This document summarizes a research study on the impact of IT-enabled customer experience management (CEM) on customer perceptions and business performance in the hotel industry. The study examined how allowing customers to personalize their stay through an online portal (Hoxell) affected: 1) The intensity and frequency of customer preference elicitation. 2) Customer satisfaction ratings. 3) The proportion of customers booking directly with the hotel on return visits. The results showed that IT-enabled personalization significantly increased both the intensity and frequency of preferences shared, as well as customer satisfaction ratings. It also increased the likelihood of customers booking directly with the hotel on subsequent visits.

1. ENTER 2017 Research Track Slide Number 1
The Impact of IT-enabled Customer
Experience Management on Service
Perceptions and Performance
Daniele Marchesani, Gabriele Piccoli, and Tsz-wai Lui
Digital Data Streams Lab - dds.cct.lsu.edu
University of Pavia, Italy - Louisiana State University, USA - Ming Chuan University, Taiwan
daniele.marchesani01@universitadipavia.it
gpiccoli@cct.lsu.edu
irislui@mail.mcu.edu.tw

2. ENTER 2017 Research Track Slide Number 2
Introduction
• Technology: a brand differentiator in hospitality industry
• Personalization: a mean to tailor products, services and
transactional environment to individual customers’ needs.
Technology for Service Personalization.
• Research objectives:
– the immediate impact of IT-enabled CEM on preference
elicitation
– the distal effects of IT-enabled CEM on guests’ satisfaction
– the effect of IT-enabled CEM on hotels’ performance.

3. ENTER 2017 Research Track Slide Number 3
IT-enabled CEM
• IT-enabled CSS: collection of information systems that
mediate and enable delivery of service experiences with
the objective of increasing overall customer value.
• Customer Experience Management (CEM):
– the «practice of designing and reacting to customer
interactions to meet or exceed customer
expectations and, thus, increase customer
satisfaction, loyalty and advocacy» (Gartner)
– «the process of strategically managing a customer’s
entire experience with a product or a company»
(Schmitt, 2003)

4. ENTER 2017 Research Track Slide Number 4
IT-enabled CSS can be incorporated within CEM strategies.
New concept of IT-enabled CEM combines concepts of IT-
enabled CSS and CEM strategies, as strategic vehicle for
differentiation and strategic advantages, through tailored
experiences and service personalization.
In literature, many studies on IT use for CEM initiatives remain
conceptual with a need for further
empirical investigation.
IT-enabled CEM

5. ENTER 2017 Research Track Slide Number 5
Context
• 7 Swiss 3* and 4* hotels, partered with Innotour to voluntary
introduce Hoxell.
• Hoxell is a CEM work system, focused on enabling a deep
interaction between guests and hotels’ staff at multiple
touchpoints in the customer experience.
• Key element of Hoxell is service personalization through
MyPage, online module to select different personalization
options.
• Preferences chosen are transmitted to service personnel
through iPad available during the room preparation.

6. ENTER 2017 Research Track Slide Number 6

7. ENTER 2017 Research Track Slide Number 7
Data & Measures
• Preferences are collected through MyPage (virtual method) as
well as via traditional means (phone call, email, reception desk)
• Archival data from Hoxell and Property Management Systems
• Guests’ service assessments gathered through Booking.com
reviews
• 105k reservations data (stay data, preferences chosen,
reservation channels)
• 2 years of observations: from 9 months before MyPage
introduction to 14 months after

8. ENTER 2017 Research Track Slide Number 8
Data & Measures
Construct Measures Data Sources
Personalization Channel
Virtual personalization (MyPage), or
Traditional personalization (phone call, email,
reception desk)
Hoxell
Personalization Intensity personalization items requested Hoxell
Personalization Frequency
personalizing reservations (MyPage &
Traditional)
Hoxell
Service Rating
four-point ordinal scale with anchors “poor,”
“fair,” “good,” and “excellent”
Booking.com
Intermediated Reservations
Reservations done via OTAs, tour operators,
GDS
Hoxell
Direct Reservations
Reservations received hotels’ webpages, call,
walk-in
Hoxell
Control Variables
ADR, LOS, adults and children in the
reservation
Hoxell (PMS)

9. ENTER 2017 Research Track Slide Number 9
Hypothesis 1
• IT for Service Personalization: process of adopting IT solutions to
collect individuals’ own information, tailor the service and improve
the benefits delivered.
• CEM initiatives supporting preference elicitation enhance
customers’ awareness personalization options.
• Those who are interested in personalizing their experience are more
likely to communicate their requests to the firm.
Hypothesis 1a: Use of IT-enabled CEM increases the intensity of
preference elicitation.
Hypothesis 1b: Use of IT-enabled CEM increases the frequency of
service personalization.

10. ENTER 2017 Research Track Slide Number 10
Hypothesis 1
H1: Service personalization through IT-enabled CEM increases intensity
and frequency of preference elicitation.
• H1a – Intensity of Personalization (Poisson regression)
• H1b – Frequency of Personalization (Binomial regression)

11. ENTER 2017 Research Track Slide Number 12
Hypothesis 1: results
H1a – Personalization Intensity
Result: personalization through MyPage positively supports
service personalization intensity.
Estimated Std.error t value p-value
Intercept 0.051 0.031 1.66 0.097
MyPage 1.226 0.034 36.336 <0.001

12. ENTER 2017 Research Track Slide Number 13
Hypothesis 1: results
H1b – Personalization Frequency
Result: IT-enabled service personalization process generates an
increase in number of personalized stays, and CEM initiative does
not cannibalize the traditional personalization process.
Estimated Std.error t value p-value
Intercept -3.722 0.035 -105.571 <0.001
MyPage 0.329 0.033 9.860 <0.001
PersModule 0.354 0.043 8.163 <0.001

13. ENTER 2017 Research Track Slide Number 14
Hypothesis 2
• Better specification of service requirements experience reduces the
expectation-delivery gap with subsequent improvement in perceived
satisfaction.
• A CEM initiative that elicits appropriate customer preferences will
lead to higher perceived service ratings.
• Service personalization through CEM makes available benefits of
personalization to those never experienced them.
Hypothesis 2a: IT-enabled service personalization increases service
ratings.
Hypothesis 2b: IT-enabled service personalization increases comfort
ratings.

14. ENTER 2017 Research Track Slide Number 15
Hypothesis 2
H2: IT-enabled service personalization increases ratings of service, as
service (H2a) and comfort (H2b) scores.
Booking.com review scores to evaluate assessment of service and
comfort. Four-point scale “poor”, “fair”, “good”, “excellent” converted
into quantitative scale: 2.5 – 5 – 7.5 – 10.
Control Variables: ADR, LOS, price paid for personalization items, number
of adults and children.

15. ENTER 2017 Research Track Slide Number 16
Hypothesis 2: results
Estimated Std.error t value p-value Odds ratio
2.5|5 -5.26 0.39 -13.49 <0.001
5|7.5 -2.82 0.15 -18.85 <0.001
7.5|10 -0.18 0.1 -1.7 0.09
Personalization 0.46 0.2 2.28 0.02 1.58
Preference Price -0.02 0.01 -1.19 0.24 0.98
ADR -0.1 0.07 -1.43 0.15 0.91
LOS -0.12 0.04 -2.75 0.01 0.89
Children 0.25 0.12 2.03 0.04 1.28
H2a – Personalization on Service score
Result: for each rating level in the scale, customers who experience IT-enabled
service personalization have a 58% higher chance than their counterparts to give
a higher service rating category.

16. ENTER 2017 Research Track Slide Number 17
Hypothesis 2: results
H2b – Personalization on Comfort score
Result: for each rating level in the scale, customers who experience IT-enabled
service personalization have a 69% higher chance than their counterparts to give
a higher comfort rating category.
Estimated Std.error t value p-value Odds ratio
2.5|5 -4.75 0.37 -12.7 <0.001
5|7.5 -2.79 0.26 -10.63 <0.001
7.5|10 -0.39 0.24 -1.61 0.11
Personalization 0.52 0.21 2.51 0.01 1.69
Preference Price -0.03 0.01 -2.03 0.04 0.97
ADR 0.11 0.08 1.48 0.14 1.12
LOS -0.11 0.04 -2.59 0.01 0.89
Adults 0.01 0.11 0.08 0.93 1.01

17. ENTER 2017 Research Track Slide Number 18
Hypothesis 3
• In hotel industry, commissions paid to third-party OTAs often
represent high costs critically affecting profits.
• IT-enabled CEM allows to develop an electronic relationship with
guests adopting service personalization.
• Service personalization ultimately increases customer loyalty
towards hotels.
• Long-term relationships translate into economic benefits through
channel disintermediation.
Hypothesis 3: IT-enabled CEM result in increased disintermediation.

18. ENTER 2017 Research Track Slide Number 19
Hypothesis 3
• H3: proportion of guests moving from intermediated channel on their
1° visit to direct channel on the 2°visit after using MyPage service
personalization.
• Classification of reservations among ones related to:
– Direct channel (i.e. hotel website, email, phone call, walk-in)
– Intermediated channels (OTAs, tour operators, GDS)
• Control variables: ADR, number of adults and children

19. ENTER 2017 Research Track Slide Number 20
Hypothesis 3: results
Estimated Std.error z-value p-value Odds ratio
Intercept -3.91 0.51 -7.75 0.00 0.02
Personalization(1st) 1.24 0.56 2.22 0.03 3.45
ADR(2nd) -0.53 0.21 -2.54 0.01 0.59
Adults(2nd) 0.25 0.40 0.61 0.54 1.28
Children(2nd) -12.87 894.34 -0.01 0.99 0.00
H3 – Personalization on Disintermediation
Result: IT-enabled service personalization through Hoxell supports
disintermediation (+245%).

20. ENTER 2017 Research Track Slide Number 21
Conclusions
Research Objectives
H1: IT-enabled CEM can be used to improve preference
elicitation from guests
H2: Service personalization results in higher guests’
satisfaction with overall experience at the hotel
H3: Service personalization results in higher guests’
propensity to reserve directly second stays.

21. ENTER 2017 Research Track Slide Number 22
Findings on Preference Elicitation
H1: IT-enabled service personalization enables guests to tailor the
experience. It does so
• by identifying appropriate items to personalize their stays
• by reducing friction created by the online system
• by increasing both number and variety of preferences (including
non-essential requests).

22. ENTER 2017 Research Track Slide Number 23
Findings on Guest’s Satisfaction
H2: through making guests more aware of preference
available for their stays personalizations, IT-enabled
service personalization significantly improves ratings of
service and comfort.

23. ENTER 2017 Research Track Slide Number 24
Findings on Disintermediation
H3: IT-enabled CEM enables the firm to foster direct
relationships with customers and, as consequence,
improves loyalty.
Hotels in the study achieved strong positive share-shift
and were able to shift returning guests to the low cost
direct channels.

24. ENTER 2017 Research Track Slide Number 25
Conclusions
• Through personalization, IT-enabled CEM strategies support
guests’ preferences elicitation, which translate into:
– enhanced personalization intensity and frequency
– higher satisfaction
– improved electronic relationships, and …
– sales disintermediation.
• Contribution to the literature: empirical research of IT use for
service personalization as part of an overall CEM strategy.
• Contribution to the industry: evidence of ways for IT to generate
benefits for both guests and hotels, developing new competitive
advantages.

25. ENTER 2017 Research Track Slide Number 26
Acknowledgements