Skill UI

This skill provides a rigorous, operational framework for product and user research. It helps researchers select the appropriate study method (generative, evaluative, validation) based on goals and product stages. It also calculates defensible sample sizes and saturation levels, and synthesizes raw observations into governed, evidence-based insights, ensuring all findings are rooted in cross-participant recurrence.

This powerful orchestrator guides the planning, funding, scoping, and synthesis of enterprise research across four critical domains: clinical R&D, finance, market analysis, and product usability. It acts as a central hub, routing complex inquiries to specialized sub-skills and generating structured digests with actionable insights and critical 'grill challenges' for operational rigor.

This comprehensive skill guides researchers through the submission process for the Chinese Journal of Management Science. It covers the journal's core academic positioning (operations research, decision analysis, complex systems), required methodological rigor (model setting, algorithms, proofs), structural guidelines, and essential formatting checks. It helps authors assess manuscript fit and identify common rejection risks before official submission.

A comprehensive guide for authors on how to position their computational or methodological contributions when submitting to the INFORMS Journal on Computing (IJOC). It emphasizes the critical need to advance against two distinct frontiers simultaneously: the Operations Research/Mathematical Science problem domain, and the core computing methodology. Use this when reviewer feedback questions the novelty or when your work straddles OR and CS boundaries.

This guide helps researchers determine if their Operations Research (OR) or analytics findings are sufficiently computation-first for submission to the INFORMS Journal on Computing (IJOC). It provides a rigorous scope test, focusing on computational/methodological advances, measurable performance claims, and reproducibility standards, ensuring authors select the correct technical area and venue.

This guide provides detailed standards for structuring and writing manuscripts submitted to the INFORMS Journal on Computing (IJOC). It mandates a precise, methods-forward, and quantitative voice, ensuring the paper is accessible to both Operations Research (OR) and Computer Science (CS) audiences. Key elements covered include abstract structure (≤300 words, no formulas), rapid contribution framing in the introduction, and using numbered pseudocode for methods.

This skill helps authors evaluate whether their research—particularly in algorithms, optimization, or machine learning for Operations Research (OR)—meets the high computational standards required by the INFORMS Journal on Computing (IJOC). It acts as a fit/venue-selection tool, guiding authors on methodological rigor, computational evidence, and structuring their submission to maximize acceptance chances.

This guide provides comprehensive strategic advice for authors submitting manuscripts related to Artificial Intelligence, Constraint Programming, and Operations Research (AI/OR) to top-tier conferences like CPAIOR. It helps refine scope, structure, evidence standards, and narrative framing to meet highly specialized reviewer expectations, ensuring the paper is positioned as a solid hybrid optimization contribution.

A comprehensive framework designed to ensure environmental economics manuscripts meet rigorous data-availability and reproducibility standards, especially for journals like JEEM. This package guides users to document the entire research pipeline, handling complex issues like data versioning, proprietary satellite/admin data, and multi-step spatial operations by establishing a credible end-to-end reproduction path.

This guide helps researchers structure and articulate the core contribution of an Operations Management manuscript for high-impact journals like JOM. It emphasizes the necessity of meeting a dual standard: demonstrating specific theoretical advances in OM theory and providing concrete, actionable practical recommendations, while rigorously ensuring operations remains the central phenomenon.

A comprehensive methodological guide for conducting rigorous statistical analysis in Operations Management (OM). It covers establishing measurement validity (CFA, reliability), selecting appropriate estimators (SEM, HLM, DiD, IV) for survey and archival data, and addressing critical issues like common-method bias and endogeneity. Essential for academic research reporting.

This guide provides a framework for authors to strategically position their empirical research within the ongoing academic debates of Operations and Supply Chain Management (OM/SCM). It teaches authors to move beyond merely identifying knowledge gaps by problematizing shared assumptions, explicitly distinguishing empirical observation from analytical modeling, and aligning the contribution with the target department's specific mission.