Online Food Orders: Customers' Preference

Home , Foodpanda, Online food ordering, Swiggy, Zomato

Journal of Critical Reviews

ISSN- 2394-5125 Vol 7, Issue 6, 2020

Review Article ONLINE FOOD ORDERS: CUSTOMERS’ PREFERENCE WITH REFERENCE TO NORTH CHENNAI

B. Eswaran1, Dr.V. Bhuvaneswari2, P. Sivasankari3, B. Mangalalakshmi4

1Assistant Professor, Department of Business Administration, Alpha Arts and Science College, Chennai, India. 2Head of the Department, Department of Business Administration, Alpha Arts and Science College. 3Assistant Professor, Department of Business Administration, Alpha Arts and Science College, Chennai. 4Assistant Professor, Department of Business Administration, Alpha Arts and Science College, Porur, Chennai.

Received: 06.02.2020 Revised: 08.03.2020 Accepted: 10.04.2020

Abstract Online Food ordering is an activity of ordering food using restaurant’s website, mobile applications or multi restaurant’s website or mobile applications. It involves the customers to choose restaurants in their choice, going through the food items’ menu and finally choosing pickup or delivery. This study deals with food ordering online by North Chennai customers. Descriptive study was used in our research. Questionnaire was used to collect data. 250 samples were collected through simple random sampling method for infinite population. This study concludes that the mobile app used by the customers had a significant impact on time and type of food ordered. Keywords: Time of Food Ordering, Type of Food Ordering, Mobile App, North Chennai Customers.

INTRODUCTION Online Food ordering is an activity of ordering food using call' to 'online food orders' and made home delivery also possible restaurant’s website, mobile applications or multi restaurant’s to customers, with the changes in the need of the customers. website or mobile applications. It involves the customers to choose restaurants in their choice, going through the food items’ Dang and Tran (2018), stated that mobile internet plays an menu and finally choosing pickup or delivery. important role to create and increase the awareness of online applications for food ordering and delivery. It also helped the Mobile internet plays an important role to create and increase customers to search restaurants, menu items, and comparing the awareness of online apps for food ordering and delivery. For their prizes with the competitors. working community, Online food ordering is a recent fashion and highly useful. This study deals with food ordering online by B. Eswaran, Dr.V. Bhuvaneswari, Sivasankari, A.S. Kiran and North Chennai customers. E. Aravind (2020), emphasized that occupation plays a crucial role in type and time of food ordered online and mobile apps were used selectively by the customers for food ordering online LITERATURE REVIEW in different times. Parashar and Ghadiyali (2002), said that online food ordering business were given life with the advent of digital technology. OBJECTIVES Zomato had become very popular brand in food delivery business in the recent times. To find out whether mobile app had an impact on time and type of food ordered online. D’Incau D. and B. Anckar (2002), said that mobile commerce emerged as a crucial and important factor and gives freedom in HYPOTHESES the life of human beings. • Ho 1: There is no significant association between Mobile Tsang and Liang (2004), said that consumer’s attitude was app used and time of food ordered. highly influenced mobile marketing, physical and online • Ho 2: There is no significant association between Mobile advertising. app used and type of food ordered. Scharl and Dickenger (2005), emphasized that text messages, time, location identification, tailor made information for RESEARCH METHODOLOGY promoting products helps to promote mobile marketing. Descriptive study was used in our research. Questionnaire was used to collect data. 250 samples were collected through simple Kimes (2011), said that the convenience and control of random sampling method for infinite population. Customers who customers, made online food ordering very popular and order food online using mobile applications in the North Chennai augmented the amount of online food orders. were the respondents. Persuad and Azhar (2012), emphasized that though people buy mobile phones to improve their private, professional ad social lives, marketers make use of this opportunity to market their products.

G. See-Kwong (2017), said that technology augmented the rate of the online food ordering and delivery in India. The food ordering method also got changed from 'ordering over phone

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R ONLINE FOOD ORDERS: CUSTOMERS’ PREFERENCE WITH REFERENCE TO NORTH CHENNAI

DATA ANALYSIS Table 1 Gender Frequency Percent Cumulative Percent Female 25 10.0 10.0 Male 225 90.0 100.0 Total 250 100.0

Graph 3

Table 3 & Graph 3 show that food ordered through online were less than or equal to 10 times in a month in majority of the cases.

Graph 1 Table 4 Mobile app preferred Table 1 & Graph 1 show that 90 percentage of the respondent were male and 10 percentage were female. Frequency Percent Cumulative Percent Uber 35 14.0 14.0 Table 2 Swiggy 142 56.8 70.8 Occupation Zomato 71 28.4 99.2 Cumulative Frequency Percent Food panda 2 .8 100.0 Percent Total 250 100.0 Student 125 50.0 50.0 Private 103 41.2 91.2 employee Govt. 7 2.8 94.0 employees Business 15 6.0 100.0 people Total 250 100.0

Graph 4

Table 4 & Graph 4 show that Swiggy was preferred more to order food online.

Hypothesis 1 Ho 1: There is no significant association between Mobile app Graph 2 used and time of food ordered. Ha 1: There is a significant association between Mobile app used Table 2 & Graph 2 show that the respondents were predominantly and time of food ordered. students and private employees. Chi-square test was used to find out the association between the mobile app used and time of food ordered. Table 3 Table 5 How often food ordered online Chi-Square Tests Cumulative Asymp. Sig. (2- Frequency Percent Value df Percent sided) Less than 5 124 49.6 49.6 a times Pearson Chi-Square 22.970 6 .001 6 to 10 times 124 49.6 99.2 Likelihood Ratio 22.290 6 .001 11 to 15 Linear-by-Linear 2 .8 100.0 2.412 1 .120 times Association

Total 250 100.0 N of Valid Cases 250

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ONLINE FOOD ORDERS: CUSTOMERS’ PREFERENCE WITH REFERENCE TO NORTH CHENNAI

This table shows that the p value of Pearson chi value is 0.001, Table 9 which is lesser than 0.05. This shows Null hypothesis is rejected Symmetric Measures and Alternative hypothesis is accepted. So, there is a significant Value Approx. Sig. association between Mobile app used and time of food ordered. Phi .229 .042 Nominal by Nominal Cramer's V .162 .042 Table 6 N of Valid Cases 250 Symmetric Measures Value Approx. Sig. This table shows the strength of the association between Mobile Phi .303 .001 Nominal by Nominal app used and type of food ordered. As Cramer’s V Value (0.162) Cramer's V .214 .001 is less than 0.30. the association is weak. N of Valid Cases 250 Table 10 This table shows the strength of the association between Mobile Non Non Veg app used and time of food ordered. As Cramer’s V Value (0.214) veg veg south Total is less than 0.30. the association is weak. South North Indian Indian Indian Table 7 Count 23 12 0 35 Breakfast Lunch Dinner Total Uber % of 9.2% 4.8% 0.0% 14.0% Count 13 9 13 35 Total Count 62 80 0 142 Uber % of 5.2% 3.6% 5.2% 14.0% Swiggy % of Total 24.8% 32.0% 0.0% 56.8% Total Count 11 41 90 142 Count 29 40 2 71 Swiggy % of Zomato % of 4.4% 16.4% 36.0% 56.8% 11.6% 16.0% .8% 28.4% Total Total Count 15 16 40 71 Count 0 2 0 2 Food Zomato % of % of 6.0% 6.4% 16.0% 28.4% panda 0.0% .8% 0.0% .8% Total Total Count 114 134 2 250 Count 0 0 2 2 Total % of Foodpanda % of 45.6% 53.6% .8% 100.0% 0.0% 0.0% .8% .8% Total Total Count 39 66 145 250 Swiggy was predominantly used for ordering food online for all Total % of type of foods. Customers preferred Zomato for ordering Non veg 15.6% 26.4% 58.0% 100.0% Total north Indian food items.

This table shows that, Swiggy was used predominantly to order FINDINGS food. Especially in breakfast, almost all the three apps such as 1. In breakfast, almost all the three apps such as Uber, Uber, Swiggy and Zomato are preferred equally. For lunch and Swiggy and Zomato are equally preferred. For lunch dinner Swiggy was used for order mostly. and dinner Swiggy was used for orders mostly. 2. Customers preferred Zomato for ordering Non veg Hypothesis 2 north Indian food items. Swiggy was predominantly Ho 2: There is no significant association between Mobile app used to order all types of foods in all the times. used and type of food ordered. Ha 2: There is a significant association between Mobile app used CONCLUSION and type of food ordered. This study concludes that the mobile app used by the customers Chi-square test was used to find out the association between the had a considerable impact on type of food items and time of food mobile app used and type of food ordered. items ordered online.

Table 8 REFERENCES 1. B. Eswaran., Dr.V. Bhuvaneswari., P. Sivasankari., A.S. Kiran Chi-Square Tests and E. Aravind.,2020, A study on Customer’s preference Asymp. Sig. (2- Value df towards online food orders with reference to south sided) Chennai, International Journal of Psychosocial Pearson Chi-Square 13.066 6 .042 Rehabilitation, vol.24, issue-04, page no. 4849 – 4858. Likelihood Ratio 13.799 6 .032 2. Anckar B., D’Incau D., Value creation in mobile commerce: findings from a consumer survey, Journal of Information Linear-by-Linear 6.242 1 .012 Technology Theory and App, vol. 4, page no. 48-57. Association 3. Scharl D., Dickinger A., Murphy J., 2005, Diffusion and N of Valid Cases 250 success factors of mobile marketing, Electronic Commerce Research and Apps, Vol. 4, page no. 164-169. This table shows that the p value of Pearson chi square value is 4. Tsang M.M., Chun ho S., Liang T., 2004, Consumers attitude 0.042, which is lesser than 0.05. This shows Null hypothesis is toward mobile advertising; an empirical study, rejected and Alternative hypothesis is accepted. So, there is a International Journal of Electronic Commerce, 3, Vol. 8, page significant association between Mobile app used and type of food no. 66-68. ordered. 5. Persuad, A, Azhar, I. 2012, Innovative mobile marketing via smartphones: are consumers ready, Marketing Intelligence and Planning, Vol no.30, page no. 1-3 and 20-23.

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6. Kimes, S, E. 2011, Consumer perceptions of online food ordering, Centre for Hospitality Research Publications, Vol. 11, page no: 4-12 7. Parashar. N, Ghadiyali. S, 2002, A study of customer’s attitude and perception towards digital food app services, page no. 1-7 8. Das J., 2018, Consumer perception towards online food ordering and delivery services: an empirical study, Journal of Management, 5, Vol. 5, page no. 158-162 9. Sethu H.S., Saini B., 2016, Customer perception and satisfaction on ordering food via internet, a case on Foodzoned.com, in Manipal, 10. Proceedings of the Seventh Asia-Pacific Conference on Global Business, economics, Finance and social science, page no. 7-10 11. Boyer K.K., M. Hult G.T., 2005, Customer behavior in an online ordering App: A decision Scoring Model, Decision Sciences Institute, 4, Vol. 36, page no. 579-580 12. See-Kwong G., Soo-Ryue N., 2017, Outsourcing to online food delivery services: perspective of F&B business owners, Journal of Internet Banking and Commerce, 2, Vol no. 22, page no. 5-7 13. Anita Vinaik., Richa Goel., Seema Sahai., Vikas Garg., 2019, The Study of Interest of Consumers in Mobile Food Ordering Apps, International Journal of Recent Technology and Engineering, Vol.8, Issue-1, page no. 3424 – 3429.

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