edge fields of science and technology but also the idea of doing something new.
Innovation includes “new ‘things’ which bring about economic value” (Yonekura &
Shimizu, 2015, p. 257), as well as measures for environmental adaptation of an
organization (Yonekura & Mckinney, 2005). One should look through a framework
of open innovation in order to bring about innovation (Yonekura & Shimizu, 2015).
Chesbrough (2006, p. xxiv) stated the following about open innovation:
Open innovation is a paradigm that assumes that firms can and should use external ideas as
well as internal ideas, and internal and external paths to market, as the firms look to advance
their technology.
Chesbrough is presenting the perspective that ideas, both internal and external to
the business, should be combined to construct a business model and ultimately create
value (Chesbrough, 2006). For example, looking at healthcare, caregiving activities
that were never seen before can be formulated through the novel utilization of
products developed and produced by new technologies, such as AI or robots, in
the healthcare service delivery process. This will ultimately lead to providing new
value to CHRs/DUs and realization of better QOL. Thus, these initiatives will be
referred to as “healthcare innovation.”
6 Measuring the Effects of Communication Robots
and Problems Therein
One problem concerning the effects of communication robot use is the difficulty of
conducting service assessments when there are patients who are older adults with
dementia. How are user satisfaction assessments conducted in research on the effects
of communication robot use in elderly care facilities? Many studies have used rating
scales or descriptive evaluations based on experimenter observation (Kawashima,
2013; Moyle et al., 2017; Obayashi, Kodate, & Masuyama, 2018; Obayashi,
Masuyama, Kojima, & Takahashi, 2018; Yokota, Ishiguro, Ohnaka, & Fujita,
2009). Most conduct the evaluation through a written description based on the
observer’s impressions, but there are others who evaluate using rating scales. For
example, Obayashi, Masuyama, et al. (2018) evaluated user’s behaviors on a 7-point
scale; Hamada et al. (2006) evaluated user’s behavior, facial expression, and conversation on a 4-point scale; and Yokoyama, Yamamoto, Kobayashi, and Doi (2010)
measured interest using a 4-point scale for whether users wished to continue
conversation with the robot. Among behavioral observation analyses, some utilized
the observers’ descriptive analyses, while others used a method of categorizing and
recording user behavior. For example, there are studies demonstrating that introducing a robot led to reduced time spent simply sitting in a chair, increased the
frequency of movements such as transferring seats, and increased interaction with
the robot (Kagawa, 2012; Watanabe, 2012). In an investigation by Yoneoka (2012),
facial expression, behavior, and speech, when responding to a robot, were evaluated
on a 5-point scale by an observer. Other research on caregivers involved behavioral
44
Y. Ikeda et al.
Innovation includes “new ‘things’ which bring about economic value” (Yonekura &
Shimizu, 2015, p. 257), as well as measures for environmental adaptation of an
organization (Yonekura & Mckinney, 2005). One should look through a framework
of open innovation in order to bring about innovation (Yonekura & Shimizu, 2015).
Chesbrough (2006, p. xxiv) stated the following about open innovation:
Open innovation is a paradigm that assumes that firms can and should use external ideas as
well as internal ideas, and internal and external paths to market, as the firms look to advance
their technology.
Chesbrough is presenting the perspective that ideas, both internal and external to
the business, should be combined to construct a business model and ultimately create
value (Chesbrough, 2006). For example, looking at healthcare, caregiving activities
that were never seen before can be formulated through the novel utilization of
products developed and produced by new technologies, such as AI or robots, in
the healthcare service delivery process. This will ultimately lead to providing new
value to CHRs/DUs and realization of better QOL. Thus, these initiatives will be
referred to as “healthcare innovation.”
6 Measuring the Effects of Communication Robots
and Problems Therein
One problem concerning the effects of communication robot use is the difficulty of
conducting service assessments when there are patients who are older adults with
dementia. How are user satisfaction assessments conducted in research on the effects
of communication robot use in elderly care facilities? Many studies have used rating
scales or descriptive evaluations based on experimenter observation (Kawashima,
2013; Moyle et al., 2017; Obayashi, Kodate, & Masuyama, 2018; Obayashi,
Masuyama, Kojima, & Takahashi, 2018; Yokota, Ishiguro, Ohnaka, & Fujita,
2009). Most conduct the evaluation through a written description based on the
observer’s impressions, but there are others who evaluate using rating scales. For
example, Obayashi, Masuyama, et al. (2018) evaluated user’s behaviors on a 7-point
scale; Hamada et al. (2006) evaluated user’s behavior, facial expression, and conversation on a 4-point scale; and Yokoyama, Yamamoto, Kobayashi, and Doi (2010)
measured interest using a 4-point scale for whether users wished to continue
conversation with the robot. Among behavioral observation analyses, some utilized
the observers’ descriptive analyses, while others used a method of categorizing and
recording user behavior. For example, there are studies demonstrating that introducing a robot led to reduced time spent simply sitting in a chair, increased the
frequency of movements such as transferring seats, and increased interaction with
the robot (Kagawa, 2012; Watanabe, 2012). In an investigation by Yoneoka (2012),
facial expression, behavior, and speech, when responding to a robot, were evaluated
on a 5-point scale by an observer. Other research on caregivers involved behavioral
44
Y. Ikeda et al.