FROM GLOBAL STANDARDIZATION TO LOCAL ADAPTATION: HOW THE WAR…

Thesis Feedback Summary – Key Points for Revision based on the meeting with supervisor

CRITICAL SECTIONS TO COMPLETELY REDO

1. Section 3: Research Methodology

Major Issues:

• Source categories are unclear and inconsistent
• You mention “academically to journal articles” (page 13)
• Later you list 3 categories: academic articles, corporate reports, marketing campaigns (page 14)
• You also mention “media reports” – need to clarify what this means
• Action needed: Clearly define and consistently use source categories throughout

Sources – Transparency Requirements:

• Must justify EVERY decision: why these specific sources? why these platforms?
• Provide step-by-step replicability – someone should be able to repeat your exact study
• Create detailed tables showing:
• All sources used for each company
• Type of each source (Instagram posts, press releases, etc.)
• Number of sources per company per type

Example table format:

Rows: Companies (McDonald’s, Nike, etc.)Columns: Source types (Instagram posts, Press releases, etc.)

Cells: Number of sources used

Academic vs. Non-Academic Sources:

• Major question: Can academic sources actually answer your research questions?
• Academic papers provide theoretical understanding but NOT concrete information about your 5 companies
• Supervisor’s concern: Some of your 20 academic papers don’t seem relevant:
• Some discuss Ukraine but not from marketing perspective
• Some discuss standardization/adaptation but not Ukraine specifically
• Some focus on economics or international relations, not marketing
• One was a bachelor thesis – remove this (not reliable)
• Mustafa paper was also questioned – review carefully

Recommended Approach for Academic Sources:

• Use academic literature to create a theoretical framework in Section 2
• Select 10-12 highly relevant papers specifically about standardization/adaptation in Ukraine context
• Use this framework to analyze your empirical data
• Do NOT mix academic and empirical sources in the analysis section

2. Section 4: Analysis (MAJOR RESTRUCTURING NEEDED)

Current Problem: You Cannot Test Hypotheses with Qualitative Data

• CRITICAL ERROR: You have hypothesis testing (H1, H2, H3) but hypothesis testing requires:
• Quantitative data
• Statistical analysis
• P-values
• This is what ChatGPT got wrong when advising you

What to Do Instead:

Remove all “hypothesis testing” language

New Structure for Section 4:

1. Title change: Instead of “Testing Hypotheses” “Qualitative Analysis” or “Findings”
2. Analyze empirical data only (non-academic sources: posts, press releases, articles)
3. Provide detailed analysis of what you found in the data
4. Within-case analysis: Analyze each company separately

• What does Coca-Cola do?
• What does McDonald’s do?
• Pattern over time (2022-2025)?

1. Cross-case analysis: Compare companies

• Similarities and differences
• Adaptation vs. standardization patterns

1. Do NOT cite academic literature in Section 4 – only cite your data sources

3. Section 5: Discussion (NEW SECTION TO CREATE)

• Connect your findings with academic literature
• Compare what you found with what theory says
• Cite academic sources here
• End with PROPOSITIONS (not hypotheses):
• Propositions = hypotheses for future research
• These are statements that could be tested in a follow-up quantitative study
• Must have clear independent and dependent variables
• Example: Instead of “brands change towards local adaptation” specify what drives what

MAJOR CONTENT ISSUES TO ADDRESS

Keyword Search Strategy

Current issues:

• Keywords listed on page 14 table but their role is unclear
• Not clear if you used keywords to:
• Find sources (like in academic databases)?
• Assign codes during analysis?
• Something else?

What you need:

• Explain the logic behind each keyword choice
• Use Boolean operators: AND, OR
• AND = both terms must appear (narrows results)
• OR = either term can appear (broadens results, used for synonyms)
• Different keywords for different platforms:
• Academic articles naturally have keywords
• Social media posts/corporate communication do NOT have formal keywords
• Explain how you searched each type of source

Data Completeness and Selection Bias

Critical concern raised by supervisor:

Imagine Coca-Cola posted 500 messages since 2022. If you only picked 15 that show adaptation and ignored 485 showing standardization, your conclusions would be wrong.

What you must document:

1. How many total sources were available?
2. Which ones did you include/exclude?
3. Inclusion/exclusion criteria
4. If you couldn’t access certain data, acknowledge this as a limitation

Example documentation needed:

• “For McDonald’s, I found 10 Instagram posts, 2 press releases, 3 news articles”
• “I excluded 5 sources because they didn’t relate to Ukraine”
• Report everything transparently

The Coding Problem (Page 20 Table)

Current confusion: Your table has 4 columns:

1. Topics (Changes, Consumer perception, Effectiveness)
2. Code/Categories (unclear what this means)
3. Description
4. Keywords/Indicators

Problems identified:

• What’s the difference between “codes” and “categories”?
• Where do keywords come from? (You said from articles where you found categories)
• Keywords work for academic articles but NOT for social media posts, press releases, etc.
• Your interpretation process is unclear

What qualitative coding actually means:

• Codes = smallest meaningful units of interpretation
• You take different wordings that mean the same thing
• Example: “support our soldiers” and “supporting Ukraine” both CODE: “Support for Ukraine”
• Group related codes Categories Themes
• This is interpretation work, not keyword matching

Required actions:

1. Delete “code” from the second column – you said you were hesitating about this
2. Explain your actual coding process step by step
3. Look at academic papers that did qualitative analysis (supervisor mentioned the “Peace Spread Activism” paper about Ukraine)
4. Provide examples of how you coded different types of content (social media posts, press releases, articles)

Effectiveness Measurement – MAJOR CHALLENGE

The Problem: Hard to measure effectiveness with secondary data. You need indicators like:

• Sales data (not publicly available)
• Market share (not disclosed for Ukraine specifically)
• Consumer surveys (you don’t have this)

Possible Solution: Use consumer reactions on social media as a proxy:

• Likes
• Comments (positive/negative)
• Engagement metrics

BUT this requires:

• Analyzing large volumes of consumer comments
• Avoiding selection bias (don’t just pick 5 positive comments if there are 400 negative ones)
• Acknowledging this is limited (you’re not measuring actual sales or brand attitudes)

Recommendation:

• Be careful with effectiveness claims
• Group effectiveness and consumer perception together
• Use available data cautiously
• Acknowledge limitations clearly

FORMATTING AND STRUCTURE ISSUES

Terminology

“Chapters” vs “Sections”:

• You had a discussion about whether to call them “chapters”
• Correct usage: In academic papers, use “SECTIONS”
• “Chapters” = book chapters
• Your thesis has numbered sections (3.1, 3.2, etc.) so use “sections”

References and Citations

Missing references found:

• Chinchenko
• Wisner
• Una Tova
• Mustafa

Actions needed:

1. Add missing references to reference list
2. Check that every in-text citation has a corresponding reference
3. Check that every reference is cited in text
4. Be careful with:

• Bachelor thesis (consider removing)
• Less relevant papers

1. Why did you send 20 specific papers? Check the logic of your selection

Citing non-academic sources: Two options for citing websites, press releases, social media:

Option 1: Direct citations

• Use author/company name + year (e.g., “McDonald’s, 2025”)
• Provide full details in reference list
• Will create lengthy reference list

Option 2: Identifiers + Table

• Create identifiers in brackets [Company A, Source 1]
• Provide table in appendix with full details
• Cleaner in-text but requires detailed appendix table

Excel Spreadsheet

• This is your coding documentation
• Critical for transparency
• Will eventually go in appendix
• Supervisor wants to review and provide feedback
• Polish it to look professional (format properly for A4)

APPENDICES AND SUPPLEMENTARY MATERIALS

What to Include:

1. Excel spreadsheet – your coding documentation
2. Source tables – detailed list of all sources used per company
3. Visual examples – screenshots as illustrations (properly cited)

What to Remove:

• Appendix C (Timeline) – supervisor said DELETE this
• Timelines showing “in October you planned to do X” are for proposals, not final thesis
• Not relevant for final submission

VISUAL CONTENT HANDLING

Screenshots and Social Media

You asked: Can I use screenshots? Answer: YES, with conditions:

• Use as illustrative examples
• Cite the source properly
• Can include in text or appendix
• Show how you interpreted visual content

How to code visual content:

• Take screenshot
• Cite the source
• Explain your interpretation (in appendix or text)
• Example: “This Instagram photo shows [description] which I interpreted as [meaning]”
• Provide 1-2 examples showing your coding logic

AI USAGE DISCLOSURE (REQUIRED)

New Requirement:

You MUST add an AI Statement to your thesis

What to disclose:

1. All AI tools used (ChatGPT, Grammarly, etc.)
2. Specific versions (GPT-4, GPT-5, etc.)
3. Exactly what you used them for:

• Consulting about organization
• Grammar checking
• Brainstorming ideas
• BUT NOTE: ChatGPT gave you WRONG ADVICE about hypothesis testing

What NOT to do:

• Do NOT use AI-generated content directly in your thesis
• If you did (you mentioned in conclusion draft), either:
• Rewrite it completely in your own words, OR
• Cite it as a source (but this looks bad)

Your note: Section 5 (Conclusion) has AI content as notes/draft

• Action: Completely rewrite this in your own words

NUMBER DISCREPANCIES

Source Count Issue

You mentioned:

• Analysis based on 32 sources initially
• But now you have more sources
• Need to update this number

Action needed:

• Count all sources actually used in final analysis
• Update the number throughout thesis
• Make sure all sources are documented

RESEARCH QUESTIONS ALIGNMENT

Current problem: Your research questions mention:

• Standardization vs. adaptation
• Concrete strategies
• Role of different factors (including culture)
• Effectiveness

But in your analysis:

• Culture doesn’t really appear
• Effectiveness is hard to measure

Two options:

1. Modify research questions to match what you actually analyzed
2. Adjust analysis to address research questions

Supervisor recommends: Option 1 – adjust research questions to fit your data

TRANSPARENCY AND REPLICABILITY CHECKLIST

Remember: Someone should be able to replicate your entire study

For Each Decision, Ask:

• Can someone else understand WHY I did this?
• Can someone else DO this themselves?
• Have I provided enough detail?

Specific Areas Requiring Detailed Explanation:

Source Selection:

• [ ] Why these source types?
• [ ] Why these specific platforms?
• [ ] How did you access them?
• [ ] What was available vs. what you used?
• [ ] What did you exclude and why?

Keyword Strategy:

• [ ] Why these specific keywords?
• [ ] How did you combine them?
• [ ] Did they differ by platform?
• [ ] How did they help you find/code data?

Coding Process:

• [ ] Step-by-step explanation
• [ ] Examples of how you coded different content types
• [ ] How you handled visual content
• [ ] How you developed codes/categories/themes

Analysis:

• [ ] Within-case analysis for each company
• [ ] Cross-case comparison logic
• [ ] Time-based patterns (2022-2025)

TIMELINE AND NEXT STEPS

Immediate Actions (This Week):

1. Send Excel spreadsheet to supervisor
2. Start working on Section 3 revisions
3. Review and select 10-12 most relevant academic papers

Next Phase:

1. Restructure Section 4 (remove hypothesis language, add qualitative analysis)
2. Create Section 5 (Discussion)
3. Rewrite any AI-generated content in Conclusion

Before Next Meeting:

• Complete Section 3 (methodology) revisions
• Send updated draft to supervisor
• Focus on transparency and replicability

Supervisor’s Scheduling Note:

“Once you’ve redone the analysis and sort of cleaned up this part, then we’re gonna have another interaction unless you have any questions beforehand”

SUPERVISOR’S POSITIVE NOTES

Despite extensive revisions needed, supervisor said:

• “I’m confident that you can get it done within the teacher’s deadlines”
• “Nothing speaking against registration”
• Your company selection is “well justified” with “good approach”
• Having structured approach with spreadsheet is “very good”
• You’re “on your way” and work is “feasible”

KEY RESOURCES MENTIONED

1. SharePoint Page: Webster Vienna Campus

• Navigate to: Connections Webster Vienna Campus
• Find: “Thesis Information” section
• Contains: Thesis template and formatting requirements

1. Academic Paper Example: “Peace Spread Activism”

• Shows qualitative data analysis with proper coding tables
• Use as reference for organizing your codes

1. Excel Spreadsheet Template: Need to format for A4 page

FORMATTING REQUIREMENTS (FINAL SUBMISSION)

Front Matter Needed:

• Title page (template available on SharePoint)
• AI Statement (new requirement)
• Abstract
• Table of Contents
• List of Figures/Tables

Check Before Submission:

• All references properly formatted
• All in-text citations match reference list
• Consistent terminology throughout
• Professional appearance
• Excel spreadsheet properly formatted in appendix

FINAL IMPORTANT REMINDERS

1. Hypothesis Testing = NO: This was ChatGPT’s mistake. You cannot test hypotheses with qualitative data.
2. Transparency is Key: Your qualitative methodology must be crystal clear. Imagine someone wants to challenge your findings – they should be unable to because you’ve documented everything.
3. Separate Theory and Empirics:

• Section 2: Literature review and theoretical framework
• Section 4: Analysis of empirical data (companies)
• Section 5: Discussion connecting the two

1. Academic Sources: Don’t mix them into Section 4 analysis. Use them for framework (Section 2) and discussion (Section 5).
2. Source Documentation: Every single source must be traceable and cited properly.
3. Cultural Aspects: Either address them in analysis or remove from research questions.
4. Effectiveness: Be cautious with claims; acknowledge limitations.

QUESTIONS TO ANSWER IN REVISION

Ask yourself while revising:

• Can someone replicate this study?
• Have I justified every decision?
• Are my research questions answerable with my data?
• Is my coding process clear and defensible?
• Have I avoided selection bias?
• Is everything properly cited?
• Does my structure (theory empirics discussion) make sense?

Remember: “The goal should be replicability. Everybody who has the right methodological knowledge could really repeat what you did and check if the same result.”

Total estimated work: Sections 3, 4, and 5 need major revisions. Section 5 needs to be created from scratch.

But you can do this! Your supervisor is confident you can complete this within deadlines.