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Managing Delphi Surveys Using Nonparametric Statistical Techniques *
Author(s) -
Schmidt Roy C.
Publication year - 1997
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1997.tb01330.x
Subject(s) - delphi method , ranking (information retrieval) , computer science , delphi , nonparametric statistics , data science , strengths and weaknesses , field (mathematics) , data collection , key (lock) , management science , data mining , operations research , information retrieval , econometrics , statistics , artificial intelligence , mathematics , psychology , engineering , social psychology , computer security , pure mathematics , operating system
Information systems researchers have often turned to a variant of the Delphi survey technique to support their research of key issues in their field. Two particular weaknesses of past studies using this approach have been a lack of a definitive method for conducting the research and a lack of statistical support for the conclusions drawn by the researchers. In this paper, the author presents a method, based on nonparametric statistical techniques, to conduct ranking‐type Delphi surveys, perform analysis, and report results. The author takes this one step further by illustrating an actual analysis of a Delphi survey. The analysis is compared to results that were presented without the benefit of the author's approach. This paper shows that use of the advocated approach can streamline and strengthen studies, improve the validity of results, and thus better serve the consumers of the research findings. Since the ranking‐type Delphi is so popular among information systems researchers, a consistent method is needed to apply to their data collection, analysis, and reporting of results. This paper provides such a method in concise form and illustrates the use of the method in a manner affording comparison between it and previous practice.