School of the Built Environment, Heriot-Watt University, Edinburgh, UK.
Ergonomics. 2010 Oct;53(10):1175-86. doi: 10.1080/00140139.2010.513453.
Since 1958 more than 80 journal papers from the mainstream ergonomics literature have used either the words 'complex' or 'complexity' in their titles. Of those, more than 90% have been published in only the past 20 years. This observation communicates something interesting about the way in which contemporary ergonomics problems are being understood. The study of complexity itself derives from non-linear mathematics but many of its core concepts have found analogies in numerous non-mathematical domains. Set against this cross-disciplinary background, the current paper aims to provide a similar initial mapping to the field of ergonomics. In it, the ergonomics problem space, complexity metrics and powerful concepts such as emergence raise complexity to the status of an important contingency factor in achieving a match between ergonomics problems and ergonomics methods. The concept of relative predictive efficiency is used to illustrate how this match could be achieved in practice. What is clear overall is that a major source of, and solution to, complexity are the humans in systems. Understanding complexity on its own terms offers the potential to leverage disproportionate effects from ergonomics interventions and to tighten up the often loose usage of the term in the titles of ergonomics papers. STATEMENT OF RELEVANCE: This paper reviews and discusses concepts from the study of complexity and maps them to ergonomics problems and methods. It concludes that humans are a major source of and solution to complexity in systems and that complexity is a powerful contingency factor, which should be considered to ensure that ergonomics approaches match the true nature of ergonomics problems.
自 1958 年以来,主流人机工程学文献中有 80 多篇期刊论文在其标题中使用了“复杂”或“复杂性”一词。其中,超过 90%是在过去 20 年发表的。这一观察结果反映了当代人机工程学问题的理解方式的有趣之处。复杂性本身的研究源于非线性数学,但它的许多核心概念在许多非数学领域都找到了类似之处。在这种跨学科的背景下,本文旨在为人机工程学领域提供类似的初步映射。在本文中,人机工程学问题空间、复杂性度量以及涌现等强大概念将复杂性提升到了一个重要的权变因素的地位,以实现人机工程学问题与方法之间的匹配。相对预测效率的概念被用来阐明如何在实践中实现这种匹配。总体而言,系统中人类是复杂性的主要来源和解决方案。从复杂性本身的角度来理解它,有可能利用人机工程学干预的不成比例的效果,并收紧人机工程学论文标题中对该术语的常用用法。相关性声明:本文回顾和讨论了复杂性研究中的概念,并将其映射到人机工程学问题和方法上。本文得出结论,人类是系统中复杂性的主要来源和解决方案,复杂性是一个强大的权变因素,应该加以考虑,以确保人机工程学方法与真正的人机工程学问题的本质相匹配。