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.
日本語の概要は準備中です。原文の説明を表示しています。
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).
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。