• No results found

Is E-personalisation a danger for the customers privacy? : A study on JIBS students

N/A
N/A
Protected

Academic year: 2021

Share "Is E-personalisation a danger for the customers privacy? : A study on JIBS students"

Copied!
70
0
0

Loading.... (view fulltext now)

Full text

(1)

J

Ö N K Ö P I N G

I

N T E R N A T I O N A L

B

U S I N E S S

S

C H O O L JÖNKÖPING UNIVERSITY

Is E-personalisation a danger for the

customer’s privacy?

A study on JIBS students

Bachelor Thesis within Business Administration Authors: Irina Brezgina

Margaux Debouchaud Julia Frehse

(2)

Bachelor’s Thesis within Business Administration

Title: Is E-personalisation a danger for the customer’s privacy? A study on JIBS’ students Authors: Irina Brezgina, Margaux Debouchaud and Julia Frehse

Tutor: Olga Sasinovskaya Date: 2008-06-05

Subject terms: Online Advertisement or E-advertising, E-Personalisation, Online Pur-chasing Decision, E-privacy, etc.

Abstract

Background:

From a marketing perspective, personalisation of online advertising is a very promising way of reaching customers and will play an increasingly important role in the future. Personalisation on the Internet is far more widespread than in the offline world and can cover all online interactions when it comes to the question of what information to personalise. It directly relates to the issue of privacy of personal data and creates a need for a privacy policy that clarifies the relation between personalisation and privacy.

Problem:

Personalisation represents one of the main advantages of the Internet and al-lows marketers to target individual customers directly and adapt their marketing communi-cations to the user’s preferences and needs. On the one hand, personalisation can give cus-tomers access to better service, products and communication and provides an experience of one. On the other, privacy issues related to the Internet and personalisation in particular are a contemporary topic of growing interest. Internet users are increasingly aware of the fact that websites collect information about them and their privacy concerns are growing. Personal information is necessary for personalising advertisements. Therefore, this devel-opment contradicts the customer’s increased demand for personalisation and the trend to-wards narrowly targeted marketing.

Purpose:

The purpose of this thesis is to explore if personalised online advertising could be perceived as a danger to customer’s privacy or on the other hand, facilitate the purchase decision process.

Method:

In order to answer the purpose and the research questions, a survey has been conducted with 152 JIBS students asking them about their opinion on e-advertising and their fears about it. After the questionnaires had been collected, different analysis such as univariate analysis and bivariate analysis has been done using SPSS.

Conclusions:

In summary it can be said that the respondent’s general perception of personalised e-ads is negative; they do not believe that they make shopping easier and they see a danger for their privacy in how companies collect the customer’s information and use it.

(3)

Table of Contents

1

Introduction ... 1

1.1 Background ... 1 1.2 Problem discussion ... 2 1.3 Purpose ... 3 1.4 Perspective ... 3 1.5 Delimitations ... 3 1.6 Definitions ... 3

2

Frame of Reference ... 4

2.1 E-Advertising ... 5 2.2 E-Personalisation ... 7 2.2.1 Personalisation vs. Customisation ... 7

2.2.2 Highlights on different personalisation approaches ... 8

2.2.3 The process of personalisation ... 11

2.2.4 Values, benefits and costs for customers and marketers ... 12

2.3 E-Privacy ... 13

2.4 Gathering and using personal information ... 15

2.5 Online consumer behaviour ... 17

2.5.1 Customer attitudes towards Internet Advertising ... 17

2.5.2 A model of online consumer purchase decision and its process ... 17

2.6 Research Questions ... 19

3

Method ... 20

3.1 Research approach ... 20

3.2 Research strategy: quantitative vs. qualitative ... 20

3.2.1 Methods of data collection ... 21

3.2.2 Planning a Survey ... 22 3.2.3 Sample choice ... 22 3.3 Survey design ... 25 3.3.1 Self-completion Questionnaire ... 25 3.3.2 Survey layout ... 25 3.3.3 Types of questions ... 26

3.3.4 Attitude measurement scale ... 28

3.4 Pilot Study ... 28

3.5 Presentation of the empirical data and analysis ... 30

3.6 Generalisability ... 32

3.7 Validity and Reliability ... 32

4

Results and analysis ... 34

4.1 Sample ... 34

4.2 Research question 1: How do different aspects of personalised advertising influence the customer’s concerns for privacy? ... 34

4.3 Research question 2: How can customers’ awareness of data collection influence the purchasing decision? ... 38

4.4 Research question 3: To what extent are personalised e-ads perceived as helpful for the purchasing decision? ... 43

(4)

5

Conclusions ... 48

6

Discussion ... 51

6.1 Managerial implications ... 51

6.2 Limitations and suggestions for further research ... 52

References ... 53

Appendices ... 56

Appendix 1 - Glossary ... 56

Appendix 2 - Questionnaire ... 58

(5)

Table of Figures

Figure 2.1 - Theoretical Structure (own model) ... 4

Figure 2.2 - E-Marketing Mix (Karlyanam & McIntyre, 2002) ... 6

Figure 2.3 - Example of adaptive personalisation (yahoo.com homepage, 2008)9 Figure 2.4 - Example of transparent personalisation, (Amazon.com homepage, 2008) ... 10

Figure 2.5 - The process of personalisation, Vesanen and Raulas (2006) ... 11

Figure 2.6 - The benefits and costs of personalisation for the customer and the marketer, (Vesanen, 2007) ... 12

Figure 2.7 - Dimensions of information privacy (recreated after Harkiolakis, 2007) ... 14

Figure 2.8 - FTC’s Fair Information Practice Principles and the Flow of Online Information (Radin et al., 2007). ... 16

Figure 2.9 - Model of Online Consumer Behaviour (Laudon & Traver, 2007) ... 18

Figure 2.10 - Online and Offline Communications in the buyer decision process (Laudon & Traver, 2007) ... 19

Figure 3.1 - The process of deduction, (Bryman & Bell, 2007) ... 20

Figure 3.2 – Steps in survey planning (after Scheaffer et al. 2006)... 22

Figure 3.3 – Sample Choice (own model) ... 24

Figure 3.4 – Visualisation of possible relationships between variables in the analysis ... 31

Figure 4.1 – Age distribution of respondents ... 34

Figure 4.2 – Types of personal information ... 35

Figure 4.3 – Concern for privacy and age groups ... 36

Figure 4.4 - Concern for privacy and level of studies ... 36

Figure 4.5 – Willingness to reveal personal information ... 37

Figure 4.6 – Correlation: “I think it is important to read privacy policies on websites” and “Some websites know too much about me” ... 38

Figure 4.7 – Respondent’s awareness of personalised e-ads ... 39

Figure 4.8 – Crosstabulation: Awareness of collection process and respondent’s gender ... 40

Figure 4.9 – Line diagram: Awareness of collection process and gender ... 40

Figure 4.11 – Perceived control over the collection process by gender ... 41

Figure 4.12 – Attitude towards personalised e-ads and purchasing decision .... 43

Figure 4.13 - Correlation: “I often see personalised advertisements on the Internet” and “I would like to see more online advertisements which exactly fit my needs and preferences” ... 44

Figure 4.14 - Correlation: “I like personalised online advertisements because they make shopping easier” and “I would purchase a product online based on a personalised recommendation or advertisement” ... 45

Figure 4.15 - Correlation table: “I like personalised online advertisements because they make shopping easier” and “I would like to see more online advertisements which exactly fit my needs and preferences”. ... 46

(6)

1 Introduction

This chapter introduces the chosen area of study by discussing the background and problem of personalised online advertisements and related privacy issues. The resulting purpose is followed by a presentation of the perspective and delimitations of this thesis.

1.1 Background

From our own experience we know that searching for information, communicating with friends as well as other everyday activities is unimaginable without the Internet nowadays. The Internet has had and continues to have a very strong influence on the formation and development of the global information society. As a social phenomenon, the Internet is a global communication tool that provides the exchange of texts, graphics, audio and video files, and access to online services without the territorial and national boundaries. It con-nects 470 million users around the world to each other and to an incredibly large informa-tion repository making it an effective tool for research, communicainforma-tion, the expansion of trade and business. The technological possibilities of the Internet cause a rapid develop-ment of the global information society and let new approaches to business and marketing evolve. The Internet became a useful advertising medium through which companies can promote their products directly to the customer and create value for customers in new and innovative ways. Currently, almost every traditional brick-and-mortar company is also rep-resented on the Internet. A large number of advertising sites, platforms and other resources help the user to find the necessary information online. Thus, the Internet has become an advertising tool, with unique and new features that can compete with the traditional types of advertising (Kotler & Armstrong, 2008).

With a steadily increasing size of the Internet population online shopping is becoming a common experience for consumers around the world. In 2007, more than 50% of consum-ers in the US, the UK, Germany and Sweden had used the Internet for online purchases at least once (eMarketer, 2008). E-commerce digitally enables commercial transactions and is more powerful than any other technology that was used in the past. Laudon and Traver (2007) list seven unique features of e-commerce technology that have significance for busi-ness and distinguish e-commerce from traditional offline busibusi-ness transactions. Among these seven E-commerce technology dimensions is personalisation which is the precise tar-geting and adaptation of advertising messages to match the user’s preferences. The increase in information density enables online merchants to easily collect and store information about the user’s purchasing and click stream behaviour. This information can then be processed and used to target advertisements to specific users (Laudon & Traver, 2007). From a marketing perspective, personalisation of online advertising is a very promising way of reaching customers and will play an increasingly important role in the future. Personal-isation on the Internet is far more widespread than in the offline world and can cover all online interactions when it comes to the question of what information to personalise. It di-rectly relates to the issue of privacy of personal data and creates a need for a privacy policy that clarifies the relation between personalisation and privacy. A useful privacy policy should provide the possibility to opt-in or opt-out (see Appendix 1) of receiving targeted advertisings and state what information is collected, whether it will be shared with third parties and how it will be used. Personalisation and privacy are closely linked to each other, affect all aspects of online marketing and do not find a counterpiece in the offline market-ing mix. These facts turn them into a topic of high interest that will be further discussed in this thesis (Karlyanam & McIntyre, 2002).

(7)

1.2 Problem discussion

Recent technological innovations caused the business environment to change and compa-nies to adapt to these new advances. Traditional or standard marketing strategies are not sufficient to cope with the New Economy anymore. Marketers need to develop new tactics and adapt to new ways of communicating with customers and advertising on the Internet, in order to stay competitive. Indeed, using the Internet as an advertising tool represents a competitive advantage for companies due to the growing number of Internet users. Since its creation in the 1990’s, the World Wide Web has changed from a simple communication tool to a certifiable revolutionary technology for marketers (Kotler, 2005). Personalisation represents one of the main advantages of the Internet. Marketers can target individual cus-tomers directly and adapt their marketing communications to the user’s preferences and needs. For marketers, personalisation results in higher prices, satisfied customers, and in-creased differentiation. At the same time, it requires investments in technology and educa-tion.

While many authors praise personalisation on the Internet as a universal solution, others question the very nature of it. They argue that personalisation is about one-to-one relation-ships between human beings and not a human being and a computer. In their opinion, us-ers value the pus-ersonal experience of shopping including a staff with whom they can be-come acquainted, a local presence or even a flavour that rounds out the experience. These expectations cannot be met online due to the nature of efficiency of e-commerce business models, which do not allow the staff size necessary to personalise every single transaction. It is further argued that due to this fact, what is called “personalisation” in online markets is merely the ultimate of target marketing that goes to the extreme market size of one indi-vidual. There is nothing personal about “personalisation” because the rules-based software does not succeed in identifying the diverse characteristics of users correctly. This may lead to dissatisfaction for customers when they feel that their hopes for personalisation are not fulfilled. These findings can be summarised as follows: “customised target marketing is the best e-commerce can hope to achieve and it’s not their fault” (Monroy, 2000).

Even if personalisation on the Internet is possible nowadays, it is questionable whether it is beneficial for customers. From the customer’s perspective, which will be used throughout this thesis, benefits as well as risks can be identified. Personalisation gives customers access to better service, products and communication and provides an experience of one. It might be helpful and convenient in the purchasing decision process. At the same time, personal-isation is time consuming, might cause extra fees and most importantly represents a risk for customer’s privacy (Vesanen & Raulas, 2007). Internet users are increasingly aware of the fact that websites collect information about them and their privacy concerns are growing. Personal information is necessary for personalising advertisements. Therefore, this devel-opment contradicts the customer’s increased demand for personalisation and the trend to-wards narrowly targeted marketing. Privacy issues related to the Internet and personalisa-tion in particular are a contemporary topic of greatest interest and that is why we decided to research in this field and take a look on the matter from the customer point of view. The following two perspectives on personalised Internet advertising will be subject to our study: First, personalised online advertising is useful for customers and influences the purchasing decision process in a positive way; second, personalised online advertising represents a threat for the customer’s privacy and affects the purchasing decision process negatively.

(8)

1.3 Purpose

The purpose of this thesis is to explore if personalised online advertising could be per-ceived as a danger to customer’s privacy or on the other hand, facilitate the purchase deci-sion process.

The purpose stated above is narrowed down further with the help of research questions. These research questions are derived from the theoretical framework and can therefore be found in the last section of the frame of reference.

1.4 Perspective

Advertisements on the Internet differ from traditional ways of advertising in the way that they are typically "pulled" by the recipient rather than "pushed" by the sender (Schlosser, Shavitt & Kanfer, 1999). The user often has to actively request further information to be displayed whereas traditional advertising is often received without asking. When a banner is displayed on a website for example, it is for the users to decide if they want to click on it or not. Also, new forms of rich media ads involve the user more and more interactively (Lau-don & Traver, 2007). Cartellieri, Parsons, Rao and Zeisser argued in 1997 that in the future a combination of "pull" and "push" technologies will dominate Internet advertising. Given these facts, it is obvious that users have a high degree of control over the advertisements they are exposed to on the Internet. Therefore we decided to conduct our empirical study from a customer’s perspective. Understanding the customers’ attitude toward the issues of personalisation as well as their privacy concerns is crucial for the success of online market-ing tools. For this reason it is useful to analyse whether the benefits or the risks related to personalisation prevail for customers. We aim to collect empirical data from a customer perspective in order to make the findings available to companies engaged in Internet adver-tising in the form of managerial implications.

1.5 Delimitations

This part is dedicated to the limits of the study. Since this study aims to investigate the cus-tomer perspective and their perception of personalised e-ads as stated above, the technical process of personalisation and the underlying databases and profiling procedures will not be discussed in detail in this thesis. In the same way, we will not go into detail about the le-gal framework regulating personalisation. The fact that there are no universal laws regulat-ing the personalisation of advertisements indicates that this is a complicated and varied is-sue which is not directly relevant for this study and will therefore not be analysed further. Among others, it has to be pointed out that there might be factors other than privacy con-cerns and personalised online advertisements that influence the user’s purchasing decision. These factors are not taken into consideration in this study. Furthermore, this study is lim-ited to a sample of JIBS students and might therefore not be representative for the Internet population in general.

1.6 Definitions

In order to avoid misunderstandings and misinterpretations, a number of important terms, which are used throughout the thesis, need to be defined. An alphabetically arranged glos-sary defining these frequently used terms can be found in Appendix 1. With the help of the glossary, the reader can look up unknown terms at anytime while, before or after reading the thesis.

(9)

2 Frame of Reference

This chapter provides an overview of research in the areas of e-personalisation, e-privacy and consumer be-haviour and introduces different models which will be used for the analysis of empirical data later on. At the end of this chapter, a specification of the research questions will be presented.

The funnel approach is used in this section to narrow the theory down and have a consis-tent structure to the research. E-advertising and Personalised E-advertising are the core body of the frame of reference with E-privacy and Information use as complimentary sub-jects. Both funnel models influence the consumer buying behaviour and the purchase deci-sion (Figure 2.1). In other terms, this model explains the influence of companies’ efforts (E-advertising, Personalised E-advertising) and external privacy issues (E-privacy, Informa-tion Use) on the consumer buying behaviour.

For the Internet user side, this model shows that companies’ efforts help the customer to balance between the positive and negative side of personalised E-advertising by considering privacy concerns and information use in order to decide if they intend to purchase or not. The sections below follow this funnel approach and aim to help first of all the develop-ment of the research questions. Later on, they are used to fulfil the purpose as well as to answer the research questions by comparing the subsequent theories with the empirical findings.

(10)

2.1 E-Advertising

The following paragraphs introduce advertising as an increasingly popular form of E-marketing or more precisely direct E-marketing. The common framework that is presented demonstrates the significance of both personalisation and privacy for the field of E-marketing and thus supports the purpose of this thesis. In the end of this part, different types of personalised advertisements are presented to demonstrate the diversity of person-alised online advertisements and to show where users can be faced with such online ads. Indeed, the Internet with its diversity and ever developing technologies and services repre-sents a platform for a number of different ways to reach the user. One of them is E-Advertising, an E-Marketing tool which has been flourishing at the same time as the stan-dardisation and democratisation of the Internet. One of the biggest advantages of E-advertising is the possibility to target ads to a specific group of users. Well-targeted ads are a useful tool for companies since they have a greater potential to result in a purchase (Lau-don & Traver, 2007). The trend towards narrowly targeted marketing caused a shift from mass marketing to direct marketing. Customers are increasingly demanding interactive one-to-one relationships and more personal marketing approaches, which pressures companies to change their marketing orientation. As consumers spend more and more time online, companies spend increasing amounts of money on online advertising, a type of direct mar-keting. Direct marketing to individual customers accounted for 48% of total U.S. advertis-ing expenditures in 2007. Spendadvertis-ing on online advertisadvertis-ing is expected to rise to more than $22 billion by 2009, representing about 11% of direct marketing expenditures. This shows the increasingly important role of online marketing in the marketing mix of companies (Kotler & Armstrong, 2008).

Karlyanam and McIntyre (2002) created a common framework and vocabulary for E-marketing which shows the important role of personalisation and privacy within the field of E-marketing. The authors base their model on the concept of the traditional marketing mix and the 4 Ps introduced by McCarthy (1960). They retain the original 4Ps (Price, Prod-uct, Promotion, and Place) and adjoin six additional elements: Personalisation and Privacy (P²), Customer Service and Community (C²), Security and Site Design (S²). The resulting new E-marketing mix can be described using the formula 4Ps+P²C²S² (Figure 2.2).

It is argued that the 4Ps as well as Site Design, Customer Service and Community should be treated as separate macro-elements in the E-marketing mix. Personalisation and Privacy together with Security then form the foundation of the model, transcending all aspects of E-marketing. They build a policy base to integrate various elements of E-marketing that does not have a counterpart in the traditional offline marketing mix. The transcending na-ture of personalisation and privacy and their position in the foundation of the E-marketing mix shows clearly the significance and importance of these issues for E-marketing and more precisely for E-advertising (Karlyanam & McIntyre, 2002).

(11)

Figure 2.2 - E-Marketing Mix (Karlyanam & McIntyre, 2002)

The following paragraphs aim to give the reader an overview of the most common types of online advertising as well as recently emerging services which can be subject to personalisa-tion. As stated in the delimitations above, technical issues will not be developed in detail since they are not relevant for this study.

The first type of Internet advertisement that was available online was the banner ad. Ban-ner ads resemble traditional print advertisements and can appear anywhere on a user’s screen, in chat rooms, search engines, blogs and on commercial or private websites. De-spite their similarity, banner ads have a number of advantages over print ads such as the in-cluded link to a company's own website and their dynamic nature. Another form of display ads are pop-ups that appear in a new window on the screen or underneath the browser's own window (pop-up ad/pop-under ad) without the user requesting them. Research has shown that pop-up ads are more effective than normal banner ads although they are dis-liked by most Internet users and often blocked by toolbars. The last type of display ads are interstitials and superstitials. They are placed between the websites the user accesses and open when the user clicks to another website. Rich media ads are more stimulating and in-teractive types of online advertising that use video, sound, and/or animation. Newer ap-proaches to Internet advertising include search-related ads, search engine optimization, paid search engine inclusion and placement. Search-related advertising accounts for 41% of the total online advertising expenditures, more than any other type of online advertising (Turban et al., 2006, Laudon & Traver, 2007).

The following online marketing strategies are becoming more and more popular. Compa-nies have the possibility to cooperate in their marketing efforts and promote each other, which is known as affiliate marketing. In content sponsorship, companies can display ads on the Internet by sponsoring special content such as news or special topics on a website. Viral marketing is the Internet version of word-of-mouth and is an effective and inexpen-sive form of online advertising. Another popular type of online advertising is direct e-mail marketing using increasingly “enriched”, animated, interactive and personalised messages. Currently companies spend about $1.1 billion a year on direct e-mails to users. This strat-egy has high response rates but the receivers’ approval of the use of their e-mail address is a

(12)

necessary prerequisite. The explosion of spam, unwanted commercial e-mail messages, frustrates many users and has to be kept in mind when dealing with direct e-mail market-ing. Recently emerging features such as video ads, podcasts, personal weblogs (blogs) as well as virtual communities like FaceBook or Myspace open up a number of new opportu-nities and platforms for online advertising and personalisation. (Laudon & Traver, 2007; Kotler & Armstrong, 2008).

This part dealt with the increasing success of e-advertising and the trend towards narrowly targeted markets and onto-one marketing. In order to help companies implement e-advertising, Karlyanam and McIntyre created an e-marketing model based on the 4p’s and extra elements such as Personalisation, Privacy, etc. Finally, we provided an overview over several types of E-advertisements that could be seen online and subject to personalisation which is explained in more detail in the following section.

2.2 E-Personalisation

“I know you. You tell me what you want. I make it. I remember

next time”

(Don Peppers and Martha Rogers, 1997)1

In this section, the key concepts of E-Personalisation are discussed. The first part gives an overview of several contemporary theoretical definitions permitting to distinguish the term Personalisation from Customisation. In the second part an outline of diverse types of Per-sonalisation systems is given. Then, we describe the process of perPer-sonalisation and the benefits and values for customers and companies in the end.

2.2.1 Personalisation vs. Customisation

Some theorists associate the term ‘Personalisation’ with ‘Customisation’ without differenti-ating the two terms. However, they do not refer to the same strategy and should be clearly defined.

It appears first, important to elucidate what is hidden behind the term “Personalisation”. Personalisation is a specialised form of product differentiation, in which a solution is tailored for a specific individual (Hanson, 2000). In other terms, E-personalisation refers to an adapta-tion of online advertisements to meet customer needs. Amazon.com usually uses this prac-tice when it sends for instance, emails following the e customers’ purchases (books, com-pact disks, etc.) with recommendations for their next purchase. The Personalisation Con-sortium (2005) also defines it as the use of technology and customer information to tailor electronic commerce interactions between a business and each individual customer. Using information either previously obtained or provided in real-time about the customer, the ex-change between the parties is altered to fit the customer’s stated needs as well as needs per-ceived by the business based on the available customer information (Vesanen, 2007). Hence, through e-personalisation, a website can serve as a matchmaker that discovers and delivers personal information to the e-customer. Other theorists have come up with spe-cific definitions of the term “Personalisation” in the last decade. Here is a sample of these definitions:

(13)

• Roberts (2003) “The process of preparing an individualised communication for a specific person based on stated or implied preferences”.

• Cöner (2003) “Personalisation is performed by the company and is based on a match of categorized content to profiled users”.

• Rangaswamy (2001) “Personalisation can be initiated by the customer (e.g. cus-tomising the look and contents of a web page) or by the firm (e.g. individual-ized offering, greeting customer by name etc.)”.

• Imhoff et al. (2001) “Personalisation is the ability of a company to recognize and treat its customers as individuals through personal messaging, targeted banner ads, special offers on bills, or other personal transactions”.

• Allen et al. (2001) “Company-driven individualization of customer web experi-ence”.

• Peppers et al. (1999) “Customising some feature of a product or service so that the customer enjoys more convenience, lower cost, or some other benefit”. Customisation on the other hand, is relatively close to the term Personalisation, but does not exactly refer to the same strategy. Indeed, Customisation is the way to create a product or a service according to the buyer’s specifications (Hanson, 2000). It aims at adapting the product and not the promotion strategy, to the customer’s needs. Even though some economists do not think those two terms should be differentiated, such as Peppers et al. (1999), others have come up with different definitions such as Hanson (2000), Allen et al. (2001), Imhoff et al. (2001), Wind and Rangaswamy (2001), Cöner (2003) or, Roberts (2003). Instead of providing you an inventory of those definitions, it seems more relevant to combine them to provide a complete definition of Customisation that can be used to show the disparity between both terms. First, the user performs customisation as the concept in-cludes individualisation of features such as web contents and so on, by customers. In other terms, regarding to the company’s point of view, it is the process of producing a product, service, or communication to the exact specifications, desires of the purchaser or recipient. Therefore, marketers could use customisation as a business strategy to recast the com-pany’s marketing and customer interfaces to be buyer-centric (Wind & Rangaswamy, 2001). Thus, the theoretical study has demonstrated that Personalisation and Customisation, even if they are interdependent terms, have some peculiarities showing that the two terms do not refer exactly to the same strategy. It appears though that customisation is a form of personalisation done by the customer that features more in depth individualisation than personalisation (Cöner 2003; Roberts 2003).

2.2.2 Highlights on different personalisation approaches

This part is dealing with the descriptive aspects of E-personalisation such as ways or strate-gies that companies generally use to personalise and advertise at the same time their web-sites. The aim of this section is to give the readers an overview and idea of what is person-alisation and its approaches related to theorists. Therefore, this part will not be compared with the empirical findings.

Many authors, such as W. Hanson (2000) and further, J. Vesanen (2007), have been trying to classify personalisation into different marketing strategies. Personalisation can be cata-logued into several approaches such as Adaptive, Cosmetic, Transparent Personalisation or even Collaborative Customisation. Each strategy has a different position along the axis of product design and representation implications. The most common type of personalisation used

(14)

online is the adaptive personalisation which consists of offering the same basic product and representation to everyone but letting users filter out most of the possibilities (Hanson, 2000). Yahoo.com is a relevant example concerning this strategy as it lets customers choose from different options such as colour of the homepage’s wallpaper, and so forth.

Figure 2.3 - Example of adaptive personalisation (yahoo.com homepage, 2008)

While speaking about personalisation, the second approach coming to mind is the Cosmetic Strategy based on taking a standard product and presenting it in a different way. In other terms, cosmetic personalisation consists of keeping the core product, changing the packag-ing, presentation, and other extra components permitting tailoring the product to a specific target group or an individual. This strategy is easy to implement online as it only implies to divide for instance the webpage into different parts such as the heading at the top, the main content of the page, and footer at the bottom. The second step could be to customise each header for each individual while keeping the rest of the content unchanged (Hanson, 2000). A famous illustration of this strategy is Google.com which changes the package of standard goods by collecting information from the customer such as behaviours, age, purchases, and so on. However, this practice is generally relevant on the unique condition that the cus-tomer looks out for the webpage presentation. Moreover, cosmetic personalisation com-pared to the adaptive one does not require a high degree of customer interaction.

With regards to more challenging strategies, the transparent personalisation is the most relevant and rewarding. The organisation or web marketers deliver completely tailored products and services to customers’ without making them aware of any changes. The marketers collect information from users such as age, status, job, hobbies, buying behaviours, purchases and so forth, in order to customise the product and adapt it to customers’ needs. Amazon.com is a perfect example to illustrate transparent personalisation. However, to be useful, the customer should have repetitive contacts with the website (Vesanen, 2007).

(15)

Figure 2.4 - Example of transparent personalisation, (Amazon.com homepage, 2008)

The last and most challenging approach is the collaborative customisation. In this strategy, mar-keters are working conjointly with customers to create the product. This type of marketing strategy is also called one-to-one marketing where marketers are looking at customers’ needs and wants to perfectly tailor the product to their expectations. A less direct version of collaborative customisation is founded on a variety of query systems to help customers discover their own best choices. Techniques such as conjoint analysis, features rating, and collaborative filtering are different methods by which a site works with customers to de-termine their preferred choices. They are finally used to deliver unique and individually tai-lored options (Hanson, 2000).

Even if that classification of personalisation types is the most commonly used and cited in E-commerce literature, other authors have been describing Personalisation through a dif-ferent angle such as Lorrie Faith Cranor (2003). In the article “‘I didn’t buy it for myself’ Privacy and E-commerce Personalisation”, the author asserts that Personalisation Systems differ on four axes: Explicit vs. Implicit data collection, Duration, User involvement, and Reliance on predictions. In this paragraph each of these characteristics is described with examples taken from the Internet.

First, Explicit vs. Implicit data collection relates to customers information that a website can collect. If the data collection is explicit, the website collects information from the custom-ers by asking them to rate products, give their preferences and age. On the other side, im-plicit data collection consists of gathering information from the user such as purchase or browsing history. Amazon.com uses both of these strategies to collect customers’ data as they ask their customers to rate for example books and collect implicit data to make rec-ommendations to their users.

The second personalisation system described by L. Faith Cranor (2003) is Duration with task or session-focused personalisation and Profile-based personalisation. The first one is by defi-nition the concept of positioning ads where they are the most relevant such as proposing to a purchaser of women’s swimsuit, some complementary products such as bathing cap, towel, and so forth. The second one is often used by websites such as Amazon.com that develop profiles of users by adding tailored information to customers’ homepage as name

(16)

or date. Each time users log into the website they can see a page customised to their inter-ests and see their last purchases and orders.

The third personalisation system, User involvement, includes user-initiated and system-initiated personalisation. This strategy has two faces: the first one implies that the user is aware of personalisation and interested in it and the other one, on the contrary, collects and uses in-formation from customers even if they do not request it. However, on the second case, us-ers can sometimes opt-out of pus-ersonalisation.

The fourth and last personalisation method relies on predictions. The first prediction is based on discovering similar user profiles. For instance, if two individuals give the same rates to some products, the organisation will deduce that both of them have similar preferences and would suggest the same services or products to both users. Regarding the other prediction technique, websites can recommend products to customers that are related to the ones they purchased previously. This technique is frequently used by Amazon.com which sends emails to customers, proposing them for instance, books to buy in the future with a theme or subject related to the one they bought before.

2.2.3 The process of personalisation

When dealing with Personalisation process, it is first important to relate it to the Targeting strategy which is a significant tool in order to seek customer’s requirements. E-commerce technology permits personalisation to an extent that was unthinkable in tradi-tional offline markets. Online merchants are able to gather more information about their customers and use this information more effectively than ever before. The Internet allows merchants to segment down to the level of the individual. Rich, personalised messages can be used to target an endless number of customer subgroups and precisely fit their needs and wants. This so-called ad-targeting is also the foundation of new information asymmetry and price discrimination whose principle is explained further on in the section 2.4 on “Gathering and using personal information”. It is argued that in general e-commerce tech-nology and online markets succeeded in reducing information asymmetry for all parties in-volved. It is much easier for customers to find information about merchants and products and to compare different offers in online markets.

Vesanen and Raulas (2006) have been studying the concept of personalisation and summa-rized its process/steps through the following model (Figure 2.5). This schema aims to show the different steps of personalisation.

Figure 2.5 - The process of personalisation, Vesanen and Raulas (2006)

The first step consists of interacting with the customer in order to fulfil the user data col-lection; after that, the processing step intends to study customers’ data (segmentation,

(17)

tar-geting, data removal, etc.) with the purpose of categorising the users through profiles and subsequently, personalise the website content to the customer needs (cf. marketing output). The final step of the personalisation process resides in delivering a personalised e-advertising, homepage contents, and so forth that matches customers’ requirements and expectations. Finally, personalisation can be processed within each of the 4P’s: Promotion, Price, Product, and Place. Within this thesis, it is important to notice that we are only fo-cusing on one of the 4P’s: Promotion and not the other variables.

2.2.4 Values, benefits and costs for customers and marketers

As mentioned in the problem discussion above, personalisation creates benefits as well as costs for both, customer and marketer. The true value then accrues from the margin be-tween these benefits and costs. Vesanen (2007) presents an overall picture of personalisa-tion from different perspectives when he summarises the benefits and costs for both par-ties involved in the model shown in Figure 2.6.

Figure 2.6 - The benefits and costs of personalisation for the customer and the marketer, (Vesanen, 2007)

From the customer side, the benefits include improvements in products, service, commu-nication, preference match, and the experience of one which are related to the marketing output which can be found in the centre of the model. Privacy risks, spam risks, spent time, additional fees, waiting time and limited choice (Haugtvedt et al., 2005) are among the costs that personalisation brings to the customer. From the perspective of the marketer, higher prices, better response rates, customer loyalty and satisfaction as well as differentiation from competitors are benefits resulting from personalisation. Among the costs for market-ers are investments in technology and education, brand conflict and the risk of irritating customers. Personalisation creates value for customers or marketers when their respective benefits exceed their costs. When relating the model to the purpose of this study, the facili-tation of the purchase decision represents a benefit for the customer comparable to the better service mentioned in the model whereas the danger for privacy or privacy risk

(18)

repre-sents a cost. From the marketer’s perspective, the facilitation of the purchase decision can lead to the benefit of increased customer satisfaction and loyalty while privacy risk is re-lated to the risk of irritating customers (Vesanen, 2007).

In this section, we first differentiated the term “Personalisation” from “Customisation” by looking at other researchers’ approaches and theories. It still seems though that both terms are closely related to each other. In this thesis only the term Personalisation is used to relate to companies’ efforts to adapt e-ads to their customers. In the second part, an outline of different Personalisation systems that companies use to adapt ads to their customers was given. Secondly, we illustrated the process of personalisation consisting of first targeting customers in order to find the right ad which would fit to its requirements, then collecting data and fulfilling personalised ad to each consumer profile. Finally, it has been shown that E-Advertisement could create value and benefits for the customer and the marketer but also involve non-negligible costs which can balance the value for the customer and risk for the customer not to purchase. Danger for Privacy is one of the most significant risks for customers, which could make them refuse to purchase a good if they do not feel at ease with a website or are not willing to reveal certain confidential information. The concern for Privacy is explained in more detail in the following section.

2.3

E-Privacy

“You do a survey and consumers say they are very concerned

about their privacy. Then you offer them a discount on a book

and they’ll tell you everything.”

(Esther Dyson, 2002)2

In the purpose of the study two different concepts were broached, personalisation and pri-vacy. The first issue was widely discussed in the previous parts; privacy is the matter that is touched upon in the following section. Initially, the definition and main attributes of the privacy are described, further ways of gathering and using personal data are presented and finally, model of fare information flow is explained.

Originally the Internet or World Wide Web was a mean of sharing and exchanging of in-formation between different parties but nowadays it becomes more of a tool for providing services such as e-commerce, e-education or e-entertainment. It is mostly regarded as a positive force as it can facilitate the purchasing process, obliterate the borders between countries and make it possible for each customer to get individualised and unique goods. Consumers can easily compare the prices and quality of goods with the help of various de-vices available on the Internet. From one hand, it enhances the power and choice of the customer, but from the other, it is a threat to their privacy (Edwards, 2003).

The term privacy is mostly defined as the right to act freely and keep thoughts and beliefs to be private from others, and in the era of changing technologies and innovations, in the era of Internet, more and more people are concerned about e-privacy. “E-privacy is an in-dividual’s right to act freely online without being monitored, traced, restricted, and to keep their personal identifiable information (PII) from being collected or distributed to other parties without their consent” (Shata, 2006).

(19)

Individuals always aim at controlling the image they convey to others while at the same time they try to gather as much information as possible about their environment including other individuals. The combination of vastness of reach, immediacy and interactivity on the Internet differentiates those online privacy issues from the ones that can be found in the offline world. Harkiolakis (2007) introduces a six-dimensional approach to online privacy as a way of creating harmony between the parties involved in the privacy issue (Figure 2.7). In order for harmony to be established there needs to be a clear understanding by all par-ties involved of the information details that is exchanged as well as the way the information will be processed. Harkiolakis addresses all possible questions that might arise concerning information exchange using six interrogatives of the English language and a diamond shaped construct that represents an ‘Information Privacy Unit’ (IPU). The interrogatives What, Where, Who and When are grouped together because they all describe the physical data of the information which is exchanged. These four dimensions form the foundation of the six-dimensional diamond. The questions How and Why play a special role in this model due to the fact that they do not describe the physical data but instead the process and pur-pose of the information exchange respectively. In order to show their distinctive role, How and Why are placed on the tips of the diamond used in this model.

Figure 2.7 - Dimensions of information privacy (recreated after Harkiolakis, 2007)

In an ideal situation, the diamond shaped IPUs of the parties involved, for example the one of the Internet user and the one of the website owners, are perfectly aligned. The alignment indicates that both parties have a common understanding of the information exchange and agree on What information is used Where, When, Why, How and by Whom. In case of misunderstandings or misinterpretations between the interacting parties a privacy issue arises and differences in one or more dimensions of the IPU can be observed. The differ-ences lead to a misalignment in one or more dimensions of the diamond shaped model. As an example of such a misalignment, a disagreement in the ‘Who’ dimension can be consid-ered. If, for example, users believe that they provide their personal information only to the website requesting the data while the website passes the data on to their affiliates, the two parties have a different perception of Who uses the personal information. In the model, this will result in a misalignment in the Who dimension, where the websites Who dimen-sion will be represented by a longer line than that of the user. The resulting diamond shaped IPUs of the two parties are not aligned anymore because the Who dimensions dif-fer. Naturally, misalignments can also arise in any of the other dimensions or even in sev-eral dimensions at once. The six-dimensional approach succeeds in structuring all possible questions that might arise concerning privacy issues. Nevertheless caution is required since the approach is based on the assumption that individuals are able to understand and put into effect their choices with regard to their personal data (Harkiolakis, 2007).

(20)

2.4 Gathering and using personal information

The following paragraphs explain how personal information can be collected and used by websites. In addition, the origin of privacy concerns and violation, as mentioned in the purpose, is explained in this part. In the end, the Fair Information Practice Principles are introduced which can companies to prevent such privacy issues from arising.

Different ways of PII information mining can be used by companies. Two categories exist: visible collected data and invisible collected data. The first type is the information that users consciously reveal in particular transactions, that can be some site registration forms or questionnaires that the user can fill in exchange for a free software or a discount. This in-formation is transparent in its collection but consumers are mostly unaware of the way it will be subsequently used (Edwards, 2003). Some organizations use various types of unau-thorized software to track the users of the e-service; the most popular are spy-ware, ad-ware, cookies and online activities trackers. This can be called invisible data collection as in most cases the customers are not aware of their existence. It is questionable to what extent it is ethical and legal to use this type of gathered information. However, some companies claim that they use PII and track the process of surfing the web-sites only for improving the customer service and make new and better suggestions for solving the customer’s prob-lems (O. Shata, 2006).

Many websites collect information about their customers and create profiles. Two different types of profiling exist: anonymous and personal, the difference is in the amount of data collected on the person (Laudon & Traver, 2007). Such profiles help companies like Dou-bleClick to target personalised advertisements to particular customers as they surf on the Internet. But the combination of information from Internet profiles and “real world” cus-tomer information can bring not only an enormous value to the e-commerce companies but an increase in the risk to the privacy of users (Edwards, 2003). That is why nowadays there are a lot of debates concerning the announcement of Google.com about their inten-tion to buy DoubleClick. Many people worry about the amount of informainten-tion that was separated previously but after merging it can make Google.com a “Big Brother” of the Internet. However, the Google.com spokesman said, “In terms of privacy, we have clear and stringent guidelines about what we do and don't do with user data, and would never do anything to undermine the confidence of web users” (Brooks, 2007).

There are various advantages and disadvantages for the consumer to disclose personal in-formation. The main advantage is that the purchasing process becomes easier, more per-sonalised and efficient. A good example is how Amazon.com uses the previously collected data. It gives the consumers advices about the new items for sale of possible interest based on the information from the previous purchases. It also facilitates the process of filling the information form and combines the orders to save postage (L. Edwards, 2003). However, organizations and individuals providing and using e-services become subject to many po-tential risks and inequalities between them (Shata, 2006). Indeed, for instance, merchants in online markets have deeper knowledge about their customers which makes it possible for them to charge customers different prices for the same products or services. This price dis-crimination represents a new type of information asymmetry. However, there are no exist-ing regulations or laws that can rule the merchants’ behaviour and nowadays, only ethicality of the company can determine to what extent customers’ information will be misused and what criteria are used in market segmentation (Radin, 2007; Rozario, 2005).

Different types of threats exist that are relevant to the Internet. The most common ones are unauthorized intrusion and collection of IP addresses or coping/stealing information. In this paper we want to concentrate more on violating the privacy of e-service users. Shata

(21)

(2006) distinguishes two types of violation. The reason for the first one is that it can be-come harmful software that collects sensitive information in order to steal or destroy it. The second type of violation is collection of some PII and using it in an inappropriate way or sharing it with the third party. Here arises the clash of opinions between organizations and users of the service. The former see Internet as a public environment and in those who join it should expect to be noticed. The users of the service consider their PII as private and belonging to them and they see revelation of their private information as unauthorized intrusion (Shata, 2006). A good example for this situation can be the FaceBook fiasco. In November 2007 FaceBook.com signed a contract with very well known and popular sites such as Blockbuster, eBay, Coca-Cola, Overstock.com and others. With the help of a Bea-con the information about purchases on these websites could be immediately published in the “mini-feed” section on FaceBook. Most users of this network were unsatisfied with re-vealing their private information as it could damage their image or spoil the surprise for their friends (H. McCracken, 2008).

Information that the company gathers is mostly regarded as a valuable asset but at the same time it can also be a source of delicate legal difficulty, especially in the cases concerning in-dividual privacy. While information increases in value, there arises the necessity in legal re-gime protecting the individual data which balance the individuals, commerce and society at-titudes towards this matter. Personal data can be protected by different laws as intellectual property, trespass to persons, and the interception of communications, however, none of these laws can fully protect the individual right to privacy (Reed C. & Angel J., 2007) Thus, the idea of protecting customer privacy arises and makes critical the fairness of data collection. Adequate protections of personal data as well as satisfactory flow of information are prerequisites for the establishment and maintenance of trust-based online relationships between firms and customers. These relationships then form the basis for customer loyalty. The Federal Trade Commission (FTC) has recognized five factors that are combined in the “Fair Information Practice Principles”: 1. Notice/Awareness, 2. Choice/Consent, 3. Ac-cess/Participation, 4. Integrity/Security, and 5. Enforcement/Redress (Figure 2.8). These factors affect both, the firm and the stakeholder or customer at various stages of the in-formation flow process. The model names Creation/Exchange, Collection/Use, and Viola-tion/Misuse as the main stages of the process (Radin et al., 2007).

Figure 2.8 - FTC’s Fair Information Practice Principles and the Flow of Online Information (Radin et al., 2007).

In the first stage, Creation/Exchange, information is created through direct or indirect key-strokes like typing in personal data or making certain choices on a visited website. The

(22)

main concern in this stage is the extent to which the firm gives notice about the personal information that is collected and the degree to which the customer is aware of this process. In the second stage, the concepts of choice, consent, access and participation are empha-sized. They refer to the ability of users to decide how their personal information is used by firms and whether it is shared with third parties. Allowing the user to participate in the process of data collection and use increases the fairness of information practices. Further, firms should preserve integrity of data and provide sufficient security for users. The third stage is concerned with enforcing compliance on firms and giving users the opportunity to seek redress in case of misuse of personal data. With regard to this study, fair information use and notice about data collection decreases the danger for privacy for the customer (Radin et al., 2007).

In summary, it can be said that in order to cope with the lack of security online and fulfil trust from e-consumers, companies need to study customers’ behaviours online and the process of purchase decision in more detail (e.g. where they are looking for information, how do they decide to buy online, etc.). If so, they could prevent some restraints from Internet users to purchase and build up trust and loyalty. The next section is specifically dealing with this subject giving an overview of customer’s attitudes and their process of purchase decision online.

2.5 Online consumer behaviour

According to the purpose of this thesis, personalisation and privacy issues should not be examined in isolation. Instead, the influence of these two matters on the purchasing deci-sion is subject of this study. Therefore, customer attitudes towards Internet advertising are discussed in the following before a model of online consumer behaviour is introduced. In the end of this part, the different types of online advertisements that were mentioned above are related to the steps of the buyer decision process to demonstrate how personal-ised advertisements can influence each step of this process.

2.5.1 Customer attitudes towards Internet Advertising

Consumer’s attitude towards advertising is likely to influence their exposure, attention and reaction to advertisements and is therefore worth analysing. Schlosser et al. (1999) com-pared users’ attitudes to Internet advertisements (IA) to those attitudes concerning adver-tising in general (GA) and found that online advertisements are perceived as less intrusive than offline advertisements. Respondents are approximately equally divided between liking IA (38%), disliking IA (35%) and feeling neutral towards IA (28%). Nevertheless more than 50% perceive IA as informative, not insulting, and trustworthy. The authors found that trust contributed only to a small percentage to the overall attitude toward IA and ex-plain this phenomenon by the fact that trust is already included in the behavioural utility of advertising, the use of an ad to make a purchasing decision. The “pull” nature of IA and the user’s control over advertising exposure could explain why users feel less indignant and why they judge IA as being more trustworthy compared to GA. (Schlosser et al., 1999). However, the personalisation of online advertisements raises a number of privacy issues as illustrated above.

2.5.2 A model of online consumer purchase decision and its process

Regarding the consumer purchasing decision process, it appears important to deal with the external and internal factors acting on the customer choice. Laudon and Traver (2007) ex-tended the general model of consumer behaviour by Kotler and Armstrong to better suit the online environment. The purchase decision in the resulting model of online consumer behaviour is shaped by the culture, social norms, psychological factors as well as

(23)

back-ground demographic factors (Figure 2.9). In addition there are a number of intervening fac-tors which influence the consumer's clickstream behaviour and finally lead to a purchase. Although privacy and personalisation are not specifically mentioned in this model they are nevertheless included in the intervening factors and could be seen as a restraint for the cus-tomer to buy on the Internet. Personalisation is very closely related to the marketing com-munications stimuli which can be personalised to better suit the targeted customer. Person-alised advertising also influences the brand awareness of customers. Privacy issues can be categorized under the heading of perceived behavioural control since the customer’s per-ceived control over their personal information influences their purchasing decision im-mensely. Privacy issues can also play a role in creating attitudes towards purchasing online (Laudon & Traver, 2007).

Figure 2.9 - Model of Online Consumer Behaviour (Laudon & Traver, 2007)

Apart from individual attitudes and external factors that have been described previously, it is also important to know how buyers make purchasing decisions and how the Internet in-fluences this process. The consumer decision process introduced by Kotler and Armstrong (2008) consists of the following five stages: need recognition, information search, evalua-tion of alternatives, purchase decision and post purchase behaviour. The different types of online advertising, which were presented above, support and influence the different stage of the process (Figure 2.10). Each step requires specific types of marketing communica-tions which can be personalised to fit the individual customer’s needs (Laudon & Traver, 2007). In the first stage the buyer recognizes a need which was triggered by internal or ex-ternal stimuli. In the next stage, buyers are aroused to find more information related to their recognized need. This information search can take place actively or result in an in-creased attentiveness to information concerning the area of interest, for example adver-tisements. In the evaluation of alternatives stage, the buyer uses the information collected previously to compare different alternatives in the choice set and create a purchasing inten-tion. It is important for marketers to investigate which criteria buyers use to evaluate alter-natives. The last steps in the process are the actual purchase and the post purchase behav-iour. In the latter stage, buyers acts according to their satisfaction or dissatisfaction and the degree to which perceived performance matched the consumer’s expectations. The larger the gap between the two, the greater is the dissatisfaction (Kotler & Armstrong 2008).

(24)

Figure 2.10 - Online and Offline Communications in the buyer decision process (Laudon & Traver, 2007)

2.6 Research Questions

From the theoretical framework presented above, we developed three research questions which narrow down the purpose of this thesis. The research questions in this study are:

1. How do different aspects of personalised advertising influence the Internet user’s concerns for privacy?

2. How can Internet users’ awareness of data collection influence their purchasing de-cision?

3. To what extent are personalised e-ads perceived as helpful for the purchasing deci-sion?

Empirical findings are used in the results and analysis section of this research study to an-swer these research questions.

(25)

3 Method

This Chapter describes the methods selected to collect and analyse empirical data in order to fulfil the pur-pose and answer the research questions.

3.1 Research approach

There exist two main different ways of researching: the deductive or inductive approach. Both describe the relationship between research and theory. In the deductive approach (see figure 3.1 below), research is conducted based on the ideas inferred from theory whereas in the inductive approach, theory is generated based on research. Concerning this study, a deduc-tive approach is applied by using theory as a basis in order to explain the empirical data that are collected.Deductive approach is very linear; each step follows the previous and con-tributes to the theory testing. A deductive approach is used when collecting the quantitative

data and evaluating the positive and negative sides of personalisation (Bryman & Bell, 2007).

Figure 3.1 - The process of deduction, (Bryman & Bell, 2007)

Within the thesis we do not formulate hypotheses, we state research questions and there-fore the process of deduction is changing. In the first step we overview the previous stud-ies and researches that were conducted concerning the personalisation of the e-advertising and privacy issues in the Internet. In the second stage, we state our research questions re-garding the linkage between personalisation and concerns for privacy, and influence of both issues on the purchasing decision. The next step is data collection and conducting of the survey. After that the gathered information is analysed and conclusions concerning the research questions are drawn. In the final stage, the findings and managerial implications are presented together with conclusions.

3.2 Research strategy: quantitative vs. qualitative

When collecting empirical data, there are two different types of research strategies that can be applied: quantitative or qualitative research. Quantitative research relies on the analysis of numbers and is driven by the ideas of the researcher whereas qualitative research is more un-structured, it focuses on the analysis of words and is driven by the participants.

The main aim of qualitative data analysis is to provide the description of the phenomenon, build a theory and after that test it. The main advantage of this method is the ability for the

(26)

researcher to discover new variables and relationships, to disclose and comprehend com-plex processes, and to describe the influence of the social context (Shah S.K. & Corley K.G., 2006).

The main aim of the quantitative research strategy is to collect data from different sponses and subsequently measure their response. The main issues of the quantitative re-search strategy are the use of formal measurement, the use of many observations, and the use of statistical analysis techniques. Quantitative analysis gives the statistically approved evidences concerning the phenomenon or the relation between several variables, well de-fined analysis tools make research easier to communicate. This method of strategy in terms of generalisability and objectivity is always superior to a qualitative approach. However, at the same time several disadvantages exist associated with the quantitative research. First of all, even if this approach is considered to be objective, still a lot of subjectivity is involved. Moreover, the uncertainty of the relevance of the research findings and theoretical con-cepts can be considered as a drawback of the quantitative method. And in comparison with the qualitative research it does not give the deep understanding of the phenomenon and in-formation is more standardised (Davidsson P., 1997).

It was decided to conduct a quantitative research to evaluate to what degree E-personalisation could be intrusive into customers’ privacy or helpful for the customer, and how both these issues affect the purchasing decision. This was done by interviewing JIBS student through surveys. As we needed to estimate opinions from many interviewees, it appeared that a quantitative research was the best alternative compared to qualitative re-search. Data can then be analysed statistically in order to answer the research questions. The survey addresses all issues mentioned in the purpose and the research questions. Fur-ther, it aims to analyse the relationship between personalisation, privacy concerns and the purchasing decision as stated in the purpose and it also considers the issues of awareness of personalised e-advertisements and the factors influencing the customer’s privacy concern according to the research questions.

3.2.1 Methods of data collection

When conducting a research, there are two different types of data that could be collected: Primary and Secondary data. Both can be independent or complementary. The secondary data already exists and has been collected before, not particularly for the same purpose (articles, books, data basis, etc.). A special type of secondary data is verbal data, in order to analyse this data a content analysis is used. The primary data are those collected specifically for re-search from the examined sample or population. Data collection procedures that are used to generate primary data are surveys or experiments. Concerning this study, the empirical data collected are primary data (Davidsson P., 1997).

In our research we use a survey in order to collect the empirical data. The main purpose of surveys is to provide information about the views of people and their motives and evalua-tions of social phenomena. As these views, motives and phenomena are objects of the re-search, surveys give the necessary information about them. The significance of surveys is growing, if there is no sufficient documented information about phenomenon and if it is not accessible by direct observation or experiment. In such situations, a survey could be-come a major method of gathering information. Data collected from the survey are subjec-tive views of the respondents; they should be compared with objecsubjec-tive information gath-ered by other researches to be more relevant and trustworthy. There are a variety of meth-ods for survey data collection. The most common is questionnaire but it can also be inter-views, postal, telephone, fax, and other expert surveys. A survey should be preceded by the development of a research program, a clear definition of goals, objectives, concepts

Figure

Figure 2.1 - Theoretical Structure (own model)
Figure 2.2 - E-Marketing Mix (Karlyanam & McIntyre, 2002)
Figure 2.3 - Example of adaptive personalisation (yahoo.com homepage, 2008)
Figure 2.4 - Example of transparent personalisation, (Amazon.com homepage, 2008)
+7

References

Related documents

En ledare såg till allas bästa intresse (Håkanson et al., 2014; Stanley, 2006) och uppfyllde en roll som ombud (Villarruel & Peragallo, 2004) genom att lyssna på synpunkter

Cite this article as: Carlfjord et al.: Key factors influencing adoption of an innovation in primary health care: a qualitative study based on

[r]

‘’I hesitate to Shop online as there is a high risk of receiving malfunctioning merchandiser’’ as can be seen from table 3, in appendix 2, 20% respondents

This dissertation describes influences on the occupational aspirations and attainments of non-Western, non-European immigrants’ descendants, from their own perspective.

Nonetheless, the results reveal that the immigrant heritage of the descendants of immigrants influences their views on labour market participation, perceptions of gender norms, and

Det behöver således inte innebära att en scen leder till att publiken tror att det ska vara på detta sätt för att man som kvinna ska vara lycklig eller lyckad.. Marnie:

Men då siffrorna för matsvinnet har ökat hos restaurangerna och skolbespisningarna (SMED, 2018) finns det fortfarande mycket som går att göra i detta motarbete Att belysa och