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Consumer Perception of Mobile Telephony Tariffs

with Cost Caps

Jan KramerKarlsruhe Institute of Technology

Karlsruhe, Germany

Email: kraemer@kit.edu

Lukas WiewiorraKarlsruhe Institute of Technology

Karlsruhe, Germany

Email: wiewiorra@kit.edu

AbstractIn this article we provide a seminal academic investi-gation of mobile telephony consumers perception of the recentlyintroduced cost cap tariff in comparison to corresponding pay-per-use and flatrate calling plans. Previous studies have identifiedseveral psychological effects through which consumers are be-lieved to be biased towards flatrate plans. However, flatrate plansalso limit customers tariff flexibility in months of low usage.Cost cap tariffs are a hybrid between pay-per-use and flatrateplans and can offer cost insurance while maintaining flexibility.

In particular, we provide evidence from a survey among 214German university students that flexibility, cost insurance andthe so-called taximeter effect are the main drivers behind costcap tariff choice. Furthermore, we show that the insurance andtaximeter effects are distinct if evaluated within a flatrate orcost cap tariff framework. Finally, based on our results we alsocomment on the profitability of cost cap plans from a strategicmanagement perspective.

I. INTRODUCTION

Competition in the mobile telephony market is fierce and

the scope for product differentiation is limited - a combination

that leads mobile telephony providers to engage in price

differentiation instead. Indeed, the actual extend of price

differentiation in the market is striking and customers are facedwith a multitude of different tariff types [1][3].

Traditionally, mobile telephony providers have only offered

two-part tariffs, which consist of fixed monthly fee and a

usage-based component [4]. Two-part tariffs have a long

tradition in telephony [5]. Their popularity stems from the fact

a large portion of the providers costs are fixed costs related

to the build up, maintenance and operation of the network

infrastructure, which can be recovered by the fixed component

of the two-part tariff [6]. On the contrary, the marginal

costs of calling, which are constituted through switching or

interconnection fees, for example, are relatively small and

can be recovered by the variable component of the two-part

tariff. In fact, if the telephony provider holds a monopoly,which has been the case for the fixed-line providers for most

of the twentieth century, two-part tariffs can even achieve to

extract customer rent completely, comparably to perfect price

discrimination [7].

However, in the mobile telephony market, which has been

liberalized much earlier than the fixed telephony market,

actual infrastructure-based competition has created a very

competitive market environment. In an effort to differentiate

their service offering, providers have experimented with new

and innovative tariff structures to the extend that the mobile

telephony market is flooded with a seemingly endless variety

of voice telephony tariffs today. Besides the classical two-part

tariff, the tariff portfolio ranges from three-part tariffs that

include a usage allowance or minimum turnover requirements

to one-part tariffs, i.e. pure pay-per-use or flatrates tariffs.

In this paper we highlight the innovative cost cap tariff

which has been introduced to the German mobile market in2009 by o2 (Telefonica).1 The cost cap tariff is a new type of

two-part tariff that constitutes a hybrid between a pay-per-use

and a flatrate tariff. It is a pure pay-per-use tariff until the

total costs exceed a predefined cost cap, at which the tariff

effectively becomes a flatrate. o2 claims that the cost cap tariff

is a great success and has significantly contributed to attracting

new customers [8].

In this article we provide a seminal academic investigation

of mobile telephony consumers perception of cost cap tariffs

based on a survey among 214 German university students. In

particular, it seems obvious that consumers will perceive the

cost cap tariff as weakly dominant over both the pay-per-use

tariff (because it offers a cost insurance in months of highusage) as well as the flatrate plan (because it offers flexibility

in months of low usage) if the cost cap tariff offers the same

per-minute prices as a pay-per-use tariff and if the cost cap is

set at the price of a corresponding flatrate plan. On the other

hand, it is questionable to which degree customers of pay-

per-use plans would in fact accept a higher per-minute price

under a cost cap tariff in order to be insured against high

monthly invoices.2 Likewise, previous studies (e.g. [9][14])

have provided strong empirical evidence that customers have a

bias towards flatrate plans due to psychological reasons. In the

following we will also investigate to what extend the cost cap

tariff is also capable to benefit from these psychological effects

compared to pure flatrate tariffs while additionally capturingthose customers that have a strong desire for flexible pay-per-

use tariffs.

The remainder of this article is structured as follows: In

Section II we introduce the psychological effects that have

1The tariff, which is called o2o, has officially been released on May 5,2009.

2In the o2o cost cap tariff customers pay 15 Euro cents per minute, whilecomparable pay-per-use plans are currently available from as low as 7.5 centsper minute.

978-1-4244-7986-3/10/$26.00 2010 IEEE

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been identified as cognitive causes of a flatrate bias and discuss

them in the context of cost cap tariffs. Section III derives our

research questions and IV presents the set up and content of

the survey. In Section V, finally, we will present and discuss

the results of our statistical analysis and conclude in Section

VI by commenting on the results with respect to customers

perception of cost cap tariffs.

I I . REASONS FOR BIASED TARIFF CHOICE

Economic theory assumes that consumers maximize their

utility when selecting a mobile tariff, such that the chosen

calling plan should (on average) lead to the lowest possi-

ble telephone bill, given correct anticipation of the average

usage. However, several studies (e.g. [12], [14][16]) have

provided strong evidence that customers actual tariff choice

may deviate from the economic prediction due to motivational,

psychological or cognitive causes that lie outside of the stan-

dard economic framework of fully rational market participants

with perfect foresight. The most prominent example of suchsystematic deviations is the the so-called flatrate bias, which

has been shown in context with all-you-can-eat buffets [17],

gym subscriptions [9], Internet access plans [10][12] and

mobile calling plans [13], [14]. The flatrate bias asserts that

consumers often favor flatrate tariffs, although a pay-per-use

tariff would be cheaper with regard to their actual usage

volume. From psychological perspective, the main difference

between a pay-per-use (or cost cap tariff for that matter) and a

flatrate tariff is that telephone costs are sunk in a flatrate plan

and consequently customers need not worry about the costs

of current or future usage.3 More specifically, with respect

to information and communication services, the literature has

identified four distinctive effects that are supposed to drive theflatrate bias:

a) Insurance: The insurance effect aims at customers

that want to insure themselves against exceptionally (and

unexpectedly) high telephony bills. Customers may be risk

averse towards the correctness of their estimation of current

service usage or with respect to future changes in demand.

Therefore these customers are willing to pay (on average) more

for a flatrate plan than what the costs of a corresponding pay-

per-use tariff would be, because they are insured against these

risks. In this vein the difference between the costs for a flatrate

and the average costs for a pay-per-use tariff can be interpreted

as an insurance premium. Indeed, [11] show that the optionvalue attached to flatrate plans is independent of the actual

usage.

b) Convenience: As outlined before, consumers face a

tremendous variety of alternative tariffs in the mobile tele-

phony markets. The convenience effect is driven by those

consumers who want to avoid the effort of finding a cheaper

3This corresponding psychological concept is known as mental account-ing and has been investigated in a number of different domains ( [18][20]).

and perhaps more complex tariff.4 The costs associated with

a flatrate, however, are easily accessible and independent of

ones own (possibly unknown) calling volume.

c) Overestimation: Consumers often fail to anticipate

their own usage of telecommunication services correctly [16];

either because of limited foresight and uncertainty in demand,

or because of bounded rationality. In anticipating their current

or future service usage, consumers have a tendency to overes-timate their actual demand, which, in turn, will induce them to

select a flatrate plan more often. At the same time, users are

often overly confident that their usage estimation is correct

[16]. This makes the overestimation effect distinct from the

insurance effect and leads consumers to repeatedly choose the

wrong calling plan.

d) Taximeter: The so-called taximeter effect is derived

from the experience of using a taxi in a foreign city: The

taxi ride can be perceived as unpleasant, because the run-

ning taximeter constantly visualizes the currently accumulated

costs. In the telecommunications domain, the analogous effect

can for example be experienced while waiting in the queue ofa very costly hotline. Under a flatrate plan, on the contrary, all

costs are sunk ex ante and the marginal costs of consumption

are zero. This prevents consumers from experiencing the

taximeter effect, who may thus favor flatrate plans.

However, there is also a distinctive reason for customers not

to choose a flatrate plan.

e) Flexibility: By choosing a flatrate, consumers commit

themselves to pay a fixed amount for telephone usage in each

billing period, independent of their actual usage. This potential

discrepancy between actual usage and committed costs can

result in two adverse effects, which we have summarized

under the roof of flexibility. First, subscribers may ex postregret their cost commitment under a flatrate plan after having

realized that a usage-based tariff would have generated lower

costs after all. Pay-per-use tariffs, on the contrary, avoid such

commitments and react flexibly to (exceptionally low) usage.

Secondly, the cost commitment may tempt flatrate subscribers

to excess telephone usage. In other words, consumers may

seek to avoid the ex post regret that they have not chosen a less

expensive pay-per-use plan and therefore exploit the flatrate by

telephoning more than reasonable. This effect is comparable

to the so-called buffet effect by which customers of all-you-

can-eat buffets eat more than they desire in an effort to justify

the break even costs of an all you can eat buffet in comparison

to the la carte menu [17]. Consequently, consumers with astrong aversion against ex post regret or the buffet effect are

more likely to opt for a flexible pay-per-use tariff and seek to

4Network providers sometimes even try to leverage the potential of conve-nient consumers and engage in so called foggy pricing. In its most extremeform, service providers deliberately offer dominated calling plans, because theadditional costs of doing so are very low and there is a positive probabilitythat convenient or uninformed consumers will actually choose this tariff. Fora critical analysis of foggy pricing see [3].

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avoid the cost commitment associated with a flatrate plan.5

III. RESEARCH QUESTIONS

The main research question we seek to investigate in this

article is whether a cost cap tariff can also tap on one or some

of these effects and if so, how strong the impact on customer

choice will be. Due to its hybrid nature, we can presume

that the cost cap tariff can capture some of the flatrate bias

components, namely the insurance and overestimation effects,

as well as the pay-per-use component, namely the flexibility

effect. At this point, it remains open, however, how consumers

will evaluate the cost cap tariff compared to a flatrate plan

with respect to the convenience and taximeter effect. Table I

summarizes the potential impact of the identified effects on

the three fundamental tariff schemes.

TABLE IPOTENTIAL EFFECTS ON THE CHOICE OF DIFFERENT TARIFF SCHEMES

Pay-per-use Cost Cap Flatrate(PPU) (CC) (FR)

Insurance - + +

Convenience - ? +Overestimation - + +Taximeter - ? +Flexibility + + -

In the seminal analysis, it is important to isolate the psycho-

logical effects that are exhibited by a certain tariff scheme from

the underlying economic effects. Therefore, in the following

the cost cap plan is compared to a pay-per-use plan with the

same per-minute price and with a flatrate plan that is priced at

the level of the cost cap. In this way, the cost cap plan weakly

dominates both the pay-per-use and the flatrate plan and hence

tariff biases can be easily identified.6

Furthermore, recall that the pay-per-use and the flatratecalling plan are both a one-part tariff, which put together,

constitute the two-part cost cap tariff. These tariffs are not

directly comparable to three-part tariffs (that consist of a fixed

fee, an included allowance of minutes for which the marginal

prize is zero, and a positive marginal price for additional

minutes beyond the allowance), and will therefore not be

considered here.7

In the following section we present the design of a survey

that is thought to quantify tariff bias effects and their impact on

consumers choice of pay-per-use, cost cap or flatrate calling

plans. In addition, in contrast to previous studies on the flatrate

bias, our analysis of the cost cap pricing scheme also offers

5It shall be annotated that in different domains, where excessive usageis a desired outcome to the consumer, the lack of flexibility may evenconstitute a flatrate bias. With a flatrate plan, customers can strategicallycommit themselves to more service usage for the same reasons as above. Forexample, people often subscribe to a long term flatrate contract for health clubsin order to commit themselves to use the gym more often. In the literature thisreverse interpretation of the flexibility effect is called self-discipline effect(cp. e.g. [9]).

6See Section VI for ideas on possible alternative choice scenarios thatshould be subject to future research.

7Three-part tariffs are for example very popular in the US cellular phoneservices market.

a new way to test the taximeter effect independent of the

insurance effect.

IV. SURVEY DESIGN

The survey is structured in four distinctive parts.

In the first part, participants are asked to decide betweenalternative tariffs in two series of hypothetical usage scenarios.

More precisely, participants are presented with several ficti-

tious usage scenarios in which they have to indicate which of

two alternative calling plans they would choose. This method-

ological approach is sometimes called quasi-experimental [12].

The first part of the survey is subdivided into two series of

choice scenarios.

In the first series of four usage scenarios participants had to

decide between a flatrate plan and a pure pay-per-use tariff.

Usage scenarios differed only by the induced minimum and

maximum usage (in minutes), whereas the average usage was

identical in all scenarios.8 Hence, the setup measures if differ-

ent perceived extrema of usage impact tariff choice.9

Moreover,it is emphasized that we have chosen realistic choice scenarios,

which are in line with average usage volumes of mobile

telephony and actual market prices in Germany at the time

of the survey.

For the first series of usage scenarios, respondents are ran-

domly assigned to one of two settings. In the first setting,

the usage scenarios are such that the costs of the flatrate plan

are identical to the average monthly costs under the pay-per-

use plan (45e). Thus, we would expect to observe an equal

distribution of participants between the two alternative calling

plans. In the second setting, the flatrate is priced slightly higher

49e). With this modified version of the question it can be

verified if a potential bias towards a flatrate is also presentunder a pricing scheme with higher than average monthly

costs.

In a second series of four similar usage scenarios, all respon-

dents were asked to choose between a cost cap tariff and a

flatrate tariff. The usage scenarios were designed such that it

is possible to check for a flatrate bias over a cost cap plan.

In the second part of the survey participants are presented

with several verbal phrases, who are then asked to indicate

their consent on a five point Likert scale. These phrases are so

called indicators which are later aggregated to constructs

that measure the effects in table I. Most of the indicators

8Analogous to the survey design of [12], [21] minimum and maximumusage is varied in all possible combinations of 33.3% and 100% deviationof the average costs per month. The corresponding min/max usage levels are0/400, 200/400, 0/600 and 200/600 minutes.

9The hypothetical questions were presented in the following manner: Pleaseimagine independently from your real usage behavior that you are using yourmobile phone on average 300 minutes per month to call into German networksand you have to pay the bill yourself. Your amount of usage fluctuates betweenthe months. Below you are presented with different values of minimum andmaximum usage per month. Average usage is always 300 minutes per month.Please indicate in all four cases your choice between tariff 1 where you pay15 Euro cents per minute and tariff 2 where you pay 45 Euros flat.

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have been adapted from [21] and [15].10 However, we derived

our own indicators with respect to those constructs that were

thought to measure the taximeter and insurance effect under

a cost cap plan as well as the flexibility effect. Additionally,

in this part of the survey respondents were asked for their

appraisal of their own usage behavior and costs. To exclude

unwanted effects stemming from the order of the items we

presented them in random order to all participants.

In the third part of the survey, data on the respondents

actual mobile telephony tariff characteristics (such as con-

tract duration, tariff model, average monthly bill is collected.

Participants were notified that from this point on, they were

asked about their real actual mobile phone usage. In the last

and fourth part of the survey, participants were confronted

with a standard risk aversion test based on [22] in which

respondents must choose between a safe and a risky lottery in

ten settings. Participants were incentivized to answer truthfully

in the risk aversion test by offering the chance for a gift

coupon of up to 38.5e value. The determination of the actual

value of the coupon is perfectly aligned with the decisions

in the risk aversion test and thus, the test was implementedas a non-hypothetical setting. More precisely, to determine

the coupon value, one of the ten settings was chosen in

which the respondents participated in the respective lottery

of his choice. Lottery outcomes were also orientated on the

average mobile phone bill of participants. Since our sample is

very homogeneous we can on average neglect income effects

influencing the results.

The survey was conducted in February 2010 through a

web-based questionnaire among undergraduate students at the

Karlsruhe Institute of Technology in Germany. Students were

invited to the questionnaire via the mailing list of an introduc-

tory economics course. We stimulated participation by offering

a chance to take part in a lottery of four 25 e gift couponsfor a large online retail store after completing the survey.

96.7% of the participants decided to participate in the lottery.

Additionally one gift coupon was awarded in the risk aversion

test. Certainly, we do not claim that students of economics

are a representative panel for the German or European mobile

telephony subscriber. However, we can presume that students

are more rational and more aware of their mobile tariff

and the associated costs than the average subscriber. Thus,

if we find empirical evidence for systematic selection biases

in our panel, it is likely that the actual effects are in fact

even stronger. We will discuss this issue in more detail in the

following sections.

V. RESULTS

A total of 214 respondents (23.5% female, 76.5% male)

with an average age of 20.5 years (S=1.47; min=16; max=27;

10In particular, [21] adapted and validated well known scales from market-ing science to measure these effects (latent variables in a statistical model)influencing the decision in favor for a flatrate tariff. Even though the originalscale was constructed to test for the effects in connection with Internet accessprices we modified the wording only if necessary.

median=20) completed our survey successfully.11 All of the

respondents are mobile telephony customers. The mean of

the reported average monthly telephone bill in our sample is

19.14e (S=17.53), with a noticeable discrepancy between the

mean average monthly bill of the 46.73% with prepaid tariffs

(M=10.15e; S=9.37) compared to those with postpaid tariffs

(M=27.03e; S=19.19). Thus, our sample contains about an

equal split of users with low and comparably high mobile

telephone usage.

At first, we investigate the degree to which the participants

in our sample are biased towards choosing a flatrate plan

over a pay-per-use plan. Table II summarizes the results.

Participants were randomly assigned to one of two settings

with different flatrate prices, in which they were asked to state

their preference for the flatrate or a pay-per-use plan in four

usage scenarios. In the first setting, which was assigned to

52.3% of the participants, the flatrate was priced at 45 e the

costs for the alternative pay-per-use plan under average usage.

The remaining 47.7% of the respondents evaluated the second

setting, in which the usage scenarios are identical, but the

flatrate is priced slightly above the average costs for the pay-per-use plan.12

TABLE IICHOICE OF FLATRATE OVER PAY-PE R-USE PLAN

Usage (minutes) Flatrate choice atMin Avg. Max 45e 49e

0 300 400 18.63% 4.46%200 300 400 46.08% 25.00%

0 300 600 41.96% 37.50%200 300 600 83.33% 66.96%

compared to a pay-per-use plan at 15 cents/minute

In both settings, except for the scenario with high minimum

and maximum usage, respondents favored a pay-per-use planover the flatrate. Previous studies have argued that in each

scenario in which the flatrate is priced at average costs

unbiased participants would be indifferent between choosing

the flatrate and the pay-per-use tariff [12], [14]. Therefore,

one would expected the flatrate to be chosen in 50% of the

cases. In a qualitatively identical setting, [12] and [14] find that

respondents chose the flatrate in three out of four scenarios at

average cost pricing and in two out of four scenarios at slightly

above average cost pricing. However, in our panel we find to

the contrary, that participants prefer the pay-per-use tariff in

three out of four scenarios in both settings. Thus, if there is a

bias in our sample, it would rather run in favor of a pay-per-

use tariff.

11A total of 346 Students followed the link and 247 of them completedthe survey. In a final validity question 7 participants indicated to haveanswered incorrectly in the survey and were eliminated from the final dataset.Moreover, in order to increase the internal validity of the responses, another17 observations were omitted from the analysis due to obviously random andirrational choices in the risk aversion test. Since there are no categorical wronganswers in the remaining parts of the survey, we generalized the validity of theanswers in the risk aversion test to the other survey questions. However, ourreported results do not significantly vary if these observations are included.

12We decided to present a price of 49 e to them.

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We offer two alternative explanations for this finding. First,

as argued above, the respondents in our sample are students

of economics and therefore (i) aware of rational choices and

expected utility theory and (ii) sensitive to costs in general.

Moreover, the participants in our survey are also very aware

of the costs of using their mobile phone. In the items that

capture cost control (cp. Table III) respondents agree to

a high degree (M=4.21; S=0.72) on a 5-point Likert scale.

Second, although the relation between the usage scenarios

is identical to those in [12] and [14] we use actual market

prices.13 In [14], for example, which also considers mobile

telephony tariffs and builds on survey data from July 2006,

the flatrate is priced unrealistically low at 30e and 33e while

the pay-per-use tariff costs 30 cents per minute.

TABLE IIISELF REPORTED COST AWARENESS

Cost Control(Cronbachss = 0.71, M=4.21, S=0.72)

I can accurately assess my own mobile telephony usagebehavior

(M=4.12; S=0.88; median=4)I know my calling plan and all costs involved very well.(M=4.43; S=0.90; median=5)I can accurately assess my own mobile telephony costs(M=4.07; S=0.92; median=4)

Next, we consider the respondents flatrate choice in com-

parison to cost cap tariffs in different usage scenarios (Table

IV). In this setting, the cost cap tariff offers a cap at the amount

of the flatrate price. Therefore, the cost cap tariff weakly

dominates the flatrate tariff for those usage scenarios where

the minimum usage may be below 300 minutes, i.e. the point

at where the cost cap becomes binding. Thus, in the absence

of tariff biases, one would expect that the flatrate plan is not

chosen in the first two scenarios. In the remaining two usagescenarios, the flatrate and the cost cap are factually identical

because the cost cap is reached even under minimum usage.

Thus, there is no advantage in selecting the cost cap tariff

anymore. To the contrary, if respondents are averse towards

the taximeter effect, they may even prefer the flatrate under

these conditions. Thus, ex ante one could presume that the

flatrate is chosen in at least 50% of the cases in the latter two

scenarios.

TABLE IVCHOICE OF FLATRATE OVER COST CAP PLAN

Usage (minutes) Flatrate choice at

Min Avg. Max 45e200 400 600 10.28%250 400 550 11.21%300 400 500 16.82%350 400 450 17.29%

compared to a cost cap plan at 15 cents/minute and 45 e cost cap

The actual choices of respondents differ substantially from

the ex ante presumptions and are strongly in favor of the cost

13At the time of the survey the o2o tariff offers per-minute prices of 15cents and a cost cap at 40e.

cap tariff. Even in those scenarios in which the cost cap tariff

has no advantage, more than 80% of the participants would

still opt for this tariff. This result reveals the great attrac-

tiveness cost cap tariffs seem to have on mobile telephony

customers, even in those settings where the cost cap tariff is

factually identical to the flatrate plan.

TABLE V

CONSTRUCTS CAPTURING FLATRATE EFFECTS

Taximeter (FR)(Cronbachss = 0.81, M=3.67, S=1.00)

A flatrate is good because I dont have to think about the costs.(M=3.73; S=1.29; median=4)I enjoy using the phone less if costs increase every minute ofuse(M=3.79; S=1.24; median=4)Only if I have a flatrate I enjoy using the mobile phone(M=3.00; S=1.39; median=3)If I have a flatrate I use my mobile phone in a more relaxedand unselfconscious manner.(M=4.16; S=1.11; median=5)

Insurance (FR)(Cronbachss = 0.76, M=2.63, S=1.05)

To be sure my costs of mobile telecommunication will neverbe higher than a certain predefined amount Im willing to paya little bit more than average(M=2.52; S=1.13; median=2)Even if a flat rate is somewhat more expensive than a pay-per-use rate Im happy because my costs wont exceed the fixedamount.(M=2.75; S=1.21; median=3)

Flexibility (FR)(Cronbachss = 0.63, M=3.66, S=0.76)

It bugs me when the flatrate wasnt profitable in a billingperiod.(M=3.66; S=1.11; median=4)It feels like a deficit when another tariff would have beencheaper than the flatrate in a billing period.(M=3.58; S=1.11; median=4)It matters to me to max out the flatrate.

(M=3.49; S=1.19; median=4)It feels like a gain when the flatrate was cheaper than the nextbest tariff in a billing period.(M=3.92; S=1.00; median=4)

Convenience(Cronbachss = 0.79, M=2.11, S=0.84)

Figuring out which rate is better takes so long that it isntworth the effort.(M=2.01; S=1.04; median=2)It is too much trouble to find out the prices for mobiletelecommunications(M=2.08; S=1.20; media=2)The money you can save by finding a better calling planthan your current one doesnt make up for the time and effortinvolved(M=2.22; S=1.02; mean=2)The time it takes to switch to a cheaper calling plan isnt worth

the effort.(M=2.11; S=1.01; median=2)

Further insight on the reasons by which mobile customers

perceive the relative attractiveness of pay-per-use, flatrate

or cost cap tariffs can be gained by evaluating the con-

structs which capture the taximeter, insurance, flexibility and

convenience effects. Furthermore, recall that cost cap tariff

framework allows us to present customers with constructs that

can capture their perception of the taximeter and insurance

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effect independently. In contrast to a flatrate framework, the

cost cap tariff allows for cost insurance, while maintaining

the taximeter property as long as the cost cap is not reached.

Therefore, we present our results separately for those con-

structs that are evaluated within the flatrate framework (Table

V) and those that are evaluated within the cost cap framework

(Table VI).14

TABLE VICONSTRUCTS CAPTURING COST CAP EFFECTS

Taximeter (CC)(Cronbachss = 0.60, M=3.11, S=1.06)

Under a cost cap tariff I enjoy the minutes before the cost capbecomes binding less.(M=2.88, S=1.29, median=3)Until the cost cap becomes binding I pay more attention to myusage behavior.(M=3.33; S=1.22; median=4)

Insurance (CC)(Cronbachss = 0.72, M=3.47, S=0.97)

With a cost cap I can use the mobile phone more jauntily.(M=3.54; S=1.06; median=4)I think less about my usage behavior in a tariff with cost cap,

because my bill can never exceed a fixed amount.(M=3.39; S=1.13; median=4)

Notice that the internal consistency of the constructs, as

evaluated by Cronbachs scale reliability coefficient , is high

throughout (M=0.72; S=0.086). This is particularly noticeable

for the flexibility and cost cap constructs, which have been

used in this study for the first time.15

Finally, we estimate the influence of the above constructs on

tariff choice in a nonlinear logit model. In the regression we

also include the available variables on the usage scenario (min

usage, max usage, flatrate price), the individual telephony be-

havior (prepaid, bill, cost control), socio-demographics (male,age) and the individual risk attitude as explanatory variables

in the regression model.16

Table VII shows the results of the logit regressions. In the

first model, which estimates the impact of the explanatory

variables on the probability to choose a flatrate plan over a

pay-per-use plan, only two of the four significant variables

have a non-negligible effect. More precisely, the choice of a

flatrate plan over a pay-per-use plan is mainly driven by the

insurance effect and the price of the flatrate. An increase of the

insurance effect by one unit will c.p increase the probability

of flatrate choice by 38.7%, whereas an increase of the price

by 1e will decrease the probability of choosing the flatrate

by 23.7%.The second model estimates the participants choice of the

flatrate over the cost cap plan with the flatrate-equivalent cost

14The convenience construct is in fact independent of the particular tariffframework, but listed under the flatrate effects for conciseness and compara-bility to previous studies.

15We followed the factor analysis methodology in order to eliminate andgroup the questions items according to the scale reliability coefficient.

16Pairwise correlations (Pearson) of all explanatory variables used in thelogit regressions were all below the threshold of 50%.

TABLE VIILOGIT REGRESSIONS ON FLATRATE CHOICE

Flatrate (1) vs. Flatrate (1) vs.Pay-per-use (0) Cost Cap (0)

Taximeter (FR) 0.109 -0.366

(0.105) (0.129)Insurance (FR) 0.327 0.310

(0.0983) (0.122)Flexibility (FR) -0.130 -0.210

(0.120) (0.147)Taximeter (CC) -0.0243 0.268

(0.0863) (0.109)Insurance (CC) -0.0747 -0.234

(0.0941) (0.119)Convenience -0.0519 -0.0461

(0.105) (0.136)Risk Aversion 0.0595 -0.212

(0.0480) (0.0587)Male 0.0909 -0.254

(0.199) (0.246)Age 0.0780 -0.0347

(0.0576) (0.0733)Prepaid -0.190 -0.167

(0.195) (0.247)Bill -0.00753 0.00451

(0.00585) (0.00620)

Cost Control -0.116 -0.0812(0.119) (0.146)Max Usage 0.00951 -0.00444

(0.000868) (0.00185)Min Usage 0.00735

(0.000855)Flatrate Price -0.213

(0.0422)Constant 2.382 4.337

(2.482) (2.130)

Observations 852 852Log likelihood -449.97 -320.28

Pseudo R2 22.15 % 6.04 %Correctly Classified 72.30 % 86.38%

Standard errors in parentheses p < 0.05, p < 0.01, p < 0.001

cap.17 In general, the explanatory power of this model, as

evaluated by Log likelihood and Pseudo R2, is lower compared

to the first model, because the flatrate is seldomly chosen in

our sample. Whether the respondents prefer the flatrate or the

cost cap plan depends foremost on the taximeter and insurance

effects as well as on the degree of risk aversion.

An increase of a participants evaluation of the taximeter

effect under a cost cap plan by one unit makes him 30.6% more

likely to choose the flatrate. Interestingly, with respect to the

flatrate taximeter effect, the impact is opposite: Respondents

who enjoy mobile telephony more under a flatrate plan (as

opposed to a pay-per-use plan) are in fact more likely to chosea cost cap plan over the flatrate, if given the option. Moreover,

this effect is strong, since an increase in the flatrate taximeter

effect by one unit increases the probability of chosing a cost

cap plan by 44.1%. This analysis also reveals that the context

is important for the evaluation of the taximeter effect. We

will return to this point during the discussion of the results in

Section VI.

17The variables min usage and flatrate price were omitted from theregression due to collinearity or invariance, respectively.

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Likewise, also the two insurance effects have opposite

impact on the respondents choice of the flatrate plan. First,

recall that the cost cap is set at the price of the flatrate in all

choice scenarios. Therefore, respondents are equally insured

against high usage under both plans. Nevertheless, participants

are 36% more likely to chose a flatrate over a cost cap tariff if

their assessment of the insurance effect of flatrates (compared

to pay-per-use plans) increases by one unit. In reverse, if asked

for the insurance effect with explicit reference to the cost cap

tariff, a unit increase will result in an increased probability of

26.3% towards choosing the cost cap plan over the flatrate.

Again, this highlights that consumers perceive the taximeter

and insurance effect differently in the context of a flatrate or

a cost cap plan.

Interestingly, also the risk preference has a strong effect

on the choice of the two equally capped tariffs. An increase

of respondents risk aversion by one unit18 increases the

chances to choose the cost cap plan by 23.7%. This result is

comprehensible, since the cost cap plan does not only insure

against high usage volumes, but also against low usage.

VI . DISCUSSION AND CONCLUSION

In this article we have investigated mobile telephony cus-

tomers perception of the recently introduced cost cap tariff

in comparison to corresponding pay-per-use and flatrate plans.

Previous studies have identified several psychological effects

which are believed to bias consumers choice towards flatrate

plans. However, flatrate plans also limit customers tariff

flexibility in months of low usage. Cost cap tariffs are a

hybrid between pay-per-use and flatrate plans and can offer

cost insurance while maintaining flexibility. Our investigation

of cost cap plans reveals three main insights.

First, customers favor cost caps tariffs over flatrates that

are priced at the cost cap level, even in those usage scenarioswhere the cost cap is reached with certainty. Obviously cost

cap tariffs seem to draw consumers attention, especially

when flexibility is important to them. In fact, in our sample

respondents show a strong desire for flexibility. In contrast to

previous quasi-experimental studies on tariff-choice, our study

cannot confirm a flatrate bias. To the contrary, our results

are in favor of a pay-per-use bias and in line with [1] and

[23], who have derived their results empirically from the 1986

Louisville, Kentucky local telephone tariff dataset. One could

argue, that the pronounced desire for flexibilty in our sample

is due to the fact that we have distributed the survey among

students of economics, who are aware of costs in general but

also primed to make rational choices. The sample is obviouslynot representative of the German population and also rather

conservative in terms of biased choice. However, the same

arguments hold true for the studies that have found a flatrate

bias in a similar group [14], [21]. Furthermore, in contrast

to [14], we have confronted respondents with realistic choice

scenarios in terms of usage and prices. Nevertheless it cannot

18Risk aversion is measured by the number of safe choices from the tennon-hypothetical choice scenarios of the risk aversion test. Thus, the riskaversion measure can take any integer value from 1 to 10.

be excluded that our findings are extenuated with a larger

representative set of participants. Furthermore, it is annotated

that it is not surprising that flexibility is not a significant factor

in our regression analysis: Because all respondents have in our

sample have confirmed a high desire for flexibility (M=3.66/5)

with small standard deviation (S=0.76), this construct is not a

good discriminator in the regression.

Secondly, we can confirm that the choice of cost caps

tariffs is in fact also driven by the taximeter and insurance

effects. The convenience effect, on the contrary, turns out to

be insignificant in our dataset. However, this may again be due

to a sample bias, since students do not tend to place emphasis

on convenience (M=2.11/5) and are rather homogeneous in

this perception (S=0.84).

Our third insight is more subtle and concerns the way

in which the taximeter and insurance effects influence tariff

choice. In particular, we find an opposite impact of these

effects if evaluated with respect to a flatrate or a cost cap tariff:

When given the opportunity to choose between a flatrate and

a comparable cost cap plan, those consumers tend to favor the

cost cap who prefer a flatrate (in lieu of a pay-per-use plan)due to the taximeter effect. On the contrary, there also seems

to be a distinct taximeter effect under a cost cap plan that

induces customers to divert away from the cost cap tariff and

towards the flatrate plan. Similarly, although participants are

equally insured under the available flatrate and cost cap plan,

those customers that have revealed the insurance effect as a

driver for choosing the flatrate plan are indeed less likely to

choose a cost cap plan instead. However, if those customers

that feel insured under a cost cap tariff will also choose this

tariff variant more likely.

In summary, we find that cost cap tariffs have combined

desirable properties of pay-per-use and flatrate plans and that

customers are well aware of this. Our insights on cost captariffs have direct ramifications for the strategic management

of mobile telephony providers that seek to offer this tariff. If

people are, as other studies suggest (e.g. [9], [10], [15], [19],

[24], [25]), presumably willing to pay a higher than average

monthly fee for a flatrate, it is likely that this holds also true

under a cost cap tariff. Thereby, cost cap tariffs are particularly

interesting for those customers that have a strong desire to

be insured against high telephony bills, but wish to maintain

tariff flexibility. Thus, on the one hand, the cost cap tariff is

attractive to those customers that are currently under a flatrate

plan if their perception of the cost-cap-related taximeter effect

is not too strong. Especially risk averse flatrate customers may

even be willing to opt for a cost cap plan although the cost capis higher than the corresponding flatrate price, because then

they are insured in months of low usage. On the other hand,

those users that have currently a pay-per-use plan, because

they have a strong desire for a flexible tariff or because they

have a comparably low usage volume, could also be lurked

into a cost cap tariff even if this means to accept higher per-

minute prices. In other words, these customers are willing to

pay an indirect risk premium via the per-minute price in order

to be insured against high telephone bills. If the cost cap does

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not become binding, the mobile operator can especially profit

from these customers.

In fact, this latter reasoning seems to have been the main

driver for o2 to introduce a cost cap tariff whose cost cap

is set at the level of the cheapest available all-net flatrate

in the market. On the contrary, the per-minute price under

this cost cap tariff is twice as high as the cheapest standard

pay-per-use rate in the market. However, from a strategic

management perspective, it is also very risky to offer a cost

cap tariff. In contrast to a flatrate, under a cost cap plan

consumers with a comparably low usage cannot compensate

for the costs of heavy users. But, the company may also

speculate on the existence of a more subtle effect: Because

customers are insured against high costs and because the cost

cap tariff may effectively mitigate the taximeter effect with

respect to a pay-per-use plan, a customer may in fact phone

more than under a pay-per-use plan, but total costs yet remain

below the cost cap. The marketing of o2 focuses on this

aspect of the consumption behavior. Users should feel save

with the so-called cost airbag and therefore do not have to

think about their consumption behavior anymore. Therefore,the target group for this tariff scheme does not seem to be the

typical heavy or actual flatrate user, but the average user who

does not want to commit himself to high monthly costs.

We have merely presented a first step into the investigation

of cost cap tariffs, which have, to the best of our knowledge,

previously not been assessed academically. While our study

has focused more on the choice between cost cap and flatrate

plans, future work should especially consider the choice be-

tween cost cap and pay-per-use tariffs in more detail. Recall

that a cost cap tariff dominates the pay-per-use and the flatrate

plan at equal per-minute prices and at a cost cap level equal to

the flatrate price. Thus, future research should systematically

investigate the cost cap tariff bias in those scenarios where(i) the per-minute price is higher in the cost cap tariff than

in an equivalent pay-per-use plan and (ii) the cost cap is

higher than the corresponding flatrate price. Furthermore, it

seems interesting to further investigate the reasons why the

insurance and taximeter effects are perceived differently under

a cost cap and flatrate tariff framework. Within the flatrate

framework, the insurance and taximeter effect are always

coincidental, whereas the effects can be separated under a cost

cap framework. The question remains if consumers experience

the taximeter effect even if they are insured and how this

affects their perception during telephony consumption as well

as their potential tariff switching behavior.

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