Skill UI

This guide helps researchers determine the primary focus of their work—whether it lies in Information Processing (algorithms, estimation) or Sensor Platforms, Tools, and Design Methods (hardware, deployment). It provides a structured methodology for selecting the most appropriate academic venue (e.g., SenSys, MobiSys, INFOCOM) based on the project's technical contribution and maturity.

A comprehensive methodological guide for researchers writing Information Systems Research (ISR) papers. It details how to establish rigorous evidence across empirical (DiD, IV, RDD), analytical (proofs, comparative statics), and design-science claims. Learn to structure your analysis, handle common-method bias, and ensure full reproducibility using modern econometric techniques.

This guide ensures that the chosen research methodology genres (e.g., behavioral empirical, analytical modeling, design science) are correctly aligned with the core research claim or phenomenon. It helps researchers identify the necessary design rigor, appropriate identification strategies (like DiD or IV), and the level of analysis required to ensure the study can genuinely support its contribution in the IS domain.

A comprehensive guide for structuring empirical exhibits (tables and figures) for Information Systems Research (ISR) manuscripts. It addresses the strict page budget (32 text / 38 total) by teaching authors how to differentiate between core arguments that belong in the main body and supporting details that must be moved to the electronic companion/online appendix, ensuring all exhibits are self-contained and highly readable.

This skill serves as a comprehensive guide for researchers to evaluate their academic manuscripts for suitability in Issues in Agricultural Economy. It covers the journal's precise scope, preferred methodologies (e.g., DID, micro-data), submission policies (blind review, fees), and common rejection pitfalls. It provides actionable advice on structuring and refining the manuscript to meet the rigorous standards of core Chinese academic journals focusing on rural and agricultural policies.

A comprehensive framework for conducting rigorous empirical data analysis required for top-tier academic journals. It guides users through building transparent archival samples, specifying appropriate panel data estimators (like firm/year fixed effects), ensuring correct standard error clustering, and executing sophisticated identification strategies (e.g., Difference-in-Differences, Instrumental Variables). Essential for addressing endogeneity and passing deep reviewer scrutiny.

A comprehensive methodological guide detailing how to design rigorous, publishable empirical or analytical studies for top-tier accounting and economics journals (like JAE). It focuses heavily on achieving causal identification by mastering techniques such as Difference-in-Differences (DiD), Instrumental Variables (IV), Regression Discontinuity (RDD), and event studies, ensuring the study design credibly supports the economic prediction.

A comprehensive guide for authors revising manuscripts for the Journal of Accounting and Economics (JAE). It details how to structure the point-by-point response letter, emphasizing the critical need to address the editor's concerns and incorporate robust empirical evidence (identification, mechanism, and alternative tests) to satisfy economics-trained reviewers.

This guide outlines the rigorous standards for preparing empirical tables and figures for top-tier academic journals, such as the Journal of Accounting and Economics (JAE). It covers the entire research workflow, including variable definition, sample construction, descriptive statistics, correlation matrices, advanced regressions, and event studies. The goal is to ensure all exhibits are self-contained, reproducible, and meet strict academic reviewer expectations.

Comprehensive guidelines for preparing and reporting complex empirical evidence across various methodologies (SEM, econometrics, design science, qualitative). This guide ensures results meet the high academic standards of top-tier journals by emphasizing theoretical traceability, statistical rigor, and required data transparency, including full correlation/covariance matrices.

A comprehensive guide detailing best practices for creating self-contained, professional, and publication-ready exhibits (tables, figures, matrices) for scholarly manuscripts. It emphasizes making the body text standalone, adhering to journal-specific styles (e.g., APA, JAIS), and presenting complex data (like SEM results) clearly for rigorous peer review.

This skill provides a comprehensive guide for authors targeting JAMA Cardiology. It helps authors evaluate the suitability of cardiovascular trials, outcomes, and registry studies against the journal's high standards. It covers required endpoints, reporting guidelines (e.g., CONSORT, STROBE), house style, and submission prerequisites, aiding in optimizing manuscript fit before submission.