working paper. are people willing to share their …...are people willing to share their personal...

Are People Willing to Share Their Personal Data? Insights from Two Survey Studies

Prof. Dr. Renate Schubert, Prof. Dr. Petros Koumoutsakos, Dr. Georgios Arampatzis, Yifei Wang, Flavia Hug, Ioana Marinica

July 5, 2018

Working Paper No. 1

Abstract Privacy has become a central issue for the digital society. The diversity and magnitude of our interactions

with computers and the advances in artificial intelligence have created new interfaces between people

and machines that touch upon every aspect of our life. Access to our personal information has been

automated and, in several cases, utilised in ways that we could have never imagined. As we are slowly

becoming aware of this situation, our perspectives on what can be shared on the internet are

continuously evolving. In this study we explore people's willingness to disclose personal information by

designing two surveys on Amazon Mechanical Turk (MTurk). The first survey was designed to examine whether willingness to share information is dependent on

the person it is shared with or on the type of information being shared. Additionally, we inquired whether

this willingness changed when the shared information was that of a family member.

In the second survey we examined the perception of supermarket customers regarding the

information content of their shopping history. In particular, we were interested in investigating how

personalised advertisements, offers and discounts would influence the customers' willingness to share

consumption data.

The present results indicate that the participants in our study are more willing to share personal information with people with whom they have a closer relationship, like their families and friends. A more

interesting result of our study is that, while the participants are concerned about information security and

privacy protection, they are not willing to pay extra to protect their data. Moreover, personalised offers

and discounts can increase their willingness to give out personal information.

Future investigations will further explore the shifting landscape between personal information and its

availability and exploitation through information technology. We will investigate how people treat their

own private information compared to information of others. With the increasing risk of exposing private

information, are people aware of the danger and actively searching for ways to protect their privacy? Is it possible to quantify and predict the new boundaries of information exchange between people through

information technology? What are the ways for people to prevent companies from sharing their personal

information without their knowledge, either intentionally or unintentionally? Is the current law sufficient

to handle privacy in our digital society?

The present study serves as a first step in our research on privacy in the information age. We expect

that this issue of privacy will become central to future debates, to the extent that information technology

becomes central to our lives. It will also become central to what defines an individual in our digital society.

2

ABSTRACT ....................................................................................................................... 1 INTRODUCTION ....................................................................................................... 3 OUR SURVEYS ........................................................................................................ 9

OVERVIEW ........................................................................................................... 9 SURVEY ON GENERAL WILLINGNESS TO SHARE .................................................... 10

2.2.1. Own Private Information ............................................................................. 10 2.2.2. Private Information of a Family Member ..................................................... 10 2.2.3. Information Shared with Websites .............................................................. 10 2.2.4. Privacy Protection Questions ...................................................................... 11

SURVEY ON WILLINGNESS TO SHARE IN SUPERMARKET CONTEXT ......................... 11 2.3.1. Purchase History for Personalised Benefits ................................................ 11 2.3.2. Willingness to Share Purchase History ....................................................... 11 2.3.3. How Informative is your Purchase History .................................................. 12 2.3.4. Buying Behaviour ....................................................................................... 12

QUESTIONS INCLUDED IN BOTH SURVEYS ............................................................. 12 2.4.1. Socio-Demographic Questions ................................................................... 12 2.4.2. Open Questions .......................................................................................... 12

PARTICIPANTS .................................................................................................... 13 RESULTS ............................................................................................................... 15

SOCIO-DEMOGRAPHIC QUESTIONS ....................................................................... 15 SENSITIVITY OF PERSONAL INFORMATION ............................................................. 15 SENSITIVITY OF FAMILY MEMBER'S PERSONAL INFORMATION .................................. 16 PEOPLE'S ATTITUDE TOWARDS INTERNET PRIVACY ................................................ 16 PRIVACY PROTECTION QUESTIONS ....................................................................... 19 PURCHASE HISTORY FOR PERSONALISED BENEFITS .............................................. 19 IMPORTANCE TO KEEP PURCHASE HISTORY PRIVATE, BY CATEGORY....................... 21 HOW INFORMATIVE THE PURCHASE HISTORY CAN BE ............................................. 22 BUYING BEHAVIOUR ............................................................................................ 22 OPEN QUESTIONS ............................................................................................... 24

CONCLUSION AND FUTURE WORK .................................................................... 25 BIBLIOGRAPHY ............................................................................................................. 26 APPENDIX ...................................................................................................................... 27

A. SURVEY ON GENERAL WILLINGNESS TO SHARE ....................................................... 27 B. SURVEY IN SUPERMARKET CONTEXT ...................................................................... 35

3

Introduction Privacy, as well as methods or laws to protect it, have been the subject of numerous studies for

centuries. As early as 1361 privacy invasion in form of trespassing was considered a crime, when

eavesdroppers in England were arrested under the Justice and Peace Act [1]. More recent reports define

privacy invasions in the following contexts: trespassing, correspondence, the press, instantaneous photography, wiretapping, psychological testing and lie detectors [2].

The emergence of new technologies has repeatedly forced us to rethink the laws protecting privacy.

For example, the introduction of instantaneous photography created a new dimension of privacy

invasion. A prominent case is Roberson v. Rochester Folding Box Co., in which a local milling company

used a photo of a girl to promote their product [3]. Despite the increasing demand for the recognition of

the Right of Privacy, the ensuing lawsuit was denied. The court argued that this would result not only in

a vast amount of litigation but in litigation bordering upon the absurd [3]. Disappointed by the court's

decision, a comment in the Yale Law Journal emphasizes that property must include not only physical objects but also the intangible [4]. It took another three years for a court to decide that the unauthorized

use of an individual's picture was indeed a violation of personal privacy [5]. In the latter case, Mr

Pavesich's picture was used by a life insurance company for advertisement. With this decision, Georgia

became one of the first states to recognize the Right of Privacy [6].

Today, the Oxford Dictionary defines privacy as a state in which one is not observed or disturbed by

other people [7]. This definition, however, is now challenged by the increased usage of artificial

intelligence technologies. In addition to analog observations by people, we are already digitally observed

and disturbed in an automated fashion through computers. Many modern technologies bring convenience, but there are some obvious problems that arise for

example from video surveillance, biometric identification, genetic data, and the Global Positioning

System (GPS). While many people are worried about privacy invasions from these technologies, we are

continuously and heavily relying on machines and software to deposit our data at an ever-increasing

pace. Our information is processed, analysed and acted upon (e.g. to increase the shopping experience

for customers or to plan a supply chain more efficiently), yet today not all of our data is used. In many

cases the data is collected as a by-product and stored without being used. One reason for this may be that there is no technical or economical incentive not to collect data; data is easy to collect and cheap

to store. In Figure 1 we show how the average storage space prices dropped dramatically for both Hard

Disk Drives and for Solid-State-Drive in the last 15 years [8].

4

Figure 1: Average Hard Disk Drives (HDD) and Solid-State-Drive (SSD) prices in USD per gigabyte (Source: [8]).

There are only few estimates about how much of the collected data is actually used. One estimate

is that between 60% and 73% of all data collected remains unused for analytics [9]. Routinely capturing

data, for example about supermarket customers or products, leads to huge volumes of historical data

[10]. This historical data might be very valuable for a company in the future by anticipated new technologies and thus many institutions, firms and private people choose to constantly collect it. This

causes threats to privacy, not only due to the sensitivity of the data, but also due to the fact that more

information can be extracted from aggregated data sets compared to looking at single observations.

This becomes even more imminent with multinational corporations. While multinational corporations

are often criticized for to their tendencies for monopolistic power in pricing and workers' rights, their

potential harm to privacy must not be forgotten. While individuals may think they only provide limited

private information to a certain supermarket by using their credit card or a loyalty card, it is unclear how

this information is used and shared within a big corporation. Combined with an easily identifiable personal piece of information like a cell phone number or an email-address, this information can also be

of interest to other companies. They could use it to enhance their existing customer profiles or to gain

additional insights on people outside their customer database. The data can either be sold at almost no

additional production costs or it can be aggregated in mergers or acquisitions of companies.

Even though much of this data might be metadata, or anonymised in some form, a question that

needs to be asked is what exactly private data or personal information is. Gandy [11] claims that

"Personal information is produced, reproduced, and shared continually as a necessary and unavoidable

by-product of human existence." Personal information, or simply information in itself, has some special characteristics: it is a non-contentious good that can easily be shared and reproduced at very low costs;

i.e. while it is consumed by one entity, it does not limit its consumption by another party. While

information can be given away and exchanged easily, it is still available to the producer of the information.

Personal information can be produced as a by-product generated in interactions between individuals or

between individuals and organizations. [11]

The fact that private information is constantly produced raises the question if we should care what

happens with this information. For example: should a customer care whether a supermarket registers that they like to buy ice-cream from a specific brand on Fridays between 7 and 8 p.m.? In this example

there are different possibilities for the supermarket to use this information. Assuming that this customer

5

is not very price-sensitive, a store could easily raise the price of this specific brand of ice-cream, between

7 and 8 p.m. on Friday evenings. Alternatively, if this customer is very price-sensitive they could do the

opposite and lower the price of this specific brand to potentially increase the total amount spent during

that particular shopping period. While this example is hypothetical, there is evidence that some form of

price discrimination is in fact happening online. In 2015, Coop was using shopping behaviour and past

shopping experiences to prompt customers with discounts when using their online shop "Coop at home" [12]. An in-store experiment, conducted by Heilman et al. [13], showed that unexpected receipts of

coupons increased the value of the shopping basket in the concerned shopping period. In particular they

found that a surprise coupon worth 1 USD led to surprise purchases 7.68 USD higher than those from

the control group. So far, it seems as if this potential is not fully exploited in practice. However, "the

combination of big data and differential pricing does raise serious concerns", reads a report from the

Obama Administration. "Big data may facilitate discrimination against protected groups, and when prices

are not transparent, differential pricing could be conducive to fraud or scams that take advantage of

unwary consumers" [14]. In 2002 it was already clear to retailers how valuable private information can be. The prominent case

of a teenage girl being pregnant and Target sending her maternity related coupons before her father

knew about the pregnancy illustrates interesting features of purchase data analysis. The company

specifically tried to identify women in their second trimester. One of the main reasons why Target was

particularly interested in pregnant women is that shopping habits are inherent and they're incredibly

difficult to change. There are however a few moments in each person's life where these habits change:

when they are going through a major life event, such as moving to a different city or starting a new job. One of these moments is a pregnancy. Now the brand loyalties of the parents-to-be are up for grabs.

"As soon as we get them buying diapers from us, they’re going to start buying everything else too. If

you’re rushing through the store, looking for bottles, and you pass orange juice, you’ll grab a carton. Oh,

and there’s that new DVD I want. Soon, you’ll be buying cereal and paper towels from us, and keep

coming back.", explains a statistician at Target. In the example of pregnant women, they realized that

women in their second trimester bought more unscented lotion, soap and supplements like magnesium

or calcium. Using this information, the statisticians at Target assigned each woman a pregnancy

prediction score which enabled them to send coupons to women having a high probability of begin pregnant. These coupons specifically pointed at their upcoming needs as a parent. [15]

So far we have looked at one's own personal information. However, as mentioned above, private

information can also be a by-product of interactions between individuals. As we socialise and interact

with others we constantly share information with them as they share information with us. As an example,

our phone book can contain anything from a first name, surname, and cell-phone number, up to work

phone, birth date, private and work e-mail address and the contact's home address. Even though the

contents of a phone book are not our own personal information, do we still treat it with the same care? A recent paper received a lot of attention when it reported that college students were willing to disclose

email addresses of three of their friends for a free pizza [16].

Private information can be very valuable. Consumers are constantly faced with the hidden trade-off

between disclosing private information to get customized services and offers and protecting their privacy.

At the same time, several political forces seek to help the consumer to regain the perceived loss of

6

control over their privacy. However, there is evidence that even though people say they want to limit

disclosure of personal information, they still provide personal information when in a disclosure situation.

This phenomenon is known as the Privacy Paradox [17].

This discrepancy between the stated opinion and actions taken is very hard to measure because

people need to first report their intentions and then actually disclose the information. This tendency can

vary significantly between individuals so it is important to measure the Privacy Paradox in a within-subject research design. The two surveys we conducted can be seen as a pilot for measuring people's

willingness to disclose personal information.

To explore the intentions of disclosing personal information, we designed two surveys on Amazon

Mechanical Turk (MTurk) a platform where tasks are being published and participants are rewarded

when they finish a given task. A total of 400 subjects from Europe participated, 200 subjects per survey.

The first survey was designed to identify whether subjects' willingness to share information is

dependent on the type of information and the people they were asked to share the information with. We

assumed that subjects' willingness to share information with people would correlate with how close those people are to them. We distinguished between immediate family members (and very close friends or

partners), friends, colleagues or supervisors and the broader public. We also expected subjects to be

more reluctant to share information with increasing degrees of sensitivity of the information. We chose

the following three personal information with varying sensitivity: medical record, high school grades and

last year's tax return. At the same time, we were curious to see if subjects would treat information

differently, depending on whom it belonged to; i.e. would they private information of a family member

just like they share their own? This led to the following hypotheses:

Hypothesis 1: People are more willing to share personal information with those they have a closer

relationship with.

Hypothesis 2: People are more reluctant to share personal information with increasing sensitivity.

Hypothesis 3: People are hesitant to share personal information of their family members.

Motivated by the fact that nowadays people do not share their information just with people around

them, but also online, we dedicated one part of the questionnaire to explore people's behaviour online.

We asked how often people accept terms and conditions from websites and, particularly, how often they

actually read through those terms and conditions. We further explored how concerned participants are

about websites giving away their personal information to different groups of people. On top of that, we

asked the participants if they would be willing to provide an online store or a social media website with

different types of information. And finally, participants were asked if there is any data they want to delete

on the Internet. This is summarized in the following hypotheses:

Hypothesis 4: People accept websites' terms and conditions without fully reading the content.

Hypothesis 5: People are concerned about websites sharing their personal information with third

parties.

7

Hypothesis 6: People distinguish between online stores and social media websites when providing

their personal information.

Hypothesis 7: People want to delete information about them on the Internet.

Finally, to get a glimpse of people's thoughts about privacy and how they might share their

information, we inquired how strongly they feel about taking actions to protect their privacy. We asked

two questions to measure that willingness in terms of whether they would pay a reasonable price to protect their data.

Hypothesis 8: People are willing to pay a reasonable extra price to increase the protection of their

data.

In the second survey, we inquire whether customers have a clear idea of how much information their shopping history contains. For example, we asked subjects whether they believed that they could be

classified into a certain group of people based on their shopping history. From this, we formed the

following hypotheses:

Hypothesis 9: People underestimate the sensitivity of the information their shopping history

contains.

Hypothesis 10: Personalised offers and discounts influence people's willingness to give out their

personal information.

Both surveys lead to a number of observations and insights on people and their relationship with

their privacy. In general, and as expected, people are more willing to share private information with their

family members and friends, while they are more hesitant to share their information with colleagues and

the public. The same is true for a family member's personal information. People were more willing to

share this information with a friend than with the broader public. However, in line with our expectations,

their willingness to share decreases with increasing sensitivity of the information. While people are on

average still willing to share their high school grades, they are on average less willing to share their last

year's tax return or their medical record. The majority of the participants accepts online terms and conditions very often. However, only 2% actually read thoroughly through the text, while 22% scan

through it quickly. People are most concerned if their online information is leaked to the public. At the

same time, their concerns about sharing with colleagues, friends, third parties and even an insecure

server are approximately the same. When comparing people's willingness to share private information

to websites and online stores, they appear to care the least about exposing their gender online, but they

do not want to share their medical record at all. Participants have a significantly higher willingness to

provide their address to an online store compared to social media. As for other types of information,

people's willingness does not vary much when sharing with either an online store or a social media website. These findings confirm Hypotheses 1-6. When it comes to information people already provided

online, only 3% of people want to delete all of it, 14% want to delete most of it, 65% of people want to

delete some and just 18% have nothing they want to delete. People generally show concerns about

information security and privacy protection, but only 8% are very willing and 24% are somewhat willing

to pay extra to protect their data, thus leading us to reject Hypotheses 7 & 8. While people are

8

concerned about their privacy, they show a high agreement to sharing their personal information to

receive a personalised service. 76% stated they would probably or definitively be willing to share their

private information to receive personalised offers and discounts. These findings support Hypotheses 9 & 10.

9

Our Surveys

Overview We designed two surveys on Amazon Mechanical Turk (MTurk) to explore people's intentions to

disclose personal information. The MTurk marketplace lets individuals ("Workers") complete a selection

of tasks whenever it's most convenient for them. They can work on Human Intelligence Task (HIT) and

collect a reward for completion. Only when a Requester approves a Worker's task completion will they

receive the corresponding payment [18].

Since each Worker has a HIT rate that captures their acceptance rate, and Requesters can assign

Workers to their Human Intelligence Tasks conditional on this HIT rate, Workers are incentivized to

deliver acceptable work. Relative to the general internet population, males are over-represented on MTurk. People with no

College degrees are under-represented, while people who completed some College or Graduate School

work are over-represented. Those who successfully finished College are represented similarly to the

general internet population. [19]

While we were specifically interested in results from Europe, 63% of MTurk Workers are from the

United States, 22.4% are from India, followed by 2.1% located in the United Kingdom, 1.4% in Canada

and 1.1% in Italy. Nevertheless, we were able to select workers located in the 20 countries with the

biggest population in Europe1 [20]. We collected answers from 200 participants for each survey, so 400 in total. On average, people

spent 487 seconds on the first survey, with a minimum of 111 seconds and a maximum of 2'807 seconds.

The second survey consisted of fewer questions, therefore people spent only 383 seconds on average,

with the fastest completion in 85 seconds and the longest in 3'557 seconds.

The first survey contained 51 questions, and the second survey 35 questions. For easier readability,

the questions were divided in different blocks. In each questionnaire there was a block of socio-

demographic and personality related questions. The participants could pick from a set of predefined

answers unless noted otherwise. In the first survey, there was a block of questions about people's attitude towards sharing different

kinds of information with different groups of people. Another block of questions concerned the question

how, instead of one's own, a family member's information is shared. There was also one block dedicated

to Internet privacy and which types of information are considered more sensitive to sharing online.

The second survey is focused particularly on supermarket customers' privacy. There was one block

about the factors affecting people's willingness to hand out their data and another block about the

categories of information which people are least willing to share. Besides that, there was one block of questions about people's beliefs that they can be classified correctly into different groups of people, just

by looking at their data. Furthermore, we asked several questions related to participants' shopping

1 Countries present in the survey sorted by population: Russia (144 Million), Germany, Turkey, France, United

Kingdom, Italy, Spain, Ukraine, Poland, Romania, Netherlands, Belgium, Greece, Czech Republic, Portugal, Sweden, Hungary, Belarus, Austria, Switzerland, Bulgaria, Serbia, Denmark, Finland, Slovakia, Norway, Ireland, Croatia, Bosnia and Herzegovina, Moldova (3.5 Million).

10

behaviour in order to highlight potential associations with the background information provided. This last

block consisted of open questions in which we asked participants to provide their own answers.

Survey on General Willingness to Share In this first survey we wanted to investigate two dimensions that could influence people's willingness

to share personal information.

One dimension we were interested in is the influence the sensitivity of the information they are asked

to share had on the disposition to provide the data.

Another dimension we wanted to investigate was the extent of the sharing of information. We

examined if people's attitudes towards sharing changed depending on who they were asked to share

the information with.

We were also interested to know if people's willingness to share more and less sensitive information differed between sharing it with an online store and sharing it on a social media website.

2.2.1. Own Private Information The goal of this block is devoted to finding out the sensitivity of different types of personal information

when sharing with different groups of people. Specifically, we asked about people's willingness to share

high school grades, last year's tax return and medical record with either a family member, friend,

colleague or the public. We provided the following 5 possibilities: definitely, very probably, probably,

probably not and definitely not. Hypothesis 2 suggests that people would be more willing to share their

high school grades compared to their last year's tax return, assuming that their high school grades are

less sensitive. Hypothesis 1 predicts that subjects are probably more willing to share personal information with their friends compared to the public.

2.2.2. Private Information of a Family Member After the questions about people's willingness to share their own private information with different

groups of people, we investigated people's attitude about sharing their family members'. Similarly, we

investigated four types of information: physical health, psychological health, current location and salary

when sharing with three different groups of people: friend, colleague and public. Note that the answering

choices for this block were identical to the previous one. Hypothesis 3 proposes that people are hesitant

to share personal information of their family members.

2.2.3. Information Shared with Websites Nowadays people do not share their information just with people around them, but also online. We

dedicated one block of questions to explore how the willingness to share depends on whether sharing

happens online or offline.

To investigate Hypothesis 4, we first asked how often people accept terms and conditions from

websites and, particularly, how often they actually read through those terms and conditions. Then we

asked participants about their concern that websites give away their personal information to different

groups of people, e.g. the public, colleagues, friends, family, insecure servers and other third parties.

Hypothesis 5 predicts a high level of concern, particularly towards other online entities. To address Hypothesis 6, we asked the participants if they would be willing to provide an online store or a social

11

media website with different types of information, such as medical records, address, location, education

and gender. Lastly, we asked our participants if there is any data they want to delete on the Internet.

This was to measure how strongly they felt about protecting their online privacy and therefore, how

strongly their intentions are supported by Hypothesis 7.

2.2.4. Privacy Protection Questions In addition to getting an insight into people's thinking about privacy and how they might share their

information, we were also interested to know how strongly they feel about taking actions to protect their privacy. We asked different questions to measure that willingness in terms of whether they would pay a

reasonable price to protect their data. Per Hypothesis 8, it is expected that people would show at least

some willingness to pay to limit data sharing. We gave them 6 answering possibilities: very willing,

somewhat willing, probably, not very willing and not willing at all.

Survey on Willingness to Share in Supermarket Context

In this second survey we were interested in the extend to which people are willing to disclose their

shopping history. Some questions specifically asked their willingness to share different aspects of their

purchase history, for example cigarette purchase versus clothing purchase history.

Other questions investigated if people realized how much data they produced while shopping and if they comprehend that this data contains answers to questions the retailer didn't need to ask.

Another part of the survey investigated which factors about the company might have an influence on

people's willingness to share information. An example would be if people put more value on a company

having clear privacy policies versus the general reputation of a company.

Also, we asked the participants about their specific shopping behaviour, for example if they would

buy a product only because it's on sale or if they tend to buy cheaper versions of a product. As this could

be highly correlated with a person's social and demographic factors, we asked all participants in both

surveys for some information about their person.

2.3.1. Purchase History for Personalised Benefits Besides the influence of different types of information and sharing with different groups of people.

We were also interested in what other factors might affect people's willingness to share their information,

this time with regard to their purchasing behaviour? First, we asked if people would be willing to share

their information in order to get personalised advertisement or personalised offers and discounts. The

possible answers were: definitely, very probably, probably, probably not, definitely not. Then we offered

them a list with 6 different factors and asked which one of these made them willing and unwilling to

provide personal information. The list for example included "The company's privacy policy is clear".

2.3.2. Willingness to Share Purchase History In the specific case of supermarket privacy, we wanted to know how important it is for people to keep

5 different categories of purchases private, including cigarettes, meat, clothing, junk food and alcohol.

Then we also investigated how important it is for people to keep 7 types of personal information private;

12

including religion, pregnancy, income, illness, age, gender and sex orientation. Participants could

choose from "crucial", "very important", "worth considering", "not very important" and "irrelevant".

2.3.3. How Informative is your Purchase History As we introduced in Chapter 1, supermarket purchase history can expose a lot of personal

information, for example, whether a woman is pregnant or not. Yet the question remains, whether people

realize how informative their purchase history is. We specifically asked them if they believed that a

supermarket can correctly classify them into a certain group of people, for example housewife or student versus alcoholic or depressive, just by looking at their purchase history (Hypothesis 9). The answers

could be "definitely", "very probably", "probably", "probably not" and "definitely not".

2.3.4. Buying Behaviour In addition to socio-demographic questions, we asked four buying behaviour questions to showcase

how supermarkets might exploit costumer information from their purchase history. The questions

included if participants prefer supermarkets' own brand or other brands, if they tend to buy cheaper

versions of products, if they choose a specific brand, and lastly if they would buy a product only because

it's on sale. Additionally, we were interested if personalised offers and discounts, as well as personalised

advertisements would increase people's willingness to disclose personal information (Hypothesis 10).

Questions included in both surveys This section looks at types of questions that were asked in both surveys. It contains some socio-

demographic questions, as well as, personality related questions. It also includes an overview of the

open questions, that the participants had to answer.

2.4.1. Socio-Demographic Questions We asked participants to answer some questions about their background, including age, gender,

education, income and their personality, in order to find out which factor might affect people's attitude

towards privacy.

For age, there were 6 options: 18-24, 25-34, 35-44, 45-54, 55-64, 65 and older. For income, there

were 6 options: below 15'000 Euros, 15'000-29'900, 30'000-44'900, 60'000-74'900, 75'000 and above.

For gender, there were three options: female, male and other. For education, there were 5 options: high

school, admission to university or college, bachelor, master and PhD. In the personality questions we

asked participants how much they agreed with statements about themselves, such as "I see myself as

someone who is reserved" or "I see myself as someone who is generally trusting".

2.4.2. Open Questions Not limiting our questions to provided answers, we prepared open questions for our participants. We

had three open questions asking our participants to write down their own answers on how they feel

about privacy, what is privacy, and the fields in which it would worry them the most if private information

would be transferred to others.

13

Participants To better understand what kind of participants answered our survey and to be able to put the results

into perspective, each participant was asked to answer a series of socio-demographic questions. From Figure 2 it can be seen that in the first survey (green bars) over 96% of participants are younger than

45, and most participants are between 25 and 34 years old. The distribution is very similar when

comparing it to participant metrics in the second survey (blue bars).

Figure 2: Age distribution in the first survey (green) and second survey (blue).

Our survey participants deviate from the general internet population, similarly to the MTurk users;

males being over-represented (73%), females being under-represented (25%) and with very little people

answering with "other" as their gender (Figure 3 (a)). However, the second survey has a more even

distribution between males and females with 61% versus 38% (Figure 3 (b)).

(a) Gender distribution in the first survey. (b) Gender distribution in the second survey.

Figure 3: Gender distribution in each survey.

Lastly, we wanted to address the concern that only people with a low or part-time income participate

in MTurk surveys. Indeed, between 82% in the second survey and 84% of the participants in the first

survey earn less than 45'000 € per year. In Figure 4 we see this cut below 45'000€, especially denoted

14

in the first survey (green bars) compared to the second survey (blue bars). However, this observation

should be treated with caution as we don't know in which country the respective participant lives; an

income of 45'000 € has very different implications in Germany compared to Croatia. In future surveys

participants should be asked their country of residence. This additional information allows to categorize

people reliably into country specific income groups, thus permitting to test if indeed only people with a

low or part-time income participate in MTurk surveys. Additionally, this information also enables to test a correlation between people's attitudes towards privacy and their income. Based on this reasoning the

two following hypotheses should be subject to future research:

Hypothesis a: People with a higher income are more concerned about privacy.

Hypothesis b: People with a higher income are more willing to pay extra for their privacy.

Figure 4: Income distribution in the first survey (green) and second survey (blue).

15

Results Selected, informative results from the surveys are visually presented in this chapter. Underlying

phenomena and patterns could be drawn out of the indicating graphs or tables, while the processed

results can also serve as a basis for further analysis. Following the structure of previous chapters, we

will present the results from the two surveys sequentially.

Socio-demographic questions This block is aimed at acquiring our participants' background information. Please refer to Chapter 2

for the detailed analysis about the distribution of background data. The variables' association with

participants' buying behaviour are presented in section 4.9. Other than the correlations in section 4.9,

we couldn't draw further definite conclusions about how participants' background information might be related to their opinions on privacy. This is possibly due to having limited and unbalanced background

information in the samples especially in the field of age, income and education. Only very few of our

participants are above 45 years old, have an income of over 60'000 €, or have an education background

above master's degree. Underling patterns could be found in the future in a study with a larger number

of participants and requiring more detailed background information.

Sensitivity of personal information Figure 5 shows people's willingness to share three different types of information, i.e. high school

grades, the previous year's tax return and medical record, with four different groups of people, i.e. family

members, friends, colleagues and the broader public. For the convenience of visualization and to

indicate people's willingness statistically, we assign each answer a value. For the answer "definitely" we

assign value 5 and for answers "very probably", "probably", "probably not", "definitely not", we assign

values 4, 3, 2, 1 respectively. So we can interpret the score (labelled on the figure) as people's

willingness to share a certain type of information to a certain group of people. In the figure, we show the average score of our 200 participants to demonstrate the difference in people's willingness to disclose

information towards different types of audiences.

Figure 5: Sensitivity of personal information.

16

In general, people are more willing to share their personal information with a family member than

with a friend or a colleague, or lastly with the public regardless of the type of information.

Results from this block show that, as hypothesized, people's willingness to share personal

information varies greatly depending on whom they share it with, and what type of information is shared.

This is consistent with the notion that people have more trust in those close to them.

Sensitivity of family member's personal information After investigating the sensitivity of personal information concerning the participants themselves, we

also inquired into the sensitivity of different types of family member's personal information when sharing

with different groups of people. Figure 6's scoring follows the same scale as that in Figure 5. It shows

people's willingness to share four different types of their family members' personal information, i.e. salary,

physical health, psychological health and current location to three different groups of people, i.e. friends, colleagues and the broader public.

Figure 6: Sensitivity of family member's personal information.

Similarly to the last section, people are also more willing to share their family members' personal

information with a friend than with a colleague or lastly with the public regardless of the type of

information. In addition, the gap between friends and public is very wide; the score of willingness to

share with friends is twice the score corresponding to willingness to share with the public. Also

interestingly, as hypothesized, people are equally concerned when it comes to sharing their family

members' information and when sharing their own personal information to friends, colleague and the public (see the score in Figure 6 and Figure 5).

People's attitude towards Internet privacy The findings regarding people's behaviour towards terms and conditions online are depicted in Figure

7 (a) and Figure 7 (b).

Figure 7 (a) shows how often people accept those terms and conditions, while Figure 7 (b) shows if people actually read those terms and conditions when they choose to accept or deny them.

17

(a) How often do people accept terms and conditions on websites.

(b) How often do people read terms and conditions on websites.

Figure 7: People's behaviour when encounter online terms and conditions.

Among our 200 participants, the majority (almost 90%) accepts online terms and conditions very often (42% always accept online terms and conditions and 47% very frequently accept them). However,

only 2% actually read thoroughly through the text, while 22% scan through it quickly.

Figure 8: How concerned people would be if websites gave a0way their personal information to different groups of people.

18

With such a high rate of acceptance and a low rate of reading the content, people appear to be

accepting the terms and conditions without being fully aware of their implication. Admittedly, many online

terms and conditions regarding privacy are long and cumbersome to read, but not reading the content

may lead to companies exploiting their power to collect personal information online, and may reduce the

Internet security for the users.

Figure 9: Willingness to share with online store and social media by category.

Figure 8 shows how concerned people would be if websites gave away their personal information to different groups of people, i.e. third parties, insecure servers, friends, family, colleagues and the broad

public. We assign scores of 5, 4, 3, 2, 1 to "extremely concerned", "very concerned", "concerned",

"somewhat concerned" and "not concerned" respectively. Figure 8 shows the average score of our 200

participants. Sharing with the public scores the highest, which indicates people are most concerned if

their online information is leaked to the public. However, what's interesting is that people's concerns

about sharing with colleagues, friends, third parties and even an insecure server are approximately the

same. We suspect that this might have to do with the fact that there are different types of information

which individuals might be equally concerned about sharing with each of the listed types of audiences.

Figure 10: How much personal information people want to delete online.

19

Figure 9 shows people's willingness to share different kinds of information (gender, education,

ethnicity, location, address and medical record) with online stores and social media. The length of the

bar indicates the number of positive votes among our 200 participants. The colour indicates to whom

they are sharing the information. Blue is sharing with online store, while orange is sharing with social

media.

While people care the least about exposing their gender online, they don't want to share their medical record at all. Participants have a significantly higher willingness to provide their address to an online

store compared to social media. This can simply be explained by the need to provide an address to

actually receive a shipment from an online store. As for other types of information, people's willingness

doesn't vary much when sharing with either an online store or a social media website.

When it comes to information people already provided online, 3% of people want to delete all of it,

14% want to delete most of it, 65% of people want to delete some and just 18% have nothing they want

to delete (see Figure 10).

Privacy protection questions People appear to be generally concerned about information security and privacy protection. However,

are people willing to pay to protect their private information from potential leakage or commercial

exploitation? As shown in Figure 11 (a), only 5% of people are very willing and 20% are somewhat

willing to pay a reasonable price to restrict companies to use or save personal data. The situation is

similar, when considering people's willingness to pay companies to apply data protection techniques, see Figure 11 (b).

(a) Willingness to pay a price to restrict companies to use or save your data.

(b) Willingness to pay companies to apply a data protection technique.

Figure 11: People's willingness to pay a reasonable price to protect their data.

Purchase history for personalised benefits In the more specific case of supermarkets, we analysed the factors which might affect people's

willingness to give out their data, and particularly their shopping history. Figure 12 (a) shows people's

willingness to share their purchase history to obtain personalised advertisement and Figure 12 (b) their

willingness to share in order to receive personalised offers and discounts.

20

(a) Agreement to share purchase history in order to get personalised advertisements.

(b) Agreement to share purchase history in order to receive personalised offers and discounts.

Figure 12: Agreement to share information for rewards.

To obtain personalised advertisement, 9% are definitely willing to provide their data and 15% state

it's very probable that they provide their data. However, in the expectation of getting a personalised

offers or discounts, 17% participants are definitely and 26% state it's very probable that they provide

their data. 17% of people are definitively willing to provide their data if they get a direct benefit or discount.

The most important factor that influences customer's willingness to give out their data is, if they feel like they personally benefit from providing their data.

The answers to the questions on factors which might affect people's willingness or unwillingness to

give out personal information also confirm that people could be persuaded to give out their data. Figure

13 shows the number of choices for each factor that affects people's willingness to provide their own

information.

Figure 13: Number of choices per factor that could affect people's willingness to provide personal information. Factor 1: I trust that my data would be secure. Factor 2: I would get benefit or special discount if I provide my data. Factor 3: This company's privacy policy is clear. Factor 4: I have received the service from this company for a long time. Factor 5: I can get personalised offers from this company if I provide my data. Factor 6: This company has a good reputation.

21

Importance to keep purchase history private, by category

In the survey, we further investigate people's willingness to share their purchase history for different

categories of products. Figure 14 shows people's willingness to keep their purchase history about

cigarettes, meat, clothing, junk food and alcohol private. We again assign scores of 5,4,3,2,1 to the

answers "crucial", "very important", "worth considering", "not very important" and "irrelevant"

respectively. We show the average score from all the participants for each category.

Figure 14: Importance to keep their purchase history private by categories.

People care most about keeping their alcohol and junk food purchases private, but do not care too

much about their clothing, meat and cigarette purchase history. A reason behind this might simply be

that people are afraid of letting others know about their bad habits. However, participants seem to

distinguish between cigarettes and alcohol. This might be caused by a bias in the sample since not all

participants smoke.

Figure 15: Importance to keep private of the personal information when shopping.

22

The different types of information people do not want to be eventually exposed by their purchase

history are represented in Figure 15.

Among all the information, income and illness are the most important types of information people

want to keep private. People care less about their religion, pregnancy, age, gender or sexual orientation

being exposed.

However, note that for the answers to the question related to pregnancy (Appendix B: Survey in Supermarket Context) we only consider the answers from female participants. This dramatically reduces

the number of answers by 52%.

How informative the purchase history can be On the one hand, people value their privacy, and for some information they only want to share with

their close family and friends. On the other hand, people sometimes freely give away information. That information can appear useless, but might indicate a lot about their personal information, when it is

combined with other pieces of information or is collected in large quantities. In the case of supermarkets,

are people aware how informative their purchase history might be? 24% of participants believe they can

be correctly classified into a certain profession judging only by their purchase history in supermarkets,

while a larger part of 39% believes they can be recognize correctly to have a mental or physical problem

judging only by their purchase history in supermarkets.

While some people are aware that their purchase history contains valuable information, the majority

of people still doubt how informative their purchase history really is. Research shows that supermarkets can use latent class mixture modelling to discover hidden customer segments on the basis of the

contents of their shopping baskets [21].

Buying behaviour We asked our participants if they tend to buy cheaper versions or specific brands. We then tried to

link their typical supermarket behaviour and their socio-demographic characteristics. Because of the limited number of participants, it would be hard for us to draw a definite conclusion

about types of purchasing behaviour associated with certain groups of people. However, we observed

that young people and males tend to buy cheaper versions of products as well as cheaper alternatives,

that are on sale.

23

(a) Tendency of buying cheaper version of products related to age.

(b) Tendency of buying products on sale related to age.

(c) Tendency of buying cheaper version of products related to gender.

(d) Tendency of buying products on sale related to gender.

Figure 16: Buying behaviour affected by different age and gender.

In Figure 16 (a) and Figure 16 (b), higher values on the Y-axis correspond to a higher likelihood of

buying a cheaper version of a product or of buying a product on sale. The lower values on the X-axis

mean younger age.

In Figure 16 (c) and Figure 16 (d), higher values on the Y-axis correspond to a higher likelihood of

buying a cheaper version of a product or of buying a product on sale. The values on the X-axis represent

the genders.

Figure 16 shows the tendency of younger people and men to choose cheaper versions and products on sale. We use this simple example to demonstrate how big chain supermarkets might collect massive

data and thus accurately establish a customer profile to reveal personal customer information.

24

Open questions In the two surveys we asked three open questions which required our participants to write down how

they describe privacy, how they feel about privacy, and, the field of information which would worry them most if it were transferred to others. We use word clouds to show the answers of our participants,

depicted in Figure 17. Note that the bigger the word, the more frequently this word is provided as an

answer.

(a) What is privacy. (b) How do you feel about privacy.

(c) Which field of information would worry you most if it were transferred to others.

Figure 17: Word clouds for the open questions.

Many people describe privacy with "security" and "personal freedom". They feel that privacy is

"important" and they are "concerned". When asked which field of information worries them most if it

were transferred to others, "ID", "income" and "health" are among the most popular choices.

25

Conclusion and Future Work From the two surveys conducted on MTurk we were able to draw the following conclusions:

• People are more willing to share personal information with those they have a closer

relationship with, like their families and friends.

• With increasing sensitivity of the data, people's willingness to share their personal

information decreases.

• People treat private information of a family member similarly to their own private information.

• Most people accept the websites' terms and conditions without fully reading the content.

• People in general show concerns about information security and privacy protection. However,

they are not very willing to pay extra to protect their data.

• Income and illness are the information people try to keep most secret.

• People in general underestimate the sensitivity of their purchasing history.

• Personalised offers and discounts can increase people's willingness to give out their

personal information.

In the era of big data and new technologies, there are more and more unexpected ways to expose

privacy and more needs to be done to protect people's privacy. Holvast [2] describes the problem of video surveillance, biometric identification, genetic data, identity theft, data warehousing and data

mining, chip or smart cards, Global Positing System (GPS), Internet, Key Logger, Radio Frequency

Identification (RFID), and Wireless Networking.

Future research should focus on a measure to capture people's willingness to share their privacy.

Additionally, a mathematical model could be developed to describe people's choices when facing the

danger of their personal information being exposed. This model could help understand which factors

are involved when making decisions on private information sharing.

Due to the setup of our questionnaires, participants taking the survey were able to go back to previous answers and change them. This may have lead to some artificially manipulated answers, such

as changing their answers to seem more rational, or to try not to contradict themselves. New answers

for previous questions may also have come to participants’ minds while continuing to fill in the

questionnaire. The effects of this long-form survey format are not entirely clear. In the future, a new

method or settings could be implemented to prevent this.

The study also leaves some open questions. How do people treat their own private information

compared to someone else's information? With the increasing risk of exposing privacy, are people aware

of the danger and actively searching for ways to protect their privacy? What are the ways for people to prevent companies from sharing their personal information without their knowledge, either intentionally

or unintentionally. Also, is the current law sufficient to protect privacy in today's new era of big data?

26

Bibliography [1] J. Michael, Privacy and human rights: an international and comparative study, with special

reference to developments in information technology. Dartmouth Pub Co, 1994. [2] J. Holvast, “History of Privacy”, Futur. Identity Inf. Soc. Priv. Secur. FIDIS/IFIP Internet Secur.

Priv. Summer Sch., p. 13. [3] Roberson v. Rochester Folding Box Co., vol. 64 App. Di, no. N.Y. App. Div. 1901. 1902, pp. 545–

546. [4] “An Actionable Right of Privacy? Roberson v. Rochester Folding Box Co.”, Yale Law J., vol. 12,

no. 1, pp. 35–38, 1902. [5] Pavesich v. New England Life Insurance Co., vol. 122 GA. 19, no. GA. 1905. 1905. [6] M. Diffenderfer, “Minors Online: Protecting the Privilege of Disaffirmance in the Digital”, vol. 54,

no. 1, pp. 131–156, 2016. [7] Oxford Dictionaries, “Definition of Privacy in English”. [8] Pingdom, “Would you pay $7,260 for a 3 TB drive? Charting HDD and SSD prices over time -

Pingdom Royal”, Dec-2011. [Online]. Available: https://royal.pingdom.com/2011/12/19/would-you-pay-7260-for-a-3-tb-drive-charting-hdd-and-ssd-prices-over-time/. [Accessed: 13-Apr-2018].

[9] M. Gualtieri, “Hadoop Is Data’s Darling For A Reason”, Jan-2016. [Online]. Available: https://go.forrester.com/blogs/hadoop-is-datas-darling-for-a-reason/. [Accessed: 08-Apr-2018].

[10] T. M. Mitchell, “Machine Learning and Data Mining”, Commun. ACM, vol. 42, no. 11, pp. 30–36, Nov. 1999.

[11] O. H. Gandy, “Toward a political economy of personal information”, Crit. Stud. Mass Commun., vol. 10, no. 1, pp. 70–97, 1993.

[12] Tages-Anzeiger, “Wenn der Nachbar fürs Brot weniger zahlt”, 2015. [Online]. Available: https://www.tagesanzeiger.ch/schweiz/standard/wenn-der-nachbar-fuers-brot-weniger-zahlt/story/13610490#overlay. [Accessed: 27-Mar-2018].

[13] C. M. Heilman, K. Nakamoto, and A. G. Rao, “Pleasant Surprises: Consumer Response to Unexpected In-Store Coupons”, J. Mark. Res., vol. 39, no. 2, pp. 242–252, 2002.

[14] Executive Office of the President of the United States, “Big Data and Differential Pricing”, 2015. [15] C. Duhigg, “How Companies Learn Your Secrets - The New York Times”, Feb-2012. [Online].

Available: https://www.nytimes.com/2012/02/19/magazine/shopping-habits.html. [Accessed: 04-Apr-2018].

[16] S. Athey, C. Catalini, and C. Tucker, “The digital privacy paradox: small money, small costs, smal talk”, Natl. Bur. Econ. Res., no. w23488, 2017.

[17] P. A. Norberg, D. R. Horne, and D. A. Horne, “The privacy paradox: Personal information disclosure intentions versus behaviors”, J. Consum. Aff., vol. 41, no. 1, pp. 100–126, 2007.

[18] Amazon Mechanical Turk, “Frequently Asked Questions” [Online]. Available: https://www.mturk.com/worker/help. [Accessed: 08-Apr-2018].

[19] Alexa, “Mturk.com Traffic, Demographics and Competitors”. [20] T. F. E. Wikipedia, “List of European countries by population”, 2018. [21] T. B. G. S. K. Vanhoof and G. Wets, “Using Shopping Baskets to Cluster Supermarket Shoppers”.

27

Appendix

A. Survey on General Willingness to Share 1. Would you share your high school grades with your colleagues?

1. Definitely

2. Very Probably

3. Probably

4. Probably Not

5. Definitely Not

2. Would you share your last year's tax return with immediate family members (and very close friends or partner)?

1. Definitely

2. Very Probably

3. Probably

4. Probably Not

5. Definitely Not

3. Would you share your medical record with your friends? 1. Definitely

2. Very Probably

3. Probably

4. Probably Not

5. Definitely Not

4. Would you share your high school grades with immediate family members (and very close

friends or partner)?

1. Definitely 2. Very Probably

3. Probably

4. Probably Not

5. Definitely Not

5. Would you share your last year's tax return with your friends?

1. Definitely

2. Very Probably

3. Probably 4. Probably Not

5. Definitely Not

6. Would you share your high school grades with a broader public?

1. Definitely

2. Very Probably

3. Probably

28

4. Probably Not

5. Definitely Not

7. Would you share your medical record with immediate family members (and very close

friends or partner)? 1. Definitely

2. Very Probably

3. Probably

4. Probably Not

5. Definitely Not

8. Would you share your last year's tax return with your colleagues?

1. Definitely

2. Very Probably 3. Probably

4. Probably Not

5. Definitely Not

9. Would you share your medical record with a broader public?

1. Definitely

2. Very Probably

3. Probably

4. Probably Not 5. Definitely Not

10. Would you share your high school grades with your friends?

1. Definitely

2. Very Probably

3. Probably

4. Probably Not

5. Definitely Not 11. Would you share your medical record with your colleagues?

1. Definitely

2. Very Probably

3. Probably

4. Probably Not

5. Definitely Not

12. Would you share your last year's tax return with a broader public?


3. Probably

4. Probably Not

5. Definitely Not

13. Would you share the physical health of a family member with a broader public?

29

1. Definitely

2. Very Probably

3. Probably


14. Would you share the current location of a family member with a friend?

1. Definitely

2. Very Probably

3. Probably

4. Probably Not

5. Definitely Not

15. Would you share the psychological health of a family member with a work colleague? 1. Definitely

2. Very Probably

3. Probably

4. Probably Not

5. Definitely Not

16. Would you share the psychological health of a family member with a broader public?

1. Definitely


4. Probably Not

5. Definitely Not

17. Would you share the salary of a family member with a friend?

1. Definitely

2. Very Probably

3. Probably 4. Probably Not

5. Definitely Not

18. Would you share the physical health of a family member with a friend?

1. Definitely

2. Very Probably

3. Probably

4. Probably Not

5. Definitely Not 19. Would you share the salary of a family member with a broader public?

1. Definitely

2. Very Probably

3. Probably

4. Probably Not

30

5. Definitely Not

20. Would you share the physical health of a family member with a work colleague?

1. Definitely


4. Probably Not

5. Definitely Not

21. Would you share the psychological health of a family member with a friend?

1. Definitely

2. Very Probably

3. Probably


22. Would you share the current location of a family member with a work colleague?

1. Definitely

2. Very Probably

3. Probably

4. Probably Not

5. Definitely Not

23. Would you share the salary of a family member with a work colleague? 1. Definitely

2. Very Probably

3. Probably

4. Probably Not

5. Definitely Not

24. Would you share the current location of a family member with a broader public?


3. Probably

4. Probably Not

5. Definitely Not

25. Assume you are purchasing a product on the internet. How important is the reputation of the

company you are buying the product from in your decision to share with them your personal

information over the Internet?

1. Crucial 2. Very Important

3. Worth Considering

4. Not very important

5. Irrelevant

31

26. How willing are you to provide personal information to web sites so that online

advertisements can be targeted to your tastes and interests?

1. Very willing

2. Somewhat willing 3. Probably

4. Not very willing

5. Not willing at all

27. Do you read the General Terms and Conditions for online services, when asked to accept

them in order to proceed with your inquiry?

1. Rarely

2. Never

3. It depends on the website 4. I scan through quickly

5. I read them thoroughly

28. How often do you accept the General Terms and Conditions online?

1. Always

2. Very Frequently

3. Occasionally

4. Very Rarely

5. Never 29. Choose which of the following options you would be willing to share on a website from an

online store like Zalando or Amazon (Choose all that apply)

• Gender

• Education

• Ethnicity

• Location

• Address

• Medical Record

30. Choose which of the following options you would be willing to share on a social media

website like Facebook or Twitter (Choose all that apply)

• Gender

• Education

• Ethnicity

• Location

• Address

• Medical Record

31. How concerned are you that websites could be using your personal information for

personalised marketing?

1. Extremely Concerned

2. Very Concerned

32

3. Concerned

4. Somewhat Concerned

5. Not Concerned

32. How concerned are you that websites could be selling your personal information to third parties?


2. Very Concerned

3. Concerned


5. Not Concerned

33. How concerned are you that websites could be saving your personal information on insecure

servers? 1. Extremely Concerned

2. Very Concerned

3. Concerned


5. Not Concerned

34. How concerned would you be if a website gave away your personal information to a friend?


2. Very Concerned 3. Concerned


5. Not Concerned

35. How concerned would you be if a website gave away your personal information to a broad

public?


2. Very Concerned 3. Concerned


5. Not Concerned

36. How concerned would you be if a website gave away your personal information to a col-

league?


2. Very Concerned

3. Concerned 4. Somewhat Concerned

5. Not Concerned

37. How concerned would you be if a website gave away your personal information to a family

member, a close friend, or partner?


33

2. Very Concerned

3. Concerned


5. Not Concerned 38. Is there any personal information online you would like to delete?

1. All of it

2. Most of it

3. Some Things

4. Just a few Things

5. None

39. Please write ONE word to describe what is privacy.

40. Please write ONE word to describe how you feel about privacy. 41. How willing are you to pay a reasonable extra price to restrict companies to use or save your

data?

1. Very willing

2. Somewhat willing

3. Probably

4. Not very willing


42. How willing are you to pay a reasonable extra price that the company applies a data protection technique to protect your privacy?

1. Very willing

2. Somewhat willing

3. Probably

4. Not very willing


43. What is your age? 1. 18-24 years old

2. 25-34 years old

3. 35-44 years old

4. 45-54 years old

5. 55-64 years old

6. 65 and older

44. What is your income per year (before tax)?

1. below 15,000 € 2. 15,000 - 29,900 €

3. 30,000 - 44,900 €

4. 45,000 - 59,900 €

5. 60,000 - 74,900 €

6. 75,000 € and above

34

45. What's your gender?

• female.

• male.

• other.

46. I see myself as someone who is reserved

1. Disagree strongly

2. Disagree a little

3. Neither agree nor disagree 4. Agree a little

5. Agree strongly

47. I see myself as someone who is generally trusting



3. Neither agree nor disagree

4. Agree a little 5. Agree strongly

48. I see myself as someone who tends to be lazy




4. Agree a little

5. Agree strongly

49. I see myself as someone who is relaxed, handles stress well 1. Disagree strongly



4. Agree a little

5. Agree strongly

50. I see myself as someone who has few artistic interests

1. Disagree strongly 2. Disagree a little


4. Agree a little

5. Agree strongly

51. How many friends do you consider close to you?

1. 0-1

2. 2-5

3. 6-10 4. 11-15

5. more than 15

35

B. Survey in Supermarket Context 1. Would you be willing to share your personal supermarket purchase history so that you can

have personalised advertisement? 1. Definitely

2. Very Probably

3. Probably

4. Probably Not

5. Definitely Not

2. Would you be willing to share your personal supermarket purchase history in order to

receive personalised offers and discounts?


3. Probably

4. Probably Not

5. Definitely Not

3. How important is it for you to keep alcohol purchase history private?

1. Crucial

2. Very Important

3. Worth Considering 4. Not very important

5. Irrelevant

4. How important is it for you to keep your junk food purchase history private?

1. Crucial

2. Very Important


4. Not very important 5. Irrelevant

5. How important is it for you to keep your clothing purchase history private?

1. Crucial

2. Very Important



5. Irrelevant

6. How important is it for you to keep your meat purchase history private? 1. Crucial

2. Very Important



5. Irrelevant

7. How important is it for you to keep your cigarette purchase history private?

36

1. Crucial

2. Very Important



5. Irrelevant

8. Would you be willing to share your fruit and vegetable purchase history? 1. Definitely

2. Very Probably

3. Probably

4. Probably Not

5. Definitely Not

9. Would you be willing to share the carbon footprint of your latest shopping experience?

1. Definitely


4. Probably Not

5. Definitely Not

10. Please select ALL the factors that would make you willing to provide your personal

information to a commercial company.

• I trust that my data would be secure

• I would get benefit or special discount if I provide my data

• This company's privacy policy is clear

• I have received the service from this company for a long time

• I can get personalized offers from this company if I provide my data This company

has a good reputation

11. Please select ALL the factors that would leave you unwilling to provide your personal

information to a commercial company.

• I doubt if my data would be secure

• I can't get any benefit from providing my data

• This company privacy policy is not clear

• I didn't receive service from this company

• I can't get personalized offers or any personalized advertisement if I provide my

data This company doesn't have a good reputation

12. Do you think people can classify you correctly to a certain group of people (for example as a

house wife, vegetarian, student etc.) by just looking at your supermarket purchase history?

1. Definitely


4. Probably Not

5. Definitely Not

37

13. Do you think people can classify you correctly to a certain group of people (for example

alcoholism, depression etc.) by looking at your supermarket purchase history?

1. Definitely

2. Very Probably

3. Probably


14. How concerned are you if you know supermarkets that you often go to store and track their

customers' purchase history?


2. Very Concerned

3. Concerned


5. Not Concerned 15. Are you aware of any laws that protects your data?

1. Definitely

2. Very Probably

3. Probably

4. Probably Not

5. Definitely Not

16. How important is it to you that your sex orientation can't be exposed by your purchase history?

1. Crucial

2. Very Important



5. Irrelevant

17. How important is it to you that your gender can't be exposed by your purchase history?

1. Crucial 2. Very Important



5. Irrelevant

18. How important is it to you that your age can't be exposed by your purchase history?

1. Crucial

2. Very Important 3. Worth Considering


5. Irrelevant

19. How important is it to you that an illness you have can't be exposed by your purchase

history?

38

1. Crucial

2. Very Important



5. Irrelevant

20. How important is it to you that your income can't be exposed by your purchase history? 1. Crucial

2. Very Important



5. Irrelevant

21. How important is it to you that your pregnancy can't be exposed by your purchase history?

1. Crucial

2. Very Important 3. Worth Considering


5. Irrelevant

22. How important is it to you that your religion can't be exposed by your purchase history?

1. Crucial

2. Very Important

3. Worth Considering 4. Not very important

5. Irrelevant

23. Do you prefer supermarkets' own brand in general or other brands?

• Supermarkets' own brand

• Other Brands 24. Do you tend to buy cheaper versions of products?

1. Definitely

2. Very Probably

3. Probably

4. Probably Not

5. Definitely Not

25. Do you tend to choose a specific brand for your purchases? 1. Definitely

2. Very Probably

3. Probably

4. Probably Not

5. Definitely Not

26. Would you buy a product only because its on sale?

1. Definitely

2. Very Probably

39

3. Probably

4. Probably Not

5. Definitely Not

27. What is your age?

1. 18-24 years old

2. 25-34 years old 3. 35-44 years old

4. 45-54 years old

5. 55-64 years old

6. 65 and older

28. What is your income per year (before tax)?

1. below 15,000 €

2. 15,000 - 29,900 €

3. 30,000 - 44,900 € 4. 45,000 - 59,900 €

5. 60,000 - 74,900 €

6. 75,000 € and above

29. What's your gender?

• female

• male

• other

30. I see myself as someone who is reserved


2. Disagree a little 3. Neither agree nor disagree

4. Agree a little

5. Agree strongly

31. I see myself as someone who is relaxed and handles stress well




4. Agree a little 5. Agree strongly

32. I see myself as hard working person




4. Agree a little

5. Agree strongly

33. I see myself as someone who tends to find faults with others 1. Disagree strongly

40



4. Agree a little

5. Agree strongly

34. What is the highest education you received?

1. High school 2. Admission to universities or college

3. Bachelor

4. Master

5. PhD

35. Please write down one to three fields for which you are most worried if your personal

information would be transferred to others

41

Collegium Helveticum

The Collegium Helveticum is a think tank and laboratory for transdisciplinary research. We aim to provide a meeting place and forum for dialogue between the humanities, social sciences, physical sciences, engineering, medical science and the arts. It is sponsored by the University of Zurich, ETH Zurich and the Zurich University of the Arts. Alongside the transdisciplinary research of our fellows and members, the Collegium organises international events on fundamental issues in science and the arts in general, as well as on the current research topic of ‘digital societies’ in our role as an institute for advanced study.

Fellows

The fellows form the core membership of the Collegium Helveticum. The seven fellows, selected by a Board of Trustees, include three fellows from each of the University of Zurich and ETH Zurich and one fellow from the Zurich University of the Arts. During their four-year terms, the institution’s fellows continue to hold professorships and other positions at their respective universities. However, they are relieved of 20 per cent of their workload in order to free up their schedules for research at the Collegium. This model of a ‘long-term, part-time fellowship’, which is unique in academia, allows researchers to benefit from intensive collaboration between the Collegium Helveticum and the Zurich research hub. In addition, the appointment of fellows for a minimum four-year period offers the best conditions for conducting successful transdisciplinary research projects. The Collegium Helveticum fellows for the 2016–2020 period are:

Nikola Biller-Andorno, UZH, Biomedical Ethics Monika Dommann, UZH, Modern History David Gugerli, ETH Zurich, Technological History Petros Koumoutsakos, ETH Zurich, Computational Science Mike Martin, UZH, Gerontopsychology Hannes Rickli, ZHdK, Contemporary Art Renate Schubert, ETH Zurich, Economics

Digital societies

During the current fellowship period (2016–2020), researchers at the Collegium Helveticum are focusing their efforts on the topic of ‘digital societies’. Digital technology is an integral, omnipresent part of our lives, which has an impact on our thoughts and behaviours, but also on our knowledge, values and principles. Yet above all, it is fundamentally changing the way in which we organise our society and culture. With its transdisciplinary approach, the Collegium Helveticum is well placed to reflect on complex processes, going far beyond our pre-existing ‘thought collectives’ and thinking styles. Within the topic of ‘digital societies’, fellowship projects are developed using a bottom-up approach, resulting in inclusive, transdisciplinary research projects led by at least two fellows and involving a number of additional disciplines.

Contact

Collegium Helveticum Schmelzbergstrasse 25 8092 Zürich www.collegium.ethz.ch

working paper. are people willing to share their …...are people willing to share their personal...

Documents