Eindhoven, April 2011

BSc Industrial Engineering and Management Science — TU/e 2008

Student identity number 0634889

in partial fulfilment of the requirements for the degree of

Master of Science

in Operations Management and Logistics

Supervisors:

Dr. ir. P.A.M. Kleingeld, TU/e, HPM

Dr. T. Bipp, TU/e, HPM

Dhr. J.V. Meuldijk, Keurwerk

Critical Competencies of Self-employed Workers: Development and Validation of a Survey Instrument

by

T.H.P. Bongers

TUE. Department Industrial Engineering & Innovation Sciences

Series Master Theses Operations Management and Logistics

Subject headings: Behavior Event Interview (BEI), Competencies, Critical Incidents, Customer

satisfaction, Self-employed workers, Survey.

III

Abstract

This master thesis project investigates which competencies determine if customers will do repeated

business with self-employed workers. Behavioral Event Interviews (BEI’s) were held with customers of

self-employed workers to investigate which experiences had an impact on the customers’ satisfaction with

the self-employed worker. Next, the behavior of self-employed workers was transformed to questionnaire

items to validate the competencies that were mentioned at the BEI’s; the questionnaire was returned by

400 customers of self-employed workers. Finally, the competencies that related significant to satisfaction

were determined and used to compose a measurement instrument.

In order to increase general satisfaction, a self-employed worker is recommended to pay attention to every

mentioned competency. The four competencies that related significantly to general satisfaction were (1)

empathy, (2) customer focus, (3) enthusiasm and (4) proactive mentality. The company Keurwerk can use

these findings to provide specific advice to self-employed workers about their behavior.

IV

Preface

This master thesis project is composed at the faculty of Industrial Engineering and Innovation Sciences of

the Eindhoven University of Technology. The project is conducted in the field of Operations Management

and Logistics (OML) at the Human Performance Management (HPM) group and is the result of six

months research at the company “Keurwerk”.

I would like to use this opportunity to express my gratitude to my supervisors. This project would not

have been possible without the support of my company supervisor and founder of the project, Jan-Volkert

Meuldijk. I appreciate the time and effort he spent in the project and I would like to thank him for all the

advice. His enthusiasm and knowledge stimulated me to great efforts. Next, I want to thank Ad Kleingeld,

my first supervisor and mentor during the master thesis project. His feedback was instant, sharp and

constructive, and had a great contribution to my master thesis project. Meetings with him were always

pleasant and really helped me moving on during the project. I would also like to thank my second

supervisor Tanja Bipp for her assistance and her feedback on the final report.

I want to thank all the people I have interviewed for their time and response. Without them it was not

possible to gather different behavior about the self-employed workers. Furthermore, I would like to thank

all respondents of the quantitative questionnaire and the people who helped me with their network

increasing the response rate.

Finally, I want to thank my family and friends for their support during my study. Thanks to my friends

from university for the necessary distraction and their weekly electronic motivating messages.

Furthermore, I want to thank my girlfriend for always creating a delicate atmosphere when I came home.

Last but not least, a special word of thanks goes to my parents for their support during the entire study.

Due to their unconditional confidence, I had the opportunity to become who I am now.

Tom Bongers

Eindhoven, April 2011

V

Management summary

Context

There are various explanations why some self-employed workers are more successful than others.

According to the company Keurwerk, their success may be determined by the general satisfaction that

customers have about a self-employed worker. In this master thesis project, a validated questionnaire (i.e.

an instrument) is designed in order to investigate which particular competencies of self-employed workers

are the best predictors of general customer satisfaction.

Research objectives

The focus of the study is to measure competencies of independent self-employed workers who work in a

business to business environment. A competency is defined as a set of behaviors that influence the

achievement of specific results or outcomes (Kurz and Bartram, 2002). Although other factors (e.g. price,

quality, expertise, etc.) may also influence the general satisfaction of customers, in this research the

influences of competencies are of interest. Therefore, the following research question is answered in this

study: “Which competencies of self-employed workers significantly influence the general impression of

customers and are quantitatively measurable?”

Methodology

The methodology of the study was based on the competency study design of Spencer and Spencer (1993)

and consists of four main phases. In the first phase of the study, 22 Behavior Event Interviews (BEI’s)

were held by telephone to identify competencies that may influence the general satisfaction of customers.

In total, 314 usable Critical Incidents were identified and clustered in categories. These categories were

based on the 112 competency components of the Great Eight competency model of Bartram (2005). In the

second phase, the clustered Critical Incidents were used to compose a quantitative questionnaire in order

to validate the results of the BEI’s. Only the 89 most relevant Critical Incidents were included in the

questionnaire. Moreover, six questions about general satisfaction were obtained from literature and

formed the dependent variable. Although it was not the main goal of the study, five self-defined questions

about the price/quality of the self-employed worker were included to determine if this factor had an

influence on the dependent variable. The quantitative questionnaire was executed online in the third phase

of the study to measure the degree to which self-employed workers exhibit each competency identified in

the previous phase, as well as the “general impression”. The questionnaires were analyzed in SPSS using

hierarchical multiple regression and correlation analyses to establish which competencies were related to

the dependent variable. In the final phase of the study, the validated instrument that can be used by

Keurwerk was defined. The items that had the highest association with the outcome variable were

selected for use in this final instrument to offer an independent assessment of the competencies of self-

employed workers.

VI

Findings

In total, 400 customers of self-employed workers filled in the online questionnaire completely. After

analyzing the questionnaire, the outcome of the factor analysis was not in conformity with the

categorization that had been executed in advance. Therefore, it was decided to use the scales that were

provided by the factor analysis, rather than the predefined scales. The scales and their (in)direct

relationship with the dependent variable is depicted in Figure 1.

Figure 1: Competencies with a direct and indirect influence on general satisfaction

The correlations between the competencies of self-employed workers and general satisfaction were all

greater than .58 (significant at the .01 level), which represents a large effect. The competencies empathy

(r = .86), proactive mentality (r = .82) and enthusiasm (r = .79) were most strongly positively related to

general satisfaction. Four background variables (i.e. sector, contract duration, hired by respondent and

contact with multiple self-employed workers) were weakly associated with general satisfaction (r ≤ .11; p

< .05). A distinction was made between two sectors; the correlation analysis showed that customers from

self-employed workers working as a professional in the service industry were in general more satisfied

compared to customers from self-employed workers who worked as a specialized worker. Strikingly,

other background variables (e.g. contact frequency) did not show a significant relationship with general

satisfaction.

A hierarchical multiple regression analysis was executed to obtain the relative importance of the

competencies in the prediction of general satisfaction. The outcome showed a R² of .82 indicating that a

high amount of variance was explained by the model. The competency empathy was the strongest

predictor of general satisfaction (β = .32; p < .01). This means that if the empathy of the self-employed

worker towards the customer increases, the general satisfaction of the customer about the self-employed

worker is also likely to increase. The second strongest predictor was a proactive mentality (β = .27; p <

.01). Other significant predictors were customer focus (β = .16; p < .01), enthusiasm (β = .15; p < .01) and

the price/quality ratio (β = .08; p < .05). The regression results suggested that the other competencies did

not make a significant contribution to the prediction equation.

VII

Since not all competencies contributed significantly to the regression equitation, it was investigated if

they may demonstrate a mediating relationship with the general satisfaction. The approach posed by

Baron and Kenny (1986) was used and a mediating effect was found. As illustrated in Figure 1, the

competencies empathy, customer focus, enthusiasm and proactive mentality have a direct influence on

general satisfaction. These four competencies also mediate between four competencies (i.e. professional

appearance, process communication, availability and professional disposition) and general satisfaction.

The suggested relations were to a large degree confirmed by a more advanced Structural Equation

Modeling (SEM) analysis. Therefore, the final instrument contained questions about all eight

competencies. It was decided to include three or four questions per competency in order to prevent the

final instrument for becoming too extensive. For every competency, the means and standard deviations

were calculated based on the sample of 400, to serve as guidelines for the advice that can be provided by

Keurwerk to self-employed workers.

For both sectors (i.e. professionals in the service industry and specialized workers), a separate hierarchical

multiple regression analysis was executed to discover if there were differences in the prediction equation.

The results showed that only the competency enthusiasm was no longer a significant predictor among

professionals in the service industry; the other predictors were equal in both sectors.

Discussion

The correlation matrix indicated that all competencies correlated significantly with general satisfaction.

However, an alternative explanation is that this is due to the influence of a general evaluation on specific

judgments (Murphy, Jako and Anhalt, 1993). When a self-employed worker is rated on multiple

performance dimensions, the customer’s overall satisfaction or evaluation is thought to strongly influence

ratings of specific attributes; this phenomenon is referred to as halo effect (Murphy et al., 1993). It is

likely to assume that the halo effect has affected the results of the analyses, because all correlations were

high and there were on average no extreme differences between the competencies. Furthermore, it was

remarkable that the price/quality ratio was not the strongest predictor of general satisfaction. According to

the hierarchical multiple regression analysis, it was more important to possess the crucial competencies.

This finding emphasizes the importance of the competencies and can be used by Keurwerk to implement

the final instrument in the market.

Limitations and suggestions for future research

Besides the two sectors that are investigated in this study, also other differentiations can be made or other

self-employed workers can be investigated in order to implement the final instrument in a larger market.

The outcome of the analyses suggested that the halo effect had a large influence on the results. The

influence can be further investigated and can also be compared to the influence of a halo effect in other

studies.

VIII

Table of Contents

Abstract .......................................................................................................................................... III

Preface ........................................................................................................................................... IV

Management summary .................................................................................................................... V

List of Figures ................................................................................................................................. X

List of Tables .................................................................................................................................. X

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

2 The research setting ................................................................................................................. 2

2.1 The company Keurwerk ................................................................................................... 2

2.2 Origin of the problem ....................................................................................................... 2

2.3 Defining the Self-employed workers ............................................................................... 4

2.4 The Great Eight competency model ................................................................................. 7

2.5 Research objectives .......................................................................................................... 9

3 Definition ............................................................................................................................... 11

3.1 Methodology for collecting the Critical Incidents ......................................................... 11

3.2 Application of BEI in this study .................................................................................... 12

3.3 Outcome of the BEI’s beyond boundaries of MTP ........................................................ 14

4 Identification .......................................................................................................................... 15

4.1 Categorization methodology including reliability and validity check ........................... 15

4.2 Application of CI’s in this study .................................................................................... 16

4.3 Including CI’s in questionnaire ...................................................................................... 16

4.4 Process from BEI to questionnaire ................................................................................. 19

4.5 Composition of the questionnaire .................................................................................. 21

4.6 Hypotheses ..................................................................................................................... 22

5 Validation ............................................................................................................................... 23

5.1 Data collection ............................................................................................................... 23

5.2 Examining the data ........................................................................................................ 24

5.2.1 Missing data, outliers and descriptive statistics ..................................................... 24

5.2.2 Normality and Linearity ......................................................................................... 25

5.2.3 Factor analysis and reliability of the scales ............................................................ 25

5.2.4 Definition of the scales .......................................................................................... 27

5.3 Results ............................................................................................................................ 29

5.3.1 Inter correlations among study variables ............................................................... 29

5.3.2 Predicting general satisfaction ............................................................................... 31

5.3.3 Testing for mediating effects ................................................................................. 32

5.3.4 Explaining the relationships among the variables .................................................. 35

5.3.5 Comparison between two sectors ........................................................................... 37

5.3.6 Underlying characteristics of competencies ........................................................... 39

6 Implementation ...................................................................................................................... 43

6.1 Introduction .................................................................................................................... 43

6.2 Final instrument ............................................................................................................. 43

6.3 Recommendations for self-employed workers............................................................... 44

7 Discussion .............................................................................................................................. 48

IX

7.1 Overview of the results .................................................................................................. 48

7.2 Recommendations .......................................................................................................... 49

7.3 Limitations and suggestions for future research ............................................................ 51

7.3.1 Evaluation of the final instrument .......................................................................... 51

7.3.2 Limitations ............................................................................................................. 52

7.3.3 Suggestions for future research .............................................................................. 53

8 References .............................................................................................................................. 55

Appendix I: The Great Eight competencies ................................................................................... 59

Appendix II: BEI (in Dutch) .......................................................................................................... 61

Appendix III: Calculation of Fleiss Kappa .................................................................................... 63

Appendix IV: Final questionnaire (in Dutch) ................................................................................ 65

Appendix V: Correlation matrix of the original scales .................................................................. 66

Appendix VI: Factor Analysis ....................................................................................................... 68

Appendix VII: Sobel test for mediating mechanisms .................................................................... 71

Appendix VIII: Structural Equation Model on latent level ............................................................ 73

Appendix IX: Final instrument (in Dutch) ..................................................................................... 74

X

List of Figures

Figure 1: Competencies with a direct and indirect influence on general satisfaction ................................. VI

Figure 2: Influencing factors on maintaining the customer .......................................................................... 3

Figure 3: Relationship between behavior and the outcome variable ............................................................ 4

Figure 4: The focus of the master thesis project ........................................................................................... 6

Figure 5: Steps in the master thesis project ................................................................................................. 10

Figure 6: Planning process .......................................................................................................................... 18

Figure 7: The mediating effect .................................................................................................................... 33

Figure 8: Competencies with a direct and indirect influence on general satisfaction ................................. 33

Figure 9: The architecture model of competencies (Roe, 2002) ................................................................. 40

Figure 10: Underlying characteristics of competencies (Spencer and Spencer, 1993) ............................... 41

Figure 11: Example of a feedback graph .................................................................................................... 45

Figure 12: Random page of the final questionnaire .................................................................................... 65

Figure 13: The mediating effect .................................................................................................................. 71

List of Tables

Table 1: Self-employed workers by occupational groups (Houtman, 2006) ................................................ 6

Table 2: The Great Eight competency model (Bartram, 2005) ..................................................................... 8

Table 3: Occupation of the self-employed workers described by respondents ........................................... 13

Table 4: Interpretation of Fleiss Kappa (Landis and Koch, 1977) .............................................................. 15

Table 5: Calculated Fleiss Kappa values .................................................................................................... 16

Table 6: Categorization process .................................................................................................................. 17

Table 7: Most important competency components according to categorization ......................................... 17

Table 8: Example of the realization of a questionnaire scale ...................................................................... 20

Table 9: Independent variables including sample question ........................................................................ 26

Table 10: Pearson correlation coefficients .................................................................................................. 30

Table 11: Hierarchical multiple regression analysis ................................................................................... 32

Table 12: Testing the best mediators .......................................................................................................... 34

Table 13: Testing mediating effect with multiple mediators ...................................................................... 35

Table 14: Path coefficients and fit indices .................................................................................................. 36

Table 15: Hierarchical multiple regression analysis for professionals in the service industry ................... 37

Table 16: Hierarchical multiple regression analysis for specialized workers ............................................. 38

Table 17: Underlying characteristics of competencies ............................................................................... 42

Table 18: Means and Standard Deviations per sector ................................................................................. 44

Table 19: Relationship between stanine scores and normal distribution .................................................... 46

Table 20: Suggestions to improve Empathy ............................................................................................... 46

Table 21: Pearson correlation coefficients .................................................................................................. 66

Table 22: Regression analysis for relationship c......................................................................................... 71

Table 23: Regression analysis for relationship a......................................................................................... 71

Table 24: Regression analysis for relationship b ........................................................................................ 71

Table 25: Regression analysis for relationship c while controlling for b .................................................... 72

1

1 Introduction

A self-employed worker can deliver decent work, but if customers go to the competitor, he or she

becomes unemployed in the long run. Therefore, it is important that customers of the self-employed

worker are satisfied, in order to come back for repeated business. To emphasize the importance of

customer satisfaction, the findings of Anderson, Fornell and Lehmann (1994) supported that customer

satisfaction has a positive impact on profitability. Until now, it was unknown which factors determine

whether self-employed workers maintain their customers. This master thesis project explored

competencies that influences if customers come back to the same self-employed worker.

As a final product, the company Keurwerk wanted to have an instrument that consists of a quantitative

questionnaire that measures the competencies of a self-employed worker. After this model is filled in by

customers of the self-employed worker, Keurwerk has insights in the strong and weak points of the self-

employed workers and can give advice accordingly.

This study describes the study that leads to this final product. It starts with the research setting of the

master thesis project, including the origin of the problem, the research question and background

information about self-employed workers. Chapter three provides information about how the behavior

that may influence general satisfaction is collected. The next chapter selects the competencies that most

likely have an influence on the general satisfaction of self-employed workers. The most important

competencies were extracted with an online questionnaire, which is also explained in chapter four. All

analyses of the online questionnaire are described in chapter five. The next chapter depicts the final

instrument to measure general satisfaction of customers. Finally, chapter seven discusses the results

including limitations and suggestions for future research.

2

2 The research setting

This chapter starts with a small description of the company that initiated the master thesis project. Next,

the origin of the problem is explained and the self-employed workers are defined. Subsequently, the

research objectives are formulated including the research question. Finally, the different phases of the

study are described in order to give an overview of the steps that were executed to answer the research

question.

2.1 The company Keurwerk

The master thesis project is commissioned by Keurwerk. Keurwerk is a virtual organization, which

consists of a small number of self-employed workers. The number of self-employed workers changes

over time, but consists at the moment of a part time website developer and a communication specialist.

The initiator of Keurwerk has experience as a self-employed worker by combining expertise and

entrepreneurship. Like most other small entrepreneurs, he gained experience in entrepreneurship by trial

and error. In his opinion, there should be a way to make the process around entrepreneurship more

efficient. Therefore, the initiator of Keurwerk involved also people from other fields into his company

(i.e. marketing, ICT, communication, graphical designers, etc.) to extent the knowledge about

entrepreneurship. The goal of Keurwerk is to provide self-employed workers with a method to enhance

their entrepreneurial skills, by giving them insight in the opinion of customers about their behavior.

Keurwerk is established for this master thesis project and intends to implement the results of the master

thesis project in the market.

2.2 Origin of the problem

Some self-employed workers are more successful than others. This can have several causes, for instance

the market in which they operate, their education, expertise, knowledge, skills or their motivation to

become a self-employed worker (Boyatzis, 2008; Hoekstra and van Sluijs, 2003). Some of the success

factors are fixed in a certain field while others are subject to influences. One of the factors that can be

influenced are competencies (e.g. Boyatzis, 2008; Hoekstra and van Sluijs, 2003). In short, competencies

consist of sets of behaviors that influence the achievement of specific results or outcomes (Kurz and

Bartram, 2002; Landy and Conte, 2004). Paragraph 2.4 will discuss competencies in detail. The next

paragraph will describe the competency model that will be used to relate behaviors of self-employed

workers to competencies. Keurwerk would like to have answers to questions like for instance: which

characteristics of a self-employed worker motivate a customer to come back to the same self-employed

worker? The assumption made by Keurwerk is that the motivation of a customer to go back to the same

self-employed worker does not only depend on price or quality of the work, but also on other factors. One

of these factors is the general impression that self-employed workers leave. To determine the general

impression of customers about self-employed workers, the general satisfaction of customers will be

measured; therefore, the terms impression and satisfaction are used interchangeably throughout the study.

The main goal of the master thesis project is to establish which way of doing business is most profitable

for the self-employed worker, in terms of maintaining the customer. Figure 2 depicts some factors that

may have an influence on maintaining the customer.

3

Within the master thesis project, the general

satisfaction of the self-employed worker will

be the outcome variable. Keurwerk has

noticed that this is a factor in which the self-

employed worker has a lack of knowledge and

experience. A proven method to establish

what the determinants of a general impression

are is by making use of competencies (e.g.

Bartram, 2005; Woodruffe, 1993).

Figure 2: Influencing factors on maintaining the customer

Figure 3 depicts graphically the relationship between behavior and the outcome variable of the master

thesis project, which is the general impression of the self-employed worker. Individual differences are

related to behavior of self-employed workers and can be divided in three main fields: ability (i.e.

cognitive- and physical ability), motivation and personality (O’Reilly and Chatman, 1994).

The colored dots in Figure 3 represent different behaviors. In the first phase of the master thesis project, it

will be investigated which behaviors are exhibited by self-employed workers in their interaction with

customers. Some of these behaviors are related to competencies. The double arrow represents a two sided

effect. In other words, the specific competencies are also related to behavior. In the second phase, it will

be investigated which competencies are recognized by customers. Consequently, these competencies

relate to the general impression of self-employed workers. Not every behavior of the self-employed

worker is observed by the customers. This is visualized in Figure 3 by the decreasing amount of colored

dots. If the general impression is positive, the customers are satisfied and there is an increased probability

that they will do repeated business with the self-employed worker. On the other hand, if the customer is

dissatisfied, the self-employed worker should change his behavior in order to leave a good impression.

Maintaining the customer

Price Quality

Other

factors

General

impression

4

Individual

differences

PersonalityAbility

Behavior of a self-employed worker

General satisfaction

Dissatisfied

customer

Satisfied

customer

Using the self-employed worker

again

Phase 1

Phase 2

Interpreted behavior by customers

Competencies

Motivation

Figure 3: Relationship between behavior and the outcome variable

2.3 Defining the Self-employed workers

Because the goal of the master thesis project is to obtain more insight in the functioning of self-employed

workers, this paragraph provides more information about these kinds of workers. Connelly and Gallagher

(2004) defined two main work arrangements which account for most workers. The first one is the

“normal” or “standard” work arrangement that (a) is performed full time, (b) continuous indefinitely and

(c) is performed at the “employer’s” place of business under the supervision of a manager. On the other

hand, there is a more alternative way of working which is called “contingent work”. A commonly use

definition of contingent work is: “any job in which an individual does not have an explicit or implicit

contract for long-term employment or one in which the minimum hours worked can vary in a

nonsystematic manner” (Polivka and Nardone, 1989, p. 11).

5

The group of contingent workers is not homogenous. In fact, four broad groupings of work arrangement

were defined by Connelly and Gallagher (2004) that fit into Polivka and Nardone’s (1989) definition.

These groups are graphically depicted in Figure 4. The first group is called “temporary staffing agencies”

or “temporary-help service firms”. Among the temporary-help service firms, there is an almost

universally explicit understanding that the contract has a fixed duration. A good example of such a

company who provides temporary-help services is Manpower (Connelly and Gallagher, 2004). A second

category of contingent workers is most often found in large organizations where irregular staffing

requirements result in the frequent use of workers for short-term assignments. This arrangement is called

“in-house” or “direct hire”. The difference with the previous arrangement is that the workers are now

directly hired, instead of only using the services of a temporary-help service firm. In the Netherlands, a

variation of the direct-hire arrangement is referred to as “zero-hour” contracts, where working hours are

only made available when a definite demand exists for such labor (Sparrow, 1998). The third category of

contingent workers also includes workers who are directly hired by an organization. However, the

workers are now hired based on a seasonal contract (e.g., resorts, tourism, etc.) where there is an absence

of a long-term contract. Matusik and Hill (1998) found evidence that many firms use contingent workers

as “technical experts” on important projects.

The focus of the master thesis lies on the fourth category, which consists of workers with “independent

contractor” or “contract” status. These independent contractors or “freelancers” are often defined as self-

employed workers. According to Connelly and Gallagher (2004), a key characteristic of the self-

employed worker is that they sell their services to client organizations on a fixed-term or a project basis.

The use of this kind of workers has become very visible in knowledge-based occupations, especially the

information technology (IT). Vroonhof et al. (2001) add to this key characteristic that self-employed

workers do not conduct their activities on their own initiative, but only after an order is distributed to

them. Furthermore, they do not receive a fixed salary, but get paid per assignment. In general, the self-

employed workers do not have their own company building. They operate from their home, or they are

located at the company they are working for (Vroonhof et al., 2001). Ho, Ang and Straub (2003)

discovered that companies occasionally terminate “standard” contracts of permanent workers and hire

these employee’s as self-employed workers in order to increase the flexibility.

Boheim and Muehlberger (2006) analyzed the characteristics of workers who provide work on the basis

of a civil or commercial contract, but who are dependent on or integrated into the firm for which they

work. Boheim and Muehlberger (2006, p. 2) define the dependent self-employed worker as: “workers

who provide work or perform services to other persons within the legal framework of a civil or

commercial contract, but who in fact are dependent on or integrated into the firm for which they perform

the work or provide the service in question.” These are also called “economically dependent workers”

because they are formally self-employed but depend on a single employer for their income. As depicted in

Figure 4 the focus of the master thesis project lies on the independent self-employed workers. More

information about contingent workers can be found in the literature study of Bongers (2010).

6

Figure 4: The focus of the master thesis project

Based on recent numbers of the CBS, there are approximately 708,000 self-employed workers in the

Netherlands (CBS, 2011). It is unknown how this number is distributed between dependent- and

independent self-employed workers. From now on, the term self-employed workers will be used in the

master thesis report to mention independent self-employed workers. The focus of the research is on self-

employed workers who act in the B2B market and have a higher education level. Examples of

occupations in this field are website developers, graphical designers, event organizers, actors and coaches.

The different occupational groups of the self-employed workers are listed in Table 1. Although the

information originates from 2006, the percentages give at least an indication about the distribution of self-

employed workers within occupational groups. Table 1 depicts that relatively many self-employed

workers in the Netherlands work as a craftsmen or industry worker, markets sales worker, technician,

associate professional, agricultural and fishery worker (Houtman, 2006).

Table 1: Self-employed workers by occupational groups (Houtman, 2006)

Occupational Group Percentage

Craftsmen and industry workers 13.9%

Transportation workers 1.9%

Clerks 3.7%

Trade and shop and market sales workers 15.9%

Service workers 7.7%

Health care professionals 6.6%

Educational professions 3.4%

Technicians and associate professionals 17.8%

Agricultural and fishery workers 17.6%

Managers and officials 1.1%

Other Professions 10.4%

Total 100.0%

7

2.4 The Great Eight competency model

The literature distinguishes several definitions of a competency, but there are two frequently used

definitions that also fit into the design of this study. Kurz and Bartram (2002, p. 229) define competencies

as: “A set of behaviors that are instrumental in the delivery of desired results or outcomes.” Hoekstra and

van Sluijs (2003, p. 33) define a competency as: “The ability to perform effectively in a specific task

situation or in a specific problem situation.” According to Kurz and Bartram (2002), a competency based

approached is based on measuring individual differences in terms of specific work related constructs that

are relevant to successful job performance. There are several models that describe and list competencies

(e.g. Hoekstra and van Sluijs, 2003; Kurz and Bartram, 2002; Spencer and Spencer, 1993). However, not

all models can be used for the development of an instrument to identify crucial competencies of self-

employed workers. According to Bongers (2010), the main reasons for the exclusion of competency

models for the master thesis project are:

• The competency model is not suitable for self-employed workers, because it is written for other

specialism’s (e.g. managers, service workers, etc.).

• The competency model does not include a comprehensive overview of competencies to compare

the characteristics of self-employed workers to.

• The overview of competencies is not complete.

The easiest way to relate self-employed workers’ characteristics to competencies is to compare the

characteristics with an extensive competency list. The competency model of Bartram (2005) has three

levels and describes a lot of details. This competency model is called “The Great Eight” and provides a

criterion-centric model that has emerged from factor analyses and multidimensional scaling analyses of

self- and manager ratings of workplace performance (Bartram, 2005). Because this competency model is

validated, it is likely that it has a high quality and predicts performance across a wide variety of jobs. The

model distinguishes 20 competency dimensions containing 112 component competencies at a detailed

level (see Appendix I). The titles and high-level definitions of the great eight competencies are depicted

in Table 2. Bartram (2005) showed that the Big Five of personality factors, motivation and ability

relationships relate to the Great Eight in the manner as described in Table 2. According to Bartram (2005)

the factors of the Great Eight appear to occupy a position within the work performance domain similar to

the Big Five in the personality predictor domain. With the validated model of Bartram (2005) it is also

possible to connect personality factors of self-employed workers to specific competencies. However, this

will not be part of the master thesis project.

8

Table 2: The Great Eight competency model (Bartram, 2005)

Factor Competency

domain title

Competency domain definition Big Five, motivation, and

ability relationships

1 Leading and

Deciding

Takes control and exercises leadership.

Initiates action, gives direction, and takes

responsibility.

Need for power and

control, extraversion

2 Supporting and

Cooperating

Supports others and shows respect and

positive regard for them in social situations.

Puts people first, working effectively with

individuals and teams, clients, and staff.

Behaves consistently with clear personal

values that complement those of the

organization.

Agreeableness

3 Interacting and

Presenting

Communicates and networks effectively.

Successfully persuades and influences

others. Relates to others in a confident,

relaxed manner.

Extraversion, general

mental ability

4 Analyzing and

Interpreting

Shows evidence of clear analytical

thinking. Gets to the heart of complex

problems and issues. Applies own expertise

effectively. Quickly takes on new

technology. Communicates well in writing

General mental ability,

openness to new

experience

5 Creating and

Conceptualizing

Works well in situations requiring openness

to new ideas and experiences. Seeks out

learning opportunities. Handles situations

and problems with innovation and

creativity. Thinks broadly and strategically.

Supports and drives organizational change.

Openness to new

experience, general

mental ability

6 Organizing and

Executing

Plans ahead and works in a systematic and

organized way. Follows directions and

procedures. Focuses on customer

satisfaction and delivers a quality service or

product to the agreed standards.

Conscientiousness, general

mental ability

7 Adapting and

Coping

Adapts and responds well to change.

Manages pressure effectively and copes

well with setbacks.

Emotional stability

8 Enterprising and

Performing

Focuses on results and achieving personal

work objectives. Works best when work is

related closely to results and the impact of

personal efforts is obvious. Shows an

understanding of business, commerce, and

finance. Seeks opportunities for self-

development and career advancement.

Need for achievement,

negative

agreeableness

9

2.5 Research objectives

Keurwerk would like to have a tool for self-employed workers to give them more insights in the

competencies they need to have in order to improve their general impression and to be successful. As

Figure 3 already showed, the competency on its own is not the only thing which is important in this study.

The way in which customers experience the actions of the self-employed worker is also an important

factor. For instance, a self-employed worker can try to act reliable, but customers may experience

something else. Therefore, it is important for self-employed workers that they have insight in how their

behavior is actually interpreted by customers. As a result, the first research objective is the development

and validation of an instrument to measure the crucial competencies of self-employed workers that satisfy

customers. Next, guidelines for the use of this validated instrument will be provided. The implementation

will be the main goal of Keurwerk after the master thesis project is finished.

The main research was a collaboration between the student and Keurwerk. The research question can be

formulated as:

“Which competencies of self-employed workers significantly influence the general impression of

customers and are quantitatively measurable?”

To answer the research question, the assessment process of the master thesis project is outlined in a

flowchart (see Figure 5) which is based on the competency study design of Spencer and Spencer (1993).

This flowchart can be interpreted as the framework of the master thesis project; every step is discussed in

a separate chapter.

10

Figure 5: Steps in the master thesis project

In the definition phase, Behavior Event Interviews (BEI’s) are held by telephone to identify

competencies that may influence the general satisfaction of customers. In the identification phase, the

Critical Incidents that are deduced from the BEI’s are clustered in categories. These categories are based

on the 112 competency components of the Great Eight competency model of Bartram (2005). The

clustered Critical Incidents lead to the composition of the quantitative questionnaire that validates the

results of the BEI’s. The quantitative questionnaire is executed in the validation phase to measure the

degree to which the self-employed worker exhibits each competency identified in the previous phase, as

well as the “general impression”.

Next, the outcomes of the questionnaire are analyzed in SPSS. Correlation and regression analysis are

executed to establish which competencies are related to the outcome variable (general impression of the

self-employed worker). The Implementation phase of this master thesis project is the design of the

validated instrument. The questions that have the highest association with the outcome variable are

selected to use in this final instrument. This instrument offers an independent judgment about the self-

employed worker according to his or her competencies.

11

3 Definition

This chapter is divided in three sections and provides information about how the Critical Incidents were

collected. The first section describes how the Behavioral Event Interviews (BEI’s) were executed to

identify Critical Incidents and gain insight in the customer perception after a self-employed worker had

finished his work. Next, the results were used to develop the final questionnaire about behaviors of self-

employed workers that influence the general impression of customers. The final section describes

additional information that was provided by respondents to support self-employed workers in their

customer interaction.

3.1 Methodology for collecting the Critical Incidents

In the first phase, questions were developed for the BEI. From now on, the first qualitative interview will

be called BEI to prevent confusion through mixing up terms. The in-depth BEI do not directly measure

competencies of self-employed workers, but measured the experiences of customers with the self-

employed worker. The BEI is derived from Flanagan’s (1954) Critical Incident Method (Spencer and

Spencer, 1993). Most important difference is that the Critical Incident Method identifies aspects of the

job. On the other hand, the BEI method identifies the competencies needed to do the job well (Spencer

and Spencer, 1993). Furthermore, the BEI asks people to identify and describe the most critical situations

they have encountered. The objective of the BEI is to get detailed behavioral descriptions of how a

customer thinks about the way people execute their work. The interviewer’s job is to keep pushing for

complete stories that describe the specific behaviors, thoughts, and actions that people show in actual

situations (Spencer and Spencer, 1993). Due to this interview technique also the probability to discover

unknown unknown’s increases. According to Mullins (2007), the “unk-unks” are things that people do

not know they do not know. Initially customers of self-employed workers may for instance say that they

only care about the quality of the delivered work. However, when they are describing their collaboration

with the self-employed worker, they may come to the conclusion that they also valued a smooth

collaboration. These underlying thoughts can be discovered using BEI’s.

Spencer and Spencer (1993) describe some aspects of the BEI which explains why this interview

technique outperforms the traditional interviewing method. First of all, traditional interviewing methods

are unable to identify competencies, because they ask directly to them (e.g. what is your greatest

strength?). The problem with this interviewing technique is that people do not know what their

competencies, strengths or weaknesses really are. Therefore, it is better to ask the interviewee to describe

several situations and deduct the competencies from these behavioral events. Second, the interviewee is in

traditional interviews not able to reveal their real competencies, due to leading interview questions

(Hodgson, 1987). As a result, the interviewee gives a “socially desirable” answer or an answer what they

think the interviewer wants to hear. These answers are not reliable, because they do not describe the

interviewee’s real preferences or opinions. Third, what people think or say about their competencies is not

credible, only what they actually do, in the most Critical Incidents they have faced, is to be believed

(Spencer and Spencer, 1993). This is accomplished with the BEI method, because people are asked to

describe how they actually behaved in specific incidents.

12

According to Spencer and Spencer (1993), a BEI contains five steps. Most of the interview should focus

on step 3; however, the other steps will also be explained. The questions are based on the literature about

BEI (Spencer and Spencer, 1993) and the Critical Incident Technique (Flanagan, 1954; Latham and

Wexley, 1982), but also on literature about competencies that determine the satisfaction of customers (e.g.

Rackham et al., 1996; Schaffer, 2002; Stumpf, 2009). The five steps of the BEI are briefly mentioned

below; the entire interview questions are described in Appendix II.

• Step 1: Introduction and Explanation

• Step 2: Job Responsibilities

• Step 3: Behavioral Events

• Step 4: Characteristics Needed to do the job

• Step 5: Conclusion and summary

To obtain at least 300 Critical Incidents, Latham and Wexley (1982) recommend that at least 30 people

should be interviewed.

3.2 Application of BEI in this study

The first respondents of the BEI’s were invited by a letter in which they were asked to participate in the

study. Using a snowball approach, other respondents were contacted. The questions of the BEI’s were

asked by telephone to a total of 22 customers of different self-employed workers and recorded on tape to

simplify the processing of the Critical Incidents. Confidentiality was guaranteed and only the researchers

had access to the tapes. Detailed sub questions were asked to validate if the answers are interpreted on

the right way. In addition to the BEI, a semi-standardized qualitative technique called laddering

(Reynolds and Gutman, 1988) is used to collect Critical Incidents. The laddering technique leads to deep

and focused results, because it constantly asks why a specific behavior is important (Gruber et al., 2008).

As a result, the underlying thoughts behind the answers were explored.

As explained before, to obtain a comprehensive sample of incidents, at least 30 people should be

interviewed (Latham and Wexley, 1982). However, only asking respondents about competencies while

disregarding the quality, price and content of their work, strongly limits the variation and number of

Critical Incidents. Hence, 22 customers of self-employed workers are interviewed telephonically to obtain

answers to the BEI questions that are depicted in Appendix II. Because in the last five interviews no

radical new Critical Incident categories showed up, it is likely to assume that all relevant behavior is

described by these 22 respondents. To validate this assumption, 10% of the Critical Incidents is set aside

and examined after the categorization to see if any of them describes behaviors that has not yet appeared

(Latham and Wexley, 1982).

13

Most of the respondents worked with different self-employed workers. As a result, they could describe

behavior of multiple self-employed workers. This positively affected the study, because the number of

Critical Incidents increased and the behavior of different self-employed workers was described, which

gave a more complete picture. Furthermore, the respondents were also asked to describe negative

behavior of self-employed workers. Especially if a respondent rejected the offer of the self-employed

worker, it was interesting to know the reason behind it. The 22 respondents produced a total of 525 useful

Critical Incidents. The Critical Incidents that were mentioned more than ones are combined, resulting into

a total of 314 unique items. Table 3 depicts the occupations of the self-employed workers that are

described by the respondents. Although the sample of respondents is quite diverse, their Critical Incidents

were less dispersed. A first impression of the Critical Incidents showed that there seems to be no strong

impact of occupation on the type of behavior that is valued as important. Examples of Critical Incidents

that are mentioned by respondents are discussed in chapter 4. This is realized according to the thematic

analysis of Spencer and Spencer (1993). The thematic analysis is the process of identifying themes or

patterns in raw data (Spencer and Spencer, 1993). This means that all the Critical Incidents are filtered out

of the BEI and all statements made during the interviews are examined and converted into items

describing only one issue (Vliegen et al., 2010).

Table 3: Occupation of the self-employed workers described by respondents

Occupation of the self-employed worker Number of respondents Percentage

Website developer 8 17.5%

Graphical designer 6 13%

Actor 5 10.9%

Photographer 5 10,9%

Trainer 5 10,9%

Coach 3 6.5%

Event organizer 2 4.3%

Interim manager 2 4.3%

Photo reviser 2 4.3%

Teacher 2 4.3%

Text writer 2 4.3%

Advisor 1 2.2%

Artist 1 2.2%

Career mentor 1 2.2%

Plumber 1 2.2%

Total 46* 100% *This number is higher than 22 because some respondents described behavior of multiple self-employed workers.

The target group for executing the master thesis project is defined by some aspects. First of all, the self-

employed worker should have the ability and the knowledge to enhance his or her daily work.

Furthermore, he or she should be willing to evaluate his or her functioning. It is likely to assume that

these are self-employed workers with a higher education. Secondly, customers should be willing to

evaluate the self-employed workers. This means that the customers should have close ties or a business

connection with the self-employed worker; otherwise they are not able to give a fair opinion. Because the

customer did business with the self-employed worker, it is likely to assume that their knowledge about the

self-employed worker is good enough to participate in the questionnaire. Thirdly, it is assumed that the

study will have the biggest impact in a business to business (B2B) relationship.

14

3.3 Outcome of the BEI’s beyond boundaries of MTP

During the interviews, many behaviors with respect to the content of the occupation were mentioned by

the respondents. Although these Critical Incidents are not part of the master thesis project, they are now

mentioned briefly because they are assumed to play an important role in the general satisfaction of

customers. Furthermore, additional information given by the respondents that is not related to general

customer satisfaction, but can improve the development of self-employed workers will also be mentioned

in this section.

According to almost all respondents, the most important characteristic of a self-employed worker should

be his knowledge about the subject. Self-employed workers are hired by customers due to their ability in a

specific field. Therefore, they have to show that they possess all the skills, expertise and capabilities to

perform well. Furthermore, there should be a clear difference between being a self-employed worker or

an employee. For instance, some self-employed workers require their customers to pay for additional skill

training. This demand would have been justified if they worked as an employee for a fixed salary.

However, self-employed workers made the choice to become independent which also includes keeping

their own knowledge on the desired level. Finally, some customers demand explicitly for a registration at

the chamber of commerce.

Some of the respondents work in a large company as an intermediary and hire self-employed workers to

work for their customers. Hiring self-employed workers to work for one’s customers exposes the risk that

the self-employed worker takes over the customer. This seriously harms the relationship between the

intermediary and the self-employed worker. As a result, the self-employed worker is strongly advised to

communicate with their customers via the intermediary about prices or other intimate information.

Furthermore, the intermediary entrusts the self-employed worker with his customers. Therefore, a good

business relationship between the customers and the self-employed worker will also be appreciated by the

intermediary.

Since self-employed workers do not have employees, valuable information about projects may be lost if

the self-employed worker is involved in for instance a serious car accident. In that case, some respondents

of the interviews mentioned that they appreciated the fact that they have their own access to relevant

project information.

In case a self-employed worker has multiple customers, the customers appreciate it when the self-

employed worker does not talk about them to competitors. Respondents of the interviews also recommend

self-employed workers not to inform them about competitors, because this can harm the mutual

confidence. Finally, the respondents gave some additional advice to self-employed workers, and

recommend them to:

• Build a network, so self-employed workers can acquire their own customers

• Have some good references, so customers know who they are working with.

• Define a Unique Selling Point (USP), so the self-employed worker distinguishes from

competitors.

• Know other self-employed workers with competencies beyond their own. When outsourcing

work to them, chances increase that they also outsource work to you.

4 Identification

In this phase, the Critical Incidents that are deduced from the BEI

categories. Based on the categorization and the frequency the CI are mentioned by customers, it is

decided which categories to include in the questionnaire.

the outcome of the questionnaire.

4.1 Categorization methodology including

Categorizing CI’s in one of the competency components means that

CI’s in the competency component that has the highest overlap with respect to content. In this

categorization process it was not allowed to classify a CI in multiple competency components.

reliability of the categorization is assessed by establishing the inter

statistical measure for calculating inter

can be defined as: (P – Pe) / (1 – Pe).

above chance, and (P – Pe) gives the degree of agreement actually achieved above chance. However,

Cohen’s kappa measures agreement between two raters only. Therefore, Fleiss kappa

similar measure of agreement, because there

calculation of Fleiss kappa, including the formulas that

and Koch (1977) formulated guidelines to interpret

Table 4: Interpretation of Fleiss Kappa (Landis and Koch, 1977)

Interpretation

<0 Poor agreement

0.0 – 0.20 Slight agreement

0.21 – 0.40 Fair agreement

0.41 – 0.60 Moderate agreement

0.61 – 0.80 Substantial agreement

0.81 – 1.00 Almost perfect agreement

The degree to which the items constitute a representative sample of the competencies that are related to

the general impression of self-employed workers (i.e. the content validity of the categorization) is verified

by categorizing the 10% that was initiall

to be met in order to conclude that the categorization was valid (Latham and Wexley, 1982):

• It was not allowed to create new categories.

• No more than two new behavioral items under an existing category

If these conditions are not met, new BEI should be organized, because apparently not all important

Critical Incidents have been collected (

discussed in the next section.

15

In this phase, the Critical Incidents that are deduced from the BEI are analyzed and

. Based on the categorization and the frequency the CI are mentioned by customers, it is

decided which categories to include in the questionnaire. Finally, hypotheses were formulated to predict

methodology including reliability and validity check

Categorizing CI’s in one of the competency components means that an individual categorizer

CI’s in the competency component that has the highest overlap with respect to content. In this

gorization process it was not allowed to classify a CI in multiple competency components.

reliability of the categorization is assessed by establishing the inter-rater agreement (Cohen, 1960). A

statistical measure for calculating inter-rater agreement is Cohen’s Kappa (Cohen, 1960). The kappa (

Pe). The factor (1–Pe) gives the degree of agreement that is attainable

gives the degree of agreement actually achieved above chance. However,

en’s kappa measures agreement between two raters only. Therefore, Fleiss kappa

similar measure of agreement, because there were more than two raters (Fleiss,

calculation of Fleiss kappa, including the formulas that were used can be found in Appendix

and Koch (1977) formulated guidelines to interpret values. These guidelines are depicted in Table 4.

: Interpretation of Fleiss Kappa (Landis and Koch, 1977)

Moderate agreement

Substantial agreement

Almost perfect agreement

The degree to which the items constitute a representative sample of the competencies that are related to

employed workers (i.e. the content validity of the categorization) is verified

by categorizing the 10% that was initially set aside. While categorizing these 31 items, two conditions had

to be met in order to conclude that the categorization was valid (Latham and Wexley, 1982):

not allowed to create new categories.

No more than two new behavioral items under an existing category were allowed to be created.

If these conditions are not met, new BEI should be organized, because apparently not all important

Critical Incidents have been collected (Latham and Wexley, 1982). The outcome of the validity check is

analyzed and clustered in

. Based on the categorization and the frequency the CI are mentioned by customers, it is

formulated to predict

check

categorizer classifies a

CI’s in the competency component that has the highest overlap with respect to content. In this

gorization process it was not allowed to classify a CI in multiple competency components. The

rater agreement (Cohen, 1960). A

is Cohen’s Kappa (Cohen, 1960). The kappa ( ),

gives the degree of agreement that is attainable

gives the degree of agreement actually achieved above chance. However,

en’s kappa measures agreement between two raters only. Therefore, Fleiss kappa was used for a

more than two raters (Fleiss, 1971). The exact

used can be found in Appendix III. Landis

values. These guidelines are depicted in Table 4.

The degree to which the items constitute a representative sample of the competencies that are related to

employed workers (i.e. the content validity of the categorization) is verified

y set aside. While categorizing these 31 items, two conditions had

to be met in order to conclude that the categorization was valid (Latham and Wexley, 1982):

allowed to be created.

If these conditions are not met, new BEI should be organized, because apparently not all important

2). The outcome of the validity check is

16

4.2 Application of CI’s in this study

The 314 Critical Incidents were categorized by the student in one of the 112 competency components of

Bartram’s (2005) Great Eight competency model. To validate the categorization, two other independent

raters (i.e. the supervisor of Keurwerk and a graduate) were also asked to categorize the items of the

Critical Incidents. All competencies were translated accurately into Dutch, to prevent language errors and

to make the categorization process easier. The clustered competencies led to the composition of the

quantitative questionnaire that validates the results of the BEI’s.

The calculated Fleiss Kappa after the categorization of the 314 items in one of the 112 competency

components was 0.56. Furthermore, Fleiss Kappa values for the 20 competency dimension and the 8

domain competencies were calculated1. The results, which are depicted in Table 5, show that every

categorization has at least moderate agreement.

Table 5: Calculated Fleiss Kappa values

314 items Agreement

8 Competency domains 0.68 Substantial

20 competency dimensions 0.64 Substantial

112 competency components 0.56 Moderate

Although there were differences in the categorization, the most important CI’s (i.e. CI’s that are

mentioned more than three times) were almost always categorized two or more times in the same

competency component. Subsequently, there was no reason to discuss the final categorization with the

supervisor of Keurwerk and the graduate.

The conditions of the content validity check defined by Latham and Wexley (1982) were both met.

Therefore, it is most likely that a sufficient number of important Critical Incidents that determine the

satisfaction of customers were taken into account (Latham and Wexley, 1982).

4.3 Including CI’s in questionnaire

All 314 Critical Incidents are categorized into competency components by three independent raters (i.e.

the researcher, a graduate and the supervisor of Keurwerk). Table 6 depicts the categorization process of

Critical Incidents in competency component 2.1.2 “Adapting to the Team”. This competency component

is discussed in more detail in section 4.4. The other Critical Incidents are categorized in a similar way into

the competency components. The most important competency components are summarized in Table 7.

1 Because not all 314 items were included in the final questionnaire, Fleiss Kappa values were also calculated

separately for the 89 items that appeared in the questionnaire. The values are respectively 0.75, 0.73 and 0.65 for the

competency domains, competency dimensions and competency components.

17

Table 6: Categorization process

Categorizer Categorized Critical Incidents

Researcher 43 45 115 135 138 157 180 225 254 314

Graduate 43 45 115 135 138 157 180 225 254 312 313 314

Supervisor 43 115 135 157 190 216 225 314

Critical Incident numbers 135, 157, 254 and 314 were included in the questionnaire

The numbers in the table refer to the following Critical Incidents; all Critical Incidents start with the phrase: “The self-

employed worker…” 43 Fits within the organization; 45 Has a close relationship to the environment; 115 Is flexible to get

on with; 135 Is able to collaborate with other people and is able to give and receive feedback; 138 Has a well developed

corporal awareness and is aware of his non-verbal communication; 157 Is able to work in a team; 180 Is able to work in a

team, able to give feedback to customers and able to receive feedback from customers; 190 Is able to deal with other

people; 216 Shares characteristics with the customer (e.g. being informal, reliable, etc.); 225 Fits to the organization and

meets the needs of the customer; 254 Is able to collaborate and able to work together to a result; 312 Is able to adjust to

the needs of the initiator; 313 Is able to adjust to customers; 314 Is able to adjust to the customers demand.

Table 7: Most important competency components according to categorization

Competency component with

corresponding number

*Number of

items

**Number of

different CI’s

Multi-

plication

3.1.1. Building Rapport † 23 16 368

3.3.5. Projecting Credibility † 19 17 323

4.1.4. Targeting Communication † 19 15 285

2.1.7. Communicating Proactively † 18 15 270

1.1.2. Taking Responsibility † 18 14 252

8.1.2. Working Energetically and

Enthusiastically † 16 15 240

1.1.3. Acting with Confidence † 11 14 151

2.1.2. Adapting to the Team † 10 13 130

2.1.12. Developing and Communicating Self-

knowledge and Insight † 11 10 110

4.1.4. Acting on Own Initiative † 10 10 100

6.2.7. Driving Projects to Results 8 8 64

3.1.2. Networking 7 9 63

7.1.1. Adapting † 6 9 54

6.1.2. Planning 6 5 30

6.2.1. Focusing on Customer Needs and

Satisfaction 6 5 30

7.1.3. Adapting Interpersonal Style 4 5 20

4.2.1. Applying Technical Expertise 4 4 16

1.1.6. Taking Calculated Risks 5 3 15

7.2.5. Handling Criticism 4 3 12

8.2.2. Identifying Business Opportunities 4 3 12 * Number of items that are at least categorized by two raters in the same competency component.

** Number of different respondents who mentioned at least one Critical Incident that fits into the corresponding

competency component. Only items that are categorized two or three times in the same competency component are taken

into account.

† Competency component included in questionnaire

18

A minimum number of questions has been established in order to prevent the questionnaire for becoming

too long, which may limit the possible respondents for participation. After analyzing Table 7, the cut-off

score for the inclusion of the competency components in the questionnaire has been set on a minimum of

6 items and at least 9 different respondents (>40% of the respondents) who mentioned at least one Critical

Incident within the component. The fourth column of Table 7 depicts the multiplication of the previous

two columns; as a consequence of previous mentioned restrictions, a multiplication score of 54 has been

used as cut-off score. There are two competency components that have a multiplication score above the

cut-off, but were not included in the final questionnaire. The first one “Driving Projects to Results” is part

of the competency dimension “Delivering Results and Meeting Customer Expectations”, which is too

closely related to the content of the job. Because the focus of this master thesis project is on general

competencies that are beyond the content of the job, this competency component was not included in the

final questionnaire. The second competency component that is not included in the final questionnaire

despite a multiplication score above the cut-off is “Networking”. Respondents mentioned this competency

mainly as an answer to the question what characteristics they think are needed to become a successful

self-employed worker. As a result, networking is interpreted as an advice to self-employed workers and

therefore explained in section 3.3 and not included in the questionnaire. Another reason for not including

networking in the questionnaire is because this competency is basically no behavior. Networking requires

other behavior such as social- and communicative skills, which are already included in the questionnaire.

Table 7 depicts that there are nine competency components left that include multiple items and are

mentioned by different respondents, but are below the cut-off score. Besides the low cut-off score,

additional reasons for excluding these competency components from the questionnaire are:

• Planning: As can be noticed in Figure 6, the self-employed worker and customer are both

involved when an appointment is made. However, the customer is not involved in the planning

process of the appointments. The third step will be visible again for both parties. As a result, all

Critical Incidents that relate to planning are not included in the final questionnaire about general

customer satisfaction, because there are no customers involved in this process. Critical Incidents

that relate to for instance keeping the appointment can be found in the competency component

“Taking Responsibility”, so all important items are included in the next step of the project.

Making the

appointment

Planning the

appointment

Following the

appointment

Self-

employed

worker

Customer

Self-

employed

worker

Self-

employed

worker

Customer

1 2 3 Figure 6: Planning process

• Focusing on Customer Needs and Satisfaction: This competency component was not included

in the final questionnaire, because it has too much overlap with the dependent variable (i.e.

general satisfaction of customers). However, some Critical Incidents that were mentioned in this

category (e.g. being customer directed) were also mentioned in the competency component

“Building Rapport”.

19

• Adapting Interpersonal Style: Items within this competency component were too vague to

include in the final questionnaire. For instance the Critical Incidents “ability to adjust to the

principal’s profile” and “equal the principal’s customer approach” were not easy to answer for

customers of self-employed workers, especially if there is no principal involvement.

• Applying Technical Expertise: This competency component had too much overlap with

competencies relating to the content of the job. Therefore, it was excluded from the general

competencies.

• Taking Calculated Risks: The interpretation of “risks” can cause confusion among the

respondents, because it can be interpreted positively and negatively. It was excluded for that

reason.

• Handling Criticism: Some of the Critical Incidents in this competency component dealt with

feedback. However, items that are related to accepting and processing feedback were already

included in the competency component “Adapting to the Team”.

• Identifying Business Opportunities: Again, this competency component is not directly visible

by the customer. If business opportunities are identified by a self-employed worker, the outcome

(i.e. taking initiative, improving existing processes) can be criticized by the customer. Therefore,

only the items that were visible for customers are included in the final questionnaire under the

competency component “Acting on Own Initiative”

Because competency components that are included in the questionnaire contain too many Critical

Incidents to include as separate questions, only the relevant Critical Incidents that had been mentioned

three or more times were retained. If the competency component did not contain enough questions for a

reliable scale, additional relevant questions were added. Finally, the list of all relevant Critical Incidents

was checked for items that had been mentioned four or more times, but had not been included in the

questionnaire. There was one item (i.e. “listening to what I really want”) meeting this requirement. Hence,

this item was added to a questionnaire category to prevent losing relevant information.

4.4 Process from BEI to questionnaire

To illustrate the way questionnaire scales were composed from BEI statements, this section provides a

complete example of how the scale of competency component number 2.1.2. (i.e. Adapting to the Team)

was composed. The CI numbers of Table 8 correspond to the numbers that were used in Table 6. The

second column depicts statements that were mentioned by the respondents during the BEI’s. Every

statement starts with the expression: “the self-employed worker”. Each letter in the third column

represents a different respondent. Hence, the total number of different respondents contributing to this

scale was 13. The item number corresponds to the items that were classified by the three categorizers. The

CI numbers above 314 are marked with † (e.g. 373, 374 and 386) because these have a large overlap with

a certain item (in this case 135). The * marked statements were transformed to questionnaire items.

Because there were five different respondents who mentioned feedback, item 135 was included in the

questionnaire. The item was divided in a question dealing with receiving feedback and an item dealing

with giving feedback. Because item nr. 157 “being able to work in a team” had a high overlap with the

competency component; it was also included in the scale. The question was negatively formulated

because every scale needs at least one reverse-phrased item to reduce response bias (Field, 2005). The **

marked statements in Table 8 were not included in the final instrument for various reasons. CI’s 43 and

20

225 were not included because they deal with an organization and a self-employed worker is not always

working for an organization. CI’s 45, 115, 138 and 180 were too restricted because they were only

mentioned by a maximum of two respondents or the statement related too strong to an existing question.

Table 8: Example of the realization of a questionnaire scale

CI

Nr.

Statement from BEI. The self-employed worker:

Mentioned by

respondent

Item

Nr.

Transformed in

questionnaire item

43 Fits within the organization ** A - B 43 Not included

45 Has a close relationship to the

environment ** C 45 Not included

115 Is flexible to get on with ** H 115 Not included

135

Is able to collaborate with other

people and is able to give and

receive feedback *

F

135

Is open to receive

feedback

373 Gives feedback † I - J

Gives constructive

feedback to other people

374 Is able to give feedback † B - C

386 Has the ability to give adequate

feedback † F

138

Has a well developed corporal

awareness and is aware of his non-

verbal communication **

F 138 Not included

157 Is able to work in a team * C 157 Is not able to work in a

team

180

Is able to work in a team, able to

give feedback to customers and able

to receive feedback from customers

**

E - J

180 Not included

398 Is able to collaborate with other

people † E

225 Fits to the organization and meets

the needs of the customer ** A - K

225 Not included

414 Fits to the organization due to his

enthusiasm † A

254 Is able to collaborate and able to

work together to a result * D

254

Is able to come to a

good result, due to a

good collaboration 428 Is able to collaborate † F - G - H - L

429 Is able to collaborate with the

principal † I

314 Is able to adjust to the customers

demand * M 314

Is able to adjust to my

needs

Total number of different respondents

in scale 13

* Included in final instrument; ** Not included in the final instrument

† Large overlap with other items

21

4.5 Composition of the questionnaire

After the items had been categorized, the competency components with the highest multiplication score

were included in the questionnaire. This questionnaire is included in Appendix IV, and is divided in four

main parts that will now be briefly discussed.

Background variables

In the questionnaire, 10 background variables about for instance gender and age of the respondent and the

contact frequency with the self-employed worker were assessed, because they may have a confounding

effect on the results. Due to these background variables, significant differences between for instance

occupational groups may be found.

Dependent variable

Questions about the general impression of customers have been partly taken from the BEI, because in the

interview was asked explicitly for factors that determine a positive general impression. Furthermore,

existing literature (e.g. Zhang et al., 2009; Homburg et al., 2001) was examined for scales and items that

determine the satisfaction of customers. Unfortunately, all customer satisfaction questionnaires that were

found included aspects that may have an influence on the general satisfaction of customers (i.e. flexibility,

communication, collaboration, etc.) in the measure itself or questions that are related to the price and

quality of the product. The purpose of this master thesis project is to determine which behavior has the

strongest relation with general satisfaction, beyond price and quality. Therefore, it was impossible to use a

standard customer satisfaction scale from the literature. Due to the confidentiality of the final instrument,

the questions that determine the general satisfaction of customers (e.g. “I would recommend this self-

employed worker to a friend”) are added in Appendix IV. Data of this self-defined scale is measured at

the interval level, using a 5-point Likert-type scale. Respondents have been asked to indicate the extent to

which they agree or disagree with each statement (1 = Strongly disagree, 2 = Disagree, 3 = Neutral, 4 =

Agree, 5 = Strongly agree).

The scale to determine general customer satisfaction consists of 6 separate items and is the most

important scale of the questionnaire. An additional separate question has been added to the questionnaire

in case the dependent variable scale is not reliable enough (i.e. low Cronbach’s Alpha). This question (i.e.

“In general, I would give the self-employed worker the following grade), is measured on a 10-point scale.

Independent variables

The questionnaire consists of fourteen scales varying from five to ten items per scale with a total number

of 95 items that are placed in a random order. The number of unique respondents who mentioned a

Critical Incident fitting in a particular scale is registered. Every scale was at least mentioned by 9 different

respondents (>40%). This is assumed to have a positive influence on the questionnaire reliability, because

otherwise the scales can be biased by talkative people (Latham and Wexley, 1982). Jansen and Joosten

(1998) give a number of guidelines concerning for instance question type and formulation of the

questions that have been taken into account while formulating the questionnaire.

As described in the previous chapter, the separate items are clustered in competency components. To

validate if the items really measure the given competency component, a factor analysis will be executed.

O’Rourke and Cappeliez (2002) recommend a minimum of three items per scale (i.e. competency

22

component). However, if an item has to be removed from a scale after the factor analysis because the item

does not measure the given competency component, the number of items per scale drops below three. To

prevent this, only scales with four or more items were included in the questionnaire. With this safety

margin, the scale would still be reliable when an item has to be deleted. The next chapter depicts all

included scales with an example question.

Price/quality questions

The purpose of the master thesis project is not to determine if the price/quality ratio of the product or

service has an influence on the general satisfaction of customers. However, it would be useful to establish

to what extent the price/quality ratio influences general satisfaction. If this is a low extent, Keurwerk can

use that information to promote the importance of the general impression. Therefore, one scale consisting

of 5 items was added at the end of the questionnaire that asks respondents to assess the price/quality ratio

(e.g. “I am satisfied with the price/quality ratio of this self-employed worker”). This scale was

deliberately placed at the end of the questionnaire and introduced with a short amount of text to make sure

that the respondents would not take the price/quality ratio into account while filling in the other questions.

4.6 Hypotheses

The BEI’s already gave an initial insight in the behavior of self-employed workers that is valued by

customers. Therefore, the first hypothesis is:

H1: All mentioned scales correlate significantly with general satisfaction of customers.

There is a difference in the frequency in which behavior is mentioned by customers of self-employed

workers. According to Table 7 in section 4.3, the six most mentioned competency components are:

Building Rapport, Projecting Credibility, Targeting Communication, Communicating Proactively, Taking

Responsibility and Working Energetically and Enthusiastically. It is likely to assume that these Critical

Incidents have the highest regression with the dependent variable. Therefore, the second hypothesis is:

H2: The competency components Building Rapport, Projecting Credibility, Targeting

Communication, Communicating Proactively, Taking Responsibility and Working Energetically and

Enthusiastically are significant predictors for general customer satisfaction.

Critical Incidents were collected from multiple respondents who did business with self-employed workers

from different fields. During the BEI’s it was already remarkable that the respondents all came up with

more or less the same Critical Incidents, independent of the self-employed workers’ occupation.

Consequently, it would also be reasonable to assume that there will be no differences in competencies that

predict general satisfaction between respondents who work with self-employed workers from different

fields. This leads to the third hypothesis:

H3: Predictors of general customer satisfaction are independent of the self-employed worker’s field.

23

5 Validation

In this phase, the quantitative questionnaire is executed to measure the degree to which the self-employed

worker exhibited each competency component identified in the previous phase, as well as the “general

impression”. In other words, the most frequently named competencies that have been found in the

identification phase are validated. The questionnaire is distributed to customers of self-employed workers,

in order to measure the competencies that are related to a good general impression to customers. Next, the

outcomes of the questionnaire are analyzed in SPSS. Correlation and regression analysis are executed to

establish which competencies relate significantly to the dependent variable (general impression of the

self-employed worker).

5.1 Data collection

Customers of the self-employed workers were approached to participate in the questionnaire. The focus of

the questionnaire was on customers who recently (i.e. in the last six months) bought something from or

retained the service of the self-employed worker. These customers could form a better picture compared

to customers who had not had contact with the self-employed worker for a longer period of time.

Furthermore, also customers who received an offer in the past, but did not hire the self-employed worker

were approached to fill in the questionnaire. The questionnaires about the self-employed workers were

executed and collected online. The possible respondents were invited by a letter sent by e-mail, in which

the study was shortly explained. Among all respondents, five gift coupons of €25 were raffled. If a

respondent did not fill in the online questionnaire within a week, a reminder was sent to remind the

respondent. Field (2005) recommends a minimum sample size of 50 +8k, where k is the number of

predictors. The previous chapter showed that the number of categories was 16. Hence, with 453

independent responses, the recommendation of Field (2005) has been met. To minimize the design effect,

only a limited number of questionnaires per single self-employed worker were collected.

Because the questionnaires were not distributed within a single company, it was a challenge to collect

enough responses. Furthermore, most questionnaires were not directly sent to customers, but first to self-

employed workers. These self-employed workers had to forward the invitation to their customers, who

should be willing to fill in the questionnaires. All these factors had a negative influence on the response

rate. Therefore, a large network has been used to approach possible respondents for filling in the

questionnaire. First, more than 10,000 e-mail addresses of self-employed workers are collected via the

Dutch Chamber of Commerce. Second, a company that executes payments for self-employed workers has

sent an invitation to their customers. Third, an author of books for self-employed workers has sent an

invitation to more than 4700 of his followers on Twitter. Fourth, LinkedIn in combination with the

personal network of the researcher and the supervisor of Keurwerk were used to find relevant

respondents. All these actions had a contribution to the recruitment of the usable respondents who filled

in the questionnaire.

24

5.2 Examining the data

Before the results of the questionnaire can be analyzed, it is necessary to verify the data, check for

missing data and outliers, check the reliability of the scales, and determine the underlying structure of

scales. Competencies that are used in the questionnaire are explained in the final section of this chapter.

5.2.1 Missing data, outliers and descriptive statistics

In total, 1051 respondents opened the questionnaire and answered at least one question. After filling in

approximately ten questions, more than 50% of the respondents closed the questionnaire; obviously, all

these cases were discarded from the analysis. If for the remaining respondents missing data was evident

on summated scales and at least 70% of the independent variables were filled in, the missing variables

were replaced by item mean using EM approach (Hair et al., 2006). In case of overall missing data over

30%, all variables of the corresponding respondent were discarded. Respondents with missing data for the

dependent variable were all deleted to avoid any artificial increase in relationships with the independent

variables (Hair et al., 2006).

Because outliers can bias and distort statistical tests, it is important to detect them and decide on retention

or deletion. Hair et al. (2006) define outliers as cases with standard scores of 4 or greater. Based on the

requirements of Hair et al. (2006), three multivariate outliers were detected and discarded from the

analysis. Furthermore, a small number of univariate outliers were detected. Based on the source of the

uniqueness and a lack of demonstrable proof indicating that they are truly aberrant and not representative

of any observations in the population, there was no reason to discard these outliers. In total, a sample of

453 respondents met the above mentioned requirements and could be used for the analysis. However,

after a closer look to the standard deviations of the individual respondents, some alarming values were

detected. 28 respondents had a standard deviation greater than one. After observing the values that were

filled in by the 28 respondents, it became clear that they filled in extreme positive as well as extreme

negative scores. Even for questions that were categorized in the same scale, their range was four. This

could be explained by the inclusion of negative formulated questions. If, for instance, a respondent filled

in mainly high scores for every question (i.e. for positive and negative formulated questions), the score of

the negative formulated questions became low after reversing. As a result, there can be concluded that

these respondents filled in a part of the questionnaire at random (i.e. without reading the question

accurately) and for that reason they are discarded from the dataset. It is also possible that respondents

filled in the questionnaire at random, but without extreme scores. In that case, their standard deviation

does not exceed the threshold value of one because only middle scores are filled in. Therefore, 25

respondents with an extremely low standard deviation were also discarded from the analysis, because

their low dispersal on the different scales could seriously disturb the analysis. Consequently, a sample of

400 respondents was used for the multivariate data analysis. Most of the participants were male (75%)

and their age ranged from 20 to 75 (M=46.6; SD=10.3). The self-employed workers were also mostly

male (88%) and were hired by the respondent in 85% of the cases. 60% of the self-employed workers

were working as a specialized worker (e.g. plumber, carpenter, mechanic, etc.), the remaining 40% of the

self-employed workers were working as a professional in the service industry (e.g. website developer,

consultant, graphical designer, etc.). In 51%, the respondents had a long lasting relationship with the self-

employed worker (i.e. more than 6 months), only 12% of the respondents worked less than a week with

the self-employed worker. In most cases (60%) the respondent and the self-employed workers had contact

25

multiple times a week. In only 6%, the contact frequency was less than once in every 6 months and 59%

of the respondents did business with multiple self-employed workers. On average, the respondents graded

the self-employed workers with 7.5 (SD =1.1) on a ten point scale.

5.2.2 Normality and Linearity

To justify the use of multivariate techniques, it is important to check assumptions before deciding which

statistical test is appropriate. The most fundamental assumption in multivariate analysis is normality (Hair

et al., 2006). This assumption was checked by kurtosis (referring to the peakedness), skewness (the

balance of the distribution) and the normal probability plot. According to Field (2005), for large samples

(200 or more) it is more important to look at the shape of the distribution visually than to calculate the

significance of the skewness and kurtosis statistics. Therefore, histograms for all variables were checked

and found to be normally distributed. Next, the data was checked for multicollinearity (i.e. predictors that

correlate too highly with each other) and because none of the predictor variables correlated very highly

(0,80 or more) no multicollinearity appeared (Field, 2005). The next assumption, homoscedasticity, refers

to the assumption that dependent variables exhibit equal levels of variance across the range of predictor

variables (Hair et al., 2006). The homoscedasticity was checked graphically and based on the patterns it

was concluded that the assumption had been met. Furthermore, the data was checked for linearity because

correlations represent only the linear association between variables (Hair et al., 2006). Based on

examination of the scatter plots, no nonlinear patterns in the data were identified.

5.2.3 Factor analysis and reliability of the scales

To define the underlying structure among the independent variables in the analysis, principal component

analysis instead of common factor analysis was applied, because the objective was to summarize the

items in a minimum number of factors for prediction purposes (Hair et al., 2006). Oblique factor rotation

was used, because this is the preferred method when the goal of the factor analysis is to obtain

theoretically meaningful factors or constructs. In contrast, orthogonal rotation extracts factors that do not

correlate, whereas oblique rotation allows factors to correlate (Hair et al., 2006). According to Hair et al.

(2006), factor loadings of ±.30 to ±.40 are minimally acceptable for practical significance at a sample size

>300. Field (2005) starts with looking at inter correlation between variables. As already indicated before,

there were no variables that did not correlate with any other variables. In the analysis, factors were

extracted when the eigenvalues exceeded 1.0 and factor loadings with an absolute value < .30 were

suppressed.

The factor analysis extracted 14 factors (in 68 iterations), which was not equal to the number of scales

that were formulated beforehand. Since all scales were self-defined, it was to be expected that not every

item would load on the corresponding factor. However, the executed factor analyses showed results that

were difficult to interpret. Only the items of the dependent variable and items of the scale about price and

quality loaded exactly on the predicted factors. All other items were distributed fairly at random

throughout the 12 remaining factors. If the original scales would be maintained, the mutual correlation

between the independent variables would be extremely high because items load on multiple factors2. Due

to the high inter correlations of the factors; no meaningful conclusions could be drawn about the relative

2 The correlation matrix of the predefined scales is depicted in Appendix V

26

importance of the factors in predicting general satisfaction. Therefore, the following transformations and

remedies were attempted to transform the factor analysis in order to reduce the mutual correlation.

• Changing the delta factor in the Oblique rotation. Increasing the delta factor allows highly

correlated factors (Field, 2005).

• Square root and logarithmic transformation of the data in order to change the distribution.

• Deleting items that load on multiple factors.

• Merging competency components that belong to the same competency dimension.

None of the remedies resulted in a substantial decrease of the mutual correlation among the predefined

scales. Therefore, a new factor analysis was executed without taking into account the predefined scales of

Bartram (2005). Since the dependent variable scale and the scale about price and quality were considered

as reliable (i.e. Cronbach’s alpha’s of respectively .92 and .88), the corresponding items were excluded

from the new factor analyses. This revised factor analysis extracted 13 factors. Three factors consisted of

only two items, which is not enough for a reliable scale. Therefore, the factor analysis was executed again

with the number of extracted factors fixed to ten. The value of the Kaiser-Meyer-Olkin measure of

sampling adequacy was .97 which indicates that patterns of correlations are relatively compact and so

factor analysis should yield distinct and reliable factors (Field, 2005). The pattern matrix of the factor

analysis is depicted in Appendix VI and shows 21 items that load on multiple factors. These items were

deleted, because they caused a high mutual correlation which negatively affected the analysis. Moreover,

items with a factor loading < .30 and scales with less than three items were also deleted from the analysis.

To prevent the final instrument for becoming too extended, items were deleted from scales with a large

number of questions. Table 9 depicts the revised scales including an example question and the degree of

consistency between the multiple measurements (Cronbach’s alpha).

Table 9: Independent variables including sample question

# Scale # items Example question The self-employed worker:

Cronbach’s α

1 Empathy 4 creates mutual trust .87

2 Customer focus 4 listens to my demands* .78

3 Professional

appearance 4 is dressed properly .76

4 Process

communication 4

communicates transparent how he/she thinks

about the project, even if he/she disagrees with me .82

5 Enthusiasm 4 is dedicated to his/her work .85

6 Availability 3 can visit me within three days if I need help .63

7 Integrity 3 is open for receiving feedback .51

8 Professional

disposition 4

takes own initiative while working on an

assignment .66

9 Not enough items to formulate a reliable scale

10 Proactive

mentality 4

contacts me if an assignment is not finished on

time .85

General satisfac-

tion (dep. var.) 6 came up to my expectations .92

Price/quality

ratio 5

I am satisfied about the price/quality ratio of this

self-employed worker .88

*This question was formulated negatively in the questionnaire

27

According to Hair et al. (2006), Cronbach’s alpha values between .6 and .7 are the lower limit of

acceptability for exploratory research. Since factor 7 has an alpha of .51 it is discarded from further

analyses. Factor nine did not contain enough items to formulate a reliable scale and was also deleted.

All in all, 31 items were retained and will be included in the final instrument. The dependent variable

scale consists of 6 items and the scale about the price/quality ratio consists of 5 items. These 11 items

were also included in the final instrument. Although the items about the dependent variable and the

price/quality ratio were not included in the factor analysis, an example question of both scales is included

in Table 9. The example question about the price/quality ratio does not start with the phrase: “the self-

employed worker”.

5.2.4 Definition of the scales

This section provides insight in the scales that were used to determine general satisfaction. Note that some

competencies overlap each other. Therefore, the descriptions are subjected to the interpretation of the

researcher. The corresponding items that are used in the final questionnaire are depicted in Appendix IX.

Empathy

By showing empathy, the perception of the customer is understood by the self-employed worker. In

addition, the own influence on customers is taken into account. Included behavior in this scale was for

instance inspiring confidence and being agreeable towards a customer in order to create a mutual

connection.

Customer focus

This competency focuses on the customer, especially during communication. It includes for instance

listening to what a customer really wants and going into the customers’ needs. Due to the customer focus,

the mutual relationship between the customer and the self-employed worker is likely to increase, because

the demands and wishes of the customer are central during the assignment.

Professional appearance

This competency does not deal with the content of the assignment, but with the appearance of the self-

employed worker. A professional appearance includes for instance proper clothing.

Process communication

Process communication includes all communication between the customer and the self-employed worker

about the process. The difference between the previous mentioned customer focus is that process

communication emphasizes on the assignment, while customer focus also takes the relationship into

account. Process communication includes for instance sharing information about the assignment in order

to exchange expectations.

Enthusiasm

The competency enthusiasm measures how dedicated a self-employed worker is towards the assignment

and the customer. This includes for instance an active and flexible attitude.

28

Availability

Availability measures if a self-employed worker is available when a customer needs him or her. When

something goes wrong with the product or service that is delivered by the self-employed workers, it

should be repaired within a short amount of time. This time aspect is the main difference between

availability and the previous mentioned competency enthusiasm.

Professional disposition

In this study, the competency professional disposition measures for instance the motivation of the self-

employed worker to finish the work and his or her working speed.

Proactive mentality

Proactive mentality has some overlap with most of the previous mentioned competencies. In this study,

proactive mentality has interfaces with for instance making concrete appointments and acting reliable.

General satisfaction (dependent variable)

The dependent variable is measured by asking customers directly how they would rate the general

satisfaction about self-employed workers. Furthermore, it is for instance asked if the contact with the self-

employed worker fulfilled the expectation of the customer and if they would recommend the self-

employed worker to other people.

Price/quality ratio

As explained before, the price/quality ratio is not a competency but it was included in the questionnaire to

establish to what extent it influences general satisfaction. This scale is for instance measured by asking

customers if they were satisfied about the price/quality ratio, or if they had the feeling they paid too much

for the services of the self-employed worker.

29

5.3 Results

The data of the quantitative questionnaire is analyzed in SPSS and the competencies that significantly

influence the general impression that is left by self-employed workers is determined. First, a correlation

matrix is showed to express the relationships between the variables. With a regression analysis will be

estimated how the value of the dependent variable (i.e. general satisfaction) will change when the value of

the independent variables (i.e. specific competencies) changes. Second, it is investigated if there is a

difference in the predictor equitation between the two sectors in which self-employed workers operate.

5.3.1 Inter correlations among study variables

Dummy variables were created for several background variables to ascertain their possible relationship

with the dependent variable. The means, standard deviations and Pearson product moment correlations of

the study variables were computed, as depicted in Table 10.

A first inspection of the correlation coefficients shows that four background variables (i.e. sector (r = -

.11), contract duration (r = .11), hired by respondent (r = -.10) and contact with multiple self-employed

workers (r = -.10)) are significantly associated at the .05 level with the general satisfaction of self-

employed workers. If a customer personally hires a self-employed worker, their general satisfaction is

higher. Furthermore, if a customer has contact with multiple self-employed workers, their general

satisfaction about a single self-employed worker is also higher. Remarkable is that the contact frequency

is not significantly associated with the general satisfaction.

Inspection of the correlations between the competencies of self-employed workers and general

satisfaction shows exclusively high correlations at the .01 level (.58 < r < .86). Since hypothesis 1 stated

that all mentioned scales correlate significantly with general satisfaction of self-employed workers, it is

empirically supported. The high mutual correlations are not unique in competency research. The

intercorrelations of Bartram’s (2005) Great Eight Competencies, which was based on > 3300 respondents,

were also relatively high (i.e. .26 < r < .61; average r = .45). Furthermore, King, Hunter and Schmidt

(1980) investigated important behavior of police officers at three points in time. This study also showed

high intercorrelations between the investigated dimensions (i.e. .33 < r < .94; average r = .67)

The competencies empathy (r = .86), proactive mentality (r = .82) and enthusiasm (r = .79) were most

strongly associated with general satisfaction. Other strong associations are customer focus, process

communication and price/quality which all had a correlation coefficient of .71. Overall, it must be noted

that the effects of the competencies on general satisfaction represent a large effect according to the

guidelines of Field (2005).

30

Table 10: Pearson correlation coefficients

#

Mean SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

1 General

satisfaction 4.12 .71 (.92)

2 Report mark 7.53 1.07 .76** (-)

3 Gender

(respondent) - - .04 0,09 (-)

4 Age 46.65 10.27 .00 -0,01 -.08 (-)

5 Gender (SEW) - - .02 0,03 .20** -.03 (-)

6 Sector - - -.11* -0,07 -.03 .10* -.30** (-)

7 Contact

duration 3.81 1.45 .11* 0,08 .01 -.01 .06 -.25** (-)

8 SEW hired by

respondent - - -.10* -0,05 .03 -.21** .19** -.19** .03 (-)

9 Contact

frequency 1.82 1.23 .03 0,02 .00 -.01 .07 -.20** .19** .17** (-)

10 Contact with

multiple SEWs - - -.10* -0,03 .05 .01 -.04 .12** -.19** .04 -.02 (-)

11 Empathy 4.09 .60 .86** .72** .06 -.01 .01 -.10* .12** -.07 .03 -.09 (.87)

12 Customer

focus 3.99 .68 .71** .64** .08 -.01 .01 -.03 .09 -.09 -.05 -.08 .66** (.78)

13 Professional

appearance 3.88 .60 .58** .50** .07 .04 .05 -.11* .09 .00 .01 -.02 .62** .52** (.76)

14 Process

communication 3.78 .62 .71** .61** .10* .00 .06 -.10* .06 -.01 .04 .04 .74** .55** .60** (.82)

15 Enthusiasm 4.11 .63 .79** .66** -.01 -.01 .02 -.11* .06 -.07 .06 -.04 .80** .63** .57** .70** (.85)

16 Availability 3.91 .59 .57** .48** .07 .01 .01 -.03 .13** -.08 -.02 -.06 .58** .48** .38** .50** .49** (.63)

17 Professional

disposition 3.89 .58 .62** .53** .09 .01 .01 -.07 .10* -.08 -.03 -.03 .66** .55** .51** .64** .62** .51** (.66)

18 Proactive

mentality 4.04 .66 .82** .67** .06 .01 .03 -.08 .05 -.07 .05 -.01 .79** .61** .56** .73** .74** .52** .60** (.85)

19 Price/Quality

ratio 3.88 .61 .71** .59** .04 .05 -.02 -.05 .14** -.16** .00 -.09 .73** .56** .45** .59** .67** .50** .60** .65** (.88)

* P < .05 (2-tailed); ** p < .01 (2-tailed)

Cronbach’s alpha values are depicted on the diagonal between brackets.

For the dummy variables: male was coded 0 and female was coded 1. Yes was coded 0 and no was coded 1. A professional in the service industry was coded 0 and a

specialized worker was coded 1. This information is necessary to interpret the direction of the effect in the correlation matrix.

31

5.3.2 Predicting general satisfaction

A hierarchical multiple regression analysis was executed to obtain the relative importance of the

competencies in the prediction of general satisfaction. Because the enter-method relies on good

theoretical reasons for including the chosen predictors (Field, 2005), this method is used to enter all

variables in the multiple regression. Step 1 contains only background variables; the other independent

variables are added in step 2.

Variance Inflation Factors (VIF) of the independent variables were checked and they all met the

guidelines formulated by Myers (1990). However, Bowerman and O’Connell (1990) suggest that an

average VIF greater than 1, may be biasing the regression model through multicollinearity. The

competencies had variance inflation factors ranging from 1.6 until 4.9; therefore, the results should be

interpreted with care. The assumption of independent errors in the regression model was assessed by the

Durbin-Watson test. According to the guidelines of Field (2005), the outcome of the test did not show

reasons for concern.

The amount of variance in the outcome explained by the model in step 1 is very low (R² = .04). Step 2

shows a R² of .82 indicating a much higher amount of variance that is explained by the model (∆R² = .78;

p < .01). The regression between background variables as predictors and general satisfaction as outcome

shows that only SEW hired by respondent makes a significant contribution (p < .05) to the prediction

equation. However, when the competencies and the price/quality ratio are included in the regression

equation, this contribution is not significant anymore. Furthermore, it was remarkable that there were no

significant differences between self-employed workers who work as a professional in the service industry

and specialized workers.

Statistically significant predictors were (mainly) found in the competencies of self-employed workers.

Table 11 depicts that empathy is the strongest predictor of general satisfaction (β = .32; p < .01). This

means that if the empathy of the self-employed worker towards the customer increases, the general

satisfaction of the customer about the self-employed worker is also likely to increase. The second

strongest predictor was a proactive mentality (β = .27; p < .01). Other significant predictors were

customer focus, enthusiasm and the price/quality ratio. The regression results suggest that the other

competencies do not make a significant contribution to the prediction equation. Hence, it was remarkable

that the price/quality ratio was not the strongest predictor of general satisfaction. According to the

hierarchical multiple regression analysis, it was more important to possess the crucial competencies. The

competency professional disposition showed a negative β coefficient. The reversed sign could be

explained by a suppression effect, which denotes instances when the “true” relationship between the

dependent and independent variable is hidden in the correlation matrix (Hair et al., 2006). Due to the

addition of competencies in the regression analyses, multicollinearity was induced and some unwanted

shared variance might be explained by the other competencies. The remaining unique variance was

explained by professional disposition which caused the negative sign. However, the negative relationship

with general satisfaction was not significant; therefore it will not be further discussed.

32

Table 11: Hierarchical multiple regression analysis

Variables B SE B β Variables B SE B β

Step 1

Step 2

Gender (respondent) .08 .08 .05

Gender (respondent) -.01 .04 -.01

Age .00 .00 -.01

Age .00 .00 .00

Gender (SEW) -.02 .12 -.01

Gender (SEW) -.01 .05 .00

Sector -.14 .08 -.10

Sector -.03 .03 -.02

Contact duration .04 .03 .08

Contact duration .00 .01 .01

SEW hired by respondent -.25 .10 -.13*

SEW hired by respondent -.05 .05 -.02

Contact frequency .01 .03 .01

Contact frequency .00 .01 .00

Contact with multiple SEWs -.10 .07 -.07

Contact with multiple SEWs -.05 .03 -.04

Empathy .38 .06 .32**

Customer focus .17 .03 .16**

Professional appearance .00 .03 .00

Process communication .03 .04 .02

Enthusiasm .17 .05 .15**

Availability .05 .03 .04

Professional disposition -.03 .04 -.03

Proactive mentality .29 .04 .27**

Price/Quality ratio .09 .04 .08*

R² .04

R² .82

Adjusted R² .02

Adjusted R² .82

∆ R² .78**

Regression F 2.07*

Regression F 104.63**

Degrees of Freedom 8 / 388

Degrees of Freedom 17 / 379

* p < .05; ** p < .01; N = 397

B = regression coefficient; SE B = standard error of regression coefficient; β = standardized regression coefficient

In sum, no background variables made a significant contribution to the prediction equation. The only

competencies that significantly relate to general satisfaction are empathy, customer focus, enthusiasm and

proactive mentality (p < .01). The price/quality ratio shows a small standardized effect size at predicting

general satisfaction (β = .08; p < .05).

Hypothesis 2 stated that the competency components Building Rapport, Projecting Credibility, Targeting

Communication, Communicating Proactively, Taking Responsibility and Working Energetically and

Enthusiastically are the best predictors for general customer satisfaction. Since the items of the

questionnaire are no longer categorized according to the Great Eight, it is impossible to confirm or reject

this hypothesis.

5.3.3 Testing for mediating effects

Since not all competencies contributed significant to the regression equitation, it is investigated if they

may have a mediating relationship with the general satisfaction. Baron and Kenny (1986) subscribed four

steps to test a mediation effect (see Figure 7). The relationships should be tested between: the independent

33

and the dependent variable (c), the independent variable and the mediator (a) and the mediator and the

dependent variable (b). If all these relationships are significant, the relationship between the independent

and the dependent variable should be tested again while controlling for the mediator (i.e. test c while

controlling for b). If the relationship (c) becomes smaller but significant, there is strong statistical

evidence for a mediating effect.

Figure 7: The mediating effect

The steps to establish mediation formulated by Baron and Kenny (1986) were executed with the

competencies professional appearance, process communication, availability and professional disposition

as independent variables and the competencies empathy, customer focus, enthusiasm and proactive

mentality as mediator. The four steps were met for all mentioned relationships which indicates that there

are mediating effects as depicted in Figure 8. In addition, a Sobel test3 is executed to check if the

mediating mechanism is significantly different than zero. The formula that is used for the Sobel test is: Z-

value � ���������������

where a and b are path coefficients and ��= standard error of a and ��= standard

error of b. Since the values were all > 1.96, the mediator carried the influence of the independent

variables to the dependent variables.

Figure 8: Competencies with a direct and indirect influence on general satisfaction

3 An example of the exact calculation of the Sobel test is included in Appendix VII.

34

Although the method of Baron and Kenny (1986) showed that empathy, customer focus, enthusiasm and

proactive mentality mediate the effect from professional appearance, process communication, availability

and professional disposition to general satisfaction, it was also tested the other way around in Table 12.

This test was executed to validate the model by showing if the competencies could also be ordered in a

different way. The left side of the table depicts the mediators and independent variables that are equal to

the model of Figure 8; the right side of the table depicts the independent variables as mediators and the

mediators as independent variables. Per mediator were four tests executed to determine the decrease of

path coefficients in path c. To summarize the effect, the average decrease in path c of the four mentioned

independent variables were calculated and depicted in Table 12. The results of the test clearly showed that

the average decrease in path coefficients in path c is larger on the left side of the table compared to the

right side, which means that a model with empathy, customer focus, enthusiasm and proactive mentality

as mediators has a better fit to the data compared to a model with professional appearance, process

communication, availability and professional disposition as mediators. All Z-values of the Sobel test were

significant at the p < .01 level, indicating a mediating mechanism that is significantly different than zero.

Table 12: Testing the best mediators

Mediator Average decrease

in path c*

Average

Z-value***

Mediator Average decrease

in path c**

Average

Z-value***

Empathy .60 13.6 Professional

appearance .11 4.7

Customer

focus .33 9.1

Process

communication .27 7.7

Enthusiasm .46 11.1 Availability .11 5.3

Proactive

mentality .49 15.6

Professional

disposition .14 5.3

* For the independent variable, the competencies professional appearance, process communication, availability and

professional disposition were used; ** For the independent variable, the competencies empathy, customer focus,

enthusiasm and proactive mentality were used; *** Significant at the p < .01 level.

Table 13 depicts the results of a test with multiple mediators. When professional appearance, process

communication, availability and professional disposition were used as mediators (right side of the table),

there was only a relatively small decrease of path coefficients in path c. On the other hand, when

empathy, customer focus, enthusiasm and proactive mentality were used as mediators (left side of the

table) the decrease of path coefficients was much larger. Moreover, in the right side of Table 13, the

mediators decreased the total effect of the independent variables to a non-significant level which indicates

full mediation. In addition, one of the conditions for testing mediation is a significant coefficient for path

b at the p < .05 level. With professional appearance, process communication, availability and professional

disposition as mediators, not all path coefficients of path b were significant. Again, this confirms the

model that is depicted in Figure 8.

35

Table 13: Testing mediating effect with multiple mediators

Independent

variable Mediators*

Decrease

in path c

Z-

value**

Independen

t variable Mediators*

Decrease

in path c

Z-

value**

Professional

appearance

Em-CF

En-PM . 68�� 14.9 Empathy

PA-PC

Av-PD . 23� 5.4

Process

communication

Em-CF

En-PM . 80�� 17.8

Customer

focus

PA-PC

Av-PD . 37� 10.8

Availability Em-CF

En-PM . 63�� 13.4 Enthusiasm

PA-PC

Av-PD . 35� 9.1

Professional

disposition

Em-CF

En-PM . 76�� 16.1

Professional

mentality

PA-PC

Av-PD . 30� 8.3

* PA = Professional appearance; PC = Process communication; Av = Availability; PD = Professional disposition; Em =

Empathy; CF = Customer focus; En = Enthusiasm; PM = Professional mentality.

** Significant at the p < .01 level; † = partial mediation; †† = full mediation

5.3.4 Explaining the relationships among the variables

The structures of the interrelationships were examined on latent variable level using Structural Equation

Modeling (SEM). Due to the SEM technique, the estimates were computed using all of the information

from all equations that made up the model (Hair et al., 2006). In other words, SEM examines a series of

dependence relationships simultaneously which is particular useful in the model of this study because

some competencies (i.e. mediators) become independent in subsequent dependence relationships. The

scale averages of the variables were used as latent variables in the model. This resulted in approximately

the same regression coefficients as depicted in Table 11.

The measurement model validity can be estimated by goodness-of-fit indices and sufficient evidence of

construct validity. According to Hair et al. (2006), reporting the χ² value and the degrees of freedom, the

CFI and the RMSEA provide sufficient unique information to evaluate a model. The χ² (chi-square) test

provides a statistical test of the difference between the observed and the estimated covariance matrices.

The degrees of freedom represent the amount of mathematical information available to estimate model

parameters. In general, χ²:df ratios on the order of 3:1 or less are associated with better-fitting models

(Hair et al., 2006). The Comparative Fit Index (CFI) is an incremental fit index that is normed so that

values range between 0 and 1, with higher values indicating better fit. CFI values higher than .90 are

usually associated with a model that fits well. The Root Mean Square Error of Approximation (RMSEA)

is an absolute fit measure that tests how well the model reproduces the observed data. Lower RMSEA

values indicate better fit and typically values are below .10 for acceptable models (Hair et al., 2006).

In a model that includes all 9 variables (see Appendix VIII), the path coefficients from the mediators to

general satisfaction are .46 for empathy, .18 for customer focus, .19 for enthusiasm and .30 for proactive

mentality (all significant at the p < .01 level). The χ² value = 330.81; df = 10; CFI = .91 and RMSEA =

.29. Total amount of variance in general satisfaction explained by the model was .79. Although the CFI

value of the model was acceptable, the other fit indices were not. Therefore, it was decided to split the

overall model into four separate models where every mediator was predicted by four competencies. Using

this approach, the main competencies for predicting the mediator could be established. The corresponding

path coefficients and fit indices are depicted in Table 14. Again, the RMSEA values were above .10,

suggesting that the model is not acceptable. However, a quite large amount of variance (i.e. between .43

and .67) in the mediators was explained by the competencies. Furthermore, the model showed that all

36

competencies were approximately equally important in predicting the mediators, because most path

coefficients of the indirect variables to the mediator had a maximum range of .10. Two indirect variables

(i.e. process communication with customer focus as mediator and availability with enthusiasm as

mediator) showed lower values compared to the other predictors, but modification indices were suggested

to improve the fit of these models. First, with customer focus as mediator, it was suggested to add the

path from process communication to general satisfaction. This path had a coefficient of .46 and decreased

the χ² value to 37.58 with 3 degrees of freedom (CFI = .97; RMSEA = .17). Since ∆χ² was 140.75 and

∆df was 1 (p < .01), the model showed significant improvement. Second, with proactive mentality as

mediator, it was suggested to add the path from availability to general satisfaction. This path had a

coefficient of .24 and decreased the χ² value to 44.44 with 3 degrees of freedom (CFI = .97; RMSEA =

.19). Since ∆χ² was 33.47 and ∆df was 1 (p < .01), this revised model also showed significant

improvement.

Table 14: Path coefficients and fit indices

* Values depict path coefficients from mediator to general satisfaction

The values of Table 14 indicate that the proposed models do not fit adequately to the data. However, this

may be declared because the models were tested on “latent level”. If the models would have been tested

by including all observed variables, it is likely to assume that the fit indices demonstrate a better fit of the

models. To amplify this assumption, the observed variables were included to test the full model again.

This resulted in a χ² value of 1238.80 with 603 degrees of freedom (p < .01), a CFI of .99 and a RMSEA

of .05. These fit indices demonstrate a good fit of the full model. Hence, the suggested model that is

depicted in Figure 8 is supported by the data. However, according to Hair et al. (2006), SEM is not used

to obtain a good fit, but to test a theory. Therefore, the above mentioned model is not necessarily the only

approach to predict general satisfaction.

Model I Model II Model III Model IV

Mediators

Empathy Customer

focus Enthusiasm

Proactive

mentality

Indirect variables

Professional appearance .21 .22 .17 .14

Process communication .39 .18 .41 .46

Availability .21 .20 .11 .16

Professional disposition .19 .22 .21 .15

General Satisfaction * .86 .71 .79 .82

Amount of variance explained in mediator

(by independent variables) .67 .43 .57 .59

Amount of variance explained in general

satisfaction (by mediator) .73 .50 .63 .67

χ² 30.86 178.32 96.83 77.91

Degrees of freedom 4 4 4 4

CFI .98 .86 .93 .95

RMSEA .13 .33 .24 .22

37

5.3.5 Comparison between two sectors

Because Keurwerk has the intention to implement the final instrument in large market, it is important to

establish if there is a difference in the crucial competencies between professionals in the service industry

and the specialized workers. For each kind of workers (i.e. 156 professionals in the service industry and

241 specialized workers), a hierarchical multiple regression is executed to discover if there are differences

in the prediction equitation. Assumptions about linearity and normally distributed errors were checked

graphically for both sectors and met the guidelines formulated by Field (2005).

Table 15: Hierarchical multiple regression analysis for professionals in the service industry

Variables B SE B β Variables B SE B β

Step 1

Step 2

Gender (respondent) .01 .13 .01

Gender (respondent) .00 .06 .00

Age .01 .01 .09

Age .00 .00 .00

Gender (SEW) -.08 .14 -.05

Gender (SEW) -.02 .06 -.01

Contact duration -.01 .05 -.02

Contact duration -.03 .02 -.05

SEW hired by respondent -.32 .14 -.20*

SEW hired by respondent -.06 .06 -.04

Contact frequency -.05 .05 -.09

Contact frequency .01 .02 .02

Contact with multiple SEWs -.09 .12 -.06

Contact with multiple SEWs -.08 .05 -.05

Empathy .44 .09 .37**

Customer focus .18 .05 .17**

Professional appearance .07 .05 .07

Process communication .04 .07 .03

Enthusiasm .11 .07 .10

Availability .01 .05 .01

Professional disposition -.03 .06 -.02

Proactive mentality .30 .07 .27**

Price/Quality ratio .07 .06 .06

R² .08

R² .85

Adjusted R² .03

Adjusted R² .83

∆R² .77**

Regression F 1.75

Regression F 49.17**

Degrees of Freedom 7 / 148

Degrees of Freedom 16 / 139

* p < .05; ** p < .01; N = 156

B = regression coefficient; SE B = standard error of regression coefficient; β = standardized regression coefficient

The hierarchical multiple regression analysis for professionals in the service industry of Table 15 shows a

large amount of consensus with Table 11. In both prediction equitation’s, no background variables have a

significant relation with the general satisfaction. The order and magnitude of the significant predictor

competencies is also comparable. However, enthusiasm is no longer a significant competency to predict

general satisfaction among professionals in the service industry.

38

Table 16: Hierarchical multiple regression analysis for specialized workers

Variable B SE B β Variable B SE B β

Step 1

Step 2

Gender (respondent) .11 .11 .07

Gender (respondent) .00 .05 .00

Age .00 .00 -.04

Age .00 .00 .00

Gender (SEW) .03 .24 .01

Gender (SEW) .01 .11 .00

Contact duration .06 .03 .13

Contact duration .02 .01 .05

SEW hired by respondent -.13 .16 -.05

SEW hired by respondent -.04 .07 -.02

Contact frequency .05 .04 .08

Contact frequency .01 .02 .01

Contact with multiple SEWs -.09 .10 -.06

Contact with multiple SEWs -.03 .04 -.02

Empathy .34 .08 .29**

Customer focus .18 .05 .17**

Professional appearance -.08 .05 -.07

Process communication .02 .06 .02

Enthusiasm .22 .07 .19**

Availability .09 .05 .07

Professional disposition -.06 .05 -.04

Proactive mentality .29 .06 .28**

Price/Quality ratio .10 .06 .09

R² .04

R² .82

Adjusted R² .01

Adjusted R² .80

∆R² .78**

Regression F 1.35

Regression F 62.35**

Degrees of Freedom 7 / 233

Degrees of Freedom 16 / 224

** p < 0.01; * p < 0.05; N = 241

B = regression coefficient; SE B = standard error of regression coefficient; β = standardized regression coefficient

Table 16 depicts the hierarchal multiple regression analysis for specialized workers. The results show

identical significant predictors for general satisfaction compared to the total sample of self-employed

workers.

Hypothesis 3 states that predictors of general customer satisfaction are independent of the self-employed

worker’s field. This hypothesis is partly rejected, because enthusiasm is not a significant predictor of

general satisfaction among professionals in the service industry. However, the predictor equitation’s show

a large amount of similarity in order and magnitude between the two groups of workers and the self-

employed workers in general. Moreover, the hierarchical multiple regression analysis with both groups of

self-employed workers (depicted in Table 11) did not show significant differences between the two

sectors.

39

5.3.6 Underlying characteristics of competencies

The results of the analyses of the previous sections showed that the competencies empathy, customer

focus, enthusiasm and proactive mentality have a direct influence on general customer satisfaction.

Furthermore, these four competencies also mediate between general satisfaction and the competencies

professional appearance, process communication, availability and professional disposition. This section

determines if there are overlapping characteristics that appear in the mediators4, but not in the

independent variables5 or vice versa.

Competency model of Bartram (2005)

Three out of the four mediators (i.e. empathy, customer focus and proactive mentality) can be categorized

in the same competency dimension (i.e. working with people) of Bartram’s (2005) great eight competency

model. The final mediator (i.e. enthusiasm) can be categorized in the competency component “working

energetically and enthusiastically”. The independent variables are more dispersed throughout the great

eight competency model. The four independent variables all fit into the definition of Kurz and Bartram

(2002) because they measure individual differences in terms of specific work related constructs that are

relevant to successful job performance. However, three independent variables (i.e. professional

appearance, availability and professional disposition) cannot be categorized into only one category of

Bartram’s (2005) great eight competency model, because the items in the independent variables are too

dispersed. Furthermore, the independent variable process communication can be categorized in the

competency dimension “presenting and communicating information”. In sum, the great eight competency

model does not contain one competency domain in which all mediators or independent variables can be

categorized. Therefore, other competency definitions and models from literature were analyzed in order to

find underlying concepts of the mediators and independent variables. The results of this analysis are

depicted in Table 17.

Competency model of Hoekstra and van Sluijs (2003)

Hoekstra and van Sluijs (2003, p. 30) defined a competency as: “The ability to perform effectively in a

specific task situation or in a specific problem situation.” They express this definition in the following

formula:

Effective performance in a situation =

[knowledge + experience + understanding] x [behavior + attention + emotion].

In other words: a competency = expertise x behavior repertoire. With behavior repertoire is meant that an

individual’s availability of behavior, attention and emotion are needed in a variety of situations. Although

expertise and behavior repertoire are both needed to define a competency, the eight self-defined

competencies in this study show more overlap with behavior repertoire. Therefore, the competency

definition of Hoekstra and van Sluijs (2003) can also not be used to find underlying concepts of the

mediators and independent variables.

4 The mediators refer in this section to the competencies empathy, customer focus, enthusiasm and proactive

mentality. 5 The independent variables refer in this section to the competencies professional appearance, process

communication, availability and professional disposition.

40

Competency model of Roe (2002)

Roe (2002, p. 206) defines a competency as: “The ability to execute a task, role or mission adequately”.

This definition has two main characteristics that deviate from other definitions. First, a concrete activity

should be accomplished to reach a result. This activity should contribute to the organizational goals and

generate value for the organization. This is a major difference with the definition of Hoekstra and van

Sluijs (2003) who state that every activity can be a competency, even general characteristics of

individuals. Second, competencies are not a synonym for knowledge or ability. According to Roe (2002),

competencies are always “integrating” with the knowledge that is learned before. This means that an

individual should merge his previously gained knowledge and ability to perform new tasks. Roe (2002)

has composed a model that indicates how competencies are related to other personality characteristics and

is depicted in Figure 9.

Figure 9: The architecture model of competencies (Roe, 2002)

The “building blocks” sub competency and competency that are depicted at the top of Figure 9 are most

relevant for this study. Sub competencies are pieces of the end competency that should be learned first.

According to Roe (2002) these sub competencies differ from competencies in a way that they are needed,

but do not contribute to organizational goals. The sub competency professional disposition is for instance

needed for several other competencies but cannot be seen as an individual competency. In Table 17, all

eight self-defined competencies are categorized into the model of Roe (2002). If the majority of the items

of a self-defined competency were not concrete activities, the self-defined competency was categorized as

a sub competency.

Competency model of Spencer and Spencer (1993)

Spencer and Spencer (1993, p. 9) define a competency as: “an underlying characteristic of an individual

that is causally related to criterion-referenced effective and/or superior performance in a job or

situation.” Most of the previous mentioned authors see knowledge, skills and ability as factors that

muddle the definition of a competency. Therefore, they agree that for superior performance knowledge,

skills and ability are needed in parallel to the competency. Spencer and Spencer (1993) define besides

41

knowledge and skills also motives, traits and self-concept as underlying characteristics for competencies.

Figure 10 depicts how these underlying characteristics relate to each other. According to Spencer and

Spencer (1993), the surface knowledge and skill competencies are easier to develop compared to the core

competencies. The self-defined competencies of Table 17 that are relatively hard to develop and also

related to personality are categorized as hidden competencies. The mediator enthusiasm deals for instance

with someone’s personality which is hard to develop. Therefore, enthusiasm was categorized as hidden

competency. In contrast, the independent variable professional disposition is relatively easier to develop;

therefore it was categorized as visible competency.

Figure 10: Underlying characteristics of competencies (Spencer and Spencer, 1993)

Overview of findings

The previous paragraphs showed that competencies are subjected to interpretation and could be defined in

multiple ways. The competency model of Hoekstra and van Sluijs (2003) did not show any differences in

underlying characteristics between the mediators and independent variables. The competency model of

Roe (2002) showed that three out of four mediators could be categorized as a sub competency. However,

also two of the independent variables could be categorized as sub competency. Therefore, this

competency model did not provide more insight in the underlying characteristics. The final competency

model that was analyzed was the competency model of Spencer and Spencer (1993). It was remarkable

that all independent variables could be categorized as visible competencies. However, also two of the

mediators could be categorized as visible competencies. Therefore, it can be concluded that the three

competency models did not provide unique underlying characteristics that distinguish between

independent variables and mediators.

42

Table 17: Underlying characteristics of competencies

Competencies

Competency models

Hoekstra and

van Sluijs (2003) Roe (2002)

Spencer and

Spencer (1993)

Behavioral Expertise Competency

Sub Visible Hidden

repertoire competency

Mediators

Empathy x

x

x

Customer focus x

x x

Enthusiasm x

x

x

Proactive mentality x

x

x

Independent variables

Professional appearance x

x x

Process communication x

x

x

Availability x

x

x

Professional disposition x

x x

In addition to the statistical proof of the relationship between the independent variables and the mediators,

some examples of the theoretical relationships will now be discussed. The examples start with aspects of

the independent variable. Next, it is discussed how this might be related to the mediator.

Example 1: availability as independent variable.

The independent variable availability contains for instance a response within 24 hours when the customer

needs it. This might increase the mediators empathy and customer focus, because the customer might feel

special due to the fast response to their problems. Moreover, availability might increase the confidence in

a self-employed worker, which also affects empathy. Furthermore, a self-employed worker who is

available might be interpreted as enthusiastic. Finally, the mediator proactive mentality contains items

that deal with making appointments and contacting the customers if an assignment is not finished on time.

It is likely that frequent available self-employed workers have a positive influence on this mediator.

Example 2: process communication as independent variable.

The independent variable process communication contains for instance discussing expectations and

exchanging information about the assignment with the customer. Due to the communication, it is likely

that the empathy increases, because communication might increase the collaboration. In addition,

customer focus might be increased because the self-employed worker listens to what a customer really

wants. A self-employed worker who communicates frequently with the customer and shares information

might be interpreted as a self-employed worker who thinks actively along with the customer. Therefore,

process communication might positively influence the mediator enthusiasm. Finally, the mediator

proactive mentality contains self-employed workers who contact the customer when an assignment is not

finished on time. The independent variable process communication might contribute to this

communication.

43

6 Implementation

The final phase of the master thesis project is the design of the validated instrument. The questions that

had the highest association with the dependent variable are selected to use in this final instrument. The

statistical instrument offers an independent judgment about the self-employed worker according to their

competencies.

6.1 Introduction

Keurwerk has the intention to formulate two different versions of the final instrument. The biggest

difference between the two is the number of respondents that will be realized. The first instrument is

called the “personal version”, and can be bought by paying a registration fee. The “personal version”

includes the questionnaire and advice about the competencies of the self-employed workers. The

respondents of the “personal version” have to be recruited by the self-employed worker. The second one

is called “professional version” and guarantees on top of the advice a certain number of respondents for

the questionnaire. The guaranteed number of respondents will be realized by making phone calls to

customers of the self-employed workers. For the professional version, customers and invoices will be

checked in order to increase the reliability of the study. By law, a self-employed worker is forced to

number all his invoices. To make sure that there is a complete overview of the sample size, all numbers

on the invoices have to be checked. According to the sequence of the numbers, it can be secured that all

relevant customers receive an invitation for the questionnaire. It is not necessary that all customers join

the questionnaire, but by knowing the whole population there is a better insight in the sample. As a result,

a validated advice can be provided and the self-employed workers can refer to this while recruiting new

customers. The “professional version” will be provided to self-employed workers for a higher registration

fee.

6.2 Final instrument

The final instrument is included in Appendix IX and is a condensed version of the questionnaire that was

sent to the customers of self-employed workers. All questions are classified per scale in the appendix,

whereas they will be asked at random to customers, to prevent respondent bias. The implementation of the

questionnaire will be realized by Keurwerk and they become the owner of the instrument.

Table 18 depicts the means and standard deviations per variable. These values can serve as guidelines for

the feedback that would be provided to self-employed workers. Statistically, 68% of the self-employed

workers should be rated ± one standard deviation from the mean. In practice, the values obtained could be

interpreted as follows: if self-employed workers “score” above the mean, there is no need to worry about

the corresponding scale. If they are on average rated more than one standard deviation below the mean of

a particular competency, there is need for concern because they belong to the lower 16% of the

corresponding competency. The unmarked competencies of Table 18 do not predict general satisfaction

directly. The competency enthusiasm is not a significant predictor for general satisfaction in the service

industry. The sum of the number of professionals in the service industry and specialized workers is 397

instead of 400, because three respondents did not mention in which sector the self-employed worker was

working.

44

Table 18: Means and Standard Deviations per sector

Variables All self-employed

workers *

Professionals in the

service industry **

Specialized

workers ***

Mean SD Mean SD Mean SD

Report mark 7.53 1.07 7.62 1.09 7.47 1.05

General satisfaction 4.12 .71 4.22 .70 4.07 .71

Empathy † 4.09 .60 4.17 .59 4.04 .59

Customer focus † 3.99 .68 4.01 .67 3.97 .68

Professional appearance 3.88 .60 3.96 .65 3.83 .57

Process communication 3.78 .62 3.86 .59 3.74 .63

Enthusiasm †† 4.11 .63 4.20 .63 4.06 .62

Availability 3.91 .59 3.93 .61 3.90 .57

Professional disposition 3.89 .58 3.95 .59 3.86 .57

Proactive mentality † 4.04 .66 4.11 .64 3.99 .68

Price/quality ratio 3.88 .61 3.92 .61 3.86 .60

* N = 400; ** N = 156; *** N = 241; † Significant predictor of general satisfaction; †† Significant predictor,

except for specialized workers.

6.3 Recommendations for self-employed workers

Although the final advice for self-employed workers will be given by Keurwerk, this section provides

recommendations for self-employed workers according to the analyses.

The correlation matrix of Table 10 indicates that all competencies correlate significant with general

satisfaction. According to Murphy, Jako and Anhalt (1993), the inflated correlations among rating

dimensions may be due to the influence of a general evaluation on specific judgments. When a self-

employed worker is rated on multiple performance dimensions, the customer’s overall satisfaction or

evaluation is thought to strongly influence ratings of specific attributes; this phenomenon is referred to as

halo effect or halo error (Murphy et al., 1993). Nisbett and DeCamp Wilson (1977, p. 250) define the halo

effect as: “the influence of a global evaluation on evaluations of individual attributes of a person” Thus,

if a customer likes a self-employed worker, they often assume that those attributes of the self-employed

worker about which they know little are also favorable. The analyses in this study show that there are four

competencies that significantly predict general satisfaction. However, the other competencies may

contribute indirectly to the general satisfaction due to the possibility of halo error. Once customers have a

positive impression of a self-employed worker, they may not distinguish between the competencies

anymore. Therefore, it may be advantageous to perform extremely well on one or two competencies to

cause a positive impression. Since empathy and a proactive mentality are the best predictors of general

satisfaction, these competencies would have priority in this respect. However, it is recommended to focus

on all competencies, including the competencies that do not influence the general satisfaction directly.

After the online questionnaire was filled in by customers, they had the opportunity to write down

comments about the questionnaire or the self-employed worker they had in mind. One of the comments

that confirm the above recommendation was: “The self-employed worker I have in mind is not always

45

strictly in deadlines, but is very creative, open and agreeable. Therefore, I accept her disorganized

behavior and keep it in mind for my own planning”. Because this self-employed worker performs very

well on several competencies, it compensates her lack in planning. Another comment from a respondent

was: “This self-employed worker shows arrogance in his communication. However, his work is always

finished in time and fulfills my demands”. Hence, the questionnaire was mainly filled in positive and the

respondent gave the self-employed worker an 8. Again, this example emphasizes that only one negative

competency does not always cause dissatisfied customers, provided that this competency can be

compensated. One of the respondents gave the self-employed worker on average a 6 and wrote down:

“Because this self-employed worker had to run the business on his own, he was answering phone calls

from other customers all the time which was very annoying”. Unfortunately, this respondent did not

mention anything about the performance of the self-employed worker. Although the 6 is still sufficient, it

was below average. It is likely to assume that answering phone calls affected multiple competencies (e.g.

customer focus, enthusiasm and availability). Taking into account the earlier mentioned recommendation,

the grade might be higher if the self-employed worker compensated his annoying behavior with other

competencies. However, the best solution might probably be switching off the phone to prevent the

annoying behavior!

The small bars at the top of Figure 11 depict the means and standard deviations per competency based on

the questionnaires of 400 respondents. This figure can form the basis for feedback that is going to be

provided to self-employed workers. The red, orange and green colored bars are an example of how a

particular self-employed worker may score on the different competencies. If the average score is above

average, the bar is colored green and there is no need to worry about the corresponding competency. If the

average score is between the mean and one standard deviation, the bar is colored orange indicating that

this competency might be improved. Finally, a red colored bar means that the score on the corresponding

competency is more than one standard deviation below the mean; these competencies are reason for

concern and definitely need to be improved.

Figure 11: Example of a feedback graph

* Competency influences general satisfaction directly

46

The right side of Figure 11 depicts the general satisfaction score with a more specific method of providing

feedback called “Stanine”. Stanine scores are normalized standard scores that range between one and nine

with a mean of five and a standard deviation of two. (Freed, Hess and Ryan, 2002). The relationship

between the Stanine scores and the normal distribution is depicted in Table 19. A limitation to Stanine is

that the data should be normally distributed. The data of this study is not perfect normally distributed,

because more than 4% of the respondents gave the maximum score of five to self-employed workers.

Therefore, the categories stanine 8 and stanine 9 are the same in this study. Although the implementation

of the instrument is executed by Keurwerk, it is recommended to use the Stanine scores since they

provide a simple way to describe customers’ achievement.

Table 19: Relationship between stanine scores and normal distribution

Stanine Percentiles included Questionnaire scores Description

9 96 - 99 4.84 – 5.00 very high

8 89 - 95 4.84 – 5.00 high

7 77 - 88 4.51 – 4.83 quite high

6 60 - 76 4.18 – 4.50 above average

5 40 - 59 3.84 – 4.17 average

4 23 - 39 3.68 – 3.83 below average

3 11 - 22 3.18 – 3.67 quite low

2 4 - 10 2.18 – 3.17 low

1 1 - 3 1.17 – 2.17 very low

The example of Figure 11 depicts that a particular self-employed worker has the lowest average score on

the competency empathy. According to Hoekstra and van Sluijs (2003), empathy includes showing in

contact with others that feelings, attitude and motivation of the other are understood. Furthermore, by

showing empathy the own influence on other people is taken into account. Table 20 provides suggestions

for self-employed workers in order to increase their empathy towards customers. Note that the

recommendations are based on the BEI’s and give just an indication how to improve the corresponding

competency. Due to the possible halo effect in the results, the suggestions that are mentioned may also be

applied to increase other competencies. The first column of Table 20 depicts suggestions that are based on

questions that are included in the final instrument. The second column depicts behavior (in random order

of importance) that was mentioned in the BEI’s but was not included in the quantitative questionnaire.

Table 20: Suggestions to improve Empathy

Behavior of self-employed worker Suggestions for improvement

Being honest towards the customer

Stick to your appointments; Inform the customer if a target of

deadline is postponed; Execute what has been promised; Inform

the customer beforehand about possible uncertainties in the

assignment.

Inspire confidence to the customer

Start as soon as possible with the assignment; Show

perseverance; Be loyal towards the customer even during a short

collaboration. Be faithful to a customer.

Coming to a result by collaborating

with a customer

Be involved in a customer; Think along to develop new insights;

Be flexible to get on with; Take initiative without

communicating with the customer about every detail; Adjust to

the customer’s need.

47

Being agreeable towards a customer

in order to create a mutual

connection

Be polite towards the customer; Show flexibility to adjust to the

profile of the initiator; Show certain amount of humor; Try to

discover how the customer thinks about issues; Act relaxed in

order to communicate in an attractive way; Show social

capabilities.

It is difficult to provide a minimal sample size that has to be collected in order to obtain accurate results,

because the calculation depends on unknown numbers and factors. One of the unknown numbers is the

size of the entire population. In this case, it is assumed that the entire population is equal to the number of

customers that a self-employed worker could theoretically have. Because this number can vary between a

very small number of potential customers until more than 1000, the range of the required sample size

varies accordingly. Furthermore, also other factors like for instance the confidence interval (i.e. margin of

error) and the confidence level should be defined. According to Bartlett, Kotrik and Higgins (2001), there

are different options to calculate a sample size. The following formula is defined by Cochran (1977) and

is used as a guideline to estimate an appropriate sample size for the final instrument:

�� � ������������� where t = value for selected alpha level; s = estimate of standard deviation in the

population; d = acceptable margin of error for mean being estimated. If the sample size exceeds 5% of the

population, Cochran’s (1977) correction formula should be used to calculate the final sample size. The

formula for the correction calculation is: � � ���� �� !"#$%&!��

Cochran’s (1977) formula is used for an assumed entire population of 100 with:

t = 1.96 (based on an alpha level in each tail of .025)

s = .63 (based on the average standard deviation of the quantitative questionnaire)

d = .15 (based on the guidelines of Bartlett et al., 2001)6

As a result, the minimum returned sample size should be 40. So, if 40 customers provide information

about a self-employed workers competencies, and this self-employed worker has 100 customers in total,

his or her true score will be within the obtained score ± .15 with a probability of 95 percent. Furthermore,

the response rate should also be taken into account. If the response rate is for instance predicted to be

50%, at least 80 customers (i.e. number of customers divided by response rate) should be asked to fill in

the questionnaire to obtain the 40 respondents. Note that this is just a guideline for the required sample

size, because the calculation depends on several unknown factors that vary per self-employed worker. As

explained earlier, one of these factors is the number of customers a self-employed worker has. If a self-

employed worker has only a small number of customers (e.g. < 10) who are all willing to participate in

the study, the instrument is still unable to generalize the results to the behavior of a self-employed worker.

In other words, a sample size of 10 is too small to give a reliable advice to self-employed workers about

their competencies. According to Somekh and Lewin (2005), correlation studies were the relationships

between particular characteristics are investigated should at least contain 30 participants.

6 The value of d is calculated by multiplying the number of points on primary scale (5) by the acceptable margin of

error (.03). The value of the acceptable margin of error is based on a general rule in social research (Krejcie &

Morgan, 1970).

48

7 Discussion

This chapter starts with providing an overview of the results and the relationships that were found

between the variables. Formulating an instrument to measure competencies was the main goal of this

master thesis project. Therefore, only recommendations related to implementing the instrument into the

market are provided in section 7.2. Finally, section 7.3 discusses the limitations of the study, followed by

suggestions for further research.

7.1 Overview of the results

The purpose of the study was to investigate which competencies of self-employed workers influence the

general satisfaction of customers. Contrary to what was expected, there was no single competency that

mainly predicted general satisfaction. In addition, there were also no investigated competencies that could

be neglected because they did not have an influence on general satisfaction. The objective of this study

was to answer the research question: “which competencies of self-employed workers significantly

influence the general impression of customers and are quantitatively measurable?” The results of the

research show a significant influence of the competencies empathy, customer focus, proactive mentality

and enthusiasm.

The correlation analysis supported the first hypothesis in showing that all mentioned scales correlated

significantly with general satisfaction of customers. It must be noted, however, that the possibility of halo

error may had an influence on the results. Because respondents may have on forehand certain (positive or

negative) thoughts about the self-employed worker, they may not distinguish between the competencies

anymore. Hence, positive thoughts may have resulted in positive overall assessments independent of the

competency and vice versa.

Hypothesis 2 mentioned six competency components as best predictors for general customer satisfaction

i.e. Building Rapport, Projecting Credibility, Targeting Communication, Communicating Proactively,

Taking Responsibility and Working Energetically and Enthusiastically. Based on the factor analysis -

which revealed other scales- it was decided not to use the predefined scales of Bartram (2005), but to

compose self-made scales. As a result, hypothesis 2 could not be confirmed or rejected. The Critical

Incidents were categorized by three independent raters, while the outcome of the factor analyses was

based on 400 respondents. The assumption that 400 independent respondents are more reliable in finding

underlying competencies compared to three raters was the main reason for the formulation of the self-

made scales. The hierarchical multiple regression analysis identified four competencies as main predictors

of general satisfaction i.e. empathy, customer focus, enthusiasm and proactive mentality. The other four

competencies -although they did not predict general satisfaction significantly- had an indirect influence

on general satisfaction, because the main predictors also served as mediators.

Since all interviewed customers of self-employed workers emphasized in the BEI’s more or less the same

behavior that may influence general satisfaction, it was hypothesized that predictors of general customer

satisfaction would always be the same, independent of the self-employed worker’s field. This hypothesis

was partly rejected because the competency enthusiasm turned out to be a significant predictor among

49

service workers, but not for professionals in the service industry. However, the other three competencies

were significant predictors in both sectors.

While not hypothesized, there was only one background variable with a significant contribution to the

prediction equation. If a self-employed worker was hired by the respondent, the general satisfaction of the

respondent increased. A possible reason may be that the respondent felt responsible or connected to the

self-employed worker which may influence the satisfaction. However, when all competencies were

included in the prediction equation, this background variable was not significant anymore. Furthermore, it

was remarkable that the price/quality ratio of the self-employed worker was not a significant predictor for

general satisfaction. Even customers of specialized workers valued for instance empathy and a proactive

mentality above a beneficial price/quality ratio.

To the author’s knowledge, there was no previous research about determinants of general satisfaction

before. Related research about satisfaction was always in a specific field (e.g. organization, health care,

etc.) and investigated how satisfied employees were. In the past, it was also investigated how satisfied

employees were with aspects of a job, or how for instance motivation or salary influenced their

satisfaction. However, the determinants of general satisfaction were never investigated before. Therefore,

this study contributes to the existing literature.

7.2 Recommendations

The aim of Keurwerk is to implement the final instrument into the market. In order to do so, they have to

approach self-employed workers and ask them whether they are interested in registration for the

questionnaire. Based on experiences while recruiting self-employed workers for the BEI’s, the best way

to approach people is by using a combination of e-mail and telephone. Only sending a commercial e-mail

will hardly cause any reaction, because people in general do not take the time to initiate action. On the

other hand, the risk of only calling people is that they refuse to take the time to listen and react in an

unresponsive way. Therefore, it is recommended to start with sending an e-mail to inform the

respondents. Next, a phone call has to be made to convince people and answer their questions. This

combination of e-mail and phone calls is likely to have the highest probability to increase the response

rate of the final instrument.

Guidelines were provided in Table 15 to advise self-employed workers according to the results of the

final instrument that is filled in by customers. In case a self-employed worker performs below average on

more than two competencies of a single questionnaire, it is recommended to contact the corresponding

customer. The negative judgment may be caused by particular behavior (e.g. making phone calls with

other customers while working) of the self-employed worker that irritates the customer. These negative

competencies can cause an overall negative impression about the self-employed worker. To discover

whether this is the case and which behavior causes the negative impression, contacting the customer

might be a solution.

The current version of the final instrument contains a number of background variables. However, the

analyses in SPSS showed that they do not have a significant influence on the dependent variable.

Therefore, it may be decided to omit certain background variables (e.g. age, gender, contact frequency,

50

etc.) in order to reduce the time that is needed to fill in the questionnaire. On the other hand, if only a

limited number of questionnaires per self-employed worker can be collected, the emphasis can be on

customers with a high contact frequency. Also the anonymity of the final instrument should be

considered. For the self-employed worker it is beneficial to know which customer filled in the

questionnaire and what his or her opinion was. On the other hand, the reliability of the outcome could be

influenced because customers know that their opinion is known by the self-employed worker.

Furthermore, it may also decrease the response rate of the final instrument, because not all customers may

be willing to fill in a questionnaire if they know that the self-employed workers are able to see their

responses. Taking into account that the main goal of the instrument is improving the self-employed

workers’ competencies, a traceable instrument is considered as the best option. This may be implemented

by Keurwerk on their website by offering a personal log in code to customers that is only know by the

customer and Keurwerk. As a result, the customers can fill in the questionnaire anonymously (because the

self-employed worker does not know who filled the questionnaires) which may increase the response rate

and the reliability. Subsequently, Keurwerk can register which customers filled in the questionnaire and

contact the customers that did not. The open question at the end of the questionnaire gives customers the

opportunity to express their opinion about the functioning of the self-employed worker, so Keurwerk can

give specific feedback accordingly.

After Keurwerk has given advice to the self-employed workers according to the questionnaires, it is

reasonable to assume that the behavior of the self-employed worker towards his or her customers

improves. However, Aderson et al. (1994) showed that economic returns from improving customer

satisfaction are not immediately realized. Therefore, Keurwerk can use another questionnaire after for

instance six months to verify if the opinion of the customer has also been significantly changed due to the

new insights and the advice which has been provided to the self-employed worker. With this repeated

measurement, Keurwerk can show the self-employed worker if the questionnaires have worked out

positively or not.

Contrary to what was expected, the price/quality ratio of self-employed worker was not the strongest

significant predictor of general satisfaction. This finding could be used by Keurwerk to attract possible

customers to use the instrument. It is likely to assume that many self-employed workers emphasize a

favorable price/quality ratio while underestimating the importance of their competencies. Therefore, the

outcome of the hierarchical multiple regression analysis can serve as an advertisement strategy to make

self-employed workers aware of the importance of possessing crucial competencies.

51

7.3 Limitations and suggestions for future research

According to Cooper and Schindler (2003), an instrument should meet three major requirements, which

are (1) reliability, (2) validity and (3) practicality. This section will first evaluate the final instrument

according to these three criteria. Second, other limitations and suggestions for future research are

provided.

7.3.1 Evaluation of the final instrument

According to Hair et al. (2006) the reliability of an instrument refers to the extent to which scales are

consistent in what is intended to be measured. The reliability can be assessed by determining the internal

consistency, the factor structure and the stability of the scale over time (Hair et al., 2006). In this study,

the internal consistency of the scales was measured by calculating Cronbach’s Alpa for every scale. The

Cronbach’s alpha values of the included scales were all greater than .66, which met the guidelines of Hair

et al. (2006). Next, the factor structure of the instrument was assessed by a factor analysis. Initially, not

all items loaded on the predicted factors. Therefore, the scales of the final instrument were reformatted

according to the outcome of the factor analysis, resulting in a stable factor structure. A limitation of the

final instrument is the stability of the scales over time, because this was not assessed in the study. To

determine the stability of the scales over time, the same questionnaire could be distributed among the

respondents again. If the two questionnaires highly correlate with each other, it can be concluded that the

final instrument is stable over time. In addition to the reliability, the objectivity of the study was secured

as much as possible. Due to the BEI’s, the respondents were not able to give socially desirable answers,

because they were asked to describe situations. As a result, their answers were objective and not

influenced by the interviewer. Furthermore, the quantitative questionnaire was distributed among a

different population. Since the respondents did not have prior knowledge about the study, it is likely to

assume that this contributed to the objectivity of the study.

According to Hair et al. (2006, p. 137), the validity of an instrument is “the extent to which a scale or set

of measures accurately represents the concept of interest.” The validity of the instrument was assessed

using Structural Equation Modeling and this analysis showed a valid model. However, the extent to which

the separate scales really measure the corresponding competencies was not explicitly determined.

Therefore, this could be considered as a limitation of this study. As explained before, there was no

previous research that examined competencies that have an influence on the general satisfaction of self-

employed workers. Therefore, the results of this study could not be compared with other similar scales.

To obtain the final instrument, only one group of people (i.e. customers of self-employed workers) was

approached to fill in the questionnaire. Implementing multiple measures to demonstrate that the results

are valid may be a suggestion for future research. However, this would be difficult for self-employed

workers, because they do not have subordinates, peers, supervisors or even subcontractors. Therefore, for

instance 360 degree feedback would not be a possible option. Since the main objective of the study was to

determine which competencies influence the general satisfaction of customers, other groups of people

may bias the results. A self-employed worker can also assess his or her own behavior. Future research

may determine if the results of this reflection are comparable with the opinion of customers. Furthermore,

this study might be subject to mono-method bias. According to Bartram (2007), the use of “ipsative”

instruments (i.e. using item formats that require respondents to make choices between items from

different scales) increases validity by 50% compared to “normative instruments” (i.e. making choices

52

between levels of the same scale). In addition, ipsative instruments also reduce the influence of halo error.

Since this study used a normative instrument, it could be further investigated if an ipsative instrument

reduces response bias. Furthermore, the results of the ipsative instrument could be compared with the

current study to assess its validity. A drawback of the ipsative measurement is that it is inherently less

reliable item-for-item compared to normative measurement (Bartram, 2007). Therefore, more items

should be included which increases the assessment time.

According to Cooper and Schindler (2003), the practicality of the instrument can be evaluated by

considering economy, convenience and interpretability. Since the final instrument is not yet implemented

by Keurwerk, not all aspects of the practicality are known. Therefore, the evaluation of the practicality is

based on the questionnaire that was used in this study. The economy refers to the length and the financial

aspects of the instrument. Based on a test panel of ten respondents, the quantitative questionnaire could be

completed in approximately 18 minutes. Since the final instrument contained only half the number of

questions of the quantitative questionnaire, it is likely that the final instrument can be completed in less

than ten minutes. The answers of the instrument will be collected online. Therefore, no major costs are

involved with the collection of the data. The online collection of the data also contributes to the

convenience of the instrument, because there is no pre-set time to fill in the questions. Hence, a clear

instruction for the instrument is provided. Finally, the interpretability is related to the extent to which

outsiders can understand the results. Since Keurwerk did not yet make the questionnaire ready for use, the

interpretability of the instrument is unknown. However, when Keurwerk uses the feedback graph of

Figure 11, the results of the instrument are easy to interpret by self-employed workers.

In conclusion, based on the previous mentioned criteria for reliability, the internal consistency and the

factor structure of the final instrument were sufficient. The stability of the scales over time was not

assessed in this study. Moreover, the validity of the scales was not determined. Therefore, Keurwerk

should provide feedback to self-employed workers with care. Finally, based on the economy, convenience

and interpretability it is believed that the practicality of the instrument is sufficient.

7.3.2 Limitations

Keurwerk wanted to have a measurement instrument to establish the most important competencies of a

self-employed worker without looking to the content of the job, in order to generalize the results to a

larger population. Initially, it was an interesting research area because at that time it was unknown which

competencies determine general customer satisfaction. However, the results of the questionnaire showed

that a lot of competencies correlated with each other. In other words, the focus of the study might be too

much on competencies, which resulted in closely related outcomes. All in all, the biggest limitation of the

study was probably the strong focus on competencies. Although it was not demanded by Keurwerk, also

other factors (e.g. content related aspects of the job) could have been taken into account. In addition, the

absence of the price/quality ratio in the prediction equation might also be declared because all

respondents were already customers of a self-employed worker. Therefore, they all accepted the price that

was demanded by the self-employed workers and customers might not take this into account while filling

in the questionnaire about general satisfaction. It is likely that the price/quality ratio was a criterion in an

earlier phase (i.e. while selecting a self-employed worker). Future research could determine how

important for instance the price/quality ratio and content related factors are in relation to competencies.

53

The next limitation is in line with the previous mentioned strong focus on competencies. After the Critical

Incidents were collected, they were categorized by three independent assessors. This categorization

process was difficult because there was no huge dispersal between the Critical Incidents. Although the

calculated kappa value showed substantial agreement between the three assessors, the Critical Incidents

were not all placed into the same category. This was a first sign that the focus of the study might be too

much on competencies. The second sign of a too strong focus on competencies were the results of the

factor analysis. Even though the sample size was large enough, the factor analysis did not show the

predicted results. For future equivalent research, it is recommended to broaden the scope to prevent

correlated results.

7.3.3 Suggestions for future research

The correlation matrix of section 5.3 indicated that all competencies correlated significantly (p < .01) with

general satisfaction. However, this may also be caused by a halo effect. Although it is expected that halo

error has affected the results of the study, its impact is unknown. The magnitude of the influence can be

further investigated and may also be compared to the influence of halo error in other studies. According to

Baltes and Parker (2000), it is difficult to eliminate this judgment bias, because research consistently

indicates that people are unaware of halo effects. A number of strategies are suggested by Murphy et al.

(1993) for removing the halo effect. These strategies include for instance increased observation,

manipulation of rating scales and scale formats and rater training. However, none of these has proved to

be fully effective in controlling the halo effect (Murphy et al., 1993). The regression analysis should be

interpreted with care due to the high mutual correlations between the competencies. In addition, the

possibility of halo error makes it more difficult to distinguish a self-employed worker’s strengths from his

or her weaknesses (Murphy, 1993). Moreover, the competencies that do not contribute significant to the

predictor equitation should not be disregarded, because they have a high correlation with general

satisfaction. Due to the possibility of halo error and the indirect effect these competencies have on general

satisfaction, they are indirectly important to increase the general satisfaction among customers.

The difference between satisfaction of customers of self-employed workers and fixed salary workers for a

company can be further investigated. The main difference between them is that self-employed workers

have to do everything on their own. In a company this is all cut into smaller pieces because everyone has

his or her own specialty. For instance, managers delegate work to professionals in a specific field and the

administration department plans the appointments. This may cause other competencies (i.e. mutual

communication between employees) that influence the satisfaction of customers. Further research can

investigate this.

To validate whether the final results can be generalized among the entire group of self-employed workers,

another group of self-employed workers that does not fit into the investigated target group may be asked

to fill in the questionnaire. The present study distinguished between two sectors (i.e. specialized workers

and professionals in de service industry), but also other differentiations can be made (e.g. B2B and B2C).

It is likely that also other groups of self-employed workers are comparable in terms of competencies. All

self-employed workers should be for instance reliable, follow their arrangements, adjust to the customers

need, etc. However, future research should determine if this can be generalized among the whole sample

of self-employed workers.

54

Finally, future research can determine the best way to implement the results of the research. This study

showed for instance that empathy is related to the satisfaction of customers. Suggestions to improve

empathy are provided based on the outcome of the BEI’s. It is likely to assume that these suggestions

have an influence on empathy, but the significance should be verified in order to give Keurwerk the

opportunity to provide a quality mark in addition to an advice to self-employed workers. Besides the

verification, the most effective way to improve the competencies can also be further investigated.

55

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59

Appendix I: The Great Eight competencies

The great eight, 20 competency dimension and 112 competency component titles (Bartram, 2005).

1 Leading and Deciding

1.1 Deciding & Initiating Action

1.1.1 Making Decisions

1.1.2 Taking Responsibility

1.1.3 Acting with Confidence

1.1.4 Acting on Own Initiative

1.1.5 Taking Action

1.1.6 Taking Calculated Risks

1.2 Leading and Supervising

1.2.1 Providing Direction and Coordinating

Action

1.2.2 Supervising and Monitoring Behavior

1.2.3 Coaching

1.2.4 Delegating

1.2.5 Empowering Staff

1.2.6 Motivating Others

1.2.7 Developing Staff

1.2.8 Identifying and Recruiting Talent

2 Supporting and Cooperating

2.1 Working with People

2.1.1 Understanding Others

2.1.2 Adapting to the Team

2.1.3 Building Team Spirit

2.1.4 Recognizing and Rewarding Contributions

2.1.5 Listening

2.1.6 Consulting Others

2.1.7 Communicating Proactively

2.1.8 Showing Tolerance and Consideration

2.1.9 Showing Empathy

2.1.10 Supporting Others

2.1.11 Caring for Others

2.1.12 Developing and Communicating Self-

knowledge and Insight

2.2 Adhering to Principles and Values

2.2.1 Upholding Ethics and Values

2.2.2 Acting with Integrity

2.2.3 Utilizing Diversity

2.2.4 Showing Social and Environmental

Responsibility

3 Interacting and Presenting

3.1 Relating & Networking

3.1.1 Building Rapport

3.1.2 Networking

3.1.3 Relating Across Levels

3.1.4 Managing Conflict

3.1.5 Using Humor

3.2 Persuading and Influencing

3.2.1 Making an Impact

3.2.2 Shaping Conversations

3.2.3 Appealing to Emotions

3.2.4 Promoting Ideas

3.2.5 Negotiating

3.2.6 Gaining Agreement

3.2.7 Dealing with Political Issues

3.3 Presenting and Communicating Information

3.3.1 Speaking Fluently

3.3.2 Explaining Concepts and Opinions

3.3.3 Articulating Key Points of an Argument

3.3.4 Presenting and Public Speaking

3.3.5 Projecting Credibility

3.3.6 Responding to an Audience

4 Analyzing and Interpreting

4.1 Writing and Reporting

4.1.1 Writing Correctly

4.1.2 Writing Clearly and Fluently

4.1.3 Writing in an Expressive and Engaging

Style

4.1.4 Targeting Communication

4.2 Applying Expertise and Technology

4.2.1 Applying Technical Expertise

4.2.2 Building Technical Expertise

4.2.3 Sharing Expertise

4.2.4 Using Technology Resources

4.2.5 Demonstrating Physical and Manual Skills

4.2.6 Demonstrating Cross Functional

Awareness

4.2.7 Demonstrating Spatial Awareness

60

4.3 Analyzing

4.3.1 Analyzing and Evaluating Information

4.3.2 Testing Assumptions and Investigating

4.3.3 Producing Solutions

4.3.4 Making Judgments

4.3.5 Demonstrating Systems Thinking

5 Creating and Conceptualizing

5.1 Learning and Researching

5.1.1 Learning Quickly

5.1.2 Gathering Information

5.1.3 Thinking Quickly

5.1.4 Encouraging and Supporting

Organizational Learning

5.1.5 Managing Knowledge

5.2 Creating and Innovating

5.2.1 Innovating

5.2.2 Seeking and Introducing Change

5.3 Formulating Strategies and Concepts

5.3.1 Thinking Broadly

5.3.2 Approaching Work Strategically

5.3.3 Setting and Developing Strategy

5.3.4 Visioning

6 Organizing and Executing

6.1 Planning and Organizing

6.1.1 Setting Objectives

6.1.2 Planning

6.1.3 Managing Time

6.1.4 Managing Resources

6.1.5 Monitoring Progress

6.2 Delivering Results and Meeting Customer

Expectations

6.2.1 Focusing on Customer Needs and

Satisfaction

6.2.2 Setting High Standards for Quality

6.2.3 Monitoring and Maintaining Quality

6.2.4 Working Systematically

6.2.5 Maintaining Quality Processes

6.2.6 Maintaining Productivity Levels

6.2.7 Driving Projects to Results

6.3 Following Instructions and Procedures

6.3.1 Following Directions

6.3.2 Following Procedures

6.3.3 Time Keeping and Attending

6.3.4 Demonstrating Commitment

6.3.5 Showing Awareness of Safety Issues

6.3.6 Complying with Legal Obligations

7 Adapting and Coping

7.1 Adapting and Responding to Change

7.1.1 Adapting

7.1.2 Accepting New Ideas

7.1.3 Adapting Interpersonal Style

7.1.4 Showing Cross-cultural Awareness

7.1.5 Dealing with Ambiguity

7.2 Coping with Pressure and Setbacks

7.2.1 Coping with Pressure

7.2.2 Showing Emotional Self-control

7.2.3 Balancing Work and Personal Life

7.2.4 Maintaining a Positive Outlook

7.2.5 Handling Criticism

8 Enterprising and Performing

8.1 Achieving Personal Work Goals and

Objectives

8.1.1 Achieving Objectives

8.1.2 Working Energetically and

Enthusiastically

8.1.3 Pursuing Self-development

8.1.4 Demonstrating Ambition

8.2 Entrepreneurial and Commercial Thinking

8.2.1 Monitoring Markets and Competitors

8.2.2 Identifying Business Opportunities

8.2.3 Demonstrating Financial Awareness

8.2.4 Controlling Costs

8.2.5 Keeping Aware of Organizational Issues

Note that each component is further defined

within the framework in terms of negative and

positive behavioral indicators.

61

Appendix II: BEI (in Dutch)

Step 1: Introduction and Explanation

Het doel van deze stap was om het vertrouwen van de geïnterviewde te winnen en om “goodwill” te

creëren. Tevens werd er om toestemming gevraagd om het gesprek op te nemen.

1. Introductie van de interviewer.

a. “Mijn naam is Tom Bongers, en ik ben aan het afstuderen aan de Technische Universiteit

Eindhoven, in de richting Human Performance Management.”

2. Uitleg over the doel en de opzet van het interview.

a. Voor het afstudeeronderzoek wil ik analyseren welke competenties het verschil maken in

de indruk die ZZP-ers (Zelfstandige Zonder Personeel) achterlaten. Dit kan een goede

indruk zijn, hiermee bedoel ik het type gedrag waarvan je hoopt dat alle ZZP-ers

waarmee je zaken doet het hebben (bv. gemotiveerd zijn). Maar dit kan ook een minder

goede indruk zijn (bv. ongemotiveerd overkomen).

b. Ik ben aan uw telefoonnummer gekomen omdat u onlangs zaken hebt gedaan met de

ZZP-er [naam]. Over uw contact met deze ZZP-er zou ik graag wat vragen stellen.

c. Het interview zal anoniem worden afgenomen, dus de ZZP-er zal niet te weten komen

wat u over hem gezegd hebt.

Step 2: Job Responsibilities

Specifieke vragen werden in deze stap gesteld over het beroep van de geïnterviewden en de betreffende

ZZP-er.

Om te beginnen wil ik u een aantal algemene vragen stellen:

3. Wat is uw huidige baan en functie?

a. Hoe groot is de organisatie waar u voor werkt?

b. Heeft u de ZZP-er zelf ingehuurd? Of was het iemand anders binnen uw bedrijf?

4. Wat is het beroep van de ZZP-er(s) over wie we het dadelijk gaan hebben?

a. Heeft u het afgelopen jaar met nog meer ZZP-ers zaken gedaan?

b. Heeft u ook contact gehad met ZZP-ers die uiteindelijk de opdracht niet hebben

gekregen? ZZP-ers die dus niet voorbij het offerte stadium zijn gekomen. Deze ZZP-ers

zijn ook waardevol voor mijn onderzoek, door de reden van de afwijzing.

5. Algemene vragen

a. Wanneer had u voor het eerst contact met de ZZP-er? Hoelang heeft de ZZP-er in totaal

in opdracht van u gewerkt?

b. Kende u de ZZP-er al voordat u hem aannam voor de opdracht?

Step 3: Behavioral Events

Deze stap beschrijft tot in detail zo veel mogelijk complete verhalen van “Critical Incidents”. In dit geval

is een “Critical Incident” een specifieke tijd of situatie waarin iets redelijk goed ging, moeilijk was, of

een situatie waarin de geïnterviewde voelt dat hij goed, of juist niet goed is behandeld.

62

6. “Ik zou nu graag van u een voorbeeld willen horen van een specifieke ervaring die u het

afgelopen jaar heeft gehad met de ZZP-er. Kunt u een situatie beschrijven waarin een handeling

van de ZZP-er erg goed uitpakte, of juist niet. Laten we beginnen met een handeling waarover u

tevreden was.”

o Herhalingsvraag: “Kunt u een situatie beschrijven waarin u erg tevreden, of ontevreden

was door een handeling van de ZZP-er.”

o Nee?!:

� Wanneer vond u dat u goed behandeld werd door de ZZP-er?

� Wat was bijvoorbeeld de eerste indruk die u had van de ZZP-er?

� Wanneer heeft u voor het laatst contact gehad met de ZZP-er, wat is er toen

gezegd? Hoe kwam dat op u over? Waar werd deze indruk door veroorzaakt?

o Kunt u ook een voorbeeld noemen van een situatie waarin u niet zo tevreden was met de

ZZP-er?

� Herhalingsvraag: “Wanneer vond u dat u slecht bent behandeld door de ZZP-er?”

� Wat vond u teleurstellend gedrag van de ZZP-er?

Om het verhaal zo compleet mogelijk te maken werden de volgende vragen gesteld:

7. Wat was de situatie? Wat waren de omstandigheden? Waardoor werd het veroorzaakt?

8. Wat deed de ZZP-er precies dat een zodanig goede, of slechte (positieve of negatieve) indruk

achterliet?

9. Hoe is het voorbeeld dat u zojuist beschreef een voorbeeld van goed, of minder goed gedrag? Met

andere woorden, hoe beïnvloedde dit het werk dat de ZZP-er aan het uitvoeren was?

10. Wat dacht u, voelde u, of deed u in die situatie?

a. Wat dacht u op dat moment over de ZZP-er?

b. Wat vond u van de hele situatie? Wat was uw gevoel bij de situatie?

c. Hoe reageerde u op de situatie? Wat motiveerde u tot deze actie?

11. Wat gebeurde er uiteindelijk, hoe liep de situatie af?

Step 4: Characteristics which are needed to do the job

12. Wat denkt u dat ervoor nodig is om een effectieve ZZP-er te zijn?

13. Welke karaktereigenschappen, kennis, of vaardigheden denkt u dat er nodig zijn om een

succesvolle ZZP-er te zijn?

14. Als u opnieuw een ZZP-er moet inhuren, waar zou u dan op letten?

15. Welke eigenschappen van een ZZP-er bepaald hoe tevreden een klant over hem is?

16. Zijn er nog andere opmerkingen die u kwijt wilt die betrekking hebben op het handelen van de

ZZP-er?

Step 5: A final note

De geïnterviewde wordt bedankt voor zijn/haar tijd en medewerking. Verder is er gevraagd of de

geïnterviewde nog meer klanten van ZZP-ers kent die ook bereid zijn om geïnterviewd te worden.

63

Appendix III: Calculation of Fleiss Kappa

The chance-corrected measure of overall agreement proposed by Fleiss (1971) is:

'() � ∑ +,-� ∑ k,/01/-� – kn41 6 �n 7 1�∑ p/01/-� 9

kn�n 7 1�:1 7 ∑ p/01/-� ;

The subscript mc is for multiple categories

k = number of Critical Incidents

n = number of raters

c = number of categories

<== ��> ∑ ?@=>@-� = proportion of all assignments to the A�B category. In this formula, ?@= is the number

of raters who assign the C�B subject to the A�B category (i = 1, 2, …k; j = 1, 2, … c)

For computational ease, Shoukri (2004) re-wrote the above mentioned formula as:

'() � <D 7 <E 1 7 <E

where

<D � ∑ ∑ ?@=0 7 �?)=-�>@-�?��� 7 1�

and

<E �FG=0)

=-�

where

<= � 1�?F?@=

>

@-�

The number of competency components is 112, therefore, c = 112. The number of independent raters (n)

is 3 and the number of relevant Critical Incidents (k) = 314. As a result of formula (3), (4) and (5):

<D � 0.57

(1)

(5)

(4)

(3)

(2)

64

If a random selected item will be categorized by a random selected individual, the probability that a

second random selected individual will categorize this item in the same category will be 0.57 (Fleiss,

1971).

<E � 0.03

Therefore,

'() � <D 7 <E 1 7 <E �

0.57 7 0.031 7 0.03 � 0.56

65

Appendix IV: Final questionnaire (in Dutch)

The final questionnaire consisted of 12 pages, so the respondents did not have to scroll down to read a

question. A print screen of the sixth page is depicted in figure 12. The remaining part of the questionnaire

is not depicted in this appendix, because the questions are confidential. For more information please

contact the initiator of Keurwerk on info@keurwerk.nl.

Figure 12: Random page of the final questionnaire

66

Appendix V: Correlation matrix of the original scales

Table 21: Pearson correlation coefficients

Mean SD N 1 2 3 4 5 6 7 8 9 10 11 12

1 General satisfaction 4.12 .71 400 (.92)

2 Report mark 7.53 1.07 400 .76** (-)

3 Gender (respondent) - - 400 .04 .09 (-)

4 Age 46.65 10.27 398 .00 -.01 -.08 (-)

5 Gender (SEW) - - 400 .02 .03 .20** -.03 (-)

6 Sector - - 397 -.11* -.08 -.02 .08 -.29** (-)

7 Contact duration 3.81 1.45 400 .11* .08 .01 -.01 .06 -.26** (-)

8 SEW hired by

respondent - - 400 -.11* -.06 .03 -.22** .19** -.20** .03 (-)

9 Contact frequency 1.81 1.24 400 .03 .02 .00 -.01 .07 -.21** .19** .17** (-)

10 Contact with multiple

SEWs - - 400 -.10* -.03 .06 .01 -.04 .11* -.18** .06 -.01 (-)

11 Reachableness 3.86 .71 400 .67** .56** .06 .03 .04 -.13** .12* -.06 -.01 -.05 (.68)

12 Follow appointment 4.15 .62 400 .80** .64** .05 .05 .09 -.12** .13** -.07 .05 -.05 .67** (.86)

13 Acting with confidence 4.01 .66 400 .86** .72** .06 .04 .06 -.08 .11* -.10* -.01 -.07 .72** .86**

14 Acting on own initiative 3.81 .61 400 .75** .65** .08 .00 .03 -.10* .07 -.06 .03 -.02 .62** .64**

15 Adapting to the team 3.83 .55 400 .79** .69** .09 .00 -.01 -.12* .08 -.07 .06 -.07 .66** .72**

16 General commu-

nication skills 3.87 .59 400 .71** .62** .11* -.02 .05 -.15** .08 .02 .08 -.02 .57** .66**

17 Project related

communication 3.84 .60 400 .81** .69** .07 .01 .00 -.06 .07 -.08 -.02 .00 .70** .78**

18 Self knowledge 3.82 .58 400 .80** .69** .07 .03 .04 -.08 .08 -.06 .06 -.03 .61** .74**

19 Building rapport 3.98 .61 400 .85** .73** .05 .01 .02 -.12* .15** -.09 .03 -.07 .70** .75**

20 Acting representative 3.90 .56 400 .65** .56** .07 .03 .03 -.10 .09 -.02 .04 -.02 .55** .59**

21 Acting professional 3.86 .53 400 .71** .61** .09 .06 .03 -.06 .09 -.04 -.01 -.02 .60** .72**

22 Targeting

communication 3.88 .62 400 .81** .70** .12* .00 .04 -.09 .09 -.10* .02 -.02 .68** .78**

23 Adapting 3.92 .55 400 .78** .70** .04 -.04 -.01 -.06 .07 -.05 .04 -.02 .67** .72**

24 Working energetically 4.00 .63 400 .77** .65** .03 -.01 .05 -.12* .10* -.07 .04 -.07 .66** .71**

25 Price/Quality ratio 3.88 .54 400 .71** .59** .04 .05 -.02 -.07 .14** -.17** .00 -.10* .57** .65**

67

Mean SD N 13 14 15 16 17 18 19 20 21 22 23 24 25

13 Acting with confidence 4.01 .66 400 (.90)

14 Acting on own initiative 3.81 .61 400 .74** (.87)

15 Adapting to the team 3.83 .55 400 .78** .75** (.80)

16 General commu-

nication skills 3.87 .59 400 .72** .72** .73** (.73)

17 Project related

communication 3.84 .60 400 .86** .81** .83** .78** (.89)

18 Self knowledge 3.82 .58 400 .82** .73** .76** .71** .81** (.81)

19 Building rapport 3.98 .61 400 .83** .78** .81** .76** .83** .78** (.85)

20 Acting representative 3.90 .56 400 .66** .65** .70** .70** .69** .65** .71** (.72)

21 Acting professional 3.86 .53 400 .75** .71** .76** .72** .78** .74** .77** .73** (.77)

22 Targeting

communication 3.88 .62 400 .84** .81** .83** .81** .89** .82** .85** .75** .79** (.88)

23 Adapting 3.92 .55 400 .80** .77** .80** .74** .80** .76** .81** .66** .73** .84** (.80)

24 Working energetically 4.00 .63 400 .78** .81** .74** .69** .77** .73** .78** .62** .67** .78** .76** (.83)

25 Price/Quality ratio 3.88 .54 400 .70** .67** .65** .58** .67** .69** .69** .52** .58** .68** .68** .67** (.88)

* P < .05 (2-tailed); ** p < .01 (2-tailed)

Cronbach’s alpha values are depicted on the diagonal between brackets.

For the dummy variables: male was coded 0 and female was coded 1. Yes was coded 0 and no was coded 1. A professional in the service industry was coded 0 and a

specialized worker was coded 1. This information is necessary to interpret the direction of the effect in the correlation matrix.

68

Appendix VI: Factor Analysis

There was one item in scale six that loaded also on factor five. Due to theoretical arguments it was

decided to retain this item in scale six.

HIJJKLM NIJLOP Q

1 2 3 4 5 6 7 8 9 10

Empathy 1* .51

.36

Empathy 2** .48

Empathy 3* .45

.35

Empathy 4** .44

Empathy 5** .43

Empathy 6 .40

Empathy 7* .39

.37

Empathy 8 .38

Empathy 9* .35

.32

Empathy 10 .34

Empathy 11** .34

Empathy 12 .33

Empathy 13** .31

Empathy 14** .31

Customer focus 1**

.63

Customer focus 2

.56

Customer focus 3

.52

Customer focus 4**

.52

Customer focus 5

.49

Customer focus 6

.43

Customer focus 7* .30 .39

Customer focus 8*

.38

.37

Customer focus 9**

.37

Customer focus 10*

.34

.34

Professional appearance 1

.77

Professional appearance 2

.77

Professional appearance 3

.48

Professional appearance 4*

.47 .33

Professional appearance 5

.41

Professional appearance 6**

.39

Professional appearance 7*

.37

.32

Professional appearance 8**

.36

Professional appearance 9 ***

Professional appearance 10**

.71

69

1 2 3 4 5 6 7 8 9 10

Process communication 1

.58

Process communication 2**

.56

Process communication 3**

.46

Process communication 4

.45

Process communication 5 **

.42

Process communication 6*

.42

.40

Process communication 7**

.40

Process communication 8**

.39

Process communication 9

.37

Process communication 10**

.36

Process communication 11**

.35

Process communication 12**

.33

Process communication 13

.33

Process communication 14 * .31

.31

Process communication 15**

.30

Enthusiasm 1*

.56

-.32

Enthusiasm 2

.52

Enthusiasm 3

.50

Enthusiasm 4

.45

Enthusiasm 5*

.43

.39

Enthusiasm 6

.42

Enthusiasm 7*

.32

-.39

Enthusiasm 8**

.39

Enthusiasm 9*

.38

.35

Enthusiasm 10**

.33

Availability 1***

Availability 2

.57

Availability 3**

.52

Availability 4

.36 .45

Availability 5

.34

Integrity 1**

.71

Integrity 2**

.32

Integrity 3**

.32

Integrity 4***

Professional disposition 1

.74

Professional disposition 2

.41

Professional disposition 3*

.37 -.32

Professional disposition 4*

.35

.31

Professional disposition 5**

.31

70

1 2 3 4 5 6 7 8 9 10

Taking initiative 1

-.73

Taking initiative 2*

-.30

-.45

Proactive mentality

.62

Proactive mentality 1**

.59

Proactive mentality 2**

.58

Proactive mentality 3

.57

Proactive mentality 4

.51

Proactive mentality 5**

.48

Proactive mentality 6*

.31

.45

Proactive mentality 7* .33

.43

Proactive mentality 8**

.41

Proactive mentality 9

.40

Proactive mentality 10**

.39

Proactive mentality 11**

.37

Proactive mentality 12**

.32

Proactive mentality 13***

Extraction Method: Principal Component Analysis.

Rotation Method: Oblimin with Kaiser Normalization.

a. Rotation converged in 68 iterations.

* Deleted items since they load on multiple factors

** Deleted items on theoretical grounds to reduce the number of items per scale

*** Deleted items due to a factor loading < .3

71

Appendix VII: Sobel test for mediating mechanisms

For the final instrument, the mediating effects and Sobel tests are calculated for every competency. This

Appendix provides an example of the calculation method.

The test starts by determining if there is a mediating effect between professional appearance (independent

variable), empathy (mediator) and general satisfaction (dependent variable) according to the method that

is defined by Baron and Kenny (1986). Figure 13 illustrates this mediating effect graphically.

Figure 13: The mediating effect

The relationship (c) between the independent variable (professional appearance) and the dependent

variable (general satisfaction) is tested and significant.

Table 22: Regression analysis for relationship c

Variable B Std. Error β

Professional appearance .68** .05 .58

Dependent Variable: General Satisfaction; ** p < .01

The relationship (a) between the independent variable (professional appearance) and the mediator

(empathy) is tested and significant.

Table 23: Regression analysis for relationship a

Variable B Std. Error β

Professional appearance .61** .04 .62

Dependent Variable: Empathy; ** p < .01

The relationship (b) between the mediator (empathy) and the dependent variable (general satisfaction) is

tested and significant.

Table 24: Regression analysis for relationship b

Variable B Std. Error β

Empathy 1.02** .03 .86

Dependent Variable: General Satisfaction; ** p < .01

72

Finally, the relationship between the independent variable and the dependent variable is tested while

controlling for the mediator (i.e. test c while controlling for b). The B coefficient of relationship c was .68

and has been reduced to .09. Hence, the relationship has become smaller but is still significant. As a

result, there is statistical evidence for partial mediation.

Table 25: Regression analysis for relationship c while controlling for b

Variables B Std. Error β

Empathy .96** .04 .81

Profession appearance .09* .04 .08

Dependent Variable: General Satisfaction; ** p < .01; * p < .05

The formula that is used to for the Sobel test is: Z-value � ���������������

where a and b are path

coefficients and ��= standard error of a and ��= standard error of b. The values of the variables for this

example are obtained with SPSS and depicted below:

a = .61

b = 1.02

�� = .04

�� = .04

The Z-value for this example is:

R � S�S0 � ��0 6 R0 � ��0

� . 61 � 1.02√1.020 �. 040 6.610 �. 040 � 13.09

Since the above calculated value is > 1.96, the mediator carried the influence of the independent variable

to the dependent variable.

73

Appendix VIII: Structural Equation Model on latent level

.18

.19

.38

.25.18

.23

74

Appendix IX: Final instrument (in Dutch)

The final instrument is confidential. For more information, please contact the initiator of Keurwerk on

info@keurwerk.nl.