我们准备好迎接服务型机器人的崛起了吗?-验收测量评审

N. Merz, J. Franke, F. Bodendorf
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引用次数: 0

摘要

人口变化带来的挑战与护理人员数量的减少是众所周知的。为了确保老年人的个人护理服务,研究人员致力于开发数字设备来支持护理人员的日常工作。特别是Covid-19大流行强调了对灵活服务的需求。在这种情况下,服务机器人不仅能够克服这一挑战,而且还可以在其他用例中提供支持,例如自闭症谱系障碍儿童的治疗或教学。不管它们的应用领域是什么,它们的使用和好处都高度依赖于用户的接受程度。因此,人们对它们的外观、行为以及它们的有用性和接受度进行了许多研究。然而,由于不同的研究设计,对验收测量的研究难以进行比较,因此难以建立基础。这是因为传统的接受模型,如Davis(1989)的技术接受模型,被认为不足以满足以交互为中心的机器人技术。因此,研究人员确定最合适的模型来衡量所开发的服务机器人的接受度是困难和耗时的。为了能够在这个快速发展的研究领域中衡量新的机器人发展,有必要对现有模型及其应用选项进行概述。为了支持研究人员和开发人员,本研究的目的是对现有的服务机器人验收测量模型进行概述。为了达到目的,提出了以下主要研究问题:目前存在哪些模型来衡量不同服务机器人的接受程度?按照Cooper(1988)对文献综述的分类,本文献综述的重点是现有的研究方法和实践。目标是通过中立的视角,将现有文献整合到一个矩阵中,以确定中心问题。本研究遵循broke et al.(2009)的指导方针,包括Webster和Watson(2002)的以概念为中心的方法进行文献分析和综合。基金会基于搜索字符串robot* AND accept* AND(测量* OR方法* OR模型* OR评估*)构建搜索,该搜索字符串用于Scopus、Science Direct、IEEE explore以及Google Scholar。从274篇已确定的研究论文中,排除了重复和非英语的研究论文,结果是226篇独特的研究论文。将这些进一步聚类,并将确定的19个服务机器人接受模型与Onnasch等人(2020)的机器人分类联系起来。概念矩阵表明,大多数模型对某一应用领域或目标群体具有高度的特异性。此外,我们还发现了大量的服务机器人的接受模型,但其中大部分并不常用。这个以概念为中心的文献综述给出了一个结构化的概述,研究人员和开发人员可以使用它来快速确定最适合他们研究的模型。然而,有些特征没有被涵盖,或者只是从不同的模型中被涵盖。因此,需要进一步研究如何克服这些差距。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Are we prepared for the Rise of Service Robots? - A Review on Acceptance Measurement
The challenge of demographic change combined with decreasing numbers of care personal is widely known. To ensure the service of individual care for seniors, researchers work on developing digital devices to support the caregivers in their day-to-day tasks. Especially the Covid-19 pandemic emphasized this need for flexible services. In this context, service robots are not only able to overcome this challenge, but to also support in other use cases such as therapy of children with autism spectrum disorder, or teaching. Regardless of their area of application, their usage and benefits highly depend on the user acceptance. Consequently, many studies on their appearance, behavior as well as their usefulness and acceptance have been undertaken. However, the studies on acceptance measurements are difficult to compare due to different study designs and therefore are hard to build upon. This is the case since traditional acceptance models such as the Technology Acceptance Model by Davis (1989), are not considered as sufficient for the interaction-focused technology of robots. Therefore, it is difficult and time-consuming for researchers to determine the most appropriate model in order to measure the acceptance of the developed service robots. To be able to measure new robot developments in this rapidly evolving research field, an overview on existing models as well as their application options is necessary.To support researchers and developers the aim of this research is to provide an overview on existing models for the acceptance measurements of service robots. To reach the objective, the following main research question is proposed: Which models currently exist to measure the acceptance of different service robots?Following the taxonomy on literature reviews by Cooper (1988), the focus of this literature review is on existing research methods and practices. The goal is to integrate existing literature within a matrix to identify central issues, by having a neutral perspective. The research follows the guidelines of Brocke et al. (2009) including a concept-centric approach of Webster and Watson (2002) for the literature analysis and synthesis. The foundation builds a search based on the search string robot* AND accept* AND (measur* OR method* OR model* OR evaluation*) which was used for Scopus, Science Direct, IEEE Xplore as well as Google Scholar. From the 274 identified research paper duplicates and non-English ones are excluded, which is resulting in 226 unique research paper. Those are further clustered and the 19 identified acceptance models for service robots are brought into relation to the robotic classification of Onnasch et al. (2020). The concept-matrix reveals that most models are highly specific to a certain field of application or target group. In addition, a large number of acceptance models for service robots were found, but most of them are not commonly used. This concept-centric literature review gives a structured overview that can be used by researchers and developers to quickly identify the most suitable model for their research. However, some characteristics are not covered or just covered from different models. Consequently, further research on how to overcome these gaps is required.
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