Skill UI

This guide details the rigorous standards for creating empirical tables and figures in academic marketing science (JAMS style). It covers building conceptual models, structural path coefficient tables, measurement validity checks, and creating highly actionable 'managerial exhibits' that translate statistical estimates into decision-making insights, ensuring all work is self-contained and adheres to APA guidelines.

A comprehensive methodology guide for designing rigorous multi-country or cross-cultural studies, essential for international marketing research. It covers critical steps such as country selection criteria, ensuring construct, translation, and sampling equivalence, and planning for measurement invariance (MGCFA). It guides researchers through advanced designs including cross-cultural experiments, multi-level estimation, and handling secondary export/entry-mode data.

A comprehensive guide for conducting and reporting rigorous statistical analysis for academic marketing manuscripts, particularly tailored for the Journal of Marketing (JM) standards. It covers selecting appropriate estimators for various designs (e.g., panel, choice, field experiments), managing identification, testing robustness, and adhering to the mandatory reporting of p-values, standard errors, and managerial effect sizes. Also covers data replication and advanced econometric techniques.

A comprehensive guide for researchers conducting advanced data analysis and reporting for top marketing journals. It details selecting the appropriate econometric estimator (e.g., ANOVA, DiD, IV, mediation models) based on the study design (experimental, observational, panel). It emphasizes meeting rigorous journal mandates, including exact p-values, standard errors, and effect sizes, and linking statistical findings to practical managerial claims.

This guide assists researchers in aligning their study design—whether behavioral (lab/field experiments) or modeling-econometric (IV/DiD/RDD)—with the rigorous standards required by the Journal of Marketing Research (JMR). It covers best practices for causal identification, power analysis, structural estimation, and meeting journal-level expectations like replication and Web Appendix planning.

This skill provides a comprehensive guide for authors targeting the Journal of Marketing Research (JMR). It analyzes the journal's demanding standards for methodological rigor, covering quantitative modeling, behavioral experiments, and design validity. Use this tool to assess if your manuscript's contribution, structure, and evidence base meet JMR's high academic bar, or to suggest more appropriate alternative venues.

A comprehensive guide for authors responding to major revisions in academic journals, particularly in policy and marketing research. It teaches how to systematically convert vague reviewer demands (e.g., "improve contribution") into concrete, visible analytical work, ensuring the response is both methodologically rigorous and policy-relevant.

This comprehensive guide assists authors in developing rigorous methodology sections for academic papers in Marketing Science. It covers advanced techniques such as structural econometrics, causal ML, dynamic games, and quasi-experiments. Key focus areas include ensuring model identifiability, specifying estimators (GMM, MLE), and rigorously defending exogeneity assumptions.

A guide for transforming abstract marketing phenomena into rigorous, mathematically testable models. It covers both analytical (game-theoretic) and structural econometric approaches, emphasizing the specification of primitives, deriving equilibria, and establishing clear identification arguments for academic research.