Application of theory of planned behaviour in determining attitude and to measure purchase intention under the fear of Covid-19

Figures & data

Figure 1. Theory of Planned Behaviour (TPB).

Source: Ajzen (1991).

Figure 2. Proposed research model based TPB Theory.

Table 1. Measurement items.

Construct	Measurement items	Previously used items	Source of items
Heath consciousness
HC1	During covid-19 I am worried about my health therefore I prefer to shop online than to go out for store shopping	I’m very self conscious about my health	Michaelidou and Hassan (2008); Shah et al. (2021); Pu et al. (2021)
HC2	Due to Covid-19 outbreak I prefer online shopping as I become conscious while going out for shopping	I’m alert to changes in my health
HC3	To stay healthy in Covid-19 era I prefer to buy online than to go for frequent shopping	I take responsibility for the state of my health
HC4	As a preventive measure in current scenario I prefer online shopping and avoiding in store shopping.	I’m aware of the state of my health as I go through the day
Covid-19 protocol
PT1	“Social Distancing” is not a limitation in Online shopping	Physical distancing and Safety measures	Sehgal et al. (2021)
PT2	“Wearing a face mask while in public place” is not required in online shopping	Self developed
PT3	There is no need to frequently hand washing with soap protocol while shopping online.	Self developed
Attitude towards online shopping
AT1	I prefer online shopping than physical or store based shopping in current scenario	The idea of buying from this online catalogue retailer web site is a good idea.	Al-Debei et al. (2015); Michaelidou and Hassan (2008)
AT2	In pandemic like situation online shopping is anyways the best way to shop than any other modes of shopping	Buying from this online catalogue retailer web site is better than buying from a real store/shop
AT3	During Covid-19 outbreak I preferred online shopping	Buying from this online catalogue retailer web site is a pleasant thing to do
Behaviour intention to purchase online
BI1	During the covid-19 I started buying products online	I plan to shop online more frequently.	Akar (2021); Tarun (2011)
BI2	I intend to purchase through online even in the near future	I intend to shop online in the near future.
BI3	In the pandemic online shopping provide me complete satisfaction	I think I would prefer to shop online rather than traditional shopping.

Table 2. Demographic profile of the respondents.

		Frequency	Percentage
a) Gender:	(i) Male	169	57.7
	(ii) Female	124	42.3
b) Age (in Years)	(i) Up to 20	98	33.4
	(ii) 21–35	172	58.7
	(iii) 35–50	18	6.1
	(iv) 51 and above	5	1.7
c) Family income (Monthly in Rs.)	(i) Up to 25000	68	23.2
	(ii) 25,001–50,000	99	33.8
	(iii) 50, 001–75,000	41	14.0
	(iv) 75,001–1,00,000	14	4.8
	(v) 1,00,000 and above	71	24.2
d) Education	i) High school/intermediate	24	8.2
	ii) Undergraduate	123	42.0
	iii) Post-graduate	142	48.5
	iv) Doctorate	4	1.4
e) Online shopping frequency	(i) Very often	27	9.2
	(ii) Regularly	39	13.3
	(iii) Normally	161	54.9
	(iv) Rarely	56	19.1
	(v) Not very often	10	3.4

Figure 3. Structural model.

Table 3. Construct reliability.

Construct	Estimate	Composite Reliability	Cronbach alpha Reliability
Heath consciousness		0.811	0.802
HCS3	0.752
HCS2	0.795
HCS1	0.723
HCS4	0.602
Behaviour control in Covid-19 Protocol		0.757	0.749
BCCP1	0.659
BCCP2	0.808
BCCP3	0.670
Attitude towards online shopping		0.833	0.831
ATOS1	0.784
ATOS2	0.788
ATOS3	0.800
Behaviour intention		0.800	0.798
BIN1	0.798
BIN2	0.761
BIN3	0.708

Table 4. AVE & discriminant validity.

	AVE	BIN	ATOS	HCS	BCCP
BIN	0.572	0.757
ATOS	0.625	0.677	0.791
HCS	0.521	0.569	0.704	0.722
BCCP	0.512	0.509	0.516	0.487	0.716

Note: BIN-behaviour intention, ATOS-attitude towards online shopping, HCS-health consciousness, BCCP-behaviour control in Covid-19 protocol.

Since the discriminant validity is assessed on the basis of the square root of AVE and it should be greater than the variance shared/correlation between latent constructs in the model (Fornell & Larcker, 1981). Therefore, this value is highlighted/bold in the table.

Table 5. Results of hypothesis testing.

Hypothesis	Independent Variable	Path	Dependent variable	Estimate (β)	S.E	C.R	P	Results
H1	HCS	→	ATOS	0.646	.107	7.030	***	Accepted
H2	HCS	→	BIN	0.108	.109	0.971	.332	Rejected
H3	BCCP	→	ATOS	0.177	.074	2.351	.019	Accepted
H4	BCCP	→	BIN	0.196	.065	2.468	.014	Accepted
H5	ATOS	→	BIN	0.496	.095	4.377	***	Accepted

* p < 0.05.

** p < 0.01.

*** p < 0.001.

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