Research Journal of Management Sciences ____________________________________________ ISSN 2319–1171 Vol. 2(9), 1-6, September (2013) Res. J. Management Sci. International Science Congress Association 1 Road to the Top- Barriers Faced by Women in the Financial Sector in Oman Sen Nupur, Kandpal Deepa and Tinani Khimya2 Department of Management, Waljat College of Applied Sciences, Rusayl, Muscat, Sultanate of OMAN, Department of Statistics, Faculty of Science, the M.S. University of Baroda, Vadodara, Gujarat, INDIAAvailable online at: www.isca.in Received 23rd July 2013, revised 3rd August 2013, accepted 1st September 2013 AbstractAccording to statistics available, women world-wide can be seen joining the workforce in large numbers. The same trend is observed in Oman, where women can be seen working in large numbers in the services sector, especially in the Financial sector. Although they form such a large proportion, almost 50%, of the working population, they still lag behind when it comes to career advancement. This study tries to identify the barriers to career advancement of women in the financial sector in Oman. Some of the statistical tests used are Chi-square and descriptive statistics like Mean and Principal Component Analysis. A definite association was found between the barriers identified and career advancement of women in the financial sector in Oman.Keywords: Barriers,Career advancement, financial Sector, Oman, Women . Introduction The Sultanate of Oman is a middleincome monarchy located in the southeast of the Arab Peninsula with an area of 309,500 km and a population of around 3.1 million (estimated in 2012) with a rapid growth rate of more than 3% per annum. Its’ major products are crude oil (and refining of crude oil) and liquefied natural gas. Other sectors include construction, cement, steel, chemicals, optical fibre and copper. The Omani banking sector, which comprises the Central Bank of Oman (CBO) and various commercial and specialised banks operating in the Sultanate, is stable, efficient and able to respond to regional and international developments, including the growing trend towards freeing up financial services within the framework of the World Trade Organisation (WTO). The Capital Market Authority (CMA), a governmental authority, is responsible for organizing and overseeing the issue and trading of securities in the Sultanate and an exchange named the Muscat Securities Market (MSM) was set up where all listed securities are traded. The financial sector in Oman also includes several Financing and leasing companies as well as Insurance companies. As per the CIA World Fact book, Oman’s GDP per capita has reached US Dollars 28,500 (2012 estimated figures).According to the latest population census in 2010, the labour force constitutes 37.3 percent of the total population, with a growth rate of 4.7 per cent per annum. Expatriates, who represent 23.9 per cent of the population, constitute almost half of this labour force. Women account for 24.7 per cent of the total Omani labour force in both the public and private sectors. Sustainable development cannot be achieved without the active involvement and participation of both men and women on a basis of full equality. The percentage of women in the labour force (for the age group 15 years+) has risen from a level of 33% in 1960 to 40% in 2010. This shows the significant level of participation of women in the labour force. In Oman, more and more women are taking up employment. In 1995, of the women older than 15 years of age, only 19.5% were employed. This figure has risen steadily to 22.7% in 2000, 25.1% in 2005 and 28% in 2010. Women form almost 50% of the population worldwide and their role in industry cannot be under-estimated today as a large proportion of women are getting educated. In Oman, since the beginning of the blessed Renaissance, His Majesty Sultan Qaboos’ policies have focused on encouraging Omani women to strengthen their self-confidence, refine their skills and enable them to participate actively in building the nation, thus making them a part of the country's development process. The challenges of globalization and free economy compelled Omani women to participate more actively in nation-building. Women in the Sultanate have moved on, from being just caretakers of their families to decision makers and policy makers in all the sectors of the Omani economy contrary to social perceptions and stereo-types. A similar study has already been done for the hospitality sector. However, such attainments are not so numerous. In the Public Sector, the number of Omani women in the labour force increased by 5,113 between 2008 and 2009 at a rate of 1.3%. During 2009, the Omani women’s share in the labour force was Research Journal of Management Sciences ________________________________________________________ ISSN 2319–1171Vol. 2(9), 1-6, September (2013) Res. J. Management Sci.International Science Congress Association 2 recorded at 19.3% as compared to 18% in 2008. However, despite such high level of participation in the labour force, how is it that we find only a handful of women in senior management positions? Obviously, there have to be some reasons behind this and this is what leads us to form an opinion that there are obstacles that exist, preventing women from occupying higher positions in the same proportion as their number in employment. Such obstacles can widely be termed as barriers. Review of Literature: Numerous studies reveal that despite possessing the necessary qualifications and skills, women are still struggling to break barriers to climb the hierarchy level in their respective organizations. Catalyst, a women’s advocacy group, reported that the most common barriers for women include concerns about their suitability for leadership positions because of stereotyping, exclusion from informal networks of communication, and an absence of effective management training. Other common obstacles include the failure of upper level managers to be accountable for the development and advancement of women, inadequate appraisal and compensation systems, inflexibility in defining work schedules, and the absence of programs that help employees balance work and non-work responsibilities. According to Salma M Al-Lamkithe absence of human resource policies and strategies to promote the recruitment and development of female managers at work was a deterrent to gender diversity. Also there is a need to significantly change the attitudes of senior male managers who do not take women manager careers seriously. A woman’s primary role in the family is as a wife and mother. Many employers feel that these roles will interfere with women’s work productivity. Hence, there is a tendency for them to give priority to men in terms of employment and promotion, even where women have the same qualifications10. Also they found out that majority of women feel there is a lack of networking among businesswomen for exchanging information, discussing issues and seeking advice on common topics. Some of these women have started to form such networks. According to Katlin Omair at almost every level, women managers globally are described as having to deal with blocked mobility, discrimination and stereotypes. Arab societies are still regarded as highly patriarchal with clear gender-role differences and that the women’s primary role in the society is still expected to be limited to domestic activities in the private sphere11. Tracey Rowe and Andy Crafford in their paper mentioned that in investment banking industry women can be impressive and competent, but often remain nameless because of the constraints put on them by the nature of the industry. Women do not have the assistance of supernatural powers to break through their constraints and the barriers they face in the advancement of their careers. The traditional structure of society expects women to take responsibility for a family over the responsibility of a career. The pressure and constraints put on career-orientated women to manage both make it extremely difficult for women to have a successful professional career in the investment banking industry12. As per an article by Saleh al Shaibany, women make up nearly 40 per cent of the total workforce of banks in Oman, and job experts say that they will outnumber men by 2020, a clear indication that Oman's financial services will be dominated by females a decade from now. Out of 9,200 employees currently working in both commercial and specialised banks, 3,680 are women and the figure is rising at between 11 and 14 per cent a year compared with only 7 to 9 per cent for men13. Objectives: i.To study if there is any association between barriers and career advancement of women in the financial sector in Oman. ii. To find out the barriers which are most significant and least significant for career advancement of women in the financial sector in Oman. iii. To find out the factors extracted using PCA and also the variability modelled by the data. Hypothesis: Ho: There is no association between the barriers and career advancement of women in the financial sector in Oman. : There is an association between the barriers and career advancement of women in the financial sector in Oman. Research Methodology Both quantitative and qualitative methods are used for this study, qualitative method provided a proper framework for the study and analysis. Data for the study used both primary as well as secondary data. The primary data has been collected using an instrument which was originally used by Zhong14 in her study, after obtaining her permission. The instrument used for this study is not the entire survey instrument used by Zhong14 but only a part of it which was relevant to this study.The survey instrument used in this study is based on a 5-point Likert Scale in which the values of the different variables were coded as 1 representing not a barrier, 2 as minor barrier, 3 as moderate barrier (neither minor nor major), 4 as less than a major barrier and 5 as a major barrier. Data was analyzed using Statistical Package for Social Sciences (SPSS) version 19. Internal consistency test was conducted on the instrument and the result indicated an overall Cronbach’s Alpha of 0.828 for the instrument used. Out of the 300 potential women using simple random sampling 126 responses were found appropriate to be used for the purpose of analysis. Respondents were selected from various banks and financial institutions in Oman. Techniques like Chi-square test, Tschuprow’s coefficient of association, Factor analysis and Research Journal of Management Sciences ________________________________________________________ ISSN 2319–1171Vol. 2(9), 1-6, September (2013) Res. J. Management Sci.International Science Congress Association 3 descriptive measure (mean) are used for analysis and data has been interpreted accordingly. Results and Discussion Ho: There is no association between the barriers and career advancement of women in the financial sector in Oman. : There is an association between the barriers and career advancement of women in the financial sector in Oman. To find out whether there is any association between the barriers identified and career advancement of women in the financial sector in Oman, Chi-square test was applied the output is shown below and the result follows. Table-1 Chi-Square test Value df Asymp. Sig. (2-sided) Pearson Chi-Square 148.943 a 56 .000 Source: Field Survey Since p-value.001 there is sufficient evidence to reject the null hypothesis and hence we conclude that there is an association between barriers and career advancement of women in the financial sector in Oman. Since there is an association between the barriers and career advancement, we now find the degree of association between them using Tschuprow’s coefficient of association. )1)(1= .43211 Using Tschuprow’s coefficient of association and based on the calculations done 43% of association was found between the barriers and career advancement in the financial sector in Oman. In the above Table 2, representing barriers and their average, 1 represents not a barrier, 2 represents minor barrier, 3 represents moderate barrier (neither minor and nor major), 4 represents less than major barrier and 5 represents a major barrier. To find out the barriers which according to the respondents affected their career advancement the most and the least in the financial sector, average of all the responses was obtained for the different barriers. On the basis of the above table it is clear that the barriers which affected their career advancement the most, in descending order are, child care responsibilities (3.21), conflicts with family responsibilities (3.18) and Job characteristics eg. irregular work hours (3.04). The barriers which according to the respondents least affect their career advancement are sexual harassment (2.51), difficulty in establishing credibility (2.54) and Old-boy network (2.71). Principal Component Analysis was performed to get the result of the third objective of the study. Table-2 Barriers and their average BarrierAverage Difficulty in establishing credibility 15 31 67 7 2 2.54 Conflicts with family responsibilities 6 32 35 37 15 3.18 Job characteristics eg. irregular work hours 14 29 29 41 11 3.04 Lack of equity in pay 16 28 47 22 13 2.90 Lack of equity in training 18 26 36 35 8 2.91 Lack of equity in promotion decisions 13 24 43 32 10 3.01 Old-boy network 13 38 43 22 4 2.71 Sexual harassment 34 28 34 18 9 2.51 Inadequate job knowledge 25 23 40 28 7 2.74 Lack of mentoring 24 20 47 23 9 2.78 Lack of role models 20 30 37 23 9 2.75 Being married 22 27 33 26 12 2.82 Being a single parent 29 29 29 24 14 2.72 Child care responsibilities 11 19 39 33 17 3.21 Lack of support systems at work 12 33 43 22 16 2.97 Source: Field Survey Research Journal of Management Sciences ________________________________________________________ ISSN 2319–1171Vol. 2(9), 1-6, September (2013) Res. J. Management Sci.International Science Congress Association 4 Table-3 Correlation Matrix Correlation Matrix DEC CFR JC LEP LET LEPD OBN SH IJK LM LRM BM BSP CCR LSSW Difficulty in establishing credibility (DEC) 1.000 .317 .401 .448 .443 .414 .263 .063 .242 .118 .132 .111 .205 .155 .334 Conflicts with family responsibilities (CFR) .317 1.000 .328 .169 .215 .226 .110 -.027 .203 .131 .264 .254 .218 .411 .187 Job characteristics eg. irregular work hours (JC) .401 .328 1.000 .429 .397 .374 .257 .095 .255 .187 .194 .113 .260 .307 .281 Lack of equity in pay (LEP) .448 .169 .429 1.000 .742 .665 .590 .081 .363 .346 .238 .077 .038 .108 .362 Lack of Equity in training (LET) .443 .215 .397 .742 1.000 .618 .491 .226 .466 .425 .341 .129 .065 .079 .269 Lack of equity in promotion decisions (LEPD) .414 .226 .374 .665 .618 1.000 .299 .064 .332 .201 .194 .033 -.058 .112 .183 Old-boy network (OBN) .263 .110 .257 .590 .491 .299 1.000 .115 .285 .354 .209 .033 .056 -.021 .165 Sexual harassment (SH) .063 -.027 .095 .081 .226 .064 .115 1.000 .218 .114 .032 .018 .150 .006 .098 Inadequate job knowledge (IJK) .242 .203 .255 .363 .466 .332 .285 .218 1.000 .711 .499 .178 .123 .146 .388 Lack of mentoring (LM) .118 .131 .187 .346 .425 .201 .354 .114 .711 1.000 .593 .166 .048 .061 .410 Lack of role models (LRM) .132 .264 .194 .238 .341 .194 .209 .032 .499 .593 1.000 .210 .079 .188 .303 Being married (BM) .111 .254 .113 .077 .129 .033 .033 .018 .178 .166 .210 1.000 .361 .560 .309 Being a single parent (BSP) .205 .218 .260 .038 .065 -.058 .056 .150 .123 .048 .079 .361 1.000 .438 .357 Child care responsibilities (CCR) .155 .411 .307 .108 .079 .112 -.021 .006 .146 .061 .188 .560 .438 1.000 .347 Lack of support systems at work (LSSW) .334 .187 .281 .362 .269 .183 .165 .098 .388 .410 .303 .309 .357 .347 1.000 Source: Field Survey Based on the correlation matrix we can see that there is a correlation between barriers like lack of equity in training and lack of equity in pay and also lack of equity in pay with promotion decisions also we can see that there is a correlation between inadequate job knowledge and lack of mentoring and between lack of role models and lack of mentoring etc and hence we can proceed for factor analysis. Table-4 KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy .801 Bartlett's Test of Sphericity Approx. Chi-Square 509.435 df 105 Sig. .000 Source: Field Survey The table given above is basically used to test assumptions; the Kaiser-Meyer-Olking (KMO) statistic should be greater than 0.60 and ranges between 0 and 1. The Bartlett's test should be significant (e.g. p .05). KMO is used for checking sampling adequacy and find the correlations and partial correlations. The Bartlett's test evaluates whether or not our correlation matrix is an identity matrix (the diagonal elements should be 1 and off diagonal elements should be 0). From table 3 we can observe that our correlation matrix (of items) is not an identity matrix. Since the off-diagonal values of our correlation matrix are not zeros, therefore the matrix is not an identity matrix. Hence now we can proceed for factor analysis. MSA values for all the variables were found as .859, .819, .900 and so on which is considered as good and also KMO value being .801 which is highly significant further Bartlett’s Test of sphericity has an associated P value of less than .001which is significant and hence we continue and perform a valid factor analysis. We also found that most of the values of communalities are greater than .5. Thus, we can conclude that the amount of variance accounted for by the factor solution for those barriers are significant for eg. Lack of equity in training accounts for 744 variability for the factor. From the above table we can say that 63.323% of variability in the data has been modelled by the extracted factors. Research Journal of Management Sciences ________________________________________________________ ISSN 2319–1171Vol. 2(9), 1-6, September (2013) Res. J. Management Sci.International Science Congress Association 5 Table-5 Total Variance Explained Component Initial Eigen values Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative % 1 4.716 31.439 31.439 4.716 31.439 31.439 3.366 22.438 22.438 2 2.110 14.065 45.504 2.110 14.065 45.504 2.502 16.678 39.116 3 1.564 10.428 55.932 1.564 10.428 55.932 2.484 16.562 55.678 4 1.109 7.391 63.323 1.109 7.391 63.323 1.147 7.645 63.323 5 .852 5.682 69.005 - - - - - - 6 .795 5.298 74.303 - - - - - - 7 .731 4.877 79.179 - - - - - - 8 .625 4.166 83.345 - - - - - - 9 .504 3.358 86.703 - - - - - - 10 .469 3.129 89.832 - - - - - - 11 .464 3.095 92.927 - - - - - - 12 .362 2.415 95.342 - - - - - - 13 .295 1.964 97.306 - - - - - - 14 .224 1.492 98.797 - - - - - - 15 .180 1.203 100.000 - - - - - - Extraction Method: Principal Component Analysis; Source: Field Survey Table-6 Rotated Component Matrix Rotated Component Matrix Component Work Related Issues Family Issues Lack of Support Sexual harassment Work Related Issues - - - - Lack of Equity in Pay .852 - - - Lack of equity in promotion decisions .793 - - - Lack of Equity in training .777 - .350 - Difficulty in establishing credibility .669 - - - Job characteristics eg. irregular work hours .594 .372 - - Old-boy network .579 - - - Family Issues - - - - Child care responsibilities - .830 - - Being a single parent - .721 - .364 Being married - .703 - - Conflicts with family responsibilities - .530 - -.364 Lack of support systems at work - .492 .392 - Lack of Support - - -- - Lack of mentoring - - .893 - Lack of role models - - .778 - Inadequate job knowledge - - .771 - Sexual harassment - - - .840 Extraction Method: Principal Component Analysis; Rotation Method: Varimax with Kaiser Normalization. a Rotation converged in 5 iterations. Source: Field Survey Table presented in previous page i.e. the Rotated Component Matrix Table displays the loadings for each item (variable) on each rotated component, clearly showing which items make up each component. As we can see, the first few questions load heavily on component 1 and since they more or less relate to work they have been labelled as Work Related Issues. Similarly, the next few questions which load on to component 2 relate to family issues and hence labelled as family Issues. The next 3 questions Research Journal of Management Sciences ________________________________________________________ ISSN 2319–1171Vol. 2(9), 1-6, September (2013) Res. J. Management Sci.International Science Congress Association 6 which load on component 3 have been labelled as Lack of Support and the last question loads on the 4th Component has been labelled sexual harassment - same as in the questionnaire. sexual harassment can actually be removed as it does not meet the requirement of a minimum of three items per component that are required for a factor model to be identified. It shows that the initial questionnaire is composed of three basic sub-scales: Work Related Issues, Family Issues and Lack of Support. ConclusionBased on the tests and analyses done on the responses given by women employed in the financial sector in Oman, it is found that there is an association to the extent of 43% between the barriers identified and career advancement of women. The barriers, which according to the respondents affected their career advancement the most and the least in the financial sector was found and it is observed that “Child care responsibilities” affected them the most and “Sexual harassment” affected them the least in their career advancement. Principal Component Analysis extracted four components from the initial questionnaire and since the fourth component extracted did not meet the basic requirement hence it may be ignored from the initial questionnaire. It is also found that 63.323% of variability in the data has been modeled by the four extracted factors. References 1.CIA, World Fact book, Sultanate of Oman https://www.cia.gov/library/publications/the-world- factbook /.../mu.html (2012) 2.Sultanate of Oman, Ministry of Information, Banking Sector www.omaninfo.co.uk/index.php (2012) 3.ILO, Employment Papers www.ilo.org (2011) 4.ILO Department of Statistics-Laborsta laborsta.ilo.org/ 2011) 5.Harthy F. 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