Does online embeddedness influence gender inequality at workplaces?

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Does online embeddedness influence

gender inequality at workplaces?

Master thesis, MSc. Human Resource Management

University of Groningen, Faculty of Economics and Business

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Abstract

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Introduction

Many people believe that gender discrimination is an issue of the past and they do not think that it still warrants attention. However, despite all attempts that have been made, gender discrimination against female employees over promotion, permeability, power and pay still is a subject in today's world. Gender discrimination is a common problem in developing countries where legislations neglect women’s education, restrict their movements or intensify physical gender stereotypes (e.g. clothing; Seager, 2003). Moreover, even in developed countries where men and women are equal according to the law, women can still face discrimination, primarily at work. This is referred to as the glass ceiling when climbing the corporate ladder (McDowell et al., 1999; Blackaby, Booth, & Frank, 2005). The glass ceiling is “the unseen, yet unreachable barrier that keeps minorities and women from rising to the upper rungs of the corporate ladder, regardless of their qualifications or achievements.” (Federal Glass Ceiling Commission, 1995) Although there is a growing trend that women in western societies have more access to leadership positions, on average, they are still mostly concentrated in lower levels of management (Eagly & Sczesny, 2009).

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possibility of online networking for work. Therefore it is suggested that men and women’s social networks, or a so called social embeddedness, should be considered in studies on gender related phenomena in the work place. (Granovetter, 1985)

The objective of this study is to examine the consequences of online and offline social networking for some aspects of gender inequality at work places. I aim to show that women workers who are embedded in dense and diverse social networks benefit from less inequality compared to those who are not embedded in such networks (Moody & White, 2003), particularly when they are involved in online social networks where power among the participants is relatively equally distributed. In the introduction section, I will first provide an overview of the literature on gender inequality and discuss the effects of off-line/online social embeddedness for people’s career. I will then continue with an explanation of how this social embeddedness may influence gender inequality over promotion, permeability, power and pay and I will present my hypotheses.

Gender discrimination in organizations

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promotion is also documented in verity of contexts (Olson & Becker, 1983; Cobb-Clark & Dunlop, 1999; McDowell et al. 1999, Hersch & Viscusi, 1996). Despite increasing attempts to eliminate these kinds of gender discrimination, still keeping women from the top management levels of organizations -which is called ‘glass ceiling effect’-(For example see: a study on promotion decisions for U.S. federal government Senior Executive Service positions in a cabinet-level department, Powell & Butterfield, 1994). Moreover, sometimes matching process at the point of hire differ for men and women and women “are allocated to occupations and establishments that pay lower wages” (Peterson & Morgan, 1995: p. 330). This process also results in gender wage gap which is crucial and widespread at workplaces (for example see: a study on gender wage gap in the US, Peterson & Morgan, 1995, and in Sweden , Albrecht, Bjorklund, & Vroman, 2003, for a review of wage difference between male and females see: Weichselbaumer & Winter-Ebmer, 2005).

Factors influencing sex discrimination

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Importantly though, there are also organizational factors that contribute to gender discrimination at workplaces. For example, organizational structures, such as compositional sex differences, and the distribution of power, influences gender discrimination (Stainback, Ratliff, & Roscigno, 2011). The experience of sex discrimination is reduced for both women and men when they are part of the numerical majority of their work group (Stainback, Ratliff, & Roscigno, 2011: 1185). Other organizational and structural conditions such as size and minority management also have been demonstrated that affect workers discrimination (Hirsh & Kornrich, 2008). Yet, relevant to my research question, most forms of sex discrimination I discussed (career permeability, power, promotion and sexual harassment) are also affected by network embeddedness.

Social embededness in informal social networks

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position. As a result, many prefer to spend their limited resources and energy on improving their own condition by individual actions rather collective actions.

Although formal social networks primarily help to obtain collective group goals, more informal types of social networks, such as online forums, are likely to influence individuals’ positions. This reasoning is supported by Granovetter (1973), who already argued that one’s personal network structure should affect individuals’ job opportunities for obtaining higher positions. Indeed, in a high-tech industry, Podolny and Baron (1997) showed that informal personal social networks (such as friendship networks at workplaces) positively affect organizational upward promotion of workers. This means that even workers do not participate in formal union social networks, their promotion and wages are still positively influenced by other networks which they are embedded in. Putnam (1995; 1993) even demonstrates how memberships to social clubs and other social groupings increase individuals’ work possibilities. Taken together, several studies affirm the positive effect of social capital on people’s job opportunities. All in all, evidences show formal as well as informal, personal social networks matter in promotion and wages of workers.

In line with the idea of ‘social capital’ (Putnam, 2000), I will investigate whether the degree to which women and men are integrated in informal work related social networks or “embeddedness” influences their pay and promotion. Informal social networks that exist at their work place are different from the informal personal networks examined in previous research, as they are specifically set up to aid employees, in an informal way, at their workplace and their job.

Social embededness and gender discrimination

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workers, it is not yet clear whether embeddedness in social networks reduces inequality in workplaces. On the one hand, McGuire (2002) stated that women received less instrumental help through their informal networks than men in workplaces. Yet, on the other hand, Elliott and Smith (2004) showed that black-women could rely more on instrumental help of social networks than white-men. These findings demonstrate the needs for more investigation on the relation between embeddedness and gender inequality.

Furthermore, at individual level, the networks where workers are embedded and workers’ social capitals affects workers inequality (Lin, 2000). Workers can get information and support through their ties in their networks and these supports and information enhance their situation in workplaces. However, according to the homophily principle (McPherson, Smith-Lovin, & James, 2001), individuals rather make contacts with similar than dissimilar people. This would imply that most networks at work are relatively homogenous in terms of gender, and thus segregated in this respect (McPherson, Smith-Lovin, & James, 2001) As there is inequality in social capital of women and men (Lin, 2000), men are probably part of larger networks that enjoy the benefits in associations with other (Lin, 2000), whereas women connected to other women at work are part of smaller, disadvantaged networks that cannot get access to higher positions. As Lin (2000, p. 788) puts it: “Since their associations and networks also tend to be homogeneous, there is likewise a network closure and reproduction of resource disadvantages among females”. I therefore expect that social embeddedness in relatively more heterogonous networks can reduce inequality in social capital and consequently many aspects of gender inequality at workplaces. This leads me to introduce the role of more informal, online social networks in inequality at workplaces, who are often more diverse in nature.

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of individuals on multiple interpersonal domains, not just objective outcomes as their wage. There are two important reasons why it can be expected that online social networks may particularly have a negative influence on the occurrence of gender discrimination at work. First, according to DiMicco et al. (2008) workers’ motivations for internal social networking are: “connecting on a personal level with coworkers, advancing their career with the company, and campaigning for the projects.” For instance, the intensive use of Facebook among students is positively correlated with social bonding and the maintenance of social capital (Ellison, Steinfield, & Lampe, 2007; Valenzuela, Park, & Kee, 2009). Social networking websites, particularly Facebook and LinkedIn, are considerably used by workers too (Skeels & Grudin, 2009). The content of Behave –a social network for employees- shows that workers share lists of their practice areas, photos of important conference they attend, and their past projects in order to their personal advancement career.

Gender stereotypes are particularly salient when people have minimal information about the other to rely on, thus, when online social networks provide more information, and enable people to individualize, women stereotyping should be decreased, such that people rely on their clearly visible capabilities and characters rather than on more group-based stereotypes.

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power differences among men and women. As such, workplace related online social networking by women may compensate their lack of access to important organizational contacts- which is a major factor of so called glass ceiling. As a result, it is expected that online social networks open a new opportunity for women to bond social capital and become able to obtain higher positions.

Hypotheses

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Method

Sample, Procedure and Participants

The data was collected through an online field questionnaire amongst male and female employees working in different organizations. Participants were randomly approached, yielding a sufficient amount of employees from a variety of organizations from diverse countries (Italy, US, The Netherlands, Iran, Australia, Turkey, Bulgaria) with different degrees of social embeddedness. There were no eligibility criteria for respondents to fill in the survey with respect to their age, gender, profession or occupation. The survey did select participants on the basis of employment – respondents worked for small to medium sized companies (10 – 250 employees) with average revenues between 2 million Euros and 50 million Euros per year.

Each respondent received a personal code to enter the online survey, assuring the high confidentiality of their answers. The questionnaire was conducted in English and of the 220 employees who were asked to participate in this study, 166 responded. This resulted in an adequate response rate of 75 %. In total, 101 (61.6%) was male and 61 (37.2%) was female. The age of the participants ranged from 18 to 60 years old, with an average of 42 years (SD 11.07 years). With respect to their educational level, 42 (25.6%) had no university degree, 66 (42.2%) had a Bachelor degree and 56 (34.1%) held a graduate degree.

Measures

Most constructs in the survey were scaled on 5-points or 7-points Likert-type scales with the anchors “strongly disagree” to “strongly agree.

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Employees'gender. Gender of participant will be measured by one item asking about

the gender of the participants: "How would you describe your gender?” “Male/female”.

Online social embededness: The moderator, the degree of social embeddedness of

each worker, was measured by the number of online networks they were member of and by the intensity with these networks were used for professional purposes. For this purpose, I developed two questions: "To what extent do you use social networks like Facebook, LinkedIn and Twitter for professional purposes?" and "To what extent do you use on-line social networking websites for getting work information?” for determining the validity and reliability of the questionnaire, since there were no gold standard for this attribute, construct validity as well as content validity and Cronbach’s Alpha were conducted. Cronbach’s α for online embeddedness was 0.68.

Dependent Measures

Promotion. Promotion was measured with a three-item scale adapted by

Nederveen-Pietersen, Rink, Ryan & Stoker (2010); "I find it easy to get ahead", "I see opportunities in the near future for a promotion to an interesting position" and "There are more than enough opportunities for personal development". Cronbach’s α of these 3 items was .74.

Permeability. I measured permeability with three items from Deborah & Terry

(2006); ' It is easy for me to gain access to interesting projects at work'', I gain access to the necessary means for projects (e.g. finances, personnel etc.) without any projects'' and ''Important social networks are well accessible for me''. Cronbach’s α for this scale was 0.73.

Power. To measure whether the respondents had any power at the work place I used

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your own level of seniority within the organization?” (1 = very junior, 2= Junior, 3= Medior, 4 = Senior, Very Senior). Cronbach’s α of these 2 questions was .62.

Pay. To measure the pay, I developed a 6 item question and asked them to indicate

their annual salary level: What is your salary (annual income)? (ranges from 1= less than 20000 $ to 6= 100000$).

Control variables

Other categorical characteristics of the respondents, such as their age, education and, ethnicity/race, and job characteristics, such as their work sector, were measured as control variables as they are reported to correlate with gender discrimination (Ro & Kyung-Hee, 2009).

Results

Descriptive: Correlation analysis

Table 1 in the Appendix displays the means, the standard deviations (SD), and the Pearson correlations of the variables outlined in the previous section. The results show that online embeddedness was positively correlated with promotion (r = .32, p < .01), permeability

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Hypothesis testing

I performed several linear regression analyses to test my hypotheses. I standardized all predictor variables, and computed interaction effects by multiplying the respective standardized predictor variables. In separate analyses, I regressed, promotion, permeability, power and pay on my predictors. In the first step, the control variables age, education, and ethnicity were added. Additionally in the second step, to measure the effects of the moderator, the standardized form of independent variable and the moderator were put in, finally the interaction effect of the standardized gender and online embeddedness were added.

Promotion.

Hypothesis 1 predicted that online embededdness has positive effect on the relationship between gender and promotion of men and women. Contrast to the hypothesis, there was no significant interaction effect of the product of gender and online ambeddedness and promotion. The analysis only revealed a main effect of online embeddedness (B=.46, p < .01). Interestingly, I also found a significant and negative effect of education on promotion (B= -.25, p = .00), which state that, education of the respondents negatively related to their promotion at work.

Permeability

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Power

Hypothesis 3 suggests that online embeddedness moderates the relationship between gender and power. Table 2 demonstrates a significant and negative interaction effect of gender and online embeddedness on the power of men and women (B = -.12, p < .05). Importantly though, the simple slope shows a negative effect of online embeddedness on power for women and a positive effect for men. Furthermore, I also detected a significant and positive effect of age (B = .22, p < .01) and ethnicity (B = .27, p < .05) on power. It states that employees’ age and ethnicity influence their amount of power.

Pay.

Hypothesis 4 suggests that online embeddedness moderates the relationship between gender and pay. Table2 in appendix I demonstrates a non-significant relationship of interaction effect of gender and online embeddedness on pay (B = .88, p = n.s). There was only a main effect for online embeddedness on pay (B = .88, p < .01).

Discussion

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Returning to my original research question, I can state that female employees’ permeability at work is contingent on their degree of online embeddedness, such that women employees with higher online embeddedness, obtain almost equal level of permeability as male employees. In other words, employees’ online embeddedness can be considered as a vehicle for improving their permeability within organizations.

I hypothesized that the higher online embeddedness women achieve, the more likely it would be that women would obtain (1) promotion (2) permeability (3) power and (4) pay. I found no support for hypothesis one and four which predicted that promotion and pay would increase by more employees’ online embeddedness.

Hypothesis 2 was supported and the findings revealed that women have almost equal level of permeability as men with higher level of online social embeddedness. I discuss one possible explanation for this. Women employees with higher participation in social online networks, such as Facebook, LinkedIn or Academia, possess greater amount of social capital refers to the resources achieved through the relationships among people (Coleman, 1988). Since women and men utilize the available networks in different ways (Heald, 1983), it is possible that men in compare to women make weaker ties and therefore less permeability than what women do under higher online embeddedness circumstances.

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women are not suitable for leadership. This makes more difficult for a woman as a leader to change the encoding their behavior by subordinates (Scott & Brown, 2006). It may reduce effectiveness of women’s leadership. As a consequence, online social networking of women decreases their power in comparison with men.

In sum, the underline reason of the effect of online embeddedness on permeability and power and not on promotion and pay could be the nature of permeability and power that are subjective and self-experience while promotion and pay are more objective.

Limitations and suggestions for further research

One of the limitations of this study is that in different countries, employees with the same position have different incomes. Moreover, the minimum salary, particularly in developing countries, differs significantly. Since the countries of participants in this study varied broadly, it is difficult to calculate the exact equivalent amount of income related to each country. This might be particularly problematic for success of this research. I would therefore suggest for further research to get information from companies located in one country or from homogenous countries i.e. from some Western Europe country organizations or merely from companies located in the U.S.

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carrier enhancement are difficult to interpret association with correlational and survey methodology, it is useful to use longitudinal and experimental designs.

Another possible limitation of this study could be the questionnaire of online social embeddedness. Questions for measuring the degree of online embeddedness were made, tested and validated for only this research. Future research should first test if this questionnaire can be applied for other studies or they have to modify or change it.

In this study, I suggested that online embeddedness influences promotion, permeability, power and pay of the employees which, according to Kram (1985), are the psychological and career advancement functions of social networks. However, networks also have an identity function for employees (McCarthy, 2004). This function “provides women with a sense of belonging and a shared identity as professional women” (Hersby, Ryan & Jetten, 2009: 426).

Future research concerning organizational development, should examine the impact of identity function of online networks on employees. As a hypothesis they can explore whether online social embeddedness provides employees with the sense of belonging and community which in turn results in job satisfaction and commitment (Haslam, 2004).

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Practical Implication

The findings of this study imply that for developing equal permeability for men and women in organizations, it is helpful to enhance employees’ online social embeddedness. These findings are likely to be used in business sphere particular in HR sectors in order to help HR managers to provide online social network opportunities for the employees and allow them to have access to them. For example, in developing countries which gender discrimination is more problematic, NGOs concerning women rights, for the purpose of decreasing inequality in corresponding permeability and power at work places, can help companies to create online communities, encourage and teach women to participate in online networks. The higher the degree of social embeddedness employee obtain, the more the effective network assistance they can achieves (Elliott & Smith, 2004). Moreover, since women more often work part-time than men (Tijdens, 2002), they need to be more encouraged to bound relationship by using online social networking.

Conclusion

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APPENDIX 1

Table 1

Means, standard deviations and correlations of the variables

M SD 1 2 3 4 5 6 7 8 1. Gender 3.40 0.52 2. Online embeddedness 2.29 0.77 –0.02 3. Promotion 4.70 1.26 –0.11 0.39** 4. Permeability 4.82 1.17 –0.04 0.40** 0.65** 5. Power 45.9 0.96 –0.09 0.32** 0.28** 0.33** 6. Pay 2.12 1.33 –0.45 –0.01 0.12 0.16* 0.19* 7. Age 2.70 1.00 0.05 –0.13 –0.14 0.03 –0.06 0.14 8. Education 4.81 1.28 –0.11 –0.15 -0.23** –0.03 0.02 0.07 0.05 9. Ethnicity 1.70 0.46 –0.09 –0.08 0.09 0.19* 0.10 –0.02 0.16* 0.08

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Table 2:

Results of regression analysis for model 1, 2, and 3

Model 1 Model 2 Model 3

dependent variable: permeability

Beta t Sig. Beta t Sig. Beta t Sig.

(Constant) 8.066 .000 7.696 .000 7.859 .000 Age -.003 -.043 .966 .043 .583 .561 .042 .576 .565 Education -.032 -.410 .682 .021 .291 .771 .013 .178 .859 Ethnicity .194 2.427 .016 .211 2.882 .005 .210 2.888 .004 Gender -.016 -.225 .822 -.022 -.305 .761 Online embeddedness .420 5.748 .000 .410 5.656 .000 Int.Gender*online embeddedness .141 1.971 .051

dependent variable: Promotion

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Int.Gender*online embeddedness

.099 1.392 .166

dependent variable: power

(Constant) 4.858 .000 4.302 .000 4.213 .000 Age .226 2.929 .004 .274 3.751 .000 .278 3.836 .000 Education -.091 -1.186 .237 -.052 -.712 .478 -.043 -.591 .556 Ethnicity .147 1.898 .059 .155 2.122 .035 .156 2.162 .032 Gender -.071 -.987 .325 -.066 -.924 .357 Online embeddedness .343 4.706 .000 .351 4.864 .000 Int.Gender*online embeddedness -.145 -2.047 .042

dependent variable: Pay

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FIGURE 2

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FIGURE 3

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FIGURE 4

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FIGURE 5

Does online embeddedness influence gender inequality at workplaces?