The purpose of this study is to understand the perceptual differences toward smiling behaviors with head inclinations displaying by the human-like robot staff and human staff in a service setting – Get Paper Help

The power of head tilts: gender and
cultural differences of perceived human vs
human-like robot smile in service
Chung-En Yu and Henrique F. Boyol Ngan
Abstract
Purpose – The purpose of this study is to understand the perceptual differences toward smiling
behaviors with head inclinations displaying by the human-like robot staff and human staff in a service
setting.
Design/methodology/approach – This study adopted a 2 (staff: robot/human personal personnel) 3
(head tilt: left/right/straight) full factorial design, while cross-examining participants’ cultural dimensions 2
(power distance: high/lower) 2 (gender: male/female) during the service encounter.
Findings – Overall, it was found that male and female customers with different cultural background
would perceive robot and human personnel with varying degrees of head tilt very differently, namely,
regarding interpersonal warmth but not customer satisfaction.
Originality/value – Nonverbal cues serve as important elements in the interaction. This paper provides
new directions on the design of anthropomorphic robot and gives insight to people’s perceptual
differences. All in all, the present study is useful in facilitating human–robot interactions.
Keywords Human-like robot, Service encounter, Power distance, Head tilt, Smile
Paper type Research paper
1. Introduction
Tourism has been transformed significantly with the growth of information communication
technologies (ICTs) over the past decades (Buhalis and Law, 2008). Specific to the
hospitality industry, the use of technology enhances the competitive advantages of the
service entity (Buhalis, 2000), improves operational efficiency and effectiveness (Yu and
Lee, 2009), serves as a marketing tool for the enterprises (Buhalis and Law, 2008) and
co-creates unique service experience (Neuhofer et al., 2015a). That is, consumers
nowadays have more choices to receive service such as face-to-face personal service
and self-service (Law et al., 2014). With a particular focus on the self-service, service
automation has evolved from kiosks to service robots owing to the progress and
advancement of ICTs (Sheldon, 1997). The field of human–robot interaction (HRI) has
become an inevitable trend and there are focuses on this specific area to improve its
usability and usefulness (Yanco et al., 2004; Sara and Pamela, 2004). Furthermore, unlike
previously, robots are no longer limited to the mechanical designs; instead, their
embodiments can be anthropomorphic, zoomorphic, caricatured and functional (Pfeifer
et al., 2007). Currently, service robots are widely used in the areas of hotels, hospitals,
and other service entities (Tung and Law, 2017). For instance, Hotel Henn-na in Japan is
the first hotel ever to employ human-like robots as front office agents (Alexis, 2017).
Other hotels apply robotics are Yotel in New York, Aloft in Cupertino and Marriott
Residence Inn in Los Angeles (Tung and Au, 2018).
Chung-En Yu is based at
Department of Innovation
and Management in
Tourism, Salzburg
University of Applied
Sciences, Salzburg,
Austria.
Henrique F. Boyol Ngan is
based at Tourism College,
Institute for Tourism
Studies, Macao, China.
Received 18 July 2018
Revised 5 October 2018
26 November 2018
Accepted 1 December 2018
© Chung-En Yu and
Henrique F. Boyol Ngan.
Published by Emerald Publishing
Limited. This article is published
under the Creative Commons
Attribution (CC BY 4.0) licence.
Anyone may reproduce,
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derivativeworks of this article (for
both commercial and noncommercial
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full attribution to the original
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PAGE 428 j TOURISM REVIEW j VOL. 74 NO. 3 2019, pp. 428-442, Emerald Publishing Limited, ISSN 1660-5373 DOI 10.1108/TR-07-2018-0097
To date, technology plays a crucial role in enhancing the service experience. One typical
example is the Inamo Restaurant that brings the world’s foremost dining experience by fully
rendering the digital and interactive ordering system (Neuhofer et al., 2014). However,
given the nature of work involved in the tourism and hospitality industries which is largely
based on human interaction, the intricacies of social interaction cannot be limited to only the
physical aspects and/or the static aspects of visual appearance, but also how these are
conveyed during the service encounter (Zinn et al., 2004). To be hospitable, one common
notion is the genuine greetings from the service representatives (Ashforth and Humphrey,
1993). However, when applying robot workers in service, there might be technological
barriers which can subsequently lead to either the positive or negative tourist experiences
and emotional responses (Neuhofer et al., 2015b).
As noted, the design of robot has developed from machine- to human-like, and the degree
of humanness could reflect the robot agents’ capacities (Waytz et al., 2010). When the
anthropomorphic robot as service personnel engages directly with humans, the affective
responses (e.g. emotions and mood) of the humanoid robot became crucial especially in
reaching unique service experiences in the hospitality industries (Tung and Law, 2017). For
instance, although a smile is an important aspect during the service encounter, it needs to
be moderated depending on the situation. Specifically, there are at least three aspects of
non-verbal cues in a smile that has been consistently shown to influence its perceived
authenticity: muscle activation around the eyes (“crow wrinkles”) (Gunnery and Ruben,
2016) and the mouth (“smiling lip”) (Gunnery and Ruben, 2016) and the inclination of head
(Costa and Bitti, 2000). However, most of what is reported in the literature refers to only the
industrial robots that do not resemble any of the human characteristics (Mara and Appel,
2015). It limits the understanding of the visual appeals of humanoid robots that may
influence customers’ experience. Additionally, cultural differences exist in processing these
non-verbal cues during the onset of a smile during social interactions (Ferna´ndez et al.,
2000), as well as gender differences (Krys et al., 2015), which cannot be ignored and needs
to be accounted.
Thus, the present study examines cultural variations in customer service experience
towards human-like robot/non-robot personnel with different variations of head tilt, the most
powerful and frequently occurring non-verbal cue in the smiling behaviors (Mara and Appel,
2015). The findings of the present study will add to existing knowledge and expand our
understanding of the role of non-verbal cues in consumer behavior in the tourism and
hospitality setting. Additionally, it will provide insights as to how human-like robots should
appear and interact in the service setting according to specific characteristics of guests
(i.e. gender and cultural orientation).
2. Literature review
2.1 Adoption of service robots in tourism
Defined by the International Federation of Robotics (2019), an organization in charge of the
robotic industry, a service robot refers to a robot that can perform service with fully or partial
autonomous to human beings except from the tasks that are manufacturing. With the
improvement of robotic technology, it enables the robots to be applicable in the service
sector and there is no exception in the tourism and hospitality industries. For instance, the
current usage includes robots working in hotels and other service entities (Tung and Law,
2017). Particularly in the hotels, service robots mainly work as receptionists (Ivanov and
Webster, 2017) whom are responsible to interact, communicate and deliver service to the
hotel guests with system-based autonomous (Wirtz et al., 2018).
Undoubtedly, the types of the robots vary since the appearance can be designed as
human-like or non-human-like (Wirtz et al., 2018). The human-like robot revolution is active
worldwide and has brought the robotic service into another level; specifically, adoption of
VOL. 74 NO. 3 2019 j TOURISM REVIEW j PAGE 429
anthropomorphic robots has become a cutting-edge concept. For example, Henn-na Hotel
in Japan is the first hotel staffed by robots in the world (Alexis, 2017). Junko Chihira, created
by Toshiba, works full time in one of the shopping malls in Tokyo to guide and offer help to
the visitors (Hongo, 2015). One of the advantages about humanoid robot is because of its
autonomy, making them move around, provide guidance to hotel guests (Kuo et al., 2017).
Nonetheless, it is worth noting that the appearance of the human-like robot counts. Previous
study pointed out that the appearance shapes people’s impression towards its
competencies (Goetz et al., 2003). It thus emphasizes the needs in understanding
customers’ perceptions and impressions. An important factor having influence on
customers’ perceptions is the degree of human-likeness, which is a theory proposed by
Mori (1970). The Uncanny Valley theory has been widely applied in robotic related literature
(Murphy et al., 2017; Strait et al., 2017), stating that when the humanoid object appears to
be human, it provokes discomfort to the observers; yet, once the objects become much
more human-like, the level of acceptance then becomes positive. Nonetheless, not all
research indicates that there is a preference for anthropomorphic appearances on robots.
For instance, tasks that are masculinity are perceived as more suitable to male robots (e.g.
working aloft and repairing cars), while tasks that are femininity in nature are expected to be
done by female-appearance robots (Eyssel and Hegel, 2012). Furthermore, depending on
the tasks, people have different feelings towards the anthropomorphism; in general, humanlike
robots match more with the jobs that are social in nature (i.e. jobs require human
interaction) (Goetz et al., 2003).
Other than the physical appearance itself, a well-cited article pointed out that trust toward
the salesperson is correlated with customer behavior and the long-term relationship (Doney
and Cannon, 1997). According to Wirtz et al. (2018), during the service encounter, there are
emotional and social value such as the rapport and trust between customers and the
service agents. Since some of the jobs have already been replaced by social robots (e.g.
Pepper replaced human employees to greet and welcome customers) and more are likely
to be taken place in the near future; it creates an issue that customers’ loss the chance to
obtain human service (Huang and Rust, 2018). Put differently, customers’ perceptions
towards the degree of social presence of the frontline agents could be lower; as pointed out
by Heerink et al. (2008), social presence is about people’s feeling on whether someone is
physically present. Moreover, it has been found to influence trust building among people
since trust is more likely to be built during a face-to-face interaction (Wirtz et al., 2018). The
same authors also suggested that to improve customers’ trustiness towards human-like
robots as front office agents in particular, the emotions and behaviors display by the robots
could make a difference since the trust would be built much easier when customers feel that
the employees understand them. Hence, apart from the physical appearance of the robots,
nonverbal cues, which will be discussed in a later section, are also important.
2.2 Gender perceptions toward the robot
According to the International Labour Organization (ILO) database, the worldwide
percentage of women working in services has exceeded 50 per cent since 2010;
especially, it peaked at 57.4 per cent in 2017. In most cases, customers can easily
encounter females as front desk agents in the service entities (e.g. tourist information
centers, restaurants, or hotels). There are, however, certain stereotyping which exists in
server gender; customers perceive female service representatives as more reliable,
assured and sympathetic (Fischer et al., 1997).
Unconsciously, users interact with machines in a similar way they interact with humans
(Reeves and Nass, 1996), but gender effect was found in the technology-related areas
such as the computer experiences where males showed higher self- efficiency, lower
anxiety and more positive attitudes (Durndell and Haag, 2002). To that end, gender
stereotypes might also exist regarding female-featured human-like robots as service
PAGE 430 j TOURISM REVIEW j VOL. 74 NO. 3 2019
agents. Moreover, as most of the available and well-established social humanoid robots
are female appearance, it is important to understand people’s perceptions. One study
found that males tend to perceive robots as more human-like whereas females perceive
robots as more machinelike; furthermore, males consider robots are more autonomous
(Schermerhorn et al., 2008). Another study administered the Negative Attitude toward
Robots Scale (NARS), a tool to measure humans’ attitude towards interacting with
robots, on 400 Japanese participants (Nomura et al., 2006); the results revealed that
females have higher negative attitude in interacting with robots. However, the same
study found that during a real HRI, males are more likely to avoid interacting with the
robots and they indicated higher negative attitudes than females. On top of that, Ivanov
et al (2018) investigated young Russian’s attitude towards the use of robots in a hotel.
The results revealed that consumers are quite supportive with the idea; yet, slightly
differences were found between male and female.
Given the fact that gender differences exist in the attitude and perceptions towards the
robots, previous literature mostly researched on either the interaction with machinelike
robots or robots with gender-neutral appearance (Dautenhahn et al., 2006; Nomura et al.,
2006). The anthropomorphic robots are still under development and there are lots of works
to be done. Alongside the appearance of the robots, subtle changes of the robots need to
be accounted.
2.3 Cultural differences
During the service encounter, the front office agents are expected to be friendly and
hospitable; these messages can be delivered through not only the physical objects offered
by the service entity but the emotional displays from the service representatives (Rafaeli
and Sutton, 1987). The emotional displays are explained by the display rules; it indicates
how an individual should express himself/herself within a social group or a certain culture
(Hochschild, 1991). According to the cultural dimensions proposed by Hofstede, Power
Distance (PD) is one of the most important dimensions in relation to the emotions
(Matsumoto, 1991), and it is also important to the organizations since it serves as the
fundamental to all relationship (Daniels and Greguras, 2014). PD refers to how people in a
certain culture view power relationship between people. Individuals with high PD normally
display positive emotions to those having higher status whereas they display negative
emotions to those in a lower position; inversely, people with low PD tend to show negative
emotions to those in a higher position while they are likely to exhibit positive emotions to
people having lower status (Matsumoto, 1991).
Take this principle into the service experience, “Customers First” are always mentioned in
the service concepts. Indirectly, it forms the idea that front office agents are in a lower status
when serving the customers while customers are in a higher position (Grandey et al., 2010).
In such case, the display rules guide the front office agents the appropriate emotional
displays during the service encounter. The service representatives are encouraged to put
on a positive emotion (i.e. a smile) when interacting with the customers (Hochschild, 1991).
However, another study researched on a group of younger and lower occupational sample
revealed that the positive emotions should be freely expressive to their coworkers instead of
the customers or their supervisors (Grandey et al., 2010). Moreover, low status people
display more the deference signs than people in higher status (Kowner and Wiseman,
2003).
2.4 Head tilts in the smiling behaviors
To become a good social partner, it is necessary that robots understand human
communication, both verbal and non-verbal. Verbal communication refers to the
exchanging of the information between individuals by using voice; non-verbal
VOL. 74 NO. 3 2019 j TOURISM REVIEW j PAGE 431
communication includes gestures that extend the verbal cues (Ferna´ndez et al., 2000).
Previous literature disclosed that during the service encounter, customers pay more
attention to the non-verbal behaviors of the service representative than the verbal one
(Tronvoll, 2007). In particular to the non-verbal cue, smiles are valued the most since it
is correlated with customers first impression, and it directly influences customer
satisfaction (Brown and Sulzer-Azaroff, 1994) and their perception towards the
interpersonal warmth of the service provider (Sundaram and Webster, 2000). Despite
that a smile varies culture by culture (Matsumoto, 1989), head tilt in the smiling behavior
is one of the most frequently occurring non-verbal cues (Mara and Appel, 2015;
Ambadar et al., 2009); additionally, people are likely to tilt their head when smiling
(Costa and Bitti, 2000).
The same goes to human-like robots as service agents and verbal communication such as
the voice of the gender has been investigated (Crowelly et al., 2009). Although the
appearance of the human-like robot might appear appropriate to the customers at the first
glance, customers are likely to find it err and uncomfortable in a long-term interaction.
Previous studies found that the non-verbal behaviors could increase human’s likability
towards the anthropomorphic robots (Clark and Rutter, 1985). There were also studies
investigated how human response and perceive the robots featured differing non-verbal
cues; Mara and Appel (2015) discovered that head tilts increase robots’ similarity with
humans. Moreover, people feel more comfortable when a robot equips with non-verbal
behaviors (i.e. nodding and head tilting) (Liu et al., 2012). Finally, the observers revealed
greater human-likeness when the robots displayed gestures in the interaction (Salem et al.,
2013).
2.5 Interpersonal warmth
Warmth and cold are originally proposed by Asch (1946); he stated that these are the two
human traits in forming first impression towards an individual. In social judgement, warmth
is the most powerful personality trait; it also refers to one’s perceived favorability towards
another person (Williams and Bargh, 2008) by judging the sensitiveness, politeness,
generosity and humbleness (Mara and Appel, 2015).
Echoing to the uncanny valley theory mentioned earlier, people might find anthropomorphic
robots uncomfortable. Nonetheless, the higher the human-likeness, the higher people’s
acceptability is (Mara and Appel, 2015) since anthropomorphism includes not only the
physical appearance but also traits intimate human nature (Eyssel et al., 2010). It is found
that interpersonal warmth serves as a crucial factor in people’s perception towards the
robots; specifically, non-verbal cues such as a smile thereby make robots warmer. In
service, where interaction is highlighted, interpersonal warmth is highly important to the
service agents as it serves as the fundamental factor in building customer satisfaction
(Sundaram and Webster, 2000).
2.6 Customer satisfaction
Customer satisfaction is a factor that helps a service entity differentiate from its competitors.
Apart from branding or having reasonable price strategy (Gronholdt et al., 2000), behaviors
from the employees such as displaying a smile during service encounter is also able to
increase customer satisfaction (Barger and Grandey, 2006; So¨derlund and Rosengren,
2008). Owing to the contagion of emotions, a smile shown by the service representative
could predict the encounter satisfaction (Barger and Grandey, 2006). Likewise, smiling
during service encounter could enhance customer satisfaction (Brown and Sulzer-Azaroff,
1994; So¨derlund and Rosengren, 2008).
PAGE 432 j TOURISM REVIEW j VOL. 74 NO. 3 2019
3. Methodology
3.1 Research design
To examine cultural differences in customer perceptions and response towards robot and
human customer service representatives with different appearances (i.e. head tilt), the
present study adopted an experimental design. Specifically, a 2 (staff: robot or human
personnel) 3 (head tilt: left or right or straights) full factorial design was employed, while
cross-examining participants’ cultural dimensions and gender: 2 (power distance: high or
lower) 2 (gender: male or female). Participants were subjected to brief a service scenario
(e.g. “Please consider the cases when your hotel experience was served with the human/
robot staff.”) in along with one of the six possible combinations of the service representative
in the form of vignette, as conventionally done in the service literature (Bitner, 1990). The
scenarios that reflected these conditions and the photos of the service representatives were
adapted and developed specifically for this study based on Mara and Appel (2015) .Thus,
photos were taken from professional front desk representatives working in major integrated
resorts and subsequently edited in Gimp (an open source photo editing software) to the
desired head tilt positions (i.e. left and right). Whereas, for the robot service representative,
we have included the photos of the robot staff at the Henn-na’s Hotel, the world’s first robotstaffed
hotel (Alexis, 2017).
3.2 Sample and sampling
To generalize participants’ background, the recruitment of participants was done through
street interception around the Ruins of St. Paul and the Cunha Street, which are the top two
major cultural sites of Macau (Ung and Vong, 2010). Participants that were approached
were briefed of the objectives and the nature of the study. At the end, those who agreed to
participate, signed an informed consent and were randomly assigned to one of the six
vignettes. In total, 233 participants agreed to participate.
3.3 Measures
For each vignette, participants were asked a series of questions that measured their
perceptions of the interpersonal warmth of the customer service representative shown to
them, as well as their perceived customer satisfaction. At the end of the questionnaire,
demographic information was collected (e.g. gender, marital status, income, education,
amongst others).
3.3.1 Interpersonal warmth. To measure interpersonal warmth which indicates the degree of
features and characteristics that are unique to humans, the interpersonal warm scale (IWS)
developed by Mara and Appel (2015) was used. It consists of 5 items (e.g. “How [helpful]
do you expect this [robot]/[human] staff to be?”), with the seven-point Likert scale as a
response format, in which, 1 means strongly disagree and 7 means strongly agree.
3.3.2 Customer satisfaction. Regarding customer satisfaction of a service encounter and
experience, the scale developed by Cronin et al. (2000) was used. The scale consists of
four positively worded items (e.g. “My feelings toward the [robot]/[human] staff’s services
can best be characterized as very satisfied”). Participants indicated their degree of
agreement with each statement on a seven-point Likert scale, where 1 is strongly disagree
and 7 is strongly agree.
3.3.3 Power distance. Participants’ power distance was measured using Hofstede’s cultural
dimensions developed by Yoo et al. (2011). It comprises of five items (e.g. People in higher
positions should make most decisions without consul people in lower positions), with a
seven-point Likert scale as the response format where 1 means strongly disagree and 7
refers to strongly agree. Participants were designated as either high or low in PD on the
basis of a median split. This median-split procedure is consistent with the technique
VOL. 74 NO. 3 2019 j TOURISM REVIEW j PAGE 433
commonly used to distinguish high and low power distance participants (Ferna´ndez et al.,
2000; Hofstede, 1991).
4. Results
4.1 Descriptive statistics
As presented in Table I, participants of the present study were mostly females (60.5 per
cent), skewed toward the younger population aged below 34 years old (55.0 per cent).
There were 128 participants (54.9 per cent) with low PD, and 105 (45.1 per cent) with high
PD. The majority of participants have attained a higher education degree or are presently
engaged in higher education (91.8 per cent) and single (67.4 per cent). There were a wide
range of nationalities; to name a few, China, Portugal and UK. In regard to monthly income,
58.4 per cent of our sample earned less than MOP 14,999, and the rest were scattered in
other salary categories.
4.2 Main analysis
A four-way MANOVA was run with four independent variables – type of staff (robot/human);
head inclination (left/right/none), participants’ gender (male/female) and cultural orientation
index in power distance (high PD/low PD) and two dependent variables – interpersonal
warmth (IW) and customer satisfaction (CS). The combined interpersonal warmth and
customer satisfaction ratings were used to assess overall consumers’ service experience. As
a result, the interaction effect between the type of staff, head inclination, participants gender
and their power distance index were statistically significant on the combined dependent
variables F(4, 384) = 3.536, p = 0.008, Wilks’ K = 0.930, partial h 2 = 0.036. There was a
statistically significant interaction effect between the type of staff, head inclination,
participants’ gender and their power distance index on the interpersonal ratings, F(2, 194) =
6.078, p = 0.003, partial h 2 = 0.060, but not for customer satisfaction F(2, 194) = 2.637, p =
0.074, partial h 2 = 0.27. That is, participants with different gender and cultural orientation
evaluated their experience differently when being served by a robot and human with
different head inclinations (Table II). Univariate tests showed that these differences were
associated specifically with the head inclination and the gender of participants, F(4, 384) =
2.976, p = 0.0019, Wilks’ K = 0.940, partial h 2 = 0.030. To that end, post hoc analysis was
conducted with Bonferroni adjustment to determine the specific differences of IW and CS
that occurred. Low power distance males evaluated interpersonal warmth of human staff
with right head inclination significantly higher than the robot staff with same head inclination
(Mhuman = 5.83 vs Mrobot = 4.05, p < 0.05). Interestingly, for female participants with low
power distance, customer satisfaction of human staff with right head inclination was
significantly lower than the robot staff with the same head inclination (Mhuman = 4.31 vs
Mrobot = 5.45, p = 0.009), while this result was opposite from those observed in low power
distance males (Mhuman = 5.47 vs Mrobot = 4.28, p = 0.027).
4.3 Correlation matrix
As shown in Table III, customers’ gender and their extent of power distance related to their
perceptions towards the interpersonal warmth and the perceived customer satisfaction
were dependent on the type of the service personnel (i.e. robot and human) and their head
inclination (right, no and left). That is, the perceptions of male and female customers with
low PD and males with high PD were positively correlated with the robot staff smile with right
head tilt (r = 0.692, p = 0.006; r = 0.758, p = 0.002; r = 0.826, p = 0.001). Positive
correlation was also found between female customers with high PD and robot staff with no
head inclination (r = 0.857, p = 0.007); in addition, male customers with low PD, male and
female customers with high PD and robot staff with left head tilt (r = 0.618, p = 0.043; r =
0.789, p = 0.020; r = 0.613, p = 0.034).
PAGE 434 j TOURISM REVIEW j VOL. 74 NO. 3 2019
Table I Summary of descriptive statistics
Variables Frequency (%)
Gender
Male 92 39.5
Female 141 60.5
Age
18-24 81 34.8
25-34 47 20.2
35-44 44 18.9
45-54 42 18.0
55 or above 19 8.2
Educational level
Primary 1 0.4
Secondary 15 6.4
Undergraduate 131 56.2
Postgraduate or above 83 35.6
Not applicable 3 1.3
Marital status
Married 76 32.6
Single 157 67.4
Monthly income
Less than 8,000 MOP 81 34.8
8,000-14,999 55 23.6
15,000-29,999 36 15.5
30,000-59,999 37 15.9
More than 60,000 MOP 24 10.3
Nationality
Australia 8 3.4
Austria 1 0.4
Belgium 3 1.3
Brazil 3 1.3
Bulgaria 1 0.4
Canada 3 1.3
China 55 23.6
Denmark 1 0.4
Egypt 1 0.4
Estonia 1 0.4
France 4 1.7
Germany 4 1.7
Ghana 1 0.4
Greece 1 0.4
Hong Kong 10 4.3
Hungary 1 0.4
India 2 0.9
Italy 4 1.7
Japan 2 0.9
Macau 19 8.2
Malaysia 3 1.3
Nepal 1 0.4
The Netherlands 2 0.9
New Zealand 1 0.4
Philippine 4 1.7
Portugal 16 6.9
Singapore 2 0.9
South Africa 5 2.1
Spain 10 4.3
Sweden 3 1.3
Switzerland 1 0.4
Taiwan 26 11.2
UK 18 7.7
The USA 15 6.4
Vietnam 1 0.4
VOL. 74 NO. 3 2019 j TOURISM REVIEW j PAGE 435
On the other hand, there were positive correlations between female customers with low PD,
male and female customers with high PD and human staff with right head tilt (r = 0.689, p =
0.001; r = 0.886, p = 0.003; r = 0.763, p = 0.006); furthermore, male customers with low PD
and human staff with no head inclination (r = 1.000, p = 0.001). Finally, male and female
customers with high PD and human staff smile with left head tilt (r = 0.822, p = 0.012; r =
0.919, p = 0.001).
5. Discussion and Conclusion
5.1 General discussion
The present study was set out to investigate whether there are differences between humanlike
robot and non-robot personnel with varying degrees of head inclinations regarding the
interpersonal warmth and customer satisfaction during customers’ service experience. It is
concluded that interpersonal warmth is one of the main dimensions in influencing the
perceptions towards human social behaviors (Fiske et al., 2007). In the case of humanoid
robots, attentions need to be paid on the degree of anthropomorphism since it is highly
correlated with the warmth of the personnel (Ho and MacDorman, 2010). To increase the
extent of human-likeness, non-verbal cues such as the head tilts, commonly displayed in
smiling behaviors, are proved to have impact on it, and eventually head inclinations could
change how users perceive the warmth of the robot (Mara and Appel, 2015). Not to mention
Table II Mean and standard deviations of participants’ perceptions towards robot/human
Robot Human
PD n Right n None n Left n Right n None n Left
IW
F
LPD 14 4.73 (1.27) 6 4.67 (0.84) 14 5.11 (1.02) 17 4.00 (0.75) 4 5.55 (0.30) 24 4.56 (1.22)
HPD 8 4.23 (0.56) 8 5.28 (1.24) 11 5.33 (0.68) 10 4.72 (0.83) 9 5.47 (1.26) 8 5.20 (1.20)
M
LPD 14 4.06 (1.40) 4 6.00 (0.75) 10 3.82 (0.82) 8 5.83 (0.53) 2 5.20 (1.70) 4 4.65 (0.84)
HPD 11 5.36 (0.72) 3 4.80 (0.72) 6 4.33 (0.78) 8 4.70 (1.61) 5 5.16 (0.61) 8 5.10 (0.95)
CS
F
LPD 14 5.45 (1.19) 6 4.00 (0.42) 14 4.59 (1.49) 17 4.31 (1.02) 4 3.94 (1.42) 24 5.13 (1.06)
HPD 8 4.31 (1.61) 8 4.56 (1.86) 11 5.52 (0.83) 10 4.63 (0.92) 9 5.78 (0.73) 8 5.28 (1.39)
M
LPD 14 4.29 (1.21) 4 5.06 (1.57) 10 4.78 (1.16) 8 5.47 (0.63) 2 4.75 (1.06) 4 5.19 (1.82)
HPD 11 4.95 (1.26) 3 3.75 (0.25) 6 4.79 (1.08) 8 4.97 (1.74) 5 4.70 (0.69) 8 5.31 (0.93)
Note: F = Female; M = Male; LPD = Low Power Distance; HPD = High Power Distance
Table III Correlation matrix
Robot Human
Low PD High PD Low PD High PD
Male Female Male Female Male Female Male Female
Head Tilt IW CS IW CS IW CS IW CS
Right IW 0.758 0.274 0.689 0.763
CS 0.692 0.826 0.025 0.886
No IW 0.561 0.857 0.357 0.417
CS 0.231 0.561 1.000 0.350
Left IW 0.043 0.613 0.290 0.919
CS 0.618 0.789 0.669 0.822
Notes: Correlation is significant at the 0.01 level (two-tailed); correlation is significant at the 0.05
level (two-tailed); PD = Power Distance; IW= Interpersonal Warmth; CS = Customer Satisfaction
PAGE 436 j TOURISM REVIEW j VOL. 74 NO. 3 2019
the customer satisfaction, when positive emotions (i.e. smiles) are demonstrated, it not only
boosts the degree of warmth, but customers’ perceived satisfaction would be higher
(Gabriel et al., 2015). Nonetheless, when individual factors are taken into account, our
findings showed that male and female customers with different cultural background
perceived robot and human personnel with varying degrees of head tilt differently,
especially when we consider their cultural orientation.
As for gender differences, male participants evaluated the robots (that appeared as female
like) more favorably than female participants did. Scientifically, evidences were found on
the gender effect of technology-related areas (Schermerhorn et al., 2008). Flandorfer (2012)
pointed out that when it comes to technology acceptance/usage, men are more taskoriented,
leading to a higher perceived usefulness towards the technology. Inversely, the
self-efficiency of females towards technology are relatively lower; it becomes challenges for
them to see the benefits of using a given device (Venkatesh and Morris, 2000). By bearing
the gender effect in mind, consistent with our findings, women are more skeptical of robots
(Ivanov et al., 2018) and found unnatural to interact with them (Flandorfer, 2012). Adding to
that, we suspect that the results were partly because of the preexisting gender stereotypes
in the workplace. Because of the fact that service industry is characterized by female
communal features, female workers are most likely to be perceived as most suitable, seeing
that it is most congruent to these stereotypical features (Eagly et al., 2000) resulting in more
favorable evaluations. Along with the opposite sex pairing (Sullivan et al., 2017), males
showed a greater interest than the female participants. Notwithstanding the current study
did not measure whether differences exist if the robot appeared as male-like; Schermerhorn
et al. (2008) explained that women reacted differently toward the robot with male-voice in a
friendlier manner.
However, the aforementioned trends change when considering the cultural aspects.
Individuals with low PD have differing viewpoints in terms of the interpersonal warmth. It is
pointed out that people with low PD tend to show positive emotions to people in a lower
position (Daniels and Greguras, 2014). Regarding the service interaction, front office agents
are believed to be in the lower position. Consequently, this group of customers is likely to
exhibit positive emotion (i.e. a smile) to the service representative, and thereby expect the
staff to also display their smile. Our findings could explain that head tilt, one of the signs of a
smile, is therefore favorable for those with low PD; yet, this was only true if the staff was nonrobot
personnel. As mentioned by Ho and MacDorman (2010), anthropomorphism also
influences how people feel about the staff. However, since the stimulus in the current study
only focused on one single robot which cannot represent the whole, echoing to the uncanny
valley theory, people might find the current humanoid robot err or inappropriate during
service encounter. Hence, head tilt could not increase the warmth of the robot.
5.2 Managerial implication
This paper addresses customer service experience from a novel aspect. Nevertheless,
service robots are rapidly evolving and are becoming more like human beings, not only
because of its physical appearance but the autonomous of humanoid robots. However, the
adoption of human-like robots is not matured yet; echoing to the innovation adoption curve
(Rogers, 2010), both the service providers and customers might still be in either the stages
of innovators or early adopters. Given that, the current research draws attention to what
most customers expected to see during the service encounter – a smile. It is possible to
increase the extent of interpersonal warmth of the robot personnel, which is positively
correlated with customers perceived satisfaction; notwithstanding, perceptual differences
exist among consumers with differing gender and cultural backgrounds. If the humanoid
robots nowadays can express emotions (e.g. Sophia), it is beneficial to also customize its
emotional expressions for different target groups given the importance of co-creating
unique values in the service. Hence, this research provides new directions on the design of
VOL. 74 NO. 3 2019 j TOURISM REVIEW j PAGE 437
anthropomorphic robot and gives insights to both the robotic enterprises and hotel
managers who would like to adopt the innovation technology. More specifically, it outlines
design principles for humanoid robots geared towards specific target customers based on
their gender and culture. In the age of computer, robots have turned into human
counterparts from something that appeared only in the science fiction; to that end, the
present study sheds light on the improvements in HRI.
5.3 Limitations and recommendations
Given such findings and contributions, the current study examined only one type of
anthropomorphic robot. We barely know the criteria that customers judged the robot;
hence, future research could manipulate other humanoid robots during service
encounter. Moreover, cross-gender effect might exist; yet, we did not investigate robots
with male and female appearance, which is encouraged for future study. Additionally,
other non-verbal cues of smiling behaviors are worth to research. Finally, continued
efforts are needed to understand how customers perceive human-like robots as service
representatives in a real-life situation.
Nonetheless, there are ethical issues that can be hardly controlled. For instance, it remains
unclear on the general acceptability of robots mimicking human behaviors; in a more serious
extent, whether it is appropriate if the manpower is replaced by the means of technology.
Shortly, the usage of human-like robots will become more common and available worldwide.
To improve HRI, it is important to design it in a way that most people will accept and strike a
balance between the ethical issue and public’s expectation and perception.
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About the authors
Chung-En Yu is currently a Master’s student in Salzburg University of Applied Sciences
studying in Innovation and Management in Tourism. Her research interests are
VOL. 74 NO. 3 2019 j TOURISM REVIEW j PAGE 441
psychological and sociological phenomena in tourism and hospitality industries. Her
studies adopt new technologies and design experiences, particularly involving sensor
technology. Chung-En Yu is the corresponding author and can be contacted at: cyu.imtem2018@
fh-salzburg.ac.at
Prior to joining IFT, Henrique F. Boyol Ngan was responsible for searching, creating and
implementing new corporate solutions for training and development in the gaming industry.
Working with clients, he specialized in designing and implementing the complex HR
processes, carried out projects in the areas of diagnosis and changes in organizational
culture of companies and management teams, improved performance and built teams. He
has taught courses in the fields of psychology, social psychology, psychology of work,
human resource management and organizational behavior at University of Saint Joseph
(former IIUM) and Macau Polytechnic Institute.
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PAGE 442 j TOURISM REVIEW j VOL. 74 NO. 3 2019

HOSP2001 – Semester 1, 2020
Assessment 1: Critical article review
Task:
This individual assessment requires students to evaluate ONE of the below articles. The articles explore traditionally held concepts of guest services in the context of the automation of hotel processes and the workforce itself.
The article are as followed and can be found online through the UQ Library or on Blackboard:
• Yu, C.-E. (2020). Humanlike robots as employees in the hotel industry: Thematic content analysis of online reviews. Journal of Hospitality Marketing & Management, 29(1), 22–38. https://doi.org/10.1080/19368623.2019.1592733
• Yu, C.-E., & Ngan, H. F. B. (2019). The power of head tilts: gender and cultural differences of perceived human vs human-like robot smile in service. Tourism Review, 74(3), 428–442. https://doi.org/10.1108/TR-07-2018-0097
This assessment requires students to identify and critically evaluate the key arguments, bias and reliability of a peer-reviewed article on the above topic. Specifically, students will need to:
• Identify the sources of key arguments
• Evaluate both the merits and limitations of these arguments in the context of the broader literature; and
• Determine the article’s position within the broader literature
Based on this, students will arrive at an informed opinion on the persuasiveness and rigour of the article being evaluated.
Please ensure that you apply the following formatting: Size 12 font, 1.5 – 2 line spacing.
Please find the marking criteria for your orientation over the next pages!
Due
20th April 2020, 12pm
Percentage of final grade
50%
Words
2,000 (+/- 10%) words
Learning objectives
3 Assess internal and external factors influencing the management of hotel operations.
4 Understand current best practices in relation to measuring the performance of hotel operations.
5 Discuss and present significant and contemporary operational issues in the international hotel industry.
HOSP2001 – Semester 1, 2020
Outstanding
Very Good
Good
Meets expectations
Below expectations
Well below expectations
Fails to address the requirements
Key arguments
You have astutely outlined the articles key arguments and in doing so, demonstrated a detailed, accurate and insightful understanding of the subject matter.
You have clearly outlined the articles key arguments and in doing so, demonstrated a detailed and accurate understanding of the subject matter.
You have outlined the articles key arguments and in doing so, demonstrated a clear understanding of the subject matter.
You have somewhat outlined the articles key arguments and in doing so, demonstrated an adequate understanding of the subject matter.
Although you have outlined some of the articles key arguments this demonstrates an emerging understanding of the subject matter.
You have not outlined the articles key arguments and/or the arguments outline were irrelevant/inaccurate. This demonstrates a lack of understanding of the subject matter.
You have not outlined any key arguments. It is unclear whether you have read the article in question.
Merits & limitations
You have provided a critical, insightful and sophisticated evaluation of both the merits and limitations of the arguments outlined. These have been extensively evaluated in the context of a wide and highly relevant range of sources from the broader literature.
You have provided a critical and sophisticated evaluation of both the merits and limitations of the arguments outlined. These have been robustly evaluated in the context of a wide and very relevant range of sources from the broader literature.
You have provided a fairly detailed and sound evaluation of both the merits and limitations of the arguments outlined. These have been evaluated in the context of a variety of relevant sources from the broader literature.
You have somewhat evaluated both the merits and limitations of the arguments outlined. This discussion was somewhat descriptive and could have been more critical. Although you have used some relevant sources from the broader literature, a larger pool of sources would have added value to your analysis.
You have outlined some relevant merits and limitations though this discussion was descriptive and could have been more critical. You have drawn on a number of sources that do not add credibility or depth to your discussion and/or have used an insufficient range of sources to build a compelling argument.
The merits and limitation outlined are nor relevant and/or accurate. You have not used appropriate sources to evaluate the key argument and your subsequent discussion lacks relevance and insight.
The merits and limitations of key arguments has not been addressed.
HOSP2001 – Semester 1, 2020
Position within the literature
Based on your analysis of this article, you have astutely and skilfully determined its position within the broader literature. Your justification of this is convincing, compelling and strongly supported with evidence.
Based on your analysis of this article, you have skilfully determined its position within the broader literature. Your justification of this is convincing and strongly supported with evidence.
Based on your analysis of this article, you have presented a sound argument for its position within the broader literature. Your justification of this is adequately supported with evidence.
Based on your analysis of this article, you have presented an adequate argument for its position within the broader literature, though this could be more compelling and convincing. Your justification of this is somewhat supported with evidence.
Based on your analysis of this article, you have struggled to present an adequate argument for its position within the broader literature. Your justification of this is lacks relevance and does not adequately support your argument.
Based on your analysis of this article, you have not adequately positioned this article within the broader literature. Your justification is largely absent and/ or lacks relevance.
No assessment of the articles position within the broader literature has been made.
Final opinion
You have skilfully and eloquently synthesised your arguments to arrive at an insightful and highly informed opinion as the persuasiveness and rigour of the article being evaluated.
You have skilfully synthesised your arguments to arrive at an insightful and well-informed opinion as the persuasiveness and rigour of the article being evaluated.
You have synthesised your arguments to arrive at an informed opinion as the persuasiveness and rigour of the article being evaluated.
You have somewhat synthesised your arguments to arrive at an adequately informed opinion as the persuasiveness and rigour of the article being evaluated.
You have struggled to synthesise your arguments and your subsequent opinion as the persuasiveness and rigour of the article being evaluated lacks credibility.
You have not synthesised your arguments. Your subsequent opinion as the persuasiveness and rigour of the article being evaluated lacks credibility and relevance.
No opinion has been outlined as to the persuasiveness or rigour of the article being presented.
Readability
There is an obvious and logical connection between your discussion points, enhancing the structure, synthesis and readability of your assignment.
There is a logical connection between your discussion points which supports the synthesis and readability of your assignment.
Ideas have been developed, but connections are not always obvious. This occasionally detracts from the flow and readability of your assignment.
There is some development of ideas/themes, but this is sometime hindered by a ‘disconnect’ between key points, detracting from the flow and/or readability of your assignment.
There are few logical connections between discussion points. This has impacted on the structure, flow and readability of your assignment.
Points are not linked together in any meaningful or obvious way. Your assignment is difficult to read.
No attempt has been made at structuring this assignment.
HOSP2001 – Semester 1, 2020
Professionalism
There were no errors in your grammar or sentence mechanics. You have presented a highly professional assignment. Your assignment is within +/- 10% of the word limit.
While there were some very minor errors in your grammar and/or sentence mechanics, you were still able to present a professional assignment. Your assignment is within +/- 10% of the word limit.
Mostly correct grammar and spelling throughout. Errors can quickly and easily be corrected. Once completed, you will be able to present a professional assignment. Your assignment is within +/- 10% of the word limit.
Better proofreading will help you find and correct the minor and major errors in your spelling and grammar, thus ensuring you submit a more professional assignment. Your assignment is within +/- 15% of the word limit.
Spelling and/or grammar is frequently incorrect, resulting in an assignment that lack professionalism. Your assignment is within +/- 20% of the word limit.
Your assignment is overflowing with grammatical and/or spelling errors. It should not have been submitted in this format. Your assignment is within +/- 25% of the word limit.
The writing was illegible. Your assignment is an inappropriate length.
Referencing
You have astutely utilised relevant academic sources to effectively build and support your discussions. In-text APA referencing is extensive and accurate. The resulting reference list is likewise accurate.
You have effectively utilised relevant academic sources to effectively build and support your discussions. In-text APA referencing is accurate. The resulting reference list is likewise accurate.
Most of your academic sources are relevant to the discussions and have been used somewhat effectively. In-text APA referencing could be more extensive. The resulting reference list has some minor errors.
While some of your academic sources have merit, better utilisation for these would enhance your discussion. In-text APA referencing could be much more extensive. The resulting reference list has some errors.
The use of academic sources was often inadequate and/or inappropriate. Your in-text referencing was insufficient. There are some major errors in your application and use of the APA referencing style.
Your choice of sources does not credibly support your discussion. You did not use APA format and/or there are numerous significant errors in your application of this style of referencing.
No attempt at referencing has been made.