Diversity and Demographic Characteristics
By: Tommy • Research Paper • 1,659 Words • February 18, 2010 • 1,183 Views
Join now to read essay Diversity and Demographic Characteristics
Diversity and Demographic Characteristics
MGT/331 Organizational Behavior
October 31, 2005
Diversity and Demographic Characteristics
Throughout this paper I will describe and analyze to some degree, diversity, and demographic characteristics with an emphasis on the following behaviors:
· Gender
· Age, as it relates to the use of technology
· Differences in skills and abilities
· Personality traits
Employee demographics, as stated by Chuang, Joshi, & Liao, (2004) “in terms of tenure, age, gender, and ethnicity has been found to predict turnover, commitment and integration, relationships with peers, altruism, organization based self-esteem and task performance.” What does this mean one asks? Well, let’s discover by starting with Gender.
When considering the behavior of gender according to Klenke, (2003) “Strategic decision making is affected by power which in turn serves as a major foundation of organizational politics. To deal with many situations effective conflict management is needed. How conflict is handled affects trust between the members of the organization. This process, and the decisions it involves, are affected by gender differences.” Therefore, one can see the characteristic of different gender plays a role within the work environment. Let us take a closer look into gender characteristics.
Klenke (2003) continues with, “Sex role congruence means that jobs are consistent with male/female stereotyping of occupations. For example, until recently we had policeman because it was perceived as a man's work. Now we have police officers. Certain professions - engineering, aeronautics, are still very much male bastions because the SKAs (skills, knowledge and abilities) required for these jobs such as mathematical fluency or spatial abilities are competencies that women have traditionally been believed to lack.”
“For men the path to power and leadership is straightforward: join the usual clubs, board of directors, civic associations, visible charities or national leadership groups; then leverage ties with financiers, power brokers, ranking politicians, competitor CEOs, opinion leaders, or potential venture partners to establish a power base. For women, on the other hand, access to power and executive leadership is less clearly defined and more limited.”
“Research on women in management suggests that women show a greater concern for interpersonal relationships and a reliance on the rules of fairness in the exercise of power whereas men's power orientation is toward maximizing individual gains.” Imagine that, an upper management relying on rules of fairness.
“Although considerable progress has been made over the past two decades in the advancement of women in organizations, in the executive suite women are still vastly underrepresented on top management team and corporate boards. “ Maybe some of this is due to Harpaz and Snir’s (Mar 2003) findings; “Married women worked fewer hours per week than unmarried women, while married men worked more hours per week than unmarried men.”
Do these findings mean that a gender divers workforce is a healthy workforce? Or is it simply that society is growing up and embracing a realistic view of the world? Let’s take a look at age as it relates to the use of technology in the workforce.
Technology has grown by leaps and bounds over the past few decades. The paper trails, are now email trails. As a young man entering the workforce, I quickly became aware that some of the more senior staff had not necessarily embraced email or computers in general. Believe it or not, there were employees who did not even read their email; their secretaries read it and provided the important details. Why is this? Let us look into Morris and Venkatesh ‘s findings.
Morris and Venkatesh conducted a study in which they introduced a new software system over a five month period to 118 employees, all varying ages. “The younger workers' technology usage decisions were more strongly influenced by attitude toward using the technology. In contrast, older workers were more strongly influenced by subjective norm and perceived behavioral control, although the effect of subjective norm diminished over time. These findings were robust, even after controlling for key confounding variables identified in prior organizational behavior research (i.e., income, occupation, and education levels).” (Morris and Venkatesh, 2000)
Morris and Venkatesh, (2000) continued with, “Specifically, in the short term, most factors outlined