Impact of Corporate Strategy Choices on Financial Performance: Evidence from Global Platform-Based Technology Firms
Budget: $30 – $250 USD
Project Title
Impact of Corporate Strategy Choices on Financial Performance: Evidence from Global Platform-Based Technology Firms
Background
I am working on a mini-dissertation for my Executive MBA program. The study analyzes how different corporate strategy patterns adopted by large platform-based technology firms affect their financial performance.
The firms under study are:
Microsoft
Google (Alphabet)
Amazon
Meta
Apple
Time period: 2019–2024
This is an applied, data-driven study (not purely theoretical).
Objective of the Study
To:
Classify each firm-year into a dominant strategy pattern:
Innovation-led
Acquisition-led
Ecosystem-led
Hybrid
Examine how these strategy patterns are associated with:
Operating Margin
Return on Assets (ROA)
Build a simple empirical model showing which strategy types tend to perform better financially.
What I Need From You (Scope of Work)
1. Data Collection Support
For each firm and year:
Strategy proxies
R&D expenditure
Revenue
Number or value of acquisitions
Platform / cloud / ecosystem revenue (if available)
Financial variables
Operating income
Net income
Total assets
Market capitalization (optional)
Revenue
Sources will mainly be:
Annual reports (10-K)
Financial databases (Yahoo Finance / Macrotrends / etc.)
2. Dataset Construction
Create a firm–year panel dataset with:
Firm name
Year
R&D intensity = R&D / Revenue
Acquisition intensity = count or acquisition spend / Revenue
Ecosystem intensity = platform or cloud revenue share
Operating margin
ROA
Control variables (firm size, leverage if possible)
Expected size: 30 rows (5 firms × 6 years)
3. Strategy Classification (Typology)
Apply this rule:
Standardize the three strategy indicators (z-scores).
The highest value determines the dominant strategy for that year.
If no clear dominance → classify as “Hybrid”.
Output:
Strategy_Type variable with 4 categories.
4. Statistical Analysis Required
Using Excel / SPSS / Stata / Python:
Descriptive statistics
Correlation matrix
Group comparison tests:
ANOVA (or Kruskal–Wallis if needed) comparing ROA and operating margin across strategy types
Multiple regression:
Dependent variables:
Operating margin
ROA
Independent variables:
Strategy type (or strategy proxies)
Controls (if feasible):
Firm size
Leverage
5. Deliverables
Clean Excel dataset
Regression output tables
ANOVA results
Correlation matrix
Short explanation of:
Method used
Key results
Interpretation
Optional:
Charts (ROA & margin by strategy type)
Important Notes
This is an academic project, but should be handled professionally.
Accuracy and replicability are important.
I will write the final dissertation — you are supporting with data and analysis.
Impact of Corporate Strategy Choices on Financial Performance: Evidence from Global Platform-Based Technology Firms
Background
I am working on a mini-dissertation for my Executive MBA program. The study analyzes how different corporate strategy patterns adopted by large platform-based technology firms affect their financial performance.
The firms under study are:
Microsoft
Google (Alphabet)
Amazon
Meta
Apple
Time period: 2019–2024
This is an applied, data-driven study (not purely theoretical).
Objective of the Study
To:
Classify each firm-year into a dominant strategy pattern:
Innovation-led
Acquisition-led
Ecosystem-led
Hybrid
Examine how these strategy patterns are associated with:
Operating Margin
Return on Assets (ROA)
Build a simple empirical model showing which strategy types tend to perform better financially.
What I Need From You (Scope of Work)
1. Data Collection Support
For each firm and year:
Strategy proxies
R&D expenditure
Revenue
Number or value of acquisitions
Platform / cloud / ecosystem revenue (if available)
Financial variables
Operating income
Net income
Total assets
Market capitalization (optional)
Revenue
Sources will mainly be:
Annual reports (10-K)
Financial databases (Yahoo Finance / Macrotrends / etc.)
2. Dataset Construction
Create a firm–year panel dataset with:
Firm name
Year
R&D intensity = R&D / Revenue
Acquisition intensity = count or acquisition spend / Revenue
Ecosystem intensity = platform or cloud revenue share
Operating margin
ROA
Control variables (firm size, leverage if possible)
Expected size: 30 rows (5 firms × 6 years)
3. Strategy Classification (Typology)
Apply this rule:
Standardize the three strategy indicators (z-scores).
The highest value determines the dominant strategy for that year.
If no clear dominance → classify as “Hybrid”.
Output:
Strategy_Type variable with 4 categories.
4. Statistical Analysis Required
Using Excel / SPSS / Stata / Python:
Descriptive statistics
Correlation matrix
Group comparison tests:
ANOVA (or Kruskal–Wallis if needed) comparing ROA and operating margin across strategy types
Multiple regression:
Dependent variables:
Operating margin
ROA
Independent variables:
Strategy type (or strategy proxies)
Controls (if feasible):
Firm size
Leverage
5. Deliverables
Clean Excel dataset
Regression output tables
ANOVA results
Correlation matrix
Short explanation of:
Method used
Key results
Interpretation
Optional:
Charts (ROA & margin by strategy type)
Important Notes
This is an academic project, but should be handled professionally.
Accuracy and replicability are important.
I will write the final dissertation — you are supporting with data and analysis.