Consumer Survey on Impact of COVID-19 on Future Holiday Travel Behaviour
Anshul Bali
Senior Business Analyst,
Merkle Sokrati, Pune
Ashish Shrivastava
Consultant Speedmart Pvt. Limited, India
Dr. Binod Sinha
Professor,
Balaji Institute of Modern Management,
Sri Balaji University,
Pune, Maharashtra
Abstract:
The increasing cases of Covid-19 (Corona virus) resulted towards lockdown not only in India but all over the world. The movement of traffic internationally was closed. The nationwide lockdown which was imposed by Government of India brought a lot of changes in the lifestyle of people. Earlier, many studies have reported about the financial impact of COVID-19 on tourism industry & the correlation between COVID-19 and trends in tourism industry. The idea is to relate those variables with onslaught of Covid-19 and to understand, more long-term impact that COVID-19 will have on travellers’ perception towards tourism. An online survey was conducted to collect primary data in which a questionnaire was circulated to travellers all over India. The results of this study can be used by the companies and government institutions to develop marketing strategies to increase travellers’ consumption experience.
Keywords: Traveller’s Perception, Travel Destination Lockdown, Vacation, Covid19, Tourism
Introduction
The first case of Covid-19 was diagnosed in Wuhan a city in China on November 17, 2019. On March 11, 2020, World Health Organization (WHO) declared the novel coronavirus (Covid-19) outbreak a global pandemic and since then the countries all around the world have sealed their borders for international travel. The nationwide lockdown announced on March 25, 2020 resulted into steep fall in the Indian economy as major industries were shut down during this period. After relaxation, as people are trying to adapt the normal lifestyle all the precautions advised by the Ministry of Health & Family Welfare should be followed. Some of the states have started lifting the travel bans since government instructions to open up industries in phases.
Objectives
Hypotheses
H0: There is no significant difference between demographic variables & perception of customer towards travelling after Covid-19.
H1: There is significant difference between demographic variables & perception of customer towards travelling after Covid-19.
H0: There is no significant difference in selection of travel destination after Covid-19.
H1: There is a significant difference in selection of travel destination after Covid-19.
H0: There is no significant association between customer travelling and preferring to save money after COVID-19.
H1: There is a significant association between customer travelling and preferring to save money after COVID-19.
Review of Literature:
(Alexandra, 2013) about ‘Consumer Behaviour in tourism and the influencing factors of the decision making process’. The purpose of this paper is to investigate “Consumer Behaviour in tourism” and helps to understand the factors which are involved in influencing the tourist towards taking a decision or planning their holiday travel. The study of consumer behaviour is done to understand the decision making process to buy or use the services of the companies. It also helps the companies to understand how to influence their customers to buy their different products according to their needs and preferences. This study also helps to understand the segmentations of the customers into different categories on basis of different factors which influence a consumer towards taking a decision. The role of a travel agent is also explained in this study. The internal and external determinants play an important role in decision making process.
(Ohlan, 2017) discussed in his paper about ‘the relationship between tourism, financial development and economic growth in India, talks about the relationship between “tourism, financial development and economic growth” in India. This study helps us understand the contribution of tourism towards foreign exchange reserves which help in bringing new technologies for production process, new infrastructure, industrial development and new job creation. The results of this study show that the earnings from international tourism positively affect India’s economic growth in both long term and short term. The model was operated with help of endogenous variable (GDP per capita) and two exogenous variables (tourism receipts per capita & financial development). The analysis also shows India’s economic growth, tourism and financial development are co-integrated. The results concluded that inbound tourism should be promoted by government by developing policies & strategies as it plays a major role towards increasing the GDP of India. The current study has opened new avenues for countries like Afghanistan, Pakistan, Sri Lanka and Bangladesh.
(Choudhury, 2020) discussed in their paper about ‘An Empirical Study of The Financial Impact of Covid-19 on The Tourism Industry in India’. The research aims to studyThe Financial Impact of Covid-19 on The Tourism Industry in India. The study broadly highlights how business connected with tourism industry are likely to suffer more than any other industry. The study has been conducted by collecting both primary and secondary data. Further, the primary data is collected by sending questionnaire to various businesses related to tourism and hospitality industry. The results show that Covid-19 has affected the most to the businesses connected with tourism industry. Author also mentions that there would be 40 % decline in tourism sector over 2019 as per study by care rating.The study concludes that tourism sector is facing a huge loss & a lot of people are unemployed in this industry and government is planning to reduce loss to this sector. This research is restricted to the city of Ranchi only and the author also mentions this study can be performed on large scale in future.
(Patil, 2020) in his paper discussed about “Trends and Development”. This research is conducted in India. This research paper helps us to gain knowledge about different policies made by Indian Tourism Development Corporation. The author used secondary data collected from online sources and official government websites as the research methodology. This study also helps to understand about the importance of developing policies and strategies to increase inbound as well as outbound tourism. The data collected in this study shows an increasing trend in the tourism whether it is inbound or outbound tourism. Tourism plays a major role in the GDP of any country and also helps in job creation, foreign currency earnings, infrastructure development, poverty eradication, inequality reduction and balanced regional development.
(Kasare, 2020) in his study helps us to understand the “Effects of Coronavirus Disease (COVID -19) on Tourism Industry of India”. The author in this present research tells us about the vital role of tourism in economic growth of India. This study helps us to understand the effects of Covid-19 on tourism in India, top 10 popular tourists’ states in India and to know the foreign exchange earnings as well as the number of tourists who visited India before Covis-19 crisis. The author has used secondary data for the research collected from journals, articles and official tourism websites. The data shows that number of foreign tourists’ arrival & foreign exchange earnings in India before Covid-19 was increasing every year with $28,585 million in 2018. The study concludes that there would be a negative effect of Covid-19 on the tourism sector as well as the GDP of the country. The author helps us to know that Maharashtra is the most tourist attractive state with 18.9% share in foreign and domestic travel (2017). The author states that Unemployment, Financial losses, Fiscal Deficit, Hostile behaviour towards foreigners would affect tourism in future. The author suggests that government should take proper measures to support the tourism industry and proper remedies should be taken so that these kinds of unseen situations can be tackled down in future.
Research Methodology
Data Analysis
Reliability Test
The reliability statistic using statistical package for social sciences (SPSS) is used with the help of Cronbach’s Alpha it was detected that 16 Items of the question was 67.2% that means that the information is credible. A value higher than 50% is considered sufficient and in this case it is 67.2%.
|
Table 1: Reliability Statistics |
|
|
Cronbach's Alpha |
No. of Items |
|
.672 |
16 |
|
|
|
Ranking of the factors affecting perception of the travellers.
|
Table 2: Ranks |
|
|
|
Mean Rank |
|
Hygiene code |
2.77 |
|
SAFETY code |
2.89 |
|
Price code |
4.20 |
|
Flexibility code |
4.34 |
|
Duration code |
4.35 |
|
Travel Insurance code |
4.61 |
|
Travel advisor code |
4.85 |
|
Mean Rank |
Ranking |
|
|
Hygiene |
2.77 |
1 |
|
Safety |
2.89 |
2 |
|
Price |
4.20 |
3 |
|
Flexibility |
4.34 |
4 |
|
Duration |
4.35 |
5 |
|
Travel Insurance |
4.61 |
6 |
|
Travel advisor |
4.85 |
7 |
|
Table 3: Test Statistics |
|
|
N |
220 |
|
Chi-square |
332.740 |
|
df |
6 |
|
Asymp. Sig. |
.000 |
Hypothesis Testing
ONE WAY ANOVA
Null Hypothesis: There is no significant difference between demographic variables & perception of customer towards traveling after COVID-19.
Alternate Hypothesis: There is significant difference between demographic variables & perception of customer towards traveling after COVID-19.
Table 4: Gender & Mean of factors influencing perception of travellers
|
ANOVA |
|||||
|
Gender |
|||||
|
|
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
Between Groups |
1.246 |
1 |
1.246 |
2.280 |
.133 |
|
Within Groups |
119.714 |
219 |
.547 |
|
|
|
Total |
120.960 |
220 |
|
|
|
p value = 0.133, Since p value is more than 0.05, Accept null Hypothesis.
Inference: There is no significant difference between gender & perception of travellers after Covid-19.
Interpretation: Respondents of different gender have same opinion about perception towards travelling after Covid-19.
Table 5: Age& Mean of factors influencing perception of travellers
|
ANOVA |
|||||
|
Age |
|||||
|
|
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
Between Groups |
7.709 |
5 |
1.542 |
2.927 |
.014 |
|
Within Groups |
113.251 |
215 |
.527 |
|
|
|
Total |
120.960 |
220 |
|
|
|
p value = 0.014, Since p value is less than 0.05, Reject null Hypothesis.
Inference: There is a significant difference between age & perception of customer towards travelling after COVID-19.
Interpretation: Respondents of different age groups have varied opinion towards travelling after COVID-19.
Table 6: Profession & Mean of factors influencing perception of travellers
|
ANOVA |
|||||
|
Profession |
|||||
|
|
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
Between Groups |
6.134 |
6 |
1.022 |
1.905 |
.081 |
|
Within Groups |
114.826 |
214 |
.537 |
|
|
|
Total |
120.960 |
220 |
|
|
|
p value = 0.81, Since p value is more than 0.05, Accept null Hypothesis.
Inference: There is no significant difference between profession & perception of customer towards travelling after Covid-19.
Interpretation: Respondents of different profession have same opinion towards travelling after Covid-19.
Table 7: Income level & Mean of factors influencing perception of travellers
|
ANOVA |
|||||
|
Income level |
|||||
|
|
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
Between Groups |
8.587 |
3 |
2.862 |
5.528 |
.001 |
|
Within Groups |
112.373 |
217 |
.518 |
|
|
|
Total |
120.960 |
220 |
|
|
|
p value = 0.001, Since p value is less than 0.05, Reject null Hypothesis.
Inference: There is a significant difference between income level & perception of customer towards travelling after Covid-19.
Interpretation: Respondents of different income level have varied opinion towards travelling after Covid-19.
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Table 8: Hometown & Mean of factors influencing perception of travellers ANOVA |
|||||
|
Hometown |
|||||
|
|
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
Between Groups |
75.906 |
128 |
.593 |
1.211 |
.166 |
|
Within Groups |
45.054 |
92 |
.490 |
|
|
|
Total |
120.960 |
220 |
|
|
|
p value = 0.166, Since p value is more than 0.05, Accept null Hypothesis.
Inference: There is no significant difference between hometown & perception of customer towards travelling after Covid-19.
Interpretation: Respondents belonging to different hometowns have same opinion towards travelling after Covid-19.
Null Hypothesis: There is no significant difference in selection of travel destination after Covid-19.
Alternate Hypothesis: There is a significant difference in selection of travel destination after Covid-19.
Table 9: CHI SQUARE TEST
|
Test Statistics |
|
|
|
Where would you prefer to travel after COVID-19? Code |
|
Chi-square |
166.163a |
|
Df |
2 |
|
Asymp. Sig. |
.000 |
|
|
|
|
|
p value = 0.000, Since p value is less than 0.05, Reject null Hypothesis.
Inference: There is a significant difference in selection of travel destination after Covid-19.
Interpretation: Respondents prefer to travel domestic over international after Covid-19.
Null Hypothesis: There is no significant association between customer travelling and preferring to save money after Covid-19.
Alternate Hypothesis: There is a significant association between customer travelling and preferring to save money after Covid-19.
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Would you like to travel for holidays after the vaccine for COVID-19 is developed? * Are you planning to use your saved money during this pandemic for next vaca_A Cross tabulation Table 10: Cross Tabulation |
|||||
|
Count |
|||||
|
|
Areyouplanningtouseyoursavedmoneyduringthispandemicfornextvaca_A |
Total |
|||
|
Maybe |
No |
Yes |
|||
|
Would you like to travel for holidays after the vaccine for COVID-19 is developed? |
Yes |
61 |
13 |
114 |
188 |
|
No |
11 |
7 |
14 |
32 |
|
|
Total |
72 |
20 |
128 |
220 |
|
|
Table11:Chi-Square Tests |
|||
|
|
Value |
df |
Asymp. Sig. (2-sided) |
|
Pearson Chi-Square |
8.118a |
2 |
.017 |
|
Likelihood Ratio |
6.641 |
2 |
.036 |
|
Linear-by-Linear Association |
1.057 |
1 |
.304 |
|
N of Valid Cases |
220 |
|
|
|
. |
|||
p value = 0.017, Since p value is less than 0.05, Reject null Hypothesis.
Inference: There is a significant association between customer travelling and preferring to save money after Covid-19.
Interpretation: Majority of respondents would like to save their money for next vacations amongst the respondents who would like to travel after the vaccine for Covid-19 is developed.
Discussion:
This study is the first to investigate about the onslaught of COVID-19 on the traveller’s travel behaviour and their perception towards decision making. The results show us that travellers are willing to travel once the vaccine for COVID-19 is developed. Chart 1& 2 helps us understand travellers’ travel behaviour before & after COVID-19. The results highlight the trend in which travellers would prefer to travel after COVID-19.
Chart 3&4 helps us to understand the difference between travellers’ perception about decision making towards travelling before & after COVID-19. The results show that travellers prefer to travel domestic over international destinations once they start to travel after COVID-19. Before the outbreak of this pandemic, 62% of the respondents travelled domestic & 38% of them travelled international whereas now, 74.10% of the respondents would prefer to travel domestic, 13.50% would like to travel international and 12.50 % would not like to travel.
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This cross tabulation gives us a detailed view of the travellers’travellingbehaviour before and after COVID-19.
|
||||||
|
Count |
||||||
|
|
Where would you prefer to travel after COVID-19? |
Total |
||||
|
Domestic |
International |
May be not |
||||
|
Where did you travel for your last vacation? Domestic or international |
Domestic |
100 |
17 |
21 |
138 |
|
|
International |
64 |
12 |
6 |
82 |
||
|
Total |
164 |
29 |
27 |
220 |
||
As COVID-19 virus has entered almost every part of the world and affected a lot of people globally, Figure 6 helps us to understand the traveller’sbehaviour towards the destinations which are less contaminated due to COVID-19. 88.80% of the respondents would like to change their preferred destination to less contaminated destinations.
Demographic Information:
The number of respondents were n=220 in which 59.4 % of the respondents between age group of (18–25), 16.1 % were of age group (26-30), 14.3 % were of age group (31-40), 6.7% were of age group (41-50), 2.2% were of age group (51-60) & 1.3% was below 18 years of age with male participants (52.2%) and female participants (47.8%). The respondents actively participated from almost all parts of India with income level of 39.7% belonging to (less than INR 30,000), 29% belonging to (INR 50,000 – 1, 00,000) 22.3% belonging to (INR 30,000 – 50,000) and 8.9 % belonging to more than INR 1,00,000.
Findings
While investigating about the consumer behaviour towards future holiday travel behaviour, the finding is that there is a change in perception of the minds of the travellers due to COVID-19 pandemic. Our study would help tour operator companies to recover after COVID-19. After collecting and analysing the data, the major findings are given below:
Conclusion
It has been found that age and income levels have significant influence on decision making of the traveller after COVID-19. Else, other demographic factors such as gender, profession and hometown did not have significant influence on decision making after COVID-19. The study has also shown that travellers were also willing to travel after COVID-19 and majority of them are saving their funds for next vacation. There is an impact on the perception of the traveller due to this pandemic and suggestions have been provided according to data, which should be incorporated the companies related to this industry.
References
