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TitleA Perspective
TagsSelf-Improvement Emotions Mentorship Journeyman
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Total Pages16
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Page 1

A perspective on effective
mentoring in the construction

industry
Krista Hoffmeister

Colorado State University, Fort Collins, Colorado, USA

Konstantin P. Cigularov
Old Dominion University, Norfolk, Virginia, USA

Julie Sampson and John C. Rosecrance
Colorado State University, Fort Collins, Colorado, USA, and

Peter Y. Chen
University of South Australia, Adelaide, Australia

Abstract

Purpose – The present study aims to provide a perspective on effective mentoring in the construction
industry by examining key mentor characteristics as perceived by construction professionals.

Design/methodology/approach – A total of 170 union construction workers rated 55 mentor
characteristics based on to what extent each was characteristic of a superior, average, or poor mentor.

Findings – To identify the most important mentor characteristics, three criteria were relied on:
means of characteristic ratings of a superior mentor; effect sizes of mean differences between ratings of
poor and superior mentors; and correlations between characteristic ratings of superior mentors and
satisfaction with mentors. Significant mean differences were found between characteristics of poor
and average mentors as well as between poor and superior mentors.

Research limitations/implications – Possible future directions include an investigation of the
relationship between competent mentors and personal characteristics, and potential health and safety
outcomes resulting from effective mentoring in the construction industry.

Originality/value – Although mentoring has been the focus of much research, the mentoring
relationship is quite different in the construction industry and little mentoring research has targeted
this industry. To develop an effective mentoring program in this industry, one of the initial steps is to
identify characteristics of effective mentors in this industry.

Keywords Mentor characteristics, Construction, Mentoring, Construction industry

Paper type Research paper

Introduction
Over the past three decades, mentoring in the workplace has become the focus of much
research and discussion (e.g. Alleman et al., 1984; Fagenson, 1989; Ploeg et al., 2008;

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

www.emeraldinsight.com/0143-7739.htm

This article is based on the honors thesis of Krista Hoffmeister, which was directed by
Peter Y. Chen. The study was supported by the Center to Protect Workers’ Rights (CPWR) as
part of a cooperative agreement with NIOSH (OH008307), and Occupational Health Psychology
Training, NIOSH (1T42 OH009229-01). Its contents are solely the responsibility of the authors
and do not necessarily represent the official views of NIOSH and CPWR.

Effective
mentoring in
construction

673

Received October 2009
Revised January 2011

Accepted February 2011

Page 9

examine the degree of correspondence between ratings of the different groups, we
followed the procedure outlined by Dearmond et al. (2006) and calculated intraclass
(ICCs) and Pearson correlation coefficients on mean ratings of the 55 characteristics. As
shown in Table II, characteristics of average and superior mentors were rated
similarly. However, characteristics of poor mentors were viewed quite differently from
those of average and superior mentors.

Results from a one-way MANOVA revealed significant mean differences in ratings
of the 55 mentor characteristics between poor, average, and superior mentors as
indicated by a Wilks’ lambda of 0.19, Fð110; 164Þ ¼ 1:98;p , .05, partial
? 2 ¼ 0:57:Univariate analyses further demonstrated that there were significant
mean differences among the three groups (i.e. poor, average, and superior mentors) on
all 55 characteristics. The significance level was adjusted to 0.001, based on the
Bonferroni correction (Abdi, 2007). Mean and standard deviations of each of the
characteristics of the three groups are presented in Table I.

Post-hoc comparisons based on Tukey’s Honestly Significant Difference test
showed that 53 of the 55 characteristics were rated significantly differently between
poor and average mentors, as well as poor and superior mentors. The characteristic
“expresses emotions” was not rated significantly differently between poor and average
mentors, and the characteristic “stern” was not rated significantly differently between
poor and average or poor and superior mentors. In addition, none of the characteristics
were rated significantly differently between average and superior mentors.

To identify the most important characteristics for mentors in the construction
industry, we relied on three criteria (summarized in Table III):

Superior
mentora

Average
mentorb Poor mentorc

Characteristic M SD M SD M SD

Intellectual 3.78 0.96 3.76 0.85 2.55 1.15
Comfortable around superiors 3.86 1.05 3.96 0.91 2.53 1.38
Has a customer focus 3.85 1.03 3.84 0.77 2.62 1.24
Interpersonally savvy 3.78 0.98 3.64 0.85 2.39 1.15
Refrains from contradictory statements 4.05 0.80 3.65 0.90 2.42 1.29
Is appropriate in a crisis 4.32 0.87 4.10 0.87 2.32 1.36
Has integrity 4.58 0.73 4.29 0.84 2.23 1.40

Notes:
a
n=64-66; bn=47-49; cn=51-53 Table I.

1 2 3

1. Characteristics of poor mentors — 0a 0a

2. Characteristics of average mentors 20.27 * — 0.89 *

3. Characteristics of superior mentors 20.49 * 0.82 * —

Note: Correlations above the diagonal are intraclass correlations, and correlations below the
diagonal are Pearson correlations; aThe intraclass correlation was set to 0 because of a negative value;
*p , 0.05, two-tailed

Table II.
Rating similarity among

three groups based on
Pearson and intraclass

correlations

Effective
mentoring in
construction

681

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