Pratyush Nidhi Sharma , Marko Sarstedt , Christian M. Ringle , Jun-Hwa Cheah , Anne Herfurth , Joseph F. Hair
{"title":"利用预测导向技术提高行为管理信息系统研究可复制性的框架","authors":"Pratyush Nidhi Sharma , Marko Sarstedt , Christian M. Ringle , Jun-Hwa Cheah , Anne Herfurth , Joseph F. Hair","doi":"10.1016/j.ijinfomgt.2024.102805","DOIUrl":null,"url":null,"abstract":"<div><p>The ongoing scientific discourse surrounding the replication crisis in behavioral research, including management information systems (MIS) research, underscores the importance of innovative and rigorous approaches to theory development and validation. This article proposes the EP-mixed framework, which addresses the necessity of an ontological distinction between explanation and prediction in MIS theories, along with the epistemological challenges associated with conflating exploratory and confirmatory research during the design of robust, replicable theories. EP-mixed refers to theories that explain and predict (i.e., EP theories) developed using a mixed mode that combines the strengths of both exploratory and confirmatory research. The EP-mixed framework guides researchers in selecting appropriate analytical approaches based on their research goals and the type of theory being developed. While it can be applied in conjunction with a broad spectrum of statistical methods to enhance the robustness and replicability of MIS theories, we elaborate on the predictive analytic tools available in partial least squares structural equation modeling (PLS-SEM) as an exemplar for operationalizing the framework.</p></div>","PeriodicalId":48422,"journal":{"name":"International Journal of Information Management","volume":"78 ","pages":"Article 102805"},"PeriodicalIF":20.1000,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A framework for enhancing the replicability of behavioral MIS research using prediction oriented techniques\",\"authors\":\"Pratyush Nidhi Sharma , Marko Sarstedt , Christian M. Ringle , Jun-Hwa Cheah , Anne Herfurth , Joseph F. Hair\",\"doi\":\"10.1016/j.ijinfomgt.2024.102805\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The ongoing scientific discourse surrounding the replication crisis in behavioral research, including management information systems (MIS) research, underscores the importance of innovative and rigorous approaches to theory development and validation. This article proposes the EP-mixed framework, which addresses the necessity of an ontological distinction between explanation and prediction in MIS theories, along with the epistemological challenges associated with conflating exploratory and confirmatory research during the design of robust, replicable theories. EP-mixed refers to theories that explain and predict (i.e., EP theories) developed using a mixed mode that combines the strengths of both exploratory and confirmatory research. The EP-mixed framework guides researchers in selecting appropriate analytical approaches based on their research goals and the type of theory being developed. While it can be applied in conjunction with a broad spectrum of statistical methods to enhance the robustness and replicability of MIS theories, we elaborate on the predictive analytic tools available in partial least squares structural equation modeling (PLS-SEM) as an exemplar for operationalizing the framework.</p></div>\",\"PeriodicalId\":48422,\"journal\":{\"name\":\"International Journal of Information Management\",\"volume\":\"78 \",\"pages\":\"Article 102805\"},\"PeriodicalIF\":20.1000,\"publicationDate\":\"2024-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Information Management\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0268401224000537\",\"RegionNum\":1,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Information Management","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0268401224000537","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0
摘要
围绕行为研究(包括管理信息系统(MIS)研究)中的复制危机正在进行的科学讨论强调了创新和严谨的理论开发与验证方法的重要性。本文提出了 EP-ixed 框架,该框架解决了 MIS 理论中解释与预测之间本体论区分的必要性,以及在设计稳健、可复制的理论过程中混淆探索性研究与确认性研究所带来的认识论挑战。EP-mixed指的是使用混合模式开发的解释和预测理论(即EP理论),该模式结合了探索性研究和证实性研究的优势。EP- 混合框架指导研究人员根据其研究目标和正在开发的理论类型选择适当的分析方法。虽然该框架可与多种统计方法结合使用,以提高管理信息系统理论的稳健性和可复制性,但我们还是以偏最小二乘结构方程模型(PLS-SEM)中的预测分析工具为例,详细阐述了该框架的操作方法。
A framework for enhancing the replicability of behavioral MIS research using prediction oriented techniques
The ongoing scientific discourse surrounding the replication crisis in behavioral research, including management information systems (MIS) research, underscores the importance of innovative and rigorous approaches to theory development and validation. This article proposes the EP-mixed framework, which addresses the necessity of an ontological distinction between explanation and prediction in MIS theories, along with the epistemological challenges associated with conflating exploratory and confirmatory research during the design of robust, replicable theories. EP-mixed refers to theories that explain and predict (i.e., EP theories) developed using a mixed mode that combines the strengths of both exploratory and confirmatory research. The EP-mixed framework guides researchers in selecting appropriate analytical approaches based on their research goals and the type of theory being developed. While it can be applied in conjunction with a broad spectrum of statistical methods to enhance the robustness and replicability of MIS theories, we elaborate on the predictive analytic tools available in partial least squares structural equation modeling (PLS-SEM) as an exemplar for operationalizing the framework.
期刊介绍:
The International Journal of Information Management (IJIM) is a distinguished, international, and peer-reviewed journal dedicated to providing its readers with top-notch analysis and discussions within the evolving field of information management. Key features of the journal include:
Comprehensive Coverage:
IJIM keeps readers informed with major papers, reports, and reviews.
Topical Relevance:
The journal remains current and relevant through Viewpoint articles and regular features like Research Notes, Case Studies, and a Reviews section, ensuring readers are updated on contemporary issues.
Focus on Quality:
IJIM prioritizes high-quality papers that address contemporary issues in information management.