Business students beginning a research project must learn how to identify relevant scholarly publications, distinguish disciplinary sources, construct database searches, and report the decisions behind their literature reviews. These tasks can be difficult because journal classification systems and bibliographic databases organize scholarly information differently. This paper introduces Journal Basket, a browser-based tool developed to help business students conduct journal-bounded literature searches and currently available in beta. Journal Basket enables users to construct journal collections from the Australian Business Deans Council (ABDC) Journal Quality List, choose from 42 business discipline presets, entire ABDC fields or the Financial Times FT50 list, apply journal rating thresholds, and generate search expressions for Scopus, Web of Science and Business Source. Users can also inspect and modify journal collections, download journal inventories, and generate methodological descriptions and deterministic identifiers for journal selections. Companion learning resources use explanations, examples and interactive activities to teach review methods, database choice, referencing and the use of contemporary AI tools. Drawing on the journal-basket concept used by Litbaskets.io, I describe the educational motivation, design rationale, technical architecture, and practical workflow of Journal Basket. I distinguish reproducing a journal collection from reproducing an entire database search and discuss the limitations of journal rankings as search boundaries. The paper addresses scholarly information retrieval through a workflow for defining journal boundaries, generating database-specific queries and documenting search decisions.

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