Highlights
Module Learning Outcomes
On successful completion of the module, students will be able to:
1. Articulate clear research aims, objectives and research questions appropriate for the type of business and management problems the student is likely to encounter.
2. Explain the relative merits of a variety of primary data collection and analysis methods.
3. Critically evaluate a management research topic and develop a justified research framework.
Assessment overview
The research proposal develops the initial research topic. It will take the format of Background, Aims and Objectives, Rationale, Outline Literature Review, Outline Methodology, Project Plan (GANTT chart or similar) and an Ethics Form. The proposal is designed to focus your thoughts on what you are trying to achieve before attempting the main project itself. It helps you and your supervisor clarify your aims and objectives and ensures that all work following the proposal is effective and productive in facilitating your achievement of the module's learning outcomes.
Criteria for selecting a topic
There are some restrictions for selecting a topic. Below is a criterion for choosing a topic for each pathway.
MSc Management and International Business (IB) Pathway
An IB Pathway proposal could be ‘international’ via:
MSc Management and Marketing Pathway
A Marketing Pathway proposal must:
1) Focus on a marketing-related topic that is relevant.
2) Consider an outcome for the research on a company or consumers.
3) Analytical and investigate beyond basic consumer market research.
4) Avoid market entry plans as they lack critical thinking and analysable data.
5) Not include a finance-related topic.
MSc Management and Finance Pathway
A Finance Pathway proposal must:
1) Focus on a finance-related topic that is relevant.
2) Avoid other pathways such as marketing and human resource management.
3) Clearly focused on facilitating an in-depth approach, subject to the availability of adequate sources and your knowledge.
4) Demonstrate evidence of financial analytical skills in your data.
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