Impact of the COVID-19 pandemic on sustainability knowledge and sustainable purchase decisions: the application of the theory of stimulus–organization–response

Figures & data

Figure 1. The proposed model.

Table 1. Self-administered questionnaire.

Variables	Measures	Code	Sources
COVID-19 situation	The COVID-19 pandemic has compelled me to adopt a more environmentally conscious approach.	CVD1	Zeng et al. (2023); Perkins et al. (2021); Srisathan and Naruetharadhol (2022).
	The COVID-19 pandemic offers valuable insights into the potential for accomplishing sustainable development goals.	CVD2
	The COVID-19 pandemic has catalyzed my decision to mitigate pollution levels actively.	CVD3
	The COVID-19 pandemic has catalyzed for me to minimize my consumption waste actively.	CVD4
	The COVID-19 pandemic has generated a realization inside me that my consumption patterns significantly impact the ecosystem.	CVD5
Sustainability knowledge	I am knowledgeable about climate change (climate change).	SK1	Perkins, et al. (2021); Batool et al. (2022); Longo, et al. (2019).
	I am knowledgeable about global warming.	SK2
	Purchasing sustainable products is vital.	SK3
	The 3R principle (reduce, reuse, refine) is essential.	SK4
	The goal of the Sustainable Development Goals is clear to me.	SK5
Sustainable purchase decisions (SPD)	I purchase products that are produced sustainably (sustainable production).	SPD1	Filho et al. (2022); Bhuwandeep and Das (2021); Batool et al. (2022).
	I prefer to purchase sustainable products.	SPD2
	I prefer to purchase products whose manufacturing process does not negatively impact the environment.	SPD3
	When purchasing a product, I am committed to preserving the lives of present and future generations.	SPD4
	To accomplish the Sustainable Development Goals (SDGs), I support sustainable consumption patterns.	SPD5

Table 2. Demographic details of the respondents.

Category	n	%
Gender
Male	91	35.41
Female	166	64.59
	257
Age
<17	7	2.7
17–20	28	10.9
21–30	166	64.6
31–40	50	19.4
>40	6	2.3
Are you familiar with the concept of sustainable development goals?
Yes	256	99.61
No	1	0.38
Have you encountered a COVID-19 outbreak?
Yes	252	98.05
No	5	1.94
Have you ever purchased environmentally responsible goods during the COVID-19 pandemic?
Yes	239	93
No	18	7
Profession
Student/student	64	24.90
Self-employed	53	20.62
Civil servant	36	14
Private employee	104	40.46

Source: Author’s calculation.

Table 3. Validity and reliability results.

Constructs	Cronbach’s alpha	Composite reliability (CR)	Average variance extracted (AVE)
COVID-19 situation	0.933	0.948	0.751
Sustainability knowledge	0.920	0.943	0.769
Sustainable consumption decision	0.808	0.872	0.595

Source: Author’s calculations using SMARTPLS 3.0.

Table 4. Constructs reliability.

Constructs	Items	Loadings	Conclusion
COVID-19 (CVD)	CVD1	0.781	Reliable
	CVD2	0.853	Reliable
	CVD3	0.906	Reliable
	CVD4	0.860	Reliable
	CVD5	0.885	Reliable
	CVD6	0.911	Reliable
Sustainability Knowledge (SK)	SK1	0.928	Reliable
	SK2	0.897	Reliable
	SK3	0.954	Reliable
	SK4	0.910	Reliable
	SK5	0.663	Reliable
Sustainable purchase decisions (SPD)	SPD1	0.817	Reliable
	SPD2	0.786	Reliable
	SPD3	0.425	Reliable
	SPD4	0.887	Reliable
	SPD5	0.893	Reliable

Source: Author’s calculations using SMARTPLS 3.0.

Table 5. Heterotrait-Monotrait (HTMT) results.

	CVD*SK	CVD	SK	SPD
CVD*SK
COVID 19 Situation	0.758
Sustainability Knowledge	0.796	0.888
Sustainability Purchase Decisions	0.690	0.778	0.916

Source: Author’s calculations using SMARTPLS 3.0.

Table 6. Variance inflation factor value.

Construct	Sustainable purchase decisions
CVD*SK	2.649
COVID-19 situation	3.570
Sustainability knowledge	3.948
VIF value < 5.0 = No collinearity

Source: Author’s calculations using SMARTPLS 3.0.

Table 7. Value of R² and Q².

Endogenous constructs	R^2	Q^2
Sustainability Knowledge (SK)	0.696	0.532
Sustainable Purchase Decisions (SPD)	0.649	0.362

Source: Author’s calculations using SMARTPLS 3.0.

Table 8. Effect size.

Constructs	f^2	Effect size
CVD -> SK	2,291	Large effect
CVD -> SPD	0.024	Small effect
SK -> SPD	0.271	Medium effect
CVD ->- SK > SPD	0.003	No effect

Source: Author’s calculations using SMARTPLS 3.0.

Table 9. Hypotheses testing.

Hypotheses	Path	Coefficient	T-statistic	Prob	Conclusion
H1	CVD -> SK	0.834	24,325	0.000	Hypothesis accepted
H2	CVD -> SPD	0.172	1,187	0.236	Hypothesis rejected
H3	SK -> SPD	0.612	4,244	0.000	Hypothesis accepted
H4	SK Mediating CVD -> SPD	−0.035	0.683	0.495	Hypothesis rejected

Note: p-value ≤ 0.05.

Figure 2. The PLS-SEM diagram.

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