BUSI1693 Global Networks and Innovation Module Handbook 2025-26 | UoG

Table of Contents

• Welcome message from your Module Leader    
• Key contacts (academic queries)    
• Enquiry-Based Learning and Research-Led Teaching    
• Module details and learning outcomes    
• Employability    
• Key Dates    
• Schedule of teaching and learning activities    
• Assessment    
• Resit assessments    
• Resource recommendations    
• Ethical Compliance for Research on Taught Courses    
• Additional module information    
• Digital Student Centre (non-academic queries)    
• Changes to the module    

BUSI1693 Module Details and Learning Outcomes

Aims

There has been a dramatic reconception of the nature of organisations in the last decade, with a new focus on the central role of relationships within and beyond organisational borders. In part, this has been an extension of the notion of the value chain, with a detailed study of the intricacies of the inter-organisational supply chain. But more recently, insights from this perspective have been supplemented by the application of the tools of social network analysis to organisational studies. Among others, innovation studies particularly benefited from these methodological and theoretical advancements.

This module provides an overview of the network concept as applicable to business and innovation, drawing from the concepts of the value system, network economics, and social capital. It surveys network applications to parent-subsidiary relationships, strategic alliances, global value chains, knowledge diffusion and the management of informal relationships within organisations. The second part of the module stimulates a critical reflection on the complex relationship between innovation and globalisation, specifically remarking the embedded and networked nature of innovative processes with regional and national innovation systems and advancing the understanding of the challenges associated with innovation management.

Learning Outcomes

1) Demonstrate deep and systematic understanding of the concepts of network analysis and the analysis of large datasets; The theory of social capital; A range of contemporary applications of network analysis to business; A range of contemporary tools and techniques of social network analysis and business analytics; the multifaceted nature
of innovation; the role of different actors and stakeholders in sustaining innovation; the impact of countries’ and regions’ characteristics on the innovation process.

2) Conceive intra- and inter-organisational relationships as networks; Critically engage with economic, sociological, psychological and mathematical literature in application to business problems; Value the varying benefits of cohesion and diversity; consider ethical dimensions of social network analysis; use computational techniques to analyse and presentation of social network data and large datasets.

3) Independently analyse data about real organisations in complex situations and solve sophisticated managerial problems, with a clear understanding of limitations.

4) Write substantial reports, utilising well-developed transferable skills in effective, professional communication, such as formatting, spelling, and storytelling.

Glossary:

• A prerequisite module must have been completed successfully before taking this module.
• A co-requisite module must be taken alongside this module.
• A learning outcome is a subject-specific statement that defines the learning to be achieved through completing this module.

BUSI1693 Employability

At the end of this module, you will be able to use advanced analytical techniques and a programming language (Python) which are highly requested in the job market nowadays – especially in large companies and institutions, and in industries such as fintech, trading, and banking.

You can find out more about the Greenwich Employability Passport at: Greenwich Employability Passport for students.

Information about the Career Centre is available at: Employability and Careers | University of Greenwich.

You can also use LinkedIn Learning to gain access to thousands of expert-led courses to support your ongoing personal development. More information can be found at: LinkedIn learning | IT and library services.

BUSI1693 Assessment

Assessment schedule:

*The weighting refers to the proportion of the overall module result that each assessment task accounts for.

Your assessment brief:

Guidance:

Company Report

Each student is expected to perform an analysis of a provided dataset. The dataset will describe a set of inter-company relationships related to a multinational company. The objective of this assessment is to measure familiarity with data management and visualisation and establish a connection between real data and theories.

Students are expected to use network analysis, visualisation and basic data analysis techniques to discuss how the network relates to the firm’s innovation capability. To do this, students are expected to collect other information about the given company, as well as to apply knowledge and theories developed in the course and use other relevant academic articles.

You are expected to use Python during the course. Python is a free programming language that comes with Anaconda. The software is available to download following the hyperlink highlighted before, and it is also available in the laboratory computers. Documentation of the key software tasks covered in the weekly lab sessions is provided in each week’s notebooks available on Moodle. Furthermore, Python is a very popular programming language with countless free online training courses.

Specifically, you are expected to:

• Provide an overview of the internationalisation strategy of the company (approximately 400 words)
• Use network analysis techniques and visualisations to describe the network in which it is embedded (approximately 700 words)
• Provide a preliminary, exploratory interpretation of the role played by the company and others of particular note, considering aspects such as their centrality (degree, betweenness, closeness/farness, and eigenvector centrality), location, activity, size and other relevant characteristics (500 words)
• Discuss the implications of industry and country environments on the innovation strategy of the firm (400 words)

Formative assessments: Students are strongly encouraged to attend the laboratory sessions, where we will work on the application of the business theories discussed in the lectures, using Python.

Feedback for summative coursework: Written feedback sandwich will be provided, as well as written comments on the Company Report (but not on the Lightning Talk.

Marking rubric: 

Company Report

BUSI1693 Resit assessments

Assessment schedule:

BUSI1693 Resource recommendations

The following are suggested readings for the module. Additionally, more detailed reading recommendations will be provided for the module topics.

Students are also expected to read some papers related to the weekly activities described in Section 4. Complete references of the selected papers are below:

De Vita, R., Sciascia, S., & Alberti, F. (2008). Managing resources for corporate entrepreneurship: the case of Naturis. The International Journal of Entrepreneurship and Innovation, 9(1), 63-68.

Ahuja, G. (2000). Collaboration networks, structural holes, and innovation: A longitudinal study. Administrative Science Quarterly, 45(3), 425-455.

Gilsing, V., Nooteboom, B., Vanhaverbeke, W., Duysters, G., & van den Oord, A. (2008). Network embeddedness and the exploration of novel technologies: Technological distance, betweenness centrality and density. Research Policy, 37(10), 1717-1731.

Capaldo, A. (2007). Network structure and innovation: The leveraging of a dual network as a distinctive relational capability. Strategic Management Journal, 28(6), 585-608.

Morschett, D., Schramn-Klein, H., & Zentes, J. (2015). The Integration/Responsiveness and the AAA-Frameworks. In Strategic International Management (pp. 25-49). Springer Gabler, Wiesbaden.

Boschma, R. A., & Ter Wal, A. L. (2007). Knowledge networks and innovative performance in an industrial district: the case of a footwear district in the South of Italy. Industry and Innovation, 14(2), 177-199.

BUSI1693 Additional module information

Activities:

All the module’s activities are described in Section 4.

Resources:

The Module Leader will be available to provide extra support and resources for those students interested in exploring different Python libraries, in addition to those presented in the laboratories and mandatory for producing the Company report.

Costs:

In this module, there are no specific additional costs. Python and Anaconda are free and open access, and all the reading materials will be provided by the Module Leader and/or via the Library system.