Duane B. Kennedy, Byron Y. Song, Theophanis C. Stratopoulos
{"title":"Does Industry Classification Matter in IT Business Value Research?","authors":"Duane B. Kennedy, Byron Y. Song, Theophanis C. Stratopoulos","doi":"10.2139/ssrn.3919658","DOIUrl":null,"url":null,"abstract":"Studies which examine the effect of IT on firm performance make the implicit assumption that the choice of industry classification (e.g., SIC instead of NAICS) and the level of aggregation (e.g., 2-digit SIC instead of 4-digit SIC) is unlikely to affect the results. Given that practically none of the studies in our literature review has tested the robustness of their results to an alternative industry classification method, we do not know whether this choice matters (i.e., we don’t know whether the evidence generated from this stream of research is robust). To answer this question, we replicated three studies (Bharadwaj 2000; Chae et al. 2014; Santhanam and Hartono 2003) and found that results are likely to differ if we change the classification method and/or the level of aggregation within a given industry classification method. We encourage IT researchers to replicate prior studies to assess the sensitivity of their results to such choices as well as encouraging future studies to consider implementing robustness checks. The need to consider such robustness checks spans all fields (e.g., accounting, strategic management, and marketing) that use statistical analysis which requires control for role of industry.","PeriodicalId":11837,"journal":{"name":"ERN: Other IO: Empirical Studies of Firms & Markets (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Other IO: Empirical Studies of Firms & Markets (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3919658","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Studies which examine the effect of IT on firm performance make the implicit assumption that the choice of industry classification (e.g., SIC instead of NAICS) and the level of aggregation (e.g., 2-digit SIC instead of 4-digit SIC) is unlikely to affect the results. Given that practically none of the studies in our literature review has tested the robustness of their results to an alternative industry classification method, we do not know whether this choice matters (i.e., we don’t know whether the evidence generated from this stream of research is robust). To answer this question, we replicated three studies (Bharadwaj 2000; Chae et al. 2014; Santhanam and Hartono 2003) and found that results are likely to differ if we change the classification method and/or the level of aggregation within a given industry classification method. We encourage IT researchers to replicate prior studies to assess the sensitivity of their results to such choices as well as encouraging future studies to consider implementing robustness checks. The need to consider such robustness checks spans all fields (e.g., accounting, strategic management, and marketing) that use statistical analysis which requires control for role of industry.
检验信息技术对企业绩效影响的研究隐含了一个假设,即行业分类的选择(例如,使用SIC而不是NAICS)和聚合水平(例如,使用2位数的SIC而不是4位数的SIC)不太可能影响结果。鉴于我们的文献综述中几乎没有一项研究对另一种行业分类方法的结果进行了稳健性测试,我们不知道这种选择是否重要(即,我们不知道从这一研究流中产生的证据是否可靠)。为了回答这个问题,我们重复了三项研究(Bharadwaj 2000;Chae et al. 2014;Santhanam and Hartono 2003),并发现如果我们改变分类方法和/或给定行业分类方法内的聚合水平,结果可能会有所不同。我们鼓励IT研究人员重复先前的研究,以评估其结果对这些选择的敏感性,并鼓励未来的研究考虑实施稳健性检查。考虑这种稳健性检查的需要跨越所有使用统计分析的领域(例如,会计,战略管理和市场营销),这需要对行业角色进行控制。