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概要と使いどころ
Use when choosing and justifying the research design for an Administrative Science Quarterly (ASQ) manuscript — qualitative (grounded-theory, ethnographic, historical) or quantitative — and setting the rigor bar. Designs the study; it does not run the analysis (see asq-data-analysis).
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Use when writing the contribution and implications section for a 《会计研究》 (Accounting Research) manuscript — articulating both the accounting-theory contribution (role of accounting information) and concrete implications for standard-setters, regulators, and audit/reporting practice. Use after results and tables are final.
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Use when framing or sharpening a topic for 《会计研究》 (Accounting Research) — turning a generic "X affects Y" empirical idea into an accounting contribution anchored in China's institutional setting, accounting theory, and standard-setting / practice relevance. Use before literature review.
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Use for the pre-submission preflight to 《会计研究》 (Accounting Research) — checking footnote (当页下注) conventions, the 著者—出版年制 reference style, abstract/keyword limits, article length, the online-only submission system via the Accounting Society of China site, double-blind anonymity, and document hygiene. Use right before submitting; verify every rule against the journal's current 投稿指南.
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 responding to 《会计研究》 (Accounting Research) reviewer reports / an R&R — drafting a point-by-point response letter and 修改说明 that addresses accounting-measure construction, institutional/standard accuracy, identification, and information-mechanism concerns, while keeping the revision anonymous. Use only after the manuscript itself has been revised.
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 writing or verifying the institutional / accounting-standard / regulatory background for a 《会计研究》 (Accounting Research) manuscript — getting standard clauses, regulatory rules, and effective dates exactly right, since precise institutional detail is a defining bar of this journal. Use before measurement and identification.
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 building the robustness section for a 《会计研究》 (Accounting Research) manuscript — replacing accounting measures with alternatives, adding governance / institutional controls, placebo tests, and endogeneity follow-ups — so the main result survives an accounting referee's scrutiny. Use after mechanism is settled.
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 the empirical identification strategy is the bottleneck for a 《会计研究》 (Accounting Research) manuscript — exogenous standard / regulatory changes (event study, DID), PSM, Heckman, IV — and you need to stress-test the design before drafting tables. Prefers standard/regulatory shocks as the cleanest accounting identification source.
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 choosing or sharpening a research question for an Accounting, Organizations and Society (AOS) manuscript — testing whether the question genuinely concerns the social, organizational, behavioral or institutional life of accounting, and picking the intellectual tradition the question demands. Screens fit; it does not build the theory (aos-theory-development).
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Use when constructing or auditing accounting measures for 《会计研究》 (Accounting Research) — discretionary accruals (modified Jones), real earnings management (Roychowdhury), conservatism (Basu / C-Score), comparability, disclosure indices, audit-quality and tax-avoidance proxies — so each measure is built transparently and reproducibly. Use before identification.
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Use when the mechanism analysis for a 《会计研究》 (Accounting Research) manuscript is missing or mis-specified — the channel must be an information mechanism (reduce information asymmetry, raise disclosure quality, constrain earnings management, improve audit assurance), not a generic pricing or financing channel. Use after the main result holds.
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 finalizing tables and figures for a 《会计研究》 (Accounting Research) manuscript — keeping the main table lean, reporting coefficients with the right precision, and interpreting economic magnitude (not just significance stars) for accounting measures. Use after robustness is settled.
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 scoping or sanity-checking a research question for an Academy of Management Journal (AMJ) manuscript — fit, theory-drivenness, and feasibility. Decides whether the idea can earn a theoretical contribution; it does not build the theory itself (use amj-theory-development) or position the literature (amj-literature-positioning).
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 the research design and method are the bottleneck for an Academy of Management Journal (AMJ) manuscript — matching design (archival, survey, experiment, multi-method, field) and level of analysis to the theoretical question. Designs the study; it does not run the estimation or validity checks (amj-data-analysis).
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 building exhibits for an Academy of Management Annals (Annals) review — the signature framework figure, who-studied-what synthesis tables, and search/coverage exhibits that summarize across a literature. Designs review exhibits; it does not produce original-estimate regression tables (an Annals review reports no new data of its own).
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 deciding whether a project is a strong AAMAS fit, comparing AAMAS with AAAI, IJCAI, NeurIPS, ICML, EC, and the JAAMAS journal, identifying whether the agents are truly the research object, naming the interaction primitive (solution concept, mechanism, coordination, negotiation), and sharpening the multiagent framing before writing begins.
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Use when systematically gathering, coding, and synthesizing a management/organization literature for an Academy of Management Annals (Annals) review — the search-and-coverage methodology and the choice of narrative vs. systematic vs. bibliometric integration. Builds the corpus and synthesis notes; it does not impose the organizing spine (amann-organizing-framework) or write prose.
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行业情报雷达：多源扫描(X/即刻/V2EX/HN) → 关键词过滤 → 趋势检测 → 每日情报简报。触发词：行业情报、竞品监控、热点扫描、情报雷达
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。
Generates Instagram Reels where product image cuts are synced to audio beats. Accepts audio as a local file, URL, or search query. Uses librosa for beat detection, FFmpeg Ken Burns for scene animation, and Pillow for text overlays. No AI video generation — fully free, fast, and scalable.
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Compare competitors' social content across platforms to identify recurring topics, formats, hooks, audience reactions, distribution patterns, and credible content opportunities for a brand.
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Mine comments and replies on social posts, videos, and ads for recurring customer language, questions, objections, desired outcomes, complaints, product requests, purchase signals, and creative opportunities. Use for voice-of-customer research grounded in linked source evidence.
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。
Provider reference for collecting public profiles, posts, comments, transcripts, trends, and ad-library data from major social platforms through ScrapeCreators. Use as a dependency of research workflows, not as the final user-facing deliverable.
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Builds personalized demo assets for top prospects using the founder's product API/MCP/SDK. Researches prospect, proposes demo concepts, builds working prototype, tests it, and generates comparison report with live demo link.
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Comprehensive SEO footprint analysis. Catalogs all content, pulls real SEO metrics (via Apify Semrush/Ahrefs scrapers or free web search probes), runs competitor analysis, builds topic/keyword and content-type gap matrices, and produces a prioritized recommendations report. The complete SEO audit for any company.
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。