A Framework and Guidelines for Context-Specific Theorizing in Information Systems Research

• 成果类型: Article
• 署名作者: Hong, Weiyin; Chan, Frank K. Y.; Thong, James Y. L.; Chasalow, Lewis C.; Dhillon, Gurpreet
• 署名单位: Hong Kong University of Science & Technology; Nevada System of Higher Education (NSHE); University of Nevada Las Vegas; ESSEC Business School; Virginia Commonwealth University
• 刊物名称: INFORMATION SYSTEMS RESEARCH
• ISSN/ISSBN: 1047-7047
• DOI: 10.1287/isre.2013.0501
• 发表日期: 2014
• 页码: 111-136
• 关键词: technology adoption decisions; computer self-efficacy; user acceptance; perceived ease; ORGANIZATIONAL-BEHAVIOR; MODEL; metaanalysis; CONTINUANCE; extension; beliefs

摘要

This paper discusses the value of context in theory development in information systems (IS) research. We examine how prior research has incorporated context in theorizing and develop a framework to classify existing approaches to contextualization. In addition, we expound on a decomposition approach to contextualization and put forth a set of guidelines for developing context-specific models. We illustrate the application of the guidelines by constructing and comparing various context-specific variations of the technology acceptance model (TAM)-i.e., the decomposed TAM that incorporates interaction effects between context-specific factors, the extended TAM with context-specific antecedents, and the integrated TAM that incorporates mediated moderation and moderated mediation effects of context-specific factors. We tested the models on 972 individuals in two technology usage contexts: a digital library and an agile Web portal. The results show that the decomposed TAM provides a better understanding of the contexts by revealing the direct and interaction effects of context-specific factors on behavioral intention that are not mediated by the TAM constructs of perceived usefulness and perceived ease of use. This work contributes to the ongoing discussion about the importance of context in theory development and provides guidance for context-specific theorizing in IS research.