Skill UI

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.

This guide helps researchers sharpen and validate their research questions to ensure they meet the rigorous standards of top marketing journals (like JM). It focuses on testing for substantive importance, dual relevance (bridging theory and practice), and overall fit, helping users differentiate if their work belongs in JM, JMR, Marketing Science, or elsewhere. It emphasizes an empirics-first approach.

This guide provides a structured methodology for designing a comprehensive robustness suite for high-stakes academic papers, particularly in monetary economics and banking. Instead of running arbitrary checks, it maps diagnostic tests directly to named econometric threats (e.g., shock contamination, specification dependence, inference understatement, regime shifts), ensuring the credibility and rigor of empirical findings.

This skill guides the structuring of theoretical and conceptual frameworks for academic manuscripts, particularly for journals focusing on family science. It helps researchers move beyond simply listing correlations by defining explicit concepts, identifying underlying family mechanisms (e.g., stress process, life course, ecological), and deriving testable hypotheses and scope conditions. It is crucial for transforming empirical findings into a robust, theory-driven contribution.

This skill helps researchers pressure-test whether their project genuinely advances the understanding of families, couples, and kinship, aligning it with the scope of top-tier family science journals. It guides users on determining the core family-science contribution, defining the interdisciplinary stakes, selecting the appropriate format (full article vs. brief report), and refining the scope for maximum impact.

This comprehensive guide helps researchers move beyond descriptive correlations to build rigorous, theory-driven manuscripts for top-tier IS journals. It outlines how to structure theoretical arguments based on specific research styles, including IT business value mechanisms, platform economics, behavioral models, and economic incentives, emphasizing the derivation of hypotheses and comparative statics before empirical testing.

A comprehensive guide for building robust, testable theoretical frameworks for submissions to the Journal of Marketing Research (JMR). It distinguishes between deriving behavioral mechanisms (mediators, processes) and specifying structural/econometric primitives and identification arguments, ensuring the research contribution meets academic rigor.

This guide helps researchers evaluate if a marketing topic meets the high academic standards of top journals like the Journal of Marketing Research (JMR). It provides a dual-bar test, requiring both methodological rigor (e.g., causal identification, experimental design) and substantive contribution (new insights). It also helps distinguish the appropriate venue among major marketing journals (JM, MS, JCR).

A comprehensive guide for structuring rigorous academic research in management studies. It helps researchers align theoretical claims (causal, exploratory, mechanism testing) with appropriate methods—including qualitative, quantitative, and multi-method designs. The guide covers advanced topics such as addressing common-method bias, endogeneity, and cross-level analysis, ensuring methodological rigor for top-tier publications.

A guide for integrating behavioral theory into rigorous empirical studies. It outlines the necessary steps to move beyond descriptive findings of irrationality by constructing a statistically identifiable behavioral model (e.g., incorporating loss aversion parameters) and testing it against rational baselines using controlled, incentive-compatible experimental designs. Essential for submitting papers requiring model explanation of behavioral biases.

This skill is designed for advanced academic writing, helping users transform vague model findings into precise, testable mathematical propositions or theorems. It guides the rigorous structuring of proofs, ensuring logical completeness, correctly handling boundary conditions, and separating detailed derivations into an appendix, meeting the standards of top-tier academic journals.

Details the rigorous, masked peer review process for top academic journals. It outlines the critical "dual gate" criteria—theoretical contribution and methodological rigor—and common desk-reject patterns. Use this guide to stress-test your manuscript, structure your arguments, and set realistic expectations for submission and revision rounds.