Trust Related Behavior and Person-Job Fit Among University Graduates in Europe

DEPARTMENT OF INDUSTRIAL ECONOMICS AND MANAGEMENT

BLEKINGE INSTITUTE OF TECHNOLOGY

Master Thesis MBA Program

TITLE

Trust Related Behavior and Person-Job Fit Among University Graduates in Europe: Evidence from REFLEX Survey

Tutor Ossi Pesämaa

Examiner Urban Ljungquist

Authors: Sanjar Nazarov

Isak Olevic Surayo Ziyadullaeva

Version Feb 15th, 2015

Key Words: trust, over education, skills, mismatch, fit model

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Abstract

The purpose of this study is to explore the preconditions of trust. Using a sample of more

than 13,000 university graduates in Europe, the impact of competence mismatch on trust-related

behavior (designated below as trust) is investigated. The existing literature estimates the overall

impact of skills matches on job outcomes, while this study explores the links between nineteen

skills/competencies and trust. Theoretical analyses are grounded in one of the mainstays of

management studies: a “fit theory” that conjectures that the performance of an individual is

driven by the extent to which the environment is congruent with that individual’s personal

characteristics. Using simple logistic regression analysis, we find a non-monotonic link between

competence mismatch and trust-related behavior. The effects of underskilling on trust is stronger

in comparison to a surplus of required skills and competencies.

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Acknowledgements

We want to thank Marie Aurell, Ossi Pesämaa and Urban Ljungquist for their valuable assistance

during the entire thesis work.

Furthermore, we would like to thank our families and friends for their support and

encouragement throughout. For any errors or inadequacies that may remain in this work, of

course, the responsibility is entirely our own.

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Contents

1. INTRODUCTION ................................................................................................................................................ 5

1.1 Problem discussion ............................................................................................................................. 9

1.2 Problem formulation and purpose .................................................................................................. 11

1.3 The structure of the thesis work...................................................................................................... 12

2. THEORETICAL BACKGROUND ............................................................................................................................ 13

2.1 Skills mismatches and labor market outcomes .............................................................................. 13

2.2 Definitions of trust in the literature ................................................................................................ 18

2.3 Creation of a relevant theoretical framework ................................................................................ 23

3. METHOD....................................................................................................................................................... 29

3.1 Research approach ........................................................................................................................... 29

3.2 Questionnaire and measurements .................................................................................................. 33

3.2.1 Individual and job-related outcomes ...................................................................................... 37

3.3 Descriptive statistics and distributions ........................................................................................... 40

4. RESULTS AND MAIN FINDINGS ......................................................................................................................... 46

4.1 Simple correlation analysis and baseline specification .................................................................. 46

4.2 Trust and skill/competence mismatches ........................................................................................ 52

4.3 The indirect effects of competence mismatches on trust ............................................................. 57

5. CONCLUSION: POLICY IMPLICATIONS AND AVENUES FOR FUTURE RESEARCH ......................................................... 58

6. REFERENCES .................................................................................................................................................. 64

APPENDIX .............................................................................................................................................................. 76

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1. INTRODUCTION

Educational attainment rates and the supply of university graduates have risen in recent

decades. For example, the proportion of the population with tertiary education in Europe has

reached 36% (EUROSTAT, 2012). This has resulted in an increase in the share of the labor force

with higher educational attainments, and enrollment rates in many developed and developing

countries across the globe have increased. Research shows that such changes exert a significant

impact on the labor market and its structure. One of the many outcomes of this is that the

demands for specific job qualities and the supply of these skills by graduates can be mismatched

during the process of hiring. Indeed, in the last few decades issues of person-job matching has

been in focus for psychology, economics, and human resource studies. This issue becomes very

important in light of the globalization of business, the reduction of barriers to migration, and the

unification of international standards. In the human resource literature, such mismatches are

covered mainly in the context of over-/underskilling and over-/undereducation. Related literature

shows that deviation from a person-job fit has adverse effects on labor market outcomes. For

example, Chevalier (2003) reports that wage penalties for education mismatches in the UK affect

almost 10% of recent graduates. More recently, Pecoraro (2013) finds that penalties of skills

mismatches are strongest when compared to those of other types of factors (gender, origins) that

can reduce an individual’s wages, based on data for Switzerland.

In a seminal study, Tsang (1988) studied the paradox of overeducation in the context of

labor market mismatches. The study concluded that the problem of overeducation for the labor

market will be a long-term issue. Moreover, in the short run, overeducation marginally reduces

output. As a result, a major concern for the government and policymakers is to reduce

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unemployment and promote education, because the match between education and the demand for

education is important. While such mismatches are important for the stability of the labor

market, the study draws a number of conclusions concerning the market where overeducation is

prevalent. First, the effect of formal education on an individual’s productivity is very weak and

quantitatively small. Second, the forecasts show that there will be an increasing supply of an

educated labor force and that the return from education will diminish further. Finally, individuals

who report an education mismatch relative to job requirements perform poorly in the workplace.

Allen and van der Velden (2001) provide an important contribution to the literature by

evaluating the impact of skill and education mismatches on earnings and well-being. A follow-up

study was done by Mavromaras et al. (2010) showing that individuals who do not match their

work environments (skills and education mismatch) suffer from wage penalties.

While existing human resource studies focused on the links between education and labor

productivity, more recently management studies have explored the effects of education

mismatches on the enterprise environment. In this thesis, we focus on one aspect of such an

environment – social capital, measured by trust. Social capital is an important aspect of the

ethical environment of an organization (Trevino et al., 1999) because it promotes risk-taking and

cooperation among employees (Weaver et al., 2005). For example, a meta-analysis by Judge et

al. (2002) finds links between aspects of an individual’s interpersonal relationships and effective

leadership. Further, Chan and Dasgow (2001) conclude that, after controlling for the

international environment in their cross-country calculations, social capital is a significant aspect

of leadership potential. Schneider et al. (1999) list personality and motivation facets among the

successful predictors of personal success among high school students. Along the same lines,

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social capital is linked with tolerance among employees and the occurrence of resignations

(Bass, 1990; De Cremer and van Knippenberg, 2004).

As stated above, social capital, measured by trust, is fundamental to society and business

since it has an indirect effect on productivity and other outcomes (Yamamura and Shin, 2010).

For example, Bjornikov (2010) reports that social trust affects effective production across the

world. Moreover, trust has an impact on knowledge sharing and knowledge accumulation within

firms and in the economy as a whole. Ikeda (2008) conducted a survey of manufacturing

enterprises in Australia and found that a higher level of trust within the corporate environment

promotes creative activities and innovation. He concludes that trust is essential for establishing

networks, exchanging knowledge and collaborating on large-scale, innovative projects. Trust

creates reputations and decreases transaction costs among business ventures and individuals. As

a result, since the work of Coleman (1988) there has been an increase in the amount of literature

on the factors that affect trust.

While previous studies explored the effects of the level of education on trust in the

context of social capital, in this thesis we explore the effects of education mismatches on trust-

related behavior among colleagues interacting at the work place.

Indeed, based on these studies, we use the education mismatch theory to show that the

links between skills match and trust is an important factor for successful leadership within

business organizations. In this thesis we make a significant contribution through the argument

that education and skills mismatches significantly affect trust outcomes. Compared to previous

studies that show a monotonic link between education and trust, we find that the relationship

between education/skills match and trust is very complex. Moreover, we show that the impact of

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skills on trust is not the same across countries or among the types of skills reported to be in

surplus or deficit. Human capital match studies have mainly focused on the links between

education match and job satisfaction, wages, or turnover. Our study supports the conclusions of

previous literature because we show that education matches matter for the quality of interactions

among colleagues.

To this end, to provide statistical support for our assumptions, we take advantage of the

unique design of the REFLEX survey. In this survey, individuals who graduated from

universities were interviewed five years after graduation, and competence-specific questions

were included in the questionnaire. The wide range of competence types in the dataset allows us

to shed light on the overeducation puzzle. The REFLEX dataset is a cross-section type of data

that has been used in a number of seminal research works. Therefore, our results are valid,

generalizable, and reliable.

In order to provide policy recommendations for nurturing successful leaders within a

business environment, we also provide a number of case studies and suggest remedial measures

for dealing with mistrust. However, these recommendations must be viewed with a great degree

of caution, since they might not work effectively under varying labor market conditions. Indeed,

to this end, we are pioneers who explore the links between trust and a wide set of eighteen skills

mismatches. Our thesis work will focus on the causes of trust, implying that a misfit between

personal traits and job characteristics reduces trust. Using data from the REFLEX survey, the

present study investigates the links between competency mismatches and trust-related behavior

among university graduates in Europe. To accomplish this, we rely on the methodology of the fit

model of Schneider (1975). This model provides a theoretical framework that allows for testing

the validity of human assignment theory. At the human resource management level this is a

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popular model that is used to explain the factors underlying aspects of an individual’s personal

situation such as trust, well-being, stress, and leadership. The fit model postulates that the

performance of an individual is driven by the extent to which the environment matches that

individual’s skills and competencies. For example, Lewin (1951) shows that a misfit

(discrepancy) between person and job environment (P-E) leads to adverse behavior, including

resignations and dissatisfaction. After the final calculation, our sample of individuals surveyed

exceeds 13,000 respondents. As suggested by seminal studies, we eliminate self-employed

individuals and those working less than twenty hours per week.

The theoretical importance of our thesis work is to study, review, and analyze

determinants of trust among university graduates in Europe and to test whether misfits between

persons and their job environments reduce trust-related behavior in organizations. The practical

importance is to address the root causes of why being overeducated and over-competent fails to

increase trust-related behavior, and to suggest measures for improving the situation.

1.1 Problem discussion

In the framework of management and the business organization, employee performance

and job satisfaction on the human resource level are closely related to such aspects as trust

(Lewicki, 1998). Trust is viewed as the vital cornerstone of human society that allows for the

functioning of markets and society. For decades, the topic of trust has been subject to economic

(Driscoll, 1978), leadership (Atwater, 1988), and game theory studies (Milgrom and Roberts,

1992). Trust has been linked with job satisfaction (Butler et al., 1999), knowledge sharing

(McEvily et al., 2003), and well-being (Bjornskov, 2003: Bjornikov, 2010). Therefore,

understanding the properties of trust is important for social and business studies. Using an

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experimental approach, Smith (2008) finds that group identity, such as background and personal

history, have an effect on trust among game players. Alesina and La Ferrara (2002) explore the

causes of trust using data from US counties on individuals. The study shows that marital status,

earnings, and prior labor market experience have a significant effect on trust. Another important

finding is that individuals with less than twelve years of education are less trusted among other

demographic groups. Along the same line, Dehey and Newton (2003) investigate the

preconditions of trust. The authors report that the stock of education has a significant effect on

trust in only two of a wide number of statistical calculations. Schoon et al. (2010) explore the

links between cognitive skills, education, and social trust in Britain among 8,800 individuals that

were born after 1958. The study reports that individuals with a higher level of education report

higher levels of trust. There are a number of other studies that explore the effect of education on

trust (e.g., Lindley and Machin, 2013; Clark and Rumbold, 2006; Reynold and Johnson, 2011).

Overall, the effect of education on trust is, at best, mixed. In organization management,

employees have various trust-related interactions in their working lives with diverse intra-

organizational parties and entities. In this thesis, we focus on this aspect of trust, and explore the

effects of competence and skills mismatches on trust-related behavior. In contrast to previous

authors, we conjecture that the links between skills and trust may be non-monotonic. Our

research analysis will develop around the main research question:

What is the nature of the links between competence mismatches and trust?

As a result, we will identify the effects of competence mismatches on trust and suggest

implications for a policy designed to offset mismatches and increase trust.

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1.2 Problem formulation and purpose

The problem formulation and the purpose of our research emerge directly from the

research methods that have been used in the literature produced prior to our own work. There are

three conventional approaches: exploratory, descriptive, and explanatory. We have selected an

exploratory approach for our study. An exploratory approach allows us to develop our theory in

order to understand the nature of an existing relationship and to assess it. This approach consists

of three major courses of action. The first action is to collect expert opinion on an existing issue.

The second is to perform large-scale interviews, and the third is to review the existing literature.

For our study we combine the second and third actions to produce more valid results. Other

advantages of an exploratory study are the flexibility that it offers and the fact that such a study

is subject to modification during the course of the study. Because the data provides new results

and unusual relationships, we can address a wide range of other, minor questions as well. It is

important to point out that secondary data that has been successfully used in related works allows

us to draw reliable conclusions and suggest policy implications.

The problem statement and purpose of this study thus focus on education mismatches in

the context of existing preconditions of trust. In line with existing studies, we explore such

causal relationships. Our major contribution is the investigation of the links between education

and trust within the corporate environment for a very large set of skills and competencies. We

challenge an existing belief that education is positively associated with trust. We assert that an

oversupply or undersupply of the skills in demand produces trust-related behavior.

Our investigation is challenged by the nature of the problem. McKnight and Chervany

(2001) show that there are more than sixty-five definitions of trust. Based on their meta-analysis,

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they define five categories of trust: dispositions to trust, institution-based trust, trusting beliefs,

trusting intentions, and trust-related behavior. Among these definitions, trust-related behavior

(designated below as trust) is the inter-personal dependency that can be viewed as the result of

the interaction between a person and the job environment (see 2.2). As can be seen from the

above, our thesis investigates the match between a person and his or her work requirements;

therefore, we base our conclusions on a Person – Job-Environment fit theory that is a mainstay of

management studies. Based on the results of our quantitative strategy, it is expected that we will

be able to analyze the impact of competency mismatches on trust and to suggest measures for

improving the situation.

The study is important because the fit theory allows us to reach conclusions concerning

the core causes of distrust in the corporate environment and, because trust is viewed as a

determinant of successful leadership and productivity (Bjornikov and Meon, 2010), to underline

factors that increase trust among colleagues.

To this end, the purpose of this study is to identify the effects of a wide range of skills

mismatches on trust-related behavior (in short – on trust).

1.3 The structure of the thesis work

The structure of the thesis work is as follows. In Chapter 2 we provide the theoretical

background of our study. First, we discuss the evolution of the concept of trust from an

interdisciplinary perspective. Then we review fit theory, a mainstay in human resource

management. In Chapter 3 we review our methodological approach. We explain the variable

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generation process and introduce the statistical tools used to answer our research question. We

devote Chapter 4 to analysis and the main findings. Chapter 5 concludes the thesis work.

2. THEORETICAL BACKGROUND

2.1 Skills mismatches and labor market outcomes

The literature investigating links between human capital and labor market outcomes is

very rich. According to labor economics, human capital is the set of skills and knowledge that

form a stock of knowledge that is measured as an input for producing goods and services. In the

same way, in business studies human capital can be viewed as the supply of labor that can be

hired to fill management or production positions and that is also viewed as an input of goods that

has an impact on revenues. Since human capital has a direct and positive effect on output, human

capital in the business environment is associated with better production quality and quantity.

This leads, consequently, to higher revenues and maximizing the wealth of shareholders. On the

other hand, different types of production, imperfect labor markets, and the dynamics of economic

indicators lead to assigning individuals with various skills to positions that do not match their

supply of knowledge. In countries where labor markets are associated with high layoff costs and

low flexibility, such mismatches occur frequently and thus must be further investigated for a

number of reasons.

The first reason for this is that there is a greater demand for skilled labor today than there

was several decades ago (Card, Kramarz and Lemieux, 1996). In Europe and other developed

countries, businesses have shifted toward higher value added production and the demand for

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workers with better skills has been rising (Ilo, 2013). A recent report by CEDEFOP asserts that

in the next five years there will be a significant reduction in employment in the primary sector

and in utilities. On the other hand, employment growth for skilled technicians, managers, and

associated professionals will increase dramatically. Technological advances will significantly

affect these employment types. As a result, there will be a greater demand for skills and

competencies. Similarly, the report finds that jobs at the lower end of skills levels will not be

affected by such changes. Trends identified in the study show that an increase in the supply of

skilled labor will inevitably lead to the supply of a skilled workforce for lower skills

employment. Consequently, the issue of matching skills between person and work environment

is a priority agenda in reforms of the labor market. This idea is supported in a number of baseline

theoretical studies that explore the links between skills supply and job requirements in the labor

market (Bulow and Summers (1986), Davis and Reeve (1997), De Groot and Van Schaik

(1997)). These studies note that, when the labor market consists of skilled and unskilled types of

jobs and employees, demand in the skilled jobs market will cause the supply of skilled labor to

increase significantly. Hence, after full employment is reached in the skilled jobs market, skilled

labor will replace the unskilled labor force in the other market, thereby explaining the increase in

unemployment rates for unskilled individuals.

At the same time, in countries with stronger social protection, the mismatches between

person and job requirements are due to increases in the wages for relatively unskilled job types.

Wasmer (1999) concludes that increasing the strength of labor unions and wage bargaining leads

to a greater level of unemployment and labor market shocks. As a result, temporary employment

is significantly affected by such dynamics.

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Another important factor highlighted in the literature is an increase in the supply of

educated labor that in turn causes overskilling and skills mismatch problems in Europe. Studies

on this issue date back to the influential work of Tsang and Levine (1985). In their study they

discuss the consequences of overeducation. The study highlights that, unlike the situation fifty

years ago, the supply of human capital has significantly changed. Recent graduates in the labor

market are looking for challenging jobs that will utilize their skills, while the labor market reacts

to such changes with a considerable lag. Most of the job offers in the labor market are

managerial and the share of productive/creative jobs has decreased. This trend will continue in

subsequent decades, forcing individuals with a high level of human capital to work at jobs

requiring lower levels of skills and education. From an economic perspective, a firm opts for the

lowest input costs, depending on the existing level of technology. An inflow of human capital

with higher levels of educational attainment allows the firm to establish wage penalties for

overskilled individuals.

A more recent study by Fleming and Kler (2008) asserts that in Australia, university

participation rates have been constantly increasing. Such labor market trends might have an

impact on other outcomes, such as job satisfaction and wages. Using a Household, Income, and

Labor Dynamics survey in Australia, the study shows that skills mismatches have a negative

influence on job satisfaction. One of the possible explanations for this is that overeducated or

overskilled workers perform tasks that do not challenge their abilities, thereby reducing effort,

productivity, and job satisfaction.

Another study by Mavromaras et al. (2010) covering respondents in Australia and Britain

revisits the evidence concerning skills and education mismatches and job satisfaction and wages.

This study shows that the wage penalty for severe overskilling is 0.041 in Australia.

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Interestingly, gender-based calculations show that the wage penalty for mismatches is double for

women. Statistical calculations for Britain show that for severe overskilling the wage penalty is

only 0.021 for men and 0.025 for women. The study concludes that benefits of hiring overskilled

individuals are only observed in the short run. In the long run, the effects of overskilled workers

are damaging because of their decrease in productivity.

A greater in-depth study was done by Sanchez-Sanchez and McGuinness (2013). Their

sample covers thirteen European countries, and they use our preferred REFLEX dataset and

construct skills mismatch variables like those used in our own methodology. This study explores

more than fifteen types of skills mismatches in the labor market. They specifically explore the

effects of competence mismatches on wages and job satisfaction. For the wage equation, they use

a log-wage Minzerian regression approach and conclude that the wage penalty for overeducated

individuals is almost 30% while the wage penalty for skills mismatches is only 5%. A possible

explanation for such a large wage penalty for overeducation is due to the underutilization of the

intellectual potential of human capital.

Tarvid (2013) explores the effects of personality and skills mismatches on the labor

market decisions of individuals in twenty-three European countries. According to these findings,

ability and personality are important aspects of turnover rates and resignations. The results

remain valid when the authors explore these issues separately for countries in Northern and

Southern Europe.

Another study shows that overeducation is a predictor of mistrust for lawyers in the USA

(Sekhon 2006). Similar conclusions were reached in a more recent study by Joona et al. (2014).

In this study, the authors explore the effects of education on the social positions of immigrants.

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The study comes to an interesting conclusion, showing that mismatches between the supply of

knowledge among immigrants and job requirements lead to significant mistrust in the job

environment. Further, the study utilizes the panel data for the period 2001–08 to show that

education mismatches effect wages and dependence on welfare benefits. The authors report that

immigrants with severe skill mismatches suffer from sizeable wage reductions and have the

lowest degree of confidence about future employment opportunities. Along these lines (Chiswick

and Miller, 2008; Chiswick and Miller, 2010a; Chiswick and Miller, 2010b; Korpi and Tåhlin,

2009; Battu and Sloane, 2002) arrive at similar conclusions based on the survey data.

Li (2009) examines the effects of educational achievement on trust. The study identifies

two major channels that effect trust. First there is the direct positive effect of education and trust

through the recognition of educational achievement. Graduation from a university signals

expertise in the process of hiring in the job market. However, there is an indirect effect of

education on trust through experience. Interaction with other educated individuals at the work

place leaves those whose skills do not match their job requirements in a disadvantaged position.

As a result, trust is reduced, and education can have negative indirect effects on labor market

outcomes. Huang et al. (2011) use the BNCD survey to find links between schooling and trust.

Overall the study finds that there are positive effects of education on trust, after controlling for

various statistical limitations. In a follow-up study, Huang et al. (2012) report that the effects of

education on trust is conditional on life experience. According to the data, life experience can

explain more than 77% of the effects of education on trust.

A summary of the empirical evidence shows that educational mismatches lead to

absenteeism, reduced effort, dissatisfaction, lower wages, and, more importantly, mistrust.

However, our thesis further advances research in this area. Previously discussed studies focus on

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a generalized trust that captures social capital among citizens, or aggregate data on a macro-

level, while we make possible the exploration of the effects of specific skills and competencies

and produce a better understanding of which skills are essential within a corporate environment.

2.2 Definitions of trust in the literature

Trust has been carefully examined in the human resource and management literature. For

example, Mayer et al. (1995) notes that trust among people belonging to a group determines the

trust level within the job environment. However, the concept of trust is very complex. Some

authors underline the fact that trust evolves around risk and that an individual who demonstrates

trust accepts vulnerability (Rosseau et al., 1998). In a seminal study by Luhmann (1988), trust is

described as a tool that an individual applies to assess whether or not to engage in risk-related

situations. In a follow-up study by Newell et al. (2002), the authors conclude that trust puts at

risk various facets of human life (self-esteem, reputation, etc.). While significant empirical

literature has emerged since the work of Rotter (1967), the results of these studies are not

directly comparable. For example, trust has been defined as an elusive idea (Yamagishi and

Yamagishi, 1994), a noun, and a verb (Barber, 1983). Some scholars document trust as a belief,

an intention, or a social norm (Lindskold, 1978; Scanzoni, 1979). Researchers have been able to

investigate the correlates and causes of trust.

Renzl et al. analyze the links between trust and intentions of knowledge sharing among

various work groups. The study distinguishes two types of trust: trust in management and trust in

co-workers. Based on data for the utility industry in Australia, the study concludes that trust

among co-workers is essential for intragroup knowledge spillover, whereas trust in management

is a determining aspect of external knowledge sharing. Further, Cook and Wall (1980) show that

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trust among employees can be directed as good intentions projected toward colleagues and

supervisors. Indeed, trust fosters cooperation and plays a fundamental role in the process of

establishing cooperation among colleagues (Morgan and Hunt, 1994). McEvily et al. (2003) find

that high levels of trust promote decision-making and reduce asymmetric information issues

within an organization. Decision-making and leadership are highly correlated with gender. Since

Rotter’s interpersonal trust scale (1967), a series of studies have investigated the links between

trust and gender. Jeanquart-Barone and Sekaran (1994) conclude that in an organizational

environment, trust-related intentions directed at the supervisor decrease for female supervisors

and vice versa. In this study, trust was captured by several indicators: participation in decision-

making, gender discrimination, and the supervisor’s role as mentor. However, Frank and Schulze

(2000) failed to find any links between gender and the level of trust. Indeed, conventional

reasoning suggests that females are more trustworthy. For instance, in an effort to reduce bribery

on the road, Mexico City used only female traffic police officers (Treaster, 1999). Swamy et al.

(2001) argue that female participation increases the quality of government institutions and

reduces the level of corruption. Another factor that is strongly associated with trust is education

and experience. Education is the factor that exhibits the highest correlation with trust (Putnam,

1995) and can be used to predict changes in social trust with a high degree of certainty (Ulsaner,

1999). A study based on the European Social Survey (ESS) dated 2008–09 shows that education

increases trust and reduces corruption in society. Indeed, an increase in the number of years of

schooling has a positive impact on social trust within a society (Putnam, 2001). Based on the

General Social Survey, a study from Columbia University1 explores the impact of human capital

on trust in various specific functions. Falk (2000) shows that trust is an aspect of social capital.

According to his definition, trust “contributes to the quality of interactions between people”. 1 http://qmss.columbia.edu/storage/Li%20Tianshu.pdf

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Indeed, Coleman (2001) defines social capital as an array of family and community assets that

establish interpersonal relations, trust, and social norms. Putnam (1995) concludes that these

assets are a determining aspect of the behavior of an individual within social and corporate

structures. Coleman (1998) develops further the study of Coleman and reports that social capital

is a determinant of effective action, norms, and trust-related behavior within a social

environment. In line with this framework, an individual’s associations within an organization

increase reliability, especially when the density of individuals within the organization is

increasing (Putnam, 2006).

The evolution of business ventures increasingly requires collaboration and

interdependence to achieve proposed goals. Mutual work relations and self-directed teams

increase risks and require reliability. Bateson (1998) asserts that a number of studies misinterpret

trust and collaboration. In line with these studies, Deutsch (1960) concludes that the main factor

that is associated with trust is perceived confidence. Indeed, sometimes both of these factors lead

to negative outcomes, such as disappointment and stress (Luhmann, 1988). The author highlights

the importance of risk perception for engagement in a risk-taking relationship. After reviewing

existing studies, Mayer et al. (1995) offer an alternative model of trust. In their study, they

conclude that trust is derived from three important factors: ability, benevolence, and integrity.

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Figure 1. Proposed model of trust Source: Mayer et al. (1995)

In addition, a meta-analysis of determinants of trust by Mayer et al. (1995) reveals that

skills, ability, and competence are crucial factors that lead to trust (see Table 1). In line with

these findings and job matching theory, a human capital match is a determining aspect of trust-

related behavior. A large percentage of the studies reviewed point out the primary role of

education (skills and competencies) in fostering trust.

Table 1. Determinants of Trust Study Factors associated with trust Boyle and Bonacich (1970) Interaction Butler (1991); Cook and Wall (1980); Deutsch (1960); Giffin (1967); Hovland et al. (1953); Lieberman (1981)

Competences, abilities, expertness

Dasgupta (1988) Threat Gabarro (1978); Hart et al. (1986) Openness Solomon (1960); Strickland (1958) Benevolence

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Source: Mayer et al. (1995)

In another celebrated meta-study of trust typologies, McKnight and Chervany (2001)

provide an interdisciplinary model of trust types (see Figure 2). The study outlines several types

of trust: a disposition to trust, institutional trust, trusting beliefs, and trust-related intentions and

behavior. The authors assert that, in line with traditional aspects of trust, aspects such as risk,

uncertainty, safety, and control are determining factors in defining a typology of trust. A

disposition to trust measures the extent of the scope to which an individual demonstrates an

inclination to be dependent on “general others” across a wide range of individuals and

circumstances, for example when an individual projects general trust (for everyone) onto specific

instances of trust for his new colleagues. Mayer et al. (1995) attribute this to personal traits. In

contrast, an institution-based trust is derived from a secure feeling that the institutional

arrangements that exist in society will prevent others from carrying out harmful intentions

toward the individual. Zucker (1986) shows that enforcement of laws has a positive impact on

institutional trust. While institutional trust is situation-specific, trusting belief is the perception of

safety toward another individual that he/she possesses traits that are beneficial to the individual

who exhibits the trusting belief. Various studies have characterized trust as behavior. According

to these studies, trust-related behavior is the reliance of one individual on another through a

perception of security, despite the first individual’s acceptance of a negative outcome of this

reliance. This is our preferred measure of trust in the present study.

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Figure 2. Model of trust constructs Source: McKnight and Chervany (2001)

2.3 Creation of a relevant theoretical framework

Following the discussion above, we have departed from Mayer et al. (1995) and

developed a theoretical framework to explore the effect of educational matches on trust.

According to Mayer et al. (1995), ability is one of the factors that build trust. Moreover,

outcomes have effects on trust through people’s abilities. In this thesis, as measures of outcomes,

we use wages, type of contract, and tenure. These factors show directly the experience of

individuals on the labor market. Relatively long tenure and permanent contracts can signal

expertise and job experience. Higher wages may indicate that the return for skills is greater,

thereby increasing trust. The goal of the thesis is to explore the effects on trust of the matches

between the educations supplied and demanded. We rely on the fit model (Schneider, 1975).

This model decomposes the outcome variable (for example, trust) into a linear function of

24

independent variables: education mismatches, wages, experience, age, etc. Indeed, as suggested

in organization management literature, firms seek individuals who perfectly match the demands

of the job and deliver commitment to the goals of the organization (Caplan, 1987). An

accomplishment of the goals requires congruence between the environment (job) and the person.

The P-E (person-environment) framework is a well-known tool in organization research

literature. Initially, this framework was developed by Caplan et al. (1974), and it was extended

by (Schneider, 1975). Indeed, the concept of “fit” has sparked a significant number of studies

(Edwards, 1991; Kristof, 1996). Early studies focused on the links between person-job fit and

organizational commitment (Alutto and Belasco, 1972). In the most recent decade, this model

has been successfully used in a large number of studies (e.g., Lauver and Kristof-Brown, 2001;

Supjarerndee et al., 2002; Ering and Youngs, 2011; Lu et al., 2014; Westerman and Cyr, 2004;

Piasentin and Chapman, 2006). Moreover, the fit model has been a mainstay in a series of studies

exploring the effects of skills on hiring in the labor market (Lievens et al., 2001; Carless, 2005;

Chuang and Sackett, 2005; Cable et al., 2006). In addition, in the last decade, organization

studies have explored the effects of “fit” on job satisfaction, resignations, and employee relations

(Lauver and Kristof-Brown, 2001; Karakurum, 2005; Iqbal et al., 2012; Ramesh, 2007;

Scroggins, 2008).

This fit theory dates back to Caplan et al. (1974) and has provided a successful

framework to theoretically and empirically explain the evolution of organizations and human

resources. Lewin (1951) argues that employee behavior and satisfaction are the outcomes of fit

or congruence between person and environment (P-E). The congruence between person and

environment has been the subject of stress research and well-being studies (Schuler, 1980). The

fundamental concepts of fit theory are shown in Figure 3. Environment includes situations and

25

events. A mismatch between person and environment may exist due to individual capacities,

denial, or organizational structure (Harrison, 1978; Weick, 1979).

One of the aspects of fit theory deals with Demand-Ability Fit. Demand-Ability Fit can

be expressed as a combination of the questions of “what an employee needs to provide for the

job” and “what do I want from the employee”. In other words, demands are a set of job

requirements and corporate norm or values, whereas abilities are skills, competencies, time, and

energy that a person must supply in order to meet the demands (Edwards et al., 1988).

Hoath (1988) examines the links between P-E fit and well-being among police officers in

Canada. The study finds that a lack of fit between career goals and work settings decreases job

satisfaction. The study highlights the value of fit theory and the method proposed by French et al.

(1974) because it allows for the investigation of static links among career adjustments in diverse

assignment classifications. However, the study suffers from a serious limitation, since the survey

data is based on a non-representative police station in Ontario. The results of the study thus lack

generalizability.

According to management studies, a misfit between person and environment results in

negative outcomes such as strain, a decrease in productivity, and even mistrust (Verquer et al.,

2003; Kristof-Brown et al., 2002; Humburg et al., 2012). Meanwhile, organizations where person

and environment match is maintained benefit from commitment, performance, and trust-related

behavior among employees (see Figure 3). This framework allows us to address this question

because it takes into account the match of skills in the interaction between person and

environment, after controlling for other potential causes that may affect outcomes.

26

Figure 3. A model describing the outcomes of fit between person and environment (job)

Source: Authors’ elaboration

Figure 4. The fit model and trust


TRUST OUTCOMES

FIT

Supply of skills

Demand of skills

27

Building on Mayer et al. (1995) and Schneider (1975), in Figure 4 we provide a

conventional approach to show the links between outcomes and trust, and with respect to the

person-job fit. On the other hand, Regh (2012) and Yann et al. (2011) show that skills have

effects on trust-related behavior among students and pupils. Along the same lines, a series of

studies shows that skills determine the level of earnings (e.g., Polaviega, 2009; Fitzenberger and

Kohn, 2006; Nieto, 2014). Therefore, fit will have indirect effects on trust through outcomes (see

Figure 5).

Figure 5. The fit model and trust Source: Authors’ elaboration

In line with the fit model, in which trust among colleagues is a function of education and

other socio-demographic factors that are linked to the person-job fit, we define and consider the

following hypotheses:

H1: Outcomes have effects on trust.

H2: Misfits between supply and demand of skills and qualifications influence trust.

TRUST OUTCOMES

FIT

Supply of skills

Demand of skills

28

H3: Misfits between supply and demand of skills have indirect effects on trust by way of

outcomes.

H1 will test the direct effects of education and competence matches on trust, while H2–

H3 will test the indirect effects of life experience on trust.

Moreover, while some of the measures of outcomes (education stock, wages, tenure, and

contract type) are found to have linear effects on trust, a P-E framework allows us to examine

other possible non-linear relations between person and job environment fit and trust (Figure 6).

This is supported by Locke (1969), who finds that bell-shaped functions exist between

discrepancy and individual behaviors (with respect to job satisfaction, happiness, turnover, etc.).

Figure 6. Possible functional forms of the relationship between trust and the congruence between

person and environment (job)


29

3. METHOD

3.1 Research approach

There are a number of ways to investigate the links between competence matches and

trust. One of the approaches is an exploratory study (Barry, 1994). Such studies are carried out in

three steps. First there is a review of previous studies. Second comes interviewing experts and,

finally, carrying out a focus-group interview. The main advantage of this approach is the

flexibility that it offers, since you can modify the nature of your investigation in a short span of

time. These studies are often performed during policy analyses when they suffer from non-

generalizability. They cannot be made to produce scientific facts, because the samples from

which conclusions are drawn are non-representative.

To ensure the validity of our results, we complement theory with analysis of data by

using appropriate statistical tools (correlation, principal component analysis, or regressions).

These tools are very useful since they allow us to investigate the problem in the context of

representative data covering regions, or even countries. Such studies are often published in

academic journals and they are valid and can be generalized.

To employ one of the above-mentioned studies we can select from a wide range of

approaches:

Face-to-face interview

Survey

Case study

Archival research

Experiment

30

For the purposes of our thesis, we have chosen to use a survey approach. Experiments are

a very time-consuming process since you must have control and treatment groups and you may

fail to postulate a theory from the results. Case studies suffer from selectivity because they cover

a small range of business establishments and the mismatches found there might not be important

issues. To this end, survey data have been widely used in theoretical and empirical studies

because they cover the entire population in a representative manner.

The next step is the choice of data. The best way to contribute to the academic discussion

is to analyze research questions on the basis of primary data. Primary data is obtained during the

data collection process from primary sources. Such data is obtained during a face-to-face

interview. However, this has several advantages and drawbacks. In order to carry out the survey,

you must follow procedural guidelines. First, you need to gain access to the enterprises in which

you are interested. You need to demonstrate your ability as an expert in your field and to have a

set of competences. Prior to conducting research you must establish a series of pre-survey

contacts, prepare introductory letters, and develop a questionnaire. Additional issues, not

discussed here, are confidentiality, language, and social norms.

Secondary data is a mainstay of existing studies (Church, 2002; Curtis, 2008; Nicholson,

2009; Brodeur et al., 2011, van der Velden and Allen, 2011). This data is downloaded from

reputed survey agencies that carry out surveys, such as REFLEX, World Values Survey, PSID,

NHYS, and others. Indeed, secondary data is often used in recurring studies that allow

comparisons to be made between the results. This saves significant research time and funds since

such data is most often available free of charge.

31

The next step in the research is processing and analyzing data. In our study, there are

several ways to analyze the data. One of the methods is simple correlation analysis. Correlation

analysis allows us to establish an association between the variable of interest and the dependent

variable, namely trust. The main drawback of such an approach is that it does not allow us to

establish the direction of causality (Wright, 1921; Wright, 1934). For example, education can be

correlated with abilities. But this does not mean that education drives abilities.

One of the approaches used to explore the direction of causality and to calculate the value

of the impact of the mismatches on trust is regression analysis. In order to test our hypothesis, we

follow previous studies for the relevant regression approach. In line with the literature, fit theory

can model trust-related behavior of an individual i (trust) at time t, that is conditional on the

person-job fit (Fi) and a set of individual and job-related factors (Xi):

TRUSTi = f (Fi; Xi)

Our market model is as follows: at time t an individual i is drawn from the labor market

by a firm in a selection process. The individual supplies k amount of human capital, while the job

demands n level stock of human capital. As a result, there can be three possible outcomes:

a) If k > n then the individual is overqualified or overeducated. The existing

literature asserts that such individuals display a low level of effort and that their productivity is

below that of non-overeducated colleagues.

b) If k = n then there is a perfect fit.

c) If k < n then this is a case of undereducation. Review of the literature shows that

the effects of undereducation on productivity, effort, and turnover intentions are mixed. Some

32

studies report that a challenging job increases effort, while other studies report poor

performance.

Regression calculations are a mainstay of empirical studies and are intended to determine

the links between a regressor and a regressand. The specification allows for the establishment of

linear and other functional forms for such relationships. A simple ordinary least squares (OLS)

method in a sample of n individuals can be expressed as:

yi=b0+b1*Xi+ei

where, in our case, y is a measure of trust, X is a vector of factors, independent variables,

and e is an error term of the regression.

The OLS technique works by minimizing the sum of squares of the error terms and it

derives the constant (bo) and the slope of the function (b1). In our empirical investigation, this

approach is not a preferred one since trust is measured as a dichotomous variable taking on the

values of 0 and 1. The predicted OLS regression results can leave the range [0;1] and can even

have negative outcomes. For such variables it is useful to apply an approach very similar to OLS

– probit or logistic regressions.

Throughout this thesis we use logistic regression analysis extensively. In our thesis, the

perceived measure of trust is a feeling of security through which professional colleagues

perceive an individual as an authoritative source of advice. The question derived from the

REFLEX survey, and the most appropriate approach to estimating the determinants of binary

response data, is basic logistic analysis. This statistical method is employed to examine the

impact of explanatory factors on response outcomes. The statistical logistic function can be

expressed as:

logit{Pr(Y=1|X)}=log{(Pr(Y=1|X)/(1- Pr(Y=1|X)}=b0+bX

33

where b0 is the intercept of the function, and X represents determinants of the response

variable (Hosmer and Lameshow, 1989).

Lee et al. (2006) define the logistic approach as the probability dispersion of y

considering the vector of control of the X variables.

Where are the coefficients to be calculated, and is the sigmoid.

Our dependent variable is trust, which is coded = 1 if a person reports trust-related

behavior, and zero otherwise. The binary nature of this factor provides us with the traditional

equation

trusti=a0+a1X1+a2X2 + E

where logit is the dependent variable, trust; X1 and X2 a set of control variables.

In this study, we follow previous studies in the human resource and management

literature and calculate the basic logistic function where determinants of trust are individual and

job-related factors (e.g., Pohlman and Leitner, 2003). To answer our research question, we

follow the recommendations provided in Chen et al., Regression with Stata.

3.2 Questionnaire and measurements

One common approach in the literature is the use of survey data. Such data offers a large

number of advantages:

- Flexibility

- Anonymity

- Quality control

34

- Large-scale accessibility in many countries

Still, among the major drawbacks of survey data are the possibility of low response rates,

limited sampling, and the fact that the survey data is a snapshot of a population at a specific point

in time. Results based on such calculations can be very sensitive to changes over time and to

trends.

However, survey data is the most widely used data in the empirical literature.

In this study we base our analysis on the REFLEX survey of individuals in a number of

European countries and in Japan. The master questionnaire consists of fourteen pages and is

limited to individuals who graduated in 1999 or 2000.

Fisher (2007) distinguishes between two different types of questionnaire. First, there are

questionnaires in which the answers have already been provided. These are called pre-coded

questionnaires. The second type of questionnaire is one where a responder must fill in the

answers in his or her own words. These are called open questionnaires.

The REFLEX survey questionnaire consists of both open-ended and pre-coded questions.

The main advantage of this questionnaire is that it has been used in numerous influential studies

in economics and human resources management.

For example, Kucel and Vilalta-Bufi (2013) use this survey to explore the job satisfaction

of drivers in Spain. The study finds that, in a sample of more than 1,700 respondents, the lack of

a challenging job or leisure time as well as other factors have a negative impact on well-being.

Using REFLEX survey data, Arthur (2010) concludes that “UK undergraduates spend

less time on higher education and feel less well-prepared for work immediately after graduation

than those in most other European countries”.

35

Allen and van der Velden (2010) report that the survey can be used to track labor market

trends and moods in European countries. The survey provides a rich set of questions on prior

experience, academic performance, and the current labor market status.

Sanchez-Sanchez and McGuinness (2013) explore the impact of mismatches on wages

and job satisfaction in Europe. Unlike other surveys, the REFLEX survey offers self-reported

levels of competence for eighteen different types of skills. This makes our investigation more

valuable and precise, since we do not aggregate mismatches.

This survey gives our work significant academic value because it increases the reliability,

validity, and generalizability of our results. The questionnaire is divided into several parts:

Part A – Study program you graduated from in 1999/2000

Part B – Other educational and related experiences

Part C – Transition from study to work

Part D – First job after graduation

Part E – Employment history and current situation

Part F – Current work

Part G – Work organization

Part H – Competencies

Part I – Evaluation of study program

Part J – Values and orientations

Part K – About yourself

In accordance with previous literature, the dependent variable is trust-related behavior.

Individuals were asked to what extent professional colleagues rely on him/her as an authoritative

source of advice on a 5-point Likert scale (1 – not at all, 5 – to a very high extent). We generate a

36

dichotomous variable, trust, that takes a value of 1 if a respondent replied with a 4 or 5, and zero

otherwise (see Table 5 for a description of the variable). Only 18% of respondents stated that

colleagues rely on them as an alternative source of advice, while 4% state that colleagues have

no professional trust in them (Table 2).

Table 2. Distribution of trust in Europe Total sample N % of total Professional colleagues rely on me as an authoritative source of advice:

1 not at all 1,16 4.25 2 2,86 10.42 3 7,93 27.89 4 10,51 38.29 5 to a very high extent 4,98 18.16


In order to test Hypothesis 1, we generate a set of dichotomous variables based on the

replies to the questions “How do you rate your own level of competence?” (own) and “What is

the required level of competence in your current work” (required). We distinguish between a

reported surplus of competencies (surplus: when the difference between “own” and “required” is

2 or above) and a deficit (deficit: when the difference between “own” and “required” is -2 or

below) of competencies. In this study, we assess nineteen competencies ranging from analytical

thinking to an ability to use computers and the internet (Table 3).

Table 3. The competencies under evaluation.

Type of competency Mastery of your own field or discipline Knowledge of other fields or disciplines Analytical thinking Ability to rapidly acquire new knowledge

37

Ability to negotiate effectively Ability to perform well under pressure Alertness to new opportunities Ability to coordinate activities Ability to use time efficiently Ability to work productively with others Ability to mobilize the capacities of others Ability to make your meaning clear to others Ability to assert your authority Ability to use computers and the internet Ability to come up with new ideas and solutions Willingness to question your own and others’ ideas Ability to present products, ideas or reports to an audience Ability to write reports, memos or documents Ability to write and speak in a foreign language

Source: REFLEX Survey

We now turn to a discussion of outcome factors as determinants of trust. Based on the

literature of human resources management, we derive two sets of factors that influence trust:

individual and job-related outcomes.

3.2.1 Individual and job-related outcomes

The first measure of outcomes is gender. Gender is an important aspect in labor market

outcomes. Specifically, it has effects on resignations, earnings, and trust (e.g., Goldin, 2014).

Female is the binary variable indicating whether an individual is female (= 1) or male (= 0). In

our study, 58% of the individuals are female, with a mean age 30.8 years.

The next outcome variable is children in the household. Children is a binary variable that

takes a value of 1 if the respondent has children and zero otherwise. According to the summary

statistics of our sample, only 25.7% of respondents have at least one child.

Marital status is also a significant factor in the human resources literature (e.g., Bardasi

and Taylor, 2008). The binary variable married takes a value of 1 if an individual is currently

38

living with a partner. According to the REFLEX survey, 38% of the respondents are reported to

be single. The mean age of the respondents in our sample is 31 years and the standard deviation

is 4.9 (see Table 4).

Current level of education is measured by a program of study that grants access to

postgraduate studies (= 1), and zero otherwise. Tenure is the duration of contract at the current

job in months. Public is a binary variable that takes a value of 1 if the respondent works in the

public sector, zero otherwise. Additionally, we control for training experience, wages, workload,

and type of contract (see Table 4, for descriptive statistics). Based on the calculations in Figure

7, 79% of the respondents have permanent jobs, 64% have received job-related training during

the past year, and almost two-thirds are married. An overall incidence of overeducation is

reported by 14% of the individuals surveyed (Figure 7). For descriptions of the variables, see

Table 5.

Table 4. Summary statistics of key variables

Variable Mean SD Min Max Trust 0.56 0.49 0 1 Permanent job contract 0.79 0.40 0 1 Received training last year 0.64 0.48 0 1 Hours of work, standardized 0 1 -3.88 9.55 Has at least one child 0.26 0.44 0 1 Female 0.59 0.49 0 1 Married 0.59 0.49 0 1 Educational level 0.62 0.48 0 1 Public job 0.40 0.49 0 1 Tenure 42.26 38.48 0 491 Wages, standardized 0 1 -1.62 56 Age 31.00 4.95 25 100

39

Figure 7. Incidence of on-the-job training, overeducation, marriage, and permanency of job


40

Table 5. Variable descriptions Variable Description Trust 1 if respondent replied 4 or 5 on “Professional

colleagues rely on me as an authoritative source of advice”, 0 otherwise

Age Age of individual Marital status How do you live at present? 1 if with partner, 0

otherwise Female 1 if respondent is female, 0 otherwise Children 1 if respondent has at least 1 child, 0 otherwise Training 1 if respondent received training in the last 12

months, 0 otherwise Educational level 1 if the study program grants access to post-

graduate studies, 0 otherwise Tenure Duration of work experience at current job in

months Wages, standardized Gross hourly wages measured in euros Public 1 if individual works in the public sector, 0

otherwise Workload, standardized Working hours at current job Permanent Type of contract, 1 if permanent, 0 otherwise Supervision 1 if individual supervises, 0 otherwise Source: Authors’ elaboration

3.3 Descriptive statistics and distributions

Here we present descriptive statistics for the key variables. As was mentioned above, the

REFLEX survey covers a number of European countries. The largest share of individuals

interviewed (20%) comes from the Czech Republic, while the smallest group of respondents

(2%), comes from Portugal (Figure 8). As it can be seen from Figure 9, aggregated on the level

of countries, the highest mean level of trust is observed in Austria, while the lowest level of trust

is found among respondents from Belgium. We also find that the range of variations in the levels

of trust differ significantly from country to country.

41

Figure 8. Distribution of respondents in the REFLEX survey


Figure 9. Levels of trust in Europe

Source: REFLEX dataset, authors’ elaboration

Figure 10 shows the mean levels of trust in Europe broken down on the basis of gender.

The first striking observation is that in all of the countries surveyed, the levels of trust people feel

42

for men is higher in comparison to the levels of trust they feel for women. The mean level of

trust among Austrian males is almost 0.9 in comparison to 0.39 among females in Belgium.

Figure 10. Gender-based levels of trust in Europe

Source: REFLEX dataset, authors’ elaboration

Our key variable of interest is a competence and skills mismatch. Figure 10 provides the

distribution of skills and deficits among university graduates in Europe based on the answers

reported in the REFLEX questionnaire. We designed Figure 11 to indicate the difference

between “Required level of skill/competence in current work” and the self-reported level. Based

on the distribution, 45% of graduates in Europe have excess foreign language skills, and among

40% of these respondents, their work does not utilize their competence in questioning their own

and others’ ideas.

In contrast, around 25% of the individuals surveyed state that they lack an ability to use

time efficiently, while 16% report a deficit in the ability to work under pressure.

43

Farooq (2006) highlights the fact that many business ventures carefully evaluate the

financial assets that they possess; however, they fail to measure one of the most vital assets,

namely, time. Time management is one of the pillars of efficiency. The ability of individuals to

allocate time efficiently is an indicator of organizational commitment and well-developed work

habits. Management studies report that because individuals strive to be promoted within the work

environment, they are required to have skills in surplus. A review of the management literature

provides several variables that are related to improvements in time management within an

organization:

- Time management is largely based on the habits of the individual

- Effective communication increases time management

- Goals and targets allow one to allocate resources (time) better

- The ranking of priorities is vital

- Procrastination produces a deterioration in time management

Time management has an indirect impact on individuals since it leads to a higher level of

self-reported job satisfaction. Another factor that is significantly related to job satisfaction and

efficiency is the ability to perform under stress/pressure. Emm et al. (2008) define stress as an

emotional condition that arises when one does not have the power to resolve requirements. It is

shown that there is a direct link between productivity and pressure. Yet the link between stress

and efficiency is not monotonic. Overwhelming stress increases aggression and tension among

colleagues and causes individuals to make mistakes, whereas tolerable levels of stress increase

effort and productivity. The literature that examines stress from the perspective of social studies

dates back to Selye (1964), who describes stress as the “natural degeneration of the body and as

the non-specific response of the body to any demand”. A study aimed at investigating the effects

44

of stress on well-being in a sample of 400 employees shows that stress has negative links to

satisfaction and productivity. Indeed, trust and cooperation are positively associated with job

satisfaction.

Figure 11. Distribution of skills among university graduates

Figure 12 shows the distribution of skills based on a gender breakdown. We can see that

overall women report higher levels of deficits in language skills and a willingness to question

ideas. Turning to men, we see that the two skills that demonstrate the highest deficits are

computer skills and a willingness to question ideas.

Surplus of skill or competence

Deficit of skill or competence

45

We now turn to a discussion of primary pairwise correlations among our factors. As it

can be seen from the data, the highest correlations between our measures of trust and factors of

trust are found with type of contract, workload, and tenure – above 10% in each case (Appendix,

Table 1). Our primary analysis shows that, other things being equal, job-related factors are

associated positively with trust. We also find that women are less trusted in comparison to men.

One of the most striking findings is that the level of education has one of the lowest correlations

with trust. On the other hand, men report a higher surplus in time management skills in

comparison to women.

Figure 12. Distribution of skills matches based on gender

46

Indeed, a primary review of the data shows that there is a highly diverse distribution of

skills mismatches in the EU market, something that highlights the importance of exploring

separately the effects of each skill on trust.

4. RESULTS AND MAIN FINDINGS

As mentioned in previous sections, there are a number of ways in which to pursue

research objectives. One of the easiest and most direct steps is the simple correlation analysis

described below.

4.1 Simple correlation analysis and baseline specification

In this section, we attempt to establish a simple association between our measure of trust

and a set of variables that indicate mismatches for eighteen skills supplied by means of the

REFLEX survey. Table 6 provides the matrix of correlation. First, it is striking that any deviation

from a fit between the supply of skills and the demand for skills is negatively correlated with our

measure of trust. The highest correlation between trust and mismatches is observed for a surplus

in the ability to write reports and memos. The lowest association is between trust and a surplus in

the knowledge of other fields and disciplines. The value of correlation is -0.014. On the other

hand, the significance of these correlations might be reduced after we take into account the

indirect effects of mismatches through job outcomes and personal characteristics such as

education, gender, tenure, or workload. In the next section we will build up our logistic model by

introducing socio-economic and job-related factors.

47

On the other hand, such correlations may not indicate that mismatches between the skills

will have negative effects on trust in reality (Bessler, 2010; Kwon and Bessler, 2011). To address

this issue, we will proceed with an investigation using basic linear regression.

Table 6. Correlation matrix between trust and the skills mismatches

Type of competency Deficit Surplus Mastery of your own field or discipline -0.08 -0.08 Knowledge of other fields or disciplines -0.05 -0.01 Analytical thinking -0.05 -0.07 Ability to rapidly acquire new knowledge -0.06 -0.05 Ability to negotiate effectively -0.03 -0.05 Ability to perform well under pressure -0.09 -0.03 Alertness to new opportunities -0.04 -0.04 Ability to coordinate activities -0.04 -0.05 Ability to use time efficiently -0.03 -0.05 Ability to work productively with others -0.04 -0.04 Ability to mobilize the capacities of others -0.03 -0.04 Ability to make your meaning clear to others -0.05 -0.04 Ability to assert your authority -0.05 -0.01 Ability to use computers and the internet -0.03 -0.04 Ability to come up with new ideas and solutions -0.03 -0.07 Willingness to question your own and others’ ideas -0.02 -0.06 Ability to present products, ideas or reports to an audience -0.04 -0.03 Ability to write reports, memos or documents -0.03 -0.08 Ability to write and speak in a foreign language -0.01 -0.01


We will calculate a baseline logit function where the dependent variable, trust, is

regressed on outcome factors (age, gender, number of children, marital status, and level of

education) (Model 1). This is very important because we must first establish the effects of

outcomes on trust-related behavior. This step allows us to control for possible factors that are

omitted if trust is regressed on the mismatch variables in a two-factor model. Most importantly,

this will allow us to test Hypothesis 1, which conjectures that outcomes have effects on trust.

48

Table 7 provides the effects of personal outcomes (gender, education stock, age, etc.).

The results show that the coefficient of the variable female has a negative sign, indicating that

being female reduces trust-related behavior in an enterprise. This is not surprising, since this has

been supported by a number of studies, e.g., Sheehan (1999), who shows that trust concerns are

greater among females. Moreover, being married increases the likelihood of being an

authoritative source of advice for colleagues. In Model 1, trust is an increasing function of age.

The results show that expertise proxied by age, education, and marital status is positively linked

with trust. On the other hand, it is important to control for the U-shaped links between age and

trust. Ermish et al. (2009), Frijters and Beaton (2012), and Tiefenbach and Kohlbacher (2010)

show that age has non-monotonic effects on trust.

In Model 2 we account for the well-known U-shaped link between age and trust. As

previous studies have shown, the links between age and labor market outcomes (such as

satisfaction) are nonlinear. Using the methodology of empirical studies, we included age and age

squared/100) to calculate the nonlinear impact of age. Model 2 shows that trust-related behavior

among colleagues decreases when an individual is very young (in the very early stage of his or

her career) and very old.

Table 7. Pooled calculations of trust

Model 1 Model 2 children -0.007

(0.007) -0.01 (0.008)

female -0.09*** (0.006)

-0.09*** (0.006)

married 0.03*** (0.006)

0.03*** (0.006)

educational level 0.05*** (0.006)

0.04*** (0.006)

49

age 0.006*** (0.00)

0.03*** (0.004)

age2 /1000 -0.33*** (0.05)

_cons 0.35*** 0.02

-0.09 (0.08)

Number of observations 25,71 25,71 Sample Pooled Pooled Note: Dependent variable: trust; standard errors in parentheses; *p<.1, **p<.05, ***p<.01

Next, we investigate the links between trust and the remaining job outcomes. Building on

the findings from the previous section, we include job factors (training, hours of work, wages,

permanent, tenure, public job) in our calculations (Table 8).

We find that the level of education has a positive impact on trust. Colleagues exhibit

more trust toward individuals whose programs provided access to post-graduate studies. This is

in line with Hakhverdian and Mayne (2012), in which the authors show that education has a

positive impact on institutional trust. Workload, professional training in the past 12 months, and

tenure increase trust-related behavior among employees.

Table 8. Trust and job-related factors

Model 3 Model 4 children -0.015 -0.011

(-0.40) (-0.27) female -0.22*** -0.19***

(-7.42) (-6.17) married 0.13*** 0.11***

(4.22) (3.34) educational level 0.17*** 0.19***

(5.79) (6.03)

50

age 0.15*** 0.13***

(5.38) (4.79) age2 -0.17*** -0.15*** (-4.58) (-4.28) permanent 0.35*** 0.33***

(9.18) (8.41) training 0.310*** 0.313***

(10.01) (9.67) workload 0.19*** 0.20***

(12.40) (11.80) public -0.27*** -0.27***

(-8.86) (-8.52) tenure 0.004*** 0.005***

(8.96) (9.68) wages 0.10***

(7.15) _cons -3.29*** -2.90***

(-6.54) (-5.85)

N 20,57 18,89 Note: t statistics in parentheses. * p<0.05, ** p<0.01, *** p<0.001

According to Trevino et al. (1999), supervision and leadership are crucial characteristics

of organizations because they provide role models for their followers (employees) (Ciulla, 1999).

Hosmer (1995) notes that “trust is the expectation … of ethically justifiable behavior – that is

morally correct decision and action based upon ethical principles of analysis – on the part of the

other person, group, or firm in a joint endeavor or economic exchange”, which serves as an

important aspect of favorable relationships between managers and individuals, promoting mutual

cooperation (Argyris, 1970). In light of the findings of the above-mentioned studies, we included

variables to account for the effects of organizational leadership on trust. In our study, this is

51

measured by a variable (super) that takes value 1 if an individual directly supervises employees.

To compare gender-based effects of leadership on trust, we additionally control for interaction

effects of female leaders (Model 6). Our results show that being a leader increases trust-related

behavior by 18% (Table 9). The impact of leadership on trust is the strongest when compared to

other individual and job-related factors (Model 5). Surprisingly, Model 6 shows that although

being female reduces trust-related behavior, female supervisors are generally more trusted in

comparison to other females in the same environment. It is important to point out that the effects

of wages remain similar across different models; therefore, one of the indirect channels of

competence mismatches may run through wages. For example, deficits in a specific skill may

reduce earnings, consequently having indirect negative effects on trust.

Table 9. Trust and supervision

Model 5 Model 6 children -0.01 -0.01 (0.01) (0.01) female -0.04*** -0.06*** (0.01) (0.01) married 0.02*** 0.02*** (0.01) (0.01) educational level 0.05*** 0.05*** (0.01) (0.01) age 0.03*** 0.03*** (0.01) (0.01) age2 -0.35*** -0.34*** (0.07) (0.07) permanent 0.07*** 0.07*** (0.01) (0.01) training 0.07*** 0.07*** (0.01) (0.01) workload 0.03*** 0.03*** (0.00) (0.00) public -0.05*** -0.05*** (0.01) (0.01) tenure 0.00*** 0.00*** (0.00) (0.00) wages 0.02*** 0.02***

52

(0.00) (0.00) supervision 0.18*** 0.15*** (0.01) (0.01) female*supervision 0.07*** (0.01) _cons -0.20** -0.18* (0.10) (0.10) Number of observations 18,82 18,82 adj. R2 0.08 0.08 Note: Standard errors in parentheses, * p<.1, ** p<.05, *** p<.01

4.2 Trust and skill/competence mismatches

In this section, we will test Hypothesis 2. We calculate the impact of competencies

mismatches on trust (Tables 2 and 3, Appendix). According to the REFLEX and Hegesco

typology of required competencies, the professional expertise competencies include mastery of

your own field, analytical thinking, and an ability to assert authority. Based on fit theory we

create a set of variables that investigate the impact of skills deficits and surplus on trust.

Following our methodology, a surplus takes a 1 if the difference between “own” and “required”

competency is -2 or below, and a deficit if the difference between “own” and “required” is 2 or

above. Our results show that both over-competency and under-competency reduce trust-related

behavior among colleagues.

Tables 2 and 3 in the Appendix show the calculation of competencies mismatches and

trust-related behavior. In each of the calculations, we include only one type of skill or

competence. Our results show that in all of the calculations deficits are far more important in

explaining trust-related behavior among colleagues.

First, we include “mastery of your own field or discipline”. We find that a deficit or

surplus of that skill reduces trust-related behavior. It is important to highlight that the effects of a

53

deficit in “mastery of your own field” is negative and five times stronger than the surplus. One

conclusion is that “mastery in your own field” is influential for trust and for the productivity of

the respondents. In addition, this supports the theory of job matching where skills are an

important determinant of human capital and labor productivity.

Next, we include “knowledge of other fields or disciplines”. In contrast to previous

results, we find that the negative effects of a deficit in that skill are much weaker, while a surplus

of that skill has no effect on trust. This confirms the robustness of our findings.

Another skill under consideration is analytical thinking. A deficit in analytical thinking

exerts a significant negative impact on trust. Snyder and Snyder (2008) conclude that analytical

thinking is an important aspect of problem-solving and productivity. Therefore, a lack of such a

skill can have indirect negative effects on trust.

Similarly, a deficit in the “ability to rapidly acquire new knowledge” reduces trust. This

could be explained by the fact that this skill is important for adapting to a new environment and

new work-task challenges. A surplus of that skill does not reduce or increase trust among

colleagues.

Interestingly, we find that both a deficit and a surplus in a number of HR skills reduce

trust. For example, an ability to use time efficiently significantly reduces trust. Kvasov (2003)

concludes that time management has direct effects on firm productivity. Research from a medical

study shows that time management is an important aspect of leadership (Al-Haddad, 2003).

Taking this into account, we find that mismatches in this skill reduce trust through low

productivity and lack of leadership. The same results apply to the “ability to coordinate

activities”. Collaborative activities are an important aspect of a firm’s success, especially within

a corporate culture that is managed by a team of experts. This poor fit between demand and

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supply of that skill reduces trust. Robust results were also found in the “ability to work

productively with others” and “ability to make your meaning clear to others”.

For the “ability to assert your authority” we find that only a deficit has negative effects on

trust. This may be one of the lowest levels of correlation (less than 2%) between trust and a

surplus in that skill. Another explanation is the low level of a surplus of that skill among men in

our survey. Indeed, Brennan and Little (2010) support our findings. In an analysis of the labor

market in UK, they found that there is a lack in flexibly and in the number of adaptive

professionals who can activate the capacities of others.

For technical skills, the results are mixed. We find that a match in computer skills is an

essential element of trust. Lack of that skill is three times as important as is a surplus. The same

conclusion applies to the ability to write reports and memos and the ability to present products.

Gender differences play an important role in explaining determinants of trust. Therefore,

it is important to examine separately the impact of mismatches on trust among male and female

individuals (see Tables 4 and 5 in the Appendix). Our results show that the coefficients of these

discrepancies vary significantly. We find that being overskilled or underskilled in “mastery of

your own field” has a stronger impact on trust among males than among females. This means

that underutilization of this competency is a vital stress factor among men. One possible

explanation is that an education wage penalty for men increases with the degree of underskilling,

while we observe the reverse situation for an “analytical thinking” mismatch. Such a mismatch

exerts a stronger effect on trust in females. Black and Spitz (2008) report that women

increasingly participate in analytical tasks, thereby reducing the gender wage gap. In line with

recent improvements in the labor market, we suggest that tasks demanding more analytical skills

will have a stronger impact on women in comparison to men.

55

Surprisingly, we find that time management skills are not important for men. Our results

show that the coefficient for time management surplus and deficit are insignificant in our

calculations. In contrast, women who can manage time more efficiently are trusted more. We

conclude that the opportunity costs between career and family are high for women. Those who

remain in their careers and get married face significant dilemmas of time allocation. Lack of time

management skills increases stress and reduces efficiency, leading to mistrust. Psychological

literature offers several solutions concerning how to increase time management skills among

women:

1. Set priorities by breaking down job-related tasks as “must”, “should”, and “non-

important”

2. Understand your limits and abilities

3. Always follow your schedule

Our results show that deficits in the ability to coordinate activities are more important for

females (Model 43, Table 5 of the Appendix). Moreover, a lack of competency has a much

stronger impact on trust in comparison to being over-competent. Interestingly, we do not find

links between a surplus for analytical thinking and an ability to assert authority and trust. Our

possible explanation is that the impact of these competencies is gender-specific. Our results show

that deficits of competencies have stronger negative effects on trust among males compared to

among females (see Tables 4 and 5 in the Appendix).

Next, we investigate where skills mismatch and trust differ across different countries.

Table 6 of the Appendix shows country-specific calculations. To save space we report only the

significance and the direction of impact. First, it is important to note that for some types of skills,

countrywide effects vary. According to the Table, it is only in the Czech Republic that a surplus

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in the mastery of one’s own field reduces trust among employers. In the rest of the countries, a

surplus of those skills does not have any impact on trust. Another striking bit of evidence: a

deficit in the mastery of one’s own field does not reduce trust in Spain or Italy. We can explain

this by the fact that wages in these countries were rising among employees at the cost of

government borrowing and public debt.

Figure 13. Labor force participation rates in EU

Source: Eurostat

Turning to “knowledge of other fields or disciplines”, it is evident that overall this is not

related to trust. A surplus of those skills reduces trust only in Spain, Austria, and the UK. In

seven of the ten countries, a deficit in expertise in other disciplines does not reduce trust. This

could be due to one of the problems of management, that is, underutilization of labor knowledge.

The overall labor force participation rates have been rising in Europe (see Figure 13). This has

led to an increase in participation rates among the population (OECD, 2010). For example, such

rates have grown by 10.4% among 15–19-year-olds and by 10.1% for 20–29-year-olds. In fact,

57

in countries such as the Czech Republic and Sweden, the growth of rates of participation was

above the 12% level. Indeed, our results are confirmed by official data. A surplus of skills in the

Czech Republic significantly reduces trust-related behavior.

4.3 The indirect effects of competence mismatches on trust

We will examine the effects of skill mismatches on wages, for a number of reasons. First,

related studies conjecture that wages are the main variable that reflects returns from investment

in human capital. Second, the effects of experience, contract type, etc. will be influenced through

the wage-trust nexus.

Several studies (e.g., Quintini, 2011; Nordin et al., 2010; Dieter and Omey, 2006;

Groeneveld and Hartog, 2004) report that over- and undereducation reduce wages, something

that in turn may have effects on trust among individuals. To explore the indirect effects of skills

and competencies mismatches on trust through wages, we have performed econometric tests.

Table 7 of the Appendix shows that an overall surplus and deficit of skills reduce trust. A deficit

in “mastery of your own field or discipline” reduces the probability of being trusted by 0.13.

Indeed, the effects of a deficit are stronger in comparison to the effects of a surplus. Turning our

attention to “knowledge of other fields or disciplines”, the effects of a deficit are five times

stronger than the effects of a surplus. This may signal to an employee that a deficit in those skills

is instrumental for successful outcomes. The same results hold for analytical thinking and the

ability to rapidly acquire new knowledge.

It is important to note that we get different results for the ability to negotiate effectively.

Indeed, while a deficit in that skill reduces trust, those who report a surplus in that skill have a

greater level of trust among colleagues. We also find that a surplus in the ability to negotiate

58

effectively does not reduce trust. In general, these two skills are associated with time

management and may signal that time management is an important factor for job outcomes. We

find negative effects for a deficit or surplus for the ability to perform well under pressure,

alertness to new opportunities, and the ability to coordinate activities.

For the ability to use time efficiently, we fail to find negative effects of a deficit in that

skill. A deficit in the ability to work productively with others is twice as strong in comparison to

a surplus in that skill. The effects of mismatches in the ability to mobilize the capacities of others

are in line with previous results.

However, among the few skills where a surplus of skills exerts stronger negative effects

on trust is an ability to make your meaning clear to others and a willingness to question your own

and others’ ideas. Finally, a surplus in foreign language skills does not influence trust.

The results in Table 7 of the Appendix show that skills mismatches have direct effects on

trust and indirect effects on trust by reducing wages.

5. CONCLUSION: POLICY IMPLICATIONS AND

AVENUES FOR FUTURE RESEARCH

In our calculations, we found that training and supervision increase trust-related behavior

among colleagues. A survey of the literature shows that trust can actually be taught. The case

study by Neal (2013) suggests that proactive training increases the level of trust within the work

environment. Moreover, the study shows that half of the value of the Fortune 500 corporations is

based on trust. There are two types of training. The first type aims to increase integrity among

colleagues. Integrity is an important part of the production process because it allows for diffusion

59

and knowledge-reducing inflation asymmetry in the environment. The second type of training is

directed at increasing the qualifications of the employees. It is argued that training increases

productivity and leads to a better utilization of skills. In these kinds of training, it is important to

account for factors such as age, gender, culture, and experience.

A case study on trust and training from Neal (2013)

A project in the USA that was to continue for ninety days, and that was supervised by a

group of IT engineers from India, was closed down and the team returned to India. The reason

was mistrust between the western workers and the Indian specialists. To save the project and the

investment, special training that addressed the issue of trust was set up. Within a few days the

result was an increase in performance, cooperation, and trust among all the members of the

project. According to the trainee, the main reasons for mistrust were cultural misunderstandings.

The Indian workers were guests in the USA, and they assumed that they would be treated as they

themselves treat guests in their home country. Meanwhile, their American colleagues were

concerned only with the launch of the project. Such relationships reduced the level of trust and

led to disruptions. The teambuilding training made it possible to recover trust and increase

productivity.

Another study by Jones et al. (2008) investigates the links between training and

productivity. This study is built around the idea that skills can be classified as either generic or

specific. Individuals who aim to increase general skills are more satisfied and have higher

turnover rates. However, underutilization of specific skills hampers well-being and creates

antagonistic behavior among individuals. This creates exit costs since these skills are firm-

specific. The study cites seminal papers that show that overskilling has a negative impact on

60

promotion. In our opinion, this is one channel of influence of skill mismatches on trust.

Individuals who are not promoted and who possess superior skills are more likely to be

mistrusted by their colleagues. These links become more complex considering that Buchel

(2002) fails to find such links in Germany.

The indirect links between mismatches on trust through employment can be seen by way

of productivity. Training leads to an increase in productivity. One of the calculations shows that

a 1% increase in skill utilization after training leads to a 0.6% increase in productivity. Further

examinations show that specific skills increase productivity and wages more than generic skills.

This is more evident in small establishments. Overeducation and overskilling are associated with

absenteeism. Absenteeism reduces effort and can be very damaging to the success of a company.

Educational mismatches have been carefully studied in the scientific literature.

Understanding the misfit between person and job is important in order to improve the efficiency

of the labor market and productivity. However, a number of issues arise in examining such labor

market interactions. First, there is the issue of measuring mismatches. Existing studies and case

studies are based on self-reported levels of matching. This measure suffers from high levels of

subjectivity. Indeed, problems become more complex when we measure the mismatches between

person and job. One of the theories that addresses the causes and the measurement of such

mismatches is human capital theory.

According to human capital theory, mismatches occur due to information asymmetry

among employers and employees (Jovanovic, 1979) or because of deficits of knowledge among

individuals. The key issue is not measuring unobservable mismatches. Significant numbers of

studies test job matching theories based on self-reported mismatch questions (see Allen and van

61

der Velden, 2001; Green and McIntosh, 2007; Verhaest and Omey, 2006). This is a preferred

approach in the literature. In this study we relied on the self-reported levels of matches between

persons and jobs. Our approach is supported in human resources literature. Locke and Schneider

argue that the deviation from the fit (required and current supply of skills) has observable

impacts on labor market decisions.

In our study, we followed the work of previous studies and examined the links between

management outcomes (trust-related behavior) and person-job skill mismatches. In order to do

this, we relied on a mainstay theory developed by Caplan et al. (1974), fit theory. This theory

postulates that misfits between person and job requirements lead to negative outcomes such as

dissatisfaction, stress, turnover, and adverse behavior (tension and mistrust). The fit theory was

statistically tested using basic logistic regression calculations.

In our study we use secondary data. This has given us a significant advantage when it

comes to contributing to existing studies. The REFLEX dataset is a cross-section type of data

which has been used in a number of seminal research works. Therefore, our results are valid,

generalizable, and reliable. After primary correlation analysis and statistical logit regressions, we

report that a number of socio-economic variables and skills mismatches are associated with the

degree of trust.

For example, being female is associated with lower trust levels in comparison to being

male. The coefficient of the female variable, after controlling for different factors, is -0.092. This

implies that female workers who suffer from mismatches report severe levels of mistrust. To

reduce such gaps, the on-the-job training must be adjusted frequently to compensate for a lack of

skills.

62

Married people, on average, report higher levels of trust compared to single respondents.

This can be a spillover effect from family life experiences. Psychological studies show that

married people have gained greater life experience in comparison to their single counterparts.

We find that age has a non-monotonic impact on trust, which is in line with previous studies in

business management literature. This means that experience gained over the life cycle and a

skills mismatch is reduced with an increase in tenure. Among other job-related factors that are

associated with trust we find that workload, supervision, and tenure have positive impacts on

trust. We maintain that these variables increase the experience of an individual, something that is

associated positively with trust.

Our main focus of interest is skills/competence mismatches. For each of the nineteen

types of skills/competencies offered in the REFLEX survey, we generated a self-reported level of

skills matches based on the difference between the required and an individual’s own level of

skills/competence. Our results show that, in general, a deficit in skills reduces trust-related

behavior. However, the impact of these mismatches is different depending on the skill type.

Surprisingly, gender-based calculations present a slightly different picture. Lack of analytical

and time management skills significantly inhibit trust-related behavior toward women.

Compared to other studies we show that it is not skills that increase trust but the match

between the required skills and a person’s own skills. One of the ways to overcome the mismatch

and increase trust is by specific job-related training. Our results show that training is a

statistically significant predictor of trust. We find an important solution when investigating

gender-based differences in trust-related behavior. Our results show that deficits in analytical and

negotiation skills reduce trust more for women in comparison to men. We suggest an increase in

leadership and communication workshops designed specifically for women to target their needs.

63

Female leaders are currently playing a greater role, yet negotiating skills are an important aspect

of a successful leader. We maintain that our results provide an important cautionary note for

management and HR studies.

On the other hand, we show that men who do not master their own fields or disciplines

and who cannot make their meaning clear to others are less trusted within the work environment

in comparison to their female colleagues. We consider underqualification the most important

factor for men since it leads to human capital depreciation and reduces productivity. Studies

suggest that this occurs also among young workers, minorities, and female workers. An increase

in the number of graduate students with skill deficits leads to labor market uncertainty.

Therefore, we suggest increasing traineeships for university students that allow them to gain the

types of skills required in the labor market. We also assume that an elimination of skills

mismatches has important social outcomes because it increases well-being, productivity, and

reduces intentions that lead to turnover among workers.

Interestingly, we find that the impact of skills mismatches on trust is also country

specific. This could be due to specific labor market conditions and laws that regulate or restrict

labor mobility by imposing employment protection laws on organizations.

64

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76

APPENDIX REFLEX Questionnaire (related questions)

MASTER QUESTIONNAIRE

• This questionnaire is about the study programme that you finished in 1999/2000. Unless explicitly indicated otherwise, the term ‘study programme’ refers to this study programme.

• If you finished more than one study programme in 1999/2000, we would like you to refer to the study programme you consider the most important for your professional development.

• Please use a black or blue pen to fill in the questionnaire. • Please mark your answer by placing a cross X in the relevant box.

Some questions allow multiple answers. Where this is the case, this is clearly indicated.

• If you would like to correct your answer, completely blacken the box, and mark the right answer. If the question requires you to fill in a number, please fill in only one digit per box.

• If the question requires you to fill in text, please use capital letters. • If you are unsure of the exact answer to some questions, please

estimate the answer to the best of your ability.

77

Please answer these questions about your current (self) employment situation ■ If you are still in the job you first held after graduation in 1999/2000, please answer these questions for the situation as it is now ■ If you have more than one job, please answer the questions for the job in which you work the highest number of hours

F1 What is your current occupation or job title? (e.g. civil engineer, lawyer, assistant accountant, nurse)

П the same as listed above for first job □ other (please specify):

F2 Please describe your current main tasks or activities. (e.g. analysing test results, making diagnoses, teaching classes,

developing a marketing plan)

□ the same as listed above for first job □ other (please specify):

F3 Are you self-employed? □ yes О no -> go to F5

F4 Are you mainly dependent on one client or several clients? □ mainly one client -> go to F6 □ several clients -> go to F6

F5 What is your current type of contract? □ unlimited term 1 1 fixed-term, for I I I months □ other (please specify):

F6 What are your average working hours?

Regular/contract hours in main employment I I I per week

Paid or unpaid average overtime in main employment I I I per week

Average hours in other paid work I I I per week

F7 What are your gross monthly earnings?

From contract hours in main employment about ! I ! I I I EURO per month

From overtime or extras in main employment about ! I ! I I I EURO per month

From other work about I I I I I I EURO per month

F8 What type of education do you feel is most appropriate for this work? □ PhD □ other postgraduate qualification □ master □ bachelor □ lower than higher education

F9 What field of study do you feel is most appropriate for this work? □ exclusively own field □ own or a related field □ a completely different field □ no particular field

F10 How much time would it take for an average graduate with the relevant

educational background to become an expert in this kind of work? □ 6 months or less □ 7 to 12 months □ 1 to 2 years П 3 to 5 years П 6 to 10 years □ more than 10 years

F11 To what extent are your knowledge and skills utilized in your current

work?

not at all 1 2 3 45 to a very high extent O O O O O

Please answer these questions about your current (self) employment situation ■ If you are still in the job you first held after graduation in 1999/2000, please answer these questions for the situation as it is now ■ If you have more than one job, please answer the questions for the job in which you work the highest number of hours

78

The following questions refer to the organization in which you are currently employed • If you are self-employed, these questions apply to yourself or, if applicable, to the organization you run

G1 When did you start working with your current employer/ start your self-

employment?

i 1 i months i i i i i (year)

G2 In what economic sector do you work? (e.g. car manufacturing, primary school, hospital)


What kind of product or service does the organization provide? (e.g. nursing patients, computer components, legal advice, scientific

research)


G3 Do you work in the public or private sector? П public sector П private non-profit sector □ private profit sector □ other (please specify):

G4 Where do you work? Town/city

Country: □ UK □ other (please specify):

G5 How strong is the competition in the market in which your organization

operates?

very weak 123 45 strong not applicable О О О О О О

G6 Does your organization compete mainly by price or by quality? mainly price 123 45 qUality not applicable О О О О О О

G7 How stable is demand in the market in which your organization

operates?

highly stable 123 45 unstable not applicable О О О О О О

G8 What is the scope of operations of your organization? □ local □ regional □ national □ international

79

H1 Below is a list of competencies. Please provide the

following information: • How do you rate your own level of competence? • What is the required level of competence in your

current work? If you are not currently employed, only fill in column A

H Competencies

B Required level in current work Very low < ......> very high

1 2 3 4 5 6 7

a Mastery of your own field or discipline О О О О О О О О О О О О О О

b Knowledge of other fields or disciplines О О О О О О О О О О О О О О

c Analytical thinking О О О О О О О О О О О О О О

d Ability to rapidly acquire new knowledge О О О О О О О О О О О О О О

A Own level Very low < ...... > very high

1 2 3 4 5 7

e Ability to negotiate effectively О О О О О О О О О О О О О О

f Ability to perform well under pressure О О О О О О О О О О О О О О

g Alertness to new opportunities О О О О О О О О О О О О О О

h Ability to coordinate activities О О О О О О О О О О О О О О

i Ability to use time efficiently О О О О О О О О О О О О О О j Ability to work productively with others О О О О О О О О О О О О О О

k Ability to mobilize the capacities of others О О О О О О О О О О О О О О

l Ability to make your meaning clear to others О О О О О О О О О О О О О О

m Ability to assert your authority О О О О О О О О О О О О О О

n Ability to use computers and the internet О О О О О О О О О О О О О О

o Ability to come up with new ideas and solutions О О О О О О О О О О О О О О

p Willingness to question your own and others’ ideas О О О О О О О О О О О О О О

q Ability to present products, ideas or reports to an audience О О О О О О О О О О О О О О

r Ability to write reports, memos or documents О О О О О О О О О О О О О О

s Ability to write and speak in a foreign language О О О О О О О О О О О О О О

80

K8 How do you live at present? Alone (incl. single parent) With a partner With parents Other, please specify

K9 Do you have children? □ yes, 1 child

E7 Are you currently in paid employment? yes, I have one job (Include self-employment) yes, I have more than one job О no

yes, 2 children yes, 3 or more children О no

81

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or

disc

iplin

es

Def

icit

-0

.24*

**

(0

.05)

Surp

lus

-0

.07

(0

.04)

Ana

lytic

al th

inki

ng

Def

icit

-0.5

6***

(0.0

7)

Surp

lus

-0.0

6

(0.0

4)

Abi

lity

to ra

pidl

y ac

quire

new

kn

owle

dge

Def

icit

-0

.71*

**

(0

.07)

Surp

lus

-0

.07

(0

.04)

Abi

lity

to n

egot

iate

effe

ctiv

ely

Def

icit

-0.2

8***

(0.0

5)

Surp

lus

-0.1

0**

(0

.05)

A

bilit

y to

per

form

wel

l und

er

pres

sure

D

efic

it

-0.4

2***

(0.0

5)

Su

rplu

s

-0.1

1**

(0

.05)

Ale

rtnes

s to

new

opp

ortu

nitie

s D

efic

it

-0

.23*

**

(0

.05)

Su

rplu

s

-0

.04

(0

.04)

A

bilit

y to

coo

rdin

ate

activ

ities

D

efic

it

-0.4

6***

(0.0

6)

Su

rplu

s

-0.1

9***

(0.0

5)

A

bilit

y to

use

tim

e ef

ficie

ntly

D

efic

it

-0

.21*

**

(0

.05)

Su

rplu

s

-0

.11*

*

(0.0

5)

N

13

955

1485

6 15

105

1522

2 14

236

1403

8 14

837

1470

6 14

012

83

Stan

dard

erro

rs in

par

enth

eses

: * p

<.1,

**

p<.0

5, *

** p

<.01

. Con

trol v

aria

bles

incl

uded

but

not

repo

rted

Tabl

e 3.

Tru

st re

late

d be

havi

or a

nd c

ompe

tenc

e m

ism

atch

con

tinue

d

Sk

ills

Mod

el 1

6 M

odel

17

Mod

el 1

8 M

odel

19

Mod

el 2

0 M

odel

21

Mod

el 2

2 M

odel

23

Mod

el 2

4 M

odel

25

Abi

lity

to w

ork

prod

uctiv

ely

with

oth

ers

Def

icit

-0.3

6***

(0

.07)

Surp

lus

-0.1

4***

(0

.05)

Abi

lity

to m

obili

ze th

e ca

paci

ties o

f oth

ers

Def

icit

-0

.10*

(0

.05)

Su

rplu

s

-0.0

5

(0

.05)

A

bilit

y to

mak

e yo

ur

mea

ning

cle

ar to

oth

ers

Def

icit

-0.3

9***

(0

.05)

Surp

lus

-0.0

9*

Abi

lity

to a

sser

t you

r au

thor

ity

Def

icit

-0

.23*

**

(0.0

5)

Surp

lus

0.

06

(0.0

5)

Abi

lity

to u

se c

ompu

ters

an

d th

e in

tern

et

Def

icit

-0.5

0***

(0

.08)

Surp

lus

-0.1

6***

(0

.04)

Abi

lity

to c

ome

up w

ith

new

idea

s and

solu

tions

D

efic

it

-0.5

5***

(0

.06)

Su

rplu

s

-0.1

7***

(0

.04)

W

illin

gnes

s to

ques

tion

your

ow

n an

d ot

hers

’ ide

as

Def

icit

-0.4

9***

(0

.07)

Surp

lus

-0.1

0***

(0

.04)

Abi

lity

to p

rese

nt p

rodu

cts,

idea

s or r

epor

ts to

an

audi

ence

Def

icit

-0

.29*

**

(0.0

5)

Surp

lus

-0

.10*

*

(0

.04)

A

bilit

y to

writ

e re

ports

, m

emos

or d

ocum

ents

Def

icit

-0.4

0***

(0

.06)

84

Surp

lus

-0.2

6***

(0

.04)

Abi

lity

to w

rite

and

spea

k in

a fo

reig

n lan

guag

e D

efic

it

-0.1

1**

(0.0

5)

Surp

lus

0.

01

(0.0

4)

N

14

924

1435

6 14

082

1438

0 16

128

1448

6 15

500

1465

3 15

025

1580

7 St

anda

rd e

rrors

in p

aren

thes

es: *

p<.

1, *

* p<

.05,

***

p<.

01. C

ontro

l var

iabl

es in

clud

ed b

ut n

ot re

porte

d

85

Tabl

e 4.

Tru

st, c

ompe

tenc

e m

ism

atch

and

gen

der

M

odel

26

Mod

el 2

7 M

odel

28

Mod

el 2

9 M

odel

30

Mod

el 3

1 M

odel

32

Mod

el 3

3 M

odel

34

Mod

el 3

5 M

odel

36

Mod

el 3

7

Ana

lytic

al th

inki

ng

defic

it -0

.58*

**

-0.5

5***

(-4

.98)

(-6

.86)

su

rplu

s -0

.07

-0.0

5

(-1

.06)

(-0

.92)

Abi

lity

to a

sser

t you

r au

thor

ity

defic

it

-0.2

5***

-0

.22*

**

(-3

.53)

(-4

.11)

surp

lus

0.

03

0.04

(0.4

8)

(0.7

0)

Mas

tery

of y

our o

wn

field

or d

iscip

line

defic

it

-0

.94*

**

(-0.0

8)

-0.6

5***

(0

.06)

Surp

lus

-0.1

8***

(0

.07)

-0

.17*

**

(0.0

6)

Kno

wled

ge o

f oth

er

field

s or d

isci

plin

es

defic

it

-0

.20*

* (0

.09)

-0

.25*

**

(0.0

7)

surp

lus

-0.0

9 (0

.06)

-0

.05

(0.0

5)

Ana

lytic

al th

inki

ng

Def

icit

-0.6

4***

(0

.11)

-0

.75*

**

(0.0

9)

Surp

lus

-0.0

71

(0.0

6)

-0.0

6 (0

.05)

Abi

lity

to n

egot

iate

ef

fect

ivel

y D

efic

it

-0

.24*

**

(0.0

7)

-0.2

7***

(0

.06)

Surp

lus

-0.0

8 (0

.07)

-0

.11*

(0

.06)

Sam

ple

Mal

e Fe

mal

e M

ale

Fem

ale

Mal

e Fe

mal

e M

ale

Fem

ale

Mal

e Fe

mal

e M

ale

Fem

ale

N

68

07

9596

64

62

9164

57

19

8236

61

52

8704

62

11

9011

58

10

8426

Not

e: st

anda

rd e

rrors

in p

aren

thes

es: *

p<0

.05,

**

p<0.

01, *

** p

<0.0

01. C

ontro

l var

iabl

es in

clud

ed b

ut n

ot re

porte

d

86

Tabl

e 5.

Tru

st, c

ompe

tenc

e m

ism

atch

and

gen

der

M

odel

38

Mod

el 3

9 M

odel

40

Mod

el 4

1 M

odel

42

Mod

el 4

3 M

odel

44

Mod

el 4

5 M

odel

46

Mod

el 4

7 M

odel

48

Mod

el 4

9

Abi

lity

to p

erfo

rm

wel

l und

er p

ress

ure

Def

icit

-0.4

0***

(0

.08)

-0

.41*

**

(0.0

6)

Surp

lus

-0.1

6**

(0.0

8)

-0.0

8 (0

.06)

Ale

rtnes

s to

new

op

portu

nitie

s D

efic

it

-0

.19*

* (0

.08)

-0

.25*

**

(0.0

6)

Surp

lus

-0.0

47

(0.0

6)

-0.0

54

(0.0

5)

Abi

lity

to c

oord

inat

e ac

tiviti

es

Def

icit

-0.3

4***

(0

.09)

-0

.55*

**

(0.0

8)

Surp

lus

-0.2

1***

(0

.07)

-0

.17*

**

(0.0

6)

Abi

lity

to u

se ti

me

effic

ient

ly

Def

icit

-0

.11

(0.0

7)

-0.2

8***

(0

.06)

Surp

lus

-0.1

12

(0.0

8)

-0.0

96

(0.0

6)

Abi

lity

to w

ork

prod

uctiv

ely

with

ot

hers

Def

icit

-0

.32*

**

(0.1

0)

-0.3

7***

(0

.08)

Surp

lus

-0.1

02

(0.0

7)

-0.1

5***

(0

.06)

Abi

lity

to m

ake

your

m

eani

ng c

lear

to

othe

rs

Def

icit

-0

.42*

**

(0.0

8))

-0.3

6***

(0

.06)

Surp

lus

-0.1

0 (0

.07)

-0

.06

(0.0

6)

Sa

mpl

e M

ale

Fem

ale

Mal

e Fe

mal

e M

ale

Fem

ale

Mal

e Fe

mal

e M

ale

Fem

ale

Mal

e Fe

mal

e

N

57

25

8313

64

62

8723

58

92

8236

56

07

8405

60

92

8832

58

11

8426

Not

e: st

anda

rd e

rrors

in p

aren

thes

es: *

p<0

.05,

**

p<0.

01, *

** p

<0.0

01. ;

We

did

not r

epor

t sta

tistic

ally

insi

gnifi

cant

skill

s ‘A

bilit

y to

mob

ilize

the

capa

citie

s of o

ther

s’. C

ontro

l var

iabl

es in

clud

ed b

ut n

ot re

porte

d

87

Tabl

e 6.

Tru

st a

nd se

lect

ed c

ount

ry sp

ecifi

c ca

lcul

atio

ns

Cou

ntry

Mas

tery

of

your

ow

n fie

ld

or d

iscip

line

Kno

wle

dge

of

othe

r fie

lds o

r di

scip

lines

Ana

lytic

al

thin

king

A

bilit

y to

rap

idly

ac

quir

e ne

w

know

ledg

e

Abi

lity

to

nego

tiate

ef

fect

ivel

y

Abi

lity

to

perf

orm

wel

l un

der

pres

sure

Ita

ly

Def

icit

of sk

ill

Not

sign

ifica

nt

Not

sign

ifica

nt

Not

sign

ifica

nt

Not

sign

ifica

nt

Not

sign

ifica

nt

Not

sign

ifica

nt

Not

sign

ifica

nt

Not

sign

ifica

nt

Not

sign

ifica

nt

Not

sign

ifica

nt

Neg

ativ

e N

egat

ive

Surp

lus o

f ski

ll Sp

ain

Def

icit

of sk

ill

Not

sign

ifica

nt

Neg

ativ

e N

ot si

gnifi

cant

N

egat

ive

Neg

ativ

e N

egat

ive

Neg

ativ

e N

ot si

gnifi

cant

N

ot si

gnifi

cant

N

ot si

gnifi

cant

N

egat

ive

Neg

ativ

e Su

rplu

s of s

kill

Fran

ce

Def

icit

of sk

ill

Neg

ativ

e N

ot si

gnifi

cant

N

egat

ive

Not

sign

ifica

nt

Neg

ativ

e N

ot si

gnifi

cant

N

egat

ive

Neg

ativ

e N

ot si

gnifi

cant

N

ot si

gnifi

cant

N

egat

ive

Not

sign

ifica

nt

Surp

lus o

f ski

ll A

ustri

a D

efic

it of

skill

N

egat

ive

Neg

ativ

e N

ot si

gnifi

cant

N

egat

ive

Neg

ativ

e N

ot si

gnifi

cant

N

egat

ive

Not

sign

ifica

nt

Neg

ativ

e N

egat

ive

Neg

ativ

e N

ot si

gnifi

cant

Su

rplu

s of s

kill

Ger

man

y D

efic

it of

skill

N

egat

ive

Not

sign

ifica

nt

Not

sign

ifica

nt

Not

sign

ifica

nt

Not

sign

ifica

nt

Not

sign

ifica

nt

Neg

ativ

e N

ot si

gnifi

cant

N

ot si

gnifi

cant

N

ot si

gnifi

cant

N

egat

ive

Not

sign

ifica

nt

Surp

lus o

f ski

ll N

ethe

rland

s

Def

icit

of sk

ill

Neg

ativ

e N

ot si

gnifi

cant

N

egat

ive

Not

sign

ifica

nt

Neg

ativ

e N

ot si

gnifi

cant

N

ot si

gnifi

cant

N

egat

ive

Neg

ativ

e N

ot si

gnifi

cant

N

egat

ive

Not

sign

ifica

nt

Surp

lus o

f ski

ll U

K

Def

icit

of sk

ill

Neg

ativ

e N

ot si

gnifi

cant

N

ot si

gnifi

cant

N

egat

ive

Not

sign

ifica

nt

Not

sign

ifica

nt

Neg

ativ

e N

ot si

gnifi

cant

N

egat

ive

Not

sign

ifica

nt

Neg

ativ

e N

ot si

gnifi

cant

Su

rplu

s of s

kill

Finl

and

Def

icit

of sk

ill

Neg

ativ

e N

ot si

gnifi

cant

N

ot si

gnifi

cant

N

ot si

gnifi

cant

N

egat

ive

Not

sign

ifica

nt

Neg

ativ

e N

ot si

gnifi

cant

N

ot si

gnifi

cant

N

ot si

gnifi

cant

N

ot si

gnifi

cant

N

egat

ive

Surp

lus o

f ski

ll N

orw

ay

Def

icit

of sk

ill

Neg

ativ

e N

ot si

gnifi

cant

N

ot si

gnifi

cant

N

ot si

gnifi

cant

N

ot si

gnifi

cant

N

ot si

gnifi

cant

N

egat

ive

Not

sign

ifica

nt

Neg

ativ

e N

ot si

gnifi

cant

N

egat

ive

Not

sign

ifica

nt

Surp

lus o

f ski

ll C

zech

D

efic

it of

skill

N

egat

ive

Neg

ativ

e N

egat

ive

Not

sign

ifica

nt

Neg

ativ

e N

ot si

gnifi

cant

N

egat

ive

Not

sign

ifica

nt

Neg

ativ

e N

egat

ive

Neg

ativ

e N

ot si

gnifi

cant

Su

rplu

s of s

kill

Not

e: F

or th

e sa

ke o

f com

paris

on p

urpo

ses,

we

prov

ide

only

sig

nific

ance

and

dire

ctio

n of

the

effe

ct o

f mis

mat

ches

. Con

trol v

aria

bles

incl

uded

but

not

repo

rted

88

Tabl

e 7.

The

effe

ct o

f ski

ll m

ism

atch

es o

n w

ages

Pane

l A

(1

) (2

) (3

) (4

) (5

) (6

) (7

) (8

)

mas

tery

of

your

ow

n fie

ld o

r di

scip

line

know

ledg

e of

ot

her f

ield

s or

dis

cipl

ines

anal

ytic

al

thin

king

ab

ility

to

rapi

dly

acqu

ire n

ew

know

ledg

e

abili

ty to

ne

gotia

te

effe

ctiv

ely

abili

ty to

pe

rform

wel

l un

der

pres

sure

aler

tnes

s to

new

op

portu

nitie

s

abili

ty to

co

ordi

nate

ac

tiviti

es

Def

icit

-0.1

3***

-0

.15*

**

-0.1

8***

-0

.12*

**

-0.1

0***

-0

.30*

**

-0.2

0***

-0

.16*

**

(0

.015

) (0

.016

) (0

.021

) (0

.021

) (0

.014

) (0

.015

) (0

.016

) (0

.019

)

Surp

lus

-0.1

0***

-0

.036

***

-0.0

30**

0.

047*

**

0.01

6 -0

.042

***

-0.0

73**

* -0

.040

***

(0

.014

) (0

.013

) (0

.013

) (0

.012

) (0

.013

) (0

.015

) (0

.012

) (0

.014

) C

onst

ant

2.37

2***

2.

351*

**

2.35

3***

2.

336*

**

2.34

4***

2.

389*

**

2.36

3***

2.

356*

**

(0

.006

) (0

.006

) (0

.006

) (0

.006

) (0

.006

) (0

.006

) (0

.006

) (0

.006

) N

1544

1 16

411

1671

0 16

815

1573

4 15

519

1637

6 16

276

adj.

R2 0.

007

0.00

6 0.

005

0.00

3 0.

004

0.02

7 0.

011

0.00

5 Pa

nel B

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

ab

ility

to u

se

time

effic

ient

ly

abili

ty to

w

ork

prod

uctiv

ely

with

oth

ers

Abili

ty to

m

obili

ze th

e ca

paci

ties o

f ot

hers

abili

ty to

m

ake

your

m

eani

ng

clea

r to

othe

rs

abili

ty to

as

sert

your

au

thor

ity

abili

ty to

use

co

mpu

ters

an

d th

e in

tern

et

abili

ty to

co

me

up

with

new

id

eas a

nd

solu

tions

will

lingn

ess t

o qu

estio

n yo

ur

own

and

othe

rs’ i

deas

Def

icit

-0.0

1 -0

.14*

**

-0.1

0***

-0

.07*

**

-0.1

7***

-0

.05*

* -0

.12*

**

-0.0

5**

(0

.014

) (0

.020

) (0

.015

) (0

.015

) (0

.014

) (0

.022

) (0

.017

) (0

.020

)

Supr

lus

-0.0

85**

* -0

.073

***

-0.0

81**

* -0

.101

***

-0.0

53**

* 0.

025*

* -0

.080

***

-0.0

54**

*

(0.0

16)

(0.0

14)

(0.0

14)

(0.0

15)

(0.0

13)

(0.0

12)

(0.0

13)

(0.0

12)

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Trust Related Behavior and Person-Job Fit Among University Graduates in Europe

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Transcript of Trust Related Behavior and Person-Job Fit Among University Graduates in Europe