The purpose of my project is to identify ways in which differing leadership styles effect group dynamics and performance within an organization using SNA. By using validated measures from the Job Satisfaction Survey and the Multifactor Leadership Questionnaire in conjunction with specified questions to understand team member dynamics I plan to have a team self-evaluate their own performance while also assessing their leadership. The team that I will be collecting data from consists of approximately 20 individuals. The organization which is being studied has a high turnover environment (1 year term of service) in which team cohesion is essential to ensure accomplishment of organizational goals. The network type that I will be studying is egocentric in nature. Egocentric network are those where focus is placed on specific actors within the network (egos) and the remaining actors are measured in relation to this ego (Carrasco et. al., 2006.). The nodes in this network would be each member of the department that chooses to participate in the study. The ego (and or egos) will be those that respondents have identified as being influential within the network (natural leaders). A name generator will be used to identify these individuals by asking questions such as, who would you go to for advice, who comes to you for advice, etc.

Ivan Miloloza explored the presence of different leadership styles found within corporations of varying sizes and phases of development (2018). In this study three theories of leadership styles were discussed to include authoritarian (task-oriented leadership style), democratic (people-oriented leadership style), and laissez faire (subordinate driven leadership) (Miloloza, 2018). The researcher used a Leadership Styles Questionnaire from the book Introduction to Leadership by P.G. Northouse to determine the level of usage of different leadership styles within his tested organizations (Miloloza, 2018). The measures that he used seem as though they would be beneficial as part of my own survey to identify and describe attributes of nodes/edges within my targeted network.

In contrast, Fiaz et. al research was focused primarily on finding the most pragmatic leadership style and its potential impact on employees’ motivation (2017). These researchers also used autocratic, democratic, and laissez-faire leadership styles as their tested variables, with employee motivation as the dependent variable (Fiaz et al, 2017). Fiaz et al. collected data through a survey questionnaire, based on the closed-ended Multifactor Leadership Questionnaire (MLQ). There sample comprised of 110 senior level and middle level managers working at a public organization. My own data sample will be on a much small scale however I believe that it would be advantageous for me adapt measure from the MLQ in my own survey design.

Researchers Tao et al. provide further perspective on the topic of leadership examining how leadership style affects the relationship between new employee intention to leave (NEIL) and their consequent work performance (2017). Tao et al. compared the moderating effects of abusive and ethical leadership styles on the relationship between NEIL and the employees’ level of performance in the organization. The researchers collected survey data from responses from a sample of 355 leader-employee dyads, with 61 leaders supervising the groups of employees. To reduce common method variance, they collected data from both group leaders and employees. The new employees responded to items to assess their intention of leaving the organization and their perception of their group leader’s leadership style. In the leaders’ survey, each leader was asked to respond to items about himself/herself (e.g., leadership style). It may be beneficial for me to develop two different sets of measures, one for leaders and one for subordinates, this I believe would allow for opportunity of the collection of more reliable node/edge attributes.

There is much literature on leadership dynamics, organizational culture and performance, this network is unique in that it provides insight into the importance of said dynamics in a network that is unstable in nature. The studied network is constantly in flux with frequent changes in leadership and team members. This increases the importance of cohesion within the organization to enable those within in it to accomplish their tasks appropriately. The use of social network analysis will allow for the better understanding of how leadership dynamics influence performance within this organization while also identify key members.

Carrasco et. al. 2006. “Collecting Social Network Data to Study Social Activity-Travel
Behaviour: An Egocentric Approach.”

Fiaz, M., Qin Su, Ikram, A., & Saqib, A. (2017). Leadership Styles and Employees’
Motivation: Perspective from an Emerging Economy. Journal of Developing Areas,
51(4), 143–156. Retrieved from http://proxy.library.vcu.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&AuthType=ip,url,cookie,uid&db=a9h&AN=123825695&site=ehost-live&scope=site

JUN TAO, WANXING JIANG, CHANG LIU, XIN YANG, WEIGUO ZHANG, &
HAOMIN ZHANG. (2017). New Employee Intention to Leave and Consequent Work Performance: Does Leadership Style Matter? Social Behavior & Personality: An International Journal, 45(10), 1707–1721. https://doi-org.proxy.library.vcu.edu/10.2224/sbp.6405

Miloloža, I. (2018). Analysis of the Leadership Style in Relation to the Characteristics of
Croatian Enterprises. Interdisciplinary Description of Complex Systems, 16(2), 249–
264. https://doi-org.proxy.library.vcu.edu/10.7906/indecs.16.2.5