From jmis-skills
Builds theoretical engine for JMIS manuscripts covering IT-business-value logic, platform/network-effects mechanisms, economic models, or behavioral IS theory.
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- Your claims are descriptive ("IT spend correlates with performance") with no economic or behavioral mechanism
JMIS spans empirical, economic-analytical, and design-oriented IS work, so "develop theory" means different things. Pick the row that matches your study; JMIS's distinctive pull is toward the economics and management of IS, so even behavioral papers benefit from naming the value or incentive at stake.
| Style | What "theory" means here | What you must produce |
|---|---|---|
| IT business value | A mechanism by which a specific IT capability creates, captures, or destroys value | Causal logic from IT capability → intermediate process → firm/market outcome, with complementarities and contingencies named |
| Platform / e-commerce | Network effects, two-sidedness, matching, governance, or pricing logic | A model or argument yielding directional predictions about adoption, cross-side effects, competition, or platform revenue |
| Economics of IS | An economic mechanism (incentives, information asymmetry, signaling, security/privacy economics) | Comparative-static, signed, falsifiable predictions and the assumptions they rest on |
| Behavioral IS | A technology-specific cognitive/behavioral mechanism (not generic TAM) | A priori hypotheses with the IT artifact in the causal path, boundary conditions, and mediation/moderation logic |
A JMIS IT-value paper is not "more IT, more performance." State which IT capability, acting through what organizational process, under which complementary conditions (process redesign, human capital, governance), produces which outcome. Theorize the complementarities and contingencies — JMIS reviewers reward a contingent value mechanism over a universal "IT pays" claim, because the field already knows the productivity-paradox debate.
State the economic force in words before any math: who has what incentive, what information, and how does the IT-mediated market structure change behavior? Then write comparative-static predictions (e.g., "stronger same-side network effects raise the platform's optimal openness"). For an analytical model, the contribution is the insight the model yields, not the model's existence. Avoid HARKing — predictions precede estimation.
If your hypotheses would survive deleting the technology, they are not IS theory. Anchor the mechanism in a feature of the system (recommendation transparency, gamification, anonymity, automation) and theorize why that feature shifts cognition or behavior, and where the effect reverses. Generic TAM/UTAUT re-tests are a desk-reject risk; extend or challenge a mechanism instead.
IS effects are contingent on the artifact, the user, the firm, the market, and the period. Name the level (individual, firm, platform, market) and the scope where the theory holds and breaks — an honest scope condition beats an over-claimed law.
A draft claims "generative-AI tools raise analyst productivity." As stated it is a correlation with no IS theory. The JMIS mechanism names which capability of the tool (it lowers the cost of drafting but not of verification), acting through what organizational process (task reallocation toward judgment-heavy work), under which complementarity (it pays only where the firm redesigns review workflows and has the human capital to vet output), producing which contingent outcome (productivity rises for routine tasks, is flat or negative for novel ones where verification cost dominates). That contingent, complementarity-laden statement is theory; "AI helps" is not. The hypotheses then follow a priori, including where the effect reverses.
JMIS theory earns its place when it implies a decision a manager, firm, or platform could make differently. After stating the mechanism and predictions, ask: whose choice does this theory inform, and how? A platform-openness model should tell a platform operator when to open vs. close an API; an IT-value mechanism should tell a CIO which complementary investments make a system pay; a privacy-economics model should tell a firm when disclosure deters vs. invites harm. Theory with no decision attached can still be correct, but at JMIS it reads as under-motivated — the journal's center of gravity is the management of IS, so the managerial hook belongs in the theory, not only in a closing implications paragraph.
Much JMIS theory imports machinery from economics, psychology, or operations — that is expected and fine. What is not fine is stopping at the import. "We apply [transaction-cost economics / regulatory focus / queueing theory] to [an IS setting]" is an application, not a contribution; the IS field already knows the borrowed theory. The contribution comes from the extension the IS context forces: a digital artifact that changes the cost structure the borrowed theory assumed, a platform feature that creates a moderator the parent theory never anticipated, an automation that breaks a behavioral mechanism's boundary. Name explicitly what the IS context adds to or revises in the parent theory, and that addition — not the import — is your theoretical contribution.
【Style & theory form】IT-value / platform / economics-of-IS / behavioral
【Core mechanism】IT capability or feature → channel → on whom → outcome
【Claims】H1..Hn / propositions P1..Pn / signed comparative statics
【Complementarities / boundary conditions】where it holds / reverses
【Level of analysis】individual / firm / platform / market
【Next step】jmis-literature-positioning
npx claudepluginhub brycewang-stanford/awesome-journal-skills --plugin jmis-skillsGuides theoretical contribution development for MIS Quarterly manuscripts across behavioral, design science, economics, and organizational traditions. Produces hypotheses, design propositions, or mechanisms before analysis.
Builds the theoretical engine of a JAIS manuscript — original theory, behavioral or economic mechanism, design theory, or pre-theoretical framing for a novel digital phenomenon.
Guides theory building for ISR manuscripts: derive behavioral hypotheses or analytical propositions centered on the IT artifact and sociotechnical interplay across levels of analysis.