MA/LLM in Maritime Law and Shipping Business

Course Information Package

Course Unit CodeMLSM506
Course Unit DetailsMA/LLM Maritime Law and Shipping Management (Required Courses) -
Number of ECTS credits allocated8
Learning Outcomes of the course unitBy the end of the course, the students should be able to:
  1. Develop specific project ideas and comment about the current research activity and methodological approaches in international economics, maritime law, international trade, and the shipping industry.
  2. Raise research questions and be able to draw from the educational research principles in order to develop research designs and methodologies suitable for investigating economic and policy issues.
  3. Identify the elements that highlight the quality of a research through certain research examples.
  4. Participate in Frederick University’s research activities that are related to the domain.
  5. Identify local and international institutional bodies and foundations that support and fund research and be informed about the funding programs and initiatives available in the area of the MSc Programme.
  6. Understand the processes followed and acquire the skills needed for writing a research proposal, through their practical involvement in the process.
  7. Develop their own, research questions and methodological designs which will lead finally to the elaboration of their Master’s Thesis.
  8. Implement a small scale research project related to their Master’s Thesis.
  9. Implement a small scale research project related to their Master’s Thesis.
Mode of DeliveryFace-to-face
Recommended optional program componentsNONE
Course Contents
Nature of Business Research – Research Topic
Understand and define the features of business research.
Obtain a clear understanding of the different characteristics of research.
Identify and evaluate the different attributes of a good research topic.
Analyze and apply the different techniques of generating research ideas
Demonstrate how research ideas can be refined.
Consider different ways of writing a research question or a hypothesis.
Comprehend the importance of theory in writing research questions and hypothesis. Understand the nature of data.

Critically reviewing the literature:
Demonstrate awareness of current state of knowledge and identify how research fits in the wider context.
Evaluate research done by other authors in a subject area.
Develop research questions and objectives finding research opportunities not done until now.
Discover and consider research approaches, strategies and techniques appropriate.
Highlight the issues where work will provide new insights demonstrating linkage to your research question and objectives.
Consider all different types of sources available.
Understand how literature needs to be properly referenced.

Research strategy and design
Understand the different strategies of doing research (quantitative and qualitative). 
Identifying when each strategy would be appropriate to use and how to choose a method.
Explain the process that has to be followed when doing research using a specific method.
Evaluate the strategies considering related benefits, difficulties, and issues the researcher should take into consideration when using each method.
Understand the concept of sampling and be able to use the appropriate sampling approach.

 Data collection using interviews
Assess the various problems a researcher is likely to face associated with gaining access to the source.
Design strategies to gain access. 
Understand how to overcome organizational concerns about the granting of access.
Identify and evaluate the different types of interviews used to collect data.
Design and conduct an interview.

Analyzing qualitative data
Identify the activities involved when analyzing qualitative data.
Evaluate the usefulness of each activity.
Understand all steps leading to a complete data analysis process.

Introduction to Quantitative research
Understand the concept of quantitative research and be able to separate it from qualitative research.
Learn about the major methods used for quantitative research, and be able to explain and compare them (advantages and disadvantages for each method).
Become aware of the major elements of quantitative research such as variables, unit of analysis and sampling.
Understand how to report quantitative data and findings.

Collection of quantitative data
Develop skills on how to use online databases from various organizations in order to obtain data for an analysis.
Become familiar with the questionnaire techniques available and when it is appropriate to use a questionnaire.
Understand the use of the questionnaire.
Develop skills on how to design a questionnaire for a research analysis.
Learn important information needed when one wants to use a questionnaire for a quantitative research analysis.

Analysis of quantitative data
Learn how to import data in the excel package to create correct spreadsheets for the analysis of any data.
Analysis of questionnaire data.
Describe various variables using graphs – graphical analysis.
Summarize data using basic statistics – descriptive analysis.
Examine relationships between two variables using graphs and statistics.
Understand the concept of significance.

Simple Regression Analysis for quantitative data
Introduced to the concept of using a statistical method.
Learn about Simple Regression analysis.
Obtain the results from the application of the analysis. 
Explain the results from regression estimation analysis.
Apply the method in excel using real actual data. 

Multiple Regression Analysis for quantitative data
Understand the multiple regression analysis framework.
Estimate the multiple regression analysis model and obtain the results.
Explain the results from the model with respect to significance and coefficients.
Calculate various effects form one variable (or more) to another.
Construct predictions of the dependent variables.
Introduced to the concept of hypothesis testing.

Multiple Regression Analysis: Extensions
Find effects and explain when the unit of measurement of one or more variables change.
Estimate and explain multiple regression relationships in the form of logarithms and growth rates.
Understand and apply the concept of nonlinearity.
Estimate in excel nonlinear models and explain their results.
Become familiar with the dummy variables properties.
Use dummy variables in regressions and evaluate the results.

Recommended and/or required reading:
  • Cohen, L., Manion, L., Morrison K. (2011). Research Methods in Education. 7th ed. London: Routledge.
  • Creswell, J.W. (2013). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. 4th Ed. Thousand Oaks, CA: Sage Publications.
  • Cooper, D. and Schindler P. (2014) Business Research Methods. 12th edition. McGraw Hill Higher Education.
  • Seidman, I., (2012). Interviewing as Qualitative Research: A Guide for Researchers in Education and the Social Sciences, 4th ed. Teachers College Press.
  • Charmaz, K (2006). Constructing Grounded Theory: A Practical Guide Through Qualitative Analysis. Thousand Oaks, CA: Sage Publications.
  • Silverman, D., (2015). Interpreting Qualitative Data. 5th ed. Sage Publications
  • Silverman, D., (2015). Interpreting Qualitative Data. 5th ed. Sage Publications
  • Crowther, D. and Lancaster, G. (2012). Research Methods, 2nd ed., Routledge.
  • Sekaran, U. and Roger B. (2011). Research Methods for Business: A skill Building Approach, 5th edition, Wiley.
  • Matthews and Ross (2010). Research Methods. A Practical Guide for the Social Sciences, Longman, Pearson education.
  • Wooldridge, M., J. (2012). Introductory Econometrics: A Modern Approach, 5th edition, South-Western College Pub.
  • Scherbaum, A., C, and Shockley, M.K. (2015). Analyzing Quantitative Data for Business and Management Students. Sage Publications.
Planned learning activities and teaching methodsLectures, discussions, oral presentations, feedback based on the evaluation of the research project submitted. Students will be able to use the computer labs while producing their project, and will have access to statistical analysis packages so as to become familiar with quantitative data processing.
Assessment methods and criteria
Coursework 50%
Final Exam50%
Language of instructionEnglish
Work placement(s)NO