Impact of COVID 19 on Buying Pattern

IMPACT OF MENTAL HEALTH, EMOTIONAL WELLBEING ON CONSUMER
BUYING PATTERN -A POST COVID-19 ANALYSIS
Isha Aggarwal, Radhika Rani Kashyap, Ritu Pandey, Dr. Vishwas Gupta
Mittal school of business, Lovely Professional University, Phagwara, Punjab, India.
Abstract
The COVID-19 pandemic has impacted the lives of many people across the globe and India has
been severely affected with 2nd
highest number of COVID cases in world. In this paper, we
examine the impact of mental health, emotional wellbeing on consumer buying pattern-a post
covid19 analysis in India (4th-10th Jan 2021). We took sample size of 156 people and divided 30
variables into 5 major factors Social Impact, Psychological Impact, Mental Health, Consumer
Buying Pattern and Emotional Wellbeing. We observed that Social impact has significant impact or
positively associated with Emotional well-being and Psychological Impact but insignificant impact
on Mental Health and Consumer Buying Pattern. Psychological Impact has significant impact on
Mental Health, Social Impact and Consumer Buying Pattern. Emotional Wellbeing too significantly
impacted Consumer Buying Pattern. We concluded that COVID19 has impacted the Mental Health,
Emotional Wellbeing and Consumer Buying Pattern of Indian Consumers and Mental Health and
Emotional Well-being act as a mediator to the relationship between Impact of COVID 19 on
consumer buying pattern.
Keywords
COVID19, Mental Health, Emotional Well-being, Consumer Buying Pattern, Social impact,
Psychological Impact
* Corresponding author. E-mail addresses:
isha.aggarwal100@gmail.com, Radhika.kashyap786@gmail.com, ritupandey191198@gmail.com
Journal of Interdisciplinary Cycle Research
Volume XIII, Issue II, February/2021
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1. INTRODUCTION:
Mental Health is level of psychological well-being or an absence of mental illness means someone who
functioning at a satisfactory level of behavioral and emotional adjustment (Princeton University,
2014). Mental Health is the “ability to adopt and self- manage” (Huber et al, 2011). According to
WHO, mental health means perceived self-efficacy, subjective well-being, autonomy, competence,
self- actualization, inter-generational dependence and self-actualization of one's intellectual and
emotional potential, among others. Mental Health include an individual’s ability to enjoy life and
create a balance between life activities and efforts to achieve psychological resilience (Snyder, C. R.
et. al., 2011).
Mental health problems can be biological like brain chemistry and genes or because of life
experiences like abuse, depression, anxiety, stress (Biddle, S. J., Ciaccioni, S., Thomas, G., &
Vergeer, I., 2019), due to loss of sleep, family size, gender, religion, occupation, marital status
(Ahmad, A., Rahman, I., & Agarwal, M., 2020), alcohol related disorders (Mortensen, E. L.,
Sørensen, H. J., Jensen, H. H., Reinisch, J. M., & Mednick, S. A., 2005), financial losses(Rossi, R.,
Socci, V., Talevi, D., Mensi, S., Niolu, C., Pacitti, F., ... & Di Lorenzo, G., 2020), age, employment
status, annual household income, ethnic minorities (Pierce, M., Hope, H., Ford, T., Hatch, S., Hotopf,
M., John, A., ... & Abel, K. M., 2020), region of residence (Wang, C., Pan, R., Wan, X., Tan, Y., Xu,
L., McIntyre, R. S., ... & Ho, C., 2020), Cannabis or drug dependence, panic disorder (Koenen, K. C.,
Moffitt, T. E., Roberts, A. L., Martin, L. T., Kubzansky, L., Harrington, H., ... & Caspi, A., 2009) and
mental health related disorders such as clinical depression (depresses mood, loss of interest in
activities, significant impairment in daily life), bipolar disorder (related to mood swings from
depressive lows to manic highs), anxiety disorder (feeling of worry, fear in daily activities), dementia
(group of thinking and social symptoms that interferes with daily life such as deterioration in memory,
behavior and thinking), attention deficit hyperactivity disorder (chronic condition includes
hyperactivity, attention difficulty and impulsiveness. It may begin in childhood lead to low self-
esteem and troubled relationships), post- traumatic stress disorder (failure to recover from some
fearful or terrifying event), schizophrenia (in this person interpret reality abnormally, it affects
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person’s ability to think, behave and feel clearly), autism (impairs the ability to communicate and
interact), (Mortensen, E. L., Sørensen, H. J., Jensen, H. H., Reinisch, J. M., & Mednick, S. A., 2005).
a Mental Health is also related to Intelligence quotient (IQ). IQ is a total score derived from set of
standardized tests and subtests designed to assess human intelligence (Dennis. et. al., 2006). Low IQ
scores may be associated with deficits in mental abilities and affect an individual’s ability to live and
function independently. An IQ score >70 considered as a benchmark formental retardation (McKenzi.
et. al., 2016).
Emotional well-being (EWB) includes a positive balance of pleasant to unpleasant affect and a
cognitive appraisal of satisfaction with life in general (Keyes, 2003). Emotional well-being has
been defined as an overall positive state of one’s emotions, life satisfaction, sense of meaning and
purpose, and ability to pursue self-defined goals. Elements of emotional well-being include a sense
of balance in emotion, thoughts, social relationships, and pursuits (Merav Sabri & Dave Clark). It
refers to emotional quality of individual experiences and it is influenced by several demographic,
economic and situational factors (Kahneman. et. al., 2010). Emotional Well-Being can be
conceptualized as the balance of feelings- both positive and negative which are experienced in life.
Emotional Wellbeing of a person can be affected because of various reasons such as economic
downturn (Patrick, et.al, 2020, Zacher, Rudolph, 2020, Kawamoto, et.al, 2004, Dsouzaa, et.al,
2020), intolerance of uncertainty (Satici, et.al, 2020), work activity status, age, gender (Kawamoto,
et.al, 2004), stress, anxiety (Dsouzaa, et.al, 2020, Sepúlveda, et.al, 2011). In this COVID19
emotional wellbeing also affected because of fear of COVID19 (Satici, et.al, 2020, Dsouzaa, et.al,
2020, Kenneth, 1997), food insecurity, unable to go back to one’s home, pressure of getting
quarantined (Dsouzaa, et.al, 2020), teaching and learning (Colleen McLaughlin, 2008, Anna Choi,
2018), social inclusion and community building (Colleen McLaughlin, 2008, Kawamoto, et.al,
2004, Anna Choi, 2018, Dsouzaa, et.al, 2020). A good emotional well- being result in better
physical health, helps in enjoying our life, and prevents us from diseases. The results of decrease in
emotional well-being have led to stress, depression and anxiety which directly impact our physical
health. Such a person with emotional distress would likely to be of low self-esteem, emotionally
sensitive, over-thinker, pessimistic, very self-critical, etc which can act as an obstacle in both
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personal as well as in professional life.
According to Philip Kotler and Garry Armstrong, “Consumer Buying Behavior refers to the buying
behavior of final consumers – individuals and household who buy goods and services for
personal consumption. All of these final consumers combined make up the consumer market”.
According to Rao, “consumer behavior is neither emotional nor rational but both. Both emotion and
common-sense influence the shopping decisions of a consumer”. In other words, a consumer does
not buy an article just because he likes it. He considers various aspects like price, durability,
availability, appearance, his immediate need and so on and then only he decides on his purchase.
Despite all these considerations the consumers’ behavior is inexplicable when he buys a product
instantly on seeing it for a moment, it is termed as impulsive buying and hence the behavior is
impulsive. Consumer Behavior is viewed as a process of problem solving. Black and Roering
observe, “Consumer Behavior comprises the activities of individuals in buying and using goods and
services”. Theyhave tried to explain the aspects of the study of consumer behavior and their buying
pattern”. Consumer Buying Pattern of a person depend on necessity of need, quality, former
experience, price, brand, product characteristics and parameters, design of product,
recommendation of specialists, relatives and friends (J. Stávková, L. Stejskal, Z. Toufarová, 2008).
Hospitality and Retail impacts also affects pattern (Michael C. Hall, Girish Prayag). Pent-up
Demand and Embracing Digital Technology also related to consumer buying pattern (Jagdish
Sheth, 2020).
Epidemics and pandemics can have significant social consequences, creating clashes between states
and citizens, eroding state capacity, driving population displacements, and heightening social tension
and discrimination (Prince-Smith 2009). As per (Latoo, 2020), Covid-19 and unusual buying behavior
strong link with self-intention to self-islation and intention to make unusual purchase, providing
empherical evidence that the reported consumer behavior was directly linked to anticipated time spent
in self-isolation As per (Serafini et. al, 2020) The emergence of coronavirus disease 2019 (COVID-19)
outbreak caused by severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) infection in the
Chinese city of Wuhan, a situation of socio-economic crisis and profound psychological distress
rapidly occurred worldwide. As (Serafini et. al, 2020) per there are various psychological problems
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and important consequences in terms of mental health including stress, anxiety, depression,
frustration, uncertainty during COVID-19 outbreak emerged progressively. As per (Braquehais et. al.,
2020) The Health professionals have confronted life threatening experience for which they were not
trained. As per (Liang et. al., 2020) the pandemics cause the public to experience psychological
problems such as post-traumatic stress disorder, psychologicaldistress, depression and anxiety. As per
(Roy et. al, 2020) Covid-19 pandemics can lead to heightened levels of stress; Anxiety is a common
response to any stressful situation. As per (Dsouza et. al, 2020) The suicide causalities include a
follow like fear of Covid-19 infection, followed by financial crisis, loneliness, social boycott and
pressure to be quarantine, Covid-19 positives, Covid-19 work related stress, unable to come back home
due to complete lockdown, unavailability of alcohol. As per (Dsouza et. al, 2020) considering the
extreme psychological impact related to Covid-19, there emerges a need for countrywide extensive
tele-mental health care services.
The aims of this study were to (1) to analyze the social and psychological impact of COVID-19 on
mental health of Indian consumers, (2) to analyze the social and psychological impact of COVID 19
on emotional well-being of Indian consumers, (3) to analyze the social and psychological impact of
COVID 19 on consumer buying pattern and (4) to measure the relationship of social and
psychological impact of COVID 19, mental health and emotional well-being on consumer buying
pattern.
2. MATERIALS AND METHODS:
2.1. Participants:
The sample comprised 156 individuals living in India. The participants were supposed to provide their
basic information like age, gender, state they belong to, employment status, household income per
month and family size. The participants were given a web-based questionnaire and they participated
were asked to respond to a number of questions. The survey was shared through hyperlink and the
participants were asked to answer questions related to emotional well-being, mental health and their
buying pattern. Everyone with the link could participate in the survey, but it is observed that young
people were most likely to fill the survey and no information about the number of participants that
failed to complete the form thus incomplete questionnaires were also not counted nor saved.
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Participant’s data were stored according to Google’s privacy policy and then transferred to Microsoft
Excel. From the data collected, the maximum number of respondents were from the state of Punjab
(n=58) comprising 37.17% of the total respondents. Jharkhand, Karnataka, Maharashtra, Odisha,
Rajasthan, Telangana, Tripura, West Bengal each were having 1 respondent that comprised for 0.64%
each of the respondents.Assam, Bihar, Chhattisgarh, Kerala, Madhya Pradesh and Manipur had 2
respondents each that comprised for 1.28% each of the 156 respondents. Andhra Pradesh had n=4
respondents comprising 2.5% of the respondents. Haryana had n=6 respondents comprising 3.8% of
the respondents. Himachal Pradesh had n=10 respondents comprising 6.41% of the respondents.
Jammu and Kashmir had n=12 respondents comprising 7.69% of the respondents. Uttar Pradesh had
n=18 respondents comprising 11.53% of the respondents. While Uttrakhand had n=28 respondents
comprising 17.94% of the respondents.
Table1. Demographic characteristics of the sample (N = 156) and descriptive statistics for variables.
Demographic
Characteristic
N %
Gender
Male 74 47.4%
Female 82 52.6%
Age
Under 18
6 3.8%
18-25
113 72.4%
26-35
28 17.9%
36-45
5 3.2%
46-55
4 2.6%
Highest Level of Education
High school
15 9.6%
Graduate
Degree
68 43.6%
Master’s
Degree
71 45.5%
Ph.D. and
above
2 1.3%
Household Income per Month
Below ₹ 25,000
44 28.2%
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₹ 25,000 – ₹
49,999
61 39.1%
₹ 50,000 – ₹
74,999
21 13.5%
₹ 75,000 – ₹
99,999
10 6.4%
Above ₹
1,00,000
20 12.8%
Employment Status
Government
Employee
12 7.7%
Housewife
7 4.5%
Private Job
49 31.4%
Self-employed
15 9.6%
Student
73 46.8%
Family Size
≤ 4
82 52.6%
5 – 7
60 38.5%
8 – 10
9 5.8%
> 10
5 3.2%
2.2) Measures:
Attributes such as Restricted Social Gathering, Social Boycott, Sexual Abuse, Domestic Violence,
Restricted Travelling, Unavailability of Alcohol, Lockdown Tension, Strain of Work from Home,
Pressure of Maintaining Social Distance, Job Insecurity, Exhausted Savings, Investment in Health
Insurance, Financial Aid from Government, Unemployment, Increased Health Expenses, Sleep
Deprivation, Depression, Loneliness, Anxiety, Stress, Fear of COVID-19, Food Insecurity,
Relationship Insecurity, Trouble in Concentrating, Medical Issues, Panic Buying of Groceries, Spent
Less on Shopping, Preferred to buy online, Spent more on Health and Spent more on Entertainment
are measured on a 5-point Likert scale ranging from “Strongly Disagree” to “Strongly Agree”. Kaiser-
Meyer-Olkin (KMO) Test was also used so that sampling adequacy for each variable is measured and
we can find how much suitable our data is. If sampling adequacy is less than 0.6 it is unacceptable but
if it is between 0.9 to 1 it is awesome (Dodge, Y., 2008). We used Exploratory and Confirmatory
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factor analysis to prove our study. In Exploratory factor analysis, Rotated Component Matrix is taken
which divide variables of study into groups or factors. In Confirmatory factor Analysis, Model fit
Summary and Structured Equation Model was studied.
2.3) Procedure:
The questionnaires were preceded by short description and aim of the study. Participation in research
was voluntary. Our survey had two steps. First participants filled demographic questionnaires
(information about gender, age, level of education, employment status, household income and family
size). Second step consisted of the check list of variables that impacted daily routine of people during
COVID 19 situation and participants have to rate on scale how much a particular attribute impacted
them. The survey was created as a Google document to limit interpersonal contact. The contents of
the text are in Appendix. The study was conducted from the beginning of January to the mid of Jan
2021.
RESULTS:
Reliability Analysis:
In Reliability Analysis number of commonly used measures of scale is calculated and also gives
information about the relationships between an individual’s items in scale. In our data the value of
Cronbach Alpha found to be 0.957 which is much better than 0.70 (Bland et. al., 1997). It depicts that
our data is reliable. Cronbach Alpha is a model of internal consistency based on the average inter-item
correlation.
Factor analysis:
Factor analysis enables the social scientist to study behavioral phenomena of great complexity and
diversity and to mold his findings into scientific theories. It offers both a technique of analysis and a
theoretical structure (RJ Rummel, 1988).
KMO (Kaiser-Meyer-Olkin): Kaiser-Meyer-Olkin (KMO) Test is a measure of how much your data
is suitable for factor analysis. In this test, sampling adequacy for each variable is measured. The
statistic is a measure of the proportion of variance among variables which might be common variance.
If sampling adequacy is less than 0.6 it is unacceptable but if it is between 0.9 to 1 it is marvelous
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(Dodge, Y., 2008). In our data the value of KMO found to be 0.938. It depicts that our data is
adequate.
Exploratory Factors Analysis:
In our study we have taken basically 5 factors such as Social Impact, Psychological Impact,
Emotional Well-Being, Mental health and Consumer buying patter. All the factors were taken in order
to understand that how these factors are impacting each other and up to what extent. In our results it
has been found that due to Covid-19 pandemic these factors were highly influenced and due to
uncertain challenges people were affecting a lot. Like due to travel restriction people were not able to
meet their loved ones due to which they were spending time all alone which was making them feel
depressed. After being in the uncertain environment and changing situation people were facing issue
with mental health which leads in affecting the emotional well-being. So the factors analysis has
shown that each of the factors is important and need to be taken into consideration while
understanding the change consumer buying pattern. Our study has shown significant results for the
same and how these factors are affecting each other’s.
Rotated Component Factors Analysis
In the rotated component matrix we were able to analyze that how variables are impacting the factors
and their alpha value. First factors was Emotional Well-being where in the value of Alpha was .930
which is significant and it has got variable like food insecurity, panic buying of groceries, fear of
Covid-19, medical issues, relationship insecurity etc. where in other factors i.e. mental health as also
got .933 alpha value which signifies the variables such as loneliness, Anxiety, stress, depression and
sleep deprivation. In the same way rest of the factors have got the alpha value like for psychological
impact it was .888, Social impact .724 lastly for Consumer buying pattern it was .678 ,so with this use
of rotated component of factor analysis we were able to find out the significant value of alpha of each
factors and their respective variables. As a result Rotational Factor analysis has omitted 2 variables
out of 30 variables that we used in the study was Work Related to Stress and Buy products according
to recommendations.
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Model fit Summary
Model fit values are shown in Table No.3 in Model Fit analysis, the model to be fit there are various
statistical tools available and in order to model to fir there are some standards. In our study all the
values are as per the standards which show that our model is fit and perfect. Getting the final values of
the various values such as Chi-Square, CFI, AGFI etc. is important in order to prove that the proposed
model is appropriate for the study and it is correct. So in our data the results are significant which
means our model is fir for the study.
Table3. The summary of model fit Indices is given below:
S No Indices (Good Fit
Measures)
Cut off Value Model Value Decision
1 Model Chi Square > .05 0.608 Fit
2 CMIN/DF 1 to 5 1.826 Fit
3 GFI 0 to 1 0.784 Fit
4 AGFI 0 to 1 0.736 Fit
5 RMSEA 0.05 to 0.08 0.073 Fit
6 CFI >=0.90 >=0.909 Fit
7 NFI 0 to 1 0.821 Fit
8 TLI 0 to 1 0.896 Fit
9 PGFI 0 to 1 0.643 Fit
Social Impact
Emotional Well-
Psychological Impact
Mental Health
Consumer Buying
Pattern
COVID 19 Impacts
Figure 1 shows the proposed model with factors
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10 PNFI 0 to 1 0.723 Fit
11 PRATIO 0 to 1 0.881 Fit
Structured Equation Model (SEM): It is a technique to test and estimate casual relationships by
integrating factor and path analysis.
SEM Model Analysis: SEM can examine a series of
dependence relationships simultaneously. With the
help of SEM, we were able to find relationship
between variables and our model to be correct. We
have found that Social impact has significant impact
on Emotional well-being as p value is less than 0.05
which shows both variables impact each other,
resulting into rejection of Null Hypothesis.
Psychological Impact has significant impact on
Mental Health as p value <0.05 which shows both variables impact each other, resulting into rejection
of Null Hypothesis. Social Impact has insignificant impact on Mental Health as p value >0.05 (0.878)
which means both variables don’t impact each other, resulting into acceptance of Null Hypothesis.
Mental Health has insignificant impact on Consumer Buying Pattern as p value >0.05 (0.462) which
means both variables don’t impact each other, resulting into acceptance of Null Hypothesis.
Emotional Well-being has significant impact on Consumer Buying Pattern as p value <0.05 which
shows both variables impact each other, resulting into rejection of Null Hypothesis. Psychological
Impact has significant impact on Consumer Buying Pattern as p value <0.05 which shows both
variables impact each other, resulting into rejection of Null Hypothesis. Social Impact has
insignificant impact on Consumer Buying Pattern as p value <0.05 but it is too close as value is 0.059
which shows both variables in general may not impact each other but there is possibility in some
cases.
Figure 2Fig. Correlation between variables of Mental
Health, Emotional Well-being, Consumer Buying Pattern,
Psychological Impact and Social Impact are shown above.
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Regression Weights:
Variables p
EWBNG1
<--
-
SOIMP1 ***
MENHEAL
1
<--
-
PSYIMP1 ***
MENHEAL
1
<--
-
SOIMP1 .878
CONBP1
<--
-
MENHEA
L1
.462
CONBP1
<--
-
EWBNG1 ***
CONBP1
<--
-
PSYIMP1 ***
CONBP1
<--
-
SOIMP1 .059
SOIMP1
<--
>
PSYIMP1 ***
In our study we have taken several assumptions in order to prove whether the hypothesis are accepted
or rejected, First hypothesis was that there is not impact of Covid-19 on mental health of Indian
consumers actually rejected which means Covid-19 do have impacted the mental health of the Indian
Consumers in the same way another hypothesis was that there is no impact of Covid-19 on the
emotional Well-being of Indian consumers is again rejected that also signifies that out hypothesis
rejected which means emotional well- being do have impacted the buying behavior of Indian
Consumers. Next one is about that there is no impact of Covid-19 on the buying pattern of Indian
consumer is again rejected, which too shows that Covid-19 has impacted the consumer buying pattern
of Indian Consumers. After all these hypothesis we can see that Emotional Well-being and Covid-19
factors are related with consumer buying pattern and they all are inter related with each other in the
same way it proves that mental health and emotional well-being act as mediator between the impact of
Covid-19 on consumer buying pattern.
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DISCUSSION
The study was conducted in order to analyze the social and psychological impact of COVID-19 on
mental health and emotional well-being of Indian consumers. Also, the study aims to analyze the
social and psychological impact of COVID-19 on consumer buying pattern and to measure the
relationship of social and psychological impact of COVID-19, mental health and emotional well-
being on consumer buying pattern. The study had a two-step procedure. First, the participants were
asked about their demographic details and then the participants were asked to answer the question in
the form of checklist of variables about how COVID-19 has impacted the social, psychological,
mental health and emotional well-being of the Indian consumers.
For the purpose of analyzing the available data, Reliability analysis was conducted in which the value
of alpha was found to be 0.957 that is better than 0.70. This shows that the data is reliable.
Furthermore, Factor analysis was done which enabled the social scientists to study behavioural
phenomena of great complexity and diversity of the data. In this firstly KMO (Kaiser-Meyer-Olkin)
test was done that measures how much data is suitable for factor analysis. The value of KMO for the
data was found to be 0.938 which depicts that the data is adequate. Then, Exploratory Factors
Analysis was conducted in which five factors could be yielded. These factors were: Social Impact,
Psychological Impact, Emotional well-being, Mental Health and Consumer Buying Pattern. In the
study Confirmatory Factor analysis which is used to test whether the data fit hypothesized
measurement model or not. In this method, we were able to understand the relationship among various
factors and whether they fit in the model that we have framed. Also, Structured Equation Model was
made that helped in establishing a relationship between variables and model. From the SEM model
we found out that: Psychological Factor has impacted the mental health of Indian Consumers during
COVID-19. Also, the Social Factor has impacted the emotional well-being of Indian Consumers and
the Psychological Factor has impacted the Consumer Buying Pattern of Indian Consumers. The
finding showed that social impact and psychological impact will affect the emotional well-being of
the people which will result in affecting mental health and consumer buying pattern. It shows that all
the variables that were taken have significant impact on each other and due to Covid-19 people's life
has changed a lot so change in the buying behaviour. Even taking precautions and guidelines people
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were scared to go out which shows their anxiety level has increased. Similarly, work from home has
increased the stress and other health issues and due to restrictions on traveling people were feeling
lonely and depressed. So, with all these results we can say that Covid-19 has significantly impacted
the emotional well-being and mental health of the people which lead to change in consumer buying
behaviour. Before Covid-19 people were not much concerned for their health but then they shifted to
buy more of products which are healthy and immunity boosters. Not just this, instead of moving out
for eating or watching movies, people preferred to order online and watch movies or series through
OTT platforms.
This study is having some limitations. The sample consists of a homogeneous group of well-educated
participants. So, the less educated people were ignored this study. Also, the sample consisted of
72.4% of people from the age group of 18-25 years and the people above the age of 55 were also
ignored in this study. So, no further conclusions can be drawn from the study for them. The maximum
number of participants was from the state of Punjab that has led to disparity among all the states of
India. The survey was easily accessible as it was held online so the possible explanation could not be
found that why this disparity was there.
CONCLUSION
The results show that Social Impact doesn’t have an impact on Mental Health. Mental Health has no
impact on Consumer Buying Pattern. Emotional Well-being has significant impact on Consumer
Buying Pattern which means that both variables impact each other. Psychological factors also impact
the Consumer Buying Pattern. Social factors may not always impact the consumer buying pattern but
there is possibility in some cases that they impact the buying behaviour of the consumers.
Psychological factors have significant impact on Social factors and vice-versa which indicate that
both the factors are inter-related. Emotional Well-being and COVID 19 factors are related with
consumer buying pattern and COVID 19 factors are further related with so everyone is interlinked to
each other in any way which proves mental health and emotional well-being act as a mediator the
relationship between Impact of COVID 19 on consumer buying pattern.
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