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EMPLOYEE-RECRUITER MATCHING A quantitative study about students’ perceptions and recruiters’ wants Authors: Emelie Lindwall Marketing Programme Johanna Gustafsson Marketing Programme Martin Stadig Marketing Programme Examiner: Dr. Setayesh Sattari Tutor: Dr. Martin Amsteus Bachelor Thesis Spring 2013

Transcript of EMPLOYEE-RECRUITER MATCHING626431/FULLTEXT01.pdf · EMPLOYEE-RECRUITER ... Attracting the right...

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EMPLOYEE-RECRUITER

MATCHING

A quantitative study about students’ perceptions and recruiters’ wants

_________________________________________________________________

______ Authors: Emelie Lindwall

Marketing Programme

Johanna Gustafsson

Marketing Programme

Martin Stadig

Marketing Programme

Examiner: Dr. Setayesh Sattari

Tutor: Dr. Martin Amsteus

Bachelor Thesis

Spring 2013

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ABSTRACT

Recruiters are hiring people with the right set of skills and attributes in order to fit the demands

of the company. Simultaneously, students who decide to invest in a university education are most

likely doing it for one major reason – to become more attractive in the labor market. A problem

arose concerning whether there is a discrepancy between students’ perceptions of sought

employee attributes and wanted attributes by recruiters, or not. Therefore, the current study

aimed at assessing the discrepancy between the employee attributes that employers want, and

students’ perceptions of sought employee attributes.

Available literature within the field was reviewed, resulting in an identified research gap which

led to a research question as well as four stated hypotheses.

Methodology wise, a pre-study was conducted in the current research which had a qualitative

approach in order to construct the questionnaires for the main part of the study, which had a

quantitative approach. The questionnaires were answered by 83 students and 126 recruiters.

The results from the study showed that discrepancies exist concerning 10 of 26 measured

attributes. Students perceived interpersonal skills, teamwork, knowledge about the market,

gender, and well formulated CV and personal letter to be more important than recruiter

considered them to be. Moreover, recruiters considered self-management, commitment,

responsibility, self-awareness, and physical well-being to be more important than students

perceived them to be.

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ACKNOWLEDGEMENTS

The following study was performed as our bachelor thesis during our last semester at the

Marketing Programme at Linnaeus University. The process of writing the thesis has not only

developed us as individuals and as a team, but has also broadened our knowledge of the chosen

subject. This thesis is valuable, not only for us, but for all students studying at marketing

programs throughout Sweden, who sooner or later will face the reality outside the walls of the

universities. Our journey of writing this thesis has come to an end, and with the final draft in our

hands we would like to conclude by thanking the people who have been important for us, as well

as for the result of the thesis.

First of all we would like to thank our examiner Dr. Setayesh Sattari who has always been there

to support us with our ongoing thesis work. The feedback has not only been invaluable, but also

crucial to how our final product is presented. We would also like to thank our tutor Dr. Martin

Amsteus, who week after week has given us invaluable comments and feedback. Thanks to Dr.

Magnus Hultman who gave us not only valuable feedback on our thesis, but who has also

broadened our knowledge and insight in how to work with the methodological tools. We would

also like to thank our fellow students who throughout the whole process of writing this thesis

have given us valuable comments.

Linnaeus University

May 2013

Emelie Lindwall Johanna Gustafsson Martin Stadig

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TABLE OF CONTENTS

1. INTRODUCTION ............................................................................................ 1

1.1 BACKGROUND ................................................................................................................... 1

1.2 PROBLEM DISCUSSION ................................................................................................... 2

1.3 DELIMITATIONS ................................................................................................................ 3

1.4 OUTLINE OF THE PAPER .................................................................................................. 3

2. THEORETICAL BACKGROUND ................................................................ 5

2.1 SKILLS ................................................................................................................................. 5

2.2 EMPLOYEE ATTRIBUTES ................................................................................................. 6

2.2.1 From a Recruiter’s Point of View ................................................................................................ 6

2.2.2 From an Employee’s Point of View ............................................................................................. 7

2.3 STUDENTS’ PERCEPTIONS .............................................................................................. 8

2.4 RECRUITERS’ WANTS ....................................................................................................... 9

2.5 EVOLUTIONARY PERSPECTIVE AND MATCHING ..................................................... 9

2.6 CHAPTER SUMMARY ..................................................................................................... 10

3. RESARCH GAP AND HYPOTHESES ....................................................... 11

3.1 RESEARCH GAP ................................................................................................................ 11

3.2 RESEARCH QUESTION AND HYPOTHESES ................................................................ 11

3.3 CHAPTER SUMMARY ..................................................................................................... 12

4. METHODOLOGY.........................................................................................13

4.1 RESEARCH APPROACHES ............................................................................................. 13

4.1.1 Inductive vs. Deductive Research .............................................................................................. 13

4.1.2 Dyadic Research ........................................................................................................................ 14

4.1.3 Quantitative vs. Qualitative Research ........................................................................................ 14

4.2 RESEARCH DESIGNS ...................................................................................................... 14

4.3 DATA SOURCES ................................................................................................................ 16

4.4 RESEARCH STRATEGIES ............................................................................................... 16

4.5 DATA COLLECTION METHODS .................................................................................... 16

4.5.1 Focus Groups ............................................................................................................................. 17

4.5.2 Interviews ................................................................................................................................... 17

4.5.3 Questionnaires ............................................................................................................................ 18

4.6 DATA COLLECTION INSTRUMENTS ............................................................................ 18

4.6.1 Operationalization ...................................................................................................................... 19

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4.6.2 Interview Guide/Questionnaire Design ...................................................................................... 20

4.6.3 Pretesting .................................................................................................................................... 22

4.7 SAMPLING ........................................................................................................................ 24

4.7.1 Sampling Frame ......................................................................................................................... 24

4.7.2 Sample Selection ........................................................................................................................ 24

4.8 DATA ANALYSIS ............................................................................................................... 26

4.8.1 Qualitative Data Analysis .......................................................................................................... 26

4.8.2 Quantitative Data Analysis ........................................................................................................ 27

4.9 QUALITY CRITERIA ........................................................................................................ 29

4.9.1 Quality Criteria for Qualitative Research .................................................................................. 29

4.9.2 Quality Criteria for Quantitative Research ................................................................................ 30

4.10 CHAPTER SUMMARY ................................................................................................... 31

5. EMPIRICAL DATA .......................................................................................33

5.1 EMPIRICAL DATA – FOCUS GROUPS ........................................................................... 33

5.2 EMPIRICAL DATA - INTERVIEWS ................................................................................. 34

5.3 CHAPTER SUMMARY ..................................................................................................... 35

6. RESULTS ........................................................................................................36

6.1 QUALITATIVE RESEARCH ............................................................................................. 36

6.1.1 Qualitative Reliability and Validity ........................................................................................... 36

6.1.2 Qualitative Results ..................................................................................................................... 36

6.2 QUANTITATIVE RESEARCH .......................................................................................... 39

6.2.1 Quantitative Reliability and Validity ......................................................................................... 39

6.2.2 Descriptive Statistics .................................................................................................................. 40

6.2.3 Hypotheses ................................................................................................................................. 42

6.2.4 Additional Results ...................................................................................................................... 45

6.3 CHAPTER SUMMARY ..................................................................................................... 47

7. DISCUSSIONS, CONCLUSION, IMPLICATIONS, LIMITATIONS &

SUGGESTIONS FOR FUTURE RESEARCH ...............................................48

7.1. DISCUSSIONS .................................................................................................................. 48

7.1.1 Discussion of Research Question and Hypotheses .................................................................... 48

7.1.2 Discussion of Additional Results ............................................................................................... 49

7.2 CONCLUSION ................................................................................................................... 51

7.3 IMPLICATIONS ................................................................................................................. 52

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7.3.1 Theoretical Implications ............................................................................................................ 52

7.3.2 Managerial Implications ............................................................................................................ 53

7.4 LIMITATIONS .................................................................................................................... 53

7.5 SUGGESTIONS FOR FUTURE RESEARCH .................................................................. 54

7.6 CHAPTER SUMMERY ...................................................................................................... 55

REFERENCE LIST ...........................................................................................56

APPENDIX A: METHOD .................................................................................63

APPENDIX B: RESULTS .................................................................................73

APPENDIX C: QUESTIONNAIRE DESIGN ................................................85

LIST OF FIGURES

Figure 3.1: Research Question .................................................................................................... 12

Figure 4.1: Inductive and Deductive Research ........................................................................... 13

Figure 4.2: Research Design ....................................................................................................... 15

Figure 4.3: Data Collection Methods .......................................................................................... 17

LIST OF TABLES

Table 4.1: Method Summary ....................................................................................................... 31

Table 5.1: Empirical Data – Focus Groups ................................................................................. 33

Table 5.2: Empirical Data – Interviews ....................................................................................... 34

Table 6.1: Soft Skills ................................................................................................................... 37

Table 6.2: Hard Skills .................................................................................................................. 38

Table 6.3: Other Attributes .......................................................................................................... 39

Table 6.4: Descriptive Statistics Students ................................................................................... 41

Table 6.5: Descriptive Statistics Recruiters................................................................................. 42

Table 6.6: Hypotheses ................................................................................................................. 43

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CHAPTER ONE - INTRODUCTION

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. INTRODUCTION

In this chapter, the background of the study is presented. This is followed by a problem

discussion of the field, which leads to the purpose of the study. Finally, the delimitations

of the study are stated followed by an outline of the paper.

1.1 BACKGROUND

“Too many leave university without the right skills” (Daily Mail, 2012) and the numbers of

students graduating from universities in Sweden are increasing (HSV, 2011). However, it is

getting harder for students with a university degree to find a job directly after graduation (SCB,

2011). The aim for these students is often to collect knowledge and skills to become attractive in

the labor market. For these students to be attractive to companies, they have to show proof of

having the skills required by the employers (Raybould & Sheedy, 2005). Employers are hiring

employees with the right knowledge and skills to fit the culture in the company (Adkins et al,

1994). Recruitment from a company perspective can be defined as a process of attracting the

right persons into a company (Gatewood et al, 1993).

It is important for companies to find the right applicants during the recruitment process, to

sustain competitive advantage against rivals in the market (Pfeffer, 1994). Burack and Singh

(1995) demonstrate the importance of hiring people that will be adjustable for rapid changes in

the market field. Pfeffer (1994) writes that it is the individual worker who is the source for

companies’ competitive advantages. With this in mind, the human resources department has an

important role to maintain this competitive advantage by recruiting the right people that fit the

company culture. Attracting the right people for the jobs is of big interest for employers, to

minimize the risk of employing wrong personnel (Kazlauskaité & Bučiūnienė, 2008).

According to Hutchinson and Brefka (1997), job objective, academic background and work

experience are important hard skills companies look for when they are looking for new

employees. Hutchinson and Brefka (1997) also argue that personal and social skills, also known

as soft skills, are not as important when employing new personnel. On the other hand, Nealy

(2005) argues that soft skills are more important in today’s labor market for productive

1

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CHAPTER ONE - INTRODUCTION

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performance and that current and future business leaders are looking more at these skills than

hard ones when employing new personnel.

Hesketh (2000) conducted a study which showed that employers prefer to recruit students from

specific universities, more specifically the universities that had “high status” in the university

market. A study conducted by Salas Velasco (2012), demonstrates that students with higher

average grades have a better chance of finding a job after graduation. However, Branine (2008)

found that recruitment of students have become more about finding people with the right

attitudes and personality.

1.2 PROBLEM DISCUSSION

Employers may have specific opinions about which attributes an employee should possess. For

instance, when an organization looks at hiring newly graduated students, employers look at

grades, personality as well as other personal qualities that an organization may have use for in

newly graduated students, according to Salas Velasco (2012). Branine (2008) highlights the

importance of applicant attitudes and personality, which he says are more important to employers

than the type or level of qualification acquired. However, Behrenz (2001) states that it is not until

in the second round of the recruitment process that employers start to look at soft skills and that

job seekers often are eliminated in the first round due to lack of experience or education. Hence,

the opinions regarding which attributes that are attractive to possess vary across available

literature.

Salas Velasco (2012) highlights that a students’ human resources and intangible assets are two of

the main things that will lead to competitive advantages for an organization. Salas Velasco

(2012) also contends that the hiring process within the graduate labor market is poorly

understood and hardly studied at all.

Students may have perceptions of what employers are looking for. What students perceive is

what employers will target in an applicant does not usually match the organization’s perception

of the subject (Salas Velasco, 2012). Moreover, according to Salas Velasco (2012), sought

employee attributes may differ depending on what kind of job and position or in what kind of

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market the applicant is applying for. If there is a mismatch, there is no adaption to the

environment. Hence, more knowledge is needed concerning whether students’ perceptions of

wanted employee attributes match the employee attributes that employers want.

Consequently, a problem arises concerning whether there is a discrepancy between students’

perceptions of sought employee attributes and wanted attributes by employers or not. Hence, a

dyadic research, which will be further explained in chapter 4, is needed to see whether there is a

mismatch or not.

Purpose: To assess the discrepancy between the employee attributes that employers want, and

students’ perceptions of sought employee attributes.

1.3 DELIMITATIONS

The study focuses exclusively on undergraduate marketing students at Linnaeus University, a

public university situated in Växjö in the south of Sweden. This delimitation is made since the

authors themselves are graduating from the marketing program at Linnaeus University 2013, but

also since the graduated labor market hardly is studied at all (Salas Velasco, 2012).

Delimitations are also made concerning which companies to conduct the study on. The study will

be conducted on manufacturing companies that were the largest employers in Sweden during

year 2012, based on a list from allabolag.se (Allabolag, 2013). Focus will exclusively lie on the

attributes perceived as important, and wanted, for employment at the marketing department in

the manufacturing industry.

1.4 OUTLINE OF THE PAPER

The current study is divided into seven chapters, containing the following structure.

Chapter 1 presents a short background within the field of recruitment. This is followed by a

problem discussion that leads to the purpose of the study. The chapter ends with the delimitations

and outline of the thesis.

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CHAPTER ONE - INTRODUCTION

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4

Chapter 2 presents the theoretical background including concepts, definitions and available

literature within the field.

Chapter 3 presents the research gap, research question and the hypotheses of the study.

Chapter 4 presents and justifies the choices of research approach, research design, data sources,

research strategy, data collection instruments, sampling, data analysis and quality criteria.

Chapter 5 presents the empirical data, collected through focus groups and interviews.

Chapter 6 presents the results from the qualitative data analysis followed by the result from the

quantitative data analysis.

Chapter 7 presents discussions around the finding from the data analysis and a conclusion,

which answers the purpose and research question. The chapter also presents the theoretical and

managerial implications of the study, limitations and suggestions for future research.

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CHAPTER TWO – THEORETICAL BACKGROUND

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. THEORETICAL BACKGROUND

This chapter presents relevant theories from available literature, including

definitions and discussions around them. First, skills are presented followed by

employee attributes seen from two perspectives. This is followed by a discussion

about perceptions, wants, and finally matching and evolutionary perspective.

2.1 SKILLS

Skills can be defined as the certain personal abilities that an individual possesses (Raybould &

Sheedy, 2005). Skills can also be divided into hard skills and soft skills. Hutchinson and Brefka

(1997) define hard skills as job objectives, work experience and academic background.

Hutchinson and Brefka (1997) further define soft skills as the personal and social skill that a

person possesses. McCorkle et al (2003) have a discussion about discipline related and support

skills. McCorkle et al (2003) say that discipline skills are knowledge gathered from school, and

support skills are the same as soft skills, and further mentions communication skills,

interpersonal skills and creativity as examples of soft skills.

Salas Velasco (2012) divides skills into four different categorizations: hard skills, practical

experience, master/languages/study abroad, and soft skills. Salas Velasco (2012) refers to hard

skills as academic ability, knowledge and computer skills. Furthermore, Salas Velasco (2012)

says that soft skills are linked to the personality of a person and examples of soft skills could be

communication, teamwork and leadership. Sharma (2009, p.19) defines soft skills as “the extra

edge that set apart the leader from the followers”. Sharma (2009) also describes soft skills as the

basic life skills or survival skills, which helps people to polish their outer veneer. Moreover,

Sharma (2009) mentions examples of soft skills such as communication skills, interpersonal

skills, negotiation skills, emotional intelligence, teamwork and cooperation.

Another author who discusses the differences between hard skills and soft skills is Robles

(2012). Robles (2012) describes hard skills as the technical expertise and knowledge needed to

find a job, and soft skills as interpersonal qualities. Interpersonal qualities are the people skills

and personal attributes that someone has. Hurrell et al (2012) define a soft skill as a non-

2

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technical skill that involves interpersonal and intrapersonal capabilities to handle performance in

different contexts.

2.2 EMPLOYEE ATTRIBUTES

Two perspectives were found to have been taken upon the attributes necessary for employees to

possess in available literature – from a recruiter’s point of view, and from an employee’s point of

view. These two perspectives are further discussed below.

2.2.1 From a Recruiter’s Point of View

Results regarding which employee attributes that are attractive in new employees, such as

graduates, vary between different articles within the field, but communication is seen as a vital

attribute in most articles. For instance, Raymond and McNabb (1993), highlight that both

employers and students regard communication skills as important to possess. Also in a study by

Robles (2012), a finding was that executives think that employees should be able to

communicate effectively. The same applies in Sharma’s study (2009), where communication

skills were voted as the most important soft skill necessary to possess to be able to succeed at the

workplace.

Authors highlight the importance of other soft skills, rather than communication skills. For

instance, Anderson and Shackleton (1990, p.69) says that “the ideal graduate for all occupational

groups was perceived as interesting, relaxed, strong, successful in life, active, mature,

enthusiastic, sensitive, pleasant, honest and dominant”. Branine (2008) highlights the importance

of soft skills and says that employers look beyond hard skills, and instead look for employees

who are motivated, responsible, and are able to work both independently and in teams. As

mentioned before, Robles (2012) discusses the importance of being able to communicate

effectively, but Robles (2012) also mentions getting along with co-workers, teamwork, initiative

taking, work ethics and professionalism as important. In the study by Sharma (2009),

communication skills were voted as most important as mentioned before, but also teamwork and

time management were mentioned as the second and third most important soft skills to possess.

Junek et al (2009) says that employers think that students who are being employed perform well

in the areas accountability, cooperation, and productivity, to mention a few. Cook and Finch

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(1994) also emphasize soft skills as more important, rather than hard skills. Anderson and

Shackleton (1990) describe the ideal graduate for all occupational groups and only mention soft

skills such as interesting, enthusiastic and honest, while Junek et al (2009) say that students are

accountable and productive. However, Behrenz (2001) highlights personal engagement and

social competence, but also professional knowledge. Cook and Finch (1994) looked at whether

educational background, prior work experience, or training potential was viewed as most

important to recruiters. The result showed that training potential was the most important of the

three, hence, the soft skills overweight the hard skills (Ibid).

Not only soft skills are highlighted as important to possess. For instance, Sharma (2009) both

mentions the soft skills that are necessary to have to succeed at the workplace as well as that

employers also want experienced staff. Similarly, Behrenz (2001) says that job seekers are often

eliminated in the first round of the recruitment process due to the fact that they lack the hard

skills needed such as experience or education, and that it is first in the second round that

employers start to look at the soft skills such as personal engagement and social competence.

However, Behrenz (2001) also says that results show that only somewhat half of those getting

hired fulfilled the demands for experience and/or education completely.

2.2.2 From an Employee’s Point of View

McCorkle et al (2003) found that students with a higher GPA score are better prepared for the

job market. This can be contrasted by Salas Velasco’s article (2012), where the author found that

grades do not matter when applying for a job, and instead discusses that the most important skills

are the soft ones. Junek et al (2009) found that students consider communication skill to be the

most important skill to possess to get employed after graduation. Raymond and McNabb (1993)

came up with the same results. They found that both students and employers have the same

opinions about social skills and communication skills – that they are the most essential skills for

companies when recruiting students (Ibid). DuPre and Williams’ study (2011), concerning the

understanding of students’ perceptions, found that students rank communication skill high, right

below work ethic. Work ethic was considered to be the most important skill (Ibid). All of the

above mentioned studies were conducted within a time span of 18 years and they all got similar

results: from a student’s point of view, communication skill is an important attribute to possess

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in order to be employed by a company. Other important attributes that students consider essential

to possess are work ethics, teamwork skills and to have a good personality (Raymond &

McNabb, 1993; DuPre & Williams, 2011; Salas Velasco, 2012). Attributes that students consider

less important include previous work experience and level of university degree (Raymond &

McNabb, 1993; Salas Velasco, 2012).

Singer and Bruhns (1991) investigated which hard skills that were important to possess from a

student’s perspective, and highlight that work experience is the most essential one. Work

experience is followed by type of education and academic achievements (Ibid). Salas Velasco’s

study (2012) shows that students think good grades are more important than previous working

experience, in the discussion concerning hard skills. The two studies are conducted with a

difference of 21 years and also in different countries, which might explain the differences in the

result. The articles that investigated both soft skills and hard skills (Raymond & McNabb, 1993;

Salas Velasco, 2012) show that students consider soft skills to be more important than hard

skills. The articles highlight the importance of applicants telling the organization or employer

that they possess both the skills and the experience that the organization is demanding.

Graduating students most often have neither experience nor specific skills, but they may have

personal interests or hobbies that in the end can turn into relevant skills. If this is the case,

applicants need to demonstrate that the skills are both transferable and important for the job they

are applying for (Dacre Pool & Sewall, 2007; Breaugh, 2008).

2.3 STUDENTS’ PERCEPTIONS

Perception is defined as the process by which stimuli are selected, organized and interpreted

(Solomon et al, 2010). Applicants who are applying for a job often have inaccurate perceptions

of the position that they are applying for, and often applicants get wrong expectations from the

employers of what the job will give them in return (Breaugh, 2008). If an applicant gets hired

with wrong expectations it will most likely lead to dissatisfaction, and subsequently quitting

within a near future, than applicants who get a more accurate perception (Ibid). Dacre Pool and

Sewall (2007) highlight the importance of aligning students’ perceptions with the industry’s

expectations over how to perform to get a job. Moreover, Dacre Pool and Sewall (2007) say that

as it is now, students’ perceptions do not match the industry’s expectations of performance.

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According to DuPre and Williams (2011) students’ perceptions of what an employer seeks in

new coworkers are: work ethic, communication skills, teamwork, analytical skills, and technical

skills.

2.4 RECRUITERS’ WANTS

Wants is defined as a need that must be satisfied, which can be both individually and culturally

determined (Solomon et al, 2010). Marketing is a broad field when it comes to applying for jobs,

and recruiters want employees to possess both soft and hard skills (Salas Velasco, 2012).

Specific jobs demand specific attributes, as well as small employers versus large employers

demand different attributes (Ibid). According to Kelley and Gaedeke (1990), the most wanted

attributes by employers who are recruiting people for marketing positions are: oral

communication skills, interpersonal skills, enthusiasm/motivation, written communication skills,

as well as work experience. Floyd and Gordon (1998), among others, also highlight the value of

problem-solving skills, while Salas Velasco (2012) highlights the importance of personal

characteristics. Employers are less concerned about numerical and information technology skills

of graduating students and instead appreciate skill such as self-management and teamwork

(Ibid). Behrenz (2001) however, highlights that there is an interaction between wanted hard and

soft skills. Behrenz (2001) says that employers mainly want job applicants with a good education

and work experience in the first round of the recruitment process, but that they in the second

round prefer skills such as professional knowledge, personal engagement as well as social

competence.

2.5 EVOLUTIONARY PERSPECTIVE AND MATCHING

Evolutionary perspective has its roots in Charles Darwin’s famous theory Darwinism (Hodgson,

2005). Darwin said that the species that best fit the environment would survive and be able to

pass on their positive attributes, while the species with non-surviving attributes will die out

(Ibid). Darwinism principles about variation, replication and selection can also be applied outside

the biological area and is then called universal Darwinism (Dawkins, 1976). Universal

Darwinism can, and has been, applied to other evolving and open systems such as social

evolution (Ibid). When general evolutionary concepts are applied to economic phenomena, this is

referred to as evolutionary economics (Powell & Wakeley, 2003). According to Powell and

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Wakeley (2003) evolutionary perspective aims to explain the process of change within a system.

If there is a change in the system, only those who best fit the environment will succeed in the

future, and the others will fail and gradually disappear (Ibid).

The importance of matching has been discussed for decades, according to Salas Velasco (2012),

for instance cornering matching the right person to the right job. Both employers and job seekers

put a lot of time and resources into the process of job search (Salas Velasco, 2012). For instance,

a conducted study in the North East showed that there was an acute mismatch between supply

and demand of individuals that possessed the wanted set of attributes in sectors such as business-

to-business services (Hartshorn & Sear, 2005). To avoid these happenings, Breaugh (2008)

mentions that organizations must provide realistic information of their wants during the

recruitment process, in order to improve the person-organization fit. Moreover, Breaugh (2008)

says that applicants need to have self-insight to be able to identify a person-organization fit.

Therefore, the process of employee recruitment should be seen as one of the biggest challenges

for organizations (Punia & Sharma, 2008). There is an ongoing uncertainty both within the

economy and the competitive marketplace, why it is crucial for companies to find employees

with the right set of attributes (Ibid). This is important since it might increase the chances for

productivity which affects a company’s earnings, why matching employees to the demands of

the organization becomes vital (Ibid).

2.6 CHAPTER SUMMARY

This chapter has gone through relevant theories from available literature. First, skills were

discussed, where the main discussion concerned the division of skills into categories. The main

focus was on the division into soft skills such as communication skills and personality, and hard

skills, such as experience and academic background. The second theory discussed employee

attributes, seen from two perspectives. Here, researchers’ opinions vary concerning which

attributes employees see as important, and which employee attributes employers find attractive.

The two following theories discussed were perceptions and wants, in relation to the current field

of study. Finally, evolutionary perspective and matching was discussed.

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. RESARCH GAP AND HYPOTHESES

Through the literature review in the previous chapter, it became clear that a research

gap exists. This gap is further discussed in this chapter, followed by the stated

research question and hypotheses of the study.

3.1 RESEARCH GAP

The results from available literature vary, both from recruiters’ and employees’ point of view on

attractive employee attributes. Hence, an updated research was considered necessary. Available

studies have also been conducted in different countries, on different target groups as well as on

slightly or majorly differing subjects. Thus, it was considered necessary to conduct the current

research since the two major viewpoints in available literature were taken together, and research

was conducted on students as well as on recruiters at a possible job market for those students.

Through the literature review, it became clear that earlier researches concerned either which

attributes students think are important to possess for an employee, i.e. from an employee’s point

of view, or concerned which attributes personnel managers want when recruiting new

employees, i.e. from a recruiter’s point of view. Hence, it became clear that no research

compared these two outcomes, which showed a research gap within the field of the study. The

authors therefore concluded that there might not be a match between students’ perceptions of

wanted employee attributes and actually wanted employee attributes, hence this is what is

covered in the current study.

3.2 RESEARCH QUESTION AND HYPOTHESES

The above identified research gap lead to the following research question:

RQ1: Is there a discrepancy between the attributes students perceive as wanted, and the

attributes personnel managers actually want? (shown in figure 3.1)

Moreover, four hypotheses were stated:

● H1: There is a mismatch between the employee attributes that students perceive recruiters

want, and the recruiters’ wants regarding employee attributes.

3

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● H2: There is a mismatch between how important recruiters consider soft skills to be, and

how important students perceive soft skills to be.

● H3: There is a mismatch between how important recruiters consider hard skills to be, and

how important students perceive hard skills to be.

● H4: There is a mismatch between how important recruiters consider other attributes to be,

and how important students perceive other attributes to be.

Figure 3.1: Research Question

3.3 CHAPTER SUMMARY

This chapter has gone through the identified research gap of the study. For instance, an updated

research was considered necessary since the results in available literature vary. Moreover, most

available researches have had either one or the other of two identified viewpoints why it was

considered necessary to combine the two viewpoints in the same research. Furthermore, a

research question was stated, as well as four hypotheses.

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. METHODOLOGY

The following chapter includes descriptions and justifications of choices of research

approach, research design, data sources, research strategies, data collection

methods and data collection instruments. The chapter also describes the process of

sampling and data analysis, and finishes of by describing the quality criteria of the study.

4.1 RESEARCH APPROACHES

This subchapter presents inductive and deductive research, dyadic research, as well as

quantitative and qualitative research, and justifies the approaches chosen for the current study.

4.1.1 Inductive vs. Deductive Research

Inductive and deductive theory are two philosophical approaches in research methodology, in

which valid conclusions can be made (Bryman & Bell, 2011). An inductive approach is mainly

the outcome of research, where conclusions are drawn from collected data and then developed

into new theoretical frameworks (Ibid). According to Bryman and Bell (2011), deductive

research is the most common type of research approach of the two, and represents the

relationship between theory and research (Ibid). When creating hypotheses or research questions,

only accessible theories within the domain are to be used (Ibid). The two approaches are

illustrated in figure 4.1. The current study was exclusively deductive since the purpose, research

question, and hypotheses were based on already existing theories. More information about

inductive and deductive research can be found in Appendix A: Method, A1.

Figure 4.1: Inductive and Deductive Research (adopted from Bryman and Bell, 2011)

4

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4.1.2 Dyadic Research

A dyad is described as when different individuals or organizations interact or work together over

a length of time (Thompson & Walker, 1982; Medlin, 2003). Thompson and Walker (1982) list

three different interpretations a dyad should have to be able to exist: consisting in time, mutual

actions, as well as engage personnel elements from the two objectives in question. When

conducting a dyadic research, conceptualizing the pattern between two individuals or

organizations is essential (Ibid). This may take many forms due to different conceptual models of

relationships and interactions, but can for instance be direction of interaction (Ibid). A dyadic

research do not only reflect one individual or organization, but the relationship and interaction

between them, hence a reflection from two perspectives (Ibid).

Since the current study combined two perspectives, which have been taken in already existing

research, the research was dyadic.

4.1.3 Quantitative vs. Qualitative Research

Research can be divided into a quantitative and/or qualitative research approach (Bryman & Bell,

2011). According to Bryman and Bell (2011), the most obvious distinction is the fact that

quantitative researchers use measurements, while qualitative researchers do not. As mentioned

by Bryman and Bell (2011), there is also a possibility to successfully combine the two

approaches into a mixed methods research approach.

For the current research, it was chosen to use a mixed methods approach, meaning that both

qualitative and quantitative research methods were used. This was chosen since both words and

quantifications were emphasized as important for the study. The qualitative research was used to

collect data for the development of the quantitative research. The main conclusions of the study

were drawn from the quantitative research. More information about quantitative and qualitative

research can be found in Appendix A: Method, A2.

4.2 RESEARCH DESIGNS

A research design is the intended plan to be followed to be able to answer research aims and

objectives, hence it gives a structure to be able to solve the actual problem (Bryman & Bell,

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2011; Hair et al, 2003). There are several types of research designs, as can be seen in figure 4.2,

but mainly three types are discussed by Bryman and Bell (2011): exploratory, descriptive, and

causal research design. Further information about these research designs can be found in

Appendix A: Method, A3.

When selecting which research design to use it is essential to look deeper into factors such as

available resources, previous research, amount of control over variables as well as the purpose

and research questions (Bryman & Bell, 2011). Two research designs were used for the current

study: exploratory research design and descriptive research design. This was due to that both

focus groups and interviews were used to come up with attributes for the questionnaires as well

as a literature review to investigate both recruiters’ and students’ beliefs and opinions concerning

recruitment. Moreover, the resources and time were limited for the current research.

Descriptive research design can be further divided into either longitudinal design or cross-

sectional design, and the choice affect time and resource dimensions (Zikmund et al, 2010;

Bryman & Bell, 2011). Dependent on the previous decision of using a descriptive research

design, a cross-sectional design was chosen thus it preferably can be used when working with

quantitative studies, but also due to the time dimensions and resource constraints. Furthermore, it

was chosen to work with multiple cross-sectional design since the study focuses on more than

one section, i.e. recruiters and students. Figure 4.2 states the choices made regarding the research

design. More information about longitudinal design and cross-sectional design can be found in

Appendix A: Method, A3.

Figure 4.2: Research Design (adopted from Bryman and Bell, 2011)

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4.3 DATA SOURCES

Primary data and secondary data is either qualitative or quantitative data that is collected to

uncover the purpose of a study (Bryman & Bell, 2011). The difference between primary and

secondary data is that the authors themselves collect primary data, while secondary data has been

collected by another researcher and for another purpose (Ghauri & Grønhaug, 2005).

The current study used both primary and secondary data. Due to the lack of previous studies

within the chosen field, the study first and foremost relied on primary data collected through

focus groups, interviews and questionnaires. Further information explaining data sources can be

found in Appendix A: Method, A4.

4.4 RESEARCH STRATEGIES

There are several different research strategies to use when conducting a research, and all

strategies are different when it comes to how to collect and analyze the empirical data (Yin,

2009). Yin (2009) presents five of these research strategies: experiment, survey, archival

analysis, history, and case study.

The research strategy experiment was dismissed since the current study had no interest in having

control over behavioral events. Since the research questions in the current study did not focus on

how and why questions, the strategies history and case study could be excluded. Archival

analysis was dismissed, due to the fact that the research was not conducted on observations and

analyzes of documents or archives. The research strategy survey was considered most

appropriate for the current study, since primary data was collected and focus was not on

collecting and analyzing secondary data. Survey was also considered appropriate since the

current study focuses on creating statistical inferences from the collected data. More information

explaining the different research strategies can be found in Appendix A: Method, A5.

4.5 DATA COLLECTION METHODS

This subchapter presents different research methods to choose from when collecting data.

Bryman and Bell (2003) points out the following five main methods that can be used to collect

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primary data: interviews, questionnaires, focus groups, observations and content analysis. The

three methods used in the current study as can be seen in figure 4.3 – focus groups, interviews

and questionnaires – are further explained in this chapter.

Figure 4.3: Data Collection Methods (adopted from Hair et al, 2003)

4.5.1 Focus Groups

According to Bryman and Bell (2003), focus group is a qualitative data collection method, which

can be described as interviewing several people in a group at the same time, concentrating on

one specific topic. Focus groups was considered to be the most appropriate data collection

instrument to use for the first phase of the data collection, since the aim was to gain greater

knowledge of the respondents’, i.e. students’, perceptions and opinions concerning a specific

topic. More information about focus groups can be found in Appendix A: Method, A6.

4.5.2 Interviews

According to Bryman and Bell (2003) and Hair et al (2003), interviews can be both qualitative

and quantitative and the goal with interviews is to collect information from respondents

concerning their true opinions regarding a complex topic. In a simple way, interviews can be

described as when a person, the interviewer, asks questions to another person, the interviewee

(Hair et al, 2003; Eriksson & Wiedersheim-Paul, 2011). According to Ghauri and Grønhaug

(2005), there are three different types of interviews: structured, unstructured, and semi-

structured. More information about interviews can be found in Appendix A: Method, A7.

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Due to the fact that semi-structured interviews give the interviewer flexibility, e.g. to change the

order as well as ask follow-up questions concerning a specific topic, this approach was

considered the most appropriate one to use. Telephone interviews were used in the current study

for the second phase of the data collection. This was seen as appropriate since it was considered

the easiest and least time consuming way to reach out to the respondents, i.e. personnel managers

at manufacturing companies, and at the same time reach the desired amount of understanding.

4.5.3 Questionnaires

Questionnaire is a quantitative data collection method that preferably can be used if the aim is to

collect data from a large amount of respondents (Hair et al, 2003; Bryman & Bell, 2011). In a

questionnaire, respondents answer pre-determined questions of key characteristics of individuals,

companies, events or other phenomena (Ibid).

For the third and last steps of the data collection, the quantitative research method questionnaire

was used, since it was considered the best way to collect a large amount of data (Bryman & Bell,

2003). Online questionnaire was considered to be the least costly quantitative method to reach

out to the desired large number of respondents, thus it was used (Ibid). More information about

questionnaires as a data collection method can be found in Appendix A: Method, A8.

4.6 DATA COLLECTION INSTRUMENTS

Two different qualitative research methods, focus groups and interviews, were used to create the

basis for the main method of the current study, which was the quantitative research method

questionnaire. Through three focus groups, a list of the employee attributes that students perceive

recruiters look for when hiring employees was created. Through five interviews with personnel

managers, a list of the employee attributes that recruiters want when hiring new employees was

created. A merger of the outcomes was developed into the foundation of the final questionnaires

which were sent to both students and personnel managers. This subchapter goes through the data

collection instruments used for the different data collection methods.

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4.6.1 Operationalization

Operationalization is the process of turning relevant concepts into something measureable, i.e.

developing questions from theories (Bryman & Bell, 2011). The following chapter includes

operationalization for each data collection method used.

4.6.1.1 Operationalization – Focus Groups

Through an operationalization, the following question was developed to be used in the focus

groups with students: “Which employee attributes do you think recruiters consider important

when hiring employees for the marketing department at a manufacturing company?”. The

operationalization can be seen in Appendix A: Method, A9.

4.6.1.2 Operationalization – Interviews

Through an operationalization, the following question was developed to be used in the interviews

with personnel managers: “Which employee attributes do you consider important when hiring

employees for the marketing department at your company?”. The operationalization can be seen

in Appendix A: Method, A10.

4.6.1.3 Operationalization – Questionnaires

Through an operationalization, the following question was developed to be used in the

questionnaire to students: “How important do you think the following employee attributes are for

recruiters, when hiring new employees to the marketing department at a manufacturing

company?”. The attributes are the ones developed through focus groups and interviews.

Through an operationalization, the following question was developed to be used in the

questionnaire to recruiters: “How important do you consider the following employee attributes to

be, when hiring new employees to the marketing department?”. The attributes are the ones

developed through focus groups and interviews.

The operationalization for the two different questionnaires can be seen in Appendix A: Method,

A11.

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4.6.2 Interview Guide/Questionnaire Design

Before a focus group or interview is conducted, there is a need to have a brief list of the topics or

areas that wants to be covered during the focus group or interview (Bryman & Bell, 2011). If

semi-structured interviews are to be conducted, there is a need to have a somewhat more

structured list of issues to be addressed or questions to be asked (Ibid). When it comes to a

questionnaire, the process of designing the questionnaire is rather crucial, due to the well-known

problem of low response rates connected to questionnaires (Ibid).

The interview guides for the focus groups and interviews are presented below, followed by the

questionnaire designs.

4.6.2.1 Interview Guide – Focus Groups

One question was stated during the focus groups:

Which employee attributes do you think recruiters consider important when hiring

employees for the marketing department at a manufacturing company?

This question was lead by a discussion around the specific topic. The students got time to list the

most important attributes individually on a paper, before the group discussion begun. The

answers were compared and discussed between the respondents. The question was asked to find

out which attributes students consider important to possess, and worked as a foundation when

developing the questionnaires.

4.6.2.2 Interview Guide – Interviews

Five interviews with personnel managers were conducted to find out which employee attributes

they consider important when hiring employees to their marketing department. During the

interviews one question was asked:

Which employee attributes do you consider important when hiring employees for the

marketing department at your company?

The aim with the interviews was similar to the aim with the focus groups. Since it was

considered problematic to conduct focus groups with personnel managers, it was decided to

conduct interviews instead. However, the question remained similar to the one asked during the

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focus groups, but was developed to aim at personnel managers’ wants instead of students’

perceptions. Hence, the current question was not developed from other researchers’ interview

questions dealing with similar topics. The aim with this question was to find out which employee

attributes recruiters consider important when hiring new employees, and as with the outcome

from the focus groups, this worked as a foundation when developing the questionnaires.

4.6.2.3 Questionnaire Design

Conducting an online questionnaire was acknowledged as the most appropriate way to reach the

targeted population. The questionnaires were designed via Google Form and a total number of 31

questions were asked in the questionnaires. Two different questionnaires were constructed, due

to that there were two different types of respondents – personnel managers and students. The

questionnaires were designed in a way that they appeared important, where the questions, layout,

color and length of the questionnaire easily could be changed to fit the wanted appeal (Hair et al,

2003). In the questionnaires, closed questions were used since questionnaires with many open

questions have a tendency to lower the response rate (Bryman & Bell, 2011). Closed questions

were also used because they are easier to answer from a respondent’s perspective and are not that

time consuming to analyze (Eliasson, 2010).

The questionnaire designs were developed through a study by Robles (2012). The first part of the

questionnaires contained a descriptive section, with an introduction where it was stated

approximately how long time the questionnaire would take to answer, the purpose of the study,

and who was responsible for it. The cover letters can be seen in Appendix A: Method, A12-A13

The questions were designed in a Likert type scale, where the respondents ranked their answer

on a 1-7 scale depending on how “Not at all important” (1) or “Extremely important” (7) they

considered the stated attribute to be (Bryman & Bell, 2011). This scale was applied on all items.

In the questionnaire sent to student the following question was asked:

How important do you think the following employee attributes are for recruiters, when

hiring new employees to the marketing department at a manufacturing company?

In the questionnaire sent to personnel manager the following questions was asked:

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How important do you consider the following employee attributes to be, when hiring new

employees to the marketing department?

The items that were measured were divided into three categories: soft skills, hard skills, and

other attributes. These categories were however not separated visibly in the questionnaires sent

to the respondents. To see the categories used and the items connected to each category, see table

6.1, 6.2 and 6.3 in chapter 6.

Questions of demography were added at the end of the questionnaires. The following questions

were asked to the students:

Your gender?

Numbers of years you have been studying at the marketing program?

Are you actively searching for a job?

Dream employer?

E-mail address (optional)?

The following questions of demography were asked to the personnel managers:

Your gender?

Your position at the company?

Number of years at current position?

Number of employees at your company?

Industry your company is in?

To see the final drafts of the questionnaires, see Appendix C: Questionnaire Design, C1 for the

questionnaire to students and Appendix C: Questionnaire Design, C2 for the questionnaire to

recruiters.

4.6.3 Pretesting

According to Ghauri and Grønhaug (2005), a pilot study should be considered before conducting

an interview, a focus group or sending out a questionnaire. The pretest should be conducted on a

sample, preferably 3-5 people from the targeted population or with experts within the field, to

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make sure that concepts and questions are understandable (Ibid). Pretesting gives the researchers

a first hint of the responses (Ibid). All together, this makes it easier to prepare the final draft of

questions, intended for the respondents (Ibid). Below, the pretesting for each data collection

instrument is further explained.

4.6.3.1 Pretesting – Focus Groups

For the current study, the question for the focus groups was shown to one academic. It was

considered hard to conduct a more thorough pretest of the intended question for the focus group,

due to the data collection method’s flexibility (Bryman & Bell, 2011).

4.6.3.2 Pretesting – Interviews

For the current study, the interview question was pretested through a review by two academics

(cf. Czaja, 1998; Ghauri & Grønhaug, 2005). Sending the questions to an academic or expert

within the field is a good way of pretesting, since academics and experts easily can detect

problems not found through other techniques (Czaja, 1998; Ghauri & Grønhaug, 2005). This

approach is rather inexpensive, and you will get critique from multiple perspectives (Czaja,

1998). The pretesting of the interview questions was done to ease the understanding of certain

words, terms, and concepts as well as to look deeper into the structure of the sentences and the

possibility of probing (cf. Czaja, 1998). The main goal of the pretest was to receive immediate

thoughts and reactions of the question, as well as to make sure that the question was well

formulated (Czaja, 1998).

4.6.3.3 Pretesting – Questionnaires

According to Czaja (1998), the importance of pretesting a questionnaire first and foremost is

about uncovering whether respondents understand the words, terms and concepts used as well as

how the questions are asked (Ibid). Other crucial factors to uncover are if the respondents

understand the answer format as well as interpret the questions as intended, otherwise the

sentence structure might be too hard and complex (Ibid). If the respondents feel comfortable with

the different response categories, and if they provide complete answers, are other aspects to look

into (Ibid). Last but not least, it is important to look deeper into the respondents attentiveness and

interest of the questionnaire which might give an overall indicator of how easy it is for the

respondents to complete the questionnaire with correct answers (Ibid). Factors affecting this are

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the overall logical flow of the questionnaire and lack of instructions (Ibid). One preferable way

of pretesting a questionnaire is to send it to an academic or expert within the field (Czaja, 1998;

Ghauri & Grønhaug, 2005).

In the current study, the two questionnaires were first sent to three academics. Once feedback

had been given and the questionnaires had been revised, they were sent to 10 potential

respondents – five students and five personnel managers (cf. Ghauri & Grønhaug, 2005).

4.7 SAMPLING

This subchapter presents the sampling frames followed by the sample selection made for each

data collection instrument used. Sample, in this sense, is defined as “the segment of the

population that is selected for an investigation” (Bryman & Bell, 2011, p.176).

4.7.1 Sampling Frame

According to Ghauri and Grønhaug (2005), a sampling frame needs to be used when sampling. A

sampling frame can be described as a list where the whole population is listed, and it is from this

list that the sample will be drawn (Hair et al, 2003; Ghauri & Grønhaug, 2005). The current

study aimed at two populations. The first population was all undergraduate students who were

studying at the marketing program at Linnaeus University in Växjö. The sampling frame for the

students hence was a list of all of these students from which the sample for the focus group could

be drawn. The sampling frame contained 229 units. The second population was personnel

managers at the manufacturing companies which were the largest employers in Sweden during

the year 2012, based on a list from the website allabolag.se. This list contained 687 units. Hence,

this list was the sampling frame for the second population, from which the sample for the

interviews could be drawn.

4.7.2 Sample Selection

When collecting data from one or more elements, there are two different methods to use (Ghauri

& Grønhaug, 2005). One method is to collect data from all people within the population, and the

second one is to collect data from a representative sample of people from the population (Ibid).

The latter one is referred to as sampling (Ibid). There are many different reasons why sampling

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should be used when conducting a research, but the two main reasons are that sampling is both

less costly and less time consuming than collecting data from whole populations (Ibid). The

sample selection for focus groups, interviews and questionnaires are further discussed below.

4.7.2.1 Sample Selection for Focus Groups

The sample for a focus group should be able to represent the population, meaning that the

respondents should be able to represent a specific group (Bryman & Bell, 2011). Opinions

concerning whether or not to select participants who are known to each other differ among

researchers (Ibid). Bryman and Bell (2011) say that some researchers prefer to exclude people

who are known to each other since their existing relationships may contaminate the session.

However, some researchers prefer to select natural groups whenever possible (Ibid). If a focus

group is meant to explore a collective understanding of a topic within a specific group, this can

be achieved more easily by selecting participants who are all members of the same group (Ibid).

The samples for the focus groups were drawn from the aforementioned sampling frame of

students. 18 people accepted the invitations to participate in the focus groups, hence giving six

participants in each of the three focus groups held.

4.7.2.2 Sample Selection for Interviews

The sample of interviewees should be able to give an in-depth analysis, and be able to represent

the targeted population. According to Bryman and Bell (2011), it is more or less impossible for

researchers to explain why the interviewees were selected. Most of the times, the interviewees

are selected randomly from the targeted population by convenience, opportunity or occasion, and

it is also widely known and accepted by the researchers (Ibid).

The sample for the interviews was drawn from the aforementioned sampling frame of personnel

managers. The first five personnel managers from the sampling frame who accepted to

participate in an interview were chosen.

4.7.2.3 Sample Selection for Questionnaires

According to Bryman and Bell (2011), there is almost always a need for sampling when

conducting quantitative research. The validity and reliability, which will be discussed later in this

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chapter, are to an extent affected by the chosen sample, according to Uprichard (2013). Bryman

and Bell (2011) state that there are two different kinds of samples, defined by the way the sample

was selected: probability sample and non-probability sample. If the sample is a probability

sample, each unit in the population has a chance of being selected (Hair et al, 2003; Bryman &

Bell, 2011). In a non-probability sample, the sample has not been selected randomly, meaning

some units are more likely to be selected than others (Ibid). As mentioned by Bryman and Bell

(2011), a probability sample is more likely to generate a representative sample as well as

minimizing the risk of sampling errors. A sampling error is by the same authors defined as “the

difference between a sample and the population from which it is selected” (Bryman & Bell,

2011, p.176).

The sampling made for the questionnaires, both the one to students and the one for personnel

managers, were considered to be probability samples. The questionnaires were sent out to each

unit of the sampling frames, why all units of the populations had the same chance to participate

in the study. Hence, the sample of students contained 229 units and the sample of personnel

managers contained 687 units, i.e. both populations.

4.8 DATA ANALYSIS

This subchapter covers techniques for analyzing qualitative and quantitative data. Analyzing

data, both qualitative and quantitative, is something that should be considered in an early stage

when conducting a research (Bryman & Bell, 2011). However, a common error is that no

concern is taken on how to analyze the collected data until later in the research process (Ibid).

Therefore, the authors should in an early stage be aware of what techniques to use to be able to

analyze collected data (Ibid).

4.8.1 Qualitative Data Analysis

In a research study, the analysis of data is made to gain knowledge and understanding of the

collected data (Ghauri & Grønhaug, 2005). Marshall and Rossman (1999) define data analysis as

when the researchers structure, order and bring meaning to the data that has been collected. The

data analysis helps the researchers to dived and reduce data, clarify problems as well as test

hypotheses (Ghauri & Grønhaug, 2005).

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Miles and Huberman (1994) present three components to use as guidance when conducting the

data analysis. The three components are: data reduction, data display, and conclusion

drawings/verification (Ibid). Data reduction is the process of simplifying, selecting, focusing,

abstracting and transforming the collected data (Ibid). During this step, the researchers categorize

the data and indentify themes and patterns (Ibid). Data display is when the relevant data is being

presented together in some context, which can be in the form of a text document, charts or

matrices (Ibid). The last step, conclusion drawing/verification, is the process of finding patterns

and to draw conclusions from the collected data (Ibid).

In the current research, the aforementioned data analysis components that Miles and Huberman

(1994) present were used to analyze the data collected from the focus groups and interviews.

When the focus groups and interviews had been conducted, the employee attributes mentioned

were transcribed in a document, which became the foundation of the empirical data. The next

step was to simplify and transform the collected data through reduction of data that was

considered irrelevant for the study. Through a table, similar attributes were identified and put

together into broader concepts that were to be used in the quantitative data collection instrument.

This process is further explained in chapter 6.1.

4.8.2 Quantitative Data Analysis

In a quantitative research, statistical analysis is conducted to test hypotheses and draw statistical

inferences (Krishnaswami & Satyaprasad, 2010). It is also conducted to determine the value of

unknown characteristics of the population investigated (Ibid). Before quantitative data is

processed and analyzed it is rather meaningless and to make quantitative data meaningful it

needs to be processed (Saunders et al, 2009). By processing data into graphs, charts, and

statistics, it becomes possible to explore, present and examine relationships and trends within the

data (Saunders et al, 2009).

4.8.2.1 Data Preparation

According to Hair et al (2003), researchers must examine data when it has been collected to

ensure its validity, before it can be analyzed. Editing data involves for instance missing data,

coding, as well as entering data (Hair et al, 2003). More information about data preparation can

be found in Appendix A: Method, A14.

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In the current study, the data was edited once it had been collected, which means that

questionnaires with missing data were eliminated. The data from the collected questionnaires

was later on entered into the system SPSS, which is a program developed for the whole process

of planning, data collection, analysis, reporting and deployment (IBM, 2013).

4.8.2.2 Descriptive Statistics

According to Befring (1994), descriptive data includes principles, methods and techniques to be

able to compile, present, identify and interpret empirical data. The descriptive data is all about

organizing and identifying different patterns from collected data (Ibid).

The questionnaire sent to students included the following descriptive items: gender, number of

years you have been studying at the marketing program, if you are actively searching for a job,

and what dream employer you have. In the questionnaire to recruiters, the following descriptive

items was included: gender, position at the company, number of the years working at the current

position, number of employees working at the company, and what industry the company are in.

Further information about descriptive statistics can be seen in Appendix A: Method, A15.

4.8.2.3 Mann-Whitney U test

The most frequently asked question within business research is whether or not the means

between two groups of respondents are significantly different (Hair et al 2003; Saunders et al,

2009). To be able to see whether or not there is a difference, a null hypothesis as well as an

alternative hypothesis needs to be stated (Hair et al, 2003). Secondly, the significance level when

testing the null hypothesis needs to be selected, where the traditional significance level (α) is

0.05 (Hair et al, 2003; Pallant, 2010). Last, an appropriate statistical test needs to be selected

(Hair et al, 2003).

A Mann-Whitney U test can be used to test the difference between two independent groups on a

single, ordinal variable, and demands no specific distribution (Weiner & Craighead, 2010). A

Mann-Whitney U test can preferably be used when required assumptions for a t-test are not

achieved (Ibid). For instance, when conducting a t-test, it is required that the items are measured

at a interval or ratio level, but a Mann-Whitney U test only requires the variables to be measured

at an ordinal level (Ibid). Moreover, a Mann-Whitney U test does not require the variables to be

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normally distributed, which a t-test does (Ibid). A Mann-Whitney U test only requires the

assumptions of random samples and independent observations (Pallant, 2010). Mann-Whitney U

test belongs to the family of non-parametric tests, which concludes that no assumptions of the

underlying population distribution are drawn, also called distribution-free tests (Weiner &

Craighead, 2010; Pallant, 2010).

According to Pallant (2010), there are six variables to take into consideration when conducting a

Mann-Whitney U test: (1) The first one to look deeper into is the median, since it is through the

median that the two groups are compared and ranked, (2) The N-value shows the respondents’

total size, (3) The median is there after converted into mean ranks, however the actual

distribution of the scores does not matter, (4) The U value shows how much one of the groups

differ from the expected, (5) The z-value shows the correction for ties in the data, (6) And last,

the two-tailed sigma (Asymp. Sig.) should correspond with the α value and in this case be less

than 0.05 to show a statistically significant difference.

Since the current study aimed at comparing the difference between two groups, from a random

sample, and with independent observations, Mann-Whitney U tests were conducted.

4.9 QUALITY CRITERIA

In the current study, multiple methods were used to guarantee the quality of the outcome. Two

qualitative researches were conducted as a pre-study for the quantitative research. The purpose

was to increase the quality of the content in the questionnaires, hence increasing the reliability

and validity of the outcome of the study. Reliability refers to the consistency of a measure of a

concept, while validity has to do with whether or not a measure of a concept is really measuring

that concept (Bryman & Bell, 2011). The quality of the study will be further discussed below.

4.9.1 Quality Criteria for Qualitative Research

According to Bryman and Bell (2011), there have been discussions among qualitative

researchers regarding the relevance of reliability and validity measures for qualitative research

such as focus groups and interviews. Bryman and Bell (2011) say that reliability and validity are

more relevant when conducting quantitative research, since both concerns measurements, which

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is more connected to quantifications. However, as mentioned by Ali and Yusof (2011), quality is

an integral part of qualitative research why there is still an explicit need to highlight the

reliability and validity of qualitative research. The reliability and validity of the qualitative

research will be further discussed below.

As mentioned before, reliability refers to the consistency of a measure of a concept, and

moreover whether the results of a study are repeatable (Bryman & Bell, 2011). Unlike reliability,

validity has to do with whether or not a measure of a concept is really measuring that concept

(Bryman & Bell, 2011). There are several different types of validity that can be considered when

conducting qualitative research (Ibid). For the current study, three types of validity were chosen

to focus on: content validity, construct validity, and external validity. Content validity, or face

validity, is that the measure should reflect the concept in questions (Bryman & Bell, 2011). One

way to seek content validity is by consulting a small sample of typical respondents and/or

experts (Hair et al, 2003). Construct validity is concerned with minimizing the risks of errors, i.e.

random error and method variance (Bagozzi et al, 1991), while external validity is concerned

with whether the results can be generalized or not (Bryman & Bell, 2011). How the reliability

and the validity of the qualitative research were assessed can be seen in chapter 6.1.1.

4.9.2 Quality Criteria for Quantitative Research

As mentioned before, Bryman and Bell (2011) say that reliability and validity is particularly an

issue when conducting quantitative research. In quantitative research, particularly three factors

should be considered when analyzing whether a measure is reliable or not: stability, internal

reliability, and inter-observation consistency (Bryman & Bell, 2011). Stability refers to whether

or not a measure is stable over time, meaning that there will be little variation over time in the

results obtained, according to Bryman and Bell (2011). The same authors state that to be able to

measure the stability of quantitative research, longitudinal research needs to be appointed.

Internal reliability is whether or not the indicators that make up a scale is consistent, meaning

whether or not a respondent’s score on one indicator seem to be related to their score on the other

indicators (Bryman & Bell, 2011). Bryman and Bell (2011), state that a Cronbach Alpha

coefficient over 0.8 shows high reliability. Inter-observation consistency refers to the subjective

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decisions when more than one observer is involved in activities such as categorizing open-ended

questions in a content analysis (Bryman & Bell, 2011).

In connection to quantitative research, validity is often referred to as measurement validity

(Bryman & Bell, 2011). As with the validity of qualitative research, there are several different

types of validity that can be considered when conducting quantitative research (Ibid). Two types

of validity mentioned by Hair et al (2003) were chosen to focus on in the current study: content

validity, and construct validity. Content validity, or face validity, is as mentioned before that the

measure reflects the concept in questions (Bryman & Bell, 2011). According to Hair et al (2003)

this can be assured through pretesting. Construct validity is, also as mentioned before, concerned

with minimizing the risks of errors, i.e. random error and method variance (Bagozzi et al, 1991).

How the reliability and the validity for the quantitative research were assessed can be seen in

chapter 6.2.1.

4.10 CHAPTER SUMMARY

The methodology chapter has contained discussions around different method approaches,

designs, strategies, etc. to use and justifications for the chosen ones. Table 4.1 shows a summary

of the methods chosen in the current study.

Table 4.1: Method Summary

Method Summary

Method chapter Chosen method

Research approach Deductive

Dyadic

Qualitative and quantitative

Research design Exploratory

Descriptive – multiple cross-sectional

Data sources Primary data

Secondary data

Research Strategy Survey

Data collection methods/instruments Focus groups

Telephone interviews

Online questionnaires

Sampling Probability samples

Data analysis method Qualitative: Miles and Huberman’s (1994) three

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components

Quantitative: Descriptive statistics and Mann-

Whitney U test

Quality criteria Reliability

Validity

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. EMPIRICAL DATA

The following chapter presents the empirical data collected through qualitative

research. First, the empirical data gathered from focus groups are presented

followed by the empirical data collected through interviews.

5.1 EMPIRICAL DATA – FOCUS GROUPS

Three focus groups were conducted with six participants (both males and females) in each focus

group, which gave a total of 18 participants. Several attributes that students perceive employers

want were mentioned during the three focus groups. The stated attributes were divided into three

categories – soft skills, hard skills, and other attributes – and can be seen in table 5.1.

Table 5.1: Empirical Data – Focus Groups

Empirical Data – Focus Groups

Soft skills Hard skills Other attributes

Outgoing

Connection between applicant and

interviewer

Humorous

Patience

Relationship building skills

Be able to manage all sort of people

Communication skills

Team work

Fit into a group fast

Independent

Self-management

Loyal

Initiative

Motivated

Motivated to develop within the

company

Future visions

Ambitious

Commitment

Engagement

Analytical

Leadership skills

Strategic thinking

Creativity

Responsibility

Work experience

Internships

Language skills

Knowledge about the market

Knowledge about the industry

Knowledge about the company

Education

University

Grades

Practical skills

Reference of skills

Look healthy

Age

Gender

Well formulated CV and personal

letter

5

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Problem solver

Conflict solver

Attitude

Enthusiasm

Flexibility

Willing to move to another

city/country

Self-awareness

Clothing

Appearance

Cultural knowledge

Exchange semester

5.2 EMPIRICAL DATA - INTERVIEWS

Five interviews with recruiters were conducted. A compilation was made of the attributes

employers want employees to possess when hiring, which were mentioned during the conducted

interviews. The stated attributes were divided into three categories – soft skills, hard skills, and

other attributes – and can be seen in table 5.2.

Table 5.2: Empirical Data – Interviews

Empirical Data – Interviews

Soft skills Hard skills Other attributes

Relationship building skills

Ability to maintain relationships

Ability to create value for the

customer

Service-oriented

Social ability

Chemistry between applicant and

interviewer

Oral communication skills

Written communication skills

Ability to cooperate with other

departments within the organization

Ability to work independently

Motivated

Strong driving force

Real interest in the business

Passion for sales

Creative

Problem solver

Be able to travel a lot

Flexible in actions and behavior

Experience from similar work

Linguist

Language skills

Relevant education

Practical skills

No other attributes but hard and soft

skills were mentioned during the

interviews.

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Professional

Businesslike

5.3 CHAPTER SUMMARY

This chapter has gone through the empirical data collected through qualitative data collection

methods. First, the data collected from the focus groups with students were stated, organized into

three categories of attributes, namely soft skills, hard skill, and other attributes. This was

followed by the attributes mentioned during the conducted interviews with personnel managers,

which were categorized in the same manner as with the attributes from the focus groups. The

attributes stated in table 5.1 and 5.2 were further analyzed as can be seen in chapter 6.1.

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. RESULTS

In this chapter, the results of the study are presented. First, the qualitative results

from the focus groups and interviews are presented which worked as the basis when

developing the questionnaires. This is followed by the quantitative results from the

questionnaires.

6.1 QUALITATIVE RESEARCH

First, this subchapter presents how the validity and reliability of the qualitative part of the study

were sought. This is followed by a presentation of the processed empirical data presented in

chapter 5.

6.1.1 Qualitative Reliability and Validity

For the conducted qualitative research, the reliability was sought through the use of multiple

focus groups and interviews, to ensure that the results were consistent. The reliability was also

sought through detailed descriptions of the data collection procedure, as can be seen in Appendix

B: Results, B1-B2.

To seek content validity of the qualitative research, pretesting was relied on to a great extent.

Moreover, the development of questions for the focus groups and interviews from available

theories was considered as increasing the content validity of the qualitative research. The

qualitative research was conducted through both focus groups and interviews, which helps to

seek construct validity for the qualitative research. Also, proper referencing, interview guides

and saved original transcripts from focus groups and interviews add on the construct validity of

the research. The construct validity was also sought during the focus groups, from the fact that

the main things mentioned during the discussions were written down on a white board for all

members to review. To seek the external validity of the qualitative research, data was gathered

through focus groups and interviews until the point of saturation.

6.1.2 Qualitative Results

The attributes collected from the focus groups and interviews were transcribed and compiled into

a list with three categories of attributes: soft skills, hard skills, and other attributes. This was the

6

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empirical data from the focus groups and interviews, and can be seen in chapter 5. Through this

list, it became clear that many attributes had similar meanings and could be compounded into

attributes with broader meanings, why this was done.

As can be seen in table 6.1, 6.2 and 6.3, all attributes mentioned during the focus groups and

interviews compose the left column. These were further compounded into broader attributes

which were to be used in the questionnaires, and can be seen in the second column of the tables.

The third column from the left, in table 6.1 and 6.2, consist of the name of the author(s) claiming

that the attribute is a soft skill (table 6.1) or a hard skill (table 6.2). To enhance the respondents

understanding of the concepts that were to be used in the questionnaires, definitions of the

concepts were added for the soft skills and hard skills, as can be seen in the right column of the

tables.

Table 6.1: Soft Skills

Soft Skills

Attributes from focus

groups/interviews

Attributes used in

questionnaires

Soft skill

according to

Definition of

attributes Outgoing Interpersonal skills Verma & Bedi (2008);

Robles (2012); Culpin

& Scott (2012)

Nice, personable, sense of

humor, friendly, nurturing,

empathetic, has self-control,

patient, sociability, warmth,

social skills (Robles, 2012,

p.455), build/maintain

relationships (Soon et al, 2010)

Connection between applicant and

interviewer

Humorous

Patience

Relationship building skills

Be able to manage all sort of people

Ability to maintain relationships

Ability to create value for the customer

Service-oriented

Oral communication skills Communication skills Verma & Bedi (2008);

Lear (2011); Robles

(2012); Culpin & Scott

(2012)

Oral, speaking capability,

written, presenting, listening

(Robles, 2012, p.455)

Written communication skills

Team work Teamwork Verma & Bedi (2008);

Robles (2012); Culpin

& Scott (2012)

Cooperative, gets along with

others, agreeable, supportive,

helpful, collaborative (Robles,

2012, p.455)

Fit into a group fast

Ability to cooperate with other departments

within the organization

Independent Self-management

Shulz (2008); Andrews

& Higson (2008)

Control of one’s own behavior,

monitoring and managing one’s

own work (Manz & Sims, 1980)

Self-management

Loyal Work ethic Robles (2012) Hard working, willing to work,

loyal, initiative, self-motivated,

on time, good attendance

(Robles, 2012, p.455)

Initiative

Motivated

Motivated to develop within the company

Future visions

Ambitious

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Strong driving force

Commitment Commitment

Lear (2011)

Workplace bonds, commitment

to the employing organization,

dedication (Klein et al, 2012)

Engagement

Real interest in the business

Passion for sales

Analytical Analytical skills Culpin & Scott (2012) Ability to analyze abstract

phenomena (NE, 2013)

Leadership skills Leadership skills Verma & Bedi (2008);

Weber et al (2009)

Lead by example, sharing

information, understanding the

needs of the team, counseling,

management skills (Verma &

Bedi, 2008)

Strategic thinking Strategic thinking Ferling (2000);

Andrews & Higson

(2008)

“A way of solving strategic

problems that combines a

rational and convergent approach

with creative and divergent

thought processes” (Bonn, 2005,

p.337)

Creativity Creativity Andrews & Higson

(2008); Thammineni

(2012);

Originality, imagination, goal-

direction, problem-solving (El-

Murad & West, 2004)

Responsibility Responsibility Robles (2012) Accountable, reliable, gets the

job done, resourceful, self-

disciplined, wants to do well,

conscientious, common sense

(Robles, 2012, p.455)

Problem solver Problem solver

Verma & Bedi (2008) Selecting the most effective

alternative when dealing with

problems (D’Zurilla &

Goldfried, 1971)

Conflict solver

Attitude Positive attitude Robles (2012) Optimistic, enthusiastic,

encouraging, happy, confident

(Robles, 2012, p.455)

Enthusiasm

Flexibility Flexibility Robles (2012) Adaptability, willing to change,

lifelong learner, accepts new

things, adjusts, teachable

(Robles, 2012, p.455)

Willing to move to another city/country

Be able to travel a lot

Be flexible in actions and behavior

Self-awareness Self-awareness Soon et al (2010) Is a state in which people attend

to their own consciousness,

body, personal history, or some

other aspect of themselves

(Duval & Wicklund, 1972)

Clothing Professionalism Andrews & Higson

(2008); Robles (2012)

Businesslike, well-dressed,

appearance, poised (Robles,

2012, p.455)

Appearance

Professional

Businesslike

Cultural knowledge Cultural experience Baker (2004) Experience from other countries,

through travelling, exchange

semesters, etc (From left

column)

Exchange semester

Table 6.2: Hard Skills

Hard Skills

Attributes from focus

groups/interviews

Attributes used in

questionnaires

Hard skill

according to

Definition of

attributes Work experience Work experience Robles (2012) Experience from working,

experience from similar work Internships

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Experience from similar work (From left column)

Language skills Multilingual Shulz (2008) Ability to communicate in

various languages (Beeth, 1997) Linguist

Knowledge about the market Knowledge about the

market

Robles (2012); Salas

Velasco (2012)

Knowledge about the industry

and market, including

customers, competitors etc

(From left column)

Knowledge about the industry

Knowledge about the company

Relevant education

Education

Robles (2012) Relevant education for the job,

grades, university (From left

column)

University

Grades

Practical skills Practical skills Robles (2012); Salas

Velasco (2012)

Ability to use software

programs (Robles, 2012) Reference of skills

Table 6.3: Other Attributes

Other Attributes

Attributes from focus groups/

interviews

Attributes used in questionnaires

Look healthy Physical well-being

Age Age

Gender Gender

Well formulated CV and personal letter Well formulated CV and personal letter

6.2 QUANTITATIVE RESEARCH

This subchapter starts by describing how the validity and reliability of the quantitative part of the

study were sought. This is followed by a presentation of the data collected from the two

questionnaires. The descriptive statistics are presented next, followed by the results from the

hypotheses tests, which were conducted through Mann-Whitney U tests in SPSS. Moreover,

additional results are presented.

6.2.1 Quantitative Reliability and Validity

The reliability of the quantitative research was as mentioned before assessed through three

factors: stability, internal reliability, and inter-observation consistency. Time-constraint limited

the ability to measure the stability of the current study, why the stability of the results cannot be

sought. The internal reliability of the questionnaires sent out, were measured according to the

scale of Bryman and Bell (2011), which state that a Cronbach Alpha coefficient over 0.8 show

high reliability. Due to the fact that two questionnaires were sent out, two reliability tests were

conducted. The reliability test of the questionnaires to students, showed a Cronbach Alpha

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coefficient of 0.881 and the reliability test of the questionnaires to recruiters showed a Cronbach

Alpha coefficient of 0.842. This indicates that the study has high reliability. The inter-

observation consistency was not regarded as a problem in the current study. The authors have

been working together several times, conducting qualitative and quantitative researches and

analyses. Moreover, all authors participated and contributed during the process of analysis to

minimize the risk of inconsistency.

As with the content validity of the qualitative research, the quantitative content validity was

sought through pretesting the questionnaires before sending them out to respondents. This is

considered a way to measure content validity according to Hair et al (2003). The questionnaires

were sent to academics for judgment before sending them to a small representative sample of the

population prior the final distribution to all respondents. The construct validity of the quantitative

research was sought by conducting a correlation analysis between the different attributes and

between the different indexes. According to Katz (2006), a correlation greater than 0.9 will cause

problem in the analysis, while those above 0.8 are in the gray area. No correlation in either the

analysis of the questionnaire to students or the questionnaire to recruiters exceeded 0.8. Hence,

the construct validity of the quantitative analysis was sought. See Appendix B: Results, B3 for

the results from the correlation analysis of indexes, and Appendix B: Results, B4 for the results

from the correlation analysis of single attributes.

6.2.2 Descriptive Statistics

Students:

With 229 questionnaires sent out to students, a total of 83 completed questionnaires were

received, which gave a total response rate of 36.2%. An outlier test was conducted and outliers

were detected. However, when they were removed the Cronbach Alpha coefficient did not

increased as expected and hence, the outliers were not removed. None of the questionnaires were

excluded due to the fact of not fully completed. The generated data resulted in 48 female

respondents (57.8%) and 34 male respondents (41.0%), while one person did not specify gender

(1.2%). See table 6.4.

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The generated data regarding how many years the students had been studying at the marketing

program showed the following result: 21 1st year students (25.3%), 18 2

nd year students (21.7%)

and 44 3rd

year students (53.0%). Furthermore, 36 students answered that they were actively

searching for a job (43.4%), and 47 students (56.6%) did not look for a job at the moment. See

table 6.4. As a future dream employer the most frequent answers from the students were IKEA

followed by Apple and Nike.

Table 6.4: Descriptive Statistics Students

Students

Total Response Rate Gender Number of Years Studying: Actively searching for a job?

Male Female 1 2 3 Yes No

36.2% 41.0% 57.8% 25.3% 21.7% 52.0% 43.4% 56.6%

The means and standard deviations retrieved from the students are presented in three different

ways. First, the mean and standard deviation of all attributes together. Secondly, the means and

standard deviations for the different indexes (soft skills/hard skills/other attributes), and last, the

means and standard deviations for all 26 attributes separated. The tables are shown in Appendix

B: Results, B5-B7.

Recruiters:

With 687 questionnaires sent out to recruiters, a total of 129 completed questionnaires were

received which gave a response rate of 18.8%. Three of the questionnaires were excluded due to

the fact of not fully completed. As with the students, an outlier test was conducted. The test

revealed some outliers, but also here the removal of the outliers did not generate a higher

Cronbach Alpha coefficient. Hence, no outliers were removed. The generated data resulted in 53

female respondents (42.1%), 72 male respondents (57.1%), and one person did not specify

gender (0.8%). See table 6.5.

The result from the question regarding how many employees the company had where the

respondents were working, showed that most of the recruiters worked for companies with 200-

499 employees (36.5 %). This was followed by more than 500 employees (27.8%) and 100-199

employees (24.6%). See table 6.5.

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Generated data concerning how many years the specific recruiter had been working at the current

position, showed that most of them had been working for 6-10 years at the current position

(27%). This was closely followed by recruiters who had been working at the current position for

3-5 years (26.2%). 23.8% had been working at the current position for 1-2 years. See table 6.5.

The most common positions at the company of the respondents were human resource manager,

CEO and marketing manager.

Table 6.5: Descriptive Statistics Recruiters

Recruiters

Total

Respon

se Rate

Gender No. of Employees at Your Company No. of Years at Current Position

Male Femal

e

0-49 50-

99

100-

199

200-

499

500+ 1-2 3-5 6-10 11-

15

16-

20

21+

18.8% 57.1% 42.1% 2.4

%

6.3

%

24.6

%

36.5

%

27.8

%

23.8

%

26.2

%

27.0

%

7.9

%

4.0

%

4.0

%

The means and standard deviations retrieved from the recruiters are presented in three different

ways. First, the mean and standard deviation of all attributes together. Secondly, the means and

standard deviations for the different indexes (soft skills/hard skills/other attributes), and last, the

means and standard deviations for all 26 attributes separated. The tables are shown in Appendix

B: Results, B5-B7.

6.2.3 Hypotheses

There are different methods to use when comparing two means between different groups, e.g. a t-

test (Pallant, 2010), but the Mann-Whitney U test was considered the most appropriate test to use

to test the four stated hypotheses of the current study. To know which test to use the collected

data have to meet specific assumptions. The data in the current study violated the assumptions

required to conduct a t-test. According to Sawilowsky and Blair (1992) and Stonehouse and

Forrester (1998), a non-parametric test is more powerful to use than a t-test when these

assumptions are violated. Hence, a Mann-Whitney U test, which is a non-parametric test, was

considered the most appropriate test in relation to these assumptions. The first assumption

required for a Mann-Whitney U test is that the research has to use random samples (Pallant,

2010). This assumption was achieved since all units of the populations had equal chances of

participating in the study. The second assumption for a Mann-Whitney U test is that the research

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has independent observations (Pallant, 2010). The current study had independent observations

since each respondent could only be counted once, and the same respondent did not appear in

more than one group. Moreover, the results from a conducted Shapiro-Wilks test, which is

sensitive to normality, showed that the data had non-normal distribution, hence a α level under

.05 (Pett, 1997). The result for the Shapiro-Wilks test can be seen in Appendix B: Results, B8.

Furthermore, a test for both skewness, which indicates the symmetry of the distribution, as well

as kurtosis, which provides information of the “peakedness” of the distribution was conducted

(Pallent 2010). According to Hair et al (2007), normally distributed data has skewness values

within a threshold of -1 to +1 and kurtosis values within -3 to +3. The test showed that some

attributes were skewed and some attributes did not pass the level for kurtosis. The results for this

test can be seen in Appendix B: Results, B9. Hence, a Mann-Whitney U test was considered

appropriate since the data does not have to be normally distributed in order to conduct this test

unlike a t-test (Weiner & Craighead, 2010). Furthermore, the data in the study was measured on

ordinal scales, which fits well when using non-parametric techniques (Pallant, 2010).

The alpha level (α) used in the current study was 0.05 (cf. Hair et al, 2003; Saunders et al, 2009),

meaning that the z-value should be less than -1.96 or greater than +1.96 in order to reject the null

hypotheses. The results from the Mann-Whitney U test for hypothesis 1 can be seen in Appendix

B: Results, B10, and the results for hypotheses 2, 3 and 4 can be seen in Appendix B: Results,

B11. Moreover, H1 was rejected in relation to hypothesis 1, 2, 3 and 4, as can be seen in table

6.6. The results are also further presented below.

Table 6.6: Hypotheses

Hypotheses

H1 was rejected H0 was rejected

Hypothesis 1 X

Hypothesis 2 X

Hypothesis 3 X

Hypothesis 4 X

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6.2.3.1 Hypothesis 1

H1: There is a mismatch between the employee attributes that students perceive employers want,

and the employers’ wants regarding employee attributes.

The result of this test show as follow:

All attributes: There was no statistically significant difference in the scores from students

(Md = 5.04, n = 83) and recruiters (Md = 5.15, n = 126), U = 4917.5, z = -.728, p = .466.

These results suggest that there is no mismatch between employee attributes that students

perceive employers want, and the employers’ wants regarding employee attributes.

Hence, H1 was rejected in relation to hypothesis 1.

6.2.3.2 Hypothesis 2

H2: There is a mismatch between how important recruiters consider soft skills to be, and how

important students perceive soft skills to be.

The result of this test show as follows:

Soft skills: There was no statistically significant difference in the scores from students (Md =

5.53, n = 83) and recruiters (Md = 5.71, n = 126), U = 4509.5, z = -1.683, p = .092. These

results suggest that there is a mismatch between how important students perceive soft skills

to be, and how important recruiters consider soft skills to be.

Hence, H1 was rejected in relation to hypothesis 2.

6.2.3.3 Hypothesis 3

H3: There is a mismatch between how important recruiters consider hard skills to be, and how

important students perceive hard skills to be.

The result of this index is as follows:

Hard skills: There was no statistically significant difference in the scores from students (Md

= 5.00, n = 83) and recruiters (Md = 4.80, n = 126), U = 4571.5, z = -1.543, p = .123. These

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results suggest that there is no mismatch between how important students perceive hard

skills to be, and how important recruiters consider hard skills to be.

Hence, H1 was rejected in relation to hypothesis 3.

6.2.3.4 Hypothesis 4

H4: There is a mismatch between how important recruiters consider other attributes to be, and

how important students perceive other attributes to be.

The results of this index is as follows:

Other attributes: There was no statistically significant difference in the scores from students

(Md = 3.75, n = 83) and recruiters (Md = 3.50, n = 126), U = 4703, z = -1.235, p = .217.

These results suggest that there is no mismatch between how important student perceive

other attributes to be, and how important recruiters consider other attributes to be.

Hence, H1 was rejected in relation to hypothesis 4.

6.2.4 Additional Results

One Mann-Whitney U test was also conducted where the medians of each single attribute was

compared. The results from this Mann-Whitney U test show that discrepancies exist between

students’ perceptions of important employee attributes to possess, and the employee attributes

recruiters consider important. The results are presented below, and can also be seen in Appendix

B: Results, B12.

At α = 0.05, there is a mismatch between the perceived/considered importance of interpersonal

skills, teamwork, self-management, commitment, responsibility, self-awareness, knowledge

about the market, physical well-being, gender, and well formulated CV and personal letter. The

results of these attributes are as follows:

Interpersonal skills: There was a statistically significant in the scores from students (Md =

6.00, n = 83) and recruiters (Md = 6.00, n = 126), U = 4371.5, z = -2.141, p = .032. These

results suggest that there is a mismatch between how important students perceive

interpersonal skills to be, and how important recruiters consider interpersonal skills to be.

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Teamwork: There was a statistically significant difference in the scores from students (Md =

6.00, n = 83) and recruiters (Md = 6.00, n = 126), U = 4404.5, z = -2.071, p = .038. These

results suggest that there is a mismatch between how important students perceive teamwork

to be, and how important recruiters consider teamwork to be.

Self-management: There was a statistically significant difference in the scores from students

(Md = 5.00, n = 83) and recruiters (Md = 6.00, n = 126), U = 3750, z = -3.656, p = .000.

These results suggest that there is a mismatch between how important students perceive self-

management to be, and how important recruiters consider self-management to be.

Commitment: There was a statistically significant difference in the scores from students (Md

= 5.00, n = 83) and recruiters (Md = 6.00, n = 126), U = 3914.5, z = -3.206, p = .001. These

results suggest that there is a mismatch between how important students perceive

commitment to be, and how important recruiters consider commitment to be.

Responsibility: There was a statistically significant difference in the scores from students

(Md = 6.00, n = 83) and recruiters (Md = 6.00, n = 126), U = 4273, z = -2.401, p = .016.

These results suggest that there is a mismatch between how important students perceive

responsibility to be, and how important recruiters consider responsibility to be.

Self-awareness: There was a statistically significant difference in the scores from students

(Md = 5.00, n = 83) and recruiters (Md = 5.00, n = 126), U = 4246, z = -2.731, p = .018.

These results suggest that there is a mismatch between how important students perceive self-

awareness to be, and how important recruiters consider self-awareness to be.

Knowledge about the market: There was a statistically significant difference in the scores

from students (Md = 5.00, n = 83) and recruiters (Md = 5.00, n = 126), U = 4051, z = -2.840,

p = .005. These results suggest that there is a mismatch between how important students

perceive knowledge about the market to be, and how important recruiters consider

knowledge about the market to be.

Physical well-being: There was a statistically significant difference in the scores from

students (Md = 5.00, n = 83) and recruiters (Md = 5.00, n = 126), U = 3701, z = -3.689, p =

.000. These results suggest that there is a mismatch between how important students

perceive physical well-being to be, and how important recruiters consider physical well-

being to be.

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Gender: There was a statistically significant difference in the scores from students (Md =

2.00, n = 83) and recruiters (Md = 1.00, n = 126), U = 4188.5, z = -2.752, p = .006. These

results suggest that there is a mismatch between how important students perceive gender to

be, and how important recruiters consider gender to be.

Well formulated CV and personal letter: There was a statistically significant difference in

the scores from students (Md = 5.00, n = 83) and recruiters (Md = 4.70, n = 126), U = 4349,

z = -2.111, p = .035. These results suggest that there is a mismatch between how important

students perceive well formulated CV and personal letter to be, and how important recruiters

consider well formulated CV and personal letter to be.

6.3 CHAPTER SUMMARY

Chapter 6 analyzed not only the results from the qualitative studies, but first and foremost the

quantitative results, since that was the main data collection of the research.

The reliability of the qualitative part of the study was sought through conduction of multiple

focus groups and interviews, as well as detailed descriptions on the data collection procedures.

Moreover, the validity of the qualitative research was also sought. When data from the

qualitative research was analyzed, it became clear that the attributes had similar meaning and

could be compounded into broader attributes. These were further developed into the attributes

stated in the quantitative study, i.e. the questionnaires.

The reliability was also sought for the quantitative part of the study, through stability (which

showed a minor problem with time-constraint), internal reliability (the Cronbach Alpha

coefficient showed high reliability) and inter-observation consistency (all authors participated

when analyzing to minimize the risk of inconsistency). Validity was also sought for the

quantitative research. For instance, the construct validity was tested through a correlation

analysis. The results from the quantitative research resulted in rejection of H1 in regard to

hypothesis 1, 2 3 and 4. However, the results indicate that there are still discrepancies between

the perceived/considered importance of 10 of the 26 measured attributes.

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. DISCUSSIONS, CONCLUSION, IMPLICATIONS,

LIMITATIONS & SUGGESTIONS FOR FUTURE

RESEARCH

This chapter begins with a discussion around the findings, which consequently answers the

purpose of the study. The chapter continues with a discussion about the theoretical and

managerial implications of the study, followed by the limitations of the study and suggestions for

future research.

7.1. DISCUSSIONS

From the statistics mentioned in the previous chapter, it could be stated that there might be

discrepancies between the employee attributes that employers want, and students’ perceptions of

sought employee attributes. When measuring the attributes indexed into categories, it could be

stated that there are no statistically significant discrepancies concerning soft skills, hard skills, or

other attributes. However, results indicate that there is a discrepancy concerning soft skills, just

not statistically significant. When measuring all 26 attributes by themselves, the discrepancies

concern the following 10 attributes: interpersonal skills, teamwork, self-management,

commitment, responsibility, self-awareness, knowledge about the market, physical well-being,

gender, and well formulated CV and personal letter. The findings are further discussed below.

7.1.1 Discussion of Research Question and Hypotheses

The results of the study show that H1 in regard to all hypotheses was rejected. Hence, there is no

proof that there are statistically significant discrepancies between the perceived/considered

importance of employee attributes. Moreover, there is no proof that there are statistically

significant discrepancies between the perceived/considered importance of soft skills, hard skills,

or other attributes. However, the results show that even though there is no statistically significant

discrepancy between perceived/considered importance of soft skills, the figures suggest that a

discrepancy can exist, but with a certainty level of 90%. Soft skills: Results show that recruiters

considered soft skills to be more important than students perceived soft skills to be. This is in

line with many previous researches, which state that soft skills are becoming more and more

7

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important for an employee to possess. For instance, Nealy (2005) argues that business leaders are

looking more at the soft skills than the hard skills, since it positively affect the productive

performance. Also Branine (2008) highlights the importance of soft skills, and says that

recruiters look beyond the hard skills. Cook and Finch (1994) had the same conclusion – soft

skills are emphasized as more important, rather than hard skills.

As the results show, H1 was rejected in regard to all hypotheses. But to answer the research

question of the study, there is a discrepancy between some of the attributes students perceive as

wanted and the attributes personnel managers actually want. These finding are further discussed

below.

7.1.2 Discussion of Additional Results

Two of the attributes, where discrepancies between perceived/considered importance were found

and where students perceived them to be more important than recruiters considered them to be,

were soft skills. These two attributes were: interpersonal skills, and teamwork. Interpersonal

skills: Interpersonal skill is a soft skill according to Verma and Bedi (2008), Robles (2012) and

Culpin and Scott (2012), and students perceived interpersonal skills to be more important than

recruiters considered interpersonal skills to be. However, Kelley and Gaedeke (1990) say that

one of the most wanted employee attributes when recruiters are hiring people for marketing

positions are interpersonal skills. Teamwork: Also teamwork is a soft skill according to Verma

and Bedi (2008), Robles (2012) and Culpin and Scott (2012). Branine (2008) highlighted that

recruiters look for employees who are able to work in teams, but as the results show, students

perceived teamwork to be more important than recruiters considered it to be. Also Robles (2012)

says that teamwork is an important employee attribute for recruiters, as well as Sharma (2009)

who says that teamwork is the second most important soft skill to possess. Other studies have

also shown that students perceive teamwork as essential to possess (Raymond & McNabb, 1993;

DuPre & Williams, 2011; Salas Velasco, 2012).

Four of the attributes, where discrepancies between the perceived/considered importance were

found, were soft skills and where recruiters considered the attributes to be more important than

students. These attributes were: self-management, commitment, responsibility, and self-

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awareness. Self-management: According to Shulz (2008) and Andrews and Higson (2008), self-

management is a soft skill. The results from the current study show that recruiters considered

self-management to be more important to possess as an employee, than students perceived it to

be. This is supported by Branine (2008) who state that recruiters are looking for employees who

are able to work independently. Also Salas Velasco (2012) states that recruiters appreciate skills

such as self-management. Commitment: Also commitment is a soft skill according to Lear

(2011). As with self-management, recruiters considered commitment to be more important than

students perceived it to be. Engagement is something that Behrenz (2001) states that recruiters

look for during the process of recruitment. Moreover, Behrenz (2001) states that personal

engagement within a company is crucial for the success of the company. Due to this fact, it is

understandable that recruiters considered commitment to be of greater importance.

Responsibility: Another soft skill is responsibility (Robles, 2012), and also here recruiters

considered the attribute to be more important than students perceived it to be. As with self-

management, Branine (2008) states that responsibility is something that recruiters are looking for

when hiring new employees. According to Robles (2012), accountability is a one of the

definitions of responsibility. Moreover, Junek et al (2009) say that students are often perceived

as accountable, why it can be considered positive to have been a student when looking for a job

since recruiters considered responsibility important. Self-awareness: Another attribute

considered as more important by recruiters is self-awareness, which is a soft skill according to

Soon et al (2010). Self-awareness was mentioned during the focus groups as important to

possess, and this is in line with previous research. For instance, Goleman (1998) revealed data

from a study which showed that factors such as self-awareness does not only affect the

successfulness of the employees, but does also lead to more successful companies. Hence, it is

understandable that recruiters considered self-awareness to be of greater importance.

It was found to be a discrepancy between the perceived/considered importance of one hard skill,

knowledge about the market. Knowledge about the market: This is a hard skill according to

Robles (2012) and Salas Velasco (2012), and in this case, students perceived knowledge about

the market to be more important than recruiters considered it to be. However, Behrenz (2001) for

instance, highlights the importance of possessing professional knowledge.

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The results also showed that there is a discrepancy between the perceived/considered importance

of one attribute categorized as other attributes, where recruiters considered the attribute to be

more important than students perceived it to be. Physical well-being: Recruiters considered

physical well-being to be more important than students perceived it to be. This is in line with

what Hurley-Hanson and Giannantonio (2006) say: image norms, such as physical attractiveness

including weight, height, clothing, facial beauty and handicap status, play a role when recruiters

consider candidates for a job.

There were also discrepancies between the perceived/considered importance of two other

attributes, categorized as other attributes, where students perceived the attributes to be more

important than recruiters considered them to be. These two attributes were gender, and well

formulated CV and personal letter. Gender: Concerning gender, the results from the current

study indicate that students perceived gender to be more important than recruiters. Since this is a

rather sensitive question, it may be hard to get an accurate result. However, if the statistics

concerning this question is accurate, gender does not have as high impact when looking for a job

as students perceive it has. Well formulated CV and personal letter: Also concerning well

formulated CV and personal letter, students perceived it to be more important than recruiters

considered it to be. According to Osoian et al (2011), students should consider their CV or

resume as one of the most important tool for their future career. But as the results show,

recruiters did not consider a well-formulated CV and personal letter as important as students

perceived it to be.

7.2 CONCLUSION

As the results show from the analysis of the attributes indexed into categories, recruiters seem to

consider soft skills to be more important than students perceive soft skills to be. As explained

earlier in the current study, those who best fit the environment will succeed in the future if there

is a change within a system (Powell & Wakely, 2003). Students must understand the importance

of possessing soft skills in order to get hired. Those students who best fit the demands from

recruiters, will have an increased chance to succeed. And moreover, recruiters must provide clear

information of how important it is to possess these skills, to be able to match the right employees

to the organization.

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The results from the analysis of each single attribute show that students seem to perceive

interpersonal skills, teamwork, knowledge about the market, gender, and well formulated CV

and personal letter to be more important than recruiters consider them to be. Moreover, recruiters

seem to consider self-management, commitment, responsibility, self-awareness, and physical

well-being to be more important than students perceive them to be.

Hence, students do not have to worry so much about possessing interpersonal skills, ability to

teamwork, knowledge about the market, to have the “right” gender, or to have a well formulated

CV and personal letter to get hired. However, students who want to get hired must understand

that self-management, commitment, responsibility, self-awareness, and physical well-being are

more important than they perceive them to be today. Since students do not have accurate

perceptions of how important these attributes are, recruiters must provide clearer information

about what they look for when hiring new employees.

7.3 IMPLICATIONS

In this subchapter, the implications of the study are discussed. First, the theoretical contributions

that the current study provides are discussed. This is followed by a discussion around the

managerial implications.

7.3.1 Theoretical Implications

Since the results from similar studies vary, an updated research was considered necessary. The

current study provides updated results concerning the importance of employee attributes.

Moreover, previous research had been conducted in different countries, and on different target

groups. The current study are limited to Sweden as well as focused on one specific target group,

and a possible job market for those students, and can hence be seen as a theoretical contribution.

Previous studies had been conducted on slightly, or majorly differing subjects than the subject in

the current study. Since no previous study is exactly like the current one, the study contributes to

available literature. Moreover, most of the available researches focused on one or the other of the

two viewpoints focused on in the current research. The current study contributes to available

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literature by providing a dyadic approach, with both an exploratory research design as well as a

descriptive research design

Moreover, the current research discusses the importance of matching in the context of

evolutionary perspective, i.e. “survival of the fittest”. By applying these theories to the study,

hence in a new context, a theoretical contribution is provided to available literature.

7.3.2 Managerial Implications

In addition to already stated theoretical contributions, the current study has provided new

insights in correspondence with available studies within the field. The results of the study can

provide information to students concerning what recruiters are looking for when hiring new

employees. By focusing on the attributes that recruiter consider important, chances for getting a

job may increase. Students who possess those attributes can better highlight the possession of the

attributes, while those who did not think of the attributes as important, but who possess them,

can take them into consideration. Those who do not possess the attributes can try to develop

them.

The results of the current study can also be of importance to recruiters. Since there are some

discrepancies between students’ perceptions of sought employee attributes and the employee

attributes that recruiters actually seek, this may indicate that recruiters have to be more clear

about what they are actually looking for. If recruiters provide accurate information about what

they are looking for, they will most likely increase their chances of getting what they look for.

Universities may also find the results useful. By focusing the educations towards the attributes

highlighted by recruiters as important, students’ chances of getting a job after graduation may

increase. Hence, by focusing on what is necessary for students to get a job after graduation, these

educations may gain popularity.

7.4 LIMITATIONS

The current study had some limitations, which could have influenced the results of the study.

First of all, the time frame for the study was limited. With a longer time frame, more time could

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have been spent on collecting data, as well as more time on analyzing the collected data. This

could have provided the study with higher reliability since there was no time to ensure stable

results. Moreover, a longer time frame would also mean that the respondents would have had

more time to answer the questionnaires, which could have resulted in a higher response rate.

The time constrains also affected the theoretical insight in the subject of the study. With a longer

time frame, a larger amount of time could have been spent on going through available literature

within the field. Increased understanding of the different theories used in the current research

could have increased the quality of the research, and other theories appropriate for the current

study could have been found which may have affected the results of the research. With a better

understanding of the theories used, a more thorough analysis could have been conducted, which

could have strengthened the result of the study.

Another limitation that constrained the study was the limited resources. If more resources would

have been available, the response rates could have increased for both questionnaires. This, by

sending the questionnaires via mail, calling several phone calls to the respondents as well as

providing a more tempting incentive to the respondents.

The support from organizations and students can also be seen as a limitation of the study. Some

companies and students did not want to participate in the current study. If all the students and

recruiters that the questionnaires were sent to would have participated, the response rate would

have increased and made the study more statistically reliable. Moreover, the access to

information has in some matters been a limitation in the current study. Some articles have not

been accessible, due to regulations or need for memberships and payments.

7.5 SUGGESTIONS FOR FUTURE RESEARCH

Since the stability of the results could not be ensured in the current study due to time constraints,

a suggestion for future research is to conduct a similar study in the future. This would be

appropriate since it would ensure the stability of the results, or to see how the results change over

time. Another suggestion for future research is to increase the sample size, hence increasing the

number of respondents. This could help to get a more accurate and reliable result.

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CHAPTER SEVEN – DISCUSSIONS, CONCLUSION, IMPLICATIONS, LIMITATIONS

AND SUGGESTIONS FOR FUTURE RESEARCH

______________________________________________________________________________

55

For future research it could also be suggested to conduct a similar research but in a new context.

The new context could be to change the geographical area of the study, hence choosing to

conduct the study on marketing student in another country and recruiters in the manufacturing

industry in another country. Another new context could be to conduct the study on other students

than marketing students, as well on recruiters in an industry appropriate to those students.

Additional research could also be suggested for a similar study but on more than one university,

i.e. use a sample from multiple universities.

Since the current study focused on attributes sought when hiring employees for the marketing

department in the manufacturing, it could be of interest to just change the industry, to see which

attributes are sought when hiring new employees to the marketing department in other industries.

The current study focused on 26 specific attributes developed during the study. For future

research it could be suggested to investigate the importance of other attributes than the ones used

in the current study. Moreover, it would be interesting to investigate how universities concentrate

on teaching students the skills that are considered important to recruiters.

Finally, as the current study had a quantitative approach, it can be of interest for future studies to

conduct a qualitative study to understand the underlying reasons behind why students and

recruiters consider some skills more important than other skills.

7.6 CHAPTER SUMMERY

In this chapter, there have been discussion of the results. The chapter also includes a conclusion

that answers the research question and purpose of the study. This was followed by implications

of the study, where it was suggested that the research for instance contributed theoretically by

testing theories in a new context, and managerially the study can be useful for students, recruiters

and universities. The chapters also discusses possible limitations for the study such as time and

resource limitations. Finally, the chapter ends with suggestions for future research, such as

conducting the study on other students than marketing students.

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56

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APPENDIX A: METHOD

A1. Inductive vs. Deductive Research

An inductive approach is mainly the outcome of research, where conclusions are drawn from

collected data and then developed to new theoretical frameworks (Bryman & Bell, 2011). The

inductive research should be seen as the “the systematic process of establishing a general

proposition on the basis of observation or particular facts” (Ghauri & Grønhaug, 2005, p.16).

Deductive theory is the most common view and represents the relationship between theory and

research, and when creating hypotheses or research questions only accessible theories within the

domain are to be used (Bryman & Bell, 2011). According to Saunders et al (2009), deductive

research can be described as testing the development of a theory. It can also be seen as “the

logical process of deriving a conclusion from a known premise or something known as true”

(Ghauri & Grønhaug, 2005, p.16). Both research approaches demand imagination and creativity

from the researchers, as well as that the research goes beyond statistics to data collection (Ibid).

Common characteristics are that the inductive research often is conducted on a small sample,

compared to the deductive research that often is carried out on larger samples (Saunders et al,

2009). Saunders et al (2009) also state that the deductive research often emphasizes the

collection of quantitative data and the inductive research often use qualitative data.

A2. Quantitative vs. Qualitative Research

Research can be divided into a quantitative and/or qualitative research approach (Bryman & Bell,

2011). According to Bryman and Bell (2011), the most obvious distinction is the fact that

quantitative researchers use measurements, while qualitative researchers do not. In a quantitative

research, quantifications are emphasized in the collection and analysis of data (Bryman & Bell,

2011). Similarly, Ghauri and Grønhaug (2005), highlight that the results of a quantitative

research should be presented through statistics. Moreover, Bryman and Bell (2011) say that

words are emphasized in the collection and analysis of data in a qualitative research, and Ghauri

and Grønhaug (2005) state that the results from a qualitative research should not be statistical

and no quantifications should be made.

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Strauss and Corbin (2008) mention that a qualitative research is often used when doing a study in

social and behavior sciences and when researchers want to investigate human behavior. A

qualitative research is also good to use when investigating people’s attitudes towards a brand,

trend or behavior (Ghauri & Grønhaug, 2005). Strauss and Corbin (2008) identify a number of

characteristics that are often used in qualitative researches. One of them is that interviews and

observations are common data collection instruments, while another characteristic is that the

report is written or verbal (Strauss & Corbin, 2008). Common data collection methods for

quantitative research are questionnaires and structured interviews (Ghauri & Grønhaug, 2005).

A3. Research Designs

Exploratory research design: Refers to a design that is preferably used when researchers are at

an early stage of a research project (Bryman & Bell, 2011). The design aims at gaining

familiarity within a phenomenon or to create greater knowledge in a specific field with already

existing data (Hair et al 2003; Dhawan, 2010). This research design is time consuming and

therefore requires a lot of resources (Zikmund et al, 2010).

Descriptive research design: Aims to investigate and portray how a specific individual, group or

situation act or behave (Hair et al, 2003; Dhawan, 2010). When using a descriptive research

design a definition of what is investigated as well as how it is measured is needed, hence it

should answer questions of who, what, when, where and how (Dhawan, 2010; Bryman & Bell,

2011). Descriptive research design can preferably be used when creating generalization patterns

and association patterns within a specific field (Zikmund et al, 2010; Bryman & Bell, 2011).

Causal research design: Aims at testing one or more hypotheses of a causal relationship between

variables (Dhawan, 2010). Causal research design is preferably used when a researcher wants to

gain more knowledge on what impact a change in one specific variable has on another (Hair et

al, 2003; Zikmund et al, 2010). This type of research design requires the researchers to have both

control and knowledge of the different variables, hence it is both complicated to conduct as well

as time consuming (Ibid).

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Longitudinal design: Is a research design that is used to map out changes in a specific business

over a long period of time and on at least two different occasions, but usually more (Hair et al,

2003; Bryman & Bell, 2011). Longitudinal design involves drawings with “phenomena at

vertical and horizontal levels” (Bryman & Bell, 2011, p.57), where the goal is to analyze

interconnections through time (Ibid). Longitudinal design is rarely used within business and

management research, due to time and resource constraints connected with this approach (Ibid).

Cross-sectional design: Is also known as social survey design, and is the “collection of data on

more than one case (usually quite lot more than one) and at a single point in time in order to

collect a body of quantitative or quantifiable data in connection with two or more variables

(usually many more than two), which are then examined to detect patterns of associations”

(Bryman & Bell, 2011, p.53). Cross-sectional design can be further divided into single cross-

sectional design and multiple cross-sectional design. Single cross-sectional design means that

data is collected from only one section, while multiple cross-sectional design means that data is

collected from more than one section (Bryman & Bell, 2011).

A4. Data Sources

There are several advantages and disadvantages with primary and secondary data sources

(Ghauri & Grønhaug, 2005). According to Ghauri and Grønhaug (2005), primary data is both

expensive and time consuming in the sense of collecting data, while secondary data is less costly

and less time consuming to collect. For this reason, secondary data can preferably be used to

lower the cost and be more time efficient (Ibid). However, according to Bryman and Bell (2011),

there might be a lack of familiarity when using secondary data and the data collected might be

too complex to understand. Moreover, the researchers do not have any control over the quality of

already collected data as well as the use of different key variables that the former researchers

used, which might be problematic (Bryman & Bell, 2011). When using secondary data, the

opportunity for cross-cultural analysis occurs (Ibid). A broader perspective is given to the

research if the authors use data not only collected by themselves or even in the same country as

where the research is being conducted (Ibid). There might thus be cultural differences between

the countries, which should be considered (Ibid). Collecting primary data is as mentioned before

time consuming and by using secondary data, more time can be spent on analyzing the data

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collected (Ghauri & Grønhaug, 2005). Analyzing data collected from other researches also gives

the opportunity to re-analyze the findings that might preferably need new insights (Ibid).

A5. Research Strategies

Experiment is a methodical process where one or more variables are altered to establish different

effects (Yin, 2009). Survey can be described as when conducting a study on a specific sample of

individuals and make statistical inferences of the result (Ibid). Archival analysis is an

observational method where the researchers collect and analyze secondary data (Ibid). A history

research strategy focuses on collection and analysis of historical documents (Ibid). The last

strategy, case study, can be described as when researchers analyze an individual unit (e.g. a

person, group, or event), with a focus on developmental factors in connection to the context or

appropriate theory (Ibid).

The table below was used when deciding which strategy that was best suited for the current

study. In the table, five different research strategies are demonstrated, including the criteria from

which they were examined. The three different criteria used in the model are: (1) how the

research questions are formulated, (2) the control over behavioral event, and (3) the focus on

contemporary events.

Research Strategies (Yin, 2009, p.8)

Method Conditions

Form of research question: Requires control over

behavioral event?

Focus on

contemporary events?

Experiment How? Why? Yes No

Survey Who? What? Where? How many? How

much?

No Yes

Archival Analysis Who? What? Where? How many? How

much?

No Yes/No

History How? Why? No No

Case Study How? Why? No Yes

A6. Focus Groups

When conducting focus groups there is one person leading the focus group, often called a

moderator, with the purpose of managing the discussion without taking too much space (Bryman

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APPENDIX A: METHOD

______________________________________________________________________________

67

& Bell, 2003). The purpose of conducting a focus group is to create understanding of group

members' perceptions, attitudes or opinions about a specific topic (Eliasson, 2010). It also helps

the researchers to gain deeper understanding and access information of a specific subject, which

becomes clearer gradually (Ibid).

The best way to collect information from a focus group is to first record the discussion and then

write down the information (Bryman & Bell, 2003). Regarding the size of the group, Morgan

(1988) writes that six to ten participants is a good number of participants. According to

Blackburn and Stokes (2000), the group should not contain more than 8 people since this could

make the group harder to maneuver. Using too large groups can make it more difficult for some

people to express their true opinions in subjects that the respondents have limited knowledge or

experience in (Bryman & Bell, 2003).

A7. Interviews

When conducting a semi-structured interview, the interviewer has a list of pre-determined topics

that are going to be covered through the interview (Bryman & Bell, 2003). The questions do not

have to follow a specific schedule and new questions can be asked during the interview

depending if new topics arise (Hair et al, 2003; Bryman & Bell, 2011). Hence, semi-structured

interviews were considered appropriate for the current study.

One way of conducting interviews is through telephone interviews, which brings several benefits

(Eriksson & Wiedersheim-Paul, 2011). Telephone interviews are cheaper, less time consuming,

have a high response rate and are easier to manage than face-to-face interviews (Ibid).

A8. Questionnaires

When conducting a questionnaire it is essential to design it in an easy way and to avoid

complicated and complex questions (Hair et al, 2003; Bryman & Bell, 2011). It is essential to

keep the questionnaires simple, hence not too long and with too many questions since the

respondents might get tired and stop answering the questionnaire (Ibid).

Questionnaire questions can be designed in two ways: open questions and/or closed questions

(Eliasson, 2010). When using closed questions, the respondent has different pre-determined

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APPENDIX A: METHOD

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68

answers to choose from, which makes the results easier to analyze and can more easily be turned

into statistics than open questions (Ibid).

One way to collect data through a questionnaire is to do it over the Internet (Evans & Marthur,

2005). Online questionnaires make it easy to reach out to a large amount of people (Ibid).

Advantages by doing the questionnaires over the Internet include that the respondents can

answer the questionnaire when they have time for it, and the cost of designing as well as

reaching out to respondents is low (Ibid).

A9. Operationalization – Focus Group

Operationalization – Focus Group

Concept Concept definition Operational

definition

Question

Perception The process by which stimuli are

selected, organized and

interpreted (Solomon et al, 2010)

Find which attributes

students perceive

recruiters want in new

employees.

Which employee attributes do you

think recruiters consider

important when hiring employees

for the marketing department at a

manufacturing company?

Employee

attributes

Skills: the certain personal

abilities that an individual

possesses (Raybould & Sheedy,

2005)

Soft skills: the personal and social

skill that a person possesses

(Hutchinson & Brefka, 1997)

Hard skills: job objectives, work

experience and academic

background (Hutchinson &

Brefka, 1997)

A10. Operationalization – Interviews

Operationalization – Interviews

Concept Concept definition Operational

definition

Questions

Wants The form needs take as shaped by

culture and individual personality

(Armstrong et al, 2009)

See if the attributes

highlighted by students

correspond to the

attributes recruiters

want when hiring new

employees.

Which employee attributes do you

consider important when hiring

employees for the marketing

department at your company? Employee

attributes

Skills: the certain personal

abilities that an individual

possesses (Raybould & Sheedy,

2005)

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APPENDIX A: METHOD

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69

Soft skills: the personal and social

skill that a person possesses

(Hutchinson & Brefka, 1997)

Hard skills: job objectives, work

experience and academic

background (Hutchinson &

Brefka, 1997)

A11. Operationalization – Questionnaires

Operationalization – Questionnaire to students

Concept Concept definition Operational

definition

Questions

Perception The process by which stimuli are

selected, organized and

interpreted (Solomon et al, 2010)

Measure which

attributes (on a 1-7

scale) students perceive

recruiters want when

hiring new employees.

How important do you think the

following employee attributes are

for recruiters, when hiring new

employees to the marketing

department at a manufacturing

company?

(The attributes are the ones

developed from the focus groups

and interviews)

Employee

attributes

Skills: the certain personal

abilities that an individual

possesses (Raybould & Sheedy,

2005).

Soft skills: the personal and social

skill that a person possesses

(Hutchinson & Brefka, 1997)

Hard skills: job objectives, work

experience and academic

background (Hutchinson &

Brefka, 1997)

Operationalization – Questionnaire to recruiters

Concept Concept definition Operational

definition

Questions

Wants The form needs take as shaped by

culture and individual personality

(Armstrong et al, 2009)

Measure which

attributes (on a 1-7

scale) recruiters want

when hiring new

employees.

How important do you consider

the following employee attributes

to be, when hiring new employees

to the marketing department?

(The attributes are the ones

developed from the focus groups

and interviews)

Employee

attributes

Skills: the certain personal

abilities that an individual

possesses (Raybould & Sheedy,

2005).

Soft skills: the personal and social

skill that a person possesses

(Hutchinson & Brefka, 1997)

Hard skills: job objectives, work

experience and academic

background (Hutchinson &

Brefka, 1997)

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APPENDIX A: METHOD

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70

A12. Cover Letter Questionnaire Students

Hello marketing students!

We are conducting our bachelor thesis and we would be truly grateful if you could help us by

answering a short questionnaire. If you answer the questions, you have the opportunity to win

lottery tickets with a chance of becoming a millionaire!

It is an interesting questionnaire about which attributes you as a marketing student think is

important to possess to get a future job at the marketing department in the manufacturing

industry. The questionnaire will take approximately 5-10 minutes to complete. You will be

anonymous, but to be able to win the lottery tickets you need to leave your e-mail address by the

end of the questionnaire. This is however optional.

Please click on the link below to answer the questionnaire:

https://docs.google.com/forms/d/1I_LqcGFcMAmnb49GTts35v_etVww3oI37z9OvAnY6uM/vie

wform

A13. Cover Letter Questionnaire Recruiters

Dear Mr/Mrs,

We are three students studying at the Marketing Program at Linnaeus University in Växjö,

Sweden. We are conducting our bachelor thesis and would appreciate your help by answering a

short questionnaire, which will only take approximately 5 minutes to complete.

Below, you find the link to the questionnaire:

https://docs.google.com/forms/d/1OHLBEBDL_6oqTKPXsz5VtTQ71jx0ygb4JpujZOxMm2w/v

iewform

By using the website allabolag.se we got a list of the largest employers in Sweden in the

manufacturing industry and your company was on that list. We would be truly grateful if you

could answer this questionnaire and by so helping us to reach our academic goal with this thesis.

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APPENDIX A: METHOD

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71

The purpose of the study is to find out which employee attributes you consider important when

you are hiring new employees to your marketing department, and then compare that outcome

with the employee attributes marketing students think you are looking for.

If you feel that you are not the right person to answer this questionnaire, please forward it to the

person within your company that you think are more appropriate to answer it.

You, and the company you are working for, will of course be anonymous. If you have any

questions or concerns about the questionnaire, contact the persons responsible at:

Emelie Lindwall phone: +46 70 450 34 97 e-mail: [email protected]

Johanna Gustafsson phone: +46 73 843 90 56 e-mail: [email protected]

Martin Stadig phone: +46 70 314 38 29 e-mail: [email protected]

Thank you for your contribution to our bachelor's thesis!

Martin Stadig, Emelie Lindwall and Johanna Gustafsson

A14. Data Preparation

According to Hair et al (2003), collected data needs to be edited, which means that data must be

inspected to ensure completeness and consistency. Editing involves the level of understanding

the questions (Ibid). To make sure that a respondent understand a question correct, the researcher

can conduct a manipulation check, which means that the researcher can ask one question in two

different ways (Ibid). Last, editing might end up in eliminating certain questionnaires due to the

fact of missing data (Ibid). If the respondent did not understand certain questions correct, skipped

questions, or if the respondent did not fit the qualification criteria, are examples of missing data

(Ibid). “Coding means assigning a number to a particular response so the answer can be entered

into a database” (Hair et al, 2003, p.230). Collected data needs to be coded, preferably using

numerical codes, which will make it easier to enter data more quickly into the database, but also

to end up with fewer errors (Saunders et al, 2009). Hair et al (2003) state that data should be

coded before data is collected, e.g. by using a 7-point Likert agree-disagree scale. The decision

must be made concerning whether strongly agree will be coded 1 or 7, but the most proper way

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APPENDIX A: METHOD

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72

would be to code the largest number to strongly agree (Ibid). Once data has been successfully

coded, it needs to be entered into a computer, which will help to find obvious errors (Ibid).

A15. Descriptive Statistics

Saunders (2009) describes descriptive statistics as a general expression for statistics that explains

different variables. The role of descriptive statistics is to summarize the large amount of data that

has been collected (Krishnaswami & Satyaprasad, 2012). Hence, by using descriptive data, the

researchers are able to organize basic characteristics, as well as summarize data in a more

straightforward and understandable way, e.g. variations between gender or age (Zikmund et al,

2010). The descriptive statistics also make it possible to explain and compare variables

numerically (Saunders, 2009).

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APPENDIX B: RESULTS

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73

APPENDIX B: RESULTS

B1. Focus Group Procedure

The number of focus groups was decided by the consideration of two facts. Firstly, conducting

too many focus groups is often a waste of time (Bryman & Bell, 2011). Secondly, too few groups

may not be enough due to the fact that the responses might be specific to that one group (Bryman

& Bell, 2011). Hence, it was considered that three focus groups would be appropriate for the

current study.

Potential respondents were contacted personally and asked to participate in one of the three

planned focus groups. The three focus groups each contained six participants to get a good

composition, with a total of 18 respondents (cf. Bryman & Bell, 2011). The 18 participants were

announced time and place for the focus group and on the day of the event, a text message was

sent to the participants as a reminder. The focus groups were conducted in a group room at the

library of Linnaeus University in Växjö.

When the respondents had been gathered, they were informed about the purpose of the study as

well as its limitations. One main question was asked and discussed, with room for both

additional and follow-up questions (cf. Jacobsen, 1993). The question was impartial and well

thought out to encourage the respondents into a discussion and to obtain each group member’s

genuine opinions (cf. Webb, 2002). A committed moderator, whose task was to encourage, guide

and stimulate the focus groups so that the participants dared to share their true thoughts and

opinions about the chosen topic and question, led the focus groups. The moderator also made

sure that the time for the focus group was not too lengthy (cf. Greenbaum, 2000). The group

sessions lasted for 30 minutes. During the sessions, a secretary on a computer took notes.

Attributes mentioned by the respondents were also written down on a whiteboard for all

respondents to review. The third focus group differed somewhat from the first and second focus

groups. Not only did the third focus group go through the above-mentioned procedure, but it also

worked as a confirmation group to test the outcomes from the first and second focus group. They

were presented to a summary of all the attributes mentioned during all focus groups and were

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APPENDIX B: RESULTS

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74

requested to discuss whether the list of attributes were representative of the reality or if any

attributes had to be added or removed.

After the sessions, a first draft of the answers were transcribed, interpreted and processed (cf.

Jacobsen, 1993). The answers were thereafter compiled into a more coherent structure, where the

responses were analyzed and further developed into a foundation of what was most important to

continue to work with (cf. Jacobsen, 1993).

B2. Interview Procedure

A total of five interviews were conducted with a sample of personnel managers. The

organizations on the sampling frame were contacted via telephone or e-mail, to get hold of the

right person for the interview. Later, an introduction letter was sent to the respondents including

the purpose of the study, how the findings might be useful for the authors and the respondents

themselves (cf. Bryman & Bell, 2011). Five personnel managers accepted to participate in an

interview, with a promise that the company and interviewee in question would remain

anonymous. Telephone appointments with the interviewees were booked, and a pretest of the

interview question was conducted to seek validity (cf. DiCicco-Bloom & Crabtree, 2006).

During the interview, the interviewees were first informed about the purpose of the study, the

importance of their participation and why they had been chosen to participate (cf. Bryman &

Bell, 2003). The interviews began with one open question that was followed up by

supplementary questions depending on the answer from the first question. Leading questions

were avoided during the interview to avoid controlling the response (Bryman & Bell, 2003).

During the interview everything that was said was recorded with the respondents’ permission, so

that the interviewer could concentrate on the conversation instead of taking notes (Ibid).

When the interviews had been conducted, a first draft of the answers was interpreted and

processed (cf. Jacobsen, 1993). The answers were thereafter compiled into a more coherent

structure, where the responses were analyzed and further developed into a foundation of what

was most important to continue to work with (Ibid).

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75

B3. Correlation Analysis Indexes

Students

Soft skills Hard skills Other attributes

Soft skills 1

Hard skills .477** 1

Other attributes .316** .366** 1

** Correlation is significant at the 0.01 level (2-tailed)

Recruiters

Soft skills Hard skills Other attributes

Soft skills 1

Hard skills .490** 1

Other attributes .263** .372** 1

** Correlation is significant at the 0.01 level (2-tailed)

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APPENDIX B: RESULTS

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76

B4. Correlation Analysis Single Attributes

Students:

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APPENDIX B: RESULTS

______________________________________________________________________________

77

** Correlation is significant at the 0.01 level (2-tailed)

* Correlation is significant at the 0.05 level (2-tailed)

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78

Recruiters:

In

terp

ers

onal

skil

ls

Com

munic

atio

n s

kil

ls

Tea

mw

ork

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f-m

anag

emen

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about

the

mar

ket

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APPENDIX B: RESULTS

______________________________________________________________________________

79

** Correlation is significant at the 0.01 level (2-tailed)

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APPENDIX B: RESULTS

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80

B5. Means and Standard Deviations – Sum All Attributes

Group N Mean Std. Deviation

Students 83 5.0943 .62320

Recruiters 126 5.1560 .44240

B6. Means and Standard Deviations – Indexes

Students Recruiters

Index N Mean Std. Deviation N Mean Std. Deviation

Soft skills 83 5.4904 .71627 126 5.6431 .49118

Hard skills 83 4.9157 .81517 126 4.8090 .63251

Other attributes 83 3.6343 .88459 126 3.5196 .69892

B7. Means and Standard Deviations – Single Attributes Students Recruiters

Attribute N Mean Std. Deviation N Mean Std. Deviation

Interpersonal skills 83 6,04 1,087 126 5,87 ,829

Communication

skills

83 6,11 1,082 126 6,17 ,728

Teamwork 83 6,07 ,908 126 5,89 ,751

Self-management 83 5,43 1,048 126 5,94 ,762

Work ethic 83 6,07 ,947 126 6,20 ,716

Commitment 83 5,41 1,166 126 5,92 ,900

Analytical skills 83 5,45 1,106 126 5,37 ,907

Leadership skills 83 5,06 1,301 126 5,10 ,978

Strategic thinking 83 5,23 1,182 126 5,28 ,932

Creativity 83 5,60 1,157 126 5,72 ,834

Responsibility 83 5,84 1,120 126 6,25 ,665

Problem solver 83 5,31 1,322 126 5,53 ,879

Positive attitude 83 5,82 1,280 126 5,91 ,877

Flexibility 83 5,59 1,200 126 5,93 ,831

Self-awareness 83 4,80 1,403 126 5,21 1,112

Professionalism 83 5,19 1,401 126 5,37 ,992

Work experience 83 4,80 1,455 126 4,64 1,082

Cultural experience 83 4,33 1,308 126 4,27 1,392

Multilingual 83 4,80 1,237 126 4,90 1,223

Knowledge about the

market

83 5,33 1,211 126 4,83 1,231

Education 83 5,00 1,325 126 4,84 ,991

Practical skills 83 4,66 1,213 126 4,83 ,961

Physical well-being 83 4,62 1,349 126 5,25 1,001

Age 83 2,92 1,399 126 2,65 1,138

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APPENDIX B: RESULTS

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81

Gender 83 2,22 1,440 126 1,74 1,245

Well formulated CV

and personal letter

83 4,79 1,454 126 4,44 1,167

B8. Shapiro-Wilks Test

Students Recruiters

Statistic df Sig. Statistic df Sig.

Interpersonal skills ,753 83 ,000 ,856 126 ,000

Communication skills ,746 83 ,000 ,810 126 ,000

Teamwork ,826 83 ,000 ,841 126 ,000

Self-management ,903 83 ,000 ,843 126 ,000

Work ethic ,808 83 ,000 ,808 126 ,000

Commitment ,895 83 ,000 ,861 126 ,000

Analytical skills ,904 83 ,000 ,897 126 ,000

Leadership skills ,921 83 ,000 ,905 126 ,000

Strategic thinking ,919 83 ,000 ,897 126 ,000

Creativity ,880 83 ,000 ,857 126 ,000

Responsibility ,845 83 ,000 ,788 126 ,000

Problem solver ,880 83 ,000 ,859 126 ,000

Positive attitude ,827 83 ,000 ,857 126 ,000

Flexibility ,859 83 ,000 ,825 126 ,000

Self-awareness ,937 83 ,000 ,905 126 ,000

Professionalism ,911 83 ,000 ,895 126 ,000

Work experience ,940 83 ,001 ,919 126 ,000

Cultural experience ,941 83 ,001 ,924 126 ,000

Multilingual ,927 83 ,000 ,923 126 ,000

Knowledge about the

market

,904 83 ,000 ,913 126 ,000

Education ,926 83 ,000 ,898 126 ,000

Practical skills ,933 83 ,000 ,894 126 ,000

Physical well-being ,939 83 ,001 ,906 126 ,000

Age ,917 83 ,000 ,902 126 ,000

Gender ,798 83 ,000 ,641 126 ,000

Well formulated CV

and personal letter

,931 83 ,000 ,934 126 ,000

B9. Skewness and Kurtosis

Students

N Skewness Kurtosis

Statistic Statistic Std. Error Statistic Std. Error

Interpersonal skills 83 -1,941 ,264 5,731 ,523

Communication skills 83 -1,818 ,264 4,141 ,523

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APPENDIX B: RESULTS

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82

Teamwork 83 -,947 ,264 ,796 ,523

Self-management 83 -,484 ,264 ,499 ,523

Work ethic 83 -1,294 ,264 2,970 ,523

Commitment 83 -,809 ,264 1,475 ,523

Analytical skills 83 -,319 ,264 -,122 ,523

Leadership skills 83 -,353 ,264 -,164 ,523

Strategic thinking 83 -,232 ,264 -,516 ,523

Creativity 83 -,419 ,264 -,445 ,523

Responsibility 83 -1,062 ,264 ,994 ,523

Problem solver 83 -1,017 ,264 1,117 ,523

Positive attitude 83 -1,227 ,264 1,749 ,523

Flexibility 83 -1,065 ,264 1,352 ,523

Self-awareness 83 -,140 ,264 -,466 ,523

Professionalism 83 -,326 ,264 -,812 ,523

Work experience 83 -,242 ,264 -,510 ,523

Cultural experience 83 -,227 ,264 -,456 ,523

Multilingual 83 -,113 ,264 -,161 ,523

Knowledge about the

market

83 -,318 ,264 -,680 ,523

Education 83 -,515 ,264 ,257 ,523

Practical skills 83 -,202 ,264 ,358 ,523

Physical well-being 83 -,087 ,264 -,202 ,523

Age 83 ,318 ,264 -,282 ,523

Gender 83 ,839 ,264 -,588 ,523

Well formulated CV

and personal letter

83 -,496 ,264 -,288 ,523

Recruiters

N Skewness Kurtosis

Statistic Statistic Std. Error Statistic Std. Error

Interpersonal skills 126 -,524 ,216 ,348 ,428

Communication skills 126 -,535 ,216 -,093 ,428

Teamwork 126 -,160 ,216 -,456 ,428

Self-management 126 -,233 ,216 -,468 ,428

Work ethic 126 -,453 ,216 -,456 ,428

Commitment 126 -,573 ,216 -,033 ,428

Analytical skills 126 -,174 ,216 -,009 ,428

Leadership skills 126 -,106 ,216 -,231 ,428

Strategic thinking 126 -,229 ,216 ,091 ,428

Creativity 126 -,416 ,216 -,237 ,428

Responsibility 126 -,346 ,216 -,745 ,428

Problem solver 126 -,696 ,216 ,446 ,428

Positive attitude 126 -,622 ,216 ,203 ,428

Flexibility 126 -,963 ,216 2,913 ,428

Self-awareness 126 -,569 ,216 ,527 ,428

Professionalism 126 -,451 ,216 -,083 ,428

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APPENDIX B: RESULTS

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83

Work experience 126 ,071 ,216 ,255 ,428

Cultural experience 126 -,569 ,216 -,040 ,428

Multilingual 126 -,530 ,216 ,619 ,428

Knowledge about the

market

126 -,583 ,216 1,082 ,428

Education 126 -,221 ,216 -,516 ,428

Practical skills 126 ,017 ,216 ,276 ,428

Physical well-being 126 -,324 ,216 -,016 ,428

Age 126 ,163 ,216 -,962 ,428

Gender 126 1,493 ,216 ,946 ,428

Well formulated CV

and personal letter

126 -,277 ,216 ,311 ,428

B10. Results Hypothesis 1

Attribute Md (n) Mean rank U-value z-value Asymp.

Sig. (2-

tailed)

Students Recruiters Students Recruiters

All attributes 5.04 (83) 5.15 (126) 101.25 107.47 4917.5 -.728 .466

B11. Results Hypotheses 2, 3 and 4

Attribute Md (n) Mean rank U-value z-value Asymp.

Sig. (2-

tailed)

Students Recruiters Students Recruiters

Soft skills 5.53 (83) 5.71 (126) 96.33 110.71 4509.5 -1.683 .092

Hard skills 5.00 (83) 4.80 (126) 112.92 99.78 4571.5 -1.543 .123

Other attributes 3.75 (83) 3.50 (126) 111.34 100.83 4703 -1.235 .217

B12. Additional Results

Attribute Md (n) Mean rank U-

value

z-value Asymp.

Sig. (2-

tailed)

Students Recruiters Students Recruiters

Interpersonal skills 6.00 (83) 6.00 (126) 115.33 98.19 4371.5 -2.141 .032

Communication

skills

6.00 (83) 6.00 (126) 107.36 103.44 5033 -.497 .619

Teamwork 6.00 (83) 6.00 (126) 114.93 98.46 4404.5 -2.071 .038

Self-management 5.00 (83) 6.00 (126) 87.18 116.74 3750 -3.656 .000

Work ethic 6.00 (83) 6.00 (126) 102.07 106.93 4985.5 -.614 .539

Commitment 5.00 (83) 6.00 (126) 89.16 115.43 3914.5 -3.206 .001

Analytical skills 5.00 (83) 5.00 (126) 107.80 103.15 4996.5 -.568 .570

Leadership skills 5.00 (83) 5.00 (126) 104.61 105.26 5196.5 -.079 .937

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Strategic thinking 5.00 (83) 5.00 (126) 103.73 105.83 5124 -.256 .798

Creativity 6.00 (83) 6.00 (126) 102.63 106.56 5032.5 -.481 .630

Responsibility 6.00 (83) 6.00 (126) 93.48 112.59 4273 -2.401 .016

Problem solver 5.30 (83) 6.00 (126) 100.96 107.66 4893.5 -.827 .408

Positive attitude 6.00 (83) 6.00 (126) 106.52 104.00 5102.5 -.311 .756

Flexibility 6.00 (83) 6.00 (126) 96.43 110.64 4518 -1.763 .078

Self-awareness 5.00 (83) 5.00 (126) 93.16 112.80 4246 -2.371 .018

Professionalism 5.00 (83) 5.00 (126) 101.54 107.28 4941.5 -.695 .487

Work experience 5.00 (83) 5.00 (126) 110.20 101.57 4797 -1.042 .298

Cultural

experience

4.00 (83) 4.15 (126) 104.93 105.05 5223 -.014 .989

Multilingual 5.00 (83) 5.00 (126) 101.29 107.44 4921 -.742 .458

Knowledge about

the market

5.00 (83) 5.00 (126) 119.19 95.65 4051 -2.840 .005

Education 5.00 (83) 5.00 (126) 111.02 101.04 4729.5 -1.212 .225

Practical skills 5.00 (83) 5.00 (126) 100.33 108.08 4841.5 -.948 .343

Physical well-

being

5.00 (83) 5.00 (126) 86.59 117.13 3701 -3.689 .000

Age 3.00 (83) 2.70 (126) 111.36 100.81 4701 -1.267 .205

Gender 2.00 (83) 1.00 (126) 117.54 96.74 4188.5 -2.752 .006

Well formulated

CV and personal

letter

5.00 (83) 4.70 (126) 115.60 98.02 4349 -2.111 .035

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APPENDIX C: QUESTIONNAIRE DESIGN

C1. Questionnaire Design Students

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APPENDIX C: QUESTIONNAIRE DESIGN

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C2. Questionnaire Design Recruiters

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Linnaeus University a firm focus on quality and competence

On 1 January 2010 Växjö University and the University of Kalmar merged to form Linnaeus University. This new

university is the product of a will to improve the quality, enhance the appeal and boost the development potential

of teaching and research, at the same time as it plays a prominent role in working closely together with local

society. Linnaeus University offers an attractive knowledge environment characterised by high quality and a

competitive portfolio of skills.

Linnaeus University is a modern, international university with the emphasis on the desire for knowledge, creative

thinking and practical innovations. For us, the focus is on proximity to our students, but also on the world around

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