Annamina Rieder, Saurav Chakraborty, Sandeep Goyal, Donald J Berndt
{"title":"A critical realist approach to agent-based modeling: Unlocking prediction in non-positivist paradigms","authors":"Annamina Rieder, Saurav Chakraborty, Sandeep Goyal, Donald J Berndt","doi":"10.1177/02683962241280657","DOIUrl":null,"url":null,"abstract":"Information systems (IS) scholarship and practice aim to predict phenomena and outcomes of IS use. These phenomena of IS use are typically set in multi-leveled, dynamic, and complex contexts that lend explanation to the non-positivist tradition in IS research. However, limited methodological options exist to make predictions. In this research, we propose stratified agent-based modeling, a step-by-step approach that enables prediction in non-positivist paradigms. Drawing upon the critical realist philosophy of science, which suggests ontological stratification and assumes open systems, we adopt a retroduction-based explanation formation and agent-based modeling to simulate different potential states of a complex system. The critical step in combining critical realism with agent-based modeling involves identifying and codifying the underlying generative mechanisms (i.e., causal powers) into various components of the agent-based model. We propose four steps toward prediction under the critical realist paradigm: (1) capturing the phenomenon, (2) identifying the generative mechanism, (3) building the agent-based model, and (4) simulating states of the system. We present an exemplar of our proposed approach that investigates the effectiveness of strategies to combat malicious content propagation in social networks.","PeriodicalId":50178,"journal":{"name":"Journal of Information Technology","volume":null,"pages":null},"PeriodicalIF":5.8000,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Information Technology","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1177/02683962241280657","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Information systems (IS) scholarship and practice aim to predict phenomena and outcomes of IS use. These phenomena of IS use are typically set in multi-leveled, dynamic, and complex contexts that lend explanation to the non-positivist tradition in IS research. However, limited methodological options exist to make predictions. In this research, we propose stratified agent-based modeling, a step-by-step approach that enables prediction in non-positivist paradigms. Drawing upon the critical realist philosophy of science, which suggests ontological stratification and assumes open systems, we adopt a retroduction-based explanation formation and agent-based modeling to simulate different potential states of a complex system. The critical step in combining critical realism with agent-based modeling involves identifying and codifying the underlying generative mechanisms (i.e., causal powers) into various components of the agent-based model. We propose four steps toward prediction under the critical realist paradigm: (1) capturing the phenomenon, (2) identifying the generative mechanism, (3) building the agent-based model, and (4) simulating states of the system. We present an exemplar of our proposed approach that investigates the effectiveness of strategies to combat malicious content propagation in social networks.
期刊介绍:
The aim of the Journal of Information Technology (JIT) is to provide academically robust papers, research, critical reviews and opinions on the organisational, social and management issues associated with significant information-based technologies. It is designed to be read by academics, scholars, advanced students, reflective practitioners, and those seeking an update on current experience and future prospects in relation to contemporary information and communications technology themes.
JIT focuses on new research addressing technology and the management of IT, including strategy, change, infrastructure, human resources, sourcing, system development and implementation, communications, technology developments, technology futures, national policies and standards. It also publishes articles that advance our understanding and application of research approaches and methods.