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Academic Research · Quantitative Analysis · Sustainability

Master's Thesis

Quantitative research into what actually drives student participation in sustainable solid waste management at Kenyan universities.

Master's thesis · Academic research

Academic work presented as evidence of research and analytical rigour. Recommendations are coursework outputs, not claimed commercial outcomes.

Business question
Do behavioural or institutional factors better explain student participation in campus waste management?
Role
Research design · Quantitative analysis
Evidence
Sole researcher: survey design, data collection and hierarchical regression across behavioural and institutional blocks.
Conceptual artwork, not a product screenshot

Quantitative research on student participation in sustainable solid waste management in Kenyan universities, using behavioural theory and hierarchical regression.

01

Context

Kenyan universities operate at the scale of small towns, and solid waste management on campus depends heavily on whether students take part in it.

Read context

Kenyan universities operate at the scale of small towns, and solid waste management on campus depends heavily on whether students take part in it.

02

Problem

Participation is often treated as a matter of individual attitude alone, which leaves institutional conditions unexamined.

Read problem

Participation is often treated as a matter of individual attitude alone, which leaves institutional conditions unexamined. The research question was whether behavioural or institutional explanations better account for student participation.

03

My role

Sole researcher: research design, instrument construction, data collection and the full quantitative analysis.

Read my role

Sole researcher: research design, instrument construction, data collection and the full quantitative analysis.

04

Approach

The study combines the Theory of Planned Behaviour (attitude, subjective norms and perceived behavioural control) with institutional factors, tested through a survey design and quantitative analysis.

Read approach

The study combines the Theory of Planned Behaviour (attitude, subjective norms and perceived behavioural control) with institutional factors, tested through a survey design and quantitative analysis.

Hierarchical regression was used so that behavioural and institutional blocks could be entered separately and their contribution examined in sequence.

  1. 01Theory of Planned Behaviour
  2. 02Institutional factors
  3. 03Survey instrument
  4. 04Quantitative analysis
  5. 05Hierarchical regression

05

Methodological choice

Choosing hierarchical regression rather than a single combined model was the methodological decision that made the study useful: it keeps the behavioural and institutional explanations distinguishable instead of collapsing them into one score.

Read methodological choice

Choosing hierarchical regression rather than a single combined model was the methodological decision that made the study useful: it keeps the behavioural and institutional explanations distinguishable instead of collapsing them into one score.

  1. AlternativesRun one combined regression on all predictors, or enter behavioural and institutional predictors as separate blocks.
  2. What the evidence pointed toThe research question was about which type of explanation accounts for participation; a single model would not show that.
  3. DecisionHierarchical regression, so each block's contribution can be read in sequence.
Keep the explanations distinguishable.

06

Current status

Completed as the Master's thesis.

Verified
The research design, survey instrument, data collection and hierarchical regression were completed by Brenda as sole researcher.
What remains untested
This page does not state an empirical finding or effect size that has not been supplied and verified for publication.
Learning / next step
Any public findings summary should be checked directly against the completed regression outputs before publication.

Focus areas

  • Theory of Planned Behaviour and institutional factors
  • Survey research design
  • Quantitative analysis and hierarchical regression
  • Statistical analysis
  • Academic writing

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Amsterdam, Netherlands

Swahili · English · Dutch

Updated September 2026