BAA1024 Global Competitiveness Analysis: Determinants, Human Development Impact & Business Performance Insights

School

Sunway University (SU)

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Assignment Type

Group Assignment

Subject

BAA1024 Principles of Business Analytics

Uploaded by Malaysia Assignment Help

Date

07/29/2025

BACKGROUND

Examining ‘Global Competitiveness’ across nations is a complex yet profoundly important endeavor to assess business sector performance. How competitive are businesses? What makes it different across countries? Do human development differences contribute? Most importantly, what are the underlying factors that determine our business competitiveness levels?

These questions are undoubtedly relevant as studying Global Competitiveness is crucial in research areas in economics and social science.

For this Group Assignment, your task is to investigate the determinants of business competitiveness across countries. Using the data spanning from 2013 to 2023, you will analyze data across at most 161 countries, depending on the NA cases for some countries in some variables.

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DATA

Download the data file from eLearn. The data file contains the following variables:

No. Variable Description
1 Country Name of country
2 Year Year of observation. Ranges from 2013 to 2023.
3 Region Development Level

  • Very High Human Development
  • High Human Development
  • Medium Human Development
  • Low Human Development

Available in separate sheet to be matched later in assignment.

5 Global Competitiveness Index (Dependent variable) It shows how competitive the business sector of the country is compared to the rest of the world.

Independent Variables

No. Independent Variables Description
6 1st pillar: Institutions It measures the quality of institutions in the country as compared to rest of the world
7 2nd pillar: Infrastructure It measures the quality of infrastructure in the country as compared to rest of the world
8 3rd pillar: Macroeconomic environment It measures the stability of macroeconomic environment in the country as compared to rest of the world
9 4th pillar: Health and primary education It measures the quality of primary health and education in the country as compared to rest of the world
10 5th pillar: Higher education and training It measures the quality of higher education and training in the country as compared to rest of the world
11 6th pillar: Goods market efficiency It measures the degree of goods market efficiency in the country as compared to rest of the world
12 7th pillar: Labor market efficiency It measures the degree of labor market efficiency in the country as compared to rest of the world
13 8th pillar: Financial market development It measures the level of financial market development in the country as compared to rest of the world
14 9th pillar: Technological readiness It measures the degree of technological readiness in the country as compared to rest of the world
15 10th pillar: Market size It measures the market size in the country as compared to the rest of the world
16 11th pillar: Business sophistication It measures the level of business sophistication in the country as compared to the rest of the world
17 12th pillar: Innovation It measures the level of innovation in the country as compared to the rest of the world

DATA PREPARATION

The dataset contains 1771 observations from the year 2013 to 2023. For this Group Assignment, you are required to conduct data analysis based on the year and variable names assigned to your group.

  1. Refer to Data file (excel) and look at sheet named “group numbers” to identify data for your group.
  2. Refer to sheet named “WEF Data” and filter the data, based on the specific year assigned to your group and select the variable columns (e.g. if the year assigned is 2018, filter observations for the year 2018, and keep the pillar number mentioned in the group information).
  3. The observations across years are same equaling to 161 before removal of NAs. You have to report the after-NA removal sample and sample reported by regression which should be same and will be checked in the cleaned data file.
  4. Once you have filtered your data, copy and paste the data into a new Excel sheet. This Excel sheet should be labelled according to the group number (e.g. if the group number is 10, you name it Group10). Your analysis should be based on the data in this new Excel sheet.
  5. For the various analyses that you may need to conduct, ensure that it is properly labelled if the results are stored in different Excel sheets and add their description in the report.
  6. Ensure that your analyses are conducted in a single Excel file. This is the Excel file that you will need to submit for marking.

ASSIGNMENT TASK

You are required to produce a research report based on the following guidelines:

1. Introduction [10 marks]

  • Include a problem statement and the motivation of the study that links why improving the dependent variable is important and how the pillars are relevant.
  • Ensure that you include appropriate citations, and each unique citation should have its APA formatted reference.
  • Your introduction should not be more than 1 page.

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2. Data Preparation and Exploratory Data Analysis [30 marks]

  • For each step add a heading using heading numbers like 2.1, 2.2 etc if there is any output show and interpret if not output then only briefly mention how it was done.
  • Replace the NAs with empty cells. Do not remove rows.
  • Add a code for development level using appropriate LOOKUP formula from sheet name ‘development categories’ to match ‘Level name’ and ‘Level code’ and insert them into your data file.
  • Construct a table in a separate sheet that groups the data across ‘Level name’ category. Ensure that you present the mean value of your dependent and independent variable for each Level name. Make an appropriate chart and interpret the output.
  • Generate and report suitable summary statistics for your dependent variable and your explanatory variable. Interpret the output of at least two variables.
  • Produce two (2) appropriate charts to visualize the data. These two chart types must be different. Ensure that the results are appropriately described. Interpret the chart.

3. Empirical Analysis [30 marks]

  • Briefly explain about each test’s method used in empirical analysis below along with the outputs. You can use heading numbers like 3.1, 3.2 etc for each analysis done in this section.
  • Identify and conduct an appropriate test to investigate whether there are significant differences in the mean ‘Global Competitiveness Index’ across Development Levels.
  • Specify and estimate an appropriate model to predict ‘Global Competitiveness Index’.
    • Make a correlation matrix of the dependent and provided explanatory variables
    • Regress the dependent variable against provided explanatory variables and the ‘Level code’.
    • Based on your results, which variables significantly influence the ‘Global Competitiveness Index’? by populating the following table. The interpretation of variables must include clarifying the direction, magnitude, and significance of the variables.
    Independent Variable Name Slope value Test for significance outcome (Significant or not significant) Correlation value with dependent variable
  • Report and explain the tests result accordingly.

4. Discussion and Implications [10 marks]

  • Based on the analysis you have conducted, summarize the key findings and provide some implications/recommendations to policymakers and key stakeholders.
  • This section should not be more than 1 page.

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