DRE 1018 Organisational Network Analysis
DRE 1018 Organisational Network Analysis
Over the past decade or so, social network analysis and theories have become an important perspective to study al phenomena. Organisational network analysis (ONA) is a term coined to describe application of the relational perspective to observe, measure, visualize organisation, and manage organisations. In other words, it is a set of theories, methods and techniques that acknowledge the fact that people, teams, and organisations are interconnected and dependent on one another to achieve their respective goals. It also upgrades the classic multivariate analysis with the understanding that independence of observations is rarely a fact.
Organisational networks can be studied at multiple levels of research (intra-organisationally and inter-organisationally) and can be meaningfully applied to numerous organisational phenomena. The typology of ties studied in organisational network analysis would range from similarities (location, membership, attribute), over social relations (cognitive, affective, kinship), interactions (e.g. gets creative ideas from and gets support to implement innovations from), to the flows (e.g. information, learning). In its essence, it aims to understand structure of organisational networks, as well as their antecedents and consequences.
Understanding these seemingly invisible networks of relationships have become central to understand various organisational behavior phenomena, leadership, performance and strategy execution, learning, creativity, and innovation topics. Research shows that appropriate connectivity in networks within and between organisations can have a substantial impact on organisational outcomes. Hence, the purpose of the ONA course is to familiarize students with the set of competences a researcher needs for research on organisational networks.
At the end of the course students will be in a better position to appreciate and understand:
- What is organisational network analysis?
- Why and when to use it?
- What are the current network theories?
- What are the key concepts that constitute organisational network theories?
- What can we do with it to better understand organisations?
- The antecedents and consequences of the network phenomena
- The multiple level aspect of organisational network research: intra-organisational (interpersonal & inter-unit) & inter-organisational and their inter-relations.
- Which software tools can we use?
- Where to go from here / how is it relevant to my research?
Disclaimer: Please note that this is a content oriented workshop led by advanced users. While you can expect a plethora of practical hints and tips as well as demonstrations and tutorials, this is not a methodological course.
At the end of the course students will be intermediately experienced users of selected social network analysis tools.
During and after the course students will be reflect upon the theory and empirics of organizational networks and connect them to their respective PhD projects.
To a large extent, the value of this course will depend on the level and quality of student preparation and participation in classroom discussion. The tentative program is as follows:
Session 1: Introduction, key network concepts, organisational network theories
Session 2: organisational Network Methodology (Tutorial with NodeXL, basic organisational network analysis concepts)
Session 3: Inter-organisational Network Applications
Session 4: Intra-organisational Network Applications
Sessions 5 & 6: Tutorial with Pajek software (advanced exploratory network anaysis concepts)
Session 7: Tutorial with UCINET software (advanced confirmatorz network analysis concepts)
Session 8: Network dynamics
Session 9 & 10: Current and future trends in network research (guest lectures & round table)
Computer-based tools: Selected social network analysis software packages: Pajek, UCINET, and NodeXL.
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Enrollment in a PhD Programme is a general requirement for participation in PhD courses at BI Norwegian Business School.
External candidates are kindly asked to attach confirmation of enrollment in a PhD programme when signing up for a course. Other candidates may be allowed to sit in on courses by approval of the courseleader. Sitting in on a course does not permit registration for the course, handing in exams or gaining credits for the course. Course certificates or confirmation letters will not be issued for sitting in on courses.
Students will not be permitted to sit in on this course. Active participation will be critical to the educational experience and all enrolled students must engage in the sequence of interactive classroom sessions (presentations, tutorials, round table, guest speakers) and at the end of course assignment.
Assessments |
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Exam category: Activity Form of assessment: Presentation and discussion Weight: 30 Grouping: Individual Exam code: DRE 10181 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
Exam category: Submission Form of assessment: Written submission Weight: 70 Grouping: Individual Duration: 1 Month(s) Exam code: DRE 10181 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
Activity | Duration | Comment |
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Prepare for teaching | 100 Hour(s) | For each session a limited number of assigned readings are indicated. Each participant is expected to read all the required reading prior to each session and to be able to comment upon them during the discussion. Additional articles may be added or substituted during the course. |
Submission(s) | 45 Hour(s) |
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.