社交机器人参与博物馆游客市场调研访谈的访谈风格

J. Schermer, K. Hindriks
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引用次数: 0

摘要

我们设计并评估了一个机器人面试官,用于收集博物馆的游客数据,用于营销目的。我们从面对面的人类拦截访谈中获得灵感。我们开发了一种个人面试风格,希望能激励参与者回答更多的问题,并将其与更正式的风格进行比较。我们还评估了机器人进行的问候仪式是否会增加参与度,以及与机器人合影是否能有效激励访问者参与采访。我们的研究是在“野外”进行的,我们分析了机器人和博物馆里路人的会话。自变量是访谈风格和是否提供激励。因变量是参与和延续率,以及博物馆评级。与预期相反,我们发现当机器人提供激励时,参与率较低。虽然我们发现个人风格被认为更具有社交性,但它并不影响延续率。博物馆的评分也不受风格的影响。我们的样式操作可能不够强大,无法产生这些效果。我们的研究表明,社交机器人在进行拦截访谈方面具有很高的潜力。参与机器人面试的意愿很高,而这是拦截面试的主要挑战之一。为了改进数据收集,可以改进人员检测和语音识别技能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interviewing Style for a Social Robot Engaging Museum Visitors for a Marketing Research Interview
We design and evaluate a robot interviewer for collecting visitor data in a museum for marketing purposes. We take inspiration from research on face-to-face human intercept interviews. We develop a personal interviewing style that is expected to motivate participants to answer more questions and compare this with a more formal style. We also evaluate whether a greeting ritual performed by the robot increases participation and whether taking a picture with the robot is an effective incentive for visitors to participate in an interview.Our study is conducted "in the wild" and we analyse sessions with the robot and passersby in a museum. The independent variables were interviewing style and whether an incentive was offered or not. The dependent variables were participation and continuation rate, and museum ratings. Contrary to expectations, we find that the participation rate is lower when the robot provides an incentive. Although we find that a personal style is perceived as more social, it does not influence the continuation rate. Museum ratings were also not affected by style. Our style manipulation may not have been strong enough to produce these effects.Our study shows that social robots have a high potential for conducting intercept interviews. Willingness to participate in a robot interview is high, while this is one of the main challenges with intercept interviews. To improve data collection, people detection and speech recognition skills could be improved.
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