Scenario Planning - Crossref Bibliographic Metadata

This dataset provides detailed bibliographic metadata records for scholarly publications related to 'Scenario Planning', as retrieved from Crossref.org. This metadata corpus facilitates in-depth exploration of the academic discourse surrounding Scenario Planning. Contextual Overview of Scenario Planning: 1. Definition and Context: Scenario Planning is a strategic foresight method used by organizations to explore and prepare for multiple plausible future environments. Its primary purpose is not to predict the future, but to challenge assumptions, enhance understanding of uncertainties, and develop robust strategies adaptable to different conditions. While its roots trace back to military and corporate planning in the mid-20th century (notably at Shell), its application has broadened across sectors facing high uncertainty. 2. Strengths and Weaknesses: Key strengths include fostering strategic thinking, improving organizational learning, enhancing adaptability, and identifying early warning signals. It encourages a proactive stance towards uncertainty. Challenges involve the resource intensity (time, expertise), potential for alysis paralysis if scenarios are too complex or numerous, and difficulty in translating scenario insights into actionable strategies. The quality of scenarios heavily depends on the diversity of perspectives involved and the rigor of the process. 3. Relevance and Research Potential: Scenario Planning's relevance is amplified in today's volatile, uncertain, complex, and ambiguous (VUCA) world, aiding in navigating issues like climate change, technological disruption, and geopolitical instability. It draws from fields like futures studies and decision theory. Research opportunities persist in integrating quantitative models with qualitative scenario narratives, its application in SMEs, assessing its impact on decision-making quality, and developing agile scenario updating mechanisms in rapidly changing environments. Dataset Structure and Content: The dataset consists of one or more archives. Each archive contains a series of approximately 850 monthly folders (e.g., spanning from January 1950 to January 2025), reflecting a granular month-by-month process of metadata retrieval and curation for Scenario Planning. Within each monthly folder, users will find several JSON files documenting the search and filtering process for that specific month: term_results/: A subfolder containing JSON files for results of initial broad keyword searches related to Scenario Planning. merged_results.json: Aggregated results from these individual term searches before advanced filtering. filtered_results.json: Results after applying a more specific, complex Boolean query (e.g., (\"scenario planning\" OR \"scenario analysis\" ...) AND (\"strategic\" OR ...)) and exact phrase matching to refine relevance. The exact query used is detailed within this file. final_results.json: This is the primary file of interest for most users. It contains the curated, deduplicated (by DOI) list of unique publication metadata records deemed most relevant to 'Scenario Planning' for that specific month. Includes fields like Title, Authors, DOI, Publication Date, Source Title, Abstract (if available from Crossref). statistics_results.json: Summary statistics of the search and filtering process for the month. This granular monthly structure allows researchers to trace the evolution of academic discourse on Scenario Planning and identify relevant publications with high temporal precision. For an overview of the general retrieval methodology, refer to the parent Dataverse description (Management Tool Bibliographic Metadata (Crossref)). Users interested in aggregated publication counts or trend analysis for Scenario Planning should consult the corresponding datasets in the Raw Extracts Dataverse and the Comparative Indices Dataverse.