Growth Strategies - Crossref Bibliographic Metadata
收藏DataONE2025-05-07 更新2025-11-01 收录
下载链接:
https://search.dataone.org/view/sha256:7649a367f453a0596e6e6cf650c48d62fe39f26ce745e6624f2854d0d0cc48eb
下载链接
链接失效反馈官方服务:
资源简介:
This dataset provides detailed bibliographic metadata records for scholarly publications related to 'Growth Strategies', as retrieved from Crossref.org. This metadata corpus facilitates in-depth exploration of the academic discourse surrounding various approaches to organizational expansion and development. Contextual Overview of Growth Strategies: 1. Definition and Context: Growth Strategies encompass the plans and actions organizations implement to expand their business in terms of market share, revenue, assets, or geographic reach. These strategies can be internal (e.g., market penetration, product development, market development) or external (e.g., diversification, mergers, acquisitions, strategic alliances). The pursuit of growth is a fundamental driver for most organizations, shaped by competitive pressures, shareholder expectations, and opportunities for innovation and market capture. 2. Strengths and Weaknesses: Successful growth strategies can lead to increased profitability, enhanced market power, economies of scale, and greater stakeholder value. They can also attract talent and foster innovation. However, growth initiatives often entail significant risks, including overstretching resources, loss of focus, cultural integration challenges (in M&A), and misjudging market demand or competitive responses. Not all growth is profitable, and rapid expansion can strain organizational capabilities if not managed effectively. 3. Relevance and Research Potential: Growth Strategies are a perennial topic in strategic management, entrepreneurship, and international business. Their relevance is amplified by dynamic markets and the constant need for adaptation and value creation. Research opportunities include exploring sustainable growth models, the role of digital platforms and ecosystems in enabling growth, growth strategies in emerging markets, managing the complexities of global expansion, and the effectiveness of different growth paths (organic vs. inorganic) under varying conditions. 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 Growth Strategies. 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 Growth Strategies. 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., (\"growth strategies\" OR \"market expansion\" ...) AND (\"business\" 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 'Growth Strategies' 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 Growth Strategies 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 Growth Strategies should consult the corresponding datasets in the Raw Extracts Dataverse and the Comparative Indices Dataverse.
创建时间:
2025-10-29



