M-insurance Overcoming Privacy Concerns in the Consumer Use of Insurance Services based on Mobile Technologies

Mobile
Insurance
Overcoming Privacy
Concerns in the
Consumer Use of
Insurance Services
based on Mobile
Technologies


Overcoming Privacy Concerns in the Consumer Use of Insurance Services based on Mobile Technologies

Disclaimer:
The copyright of this document rests with the author. The views expressed in this thesis are
those of the author and do not necessarily express the views of the Delft University of
Technology or Deloitte consulting.

ii


M-insurance
Overcoming Privacy Concerns in the Consumer Use of
Insurance Services based on Mobile Technologies
Master thesis
December, 2014

S.A.J.P. (Sebastian) Derikx


Delft University of Technology
MSc. System, Engineering, Policy Analysis & Management (SEPAM)

Faculty of Technology, Policy and Management
Section Information and Communication Technology
SPM5910 Master Thesis Project
The Netherlands

Graduation Committee
Chair: Prof. Dr. Yao-Hua Tan – ICT section
Officious Chair: Prof. Dr. W.A.G.A. Bouwman – ICT section
First Supervisor: Dr. ir. G.A. Reuver MSc. – ICT section
Second Supervisor: Dr. ir. M. Kroesen TLO section
External Supervisor: Drs. A. Beers – Deloitte Consulting
External Supervisor: A. Mahawat Khan MSc. – Deloitte Consulting


Overcoming Privacy Concerns in the Consumer Use of Insurance Services based on Mobile Technologies

“Science and technology revolutionize our lives, but memory, tradition and
myth frame our response” – Arthur M. Schlesinger Jr.

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|SEPAM Master Thesis |December 2014 | S.A.J.P Derikx|

Acknowledgements
This thesis marks the final step for the completion of my Master System Engineering, Policy Analysis
and Management (SEPAM) at the Delft University of Technology. This graduation project started in
May 2014 intern at Deloitte Consulting and since that moment a significant part of my life has been
spent on this thesis. Therefore, I am proud to present the final version of my thesis.
First, I would like to express my gratitude to my graduation committee for their great support last

seven months. I would like to thank Assistant Professor Mark de Reuver, my first supervisor, for his
general support in both theoretical and practical field. I would like to thank Assistant Professor
Maarten Kroesen, my second supervisor, for his sharpening insights in the statistical methodologies
and Professor Harry Bouwman for chairing my graduation committee.
Second, I would like to thank Deloitte Consulting for giving me the great opportunity to conduct my
master thesis intern. Your innovative and progressive mindset helped me to finalize this thesis. I would
like to express special thanks to Arjen Beers and Amira Mahawat Khan for their feedback, enjoyable
way of working and involving me in the business of mobile insurance.
Third, I would like to thank my friends and family for their support during my graduation. Special
thanks to my friends, siblings and (former) roommates for lending their listening ears and
encouragement, my parents for bringing me to this point in life and my girlfriend for giving me the
freedom and loving support required for this accomplishment.
I hope you all enjoy reading the result,

Amsterdam, December 2014,
Sebastian Derikx

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Overcoming Privacy Concerns in the Consumer Use of Insurance Services based on Mobile Technologies

List of Acronyms
AV
B1/B2
BMT
BR
CB
CSMIS
CSMS

DOI
FA
FSI
GR
IID
IoT
KR
LU
MB
MI
M-Insurance
MNL-model
MOE
PAYD
PC
PU
RW
SD
SEM
TAM
UBI
WTP

ii

Additional insurance offerings
Relative consumer saving
Business Model Transformations (innovation)
Behavioral rewarding
Choice-based conjoint

Context Sensitive Mobile Insurance Services
Context Sensitive Mobile Services
Diffusion of innovation
Factor Analysis
Financial Service Industry
Third party advertisement
Independently and Identically Distributed
Internet of Things
Kilometer Registration
Likelihood of use
Expected monetary benefit
Mobile insurance
Mobile insurance
Multinomial logit model
Margin of error
Pay-as-you-drive
Privacy concerns
Perceived usefulness
Registration road behavior
Standard deviation
Structural Equation modeling
Technology acceptance model
Usage based insurance
Willingness to pay


|SEPAM Master Thesis |December 2014 | S.A.J.P Derikx|

Management summary:
Research problem

Ongoing digitalization results in both threats as opportunities for the insurance sector. Increased
transparency stimulates switching behavior and shifts the insurance market to a more price based
competition. Together with recent developments such as the ban on intermediary commissions and
the separation of banking and insurance activities, the traditional business model is put under
pressure. By fully reaping the benefits of mobile technologies, such as portability, social interactivity,
context sensitivity, connectivity and individuality, a variety of opportunities for innovative insurance
services arises. A more differentiated product portfolio can shift the price based competition to a more
quality focus which enables insurers to operate in more niche markets focusing on higher margins.
In the last few years, privacy concerns associated with the consumer use of mobile technologies, have
been the subject of many research papers. A number of privacy studies empirically verified the
negative effect of perceived privacy concerns on the intention of use online and mobile services. As
the disclosure of personal information is often necessary in obtaining online and mobile services,
privacy concerns could inhibit people’s intention to use them as well. This could have major
implications for the adoption of mobile insurance since privacy concerns regarding the insurance
industry are already relatively high in general. Therefore, it is essential, in the development of future
mobile insurance services, to understand the role of associated privacy concerns. Accordingly, this
study aims to increase understanding of mobile insurance related privacy concerns, its relation on
consumer’s ‘likelihood of use’ and potential compensating factors as perceived usefulness and
expected monetary benefits. Therefore, the objective of this research is to further develop
understanding towards the mitigating effect of perceived usefulness and monetary rewards on privacy
concerns regarding the likelihood of use for mobile insurance services. In line with this objective the
following main research question is developed:
RQ

In what way can privacy concerns, affecting the likelihood of use mobile insurance services,
be mitigated by expected monetary benefits and perceived usefulness?

Domain on Mobile Insurance
For a clear and consistent understanding of this research question the definition of mobile insurance
for this study is defined as “insurance products and services based on context sensitive mobile

technologies”. Hereby insurance products and services involve all direct customer focused activities
of an insurer. Thus, both the insurance policy itself and supportive services are involved. Context
sensitivity of mobile technologies involves the ability to both gather and respond to real or simulated
data unique to current location, environment, and time.
Mobile insurance covers a broad field of insurance services. In order to get a better understanding on
the scope of mobile insurance a categorization is made. This categorization is based on an explorative
scan to all worldwide mobile insurance services. These worldwide mobile insurance services are
subsequently categorized on its consumer functionalities and validated with insurance industry and
technology experts. The final categorization, with a brief elaboration per category is listed below:
1. Usage based
insurance;
2. Behavioral
rewarding;
3. Up-to-date insurance
package;

With a usage-based insurance premium, consumers pay only premium
for actual use of their insurance.
By rewarding customers for less risky behavior, the insurer is trying to
reduce the risk of accidents.
By using personal (context sensitive) information of consumers,
relevant personalized insurance products could be provided.
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Overcoming Privacy Concerns in the Consumer Use of Insurance Services based on Mobile Technologies

4. Preventative
information services;
5. Accident detection &

prevention;
6. Mobile accessibility;
7. Personal dashboards;
8. Additional
informative services;

Consumer context information offers insurers the opportunity to
provide consumers with relevant context related preventative
information.
By detecting (potential) accidents as early as possible, damages could
be prevented and minimized.
Mobile technologies facilitate a communication channel for sales and
services.
By measuring individual behavior, insight could be provided in risk
profiles of consumers to increase risk awareness.
Context sensitive information offers opportunities for several semiinsurance services.

Theoretical background on the concept of privacy
Within literature a variety of definitions and interpretations for privacy is present, however a unified
account of privacy has yet to emerge. This study interprets the definition of privacy as a tradable
interest; “an interest that individuals have in sustaining a ‘personal space’ free from interference by
other people and organizations”. Subsequently, this definition is operationalized to facilitate the
measurement of privacy. A commonly used (reverse) operationalization of privacy in literature is the
measurement of privacy concerns. Therefore, privacy is measured in this study by privacy concerns.
Due to its plurality and inconsistency, a unified account for privacy is still absent in literature. Some
scholars used another approach and instead of searching for an inclusive definition of privacy, they
developed a typology for privacy. Recent literature defined seven types of privacy of which three are
relevant for the application of (current) mobile insurance:
"The right to move about in public or semi-public space without being
Privacy of location and space

identified, tracked, or monitored."

Privacy of behavior and action

"The ability to behave in public, semi-public or one’s private space
without having actions monitored or controlled by others."

Privacy of data and image

"Concerns about making sure that individuals’ data is not automatically
available to other individuals and organizations and that people can
exercise a substantial degree of control over that data and its use.”

A majority of consumers considers the disclosure of personal information as essential in modern life.
The disclosure of personal information is however contrary with the definition of privacy; sustaining a
‘personal space’. Consequently, numerous studies consistently concluded that people are very
concerned about their online privacy. Aforementioned contradiction imply that individuals consider a
utilitarian trade-off between perceived benefits and sacrifices of disclosing personal information.
Hereby privacy concerns have to be considered as a sacrifice. Previous literature states that providers
can mitigate the negative effect of privacy concerns on the ‘likelihood of use’ in two ways; (1) by
offering privacy policies regarding the handling and use of personal information and (2) by offering
benefits such as monetary rewards or convenience. These compensating are further operationalized
as expected monetary benefits and perceived usefulness.
No existence of a direct relation between the construct of privacy concerns, perceived
usefulness and expected monetary benefits is found in literature. However, several IT adoption studies
in literature suggest an indirect relation through the construct of likelihood of use. Hereby, the
likelihood of use is positively affected by the perceived usefulness and expected monetary benefits
and negatively affected by privacy concerns. These findings are combined in a conceptual model which
is validated for the case of mobile insurance by the explorative assessment.
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|SEPAM Master Thesis |December 2014 | S.A.J.P Derikx|

Analysis and results
In order to provide an answer on the main research question, two quantitative assessments are
conducted. By means of a consumer survey and multiple regression, an explorative assessment is
conducted to the relations between the constructs of likelihood of use, privacy concerns, perceived
usefulness and expected monetary benefit. Hereby, the conceptual model is validated.
By means of a conjoint survey, a more in-depth assessment to the buy-off value of privacy is
conducted for all relevant types of privacy, for the case of Pay-As-You-Drive (PAYD) insurance. An
overview of both assessments is provided in Table 0.1.
Table 0.1: Overview assessments
Explorative assessment:

Conjoint assessment

Method

Descriptive statistics & multiple linear regression

MI Category

All identified categories of MI services

Conjoint analysis (statedchoice)
One MI service (PAYD)

Goal output:
Collection technique:

Consumer attitude on Likelihood of use &
relation to PC, PU & MB
Hard-copy & electronic survey

Buy-off value for privacy
concerns
Hard-copy survey

Number of respondents

137

55

Explorative assessment
The construct of perceived usefulness appears to be in general the strongest predictor for the
likelihood of use mobile insurance. The relation between these two constructs is significant for all
categories of mobile insurance. Mobile insurance services with a higher perceived usefulness are likely
to raise more interest of consumers for future use.
The relation between the construct of expected monetary benefits and the likelihood of use
shows to be positive as well, however not significant for all categories of mobile insurance. Expected
monetary benefits appear not to be a significant predictor for the use of mobile accessibility. Overall
it can be concluded that mobile insurance services with a higher expected monetary benefit for the
consumer are likely to raise more interest of consumers for future use.
In contrast to previous constructs, the relationship between the construct of privacy concerns
and the likelihood of use appears to be negative, however not significant for all categories of mobile
insurance. Privacy concerns appear not to be a significant predictor for the use of Accident detection
and prevention and Mobile accessibility. Overall it can be concluded that mobile insurance service
with raised privacy concerns are likely to have a negative impact on the likelihood of use mobile

insurance.
Altogether, it can be concluded that the likelihood of use mobile insurance services is primarily driven
by its perceived usefulness. Thereafter, consumers’ likelihood of use mobile insurance services is
driven by raised expectations on accompanied monetary benefits and inhibited by increased privacy
concerns. However, not for every category of mobile insurance the predictors have a significant
relation with the likelihood of use, no significant contra relations are found. These findings seem to
support the relations as found in literature.
Conjoint assessment
Although the explorative assessment shows us that monetary benefits are not the strongest predictor
for consumers’ likelihood of use mobile insurance services, the conjoint assessment is used for a more
in-depth analysis to the buy-off value of privacy. For this analysis, the buy-off value of privacy is
determined for all individual relevant types of privacy for the case of pay-as-you-drive (PAYD)
insurance. PAYD insurance is an automobile insurance whereby the premium is dependent on the
actual car-use. Most common used indicators for car-use are mileages, and driving behavior.
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Overcoming Privacy Concerns in the Consumer Use of Insurance Services based on Mobile Technologies

Respondents are willing to sell their privacy of location and space through continuously disclosing the
GPS-location of their car for a financial compensation of €2,27 per month. Privacy of behavior and
actions appears to have slightly higher buy-off value since respondents are willing to continuously
provide insight in their car-acceleration, car-deceleration and steering behavior, for a financial
compensation of €2,98 per month.
Regarding the privacy of data and image two buy-off values are determined related to the
internal and external (secondary) use of personal information. Hereby, secondary use is
operationalized as the unauthorized use of personal information for personalized advertisement.
Respondents are willing to sell their privacy of data image for third party advertisement for a financial
compensation of €2,77 per month. In contrast to the external use of personal information,
respondents are willing to pay a monthly contribution of €2,91 for internal (insurance related)

personalized advertisement. However, these outcomes cannot blind be generalized to the entire
population, it can be concluded that respondents derive more disutility from external use of privacy
related information than internal use.
Discussion and conclusion
In conclusion, we can say that privacy concern are likely to rise with the use of mobile insurance
services. However these concerns can be compensated by both perceived usefulness of the service
and an expected monetary benefits. The compensation by the expectation for financial benefits
appears to have a smaller effect than compensation by elevated perceptions on the usefulness of a
mobile insurance service.
However when the expectation on monetary benefits is amplified with a financial
compensation, the buy-off values for different types of privacy appear to be rather small. Hereby,
consumers perceive their privacy of behavior and action as more valuable than their privacy of
location and space. Regarding privacy of data and image, the buy-off value seems to be dependent on
the one who exploits their data; the data holder or an external party. While the use of consumers’
personal information for personalized advertisement by the data holder appears to be beneficial,
personalized advertisement by third parties is perceived as adversely.
This study is the first attempt in literature in which the buy-off value for different types of privacy is
determined. As this study proves, is the buy-off value of privacy varying for different types of privacy,
supporting its plurality. A plural approach on privacy could provide a more detailed method for future
technology acceptance studies. Emerging trends, such as the ongoing digitalization, quantified-self,
internet of things and big data require the disclosure of different sets of personal and contextual
information. Consequently, different types of privacy may be involved affecting consumer adoption
to another extent. Therefore, it is recommended to include a plural construct of privacy in future
technology acceptance studies. Further research is recommended to evaluation the value of privacy
for other mobile (insurance) services. A comparison between the values of privacy of these individual
services may result in interesting insights for technology adoption and privacy literature.
By proving the existence of multiple types of privacy dependent on the specific characteristics of
concerned (mobile) services, this study validates the findings of Nikou (2012) that IT artifact should no
longer be treated as ‘Black-Box’. Further, analysis methods such as factor analysis and structural
equation modeling (SEM) have not been applied in the explorative survey. By applying SEM in further

research on the explorative dataset to examine both the effect of individual constructs per categories
of mobile insurance and a generic constructs on the likelihood of use, could result in interesting
insights, in line with Nikou’s (2012) findings, that IT artifact should no longer be treated as ‘Black-Box’.

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Overcoming Privacy Concerns in the Consumer Use of Insurance Services based on Mobile Technologies

Contents
Acknowledgements ................................................................................................................................................. i
Management summary: ........................................................................................................................................ iii
List of Figures .......................................................................................................................................................... x
List of Tables .......................................................................................................................................................... xi
1.

Research introduction ............................................................................................................................. 2
1.1.
Problem introduction: Mobile technologies as enabler for business innovation ................................. 2
1.2.
Knowledge gap: The value of privacy .................................................................................................... 3
1.3.
Research objective ................................................................................................................................ 4
1.4.
Research questions ............................................................................................................................... 4

1.5.
Research scope ..................................................................................................................................... 6
1.6.
Research approach ................................................................................................................................ 7
1.7.
Report structure .................................................................................................................................... 9

2.

Domain: Insurance ...................................................................................................................................... 11
2.1.
The insurance industry ........................................................................................................................ 11
2.1.1.
The concept of insurance ........................................................................................................... 11
2.1.2.
Key stakeholders ........................................................................................................................ 11
2.1.3.
Types of insurance ...................................................................................................................... 12
2.1.4.
The insurance value chain .......................................................................................................... 13
2.1.5.
Insurer’s revenue model – collective goals for mobile insurance .............................................. 13
2.2.
The concept of Mobile insurance ........................................................................................................ 15
2.3.
Identification of mobile insurance services ........................................................................................ 17
2.3.1.
Exploration method .................................................................................................................... 17
2.3.2.
Composing a long-list of mobile insurance services ................................................................... 18

2.3.3.
Categorization of mobile insurance services .............................................................................. 18
2.3.4.
Category validation .................................................................................................................... 21
2.4.
Domain conclusion .............................................................................................................................. 22

3.

Relevant Theories and Concepts on Privacy ............................................................................................... 24
3.1.
Search strategy .................................................................................................................................... 24
3.2.
The concept of privacy ........................................................................................................................ 26
3.2.1.
Defining privacy .......................................................................................................................... 26
3.2.2.
Measuring privacy as a concern ................................................................................................. 29
3.2.3.
Types of privacy .......................................................................................................................... 29
3.3.
Privacy and technology ....................................................................................................................... 33
3.3.1.
Categorizing privacy harm .......................................................................................................... 33
3.3.2.
Technology enabling privacy harm ............................................................................................. 34
3.4.
Theory applied: Involved privacy types with MI ................................................................................. 36
3.5.
Hypothesis development .................................................................................................................... 37

3.6.
Theory conclusion ............................................................................................................................... 39

4.

Survey research design ............................................................................................................................... 42
4.1.
Explorative assessment to the effect of PC, PU and MB on likelihood of use .................................... 42
4.1.1.
The survey and sample design ................................................................................................... 42
4.1.2.
Survey operationalization........................................................................................................... 45
4.1.3.
Validity and testing of assumptions ........................................................................................... 47
4.2.
An extensive assessments to the buy-off value of CSMIS related privacy concerns .......................... 49
4.2.1.
Case selection: PAYD insurance .................................................................................................. 49
4.2.2.
Background on conjoint analysis ................................................................................................ 50
4.2.3.
The survey and sample design ................................................................................................... 52
4.2.4.
Defining the attributes and attribute levels ............................................................................... 54
4.2.5.
Composition of the choice sets .................................................................................................. 56
4.2.6.
Data processing and analysis ...................................................................................................... 57
4.2.7.
Reliability and validity ................................................................................................................ 57

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5.

Analysis and results ..................................................................................................................................... 60
5.1.
Explorative analysis ............................................................................................................................. 60
5.1.1.
Data processing and analysis ...................................................................................................... 60
5.1.2.
Descriptive analysis .................................................................................................................... 60
5.1.3.
Hypotheses testing ..................................................................................................................... 63
5.1.4.
Conclusion and discussion on the results of the explorative study............................................ 65
5.2.
Conjoint analysis ................................................................................................................................. 68
5.2.1.
Estimated coefficients ................................................................................................................ 68
5.2.2.
Part worth utilities ...................................................................................................................... 69
5.2.3.
Willingness to pay ...................................................................................................................... 70
5.2.4.
Buy-off value for privacy ............................................................................................................ 71
5.2.5.

Influential factors for the buy-off value of privacy ..................................................................... 72
5.2.6.
Conclusion and discussion on the results of the conjoint study ................................................ 74
5.3.
Cross-survey comparison of results .................................................................................................... 77

6.

Discussion and conclusion .......................................................................................................................... 79
6.1.
Main findings....................................................................................................................................... 79
6.2.
Implications ......................................................................................................................................... 82
6.2.1.
Theoretical implications ............................................................................................................. 82
6.2.2.
Managerial implications ............................................................................................................. 83
6.3.
Limitations and further research ........................................................................................................ 83
6.4.
Reflection on research process ........................................................................................................... 85

Literature .............................................................................................................................................................. 87
7.

Appendices .................................................................................................................................................. 93
A: Long list Mobile Insurance ........................................................................................................................... 94
B: Literature background.................................................................................................................................. 97
C. Hypotheses overview ................................................................................................................................. 102
D. Surveys ....................................................................................................................................................... 103

D1. Explorative survey ............................................................................................................................... 103
D2. Conjoint survey .................................................................................................................................... 115
E. Multiple regression .................................................................................................................................... 121
E1. Validation an verification ..................................................................................................................... 121
E2. Descriptive statistics (Multiple regression) .......................................................................................... 131
E3. Hypotheses testing............................................................................................................................... 132
E4. Estimation General model ................................................................................................................... 140
F. Conjoint analysis ......................................................................................................................................... 142
F1. Effect coding......................................................................................................................................... 142
F2. Ngene ................................................................................................................................................... 142
F3. Biogeme ............................................................................................................................................... 143
F4. Output Biogeme output ....................................................................................................................... 145

8.

Scientific article ......................................................................................................................................... 146

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Overcoming Privacy Concerns in the Consumer Use of Insurance Services based on Mobile Technologies

List of Figures
Figure 1.1: Research approach ............................................................................................................................... 8
Figure 1.2: Report outline ....................................................................................................................................... 9
Figure 2.1: Classification insurance industry ........................................................................................................ 12
Figure 2.2: The insurance value chain .................................................................................................................. 13
Figure 3.1: Solove's Taxonomy of Privacy (D. Solove, 2006) ................................................................................ 34
Figure 3.2: Conceptual model ............................................................................................................................... 38
Figure 4.1: Explorative survey representation (age & education) ........................................................................ 44

Figure 4.2: Correlation driven kilometers and amount of damages (Vonk et al., 2003) ...................................... 49
Figure 4.3: Conjoint survey representation (age & education) ............................................................................ 53
Figure 4.4: Survey experience by respondents ..................................................................................................... 54
Figure 4.5: Ngene syntax ...................................................................................................................................... 56
Figure 4.6: Biogeme utility functions .................................................................................................................... 57
Figure 5.1: Rating on likelihood of use ................................................................................................................. 61
Figure 5.2: Rating on perceived usefulness14 ....................................................................................................... 61
Figure 5.3: Rating on expected monetary benefits .............................................................................................. 62
Figure 5.4: Rating on privacy concerns15 .............................................................................................................. 63
Figure 5.5: Utility graph for the attribute relative consumer saving .................................................................... 69
Figure 5.6: Willingness to sell privacy ................................................................................................................... 76
Figure 7.1: Normality check on error terms ....................................................................................................... 127
Figure 7.2: Linearity check all indicators............................................................................................................. 130
Figure 7.3: Biogeme interface............................................................................................................................. 143
Figure 7.4: Biogeme MODfile.............................................................................................................................. 143
Figure 7.5: Biogeme DATfile (example) .............................................................................................................. 144
Figure 7.6: Biogeme REPfile ................................................................................................................................ 145

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List of Tables
Table 0.1: Overview assessments ........................................................................................................................... v
Table 1.1: Overview of examined sub-questions per chapter ................................................................................ 5
Table 1.2: Research scope ...................................................................................................................................... 6
Table 2.1: Exploration sources Mobile Insurance services ................................................................................... 17
Table 2.2: Categorization of MI ............................................................................................................................ 20
Table 2.3: MI Workshop Deloitte participants (27-10-2014) ................................................................................ 21

Table 3.1: Search engines and search terms used for this study.......................................................................... 24
Table 3.2: Concepts of privacy .............................................................................................................................. 28
Table 3.3 Seven Types of Privacy (Finn et al., 2013) ............................................................................................. 32
Table 3.4: Overview hypotheses ........................................................................................................................... 40
Table 4.1: Overview (sub) hypotheses.................................................................................................................. 45
Table 4.2: Overview of MI categories with survey examples ............................................................................... 45
Table 4.3: Overview of constructs and their operationalization in English and Dutch ......................................... 46
Table 4.4: Attribute levels for privacy................................................................................................................... 54
Table 4.5: Attribute levels for relative consumer saving ...................................................................................... 55
Table 4.6: Conjoint attributes and attribute levels (Dutch) .................................................................................. 56
Table 4.7: Model consistency verification ............................................................................................................ 58
Table 5.1: Standardized coefficients (Beta) for dependent variable Likelihood of use ,, ....................................... 63
Table 5.2: Hypotheses testing .............................................................................................................................. 64
Table 5.3: Generic model ...................................................................................................................................... 66
Table 5.4: Estimated coefficients.......................................................................................................................... 68
Table 5.5: Part worth utilities ............................................................................................................................... 69
Table 5.6: Monetary value of utility points .......................................................................................................... 70
Table 5.7: Monetary value of non-financial attributes ......................................................................................... 70
Table 5.8: Monetary value of financial attribute levels ........................................................................................ 71
Table 5.9: Comparison of utilities on influential factors....................................................................................... 72
Table 5.10: Comparison of buy-off values (willingness to pay) on influential factors [euro] ............................... 72
Table 5.11: Privacy buy-off values for the case of PAYD insurance ...................................................................... 74
Table 7.1: Long-list Mobile Insurance ................................................................................................................... 94
Table 7.2: Involved privacy types per category of MI ......................................................................................... 100
Table 7.3: Hypotheses subdivision per MI category ........................................................................................... 102
Table 7.4: Group statistics Online/Offline experiment ....................................................................................... 121
Table 7.5: Independent Samples Test (Offline/Online) ...................................................................................... 123
Table 7.6: Multiple regression on C7 (only offline) ............................................................................................ 125
Table 7.7: Multiple regression on C7 (only online) ............................................................................................. 126
Table 7.8: Frequency statistics (skewness and kurtosis) .................................................................................... 127

Table 7.9: Descriptive statistics Explorative assessment .................................................................................... 131
Table 7.10: Multiple regression C1 ..................................................................................................................... 132
Table 7.11: Multiple regression C2a ................................................................................................................... 133
Table 7.12: Multiple regression C2b ................................................................................................................... 134
Table 7.13: Multiple regression C3 ..................................................................................................................... 135
Table 7.14: Multiple regression C4 ..................................................................................................................... 136
Table 7.15: Multiple regression C5 ..................................................................................................................... 137
Table 7.16: Multiple regression C6 ..................................................................................................................... 138
Table 7.17: Multiple regression C7 ..................................................................................................................... 139
Table 7.18: Multiple regression generic model .................................................................................................. 140
Table 7.19: Fit generic model ............................................................................................................................. 141
Table 7.20: Conjoint analysis effect coding ........................................................................................................ 142
Table 7.21: Ngene choice set .............................................................................................................................. 142

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Chapter 1
Research Introduction
2.1
2.1
2.1
2.1
2.1
2.1
2.1

Problem introduction
Knowledge gap
Research objective
Research questions
Research scope
Research approach
Report structure

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Overcoming Privacy Concerns in the Consumer Use of Insurance Services based on Mobile Technologies

1. Research introduction
This chapter introduces the significance of privacy concern mitigation, in the development of mobile
insurance services. The subsequent sections elaborate on the objective, scope, approach and research
questions of this study.

1.1.

Problem introduction: Mobile technologies as enabler for business innovation

Since internet gained ground in the later nineties the digital revolution rapidly penetrated deep into
society and transformed the way people communicate, work and live. The internet gave social life an
entirely different meaning and radically changed the way business was done. Easier and more efficient
online communication channels were born and a more online oriented consumer market arose
(Pantano & Viassone, 2014). Today 87% of Dutch population uses internet on daily basis and 75% uses
internet for commercial purposes (Stichting Internet Domeinregistratie Nederland, 2012). The digital
revolution penetrated into the insurance sector as well. Almost all Dutch insurers rolled out online
platforms and 64% of them even launched a mobile platform (Deloitte, 2014).

Ongoing digitalization both results in threats as opportunities for the insurance sector. Increased
transparency stimulates switching behavior and shifts the insurance market to a more price based
competition (Libbenga, 2013). Together with recent developments as the ban on intermediary
commissions and the separation of banking and insurance activities, the traditional business model is
put under pressure. Given market circumstances Dutch insurers should carefully consider how to
differentiate themselves in a world of continued (digital) disruption.
By fully reaping the benefits of mobile technologies, such as portability, social interactivity, context
sensitivity, connectivity and individuality, a variety of opportunities for innovative insurance services
arises (Klopfer, Squire, & Jenkins, 2002). A more differentiated product portfolio can shift the price
based competition to a more quality focus which enables insurers to operate in more niche markets
focusing on higher margins (Granados, Gupta, & Kauffman, 2008). For example; Allstate (US) uses
mobile technologies in their Drivewise program to offer car insurance policies in which premiums are
calculated on the basis of driven miles and driving behavior; and BNP Parisbas Cardif (Italy) enhanced
damage control by providing home-policy-owners with accident detection technologies. Nevertheless,
minimal innovative applications of mobile technologies exist within the Dutch insurance market and
the applications that are present mainly serve as an additional distribution channel (Berdak & Carney,
2014; Deloitte, 2014b).
In the last few years, privacy concerns associated with the consumer use of mobile technologies, have
been the subject of many research papers. A number of privacy studies empirically verified the
negative effect of perceived privacy concerns on the intention of use online and mobile services
(Malhotra, Kim, & Agarwal, 2004; Miyazaki & Fernandez, 2001). As the disclosure of personal
information is often necessary in obtaining online and mobile services, privacy concerns could inhibit
people’s intention to use them as well. This could have major implications for the adoption of mobile
insurance since privacy concerns regarding the insurance industry are already relatively high in general
(Cheung, 2014; Milne & Boza, 1999). Therefore, it is essential, in the development of future mobile
insurance services, to understand the role of associated privacy concerns. Accordingly, this study aims
to increase understanding of mobile insurance related privacy concerns, its relation on consumer’s
‘likelihood of use’ and potential compensating factors.

2

|SEPAM Master Thesis |December 2014 | S.A.J.P Derikx|

1.2.

Knowledge gap: The value of privacy

Today, a wide range of Dutch mobile banking services is present, however minor mobile applications
exist in which financial services are directly sensitive to the user’s context. Hereby, context sensitivity
is defined as ‘the ability to both gather and respond to real or simulated data unique to current
location, environment, and time of the user’ (Klopfer et al., 2002). Examples of context sensitive mobile
services (CSMS) are, the use of (user’s) GPS-location for navigations services or (user’s) browse history
as input for personal advertising (Google’s search engine). Current mobile financial services, including
aforementioned Dutch mobile banking services mainly function as an extension of existing online
platforms, reaping the benefits of mobile technologies as portability, individuality and connectivity,
but disregarding the potential of context sensitivity.
The rapid mobilization of technology in today’s society, cleared the path for Context Sensitive Mobile
Services (CSMS). As the name suggests, are CSMS using user’s context information as input for its
service. Compared to e-commerce and not-context-sensitive mobile services, CSMS requires users to
disclose extensive sets of personal information such as GPS-location, acceleration and social networks.
In line with previous research, this could result in elevated privacy concerns since Bansal, Zahedi, &
Gefen (2010) show us that the sensitivity of disclosed personal data has a significant positive effect on
related privacy concerns. Thus, the disclosure of more sensitive personal data, such as with the use of
CSMS, could result in elevated privacy concerns.
As the disclosure of contextual information seems to be an unavoidable condition in obtaining
innovative (next-level) insurance services, privacy concerns are likely to rise with the use of mobile
insurance. Hereby ‘Mobile Insurance’ (M-insurance) is defined in this study as mobile technologybased insurance services, in which CSMS is integrated. A number of privacy studies empirically verified
the negative effect of perceived privacy concerns on the intention of use online and mobile services
(Malhotra et al., 2004; Miyazaki & Fernandez, 2001). Therefore, it is assumed that related privacy

concerns negatively affect consumer’s intention to use mobile insurance.
Previous research of Laufer and Wolfe (1977) suggests that individuals perform a “calculus of
behavior” to assess the consequences of providing personal information. On the basis of this
theoretical construct, individuals consider a trade-off between perceived benefits and sacrifices of
disclosing personal information. This implies that unavoidable privacy concerns, associated with the
use of mobile insurance, have to be compensated in order to persuade consumers to adopt. Hann,
Hui, Lee & Png (2007) state that organizations can mitigate this negative effect of privacy concerns on
the ‘likelihood of use’ in two ways; (1) by offering privacy policies regarding the handling and use of
personal information and (2) by offering benefits such as monetary rewards or convenience. Li,
Sarathy, & Xu (2010) further operationalized these compensating benefits as ‘monetary benefits’ and
‘perceived usefulness’.
A number of studies to the relation of privacy concerns on consumer’s ‘likelihood of use’ endorsed
the compensating effect of ‘monetary benefits’ and ‘perceived usefulness’ in an e-commerce
environment (Dinev & Hart, 2006; Hann et al., 2007; Laudon, 1996; Li et al., 2010). People are willing
to disclose personal information, as long as the benefits overrun the privacy sacrifice. Although
literature to e-commerce related privacy concerns, its relation on consumer’s ‘likelihood of use’ and
potential compensating factors are present in literature, the effect of CSMS related privacy concerns
is still unclear. The use CSMS in mobile insurance requires users to disclose more sensitive sets of
personal information, which could accelerate the effect on related privacy concerns (Bansal et al.,
2010). Thereby, are privacy concerns regarding the insurance industry and its online platforms already
high in general (Cheung, 2014; Milne & Boza, 1999). Therefore the insurance industry environment is
likely to be more sensitive to privacy issues.
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Overcoming Privacy Concerns in the Consumer Use of Insurance Services based on Mobile Technologies

Insight in mitigating factors for CSMS related privacy concerns is essential in the development of
mobile insurance services. However, to my best knowledge no literature focusses on the perception
of privacy and mitigating mechanisms in the use of (insurance) CSMS exists. Therefore, this study will

assess aforementioned construct, in which the negative effect of privacy concerns on consumer’s
likelihood of use is compensated by monetary benefits and usefulness, for the insurance CSMS.

1.3.

Research objective

Based on the knowledge gap and problem statement, the research objective is composed. The
research objective will function as input for the composition of the research questions.
The objective of this research is to further develop understanding towards the mitigating effect of
perceived usefulness and monetary rewards on privacy concerns regarding the likelihood of use for
mobile insurance services1.
Hereby, it should be noted that a single concept for mobile insurance not exists, as the term serves as
a container definition for a broad range of insurance applications based on mobile technologies.
Recent studies show us that privacy concerns are situation-specific, which implies that a single
assessment to mobile insurance related privacy concerns is rather difficult (Margulis, 2003; D. Solove,
2006). Therefore, this study will assess privacy concerns and mitigating relations per category of
mobile insurance applications.

1.4.

Research questions

In order to achieve aforementioned research objective this section provides the research questions of
this study. Derived from the problem statement and the objective of this research, the following main
research question (RQ) is proposed:
RQ

In what way can privacy concerns, affecting the likelihood of use mobile insurance services,
be mitigated by expected monetary benefits and perceived usefulness?

In order to answer the research question, multiple sub questions are composed, embodying both
theoretical as practical aspects of the study. All composed sub questions incorporate some practical
aspects. The theoretical aspect of this study is mainly reflected in the second sub question. The
composed sub questions (SQ) accompanied by a brief argumentation are provided below. Table 1.1
provides an overview of examined sub-questions per chapter.
Since privacy concerns cannot be assessed for mobile insurance in general (section 1.3), a subdivision
of mobile insurance is required. By identifying and categorizing existing mobile insurance services on
its functional characteristics, privacy concerns could be assessed per individual category. Therefore,
sub question 1 is formulated as follows:
SQ1

1

Which categories of consumer insurance services based on mobile technologies can be
identified?

Although the insurance industry considers insurance undertakings/policies as a product and customer
assistance as a service, science tells us that both meet the characteristics of a service (Vargo & Lusch, 2008). For
a consistent terminology, insurance services are further defined in this study as a catchall for both insurance
undertakings/polices and customer assistance.
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|SEPAM Master Thesis |December 2014 | S.A.J.P Derikx|

Central to this study is the concept of privacy. Literature on privacy provides definitions, measures,
subdivisions and relations to assess the mitigating effect on privacy concerns related to mobile
insurance. In order to incorporate relevant privacy literature in this study, sub question 2 is formulated
as follows:

SQ2

What is privacy and how is it related to perceived usefulness and monetary benefits?

Since the term ‘mobile insurance’ serves as a container definition for a broad range of insurance
services based on mobile technologies, and privacy concerns are situation-specific (Section 1.3), privacy
(relations) need to be assessed per individual mobile insurance category. However, this study is bound
to time constraints, which excludes extensive individual assessments per mobile insurance category.
Nevertheless, individual assessments could be relevant for insurance companies in the composition of
future product portfolios. Therefore, an explorative assessment is conducted in which the mitigating
relations of privacy concerns are explored for each category of mobile insurance (SQ3). Hereby, it
should be explicitly noted that the ambition level of this assessment is purely explorative and outcomes
have to be interpret with care.
SQ3

To what extent are privacy concerns, perceived usefulness and expected monetary benefits
affecting the likelihood of use of mobile insurance services?

Elevated privacy concerns are inevitable with the use of certain mobile technologies (Chorppath &
Alpcan, 2013). Aforementioned literature by Hann, Hui, Lee & Png (2007) states that these concerns
can be compensated by means of monetary benefits or perceived usefulness. Although the insurance
provider could influence the customer perception on usefulness by both service characteristics as
market positioning (marketing) (Davis, 1989), monetary compensation is relatively easier
accomplished. Therefore, an extensive assessment will be conducted towards the compensating effect
of “monetary benefits” on “privacy concerns” for one mobile insurance service (SQ4). Insight in how
much monetary benefits are required to buy off inevitable privacy concerns, offers opportunities for
CSMS providers to stimulate adoption through the adaption of their revenue model.
SQ4

How much monetary benefits are required to buy off mobile insurance related privacy

concerns? 2

Chapter
1
2
3
4
5
6

2

Table 1.1: Overview of examined sub-questions per chapter
Title
Research question
Research introduction
Domain Description
SQ1
Relevant Theories and Concepts
SQ2
Research design
Survey results
SQ3, SQ4
Discussion and conclusion
RQ

Due to time constraints SQ4 will only be assessed for one mobile insurance service.
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Overcoming Privacy Concerns in the Consumer Use of Insurance Services based on Mobile Technologies

1.5.

Research scope

This section describes considerations regarding the scope of this study. By setting boundaries in line
with the research objective, the section defines the research space. A schematic overview of relevant
scope choices is provided in Table 1.2.
To remain competitive insurers require a constant focus on business innovation (Yodokawa, 2007).
Driven by a ‘mobilizing’ environment, opportunities for innovation in the insurance sector arise
(Deloitte, 2014b). Mobile technologies could incentivize insurance innovation in multiple ways.
However, current mobile financial services mainly function as an extension of existing online
platforms, reaping the benefits of mobile technologies as portability, individuality and connectivity,
but disregarding the potential of context sensitivity. Therefore this study focusses on context sensitive
mobile insurance services (CSMS).
Regarding consumer insurance products basically two types can be distinguished; life and non- life
insurances. According to Dutch law, conditions for disbursement of life insurances are directly related
to human loss. Non-life insurance, is a catchall phrase to describe almost any insurance other than life
coverage, including property, casualty and health policies. Life insurances are usually contracted in
smaller quantities but for longer, often life-time periods while non-life insurances can be considered
as fast moving, short term products. Non-life insurance is characterized by a higher claim frequency,
higher reciprocity and more intensive customer interaction (Deloitte, 2014a), offering more
possibilities for the involvement of mobile insurance services. Hence this study will focus on mobile
product opportunities for non-life insurance.
Traditionally non-life insurances were mainly distributed by intermediaries, but with the broad
introduction of the internet and recent legal adjustments, as the ban on intermediary commissions
and the separation of banking and insurance activities, direct sales (over the internet) became the
most used distribution channel (Deloitte, 2014b). Although online insurance agents are present (e.g.
Independer & Hoyhoy), they mainly function as a selling partner. Insurance services are still directly

delivered to the customer. Regarding mobile insurance, this study will therefore focus on consumer
services offered by the insurer to the consumer, disregarding mobile services for intermediaries (B-C).
Previous research shows us that efficiency improvements can be achieved with the use of mobile
technologies for insurance purposes (Berdak & Carney, 2014). Less labor intensive enclosure and claim
procedures, faster customer contact and easier information gathering methods can result in gains for
both insurance companies as customers (Baquero Forero, 2013; Carney, 2014). For example; Achmea
recently announced that they expect that with the introduction of those self-service (mobile)
platforms, 4,000 employees, almost a fifth of all staff, would be made redundant (Achmea, 2013).
However, mobile insurance services could have major impact on insurer’s business model, this study
focuses on consumer attitude on functionalities of mobile insurance.
Table 1.2: Research scope

Within scope
Insurance industry
CSMS
Non-life Insurance
B-C
Consumer functionalities
Application for Dutch market

6

Out of scope
Other (non) financial sectors
Other mobile/insurance services
Life insurance
B-B, C-C
Business efficiency gains
Application for international market

|SEPAM Master Thesis |December 2014 | S.A.J.P Derikx|

1.6.

Research approach

In order to answer formulated research questions, this section provides a structured approach
substantiated by multiple research methods. A visual overview of described research approach and
research methods is presented in Figure 1.1.
For a full comprehension of the problem area, this study will commence with a context exploration.
An introduction in relevant insurance processes and mobile insurance technologies is provided. This
information is mainly gathered by means of a desk research complemented by expert interviews,
where necessary.
Subsequently, an explorative identification and categorization of global practices regarding
mobile insurance services, is carried out. Mobile services in current, national and foreign, insurance
markets will serve as an input. Based on market research publications (e.g. Forrester & Gartner),
scientific literature and expert validation (workshops), an overview of global mobile insurance
applications is composed (SQ1). These global MI application are categorized on the basis of their
properties.
Thereafter, relevant privacy literature will be analyzed (SQ2). Privacy is plural and within literature a
single account of privacy has yet to emerge. Thereby multiple types of privacy could be distinguished
and privacy could be harmed in various ways. These types of privacy (harms) serve as a guideline for
further research steps. Aforementioned privacy literature is also used to identify the types of privacy
that is harmed by each category of mobile insurance applications. In addition scientific literature will
be used as a foundation for the research hypotheses. Hypotheses on the mitigating effect of
‘usefulness’ and ‘monetary rewards’ for ‘privacy concerns’ regarding the ‘likelihood of use’ mobile
insurance products and services, will be composed in this section.
Since the answer to sub question 3 and 4 reflects the attitude of consumers regarding mobile
insurance, a consumer survey is subsequently conducted to answer them. Hereby, two consumer

surveys are conducted to answer sub question 3 and 4 individually; an explorative and a conjoint
survey3. A (consumer) survey is a helpful data-collection method to reveal consumer attitudes and
preferences regarding mobile insurance. It offers the opportunity for numerous questions and a broad
range of data can be collected. In line with the aim of the research questions, a survey is the ideal
method to get insight in the preference and attitude of the population by conducting a relative small
experiment.
By means of an explorative survey consumer’s attitude on mobile insurance is assessed.
Consumer attitude on mobile insurance regarding ‘usefulness’, ‘monetary rewards’, ‘privacy concerns’
and the ‘likelihood of use’ provides insight in mitigating factors for privacy concerns (SQ3). Multiple
regression is used to assess the effect of mitigating factors on privacy concerns for all categories of
mobile insurance service. Multiple regression is an appropriate method of analyses when a single
metric dependent variable is presumed to be predicted by two or more metric independent variables.
In order to assess how much monetary benefits are required to buy off mobile insurance
related privacy concerns, a conjoint survey is conducted (SQ4). Conjoint analysis is a statistical
approach, often used in market research to determine customer preferences and product pricing
points (Green, Krieger, & Wind, 2001; Henscher, Rose, & Greene, 2005; Louviere, Hensher, & Swait,
2000). “It is a utilitarian methodology in which respondents value different alternatives or profiles by
making implicit trade-offs, from which their preferences are obtained” (Green et al., 2001). Due to
time constraints this research only assesses the monetary value for one individual MI practice. Further
elaboration on the research methodology can be found in chapter 4.
3

Further argumentation on the two-folded survey design can be found at section 1.4.

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Overcoming Privacy Concerns in the Consumer Use of Insurance Services based on Mobile Technologies

Eventually, conclusion will be drawn, outcomes will be discussed and both theoretical as practical

implications will be discussed.
1. Context exploration insurance & mobile

2. Identification of categories
of insurance applications
based on mobile
technologies
SQ1

3. Literature study to types
of privacy and adoption
factors for mobile insurance
services
SQ2

4. Survey mobile insurance applications with consumers

5a. Explorative analysis to
the likelihood to use of
mobile insurance
SQ3

5b. Conjunct analysis to the
value of privacy regarding
one mobile insurance service
SQ4

7. Discussion and conclusion
RQ

Figure 1.1: Research approach

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|SEPAM Master Thesis |December 2014 | S.A.J.P Derikx|

1.7.

Report structure

This section provides the structure of this report, as presented in Figure 1.2. Chapter two describes the relevant domain for this study; it gives some context
information on the insurance industry, provides definition for mobile insurance and identifies and categorizes mobile insurance service. Chapter three will
discuss the relevant theories and concept on privacy. In addition a conceptual model is developed and hypotheses are drawn. Subsequently, chapter four is
used to describe the research designs for the surveys and in chapter five the results are given. Finally, the discussion, conclusions, recommendations,
implications and reflection is provided in chapter six.

Chapter 1:
Research introduction

Chapter 2:
Domain description
Mobile insurance practices
(SQ1)

Chapter 3:
Relevant Theories and
Concepts
(SQ 2)

Chapter 4:
Research design

Desk Research
Literature Research
Interviews

Survey
Data analysis

Explorative Survey
Conjoint Survey

Hypothesis testing
Survey results

Methods:

Desk Research
Literature Research
Interviews

Desk Research
Literature Research
Interviews

Desk Research
Literature Research

Product of

chapter:

Research questions
Demarcation
Research Methods

Identification
Mobile Insurance services

Definition of privacy
Types of privacy
Hypotheses

Chapter 5:
Survey results
(SQ3, SQ4)

Chapter 6:
Practical and theoretical
implications,
Conclusions,
recommendations
and reflection
(RQ)

Conclusion, discussion and
recommendations

Figure 1.2: Report outline

9