An empirical analysis of factorsimpacting career decisions

in South Africanconstruction industry

Male and female high school students’perspectives

Nicholas ChilesheSchool of Natural and Built Environments, University of South Australia,

Adelaide, Australia, and

Theodore C. HauptCollege of Architecture, Art and Design, Mississippi State University,

Starkville, Mississippi, USA

Abstract

Purpose – The purpose of this paper is to investigate the perception of high school students onthe factors impacting their career decisions and whether gender and grade have an influence on thedecision-making process.

Design/methodology/approach – Literature review was used to identify relevant factors which wereincorporated into the design of the survey instrument. The questionnaire was administered via a postalsurvey and information collected from 599 male and 491 female high school students in the Western CapeProvince. Survey response data were subjected to descriptive statistics and subsequently parametric tests.

Findings – Salary, working conditions, opportunities for promotion and lifelong learning werereported by both male and female students as the most important factors, whereas family tradition andpeers were the least important factors according to the male and female high school students,respectively. Grade had a significant impact on the process with students in Grade 11 scoring higher onsalary, working conditions and lifelong learning opportunities whereas Grades 12 and 10 scored higheron skills shortage and family tradition, respectively.

Research limitations/implications – The cross-sectional data made it difficult to generalise thefindings.

Practical implications – The findings are of particular importance to high school teachers andguidance counsellors who influence career choices amongst high school students. It is likely thatteachers and counsellors themselves have been negatively influenced by the poor image of theconstruction industry. The identification of factors enables the development of viable strategies andbalances the social dynamics of the male dominated environment.

Originality/value – There are few studies which try to investigate the career decision-making processof high school students in an African environment. These results challenge the factors impacting careerdecision making among South African high school students and provide information rarely examined.Conclusively, the paper finds that control variables such as grade and gender are significant in the careerdecision-making process of high school students. This paper contributes to bridging that gap.

Keywords Careers, Decision making, Construction industry, Gender, Secondary education, South Africa

Paper type Research paper

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

www.emeraldinsight.com/1726-0531.htm

Factorsimpacting career

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Received 7 July 2009Accepted 5 August 2009

Journal of Engineering, Design andTechnology

Vol. 8 No. 2, 2010pp. 221-239

q Emerald Group Publishing Limited1726-0531

DOI 10.1108/17260531011062573

IntroductionThe main objectives of this paper are to investigate the perceptions of high schoolstudents on the factors impacting their career decisions within the South Africanconstruction industry and to explore the influence of gender and grade on the careerdecision-making process. While there have been several career decision factor (CDF)studies carried out in various countries, a few of them are within the African context.The majority of the published literature presented by Dainty et al. (2004a, b), Fielden et al.(2001), Gale (1994) and Ling and Poh (2004) among others indicates that research hasmostly been conducted in developed countries. Some research within the Africancontext, in particular Nigeria, has explored the under-representation of women inconstruction (Adeyemi et al., 2006). However, this study did not explore perceptionsof high school students at entry level. Furthermore, despite the existence of a range ofstudies on equality such as; gender differences in ethical decision making (Glover et al.,2002); project management environment (Gale and Cartwright, 1995); gender roles andattitudes (Agapiou, 2002b) and women’s careers in construction and engineering(Fielden et al., 2000; Powell et al., 2004), little research has been undertaken to examine ifthese interventions can be applied to the South African construction industry. Based onthe existing studies there has emerged two significant gaps in the knowledge that existsregarding the factors that impact of career decisions by high school students. First, thereis a distinct lack of information specific to the South African context, particularly theSouth African context. Second, the past studies have focussed on service and academiarelated organisations. This study overcomes these two gaps and meets the objectivesstated at the start of this paper.

Against a backdrop of skills shortages in the South African construction industryand a reducing number of new entrants, this study presents several challenges andopportunities for the construction sector to address these issues. Opportunity exists foreducation officers to directly promote the construction industry in high schoolclassrooms and use forums such as career exhibitions at schools in this effort. Such anintervention becomes more critical considering the evident lack of knowledge aboutwhat construction in fact includes. It is imperative that students recognize that theconstruction industry encompasses more than the delivery of houses and schools.Learned societies such as the Chartered Institute of Building – Africa and Association ofSouth African Quantity Surveyors have much to do to promote their particulardisciplines. Consideration for choosing contracting as a career presents a particularchallenge to the industry since it ranks poorly on the list of careers that constructionmanagement graduates consider for themselves. Perceptions that construction isdangerous, hard, physically demanding, dirty, experiences “bad times”, and require longworking hours for little money exacerbate the challenges facing the industry.

Literature reviewCareer decision factorsStudies on the factors impacting the career decision-making process have being examinedin a number of countries. For example, in Scotland, Agapiou (2002a) conducted anempirical review of the attitudes of school-age girls, their parents and educators aboutcareer prospects in construction. His study found that the reservations held by the girls aremostly to do with issues such as the physical nature of the work; the social dynamics ofworking in a male-dominated environment and the availability of career paths following

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completion of apprenticeship training. Some of the factors impacting the career decisionswere identified as follows: other family members, peers, exposure to experiences;recognition of their own aptitudes and preferences; and exposure to role models.

Dainty et al. (2000) investigated the women’s career under-achievement in large UKconstruction companies. They found that the poor image of the industry adversely affectspopularity as a career choice. Moreover, Dainty et al. (2000) found that a lack of dedicatedcurriculum and partnership centres impacted on the career choices of school children.

Bennett et al. (1999) investigated whether the career aspirations of women, incomparison to men changed once they worked in the construction industry. They foundwomen’s choices to be influenced by family background factors. They identified thefactors to be more complex and inter-related and classified them into the followingfactors: facultative or women’s career development; individual, background, educationaland adult lifestyle.

Court and Moralee (1995) suggest that family and friends influence female studentson whether to enter the construction industry or not. In Asia and specifically Singapore,Ling and Poh (2004) conducted a literature search in their study which investigatedthe barriers that were preventing female undergraduates, who majored in quantitysurveying, from entering the construction industry. They operationalised the variablesof these potential situations into internal and external factors. Citing Dainty et al. (2000)and Ling and Poh (2004) defined the internal factors as personal attributes,circumstances, characteristics and abilities. External factors were deemed to includethe nature of the industry, working conditions and the sexist’s attitudes amongthe industry players. According to a report commissioned by the DTI (2006) a positiveimage of the industry as well as positive advice and guidance given by parents, peersand career teachers were found to influence career decisions amongst school children.

Other studies such as that carried out by Wilkinson (1996) examined the factorsaffecting the career choice of male and female civil engineering students in the UK.The findings suggested that although they were significant differences exist betweenmale and female civil engineering students in the factors impacting career choice, thesefactors ranked low in their importance. Whereas females considered “location oforganisation nearer to family and friends” as the most important, the men weresignificantly influenced by “salary”. Some factors such as “opportunity for overseastravel” and “benefits like pensions” were found to be equally important for both male andfemale high students. However, the approach adopted in this study was qualitative and nodescriptive or statistical analysis was conducted which would have enabled the ranking ofthe factors impacting on the career decisions. Dimaki et al. (2005) investigate theeducational and occupational preferences of high school students in Greece and found thatbackground variables such as family education and income were significant in theformation of students’ education and occupational preferences. Maringe and Carter (2007)in citing Kotler (2003) conceptualise decision making as a five-stage process involving:the identification of a problem needing a solution; the search for information; an evaluationof alternatives; making the purchase decision; and finally evaluating the purchase decision(Maringe and Carter, 2007, p. 460).

Career progression within the construction industry is also influenced by gender.For example, Dainty et al. (1999) study revealed a hostile and discriminatoryenvironment for women wish to progress within the industry. The hostility was furthercompounded by over resentment from male managers and colleagues.

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Studies into the impact of gender on factors influencing the choice of a career orsubject have being examined before. For example, Calkins and Welki (2006) foundsignificant gender differences in the perception of the important factors in the choice ofmajor subjects with female respondents placing greater emphasis on subject interestwhereas the males were concerned with perceived, marketability and expected income(or salary) associated with the subject.

Research conceptual frameworkThe conceptual framework in this study was developed by drawing data from currentand key concepts factors impacting career decisions from literature, research papers andexamples from other successful industries. Culminating from this, five key elementswhich underline the career decision making within the South African constructionindustry was translated into the following research question to operationlise andcontextualise the study. These were:

RQ1. What are the factors impacting the career decisions of high school students?

RQ2. Did the importance of the CDF differ for high school students in terms of theirgender?

RQ3. What is the impact of grade and gender on the career decision makingprocess? Does gender moderate the relationship between grade and careerdecision making process?

RQ4. How significant are these differences?

RQ5. What is the possibility of women becoming construction managers?

Research methodologyTo investigate the factors impacting career decisions of high school students andexplore the possibility of women becoming construction managers, the followingresearch methodology was employed in the study.

The sampleA questionnaire survey was conducted in 2005. Survey targets were limited to highschool students in the Western Cape. A total of 1,500 questionnaires were sent out tothe high school students in three different grades: 10, 11 and 12. A total of 1,121questionnaires were returned. This provided an effective response rate of 75 per centwhich was considered very high despite the difficulties encountered in engaging theGrade 12s relative to participation in the study. The response rate was therefore deemedadequate for the purpose of data analysis.

The breakdown of the respondents according to grade as indicated in Table I is asfollows: 36.85 per cent Grade 10, 50.60 per cent Grade 11 and 12.55 per cent Grade 12 highschool students in the Western Cape. Males made up the larger proportion of the sample,namely 55.1 per cent. The schools who participated in the survey are listed in Table IItogether with the distribution of the sample. It is evident that the schools are locatedacross the full socio-economic profile of the region being situated inter alia,in Khayelitsha, Guguletu, Kasselsvlei, Bellville, Mitchells Plain and Pinelands.

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Table II indicates that the majority (16.6 per cent) of the respondents were fromTafelsig High school. The schools had an average number of 104 students. Other schoolsin the survey with .10 respondents are shown in Table III.

Table III indicates that only a minority (57) had respondents ,10.Table I shows the frequency of the respondents by grade. It is evident that the

majority (50.60 per cent) of the respondents were Grade 11s.

InstrumentThe data collection instrument was self-administered structured questionnaire. The finalquestionnaire was pre-tested by sending it to randomly selected high schools. Based onthe feedback, the questionnaire was modified. Piloting is necessary as it is very difficult

School Frequency Percentage

Kasselsvlei High 120 10.9Elsies River High 108 9.8Oval North 77 7.0Tafelsig High 183 16.6Joe Slovo High 123 11.2Bellville Technical HS 100 9.1Masiyile Senior Secondary 130 11.8Symphony High 50 4.5Perseverence Secondary 14 1.3Oude Molen Technical HS 138 12.5Total 1,043 94.7

Table II.Frequencies of

respondents bysocio-economic location

School Frequency Percentage

Robinvale High 3 5.26Matthew Goniwe High 6 10.52Pelican Park High 6 10.52Westcliff High 9 15.78Malibu High 9 15.78John Ramsay Senior Secondary 5 8.77Alexander Sinton High 1 1.75Klein Nederburg 1 1.75Scottsville High 4 7.01Other schools 13 22.81Total 57 100.0

Table III.Frequency of respondents

(,10)

Grade Frequency Percentage

10 402 36.8511 552 50.6012 137 12.55Total 1,091 100.0

Table I.Frequencies of

respondents by grade

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to predict how respondents will interpret and react to questions (Gill and Johnson, 1991).The questionnaire comprised of nine parts. The first part examined backgroundinformation about the respondents. The second part examined factors impacting oncareer decisions. The third part investigated student knowledge of the constructionindustry. Part four identified the construction disciplines and professions consideredamong the high school students. The activities included in the work of a constructionmanager were examined in part five, whereas part six investigated the pre-requisite highschool subjects for construction management degree enrolment.

Part seven explored the fields of employment for construction managementgraduates. Various levels of agreement on construction-related statements were soughtin part eight. The 23 statements could be categorized into internal and external factorsaffecting the image of the construction industry. Finally, part nine investigates thecategories of construction employment that school children should seek.

The paper reports on the first and second parts of the survey instrument. The majorityof the second part had questions confined to simple “yes”, “no” and “unsure” consideringthe limited time available to interact with them.

Analysis of resultsAccording to Forza (2002), data analysis can be schematically divided into two phases:preliminary and hypothesis testing. Boyer et al. (2002) described these phases as macroand micro-level analysis. This study adopted both approaches. The first level (macro)was concerned with the aggregate surface characteristics of the respondents usingmeasures of the descriptive statistics such as the mean, standard deviation andmeasures of central tendency. Whereas the second level (micro) analysis involvedparametric tests such as separate independent t-test given that gender have only twocategories.

Statistical methodsThe primary focus of this study presented in this paper was to determine whetherdifferences existed in the factors affecting career decision in the South Africanconstruction industry between male and female high school students. Statistical packagefor social sciences (SPSS) computer program was used to analyse the data generated by theresearch questions. Separate independent t-test was used for the analysis. The overallreliability of the factors impact career decisions as measured by the Alpha Cronbach wasvery low (0.525 , 0.7). As observed by Wetzel (2005), descriptive statistics are concernedwith taking data and turning it into useful and consumable information. Forza (2002)opines that carrying out such preliminary data analysis before assessing the measurementof quality gives preliminary indication of how well the coding and entering of data havebeen, how good the scales are, and whether there is suspicion of poor content validity orsystematic bias. To find out whether there was a significant difference between the groups(male and female students); the Levene’s test also provided the solution in testing the equalvariance assumptions (Field, 2000). As asserted by Forza (2002), the function of t-tests is tosee whether there is a significant difference in the means for two groups in the variable ofinterest. To measure the impact of gender on career decision making in the South Africanconstruction industry, independent t-tests were conducted. The Kruskal-Wallis test wasused to compare the scores of the CDF across the three grades.

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Exploring the decision on the future careerAs far as their future careers are concerned, the majority (92.5 per cent) of the studentsstate that they have decided which profession to follow. Figure 1 shows the frequency ofrespondents by gender on considering a career in construction management.

Examination of Figure 1 shows that out of the 491 female respondents, 86.4 per centhad not considered a career in construction. But only 13.3 per cent reported thatthey had considered a career in construction or building. Slightly a higher proportion(16.5 per cent) of the males had considered a career in construction.

As Dainty et al. (2001) observe, maintaining an upwards trend in the number ofwomen in construction has always proved to be problematic. More so, the lack of femalerole models, diversity training and poor implementation of initiatives attribute to theprevailing stereotypes within the industry as a male dominated one (Ginige et al., 2007).When asked whether they had decided on their future career already, 72.5 per centresponded affirmatively.

Importance of construction disciplines and professionsThose students who had considered careers in construction were asked whichconstruction disciplines and professions they had in fact though about. Their responsesare indicated in Table IV.

The engineering disciplines of mechanical, electrical and civil predominated followedby project management (rank ¼ 4). Construction management and quantity surveyingranked 7th and last (10th), respectively. In order to ascertain the influence of parents orfamily on the decision not to enter construction, respondents were asked in whichdisciplines the parents were employed. Only 18.3 per cent of the students had parentsemployed in the various disciplines or practising as construction consulting professionals.The predominating disciplines or professions were mechanical engineering (18.3 per cent),electrical engineering (36.6 per cent), project management (9.2 per cent), civil engineering(8.5 per cent) and construction management (13.7 per cent).

Figure 1.Frequency of respondents

by gender on whether tohave a construction

management as a career

Have you considered a career in construction management?

16.5

83.5

13.3

86.4

Yes

No

Res

pons

e

Frequency of respondents

Male Female

0 10 20 30 40 50 60 70 80 90 100

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To analyse the importance of the construction discipline and professions, it wasimperative to compare the rankings and means of males and females high schoolstudents for all the ten disciplines included in the questionnaire. Results are shown inTable V.

Males reported significantly higher scores of the following disciplines as beingimportant; “mechanical engineering” (F ¼ 494.47, t ¼ 211.039, p ¼ 0.000 , 0.05),“electrical engineering” (F ¼ 397.46, t ¼ 29.578, p ¼ 0.000 , 0.05), “civil engineering”(F ¼ 302.691, t ¼ 28.359, p ¼ 0.000 , 0.05), “architecture” (F ¼ 285.86, t ¼ 28.069,p ¼ 0.000 , 0.05), “landscape architecture” (F ¼ 494.47, t ¼ 24.744, p ¼ 0.000 , 0.05)and “quantity surveying” (F ¼ 20.384, t ¼ 22.743, p ¼ 0.006 , 0.05). Femalesreported significantly higher score than males on “interior design” (F ¼ 26.553,t ¼ 2.553 p ¼ 0.011 , 0.05).

Exploring the possibility of women becoming construction managersMost students (82 per cent) believed that women could become construction managers.Interestingly, although there were no significant differences (F ¼ 0.030, t ¼ 1.476,p ¼ 0.140 . 0.05) in the scores between males and females on whether a woman could

Discipline/profession Yes (%) No (%) Meana SD Ranking

Mechanical engineering 31.0 69.0 1.69 0.46 1Electrical engineering 28.7 71.3 1.71 0.45 2Civil engineering 24.1 75.9 1.76 0.43 3Project management 22.9 77.1 1.77 0.42 4Interior design 20.6 79.4 1.80 0.41 5Architecture 18.7 81.3 1.81 0.39 6Construction management 15.2 84.8 1.85 0.36 7Landscape architecture 7.3 92.7 1.93 0.26 8Land surveying 7.1 92.9 1.93 0.26 9Quantity surveying 5.6 94.1 1.95 0.24 10

Notes: aThe smaller the mean the more students had considered the various disciplines andprofessions; full sample

Table IV.Construction disciplinesand professionsconsidered

M-rank F-rank Construction discipline M-mean F-mean t-stat.

1 3 Mechanical engineering 1.523 * 1.847 211.0392 4 Electrical engineering 1.660 * 1.848 29.5783 6 Civil engineering 1.669 * 1.873 28.3595 2 Project management 1.771 1.776 20.2096 1 Interior design 1.827 1.763 * 2.5534 7 Architecture 1.735 * 1.913 28.0697 5 Construction management 1.838 1.863 21.1778 10 Landscape architecture 1.895 * 1.966 24.7449 8 Land surveying 1.838 1.864 20.910

10 9 Quantity surveying 1.929 * 1.968 * 22.743

Notes: *Significant at: 95 per cent confidence interval; M-rank, male students’ rank; F-rank, femalestudents’ rank; M-mean, male students’ mean; F-mean, female students’ mean

Table V.Comparison of rankingsof males (M) and females(F) for importance ofconstruction disciplinesand professions

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become a construction manager, a minority 80 (12.9 per cent) were unsure whereas themajority (80.1 per cent) of the males agreed while 39 (6.3 per cent) disagreed that womencould become construction managers. On the other hand, the percentage of femalerespondents (13.3 per cent) who felt unsure about women becoming constructionmanagers was slightly higher than those of males, this despite the majority(83.5 per cent) stating that women could become construction managers. The results areconsistent with literature as Dainty et al. (1999) demonstrated that male peers perceivefemales as added competition for the limited promotion opportunities. Although theDainty et al. (1999) study was conducted within the UK, it reinforces the generally heldview that males considered construction to be their domain and has being a historicallymale-dominated sector (Dainty et al., 1999, p. 356).

Factors influencing career decisionsHigh school students were asked whether the listed factors influenced them in making acareer decision. The results are summarised in Table VI. The predominating factors forthe high school students as evidenced in Table V influencing their career choices weresalary (58.5 per cent), working conditions (40.2 per cent), opportunities for promotion(36.0 per cent) and lifelong learning (30.4 per cent). The choices of the few students(16.6 per cent) had being influenced by their teachers and/or guidance counsellorssuggesting that they were not major players in guiding career choices of students.

Table VI also sets out the means scores and standard deviations of ten factors for thefull sample of male and female high school students. As seen from the table, respondentsranked “salary” as the most important factor impacting career decisions. “Workingconditions”, “opportunities for promotion” and “lifelong learning opportunities” followedin order. “Family tradition” was insignificant in this study. It ranked 10th in order ofimportance.

In Table VI, the frequency of the responses of the ten factors is also presented for thefull sample whereas the statistics for the two groups, first males and then females arereported in Table VII. As seen from the Table VII, both male and female high schoolstudents ranked “salary” as the most important factor impacting career decisions.“Working conditions”, “opportunities for promotion” and “lifelong learning opportunities”

Career factors Yes (%) No (%) N/A (%) Meana SD

Salary 58.5 41.3 0.2 1.41 0.50Working conditions 40.2 59.6 0.2 1.59 0.49Opportunities for promotion 36.0 63.9 0.2 1.64 0.48Lifelong learning opportunities 30.4 69.4 0.2 1.69 0.47Status and prestige 17.0 82.8 0.2 1.83 0.38Teachers and counsellors 16.6 83.2 0.2 1.83 0.38Skills shortage 16.1 83.7 0.2 1.83 0.38Peers 12.7 87.3 0.2 1.87 0.34Media coverage 12.1 87.7 0.2 1.88 0.34Family tradition 11.3 88.5 0.2 1.88 0.33

Notes: aThe smaller the mean the more influential the factor on the career choice of the students; fullsample

Table VI.Factors impacting career

decisions

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followed in order. “Family tradition” and “peers” were insignificant in this study for maleand female high school students, respectively. They ranked 10th in order of importance.

Table VIII sets out the frequency of the responses to the ten CDF according to thegender of the high school students.

The findings in Tables VI-VIII contradict those of Courts and Moralee’s (1995)investigation into gender issues in the building professions who ranked family andfriends. Within the Greek context, Dimaki et al. (2005) drew similar conclusions withfamily, relatives as having the greater influence on the student’s choice of profession.On the contrary in this study the females ranked family tradition as one of the leastfactors (ranked 7th) likely to influence their career decisions. However, some limitationsin making the comparisons are noted as Court and Moralee’s sample consisted of firstand second-year under graduates from the university whereas this sample draws fromhigh school students. It must be acknowledged that the university sample provides moremeaningful responses as they are nearer to entering the profession world whereas thoseof high school students could still change.

Total sample (n ¼ 1,090)CDF Yes No Rank

Salary 637 451 1Working conditions 438 649 2Opportunities for promotion 391 696 3Lifelong learning opportunities 330 757 4Status and prestige 185 902 5Teachers and counsellors 181 906 6Skills shortage 176 911 7Peers 136 951 8Media coverage 132 955 9Family tradition 123 964 10

Note: Frequency of respondents (full sample)

Table VII.Factors impacting careerdecisions

Male (n ¼ 599) Female (n ¼ 491)CDF Yes No Rank Yes No Rank

Salary 369 229 1 268 222 1Working conditions 263 334 2 175 315 2Opportunities for promotion 245 352 3 146 344 3Lifelong learning opportunities 188 409 4 142 348 4Status and prestige 120 477 5 65 425 6Teachers and counsellors 80 517 6 101 389 5Skills shortage 119 478 7 57 433 9Peers 80 517 8 56 434 10Media coverage 73 524 9 59 431 7Family tradition 64 533 10 59 431 7

Note: Frequency of respondents by gender

Table VIII.Factors impacting careerdecisions

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To analyse the importance of CDF, it was imperative to compare the rankings and meansof males and female high school students for all ten CDF included in the questionnaire.Results are shown in Table IX.

There were six statistically significant differences in the degree of importance thatmales and female high school students placed on the particular CDF. To help in theunderstanding of these differences, the following section includes a discussion of thefive CDF perceived by male high school students to be more important, followed by adiscussion of the one factor perceived by female high school students to be moreimportant.

Gender differencesMale high school studentsMales reported significantly higher scores of “salary” (F ¼ 14.981, t ¼ 22.299,p ¼ 0.022 , 0.05), “opportunities for promotion” (F ¼ 51.172, t ¼ 23.829,p ¼ 0.000 , 0.05), “status and prestige” (F ¼ 34.210, t ¼ 22.901, p ¼ 0.002 , 0.05),“working conditions” (F ¼ 23.454, t ¼ 2.759, p ¼ 0.006 , 0.05) and “skills shortage”(F ¼ 53.77, t ¼ 23.603, p ¼ 0.000 , 0.05).

Table IX also shows the rankings (R) of the CDF according to gender. There were somedifferences in the rankings at the bottom of the factors. By far the biggest difference was infamily tradition. Males considered family tradition least important (tenth overall) whereasfemales considered it as seventh most important. This finding is consistent with literature.For example, Maringe (2006) found male students to consider parents, teachers and careerguidance as relatively unimportant to their decision making compared to their femalecounterparts. The research argued that the reasons for this difference could be attributedto the boys desire to demonstrate greater independence whereas girls were moreconcerned with building and strengthening relationships (Maringe, 2006, p. 476).

Female high school studentsFemales reported significantly higher score than males of “teachers and counsellors”(t ¼ 3.097, p , 0.05). The inference to be made is that gender does have an influence onthe factors impacting career decisions within the South African construction industryapart from where salary is concerned.

M-rank F-rank CDF M-mean F-mean t-stat.

1 1 Salary 1.381 * 1.450 22.3052 2 Working conditions 1.557 * 1.639 22.7503 3 Opportunities for promotion 1.587 * 1.699 23.8044 4 Lifelong learning opportunities 1.682 1.707 20.8635 6 Status and prestige 1.796 * 1.864 22.9016 5 Teachers and counsellors 1.863 1.790 * 3.1487 9 Skills shortage 1.798 * 1.879 23.6038 10 Peers 1.863 1.882 20.9179 7 Media coverage 1.875 1.876 20.058

10 7 Family tradition 1.889 1.876 0.697

Notes: *Significant at 95 per cent confidence interval; M-rank, male students’ rank; F-rank, femalestudents’ rank; M-mean, male students’ mean; F-mean, female students’ mean

Table IX.Comparison of rankings

of males (M) and females(F) for factors impacting

career decisions scores

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In order to ensure the correct interpretation of results from the independent-samplest-test, Levene’s test of equality of variances was conducted. This test whether the(variance) variation of scores for the two groups (males and females) is the same.This enabled the correct usage of which t-value that SPSS provides. As evident fromTable X the following factors (“life long learning”; “family tradition”; “media coverage”;and “ peers”) had sig. value larger than 0.05, therefore the t-value for equal variancesassumed was used. The remaining six CDF (“salary”; “opportunities for promotion”;“status and prestige”; “working conditions”; “teachers/counsellors”; and “skillsshortage”) had sig value , 0.05 and equal variances was not assumed.

Assessing the significance of the differences due to genderOne of the research questions that this study sought to investigate was how significantthese differences were to gender?

In order to find out whether there was a significant difference between the two groups(males and females) in the scores for the CDF, separate independent t-test was carried outin order to find out the effects of gender in career decision making the value of sig.(two-tailed) from the SPSS output provided the solution where sig. (two-tailed) is equal or,0.05 indicated a significant difference in the mean scores and for the value above 0.05,meant there was no significant difference between the two groups. Table XI shows theresults of the separate independent samples test (t-test) for assessing the differencebetween the mean scores. There was no significant difference in scores for males andfemales of “lifelong learning” (t ¼ 20.863, p . 0.05), “family tradition” (t ¼ 0.486,p . 0.05), “media coverage” (t ¼ 0.954, p . 0.05) and “peers” (t ¼ 0.360, p . 0.05).The findings indicate that there was no consensus among the males and female highschool students on the importance of the factors affecting the career decisions.

Figure 2 shows the association between gender and the CDF designated asCDF1-CDF10.

Given the concern about the persistent under-representation of women inconstruction, the responses to the career decision-making factors are stratified bygender to see if the pattern of influences is the same for males and females. Figure 2shows that the pattern is the same.

Levene’s testfor equalityof variances t-test for equality of means

CDF F Sig. T df Sig. (two-tailed) ( p , 0.05) Sig.

Salary 14.981 0.000 22.299 1,036 0.022 YesWorking conditions 23.454 0.000 22.759 1,085 0.006 YesOpportunities for promotion 51.172 0.000 23.829 1,067 0.000 YesLifelong learning opportunities 2.782 0.096 2 .863 1,054 0.389 NoStatus and prestige 34.210 0.000 22.901 1,085 0.003 YesTeachers and counsellors 38.977 0.000 3.0978 963 0.002 YesSkills shortage 53.777 0.000 23.603 1,087 0.000 YesPeers 3.306 0.069 20.917 1,087 0.360 NoMedia coverage 0.012 0.914 20.058 1,087 0.954 NoFamily tradition 1.921 0.166 0.697 1,087 0.486 No

Table X.Results of t-testcomparing factorsimpacting careerdecisions scores of malesand females

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CDF Grade n Mean rank Ranking

CDF1 ¼ salary 10 402 573.43 311 552 520.58 112 137 567.92 2

CDF2 ¼ working conditions 10 402 573.34 311 552 520.84 112 137 562.99 2

CDF3 ¼ opportunities for promotion 10 402 546.28 211 552 541.36 112 137 559.84 3

CDF4 ¼ lifelong learning opportunities 10 402 550.97 211 552 524.80 112 137 612.73 3

CDF5 ¼ status and prestige 10 402 546.98 211 552 547.83 312 137 531.79 1

CDF6 ¼ teachers and counsellors 10 402 551.75 311 552 540.90 112 137 545.67 2

CDF7 ¼ skills shortage 10 402 565.49 311 552 534.46 212 137 531.26 1

CDF8 ¼ peers 10 402 556.31 311 552 535.27 112 137 554.94 2

CDF9 ¼ media coverage 10 402 558.37 311 552 537.22 112 137 541.03 2

CDF10 ¼ family tradition 10 402 526.81 111 552 553.47 212 137 568.29 3

Note: Italicised values represent ranking of career decision factors based on grade of respondents

Table XI.Kruskal-Wallis test of

ranking of career decisionscores by grade

Figure 2.The relationship between

gender and CDF

The relationship between gender and positive (%) career decision scores

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CDF1 CDF2 CDF3 CDF4 CDF5 CDF6 CDF7 CDF8 CDF9 CDF10

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Assessing the significance of the differences due to gradeOne of the research questions that this study sought was to investigate the impact ofgrade on the career decision-making process? And whether there was a difference incareer decision-making scores across three grade levels. The Kruskal-Wallis test whichis the non-parametric alternative to a one-way between groups analysis of variance wasused to compare the scores for the three grade groups. Table X shows the results of theKruskal-Wallis test. The lower the mean score (based on category scoring of “yes ¼ 1”and “no ¼ 2”), indicates the group having the highest overall ranking that correspondsto the CDF.

An inspection of the mean ranks for the groups suggests that the middle grade (11) hadthe majority (70 per cent) of highest ranking of the CDF namely those of “salary”, “workingconditions”, “opportunities for promotion”, “lifelong learning opportunities”, “teachersand counsellors”, “peers” and “ media coverage” where as the lower grade reporting thehighest ranking on “family tradition” and the higher grade (12) considered “status andprestige” and “skills shortage” as the most important factors likely to influence their careerdecision-making process.

Exploring the relationship among the CDF and gradeThe x 2 for independence was used to explore the relationships among the variablesand sought to ascertain the following research question:

RQ. What is the relationship between grade and CDF?

Table XII shows the test statistics of the x 2 value, degrees of freedom (df) and thesignificance level (presented as asymp. sig.). If this significance level is a value ,0.05,then a conclusion could be drawn that there is a statistically significant difference in theCDF scores across the three groups or grades.

Examination of Table XII indicates that there is a difference in the five CDF scoresacross the different grades. Grade 11’s reported significantly higher scores of “salary”(x 2 (2) ¼ 10.011, p ¼ 0.007 , 0.05), “working conditions” (x 2 (2) ¼ 9.610,p ¼ 0.008 , 0.05) and “lifelong learning opportunities” (x 2 (2) ¼ 13.740,p ¼ 0.001 , 0.05), whereas Grade 12’s reported higher scores of “skills shortage”

CDF x 2 df Asymp. sig. ( p , 0.05) Significance (yes or no)

Salary 10.011 2 0.007 * YesWorking conditions 9.610 2 0.008 * YesOpportunities for promotion 0.551 2 0.759 NoLifelong learning opportunities 13.740 2 0.001 * YesStatus and prestige 0.701 2 0.704 NoTeachers and counsellors 0.658 2 0.720 NoSkills shortage 6.288 2 0.043 * YesPeers 3.555 2 0.169 NoMedia coverage 3.340 2 0.188 NoFamily tradition 8.170 2 0.017 * Yes

Notes: *Significantly different p , 0.05; aKruskal-Wallis test; grouping variable: what grade areyou in?

Table XII.Kruskal-Wallis teststatisticsa of significance

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(x 2 (2) ¼ 6.288, p ¼ 0.043 , 0.05), and Grade 10’s had higher scores in “familytradition” (x 2 (2) ¼ 8.170, p ¼ 0.017 , 0.05).

The above results are particularly important and significant as choices made duringthe early years of high school are particularly significant in setting the foundation for thefuture occupational preferences, more so the factors considered important in the earlyyears are paramount if students are to consider a career in construction. The findingsalso indicate that students in the early years of high school are likely to be influenced byfamily tradition whereas as they progress, they begin to discover their own interests andtalents which inevitably leads to a shift to other import factors such as salary asevidenced by those in grade 13’s.

Key findingsThis paper the impact of gender on factors impacting on their career decisions inSouth African construction industry. Descriptive statistics and analysis of variancewas used to identify differences in perceptions of the factors on career decisions fromthe view of male and female high school students. The findings indicate that althoughsalary, working conditions, opportunities for promotion and lifelong learning are likelyto be the most important factors for high school students considering a career withinthe construction industry, this is not dependent on the gender of the students expectwhere salary is concerned. In particular, this study found that male students were morelikely to be influenced by salary, working conditions, opportunities for promotion,status and prestige, and skills shortage than their female counterparts as a decisivefactor in joining the construction industry. On the other hand females are more likely tobe influenced by teachers and counsellors. Borrowing from studies conducted withinthe USA, factors affecting the major choices can be classified into external and internal.Some of the internal factors are related to the following; lack of self-confidence;fear/anxiety; conflicting values; conflict with significant others; and multipotentiality,whereas external factors relate to lack of information; too much information; andsubjects studies and careers do not seem to relate. The following subsection presentsa summary of discussion of these factors as identified within this study.

External factorsThe sub external factors are discussed as follows:

. Lack of information. Further, traditional universities need to advertise morewidely than at present those construction management qualifications may begained on their campuses. There is clearly a role for Higher Education Institutionsto play in promoting careers in construction. This could be attributed tonon-promotion of construction as a career which also has been influenced bythe lethargy of industry stakeholders to promote them positively. For example, thenegative publicity in the media consequent to recent construction-related fatalitiesand injuries has not drawn any response from the industry to promote itself as onethat is not typically characterized by such incidents. Rather the industry has beenconspicuous by its silence and resultantly perpetuating the pervasive negativity.Studies such Gale (1994) and Fielden et al. (2001) within the western context haveargued that the low level image of the industry could act as a constraint for peoplewishing to join it.

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. Too much information. Too much information can lead students to beingoverwhelmed with deciding on the correct career. As argued by Maringe andCarter (2007), this is the second stage of any decision-making model or process;that of searching for information. This aspect requires the input of the teachersand counsellors to assist with the process, however the findings of this studyshows that only the females consider them to be more important compared theirmale counterparts.

. Subjects and careers do not seem to relate. There is a clear need for differentiatingbetween the subjects offered within the high schools and the types of work(career) that the students might choose. According to research, the inherentdifference lies in careers being largely skill based whereas taught subjects wereschool driven. Given the brief description of the external factors, the followingsub section now discusses the internal factors.

Internal factorsGiven the discussion of the external factors, the following sub section now explores theinternal sub-factors.

Lack of self confidenceResearch has shown that this sub factor is closely linked to the “lack of information”,which inevitably manifests itself in high school students not being aware of what theproducts of the construction industry are:

. Fear/anxiety. Evidence from literature indicates that “fear and anxiety” impactson the career decision-making process resulting in making bad decisions. Moreso, previous research such as Gale (1994) and Dainty et al. (2004b) found lowerlevels of female’s self confidence at career level compared to the males.

. Conflicting values. High school students have different expectations; as suchpersonal values would not be compatible with the work desired.

. Conflict with significant others. High school teachers and guidance counsellors areineffectual agencies to influence career choices especially in construction. It islikely that teachers and counsellors themselves have been negatively influencedby the poor image of the industry. The findings of this study indicate that highschool students are unlikely to be influenced by the teachers and counsellorsaccording to males (mean ¼ 1.863; rank ¼ 6) and females (mean ¼ 1.790;rank ¼ 5).

. Multipotentiality. According to the research in the USA, multipotentiality refersto have having more interests and even more abilities resulting in a situationwhere more options are drawn than narrowing to a specific career choice.

LimitationsWhile this study contributes to the literature by examining an under-researched topicand increasing our understanding of the factors impacting career decisions among highschool students in South Africa, it is not without limitations. This study has severallimitations. First, usage of a cross-sectional nature of this study as this thoughrepresenting a snapshot of the high school students perceptions at a point in time,it presents more of a picture, albeit far from complete, than what is available in

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the literature. Second, although the descriptive statistics used in this research paper aretaken from within the South African high schools, the factors impacting career decisionsare universal and of interest to the academia and construction industry world wide.

Conclusions and implications for future researchThis paper explores the factors impacting on the career decisions of high schoolstudents in a South African context. Descriptive statistics and analysis of variancewere used to identify differences in perceptions of female and male high schoolstudents. Despite the similarities in the importance of the factors associated with maleand female decision-making process such as salary, working conditions, opportunitiesfor promotion and life learning opportunities, there are some important differences,particularly in the least important factors. Whereas males regard “media coverage”and “family tradition” as having the least impact on the CDF, on the contrary femalesfound “peers” and “skills shortage” to be the least important factors:

. In the study, the genders exhibit significant differences in their rankings of “salary”,“working conditions”, “opportunities for promotion”, “status and prestige”,“teachers and counsellors” and “skills shortage”, all favouring males apart from“teachers and counsellors” in which females scored higher. This evidence isconsistent with that of Wilkinson (1996), who found that the men were significantlyinfluenced by “salary”. Although in this study both males and female’s rankedsalary has the most important factor, some significant differences existed withmales reporting higher scores than the females.

. In the study, the grades exhibit significant differences in their rankings of“salary”, “working conditions” and “lifelong learning opportunities”, all favouringGrade 11’s apart from “skills shortage” and “family tradition” in which Grade 12’sand 10’s scored higher, respectively. This evidence indicates that as studentsprogress to higher grades, they become more aware of other external influences intheir decision making and examine their motivation for engaging in the process.

. Furthermore, despite significant differences between male and female high schoolstudents in the importance of the CDF, the top four rankings were the same. Othersthe positions were reversed for status and prestige (fifth for male and sixth forfemales) and teachers and counsellors (fifth for female and sixth for males).

ContributionsThe results presented in this paper are important in several ways. First, they suggestthat both male and female high school students are influenced by common factors indeciding to enter the construction industry, these being salary, working conditions,opportunities for promotion and lifelong learning opportunities. As argued byWilkinson (1996), women and men tend to agree on which factors are of the greatestimportance and so, other things being equal, there should be a fair representation of bothsexes within the South African construction industry, however that appears not be thecase. Therefore, the results presents an opportunity for both industry and agencies suchas the construction industry development board, construction education and trainingauthority and learned societies need to embark on a vigorous marketing campaign topromote the construction industry. Such a strategy needs to project the industry as onethat provides sustainable and financially rewarding employment in an environment

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characterized by good working conditions and opportunities for promotion and lifelonglearning.

Second, in order to address one of the external factors, namely “lack of information”and considering that this study focused on high school students prior to embarking ontheir university course selection, there is still an opportunity for effective marketingstrategies from the industry geared towards high school students. This in essence wouldhelp them to consider studying for courses geared toward a career within theconstruction industry.

References

Adeyemi, A.Y., Ojo, S.O., Aina, O.O. and Olanipekun, E.A. (2006), “Empirical evidence of womenunder-representation in the construction industry in Nigeria”, Women in ManagementReview, Vol. 21 No. 7, pp. 567-77.

Agapiou, A. (2002a), “Exploring the attitudes of school-age children, their parents and educators tocareer prospects in the Scottish construction industry”, Equal Opportunities International,Vol. 21 No. 8, pp. 18-29.

Agapiou, A. (2002b), “Perceptions of gender roles and attitudes towards among male and femaleoperatives in the Scottish construction industry”, Construction Management andEconomics, Vol. 20 No. 8, pp. 697-706.

Bennett, J.F., Davidson, M.J. and Gale, A.W. (1999), “Women in construction: a comparativeinvestigation into the expectations and experiences of female and male constructionundergraduates and employees”, Women in Management Review, Vol. 14 No. 7, pp. 273-91.

Boyer, K.K., Olson, J.R., Catantone, R.J. and Jackson, E.C. (2002), “Print versus electronic surveys:a comparison of two data collection methodologies”, Journal of Operations Management,Vol. 18, pp. 357-73.

Calkins, L.N. and Welki, A. (2006), “Factors that influence choice of major: why some studentsnever consider economics”, International Journal of Social Economics, Vol. 33 No. 8,pp. 547-64.

Court, G. and Moralee, J. (1995), “Balancing the building team-gender issues in the buildingprofessions”, Report 284, The Institute for Employment Studies, Brighton.

Dainty, A.R.J., Bagihole, B.M. and Neale, R.H. (2000), “A grounded theory of women’s careerunderachievement in large UK construction companies”, Construction Management andEconomics, Vol. 18 No. 2, pp. 239-50.

Dainty, A.R.J., Bagihole, B.M. and Neale, R.H. (2001), “Male and female perspectives on equalitymeasures for the UK construction sector”, Women in Management Review, Vol. 16 No. 6,pp. 297-304.

Dainty, A.R.J., Ison, S.G. and Root, D.S. (2004a), “Bridging the skills gap: a regionally drivenstrategy for resolving the construction labour market crisis”,Engineering, Construction andArchitectural Management, Vol. 11 No. 4, pp. 275-83.

Dainty, A.R.J., Neale, R.H. and Bagihole, B.M. (1999), “Women careers in large constructioncompanies: expectations unfulfilled?”, Career Development International, Vol. 4 No. 7,pp. 353-7.

Dainty, A.R.J., Bagilhole, B.M., Ansari, K.H. and Jackson, J. (2004b), “Creating equality in theconstruction industry: an agenda for change for women and ethnic minorities”, Journal ofConstruction Research, Vol. 5 No. 1, pp. 75-86.

JEDT8,2

238

Dimaki, K., Kaminioti, O., Kostaki, A., Psarakis, S. and Tsourti, Z. (2005), “Education andoccupational preferences of high school students in Greece”, Educationþ Training, Vol. 47No. 6, pp. 432-46.

DTI (2006), Review of Sustainable Construction 2006 – A Summary, Department of Trade andIndustry, Makati City.

Field, A. (2000), Discovering Statistics Using SPSS for Windows, Sage, Thousands Oaks,CA.Fielden, S.L., Davidson, M.J., Gale, A. and Davey, C.L. (2000), “Women in construction:the untapped resource”, Construction Management and Economics, Vol. 18 No. 2,pp. 239-50.

Fielden, S.L., Davidson, M.J., Gale, A. and Davey, C.L. (2001), “Women, equality andconstruction”, Journal of Management Development, Vol. 20 No. 4, pp. 293-304.

Forza, C. (2002), “Survey research in operations management: a process based perspective”,International Journal of Operations & Production Management, Vol. 22 No. 2, pp. 152-94.

Gale, A.W. (1994), “Women in non-tradition occupations – the construction industry”, Women inManagement Review, Vol. 9 No. 2, pp. 3-14.

Gale, A.W. and Cartwright, S. (1995), “Women in project management: entry into a male domain?A discussion on gender and organizational culture – part 1”, Leadership & OrganizationalDevelopment Journal, Vol. 16 No. 2, pp. 3-8.

Gill, J. and Johnson, P. (1991), Research Methods for Managers, Paul Chapman, London.

Ginige, K., Amaratunga, D. and Haigh, R. (2007), “Gender stereotypes: a barrier for careerdevelopment of women in construction”, Proceedings of the Built Environment EducationConference (BEECON 2007), 12-13 September, CEBE, London.

Glover, S.H., Bumpus, M.A., Sharp, G.F. and Munchus, G.A. (2002), “Gender differences in ethicaldecision making”, Women in Management Review, Vol. 17 No. 5, pp. 217-27.

Ling, F.Y.Y. and Poh, Y.P. (2004), “Encouraging more female quantity surveying graduates toenter the construction industry in Singapore”, Women in Management Review, Vol. 19No. 8, pp. 431-6.

Maringe, F. (2006), “University and course choice: implications for positioning, recruitment andmarketing”, International Journal of Educational Management, Vol. 20 No. 6, pp. 466-79.

Maringe, F. and Carter, S. (2007), “International students’ motivation for studying in UK HE:insights into choice and decision making of African students”, International Journal ofEducational Management, Vol. 21 No. 6, pp. 459-75.

Powell, A., Bagihole, B.M., Dainty, A.R.J. and Neale, R. (2004), “Does the engineering culture inUK higher education advance women’s careers?”, Equal Opportunities International,Vol. 23 Nos 7/8, pp. 21-38.

Wetzel, D. (2005), “Statistics do three things – describe, compare and relate”, iSixSigma Insights,Vol. 6 No. 54, pp. 1-9, available at: www.isixsigma.com/library/content/c050713a.asp

Wilkinson, S. (1996), “The factors affecting the career choice of male and female engineeringstudents in the UK”, Career Development International, Vol. 1 No. 5, pp. 45-50.

Corresponding authorNicholas Chileshe can be contacted at: Nicholas.Chileshe@unisa.edu.au

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