Master Thesis

Brand Equity for E-recruitment companies

A quantitative research on individuals’ intention to

use e-recruitment websites

Authors: Mathias Guselin, Joakim

Jörgensen, Sebastian Johansson

Supervisor: Setayesh Sattari

Examiner: Anders Pehrsson

Date: 2016-05-27

Subject: Marketing

Level: Graduate Level

Course code: 4FE15E

II

III

Acknowledgements

This master thesis was conducted in the spring semester 2016. The thesis aimed to contribute

to the understanding of the determinants of brand equity of e-recruitment websites and how

they affect individuals’ intention to use such websites. Conducting the thesis has been a great

challenge, however the execution was dependent on support and feedback from several

individuals. Therefore, we would like to take this moment to show our gratefulness towards

these individuals.

We would like to express our gratefulness to our tutor, Dr. Setayesh Sattari, who has provided

us with valuable feedback and expertise during the whole process; we admire your

helpfulness and commitment. Also, we would like to thank our examiner, Prof. Anders

Pehrsson, who made it possible for us to improve the thesis by providing us with valuable

feedback and guidelines. Furthermore, we also would like to show our gratefulness to the

individuals that answered the online questionnaire. Finally, we would like to thank our

opponents and fellow students for giving us valuable feedback and recommendation during

the whole process of this thesis.

Växjö 2016-05-27

Mathias Guselin Joakim Jörgensen Sebastian Johansson

IV

Abstract

Course/Level: 4FE15E/ Graduate Level

Authors: Mathias Guselin, Joakim Jörgensen, Sebastian Johansson

Tutor: Dr. Setayesh Sattari

Examiner: Prof. Anders Pehrsson

Background: Internet has brought radical changes in the recruitment industry where

individuals are increasingly turning to the Internet when seeking jobs. The

increased use of e-recruitment is partly because it is considered to be the

most effective way to reach the target group of applicants, and partly

because of the cost savings and competitive pressure in the market.

Therefore, is the brand a crucial factor for online companies such as e-

recruitment websites thus having a strong brand can lead to competitive

advantage in the market. The role of branding in e-marketing is increasingly

getting more important. Previous research has used intention to purchase as

an outcome of brand equity. However, this research studies brand equity

towards intention to use as most e-recruitment websites offer free services.

Purpose: To describe the determinants of brand equity of e-recruitment websites and

how they affect individuals’ intention to use such websites.

Methodology: A quantitative research was chosen to collect the data using an online

questionnaire to be able to describe the variables relationship in this

research.

Conclusion: The findings of this research suggests that brand equity as a whole increases

individuals’ intention to use an e-recruitment website. The determinant of

brand equity; brand awareness, perceived quality and brand loyalty gave a

positive and significant relationship towards individuals’ intention to use.

The findings involving the moderator were found to be significant when

using brand equity as whole, while being rejected when involving the

determinants of brand equity.

Keywords: Brand equity, Brand awareness, Brand association, Perceived quality, Brand

loyalty, Intention to use, E-recruitment

V

Table of content

1. Introduction .......................................................................................................................... 1

1.1 Background ..................................................................................................................... 1

1.2 Problem Discussion ........................................................................................................ 2

1.3 Purpose ............................................................................................................................ 4

1.4 Research Questions ........................................................................................................ 4

1.5 Outline of The Paper ...................................................................................................... 4

2. Theoretical Framework ....................................................................................................... 5

2.1 Brand Equity .................................................................................................................. 5

2.1.1 Service Brand Equity ................................................................................................ 6

2.1.2 Online Service Brad Equity ....................................................................................... 6

2.2 Brand Awareness ............................................................................................................ 7

2.3 Brand Association .......................................................................................................... 8

2.4 Perceived Quality ........................................................................................................... 9

2.5 Brand Loyalty ................................................................................................................. 9

2.6 Intention to Use ............................................................................................................. 10

2.7 Hypothesis Formulation .............................................................................................. 11

3. Conceptual Framework ..................................................................................................... 13

3.1 Research Model ............................................................................................................ 13

4. Methodology ....................................................................................................................... 15

4.1 Research Approach and Research Design ................................................................. 15

4.2 Data Sources ................................................................................................................. 15

4.3 Data Collection Method ............................................................................................... 15

4.4 Operationalization and Data Collection Instrument ................................................ 16

4.5 Pre-test ........................................................................................................................... 17

4.6 Sample ........................................................................................................................... 18

4.7 Data Analysis Method .................................................................................................. 18

4.8 Quality Criteria ............................................................................................................ 20

4.8.1 Validity .................................................................................................................... 20

4.8.2 Reliability ................................................................................................................ 21

4.8.3 Quality Data Control ............................................................................................... 21

4.9 Methodology Summary ................................................................................................ 22

VI

5. Results ................................................................................................................................. 23

5.1 Descriptive Statistics .................................................................................................... 23

5.3 Hypothesis Testing ....................................................................................................... 25

5.4 Moderated Regression Analysis .................................................................................. 27

5.5 Summary of Hypothesis Testing ................................................................................. 31

6. Discussion ............................................................................................................................ 32

6.1 Brand Equity ................................................................................................................ 32

6.2 The Determinants of Brand Equity ............................................................................ 32

6.2.1 Brand Awareness ..................................................................................................... 32

6.2.2 Brand Association ................................................................................................... 33

6.2.3 Perceived Quality .................................................................................................... 34

6.2.4 Brand Loyalty .......................................................................................................... 34

6.3 Moderating Effect ........................................................................................................ 35

7. Conclusion ........................................................................................................................... 36

8. Research Implications ........................................................................................................ 37

8.1 Theoretical Implications .............................................................................................. 37

8.2 Managerial Implications .............................................................................................. 37

8.3 Limitations and Future Research ............................................................................... 38

List of References ................................................................................................................... 39

Appendix 1 - Descriptive of the constructs items ................................................................ 47

Appendix 2 – Online Questionnaire ..................................................................................... 48

1

1. Introduction

This chapter provides an introduction of e-recruitment and brand equity. The chapter also

includes a problem discussion that problematizes the area and importance of brand equity for

e-recruitment companies, which leads to the purpose of the study.

1.1 Background

The way individuals gather information and resources on the Internet has been revolutionized

due to the rise of globalization (Selden & Orenstein, 2011). The increased role of Internet and

the number of individuals using it has developed new markets and in line with this, businesses

have moved to the online environment (Ngai & Gunasekaran 2007; Rafiq et al., 2013). In

accordance with this, Internet has brought radical changes in the recruitment industry where

individuals are increasingly turning to the Internet when seeking jobs. At the same time,

companies use commercial recruiting websites seeking for qualified applicants to conduct

their recruiting procedure online (Singh & Narang, 2008; Sylva et al., 2009; Selden &

Orenstein, 2011). This phenomenon is called e-recruitment, which is defined as “...a hiring

process that utilizes a variety of electronic means and technologies with the primary purpose

of identifying, attracting, and selecting potential employees” (Lee, 2011, pp. 231). The

increased use of e-recruitment is partly because it is considered to be the most effective way

to reach the target group of applicants, and partly because of the cost savings and competitive

pressure in the market (Pfieffelmann et al., 2010; Thielsch et al., 2012). Firms that manage to

recruit the most qualified individuals have higher potential to get a better position in the

market (Thielsch et al., 2012). Accordingly, research shows that e-recruitment websites can

play a crucial role in determining if companies attract qualified applicants (Allen et al., 2007;

Dineen et al., 2007). In line with the advance of the technology within the e-recruitment

business, new features and modern systems has been created to achieve strategic advantage

within the market (Lee, 2007).

The brand is a crucial factor for online companies such as e-recruitment websites and having

a strong brand can lead to competitive advantage in the market (Christodoulides et al., 2006;

Kim and Hyun, 2011). In order to measure how strong a brand is the concept brand equity is

used (Rios & Riquelme, 2010). Brand equity is defined by Aaker (1991, p. 15) as “...a set of

assets and liabilities linked to a brand, its name and symbol, that add to or subtract from the

value provided by a product or service to a firm and/or that firm’s customers”. Previous

2

research suggests that there are two different perspectives of brand equity, which are;

consumer-based brand equity, focusing on the consumer's perception of the brand and firm-

based brand equity, focusing on the financial value to the brand asset (Simon & Sullivan,

1993; Christodoulides et al., 2015). However, most marketing research regarding brand equity

has focused on consumer-based brand equity (Aaker, 1991; Keller, 1993).

1.2 Problem Discussion

The number of Internet users around the world is steadily increasing and this has created an

opportunity for companies to conduct their business transactions online (Japhet & Usman,

2010). However, this has resulted in a highly competitive marketplace for online companies

to be in (Zhilin et al., 2004). A big challenge for online companies is that customers now with

the use of Internet seek, evaluate and compare information about products and services by

themselves (Kucuk & Krishnamurthy, 2007; Chen, 2001). Bhatti et al. (2000) explains that

because the customer can gather their own information on the Internet and that there exist

many brands that offer the same type of service and products on their websites, is it difficult

for online companies to retain and attract customers to their specific website. Therefore, it has

become important for online companies to differentiate their brand from the competitors since

a brand is vital for a company to be successful (Kim et al., 2002). Differentiating a brand

against competitors can be a difficult task due to the fact that the services or products that are

offered can be identical between different brands (Kim et al., 2002). However, brand equity

can function as a powerful differentiator for companies and as a decision making tool for

individuals (Aaker, 1991; Aaker, 1996; Keller & Lehmann, 2006; Keller, 2013). Researchers

have focused attention to this as they have realized that building strong brand equity can give

a competitive advantage in the form of being the brand that gives the customer most value

(Biedenbach et al., 2015).

Most of the research conducted concerning brand equity has focused on traditional firms, and

little on how it affects online companies (Christodoulides & de Chernatony, 2010; Rios &

Riquelme, 2008). This is in accordance with Alwi and Ismail (2013) given the increasing

number of Internet users around the world, the role of branding in e-marketing is increasingly

getting more important, still it is scarce attempts to measure brand equity in an online context.

Rios and Riquelme (2008) explains that online companies need to think of brand equity in a

different way since an online business context can differ from an offline business context as

consumers may experience a brand differently when interacting with technology rather than

3

with people as it is intangible. Therefore, it is important for online companies through their

websites to know what factors the consumers value the most in order to attract and

differentiate themselves from the crowd (Hong-Youl, 2004). Especially, this has become a

challenge for e-recruitment websites as it is one of the most widely practiced e-business areas

(Lee, 2011) and the online service those companies provide for the users are similar (Kim et

al., 2002). Hence, brand equity for these types of companies is a good measurement as it

explains the added value for a brand, which a customer would evaluate his or hers preferences

on which website to use (Aaker, 1991; Keller, 2003).

Brand equity can be seen as a vital factor for being able to be associated with good

performance in the customer’s mind, thereby the companies should focus to look on what the

customers base their values on, to strengthen customer loyalty and relationships in order to

optimise pricing (Aaker, 1991). In the branding literature, consumer-based brand equity is

traditionally recognized with four different determinants; brand awareness, brand association,

perceived quality and brand loyalty (Aaker, 1996; Biedenbach et al., 2015; Cobb-Walgren et

al., 1995; Yoo & Donthu, 2001). According to Christodoulides et al. (2015) one of the most

recognized and adopted model of consumer-based brand equity stems from Aaker (1991).

Aaker (1991) argues that brand equity can be seen as a set of assets that is conceptualized into

multidimensional concepts, which are the determinants mentioned above. Previous research

has used intention to purchase as an outcome of brand equity (Agarwal & Rao, 1996; Cobb-

Walgren et al., 1995). However, in this study, intention to purchase is referred to as intention

to use as most e-recruitment websites offer free service in which the users do not actually

purchase anything (Galanaki, 2002). In the context of e-commerce, previous research shows

that individuals’ earlier experience with a website and fulfillment of the service delivery has

an influence on individuals’ intention to use the website in the future (Cho, 2015; Chen et al.,

2009; Wang et al., 2006). Therefore, in this study brand equity and its determinants will be

used to measure individuals’ intention to use e-recruitment websites, since it is important to

understand how the brand value is formed in the mind of the users and how it translates into

choice behavior in the future (Cobb-Walgren et al., 1995). Research in the e-recruitment area

is still called for since it has not been widely explored (Lee, 2011). By combining the lack of

research regarding how brand equity and its determinants affects online service companies

(Agiwal, 2013) and the research on e-recruitment businesses (Lee, 2011) will this study try to

fill this gap.

4

1.3 Purpose

The purpose of this study is to examine the determinants of brand equity of e-recruitment

websites and how they affect individuals’ intention to use such websites.

1.4 Research Questions

How are brand equity and its determinants related to individuals’ intention to use e-

recruitment websites?

How does the relationship of brand equity and its determinants to individuals’

intention to use e-recruitment websites change if individuals have acquired a job via

an e-recruitment website?

1.5 Outline of The Paper

Chapter 2 presents existing theory that has been utilized for this research and ends with the

formulations of hypotheses. In chapter 3 a conceptual framework is presented with a

conceptual model. Further, chapter 4 explains how the research was conducted and presents

different methodology sections of how the researchers have followed through this research.

Chapter 5 presents the results from the data collection, which further is discussed in chapter 6.

Chapter 7 presents a conclusion, where the purpose of the study is answered and finally

chapter 8 brings up theoretical and managerial implications, limitations and future research.

5

2. Theoretical Framework

This chapter presents existing theory that has been utilized for this study. The theory consists

of the following parts; Brand equity, brand awareness, brand association, perceived quality,

brand loyalty and intention to use. To finalize the chapter, the formulations of hypotheses are

presented.

2.1 Brand Equity

A brand is a name and a symbol that is unique to the producer, which identifies the services or

products of the producer. The brand signals the source of the product and distinguishes it from

other competitors (Aaker, 1991). Having loyal customers for a company is essential to

maintain a good customer base of returning customers since they are willing to pay more and

are also less costly to serve (Zhang et al., 2014). Thus, showing commitment to customers and

establish a satisfied customer base is a valuable asset which far exceeds the value of a single

transaction as the values of a lifetime customer and the customers’ opinions will bring more

business in future periods (Ambler, 1994; Shugan, 2005). In order to measure a brand’s value,

the term brand equity is used (Aaker, 1991). The most common definition of what brand

equity conceptualizes is the added value to the product or service once the brand is presented

(Farquhar, 1989; Aaker, 1991; Park & Srinivasan, 1994; Keller, 1993). A product offers a

functional benefit, but the brand asset enhances its value beyond its functional use (Farquhar,

1989). There are two perspectives of brand equity, firm-based brand equity and customer-

based brand equity. For firms, strong brand equity increases cash flow to the company and

have even been accountable as an intangible financial value on firm’s balance sheets

(Christodoulides & de Chernatony, 2010; Simon & Sullivan, 1993; Pike et al., 2010). The

benefit of strong customer-based brand equity is how customer values one product over the

other despite the same product utility, due to the favorable brand association the customers

holds in mind towards the brand or trademark (Keller, 2003). Consumer-based brand equity is

accepted to many being measured in four key constructs, which is brand awareness, brand

association, perceived quality, brand loyalty (Aaker, 1996; Yoo et al., 2000; Pike et al., 2010;

Kim & Hyun, 2011; Buil et al., 2013).

6

2.1.1 Service Brand Equity

Brands play an important role to customers when buying or selecting between different

services, since the brand can help the customer to better visualize and understand the service

before a purchase (Berry, 2000). Services lack tangibility, which makes the company and the

brand in focus, different from products the service interaction is more representative of the

brand (Berry, 2000). Trust in terms of being able to live up to promises, can both enhance or

kill a brand (Keller, 2003). Therefore, the experiences of the service is vital for the brand, if

the marketing does not live up to the customers expectations the brand cannot save the

service, as the brand itself is the promise of a good service (Berry, 2000; Kimpakorn &

Tocquer, 2010). According to He and Li (2011) the main focus of brand equity for service

brands is the overall service quality, as investments in service quality will positively affect

customers’ perception and the service experience, which in turn would strengthen the brand

associations. Kimpakorn and Tocquer (2010) explains that service brands have to rely more

on the employees as the brand is formulated internal, then forwarded by the staff as they are

the foundation of the brand. Reaching high brand equity for services is about delivering

consistent and compelling experiences, which the customer will hold favourable (Kimpakorn

& Tocquer, 2010). However, the context of the service may differ as new ways of delivering

services has emerged through technology, e.g. self service systems online where an

interpersonal service system can take place, does not create brand equity through the

interaction between customer and employees (Meuter et al., 2000).

2.1.2 Online Service Brad Equity

Online service brand equity differs from traditional consumers’ perspective on good’s brand

equity (Rios & Riquelme, 2008). In accordance to how Berry (2000) explains that a product

represents the brand, online services differ, as the derived experience is the actual brand

formation. In an online environment the service is delivered without an interaction between an

employee and customer, which differs from traditional services (Meuter et al., 2000; Rios &

Riquelme, 2008). Hence, for web-based brands the brand equity is argued for being formed

on some additional antecedents as security, navigation and accessibility (Rios & Riquelme,

2008). Page and Lepowska-White (2002) has from traditional brand equity theories (Keller,

2003; Aaker, 1991), conceptualised web equity. Web equity is a framework for how online

companies can build or create added value online (Page & Lepkowska-White, 2002). Since

there are several different e-recruitment websites online (monster.se, criutway.se, mycarer.se,

linkedin.com, framtiden.se ect.), an important goal for such companies would be to enhance

the likelihood the potential customer would think of their website first (Page & Lepkowska-

7

White, 2002). This is in line with Keller (2003) and Aaker’s (1991) traditional theory about

brand equity, that having strong brand equity will lead to customers choosing one product or

service over the other once the brand is introduced. But also that it will bring increased

financial value in future periods (Ambler, 1994; Shugan, 2005), in this case traffic to the

company’s website. Therefore, brand equity will be measured in the four different

dimensions, brand awareness, brand association, brand loyalty and perceived quality.

2.2 Brand Awareness

According to previous research brand awareness is a factor affecting brand equity for online

companies (Kim et al., 2002; Rios & Riquelme, 2010). Brand awareness takes place when an

individual is familiar with a specific brand and the likelihood that the brand will come to the

individual’s mind. Berry (2000) states that brand awareness is an individual’s ability to think

of a firm when a certain product category is recalled. Brand awareness is divided into two

different parts; Brand recognition and brand recall (Keller, 1993; Aaker, 1991). Brand

recognition is when an individual can verify a prior exposure to a specific brand when a cue is

given to the brand (Keller, 1993). Further, brand recognition requires that the individual

correctly separate the brand as having been heard or seen earlier (Keller, 1993). Brand recall

is an individual’s capability to retrieve a brand when it is being mentioned (Rosenbaum-

Elliott et al., 2011).

Brand awareness is a crucial first step for consumers when selecting to purchase from a

certain brand and can have a crucial impact on individuals’ consideration in the purchase

phase of a product or service (Konecnik & Gartner, 2007; Page & Lepkowska-White, 2002).

Lin et al. (2014) argue that brand awareness has a significant importance in individuals’

decision-making process when being exposed to new situations. When an individual chose a

product the choice could be based on perceptions about the brand such as popularity of the

brand, how strong reputation the brand has and how well known the brand is (Lin et al.,

2014). According to Page and Lepkowska-White (2002) brand awareness can be built upon

two different perspectives; communication from the firm itself or external communication

without support from the company. The communication by the firm itself refers to when the

company communicates their message by online channels such as banner ads and offline

channels such as advisement in newspapers. The external communication is communication

without help from the firm itself such as word of mouth, which have been found to be a

8

powerful tool in order to leading individuals to visiting web sites (Page & Lepkowska-White,

2002).

2.3 Brand Association

Brand association has according to previous research an impact on brand equity (Aaker, 1996;

Biedenbach et al., 2015; Cobb-Walgren et al., 2005; Yoo & Donthu, 2001). Aaker (1991, p.

109) defines brand association as ”anything linked in memory to a brand”. Balaji (2011)

argues that brand association is a factor that differentiates the brand in individuals’ minds and

can give individuals a reason for purchasing a specific product or service. In the aspect of

brand association, the information connected in the memory for individuals is a crucial part

for brand equity and are considered to include the meaning of the brand for individuals

(Keller, 1993; Balaji, 2011).

According to previous research trust is a crucial factor for online companies in order to create

positive brand association (Rios & Riquelme, 2008; Page & Lepkowska-White, 2002).

According to Delgado-Balleste et al. (2003, p.11) trust is defined as “feeling of security held

by the consumer in his/her interaction with the brand, that is based on the perceptions that the

brand is reliable and responsible for the interests and welfare of the consumer”. The main

reason why trust must be created is because online businesses are intangible and therefore it is

difficult for individuals to judge the companies from intangible cues (Berry, 2000).

Individual’s inability to trust online companies has been a barrier for online transactions due

to that individuals want to feel safe when making a purchase from an online business (Rios &

Riquelme, 2008; Rios & Riquelme, 2010).

Another factor affecting individuals’ brand association is customer service support. However,

this factor is argued to not directly influence brand equity (Rios & Riquelme, 2010). On the

other hand, the factor customer service is probably the most crucial characteristic for online

businesses and can be a key determinant in order to differentiate the company from

competitors in the market (Chaffey, 2000; Kim et al., 2002; Lennon & Harris, 2002;

Christodoulides et al., 2006). If it is easy to come in contact with the online business, the

customer’s trust and confidence towards the firm will increase (Page & Lepkowska-White,

2002).

9

2.4 Perceived Quality

Perceived quality is according to Aaker (1996) a key dimension used when measuring brand

equity. Previous research within the brand equity context has found that there is a relationship

between perceived quality and brand equity (Buil et al., 2013; Kim & Hyun, 2011; Pinar et

al., 2014; Yoo et al., 2000). Perceived quality can be defined as the superiority or excellence

of a product based on the consumer’s judgement (Zeithaml, 1988). Having brand superiority

is vital aspect to consider when building relationship with the customers as it relates to the

extent customers think of the brand as better and more unique than other brands (Keller,

1993). Parasuraman et al. (1985) argue that it is difficult for consumers to evaluate the quality

of a service compared to products or goods, as there are no tangible comparisons that can be

made. This is in accordance with Berry (2000) and Kim et al. (2002) who explain that service

companies needs to deliver better visualization and make it easy for customers to understand

the intangible products (e.g., website quality). Kim et al. (2002) argue that this is important

for online service companies and that the brand is reflected upon its website. Most of the

interaction between an online company and customer is through the website and therefore it is

important for the brand to have a high quality website. According to Kim et al. (2002) and

Gommans et al. (2001) there are three underlying factors that assist in order to build a high

quality website; web usability, design and information architecture. The meaning of these

factors are that it should be easy to navigate on the website, easy to use and that the

information on the website is accurate (Kim et al., 2002). This is in accordance with Yang and

Fang (2004) who argue that ease of use and easy of navigation of a website is key to attract

both experienced and new customers. If the perceived quality of a website is lacking it can

hinder the success of an online business (Yang & Fang, 2004; Jiang et al., 2015).

As mentioned above, perceived quality is seen as a key dimension when creating brand equity

(Aaker, 1996). This is consistent with Pinar et al. (2014) who argue when measuring the

dimension towards brand equity in an university context, perceived quality is seen as the most

important dimension. This is contradictory with Yoo et al. (2000) who find that brand loyalty

is the dimension that has the strongest relationship with brand equity.

2.5 Brand Loyalty

Brand loyalty is another dimension that researchers have acknowledged impact brand equity

(Aaker, 1996). According to Rios and Riquelme (2008) brand loyalty is by far the most

influential among the different determinants of brand equity. Brand loyalty can be defined as

10

how likely it is for a customer to switch to another brand, especially in situation when a brand

is making changes within the company (e.g., product features or price) (Aaker, 1996).

Gommans et al. (2001) describe it in a more traditional view that loyalty is when a consumer

repeats their buying behavior towards a specific brand. Creating customers into loyal

customers is important for companies as it can give several strategic advantages such as

higher market share, reducing marketing costs (less expensive to retain customers than attract

new), gaining new customers and minimize the risk of competitive threats (Atilgan et al.,

2005). Keller (2001) argues that a company has gained loyal customers when they are willing

to invest time, energy, or money into a specific brand. This could be that the customers join a

community that is representing the brand, receive updates or visit websites that is related to

the brand (Keller, 2001). For online brands it is important that the website is of high quality in

order to attract loyal customers (Gommans et al., 2001). The information, design, and fast

page loading are important factors to build a loyal customer base. Further, Gommans et al.

(2001) argue that online consumers nowadays expect that websites are efficient and not time

consuming. Hence, it is important to have a good quality website in order for the customer to

not switch to another brand’s website (Gommans et al., 2001).

Previous research has found that brand loyalty has a direct relationship to brand equity (Yoo

& Donthu, 2001; Buil et al., 2013; Pinar et al., 2015). However, there have been discussions

among brand equity literature if brand equity is an outcome of brand loyalty (Aaker, 1996) or

if brand loyalty is an outcome of brand equity (Rios & Riquelme, 2008; Page & Lepkowska,

2002). Rios and Riquelme (2008) argue that there is no evidence that brand loyalty is an

outcome of brand equity and that this is just an assumption.

2.6 Intention to Use

In order to be able to gain understanding of certain behavior, one has to identify intentions to

perform that behavior (Ajzen & Fishbein, 1980). Behavioral intention could be the likelihood

that an individual repeats a purchase and the intention to continue to be a customer of a

company (Wang et al., 2006; Cho, 2015). Favorable behavioral intentions show that

individuals have established a bond with the firm, which is considered as an outcome

influenced by individual’s emotions (Zeithaml et al., 1996; Kuo et al., 2012). Ajzen (1991)

and Zeithaml (1988) argue for the importance of intention to use and its connection to

attitude, where the intention representing an individual’s decision-making process and

behavior. In the context of e-commerce, previous research shows that customers’ earlier

11

experience with a website and fulfillment of the service delivery has an influence on the

consumer’s intention to use the website in the future (Cho, 2015; Chen et al., 2009). Further,

they have found that if a online service can establish perceived usefulness (relevant jobs) and

perceived ease of use (quality and navigation) the satisfaction of the online service will lead

to a continuous usage (Chen et al., 2009). This is in line with Park et al. (2007) who finds that

for online service companies, website quality is an important factor for making individuals

willing to use a website. The factors within website quality were, ease of use, information

quality, responsiveness and security/privacy which all had a positive relationship towards

individuals’ intention to use (Park et al., 2007).

2.7 Hypothesis Formulation

Previous research have found that brand equity positively affect a consumer's intention

to purchase (Berry, 2000; Buil et al., 2013; Cobb-Walgren et al., 1995; Yoo & Donthu, 2001).

Buil et al. (2013) argue that firms who possess a high level of brand equity has the ability to

easier capture consumers’ intention to use their products or services. With this in

consideration the following hypothesis was formulated:

H1 - Brand equity has a positive relationship on individuals’ intention to use e-recruitment

websites. Also, if that relationship is moderated by a usage of an e-recruitment website which

had lead to a job in the past, as an earlier experience of the service delivery influence

individuals’ intention to use (Cho, 2015; Chen et al., 2009), thereby:

H1a - Acquired a job via an e-recruitment website moderates the relationship between brand

equity and individuals’ intention to use e-recruitment websites.

The determinants that measures brand equity has also been investigated in how it relates to

intention to use. Hutter et al. (2013) suggests that brand awareness has a positive relationship

to individuals’ intention to use in an online context. Therefore, this study test if it exists in the

context of e-recruitment websites:

H2 - Brand awareness has a positive relationship on individuals’ intention to use e-

recruitment websites. Also, if that relation affected by the usage of an e-recruitment website

had lead to a job in the past (Cho, 2015; Chen et al., 2009), thereby:

H2a - Acquired a job via an e-recruitment website moderates the relationship between brand

awareness and individuals’ intention to use e-recruitment websites.

12

Another dimension that have been investigated towards individuals’ intention to use is brand

association (O’Gass & Grace, 2004). Previous research has found that brand association has a

positive effect on individuals’ intention to use (O’Gass & Grace, 2004). With this in

consideration the following hypothesis was established:

H3 - Brand association has a positive relationship on individuals’ intention to use e-

recruitment websites. Also, if that affected by the usage of an e-recruitment website had lead

to a job in the past (Cho, 2015; Chen et al., 2009), thereby:

H3a - Acquired a job via an e-recruitment website moderates the relationship between brand

association and individuals’ intention to use e-recruitment websites.

Perceived quality has also been researched towards intention to use. Netemeyer et al. (2004)

mentions that perceived quality has been associated with intention to purchase and that it is a

core construct within brand among the determinants of brand equity. It has been found that

there is a positive relationship between perceived quality and intention to purchase (Tsiotsou,

2006) and therefore is the following hypothesis considered in this study:

H4 - Perceived quality has a positive relationship on individuals’ intention to use e-

recruitment websites. Also, if that relation is affected by the usage of an e-recruitment website

had lead to a job in the past (Cho, 2015; Chen et al., 2009), thereby:

H4a - Acquired a job via an e-recruitment website moderates the relationship between

perceived quality and individuals’ intention to use e-recruitment websites.

Brand loyalty is also considered to have an effect on individuals’ intention to use. According

to Shukla (2009) brand loyalty has a positive impact on use intention. This will this be tested

in the context of e-recruitment website which generates this hypothesis:

H5 - Brand loyalty has a positive relationship on individuals’ intention to use e-recruitment

websites. Also, if that relation is affected by the usage of an e-recruitment website had lead to

a job in the past (Cho, 2015; Chen et al., 2009), thereby:

H5a - Acquired a job via an e-recruitment website moderates the relationship between brand

loyalty and individuals’ intention to use e-recruitment websites.

The relationships are further explained and motivated in the next chapter where a conceptual

model of the framework is displayed.

13

3. Conceptual Framework

Based on the theoretical framework, the conceptual model is developed which presents how

the research will be conducted.

3.1 Research Model

It is known among the branding literature that brand equity is affected by four dimensions;

brand awareness, brand association, perceived quality and brand loyalty (Aaker, 1991, 1996;

Pinar et al., 2014; Yoo et al., 2000). However, there is scarce research that has investigated

brand equity and its determinants in an online service context (Alwi & Ismail, 2013), which

this study aims to investigate. The model that the authors of this study were influenced by

stems from the model that (Aaker, 1991) developed. This model is widely referred to and one

of the most recognized when measuring consumer-based brand equity (Christodoulides et al.,

2015). In this study brand equity and its determinants will function as independent variables

and have intention to use as the dependent variable. Usually brand equity is measured to

intention to purchase (Agarwal & Rao, 1996; Cobb-Walgren et al., 1995). Despite this,

intention to purchase is in this study referred to as intention to use because of the free service

of e-recruitment websites (Galanaki, 2002). However, as Park et al. (2007) and Chen et al.

(2009) explains that the factors leading to intention to use websites are similar to those of

brand equity online. Therefore, the model assisted and explained how this research intends to

measure brand equity and its dimensions to intention to use within the context of e-

recruitment websites. Further, if the relationships are moderated by if a respondent have

acquired a job via an e-recruitment website.

14

Figure 3.1 Conceptual model

H1

Brand equity has a positive relationship on individuals’ intention to use e-

recruitment websites.

H1a Acquired a job via an e-recruitment website moderates the relationship between

brand equity and individuals’ intention to use e-recruitment websites.

H2 Brand awareness has a positive relationship on individuals’ intention to use e-

recruitment websites.

H2a Acquired a job via an e-recruitment website moderates the relationship between

brand awareness and individuals’ intention to use e-recruitment websites.

H3 Brand association has a positive relationship on individuals’ intention to use e-

recruitment websites.

H3a Acquired a job via an e-recruitment website moderates the relationship between

brand association and individuals’ intention to use e-recruitment websites.

H4 Perceived quality has a positive relationship on individuals’ intention to use e-

recruitment websites.

H4a Acquired a job via an e-recruitment website moderates the relationship between

perceived quality and individuals’ intention to use e-recruitment websites.

H5 Brand loyalty has a positive relationship on individuals’ intention to use e-

recruitment websites.

H5a Acquired a job via an e-recruitment website moderates the relationship between

brand loyalty and individuals’ intention to use e-recruitment websites.

15

4. Methodology

This chapter explains how the research was conducted and presents different methodology

sections of how the researchers have followed through this research. The chapter describes

both theoretical and practical implementations of how it was performed.

4.1 Research Approach and Research Design

A descriptive design of the research was used to describe the different concepts in relation to

each other, it allowed to answer and analyze the data on how, what and why concerning a

specific situation (Aaker et al., 2010). Already established research within the field of brand

equity and its constructs together with intention to use was studied and interpreted towards the

collected data. This gave the research a deductive approach (Hyde, 2000; Creswell, 2014), to

which a quantitative approach was adopted to collect data as it helps to draw a large sample of

the population to draw general conclusions of the characteristics of the population (Hyde,

2000). As for the research design, a social survey research was appointed. A social survey

research implies that the information is gathered from multiple cases at one specific time

(Bryman & Bell, 2011). This is followed in order to make it possible to make associations and

patterns between different variables (Bryman & Bell, 2011).

4.2 Data Sources

This study chose to make use of primary data. The use of primary data gives the opportunity

to more specifically answer the purpose regarding the particular problem within the research

since it contains the accurate information of the investigated subject (Bryman & Bell, 2011;

Saunders et al., 2009). Since there is scarce research of brand equity in a e-recruitment

context towards intention to use, collecting primary data was more accurate and reliable to

answer the purpose.

4.3 Data Collection Method

This research aimed to generalize the result from a larger population and therefore an online

questionnaire was used as data collection method (Hyde, 2000). The online questionnaire was

posted on the social media Facebook during a period of seven days in order to collect the data

in different days of the week. Further, a mail with a link to the online questionnaire was sent

out to students at Linnaeus University. The first part of the online questionnaire consisted of a

short explanation of e-recruitment and examples of e-recruitment websites. In addition, the

16

first part consisted of a question regarding if the respondents had used e-recruitment websites

before. In addition, the respondents was given the possibility to write the e-recruitment

website they were most active on in order to have this e-recruitment website in mind during

the online questionnaire. The second part of the questionnaire consisted of questions

regarding the constructs brand awareness, brand association, perceived quality, brand loyalty

and intention to use. In order to measure the different items within each construct a likert

scale was used. The labels were conducted as follow; 1 Strongly disagree, 2 Disagree, 3

Somewhat disagree, 4 Neither agree or disagree, 5 Somewhat agree, 6 Agree, 7 Strongly

agree. In the end of the questionnaire a moderator question was asked regarding if the

respondents ever had got an employment via an e-recruitment website followed by four

questions about the respondents’ demographics, which were gender, age, occupation and level

of education.

4.4 Operationalization and Data Collection Instrument

The operationalization was used in order to handle the framework for the data collection and

analysis (Bryman & Bell, 2011). In addition, it describes in what way the theoretical

framework was divided into different concepts, which could be examined and measured

(Ghauri & Grønhaug, 2005). The operationalization has been divided into five different

dimensions, Intention to use, brand awareness, brand association, perceived quality and brand

loyalty.

Construct Definition Items adopted

from article Items

Intention to use Is the likelihood that an

individual repeats a

purchase and the

intention to continue to

be a customer of a

company (Wang et al.,

2006, Chen et al.,

2009).

Belanche et al., 2012

Brahmana &

Brahmana, 2013

Lee & Lee, 2015

ITU1.The likelihood that I use this e-

recruitment website is high.

ITU2. I think it is a good idea to use

this e-recruitment website.

ITU3. I am eager to use this this e-

recruitment website in the future.

Brand awareness When an individual is

familiar with a specific

brand and the

likelihood that the

brand will come to the

individual’s mind

(Berry, 2000).

Yoo & Donthu, 2001

Pinar et al., 2014

Page & Lepkowska-

White, 2002

AW1. I recognize this e-recruitment

website among other similar websites.

AW2. I would recognize the logo of

this e-recruitment website.

AW3. I only use e-recruitment

websites that I am aware of.

AW4. I came in contact with this e-

recruitment website because I heard

about it from friends or family.

17

Brand awareness Anything linked in

memory to a brand and

a factor that

differentiates the brand

in individuals’ minds

and can give

individuals a reason for

selecting a specific

product or service

(Aaker, 1991; Balaji,

2011)

Balaji, 2011

Aaker, 1996

Rios & Riquelme,

2008

Rios & Riquelme,

2010

Nath & Bawa, 2011

Wang et al., 2004

AS1. I trust this e-recruitment website.

AS2. I trust that this e-recruitment

website keeps my personal information

safe.

AS3. It feels safe to disclose personal

information on this e-recruitment

website.

AS4. The customer service is easy to

contact on this e-recruitment website.

AS5. The customer service can be

contacted in different ways on this e-

recruitment website.

Perceived quality The superiority or

excellence of a product

based on the

consumer's judgments

(Zeithaml, 1988).

He & Li, 2011

Kao & Lin., 2016

Pinar et al., 2014

Rios & Riquelme,

2008

Yoo & Donthu, 2001

Yoo et al., 2000

PQ1. This e-recruitment website has

high quality.

PQ2. It is easy to navigate on this e-

recruitment website.

PQ3. The information is easy to

understand on this e-recruitment

website.

PQ4. This e-recruitment website has an

appealing design.

PQ5. This e-recruitment website offers

jobs that is of good quality

PQ6. This e-recruitment website has a

wide variety of job offers.

Brand loyalty When a consumer

repeat their buying

behavior toward a

specific brand

(Gommans et al.,

2001).

Keller, 2001

Yoo et al., 2000

Yoo & Donthu, 2001

BL1. I consider myself to be loyal to

this e-recruitment website.

BL2. This e-recruitment website would

be my first choice.

BL3. I will not choose other e-

recruitment websites if this e-

recruitment website is available.

Table 4.1 Operationalization

4.5 Pre-test

A pre-test was conducted in order to generate valuable information of how the study should

be designed and to make the questions in the questionnaire as relevant as possible (Ghauri &

Grønhaug, 2005). It is crucial to conduct a pre-test when conducting a self-completing

questionnaire since there is no moderator available to answer potential questions from the

participants. In addition, it helps to improve potential deficit in the research (Bryman & Bell,

2011). In order to assure that the questions were correctly formulated and to see if there was

any questions, which could be excluded or added the questionnaire was presented to two

lectures at Linnaeus University, Växjö, Sweden. In addition, a pre-test was conducted by

18

randomly selecting 10 representatives of the sample that answered the questionnaire in order

to get feedback and avoid potential misunderstandings.

4.6 Sample

The study was aimed towards individuals who had used e-recruitment websites before. A non-

probability sample technique with convenience sampling method was used since it was the

most suitable for the time frame (Bryman & Bell, 2011). However, the convenience sampling

method can be criticized due to the lack of randomness of the sampling process, which is

needed to be able to generalize the results to a whole population (Bryman & Bell, 2011).

Nevertheless, collecting the data during a longer period and different times during the week

gives more credibility since the diversity of the population increases. Therefore, the results

can be generalized to a greater extent (Malhotra & Birks, 2010; Aczel & Sounderpandian,

2009). The only criteria to submit the questionnaire was to have experience of a e-recruitment

website before, since the study is aimed towards users of these types of websites. Therefore, a

question concerning if the individual had used an e-recruitment website before opened the

questionnaire. If the respondent did not have any past experience they were not allowed to

complete the questionnaire to avoid misleading and not influencing the data with ignorance to

get as much reliable data as possible. To be able to quantify data and make generalizations

from it, the study needed an appropriate sample size (Green, 1991; Ghauri & Grønhaug, 2005;

Hair et al., 2010; Malhotra & Birks, 2010). A questionnaire should have the foundation of 50

respondents, adding eight times the number of independent variables, N > 50+8 x m, while m

being the number of independent variables (Green, 1991; Pallant, 2010). Therefore, the

questionnaire was continuously spread until it achieved a minimum of 90 completed

questionnaires, in excess of the samples, which have no past experience with e-recruitment

websites. After the data was collected, there were 128 out of 175, which could be used for

further analysis.

4.7 Data Analysis Method

This study used the statistical program SPSS to analyze the results that was collected from the

online questionnaire. This program helped the researchers to organize and calculate the data

in order to answer this study’s hypothesis. According to Bryman and Bell (2011) SPSS is a

software that is widely used among research which conducts quantitative studies. It gives the

user precise data when performing analysis (Bryman & Bell, 2011). The following parts that

are presented below were taken into consideration when performing the SPSS analysis.

19

Descriptive statistics

Firstly, before running the descriptive statistics was the data from the questionnaire coded and

categorized in numbers in order to make calculations in the SPSS. According to Gravetter and

Wallnau (2008) descriptive statistics are usually conducted in order to summarize and

describe each of the participants’ score to simplify the data gathered, which then can be

organized and presented in graphs or tables to make it easy for the researcher. By doing this

gave a clear understanding of how each participant within the sample answered the questions

and how the characteristic distribution of the population was. Therefore, to simplify the data

collected in this research the authors displayed and categorized the descriptive data into

gender, age, occupation and level of education in order to summarize the data in a simple

manner to show the reader what sample the study based it findings on. These four different

demographic aspects were also used as control variables in the regression analysis presented

below to see if these additional variables might have had an influence of the relationships

between this study’s independent variables towards the dependent variable (Bryman & Bell,

2011).

Regression analysis

To test the hypothesis of this study a multiple linear regression was included. The data was

analyzed in order to test the relationship between this study’s independent variables; brand

awareness, brand association, perceived quality and brand loyalty, towards the dependent

variable intention to use. In order for the relationships to be statistically significant it had to

display a p< 0.05 (Richardson, 2011). Moreover, by conducting a regression analysis one can

see how much one variable affects another variable by looking at the beta value. The beta

value shows if the relationship between the two variables indicates a positive or a negative

relationship and how relatively strong that relationship is (Pallant, 2010). Another factor to

consider in this type of analysis is the adjusted R2, which suggests how much of the

dependent variable can be predicted by an independent variable (Pallant, 2010).

Interaction variable

A moderator analysis of the variables brand equity, brand awareness, brand association,

perceived quality and brand loyalty was conducted to see if the relationship between the

independent variables and the dependent variable was moderated by if the use of an e-

recruitment website had lead to a job. By dividing the sample into two groups to calculate an

interaction variable, could determine an effect on intention to use e-recruitment websites if an

individual had acquired a job via an e-recruitment website. The participants who previously

20

had acquired a job via an e-recruitment website was coded 1 where respondents which had

not acquired a job via an e-recruitment sites was coded 0. A moderator being an interaction

variable, (group independent variable), tests if the relationship of a independent variable to

the dependent variable is affected by a third variable (Baron et al., 1986; Pallant, 2010). To

avoid multicollinearity in the interaction variables and accounting for the different scales of

measure (1-7 and 0-1), they were computed by using the variables standardized values.

Therefore, moderator was calculated by computing a new variable in SPSS, by calculating the

-values from the independent variables and multiplying each of them with the -value of

the moderator separately. This gave a specific interaction variable for each corresponding

relationship between an independent variable and the dependent variable. These were used for

hypothesis H1a, H2a, H3a, H4a and H5a.

Interaction variable Construct

Brand awareness -value of Brand awareness -value of acquired job

Brand association -value of Perceived quality -value of acquired job

Perceived quality -value of Perceived quality -value of acquired job

Brand loyalty -value of Brand loyalty -value of acquired job

Table 4.2 Interaction variable

4.8 Quality Criteria

4.8.1 Validity

Validity and reliability is considered as the most crucial quality criteria when conducting

measurements of a study (Hair et al., 2010; Bryman & Bell, 2011). There are according to

Bryman and Bell (2011) several types of measurements to assure validity, such as face

validity and construct validity. Face validity test if the measurement reflects the investigated

concepts, which in this study was done by the previous mentioned pre-tests. The construct

validity has the aim to assure that the operationalization measures the concepts it is aimed to

measure (Bryman & Bell, 2011). The construct validity is accomplished when the conducted

hypotheses are derived from relevant theories and has a connection to the concepts (Aaker et

al., 2011; Bryman & Bell, 2011). In order to assure the construct validity in this study the

different constructs in the operationalization was deducted from relevant theories and from

previous research. To further ensure the construct validity, the constructs were measured in a

correlation analysis. In the SPSS the correlation analysis is called Pearson’s r correlation

coefficient, which makes it possible to see the strength and direction of the relationship

21

between different constructs (Richardson, 2011). Therefore, in this study brand equity, brand

awareness, brand association, perceived quality, brand loyalty and intention to use were tested

against each other. According to Richardson (2011) the value in a Pearson’s r correlation

analysis varies between a value of -1 (perfectly negative correlation) and 1 (perfectly positive

correlation) with 0 in between that indicates that there is no correlation. A value between 0

and 0.3 is seen as a weak correlation. It should be noted that the value should not exceed the

value of 0.9 in any direction as it can indicate that the different constructs measure the same

thing (Hair et al., 2010; Nolan and Heinzen, 2008).

4.8.2 Reliability

According to Gray (2009) external reliability has the aim to make it possible for other

researchers to replicate the study. The choices in the methodology chapter were carefully and

clearly presented and described. When a measure can assure the same result with the same

measurement on different occasions it is considered to have external reliability (Bryman &

Bell, 2011; Nardi, 2003; Saunders et al., 2009). Hence, the authors of this study present all the

steps that were conducted when measuring the variables, for other studies to have the chance

to replicate. Further, this research was inspired by questions from previous research (See

operationalization) as Saunders et al. (2009) argue that both the reliability and validity is

strengthened when using questions from other researchers since the questions already has

been used and accepted by previous research.

To ensure the quality and strength of the collected data the authors of this study also

performed a reliability test. A reliability test is performed to test if the statements around one

variable investigate the same area (Bryman & Bell, 2011). To be able to test this, the authors

used a statistical tool, which is called Cronbach’s alpha to ensure the internal reliability.

According to Bryman and Bell (2011) can the alpha score vary between 1 to 0, meaning that 1

indicates a perfect internal reliability and 0 indicates no internal reliability. For the score to be

significant it has to have a score of at least 0.6 otherwise it cannot be seen as reliable

(Malhotra et al., 2012). Therefore, if a construct did not reach an alpha score of 0.6, the items

of the construct would be evaluated to be deleted to achieve a valid value.

4.8.3 Quality Data Control

Since regressions are very sensitive to extreme low or high values, preliminary analyses were

conducted before the to ensure no violation of normality, linearity, multicollinearity and

homoscedasticity (Pallant, 2010). This was observed using regression analysis with residuals

scatterplot. To further look for inconveniences regarding multicollinearity the coefficients for

22

tolerance and variance inflation factors was observed, which all the independent variables;

brand awareness, brand association, perceived quality and brand loyalty showed a tolerance

value of >0.1, respectively <10 for variance inflation factor, therefore the multicollinearity

assumption has not been violated (Pallant, 2010). However, the independent variable brand

equity which is a variable built of all the same items as the other independent variables was

not included in the same regression analysis as brand awareness, brand association, perceived

quality and brand loyalty to avoid singularity in the regression (Pallant, 2010). However,

when looking at the Mahalanobis distance, one of the respondents scored an extreme value of

32.221, which exceeds the critical value of 20.52 when using 5 independent variables

(Pallant, 2010). Therefore, respondent 7 was excluded for the analysis.

4.9 Methodology Summary

All the different methodological approaches that the authors chose to include in this study are

summarized in table 4.3.

Research Methodology

Research approach Deductive and quantitative

Research design Descriptive, social survey research

Data sources Primary

Data collection method Online questionnaire

Sample Non-probability sampling

Convenience sampling

Data analysis method Data coding

Descriptive statistics

Correlation analysis

Regression analysis

Moderator analysis

Quality criteria Validity

Reliability

Quality data control

Table 4.3 Methodology summary

23

5. Results

This chapter presents the collected data and results. It will outline the descriptive statistics,

reliability and validity analysis, correlation analysis, multiple regression analysis and the

moderated regression analysis. To conclude the chapter, a table of the hypotheses is

summarized and presented with its significance level.

5.1 Descriptive Statistics

To be able to make a clearer test and distinction of how the answers differed among the

sample, this study categorized and simplified (Gravetter & Wallnau, 2008) four different

demographic variables; gender, age, occupation and level of education. Looking at the gender

distribution of the 128 participants in table 5.1, it can be noticed that there is a relative equal

distribution between males and females with a percentage of (54.7%) male and (45.3%)

female. The age distribution was not hugely diverse as all of the respondents were in between

the age groups; 18-24 (39.1%), 25-29 (53.1%), 30-34 (7.8%). Further, looking at the

occupation, the majority of the respondents were students (62.5%) followed by those who had

an employment (36.7%). When it came to the level of education the majority of the

respondent were divided in either having taken a bachelor degree (56.3%) or master’s degree

(34.4%). Finally, (34,7 %) of the participants had acquired a job via an e-recruitment website

before.

Characteristic Frequency Percentage

Gender Male

Female

70

58

54.7

45.3

Age 18-24

25-29

30-34

50

68

10

39.1

53.1

7.8

Occupation Student

Employed

Unemployed

80

47

1

62.5

36.7

0.8

Level of education Secondary school

High school

Bachelor or equivalent

Master or equivalent

2

10

72

44

1.6

7.8

56.3

34.4

Have you ever got an

employment via an e-

recruitment website?

Yes

No

46

82 35.9

64.1

Table 5.1 Demographics Statistics. N=128

24

5.2 Reliability and Validity

This section illustrates the validity and reliability, which is presented in table 5.2 to ensure the

quality of this research. The first column of table displayed the Cronbach’s alpha of each

construct in order to check for internal reliability. As illustrated in the table 5.2, the highest

alpha value showed (.880), which was the variable brand equity, followed by perceived

quality (.865), intention to use (.863), brand loyalty (.788), brand association (.698) and the

lowest alpha value brand awareness (.652). This indicated that all of the constructs used in

this study had an accepted internal reliability since the reliability coefficient of 0.6 or higher

was considered acceptable (Malhotra et al., 2012). To ensure that all of the constructs

received a alpha value of 0.6 or higher the authors had to withdraw the items AW3 and AW4

from the brand awareness variable (see operationalization). These items were not considered

for further calculations throughout the paper. Hence, with all of the construct reaching the

limit, could all of the constructs be used for further analysis.

To ensure the validity of this research the Pearson’s r correlation was used in order to

determine if the constructs measured what it was intended to measure. In table 5.2 it shown

that the correlation differs, ranging from the lowest score of (.318) and highest (0.899) with

all the correlations being positive and significant at p<.001. The variables brand association

together with brand loyalty showed the weakest correlation (.318) followed by the variables

brand association together with brand awareness with a correlation of (.375). The other

variables showed a relatively strong to a very strong correlation in which the variables brand

equity and perceived quality showed the strongest correlation with a value of (.899). Since all

of the constructs displayed a correlation under 0.9 it ensures that neither of the constructs

Cronbach’s α Mean SD 1. 2. 3. 4. 5. 6.

1. Intention

to use

.863 5.48 1.170 1

2. Brand

awareness

.652 5.94 .988 .556** 1

3. Brand

association

.698 5.16 .850 .482** .375** 1

4. Perceived

quality

.865 5.64 .932 .759** .503** .623** 1

5. Brand

loyalty

.788 4.30 1.589 .673** .397** .318** .537** 1

6. Brand

equity

.880 5.28 .820 .808** .613** .762** .899** .755** 1

** Correlation significant at the 0.001 level (2-tailed)

Table 5.2 Reliability and Correlations

25

measured the same area, which tells that the construct validity was intact (Hair et al., 2010;

Nolan and Heinzen, 2008).

5.3 Hypothesis Testing

Table 5.4 illustrate the findings resulting from the multiple regression analysis, the table is

divided into three models. Firstly, the control variables; gender, age, occupation and

education were checked against the dependent variable intention to use, which are displayed

in model 1. Looking at the results in model 1, neither of the control variables displayed a

significant relationship meaning that the control variables do not have any direct relationship

to individuals’ intention to use. This suggests that the independent variables used in model 2

and 3 may be more suitable predictors of intention to use, as the adjusted R2

in model 1 only

measure (.029).

Model 2 in table 5.4 include the control variables together with the independent variable

brand equity against the dependent variable intention to use. It can be observed that the

control variable age has a significant relationship to intention to use. This indicates that if the

standard deviation in age variable increases by one would lead to an increase by (.114) for

intention to use. Looking at hypothesis one, can it be observed that it is has a p<0.001 and that

the relationship is positive due to the beta being (.791). This means that if the brand equity’s

standard deviation increases by one would lead to an increase in intention to use by (.791).

Moreover, the adjusted R2

shows a value of (.654) which suggests that brand equity can be

interpreted to predict 65.4 % of the dependent variable. Hence, hypothesis 1; Brand equity

has a positive relationship on individuals’ intention to use e-recruitment websites is accepted.

Model 1 Gender, Age, Occupation, Education

Model 2 Gender, Age, Occupation, Education, Brand Equity

Model 3 Gender, Age, Occupation, Education, Brand awareness,

Brand association, Perceived quality and Brand loyalty

Table 5.3 Predictors to dependent variable: Intention to use

26

Model 3 in table 5.4 included the control variables and the different determinants; Brand

awareness, brand association, perceived quality and brand loyalty against the dependent

variable intention to use. None of the control variables were significant. However, the

independent variables brand awareness, perceived quality and brand loyalty were shown to

have a significant relationship towards intention to use as it can be observed that the

significance level was for brand awareness p<0.01, and for perceived quality and brand

loyalty p<0.001. The beta value for brand awareness was (.173), the beta value for perceived

quality was (.479) and brand loyalty had a beta value of (.326) which indicates that there is a

positive relationship towards intention to use. Further, the variable brand association showed

no evidence of having a significant relationship with intention to use as can be seen in model

3 as the p-value exceeds p>0.05. The adjusted R2 for model 3 was (.681) which suggests that

these independent variables can predict intention to use by 68,1%. With these results can H2 -

Brand awareness has a positive relationship on individuals’ intention to use e-recruitment

websites, H4 - Perceived quality has a positive relationship on individuals’ intention to use e-

recruitment websites, H5 - Brand loyalty has a positive relationship on individuals’ intention

to use e-recruitment websites be accepted while H3 - Brand association has a positive

relationship on individuals’ intention to use e-recruitment websites is rejected due to its

significant level of p>0.05.

Variables Model 1 Model 2 Model 3

Control Variables

Gender .125 (.208) .061 (.124) .038 (.120)

Age .185 (.178) .116 (.107)* .066 (.105)

Occupation .037 (.217) -.024 (.130) -.017 (.125)

Education -.053 (158) -.015 (.094) -.047 (.092)

Independent Variables

H1 Brand Equity .792 (.075)**

H2 Brand Awareness .173 (.070)**

H3 Brand Association .015 (.092)

H4 Perceived Quality .479 (.096)***

H5 Brand Loyalty .326 (.045)***

R2 .059 .669 .705

Adjusted R2 .028 .655 .685

Change in R2 .059 .610*** .646***

St. Error of Estimate 1.15375 .68701 .65695

F-Value 1.921 49.313 35.509

Degrees of freedom 4 5 8 Dependent Variable: Intention to use. *p<0.05 ** p<0.01 ***p<0.001. Standard error is presented within

parenthesis next to the Beta of each independent variable

Table 5.4 Multiple regression analysis

27

5.4 Moderated Regression Analysis

For model 2, the variable brand equity is calculated as one variable containing all the

constructs connected to brand equity as whole. Therefore, in the moderating regression

analysis the variable brand equity is not run with the other independent variables as it already

is explained by its dimensions. Nevertheless, from model 2 to model 6, each independent

variable was exchanged with its corresponding interaction variable, one at a time for each test.

In model 7, each of the determinants of brand equity is calculated together.

Model 1 Gender, Age, Occupation, Education

Model 2 Gender, Age, Occupation, Education, Interaction: Brand equity

Model 3 Gender, Age, Occupation, Education, Brand Association, Perceived

quality, Brand loyalty, Interaction: Brand awareness

Model 4 Gender, Age, Occupation, Education, Brand awareness, Perceived quality,

Brand loyalty, Interaction: Brand association

Model 5 Gender, Age, Occupation, Education, Brand awareness, Brand association,

Brand loyalty, Interaction: Perceived quality

Model 6 Gender, Age, Occupation, Education, Brand awareness, Brand association,

Perceived quality and Interaction: Brand loyalty

Model 7 Gender, Age, Occupation, Education, Interaction: Brand awareness,

Interaction: Brand association, Interaction: Perceived quality and

Interaction: Brand loyalty

Table 5.5 Predictors to dependent variable: Intention to use.

Model 2 in table 5.6, shows the result if the independent variable brand equity is moderated if

the individual had acquired a job via an e- recruitment website. Two variables which showed

a statistical significant level was the interaction variable between brand equity and if the

individual had acquired a job via an e-recruitment website, also the control variable age. Both

possess a p <0.05. The interaction variable brand equity showed a beta equal to (-.182) with a

st. error of (.106). The control variable age showed a beta equal to (.203) with a st. error of

(.177). This generated an adjusted R2

of (.054) which suggests that it only predicts 5,4% of

intention to use. Since the moderating effect was statistically significant, the moderator is

accepted. Thus, H1a - Acquired a job via an e-recruitment website moderates the relationship

between brand equity and individuals’ intention to use e-recruitment websites, is accepted.

28

Variables Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7

Control Variables

Gender .125 (.208) .130 (.205) .033 (.123) .049 (.120) .043 (.137) .071 (.133) .039 (.123)

Age .185 (.178) .203 (.177)* .085 (.108) .069 (.102) .137 (.118) .082 (.116) .084 (.106)

Occupation .037 (.217) .055 (.215) .003 (.127) -.014 (.124) -.039 (.142) .005 (.141) -.017 (.126)

Education -.053 (158) -.036 (.157) -.031 (.094) -.043 (.090) .010 (.104) -.073 (.102) -.037 (.092)

Independent variables

Brand awareness .165 (.069)** .258 (.077)*** .226 (.077)** .149 (.074)*

Brand association .027 (.093) .234 (.088)*** .001 (.102) .000 (.093)

Perceived quality .519 (.095)*** .478 (.080)*** .630 (.099)*** .484 (.097)***

Brand loyalty .371 (.046)*** .331 (.045)*** .472 (.047)*** .334 (.046)***

Interaction Variable

Moderator H1a

Brand equity

-.182(.106)*

Moderator H2a

Brand awareness

-.105 (.073)

-.030 (.088)

Moderator H3a

Brand association

-.073 (.061)

-.013 (.075)

Moderator H4a

Perceived quality

-.101 (.069)

-.116 (.085)

Moderator H5a

Brand loyalty

-.037 (.068) .046 (076)

R2 .059 .091 .694 .710 .617 .636 .718

Adjusted R2 .028 .054 .673 .690 .597 .611 .689

Change in R2

.059 .032* .635*** .651*** .558*** .577*** .013

St. Error of Estimate 1.15375 1.13849 .66910 .65160 .74813 .72979 .65286

F-Value 1.921 2.442 33.696 36.340 23.976 25.953 24.428

Degrees of freedom 4 5 8 8 8 8 12 Dependent Variable: Intention to use. Moderator: Acquired a job via an e-recruitment website. *p<0.05 ** p<0.01 ***p<0.001. Standard error is presented within parenthesis next

to the Beta of each independent variable.

Table 5.6 Moderated regression analysis

29

Model 3 in table 5.6, shows the result if the independent variable brand awareness is

moderated if the individual had acquired a job via an e-recruitment website. Two variables,

which showed a statistical significant level was the independent variables perceived quality

and brand loyalty. Both perceived quality and brand loyalty showed a significance level of

p<0.001. Perceived quality had a beta of (.519) and a st. error of (.095) and brand loyalty

showed a beta of (.371) and a st. error of (.046). The interaction variable of brand awareness

and if the individual had acquired a job via an e-recruitment website showed a beta equal to (-

.105) with a st. error of (.073). Model 3 generated an adjusted R2

of (.673) which suggests

that 67.3 % of the relationships can be explained. However, the moderating effect was not

statistically significant. Thereby, H2a - Acquired a job via an e-recruitment website

moderates the relationship between brand awareness and individuals’ intention to use e-

recruitment websites, is rejected.

Model 4 in table 5.6, shows the result if the independent variable brand association is

moderated if the individual had acquired a job via an e-recruitment website. Three variables

showed a statistical significant level, which was the independent variables brand awareness,

perceived quality and brand loyalty. All of them showed a strong significant level of p<0.001.

Brand awareness had a beta of (.165) and a st. error of (.069). Perceived quality had a beta of

(.478) and a st. error of (.080). Finally, brand loyalty possessed a beta of (.331) and a st. error

of (.045). The interaction variable brand association showed a beta equal to (-.073) with a st.

error of (.061). Model 4 generated an adjusted R2

of (.690). However, the moderating effect

was not statistically significant. Thereby, H3a - Acquired a job via an e-recruitment website

moderates the relationship between brand association and individuals’ intention to use e-

recruitment websites, is rejected.

Model 5 in table 5.6, shows the result if the independent variable perceived quality is

moderated if the individual had acquired a job via an e-recruitment website. Three variables

showed a statistical significant level, which were the independent variables brand awareness,

brand association and brand loyalty. It shows that all the three independent variables had a

very strong significant level of p<0.001. Brand awareness had a beta of (.258) and a st. error

of (.077). Brand association had a beta of (.234) and a st. error of (.088). Brand loyalty had a

beta of (.472) and a st. error of (.047). The interaction variable of perceived quality and if the

individual had acquired a job via an e-recruitment website showed a beta equal to (-.101) with

a st. error of (.069). Model 5 generated an adjusted R2 of (.597). However, the moderating

30

effect was not statistically significant. Thereby, H4a - Acquired a job via an e-recruitment

website moderates the relationship between perceived quality and individuals’ intention to

use e-recruitment websites, is rejected.

Model 6 in table 5.6, shows the result if the independent variable brand loyalty is moderated if

the individual had acquired a job via an e-recruitment website. Two variables showed a

statistical significant level, brand awareness p<0.01 and perceived quality p<0.001. Brand

awareness showed a beta of (.226) and a st. error of (.077). Perceived quality had a beta of

(.630) and a st. error of (.099). The moderating variable of brand loyalty and if the individual

had acquired a job via an e-recruitment website showed a beta equal to (-.037) with a st. error

of (.068). Model 6 generated an adjusted R2

of (.611). However, since the moderating effect

was not statistically significant, the hypothesis is rejected. Thereby, H5a - Acquired a job via

an e-recruitment website moderates the relationship between brand loyalty and individuals’

intention to use e-recruitment websites, is rejected.

Model 7 in table 5.6, shows the result if the independent variables brand awareness, brand

association, perceived quality and brand loyalty are moderated if the individual had acquired a

job via an e-recruitment website. However, as illustrated in model 7 it can be noticed that the

results of the different moderators together did not show any significance.

31

5.5 Summary of Hypothesis Testing

Hypothesis Supported

H1

Brand equity has a positive relationship on individuals’ intention to

use e-recruitment websites.

Yes **

H1a Acquired a job via an e-recruitment website moderates the

relationship between brand equity and individuals’ intention to use

e-recruitment websites.

Yes *

H2 Brand awareness has a positive relationship on individuals’ intention

to use e-recruitment websites.

Yes**

H2a Acquired a job via an e-recruitment website moderates the

relationship between brand awareness and individuals’ intention to

use e-recruitment websites.

No

H3 Brand association has a positive relationship on individuals’

intention to use e-recruitment websites.

No

H3a Acquired a job via an e-recruitment website moderates the

relationship between brand association and individuals’ intention to

use e-recruitment websites.

No

H4 Perceived quality has a positive relationship on individuals’

intention to use e-recruitment websites.

Yes***

H4a Acquired a job via an e-recruitment website moderates the

relationship between perceived quality and individuals’ intention to

use e-recruitment websites.

No

H5 Brand loyalty has a positive relationship on individuals’ intention to

use e-recruitment websites.

Yes***

H5a Acquired a job via an e-recruitment website moderates the

relationship between brand loyalty and individuals’ intention to use

e-recruitment websites.

No

Table 5.7 Summary of hypothesis testing. *p<0.05 ** p<0.01 ***p<0.001.

32

6. Discussion

This chapter presents a discussion regarding the results from the online questionnaire in

relation to the hypothesis. The discussion is connected to the research questions of the study

as well as the theory in the theoretical framework.

6.1 Brand Equity

Brand equity being what conceptualizes the added value to the brand (Keller, 2003) is

applicable to the results of this study of how brand equity affects the intention to use a e-

recruitment website. The results in table 5.4, model 2, confirmed the relationship of brand

equity as a whole would increase the intention to use for customers. This is in line with Berry

(2000), Buil et al. (2013), Cobb-Walgren et al. (1995) and Yoo and Donthu (2001), which

means brand equity leads to intention to purchase. This is in accordance with the findings

from Keller (2003) and Aaker (1991) who means that brand awareness, brand association,

perceived quality and brand loyalty affects one’s perception of a brand. Rios and Riquelme

(2008) and Park et al. (2007) also argue of how online brands should focus on security,

navigation and accessibility to build strong brand equity to achieve more traffic on the

website, which was included in the variables items. Thus, having high brand equity for e-

recruitment websites increases the intention to use, which according to Ambler (1994) and

Shugan (2005) could generate more profit in future periods. The high positive beta value of

(.792) describes that the relation between brand equity and intention to use is positive,

meaning brand equity has a positive effect on intention to use. This could be connected to if

the consumer’s emotions are positive towards the e-recruitment website based on the

dimensions of brand equity, would lead to a continuous usage (Zeithaml et al., 1996; Kuo et

al., 2012; Wang et al., 2006).

6.2 The Determinants of Brand Equity

6.2.1 Brand Awareness

Prior to this research there has been acknowledged that brand awareness has a positive

relationship towards intention to use in an online context (Hutter et al., 2013). The result of

this study is in accordance with the latter, and that brand awareness has a relationship with

individuals’ intention to use e-recruitment websites as the result indicated a significance level

of p<0.01. The beta value of brand awareness also indicates that each time the standard

deviation of brand awareness increases by one will lead to an increase in intention to use by

33

(.173) which indicates a positive relationship. However, among the determinants that were

significant was brand awareness relationship with intention to use is seen to have the weakest

influence. This result may indicate that brand awareness is seen as the crucial first step when

selecting to purchase or use a certain brand (Konecnik & Gartner, 2007; Page & Lepkowska-

White, 2002) and that other factors are more important when having the intention to use an e-

recruitment website.

The most important factor according to the result in this study within brand awareness was

brand recognition. This is when individuals can correctly separate the brand among other

similar brands when having seen or heard of the brand earlier (Keller, 1993). This result

indicates that individuals are more eager to use e-recruitment websites if having seen or heard

of the brand before which is in line with Konecnik and Gartner (2007) and Page and

Lepkowska-White (2002) who argue that this can have a crucial impact when considering to

use a product or service.

6.2.2 Brand Association

The result of the relationship between brand association and intention to use in this study

indicates that there is no significant relationship as the regression analysis displayed a

significance level of p>0.05. This is not in line with the findings from O’Gass and Grace

(2004) who concluded that brand association has a positive effect on individuals’ intention to

use when measured towards the banking service sector. The different results are interesting

since this study does not differ significantly from the latter as an e-recruitment business also

is within the service sector (Lee, 2011).

The items used to measure the construct brand association were connected to factors such as

security/privacy and responsiveness, which according to previous research are items that can

be used to measure brand association (Chaffey, 2000; Christodoulides et al., 2006; Kim et al.,

2002; Lennon & Harris, 2002; Page & Lepkowska-White, 2002; Rios & Riquelme, 2008).

According to Park et al. (2007) can these factors within an online context increase an

individual’s willingness to use a website. However, this seems not to be the circumstance

within an e-recruitment context as the items used did not contribute to an significant

relationship between brand association and intention to use.

34

6.2.3 Perceived Quality

The result of perceived quality and its relationship to individuals’ intention to use showed to

be significant at a level of p<0.001. This result is in line with Tsiotsou (2006) who concludes

in their findings that perceived quality has a positive effect on the intention to use. The

measurements predicts that if the standard deviation of perceived quality increases by one will

lead to an increase in intention to use by (.479). Further, this indicates that perceived quality

compared to the other determinants of brand equity has the strongest relationship towards

individuals’ intention to use. This is in accordance with Aaker (1996) who argues that

perceived quality is seen as a key dimension within brand equity, which also is supported by

Pinar et al. (2014) who finds that in the context of universities, perceived quality is the most

important factor. Looking at the means of the items concerning perceived quality (Appendix

1), it can be noted that all of the factors within perceived quality is important for e-

recruitment websites to consider as all of them received a relatively high mean.

However, the most important factors of perceived quality of an e-recruitment website were

that they should have a wide variety of job offers and that the information should be easy to

understand. This is in line with Kim et al. (2002) and Gommans et al. (2001) that describe that

the website is one of the most important aspects to consider for online companies. In order for

users to visit the website it is important that the website offers information that is easy for the

user to interpret (Kim et al., 2002). This is a key in order to attract customers to use the

website (Yang & Fang, 2004).

6.2.4 Brand Loyalty

The result of brand loyalty and individuals’ intention to use showed to have a significant

relationship as the significance level was p<0.001. This is in accordance with Shukla (2009)

who suggests based on their findings that there exists a positive relationship between brand

loyalty and individuals’ intention to purchase. The findings in this study also suggests that

there is a positive relationship as the beta value indicates that if brand loyalty increase by one

in standard deviation will lead to an increase in intention to use by (.326). This result indicates

that brand loyalty has the second highest impact among the determinants of brand equity on

individuals’ intention to use e-recruitment websites. The indication of the relationship being

positive can be argued that the e-recruitment websites that the participants used had a high

quality website which excluded a desire to switch to another brand or webpage (Gommans et

al., 2001). Meaning that the design and information was clear and that the websites had fast

35

loading pages which according to Gommans et al. (2001) are important factors for having

loyal customers.

6.3 Moderating Effect

However, when brand equity was tested with the moderator, it changed the relation

remarkably from a positive beta (.792) in table 5.3 to a negative effect of (-.182) in table 5.6,

model 2. Meaning that individuals who had acquired a job via an e-recruitment website would

have less intention to use compared to individuals who had not. One would suggest according

to theory, if the online service is capable of delivering a fulfillment of its service, which for an

e-recruitment website would be a job, the intention to further use the website would increase

(Chen et al., 2009; Cho, 2015). On the other hand, this may be the result of a saturated need

for job, as individuals would use e-recruitment websites to find jobs. Therefore, brand equity

generates a positive relation to intention to use, but if an individual's previous usage had lead

to a job, the need for job is satisfied. Hence, the relationship becomes negative when tested

with its moderator. However, this relationship is only explained by 5.4%, which means that

there are other factors that are better predictors.

When the determinants of brand equity were measured with the moderator none of variables

was significant. This suggests that the relationship between the independent variables; brand

awareness, brand association, perceived quality and brand loyalty and the dependent variable

intention to use had no effect when interacted with the third variable regarding if an

individual had acquired a job via an e-recruitment website before.

36

7. Conclusion

In this chapter the conclusion of the study is presented, where the purpose of the study is

answered.

This study aimed to describe brand equity and the determinants of brand equity on how it

affects individuals’ intention to use e-recruitment websites. The findings of this research

suggests that brand equity as a whole increases individuals’ intention to use an e-recruitment

website. When the determinant of brand equity are measured separately it can be observed

that brand awareness, perceived quality and brand loyalty are the three determinants, which

gave a positive and significant relationship towards individuals’ intention to use. Further,

according to the findings from this research it is suggested that perceived quality has the

highest impact on individuals’ intention to use an e-recruitment website followed by brand

loyalty and lastly brand awareness. Brand association is the only determinant of brand equity

that does not affects individuals’ intention to use e-recruitment websites. The results of a

positive relationship of brand equity towards intention to use is exchanged to a negative

relationship if the individual had acquired a job via an e-recruitment website before.

Although, when the determinants of brand equity was tested separately with the moderator it

had no effect.

37

8. Research Implications

This chapter presents implications, both theoretical and managerial, which were developed

from the findings in this study. Furthermore, the limitations of this study as well suggestions

for future research are presented.

8.1 Theoretical Implications

The topic brand equity has been widely explored in the branding literature (Farquhar, 1989;

Aaker, 1991; Park & Srinivasan, 1994; Keller, 1993). Although it has not been deeply

explored in a Swedish context of e-recruitment and how it affects individuals’ intention to

use. This research therefore tried to enlighten this relationship in order to contribute to the

branding literature.

This research aimed to describe brand equity and its determinants relationship to individuals’

intention to use e-recruitment websites. The result of this study suggests that the determinant

brand association should be used carefully since it did not have a significant value. However,

the findings should not falsify the theory, as the relation still may exist and instead the result

suggest that the aspect of brand association in the context of e-recruitment websites and

individuals’ intention to use should further be looked upon. However, this study contributes

by arguing that brand awareness, perceived quality and brand loyalty has a positive relation

towards intention to use which conforms with previous studies in similar areas (Hutter et al.,

2013; Netemeyer et al., 2004; Shukla, 2009). Therefore, in similar online contexts where self-

service systems are used, brand equity could be predictors of intention to use.

8.2 Managerial Implications

The result from this study has generated information about individuals’ intention to use e-

recruitment websites that can be valuable information for e-recruitment managers to obtain

into their marketing strategy. As the e-recruitment industry is one of the most widely

practiced e-business areas (Lee, 2011) this research can be of importance in order for e-

recruitment managers to know where to allocate resources in order for them to attract and

retain job seekers. Moreover, the findings of this research suggest that companies within the

e-recruitment industry should focus on building brand awareness, perceived quality and brand

loyalty in order to differentiate themselves from competitors in the market. Nevertheless, the

findings also showed that the main focus should be on the perceived quality as it had the

38

strongest relation towards intention to use. Regarding the aspect if the individual had acquired

a job gave diverse impact, it showed within brand equity’s relation to intention to use that

those who had acquired a job via an e-recruitment website were less likely to use an e-

recruitment website in the future. Given this information, e-recruitment managers should also

think of strategies that could make job seekers that already acquired a job via their e-

recruitment website to stay updated and make them follow the website in order to receive a

higher traffic on the e-recruitment website.

8.3 Limitations and Future Research

This research screened the data and made thoughtful measures to ensure a valid data to

provide for a relevant analysis on the hypothesis. However, since the data was collected on a

convenience sampling method there still might be some limitations to the research.

Firstly, collecting the data on random sampling method would perhaps create more diversity

in the data, which would be more generalizable. This study was made only on a Swedish

sample, which of 62.8% were students and 53.5% were in the age group of 25-29. The data

therefore could have been interesting if it would contain more of different age groups and

nationalities. Also, examine the data over borders could also give a different result as cultures

may have differed, as the research on brand equity by Aaker (1991) and Keller (2003), was

conducted on a different sample. Secondly, when asking if the respondents had a specific e-

recruitment website in mind when answering the questions made sure they were relating to a

specific e-recruitment website. However, it would also be interesting to see if groups who

searched for jobs in different sectors would perceive the e-recruitment websites differently,

and therefore showing different intentions to use depending on what type of job they are

looking for. This could give some insight for online companies of what sectors to explore

more on. Furthermore, research of brand equity on e-recruitment websites has been scarce and

the adopted measures to this context could have been more suitable for the context. Regarding

the aspect of intention to use and if the individual have acquired a job from an e-recruitment

website before gave a negative result. Meaning in a e-recruitment context, keeping satisfied

customers is a challenge, which could be further studied.

39

List of References

Aaker, D. A. 1991, Managing Brand Equity: Capitalizing the value of a brand name. New

York: THE FREE PRESS.

Aaker, D. A. 1996, “Measuring Brand Equity Across Products and Markets”, California

Management Review, Vol. 38, No. 3, pp. 102-120

Aaker, D.A., Kumar, V., George, D.S. and Robert, L.P. 2010, Marketing Research. (10th

edn). Asia: John Wiley and Sons.

Aczel, A. & Sounderpandian, J. 2009, Complete business statistics, McGraw-Hill, Boston,

Mass.

Agarwal, M.K. & Rao, R.V. 1996, “An Empirical Comparison of Consumer-Based Measures

of Brand Equity”, Marketing Letters, Vol. 7, No. 3, pp. 237-247

Ajzen, I. 1991, “The Theory of Planned Behavior”, Organizational Behavior and Human

Decision Processes, Vol. 50, Issue 2, pp. 179-211

Ajzen, I. and Fishbein, M. 1980, Understanding attitudes and predicting social behavior.

Englewood Cliffs, N.J.: Prentice-Hall.

Allen, D, Mahto, R, & Otondo, R. 2007, “Web-based recruitment: Effects of information,

organizational brand, and attitudes toward a Web site on applicant attraction”, Journal Of

Applied Psychology, Vol. 92, No. 6, pp. 1696-1708

Alwi, S, & Ismail, S. 2013, “A framework to attain brand promise in an online setting”,

Marketing Intelligence & Planning, Vol. 31, No. 5, pp. 557-578

Ambler, T. 1994, “Marketing's Third Paradigm: Guanxi”, Business Strategy Review, Vol. 5,

No. 4, p. 69

Atilgan, E, Aksoy, Ş, & Akinci, S. 2005, “Determinants of the brand equity: A verification

approach in the beverage industry in Turkey”, Marketing Intelligence & Planning, Vol. 23,

No. 3, pp. 237-248

Balaji, M. S. 2011, “Building Strong Service Brands: The Hierarchical Relationship Between

Brand Equity Dimensions”, IUP Journal Of Brand Management, Vol. 8, No, 3, pp. 7-24

Baron, R. M., & Kenny, D. A. 1986, “The moderator-mediator variable distinction in social

psychological research: Conceptual, strategic, and statistical considerations”, Journal of

Personality and Social Psychology, Vol. 51, No. 6, pp. 1173-1182

40

Belanche, D, Casaló, L, & Guinalíu, M. 2012, “Website usability, consumer satisfaction and

the intention to use a website: The moderating effect of perceived risk”, Journal Of Retailing

And Consumer Services, Vol. 19, Issue 1, pp. 124-132

Berry, L. 2000, “Cultivating service brand equity”, Journal of the Academy of marketing

Science, Vol. 28, No. 1 pp. 128-137

Bhatti, N, Bouch, A, & Kuchinsky, A. 2000, “Integrating user-perceived quality into Web

server design”, Computer Networks, Vol. 33, No. 1-6, pp. 1-16

Biedenbach, G. Bengtsson, M. & Marell, A. 2015, “Brand equity, satisfaction, and switching

costs: An examination of effects in the business-to-business setting”, Marketing Intelligence

& Planning, Vol. 33, No. 2, pp. 164-178

Brahmana, R, & Brahmana, R. 2013, “What factors drive job seekers attitude in using e-

recruitment?”, South East Asian Journal Of Management, Vol. 7, No. 2, pp. 123-134

Bryman, A. & Bell, E. 2011, Business Research Methods. 3rd ed. United States: Oxford

University Press Inc., New York.

Buil, I, Martínez, E, & de Chernatony, L. 2013, “The influence of brand equity on consumer

responses”, Journal Of Consumer Marketing, Vol. 30, No. 1, pp. 62-74

Chaffey, D. 2000, “Achieving Internet Marketing Success”, Marketing Review, Vol. 1, No.1,

pp. 35-59

Chen, S. 2001, “Assessing the impact of the Internet on brands”, Journal Of Brand

Management, Vol 8, Issue 4/5, pp. 288

Chen, Y, Shang, R, & Kao, C. 2009, “The effects of information overload on consumers”

subjective state towards buying decision in the internet shopping environment”, Electronic

Commerce Research And Applications, Vol. 8, pp. 48-58

Cho, Y. K. 2015, “Creating customer repurchase intention in Internet retailing: The effects of

multiple service events and product type”, Journal Of Retailing And Consumer Services, Vol.

22, pp. 213-222

Christodoulides, G, Cadogan, J, & Veloutsou, C. 2015, “Consumer-based brand equity

measurement: lessons learned from an international study”, International Marketing Review,

Vol. 32, No. 3/4, pp. 307-328

Christodoulides, G. & de Chernatony, L. 2010, “Consumer-based brand equity

conceptualisation and measurement”, International Journal Of Market Research, Vol. 52, No.

1, pp. 43-66

41

Christodoulides, G, de Chernatony, L, Furrer, O, Shiu, E, & Abimbola, T, 2006,

“Conceptualising and Measuring the Equity of Online Brands”, Journal Of Marketing

Management, Vol. 22, Issue 7/8, pp. 799-825

Cobb-Walgren, C .J. Ruble, C .A. & Donthu, N. 1995, “Brand equity, brand preferences, and

purchase intent”, Journal of Advertising, Vol. 24 No. 3, pp. 25-40

Creswell, J. W. 2014, Research design: qualitative, quantitative, and mixed methods

approaches. Fourth edition, international student edition. Los Angeles, Calif.: SAGE

Delgado-Ballester, E., Munuera-Aleman, J. L. & Yagoe-Guillin, M. J. 2003, “Development

and Validation of a Brand Trust Scale”, International Journal of Market Research, Vol. 45,

No, 1, pp. 35-53

Dineen, B, Ling, J, Ash, S, & DelVecchio, D. 2007, “Aesthetic properties and message

customization: Navigating the dark side of web recruitment”', Journal Of Applied Psychology,

Vol. 92, No. 2, pp. 356-372

Farquhar, P. H. 1989, “Managing Brand Equity”, Marketing Research, Vol. 1, No. 3, pp. 24-

33

Galanaki, E. 2002, “The decision to recruit online: a descriptive study”, Career Development

International, Vol. 7 No. 4, pp. 243-251

Ghauri, P. N. & Grønhaug, K. 2005, Research methods in business studies: A practical guide.

Harlow: Financial Times Prentice Hall.

Gommans, M. Krishman, K, & Scheffold, K. 2001, “From Brand Loyalty to E-Loyalty: A

Conceptual Framework”, Journal Of Economic & Social Research, Vol. 3, No. 1, pp. 43

Gravetter, F. J. & Wallnau L. B. 2008, Statistics for behavioural sciences, Cengage Learning,

Wadsworth, Belmont.

Gray, D. E. 2009, Doing Research in the Real World, 2nd ed., Sage Publications: London

Green, S. B. 1991, “How many subjects does it take to do a regression analysis?”,

Multivariate Behavioral Research, Vol. 26, No. 3, pp. 499‐510

Hair, J., Black, W., Babin, B. and Anderson, R. 2010, Multivariate Data Analysis, Upper

Saddle River: Pearson Education.

He, H, & Li, Y. 2011, “Key service drivers for high-tech service brand equity: The mediating

role of overall service quality and perceived value”, Journal Of Marketing Management, Vol.

27, No. 1/2, pp. 77-99

42

Hong-Youl, H. 2004, “Factors influencing consumer perceptions of brand trust online”,

Journal of Product & Brand Management, Vol. 13 Issue 5, pp. 329-342

Hutter, K, Hautz, J, Dennhardt, S, & Fuller, J. 2013, “The impact of user interactions in social

media on brand awareness and purchase intention: the case of MINI on Facebook”, Journal

Of Product & Brand Management, Vol. 22, No. 5, pp. 342-351

Hyde, F. K. 2000, “Recognising deductive processes in qualitative research”, Qualitative

Market Research: An International Journal, Vol. 3, Issue 2, pp. 82-90

Japhet, E, L. & Usman, A, T. 2010, “Barriers to ecommerce in developing countries”,

Information, Society and Justice, Vol. 3, No. 1, pp. 23-35

Jiang, L., Jun, M., & Yang, Z. 2015, “Customer-perceived value and loyalty: how do key

service quality dimensions matter in the context of B2C e-commerce?”, Service Business,

Vol. 25, No. 4, pp. 1-17

Kao, T, & Lin, W. 2016, “The relationship between perceived e-service quality and brand

equity: A simultaneous equations system approach”, Computers In Human Behavior, Vol. 57,

pp. 208-218

Keller, K. L. 1993, “Conceptualizing, measuring, and managing customer-based brand

equity”, The Journal of Marketing, Vol. 57, No. 1, pp. 1-22

Keller, K. L. 2001, “Building customer-based brand equity: A blueprint for creating strong

brands.”, Report number. 01-107, pp. 3-38.

Keller, K. L. 2003, Strategic Brand Management: Building, Measuring, and Managing Brand

Equity, 2nd ed., Upper Saddle River, NJ; Prentice Hall

Keller, K. L. 2013, Strategic Brand Management: Building, Measuring, and Managing Brand

Equity, 4th ed., Pearson, Boston, MA.

Keller, K. L. & Lehmann, D. 2006, “Brands and Branding: Research Findings and Future

Priorities”, Marketing Science, Vol. 25, Issue 6, pp. 740-759

Kim, J. Sharma, S. & Setzekorn, K. 2002, “A Framework for Building Brand Equity Online

for Pure-Play B2C Retailers and Services”, JMM: The International Journal On Media

Management, Vol. 4, No. 2, pp. 123-131

Kim, J. H. & Hyun, Y. J. 2011, “A model to investigate the influence of marketing-mix

efforts and corporate image on brand equity in the IT software sector”. Industrial Marketing

Management, Vol. 40, No. 3, pp. 424-438

43

Kimpakorn, N. & Tocquer, G. 2010, ”Service brand equity and employee brand

commitment”, Journal of Services Marketing, Vol. 24, Issue 5, pp. 378-388

Konecnik, M., & Gartner, W. C. 2007, ”Customer-based brand equity for a destination”,

Annals of Tourism Research, Vol. 34, Issue 2, pp. 400-421

Kuo, N, Chang, K, Chen, M, & Hsu, C. 2012, ”Investigating the Effect of Service Quality on

Customer Post-Purchasing Behaviors in the Hotel Sector: The Moderating Role of Service

Convenience”, Journal Of Quality Assurance In Hospitality & Tourism, Vol. 13, No. 3, pp.

212-234

Kucuk, U, S. & Krishnamurthy, S. 2007, “An analysis of consumer power on the Internet”,

Technovation, Vol. 27, No. 1, pp. 47-56

Lee, I. 2007, “An architecture for a next-generation holistic e-recruiting system”,

Communications Of The ACM, No. 50, Vol. 7, pp. 81-85

Lee, I. 2011, “Modeling the benefit of e-recruiting process integration”, Decision Support

Systems, Vol. 51, No.1, pp. 230-239

Lee, J. & Lee, J. 2015, ”How purchase intention consummates purchase behaviour: the

stochastic nature of product valuation in electronic commerce”, Behaviour & Information

Technology, Vol. 34, No. 1, pp. 57-68.

Lennon, R. & Harris, J. 2002, “Customer Service on the Web: A Cross Industry

Investigation”, Journal of Targeting, Measurement and Analysis for Marketing, Vol. 10, No.

4, pp. 325-338

Lin, Y., Lin, F. & Ryan, C. 2014, “Tourists' purchase intentions: impact of franchise brand

awareness”, Service Industries Journal, Vol. 34, No. 9/10, pp. 811-827

Malhotra, N. K. & Birks, D.F. 2010, Marketing Research: An Applied Orientation. London:

Pearson Education.

Malhotra, N. K., Birks, D. F. & Wills, P. 2012, “Marketing research: an applied approach”.

4. ed. Harlow: Pearson

Meuter, M. L., Ostrom, A. L., Roundtree, R. I., & Bitner, M. J. 2000, “Self-service

technologies: understanding customer satisfaction with technology-based service encounters”,

Journal of marketing, Vol. 64, No. 3, pp. 50-64

Nath, P. & Bawa, A, 2011, “Measurement of brand equity of services-scale construction and

validation”, Journal Of Services Research, Vol. 11, No. 2, pp. 135-154

44

Nardi, P. M. 2003, Doing Survey Research: A Guide To Quantitative Methods, Allyn and

Bacon, Boston

Netemeyer, R, Krishnan, B, Pullig, C, Wang, G, Yagci, M, Dean, D, Ricks, J, & Wirth, F.

2004, “Developing and validating measures of facets of customer-based brand equity”,

Journal Of Business Research, Vol. 57, Issue 2, pp. 209-224

Ngai, E. W. T. & Gunasekaran, A. 2007, “A Review for Mobile Commerce Research and

Applications”, Decision Support Systems, Vol. 43, No. 1, pp. 3-15

Nolan S., & Heinzen T. 2008, Statistics for the behavioural sciences, Worth publishers, 1st

edition

O'Gass, A, & Grace, D. 2004, “Exploring consumer experiences with a service brand”,

Journal Of Product & Brand Management, Vol. 13, No. 4, pp. 257-268

Page, C., & Lepkowska-White, E. 2002, “Web equity: a framework for building consumer

value in online companies”, Journal of Consumer Marketing, Vol. 19, No. 3, pp. 231-248

Pallant, J. 2010, “SPSS Survival Manual: A step by step guide to data analysis using SPSS”

4th Edition, Allen & Unwin, Australia

Parasuraman, A., Zeithaml, V., & Berry, L. 1985, “A Conceptual Model of Service Quality

and Its Implications for Future Research”, Journal of Marketing, Vol. 49, No. 4, pp. 41-50

Park, C., & Srinivasan, V. 1994, “A Survey-Based Method for Measuring and Understanding

Brand Equity and Its Extendibility”, Journal Of Marketing Research (JMR), Vol. 31, No. 2,

pp. 271-288

Park, Y, Gretzel, U, & Sirakaya-Turk, E. 2007, “Measuring Web Site Quality for Online

Travel Agencies”, Journal Of Travel & Tourism Marketing, Vol. 23, No. 1, pp. 15-30

Pfieffelmann, B., Wagner, S., & Libkuman, T. 2010, “Recruiting on Corporate Web Sites:

Perceptions of fit and attraction”, International Journal Of Selection & Assessment, Vol. 18,

No. 1, pp. 40-47

Pike, S., Bianchi, C., Kerr, G. & Patti, C. 2010, “Consumer-based brand equity for Australia

as a long-haul tourism destination in an emerging market”, International marketing review,

Vol. 27, No. 4, pp. 434-449

Pinar, M, Trapp, P, Girard, T, & Boyt, T. 2014, “University brand equity: an empirical

investigation of its dimensions”, International Journal Of Educational Management, Vol. 28,

No. 6, pp. 616-634

45

Rafiq, M., Fulford, H., & Lu, X. 2013, ”Building customer loyalty in online retailing: The

role of relationship quality”, Journal Of Marketing Management, Vol. 29, Issue 3/4, pp. 494-

517

Richardson, R. 2011, “Business Applications of Multiple Regression (Quantitative

Approaches to Decision Making Collection)” [Electronic resource]. Business Expert Press

Rios, R, & Riquelme, H. 2008, “Brand equity for online companies”, Marketing Intelligence

& Planning, Vol. 26, No. 7, pp. 719-742

Rios, R, & Riquelme, H. 2010, “Sources of brand equity for online companies”, Journal Of

Research In Interactive Marketing, Vol. 4, Issue. 3, pp. 214-240

Rosenbaum-Elliott, R, Percy, L, & Pervan, S., 2011, Strategic Brand Management, Oxford:

Oxford University Press

Saunders, M., Lewis, P. & Thornhill, A. 2009, Research methods for business students.

Harlow: Financial Times Prentice Hall

Selden, S, & Orenstein, J. 2011, “Government e‐recruiting web sites: The influence of

e‐recruitment content and usability on recruiting and hiring outcomes in US state

governments”, International Journal Of Selection And Assessment, Vol. 19, No. 1, pp. 31-40

Shugan, S. 2005, “Brand loyalty programs: Are they shams?” Marketing Science, Vol. 24,

No. 2, pp. 185-193.

Shukla, P. 2009, “Impact of contextual factors, brand loyalty and brand switching on purchase

decisions”, Journal of Consumer Marketing, Vol. 26 Issue 5, pp. 348-357

Simon, C. J. & Sullivan, M. W. 1993, “The measurement and determinants of brand equity: A

financial approach”, Marketing science, Vol. 12, No, 1, pp. 28-52

Singh, L, & Narang, L. 2008, “Behavioral Revelation Concerning E-Recruitments”, ICFAI

Journal Of Organizational Behavior, Vol. 7, No. 4, pp. 45-53

Sylva, H. & Mol, S. T. 2009, “E-Recruitment: A study into applicant perceptions of an online

application system”, International Journal of Selection and Assessment, Vol. 17, No. 3,

pp. 311–323

Thielsch, M, Träumer, L, & Pytlik, L. 2012, “E-recruiting and fairness: the applicant's point

of view”, Information Technology & Management, Vol. 13, No. 2, pp. 59-67

Tsiotsou, R. 2006, “The role of perceived product quality and overall satisfaction on purchase

intentions”, International Journal Of Consumer Studies, Vol. 30, No. 2, pp. 207-217

46

Wang, W., Liang, C., & Wu, Y. 2006, Relationship bonding tactics, relationship quality, and

customer behavioral loyalty-behavioral sequence in Taiwan’s information services industry”,

Journal of Services Research, Vol. 6, No. 1, pp. 31–57

Yang, Z., & Fang, X. 2004, “Online service quality dimensions and their relationships with

satisfaction: A content analysis of customer reviews of securities brokerage services”,

International Journal of Service Industry Management, Vol. 15, No. 3, pp. 302-326

Yoo, B. & Donthu, N. 2001, “Developing and validating a multidimensional consumer-based

brand equity scale”, Journal of Business Research, Vol. 52, No. 1, pp. 1-14

Yoo, B., Donthu, N. & Lee, S. 2000, “An examination of selected marketing mix elements

and brand equity”, Journal of the Academy of Marketing Science, Vol. 28, No. 2, pp. 195-211

Zeithaml, V, A. (1988), “Consumer Perceptions of Price, Quality, and Value: A Means-End

Model and Synthesis of Evidence”, Journal Of Marketing, Vol. 52, No. 3, pp. 2-22

Zeithaml, V, Berry, L, & Parasuraman, A. 1996, ”The Behavioral Consequences of Service

Quality”, Journal Of Marketing, Vol. 60, No. 2, pp. 31-46

Zhang, S., van Doorn, J., & Leeflang, P. 2014, “Does the importance of value, brand and

relationship equity for customer loyalty differ between Eastern and Western cultures?”,

International Business Review, Vol. 23, No. 1, pp. 284-292

Zhilin, Y., Minjoon, J., & Peterson, R. 2004, “Measuring customer perceived online service

quality”, International Journal Of Operations & Production Management, Vol. 24, No. 11,

pp. 1149-1174

47

Appendix 1 - Descriptive of the constructs items

Construct Item Mean Std. Deviation

Intention to use

ITU1 5.39 1.399

ITU2 5.76 1.155

ITU3 5.30 1.394

Brand Awareness AW1 5.99 1.016

AW2 5.88 1.265

Brand Association

AS1 5.86 1.148

AS2 5.67 1.224

AS3 5.83 1.130

AS4 4.16 1.362

AS5 4.27 1.418

Perceived quality

PQ1 5.62 1.130

PQ2 5.62 1.217

PQ3 5.80 .973

PQ4 5.30 1.416

PQ5 5.63 1.241

PQ6 5.84 1.215

Brand Loyalty

BL1 4.04 2.060

BL2 4.95 1.554

BL3 3.94 2.030

48

Appendix 2 – Online Questionnaire

Dear participants,

We are three students at Linnaeus University within the field of marketing. We are currently

writing our Master's thesis and would appreciate if you could help us fill in this survey. The

survey will only take a couple of minutes to perform and your answers will be treated

anonymously.

E-recruitment websites are a link between the employer and the potential candidate. The

website advertises jobs that may be relevant based on a candidate's customized profile which

makes the job seeking process easier. Ex, Graduateland, MyCareer, Monster, Cruitway,

Student Consulting and Academic Work.

If you have any concerns regarding the questionnaire, please contact: jj222hw@student.lnu.se

Thanks in advance!

Joakim, Mathias & Sebastian

Part 1

Control questions

1. I have used e-recruitment websites before.

☐ Yes

☐ No

2. Which e-recruitment website are you most active on?

Please, type the e-recruitment website that you are most active on.

49

Part 2

Please, have the e-recruitment website you wrote in the previous section in mind when

answering the following questions.

Answer the questions by choosing a number on the scale rating from one to seven, depending

on how you relate the question towards your e-recruitment website.

1 = Strongly Disagree, 2 = Disagree, 3 = Slightly Disagree, 4 = Neither Agree or Disagree, 5

= Slightly Agree, 6 = Agree, 7 = Strongly Agree.

Brand awareness

3. I recognize this e-recruitment website among other similar websites.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

4. I would recognize the logo of this e-recruitment website.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

5. I only use e-recruitment websites that I am aware of.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

6. I came in contact with this e-recruitment website because I heard about it from

friends or family.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

50

Brand association

7. I trust this e-recruitment website.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

8. I trust that this e-recruitment website keeps my personal information safe.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

9. It feels safe to disclose personal information on this e-recruitment website.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

10. The customer service is easy to contact on this e-recruitment website.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

11. The customer service can be contacted in different ways on this e-recruitment

website.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

Perceived Quality

12. This e-recruitment website has high quality.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

13. It is easy to navigate on this e-recruitment website.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

51

14. The information is easy to understand on this e-recruitment website.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

15. This e-recruitment website has an appealing design.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

16. This e-recruitment website offer jobs that is of good quality.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

17. This e-recruitment website has a wide variety of job offers.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

Brand loyalty

18. I consider myself to be loyal to this e-recruitment website.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

19. This e-recruitment website would be my first choice.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

20. I will not choose other e-recruitment websites if this e-recruitment website is

available.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

52

Intention to use

21. The likelihood that I use this e-recruitment website is high.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

22. I think it is a good idea to use this e-recruitment website.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

23. I am eager to use this this e-recruitment website in the future.

1 2 3 4 5 6 7

Strongly disagree ☐ ☐ ☐ ☐ ☐ ☐ ☐ Strongly agree

Moderator question

24. Have you ever got an employment via an e-recruitment website?

☐ Yes

☐ No

Control variables

25. Gender

☐ Female

☐ Male

26. Age

☐ 18-24

☐ 25-29

☐ 30-34

☐ 35-39

☐ 40-44

☐ 45-49

☐ 50+

53

27. Occupation

☐ Student

☐ Employed

☐ Unemployed

☐ Other

28. Level of education

☐ Secondary school

☐ High school

☐ Bachelor or equivalent

☐ Master or equivalent

☐ Other

If you answered "other" on the previous question, please type your education here.

54