Module Code : BMM5123 Module Title : Global Business Environment Assessment 2: Individual Report Learning Outcomes: Describe the complexities of the global business environment, including historical economic philosophies, macroeconomic factors, trade patterns, and the role of multinational corporations. Analyse the impact of globalisation, neoliberalism, and technological advancements on business dynamics, considering international trade law, labour laws, and intellectual property law. Evaluate ethical and legal considerations in the digital business landscape, including data privacy, algorithmic bias, surveillance capitalism, and global-local pressures. Apply theoretical knowledge to global business challenges by synthesising research, case studies, and strategic insights to develop problem-solving and decision-making skills. What is required:
Building on the group presentation, you are required to submit an individual report (3,000 words) that further develops your chosen topic. While the presentation focuses on summarising and communicating ideas collaboratively, this report allows you to demonstrate independent research, analytical depth, and academic writing skills.
Instructions:
Your report should focus on one specific topic (the same as to your group presentation), but your analysis must reflect your individual perspective and go beyond what was presented by the group.
Your report must include the following:
Historical Context Trace the origins and development of the selected topic. For example, if focusing on AI in business strategy, discuss the evolution of AI from early automation tools to present-day generative AI systems. Analysis of Key Challenges in a Global Context Identify and discuss the primary challenges organisations face due to your chosen issue or trend. For instance, in the context of data privacy, explore how global tech firms navigate differing regulations in the EU, US, and China. Evaluation of Legal, Economic, and Ethical Implications Examine how your topic intersects with international business law, macroeconomic impacts, and ethical concerns. If analysing algorithmic bias, consider its ethical implications for workplace equality and the legal responsibilities of companies under anti-discrimination laws. Proposed Strategies for Responsible and Sustainable Decision-Making Offer realistic and forward-looking strategies that global businesses can adopt to address the challenges you’ve outlined. Support your strategies with academic models or policy recommendations (e.g., ESG frameworks, Porter’s Five Forces, etc.). What are the main topics I need to research?
Choose ONE of the following broad themes:
Macroeconomic Trends and Trade Patterns Focus on one key macroeconomic indicator, such as:
GDP growth: e.g., impact of China’s slowing GDP growth on global tech companies. Inflation: e.g., how post-COVID inflation is influencing consumer goods pricing across markets. Global trade flows: e.g., the effect of U.S.–China trade tensions on supply chain strategies. Your analysis should demonstrate how this indicator affects multinational corporations in terms of strategy, investment, or operations.
International Trade Law and Labour Laws Focus on one aspect only:
Tariffs: e.g., implications of Brexit-related tariffs for UK-based exporters. Labour laws: e.g., how stricter EU labour laws affect gig economy platforms like Uber or Deliveroo. You should examine the legal framework and its business consequences across different markets.
Technological Disruptions and Business Strategy Choose one technological innovation, such as:
Artificial Intelligence (AI): e.g., AI’s role in transforming HR recruitment practices in multinational firms. Internet of Things (IoT): e.g., its impact on global logistics and inventory management. Data analytics: e.g., how predictive analytics is influencing retail marketing strategies. Discuss how the chosen technology disrupts traditional business models and informs strategic decisions.
Ethical or Legal Challenges in the Digital Economy Focus on a single issue, such as:
Data privacy: e.g., how GDPR affects cross-border data sharing in tech companies. Algorithmic bias: e.g., risks of discriminatory outcomes in algorithm-driven hiring platforms. Intellectual property rights: e.g., protecting innovations in global pharmaceutical companies. Surveillance capitalism: e.g., how tech firms monetise user data and its ethical consequences. Critically assess the ethical or legal tensions and their broader implications for stakeholders.
