Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when articulating and differentiating the theoretical contribution of an Academy of Management Review (AMR) manuscript — showing precisely what is NEW versus prior theory and why it matters. Frames the contribution; it does NOT build the theory (amr-theory-development) or check its internal logic (amr-data-analysis).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
실행 점수 미검증
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
AMR seeks "novel, insightful, and carefully crafted conceptual articles that challenge conventional wisdom." Whetten's classic AMR editorial, "What Constitutes a Theoretical Contribution?" (1989, DOI 10.5465/amr.1989.4308371), is the rubric: a complete contribution specifies the What (constructs), How (relationships), Why (the underlying logic), and Who/Where/When (boundary conditions). The Why is the centerpiece — it is what separates theory from description. AMR's scope frames the four legitimate contribution paths: develop new theory; significantly challenge or clarify existing theory; synthesize advances into fresh theory; or identify and delineate a novel theoretical problem.
A contribution claim that cannot be stated as "Before this paper, theory could not X; after it, theory can X" is not yet a contribution.
The single most common AMR rejection reason is "contribution not differentiated from prior work." Defend against it explicitly:
| Contribution type | Strength at AMR |
|---|---|
| New theory / reconceptualization that reorients a conversation | Strongest |
| New construct + mechanism that explains a persistent puzzle | Strong |
| Bridging two conversations to generate new propositions | Strong |
| Bounding an existing theory in a newly theorized way | Solid |
| Adding a contingency/moderator to existing theory | Usually too thin for AMR alone |
| Reviewing/organizing a literature | Not a theoretical contribution |
Dyer & Singh's "The Relational View" (AMR 1998, DOI 10.5465/amr.1998.1255632) states its "before → after" crisply: before, competitive advantage was theorized at the firm or industry level; after, relational rents can accrue to dyads and networks, with four specified sources. That is new theoretical machinery, differentiated from the nearest prior theories — not a relabel and not an added moderator.
A complete AMR contribution closes with implications:
【What's new】the theoretical machinery that did not exist before
【Before → after】theory could not X; now it can X
【Closest prior theory】name + the specific difference
【Contribution type】reconceptualization / new construct+mechanism / bridge / bounding
【Implications】theory / future research / practice
【Over-claim risk】none / trim to: ...
【Next step】amr-tables-figures
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Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance, AI-generated-review handling, and the AAAI two-phase review process where Phase-2 papers receive one feedback round before SPC/AC discussion.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and final public artifact release.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and reproducibility-checklist alignment for Phase-1 survival.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across the broad AI scope, while staying inside AAAI's dual-submission and AI-as-source policy constraints and writing a related-work section legible to non-specialist reviewers.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that Phase-1 reviewers use to judge rigor across AAAI's broad AI scope.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.