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Seminar: Organizations and Social Networks - Implications for Human Resource Management

People and Contacts

Lectures and tutorials: Dr. Marco Tonellato, Schackstr. 4, Room 004, tonellato@bwl.lmu.de

Logistics

Lectures: Tuesday, 4-5.30pm (s.t.), Room: Kaulbachstr. 45, room 006
Tutorials: Wednesday, 2- 3.30pm (s.t.), Room: Ludwigstr. 28, back building, room III

Course Description and Objectives

One of the most powerful ideas in the social sciences is that individuals are connected to one another through networks of social relations. Research and practice have demonstrated how social networks – not to be confused with social media – are crucial in determining the effectiveness of information flows in organizations, the dynamics of individual careers and internal labor markets, the structure of coordination and collaboration within and across organizational boundaries. This course introduces the conceptual and practical tools that define the field of social network analysis (SNA) and its application to organizations and human resource management (HRM). Some of the main analytical areas discussed include centrality, community detection, brokerage, closure and small worlds. Substantive topics covered include how networks affect behavior, performance, job satisfaction and career prospects of people within organizations. Contemporary network research is unique in that its methodological tools derive directly from practical as well as theoretical concerns. For this reason, class time is allocated equally to methodological and substantive issues, with each substantive topic tied to specific analytical strategies to be conducted in a computer lab. Practical examples and in-depth case studies will be presented, analyzed and discusses in class, in order to unveil how organizations achieve strategic outcomes through the creation, use, and evaluation of social network analysis.

By the end of the course, students are expected to have gained a broader understanding of:

  • How and why networks of relations are relevant for individuals and groups
  • The implication of SNA for HRM and organizational design
  • The difference between formal and informal structure in organizations
  • The impact of network structure on individual and group performance
  • How to collect and plot network data
  • How to derive SNA metrics that inform and help decision making

Teaching Approach

The course involves a mix of lectures, workshops, and interactive examples of analysis of actual and simulated network data. The course will also offer a number of laboratory exercises using various software packages for the analysis of social networks designed to help participants to gain hands-on experience in the visualization, analysis and interpretation of relational data.

Course Outline and Lecture Days

April 25th, 2017: Introduction to SNA: basic concepts and the role of formal and informal structure in organizations (lecture)
April 26th, 2017: Introduction to SNA using UCINET and network data visualization using Net-draw/Gephi (tutorial)
May 2nd, 2017: Network centrality and its relevance for organizations (lecture)
May 3rd, 2017: Computing and mapping network centrality (tutorial)
May 9th, 2017: Brokerage and closure: the impact of structural holes on career advancement (lecture)
May 10th, 2017: Computing and interpreting brokerage and closure metrics (tutorial)
May 16th, 2017: The network structure of groups and teams in organizations (lecture)
May 17th, 2017: Community detection, cliques and the analysis of groups (tutorial)
May 23th, 2017: Small worlds, job search and the strength of weak ties (lecture)
May 24th, 2017: Small world networks, clustering and structural equivalence (tutorial)
June 14th, 2017: Group presentations

The tutorials are based on the preceding lectures. Tutorials are scheduled the day after the theory-based lectures so that students will have the chance to apply what they learned with real data.

Evaluation

Students will be evaluated on the basis of group work, class participation, and individual performance in a written exam.

  • The final exam accounts for 50% of the final grade. It consists of a one hour, closed book test based on the topics discussed in class. The exam will feature a combination of multiple-choice questions, open-ended questions and/or mini-case analysis. The questions re-late equally to the lectures and tutorials; in addition to the slides, mandatory readings and further materials handed out during the classes are also subject of examination. During the class students will receive additional information regarding the exact amount of questions and their relative weighting. Information on where and when the exam will take place will be posted as soon as available.
  • The group presentations account for 30% of the final grade. The day of final presentations is scheduled a few weeks after the end of the class (see course outline for a precise schedule). Group presentations are evaluated at the group level and are based on the discussion of business cases that will be made available during the course of the class. Students are expected to apply concepts and ideas discussed in class to analyze the business case, and to answer to a set of questions provided by the instructor.
  • Class participation accounts for 20% of the final grade. To receive credit for class participation students must show up in class, actively participate in class discussion and hand in exercises during tutorials.

Requirements

Students are requested to enroll for this class by sending an email to the instructor at tonellato@bwl.lmu.de

Reading Material

Recommended book
The class will be mostly based on lecture slides and ad-hoc readings. However, the book that is recommended for this course is: Borgatti, S.P., Everett, M.G., and Johnson, C.J. 2013. Analyzing Social Networks. Sage Publications. When needed, additional readings will be made available by distributing password-protected pdf files, intended for personal use only.

Open online resources
The following freely available online textbook introduces many of the topics that we will be discussing in the course:
Hanneman, Robert A. and Mark Riddle. 2005. Introduction to social network methods. Riverside, CA: University of California, Riverside (published in digital form at: http://faculty.ucr.edu/~hanneman/nettext/

The trial version (90 days) of the main software that we will be using may be downloaded freely from:
Borgatti, S.P., Everett, M.G. and Freeman, L.C. 2002. Ucinet for Windows: Software for Social Network Analysis. Harvard, MA: Analytic Technologies. The software may be downloaded freely from: https://sites.google.com/site/ucinetsoftware/home

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