For around
three years now, I have a friend who has been
working as a sales promoter for Zara Fashions. His workstation is a retail
store situated in the heart of New York City, adjacent to Broadway Street. The
retail store has employed 23 employees from diverse racial backgrounds and
receives close to 500,000 customers in a year[1].
The greatest
challenge for the organization is the social differences existing between
employees and even the management. The institution has been at the center of
racial discrimination controversies for a long time. Reports have emerged in
the past implicating the company with serious allegations of racial
discrimination. When black customers come to shop, employees follow them around
until they finish shopping and leave the stores because the management views
them as potential thieves. Furthermore, the administration gives harsh
treatment and inequitable employment terms to black employees compared to the
whites[2].
The goal of
this paper is to use SNA to identify the people the victims of racial
discrimination by Zara and question them to establish the authenticity of the
allegation. I will need the following data to achieve this goal: names of the
employees or customers who suffered from racial discrimination, circumstances
that surrounded their victimization, the date, and place where the events
happened.
With this
information, I will measure the networks of the affected people and the time of
the events to ensure that the issues under discussion are the correct ones. I
will also evaluate events that surrounded the allegations to establish if it
was really a case of discrimination. I will use the data to do a centrality
analysis and develop the correct networks.
At this level,
SNA will help me in achieving two things: identifying the victims and
diagnosing the problem. The nodes in the network will be the employees,
customers, and the administrators. The networks will be the relationship
between the employees and administrators or between the customers, and the
organization. The nodes will not be connected if employees and managers do not
interact frequently, implying a poor interpersonal relationship[3].
References
Gajanan,
Mahita. “Zara Accused of Creating Culture of Customer Discrimination in New
Report,” June 22, 2015. http://www.theguardian.com/us-news/2015/jun/22/zara-reports-culture-of-favoritism-based-on-race.
Scott, John. Social
Network Analysis. London: SAGE, 2012.
Zara. “ZARA,”
May 14, 2016.
http://www.zara.com/us/en/info/company/our-mission-statement-c18001.html#utm_referrer=http%3A%2F%2Fwww.zara.com%2F%3Fgo%3Dhttp%253A%2F%2Fwww.zara.com%2Fshare%2Finfo%2Fcompany%2Four-mission-statement-c18001.html.
[1] Zara,
“ZARA,” 1.
[2] Gajanan,
“The Guardian,” 1.
[3] Scott, Social
Network Analysis, 78.
1 comment:
A powerful idea, but I'm not sure how you plan to implement it. How do you plan "to use SNA to identify the people the victims of racial discrimination?" You say you will already know who they are, so this is confusing. You're on the right track when you say that the networks will be the relationships between the employees, but what kind of relationships? You also say that you'll "measure the networks of the affected people," but you don't say which SNA measures you'll use, except to say that you'll use centrality measures to develop the "correct networks," yet you don't tell us what you mean by correct.
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