Social Network Theory Quiz

Lecture 1: Exploring the Field

• Setting the stage: Draw your ego-network (you, family, 5 closest friends). Examine relationships (e.g., Person A knows Person B).
• Rationale: Performance feedback is crucial, as shown in Greve (1998) US Radio broadcasting industry. Factors like peer performance and historical aspiration affect performance.
• Course introduction: Students gain knowledge of inter-organizational concepts and theories. Learning includes quantitative/qualitative measurements related to networks and relational theories. Also includes analyzing network data via R, comparing inter-organizational theories, and formulating policies based on empirical results. This course also covers English communication abilities applicable to the theoretical and empirical aspects.

Lecture 2: Social Network Analysis

• What is a network?: Networks are patterns of interaction. Roger Brown described patterns in insect colonies and social structures.
• Case example: Safety Houses, crime prevention program with social service partners; operational goal: joint treatment, societal goal: reduce recidivism/crime.
• History of social network analysis: Simmel, the basis of social theory; Moreno and Jennings’ sociometric approach; Roethlisberger, Mayo, and others’ use of networks in HR; Computerized analysis becoming more common in the 1970s; a well-established academic field today.

Lecture 3: Social Capital

• What is social capital?: An advantage created by an actor's advantageous connections. Social capital helps accomplish goals by linking individuals.
• Ego network: A network of relationships centered around oneself. IORs (inter-organizational relationships) and networks are part of this.
• Closure/Brokerage: concepts that contribute to the effectiveness of social structures.

Lecture 4: Network Primitives

• Network primitives: Concepts like nodes, ties (connections), and structure are essential. Analyzing change in uncertainty within a network is possible due to shifts in ties and connections across actors.
• Causes and Consequences of Change in Tie Relations: Networks fluctuate based on changes in environment/resources.

Lecture 5: Network Innovation

• Innovation policy and the role of collaboration: Policies and norms influence the structure of networks and innovation outcomes.
• Small world structure: Analysis of interconnectedness in network structures, relationships between collaborators, and what creates potential for innovation is important.
• Positioning Manna (2019): A framework to understand the relationships between individuals, dyads, subnetworks, and overall networks, to describe and analyze the formation of new consortia and repeated collaborative ties within these units.

Lecture 6: Management and Effectiveness of Networks I

• Network effectiveness: Achieving positive outcomes not attainable via individual actions. Various factors (structural/contextual) are involved in effectiveness.
• Evaluation criteria: Important factors include stakeholders, understanding organizational goals, and using broad and aggregate indicators to evaluate.

Lecture 7: Management and Effectiveness of Networks II

• Cross sector partnerships (CSPs): Intensive, long-term collaborations involving organizations in different sectors (business, government, civil society) for social or environmental problem solving.
• CSP Challenges: Examples such as issues of coordinating/ managing various time constraints and power imbalances within the collaboration.

Other Lectures:

• Lecture 8(possible): This section covers other relevant topics including but not limited to, co-creation paradigm, conceptual frameworks, and research approaches, including quantitative and qualitative elements, used to analyze cases/results.
• Cases (throughout): The presentations also include specific industry cases (e.g., Building & Construction, Safety Houses, Garment, etc.). Analyzing these specific cases adds contextual, real-world examples and considerations for network analysis.
• Methodological details (throughout): The lectures introduce specific research methodologies in practice, including surveys, interviews, archival data, and experiments, for studying and analyzing relational data.
• Paradoxes within networks (throughout): Understanding and addressing conflicting or contradictory aspects of relationships and strategies within collaborative networks.
• Theoretical frameworks/models (throughout): Introduction of theoretical frameworks and models (e.g., Social Capital, Closure, Brokerage, Network Effectiveness, etc.) are key for conceptual understandings.

Test your knowledge on the key concepts of social network theory, including centrality measures, cohesive subgroups, and the roles of networks in governance. This quiz covers essential theories and methods used in social network analysis and their applications. Challenge your understanding and see how well you grasp the intricate dynamics within social networks!