Human-Robot Collaboration Acceptance Model: Development and Comparison for Germany, Japan, China and the USA
Human-Robot Collaboration Acceptance Model: Development and Comparison for Germany, Japan, China and the USA
复制标题
DOI：
10.1007/s12369-019-00593-0
复制
发表时间：
2019-11-05
影响因子：
4.7
通讯作者：
Nitsch, Verena
中科院分区：
文献类型：
--
作者：
Broehl, Christina;Nelles, Jochen;Nitsch, Verena
机器人在国民经济中的使用--特别是在工业化国家--正在增长。与此同时，人类和机器人之间的相互依存关系也越来越紧密：随着越来越多的组织让机器人和人类携手工作，人类和机器人正在进行直接接触。预测成功的人与机器人相互依赖的一个因素是人类对机器人的接受程度。一般来说，只有当一个创新的辅助工作系统满足人类的需求和期望时，它才被认为是有用的，并因此被接受。此外，还发现文化背景对人与机器人的互动有影响，因为人们会觉得以一种文化规范的方式与机器人互动更舒服。因此，本文旨在提出一种人-机器人协作接受模型(HRCAM)，该模型基于先前的接受模型，同时考虑了技术亲和力以及伦理、法律和社会影响。此外，还显示了四个选定国家在接受机器人方面的相似之处和不同之处--无论是与整个人类-机器人协作接受模式相比，还是与国家之间的接受情况相比。HRCAM还显示了哪些变量影响感知的有用性和感知的易用性，从而影响使用的行为意图和使用行为。对可能长期受影响的锚定变量和可能在中短期内受影响的调整变量进行了进一步的区分。因此，该模型为人类-机器人协作领域的从业者提供了提高机器人接受度的建议。
The use of robots in the national economy-especially in industrialized countries-is growing. At the same time, the interdependency between humans and robots is getting increasingly closer: they are engaging in direct contact with each other as more and more organizations let robots and humans work hand-in-hand. One factor that predicts successful human-robot interdependency is the acceptance of the robot by the human. Generally, only when an innovative assistive working system covers human needs and expectations, it is perceived to be useful and hence accepted. Furthermore, it has been found that cultural context has an impact on human-robot interaction, as people feel more comfortable interacting with a robot in a culturally normative way. Therefore this paper aims at presenting a human-robot collaboration acceptance model (HRCAM) with regard to the collaboration between humans and robots that is based on prior acceptance models, while also considering technology affinity and ethical, legal and social implications. Additionally, similarities and differences in robot acceptance are shown for four selected countries-both in comparison to the overall human-robot collaboration acceptance model and between the countries. The HRCAM additionally shows which variables influence perceived usefulness and perceived ease of use, and thus behavioral intention to use and use behavior. A further distinction is made between anchor variables, which can be influenced in the long term, and adjustment variables, which can be influenced in the short to medium term. The model therefore offers practitioners in the field of human-robot collaboration recommendations to increase the acceptance of robots.