ENTER2017 eTourism Conference presentation

1. ENTER 2017 Research Track Slide Number 1
Key factors in the booking activity process:
the case of self-catering in Romand-Valais
destinations, Switzerland
Miriam Scaglione (a)
Colin Johnson (b)
Pascal Favre (a)
(a)
Institute of Tourism, University of Applied Sciences and Arts Western
Switzerland Valais
{miriam.scaglione, pascal.favre}@hevs.ch
http://www.hesvs.ch
(b)
San Francisco State University, California, USA
cj7@sfsu.edu

2. ENTER 2017 Research Track Slide Number 2
Agenda
• Relevance of the research subject
• Literature review
• Research questions
• Data & methodology
• Results
• Managerial conclusions
• Scientific conclusions
• Limits and future research

3. ENTER 2017 Research Track Slide Number 3
Relevance of the research
• Planning vacation process (PVP): set of
decisions that the vacationer takes prior to
departure.
– multi-faced and interrelated decisions
– lasts more than one day
• Internet increased interest in the PVP.
• Understanding the stages and the timing of
them could help to make better marketing
decisions.

4. ENTER 2017 Research Track Slide Number 4
Literature review (I)
Online PVP analysis
• Identifies
– Needs
– Determinants
– Antecedents
– Outcomes
– Online sources (Pan&Yang, 2016; Vogt &Fesenmaier, 1998)
• Usage
• Direction
• Degree
The importance of information sources change or shifts
depending on the phases of the decision process.

5. ENTER 2017 Research Track Slide Number 5
Literature review (II)
PVP stages
• Several models are in the literature i.e. Moutinho
(1987) van Raaij & Francken (1984) Vogt & Fesenmaier
(1998).
• Bieger and Laesser (2004) presented a 3 stages model
inspired by early scholars’ works Correia (2002), Leiper
(1990).
1. pre-decision stage : processing different sources of information.
2. trip decision : choice is almost irreversible with regard to the
destination, accommodation or the package of
chosen activities.
3. post-decision stage: further preparation of the travel after the
constraining decision.

6. ENTER 2017 Research Track Slide Number 6
Literature review (II)
PVP sequence / structural constraints
• PVP has two different dimensions:
– Structural constraints (Dellaert et al., 1998; Rashidi & Koo, 2016)
i.e. Vacation periods defined by school calendars
– Sequence or temporal dimension
Dellaert et al. (1998) suggest a conceptual framework for PVP
timing. The span of time between each choice and the actual
travel date are listed by time sequence order: (1) the choice of
destination, on average 7.17 months (2) travel companions
6.20 months (3) accommodation, 5.58 months (4) length of the
trip,5.57 months (5) bookings, 3.81 months.

7. ENTER 2017 Research Track Slide Number 7
Literature review (II)
PVP and attractions
Scholars inspired by Leiper (1990) classified the
attraction in the PVP taking into account the time
that the visitor decides to expend on each of them
once they decide the destination.
– primary and secondary attractions are those whose
length of visit can be evaluated.
– Tertiary attractions are those which the visitors are
not aware of their existence when they made the
destination decision (Botti, Peypoch, &
Solonandrasana, 2008).

8. ENTER 2017 Research Track Slide Number 8
Research question
• The present research focused on the booking timing period (BP) that is the
span of time or duration between the booking of the accommodation and
the actual travel date. In line with Dellaert et al. (1998).
• In terms of the three-stage model by Bieger and Laesser (2004), booking
activity is a part of the middle stage namely the trip decision.
– BP is a proxy for the duration of the third and last stage: post-decision
information.
• During BP Tertiary attractions Leiper (1990) discovered, BP estimations
give relevant marketing timing information by suppliers.
The aim of this research is to show any links
between the variable BP as the dependent
variable and countries of origin and/or
seasonal periods.

9. ENTER 2017 Research Track Slide Number 9
Survival Methods (I)
T is the random variable
measuring the arrival
time. For the BP
cumulative distribution
function is
To calculate this function,
a non-parametric
estimator is used:
Kaplan-Meier (KM)
estimator.
If we fix the share of bookings that have not
yet reached the actual travel date at 40% for
HW the BP is 135 days, whereas for LS it is
only 37 days.
LS in the Swiss market up to the moment
that the lines cross near 400 days and for
HW is more than 600 days.
( ) Pr( )B t T t= >
( ) 1 ( ) 1 ( )P T t P T t B t≤ = − > = −

10. ENTER 2017 Research Track Slide Number 10
Survival Methods (II)
• Roughly speaking, in order to compare the
different cases (origin and seasons), it is
necessary to compare the shape of the
survival plot pairwise.
• A nonparametric hypothesis test based on
Wilcoxon statistics having as a null
hypothesis that the two groups survival
function are equal (Allison, 2010).

11. ENTER 2017 Research Track Slide Number 11
Data (I)
• CITI / Rentalp platform
– Online self-catering booking
– 46 real estate agencies with more than 6’000
objects
– 6 months booking data sent every Monday to
Tourism Observatory of Valais
– Origin outside Europe not taken into account
– In total, this research has 130,677 transactions,
from 1 Jan 2010 to 26 Dec 2016.
– The cancelation conditions
• cancelation without charge, 89 days before arrival
• 50% : between 89 and 29 days,

12. ENTER 2017 Research Track Slide Number 12
Data (II)
The cancelation policy
• cancelation without charge -> 89 days before arrival
• 50% of charge : between 89 and 29 days,
• 100% to be paid if less than 29 days
New product “last minute bookings” BP is
between 7 to 28 days
•free cancelation 24 to 48 hours before the date
(but transaction fees will be levied).

13. ENTER 2017 Research Track Slide Number 13
Data (III)

14. ENTER 2017 Research Track Slide Number 14
Methodology
Loop 100 times
Resampling –test binomial

15. ENTER 2017 Research Track Slide Number 15
Results (I)
Median of the 100 simulations per origin

16. ENTER 2017 Research Track Slide Number 16
Results (II)
Median of the 100 simulations pairwise country/seasons having
significant different survival function

17. ENTER 2017 Research Track Slide Number 17
Managerial conclusions
• This research shows that there is a link between
timeliness and origin/season. This is relevant for DMOs
and service providers. They can differentiate the timing of
marketing actions depending on the market.
• Agencies should adapt their cancellation policy for
summer as the span of the BP is shorter than in winter,
especially high winter.
– Competition with other destinations and other
distribution channels like OTA.

18. ENTER 2017 Research Track Slide Number 18
Scientific conclusions
• Our methodology seems to be appropriate for
the analysis of BP using big data:
– Sampling methods
– KM and nonparametric hypothesis test based on
Wilcoxon statistics
– Binomial distribution for the analysis of the pairwise
results of the Wilcoxon hypothesis test

19. ENTER 2017 Research Track Slide Number 19
Limits and future research
• Very specific type of accommodation
– Only chalets or appartements
– Attracts specific publics
• Next : to complete a broader picture that could
identify main drivers within PVP, it would be
interesting to use new variables such as the
length of stay or the number of persons

20. ENTER 2017 Research Track Slide Number 20
Contact :
Miriam Scaglione
E-mail:
miriam.scaglione@hevs.ch
Tel : +41 27 606 9084