The Post Apprentice Student and the Others,

Field Evidence from an Entrepreneurship Module in Higher Education in Norway

Øivind Strand*a

Ola Jon Morkb

* Corresponding author; a Aalesund University College, Department of International Business, PO Box 1517, 6025 Aalesund,

Norway; +47 70 16 12 00; ost@hials.no

b Aalesund University College, Department of Maritime Technology and Operations, PO Box 1517, 6025 Aalesund, Norway; +47 70 16 14 90; om@hials.no

Abstract:

This paper deals with the measurements of emotions, power, status and performance in teams within an entrepreneurship module at Ålesund University College. Our focus is on the difference between post apprentice students who hold a vocational diploma when entering a degree programme and the other students. The purpose of the paper is threefold: First to develop and verify a Norwegian version of the Pana X scale for measurement of emotions. Second we develop and test a questionnaire measuring power and status in teams. Third we search for systematic differences between the two student groups. The main findings can be summarized as follows:

• The diploma students report more joy, less fear, and less ambivalence. • The moderation of joy is associated with interaction between fear and status for the

diploma student, whereas interactions with the power factor are more important for the non-diploma students.

• The diploma students have a higher level of status in the groups. Keywords: emotions, entrepreneurship, vocational training, ambivalence

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Are post apprentice students different from other students?

The authors have observed that most entrepreneurship competitions in higher education in

Norway are dominated by teams with one or more post apprentice, or diploma student (Hatlø

et al. 2011, Mork et al. 2013). A post apprentice student is a student who, when entering

higher education already holds a diploma in an industrial skill. Based on experience with

more than 100 student teams, the authors have observed that there seem to be stronger

emotional conflicts in entrepreneurial teams with diploma students (Mork and Strand, 2014).

The important role of emotions in these processes is closely aligned to an increased research

interest into the role of emotions in entrepreneurship (Souitaris et al. 2007, Podoynitsya et al.

2012, Welpe et al. 2012).

The students entering higher education institutions have varied backgrounds. In Norway,

most students traditionally come from upper secondary schools with exams in

theoretical/academic subjects. It is expected that the number of post apprentice students with

a vocational training and background from the industry, will increase in the years to come. In

Ålesund University College (AUC), Department of Maritime Technology and Operations, a

third of the engineering students have such a background. This development is due to an

increasing emphasis on lifelong learning for competitiveness, employability, and social

inclusion (EU, 2006; OECD, 2005), but also to rapid transformations in traditional industries.

The development of the knowledge-based economy causes the pace of change in the industry

to be high. The institutional setting for this study is a small university college (2000 students)

located in Ålesund (45,000 inhabitants) in the county of Møre and Romsdal (260,000

inhabitants) (Helgesen et al 2013). The respondents are recruited from the second year of a

three year bachelor program in Product Development and System Design. The study relates

to a course module in entrepreneurship, where students in groups are required to develop a

business idea and to build a prototype of the actual product. This study is a part of ongoing

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research aiming to better understanding the dynamics of student teams comprising a mix of

students with and without an industrial background.

It is generally known that one of the major challenges using quantitative research methods in

entrepreneurship research are the small samples. This paper overcomes this challenge through

the use of multiple responses from the same participants.

This study uses the Pana X- scale (Watson and Clark, 1994) for measuring the emotional

constructs, fear and joy. These scales have previously been used by Welpe et al. (2012) in the

field of entrepreneurship. To our knowledge this paper is the first attempt to use this scale in

the Norwegian language and in an entrepreneurial context. Based on observations of the

various teams we also measure the emotional construct ambivalence which is done according

to Håvold et al. (2011), but based on joy and fear as a measure of positive and negative

emotions. This parameter is used in order to link to the entrepreneurship literature on

entrepreneurial ambivalence (Chwolka and Raith 2012, Brinkmann et al. 2010).

This paper also includes power and status of the individual student in the team as the students

in this study work together in teams of three to four. Power is defined as the extent to which

an individual can control others’ outcomes by granting or withholding valued resources.

Status is defined as the extent to which an individual is respected, admired and highly

regarded by others. To a certain extent, the concepts of power and status overlap and the

similarities are obvious:

Power and status are similar in the way that they are both sources of potential influence over

others. Individuals are more likely to comply with the wishes of those whom they highly

regard or who control valued resources. Further both power and status are commonly

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bestowed upon individuals who can make the most valued contribution to the group,

reflecting the process of social exchange Fragale et al. 2011.

Knowledge exists both at the individual and the organizational level (Nelson and Winter,

1982). The role of personal knowledge in vocational education has been discussed by Schaap

et al. (2011) and Billett (2001). The term “embedded knowledge” has been used by

Badaracco (1991) to describe tacit knowledge amongst individuals or groups. The distinction

between explicit and tacit knowledge in organizations has been discussed by Hedlund and

Nonaka (1993). Nonaka and Takeuchi (1995) have argued that the zone between tacit and

codified knowledge is what matters most. Lundvall and Johnson (1994) distinguish between

four types of knowledge (Jensen et al. 2007): Know-what, Know-why, Know-how and

Know-who. Know-what and Know-why knowledge is typically academic knowledge and is

obtained through reading textbooks and/or attending lectures. This may take place in an

educational or industrial setting. The Know-how knowledge is typically learnt in a master-

apprentice relationship within an industrial sector. This relation can be formal, as part of a

vocational diploma, or informal, as in a community of practice (Lave and Wenger 1991),

where highly skilled craftsmen are role models for younger craftsmen. The Know-who

knowledge is learnt in social practice (Jensen et al. 2007; Carter 1989), which, in an

industrial setting, will include contact with vendors, customers, and competitors. As pointed

out by several authors (Maskel and Malmberg, 1999; Gertler 2003) tacit knowledge is

increasingly more important as codified knowledge becomes more easily accessible. Based

on the findings in the literature we would expect diploma students to have more Know-how

and Know-who (network) knowledge compared to the other students. We would not expect

differences in the groups in the more academic Know-why and Know-what knowledge.

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The performance of the students was measured using grades in the subject. These grades are

based on individual work as well as group work and quality of final prototype.

For a higher education institution these post apprentice diploma students represent

opportunities as well as challenges. Opportunities arise from the industrial knowledge, skills,

and professional network they bring into the classroom. Challenges arise from a more

heterogeneous student population and the fact that the diploma students may challenge the

knowledge of the lecturer. Further knowledge on how these students feel, act, and behave in

mixed student teams is of vital importance for enhancing the quality of teaching and learning

in such teams. From the entrepreneurship literature there is evidence that emotions like joy

increase the propensity for a positive evaluation of entrepreneurial opportunities (Welbe et al.

2012). Likewise the feeling of fear is linked to negative evaluations of the same

opportunities.

In research on students and learning in higher education these students have hardly been

visible. It is emphasized that this study focuses on the most practical subjects in the actual

engineering degree pathway and results should not be transferred to more academic subjects

such as math or physics. New knowledge of this student group will have practical

implications for teaching and learning outcomes in these subjects.

Research questions

The intended contribution of this paper is to shed new light on the post apprentice diploma

students and to show how they differ from other students with regard to emotions,

knowledge, power, status and grades in an entrepreneurship educational setting.

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Methodology

Instrument

A self-administered questionnaire comprising two parts was developed. The first part relates

to how often the respondents have had different feelings or emotions. The feelings and

emotions are drawn from the Pana-X battery (Watson and Clark, 1994) and contain 28 of the

original 60 items covering general positive and negative emotions. The second part of the

questionnaire relates to power which is measured by eight self-developed items and five self-

developed items for status. The instrument was composed of the same two parts related to

four distinct phases of the entrepreneurship module, so that each respondent was asked to

answer the questionnaire related to each of the four phases retrospectively. The phases are

tabulated in Table 1 below and relate to modules in the lecturing plan.

Table 1 to be inserted here

Emotions: The Pana-X items were translated from English to Norwegian by two separate

translators, one native English speaker and one native Norwegian speaker. The translations

were compared and final translations were decided together with the translators. In this study,

we will restrict ourselves to use the two sub-scales: joviality and fear. The subscales will be

further discussed later in this paper. Ambivalence was measured following Håvold et al.

(2011). This construct was included because several researchers have focused attention on the

role of ambivalence in entrepreneurship (Brinkman et al. 2010, Chwolka and Raith 2012).

Power: The eight items relates to whether the respondent has used a specific knowledge type

((Jensen et al. 2007): know-how, know-why, know-what, know-who) to take initiatives and

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to prevent initiatives in the teamwork. Knowledge is a valuable resource in team work and we

intend to measure to what extent the students grant or withhold these recourses.

Knowledge: The four items relate to positive use (initiative) of the various knowledge types

given in the previous section.

Status: The five items relates to whether the group values the respondent’s contribution and

whether the respondent’s knowledge and experience are important for the team.

Performance: The final grades given for the course.

Nominal questions about age, sex, group and whether they held a vocational diploma were

also asked. The questionnaire contained a personal code which allowed the authors to identify

the respondents without identifying names. The instrument was handed out by one of the

authors and collected later the same day.

This study restricts itself to analysing these data with basic statistical techniques and does not

use more advanced methods such as non-parametric statistics, or panel/multiple response

methods. The number of respondents was 27, in a class of 32. We removed questionnaires

that were not completed and ended up with 102 complete responses.

Construction of variables

The construction of the variables used in this study is explained below. This will be done by

first describing how the items were developed and later the use of factor analysis to group the

items and test their validity.

The joviality scale

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We have used a Norwegian translation of the he Pana-X instrument for measuring emotional

states. The original and translated items for the joviality scale are found in Table 2.

Table 2 to be inserted here

The respondents were asked to indicate to what extent they had felt this way during the actual

phase of the Project M1 to M4 in Table 1.

1 2 3 4 5

Very slightly a little moderately quite a bit extremely

or not at all

The fear scale

We have used a Norwegian translation of the he Pana-X instrument for measuring emotional

states. The original and translated items for the fear scale are found in Table 3.

Table 3 to be inserted here

There were discussions among the translators regarding the translation of jittery and shaky.

When referring to these terms later in this paper, we have used the original English terms.

The power scale

The eight items relate to whether the respondent has used a specific knowledge type (Jensen

et al. 2007) to take initiatives or to stop various initiatives in the teamwork. Power is,

according to Fagale et al. (2011), the extent to which an individual can control others’

outcomes by granting or withholding valued resources.

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The respondents were asked to indicate how much they agree with each of the statements

Power1-Power 8 in relation to the actual phase of the project.

1 2 3 4 5

disagree partly disagree neutral partly agree agree

The items are:

Power 1: I have taken initiatives in the group because I have knowledge in how things are

done in the industry.

Power 2: I have stopped initiatives in the group because I have knowledge in how things are

done in the industry.

Power 3: I have taken initiatives in the group because I have knowledge of what is usually

done in such situations.

Power 4: I have stopped initiatives in the group because I have knowledge of what is usually

done in such situations.

Power 5: I have taken initiatives in the group because I have knowledge of why things need

to be done.

Power 6: I have stopped initiatives in the group because I have knowledge of why things need

to be done.

Power 7: I have taken initiatives in the group because I know someone that can help the

group.

Power 8: I have stopped initiatives in the group because I know someone that knows that this

initiative won’t work.

The status scale

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Status is, according to Fragale et al. (2011) the extent to which an individual is respected,

admired and highly regarded by others. The respondent is asked to indicate, on a five point

Likert scale, how much he or she agrees with the following statements:

Status 1: In order to succeed, the team is completely dependent on my knowledge and

experience.

Status 2: The team values my knowledge and experience.

Status 3: My knowledge and experience are of great value for the team.

Status 4: I have little influence in the team (R).

Status 5: I am probably the one with most influence in the team.

Item S4 is reverse recoded in order for all items to score high on high status.

Analysis of Factors

In order to ensure that the items correlate and are reliable measures for the defined concept,

we performed an exploratory factor analysis using SPSS (Hair et al. 2006, Palant 2010,

Ringdal 2007). The seven items for joy, the six items for fear, Power 1-Power 8, and Status

1-Status 5 were used as input items in the factor analysis. Varimax orthogonal rotation was

used. We follow Kaiser’s recommendation of keeping eigenvalues of the factors above 1

(Field, 2005). By inspection of the diagonal in the anti-image matrix we exclude items with

correlation<0.7. After inspection of the extracted communalities we remove items which load

lower than 0.5 (ibid). After these operations, the Kaiser-Meyer-Olkin (KMO) measure of

sampling adequacy is 0,816, which, according to Field (ibid), is very good, since a value

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close to 1 indicates that pattern of correlation are compact and ensure distinct and reliable

factors. The determinant of the correlation matrix is 1,030E-5, which is above the

recommendation (ibid). This ensures that multicollinearity is not a major problem. The

analysis resulted in four factors as given in Table 4. They explain 68% of the variance in the

data.

Table 4 to be inserted here

A reliability analyses for the new factors was performed and tabulated in Table 5. The two

emotional factors are confirmed, although one item from the joy scale loaded to low (<0, 5).

Three of the items of Pana X, fear scale loaded to low. This may indicate that the translation

of the items should be re-examined in further development of the questionnaires. The factor

items for measuring the concept of power and status are somewhat confusing. This indicates

that items should include more aspects than various type of knowledge in the concept. It is

interesting to observe that know-how (Power 1), know-what (Power 3) and know-who

(Power 7) loads together with the intended status items. We decided to keep the original

names of the concepts on the calculated factors (bearing in mind the limitations in our

questionnaire).

A re-run of the analysis with a direct oblim rotation, results in the same factor for the pattern

matrix, but with one exception: Power 4 loads on both status and power in the structure

matrix. Inspection of the component correlation matrix shows a slightly higher correlation

between status and power, than for the other factors.

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Table 5 to be inserted here

Results: are post apprentice student different?

Descriptive statistics

The four factors were calculated as mean values for the items involved. The descriptive

statistics for these factors are given in Table 6. The Fear factor is highly skewed to the left

(lower values) and very peaked (clustered). This indicates that assumptions of the Fear factor

as having a normal distribution is very questionable.

Table 6 to be inserted here

The first section is devoted to the research question concerned with whether there are any

statistically significant differences in the four calculated factors for students with and without

a vocational diploma.

We split our data into students with a diploma and other students. Status and power are often

linked to age, so we first compared the mean values of the age for the two groups. In all

comparisons between the two groups we used an independent-samples T test procedure (Field

2005). The results are given in Table 7. Levene’s test of equality of variance for the two

samples is not significant (p>5%) and the difference is not significant (p= 40,7%). We

conclude that the groups are not significantly different with regard to age.

Table 7 to be inserted here

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Levene’s test for equality of variance is significant (<5% level) for Status factor and Fear

factor. There is a significant difference between the two groups with regard to Status factor

(p<1%), Joy factor (p<1%), and Fear factor (<5%). Diploma students have, as shown in

Table 7, a higher level of joy, less fear and higher status compared to the other students.

Comparing performance (grades) for the two groups, there is an indication that the diploma

student have better grades (p=7.2%) but that this is not statistically significant (p<5%).

Next, we used the split sample and calculated correlations between the factors for the two

groups. The results are given in Table 8. For the diploma students there seems to be a

significant and strong link between joy and status. For the other students there is a negative

correlation between joy and fear (low level of fear gives high level of joy), as expected. The

negative correlation between joy and power is more difficult to understand.

Table 8 to be inserted here

Regression model

We would like to develop regression equations explaining the joy factor as a function of the

other factors. We split the sample into students with and without diploma. All variables were

centred with the mean of the actual variable. In order to increase the explained variance, we

introduced higher order interaction terms. These were manually defined and calculated in

SPSS and included as a second (two-way interaction) and a third (three way interaction) term.

We used the three factors as the first block. The second block contained two-way interactions

between the factors which do not involve the dependent variable (joy). Finally the third block

is the three way interaction term. The results for the calculations are summarized in Table 9

for both students groups. Model 1 explains 44.7% of the variance in the data for the diploma

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students. Model 2 adds the two-way interaction terms, which results in explanation of 66.7%

of the variance in the data. Model 3 adds only 0.1% more of explanation of the variance. Un-

standardized residuals were tested for normality and the null hypothesis regarding normality

of the residuals was kept. Only two regression coefficients are significant (p<1%). The

Variance Inflation Factor (VIF), indicating multicollinearity if higher than 10, is below four

for all parameters.

For the non-diploma students, Model 1 explains 17.1% of the variance in the data. Model 2

adds the two-way interaction terms, which results in explanation of 38.5% of the variance.

Model 3 adds only 0.1% more of the explained variance. As for the diploma student data, un-

standardized residuals were tested for normality and null hypothesis regarding normality of

the residuals was kept. Only one regression coefficient is significant at 1% level (p<1%),

however three coefficients are significant at (p<5%) The VIF is below four for all parameters.

Table 9 to be inserted here

Summing our findings up, we compare the significant coefficients for the two student groups

in Table 10.

As can be seen from Table 10, there seems to be different mechanisms present for the two

groups. The status factor explains the level of joy for diploma students, whereas a low level

of fear explains the high level of joy for non-diploma students. There are also significant

differences in the interaction terms. Interactions with the power factor seem to be

predominant for non-diploma student and status-fear interaction seems to moderate joy for

both groups.

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Table 10 to be inserted here

Ambivalence

In addition to the emotional concepts, fear and joy, we introduced a new emotional construct;

ambivalence. This is motivated by the literature on entrepreneurial ambivalence (Brinckmann

et al. (2010), Chwolka and Reith 2012). We followed the method found in Håvold et al.

(2011) and modified their definition of ambivalence. This was done as follows:

PA (Positive emotions/affects)

NA (Negative emotions/affects)

Ambivalence = (PA+NA)/2-ABS(PA-NA)

With our factors we obtained the following expression:

Ambivalence = (Joy_factor + Fear_factor)/2 – ABS(Joy_factor-Fear_factor)

We split the sample, compare means and test for significance. Diploma students have a

significantly lower level of ambivalence (p<1%), than the rest of the students.

Discussion, how can we explain the differences?

The questionnaire

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There appears to be several weaknesses in the questions asked in the survey. Regarding the

emotional states, the Norwegian translation of several fear scale items should be discussed

with other students of the respondents’ age.

The power and status items need to be refined and the literature on these constructs should be

examined in more detail. The loading of items from different theoretical constructs indicate

that these items should be refined further. The various knowledge typologies should have

been examined using more than one question for each type.

The factor analysis includes two different types of items: emotional items with a 5 point

Likerts’ scale referring to frequency of emotional states. The power and status items use

another 5 point Likerts’ scale which refers to what extent the respondent agrees with the

sentence. This should have been split into two separate factor analysis.

The respondents’ answers to the questions is based on retrospection with reference to various

stages in the project. This can introduce errors, since we generally tend to remember very

positive and very negative emotions. The number of respondents should, if possible, be

increased.

The diploma student

The results give a broader picture of the diploma student and confirm several of our

observations regarding these students.

Emotions

Emotions play an important part in the evaluation of entrepreneurial opportunities. Welpe et

al. (2012) show that fear reduces, and joy increases the tendency to exploit entrepreneurial

opportunities.

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The regression equations explaining the joy factor as a combination of the other factors give

interesting result for the split sample. For the diploma student the status factor affects the joy

factor positively. A significant interaction effect is found between status and fear; this factor

has a negative sign. This indicates that fear moderates the effect of status.

For non-diploma student, the picture is a bit different. The fear factor, with a negative sign

explains the joy factor. This indicates that a low fear level is associated with a high level of

joy. There are several interactional effects for this sub-sample. As for diploma students, fear

and status has a negative sign. A positive effect of power-status interaction is also present. It

is however difficult to interpret the positive interaction between power and fear.

How should these results be interpreted and what might cause these observed differences?

We may speculate that several factors may be relevant in explaining the findings. First, the

post apprentice students have an industrial network and experience which make it easier to

judge if a business idea has potential. Second, the quality of the prototype for the product is

generally significantly higher for groups with post apprentice students. Both factors are

important for the judging whether this is a ‘real life’ idea which could be of value to the

industry, or if it is a ‘school life’ idea of only academic interest. Both factors will probably

affect the position of the post apprentice student in the group giving him both increased

power and status as a result of which he feels more joy and less fear. When it comes to the

prototype, it may be that the diploma students, based on experience, are confident that they

will manage to finish it to a high quality, whereas the ordinary students fear that they will not

be able to do so. Research in which we investigate the role of prototyping as a knowledge

integrator is in preparation as a separate publication (Mork and Strand, forthcoming).

Ambivalence

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Ambivalence can have both positive and negative effects on behaviour (Wheeler and Jones,

2006; Håvold et al. 2011). Positive effects include willingness to compromise, negotiate and

seek further information. Negative effects may be the delay of decisions, quality of work, and

lowered self-esteem. Our findings show that diploma students are characterised by a

significantly lower level of ambivalence. On the other hand, given that ambivalence is an

unwanted state, the lecturer should take steps in order to lower the ambivalence for the non-

diploma students.

In an entrepreneurship educational setting, where the presentation of the teams’ business idea

is important, then a low level of ambivalence is vital in order to convince juries, external

examiners or potential investors.

Conclusions

The authors’ impressions and experience gathered from a large number of student enterprises

during recent years is, to a large extent, confirmed. The post apprentice diploma students use

their significantly higher Know-how and Know-who knowledge actively in their

entrepreneurship project. Know-how is learnt in industrial apprenticeship and Know-who is

learnt through participating and interacting in business networks with vendors, customers and

competitors. The lower level of fear and ambivalence is also an interesting finding. The

importance of status to explain joy, and the moderating effect of the interaction of fear and

status on joy is highly relevant.

In contrast, the non-diploma students’ level of joy is explained by a low level of fear. This

level is negatively moderated by the same interaction term as for the diploma student. In

addition positive moderating effects are found from interaction among power and status, and

between power and fear.

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These findings are relevant in more practice oriented subjects in a higher educational setting.

The lecturer should pay attention to the significant discrepancy of ambivalence and fear

between the two groups. Great care and consideration should be taken when the groups are

compiled. A balance between the various types of students in the group is favourable, but will

require special/individual coaching for both types of students within each group.

In terms of future research we have pointed to several weaknesses in our measuring

instruments and made several suggestions for improvement. An obvious extension would be

to repeat the study within a subject of a more academic nature.

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Welpe, I. M., Spørrle, M., Grichnik, D., Michl, T., & Auderetsch D. B. (2012). Emotions and Opportunities: The Ineterpolay of Opportunity Evaluation, Fear, Joy, and Anger as Antecedents of Entrepreneurial Exploitation. Entrepreneurship Theory and Practice, 36(1), 69-96. Wheeler, P,. Jones, D. R. (2006). The effects of attitudinal ambivalence and exploratory switching behavior on the use of two decision aids. International Journal of Accounting Information Systems, 7, 251–271.

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Table 1. The various phases of the entrepreneurship education modules.

Phases Main theme

M1 Ideation

M2 Establishing teams

M3 Establishing business network

M4 Prototype 1

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Table 2. The original and the translated version of the joviality scale. English Norwegian

happy lykkelig

delighted henrykt

cheerful munter

excited begeistret

enthusiastic entusiastisk

lively livlig

energetic energisk

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Table 3. The original and the translated version of the fear scale. English Norwegian

afraid engstelig

frightened skremt

scared redd

nervous nervøs

jittery skjelven

shaky rystet

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Table 4, Results from the factor analysis. Rotated Component Matrixa

Component Communalities

1 2 3 4

Status 1 ,803 ,666

Power 3 ,788 ,761

Power 1 ,766 ,697

Status 5 ,729 ,648

Status 2 ,722 ,602

Power 7 ,671 ,556

Cheerful ,810 ,711

Delighted ,802 ,666

Enthusiastic ,796 ,723

Energetic ,752 ,687

Happy ,666 ,547

Excited ,648 ,615

Nervous ,849 ,750

Afraid ,842 ,755

Frightened ,816 ,684

Scared ,812 ,692

Power 6 ,837 ,757

Power 5 ,719 ,667

Power 4 ,713 ,769

Eigenvalues 5,441 4,124 2,226 1,173

Extraction Method: Principal Component Analysis. Rotation

Method: Varimax with Kaiser Normalization

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Table 5. The reliability of the new factors.

Factor Cronbach’s Alpha

Status (Status 1, Status 2, Status 4, Power 1,

Power 3, Power 7)

0,86

Joy (cheerful, delighted, enthusiastic, energetic,

happy, excited)

0,86

Fear (scared, frightened, nervous ,afraid) 0,87

Power (Power 4,Power 5,Power 6) 0,79

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Table 6. Descriptive statistics of the factors.

Status_factor Power_factor Fear_factor Joy_factor

Mean 3,0033 2,8595 1,6176 3,2639

Std. Deviation ,80290 ,82379 ,75428 ,73767

Kurtosis -,047 ,090 2,783 -,408

Skewness -,617 -,188 1,654 -,050

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Table 7. Parameter difference between the two groups. Diploma students Non-diploma students

Mean Std. Error Mean Mean Std. Error Mean

Age 24,56 ,553 23,91 ,5450

Status_factor 3,5417 ,08277 2,7096 ,09698

Power_factor 2,9722 ,11682 2,7980 ,10865

Fear_factor 1,4028 ,08109 1,7348 ,10423

Joy_factor 3,5880 ,09379 3,0871 ,09416

Performance 2,2222 ,10624 1,9697 ,08895

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Table 8. Correlations between the factors for the two groups. Factors Diploma

students Non-diploma students

Joy-Fear -,346**

Joy-Power -,249*

Joy-Status 643** .

Fear-Performance -,343* -,314*

Power-Status ,469** ,567**

Power-Performance -,343* -,275*

Correlation is significant at the 0.01 level (2-tailed).**

Correlation is significant at the 0.05 level (2-tailed).*

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Table 9. Regression results for the two student groups.

Model Diploma students Non-diploma students Unstandardized

Coefficients Sig. R

Square Unstandardized

Coefficients Sig. R

Square B Std.

Error B Std.

Error

1

(Constant) -3,153E-006 ,073 1,000 2,975E-

005 ,088 1,000

Fear ,131 ,154 ,399 ,447 -,266 ,107 ,016 ,171 Status ,837 ,170 ,000 -,244 ,125 ,055 Power -,138 ,120 ,258 ,146 ,138 ,294

2

(Constant) -,006 ,072 ,935 -,214 ,093 ,024 Fear ,122 ,163 ,460 -,289 ,098 ,005 Status ,776 ,143 ,000 -,155 ,112 ,171 Power ,095 ,125 ,453 ,667 ,183 ,124 ,147 ,385 Fear*Status -1,472 ,366 ,000 -,437 ,191 ,026 Fear*Power -,249 ,234 ,295 ,440 ,123 ,001 Status*Power* ,329 ,200 ,111 ,308 ,114 ,009

3

(Constant) -8,034E-005 ,076 ,999 -,211 ,096 ,031

Fear ,171 ,238 ,480 -,281 ,108 ,012 Status ,786 ,149 ,000 ,668 -,155 ,113 ,175 ,386 Power ,081 ,137 ,562 ,189 ,131 ,153 Fear*Status -1,479 ,373 ,000 -,429 ,198 ,034 Fear*Power -,221 ,258 ,398 ,429 ,138 ,003 Status*Power ,375 ,260 ,160 ,305 ,116 ,011 Fear*Status*Power -,148 ,520 ,778 -,028 ,157 ,859

a. Dependent Variable: Joy

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Table 10. The regression results with only significant coefficients shown.

Non-diploma student Diploma Students

Coeff. (std. error) Coeff. (std. error)

Independent original variables

Status_factor 0,786 (0,149)***

Fear _factor -,281 (0,108)** NS

Two-way interactions

Status_factor*Fear_factor -0,429 (0,198)** -1,479 (0,373)***

Status_factor*Power_factor 0,479 (0,138)*** NS

Power_factor*Fear_factor 0,305 (0,116)** NS

R =0,621 R =0,817

R2 =0,386 R2 =0,667

R2 adj =0,311 R2 adj =0,598

***p<0.001; **p<0.05; NS=Not Significant

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Biblographical Notes

Øivind Strand, Dr. Scient., is an Associate Professor in Innovation and Entrepreneurship at the Department of International Business of Aalesund University College in Norway. His teaching and research interests relate to innovation, entrepreneurship and entrepreneurship education. He had 10 year of experience from various industrial sectors before entering academia. His has published papers in European Planning Studies, Technology Forecasting and Social Change, Journal of the American Society for Information Science and Technology, and Journal Advances in Higher Education.

Ola Jon Mork, MSc. in Industrial Economy, is an Assistant Professor in Product Development at the Department of Maritime Technology and Operations, Aalesund University College in Norway. He has broad experience as CEO in numerous companies in industry. His teaching and research interests relate to Lean Manufacturing, Innovation, Entrepreneurship, and Product Development. His published papers have appeared in Journal Advances in Higher Education, among others.

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