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Nzama and Olarewaju

that the construct explains at least 50% or more of the 5. Discussion
variation in the components that comprise it. Results
presented in Table 2 confirm the variance values are The purpose of this study was to investigate the impact
within the recommended threshold. The KMO test of CES on plastic pollution management in F&B
result of 0.77 suggests that the research sample size of manufacturing enterprises. The study’s goal was to
124 is adequate. The Bartlett test of sphericity, which examine if any variations applied inside the organizational
explains why EFA was performed, is statistically structure may have an impact on waste management.
significant (p < 0.001). The study focused on the F&B industries because of
their excessive usage of SUP packaging. The findings of
4.3. Pearson correlation coefficient and regression the study found a significant relationship between CES
analysis and PPC, and the proposed hypothesis was confirmed.
4.3.1. The relationship between CES and PPC A study conducted by Wang et al. revealed that
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The outcome of the statistical analysis is shown in stakeholder pressures may have a greater impact on CESs
Table 4. This table illustrates a correlation between in developed nations and non-manufacturing enterprises
CESs and PPC. maybe can easily adapt their environmental strategy than
Table 4 shows a substantial link between CES and manufacturing firms. Although the firms might be willing
plastic pollution reduction in F&B manufacturing to implement the strategies for manufacturing companies
enterprises (r = 0.385, P < 0.0005). The significant might find it difficult to do so as the means altering the
relationship suggests a direct link between the two entire processes at all levels. However, the finding of
constructs. This means that, as CES improves within Zeng et al. contradicts this because heavy-polluting
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an organization, they will be able to address or control companies are likely to incorporate prevention strategies.
plastic pollution to a greater extent. Our study’s finding aligns with the results obtained
An examination of regression was performed to by Aftab et al. that revealed that CES strengthens and
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determine the amount of influence between the two drives sustainable innovation within an organization.
components. Table 5 shows the linear regression results. Furthermore, the findings indicate the necessity for
The regression study, presented in Table 5, yielded an senior organizational management to strengthen their
R value of 0.149, implying that business environmental commitment to environmental ethics by developing
2
policy accounted for 14.9% of the variation in PPC. The and implementing diverse environmental practices in
R score indicates how much of the overall variance in day-to-day operations to successfully address critical
2
the dependent variable (PPC) can be explained by the sustainability concerns. Kuo et al. found that CESs
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independent variable (CES). There is a substantial linear have a favorable impact on sustainable innovation. The
link between environmental knowledge and plastic results obtained in this study and the previous scholarly
pollution prevention, with F (1,122) = 21.286; p < 0.0005. empirical research indicated that enhancing CES
A p < 0.0005 suggests a significant relationship between improves sustainable measures such as developing new
the independent variable (CES) and the dependent environmentally friendly products, greener operations,
variable (Plastic Pollution Reduction), with B = 0.385 and processes. The outcomes of Javeed et al. revealed
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and p < 0.0005. The results confirmed the hypothesis that firms with business environmental strategies such
of the study. as environmental regulation, proactive environmental

Table 4. Relationship between corporate environmental strategy and plastic pollution control
Construct A Construct B Pearson’s correlation (r) p
Corporate environmental strategy Plastic pollution control 0.385** <0.0005
Note: **The association becomes statistically significant at the 0.01 level (two-tailed).

Table 5. Linear regression between corporate environmental strategy and plastic pollution control

Variables in the equation B Beta t P R 2 F df p
Constant 14.848 5.919 <0.0005 0.149 21.286 1; 122 <0.0005
Corporate environmental strategy 0.824 0.385 4.614 <0.0005
Note: Dependent variable: Plastic pollution control; Predictor (Constant): Corporate environmental strategy.

Volume 22 Issue 1 (2025) 90 doi: 10.36922/ajwep.7089