Skill UI

This guide helps researchers select and defend the appropriate empirical methodology for Operations Management (OM) studies. It covers diverse design types—including surveys, archival data analysis, behavioral experiments, field studies, and intervention-based research—ensuring the design is observation-grounded, matches the operational claim, and anticipates rigorous methodological checks.

A comprehensive guide detailing the mandatory pre-submission steps for submitting manuscripts to the Journal of Operations Management (JOM) via the Wiley Research Exchange (ReX) portal. It covers departmental routing, cover letter protocols, double-anonymization rules, required checklists, formatting compliance, and handling disclosure requirements to ensure successful initial review.

This guide helps researchers rigorously evaluate whether their operations management or supply chain research topic is suitable for the Journal of Operations Management (JOM). It employs a four-screen test to ensure the topic meets academic criteria: operations must be the core phenomenon, the study must be empirically grounded, it must advance theory, and it must maintain practical relevance for managers.

This skill acts as a comprehensive workflow router for submitting empirical research to the Journal of Operations Management (JOM). It guides researchers through every stage of the manuscript lifecycle, from initial topic selection and theory development to rigorous data analysis, contribution framing, and point-by-point rebuttal. It does not replace specialized skills but diagnoses the current bottleneck and suggests the appropriate next step in the submission process.

This guide provides detailed instructions for authors preparing empirical manuscripts for the Journal of Operations Management (JOM). It emphasizes front-loading the core operations argument, structuring content for a dual audience (academics and practitioners), and adhering to rigorous academic publishing standards, including APA citation and strict text-overlap rules.

This guide details the rigorous requirements for publishing in top-tier quantitative management journals. It specifically targets research outputs that utilize mathematical models, theoretical proofs, and computational algorithms (e.g., operations research, decision theory). It strongly advises against purely empirical surveys or case studies, emphasizing methodological contribution over policy implication.

This comprehensive skill guides researchers through assessing whether their operations and supply chain manuscript meets the rigorous standards of the Journal of Operations Management (JOM). It covers key areas including theoretical framing, empirical rigor (e.g., common-method bias, identification), structural best practices, and common desk-reject triggers, helping authors refine their work for high-impact academic publishing.

This guide helps researchers evaluate if their operations management (OM) paper is suitable for the Manufacturing and Service Operations Management (M&SOM) journal. It provides detailed criteria on scope, required operational insight, method rigor (analytical or empirical), and structural house style, ensuring the core contribution addresses practical operations problems rather than just technical methodology.

A comprehensive guide detailing the methodological standards for conducting high-impact research in Manufacturing and Service Operations Management. It covers both analytical modeling (proofs, sensitivity) and empirical studies (identification, robustness), emphasizing the necessity of full data and code replicability for published findings.

This guide instructs authors on how to strategically position their research manuscript within the established body of Operations Management (OM) literature. Instead of claiming an unstudied 'void,' the focus is on joining and advancing specific 'operational conversations' within canonical OM streams (e.g., queueing, supply chain, revenue management). It emphasizes differentiating contributions based on novel operational mechanisms or decision levers, ensuring the paper's fit is clear to expert reviewers and editors.

A comprehensive guide for researchers writing about Manufacturing and Service Operations Management (M&SOM). It mandates that the method chosen must be dictated by the core operational decision. Provides detailed frameworks for both the analytical lane (e.g., stochastic optimization, queueing theory, game theory) and the empirical/causal lane (e.g., Difference-in-Differences, Instrumental Variables), ensuring the research delivers actionable operational insights.

This guide provides a critical framework for academic authorship targeting top-tier Operations Management journals. It instructs researchers on how to centralize the operational decision, select the appropriate analytical or empirical 'lane,' and correctly map the research question to a specific editorial department, ensuring the work meets the journal's core scope before any modeling or data analysis begins.