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准备、开展和分析德尔菲调查:跨学科实践、新方向与进展

Preparing, conducting, and analyzing Delphi surveys: Cross-disciplinary practices, new directions, and advancements.

作者信息

Beiderbeck Daniel, Frevel Nicolas, von der Gracht Heiko A, Schmidt Sascha L, Schweitzer Vera M

机构信息

Center for Sports and Management, WHU, Otto Beisheim School of Management, Erkrather Str. 224a, 40233 Düsseldorf, Germany.

School of International Business and Entrepreneurship, Steinbeis University, Kalkofenstr. 53, 71083 Herrenberg, Germany.

出版信息

MethodsX. 2021 May 28;8:101401. doi: 10.1016/j.mex.2021.101401. eCollection 2021.

Abstract

Delphi is a scientific method to organize and structure an expert discussion aiming to generate insights on controversial topics with limited information. The technique has seen a rise in publication frequency in various disciplines, especially over the past decades. In April 2021, the term yielded 28,200 search hits in Google Scholar for the past five years alone. Given the increasing level of uncertainty caused by rapid technological and social change around the globe, collective expert opinions and assessments are likely to gain even more importance. Therefore, the paper at hand presents technical recommendations derived from a Delphi study that was conducted amid the outbreak of the COVID-19 pandemic in 2020.•The paper comprehensively demonstrates how to prepare, conduct, and analyze a Delphi study. In this regard, it combines several methodological advancements of the recent past (e.g., dissent analyses, scenario analyses) with state-of-the-art impulses from other disciplines like strategic management (e.g., fuzzy clustering), psychology (e.g., sentiment analyses), or clinical trials (e.g., consensus measurement).•By offering insights on the variety of possibilities to exploit Delphi-based data, we aim to support researchers across all disciplines in conducting Delphi studies and potentially expand and improve the method's field of application.

摘要

德尔菲法是一种科学方法,用于组织和构建专家讨论,旨在在信息有限的情况下就有争议的话题产生深刻见解。该技术在各个学科中的发表频率都有所上升,尤其是在过去几十年。仅在2021年4月,“德尔菲法”这个词在谷歌学术上过去五年就有28200条搜索结果。鉴于全球快速的技术和社会变革导致不确定性增加,专家的集体意见和评估可能会变得更加重要。因此,本文提出了2020年新冠疫情爆发期间进行的一项德尔菲研究得出的技术建议。

•本文全面展示了如何准备、开展和分析德尔菲研究。在这方面,它将近期的一些方法改进(如不同意见分析、情景分析)与来自战略管理(如模糊聚类)、心理学(如情感分析)或临床试验(如共识度量)等其他学科的最新理念相结合。

•通过提供关于利用基于德尔菲法的数据的各种可能性的见解,我们旨在支持所有学科的研究人员开展德尔菲研究,并有可能扩大和改进该方法的应用领域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be1e/8374446/d9a248d03623/fx1.jpg

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