作为文献审查方法的可变科学绘图

IF 4 Q2 BUSINESS Journal of Marketing Analytics Pub Date : 2024-07-02 DOI:10.1057/s41270-024-00336-9
Przemyslaw Tomczyk, Philipp Brüggemann, Justin Paul
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引用次数: 0

摘要

本研究调查了一种用于系统分析实证研究的新型绘图方法,称为变量科学绘图(VSM)。这种方法通过纳入变量及其相互关系,增强了系统文献综述(SLR)的现有能力,超越了科学绘图(SM)等主要分析关键词、引文和作者的传统方法。我们介绍了实施 VSM 方法的逐步概念协议。随后,我们在 SLR 的 12 个阶段考察了 VSM 与 SM 相比的优势和局限性。为此,我们在对 63 篇采用 SM 方法的论文进行分析的基础上,评估了 SM 在每个阶段的实际使用情况。此外,我们还进行了专家访谈,以评估 SM 和 VSM 在相同分析阶段的实用性。值得注意的是,SLR 的结果与专家对 SM 的评估结果明显一致。研究结果表明,在 12 个阶段中,有 8 个阶段对 VSM 给予了好评。在一个阶段,专家对 SM 和 VSM 的评价相等,而在三个阶段,SM 被认为更有利。这种细致入微的评估强调了两种方法的优势和局限性。其影响延伸到科学和管理领域,为可持续土地管理的未来发展提供了宝贵的见解。总之,这项分析不仅揭示了 VSM 的潜在优势,还为指导未来的研究方法奠定了基础,以拓宽 SLR 不同阶段的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Variable science mapping as literature review method

This study investigates a novel mapping approach for the systematic analysis of empirical research, termed Variable Science Mapping (VSM). This approach enhances the current capabilities of Systematic Literature Reviews (SLRs) by incorporating variables and their interrelationships, surpassing traditional methods, such as Science Mapping (SM), which primarily analyze keywords, citations, and authorship. We present a step-by-step conceptual protocol for implementing the VSM approach. Subsequently, the strengths and limitations of VSM compared to SM are examined across 12 SLR stages. To this end, we assess the actual usage of SM for each stage based on an analysis of 63 papers employing the SM approach. Additionally, expert interviews are conducted to evaluate the utility of both SM and VSM across identical analytical stages. Notably, a distinct alignment emerged between the outcomes of the SLR and expert assessments pertaining to SM. The findings reveal VSM’s favorable ratings in eight out of 12 stages. Equivalence in expert ratings between SM and VSM surfaced in one stage, while SM was deemed more beneficial in three stages. This nuanced evaluation underscores the contextual strengths and limitations of both approaches. The implications extend to both scientific and managerial domains, offering valuable insights into the prospective advancements in SLRs. In conclusion, this analysis not only sheds light on the potential advantages of VSM but also serves as a foundation for guiding future research methodologies to widen capabilities among different SLR stages.

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来源期刊
CiteScore
5.40
自引率
16.70%
发文量
46
期刊介绍: Data has become the new ore in today’s knowledge economy. However, merely storing and reporting are not enough to thrive in today’s increasingly competitive markets. What is called for is the ability to make sense of all these oceans of data, and to apply those insights to the way companies approach their markets, adjust to changing market conditions, and respond to new competitors. Marketing analytics lies at the heart of this contemporary wave of data driven decision-making. Companies can no longer survive when they rely on gut instinct to make decisions. Strategic leverage of data is one of the few remaining sources of sustainable competitive advantage. New products can be copied faster than ever before. Staff are becoming less loyal as well as more mobile, and business centers themselves are moving across the globe in a world that is getting flatter and flatter. The Journal of Marketing Analytics brings together applied research and practice papers in this blossoming field. A unique blend of applied academic research, combined with insights from commercial best practices makes the Journal of Marketing Analytics a perfect companion for academics and practitioners alike. Academics can stay in touch with the latest developments in this field. Marketing analytics professionals can read about the latest trends, and cutting edge academic research in this discipline. The Journal of Marketing Analytics will feature applied research papers on topics like targeting, segmentation, big data, customer loyalty and lifecycle management, cross-selling, CRM, data quality management, multi-channel marketing, and marketing strategy. The Journal of Marketing Analytics aims to combine the rigor of carefully controlled scientific research methods with applicability of real world case studies. Our double blind review process ensures that papers are selected on their content and merits alone, selecting the best possible papers in this field.
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