for theories that explain why things happen. Green for theories that explain what happens next. Red for the traps and boundaries that prevent me from claiming too much. The blue cluster has institutional theory and TOE, which explain adoption drivers. The green cluster has structuration, affordance theory, and dynamic capabilities, which explain what unfolds after the technology arrives. And the red annotations, added later, mark where students and professors alike make mistakes: calling TOE a theory when it is just a contextual bucket, treating coercive isomorphism as an internal mandate when it must come from external regulation, confusing resource possession in RBV with resource reconfiguration in dynamic capabilities.

I think the most useful thing this map has done for me is not help me memorize theories. It has shown me where the edges are. Every theory has a boundary, and the boundaries are where the other theories start. Institutional theory ends where adoption becomes use. Affordance theory starts where the actor meets the artifact. Structuration theory runs across the whole timeline but requires time and repeated practice to play out, so it cannot explain a single adoption decision at a single point. RBV and dynamic capabilities are separated by whether the environment is stable or turbulent. None of these are weaknesses. They are the contours that make each theory useful for a specific kind of question.

I keep a blank set of sticky notes next to the board. Every time I read a paper that introduces a new construct or mechanism, I write it on a note and try to find where it connects. Some notes stay in my hand for a long time before I find the right place. Some never make it onto the board, because they duplicate theories that are already there under different names. The ones that stick are the ones that fill a gap between two existing nodes without contradicting either one.

The map is not finished. I do not expect it to be. Every reading rearranges something. A paper on digital objects and social positioning, like Faulkner and Runde (2019), adds a note about how the identity of a digital artifact depends on the social position it occupies, which connects to both affordance theory and structuration from an angle I had not considered. A paper like Burton-Jones et al. (2021), about how the IS field should think about theory itself, adds not a node but a rule for how to evaluate the arrows: is this connection an extension, a reformulation, or something new? The map grows not because I add more sticky notes but because the connections between them keep changing.

I have written separately about structuration and technology appropriation and about RBV versus dynamic capabilities and about why affordances are not just features. Each of those posts assumes one theory is the focus. What the map taught me is that the real object of study is not any single theory. It is the relationship between them. The theories do not compete. They partition the same complex phenomenon at different seams.