Intra-organizational network

resources

How they relate to career success and

organizational commitment

Nikos Bozionelos

University of Durham, Durham, UK

Abstract

Purpose – The purpose of this paper is to investigate the relationship of intra-organizational
network resources with career success and organizational commitment.
Design/methodology/approach – The study utilized survey data from 316 British individuals who
composed a highly heterogeneous sample in terms of both organizational roles and employment
settings.
Findings – The study finds that total intra-organizational network resources were related to extrinsic
and intrinsic career success, and to affective organizational commitment. Instrumental and expressive
network resources were differentially related to career success and organizational commitment.
Research limitations/implications – The relationships were identified after controlling for an
array of factors and for mentoring received, which attests to the importance of intra-organizational
network resources for career outcomes and attitudes towards the organization. The cross-sectional
design is a limitation of the study. Future research should investigate moderating factors, and must be
extended to cultural clusters other from the Anglo-Saxon one.
Practical implications – From an individual point of view, building networks of relationships
within the organization enhances career prospects, regardless of whether a mentor is present. From an
organizational viewpoint, organizational designs and human resource systems that promote the
development of informal relationship ties foster those aspects of commitment that have positive
consequences and inhibit those that have negative consequences.
Originality/value – The study provided original evidence for the link between intra-organizational
relationship ties and commitment towards the organization. In addition, it consolidated evidence on
the relationship of network resources to career success, the distinct nature of instrumental and
expressive network resources, and the additive value of network resources and mentoring as parts of
social capital.

Keywords Social capital, Mentoring, Networking, Career development

Paper type Research paper

An individual’s network resources within a particular context (e.g. work organization)
include one’s totality of interpersonal ties, of any strength and in any direction, within this
context, excluding traditional mentoring relationships the individual may have
(Bozionelos, 2003a; and see Kram and Isabella, 1985; Podolny and Baron, 1997). A
traditional mentoring relationship is a strong interpersonal relationship between two
individuals of unequal status in which the more powerful individual, the mentor, provides
career development and socio-emotional functions for the less powerful one (e.g. Kram,
1985; Whitely et al., 1991). Network resources are distinguished into instrumental and
expressive. The former include those relationship ties whose main purpose is to advance

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/0048-3486.htm

Network

resources

249

Received 12 March 2006

Revised 15 February 2007

Accepted 27 March 2007

Personnel Review

Vol. 37 No. 3, 2008

pp. 249-263

q Emerald Group Publishing Limited

0048-3486

DOI 10.1108/00483480810862251

the individual’s career and professional interests, whereas the latter include relationship
ties whose primary purpose is to provide socio-emotional support for the individual
(Ibarra, 1993; Kram and Isabella, 1985; Fombrun, 1982, 1983).

Network resources along with traditional mentoring relationships compose an

individual’s social capital (Bozionelos, 2003a; Seibert et al., 2001; and see also Higgins
and Kram, 2001; Dobrow and Higgins, 2005), which refers to the structure and quality
of all interpersonal ties of that individual within a particular social context (Adler and
Kwon, 2002). Social capital is a concept that is receiving increasing attention in the
literature because it can improve our ability to explain certain processes and outcomes,
such as career progression. For example, mentors and network resources can assist
career progression by providing access to power and influence bases, information,
encouragement and emotional support (e.g. see Adler and Kwon, 2002).

Mentoring has been the focus of substantial attention in the empirical literature

from the individual level of analysis point of view. Evidence for this is recent
quantitative review research (Allen et al., 2004) which summarized extant empirical
findings on the relationship of receipt of mentoring and career outcomes. However,
network resources has been deprived from such attention, which led Krackhardt and
Brass (1994) to stress the conspicuous absence of empirical work on the role of network
resources in the organizational environment from a micro-level perspective, despite its
promising potential (see also Molloy, 2005). Only lately has empirical research that
adopted the micro-level perspective started to systematically investigate the
relationship of network resources with individual level outcomes, such as career
success, with the utilization of systematically developed instruments (Bozionelos,
2003a; Forret and Dougherty, 2004).

In particular, recent work by Bozionelos (2003a) focused on careers within single

organizational environments and investigated the relationship of individuals’
intra-organizational network resources (i.e. network resources within the particular
organization the individual is employed) with career success within the single
organizational setting. Bozionelos (2003a) conceptually and empirically distinguished
between network resources and mentoring received in traditional mentoring
relationships, a distinction that has not often been made in the empirical literature.
As noted, both mentors and network resources are distinct parts of the individual’s
social capital, and they make, or are presumed to make, contributions of similar nature
to individual level outcomes (Seibert et al., 2001; Molloy, 2005; see also Bozionelos,
2006). Therefore, investigating the relationship of network resources with career and
other outcomes without taking into account the effects of mentoring introduces
confounding and casts doubts on the validity of conclusions. Hence, the relationship of
network resources with career and other outcomes must be tested over and above the
contributions of mentoring received.

Bozionelos (2003a) employed a sample of British public sector white-collar workers

and found that intra-organizational network resources were related to extrinsic and
intrinsic career success, after controlling for the contributions of demographics, human
capital and mentoring received. Extrinsic career success pertains to evaluations of
careers with the use of external or objective reference criteria (e.g. financial
compensation, organizational grade), while intrinsic career success refers to
evaluations of careers by individuals themselves using subjective criteria of success
or failure (e.g. Gattiker and Larwood, 1986; and see Heslin, 2005). Furthermore,

PR
37,3

250

confirming logical expectations, the study found differential relationships of
instrumental and expressive network resources with the criteria variables. In
particular, although both instrumental and expressive network resources contributed
to intrinsic career success, only instrumental network resources contributed to extrinsic
career success. This was in line with the conceptual distinction of instrumental and
expressive network resources as reflecting those relationship ties whose primary
function is the advancement of career interests and the gain of socio-emotional support,
respectively. From this point onwards, and taking into account that the focus of the
present work is on intra-organizational network resources, the term “network resources”
will refer to intra-organizational network resources, unless otherwise specified.

However, replicatory research is imperative in order to accumulate and consolidate

empirical evidence on a particular relationship (see, for example, Allen and Preiss,
1993). Replicatory research with samples of different nature is especially useful,
because it provides evidence on the applicability of conclusions across settings and
populations. Bozionelos’ (2003a) sample was highly homogeneous from both
occupational and organizational setting point of view. Therefore, the first purpose of
the present study was to test the generalizability of those results in a sample that was
heterogeneous both occupationally and in terms of organizational settings in which
careers evolved. The following hypotheses were posed:

H1.

Total network resources will be positively related to extrinsic career success
over and above the contribution of mentoring received.

H2.

Total network resources will be positively related to intrinsic career success
over and above the contribution of mentoring received.

H3.

Instrumental network resources will be more strongly related to extrinsic
career success than expressive network resources will be.

The additional intention of the present work was to extend knowledge by investigating
the relationship of intra-organizational network resources with organizational
commitment; an issue that has not been researched up to date. The most prominent
conceptualization of organizational commitment considers it a multi-dimensional
entity (Allen and Meyer, 1990), with affective and continuance commitment being the
most well-established dimensions (e.g., see Meyer et al., 2002). The former refers to the
degree of individuals’ identification with and genuine involvement in the organization,
and signifies that individuals stay with the organization because this is what they
desire to do. The latter refers to the degree to which individuals perceive that leaving
the organization entails costs, and signifies that individuals remain in the organization
mainly because they perceive substantial costs of leaving and lack of better
alternatives (e.g., Meyer and Allen, 1991).

It is reasonable to expect that network resources relate to both of these dimensions

of organizational commitment. A network of relationships provides information on
what is happening in the organization, access to power structures, emotional support
and friendship. This should increase the person’s involvement in the affairs of the
organization and attachment to the organization, hence, affective organizational
commitment.

H4.

Total network resources will be positively related to affective organizational
commitment over and above the contribution of mentoring received.

Network

resources

251

Furthermore, having an established network of relationships within the organization
should make the person more likely to perceive costs associated with leaving this
organization. For example, as hypothesized, network resources improve career
prospects within the organization. Moving to another organization will necessitate
effort and time to re-build such a network and will involve uncertainty regarding
whether this effort will be successful. Hence, the more extensive an individual’s
network resources the greater one’s continuance commitment should be.

H5.

Total network resources will be positively related to continuance
organizational commitment over and above the contribution of mentoring
received.

It is also reasonable to expect that instrumental and expressive network resources are
differentially related to affective and continuance organizational commitment.
Expressive network resources must relate more strongly than instrumental network
resources to affective commitment. Logically, the functions expressive network
resources provide, including support, friendship and a safe outlet for the expression of
emotions, must strengthen the individual’s sense of belonging to the organization to a
greater extent than the weaker, utilitarian, and less intimate relationship ties of
instrumental network resources. On the other hand, instrumental network resources
primarily serve to advance the individual’s career and professional interests, and they
have been hypothesized to relate more strongly than expressive network resources to
extrinsic career success. Hence, they should be more strongly associated with the
calculation of costs of leaving the organization; because leaving will mean that access
to resources (e.g. power, decision structures, information) that are necessary for one’s
advancement will be, at least temporarily, lost in a new organizational environment. In
this case, individuals who perceive that they have built a network of instrumental
relationships should be more likely to stay with the organization not only because of
obligation, but also because of perceived necessity.

H6.

Expressive network resources will be more strongly related to affective
organizational commitment than instrumental network resources will be.

H7.

Instrumental network resources will be more strongly related to continuance
organizational commitment than expressive network resources will be.

Method
Participants
Participants were 316 (149 women and 167 men) first year executive MBA students
and delegates in advanced courses in management in a Business School in the North of
the UK. Participants were employed on a full-time basis in a large variety of
occupations and organizational settings. This made the sample highly heterogeneous
occupationally and contextually. These respondents were selected from a larger pool
(343) on the criterion that they were not self-employed and had at least two years of
tenure with their present employer. A respectable amount of time is needed for the
development of a network of relationship ties and for mentoring relationships to unfold
(e.g. Fagenson-Eland et al., 1997). Mean age and tenure were 33.94 (SD ¼ 6.04) and 6.76
(SD ¼ 5.22) years, respectively.

PR
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252

Measures
Network resources. This was measured with the scale developed by Bozionelos (2003a),
which contains six items on a five-point response format (1: completely disagree, 5: to
completely agree). Three items assess instrumental network resources (e.g. “I have a
network of friendships in the organization that can help to further my career
progression”) and three items assess expressive network resources (e.g., “there are
individuals in the organization whom I consider as best friends and share any kind of
issue, professional or personal”).

Based on the assumption that expressive and instrumental network resources,

though different in nature, should partly overlap, Bozionelos (2003a) factor-analyzed
the full scale with the application of oblique rotation and derived two factors, assessing
expressive and instrumental network resources, respectively. This permits the
utilization of both the total scale, scores on which provide a measure of the total
amount of network resources the individual has at one’s disposal, and the two
individual factors, scores on which provide measures of instrumental and expressive
network resources. Cronbach alphas for the present sample were 0.75, 0.69 and 0.71 for
the total, instrumental and expressive scales, respectively. These alphas were
somewhat lower than those reported by Bozionelos (2003a), but still within acceptable
limits (e.g. DeVellis, 1991).

Mentoring received. This was measured with seven items on a five-point response

format (1: not at all, to 5: to a great extent) from Dreher and Ash (1990). Respondents
were asked to consider their career history in the organization they were working for
and indicate the extent to which “a higher-ranking individual (this need not be limited
to one person) who had advanced experience and knowledge” had provided a variety of
mentoring functions for them. Cronbach a for the present sample was 0.86.

In order to ensure that the network resources scale and the mentoring received scale

tapped different constructs, their items were subjected to principal components
analysis forcing a two-factor solution that was followed by varimax rotation. Each
scale formed a different factor with unambiguous loadings (highest and median
cross-loading were 0.29 and 0.14, respectively). Only one item, included in the network
resources scale (“I keep in touch with a number of people in the organization who are at
higher levels than I am”), had ambiguous loadings (0.31 and 0.37 in the mentoring
received and network resources factor, respectively). It was decided to proceed by
keeping this item into the network resources scale, considering Bozionelos’ (2003a)
finding of unambiguous loadings by this item.

Extrinsic career success. This was measured in terms of total annual monetary

compensation (salary plus bonuses) in British sterling. Self-report data of income are
highly related to those found in organizational records (Dreher, 1977). Statistical
control was imposed for a number of factors that may affect total compensation,
including age, gender, educational attainment, managerial grade, tenure, type of
industry (i.e. service or manufacturing, public or private sector), organizational size,
and staff or line position (e.g. see Melamed, 1996).

Intrinsic career success. This was measured with eight items from Gattiker and

Larwood (1986). The items covered all identified dimensions on which careers are
intrinsically evaluated, namely, hierarchical, financial, job, interpersonal and life.
Cronbach a for the present sample was 0.71.

Network

resources

253

Affective and continuance organizational commitment. These were measured with

Allen and Meyer’s (1990) eight-item scales. Cronbach alphas for the present sample
were 0.74 and 0.70 for the affective and the continuance commitment scale,
respectively.

Controls. These variables were measured with single items.

Results
Descriptive statistics and correlation coefficients are presented in Table I. Hierarchical
regressions were utilized to test the hypotheses. Controls were entered in the first step
and included the demographic factors: age, gender (1: male, 2: female), socio-economic
origin (1: working class to 5: upper class), marital status (1: single, 2: co-habiting, 3:
married), number of dependents and educational attainment (1: GCSE and below to 7:
doctoral degree); organizational characteristics: organizational size (1: below 20
employees to 6: 1,000 employees or more), public or private sector (1: public, 2: private)
and service or manufacturing industry (1: service, 2: manufacturing); and individual
organizational demographic characteristics: tenure, current managerial grade (1:
subordinate to 7: CEO/managing director) and staff or line position (1: staff, 2: line).
Monetary compensation was added to these controls in the regressions that utilized
intrinsic career success and continuance commitment as criteria (i.e. H2, H5 and H7),
because, logically, monetary compensation, which is the index of extrinsic career
success, can affect intrinsic career evaluations (see also Poole et al., 1993) and perceived
costs of leaving the organization. The stepwise procedure for variable inclusion into
the regression model was employed with the control block, so the final models
contained only those controls that made significant contributions to the criterion
variables. Mentoring received was forcibly entered into the equation in the second step
across regressions.

In testing H1, H2, H4 and H5, total network resources was forcibly entered into the

regression equation in the third step. The results of the regressions are presented in
Tables II and III.

Scores on total network resources significantly improved the total amount of

variance accounted for in scores on monetary compensation, DF (1, 307) ¼ 4.42,

b

¼ 0.11, t ¼ 2.10, p , 0.05, DR

2

¼ 0.009, in a significant total model,

F (8, 307) ¼ 20.10, p , 0.001, R

2

¼ 0.344. Therefore, H1 was supported. It should be

noted that the contribution of mentoring received to monetary compensation was not
significant either before (

b

¼ 0.06, t ¼ 1.20, ns) or after (

b

¼ 0.02, t ¼ 0.45, ns) the

entry of network resources into the equation.

Scores on total network resources made a significant addition to the total amount of

variance accounted for in scores on intrinsic career success, DF (1, 306) ¼ 4.69,

b

¼ 0.11, t ¼ 2.17, p , 0.05, DR

2

¼ 0.010, over and above the contribution of scores

on mentoring received (

b

¼ 0.32, t ¼ 6.41, p , 0.001), in a significant total model,

F (9, 306) ¼ 20.22, p , 0.001, R

2

¼ 0.373. Therefore, H2 was supported.

Scores on total network resources achieved a marginally significant improvement to

the total amount of variance accounted for in scores on affective organizational
commitment, DF (1, 310) ¼ 3.16,

b

¼ 0.10, t ¼ 1.78, p , 0.10, DR

2

¼ 0.008, over and

above the contribution of scores on mentoring received (

b

¼ 0.23, t ¼ 4.32, p , 0.001),

in a significant total model, F (5, 310) ¼ 18.31, p , 0.001, R

2

¼ 0.228. Therefore, H4

was marginally supported.

PR
37,3

254

M

S

D

12

3456789

1

0

1

1

1

2

1

3

1

4

1.

Age

(in

years)

39.94

6.04

–

2.

Educational

attainment

4.65

0.91

2

0.12

–

3.

Socioeconomic

origin

2.20

0.93

2

0.19

0.01

–

4.

Number

of

dependents

0.57

0.89

0.41

2

0.07

2

0.07

–

5.

Tenure

(in

years)

6.76

5.22

0.48

2

0.27

2

0.15

0.21

–

6.

Managerial

grade

3.71

1.51

0.42

0.02

2

0.12

0.20

0.18

–

7.

Organizational

size

4.98

1.41

2

0.17

0.01

0.12

2

0.08

0

2

0.32

–

8.

Monetary

compensation

(in

1,000s

British

Sterling)

34.97

16.92

0.28

0.02

2

0.11

0.25

0.07

0.50

2

0.03

–

9.

Intrinsic

career

success

28.50

4.5

0.10

2

0.15

2

0.01

0.09

0.17

0.29

0.05

0.33

–

10.

Total

network

resources

22.26

3.62

2

0.11

2

0.01

0.11

2

0.06

0.06

0.01

2

0.05

0.07

0.28

–

11.

Instr.

network

resources

10.88

2.13

2

0.09

2

0.03

0.09

2

0.07

2

0.06

0.09

2

0.03

0.14

0.32

0.83

–

12.

Expressive

network

resources

11.37

2.20

2

0.09

0.02

0.10

2

0.03

0.16

2

0.08

2

0.06

2

0.02

0.15

0.84

0.40

–

13.

Mentoring

received

9.89

2.92

0

2

0.11

0.06

2

0.03

0.16

0.14

0.13

0.11

0.45

0.35

0.34

0.25

–

14.

Affective

commitment

23.41

5.84

0.02

0.04

2

0.10

0.06

0.26

0.33

2

0.11

0.24

0.41

0.19

0.13

0.19

0.33

–

15.

Continuance

commitment

23.55

5.57

0.01

2

0.04

0.03

2

0.08

0.18

2

0.07

2

0.08

2

0.20

2

0.19

2

0.03

2

0.18

0.12

2

0.08

0.05

Notes:

Correlations

$

j0.09

j,

j0.11

j,

j0.15

j,

j0.19

j

are

significant

at

p

,

0.10,

p

,

0.05,

p

,

0.01,

p

,

0.001,

respectively

Table I.

Descriptive statistics and

intercorrelations

(n ¼ 316)

Network

resources

255

Extrinsic

career

success

(monetary

compensation)

Intrinsic

career

success

Variables

b

t

value

b

t

value

b

t

value

b

t

value

Step

1:

stepwise

Age

2

0.26

2

5.15

****

0.25

2

4.94

****

0.26

2

5.06

****

Gender

0.10

1.98

**

0.11

2.05

**

0.09

1.8

*

0.22

4.27

****

Dependents

0.05

0.94

Educational

attainment

2

0.09

2

1.97

**

Public/private

sector

0.14

2.92

***

0.15

3.06

***

0.13

2.77

***

Services/manufacturing

2

0.09

2

1.81

*

2

0.09

2

1.89

*

2

0.09

2

1.82

*

2

0.06

2

1.23

Staff/Line

0.04

0.76

0.04

0.72

0.04

0.75

2

0.01

2

0.14

Monetary

compensation

0.27

4.85

****

D

R

2

/F

D

0.331/25.5

****

0.331/25.5

****

0.331/25.5

****

0.247/14.47

****

Step

2:

forcible

entry

Mentoring

received

0.02

0.45

0.02

0.36

0.05

0.92

0.32

6.41

****

D

R

2

/F

D

0.003/1.43

0.003/1.43

0.003/1.43

0.116/55.87

****

Step

3:

forcible

entry

Total

network

resources

0.11

2.1

**

0.11

2.17

**

Instrumental

network

resources

0.12

2.37

**

Expressive

network

resources

0.06

1.14

D

R

2

/F

D

0.01/4.42

**

0.012/5.59

**

0.003/1.29

0.010/4.69

**

R

2

/F

0.344/20.1

****

0.346/20.32

****

0.337/19.51

****

0.373/20.22

****

Notes:

*

p

,

0.1,

**

p

,

0.05,

***

p

,

0.01,

****

p

,

0.001;

beta

coefficients

in

the

final

models

are

presented.

R

2

increments

and

F

changes

refer

to

intermediate

models.

No

statistical

value

next

to

a

variable

under

step

1

indicates

that

the

variable

did

not

survive

the

stepwise

procedure

to

enter

this

particular

equation.

No

inclusion

of

a

variable

utilized

in

step

1

in

a

table

indicates

that

the

variable

made

no

significant

contribution

to

any

of

the

equations

described

in

the

particular

table

Table II.
Hierarchical regression
models testing for the
association of network
resources with extrinsic
and intrinsic career
success (n ¼ 316)

PR
37,3

256

Scores on total network resources failed to significantly improve the total amount of
variance accounted for in scores on continuance organizational commitment,

b

¼ 2 0.02, t ¼ 2 0.37, ns; F (5, 310) ¼ 6.68, p , 0.001, R

2

¼ 0.097. Therefore, H5

was not supported.

In testing H3, H6 and H7, three pairs of regression models were constructed, with

monetary compensation, affective, and continuance organizational commitment as
criteria, respectively. Instrumental and expressive network resources were forcibly
entered in the third step of each regression, respectively. Although the strength of their
relationship (r ¼ 0.40, p , 0.001) was below what authors consider as alerting for
multicollinearity phenomena (e.g. Berry and Feldman, 1985), experience suggests that
correlations at this level represent rather strong relationships in social sciences.
Therefore, the option of including each variable into a different equation was preferred
over entering them simultaneously in a single block, because the former tactic
eliminated the possibility of artificial findings due to multicollinearity. Tables II and IV
contain the results of the regressions.

The contribution of scores on instrumental network resources to monetary

compensation was significant, DF (1, 307) ¼ 5.59,

b

¼ 0.12, t ¼ 2.37, p , 0.05,

DR

2

¼ 0.012; F (8, 307) ¼ 20.32, p , 0.001, R

2

¼ 0.346, but the contribution of

expressive network resources was not,

b

¼ 0.06, t ¼ 1.14, ns; F (8, 307) ¼ 19.51,

p , 0.001, R

2

¼ 0.337. Hence, H3, which postulated that the relationship of

instrumental network resources to extrinsic career success would be stronger than
that of expressive network resources, was supported[1].

Affective

commitment

Continuance
commitment

Variables

b

t value

b

t value

Step 1: stepwise
Gender

0.12

2.08**

Tenure

0.17

3.23***

0.21

3.81****

Staff/line

0.01

0.25

Monetary compensation

2 0.16

2 2.71***

DR

2

/FD

0.151/18.50****

0.087/9.87****

Step 2: forcible entry
Mentoring received

0.23

4.32****

2 0.10

2 1.65*

DR

2

/FD

0.069/27.55****

0.10/3.51*

Step 3: forcible entry
Total network resources

0.10

1.78*

2 0.02

2 0.37

Instrumental network resources
Expressive network resources
DR

2

/FD

0.008/3.16*

0/0.14

R

2

/ F

0.228/18.31****

0.097/6.68****

Notes: * p , 0.1, ** p , 0.05, *** p , 0.01, **** p , 0.001; beta coefficients in the final models are
presented. R

2

increments and F changes refer to intermediate models. No statistical value next to a

variable under step 1 indicates that the variable did not survive the stepwise procedure to enter this
particular equation. No inclusion of a variable utilized in step 1 in a table indicates that the variable
made no significant contribution to any of the equations described in the particular table

Table III.

Hierarchical regression

models testing for the

association of total

network resources with

organizational

commitment (n ¼ 316)

Network

resources

257

Affective

commitment

Continuance

commitment

Variables

b

t

value

b

t

value

b

t

value

b

t

value

Step

1:

stepwise

Gender

0.10

1.7†

0.12

2.13

**

Tenure

0.15

2.87

***

0.17

3.28

***

0.20

3.59

****

0.19

3.52

****

Staff/Line

0.02

0.27

0.01

0.20

D

R

2

/F

D

0.151/18.50

****

0.151/18.50

****

0.087/9.87

****

0.087/9.87

****

Step

2:

forcible

entry

Mentoring

received

0.24

4.54

****

0.26

4.75

****

2

0.12

2

2.15

**

2

0.06

2

1.0

D

R

2

/F

D

0.069/27.55

****

0.069/27.55

****

0.010/3.51

*

0.10/3.51

*

Step

3:

forcible

entry

Total

network

resources

Instrumental

network

resources

0.03

0.46

2

0.13

2

2.25

**

Expressive

network

resources

0.13

2.45

**

0.09

1.54

D

R

2

/F

D

0.015/5.98

**

0.001/0.21

0.007/2.37

0.015/5.08

**

R

2

/F

0.235/19.03

****

0.221/17.55

****

0.104/7.18

****

0.111/7.78

****

Notes:

*

p

,

0.1,

**

p

,

0.05,

***

p

,

0.01,

****

p

,

0.001;

beta

coefficients

in

the

final

models

are

presented.

R

2

increments

and

F

changes

refer

to

intermediate

models.

No

statistical

value

next

to

a

variable

under

step

1

indicates

that

the

variable

did

not

survive

the

stepwise

procedure

to

enter

this

particular

equation.

No

inclusion

of

a

variable

utilized

in

step

1

in

a

table

indicates

that

the

variable

made

no

significant

contribution

to

any

of

the

equations

described

in

the

particular

table

Table IV.
Hierarchical regression
models testing for the
association of
instrumental and
expressive network
resources with
organizational
commitment (n ¼ 316)

PR
37,3

258

Expressive network resources made a significant addition to the total amount of variance
accounted for in scores on affective organizational commitment, DF (1, 310) ¼ 5.98,

b

¼ 0.13, t ¼ 2.45, p , 0.05, DR

2

¼ 0.015; F (5, 310) ¼ 19.03, p , 0.001, R

2

¼ 0.235;

while instrumental network resources did not,

b

¼ 0.03, t ¼ 0.46, ns; F (5, 310) ¼ 17.55,

p , 0.001, R

2

¼ 0.221. Hence, H6, which postulated that the relationship of expressive

network resources to affective organizational commitment would be stronger than that of
instrumental network resources, was also supported (see also[1]).

Finally, scores on instrumental network resources significantly improved the total

amount of variance accounted for in scores on continuance commitment,
DF (1, 310) ¼ 5.08,

b

¼ 2 0.13, t ¼ 2 2.25, p , 0.05, DR

2

¼ 0.015; F (5, 310) ¼ 7.78,

p , 0.001, R

2

¼ 0.111; while scores on expressive network resources did not,

b

¼ 0.09,

t ¼ 1.54, ns; F (5, 310) ¼ 7.18, p , 0.001, R

2

¼ 0.104. However, although in terms of

strength and significance the pattern of relationships concurred with H7, the direction
of the relationship between instrumental network resources and continuance
commitment was negative, which was opposite from the expected direction.

Discussion
The findings consolidated evidence on the positive relationship of intra-organizational
network resources with individual career outcomes, extrinsic and intrinsic.
Furthermore, and importantly, the results suggested that individuals’ perceptions of
their network resources are associated with individuals’ organizational commitment,
an outcome that is of interest to organizations. In addition, the findings provided
further empirical evidence for the distinctive nature of instrumental and expressive
network resources; as they were related differentially with extrinsic career success and
the dimensions of organizational commitment. By extension, the findings offered
additional evidence on the construct validity of the measure of intra-organizational
network resources developed by Bozionelos (2003a).

Although findings were mostly in line with hypotheses, the direction of the

relationship between instrumental network resources and continuance commitment
was opposite from the expected. It is likely that instrumental network resources, via
their contribution to career success, increase individuals’ confidence regarding their
ability to survive and succeed in any organization, and not only in the one they are
currently employed by. This, in turn, reduces their perceptions of costs of leaving their
current employer and joining another one. This account appears plausible, but it is post
hoc and needs to be tested in future research.

Instrumental and expressive network resources were related to organizational

commitment in different, but equally favourable to the organization, ways. Expressive
network resources were related to reports of higher identification with and feelings of
belongingness to the organization; and instrumental network resources were related to
reports of reduced likelihood that employees would stay with the organization because
of necessity and perceived inability to find a better alternative. Hence, the results
suggest that participation in expressive and instrumental networks increases the
probability of employees to stay with the organization because they want to even
though they believe that available alternatives do exist (see also Meyer et al., 2002,
p. 39). Therefore, organizational designs and human resource systems that promote the
development of informal relationship ties between organizational members should be
of benefit from the viewpoint of fostering and inhibiting those aspects of organizational

Network

resources

259

commitment that have positive and negative consequences, respectively, for
organizations.

It is important to keep in mind that the identified relationships were held over and

above the contributions of a comprehensive array of demographic, human capital and
structural controls, and, especially, the contribution of mentoring received. This
suggests that network resources are beneficial even in the presence of a mentor, or even
more beneficial than mentors when certain outcomes, such as extrinsic career success,
are considered. This is a critical implication because in the contemporary
organizational environment, which is characterized by constant restructuring,
uncertainty and flattened hierarchies, managers and supervisors are less likely to
provide mentoring for subordinates (Allen, 2003). Our findings, however, suggest that
network resources are able to serve as an alternative to traditional mentoring
relationships (see also Kram and Isabella, 1985; Higgins and Thomas, 2001).

Regarding limitations of the study, the utilization of self-report data introduces the

possibility of percept-percept inflation, which refers to artificial increase in the strength
of measures of co-variation (e.g. regression coefficients). At this point, it should be
noted that meta-analytic work (Crampton and Wagner, 1994) indicates that
percept-percept inflation with self-report data is only the exception. Nevertheless, in
the course of developing the network resources scale, Bozionelos (2003a) established
that scores on the scale and its individual factors are unrelated to social desirability,
which represents a serious underlying cause of percept-percept inflation (Podsakoff
et al., 2003). Furthermore, measures that, to some extent, guard against percept-percept
inflation were introduced in the implementation of the empirical part of the study.
These included stating in the instructions that there were no correct or incorrect
responses, and assuring respondents about the anonymity of the study (Podsakoff et al.,
2003).

The cross-sectional design does not permit definite conclusions on causal

relationships, regardless of the soundness and sophistication of data-analytic
procedures (Bozionelos, 2003b). This is a point to be borne in mind. However, there
is accumulating evidence that mentoring, the other component of social capital,
causally precedes career success and work attitudes (Donaldson et al., 2000; Laband
and Lentz, 1999; Payne and Huffman, 2005). Although direct extrapolation to the
relationship of network resources with career success and organizational commitment
cannot be made, this fact instils some confidence on causality directions between
variables in the present study. Nevertheless, longitudinal designs can be of help in
future research.

Future research should investigate the relationship of intra-organizational network

resources with other valuable outcomes, including employee task and contextual
performance, well-being, and withdrawal behaviours. Furthermore, extant empirical
research on network resources has not taken into account the career stage of the
individual. However, it is likely that career stage, or more generally development stage,
affects the way individuals approach, utilize and respond to their relationship ties (see
Chandler and Kram, 2005). Therefore, future studies should also investigate the
potentially moderating role of development stage in the relationship of network
resources with outcomes of importance for individuals and organizations.

In addition, future research must seek to investigate the relationship of network

resources to career advancement and organizational commitment in cultural clusters

PR
37,3

260

other from the Anglo-Saxon one, to which the UK belongs (e.g. Ronen and Shenkar,
1985). The degree to which inter-personal relationship ties contribute to career
advancement may differ across national cultures. For example, it is likely that there are
variations across national cultural contexts in the extent to which it is acceptable to use
one’s social capital for career and employment purposes (Bozionelos, 2006; De Graaf
and Flap, 1988). Furthermore, the national cultural context may affect the nature of
intra-organizational network resources and organizational commitment. For instance,
the degree to which a culture is collectivistic (utilizing the cultural dimension of
individualism-collectivism identified by Hofstede, 1980) may be associated with the
amount and strength of network ties individuals form, but also with the extent to
which these ties are distinguished into expressive and instrumental (see Bozionelos
and Wang, 2006). And although the three-component model of organizational
commitment has been validated in the Anglo-Saxon cultural context, the nature and
dimensionality of organizational commitment may vary across cultures (e.g. see Cheng
and Stockdale, 2003; Wang, 2004). The above issues open important horizons that
future research must explore.

Note

1. The fact that one of the regression coefficients was significant while the other was not made

testing for the difference in size between the two coefficients redundant, because a
non-significant coefficient must be interpreted as indicative of a non-existent relationship.

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About the author
Nikos Bozionelos is Professor of Organizational Behaviour and Human Resource Management in
Durham Business School of the University of Durham in the United Kingdom. He received his PhD
from the University of Strathclyde, and his Master’s degree from Cranfield School of Management.
His research interests include antecedents of career success, factors that contribute to the
accumulation of human capital, and the influence of social capital on individual and organisational
outcomes. Nikos Bozionelos can be contacted at: [e-mail]

Network

resources

263

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