Advancing Next-Generation Multimethod Research in Information Systems: A Framework and Some Recommendations for Authors and Evaluators

• 成果类型: Article
• 署名作者: Sarker, Suprateek; Bala, Hillol; Hong, Yili; Kankanhalli, Atreyi; Rossi, Matti; Gu, Bin; Oestreicher-Singer, Gal
• 署名单位: University of Virginia; Indiana University System; IU Kelley School of Business; Indiana University Bloomington; University of Miami; National University of Singapore; Aalto University; Boston University; Tel Aviv University
• 刊物名称: INFORMATION SYSTEMS RESEARCH
• ISSN/ISSBN: 1047-7047
• DOI: 10.1287/isre.2025.editorial.v36.n2
• 发表日期: 2025
• 关键词: mixed-methods research; CRITICAL REALISM; management; GUIDELINES; modularity; KNOWLEDGE; product; field

摘要

The increasing complexity of sociotechnical phenomena, proliferation of diverse data sources, expanding repertoire of research methods, and broadening multiparadigmatic awareness and competence have spurred a growing interest in multimethod research in the information systems (IS) field. This editorial recognizes and celebrates the value of integrating diverse methods and offers a framework to classify multimethod research using two dimensions: (a) methodological distance-the degree of difference (proximate or distant) between methods employed in terms of characteristics such as paradigmatic assumptions, techniques, and goals; and (b) nature of integration-the extent to which the methods are combined in loosely coupled (interlayered) or tightly coupled (intertwined) ways. These dimensions yield four types of multimethod research: assembly (proximate methods with interlayered integration), blend (proximate methods with intertwined integration), bridge (distant methods with interlayered integration), and fusion (distant methods with intertwined integration). We illustrate each archetype with studies published in leading IS journals. Building on these examples, we provide actionable guidance for authors on conducting and presenting multimethod research and also offer recommendations for evaluators of multimethod work. More broadly, we call on the IS community to embrace multimethod research not as an ad hoc stack of methods, but as a systematic strategy, aligning with these recommendations related to methodological distance and nature of integration, to produce a credible, revelatory, and rich body of knowledge on multifaceted IS phenomena.