Slides that correspond to the paper: Schulz, Fabian / Schlereth, Christian / Skiera, Bernd / Mazar, Nina (2015), "Advance Payment Systems: Paying Too Much Today and Being Satisfied Tomorrow", International Journal of Research in Marketing, Vol. 32, Issue 3, forthcoming. Abstract: Advance payment systems represent a pricing innovation, in which companies predict customers' future consumption for the following year and then bill a series of monthly, uniform advance payments. Any difference between predicted and actual consumption gets settled at the end of the year with a refund or extra payment. Companies thus gain earlier access to funds and lower risk of customer defaults; customers benefit from predictable monthly payments. However, customers' reactions to a refund or extra payment sequence in an advance payment system remain unclear. Three theoretical lenses offer predictions about customers' advance payment system preferences: prospect theory, with a focus on silver lining and hedonic editing principles; mental accounting; and the value of sequences. Using three empirical studies with survey and billing data of more than 20,000 customers to examine their reactions to refunds and extra payments, this paper reveals that receiving a refund reduces customers' price awareness, increases their recommendation likelihood, and reduces churn and tariff switching, as long as the refund is not too high. The findings illustrate both the consequences and the boundary conditions of the silver lining principle with large-scale field studies.

1. Advance Payment Systems:
Paying Too Much Today and
Being Satisfied Tomorrow
Forthcoming in International Journal of Research in
Marketing, 2015, Vol. 32, Issue 3, 238-250
Fabian Schulz
Goethe University Frankfurt
Christian Schlereth
WHU – Otto Beisheim School of Management
Nina Mazar
University of Toronto
Bernd Skiera
Goethe University Frankfurt

2. AdvancePpayment Systems (also referred to as equal billing)
Refund
Extra
payment
Usage predic-
tion for billing
cycle
Calculation of
advance pay-
ment rates
Determina-
tion of actual
usage in
billing cycle
Determination
of last billing
rate
1

3. Advance Payment Systems (APS) are best known for utility services
billing and taxes
 e.g., electricity, water, gas… taxes
But APS are applicable to ANY recurring service where consumption and
payments are separated in time
Credit cards balances Cloud computing services Pay-as-you-drive car insurances
2

4. Also outside of Germany, APS are increasingly advertised by
electricity service providers
Company
Advance
payment
system
offered
Optional or
mandatory
France
EDF Yes Optional
ENI Yes Optional
GDF Suez Yes Optional
Poweo Direct Energy Yes Optional
Germany
EnBW Yes Mandatory
Eon Yes Mandatory
EWE Yes Mandatory
RWE Yes Mandatory
Vattenfall Europe Yes Mandatory
Italy
Acqua Gas Azienda
Municipale No -
Aem No -
Edison SpA No -
Enel No -
Hera Group No -
Spain
EDP Renováveis No -
Endesa Yes Optional
Eon Spain No -
Gas Natural Yes Optional
Iberdrola Yes Optional
UK
EDF Energy Yes Optional
Eon UK Yes Optional
National Grid Yes Optional
RWE npower Yes Optional
Scottish and Southern nergy Yes Optional
Europe US
3

5. Service providers can choose between three payment systems;
our focus: advance payments
Pros
Small non-
payment
risk
Earlier
cash flow
Low oper-
ational
costs
Customer
loyalty
High Low
Payment
timing
Advance payment
(Predicted usage
paid upfront)
Prepaid
(Usage allowance
bought)
Ex ante
Ex post
Focus of this study
4

6. Do you remember the feeling you had when filing your last tax return?
Refund Extra payment
Most people have one of the following two reactions:
5

7. Inconsistent research findings on payment sequence preferences
Pre-pay for
hedonic goods
Payment sequence
preferences for goods
Payment sequence
preferences for taxes
Income sequence preferences
Present
value
120.8 118.7
Choice 17% 83%
e.g., Loewenstein & Sicherman (1991)
Guyse et al. (2002)
Read & Powell (2002)
Pos-tpay for
utilitarian goods Tax-payers prefer to pre-pay
Consumers prefer to
• Preference to prepay for hedonic
goods to enjoy consumption as if
it was for free
• Lack of self-control
• Asymmetric penalties
• Alignment with productivity
• Convenience
e.g., Ayers, et al. (1999)
Jones (2012)
Highfill, Thorson and Weber (1998)
e.g., Prelec and Loewenstein (1998)
Patrick and Park (2006)
ReasonDirection
Workers prefer rising income
streams
• Different results with regards to direction of payment sequence preferences
• Mainly small experiments in lab (with exception of taxes)
• Consequences on payment sequence preferences in the consumption sphere is unknown
6

8.  Δ: refund (+) or extra payment (-)
 b: total yearly bill according to actual consumption
Prospect Theory (e.g., Silverlining principle) is not able to explain
preference for a refund
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7

9. Research goals: Analyze payment sequence preferences, as well as
causes and consequences
Question 1 Question 2 Question 3
Question
Managerial
implications
 Support decision for payment system (sdvance vs. pre-payment vs. post-
payment)
 Support decision for advance payment system design
 Provide insights into causes for preferences to support offer design and
communication
 First paper to examine „irrational behaviour“ in advance payment
sequences and whether customers’ preferences shift with relative
magnitude of last bill
 First paper to examine behavioral and attitudinal consequences
 First paper to use survey data and billing data
Scientific
contribution
Do preferences for
payment sequences
exist?
Do payment
sequences have
attitudinal
consequences?
Do payment
sequences have
behavioral
consequences?
8

10. Three research questions  three studies
Study 1 Study 2 Study 3
Question
Do preferences for
payment sequences
exist?
Do payment
sequences have
attitudinal
consequences?
Do payment sequences
have behavioral
consequences?
Type of data
Respondents
/ customers
included
N
Survey 1
Survey 2 merged
with billing data 1
Billing data 2
General electricity
customers
Customers of
specific European
electricity provider
Customers of specific
European electricity provider
incl. churners (2,672), tariff
switchers (3,411), and
passive customers (16,838)
259 779 22,921
9

11. Three research questions = three studies
Study 1 Study 2 Study 3
Question
Do preferences for
payment sequences
exist?
Do payment
sequences have
attitudinal
consequences?
Do payment sequences
have behavioural
consequences?
Type of data
Respondents
/ customers
included
N
Survey 1
Survey 2 merged
with billing data 1
Billing data 2
General electricity
customers
Customers of
specific European
electricity provider
Customers of specific
European electricity
provider
259 779 22,921
10

12. Test for preference of payment sequence preference: Survey 1
Methodology: Survey Versions 1 + 2
Alternative 1:
Extra payment
sequence
Alternative 2:
Refund sequence
Monthly
advance
payment
rate
Predicted
extra
payment at
end of year
Monthly
advance
payment
rate
Predicted
refund at end
of year
Version 1:
Equal total
payments
Choice-set 1 (low, low) 45€ 60€ 55€ 60€
Choice-set 2 (high, high) 40€ 120€ 60€ 120€
Choice-set 3 (low, high) 45€ 60€ 60€ 120€
Choice-set 4 (high, low) 40€ 120€ 55€ 60€
Choice experiment set-up:
Which sequence would you prefer for expected yearly electricity bill of 600€?
Version 2:
Higher total
payments
for refund
sequence
Choice-set 1 (low, low) 45€ 60€ 55€ 57.50€
Choice-set 2 (high, high) 40€ 120€ 60€ 115€
Choice-set 3 (low, high) 45€ 60€ 60€ 115€
Choice-set 4 (high, low) 40€ 120€ 55€ 57.50€
Version 3: Low
uncertainty
Version 4: High
uncertainty
11

13. Study 1: Percentage of respondents prefering refund sequence
Significantly different from 50%: ***p<0.01; **p<0.05;*p<0.1
A
preference
for refund
sequences
exists
Preference
for refund
sequences
decreases
with the
relative size
of the
refund to
the extra
payment
The majority of respondents is
still preferring refund, even if
they eventually pay more
Choice-set
(Extra Payment, Refund)
Version 1
Equal total
payments
Version 2
Higher total
payments
for refund
Version 3
Low
uncertainty
Version 4
High
uncertainty
Total
across all
versions
N 66 60 64 69 259
Choice-set 1 (low, low) 62%** 58% 67%*** 75%*** 65%***
Choice-set 2 (high, high) 64%** 61%* 67%*** 67%*** 64%***
Choice-set 3 (low, high) 47% 39%* 52% 64%** 50%
Choice-set 4 (high, low) 73%*** 67%*** 72%*** 77%*** 72%***
Total across all choice-sets 61%*** 56%** 64%*** 71%*** 63%***
High uncertainty in usage
leads to higher preference for
refund sequence
12

14. Three research questions = three studies
Study 1 Study 2 Study 3
Question
Do preferences for
payment sequences
exist?
Do payment
sequences have
attitudinal
consequences?
Do payment sequences
have behavioral
consequences?
Type of data
Respondents
/ customers
included
N
Survey 1
Survey 2 merged
with billing data 1
Billing data 2
General electricity
customers
Customers of
specific European
electricity provider
Customers of specific
European electricity provider
259 779 22,921
13

15. Impact of payment sequence on attitudes: billing + survey data
Survey data: n=779 (customers of
European electricity provider)
Billing data: n=782 (customers of
European electricity provider)
Dependent
variables
+
 Price awareness
 Likelihood to recommend
provider
Price awareness
-
Independent
variable
 Refund or extra payment
 Relative last billing rate (in % of
total yearly rate)
Control
variables
Timing Customers received last bill at 16th of
a random month in 2011
January 2012
 Gender
 Age
 Income
 Education
 Total electricity spending
 Type of contract
 Avg. Price / kWh
14

16. Simple 2 sample comparison already shows impact of payment
sequences on attitudes …
Refund receivers are half as accurate in
their price estimate …
… and more likely to recommend their
provider
% of customers (difference significant at 1% leve)lPrice awareness: Refund receivers vs.
extra payment makers
Average probability to recommend
provider on 10 point scale
38.81%
20.00%
Refund receivers Extra payment
makers
.
Reading example: People
who received a refund with
their last billing rate over-/
underestimate their monthly
advance payments on
average by 38%
6.44
6.13
Refund receivers Extra payment
makers
Note: Extra payment makers: N= 384; Refund receivers: N=398; mean difference significant at 5% / 10% confidence level
45,70%
74,25%
Advance
payments
Yearly
bill
Advance
payments
Yearly
bill
15

17. … which is confirmed by linearly regressing relative last billing rate
with attitude measures
Model 1: Refund Sequence Dummy
Model
Model 2: Asymmetric Magnitude
Model
Advance
payment
awareness:
Absolute
percentage
error
Yearly bill
awareness:
Absolute
percentage
error
Likelihood of
recom-
mending
provider on
10-point
scale
Advance
payment
awareness:
Absolute
percentage
error
Yearly bill
awareness:
Absolute
percentage
error
Likelihood
of recom-
mending
provider on
10-point
scale
Payment sequence
information
Refund sequence dummy .26*** .28** .31* - - -
Relative magnitude of
refund
- - - .74** 3.61*** 2.64***
Relative magnitude of
extra payment sequence
- - - -.09 2.23*** .93
Model fit
R-square .15 .07 .03 .15 .14 .05
F-Value 13.29*** 5.23*** 2.60*** 11.85*** 10.85*** 3.41***
Number of observations 779 779 779 779 770 779
***p<0.01; **p<0.05;*p<0.1
Note: Control variables not reported due to lack of space Refund sequences
reduce price con-
sciousness
Refund sequences have a
positive influence on likelihood
to recommend the provider
( )
Results of linear regression models
16

18. Three research questions = three studies
Study 1 Study 2 Study 3
Question
Do preferences for
payment sequences
exist?
Do payment
sequences have
attitudinal
consequences?
Do payment
sequences have
behavioral
consequences?
Type of data
Respondents
/ customers
included
N
Survey 1
Survey 2 merged
with billing data 1
Billing data 2
General electricity
customers
Customers of
specific European
electricity provider
Customers of specific
European electricity provider
259 779 22,921
17

19. Methodology – Question 3: Behavioral consequences
We created a sample of churners, tariff
switchers, and passive customers …
… to calculate impact of payment sequence
 How does type of payment sequence affect
odds of churning and tariff switching?
 What is effect of magnitude of last billing rate
on odds of churning and tariff switching?
Questions:
Methodology:
Multinomial logit model: Basis=staying passive
 Model 1: Dummy for refund sequence
 Model 2: Assymetric magnitude model
(absolute of last billing rate/total yearly bill)
All tariff switchers of European
electricity company in 2011:
N= 3,411
Random sample of passive
customers (did not churn, or
switch tariffs) in 2011:
N= 16,838
All churners of European
electricity provider in 2011:
N= 2,672
N= 22,921
18

20. Payment sequences have significant impact on behavior
More than 50% of churners‘ and tariff
switchers had to make extra payments …
… leading to a significant difference in mean
relative last billing rate
37 44
53
63 56
47
Churners Tariff
switchers
Passive
customers
Extra
paymen
t made
Refund
receive
d
% of customers (difference
significant at 1% level)
% of customers with refunds and extra
payment in last billing rate
Mean last billing rate in % of total yearly rate
-5.1%
-2.3%
+0.7%
Churners
Reading example:
People who churned are those
that had to make an extra
payment of 5% of their total
yearly billing rate to complete
their last billing cycle.
Note: all differences to passive customer sample significant at 1%
Analysis excluding outliers with last billing rate >100% or <-100% of total amount
Tariff
switchers
Passive
customers
19

21. Results hold if we control for other variables, but high refunds can
also have negative effects
Model 1: Refund
sequence dummy model
Model 2: Asymmetric
magnitude model
Odds-
ratios:
Churn
Odds-
ratios: Tariff
switch
Odds-
ratios:
Churn
Odds-
ratios: Tariff
switch
Payment
sequence
information
Refund sequence dummy 0.627*** 0.788*** - -
Magnitude of refund sequence - - 1.530* 1.708***
Magnitude of extra payment sequence - - 8.489*** 4.187***
Customer
information
Length of customer relationship (in month) 0.878*** 0.883*** 0.879*** 0.883***
Average price per kWh paid (in €) 0.615*** 1.010 0.576*** 0.995
Total usage (in kWh/yr.) 1.076*** 1.060*** 1.075*** 1.060***
Model fit
Nagelkerke's R-Square 0.326 0.328
-2Loglikelihood 28,025 28,076
Chi-Square 6,731 6,777
N 22,921 22,921
H4a/b: Refund sequences
have a negative influence
on churn / tariff switching
probability
Refund sequences have a
negative influence on
churn / tariff switching
probability
High refunds may also
have negative effects,
but effect of high extra
payment 4 x as large
Results of multinomial logit model: three variables (stay passive (basis), churn, switch)
***p<0.01; **p<0.05;*p<0.1
20

22. Findings & implications
Question 1: Question 2: Question 3:
Question
 Preference for
refund sequences
exist and people
are willing to pay
more just to
experience refund.
 Preference for
refund sequences
decreases with the
relative size of the
refund to the extra
payment
Findings
Do preferences for
payment sequences
exist?
Do payment sequences
have attitudinal
consequences?
Do payment sequences
have behavioral
consequences?
Refund sequences …
 … decrease price
consciousness
 … (increase
likelihood to
recommend
provider)
Refund sequences …
 … decrease churn
and tariff switching
probability …
 … but refunds
should not be too
high
21

23.  Advance payment systems could be a viable
alternative to post-payment or pre-payment
systems
 Advance payment rates should be set such
that chance of receiving a refund is increased
 However, there is a limit to how much
providers should overcharge
Implications of our research
Managerial implications Theoretical implications
 Advance payment systems may be subject to
further research to identify preferences
between different payment systems
 Commonly accepted finding that customers
show more "rational" payment timing
preferences for utilitarian goods (Prelec &
Loewenstein, 1998; Patrick & Park, 2006)
does not hold in advance payment systems
22

24. Managerial Implication: Purposely aim for refunds!
Last billing rate in % of total amount due**
* Note: Change = Refund / 11 such that 11*monthly advance payment equals total billing rate for 1 year
** Source: Customer sample from survey 2 (cut-off at +/- 100%): N=840
… mostly leading to a zero-centered
distribution of last billing rate
Single customer
example
Last billing rate in
2011
-€190
Change of
monthly advance
payment for 2012*
-€18
Advance payments are adjusted
every year….
Increase in advance payment rate 5% (i.e., 3.45€ per month on average)
Share of customers receiving a refund 70%
Decrease in churn 7.7%
23