Acta Universitatis Danubius. Œconomica, Vol 10, No 4 (2014)

Demographic Variables and Job Performance: Any Link?

(A Case of Insurance Salesmen)

Banjo Hassan1, Olufemi Ogunkoya2

Abstract: This paper examines the relationship between socio-economic backgrounds of insurance salesmen on the job performance. The demographic factors studied include age, marital status, educational qualification, job tenure and gender. Using a descriptive design, a total of one hundred and thirteen respondents were studied. Using primary data generated through 1questionnaire, the result of the study analyzed by both regression and correlation indicated a moderate positive relationship between the variable studied and job performance. Jointly, they account for 13% of factors explaining the performance of job of the respondents. However marital status and job tenure were found to be mostly predictive of job performance of insurance salesmen. The paper discussed the implications for the practice of management and human resource management.

Keywords: demographic characteristics; salesmen; Job Performance; insurance

1. Introduction

The Nigerian insurance industry has since witnessed growth with many more insurance firms entering the industry. This monumental growth is evident in the number of actors in the industry with almost all the commercial banks having its own insurance company. This coupled with bad attitude to insurance in the developing nation like Nigeria has consequently resulted in stiffer competition among the players in the industry. To this end, Nigerian insurance companies are now responding to such challenges by adopting various strategies that can help them survive in the long run. One of such strategies is the use of aggressive marketing strategies using sales force.

However, human resource managers are concerned with qualities and background of staff that best suit marketing positions. To achieve a fit between the job and the jobholders, managers either have to make the job to match the person characteristic or make the persons characteristics to match required job. Obviously, the former is easier and cheaper. These socio-economic characteristics of the marketing/sales force personnel like age, educational qualification, sex, marital status and years of service jointly known as demographic factors are capable of affecting their different work performance dimensions (Palakurthi & Parks, 2000). For instance Gelles et al. (1994) observed that males are physically active than their female counterparts while females tend to be more verbal than the males. Women have also been found to be faster in the use of the hand/fingers to do manual jobs like typesetting, weaving etc.

As a rule, males are more physically active than females. Females tend to be more verbal than males. Men value independence and achievement while women value intimacy and attachment. While men are action oriented “they take care of the business”, while women are people oriented they take care of others. It is thus logical to expect difference attitude to and work performance.

Also lengths of job service also tend to improve job performance because of acquaintance. Hari (1989) posits that training efforts have in fact led to improvement in performance. Organisations are concerned with placing the right person in the right job and positions, because of its effectiveness and efficiency.

While various literatures, academics and authors have found the relationship between employees’ demography and job performance to be vague, professionals seem to place emphasis on employees socio-economics background in employing and job placement decisions. Although, Davies et al, 1991, Rhodes 1983 and Warr 1994 in their studies said demography affects performance insignificantly, Waldman & Avilio (1986) concluded it does with positive r-value (r = 0.07).

Therefore, this study seeks to investigate the nature of the relationship between the demographic features of insurance salesmen and their performance, the remaining parts of this study include a brief literature review, research methods, data analysis, conclusions and recommendations.

2. Literature Review

2.1. The Concept of Job Performance

Job performance is a dynamic, multidimensional construct assumed to be an indicating of an employee’s behaviour in executing the requirement of a given organizational role (Kavanagh, 1982). It has been studied and well documented that individual job performance is dynamic (i.e. it changed, over time) (Deadrick & Madigan, 1990: Polyhard & Barratta, 1993; Henry & Hullin, 1987).

However, despite the fundamental importance of predicting job performance to industrial-organizational psychology and organizational practice, the field still knows relatively little about the nature of individual performance change overtime (Polyhart & Hakel, 1998). Although there is nothing inherently causal about time (Hulin et al., 1990), some changes in any measure of job performance may be attributed to effects approximated by temporal variables (Deadrick et al., 1997; Hofman et al., 1992, 1993).

Kavangh argues that job performance, as a construct can be directly observable. What one does observe is the individual’s behaviours on the job and one assumes that this corresponds to job performance. Thus there is a set of observable phenomena (job behaviours) that one hypothesis do, in fact, represents job performance, an abstract.

According to Sawyer (1953) and Portar, performance is the end result of application of effort. They contend that it is the aspects of organisations are most desiring of measuring and influencing. Mitchell, Terry made an insight that the process of change in the performance of individuals is further complicated by the fact that what might be considered “good” behaviours of performance by the organisation changes over time. Thus he contends that employees are changing in term of their perception of what is “good” job performance and the company’s perception of what is “good” job performance is also changing. This he argues is the strongest reason for the need for building a dynamic component into job performance appraisal programmes.

2.2. Education and Job Performance

Hacket (1979) defined education as the process of acquiring background knowledge of a subject. It is person rather than job or company oriented. It is the knowledge and abilities, development of character and mental power resulting from intellectual training. It can and thus influences attitudes both positive and negative towards work and commitment.

Entry into higher level jobs is often restricted to college graduates and in many cases, college graduates and professionals degrees are required. Persons are selected and certified by higher institutions largely on the basis of measures of academic aptitude or performance but the relationship between this measures and job performance (or productivity) is not largely known (Wise, 1975). Yet, the assumption of economic efficiency, would however suggest an existence of a causal relationship while equity would require it.

In a widely cited work of Ng & Feldman (2009), education is positively related to task performance. Their meta-analysis study on the relationships between education level and 9 dimensions of job behaviors representing task, citizenship, and counterproductive performance indicates that, in addition to positively influencing core task performance, education level is also positively related to creativity and citizenship behaviour and negatively related to on-the-job substance use and absenteeism. Other authors (Hunter, 1986; Kuncel et al., 2004) also believe education facilitates performance in most jobs.

2.3. Gender and Job Performance

One difficulty encountered by investigators of sex differences and performance among workers in organizational settings is the difficulty of comparing the performance of men and women carrying out exactly the same job owing to gender segregation in the allocation of work tasks (Rydstedt & Evans, 1998).

Men and women differ significantly in their characteristics. Although sex refers to the biological differences between male and females, the list of actual differences is potentially long. Obviously, males and females differ automatically. As a rule, males are more physically active than females. Females tend to be more verbal than males. Men value independence and achievement, women value intimacy and attachment. While men are action oriented “they take care of the business”, while women are people oriented they take care of others.

In many countries of the world, these differences cause government labour regulating agencies to regulate the employment of women. For example the employment of women on night work or underground is severely limited in the US. Hence, some of these restrictions among others mean that other things being equal, an employer who is faced with the choice of hiring either a male or a female for a job would choose the male. It is therefore not so much a matter of “gender discrimination” as some writers have argued but one of economic logic.

To a high degree, the job market is still segregated by gender. The world of “men’s work” and “women’s work” are as different as east and west; they are vastly unequal in power, pay and prestige. This have made comparison of performance between the two genders to come late. Kundson (1982) believes that women were as able as men if given similar exposure. Although according to Hartman (1988), men were seen as more powerful than women and viewed good performance as a male characteristic. Also, Yammarino & Dubinsky (1988) found gender and job differences in their study of the influence of gender on performance.

In a similar vein, Green, Jegadeesh & Tang (2009) studied the relationship between gender and job performance among brokerage firm equity analysts. The study found significant gender-based differences in performance on various dimension. Although it added that women are significantly more likely than men to be designated as All-Stars, which indicates that they outperform men in other aspects of job performance.

2.4. Marital Status and Job Performance

Some studies have found that women who held both work and family roles reported better physical and mental health and consequently better job performance than was reported by women who stayed at home or single. Traditional conceptions of marriage as entailing greater social responsibilities outside the workplace for women as noted by Hoobler, Wayne & Lemmon (2009) may promote perceptions of married women as less suitable for employment compared to single women. (Jordan & Ziteck, 2012)

Due to the assumption that women are less likely to be relied upon as the primary breadwinner for a married couple, people might expect married female employees to be less dedicated to their jobs compared to their single counterparts (who must provide their own income), whereas people might expect male employees to be more motivated in their jobs if married.

2.5. Service Years and Job Performance

Obikoya (2002) while identifying training needs quickly pointed at the new employees orientation. According to him, new employees often require new or additional training to learn skill specific to the job. As pointed earlier, education, which new employees have, is person oriented and not job or company oriented. This therefore goes to show that people who have stayed long on the job are not likely to make mistakes like new employees on the job, hence perform better.

Researches however find that beyond a certain stage, years in the service do not affect job performance. Yet employers are reluctant to retire the old employees of their organisations. This is because they want them to say back and train those who will replace them.

Ng and Feldman (2010) found evidence of a curvilinear relationship between organizational tenure and job performance. According to them, although the relationship of organizational tenure with job performance is positive in general, the strength of the association decreases as organizational tenure increases

Also worthy of note is that training of workers of organisations is a form of cost to the organisation and represents investment in human capital. This provides the reason why management prefers workers who have stayed relatively longer on the job to new employees. Reports say that most organisations in retrenching workers prefer to keep employees of more service years to less ones.

2.6. Empirical Evidence

The connection between formal schooling and occupational performance has been challenged by Anderson in the suggestion that the correlation between the two especially in developed countries is comparatively loose. In his conclusion, Berg (1971) had used a formidable array of statistical data to argue that the familiar correlation between educational training and job performance is a myth. From his studies, he observed that there is no association between the education attainment of these technicians and the evaluations they receive from supervisory personnel, nor was there any association between education and absenteeism.

In white-collar study, he also noted that performance in 125 branch offices of a major New-York bank, measured by turnover and data, and by the number of lost accounts per teller was inversely associated with educational achievements of those 500 workers. Ariss & Timmins (1989) also examines the relationship between the type of college degree, level of college degree, and superiors' perceptions of managers' attributes and their work performance in some management areas. Their study found no significant relationship between managers' college education and their performance at work

In spite of those rather, iconoclastic remark on the erstwhile assumptions about the relationship between education, productivity and economic development, even Berg himself admitted that “it would be foolish to deny that level of education is involved in the nation’s capacity to produce goods and services”.

In another research carried out by Sturman (2001), he argues that empirical research suggested that Job experience; organizational tenure and age have non-linear relationships with job performance. Considered simultaneously, there should exist an inverted U-shape relationship between time and performance.

Alli (2003) also studied the effect of age, sex and tenure in the job performance of rubber tapers. He stated that job performance can be assessed both by objective measures, using data derived from production records, and by performance ratings made by managers, supervisors and peers. Studies of the relation between age and job performance according to him, using objective production records data are relatively rare partly because of the various methodological and practical difficulties inherent in this kind of research.

Most reviews have generally concluded that the effects of age on job performance are slight (Davies et al, 1991; Rhodes, 1983; Warr, 1994). The meta-analysis conducted by Waldman and Avilio (1993) showed a small but positive relationship between age and productivity (r = 0.27) while a later one (Evoy & Cascio, 1989) indicated that age and productivity were essentially related (r = 0.07).

For skilled and semi-skilled and technical jobs, an inverted U-shaped relation between age and job performance has often been found with performance peaking in late 30s or early 40s (Clay, 1956; Greenbery, 1960; King, 1956; Sparrow & Davies, 1988). A curvilinear relationship between age and job performance have also been found reported for sales people (Day, 1993; Kelleher & Quick, 1973).

The empirical findings of Tillou & Liarte (2008) in their study confirm the positive impact of group members' experience on the global performance of the group. Their analysis shows a strong positive impact of age on group performance. Moreso, experience within the organization (tenure experience) also had an impact on performance though less significant.

Experience, usually measured by tenure or length of service tends to be highly positively correlated with worker age. Some studies of industrial and clerical jobs have shown that when tenure is controlled, age effects on job performance disappear, conversely when age is controlled, effects of tenure remains (Avolio; Waldman & Denial, 1990; Giniger; Dispenzieri & Eisenberg, 1983).

Studies examine sex differences in job performance have mainly focused on performance evaluations using ratings and rankings carried out by supervisors or managers (Arvey et al., 1992). However job performance rating are susceptible to bias (Nieva & Gutek, 1980) and where they involve male and female workers, they may be influenced by gender stereotyping (Maurer & Taylor, 1994) and by negative evaluations of women’s job related abilities (Greenhaus & Parasuraman, 1983).


H0: Demographic factors of insurance salesmen do not have any relationship with job performance

H1: The demographic characteristics of insurance salesmen have strong relationship with job performance

3. Methodology

This study examined the nature of the relationship between the socio-economic characteristics of salesmen and their performance in Nigeria insurance industry. To achieve this, a survey research design was adopted as data was generated through a well-structured questionnaire designed by the authors. We used a five point Likert scale (1=strongly disagree; 5=strongly agree). The questionnaire includes two aspects; the first aspects deals with the demographic characteristics of the respondents while the second aspects test the extent of their agreement to the various statements designed to establish the nature of the relationship that exist between these demographic variables and their performance.

The respondents comprised of various insurance policy salesmen in Lagos asked to fill in the questionnaire and recommended other potential respondents. In all, One hundred and fifty eight (158) questionnaires were administered while only one hundred and thirteen (113) completed questionnaires were received giving a response rate of 69%. The sample consisted only of insurance policy salesmen in Lagos. While job performance was the dependent variable, demographic factors are the independent variables. The nature of relationship and the direction were tested using Pearson Product Moment Correlation and regression analysis. The demographic variables tested in the study against job performance are Age, Marital status, Years of in-service, Educational qualification and sex respectively.

4. Results and Discussions

Table 1. Frequency Table showing Socio-Economic Characteristics of the respondents










Marital status




Not Married




Above 30









50 and above













Year of Employment

Below 1 year



1 to 3 years



3 years and above



Table 1 above reveals the demography of the respondents of the study. It shows that majority of the salesmen are Males and between 31 and 40 years olds. About 60% are also married. A larger portion of the respondents have also spent between 1 and 3 years in the service representing about 47%. It also appears that the use of non-degree holders in the marketing of insurance product is almost disappearing as only 18% have either OND or NCE.

Table showing the relationship between Demographic features and job performance.

Table 2. Correlation Matrix



























Field survey 2014. Critical Value r=0.272

Table 2 presents the correlation of the selected five demographic characteristics of the salesmen believed to be capable of influencing job performance. The table reveals that marital status and age are significantly negatively correlated as r= -0.59. Equally, Age is found to be negatively correlated with years of service. (r= -0.4) just as years of service and academic qualification are negatively correlated.

Table 3. Multiple Regression Analysis table of Job Performance and with the Five Demographic variables

Score of Variation


Sum of Square

Mean Square
















Significant at 0.05 F tab=1.34, N=113 Source: Field survey


Standard error = 0.44

Multiple regression Coefficient= 0.42

The analysis of the multiple regressions is presented in table 3. The multiple regression coefficient obtained is 0.42 and standard error 0.44. The demographic variables included in the model jointly account for about 13% of the factors that influence job performance. This is significant at 95% confidence level, though the co-efficient R2 appears low. This finding is in congruence with that of Alli (2003) to the effect that performance of employees can be determined by their personal characteristics.

Summary Table of regression Analysis of Job Performance with the Demographic Variables Tested




Std Error

Std.PartialRegr. Coeff

Std. Error of Partial Coeff.


T- Val









Marital Status







Yrs of Service







Educational Qualification














Source: Field Survey 2014

Table 5 shows that out of the variables considered, only two actually predict job performance of salesmen. They are years of employment on the current job and marital status. Both are found to be significant at 0.05. This shows that the more the salesmen stay on their jobs as salesperson, the more their performance. Therefore the experience curve is found to be applicable to the performance of sales men. This however should call the attention of the management of the insurance companies as it is found that as years pass by, the number of sales men reduces. This is evident in table 1. Sometimes also, they are transferred to administrative works like training when in fact; they can still be more useful to the company in the capacity of a salesman.

Equally, marital status was found to be predictive of job performance. This may be due to the seeming difficulty in managing work/family combination challenges. The work of field salesmen like that of insurance may require them to stay late in closing sales and deals among other challenges which may be difficult for married parents especially women. The result of the study is not too different from that of Shaffril & Uli (2010) who found that age, working experience and gross salary are correlated with work performance.

5. Conclusion and Implication for Management

The result of the study shows that only marital status and years of service are mostly predictive of performance of insurance salesmen. Age is significantly negatively correlated with marital status. Jointly considered however, the five studied demographic variables are positively correlated with performance as explain about 13% of the factors that influence performance of the insurance sales men. This was also significant at 5%.

Consequent on the findings of this study and others in the literatures, we hereby make the following recommendations:

  1. the range of time when experience (years of service) ceases to contribute to performance should be investigated;

  2. efforts should be made by management to retain salesmen as their experience have been found to predict their performance if well managed and coordinated;

  3. more of the middle aged should be employed as salesmen.

6. References

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1 Department of Business Administration, Olabisi Onabanjo University, Nigeria. Address: Ago-Iwoye, 23437, Ogun State, Nigeria. Tel.: 2348157711895. Corresponding author:

2 Department of Business Administration, Olabisi Onabanjo University, Nigeria. Address: Ago-Iwoye, 23437, Ogun State, Nigeria. Tel: 2348059490311. E-mail:

AUDŒ, Vol. 10, no. 4, pp. 19-30


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