{"title":"Returning the “socio” to decision support research: Expanding beyond a purely technical mindset","authors":"Cecil Eng Huang Chua , Fred Niederman","doi":"10.1016/j.dss.2024.114352","DOIUrl":null,"url":null,"abstract":"<div><div>This editorial essay argues the design science decision support literature has unduly focused on developing technical systems when organizational problem solving and decision making often require socio-technical ones. Decision making in uncertain environments requires other aspects the technical view actively suppresses, such as effectiveness and innovation. We explore this in a three-step argument. First, we show the necessity of a socio-technical mindset using the example of how cholera was demonstrated to be a waterborne disease in 1854 London in two independent investigations - one technical and one socio-technical. The insights from the socio-technical investigation were ultimately found correct; the technical one arrived at a completely wrong conclusion. Second, we argue authors are discouraged from publishing research on socio-technical design artifacts. We use spreadsheets as an example, and show developers prefer publishing their incremental contributions in other outlets. Puzzlingly, researchers prefer publishing technical design science contributions in DSS journal given their preponderance in our pages. Thus, in our third step, we argue the lack of socio-technical design science research arises from a mismatch of evaluation criteria. We suggest DSS journal cultivate a subset of editorial board members with a socio-technical mindset to apply the appropriate criteria while encouraging submissions of this type.</div></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"188 ","pages":"Article 114352"},"PeriodicalIF":6.7000,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Decision Support Systems","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167923624001854","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
This editorial essay argues the design science decision support literature has unduly focused on developing technical systems when organizational problem solving and decision making often require socio-technical ones. Decision making in uncertain environments requires other aspects the technical view actively suppresses, such as effectiveness and innovation. We explore this in a three-step argument. First, we show the necessity of a socio-technical mindset using the example of how cholera was demonstrated to be a waterborne disease in 1854 London in two independent investigations - one technical and one socio-technical. The insights from the socio-technical investigation were ultimately found correct; the technical one arrived at a completely wrong conclusion. Second, we argue authors are discouraged from publishing research on socio-technical design artifacts. We use spreadsheets as an example, and show developers prefer publishing their incremental contributions in other outlets. Puzzlingly, researchers prefer publishing technical design science contributions in DSS journal given their preponderance in our pages. Thus, in our third step, we argue the lack of socio-technical design science research arises from a mismatch of evaluation criteria. We suggest DSS journal cultivate a subset of editorial board members with a socio-technical mindset to apply the appropriate criteria while encouraging submissions of this type.
期刊介绍:
The common thread of articles published in Decision Support Systems is their relevance to theoretical and technical issues in the support of enhanced decision making. The areas addressed may include foundations, functionality, interfaces, implementation, impacts, and evaluation of decision support systems (DSSs).