Complexity and Information Systems Research in the Emerging Digital World

Hind Benbya, Ning Nan, Hüseyin Tanriverdi, Youngjin Yoo
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引用次数: 4

Abstract

Complexity is all around us in this increasingly digital world. Global digital infrastructure, social media, Internet of Things, robotic process automation, digital business platforms, algorithmic decision making, and other digitally enabled networks and ecosystems fuel complexity by fostering hyper-connections and mutual dependencies among human actors, technical artifacts, processes, organizations, and institutions. Complexity affects human agencies and experiences in all dimensions. Individuals and organizations turn to digitally-enabled solutions to cope with the wicked problems arising out of digitalization. In the digital world, complexity and digital solutions present new opportunities and challenges for information systems (IS) research. The purpose of this special issue is to foster the development of new IS theories on the causes, dynamics, and consequences of complexity in increasing digital sociotechnical systems. In this essay, we discuss the key theories and methods of complexity science, and illustrate emerging new IS research challenges and opportunities in complex sociotechnical systems. We also provide an overview of the five articles included in the special issue. These articles illustrate how IS researchers build on theories and methods from complexity science to study wicked problems in the emerging digital world. They also illustrate how IS researchers leverage the uniqueness of the IS context to generate new insights to contribute back to complexity science.
新兴数字世界中的复杂性和信息系统研究
在这个日益数字化的世界里,复杂性无处不在。全球数字基础设施、社交媒体、物联网、机器人流程自动化、数字业务平台、算法决策以及其他数字化网络和生态系统,通过促进人类参与者、技术工件、流程、组织和机构之间的超连接和相互依赖,加剧了复杂性。复杂性影响所有维度的人类机构和经验。个人和组织都转向数字化解决方案来应对数字化带来的棘手问题。在数字世界中,复杂性和数字解决方案为信息系统(IS)研究带来了新的机遇和挑战。本期特刊的目的是促进关于日益增长的数字社会技术系统复杂性的原因、动态和后果的新信息系统理论的发展。在本文中,我们讨论了复杂性科学的关键理论和方法,并说明了在复杂的社会技术系统中出现的新的IS研究挑战和机遇。我们还提供特刊中包含的五篇文章的概述。这些文章说明了信息系统研究人员如何利用复杂性科学的理论和方法来研究新兴数字世界中的棘手问题。它们还说明了信息系统研究人员如何利用信息系统背景的独特性来产生新的见解,从而为复杂性科学做出贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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