Retail Sustainability: Predictive Impact Analysis
STRATEGIES FOR SUSTAINABLE SUPPLY CHAINS: A QUANTITATIVE
ANALYSIS
Presented By Edward Osiemo Kirochi, MBA (University of Nairobi)
Abstract
This analysis identifies and quantifies the key strategic drivers—including eprocurement, cost minimization, and supplier engagement—that directly enhance
sustainability within modern retail supply chains. Utilizing a cross-sectional research
design, the study surveyed 52 supermarket operations in Nairobi. Data was analyzed
using SPSS, applying frequency distribution and multiple linear regression to model the
measurable impact of specific strategies on overall supply chain sustainability. The
findings provide a data-driven framework for businesses to prioritize investments that
strengthen both operational resilience and sustainable performance.
Methodology
The research analyzed supply chain strategies within the Nairobi retail market using a
cross-sectional descriptive design. The study engaged a representative sample of 52
supermarket chains, utilizing standardized statistical sampling to ensure validity. Primary
quantitative data was collected via structured questionnaires administered to supply chain
officers. All analysis was performed in SPSS. Descriptive statistics quantified adoption
rates, while Multiple Linear Regression modeled the relationship between five key
strategic variables to produce a validated predictive model.
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Data Analysis & Results
A multiple linear regression was performed to model the impact of key strategic drivers.
Table 4.15: Strategic Impact Matrix
Relative
Impact
(Beta)
Significance
Business Result
1. Supplier Engagement
0.384
**
High Impact: Primary driver of
sustainability performance.
2. E-Procurement
0.279
*
Moderate Impact: Key digital
accelerator.
3. Supplier Collaboration
0.172
-
Low Influence:
support factor.
4. Risk Management
0.169
-
Low
Influence:
predictive power.
5. Cost Minimization
-0.222
*
Negative Pressure: Aggressive
cost cutting hurts sustainability.
Strategy Priority
Secondary
Minimal
Significance levels: ** p < 0.01; * p < 0.05
As demonstrated in Table 4.15, the standardized coefficients (Beta) quantify each driver's
relative strength: Supplier Engagement (β = .384) is the most powerful, followed by EProcurement (β = .279). While Supply Chain Collaboration (β = .172) and Risk
Management (β = .169) contribute to the model, they did not reach statistical
significance at the 95% confidence interval, indicating they are secondary to digital and
engagement strategies.
The predictive model
To calculate the forecasted impact on sustainability, the following validated regression
equation is applied:
𝒀 = 𝟎. 𝟖𝟒𝟎 + 𝟎. 𝟏𝟔𝟎𝒙𝟏 + 𝟎. 𝟏𝟓𝟗𝒙𝟐 − 𝟎. 𝟐𝟓𝟐𝒙𝟑 + 𝟎. 𝟑𝟎𝟓𝒙𝟒 + 𝟎. 𝟏𝟒𝟏𝒙𝟓
(Where: Y=Supply Chain Sustainability (Dependent Variable), x1=Supplier
Collaboration, x2=E-Procurement, x3=Cost Minimization, x4=Supplier Engagement,
x5=Risk Management)
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