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

Kashyap, Anil Kumar; Kumar, Ajay Article Application of theory of planned behaviour in determining attitude and to measure purchase intention under the fear of Covid-19 Cogent Business & Management Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Kashyap, Anil Kumar; Kumar, Ajay (2024) : Application of theory of planned behaviour in determining attitude and to measure purchase intention under the fear of Covid-19, Cogent Business & Management, ISSN 2331-1975, Taylor & Francis, Abingdon, Vol. 11, Iss. 1, pp. 1-11, https://doi.org/10.1080/23311975.2024.2376108 This Version is available at: https://hdl.handle.net/10419/326419 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Cogent Business & Management ISSN: 2331-1975 (Online) Journal homepage: www.tandfonline.com/journals/oabm20 Application of theory of planned behaviour in determining attitude and to measure purchase intention under the fear of Covid-19 Anil Kumar Kashyap & Ajay Kumar To cite this article: Anil Kumar Kashyap & Ajay Kumar (2024) Application of theory of planned behaviour in determining attitude and to measure purchase intention under the fear of Covid-19, Cogent Business & Management, 11:1, 2376108, DOI: 10.1080/23311975.2024.2376108 To link to this article: https://doi.org/10.1080/23311975.2024.2376108 © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group Published online: 12 Jul 2024. Submit your article to this journal Article views: 1213 View related articles View Crossmark data Citing articles: 3 View citing articles Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=oabm20 Marketing | research article Cogent Business & ManageMent 2024, VoL. 11, no. 1, 2376108 Application of theory of planned behaviour in determining attitude and to measure purchase intention under the fear of Covid-19 anil kumar kashyapa and ajay kumarb aDepartment of HPKV Business school, Central university of Himachal Pradesh, Dharamshala, india; bDepartment of Management, sharda school of Business studies, sharda university, greater noida, uttar Pradesh, india ABSTRACT this study attempts to examine the role of health consciousness and covid-19 protocol on attitude towards online shopping followed by its effect on purchase intention. the framework of the study is derived from tPB theory. Data for the study are collected from the online shoppers during the covid-19 outbreak. structural equation modelling (seM) is used to test the relationship and to predict shopping behaviour. the results report that health consciousness and covid-19 protocol have shown significant and positive effect on attitude towards online shopping. Further, attitude and covid-19 are found the predictor of behaviour intention to purchase online. however, health consciousness has shown insignificant effect on behaviour intention. the outcome of the study may help retailers to understand consumer shopping behaviour and the changes occurred during covid-19 outbreak. Findings may help retailers to rationalize their resources as per the change in customer preference. 1. Introduction it is evident that covid-19 is responsible for the significant change in behaviour. Whether to avoid the risk of infection or due to lockdown restriction, behavioural changes were constantly observed. the longetivity of covid-19 made some of these changes stable. it further stressed out business activities but also flourished opportunities for new ideas in business. researchers across the World researched the impact of changes witnessed due to covid-19 outbreak (Mehta et al., 2020; Pham et al., 2020). in this series the impact of covid-19 on consumer behaviour is also addressed (Zwanka & Buff, 2021). study confirmed that covid-19 accelerated the shift towards a more digital world and triggered changes in online shopping behaviours that are likely to have lasting effects (UnctaD, 2020). a surge in number of customers shopping online and first time users are observed during the pandemic (halan, 2020). Under these circumstances examining the validity of theory of planned behaviour (tPB) make sense. this theory advocates that behavioural achievement or changes depends on both motivation (intention) and ability (behavioural control). ajzen (1991) stated that intention to perform different kind of behaviour can be predicted with high accuracy from attitudes toward the behaviour, subjective norms, and perceived behavioural control; and these intentions, together with perceptions of behavioural control, account for considerable variance in actual behaviour. the outbreaks of covid-19 produce the circumstances where performing normal shopping behaviour was not possible. Fear to spread of virus, restrictions imposed, mandate of covid-19 protocol including social distancing norms, and wearing a mask are the factors responsible for change in shopping behaviour. lockdown and curfew which lead closure of markets and shop are also responsible to shift shopping © 2024 the author(s). Published by informa uK Limited, trading as taylor & Francis group CONTACT anil Kumar Kashyap [email protected]om Department of HPKV Business school, Central university of Himachal Pradesh, Dharamshala 176215, india. this article has been corrected with minor changes. these changes do not impact the academic content of the article. https://doi.org/10.1080/23311975.2024.2376108 this is an open access article distributed under the terms of the Creative Commons attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. the terms on which this article has been published allow the posting of the accepted Manuscript in a repository by the author(s) or with their consent. ARTICLE HISTORY received 29 January 2022 revised 15 May 2024 accepted 1 July 2024 KEYWORDS tPB; purchase intention; covid-19; e-commerce; health consciousness; customer preference; online shopping REVIEWING EDITOR huifen (helen) cai, Middlesex University Business school, United kingdom SUBJECTS health & Development; Business, Management and accounting; industry & industrial studies 2 a. k. kashYaP anD a. kUMar physical to online. recently conducted studies concluded that health concerns positively increases the likelihood of ordering online during the pandemic and post pandemic (Unnikrishnan & Figliozzi, 2021). also the study in the context of Malaysian retail industry by naseri (2021) highlighted the challenges of shopping during pandemic and discussed the online shopping activities during covid-19 outbreak. therefore it can be assured that to ensure the safety and to avoid the breach of social distancing or to follow the covid-19 protocol customers preferred online shopping during the outbreak. the proposed study is an effort to examine the application of theory of planned behaviour in measuring the changes in shopping behaviour during covid-19 outbreak. First, the study explained the conceptual framework of tPB (theory of Planned Behaviour) followed by its components such as attitude and behaviour intention and perceived control. later, it explains covid-19 related factors responsible for the changes in attitude and behavioural intentions and accountable to form perceived control. these factors are termed as health consciousness and covid-19 protocol. Online shopping behaviour, purchase intention and shopping attitude towards online are extensively researched in the pre covid era or in normal circumstance. But, because of intense impact of covid-19 on behavioural aspects it is significant to explore behavioural change and also to identify the factors responsible for these changes. as per tPB, any action a person takes is guided by three types of considerations: behavioral beliefs, normative beliefs and control beliefs. as of now tPB (theory of planned behavior) is mostly applied to predict health behavior (conner & norman, 1994). however, its application to determine the change in consumer behavior is rarely available in literature. to validate the application of tPB, the proposed study aims to examine the influence of health consciousness and covid-19 protocol on attitude and its influence on behaviour intention to purchase. the outcome of the study may help retailers to understand consumer shopping behaviour and respective changes during covid-19 outbreak. Findings may help retailers to rationalize their resources as per the change in customer preference. confirmatory factor analysis is used to predict shopping behaviour followed by aMOs to validate the model. Data for the study is collected from the online shoppers during covid-19 outbreak. items used in the instrument are extracted from the previous studies and wherever required a little modification are made. 2. Conceptual framework and hypothesis development 2.1. Theory of planned behaviour (TPB) theory of planned behaviour (tPB) is proposed by ajzen (1991) to address the relationship between attitude, subjective norm, perceived behaviour control, intention and behaviour. tPB is the extension of theory of reasoned action developed by ajzen and Fishbein (1977). tra carried some limitations in dealing voluntary behaviour of consumers. however, both the theories predict the behaviour of consumers. But tPB is more likely used in prediction of consumer behaviour (ahmmadi et al., 2021; chen & tung, 2014). in online shopping tPB and its application are discussed in various studies (akar, 2021; crespo & rodríguez del Bosque, 2008; ha etal., 2019; hsu etal., 2006; rehman etal., 2019). lim etal. (2016) reported subjective norm and perceived usefulness as the significant influencers to the online purchase intention Online shopping attitude is driven by the concept of utility, accessibility, convenience, perceived usefulness, perceived price and information etc. While predicting change in behavioural using tPB model attitude, subjective norms and behaviour control are the major components. During the outbreak of covid-19 several factors emerged in support of online shopping. a noteworthy change in consumer perception for online shopping is thoroughly observed during the spread of corona virus. it may assume that these changes followed the pattern of theory of planned behaviour where online shopping was influenced by behavioural beliefs (beliefs about the probable consequences of the practiced behaviour), normative beliefs (beliefs about the normative expectations of other people), and control beliefs (beliefs about the presence of factors that may enable or obstruct the performance of the behaviour. During the outbreak of covid-19 shopping in usual practice was not possible. there was a tangible risk of getting infected in the usual way of shopping. therefore, behavioural belief was affected during the pandemic. as far as normative belief is concerned previous study argued that subjective norm has direct relationship with online purchase behaviour (george, 2004). in online shopping context, subjective cOgent BUsiness & ManageMent 3 norms refer to consumer perception regarding the use of online shopping by the opinions of the referent group (e.g., friends or colleagues) (lin, 2007, p. 434). in the stressed situation of pandemic consumer perception for online shopping was persuaded by the opinion of other users (friends and colleagues). however, the change in consumer perception was apparently influenced by the utilitarian aspects of online shopping. in case of control beliefs there were number of factors present during the covid-19 pandemic especially the covid protocol (social distancing, wearing a mask, frequent hand washing etc.). these beliefs enabled online shopping and hindered the physical shopping (Figure 1). 2.2. Health consciousness, attitude and behaviour intention the lockdown came up with shop closure, restrictions on person-to-person contact and public gathering significantly influenced consumers purchase liberty (addo etal., 2020). Online shopping was considered more useful due to its perceived benefits and utility. in pandemic researcher stressed on safety practice which muted consumer buying behaviour (sehgal et al., 2021). customer concerns about health and safety emerged as the prime motive to buy online rather than the monetary and utilitarian benefits they derived from online shopping. therefore, it is evident that online shopping in pandemic is not only driven by its conventional benefits but also motivated by the circumstantial factors. customer preference to reduce the health risk is identified as one of the reasons to shift towards online shopping (ivanović & antonijević, 2020). change in consumer preference due to pandemic associated risk is stated in other study too (kulkarni et al., 2020). Under the fear of spread of virus, hygiene, health and safety are anticipated as new shopping standard (leggett, 2021). Online retailers took over the lead in executing and promoting these standards. contactless delivery, sanitization of each consignment and promoting covid-19 protocol are some of the initiatives which gave an advantage to the online retailers. customer concern about health and safety termed as customer pandemic concern had an impact on their purchase intentions (akar, 2021). study also stated that health concern and anxiety might impact a customer’s online purchase intention with the occurrence and spread of covid-19 (chan et al., 2020). therefore, customers started following covid preventative strategies in their shopping. Online shopping emerged as one of such strategy. study confirmed that perceived potential threat to life (death threat) is positively related to online purchase intention (Öztürk, 2020). h1: health consciousness has a significant positive effect on customers’ online shopping attitude. h2: health consciousness has a significant positive effect on customers’ online behaviour intentions. 2.3. Behaviour control in Covid-19 protocol, attitude, and behaviour intention Based on theory of planned behaviour (tPB), perceived behaviour control is defined as an individual’s confidence that he or she is capable of performing the behaviour (ajzen, 1991). it has two aspects first, how much a person has control over behaviour and the second, how confident a person feels about being able to perform or not to perform the behaviour. Online shopping during pandemic exerts on Figure 1. theory of Planned Behaviour (tPB). Source: ajzen (1991). 4 a. k. kashYaP anD a. kUMar shopping behaviour without breaking covid-19 norms or protocol such as social distancing, bearing mask, and stay at home etc. Further, it allows shoppers to control their shopping behaviour. the more control an individual express to follow covid protocol and making purchase online, more likely he or she will do online shopping. in previous studies, behavioural control in online context is addressed as customers’ perceived ease (Pavlou & Fygenson, 2006). But as per this study, e-shopping platform enable customer to control shopping in covid-19 protocol. With the occurrence and spread of covid-19, customers perceived online shopping an easy way to stay away from physical stores and places to avoid crowd to decrease the possibility of virus infection (Öztürk, 2020). h3: covid-19 protocol has a significant positive effect on customers’ attitude towards online shopping. h4: covid-19 protocol has a significant positive effect on customers’ online behaviour intentions. 2.4. Attitude and behaviour intention consumer attitude is “a psychological tendency expressed by evaluating a particular entity with some degree of favour or disfavour” (eagly & chaiken, 1993, p. 1). initially, chen and Wells (1999) conceptualised attitude towards a web site. attitude captures the degree to which an individual may evaluate behaviour as favourable or unfavourable. attitude is formed by the beliefs held towards an object by the individual (cited al-Debei etal., 2015 study after checking belief concept). as per ajzen and Fishbein (1980), in theory of planned behaviour, attitude is a key predictor of behavioural adoption intention. generally, online shopping attitude is determined based on perceived usefulness, perceived service quality, perceived trust, perceived ease of use, product offer and customized information (atchariyachanvanich et al., 2008; ha et al., 2010; teo, 2002). Perceived advantages are found the key predictors of consumer attitude toward online shopping (akroush & al-Debei, 2015). it means if shopping website is able to offer benefits, it results in forming attitude. the impact of perceived benefits on attitude is stated in the study (arora & aggarwal, 2018). also, attitude’s effect on behaviour intention is reported significantly (hsu etal., 2014; Jayawardhena, 2004) and emerged as a direct predicator of e-shopping behaviour (Jayawardhena, 2004) (Figure 2). h5: attitude towards online shopping has a significant positive effect on customers’ behaviour intentions to purchase online. 3. Research methodology 3.1. Sampling design and procedure a convenience sampling technique was employed to collect the data from targeted population. the online survey was conducted. the target population for the study was online shopper who was involved in online shopping during covid-19 pandemic. Whether they were involved in online shopping, was ensured by asking a filtering question “have you ever done shopping online during covid-19 pandemic” Figure 2. Proposed research model based tPB theory. cOgent BUsiness & ManageMent 5 at the beginning of the survey questionnaire. When they opted yes, they were directed to continue with the remaining questions of the survey questionnaire. the sample elements were chosen because they are believed to be representatives of online shoppers. the link of the questionnaire was developed over google form and shared on social media (Facebook, Whatsapp) and e-mails. in recent studies, collecting a sample through social media is seen (alhaimer, 2021). also, data collection through social media is quite reasonable during covid-19 because of safety and health concerns. the sample size in this study is calculated as per hair etal. (2009) recommendations. 3.2. Survey instrument the items measuring the attitude, health consciousness, behaviour control in covid-19 protocol, and behaviour intention are extracted from the literature review. the items to define health consciousness are adapted from Michaelidou and hassan (2008), shah et al. (2021) and Pu et al. (2021), items for attitude toward online shopping from al-Debei et al. (2015) and for behaviour intention towards online shopping from akar (2021) and tarun (2011). single item on behaviour control in covid-19 protocol adapted from segal and 2 items are self-developed. the adapted items were modified in indian context (see table 1). all items were measured on five-point likert-type of scale (ranging from 5 “strongly agree” to 1 “strongly disagree). also, questions about respondent’s demographic characteristics such as gender, age, family income, occupation, online shopping frequency and family size were asked. 4. Data analysis and results 4.1. Demographic profile of the respondents table 2 exhibits the respondents’ demographic characteristics. it shows that 57.7% respondents are male and 42.3% are female. Data in age category shows that most of the respondents are young age range upto 20 and 21-35 year. related to family income, more than 50% respondents come family income range Up to rs. 25,000 and rs. 25,001-rs. 50,000 per month. the next family income group ranged rs.1,00,00 and above represents 24.20%. Data related to education shows that 48.50% respondents are post graduate, followed by 42.00% graduate, 8.20% high school/intermediate (10th/10th +2) and 1.4% are doctorate. Variation in online shopping frequency can be seen in table 2. Most of the shoppers do shopping normally 50%. 4.2. Measurement model confirmatory factor analysis (cFa) is used to know whether the construct within a proposed model is fit or not to produce desire results. the model fit is determined based on the indices such as gFi, cFi, rMsea, tFi and nFi. also, χ2, chi-square/df. in the current study, value of cMin = 106.966, df = 58, p = 0.000, cMin/DF = 1.844, rMsea = 0.054 gFi = 0.950, agFi = 0.921, iFi = 0.969, tli = 0.958, cFi = 0.969, and nFi = 0.935, rMr = 0.031, are under the accepted criteria. thus, based on values the model is fits the data reasonably well. Further, the reliability and validity of the measurement model is also examined. Both, composite reliability and cronbach alpha reliability are calculated and reported in table 3. all constructs’ composite reliability and cronbach’s alpha reliability are above than the threshold value (>0.7). also, the discriminant validity is assessed on the basis of the square root of aVe should be greater than the variance shared/correlation between latent constructs in the model (Fornell & larcker, 1981). the results of discriminant validity and the value of aVe are given in table 4, which indicates the presence of discriminant validity (Figure 3). 4.3. Structural equation modelling (SEM) and hypothesis testing the structural equation modelling using amos 24 software was run to test the proposed research model and hypothesised relationship (see Figure 1) and the results of tested hypothesis are exhibited in table 5. Five research hypotheses had been developed. the value of model fit indicates for a structural model 6 a. k. kashYaP anD a. kUMar 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 cOgent BUsiness & ManageMent 7 are χ2 = 106.966, p = 0.000, df = 58, chi-square/degree of freedom = 1.844, rMsea = 0.054, gFi = 0.950, agFi = 0.921, iFi = 0.967, cFi = 0.969, tli = 0.958, rMr = 0.031. these values seem to be a good fit for structural model. after testing model fit, we examined the proposed relationships. in the structural equation analysis, except hypothesis h2, all hypotheses are accepted. the hypothesis h1 health consciousness (β = 0.646, t = 7.030) has shown a positive significant impact on attitude towards online shopping at <0.001. hypothesis h3, government protocol (β = 0.177, t = 2.351) has shown significant positive impact on attitude towards online shopping at <0.05, the hypothesis h4, government protocol (β = 0.196, t = 2.468) has positive significant impact on behaviour intention towards online shopping at <0.05, hypothesis h5, attitude (β = 0.496, t = 4.377) has positive significant impact on behaviour intention towards online shopping at <0.001. the hypothesis h2, developed to measure the impact of health 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. Figure 3. structural model.