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A number of scholars have called our attention to the need to consider the social significance of demographic categories when evaluating the association between a team's composition and its performance. Implicit in the call is the idea that the association between a team's composition and its performance is more predictable when the demographic categories that define the team's composition are more significant. How to define the social significance of a demographic category is unclear. One approach is to define the importance of a demographic category in terms of interpersonal attraction. Important demographic categories generate more positive affect between category members. Alternatively, one could define the social significance of a demographic category in the context of task-related processes and activities. A demographic category is significant if it affects the activities that are more likely to be assigned to a team member (i.e., an individual's work-set). I maintain there is much to gain by adopting a role-based approach to the question. An attraction-based approach is a subset of a role-based approach. Moreover, an empirical analysis of the association between demographic categories and job categories would allow us to uncover how categorical people are in their thinking and therefore how socially significant different demographic categories are at work. When combined with a team's demographic composition and the activities that a team must accomplish, the empirical results would move us one step closer to predicting a team's success rate a priori.

This chapter proposes a model of person-situation interactions to explain when individuals react to demographic diversity in their work places. Qualitative research reported here suggests individual identities likely influence reactions to diversity and should be considered in conjunction with traditional situational factors. The model developed from this research looks at interactions between high and low identification with demographic categories and strong and weak situational cues toward such categories to explain when individuals are most likely to respond (or not respond) to diversity. The proposition that motivated reactions to diversity are observable only when both situational and personal factors contribute is advanced.

Every employee embodies manifestations of every demographic that attach to him or her different minority and majority statuses at the same time. As these statuses are often related to organizational hierarchies, employees frequently hold positions of dominance and subordination at the same time. Thus, a given individual’s coping strategies (or coping behavior) in terms of minority stress due to organizational processes of hierarchization, marginalization, and discrimination, are very often a simultaneous coping in terms of more than one demographic. Research on minority stress mostly focuses on single demographics representing only single facets of workforce diversity. By integrating the demographics of age, disability status, nationality, ethnicity, race, sexual orientation, and religion into one framework, the intersectional model proposed in this chapter broadens the perspective on minorities and related minority stress in the workplace. It is shown that coping with minority stress because of one demographic must always be interpreted in relation to the other demographics. The manifestation of one demographic can limit or broaden one’s coping resources for coping with minority stress because of another dimension. Thus, the manifestation of one demographic can determine the coping opportunities and coping behavior one applies to situations because of the minority status of another demographic. This coping behavior can include disclosure decisions about invisible demographics. Therefore, organizational interventions aiming to create a supportive workplace environment and equal opportunities for every employee (e.g., diversity management approaches) should include more demographics instead of focusing only on few.

The popular press often touts workforce demographic diversity as profit enhancing because it may reduce the firm's communication costs with particular segments of customers or yield greater team problem-solving abilities. On the other hand, diversity also may raise communication costs within teams, thereby retarding problem solving and lowering productivity. Unfortunately, there is little empirical research that disentangles the above countervailing effects. Diversity in ability enhances the team productivity if there is significant mutual learning and collaboration within the team, while demographic diversity may harm productivity by making learning and peer pressure less effective and increasing team-member turnover. We evaluate these propositions using a novel panel data from a garment plant that shifted from individual piece rate to group piece rate production over three years. Because we observe individual productivity data, we are able to econometrically distinguish between the impacts of diversity in worker abilities and demographic diversity. Teams with more heterogeneous worker abilities are more productive at the plant. Holding the distribution of team ability constant, teams composed of only one ethnicity (Hispanic workers in our case) are more productive, but this finding does not hold for marginal changes in team composition. We find little evidence that workers prefer to be segregated; demographically diverse teams are no more likely to dissolve, holding team productivity (and hence pay) constant, than homogeneous teams.

South Africa is in the last stage of the first demographic transition (FDT) – yet already depicts aspects of the second transition. The last stage of the FDT is characterized by lower levels of fertility closer to or at the replacement level of the average of 2.1 children per woman, and improvements in mortality displayed by declining infant and childhood mortality leading to increasing life expectancy at birth. The second demographic transition (SDT) is driven by lifestyle changes that are determinants of demographic patterns. Such lifestyle changes are declining marriage rates, increasing attention on human development, and thus changing family formation patterns. South Africa’s youth are at the centre of this transition. The population census of 2011 shows an age structure of South Africa that is characterized by a larger proportion of 20-35-year-olds. This resulted from a long period of declining fertility and to some extent improvements in mortality at all ages. This age structure, with adequate investments - is expected to yield a period of economic growth resulting from a reduced dependency ratio. However, improved health care, investments in human development, and higher employment opportunities are required to harness the benefit. This chapter aims to explore the national and provincial preparedness of South African youth to contribute to economic growth of the country. In particular, the chapter will focus on demographic factors such as sex ratio; youth mortality and morbidity; and youth fertility levels as these factors are highly correlated with human development.

Citizens are substantial stakeholders in every e-government system, thus their willingness to use and ability to access the system are critical. Unequal access and information and communication technology usage, which is known as digital divide, however has been identified as one of the major obstacles to the implementation of e-government system. As digital divide inhibits citizen’s acceptance to e-government, it should be overcome despite the lack of deep theoretical understanding on this issue. This research aimed to investigate the digital divide and its direct impact on e-government system success of local governments in Indonesia as well as indirect impact through the mediation role of trust. In order to get a comprehensive understanding of digital divide, this study introduced a new type of digital divide, the innovativeness divide.

The research problems were approached by applying two-stage sequential mixed method research approach comprising of both qualitative and quantitative studies. In the first phase, an initial research model was proposed based on a literature review. Semi-structured interview with 12 users of e-government systems was then conducted to explore and enhance this initial research model. Data collected in this phase were analyzed with a two-stage content analysis approach and the initial model was then amended based on the findings. As a result, a comprehensive research model with 16 hypotheses was proposed for examination in the second phase.

In the second phase, quantitative method was applied. A questionnaire was developed based on findings in the first phase. A pilot study was conducted to refine the questionnaire, which was then distributed in a national survey resulting in 237 useable responses. Data collected in this phase were analyzed using Partial Least Square based Structural Equation Modeling.

The results of quantitative analysis confirmed 13 hypotheses. All direct influences of the variables of digital divide on e-government system success were supported. The mediating effects of trust in e-government in the relationship between capability divide and e-government system success as well as in the relationship between innovativeness divide and e-government system success were supported, but was rejected in the relationship between access divide and e-government system success. Furthermore, the results supported the moderating effects of demographic variables of age, residential place, and education.

This research has both theoretical and practical contributions. The study contributes to the developments of literature on digital divide and e-government by providing a more comprehensive framework, and also to the implementation of e-government by local governments and the improvement of e-government Readiness Index of Indonesia.