Article

The Service Revolution, Intelligent Automation and Service Robots

Abstract

Accepted for publication in The European Business Review in a Special Issue organized by the Centre on AI Technology for Humankind, National University of Singapore. Suggested citation: Jochen Wirtz, Werner Kunz and Stefanie Paluch (2021), “The Service Revolution, Intelligent Automation and Service Robots,” The European Business Review, forthcoming.
AI AND HUMANS
A SPECIAL REPORT ON
By AiTH, NUS Business School
Dawn of the Service Revolution1
The industrial revolutions started in the
late eighteenth century and automated
blue-collar jobs in manufacturing, thereby
providing massive structural benets to our
societies. They rapidly increased our standard
of living by bringing high-quality, low-cost
manufactured goods to the masses, and relieved
people from laborious manual work.
Are there parallels between
the Industrial Revolution
of the eighteenth century
and the changes now
being wrought on twen-
ty-rst-century society by
recent advances in AI and
robot technology? And, if
so, what are some of the
consequences for which we
should prepare ourselves
this time round?
Today, our economies seem to face a turning
point similar to the industrial revolution, but this
time in the service sector. Technologies rapidly
become smarter and more powerful, while, at the
same time, they get smaller, lighter and cheaper.
These technologies include hardware such as that
related to physical robots, drones and autonomous
vehicles and their components (e.g., processors,
38 The European Business Review January - February 2021
BY JOCHEN WIRTZ,
WERNER KUNZ
AND STEFANIE PALUCH
THE SERVICE REVOLUTION,
INTELLIGENT AUTOMATION AND
SERVICE ROBOTS
The "Gran Caè Rapallo"
restaurant in Liguria is the
first restaurant in Italy to
use robot waiters.
Stefano Mazzola / Shutterstock.com
sensors, cameras, chips), wearable technologies,
and code or software such as analytics, speech
processing, image processing, biometrics, virtual
reality, augmented reality, cloud technologies,
mobile technologies, geo-tagging, low-code plat-
forms, robotic process automation (RPA) and
machine learning. Together, these technologies
will transform virtually all service sectors. Service
robots and articial intelligence (AI), combined
with these technologies, will lead to rapid innova-
tion that can dramatically improve the customer
experience, service quality and productivity, all at
the same time.2
Robot- and AI-delivered service offers
unprecedented economies of scale and scope,
as the bulk of the costs are incurred in their
development. Physical robots cost a fraction
of adding to the headcount, and virtual robots
can be deployed at negligible incremental cost.
Virtual service robots (e.g., chatbots and virtual
agents) can be scaled at close to zero incre-
mental cost. Such dramatic scalability does not
apply only to virtual service robots such as
chatbots, but also to ‘visible’ ones such as holo-
grams. For example, an airport could install a
hologram-based humanoid service robot every
50 metres to assist passengers and deal with
common questions (e.g., provide arrival and
departure information, directions to check-in
counters for a particular airline, and an airport
hotel) in all common languages. These holo-
grams only require low-cost hardware (i.e., a
camera, microphone, speaker and projector) and
do not need to take up oor space (travellers can
push their baggage carts through a hologram
when it gets crowded).
Already, many rms are showing eager
interest in experimenting with service robots.
For example, hotels are introducing humanoid
robots in their lobbies, where they welcome
guests, provide information and entertain guests.
At airports, they scan boarding passes and help
passengers to nd the right departure gate. Self-
moving check-in-kiosk robots detect busy areas
and autonomously go there to help passengers
reduce waiting time. Particularly, the outbreak
of COVID-19 has increased the demand for
medical service robots that check people’s
temperature or take over disinfection work3.
The market size for service robots is projected
to reach USD 41.5 billion by 2027.4
Such robots in hotels, airports and restaurants,
chatbots and delivery bots are only the begin-
ning of the service revolution. This means that,
similar to the shift that started in the industrial
revolution from craftsmen to mass produc-
tion, an accelerated shift in the service sector
towards robot- and AI-delivered services can
be expected. The exciting prospect is that many
services, including healthcare and education, are
likely to become available at much lower prices
and much better quality, and lead to a dramatic
increase in our standard of living.
What Are Service Robots and
How Are They Different from Current
Self-Service Technologies?
Service robots have been dened as “system-
based autonomous and adaptable interfaces that
interact, communicate and deliver service to an
organisation’s customers”.5 These abilities differ-
entiate service robots from traditional self-service
technologies (SSTs) that we are familiar with in
the context of ticketing machines, websites and
apps. As shown in table 1, service robots can
deal with unstructured interactions and guide
customers through their service journey. For
example, a ticketing robot will not let customers
get stuck, as it can ask clarifying questions (e.g.,
“Is your return trip today?” “Can you travel
off-peak?) and can even recover customer errors
Robot- and
AI-delivered
service offers
unprecedented
economies
of scale and
scope, as
the bulk of
the costs
are incurred
in their
development.
www.europeanbusinessreview.com 39
AI AND HUMANS
A SPECIAL REPORT ON
By AiTH, NUS Business School
Service Aspect Self-Service Technologies (SSTs) Service Robots
Customer Service
Scripts and Roles
• Customers have to learn the service script and
role, and follow it closely.
• Deviations from the script tend to lead to
service failure and abandonment of
unsuccessful transactions.
• Need to be self-explanatory and intuitive,
as customers have to control and navigate
the interaction.
• Customers do not need to learn a particular
role and script beyond what they would do
when interacting with a frontline employee.
• Flexible customer journeys, interaction and
scripts are supported.
• Can guide the customer through the
service process very much as a service
employee would.
Customer Error
Tolerance
• Generally, do not function when customers
make errors or use the SST incorrectly.
• Generally, are not eective in recovering
customer errors; customers typically have
to start the transaction again, or a service
employee needs to take over.
• Are customer error-tolerant.
• Can recover customer errors and guide
the customer to conclude a successful
service transaction.
Service Recovery
Capability
• The service process tends to break down when
there is a service failure; recovery is unlikely
within the technology.
• Is “trained” to recover common
service failures.
• Can recover the service by oering
alternative solutions, very much as a
service employee would.
(e.g., a wrong button pressed, incorrect informa-
tion entered or a rejected credit card). For most
standard services, customers will interact with
service robots in much the same way as with
service employees (e.g., “I need a same-day return
ticket and can I use Apple Pay?”).
What Are the Differences Between Service
Robots and Human Employees?
Robots are not able to feel and express real
emotions. This can be important in some
services, whereby the service management liter-
ature distinguishes between deep acting (i.e.,
employees displaying real emotions) and surface
acting (i.e., they show supercial fake emotional
responses).7 In contrast, a robot’s emotions are
just displayed and not authentic. Consumers
generally know this and respond accordingly.
On the other hand, robots can surface-act and
consistently be pleasant; they are not prone
to emotional burnout. This may make robots
perform better than humans in jobs that require
display of surface-acted emotions. Other signi-
cant differences are summarised in table 2.
What Services Will Be Delivered by Robots?
Initial deployments of service robots focused
on simple and repetitive tasks that tended to be
low in their cognitive and emotional complexity
(gure 1). For example, physical robots in hotels
deliver room service and bring baggage to guest
rooms. Text and voice-based conversational
agents increasingly handle routine customer
interactions. Even when interacting with a
Robots can
surface-act and
consistently be
pleasant; they
are not prone
to emotional
burnout.
Table 1 Contrasting Service Robots with Traditional Self-Service Technologies6
40 The European Business Review January - February 2021
Service Aspect Self-Service Technologies (SSTs) Service Robots
Customer Service
Scripts and Roles
• Customers have to learn the service script and
role, and follow it closely.
• Deviations from the script tend to lead to
service failure and abandonment of
unsuccessful transactions.
• Need to be self-explanatory and intuitive,
as customers have to control and navigate
the interaction.
• Customers do not need to learn a particular
role and script beyond what they would do
when interacting with a frontline employee.
• Flexible customer journeys, interaction and
scripts are supported.
• Can guide the customer through the
service process very much as a service
employee would.
Customer Error
Tolerance
• Generally, do not function when customers
make errors or use the SST incorrectly.
• Generally, are not eective in recovering
customer errors; customers typically have
to start the transaction again, or a service
employee needs to take over.
• Are customer error-tolerant.
• Can recover customer errors and guide
the customer to conclude a successful
service transaction.
Service Recovery
Capability
• The service process tends to break down when
there is a service failure; recovery is unlikely
within the technology.
• Is “trained” to recover common
service failures.
• Can recover the service by oering
alternative solutions, very much as a
service employee would.
human service employee, that employee may well
be supported by AI, and calls are pre-screened,
preprocessed and then escalated to the human
agent because of their complexity. The outcome
is that customer contact staff do not have to deal
with high volumes of trivial customer requests
but instead can spend their time on higher-value
and higher-level tasks. For example, a chatbot
for the NUS MBA Programme handled 20,000
unique conversations per month right after
launch and answered all the routine questions
the admission team had to deal with previously
(e.g., “Do I need a GMAT?” “When are the fees
payable?” and “When is the application dead-
line?”). The admission team can now focus on
top-quality candidates and the trickier and more
complex discussions.9
Dimension Service Employees Service Robots
Employee/ Robot
Training and Learning
• Act as individuals, individual learning
• Need training
• Limited memory and access
• Act as part of systems, are connected,
system learning
• Upgradable, system-wide
• Virtually endless memory and access
Customer Experience • Heterogeneous output
• Customisation and personalisation depend
on employee skill and eort
• Unintended biases
• Have genuine emotions
• Can engage in deep acting
• Can engage in out-of-box thinking and
creative problem-solving
• Homogenous output
• Customisation and personalisation can
be delivered on scale at consistent
quality and performance
• Potentially no biases
• Can mimic emotions
• Can engage in surface acting
• Limited out-of-box thinking, have
rule-bound limits
Firm Strategy • Service employees can be a source of
competitive advantage
• High incremental cost
• Low economies of scale and scope
• Dierentiation on service can be based on
better hiring, selection, training, motivation
and organisation of service employees
• Service robots are unlikely to be a source of
competitive advantage, as service robot
solutions are likely to be supplied by third-party
providers (very much as ATMs are sold to banks)
• Low incremental cost
• High economies of scale and scope
• Economies of scale and scope and related
network and service platform eects will become
important sources of competitive advantage
Table 2 Contrasting Frontline Employees with Service Robots8
www.europeanbusinessreview.com 41
helloabc / Shutterstock.com
AI AND HUMANS
A SPECIAL REPORT ON
By AiTH, NUS Business School
In addition to routine tasks, services that
require high cognitive and analytical skills
will be delivered effectively by service robots
(e.g., nancial services). For example, service
robots can analyse large volumes of data,
integrate internal and external information,
recognise patterns and relate these to customer
proles. Within minutes, these robots can
propose best-tting solutions and make
recommendations.
It is difcult for robots to deal with
emotions that go beyond a pleasant display of
surface demeanour. Especially complex and
emotionally demanding tasks are still better
handled by service employees, as they can
bring genuine emotions such as excitement
and joy or empathy and compassion to the
service encounter. For example, in complaint
and service recovery situations, humans can
respond better to the individual context and
show understanding.
Human-robot teams will increasingly deliver
tasks that require high cognitive and emotional
skills. For example, in a healthcare context,
service robots will do the analytical work (e.g.,
analyse symptoms and compare them with
databases to identify possible diagnoses), and
humans will make the nal recommendations
and decisions and take over the social and
emotional tasks (e.g., advising and persuading
patients). For example, the rst author’s
daughter returned from Singapore to Munich
with dengue fever; the symptoms only showed
a week after her return. General practitioners in
Germany may never see a dengue fever patient
in their professional life and may not be effective
in diagnosing it. On the other hand, a service
robot compares patient data and symptoms and
provides a ‘hit list’ of possible diseases with a t
index. The general practitioner can then work
down the list and discuss with the patient (e.g.,
“Have you been in the tropics in the last two
weeks?”) and then identify the most likely diag-
nosis and test for it.
Implications for Service Organisations
This revolution of the service sector will have
enormous implications for business. Some of
the most pressing issues for service organisa-
tions to tackle include11:
Implication # 1
Restructure the Service Frontline.
With the implementation of service robots,
organisations will inevitably transform and be
dramatically reorganised. This requires strong
leadership and support, and the willingness
and ability of employees to change. That is,
employees will be assigned to new tasks and
responsibilities and will need to develop the
required skills (incl., RPA, basic programming
and technology troubleshooting).
Implication # 2
See Robots as a Long-Term
Investment.
The deployment of service robots comes with
investments, including acquisition costs, devel-
opment of IT specialists and programmers,
and building virtual networks and maintenance
of systems. It takes some time for these invest-
ments to be recouped; typically less than 12
months for successful implementations.12
It is difcult for
robots to deal
with emotions
that go beyond
a pleasant
display of
surface
demeanour.
Figure 1
The Service Robot Deployment Model10
SOCIAL /
EMOTIONAL
SKILLS
Simple tasks
Complex tasks
COGNITIVE /
ANALYTICAL
SKILLS
HUMAN
ROBOT
HUMAN & ROBOT
Simple
tasks
Complex
tasks
42 The European Business Review January - February 2021
Implication # 3
for Cost-Effective Service Excellence.
We predict that hybrid human-robot teams
and collaboration will be the service model
of the future for many more complex service
contexts. These hybrid teams will be able to
realise productivity and service quality gains
for the company by combining the advantages
of AI and human employees. Robots’ enor-
mous knowledge and data is an undeniable
advantage for creating customised services.
Organisations should focus on implementing,
managing and ne-tuning the deployment of
robot-employee-customer co-creation teams
to deliver unprecedented quality of interac-
tion for their customers.13
Implication # 4
Mitigate Potential Risks of Robot
Deployment.
Organisations need to mitigate potential
misconceptions, prejudice and anxieties related
to customer-facing service robots, such as
algorithm aversion, perceived loss of the
human touch, and consumer privacy. This
requires organisations to embrace corporate
digital responsibility (CDR) and develop a set
of shared values, norms and actionable guide-
lines on the responsible use of technology
along the full cycle. For example, related to
data, it includes their capturing (e.g., using
biometrics or social media accounts), their use
(e.g., building variables such as a healthiness
index or nancial score), decision-making (e.g.,
approving loans and setting interest rates), and
their retirement (e.g., when information on a
bounced payment should be deleted from the
rm’s database).14
In summary, service robots and AI will trans-
form our service sector and bring unprecedented
improvements to the customer experience,
service quality and productivity, all at the same
time.15 In turn, this service revolution has the
potential to dramatically increase our standard
of living, very much as the industrial revolution
did for manufactured goods. The difference is
that, this time, it is services such as nancial,
logistics, healthcare and education that are
being industrialised.
We predict
that hybrid
human-robot
teams and
collaboration
will be the
service model
of the future
for many
more complex
service
contexts.
AI as an Opportunity
www.europeanbusinessreview.com 43
AI AND HUMANS
A SPECIAL REPORT ON
By AiTH, NUS Business School
References
1
This article draws on Jochen Wirtz, Paul Patterson, Werner Kunz,
Thorsten Gruber, Vinh Nhat Lu, Stefanie Paluch, and Antje Martins (2018),
“Brave New World: Service Robots in the Frontline”, Journal of Service
Management, Vol. 29, No. 5, p. 909, https://doi.org/10.1108/JOSM-04-
2018-0119; Pascal Bornet, Ian Barkin and Jochen Wirtz (2021), Intelligent
Automation - Learn How to Harness Articial Intelligence to Boost Business
& Make Our World More Human, https://intelligentautomationbook.com;
Jochen Wirtz (2020), “Organizational Ambidexterity: Cost-Effective Service
Excellence, Service Robots, and Articial Intelligence”, Organizational
Dynamics, Vol. 49, No. 3, https://doi.org/10.1016/j.orgdyn.2019.04.005.
2
Jochen Wirtz and Valarie Zeithaml (2018), “Cost-Effective Service
Excellence”, Journal of the Academy of Marketing Science, Vol. 46, No. 1,
pp. 59-80. https://link.springer.com/article/10.1007/s11747-017-0560-7
3
Paluch, Stephanie, Wirtz, Jochen and Kunz, Werner H. (2020), “Service
Robots and the Future of Service”, in Marketing Weiterdenken –
Zukunftspfade für eine marktorientierte Unternehmensführung, 2nd ed.,
Bruhn, M. and Kirchgeorg, M., and Burmann, C., eds., Springer Gabler-
Verlag, pp. 423-435, https://doi.org/10.1007/978-3-658-31563-4
4
Service Robotics Market Size Report and Industry Forecast, Fortune
Business Insights, 2020. https://www.fortunebusinessinsights.com/
industry-reports/service-robotics-market-101805
5
Jochen Wirtz, Paul Patterson, Werner Kunz, Thorsten Gruber, Vinh Nhat
Lu, Stefanie Paluch, and Antje Martins (2018), “Brave New World: Service
Robots in the Frontline”, Journal of Service Management, Vol. 29, No. 5, p.
909, https://doi.org/10.1108/JOSM-04-2018-0119;
6
Adapted from Jochen Wirtz, Paul Patterson, Werner Kunz, Thorsten
Gruber, Vinh Nhat Lu, Stefanie Paluch, and Antje Martins (2018),
“Brave New World: Service Robots in the Frontline”, Journal of
Service Management, Vol. 29, No. 5, p. 909, https://doi.org/10.1108/
JOSM-04-2018-0119.
7
Jochen Wirtz and Christina Jerger (2017), “Managing Service Employees:
Literature Review, Expert Opinions, and Research Directions”, Service
Industries Journal, 36(15-16), 757-788.
8
Adapted from Jochen Wirtz, Paul Patterson, Werner Kunz, Thorsten
Gruber, Vinh Nhat Lu, Stefanie Paluch, and Antje Martins (2018),
“Brave New World: Service Robots in the Frontline”, Journal of
Service Management, Vol. 29, No. 5, p. 909, https://doi.org/10.1108/
JOSM-04-2018-0119.
9
Try this chatbot at https://mba.nus.edu.sg/.
10
Adapted from Jochen Wirtz, Paul Patterson, Werner Kunz, Thorsten
Gruber, Vinh Nhat Lu, Stefanie Paluch, and Antje Martins (2018),
“Brave New World: Service Robots in the Frontline”, Journal of Service
Management, Vol. 29, No. 5, pp. 907-931, https://doi.org/10.1108/
JOSM-04-2018-0119.
11
This section is based on Paluch S., Wirtz J., Kunz W.H. (2020) Service
Robots and the Future of Services. In: Bruhn M., Burmann C., Kirchgeorg
M. (eds) Marketing Weiterdenken. Springer Gabler, Wiesbaden. S. 423-435
https://doi.org/10.1007/978-3-658-31563-4_21
12
Pascal Bornet, Ian Barkin and Jochen Wirtz (2021), Intelligent Automation
- Learn How to Harness Articial Intelligence to Boost Business & Make
Our World More Human, https://intelligentautomationbook.com;
13
Jochen Wirtz (2020), “Organizational Ambidexterity: Cost-Effective Service
Excellence, Service Robots, and Articial Intelligence”, Organizational
Dynamics, Vol. 49, No. 3, https://doi.org/10.1016/j.orgdyn.2019.04.005.
14
Lara Lobschat, Benjamin Müller, Felix Eggers, Laura Brandimarte, Sarah
Diefenbach, Mirja Kroschke and Jochen Wirtz (2020), “Corporate Digital
Responsibility”, Journal of Business Research, published online rst.
15
Jochen Wirtz and Valarie Zeithaml (2018), “Cost-Effective Service
Excellence”, Journal of the Academy of Marketing Science, Vol. 46, No. 1,
pp. 59-80. https://link.springer.com/article/10.1007/s11747-017-0560-7
About the Authors
Jochen Wirtz is Vice Dean MBA Programmes and
Professor of Marketing at the National University
of Singapore. He is also an international fellow of
the Service Research Center at Karlstad University,
Sweden, an academic scholar at the Cornell Institute
for Healthy Futures (CIHF) at Cornell University, US,
and at the Global Faculty of the Center for Services
Leadership (CSL) at Arizona State University, USA.
Dr Wirtz is a leading authority on service manage-
ment and has over 200 academic publications,
including six features in Harvard Business Review
and over 20 books. His latest books include Intelligent
Automation - Learn How to Harness Articial Intelligence
to Boost Business & Make Our World More Human (2021)
and Services Marketing: People, Technology, Strategy (9th
edition, 2021). Watch Jochens Master Class to better
understand service robots and their implications -
https://www.youtube.com/c/ProfessorJochenWirtz
Werner H. Kunz is Professor of Marketing and
director of the digital media lab at the University
of Massachusetts Boston. His research interests
are in AI, robots, digital and social media, social
networks, innovation and service research. His
work has been published, amongst others, in the
International Journal of Research in Marketing, Journal
of Retailing, British Journal of Management, Journal of
Medical Internet Research, Journal of Business Research,
Journal of Service Management and Computational Statistics
and has been awarded multiple times. He is founder
and host of the Social Media Days at UMass Boston
and current board member of the Service Research
Special Interest Group (SERVSIG) of the American
Marketing Association (AMA), the primary profes-
sional association of service research, with over 2,000
community members worldwide.
Stefanie Paluch is Professor for Services and
Technology Marketing at RWTH Aachen University.
She is a research fellow at King's College in London
and she was appointed Senior Fellow at Hanken School
of Economics in Helsinki. Her research focuses on the
perception and acceptance of AI, e.g., service robots
and smart services, by consumers, and their imple-
mentation in an organisational context. She publishes
her research in leading international journals, such as
the Journal of Service Research, Journal of Business Research,
Journal of Service Management, Journal of Service Marketing
and the Journal of Service Theory and Practice.
44 The European Business Review January - February 2021
Click or scan to see the book's
website for further resources:
Click or scan to order
from Amazon:
Click or scan to watch Jochen's
Masterclass on Robotics and AI:
... A.I and frontline robots are trying to increase productivity and reduce costs globally by encouraging considerable growth in sales of frontline robots and theoretically, research are committed to understanding their consequences. Recently, robots has been used to interact directly and physically with customers in frontline services, which is shaking up service delivery and customerorganization relationships in many sectors of economy such as banking (Belanche et al., 2019), hospitality and tourism (Akdim et al., 2021;Belanche, Casaló, Flavián, et al., 2020b;Byrd et al., 2021;Romero & Lado, 2021), service delivery (Webster & Ivanov, 2020) and healthcare (Wirtz et al., 2021). For example, as (Mende et al., 2019) noted, it is uncertain whether AI services (i.e. ...
... Equally, (Puntoni et al., 2021) noted the advantages that AI can offer to consumers and the expenses consumers can experience when interacting with AI. The use of robots to interact in services is an originality that can affect customer choices (Van Doorn et al., 2017), customer experience, quality of service and production (Wirtz et al., 2021). Ground-breaking organizations have started using robots instead of human agent in frontline services. ...
... The differences between Frontline Robot and Self Service Technologies (SSTs) is stated in these studies (Belanche, Casaló, Flavián, et al., 2020b;Wirtz et al., 2018Wirtz et al., , 2021 have clearly differentiated between the two technologies. The differences between Frontline Robot and Human Agent were highlighted in these studies (Belanche, Casaló, Flavián, et al., 2020b;Wirtz et al., 2018Wirtz et al., , 2021. ...
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Robotic technology is an application of Artificial Intelligence (A.I.) where machines mimic the intelligence of human agents. Globally, frontline robots are replacing frontline employees in several sectors of the economy for different services. Analogous to the industrial revolution, the service sector of our economy is facing critical changes. The overall result of this is to have a revolutionized smart nation. This study utilizes a conceptual method that is based on service robot theories. Although, the hotel industry globally has already started adopting and implementing frontline robots in their frontline services, however, only a little information is obtainable about the potential consequences of using the frontline robots in the hotels industry exist. With this, the study tends to achieve the following objectives; 1) to give an insight into the basic concepts of frontline robots, and service robots as it relates to service delivery. 2) to review extant literature to analyze and compare the implications of adopting the use of Frontline Robots as Service Robots in hotel as one of the hospitality industry as compared to the use of human agents in a global perspective but considering only micro level because it is the fundamental level at the same time a litmus ground for testing every business progress (productivity and acceptance). The implications can be viewed at the micro level for all the key stakeholders at that level. 3) To determine the most recommendable agents by customers i.e., Frontline Robots or Human Agents or Human-Robots-Collaboration (HRC) known as a semi-automated system. 4) To highlight the gap in the research field particularly in the African context. Based on the analyses, the result revealed that the use of humanoid robots that can handle cognitive and emotional tasks is advisable or the use of a semi-automated system that gives a better customer relation management (CRM) service than the conventional customer-human agent service.
... The retail industry is facing several challenges, compelling companies to reinvent their business models to enhance the customer experience and offer personalized services to shoppers . Following these changes, companies are introducing new technologies and orchestrating their service encounters with the support of AI and robotics (Lariviere et al., 2017;Marinova et al., 2017;Wirtz and Jerger, 2016;Wirtz et al., 2021). In particular, the market of robotics is rapidly growing across all sectors, with the potential of providing a broad range of benefits to organizations. ...
... However, we observe that this relationship is significantly stronger when customers are interacting with a human sales associate than with a service robot. Interactions with a robot tend to make the experience more efficient, while simultaneously reducing the level of immersion across the key moments of the service encounter, such as store introduction and brand storytelling, leading to a shorter time spent in store by customers (Wirtz et al., 2021). This might also be explained by the customers' understanding that the emotions exhibited by robots are artificial . ...
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... Existing studies on service robots are mainly conceptual (Ivanov and Webster 2020;Murphy, Hofacker, and Gretzel 2017;Robinson et al. 2020;Tung and Au 2018;Van Doorn et al. 2017;Wirtz, Kunz, and Paluch 2021), while the limited empirical studies have primarily focused on the drivers of adoption, emphasizing the importance of robot appearance (Blut et al. 2021;Tussyadiah and Park 2018). Other scholars have instead used experimental methods to understand how customers would hypothetically interact and respond to service encounters with robots (e.g., Jörling, Böhm, and Paluch 2019;McLeay et al. 2021;Mende et al. 2019;Tussyadiah, Zach, and Wang 2020;Van Doorn et al. 2017). ...
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... Service robots (SRs) are automated technology in a physical embodiment equipped with some degree of Artificial Intelligence (AI), and consisting of adaptable interfaces enabling them to interact and communicate with customers in co-producing services (Paluch, Tuzovic, Holz, Kies, & Jörling, 2021;. The integration of AI into these embodied machines allows SRs to be programmed to "learn" so as to offer better functional performance (e.g., ask clarifying questions, recover customer errors, provide counter-intuitive solutions) and better respond to socio-emotional cues (e.g., provide sympathetic responses and gestures depending on customer emotions), making service interactions more similar to those experienced with human staff (Wirtz, Kunz, & Paluch, 2021). Thus, it is not surprising that an increasing number of firms have leveraged AI to enhance their customers' service experience (Forbes, 2021). ...
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... While AI-empowered robots are speedily occupying a larger share of mechanical and analytical tasks, they are still incapable of reaching the empathetic intelligence level because they do not have the ability to "experience" and "feel" (Huang and Rust, 2018;Luo et al., 2019b). Indeed, given the limits for out-of-box thinking, robots are unable to feel and express real and authentic emotions with care (Wirtz et al., 2021). This lack of empathy is a hard problem in computationalism (McDermott, 2007), which can lead to the dehumanization issue of services (Fust e-Forn e, 2021). ...
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... industrial or domestic robots) based on their ability to work as a team with human stakeholders . Previous research has compared FLEs and FLRs extensively in various aspects of service provision (Huang andRust, 2018, 2021b;Wirtz et al., , 2021. A primary aspect of this comparison is their intelligence levels (Huang and Rust, 2018). ...
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Jochen Wirtz (2020), "Organizational Ambidexterity: Cost-Effective Service Excellence, Service Robots, and Artificial Intelligence", Organizational Dynamics, Vol. 49, No. 3, https://doi.org/10.1016/j.orgdyn.2019.04.005. 14