Keywords

Media usage, mobile applications, Food Service Aggregators, Consumer behavior, Use of Food Service aggregators, Usage of Mobile applications.

Introduction

The consumption patterns of any country are greatly influenced by its demographic factors, particularly among the youth population. According to the 2011 census data of India, the country has over 700 million people aged between 15 and 35 years. In addition, as of August 2019, India had a staggering 1.17 billion wireless subscribers, out of which 970.23 million were active users. Furthermore, a report revealed that by December 2019, approximately 500 million Indians were using smartphones. Analyzing these figures in conjunction with the youth population and the widespread adoption of mobile technology, it becomes evident that industries associated with the youth and mobile technology are poised to be significantly impacted.

This study aims to explore the influence of technology and demographic factors on consumption patterns, specifically within the online food delivery market. The convergence of technology, demographic dividends, and the expanding base of wireless subscribers plays a pivotal role in shaping consumption patterns in this sector. Notably, the Indian market has witnessed a consolidation of food aggregators, resulting in decreased competition. In the beginning of 2020, a major Indian company acquired an international player, leading to the dominance of two primary online food delivery companies in the local market. Consequently, new strategies are being sought to attract consumers, such as implementing time limits due to the surge in online food demand. Furthermore, the demographic profiles of customers also serve as crucial driving factors in this industry. India benefits from a demographic dividend, boasting a sizable population of young individuals, and the number of smartphone users continues to rise each year. Recognizing the significance of these factors is essential for the growth and development of online food delivery companies in India.

By delving into the relationship between demographic factors, technological advancements, and consumption patterns in the online food delivery market, this research aims to provide valuable insights and contribute to the understanding of this evolving industry landscape.

Objective

The primary objective of this research is to investigate the consumption patterns of mobile applications for food service aggregators among smartphone users. Specifically, the study aims to examine the association between the consumption patterns for online food service aggregators' mobile applications and demographic factors.The research seeks to understand how smartphone users engage with and utilize mobile applications offered by food service aggregators for ordering food. By analyzing the consumption patterns, the study aims to identify trends and preferences among users, considering factors such as frequency of usage, amount of money spent per order, and meal type preferences.

Literature Review

The systematic literature review includes previous studies and research papers that have provided valuable insights into various aspects of food delivery applications and consumer behavior. These studies have been organized according to their key themes and findings, highlighting the relevant variables and outcomes examined in each study. The systematic literature review is as follows:

Chakraborty (2019) focused on customer behavior towards food service applications in Indian metro cities. The study emphasized the convenience and satisfaction experienced by consumers in terms of ordering and purchasing products at their preferred time and day. It highlighted the significance of internet service, website quality, and administration in ensuring customer satisfaction. Bhotawala et al. (2016) examined the growth and operating strategies of aggregator food delivery companies. The study revealed the value of the food delivery market and projected its annual growth rate. It also explored factors contributing to customer satisfaction and loyalty in the context of food delivery applications.

Juniwati (2014) investigated the influence of perceived usefulness and ease of use on attitudes toward online shopping. The study found that these factors significantly influenced consumers' attitudes but had no significant impact on their intention to shop online. Hasan and Bajwa (2021) explored the factors influencing consumer adoption of food delivery apps. The study examined variables such as perceived usefulness, perceived ease of use, trust, and perceived risk to understand consumer behavior in adopting and using these apps.

Wang et al. (2020) analyzed user behavior in the context of food delivery apps and investigated factors contributing to users' continued usage. The study examined variables such as perceived usefulness, perceived ease of use, satisfaction, and switching costs to understand the drivers of user retention. Ng et al. (2020) focused on factors influencing consumers' continued use of food delivery apps in a developing country context. The study explored variables such as perceived usefulness, perceived ease of use, social influence, and satisfaction to understand the factors affecting consumers' loyalty and continued engagement. Sodhi and Singh (2020) specifically examined the antecedents and outcomes of online food delivery app usage among Indian millennials. The study investigated factors such as perceived usefulness, perceived ease of use, perceived risk, and satisfaction, and analyzed their impact on user intention to continue using these apps.

By systematically reviewing and analyzing these studies, this research aims to build upon existing knowledge and provide further insights into the consumption patterns and behaviors related to food service aggregator's mobile applications.

Hypothesis: - For the study seven null and alternative hypotheses were framed to find out the relation between different variables.

1) Null Hypothesis H0(1): There is no significant relationship between Gender and Types of FSA app used.
Null Hypothesis H0(2): There is no significant relationship between Income and Types of FSA app used.
2) Null Hypothesis H0(3): There is no significant relationship between Income and Frequency of Buying from FSA app
3) Null Hypothesis H0(4): There is no significant relationship between Income and Money spend in ordering food
4) Null Hypothesis H0(5): There is no significant relationship between Family type and frequency of Buying from FSA app.
5) Null Hypothesis H0(6): There is no significant relationship between Family type and Money spend in ordering food
6) Null Hypothesis H0(7): There is no significant relationship between Family type and Type of Meal Alternative Hypothesis.

Research Methodology

For this study, a representative sample of respondents was surveyed both online and offline to gather their feedback. The survey utilized a questionnaire as the primary research tool. The sample selection for the field study was conducted using convenient random sampling, ensuring diversity among the respondents. The questionnaires were administered to individuals who met the criteria of using mobile applications for their primary food-related needs.

The survey was conducted using Google online forms, and some respondents also filled out the survey manually. Only completed questionnaires were considered for analysis. The primary data collected from a sample of 228 respondents were included in the survey, representing various genders, age groups, marital statuses, socioeconomic statuses, occupations, educational qualifications, and geographical locations across India.

Analysis and Interpretation

Data was analyzed using appropriate data analysis techniques and SPSS 16.0 version was used for quantitative data analysis and percentage analysis and chi square tests were administered.

Consumption Pattern

The study revealed that among the respondents, 46.05% preferred using Zomato as their food service aggregator app, with a higher number of female consumers compared to male consumers. On the other hand, 48.68% of the respondents preferred Swiggy, with a higher proportion of male customers than female. A small percentage, 5.45%, expressed a preference for other mobile applications.The findings also indicated that weekly ordering through mobile applications was the most common, accounting for 61.98% of the orders. Fortnightly orders constituted 9.94% of the total, while monthly orders accounted for 28.08%. This suggests that a significant portion of the respondents frequently utilized food delivery services through mobile applications.

Furthermore, the study unveiled a positive correlation between customers' income levels and the amount spent on each order. Customers with an annual income below INR 3 lakhs tended to place orders below INR 500. As the income levels of customers increased, there was a corresponding increase in the amount of money spent on each order. Overall, these findings highlight the preferences of the respondents regarding food service aggregator apps, the frequency of ordering, and the influence of income levels on expenditure patterns.

Association between Consumption Pattern of FSA App and Demographics

Table 1 suggests that since the p value is greater than 0.05, the null hypothesis is accepted and it is inferred that there is no significant association between gender and type of FSA (food service aggregators) used. Similarly there is no significant association between income and type of FSA used.

Table 1 Type Of Fsa App Used - Chi-Square Tests
		Value	df	Asymp. Sig. (2-sided)	Result
Gender  Male Female	Pearson Chi-Square	1.837a	2	.399	Not significant
	Likelihood Ratio	1.839	2	.399
	N of Valid Cases	228
Income	Pearson Chi-Square	4.490a
	Likelihood Ratio	5.425	6	.611	Not significant
	N of Valid Cases	228	6	.491

Table 2 suggests that since the p value is less than 0.05, the null hypothesis is rejected and the alternative hypothesis is accepted. It is concluded that there is a significant relationship between income and frequency of buying from FSA app. Similarly there is significant association between income and money spent in ordering food.

Table 2 Income- Chi-Square Tests
			Value		Df		Asymp. Sig. (2-sided)		Result
Frequency of Buying from FSA app	Pearson Chi-Square		29.399a		18		.044		Significant @ 5%
	Likelihood Ratio		30.520		18		.033
	N of Valid Cases		228
	Pearson Chi-Square		71.561a
Money spend in  ordering food	Likelihood Ratio		49.915		12		.000		Significant @ 5%
	N of Valid Cases		228		12		.000

Table 3 suggests that since the p value is greater than 0.05, the null hypothesis is accepted and it is inferred that there is no significant association between family type and frequency of food ordered. Since the p value is less than 0.05, the null hypothesis is rejected and the alternative hypothesis is accepted. It is concluded that there is a significant relationship between family type and money spend online per order. Similarly there is significant association between family type and type of Meal ordered.

Table 3 Family Type & Frequency Of Buying Chi-Square Test
		Value	Df	Asymp. Sig. (2-sided)	Result
	Pearson Chi-Square	5.749a	6	0.452	Not Significant
Frequency of food ordered	Likelihood Ratio	6.151	6	0.406
	N of Valid Cases	228
Money Spend Online per Order.	Pearson Chi-Square	27.919a	4	0.000	Significant @ 5%
	Likelihood Ratio	30.185	4	0.000
	N of Valid Cases	228
Type of Meal ordered.	Pearson Chi-Square	9.788a	4	0.044	Significant @ 5%
	Likelihood Ratio	9.461	4	0.044
	N of Valid Cases	228

Conclusion

In conclusion, this study sheds light on the consumption patterns and preferences of users of online food delivery mobile applications, with a specific focus on Swiggy Zomato and Uber Eat. The findings indicate that Swiggy is the preferred choice among users, with Zomato following closely behind. The study reveals significant associations between income levels, family types, and the frequency of buying and money spent on food orders.

The implications of this research suggest that food service aggregators should adopt a customer-centric approach by offering customized plans tailored to different consumer segments, particularly joint families and nuclear families. Emphasizing popular meal types such as snacks and dinner, along with attractive deals and weekly offers, can further attract and retain customers, especially those with lower incomes.

Additionally, the study highlights the importance of enhancing the user experience and app design to ensure a seamless and user-friendly interface. This can be achieved through continuous innovation and incorporation of user feedback.

The implications also point towards market expansion opportunities for Swiggy, given its popularity among users. By leveraging its strengths and understanding consumer preferences, Swiggy can explore new geographical areas and target specific demographics to sustain its growth.

Furthermore, the limitations of this study, such as the sample size and geographic scope, suggest avenues for future research. Longitudinal studies, comparative analyses, and deeper investigations into consumer behavior can provide further insights to guide the strategies of food service aggregators. Overall, the findings and implications of this study provide valuable guidance for food service aggregators in understanding consumer preferences, tailoring their offerings, and improving user experiences. By incorporating these insights, companies can enhance customer satisfaction, loyalty, and overall market competitiveness in the dynamic online food delivery industry.

References

Bhotvawala, M. A., Balihallimath, H., Bidichandani, N., & Khond, M. P. (2016). Growth of food tech: a comparative study of aggregator food delivery services in India. In Proceedings of the 2016 International Conference on Industrial Engineering and Operations Management, Detroit, Michigan, USA (pp. 140-149).

Indexed at, Google Scholar

Chakraborty, D. (2019). Customer Satisfaction Towards Food Service Apps in Indian Metro Cities. Journal of Emerging Technologies and Innovative Research, 6(3), 245-255.

Indexed at, Google Scholar, Cross Ref

Hasan, S., & Bajwa, I. S. (2021). Factors influencing consumer adoption of food delivery apps: An empirical investigation. International Journal of Information Management, 56, 102240.

Juniwati, J. (2014). Influence of perceived usefulness, ease of use, risk on attitude and intention to shop online. European Journal of Business and Management, 6(27), 218-229.

Google Scholar

Ng, I. C., Lai, C. H., & Cheng, T. E. (2020). Factors affecting consumers' continued use of food delivery apps in a developing country. Journal of Hospitality Marketing & Management, 29(7), 758-778.

Sodhi, J. S., & Singh, N. (2020). Antecedents and outcomes of online food delivery app usage: A study of Indian millennials. Journal of Retailing and Consumer Services, 55, 102089.

Wang, D., Min, Q., & Zhang, Y. (2020). What drives users to continue using food delivery apps? An empirical study. Computers in Human Behavior, 103, 131-142.

Received: 24-May-2023, Manuscript No. AMSJ-23-13626; Editor assigned: 25-May-2023, PreQC No. AMSJ-23-13626(PQ); Reviewed: 26-Sep-2023, QC No. AMSJ-23-13626; Revised: 02-Oct-2023, Manuscript No. AMSJ-23-13626(R); Published: 03-Nov-2023