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
AdvancePpayment Systems (also referred to as equal billing)
Usage prediction for billing
cycle
Calculation of
advance payment rates
Determination of actual
usage in
billing cycle
Determination
of last billing
rate
Refund
Extra
payment
1
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
Also outside of Germany, APS are increasingly advertised by
electricity service providers
Europe
US
Advance
payment
Company
France
Germany
system
Optional or
offered
mandatory
EDF
Yes
Optional
ENI
Yes
Optional
GDF Suez
Yes
Optional
Poweo Direct Energy
Yes
Optional
EnBW
Yes
Mandatory
Eon
Yes
Mandatory
EWE
Yes
Mandatory
RWE
Yes
Mandatory
Vattenfall Europe
Yes
Mandatory
Municipale
No
-
Aem
No
-
Edison SpA
No
-
Enel
No
-
Hera Group
No
-
EDP Renováveis
No
-
Endesa
Yes
Optional
Eon Spain
No
-
Gas Natural
Yes
Optional
Iberdrola
Yes
Optional
EDF Energy
Yes
Optional
Eon UK
Yes
Optional
National Grid
Yes
Optional
RWE npower
Scottish and Southern nergy
Yes
Yes
Optional
Optional
Acqua Gas Azienda
Italy
Spain
UK
3
Service providers can choose between three payment systems;
our focus: advance payments
Pros
Focus of this study
Small nonpayment
risk
Earlier
cash flow
Low operational
costs
Customer
loyalty
Advance payment
(Predicted usage
paid upfront)
Ex ante
Prepaid
(Usage allowance
bought)
Payment
timing
Ex post
High
Low
4
Do you remember the feeling you had when filing your last tax return?
Most people have one of the following two reactions:
Refund
Extra payment
5
Inconsistent research findings on payment sequence preferences
Payment sequence
preferences for goods
Payment sequence
preferences for taxes
Income sequence preferences
e.g., Loewenstein & Sicherman (1991)
Guyse et al. (2002)
Read & Powell (2002)
e.g., Ayers, et al. (1999)
Jones (2012)
Highfill, Thorson and Weber (1998)
e.g., Prelec and Loewenstein (1998)
Patrick and Park (2006)
Direction
Consumers prefer to
Pos-tpay for
Pre-pay for
hedonic goods utilitarian goods
Tax-payers prefer to pre-pay
Present
value
120.8
118.7
Choice
17%
83%
Reason
Workers prefer rising income
streams
•
Preference to prepay for hedonic
goods to enjoy consumption as if
it was for free
•
•
•
•
•
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
Lack of self-control
Asymmetric penalties
•
•
Alignment with productivity
Convenience
6
Prospect Theory (e.g., Silverlining principle) is not able to explain
preference for a refund
, if   0


v(b, )    ((b ))  

  () , if   0
, if   0
 
v(b, )  1  ((b ))  

  () , if   0
 Δ: refund (+) or extra payment (-)
   ( b) ;



v(b, )  max 
, if   0 



   ((b  ))    ( ) , if   0 



 b: total yearly bill according to actual consumption
7
Research goals: Analyze payment sequence preferences, as well as
causes and consequences
Question
Scientific
contribution
Question 1
Question 2
Question 3
Do preferences for
payment sequences
exist?
Do payment
sequences have
attitudinal
consequences?
Do payment
sequences have
behavioral
consequences?
 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
 Support decision for payment system (sdvance vs. pre-payment vs. postpayment)
Managerial
implications
 Support decision for advance payment system design
 Provide insights into causes for preferences to support offer design and
communication
8
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
Survey 1
Survey 2 merged
with billing data 1
Billing data 2
Respondents
/ customers
included
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)
N
259
779
22,921
9
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
Survey 1
Survey 2 merged
with billing data 1
Billing data 2
Respondents
/ customers
included
General electricity
customers
Customers of
specific European
electricity provider
Customers of specific
European electricity
provider
N
259
779
22,921
10
Test for preference of payment sequence preference: Survey 1
Methodology: Survey Versions 1 + 2
Choice experiment set-up:
Which sequence would you prefer for expected yearly electricity bill of 600€?
Alternative 1:
Extra payment
sequence
Version 1:
Equal total
payments
Version 2:
Higher total
payments
for refund
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
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-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
Study 1: Percentage of respondents prefering refund sequence
Choice-set
(Extra Payment, Refund)
Version 1
Version 2
Version 3
Version 4
Equal total
payments
Higher total
payments
for refund
Low
uncertainty
High
uncertainty
66
60
64
69
259
N
Total
across all
versions
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%***
Preference
for refund
sequences
decreases
with the
relative size
of the
refund to
the extra
payment
A
preference
for refund
sequences
exists
Significantly different from 50%: ***p<0.01; **p<0.05;*p<0.1
The majority of respondents is
still preferring refund, even if
they eventually pay more
High uncertainty in usage
leads to higher preference for
refund sequence
12
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
Survey 1
Survey 2 merged
with billing data 1
Respondents
/ customers
included
General electricity
customers
Customers of
specific European
electricity provider
N
259
779
Billing data 2
Customers of specific
European electricity provider
22,921
13
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
Independent
variable
-
Control
variables




Timing
January 2012
Gender
Age
Income
Education
Price awareness
 Refund or extra payment
 Relative last billing rate (in % of
total yearly rate)
 Total electricity spending
 Type of contract
 Avg. Price / kWh
Customers received last bill at 16th of
a random month in 2011
14
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
Price awareness:
Refund
receivers
vs.
% of customers (difference
significant at 1%
leve)l
extra payment makers
Average probability to recommend
provider on 10 point scale
74,25%
38.81%
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
45,70%
20.00%
Refund receivers
Advance Yearly
payments bill
Extra payment
makers
Refund receivers
Extra payment
makers
Advance Yearly
payments. bill
Note: Extra payment makers: N= 384; Refund receivers: N=398; mean difference significant at 5% / 10% confidence level
15
… which is confirmed by linearly regressing relative last billing rate
with attitude measures
Results of linear regression models
Model 1: Refund Sequence Dummy
Model 2: Asymmetric Magnitude
Model
Model
Advance
Yearly bill
payment
awareness:
recom-
awareness:
Absolute
mending
Absolute
percentage
Likelihood of Advance
percentage provider on
error
Payment sequence
information
Relative magnitude of
refund
Relative magnitude of
extra payment sequence
Model fit
R-square
F-Value
***p<0.01; **p<0.05;*p<0.1
Note: Control variables not reported due to lack of space
payment
awareness:
of recom-
awareness:
Absolute
mending
Absolute
percentage
scale
error
percentage provider on
error
10-point
scale
.26 ***
.28 **
.31 *
-
-
-
-
-
-
.74 **
3.61 ***
2.64 ***
-
-
-
-.09
.15
.07
.03
.15
.14
11.85 ***
10.85 ***
779
770
13.29 ***
Number of observations
Likelihood
10-point
error
Refund sequence dummy
Yearly bill
779
5.23 ***
2.60 ***
779
779
Refund sequences
reduce price consciousness
2.23 ***
.93
.05
3.41 ***
779
Refund sequences have a
positive influence on likelihood
to recommend the provider
( )
16
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
Survey 1
Survey 2 merged
with billing data 1
Billing data 2
Respondents
/ customers
included
General electricity
customers
Customers of
specific European
electricity provider
N
259
779
Customers of specific
European electricity provider
22,921
17
Methodology – Question 3: Behavioral consequences
We created a sample of churners, tariff
switchers, and passive customers …
All churners of European
electricity provider in 2011:
N= 2,672
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
… to calculate impact of payment sequence
Questions:

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?
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)
N= 22,921
18
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
% of customers with refunds and extra
payment in last billing rate
Mean last billing rate in % of total yearly rate
% of customers (difference
significant at 1% level)
63
56
47
Churners
Tariff
switchers
+0.7%
Passive
customers
Extra
paymen
t made
-2.3%
37
44
Churners
Tariff
switchers
53
Refund
receive
d
Passive
customers
-5.1%
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
19
Results hold if we control for other variables, but high refunds can
also have negative effects
Results of multinomial logit model: three variables (stay passive (basis), churn, switch)
Model 1: Refund
sequence dummy model
Payment
sequence
information
Customer
information
Model fit
Model 2: Asymmetric
magnitude model
Oddsratios:
Churn
0.627***
Oddsratios: Tariff
switch
0.788***
Oddsratios:
Churn
-
Oddsratios: Tariff
switch
-
Magnitude of refund sequence
-
-
1.530*
1.708***
Magnitude of extra payment sequence
-
-
8.489***
4.187***
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***
Refund sequence dummy
Nagelkerke's R-Square
0.326
0.328
-2Loglikelihood
28,025
28,076
Chi-Square
6,731
6,777
N
22,921
22,921
***p<0.01; **p<0.05;*p<0.1
H4a/b: Refund
sequences
Refund
sequences
have a
have
a negative
influence
negative
influence
on
onchurn
churn/ tariff
/ tariffswitching
switching
probability
High refunds may also
have negative effects,
but effect of high extra
payment 4 x as large
20
Findings & implications
Question

Findings

Question 1:
Question 2:
Question 3:
Do preferences for
payment sequences
exist?
Do payment sequences
have attitudinal
consequences?
Do payment sequences
have behavioral
consequences?
Refund sequences …
Refund sequences …
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

… decrease price
consciousness

… (increase
likelihood to
recommend
provider)

… decrease churn
and tariff switching
probability …

… but refunds
should not be too
high
21
Implications of our research
Managerial implications
Theoretical implications

Advance payment systems could be a viable
alternative to post-payment or pre-payment
systems

Advance payment systems may be subject to
further research to identify preferences
between different 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
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
Managerial Implication: Purposely aim for refunds!
Advance payments are adjusted
every year….
… 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
Last billing rate in % of total amount due**
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%
* 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
23