Do emotions matter? A quantitative research in Employer branding.

Author:

Henrik Gedda

Nicklas Nordmark

Supervisor: Viktor Magnusson

Examiner: Åsa Devine

Date: 2017-05-24

Subject: Branding

Level: Bachelor

Course code: 2FE21E

Abstract Employer branding is a key concept when managing human resources. Such

management distinguishes the possibility to increase attractiveness with the use of

employer brand associations when being an employer of choice. Employer brand

emotions have been displaced to have fundamental role in prediction of becoming an

employer of choice, as positive emotions boost employer branding.

Students are entering the business world and it is of importance to create an

understanding of what variables students find as most attractive. By creating an

understanding of the most essential variables in the right environment, organisations can

differentiate and attract the most talented students. Hence, the purpose of this research is

to describe the impact of employer brand emotions as a mediator between the

relationship of employer brand associations and being an employer of choice, when

investigating in a new context. Empirical data has been gathered among student on a

university level in Sweden, studying economy courses, through the data collection

method of a quantitative approach. Questionnaires were sent out and 133 respondents

were used to create an understanding of the impact of emotions in regard to the

relationship between employer brand associations and an employer of choice.

The results indicate emotions to have a big influence on employer brand associations

and moreover work content and social value to be the most fundamental employer brand

associations in regard to emotions when investigating the perception of students.

Therefor it is of great importance for management levels to understand the importance

of the two variables when attracting Swedish students studying economy.

Keywords Employer branding, employer of choice, employer brand emotions, employer brand

associations, advancement opportunity, brand reputation, economic value, social value,

work content.

Acknowledgements First and foremost, we would like to direct our biggest thanks to Viktor Magnusson for

always prioritize us whenever we needed help and guide us through this bachelor thesis.

Without his help this research would not be of the same quality as it turned out to be.

We would also like to thank Dr. Setayesh Sattari for her support with our problematic

methodology chapter and conceptual framework due to her impeccable knowledge

within the field.

Last but not least would like to express our thanks to Åsa Devine, who always pushed

us to do our best with the paper and always trying to increase the quality of our work.

We would also like to send a thanks to our opposition group who always made their

furthest to find improvements with our paper.

Linnaeus University, 2017-05-24

Henrik Gedda Nicklas Nordmark

______________________ ______________________

Table of content 1. Introduction 1

1.1 Background 1

1.2 Problem discussion 2

1.3 Purpose 4

2. Theoretical framework 5

2.1 Employer brand associations 5

2.1.1 Advancement opportunity 7

2.1.2 Brand reputation 7

2.1.3 Economic value 8

2.1.4 Social value 8

2.1.5 Work content 8

2.2 Employer of choice 9

2.3 Employer Brand Emotions 9

3. Conceptual framework 12

4. Methodology 17

4.1 Research approach 17

4.1.1 Deductive vs inductive 17

4.1.2 Quantitative vs Qualitative research 18

4.2 Research purpose 19

4.2.1 Exploratory, descriptive and explanatory research 19

4.3 Research design 20

4.4 Data source 22

4.5 Data collection method 23

4.5.1 Questionnaires 23

4.5.2 Questionnaire design 24

4.5.3 Execution questionnaire design 25

4.5.4 Operationalization 26

4.5.5 Pre-testing 28

4.5.6 Results - Pre-test questionnaire 29

4.6 Sampling 29

4.6.1 Sampling Frame and Sample Selection 30

4.7 Data analysis method 31

4.7.1 Descriptive statistics 31

4.7.2 Regression 32

4.7.3 Mediation analysis 33

4.8 Quality criteria 35

4.8.1 Reliability 35

4.8.2 Replication 36

4.8.3 Validity 37

4.9 Ethical principles 38

4.10 Chapter summary 40

5. Results 41

5.1 Descriptive statistics - Sample 41

5.2 Hypothesis testing 43

5.2.1 Descriptive statistics 43

5.2.2 Multiple Linear Regression Analysis 43

5.2.3 Mediation analysis 45

5.2.5 Reliability (Cronbach’s alpha) 46

5.2.6 Validity (Correlation) 46

6. Discussion 47

7. Conclusion 50

7.1 Managerial implications 51

7.2 Academic implications 51

8. Limitations and future research 52

Reference list 53

Appendices I

Appendix 1 I

Appendix 2 IX

Appendix 3 X

Appendix 4 XI

Appendix 5 XII

Appendix 6 XIII

Appendix 7 XV

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1. Introduction 1.1 Background Branding is a common term within marketing, describing the management of a brand’s

attributes, hence seeking to enhance the consumer’s value when purchasing a product

(Armstrong and Kotler, 2011). Through such management, marketers aim for improving

the perception and attitude customers have towards the brand (Kapferer, 2008).

However, branding is not only used for products but additionally for management to use

within human resources. By working with such management, a company can reach a

superior attractiveness for potential employees over other companies. This kind of

management is often entitled as employer branding, a management concept most

essential to attract the most talented employees in today's globalised business world

(Backhaus and Tikoo, 2004). The term of employer branding is defined as “a targeted,

long-term strategy to manage the awareness and perceptions of employees, potential

employees, and related stakeholders with regards to a particular firm” (Backhaus and

Tikoo, 2014, p.501). Similarly, to brand associations, employer branding aims to create

employer brand associations, a perfect image of the company, in order to gain

attractiveness on the employment market (Verma and Ahmad, 2016). Employer brand

association could for instance be the brand’s reputation, opportunity for advancement

within the company or work environment (Rampl, 2014).

Manpower group, a multinational recruitment agency has presented research regarding

the shortage of talents within global businesses 2016/2017. Reports involving 42 300

employers in 43 countries display forty percent of the employers to report a difficulty of

employing individuals to fill the job application, which is the highest percentage

received since 2007 (Manpower group, 2017). However, by applying the concept of

employer branding, organisations are capable of employing more skilled and talented

employees. (Parment and Dyhre, 2009). Furthermore, with the increased competition to

attract potential employees, portraying favourable employer brand associations have a

tendency to differentiate a strong brand towards competitors (Jain and Bhatt, 2015).

Hence, making it difficult for competitors to imitate the brand and thus providing a

competitive advantage of attracting employees (Wright, et al., 1995).

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In the essence of achieving advantage and competitiveness on the employment market,

an organisation must continually compete to attract and find the most attractive talents

by becoming an employer of choice (Branham, 2005). The concept of employer of

choice means that organisations define and differentiate themselves for external

reputation. Employer of choice is further described to portray important attributes

providing a recognition of being the best employment practice, meaning individuals

choose to work for an employer over alternative employers. An employer of choice also

implies that employees tend to portray higher engagement levels and loyalty towards

the employer, hence the possibility for a longer employment increases. (Sedighi and

Loosemore, 2012; Parment and Dyhre, 2009). Sedighi and Loosemore (2012) describe

series of associations to affect the employer of choice including variables concerning

personnel, work benefits and salary. In addition to the prospect of achieving advantage

by competing of attracting employees, Rampl (2014) has presented research regarding

how employer brand emotions affects the perceptions of a variable which affects the

employer of choice. Employer brand emotions indicated the ability to predict becoming

an employer of choice and the researcher enhances for an inclusion of employer brand

emotion when researching the aspect of employer branding and employer of choice.

Rampl (2014) predicts the importance of employer brand emotions and the

attractiveness of a brand, where positive emotions boost employer branding.

1.2 Problem discussion

The growing globalization increases the importance for organizations to attract the most

talented employees in a world wide competitive employment market (Jain and Bhatt,

2015; Almacik, et al., 2014). By creating an understanding of what variables attract

employees to an organisation, organisations can attract the right employee for the

specific employment (Almacik, et al., 2014). Research has found several different

variables which affect people in their choice of a preferable employer, i.e. Berthon,

Erwing and Hah (2005), Rampl (2014), Bellou, et al. (2015). For instance, Berthon,

Ewing and Hah (2005) discovered the variables of economic-, interest-, social-,

development- and application value to have a remarkable effect for an employer of

choice when investigating final-year students in Australia. Rampl (2014) further found

that advancement, reputation, salary, location, work content and work culture to have an

essential role in the context of consulting students in Germany, whereas Bellou, et al.

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(2015) discovered the variables of remuneration, relationship, opportunities, recognition

and corporate image in the context of employees.

Although the variables discovered are very similar, the context of each study is

different. Almacik, et al., (2014) describe the importance for organisations to customize

the employer brand associations to address different cultures and nationalities. Almacik,

et al. (2014) and Bellou, et al. (2015) argue for differences between nations and address

the importance of further research on various nationalities in order to create an

understanding of how to attract employees from from different nations, but also to

attract students, who are on the verge of entering the business world (Berthon, Ewin and

Hah, 2005).

Berthon, Ewin and Hah (2005) argue for students to have low employment experience.

although students are perceived to be the primary target for businesses, as the students

are to advance into the business life within a near future (Berthon, Ewin and Hah,

2005). Jain and Bhatt (2015) portray the importance of organisations to develop an

understanding of what expectations newly graduates are to consider as important

variables when searching for a first employment. Rampl (2014) and Almacik, et al.,

(2014) describe the limited research of the concept of employer of choice in different

industries and address for future research to minimize the gap. This research will

contribute with a specific industry regarding university students within economy

programmes, in Sweden, as according to SCB (2016), the largest amount of newly

examined students in Sweden come from programmes within business and

administration. Almost 8000 people were granted a degree within the field during the

academic year of 2015/2016 (SCB, 2016). As Almacik, et al., (2014) and Bellou, et al.

(2015) discuss the relevance of attracting the most appropriate employees in a

competitive market which may be of particular concern due to the large number of

students within the specific field. Businesses therefore have to create an understanding

of the most important variable of the potential employees in order to become the

employer of choice (Parment and Dyhre, 2009; Rampl, 2014).

Rampl, et al. (2014) further describe limited research of what aspects affect the

decision-making process of an employer brand. However, emotion is a considerable

variable for the brand management when attracting potential employee candidates and

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affecting their decision-making process of the employer of choice (Chou, et al., 2007;

Rampl, et al., 2014) Due to the lack of research of the relationship between employer

brand emotions and employer branding, the brand employment management most often

underestimates the efficient use of employer brand emotions associated with

attractiveness of an employer (Rampl, et al., 2014). Rampl, et al. (2014) suggest for

management levels to follow a similar approach as in regard to linking positive

emotions to consumer brands as the positive employer brand emotions have a

substantial impact on decisions (Vytal and Hamann, 2010; Rampl, et al., 2014; Deppe,

et al., 2005). The management can therefore apply a similar process, linking positive

emotions in the recruitment process to attract the most profitable employees for the

company. Moreover, Rampl, et al. (2014) suggest for employer brand emotions to be

integrated in the theoretical approach in research regarding employer brands for further

research, however, the question of the associations between employer brand emotions

and certain employer brand associations remain. Only Rampl (2014) has approached the

question, where the researcher provided results indicating the brand associations of

work content and work culture to be connected to employer brand emotions. The results

provided an indication of an employer of choice only to be established if employer

brand associations mend out into positive employer emotions. Hence, this research

will further contribute with an important understanding and describe the association

between positive emotions and employer brand associations in the sense of attracting

potential employees. The contribution will follow a replication of earlier research

conducted by Rampl in 2014 due to the limited research within employer brand

emotions role in employer branding.

1.3 Purpose

The purpose of study is to describe the relationship between employer brand

associations, employer brand emotions and employer of choice.

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2. Theoretical framework The following theoretical framework will begin with a literature review about employer

brand associations and further explain the chosen associations used within this

research in more depth. Additionally, the concepts of employer brand emotions and

employer of choice is explained since these also will be used as important variables

throughout the research.

2.1 Employer brand associations

According to Mandhanya and Shah (2010), brand associations are the connections of

ideas which arise in a consumer's mind when thinking of a brand’s name. Hence, brand

associations are key factors of a brand’s image. Employer brand image on the other

hand is the brands’ associations in relation to an employment. These associations could

thus be variables as; work environment, salary and so forth (Mandhanya and Shah,

2010).

According to Rampl (2014), there are former studies investigating employer brand

associations. Although some research might use the concept of employer brand

attractiveness, Rampl include this concept with employer brand associations. Previous

research made by Collins and Zedeck (2007), investigates the behaviours of people

seeking an employment and the different variables that are included. How aware the

applicant is of the employer, as well as the brand’s products and services showed to be

essential. The brand image and reputation also appeared to affect applicants when

applying for jobs. Earlier research by Cable and Turban (2003) additionally

present brand reputation to be an important factor related to employer brand

associations.

In 2005, Berthon, Ewing and Hah identified five variables which are influential when

choosing an employer. The scale created by the researchers contains variables of;

economic value which connects to employee salary and interest value which measures

the personal interest an employee has towards the work assignments. Social value

includes the environment of the work, whereas development value and application value

indicates for the advancement and opportunity to contribute with own knowledge. The

6

study further shows that the variable of social value was proven to be the most vital

variable when choosing an employer (Berthon, Ewing and Hah, 2005).

More recently research by Bellou, et al. (2015) investigated the components of an

employer of choice among working adults. The study shows results of five variables;

remuneration, relationship, opportunities for self development, recognition and

corporate image. Remuneration measures salary and added value, relationship shows the

relationship between the employee and the colleagues as well as the

managers. Corporate image could be seen as the reputation of the company and self

development as opportunity of advancement.

Rampl (2014) contributes with results indicating the variables of work content and work

culture to be the driving variables of becoming the first brand of choice. Moreover,

employer brand emotion was considered as a mediator for the constructed model,

suggesting the variables to be coupled with employer brand emotions. Results predict

positive emotions of brand associations to be the significant factor of becoming an

employer of choice. The results further provided no evidence of salary, advancement,

location and reputation to have any emotional support of becoming an employer of

choice The constructed study is the first framework investigating the driver of employer

brand emotion in regard to an employer of choice (Rampl, 2014).

By summarizing the variables discovered throughout the literature review, only

including variables which are mentioned by several authors, the variables which will be

used within this research are; advancement opportunity, brand reputation, economic

value, social value and work content. Since Rampl’s variable of Location and Berthon,

Erwing and Hah’s variable of application value are not used within other studies, these

will be excluded from the remainder of this research. The variable of economic value

includes the variable of salary as mentioned by Rampl and additionally includes the

aspect of added value as mentioned by Bellou et al. Social value indicates Berthon,

Ewing and Hah’s variable, but additionally the variable of work culture, presented by

Rampl and relationship presented by Bellou et al. Work content indicates for the work

assignments employees are given, whether the assignments are challenging or if the

employee finds a personal interest in the assignments.

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2.1.1 Advancement opportunity

Figurska and Matuska (2013) discuss that a business is to provide the employee with a

development value to the extent of which the employee is attracted to the business. The

development factor for employees ensures the possibility for employees to learn new

technologies and contribute additionally to the organisation (Mak and Sockel, 1999).

The business should provide confidence building opportunities coupled with

advancement opportunities within the business in order to maintain the attractiveness of

the employee (Figurska and Matuska, 2013). Developing employees with international

assignments have a positive impact on the employee and enhance the possibility for a

development of an international career (Dickmann and Harris, 2005). Backhaus and

Tikoo (2004) discuss business internal training, such as workshops and seminars (Mak

and Sockel, 1999) to present further opportunities of advancement, enhancing the

experience of the brand, hence, attracting potential employees. The investment in

employer training does not only reward the organisation with more competence but

additionally adds to the satisfaction among employees and customers of the organisation

(Roper and Davies, 2010).

2.1.2 Brand reputation

Bellou, et al. (2015) explain that the variable of brand reputation to include the financial

stability of the brand, as well as whether the brand develops innovative and modern

products. The term of reputations acts as a contributor of the perceived quality of a

brand and the products of the brand name. The reputation reflects the expectation of

consumers, and the expectations of the quality of products as the consumers expect the

quality of the products to correlate to the brands reputation (Milewicz and Herbig,

1994) The brand reputation also includes the company’s targeted market and how the

brand is facing social and environmental issues such as global warming (Bellou, et al.,

2015). According to Cable and Turban (2003) with support of Collins and Zedeck

(2007) there are scientific findings which show that people who are searching for an

employment are more attracted to brands with stronger reputation, than brands with less

or no reputation. However, if stated market targets of an organisation are failed to be

achieved, negative perceptions will occur and reduce the strong reputation of a brand

(Milewicz and Herbig, 1994). Milewicz and Herbig (1994) continue to explain the

development of brand reputation, by describing reputation to be something that is

earned over a period of time depending on how individuals evaluate a brand.

8

2.1.3 Economic value

In order to retain and attract talented employees, the economic value is essential and the

employees have to feel fairly paid for the work they contribute with (Figurska and

Matuska, 2013). Caldwell, Chatman and O'Reilly (1990) explain extrinsic rewards,

physical rewards for achievement, to reflect an essential role in the commitment

towards an employer. Figurska and Matuska (2013) further explain that the economic

value reflects if the brand offers a salary above average or the opportunity of

promotions. With an increase of salary an employee's affection towards and employer

and the work performance may be enhanced (Zhao and Zhou, 2008).

2.1.4 Social value

The variable of social value refers to the extent of which an employer provides the

employees with an attractive social environment. The social environment of a business

is to provide the employees with a fun, creative and supportive team atmosphere

(Figurska and Matuska, 2013). Berthon, Erwing and Hah (2005) further explain that the

relationship an employee has with both colleagues and managers are included in the

variable of social value. Albinger and Freeman (2000) describe that with a positive

social relationship within the organisation, organisations can display positive levels of

ethical and moral reflections which provide benefits. The benefits reflect the advantage

of increased positive reputation and enhanced motivation levels among employees

resolving in beneficial employer attractiveness.

2.1.5 Work content

The variable of work content does not entirely reflect the assignments employees are

supposed to do, but instead how challenging the assignments are and how challenged

the employees are when performing the work assignments (Agrawal and Swaroop,

2009). Agrawal and Swaroop (2009) further mean that the level of working

independently and empowerment towards certain assignments are included into the

variable. Bellou, et al. (2015) discuss the employee's personal interest towards the

brands products to be accounted within the variable as well. With interests matching the

work environment, the employees are perceived to involve themselves more with the

work content and also provide the organisation with a boosted motivational level. (De

Fruyt, 2002). Moreover, Lievens, Van Hoye and Anseel (2007) mention in their study

9

that the variable of work content also could include the amount of variety of work

assignments an employee has.

2.2 Employer of choice

Lately, in order to gain advantage of the competition on the market, employer branding

has become a new approach. The approach of employer branding targets the process of

creating a company message in order to become an employer of choice (Sutherland,

Toricelli and Karg 2002; Branham, 2005). Sutherland, Toricelli and Karg (2002)

describe a candidate of becoming an employer of choice refers to the status and

reputation of an organisation. The organisations which outperform the market in sense

of competition when developing, attracting and retaining talented employees are

described as the employers of choice.

The employers of choice achieve the advantage in regard to the recognition which is

achieved through beneficial employee advantages of the employer. The employee

advantage mends out in a choice of employer for a talent, due to the results of

reputation, which is appealed to the targeted audience. The concept of becoming an

employer of choice does not refer to only receiving more applicants, moreover shifting

objective to attract the best of the best, attracting employees who choose to work for an

employer over another (Sutherland, Toricelli and Karg 2002; Sedighi and Loosemore,

2012).

2.3 Employer Brand Emotions

Rosenbaum-Elliott (2015, p. 24) states “emotions are made up of a number of

components, most often considered within the context of the so-called ‘reaction triad’ of

psychological arousal, motor expression and subjective feeling.”. Emotions are

experienced by everyone, either through the primary source of emotions reflecting

surprise, anger, disgust, sadness, fear or joy, or through the secondary emotions.

Secondary emotions are constructed through experience while the primary source of

emotions is argued to the same for everyone. As emotions are experienced by everyone,

Rampl, et al. (2014) argue for emotions to be a relevant factor of decision-making in

order to understand the beneficial use of employer brand management.

10

The decision making process is advised to be strongly driven by emotions as individuals

shift focus to features of opportunity (Chou, et al., 2007). Rampl, et al. (2014) present

results of a research focusing on the role of emotions in the decision-making process on

employer brands by using functional magnetic resonance illustration of the brain. The

results indicate emotions to affect the decision-making process of employer brands. In

contrast to employers of choice, less preferable employer brands processed less brain

activity in the regions of emotional processing, hence resulting in less emotional

attachment towards an employer brand (Rampl, et al., 2014). Further research provides

results indicating the importance of employer brand emotions in regard to the choice of

a brand, as results from different researches strengthen the connection between

decisions which include emotions. (Vytal and Hamann, 2010; Rampl, et al., 2014;

Deppe, et al., 2005).

Employer brands associated with employer brand emotions is defined by Rampl, et al.

(2014) as an underestimated power within brand employment management, considering

the lack of research within employer brand emotions and employer branding. However,

the competitive era has started to create a recognising value of the differentiation of a

brand considering emotional components for instance, trust, pride and security (Lynch

and de Chernatony, 2004) Creating an increased attractiveness as an employer requires

for a positive stimulus to be established, thus increasing the positive emotions as a

potential employer brand. The more positive stimuli, the higher chance of increasing the

positive emotions associated with the brand, resolving in higher attractiveness as an

employer (Rampl, et al., 2014). Albert and Merunka (2013) present research providing

evidence of the emotional benefits resolving in loyalty towards the brand and thus

develop resistance of appealing to a competitive brand.

The positive emotions and stimulus created are argued by Laros and Steenkamp (2005)

to include more than a general concept of emotion, as the research describes emotions

of contentment, happiness, love and pride. The general concept of joy has a broad

definition and the authors argue for basic emotions to be included in research, separately

compared to the large concept of emotion and joy. Gruber et al., (2011) are further

aligned with earlier research conducted regarding the topic of pride as an emotion. The

label of positive emotions is a broad concept, however, results provided by

11

Griskevicius, Shiota and Nowlis (2010), describe the role of the positive emotion of

pride, to affect the judgement level of an individual.

Moreover, research regarding the customer experience, addressing the link of emotions,

provided results of the positive emotions of inspiration and joy to be key determinants

of goal congruency, indicating that addressing basic positive emotions to provide results

is of concern (Liu, Sparks and Coghlan, 2016). Other researchers describe the

relationship between emotional response and the term of inspiration. Inspiration inspires

for positive emotions, contributing with happiness and better well-being for an

employer (Yuan, 2015; Thrash and Elliot, 2003). Straume and Vittersø (2012)

additionally add to the positive- activated emotion of inspiration to be associated with

the behaviour of an individual. Further Thrash and Elliot (2003) provide results of the

positive relationship of inspiration to create positive emotions. The results indicate

inspiration to impact the individual positively and strengthens the relation of emotion

and inspiration.

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3. Conceptual framework For this chapter, the four hypotheses tested in this research is presented and argued for.

Each hypothesis will have its own model explaining the relationship in the model.

It has been hypothesized that employer brand associations have a positive relationship

with employer brand emotions. The theoretical framework describes limited research of

such emotions and certain employer brand associations, however employer brand

emotions are argued to be an essential variable in employer branding. The conceptual

framework illustrates the relationship between specific employer brand associations and

employer brand emotions, which is defined from a regression analysis for an

interpretation of the statistical relationship. The relationship is drawn from each

independent variable of employer brand associations and the dependent variable of

employer brand emotions.

H1. Employer brand associations have a positive relationship with employer brand

emotions.

H1a: Advancement opportunities have a positive relationship with employer brand

emotions.

H1b: Brand reputation has a positive relationship with employer brand emotions.

H1c: Economic value has a positive relationship with employer brand emotions.

H1d: Social value has a positive relationship with employer brand emotions.

H1e: Work content has a positive relationship with employer brand emotions.

13

Figure 1. (own)

Further, it has been hypothesized that employer brand associations can predict being an

employer of choice (H2). Therefore, the conceptual model illustrates the significance of

brand associations when choosing an employer of choice. The conceptual model

distinguishes each brand association alone in order to interpret the coefficient

correlation and the significance level of each variable.

H2: Employer brand associations predict being an employer of choice.

H2a: Advancement opportunities predict being an employer of choice

H2b: Brand reputation predicts being an employer of choice

H2c: Economic value predicts being an employer of choice

H2d: Social value predicts being an employer of choice

H2e: Work content predicts being an employer of choice

Employer Brand Associations H1a: Advancement opportunity H1b: Brand reputation H1c: Economic value H1d: Social value H1e: Work content

Employer Brand Emotions

Employer of choice

H1a-e A

14

Figure 2. (own)

The third hypothesis describes whether there is a relationship between employer brand

emotions and the employer of choice. The theoretical framework describes the role of

emotions to affect the decision-making process and describe the importance of

employer brand emotions to consider when becoming an employer of choice (Rampl et

al., 2014). The conceptual model illustrates the relationship of employer brand

emotions in regard to the employer of choice. When measuring the relationship, the

variable of employer brand emotions will work as an independent variable and the

dependent variable of the conceptual model is employer of choice.

H3. Employer brand emotions predicts being an employer of choice.

Employer Brand Emotions

Employer of choice H2a-e

C

Employer Brand Associations H2a: Advancement opportunity H2b: Brand reputation H2c: Economic value H2d: Social value H2e: Work content

15

Figure 3. (own)

The last hypothesis is discovering whether the employer brand emotions work as a

mediator between employer brand associations and employer of choice, hence how the

relationship between employer brand associations and employer choice is affected by

the intervening variable of employer brand emotions. The conceptual model hence

illustrates employer brand emotions as a mediator between employer brand associations

and being an employer of choice.

H4: Employer brand emotions function as a mediator between the relationship of

employer brand associations and being an employer of choice.

H4a: Employer brand emotions function as a mediator between the relationship of

advancement opportunity and being an employer of choice.

H4b: Employer brand emotions function as a mediator between the relationship of

brand reputation and being an employer of choice.

H4c: Employer brand emotions function as a mediator between the relationship of the

economic value and being an employer of choice.

H4d: Employer brand emotions function as a mediator between the relationship of

social value and being an employer of choice.

H4e: Employer brand emotions function as a mediator between the relationship of work

content and being an employer of choice.

Employer Brand Associations

Employer Brand Emotions

Employer of choice

H3 B

16

Figure 4. (own)

Employer Brand Emotions

Employer of choice

H4

A B

C’ Employer Brand Associations H2a: Advancement opportunity H2b: Brand reputation H2c: Economic value H2d: Social value H2e: Work content

17

4. Methodology The following methodology chapter describes and justifies the research approaches and

the research design which are to be used for the study. The methodology chapter will

further present the data collection and data sources considered for the study. An

operationalization will connect the independent variables gathered from the literature

review to the main research method. Additionally, concepts of descriptive statistics,

regression and mediation analysis is explained, since these concepts are to be used

when measuring data. Furthermore, validity and reliability along with replicability will

be described further followed by the description of the ethical considerations of the

study.

4.1 Research approach

This research will follow the work presented by Rampl in 2014 who interprets the field

of employer branding, by investigating how employer brand emotions affect the

perception of a brand association which influences the employer of choice. As

according to the method used by Rampl, a pre study was made in order to distinguish

which variables were to be used. A questionnaire was sent out to respondents and

further analysed through regression analysis. The purpose of Rampl’s research were to

determine whether positive employer brand emotions had a mediating effect on being or

not being an employer of choice.

4.1.1 Deductive vs inductive

Deductivism and inductivism are two essential approaches when conducting research. A

deductive approach is described by Bryman and Bell (2015) as the most frequently used

view when interpreting the relation between theory and the research topic of choice.

Ghauri and Grønhaug (2005) and Bryman and Bell (2015) present deduction, as an

approach associated with quantitative data collection, to be drawn from constructing

hypotheses from existing theory connected to the empirical framework of a research.

The hypothesis which is the the building block of the research process, can then be

either accepted or rejected. The construction of deduction acquires for the researcher to

construct an operationalization to connect theory with concepts (Ghauri and Grønhaug,

2005; Bryman and Bell, 2015).

18

The opposite of deductivism considers inductivism, a research compiled by theory

being the outcome of the research. With the use of induction, the process follows from

observations to findings and into theory building where the findings are used to

strengthen the existing theory. (Ghauri and Grønhaug, 2005). The research of the

approach often contributes this interesting findings, however the significance of the

constructed theory is not always clear. Compared to the deductive research, the

inductive research is associated with constructing the empirical framework with the use

of qualitative research methods. (Bryman and Bell, 2015; Bryman, 2016).

As a conclusion of deductivism, theory and deduced hypotheses are the first steps in

order to advance to the process of gathering data, an approach which is followed for this

research. When the findings have been made, the research findings are to be connected

again to the proposed theory of the research (Ghauri and Grønhaug, 2005) The process

follows a clear structure, although changes may be made if the theory of the research is

modified. Bryman and Bell (2015) state the most significant source of empirical data is

gathered through a quantitative research method (Bryman and Bell, 2015; Bryman,

2016; Ghauri and Grønhaug, 2005). Thus, this research follows a deductive approach

and connects the findings to the theoretical chapter created with the aim of testing the

independent and dependent variables among Swedish students within economy

programmes. By interpreting the effect of positive employer brand emotions towards

the variables of brand associations and the prospect of being an employer of choice, an

interpretation of the theory in relation to the research topic is considered, which is

aligned with the deductive approach. Hypotheses are constructed from the theoretical

framework which are connected to the empirical chapter of the research. In accordance

to Ghauri and Grønhaug (2005) who present an acquirement of an operationalization

connected to the theory and the concepts, an operationalization has been constructed.

4.1.2 Quantitative vs Qualitative research

Collecting data is most frequently used as a method when constructing a research. The

collection of data may be carried out in numerous different approaches; observations,

interviews or surveys. However, the researcher is to decide what data collection method

is to be used, qualitative or quantitative approach (Ghauri and Grønhaug, 2005).

Bryman and Bell (2015) describe how qualitative research differs significantly from

quantitative research considering the aspect of qualitative research concerning words

19

compared to quantitative research which concerns numbers rather than words (Bryman

and Bell, 2015; Schmidt, 2010). Qualitative data may be derived from numerous

sources, with interviews and observations being the most basic forms of qualitative

research methods. The collection of qualitative research resolves in huge depth of data,

thus it is of importance to select significant variables of focus (Cohen, Manion and

Morrison, 2011; Krishnaswami and Satyaprasad, 2010). Quantitative data collection,

rather than qualitative data collection focuses on the quantity of data for a broad

information channel (Krishnaswami and Satyaprasad 2010).

Continually Bryman and Bell (2015) describe the differences between quantitative and

qualitative data collection by arguing for the quantitative approach of research strategy

to follow a deductive approach with a relationship between theory and the testing of the

research (Bryman and Bell, 2015). In contrast to quantitative strategies, qualitative

research analyses data in concern of the approach of inductive research, where theory is

the outcome of the research made. The qualitative strategy views social reality from a

constantly changing approach of what individuals have created (Bryman and Bell,

2015).

Krishnaswami and Satyaprasad (2010) describe the quantitative research to focus on

quantity of data collection, which will be of concern for this research as questionnaires

were sent out to the respondents with the aim of collecting a large number of data for a

broad information gathering. The main empirical framework was gathered from

questionnaires by of creating an objective relativity from an external social reality

approach, which is explained by Bryman and Bell (2015) as the main strategy

considered in the quantitative research. As earlier explained the method distinguishes

the approach of deduction to be relevant for the research. Deduction follows a

quantitative approach with a relationship between theory and the test of the research,

which strengthens the use of quantitative research.

4.2 Research purpose

4.2.1 Exploratory, descriptive and explanatory research

Explanatory research focuses on answering and finding solutions for issues which are

already known. Hence, explanatory research is founded upon existing theories. The

purpose of this kind of research is to answer the question why something happens and

20

discover the underlying reasons for why it occurs. Explanatory researcher's goal is to

deliver a clear picture of a situation of phenomena (Neuman, 2003).

Exploratory research indicates that research has to be further discovered and hence

make new findings within a specific field. These new findings then help future research

for further discoveries of the field (Zikmund, et al., 2010). For example, researchers

may contribute with new theories, measurements techniques or focus questions for

future research. Because of exploratory brings forward such discoveries, it is usually not

factual nor generalizable evidences and instead focuses on answering the question of

what. Exploratory research often builds upon a qualitative research approach (Neuman,

2003).

Descriptive research is specific to a larger extent than exploratory research. It has its

foundation in some focus on a certain problem or phenomenon (Krishnaswamy and

Satyaprasad, 2010; Zikmund, et al., 2010). Neuman (2003) means that this type of

research provides a more detailed picture in contrast to the exploratory and locates new

findings which strengthens the past data of the field. The research aims to answer the

questions of how and who. How something happens and who is performing it (Neuman,

2003; Zikmund, et al., 2010). Krishnaswamy and Satyaprasad (2010) further explain

that the data collection often has a quantitative approach.

As this research has its theoretical foundation from several previous researches, hence

enlarges already existing theories, the most appropriate research approach would either

be descriptive or explanatory. However, since the research will be testing already

existing theories on an unexplored context, this research will contribute with deeper

knowledge, or as previously mentioned, a clearer picture of the studied field. Hence, the

used approach for this research will then be of descriptive approach.

4.3 Research design

According to Bryman and Bell (2011), the five most common types of research designs

are; experimental design, longitudinal design, case study design, comparative design

and cross-sectional design.

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Experimental research tests and compares the results of two groups, an experimental

test group and a control group. By manipulating one or more of the independent

variables, researchers aim to discover whether a change of the dependent variable

occurs or not. The strengths of this design is the validity of the results. However, this

design is not commonly used within business research due to the lack of independent

variables to manipulate (Bryman and Bell, 2011).

The cross-sectional research design entails data collection from multiple cases or

observations but for a single point of time (Bryman and Bell, 2011; Neuman, 2003).

The independent variables are then compared and analysed in correlation to the

dependent variable. The strength of cross-sectional research is that it is quick and cheap

to perform (Ghauri and Grønhaug, 2005; Bryman and Bell, 2011). Additionally,

according to Neuman (2003) the cross-sectional design is the simplest method to use for

the least amount of money.

With a longitudinal design, researchers aim to map out a change over time (Bryman and

Bell, 2011; Neuman, 2003). Although, this type of research is neither commonly used

within business and management research due to time consumption and the fact that it is

costly (Bryman and Bell, 2011). The longitudinal research design is commonly used

when looking for changes within social situations. However, it is costlier and complex

than cross-sectional research (Neuman, 2003).

Case study design analyse one single case, as it is seen through a single location,

organisation, person or event. This kind of research is commonly used within business

researcher as it is anchored in real-life situations. However, researchers have to be

careful due to the lack of generalizability and external validity (Bryman and Bell, 2011).

The last kind of research design is the comparative design, which basically compare two

different cases which has been treated with the same method. The context which

changes within such research is often national or cultural. The advantage is that

comparative research broadens the generalizability and find new findings for further

studies (Bryman and Bell, 2011). Bryman and Bell (2011) further explain that from a

quantitative perspective, the comparative research design is an extension of a cross-

22

sectional design, as from a qualitative approach it is an extension of the case study

method.

As Ghauri and Grønhaug (2005) describe, the cross-sectional design measures whether

the correlation between variables causes a change or not. Which will be done

throughout this study, investigating how the respondents’ employer brand emotions are

causing a change in employer brand associations and hence the employer of choice.

Therefore, the chosen research design for this study is the cross-sectional design, since

it is the most appropriate.

4.4 Data source

In all research, researchers need to collect current and reliable data. Researchers also

need to be able to analyse the gathered data and be able to understand the limitations

and errors of it (Ghauri and Grønhaug, 2005). Data could be collected in two ways;

primary and secondary. Whereas primary data is gathered information from the

researcher in first hand, and is useful in order to solve a specific and unique research

problem. Secondary data, on the other hand is currently existing sources from previous

research. Most often, primary data is collected through either observations or

questioning. Thus primary methods are often more time and cost consuming, but might

be necessary in order to steer into the complexity of a research. As primary research

discovers new contexts within research fields, research becomes more broaden (Ghauri

and Grønhaug, 2005; Krishnaswami and Satyaprasad, 2010).

For this research, primary data was used in order to gather information. Since

information about the research field was not available through secondary data, primary

data was highly needed in order to be able to broaden the field of research with the

specific context. The information was collected through a questionnaire which was

distributed over social media and private messages in order to receive answers from the

specific target group. The data was further analysed in order to be able to determine new

contribution within the field of employer branding.

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4.5 Data collection method

4.5.1 Questionnaires

The widely use of questionnaires is a valuable tool for collecting data for a

straightforward analysis (Cohen, Manion and Morrison, 2011; Bryman and Bell, 2015).

The method of surveys is used to gather data for the conducted research. The method

may be constructed in numerous approaches, from printed questionnaires, telephone

interviews or formalities on the internet. The aim of the use of the method is to collect

factual information and/or behaviours of participating individuals (Bryman and Bell,

2015). However, the respondent of a questionnaire is not to be forced to answer the

provided questionnaire but rather encouraged to provide answers, although the decision

is for the respondent to choose (Cohen, Manion and Morrison, 2011).

The construction of a survey follows questions with options of answers in order to

evaluate the participant’s selection of the different codes connected to the questions.

The layout of a questionnaire is to provide clarity of questions with no difficulty in the

interpretation of words or sentences. The questionnaires should not be too simple nor to

difficult to answer neither too long nor too short (Cohen, Manion and Morrison, 2011).

It is essential to gather a considerable amount of data, as too much data may harm the

research with a broad result (Findlay, Hofmeyr and Louw, 2014).

Cohen, Manion and Morrison (2011) present a simple rule to consider when conducting

a questionnaire. When conducting a questionnaire, a larger sample size refers to a more

structured questionnaire. Different types are relevant for different approaches and may

be either structured, semi structured or unstructured questionnaires. Structured

questionnaires resolve in questions for the respondent to follow, while semi-structured

questionnaires invite the participant to reply in own terms. Unstructured refers to an

open questionnaire where the participant may write what he or she prefers. The

structured and closed questionnaire are less difficult and provide the researcher with

frequencies of responses that are statistically easy to analyse. However, the unstructured

and semi structured questionnaires provide the possibility to capture specific variables

in a specific situation (Cohen, Manion and Morrison, 2011).

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4.5.2 Questionnaire design

The construction of a questionnaire is essential in order to make it easy for the

respondent to understand (Ghauri and Grønhaug, 2005). Additionally, Bryman and Bell

(2011) push for a more straightforward and simple design layout in order to minimize

the amount of participants not finishing the questionnaire and thus having a lower

response rate. Furthermore, it is vital to follow some steps in order to make the

questionnaire more appealing and pleasant for the respondent. The initiate step of the

survey should be to have clear information about the research and how the respondent

should think when filling in the questionnaire (Bryman and Bell, 2011). In order for the

respondents to understand what the research is about, the information in the beginning

should explain such (Bryman and Bell, 2011).

The questions of the questionnaire are also essential parts. Researchers are to consider

the participant’s level of education, cultural background and knowledge within the

researched field. Therefore, the language of the questions should be simple for all

respondents to understand. Furthermore, Bryman and Bell (2011) explains that there is

an immense difference between different questions, i.e. structured, unstructured, open

and closed questions. With open or open-ended questions, the respondent is not given

any alternatives and is usually to fill in the answer manually in a text box. In contrast,

closed questions gives the respondent alternative to choose from, usually to check a

box. The amount of alternatives is also important, whether questions only should have a

simply “yes” and “no” alternative or a likert scale with five or seven alternatives

between “agree” or “disagree” (Bryman and Bell, 2011). However, this is also

depending on the question where questions about the respondents formed as an interval

instead of a ranking formation. For questions where the respondent is asked to rank a

specific scenario, a likert scale is often used. This allows the respondent to choose from

five or seven alternatives depending on which level they agree upon the stated scenario

(Bryman and Bell, 2011).

Both Ghauri and Grønhaug (2005) and Bryman and Bell (2011) discuss the length of a

questionnaire, where both mean the impression of a questionnaire being shorter is more

likely to increase the amount of responses. However, according to Ghauri and Grønhaug

(2005), there is no research confirming the appropriate length of a questionnaire.

25

Additionally, surveys can have many different types of shapes and be distributed both

physical or over the internet (Bryman and Bell, 2011). According to Bryman and Bell

(2011), it is more commonly today that respondents are invited to a web site in order to

answer the questionnaire. One of the advantages for the online questionnaire is the

ability to send the respondent to a specific question depending on the previous answer.

Another advantage is the ability to hide questions for the respondents and hence only

make couple of questions appear at a time (Bryman and Bell, 2011). There are several

services for online questionnaires, where Bryman and Bell (2011) mentions

surveymonkey.com as one. However, another is Google's version of “Google forms”.

4.5.3 Execution questionnaire design

The constructed questionnaire for this research was created through Google’s tool

“Google forms”, since the authors has more knowledge about this tool. The respondents

were invited through social media as it is a commonly used method of today. The

questionnaire had a structured design since it simplifies the gathering and analysis of the

data, as according to Cohen, Manion and Morrison (2011). In accordance to Bryman

and Bell (2011) a brief information introduction was given to the respondents in the

initial part of the questionnaire, not too long nor to short, just briefly in order for the

respondent to understand the field of research and what the research was about.

Since the sample frame of this research only included Swedish students studying within

economy programmes at a university level, the first question asked the respondent if

they were students within economy. As Bryman and Bell (2011) describe the advantage

of sending a respondent to a specific question, the questionnaire was constructed as if

respondents answered no, the respondent was thanked for the participation but informed

that they were not included within the sample frame. If answered yes, they were sent to

the continuation of the questionnaire.

The first part question of the actual questionnaire encouraged the respondent to think

about an employer and type in, hence as an open question. The next part included

questions regarding the independent and dependent variables of; advancement

opportunity, brand reputation, economic value, social value, work content, employer

brand emotions and employer of choice. However, since Ghauri and Grønhaug (2005)

as well as Bryman and Bell (2011) argue for the impression of a shorter looking

26

questionnaire, the questions about employer brand emotions and employer of choice

were moved to a separate page, making the survey appear as shorter. For the questions

about the independent and dependent variables, a seven step horizontal likert scale was

used, where 1 indicated “Strongly disagree”, 4 indicated “Neutral” and 7 indicated

“Strongly agree”. Each variable had three questions, except for brand reputation, since

too many questions may be too much for the researchers to handle and hence harm the

result of the research (Findlay, Hofmeyr and Louw, 2014).

The page after included general questions such as gender, age and if the respondent had

experience of working before starting their education at the university. Lastly, the

respondents were thanked for their participation and the answers were registered. The

questionnaire design can be seen in Appendix 1.

4.5.4 Operationalization

According to Bryman and Bell (2011) an operationalization focuses on breaking down

the theoretical concepts of a research in order to make it easier to manage. Another

aspect of the operationalization is the to explain the measuring of the concepts (Mueller,

2007). Bryman and Bell (2011) further explain the connection between indicators, such

as theoretical concepts, and the observations or questionnaires that the study will be

built upon.

The following operationalization will tie together the theoretical concepts, or variables,

to the questions in the upcoming questionnaire which will work as the main study of

this research. Each question will have a brief explanation of theory and a reasoning why

it will be asked and measured.

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Theory Theoretical source Measurement Question I associate the chosen

employer with… Advancement opportunity

Bellou, et al. (2015), Berthon, Ewing and Hah (2005), Figurska and Matuska (2013) Rampl (2014).

Aims to measure the significance of each employer brand association.

1. ... good opportunities for an advancement within the company.

2. ... the opportunity to offer an international career.

3. ...offering internal training programs.

Brand reputation

Bellou, et al. (2015), Cable and Turban (2003), Collins and Zedeck (2007), Rampl (2014).

4. ...having good reputation in general.

5. ...producing innovative products or services.

6. ...being environmentally conscious.

7. ...being financially stable.

Economic value Berthon, Ewing and Hah (2005), Bellou, et al. (2015), Figurska and Matuska (2013) Rampl (2014).

8. ...offering a salary above average.

9. ...offering financial benefits (e.g. Christmas bonus).

10. ...offering good opportunities for salary advancement.

Work content Agrawal and Swaroop (2009), Berthon, Ewing and Hah (2005), Rampl (2014).

11. ...offering opportunity to work independently.

12. ...offering challenging work assignments.

13. ...offering work assignments which interest me.

Social value Berthon, Ewing and Hah (2005), Figurska and Matuska , (2013), Rampl (2014)

14. ...having a creative work environment.

15. ...offering good relationship with colleagues.

16. ...offering a good relationship with managers.

Employer brand emotions

Albert and Merunka (2013), Vytal and Hamann, (2010) Rampl, et al., (2014) Deppe,

Investigates the positive emotions the respondents have towards

17. I have positive emotions towards the chosen employer.

18. The chosen employer brand inspires me.

28

et al., (2005)

the chosen company.

19. I would feel proud to work for the chosen employer.

Employer of choice

Sutherland, et.al, (2002), Branham (2005) Sedighi and Loosemore, (2012).

Evaluates the choice of the respondent, to investigate the relevance of the brand being an employer of choice.

20. I would like to work for the chosen employer.

21. I speak well of the chosen employer to others.

22. I would have chosen to work for the chosen employer over other employers.

Table 4.5.4 - Operationalization

4.5.5 Pre-testing

Bryman (2016) describe it as preferable to conduct a pre-study in advance before

presenting a questionnaire or a structured interview to the sample of choice

(Krishnaswami and Satyaprasad, 2010). Malhotra (2009), describes how the pre-testing

is used to eliminate potential issues by testing questionnaires and testing small samples

of respondents. Most relevant is to test respondents of similar backgrounds of the main

respondents of the research. By conducting a pre-test of a questionnaire is it of priority

to interview the respondents rather than presenting the respondents with the actual

questionnaire, in order to examine reactions and attitudes of the respondent and

potential issues. The pre-study does not solely test the procedure of the method, but a

pre-test can evaluate the research instrument from an overall perspective, evaluating

questions, sentences, words and instructions (Malhotra, 2009).

Since a questionnaire is processed by the respondent alone, the clearness of the

questionnaire must be constructed with no further confusion for the respondent

(Bryman, 2016). Hence, this research will collect data through questionnaires, therefore

the procedure of testing the questionnaire was carried out in order to evaluate the

research instrument chosen. The pre-test applies an understanding of the questionnaire

in order to distinguish the potential threats of confusion for respondents and is tested by

respondents of similar backgrounds to the specific sample of choice for this research.

The questionnaire is tested accordingly to Malhotra (2009), by interviewing respondents

with the questions for the questionnaire in order to evaluate the reactions of respondents

to reduce potential problems in understanding.

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4.5.6 Results - Pre-test questionnaire

In order to validate the questionnaire, a pre-test was tested with the help of a lecturer

and a senior lecturer of the marketing department of the Linnaeus university. The pre-

test resolved in an adjustment of questions along with new questions for a greater

understanding of the questionnaire. After the changes of the suggestions, the revision

was again sent back to both lecturers for an approval of the questionnaire. Once the

questionnaire was approved, twelve individuals of the sample selection were asked to

answer the questionnaire in order to provide feedback of the understanding and the

content of the questionnaire. After minor adjustments, the questionnaire was ready to be

sent out to the respondents. The questionnaire is available in Appendix 1.

4.6 Sampling

Bryman and Bell (2015) state that it is unlikely for the researcher to target the whole of

a population when conducting research. It is both time consuming and expensive to

reach the whole target population. Thus, it is most certain one will have to create a

sample of the total population, a sample referred to as the segment which is

representative of a population selected for a research. A sample selection is most often

encountered in quantitative studies (Bryman and Bell, 2015).

One distinctive approach of sampling is probability sampling, a process of gathering

information from random samples from the interpreted population, referring to the

generalizability of the sampling (Bryman and Bell 2015; Krishnaswami and

Satyaprasad, 2010). In contrast to probability sampling, non-probability sampling

captures the forms of sampling efforts not associated with the description of probability

sampling, random sampling. Bryman and Bell (2015) describe non-probability sampling

to be divided into three subcategories, quota sampling, snowball sampling and

convenience sampling.

Quota sampling has an aim of considering a sample which reflects the population from

different categories such as age and gender among other categories selected by the

interviewer. Snowball sampling refers to the contact that is made with a relevant

selected group which are used to create contact with other relevant respondents for the

research. Moreover, the convenience sampling is the sampling method most accessible

and the cheapest for the researcher, even though a convenience sample is by some

30

authors argued to be hard to generalize (Bryman and Bell, 2015; Krishnaswami and

Satyaprasad, 2010).

Further Bryman and Bell (2015) discuss the difficulty of determining the sample size of

the research. It is of significant importance for the researcher to evaluate and

compromise between time and cost of the research in order to determine a suitable

sample size, as there is no definite answer of a correct sample size number (Bryman and

Bell, 2015; Krishnaswami and Satyaprasad, 2010). In contrast, Van Voorhis and

Morgan (2007) describe a simple thumb rule of no less than 50 respondents when

interpreting the correlation or regression of a concept. For a larger number of

independent variables, it is advised to increase the number of participants. The formula

provided by Green (1991) suggests to determine the sample size as following; N> 50+

8m, where m reflects the number of independent variable used in the research.

However, Krishnaswami and Satyaprasad (2010) describe the main strengths of

sampling to consider the reduction of time and cost as a sample is conducted to measure

a population.

4.6.1 Sampling Frame and Sample Selection

The sample frame of choice is to reflect the population targeted for the research

(Bryman and Bell, 2015). The authors of this study have chosen a convenient sample as

a method for this specific research as the sample approach allows for accessible source

of data collection. The sampling frame will contain individuals who study programmes

within economy on a University level in Sweden, which is requisite to participant in the

study. The selected sample frame furthers contribute to earlier research within the topic,

as it is argued that it is of importance to customize brand associations to different

cultures and nationalities, for organisations to understand a target global employees

(Almacik, et al. 2014). It is argued for differences between nations and culture and

further research is advices to address context with lack of research of different nations

(Bellou, et al.,2015).

A number of 133 respondents were accepted as respondents, following the criteria of

studying within economy programmes on a university level in Sweden, and were carried

out in the research. The majority of the respondents were contacted individually with

additional support of individuals, who provided relevant respondent candidates.

31

A number of at least 98 respondents was selected as the targeted sample size to

compromise the time consumption of the gathering of the sample in regard to the

formula provided by Green (1991); N> 50+ 8m, where m reflects the number of

independent variable used in the research, to determine the sample size for research.

This research identifies 6 independent variables, which solved the suggestive formula

with a number of 98 respondents for a relevant sample size. However, the questionnaire

resulted in 133 respondents. Moreover, Snowball sampling was considered for the

gathering of data, as respondents were asked to create contact with other relevant

respondents for the research. The majority of the respondents were contacted personally

being asked to fill in the questionnaire and the questionnaire was posted on a social

media platform in order to reach the targeted sample size. The questionnaire was closed

for one answer per respondent and control questions of the survey are directed in order

to justify the respondents to be students within economy programmes on a University

level.

The students of the sample were selected due to the aspect of students soon to enter the

business world (Berthon, Ewin and Hah, 2005) and the context of including students

within economy programmes is strengthened by the aspect of statistics created by the

SCB. SCB (2016) presented numbers of 8000 individuals being granted a degree within

the field of economy or business administration during the year of 2015/2016, which is

the largest number of graduating student within a specific field of study in Sweden

(SCB, 2016). As Almacik, et al., (2014) and Bellou, et al. (2015) argue of the essential

role of attracting the most suitable employee for an organisation to compete of the

market of today, it may be of great concern due to the large number of graduated

students, to find the most suitable employee.

4.7 Data analysis method

4.7.1 Descriptive statistics

According to Ghauri and Grønhaug (2005), descriptive statistics allow the researcher to

summarize the collected data and describe the variables from a numeric perspective.

The research questions and the objectives of a research is to guide the researcher in the

choice of statistics and should either focus on the central tendency of the dispersion.

Describing the statistical approach of central tendency, focus on describing the values

32

and findings from a general impression of being either common, average or middling.

The approach may be divided into three different categories measuring techniques;

mode (most occurring value), median (the middle value of the concluded data) and

mean (the average of all responses) (Ghauri and Grønhaug, 2005). According to

Bryman and Bell (2011), the advantage of measuring median is the non-influential of

extreme values, whereas the mean is the most frequently used measurement. The

descriptive statistics provide a summarization of the collected data, which present

numbers of the variables. The statistical contribution provides a summary of the central

tendency of the gathered data.

Measurement of dispersion include the variance and the deviation of the distribution,

which could be used for both metric and non-metric variables. A commonly used

measurement for dispersion is standard deviation which measures the deviation of the

mean. If the standard deviation is closer to the mean, the mean is more useful (Ghauri

and Grønhaug, 2005).

4.7.2 Regression

According to Iacobucci and Churchill (2015), regression analysis is used in order to

statistically measure the relationship between independent and dependent variables.

Thus, regression analysis is simply used to discover whether a change of the dependent

variable is noticeable or not when one of the independent's value is changed. The

relationship between dependent and independent variable could be more specifically

explained as how associated the variables are to one another. Depending on the size of

change, the independent and dependent variable is significant to each other in its

relationship (Iacobucci and Churchill, 2015). Additionally, Malhotra and Birks (2003)

explain the coefficient of determination (r2), which measure the association between

variables, hence the strength of the linear relationship. Although, the measure of r2

includes the if there is a non-linear relationship between variables, which r are not able

to notice. As for a deeper understanding in correlation coefficients, the unstandardized

regression coefficient (b) shows the slope of the regression line and indication for the

predicted change in the dependent variable when the independent variable is changed.

Regression analysis could also be done in a multiple procedure, measuring several

independent variables in relation to the dependent variable. Furthermore, it is necessary

33

to measure the significance level for the regression, often with a margin of 5% or lower

(Malhotra and Birks, 2003).

In accordance to Iacobucci and Churchill (2015), the regression analysis was used in

order to interpret the relationship between variables and explain how related the

variables are to one and other in order to test the hypotheses. The results also showed a

confidence interval for the distribution, which was further analysed. The aim for this

research was to receive a positive confidence interval which did not cross zero (0). If the

confidence interval is positive and at the same time the significance level is below 0,05

(5%), this indicates for a positive result and hence the research’s hypothesis is to be

accepted (Bryman and Bell, 2011).

4.7.3 Mediation analysis

As seen for the model used in this research, the variable of employer brand emotions

works as a mediator between the independent variables and the dependent variable. A

mediation variable, or intervening variable, is according to MacKinnon (2008) a

measurement where it is determined how much of an impact the mediating variable has

on the independent and dependent variable. More easily described by Hair et.al., (2010)

as “the effect of a third variable intervening between other related constructs” (pp.690).

In order to interpret the mediating effect it is vital to construct multiple regression

analysis. First off, one must estimate the relationship between the independent variable

and the mediator (A). Secondly, the relationship between the mediator and the

dependent variable (B) is calculated. Thirdly the relationship between the independent

and the dependent variable is measured (C). Lastly, in order to measure the effect of

mediation, the independent variable and the mediating variable is ran together towards

the dependent variable, where the independent variable influence the mediator and not

the dependent variable. If the four steps are accomplished, mediation is shown (Baron

and Kenny, 1986).

Mediation analysis may mend out in either full or partial mediation, interpreting the

relationship between variables. Full mediation reflects the explanation of the

relationship to be mostly explained, with no further need to test more effects. In contrast

to full mediation, partial mediation indicates for further testing, as the explanation of the

34

influence of the variables are not completely explained, and implications for indirect

effects which should be tested further (Rucker et al., 2011).

If paths A,B and C show a significant effect mediation has been established. However,

in order to establish whether the mediation is partial or full, researchers need to test the

fourth step of mediation analysis, testing the independent and mediating variable

together towards the dependent variable. If a significant effect is shown, partial

mediation is established and hence there could be other indirect implications which

could influence the variable. However, if the change in C’ does not show any significant

effect, full mediation is proven and there is no other implications that influence the

relationship between the independent, mediating and dependent variable (Rucker et al.,

2011).

Figure 5. (own)

The four steps reported by Baron and Kenny (1986) were followed, in order to

determine the mediation effect. Where each step was considered to report the

significance level between the variables. Considering the first step, the relationship

between the mediation variable of employer brand emotions and the independent

variables of advancement, brand reputation, economic value, social value and work

content. In accordance to the second step, the relationship between the mediating

variable of employer brand emotions and the dependent variable of employer of choice

Independent variable

Mediating variable

Dependent variable

A B

C à C’

35

was measured. Thirdly the relationship between the independent variables and the

dependent variable was measured. After the third step, mediation was proven for two of

the five independent variables. In order to test if the mediation was either full or partial,

the fourth step was conducted.

4.7.4 Data coding

In order to code the gathered data, IBM SPSS Statistics Data Editor was used. All of the

data gathered from the questionnaire were inserted into SPSS and coded. The survey

questions for the independent and dependent variable were ranked according to a likert

scale where 1 equalled to strongly disagree and 7 equalled to strongly agree. Hence the

middle number of 4 equalled a neutral number. Therefore, if the participant’s response

was 5, it was coded as 5 in SPSS. The questions about age and gender were coded as a

nominal scale were gender was coded as; 0 = male, 1 = female and 2 = other. Age was

additionally coded as; 0 = 18-22, 1= 23-27, 2 = 28 - 32, 3 = 33-37, 4 = 38-42, 5 = 43+

respectively.

When several independent variables were measured as one, these were transformed into

one variable within SPSS. To do that, all questions for each of the variables were

summed into one. This was necessary in order to obtain significance level and

confidence interval for a dependent variable in relation to several independent variables.

4.8 Quality criteria

4.8.1 Reliability

The concern of a research being repeatable reflects the term of reliability. The concept

refers to the opportunity for a researcher to find consistency, which is in regard to

relationship between concepts commonly associated with the term of reliability, by

replicating earlier research. Reliability is most often deceived with the use of

quantitative research, where the researcher is to determine whether a measurement is

stable or not (Bryman and Bell, 2015; Saunders, Lewis and Thornhill, (2016). Saunders,

Lewis and Thornhill (2016) describe a distinction between internal and external

reliability. The internal reliability refers to ensuring consistency when collecting data by

having more than one researcher who stages through the data, moreover scripting

36

memos of how to code data, for a stable interpretation. In comparison to internal

reliability, external reliability refers to whether the data collection approach produces

consistent findings depending on if more than one research collect data during different

occasions (Saunders, Lewis and Thornhill, 2016).

Bryman and Bell (2015) describe that in order to test the reliability of the internal

process of the research, Cronbach’s alpha is a commonly used test measure. Cronbach's

alpha of which calculates the approach of calculating the split- half reliability, a

reliability measure of which is split into two different halves. The measurement divides

the indicators of the results and measures the correlation between indicators, measuring

how close the scores of respondents are related. Cronbach’s alpha ranges from 0,

showing no correlation and hence no internal consistency to 1, showing correlation

between indicators and hence internal consistency. Gliem and Gliem (2003) use a rule

of thumb as following; 0,9 - excellent, 0,8 - Good, 0,7 - Acceptable, 0,6 - questionable,

0,5 - poor and below 0,5 is unacceptable.

This research provides a replication of earlier framework provided by Rampl (2014) to

provide quality and to determine the stability of the earlier research. The process of the

research is constructed by more than one researcher, who have collected data, and

interpreted data during the same occasion to maximize the consistency of the internal

and external reliability. To create an understanding of the consistency and correlation

between the variables, Cronbach's alpha was interpreted. No values under 0.6 are used

in order to grant reliability of the measurements, as Gliem and Gliem (2003) argue for

levels of 0,5 to be poor and unacceptable.

4.8.2 Replication

Replication is relatively close criterion to reliability, the term replication and the term

replicability focuses on replicating an earlier research. The reasons for conducting a

replication are many, as wanting to provide further evidence of the original research and

replication of earlier research enhance the generalizability of a concept or model

presented in an original research. To do so, the replicability of the original must be

adequate. The original research procedure must be presented in detail in order of the

replication process to take place. Replicability itself is a most recommended approach in

37

regard to the quality of quantitative research as the methods used to create findings are

accurate (Bryman and Bell, 2015).

This research focuses on earlier framework provided by Rampl, a framework of which

is replicated in order to enhance the generalizability of the original research. The

generalizability of the prior research is enhanced by adding a new context to the earlier

research, a context of a different industry and a different country of origin. To

strengthen replicated research, this research presents the research procedure in detail,

for future research to further develop the research topic. Future research can contribute

with generalizability of of the original research and this research. Although, some

differences occurred during the process of the replica, whereas Rampl (2014) is

presenting a pre-study where all variable were discovered through individual phone

interviews. However, for this research all variable used were discovered through

existing research within employer branding, in order to see if other variables were

existing.

4.8.3 Validity

The most important criterion for conducting research is by Bryman and Bell (2015)

described as validity. Validity relates to the extent of the measurements measuring what

is supposed to be measured also measuring to what the degree the findings are

generalizable to a larger population than the selected sample (Wilson and MacLean,

2011). Bryman and Bell (2015) describe validity measurements to target the integrity of

the conclusions that have evolved from research and may be distinguished in many

different approaches. One matter of distinguishing the validity is through face validity, a

validity measurement established by interaction with expertise within the area of focus

who can react to the presented concept and judge the presented framework and the

validity measurement. The construct validity is a measurement approach of which tests

the hypotheses stated from the theory and its relevance to the concept of choice.

Findings indicating a consistency with the theory, is defined as valid through the

measurement (Bryman and Bell, 2015).

Furthermore, Malhotra and Birks (2003) explain that the correlation coefficient (r), also

referred as the Pearson’s correlation coefficient, simple correlation and bivariate

correlation, measures the relationship between variables. It determines if the variation in

38

one variable is associated with the variation in another variable, and to what degree. The

numeric measure of (r) is always a number between -1 and +1, where 0 indicates that

there is no association between the variables, hence making them totally independent to

each other. The closer the numeric measure moves towards +1, the indication for a

positive relationship is determined. Consequently, if the number moves towards -1 a

negative coefficient also indicates for a relationship between the variables (Malhotra

and Birks, 2003).

The concept of which Bryman and Bell (2015) describe as face validity was

implemented by initially contacting two senior lecturers at the Linnaeus University of

the marketing department. By means of the face validity approach, the authors of the

study asked for evaluation and critical response of the operationalization. Moreover, a

pre-test was considered by asking students of the sample frame to critically evaluated

the questionnaire to validate the understanding of the questions of the questionnaire.

This research has been measured from a construct validity approach. The construct of

the research was concluded by investigating the theoretical contribution of the research

in regard to the operationalization. Through the statistical tool of SPSS, a correlation

analysis was made in order to conclude a correlation between the variables referred in

the operationalization. In accordance to Malhotra and Birks (2003) who explain the

correlation analysis to measure of the strength of the relationship between the variables

and determining if the variation of a variable is associated with another variable.

4.9 Ethical principles

Bryman and Bell (2015) present four main descriptions of ethical issue to consider in

business research, they are divided into harm to participant, lack of informed consent,

invasion of privacy and deception. Examining the first ethical principle of harm to

participant. Harm to participants reflect many matters of harm, regarding, physical

harm, harm to the participant’s self esteem, stress and so forth. It is therefore of

responsibility for the researcher to conduct research with carefully constructed material

for the participant to access.

Bryman and Bell (2015) describe an issue of lack of informed consent, which questions

the prospect of information and discusses the importance of participants being informed

39

of the research in order to evaluate if the participants are to participate or not (Bryman

and Bell, 2015; Saunders, Lewis and Thornhill, 2016). The respondents of the research

have been informed for a clear understanding and evaluation of the participation for the

questionnaire and the research. Neither does this research invade the privacy of the

participants as Bryman and Bell (2015) mention invasion of privacy as an ethical issue.

Aligned with Bryman and Bell (2015) and Saunders, Lewis and Thornhill (2016) this

research will guarantee anonymous participation for the respondent, where no

information connected to the individuals will be presented. Lastly the researcher is to

accurately present their research of what it is, with a clear understanding for the

respondent (Bryman and Bell, 2015). The questionnaire available includes a cover letter

with an understanding of what the study is about in order to accurately inform the

respondents of what they are to participate in.

40

4.10 Chapter summary

Research approach Deductive

Quantitative

Research purpose Descriptive research

Research design

Cross-sectional design

Data source Primary data

Data collection method

Questionnaires

Sampling Convenience sampling

Snowball sampling

Data analysis method Simple linear regression

Multiple linear regression Mediation analysis

Quality criteria

Validity Replication Reliability

Ethical considerations

Table 4.10

41

5. Results The information presented in this chapter is the collected data from the Google form

questionnaire. This data was further inserted and interpreted in the data analysis

program of SPSS. Initially, the descriptive statistics are presented, which will be

followed by the multiple linear regression tables and the mediation analysis.

5.1 Descriptive statistics - Sample As earlier mentioned, Van Voorhis and Morgan (2007) with support from Green’s

(1991) formula for a sample frame, the minimum number of responses is calculated.

The formula states; 50 + 8m, where m is the number of independent variables. Since

employer brand emotions is used both as an independent and dependent variable when

running regressions analysis, the total amount of independent variables used in this

research is six. Hence, the least accepted amount of responses would be 98.

Since the participants were contacted either personally or via the open link through a

Facebook wall post, it is not possible to know how many people were in contact and

paid attention to the Facebook post. However, the amount of responses collected

totalled in 133.

For the control question whether the participants studied economy or not, only one

participant answered no. This could be explaining that the survey encourages the

participants to skip to answer the survey if they were not students within economy.

Furthermore, the distribution between genders amounted to 82 males, 49 females and 2

others as seen in appendix table 5.1a. The distribution of participant age concluded in

131 between the two intervals of 18-22 and 23-27. The third table, table 5.1c, shows the

distribution of the participants’ work experience, whether they had work before entering

the university.

42

Table 5.1a – Distribution of participants’ gender.

Table 5.1b – Distribution of participants’ age.

0

10

20

30

40

50

60

70

80

90

Male Female Other

Gender

Gender

0

10

20

30

40

50

60

70

80

90

18-22 23-27 28-32 33-37 38-42 43+

Age

Age

43

Table 5.1c – Distribution of participants’ work experience.

5.2 Hypothesis testing

5.2.1 Descriptive statistics

Appendix 2 displays the mean of each independent and dependent variable. The mean is

the sum of all answers for each individual question added together and then divided by

the amount of question for the specific independent variable. The mean hence displays

which variable the survey’s participants associated the chosen employer the strongest.

As seen the highest number belongs to social value, however, all variables are quite

close to each other.

5.2.2 Multiple Linear Regression Analysis

To test the hypotheses stated, a multi linear regression analysis was

conducted. Appendix 3 present the results regarding the hypothesis testing of H1 which

is divided into five hypotheses for each independent variable. For each variable the beta

value, significance level, R2, adjusted R2, F value and degrees of freedom are

presented. As seen in Table 5.2.2a the control variables of gender, age and work

experience are included. When interpreting the table one can see that the control

variables are analysed in relation to each of the independent variables. Model 7

interprets the independent variables all together with the control variables. The results

of appendix 3 presents to accept H1a, H1b, H1d and H1e while the hypothesis regarding

H1c and the variable of economic value is rejected. The significance level of this

0

20

40

60

80

100

120

140

Yes No

Work experience

Workexperience

44

research reflects a level of <0,05 which indicates the rejection of H1c which is not

significant as it presents a significance level of 0,832.

The table in appendix 4 is constructed in the same procedure as the table in appendix 3,

however shows the relationship between employer brand associations and employer of

choice. Following a significance level of 0,05, results indicate a rejection of three

hypotheses. The hypothesis of H2d and H2e are accepted, meaning the employer brand

associations of work content and social value are predictors of being an employer of

choice.

Appendix 5 further reflects the third hypothesis, H3. The table presents the independent

variable of employer of choice in relation to employer brand emotions. The significance

level of employer brand emotions is aligned with the 95% confidence interval, which a

significance level of 0,000. Hence, the hypothesis is accepted and presents employer

brand emotions to have a strong relationship with the decision of employer of choice.

The final table, presented in appendix 6, responds to the fourth hypothesis. The

mediating variable of employer brand emotions is measured with the independent

variables of social value and work content independently. are measured independently.

Employer of choice is the dependent variable. Since the other independent varibales got

rejected in hypothesis 1 or 2, these are already rejected automatically. The regression

analysis shows that social value, measured with the mediator of employer brand

emotions, is rejected. However, work content showed a significant value when

measured with temployer brand emotions and hence is accepted. Therefore, since social

value got accepted in hypothesis 1,2 and 3 but rejected in the fourth hypothesis, it

function as a full mediator. Work content is accepted through all hypothesis and hence

function as a partial mediator.

45

5.2.3 Mediation analysis

Test 1 Test 2 Test 3 Test 4 Mediation

Independent variable Advancement opportunity

**

Brand reputation **

Economic value

Social value ** ** Full Work content ** ** ** Partial Employer brand emotions

**

Table 5.2.3b – Summarization of mediation. ** indicates for accepted hypothesis, hence significant values.

Table 5.2.3 shows a summarization of the different regressions analysis tests which

were run through SPSS. Test 1 refers to appendix 3 where employer brand emotions

were dependent variable, test 2 refers to appendix 4 where employer of choice was the

dependent variable. Test 3 was the relationship between employer brand emotions and

being an employer of choice, which is seen in table of appendix 5. Finally, test 4 is the

test of mediation, which can be seen in table presented in appendix 6.

Appendix 3 indicates for advancement opportunity and brand reputation to be significant

in correlation to employer brand emotions. However, when running the same variables

in SPSS in relation to employer of choice as the dependent variable, advancement

opportunity and brand reputation did not show a significant relationship to the

dependent variable. Moreover, the variable of economic value did not show any

significant relationship neither to employer brand emotions as the dependent variable or

employer of choice as the dependent variable.

Furthermore, the variable of social value did show significance in the test with

employer brand emotions and employer of choice as dependent variables separately for

test 1 and test 2. However, when testing the mediating effect with test 4 for social value,

it indicated for a non-significant value. Hence social value only was accepted through

three of the four tests. Although, this indicates that employer brand emotions have a full

46

mediating effect on the relationship of employer brand associations and being an

employer of choice.

Lastly, when testing the significance for the variable of work content, it was accepted

through all four tests. In contrast to social value where employer brand emotions

indicated for a full mediator, employer brand emotions only indicate for a partial

mediation between the relationship of employer brand associations and being an

employer of choice.

5.2.5 Reliability (Cronbach’s alpha)

As seen in table 5.2.5, the Cronbach’s alpha is accepted throughout all the questions.

Most of the variables lied between 0,9 and top 0,7. Although, the variable of social

value is questionable since it had a score of 0,692. However, the score is so close to 0,7

it is accepted for the research as according to Gliem and Gliem (2003) scores of 0,6 is

questionable but could still be used.

Table 5.2.5

5.2.6 Validity (Correlation)

As seen in appendix 7, Pearson’s correlation as well as the two-tailed significance level

is presented for each variable. The correlation between the variables of; Advancement

opportunity, Brand reputation, Economic Value, Social Value, Work content, Employer

brand emotions and Employer of choice are all within the range of -1 and +1. Actually,

all variables have a positive relationship between one another, where the smallest score

is 0,274 and the highest is 0,892. Further, all variables are significant since the

significance level are below 0,01 for all.

Advancement Opportunity

Brand Reputation

Economic Value

Social Value

Work content

Emotions Employer of choice

Cronbach’s Alpha

0,770 0,770 0,822 0,692 0,834 0,912 0,865

Number of Questions

3 4 3 3 3 3 3

47

6. Discussion Interpreting the results of appendix 3, the table presents seven models. The first model

reflects the control variables of gender, age and work experience which all show no

significance in regard to employer brand emotions. For a further interpretation, more

variables are needed to define the employer brand emotions. Model 2 to model 6

distinguishes the independent variables separately in regard to the control questions

while model 7 interprets the control variables together with all independent variables.

The models reflect the first hypotheses stated and conclude for all variables but the

economic variable to be influenced by employer brand emotions. Interpreted from

appendix 3 the significance level of the economic variable presented 0,832 when

connected to all independent variables which is higher than the significance level of

0,05, hence the hypothesis is rejected. In accordance to Rampl (2014) who advice for

employer brand emotions to be coupled with the variables of brand associations, the

result present the majority of the variables to have a significant relationship with

positive employer brand emotions.

A target for this research was to identify the significance of employer brand associations

in relation to an employer of choice. To understand the most significant variables in

order to address the approach of attracting the most suitable employees in today's

increasing employment market (Jain and Bhatt, 2015; Almacik, et al., 2014),

organisations and management need the distinguish the main employer brand

associations to differentiate and create an attractive employer brand for a successful

employment (Jain and Bhatt, 2015). The study aimed for students, as students are on the

verge of entering the market of employment. Students are attractive for employers,

however the difficulty of attracting the right employer still remains (Berthon, Ewin and

Hah, 2005).

The results gathered provide knowledge of Swedish students on a university level,

studying within the economy programmes, to find the employer brand associations of

social value and work content to be the most considerable factors when choosing an

employer of choice. As the second hypothesis (H2) addresses “Employer brand

associations predict being an employer of choice”, the hypotheses concerning the

variables of advancement opportunities, brand reputation and economic values are

rejected. The variable of economic factor, including salary and bonuses (Figurska and

48

Matuska, 2013) provided no further indication of relationship for an employer of choice.

As students are the targeted sample frame, the economic value may not yet provide a

value when evaluating an employer of choice. Brand reputation and advancement

opportunity moreover provided no sincere connection to being an employer of choice.

As advancement opportunity discusses the future development value (Figurska and

Matuska, 2013), the significance may not yet show any indication of relationship

towards the employer of choice, as the students are yet only about to enter the market of

employment (Berthon, Ewin and Hah, 2005). Even if Collins and Zedeck (2007)

provides research with scientific findings which indicate individuals who are searching

for an employment tend to be more attracted to brands with stronger reputation, the

findings of this research distinguishes no direct indication of the variable of brand

reputation to affect the students, when targeting an employer of choice. Moreover,

social value and work content are showed to be significant employer brand associations

in relation to the employer of choice whereas social value reflects the creative and

supportive team atmosphere (Figurska and Matuska, 2013). The variable of work

content focuses on the work assignments and the interest of each task and how the work

content motivates the individuals (De Fruyt, 2002). Hence, the results show work

content and social value to be the most essential variables for student when considering

an employer of choice. Thus, brand managers need to evaluate how the organisation is

represented towards the target group of employment as Sutherland, Toricelli and Karg

(2002) and Sedighi and Loosemore (2012) describe an employer of choice to be chosen

over other employers.

Furthermore, this research aimed to address whether employer brand emotions have an

impact on the employer of choice. Everyone experiences emotions and it is argued by

Rampl, et. al (2014) that the decision process is affected by positive emotions, which

therefore may be of importance of the employer brand management. The connection

between decisions and employer brand emotions is argued to be positive, hence,

indicating the importance of understanding and applying employer brand emotions as a

variable for being an employer of choice. (Vytal and Hamann, 2010; Rampl, et al.,

2014; Deppe, et al., 2005). In order to increase the level of attractiveness, positive

emotions are needed. The more positive emotions, the higher level of attractiveness

(Rampl, et al., 2014). As the relationship between the two variables were tested, it was

indicated that employer brand emotions predict being an employer of choice. Hence the

third hypothesis (H3) was accepted, strengthening the earlier research regarding the

49

connection between employer brand emotions and an employer of choice (Vytal and

Hamann, 2010; Rampl, et al., 2014; Deppe, et al., 2005).

The fourth hypothesis (H4), investigated the employer brand emotions as a mediator

between employer brand associations and being an employer of choice. The results

defined, provide findings which accept the hypothesis for two variables, however in

different approaches. The results of the mediation analysis indicate that social value is

accepted through three of the four tests, which indicates for social value to function as a

full mediator (MacKinnon, 2008), whereas the variable of work content is accepted

through all four tests and hence function as a partial mediator (MacKinnon, 2008).

Therefore, since the hypothesis of H4d works as a full mediator, while H4e works as a

partial mediator as seen in table 5.2.3, both hypotheses are accepted, indicating for the

two variables aligned with the variable of employer brand emotions to be the most

essential employer brand associations. In relation to Rampl (2014), who discovered the

variables of work content and social value to have a full mediator effect, this research

suggests for work content to function as a partial mediation rather than as a full

mediator.

50

7. Conclusion The aim for this study was to further extend the work of Rampl by describing the role of

employer brand emotions towards an employer of choice and to interpret the mediating

effect on employer brand associations in regard to an employer of choice. Concluding

the results, it is defined that the employer brand emotions have a positive relationship

with employer brand associations as four of the five hypotheses are accepted (H1a, b, d,

e). The one variable which was rejected identifies the economic value to provide no

further connection to employer brand emotions. The second hypothesis, described the

role of employer brand associations in regard to an employer of choice, indicated only

the importance of two variables when evaluating an employer of choice. Social value

and work content were proven to be the most significant variables (H2d, e) for students

on a university level. Thus, advancement opportunity (H2a), brand reputation (H2b) and

economic value (H2c) were all rejected, indicating a weak relationship. Interpreting the

effect of employer brand emotions, it is clear to define the important relationship

between employer brand emotions and an employer of choice as H3 was accepted.

The last hypotheses focused on the mediation effect of employer brand emotions

intervening in the relationship between employer brand associations and being an

employer of choice which addresses the purpose of the research. Since the variables of

advancement opportunity (H4a), brand reputation (H4b) and economic value (H4c)

were not accepted in both H1 and H2, these were excluded for the mediation analysis,

since it is theoretically required to be accepted for both H1 and H2. The two employer

brand associations of social value and work content, earlier accepted in the first and

second hypothesis, showed a significant relationship in the mediation analysis and

hence H4d and H4e were accepted. Interpreting the mediation affect, the results defined

the variable of social value to have a full mediator affect, and work content to have a

partial mediation effect.

51

7.1 Managerial implications

Employer brand emotions are proven to have a strong relationship with employer brand

associations, indicating the importance of brand managers to include the positive

employer brand emotions to capture interest of potential employees. Moreover, the

results indicated the significant variable of social value and work content among

students as important associations towards an employer of choice. Thus, in order to

attract the most suitable and appropriate employees, in regards to students on a

university level, brand managers should act on the employer’s brand associations of

social value and work content. By doing so organisations should consider the positive

employer brand emotions to become an employer of choice, hence differentiate itself

and compete for attracting the most talented employees. However, the research only

reflects students on a university level in Sweden, which is of importance for brand

managers to reflect upon.

7.2 Academic implications Earlier research indicates for emotions to have an impact on the decision-making

process when becoming an employer of choice (Chou, et al., 2007; Rampl, et al., 2014).

Bhatt (2015) explained the importance to understand what expectations students have o

an employer when searching for a new employment. However, limited research is

described by Rampl (2014) and Almacik, et al., (2014) when interpreting the term of

employer of choice in different contexts, an address for more research within the area.

Therefore, in line with Rampl, it is suggested for implementing employer brand

emotions as a relevant variable in branding research. The findings of the research in the

context of Swedish university students suggest positive employer brand emotions to be

a driving force in connection to the employer brand associations of social value and

work content when becoming an employer of choice. The research contributes with an

understanding of the significant variables of Swedish university students and strengthen

the indication earlier founded by Rampl, of employer brand emotions to have a

mediating effect on the variables of social value and work content in relation to

employer of choice.

52

8. Limitations and future research The research interpreted the context of university students in Sweden, studying

programmes within economy and resulted in 133 respondents to address the purpose of

the research. In regard to the method used, the number of respondents is a relevant

sample size, however a larger number of respondents would increase the

generalizability of the context. Moreover, the age, gender and work experience could

have been interpreted further to evaluate and describe a difference between the

respondents.

A convenience sample was considered for the research and hence may question the

generalizability of the research (Bryman and Bell, 2015). The majority of the sample

were students of Linnaeus University in Växjö, which also may question the

generalizability of the study.

The research focuses on the foundation of the earlier constructed research by Rampl.

The research is in line with her findings, thus strengthening the reliability of the

framework. The research was conducted within a different context and addressed the

gap of describing the role of employer brand emotions and the employer brand

associations in a different context. Future research should still address to describe the

role of employer brand emotions and the relation to employer brand associations when

becoming an employer of choice in different contexts, to generalize the research.

Additionally, this study aligned with Rampl addressed students as target participants.

Although, future research may be advised to continue to focus on adding to existing

research by interpreting additional contexts. Moreover, future research is advised to

discover the significant role of employer brand associations on previous students with

an employement to distinguish if differences in work experience may impact the

employer of choice.

53

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I

Appendices Appendix 1

II

III

IV

V

VI

VII

VIII

IX

Appendix 2 N Minimum Maximum Mean Std.

Deviation Skewness Kurtosis

Statistic Statistic Statistic Statistic Statistic Statistic Std. Error

Statistic Std. Error

Advancement opportunity 1

133 1 7 5,56

1,339

-0,907

0,210

0,503

0,417

Advancement opportunity 2

133 1 7 5,05

2,165

-0,733

0,210

-0,957

0,417

Advancement opportunity 3

133 1 7 5,65

1,442

-0,991

0,210

0,353

0,417

Brand reputation1

133 2 7 6,00

1,121

-1,178

0,210

1,132

0,417

Brand reputation 2

133 1 7 5,11

1,675

-0,522

0,210

-0,701

0,417

Brand reputation 3

133 1 7 4,74

1,381

-0,075

0,210

-0,436

0,417

Brand reputation 4

133 3 7 6,14

0,998

-1,111

0,210

0,804

0,417

Economic value 1

133 1 7 4,63

1,459

-0,242

0,210

-0,410

0,417

Economic value 2

133 1 7 4,77

1,632

-0,657

0,210

-0,183

0,417

Economic value 3

133 1 7 5,06

1,418

-1,030

0,210

1,030

0,417

Social value 1 133 1 7 5,19

1,746

-0,744

0,210

-0,355

0,417

Social value 2 133 2 7 5,89

1,099

-1,131

0,210

1,377

0,417

Social value 3 133 2 7 5,57

1,195

-0,577

0,210

-0,190

0,417

Work content 1

133 1 7 5,12

1,488

-0,644

0,210

0,048

0,417

Work content 2

133 1 7 5,43

1,484

-1,039

0,210

0,645

0,417

Work content 3

133 1 7 5,22

1,616

-0,962

0,210

0,229

0,417

Employer brand emotions 1

133 1 7 5,83

1,213

-1,278

0,210

1,734

0,417

Employer brand emotions 2

133 1 7 5,21

1,728

-0,877

0,210

-0,179

0,417

Employer brand emotions 3

133 1 7 5,50

1,668

-1,006

0,210

0,163

0,417

Employer of choice 1

133 1 7 5,42

1,810

-1,092

0,210

0,091

0,417

Employer of choice 2

133 1 7 5,41

1,567

-0,807

0,210

-0,079

0,417

Employer of choice 3

133 1 7 4,86

1,843

-0,731

0,210

-0,540

0,417

Valid N 133 Appendix 2 – Descriptive statistics

X

Appendix 3 Model 1

Control Model 2

Model 3

Model 4

Model 5

Model 6

Model 7 All

Result

Intercept 5,320 0,000

1,683 0,000

0,625 0,269

2,285 0,000

0,046 0,920

1,126 0,002

-0,929 0,038

Control variables

Gender Beta Std. Error Sig.

-0,014 0,239 0,870

0,079 0,185 0,246

-0,001 0,190 0,991

0,008 0,195 0,906

-0,023 0,163 0,705

0,035 0,161 0,555

0,037 0,140 0,470

Age Beta Std. Error Sig.

0,113 0,177 0,209

0,066 0,136 0,340

0,111 0,141 0,122

0,061 0,145 0,403

0,075 0,121 0,218

0,089 0,119 0,142

0,075 0,102 0,149

Work experience

Beta Std. Error Sig.

0,121 0,463 0,178

0,017 0,358 0,803

0,078 0,368 0,275

0,088 0,378 0,227

0,077 0,315 0,211

0,076 0,311 0,210

0,042 0,268 0,418

Independent variable

H1a – Advancement opportunity

Beta Std. Error Sig.

0,656 0,070 0,000

0,183 0,077 0,016*

Accepted

H1b – Brand reputation

Beta Std. Error Sig.

0,607 0,098 0,000

0,170 0,103 0,022*

Accepted

H1c – Economic value

Beta Std. Error Sig.

0,580 0,079 0,000

-0,016 0,082 0,832

Rejected

H1d – Social value

Beta Std. Error Sig.

0,729 0,079 0,000

0,257 0,108 0,002*

Accepted

H1e – Work content

Beta Std. Error Sig.

0,739 0,063 0,000

0,377 0,082 0,000*

Accepted

Entry mode R2 0,022 0,433 0,388 0,354 0,551 0,563 0,693 Adjusted R2 -0,001 0,415 0,369 0,334 0,537 0,549 0,673 F-value Sig.

0,953 0,417

24,403 0,000

20,276 0,000

17,569 0,000

39,252 0,000

41,170 0,000

34,934 0,000

Degrees of freedom (df) Regression

3 4 4 4 4 4 8

* Significant to 95% Appendix 3 – Dependent variable: Employer brand emotions

XI

Appendix 4 Model 1

Control Model 2

Model 3

Model 4

Model 5

Model 6

Model 7 All

Result

Intercept 5,074 0,000

1,685 0,001

1,000 0,140

2,093 0,000

-0,339 0,518

0,468 0,230

-0,838 0,114

Control variables

Gender Beta Std. Error Sig.

-0,018 0,260 0,839

0,062 0,219 0,401

-0,007 0,227 0,928

0,003 0,222 0,970

-0,026 0,187 0,686

0,032 0,172 0,582

0,029 0,166 0,608

Age Beta Std. Error Sig.

0,088 0,192 0,329

0,047 0,161 0,535

0,086 0,168 0,276

0,041 0,165 0,594

0,052 0,139 0,422

0,063 0,127 0,289

0,050 0,122 0,376

Work experience

Beta Std. Error Sig.

0,088 0,502 0,330

-0,002 0,424 0,983

0,053 0,441 0,500

0,058 0,429 0,448

0,046 0,363 0,483

0,042 0,333 0,483

0,022 0,319 0,696

Independent variable

H2a Beta Std. Error Sig.

0,566 0,083 0,000

0,113 0,092 0,176

Rejected

H2b Beta Std. Error Sig.

0,487 0,117 0,000

0,034 0,123 0,674

Rejected

H2c Beta Std. Error Sig.

0,527 0,090 0,000

0,007 0,098 0,936

Rejected

H2d Beta Std. Error Sig.

0,693 0,090 0,000

0,245 0,128 0,007*

Accepted

H2e Beta Std. Error Sig.

0,751 0,068 0,000

0,490 0,098 0,000*

Accepted

Entry mode R2 0,012 0,318 0,249 0,288 0,490 0,572 0,627 Adjusted R2 -0,010 0,297

0,225 0,265 0,474 0,559 0,603

F-value Sig.

0,544 0,653

14,944 0,000

10,602 0,000

12,923 0,000

30,785 0,000

42,755 0,000

26,050 0,000

Degrees of freedom (df) Regression

3 4 4 4 4 4 8

* Significant to 95% Appendix 4 – Dependent variable: Employer of choice

XII

Appendix 5 Model 1

Control Model 2

Result

Intercept 5,074 0,000

-0,069 0,786

Control variables Gender Beta

Std. Error Sig.

-0,018 0,260 0,839

-0,005 0,118 0,900

Age Beta Std. Error Sig.

0,088 0,192 0,329

-0,013 0,088 0,750

Work experience

Beta Std. Error Sig.

0,088 0,502 0,330

-0,020 0,231 0,621

Independent variable H3 - Employer brand emotions

Beta Std. Error Sig.

0,895 0,044 0,000

Accepted

Entry mode R2 0,012 0,796 Adjusted R2 -0,010 0,790 F-value Sig.

0,544 0,653

125,236 0,000

Degrees of freedom (df) Regression

3 4

* Significant to 95% Appendix 5: Dependent variable: Employer of choice

XIII

Appendix 6 Model 1

Control Model 2

Model 3

Model 4

Result

Intercept 5,074 0,000

-0,069 0,786

-0,380 0,250

-0,438 0,102

Control variables

Gender Beta Std. Error Sig.

-0,018 0,260 0,839

-0,005 0,118 0,900

-0,007 0,118 0,862

0,006 0,114 0,873

Age Beta Std. Error Sig.

0,088 0,192 0,329

-0,013 0,088 0,750

-0,010 0,088 0,802

-0,003 0,085 0,945

Work experience

Beta Std. Error Sig.

0,088 0,502 0,330

-0,02 0,231 0,621

-0,018 0,230 0,663

-0,015 0,221 0,713

Independent variable

H4d – Social value

Beta Std. Error Sig.

0,087 0,084 0,139

Rejected

H4e - Work content

Beta Std. Error Sig.

0,201 0,066 0,001**

Accepted

Employer brand emotions

Beta Std. Error Sig.

0,895 0,063 0,000

0,830 0,064 0,000

0,745 0,062 0,000

Entry mode

R2 0,012 0,796 0,800 0,814

Adjusted R2 -0,010 0,790 0,792 0,807

F-value Sig.

0,544 125,236 0,000

101,584 0,000

111,466 0,000

Degrees of freedom (df) Regression

3 4 5 5

** Significant to 95% Appendix 6 – The fourth step of the mediation analysis where the independent variables which were accepted in the earlier steps of the mediation process, are measured independently with the mediator of employer brand emotions. Employer of choice is dependent variable.

XIV

XV

Appendix 7 Correlations

Advancement opportunity 1

Advancement opportunity 2

Advancement opportunity 3

Advancement opportunity 1

Pearson Correlation

1 ,638** ,555**

Sig. (2-tailed) 0,000 0,000

N 133 133 133

Advancement opportunity 2

Pearson Correlation

,638** 1 ,511**

Sig. (2-tailed) 0,000 0,000

N 133 133 133

Advancement opportunity 3

Pearson Correlation

,555** ,511** 1

Sig. (2-tailed) 0,000 0,000

N 133 133 133

**. Correlation is significant at the 0.01 level (2-tailed).

Correlations

Brand

reputation 1 Brand

reputation 2 Brand

reputation 3 Brand

reputation 4 Brand reputation 1 Pearson

Correlation 1 ,609** ,274** ,623**

Sig. (2-tailed) 0,000 0,001 0,000 N 133 133 133 133

Brand reputation 2 Pearson Correlation ,609** 1 ,497** ,485**

Sig. (2-tailed) 0,000 0,000 0,000 N 133 133 133 133

Brand reputation 3 Pearson Correlation ,274** ,497** 1 ,394**

Sig. (2-tailed) 0,001 0,000 0,000 N 133 133 133 133

Brand reputation 4 Pearson Correlation ,623** ,485** ,394** 1

Sig. (2-tailed) 0,000 0,000 0,000 N 133 133 133 133

**. Correlation is significant at the 0.01 level (2-tailed).

XVI

Correlations

Economic value 1 Economic value 2 Economic value 3 Economic value 1 Pearson Correlation 1 ,495** ,688**

Sig. (2-tailed) 0,000 0,000 N 133 133 133

Economic value 2 Pearson Correlation ,495** 1 ,657** Sig. (2-tailed) 0,000 0,000 N 133 133 133

Economic value 3 Pearson Correlation ,688** ,657** 1 Sig. (2-tailed) 0,000 0,000 N 133 133 133

**. Correlation is significant at the 0.01 level (2-tailed).

Correlations

Social value 1 Social value 2 Social value 3 Social value 1 Pearson Correlation 1 ,446** ,340**

Sig. (2-tailed) 0,000 0,000 N 133 133 133

Social value 2 Pearson Correlation ,446** 1 ,661** Sig. (2-tailed) 0,000 0,000 N 133 133 133

Social value 3 Pearson Correlation ,340** ,661** 1 Sig. (2-tailed) 0,000 0,000 N 133 133 133

**. Correlation is significant at the 0.01 level (2-tailed).

Correlations

Work content 1 Work content 2 Work content 3 Work content 1 Pearson Correlation 1 ,653** ,496**

Sig. (2-tailed) 0,000 0,000 N 133 133 133

Work content 2 Pearson Correlation ,653** 1 ,738** Sig. (2-tailed) 0,000 0,000 N 133 133 133

Work content 3 Pearson Correlation ,496** ,738** 1 Sig. (2-tailed) 0,000 0,000 N 133 133 133

**. Correlation is significant at the 0.01 level (2-tailed).

XVII

Correlations

Employer brand

emotions 1 Employer brand

emotions 2 Employer brand

emotions 3 Employer brand emotions 1 Pearson Correlation 1 ,779** ,741**

Sig. (2-tailed) 0,000 0,000 N 133 133 133

Employer brand emotions 2 Pearson Correlation ,779** 1 ,862** Sig. (2-tailed) 0,000 0,000 N 133 133 133

Employer brand emotions 3 Pearson Correlation ,741** ,862** 1 Sig. (2-tailed) 0,000 0,000 N 133 133 133

**. Correlation is significant at the 0.01 level (2-tailed).

Correlations

Employer of choice 1 Employer of choice 2 Employer of choice 3 Employer of choice 1 Pearson Correlation 1 ,572** ,834**

Sig. (2-tailed) 0,000 0,000 N 133 133 133

Employer of choice 2 Pearson Correlation ,572** 1 ,626** Sig. (2-tailed) 0,000 0,000 N 133 133 133

Employer of choice 3 Pearson Correlation ,834** ,626** 1 Sig. (2-tailed) 0,000 0,000 N 133 133 133

**. Correlation is significant at the 0.01 level (2-tailed).