Brand image’s impression on impulsive buying of healthcare products

The COVID-19 pandemic is a disease outbreak that makes almost everyone unable to travel freely, especially in Indonesia. Shopee is one of the marketplaces used in this research. This study aims to analyse the impression of Shopee's brand image moderated by content marketing and its impact on impulsive buying of health products during the current pandemic. Data analysis used IBM SPSS Statistics 26 and involved 119 samples using survey methods and data collection instruments in questionnaires. The implication of this research shows that optimising content marketing techniques across various digital channels is a top priority to boost impulse buying, indirectly also improving brand image.


INTRODUCTION
Mona et al. (2020) state that brand image can positively contribute to stimulating impulse buying behaviour, starting from forming a brand image that is well embedded in consumers' minds to make unexpected purchases when shopping. Che Hui Lien (2015) added that the research results revealed that brand image is one of the critical factors influencing a product's purchase. Novan (Andrianto & Fianto, 2020) also stated in his research using a brand image as an intervening variable between word of mouth, perceived price, service quality and purchasing decisions. His research proves that brand image has a dominant positive influence on purchasing decisions between the three independent variables. John M. T. Balmer et al. (2020), in their research related to logistics companies, stated that the brand image of an industrial company has a positive influence and has a beneficial impact on premium pricing and brand retention. In their research, Karim et al. (2020) stated that it is not always easy to put forward the importance of brand image using only one way, namely advertising. Several other factors strengthen the brand image, for example, the suitability of the fragrance from the diffuser with the advertised brand image. In their research related to social mission, Yi-Hsin Lin et al. (2021), in their research related to social mission, also stated that the information and value philosophy conveyed by the social mission can be of value to customers in addition to the brand image of a product. In addition, like any business in the industry, social enterprises must carefully employ customers who have a positive relationship with their product (brand image) and service philosophy in the service space to influence consumer experience and repurchase intentions positively.
This research examines the direct influence of Shopee's Brand Image to encourage impulse buying of health products and reviews the mediating function of content marketing techniques between the two variables. The term health, as the central issue of this research, has many versions of definition. There are various views on the definition of health. It started in 1948 when WHO started defining the term health (Bok, 2016). At that time, the definition of health caused many controversies because it invited the medicalisation of a large part of human existence and the abuse of state power in the name of health promotion (Arcaya et al., 2015;Gessert et al., 2015).
Health is an essential thing in promotional action that can be said not only in the absence of health and disease, especially in physical and mental health (Felman, 2020;Galderisi et al., 2017), and soul due to positive factors. Simple examples include adequate feeding, housing and training. Others consider health to be the basis of all joys of life. Many experts provide opinions on the definition of health (Bircher, 2005;Leonardi, 2018;Lerner, 2019), one of which came to the fore by Daniel Callahan (1973). He mentioned health as a condition for someone who has experienced well-being and integrity of body and mind. Furthermore, this condition can achieve various vital goals, then function in a general social and occupational context. Health can also be defined as the absence of physical pain, suffering, and dangerous diseases supported by a clean environment and sanitation (Liem et al., 2019).In order to support the creation of health, several resources are needed in the health sector, one of which is in the form of health products. Nowadays, health products are traditionally sold in pharmacies and other health stores but are sold online. Those are mainly done through online applications such as Shopee, Tokopedia, and many more. At the end of December 2019, a new type of disease known as Coronavirus or COVID-19 was discovered in Wuhan, China. In Indonesia, COVID-19 (Sohrabi et al., 2020;Tsang et al., 2020) has only started infecting Indonesian society since January 2020.
COVID-19 is a highly contagious and pathogenic viral infection caused by acute respiratory syndrome (Shereen et al., 2020;Zhong et al., 2020). Based on Herdiana (2020), the rapid spread of the disease has caused the Indonesian government to adopt policies to limit public interaction, including the PSBB or in Indonesian as the abbreviation of Pembatasan Sosial Berskala Besar (Large-Scale Social Restrictions). The impact of the PSBB (Andriani, 2020;Saputra & Salma, 2020) caused the Indonesian people to carry out trading activities through online applications, including buying health products. Various trade-based online applications (e-commerce) are prevalent in Indonesia (See Figure  1). One that is unique is Shopee; since its launch in 2015, various innovations have been added to pamper its consumers (Harun & Ayu Salmah, 2020;Latifah et al., 2020). Two of them are Shopee Coin and Shopee Pay, which were launched in 2020. In contrast to its competitors, which are dominated by green and blue, Shopee comes with a striking orange colour (Japarianto & Adelia, 2020). Source: Tempo.Co (Christy, 2020)  Top 10 E-Commerce in Indonesia Q1 2020 (Per Million Clicks) Shopee conveys a guarantee of the quality of a product, whether a brand is good or not (Marta & Septyana, 2015;Nissi & Budiono, 2019) helps consumers to identify valuable products and provide specific experiences for a product to be of interest (Kotler & Armstrong, 2018). Consumers will always buy products with the same brand if they get the same benefits and quality at every purchase (Schiffman & Wisenblit, 2019). All that consumers will obtain from the brand image (Amilia, 2017;Gandakusumah & Marta, 2021;Lien et al., 2015b;Shabbir et al., 2017) which is displayed, which is not only determined by how to give a good name to a product but is needed how to introduce the product so that it becomes an exciting experience for consumers in forming a perception of a product .
Content marketing also has a significant influence on increasing consumer attractiveness to a product (Kotler et al., 2019;Lieb, 2012). Joel Jarvinen (2016) investigated organisational processes for developing valuable and timely content to meet customer needs and integrating content marketing with B2B sales processes and discovered the use of marketing automation to generate high-quality sales leads through behaviour and content personalisation. Nur Syakirah Ahmad (2016) also investigated the implications of content marketing on the health of a product. He proved that this element is essential for companies to consider in encouraging good brand sustainability. At the same time, Wen Lin Wang et al. (2019) and Johannes Muller et al.
(2019) also stated that Content marketing is one of the product marketing strategies by creating content that can attract targeted consumers and shape them into customers.
The tendency to purchase from consumers occurs when individuals experience a strong urge to make buying, so that consumers no longer reason in their buying, especially when consumers see advertisements (Marta & Septyana, 2015;Sasongko & Marta, 2018) or the brand of a product (Jacqueline & Kusniadji, 2019). The indicators used in this buying trend can be seen from consumer interest in a product brand, confidence in buying at affordable product prices, and easily accessible product purchase locations.
Offering easy access to health products as preventive measures also triggers impulsive buying, stimulated by the impression of the brand image and the marketing content created by the brand manager. Therefore, this research will be dedicated to answering the hypothesis of the impression of Shopee's Brand Image through content marketing that impacts impulsive buying of health products (H1). On the other hand, the research results can also show that impulse buying of health products is not influenced by Shopee Brand Image content marketing (H0).

METHODOLOGY
In analysing the results of hypothesis testing in this study where the hypothesis used in this research is how the influence of brand image on impulse buying of health products, the researcher relies on a positivistic paradigm to link the influence of the Shopee Brand Image through content marketing in its online applications to consumer impulse buying. This study rests on using quantitative methods (Lo et al., 2020;Strijker et al., 2020) with the classic assumption test with IBM SPSS Statistics 26 software. This research is a quantitative study using a questionnaire as a research instrument. Data collection in this study was carried out using power analysis (Memon et al., 2020).
This analytical method allows the minimum number of samples to be used in this study. This method requires information related to power, effect size and significance level to calculate the minimum sample size. Power is the ability of statistical calculations to correctly reject the null hypothesis when it is false, which in this research, the power value is 0.95. Effect size measures the magnitude of the effect that the individual independent variable has on the dependent variable, which in this research, the value of the effect size is 0.15. The significance level relates to the probability of rejecting the null hypothesis, which in this study is worth 0.05. Researchers use the G*Power application as an application that applies power analysis in its application. Based on the G*Power application calculation, 119 is obtained as the minimum sample size used in this research. The sample in this research was taken randomly from Shopee users in Jakarta who made multi-product buying in the last few years. The population of this study was all Shopee users in Indonesia, both in Java and outside Java.
The data analysis technique used is the inferential quantitative analysis technique by performing a classical assumption test. The classical assumption test used is the Normality Test, Multicollinearity Test, and Heteroscedasticity Test (Charpentier et al., 2019).

RESULTS AND DISCUSSION
Based on the research test results, it was found that there were respondents who were processed and who entered, which then carried out the feasibility of screening. A total of 66 people were male respondents, and as many as 53 people were female respondents. It shows that in this study, the majority came from male Shopee users. The age distribution range of respondents in this study was 105 people aged 17-25 years, eight people aged 26-35 years, four people aged 36-45 years, one person aged 46-55 years, and 56-65 years old. It explains that in this study, the majority came from Shopee users aged 17-25 years.

Measuring Variable Validity
Items on each question in the questionnaire in this study will be tested for validity before testing the hypothesis. Table 1 summarises the validity test results of the brand image variable represented by the BI code, the CM code represents the content marketing variable, and the IB code represents the impulsive buying variable from the Shopee Brand. In order to test the reliability of each variable in this study, it was tested using the Cronbach's Alpha value above 0.6 for the brand image variable. It can be seen in table 2 that the Cronbach's Alpha value (Amirrudin et al., 2020)is 0.913, which can be concluded that all statement items to measure the brand image variable are declared to have good reliability. The content marketing variable can be seen in Table 2, and it can be seen that the Cronbach's Alpha value is 0.906, which can be concluded that all statement items to measure the content marketing variable are declared to have good reliability. The impulse buying variable can be seen in Table 2; it can be seen that the Cronbach's Alpha value is 0.920, which can be concluded that all statement items to measure the impulse buying variable are stated to have good reliability.

Testing Data Distribution
In order to determine the type of data distribution, the researcher involved a series of classical assumption tests, which were carried out with three tests, namely the normality test, multicollinearity, and heteroscedasticity. The normality test in this research was carried out with the Kolmogorov-Smirnov test. The normality test was tested with the brand image as the independent variable and content marketing as the dependent variable Based on the Normality Test using the Kolmogorov-Smirnov, which can be seen in Table 3, it can be seen that the value of the normality test results based on the primary data obtained by the researcher is Asymp. Sig. (2-tailed) 0.200> 0.05. It indicates that the results of the normality test are normally distributed. The multicollinearity test aims to test the correlation between the independent variables in the found regression model. This test is carried out using VIF with the criteria; if the VIF of an independent variable is <10, it can be concluded that the independent variable does not occur multicollinearity. This test is also carried out using Tolerance with the criteria; if the Tolerance of an independent variable is> 0.1, it can be concluded that the independent variable is no multicollinearity. Based on Table 4, the results of the classical assumption test show that there are no independent variables that have a tolerance value less than 0.10, and there are also no independent variables that have a VIF value of more than 10. Thus, it can be concluded that there is no multicollinearity symptom between the independent variables in the regression model. The heteroscedasticity test in this study was conducted to determine whether there is an inequality of variants from the residuals of one observation to another in the Spearman Rank regression model. This heteroscedasticity test uses a significance value (Sig.) Which must be greater than 0.05 so that there are no symptoms of heteroscedasticity in the regression model.
If seen from Table 5, the significance value (Sig.) The Brand Image variable is 0.844> 0.05. It can be concluded that there are no symptoms of heteroscedasticity in the regression model.

Confirmation of the Preliminary Alleged Research
Hypothesis testing is divided into three tests, namely the coefficient of determination (R2), simultaneous test (F-Test), and partial test (T-Test). Multiple linear regression analysis is a regression analysis that explains the relationship between the dependent variable and factors that affect more than one independent variable. The use of this method aims to measure the presence of more than two independent variables against one dependent variable, where the independent variables in this study are Brand Image (BI), Content Marketing (CM), and the dependent variable in this study is Impulse Buying (IB). Based on predetermined independent variables and dependent variables, the multiple regression equation models used to test the hypothesis is as follows: Model 1: CM = α + β1BI + e Model 2: IB = α + β1CM + e Note: BI = Brand Image CM = Content Marketing IB = Impulse Buying Based on the multiple linear regression equation models above, the regression coefficient test was carried out. Multiple linear regression analysis testing using IBM SPSS Statistic 26 can be seen in Table 7. Based on Table 7, the regression equation for model 1 is CM = 9,232 + 0,603BI + e The following meanings are obtained from the regression equation results: the constant value obtained shows a value of 9.232. It means that if BI is assumed to be zero, then the CM will be 9.232 and The value of the BI coefficient is obtained at 0.603. It means that if the BI variable increases by one point, it will cause an increase in CM of 0.603. Table 7, the regression equation for model 2 is IB = 1.626 + 0.399CM + e

Based on
The following meanings are obtained from the regression equation results above, that the constant value obtained shows a value of 1.626. It means that if CM is assumed to be zero, then the IB size is 1.626 and The value of the CM coefficient is 0.399. It means that if the CM variable has increased by one point, it will cause an increase in IB by 0.399. The Adjusted R2 in Table 8 show that in model 1, the Adjusted R2 value is 0.505 or 50.5%. It means that the BI variable influences 50.5% on the CM variable, while the remaining 49.5% is influenced by other variables that are not modelled in this study.
The Adjusted R2 in Table 8 show that in model 2, the Adjusted R2 value is 0.808 or 80.8%. It means that the CM variable influences 80.8% on the IB variable, while the remaining 19.2% is influenced by other variables that are not modelled in this study.
The F test was conducted to determine the significance of the independent variables on the dependent variable simultaneously. The independent variable is statistically stated to affect the dependent variable simultaneously if the probability value is significant <0.05.  Table 9 shows the significant value in regression model 1, which is equal to 0.000, which indicates that the significance value is less than 0.05. So it can be concluded that regression model 1 is suitable for use. Model 1 shows that the BI variable simultaneously affects the CM variable. Table 9 shows the significant value in regression model 2, which is equal to 0.000, which indicates that the significance value is less than 0.05. So it can be concluded that regression model 2 is feasible to use. Model 2 shows that the CM variable simultaneously affects the IB variable.
The t-test is carried out to show the effect of one independent variable individually in explaining the variation of the dependent variable (Ghozali, 2011). The basis for the decision is that if the significance is <0.05, then H0 is rejected, and H1 is accepted, which means that the independent variable influences the dependent variable.  Table 10 shows a significance value of 0.000, this value is less than 0.05, so the results are said to be significant. Thus, there is an influence between the BI variable and the CM variable.
H2: there is an effect of CM on IB H0: no influence CM to IB The CM variable in Table 10 shows a significance value of 0.000, this value is less than 0.05, so the results are significant. Thus, there is an influence between the CM variable and the IB variable Path analysis is used to examine the effect of intervening variables and analyse the pattern of relationships between variables to know the direct or indirect effect of a set of independent (exogenous) variables on the dependent (endogenous) variable. In this study, to prove the effect of mediation by the CM variable, it was proven by multiplying the unstandardised coefficient between variables, provided that the results in both regression models were significant. When seen in Table 11, the obtained figures indirect influence (0.2680) greater than 0.184 difference in the figures from direct influence (0.084). Researchers can state that H1 is acceptable, while H0 is rejected that brand image influences impulse buying mediated by content marketing. Based on the research results, it can be seen that content marketing has a more significant influence on impulsive buying behaviour of 0.376. In line with the thoughts of Nur Syakirah Ahmad et al. (2016), it is just that the research conducted by Nur Syakirah Ahmad was in the context of using social media in general to implement content marketing and in typical situations. While in this study, the media used to implement content marketing is a television media where Shopee assists the government in making it easier for Indonesian people to buy health products during the COVID-19 pandemic situation in Indonesia.
Furthermore, the finding of the effect between Shopee's content marketing and Impulse Buying is more significant than the influence of Shopee's brand image with Impulse Buying, which is only 0.084. Referring to the findings of John M.T. Balmer (2020) et al., which states that the brand image of a logistics industry company in China has a positive influence (Amilia, 2017;Lien et al., 2015a;Marta & Septyana, 2015;Menayang & Marta, 2020) and has a beneficial impact on premium pricing and brand retention. Meanwhile, in this study, the brand image that is used as the object of research is Shopee, whose brand image does not have a significant influence where the situation and conditions that occur when this research is carried out are the COVID-19 pandemic condition and the subsequent difference is the difference in the country where the country is the research location. John is from China, while the location of this research is in Indonesia.
Moreover, The influence of Shopee's brand image mediated by content marketing in this study is still less influential on impulsive buying behaviour, which is 0.2680. It is in line with the thoughts of Karim et al. (2020). It is just that the research conducted by Karim uses a different research object, namely a diffuser product, while this research is a health product.
The implications of the findings of this study indicate that the influence of brand image in the research of Che Hui Lien (Lien et al.,