Determinants of intentions to use Grocery Apps in India: The role of

Determinants of intentions to use Grocery Apps in

India: The role of attitude and offers

Madhu Arora

, Shubham Agarwal

, Meenakshi Kaushik

{[email protected]

, [email protected]

,[email protected]

}

Professor and HOD(Research), NDIM Delhi, India

, Associate Professor, NDIM, Delhi, India

Associate Professor and HOD, SIMS, Delhi, India

Abstract.Present study is to know the Determinants of intentions to use Grocery Apps in

India: The role of attitude and offers. Primary data based on structured questionnaire is

collected from consumers using grocery apps. Independent variables are taken attitude of

customers and offers provided. An intention to use grocery apps is treated as dependent

variable. attitude also affects the intention positively and significantly. Further analysis

can be done for relationship of customer satisfaction with independent variables.

Demographic perception may be scope for further studies.

Keywords:Grocery Apps, Innovation, Customers, Perception.

1 Introduction

With the aid of mobile apps and websites, the Internet simplifies every aspect of human

existence, from booking to purchasing. In order to maintain daily living, groceries are a must.

Over the years, the business of online grocery shopping in India 2022 has grown quickly. For

the majority of individuals, finding a list of items and waiting in line for payment makes going

to the supermarket a monotonous experience.Online grocery shopping apps make strides in the

app market to make people's jobs easier. With just a few clicks, this creative concept puts the

entire buying experience in your hands. People can save more time and have access to a variety

of new experiences by purchasing online.

India's economy is the one with the quickest rate of expansion and it has adapted to all

forms of technology over time. The country's best demonstration of Internet usage is online

commerce. Users are interested in purchasing food items, fresh produce, fruits, and other

grocery items online via the internet, just like they are in buying electrical appliances.Some of

the top Indian cities for online grocery shopping, according the report, include Bangalore,

Mumbai, Delhi, Hyderabad, Pune, and Chennai. These cities are the focus of many businesses

looking to use mobile apps to bring their concepts to life. Grocery app growth is accelerating,

much like online food delivery.

Apps for online shopping make it possible for anybody, anywhere to order groceries

online. The provided address will receive the ordered item at its doorstep. The shopping

software also provides a user with a variety of payment choices to complete the transaction.

ICASDMBW 2022, December 16-17, Delhi, India

DOI 10.4108/eai.16-12-2022.2326242

The entire procedure is quick, stress-free, and simple to use.Top 10 most popular Online

Grocery Shopping App:

 BigBasket

 Grofers

 ZopNow

 Amazon Pantry

 Flipkart Supermarket

 Nature’s Basket

 Spencer’s Online Grocery

 Paytm Mall

 DMart Online Grocery Shopping

 Reliance Smart

2 Attitude towards Grocery mobile app

Consumers' expectations that service providers may be trusted or depended upon to keep their

promises are referred to as state trust on attitude. Ability, customer believe, and compassion

are the three qualities that make up trust, which is a perception of competence. Consumer trust

is a result of service providers' capability to easily supply goods and services (Ganesan, 1994;

Pavlou, 2003). According to Sugandini et al. (2018), 2018a and 2018b, as well as Yuliansyah,

Rammal & Rose (2016) and Kim et al. (2016), trust is a factor in establishing long-term

commercial connections and can influence online purchases (2008). According to Suh et al.

(2015), the variable trust has a sizable favourable impact on customers' online purchase

intentions.

3 Intentions to use grocery mobile app

The primary factor impacting real purchasing behaviour is consumer attitude toward online

shopping (Baba & Siddiqi, 2016). According to Kothari & Maindargi (2016), shoppers have

the best alternative while making online purchases thanks to online buying attitudes.

4 Offers

Cheap deals and better prices are available online, because products come to you direct from

the manufacturer or seller without involving middlemen. Plus, it's easier to compare prices and

find a better deal. Many online sites offer discount coupons and rebates, as well.

5 Literature Review

In their study, Rakesh, T S, and S Madhushree (2015) looked at how socio demographic

factors (such as age, income, and occupation) and buy perception affect consumers' attitudes

toward online shopping. They also looked at the best payment methods for making payments

while shopping online.

RadkaBauerova (2019) investigated whether pressure to incorporate new technology

into the purchasing process is felt equally by all customer generations and how consumer

behaviour may be influenced by prior adoption of online grocery shopping. The acceptability

of online grocery shopping is a predictor of favourable opinion of other technologies in

retailing, according to this study, which offers a fresh perspective on online and offline

generations of consumers. In order to streamline corporate procedures and maximize the usage

of the workforce, managers should take initiatives to enhance technology adoption in their

establishments. The possibilities for conventional shops to enter the online industry are also

illustrated in this study.

Avinash K S and S Srivastava (2022) concentrated on big basket for online grocery

buying. Technology is used to promote marketing initiatives and sell products via online

shopping and marketing. We offer the most inexpensive pricing for Indian grocery products

that one may purchase online. Customers purchase products from online retailers based on

features including deals and discounts, a wide selection of products, free home delivery,

website usability, and the cash on delivery payment option. The online food store's

promotional discounts are drawing customers in (big basket). Numerous factors influence how

consumers see grocery shopping online.

Sabari S R and Nareshkkumar S (2018) sought to comprehend how consumers felt

about food shopping online and the influence of demographic factors on that view. The main

conclusions were that demographics had an impact on how consumers saw online grocery

shopping, that monthly savings and budget control were attainable, and that they also

identified the crucial factors to be taken into account.

As part of their investigation into Amazon, Chatterjee A and Roy P K (2020) gave us

a glimpse of their corporate strategy for the m-commerce sector and how it affects consumers'

perceptions in the interest of potential future business. The research's findings, however,

would also be helpful in understanding the factors that matter to customers when they are

making a purchase.

Anne K. and Tommi L. (2019) investigated how user engagement and suggestion

behaviour with a mobile grocery shopping application are influenced by utilitarian and

hedonic values. The study also looked at whether customer involvement, as measured by how

often they used the mobile app, affected how much money they actually spent.

Suguna S. and Pooja V. (2020) concentrated solely on big basket's online food

purchasing. Technology is used to promote marketing initiatives and sell products via online

shopping and marketing. We offer the most inexpensive pricing for Indian grocery products

that one may purchase online. Customers purchase things from an online retailer based on

considerations such as deals and discounts, the range of products offered, free home delivery,

website usability, and the cash on delivery payment option. The online food store's

promotional discounts are drawing customers in (big basket). Numerous factors influence how

consumers see grocery shopping online.

According to Mahesh V J and Hari P (2020), improving packing, tracking, payments,

prices, and delivery schedules has a positive linear link with how customers perceive and

behave. The purpose of this study is to understand how customers perceive a product delivery.

Four situational elements, according to Huang and Oppewal (2006), influence

consumers' preference for certain purchasing channels. Consumer purchasing behaviour,

online delivery fees, grocery retailing, choice experiments, and Internet shopping It was also

determined that, when influence is taken into account, delivery fees are not the most crucial

element. The relative preference to shop in-store or online was more affected by a fifteen

minute difference in travel time to the food store than by a delivery fee.

Goethals (2012) discussed supermarket delivery and plans to make online grocery

purchases. If domestic shipping is made available, some customer firms plan to start offering

e-groceries, but they are not willing to pay much for transportation. Furthermore, willingness

to pay is unrelated to the distance to the store or the length of the shopping trip, which could

aid supermarkets in defraying costs.

For shops involved in e-commerce, excellent delivery service is becoming more and

more important, according to Tandon and Kiran (2018). In order to better serve their clients,

many are therefore interested in transferring from their existing service to one that is more

generally successful. Better carriers charge more, therefore the merchant will either have to

get a revenue reduction or pass the transportation expense on to their customers as a result of

this switch.

The impact of perceived utility and perceived simplicity of use on customer

purchasing behaviour for online grocery use in Melaka was explored by Fong C M (2020),

who came to the conclusion that these factors have a substantial impact on consumer

behaviour.

The reason why a consumer is eager to buy for groceries online is because of the

perceived convenience of doing so and the potential time savings, according to Morganosky

and Cude (2000).

According to Shipra A, Snehal, and Tushar K (2021), consumers' purchasing habits

when they shop for groceries online are entirely different from those when they purchase at

real marketplaces. This study aimed to quantify sustainability and comprehend consumer

perceptions of online food purchasing. The present pandemic crisis has encouraged people to

purchase for goods online and instilled confidence in the customers, giving the online grocery

industry a more secure future. However, it is critical to examine the market when things have

normalized in order to gauge sustainability.

6 Research Methodology

Present study is exploratory in nature.

7 Objectives of the study

To find out factors Grocery Apps is India: a breakthrough innovation in retailing from

customers’ perspective.

8 Data used

Primary data is used on structured questionnaire.

9 Scale of study

Table 1.Scale of Study considered for Examination

Variable

Authors Details

Attitude

(Ganesan, 1994; Pavlou, 2003). Yuliansyah, Rammal & Rose

(2016) and Kim et al. (2016 Suh et al. (2015)

Offers

RadkaBauerova (2019), Suguna S. and Pooja V. (2020)

Intention to purchase

Baba & Siddiqi, 2016). Kothari & Maindargi (2016),

10 Statement description

Table 2.Statement Description

Coding

Attitude towards Grocery mobile app

Att1

Purchasing food using grocery app is wise.

Att2

Purchasing food using grocery app is good

Att3

Purchasing food using food panda mobile app is

sensible

Att4

Purchasing food using grocery app is rewarding.

Coding

Intentions to use grocery mobile app

Intent1

I intend to continue using grocery app in the future

Intent2

I will always try to use grocery app in my daily life.

Intent3

I plan to continue to use grocery app frequently.

Intent4

I have decided to use grocery mobile app for

purchasing foods the next time.

Coding

Offers

Offer1

I use grocery apps due to offers like discounts

Offer2

I use grocery apps due to offers like money back in

case of non satisfactory quality

Offer3

I use grocery apps due to offers like money back in

case of non satisfactory quantity

Offer4

I use grocery apps due to offers like money back in

case of non satisfactory size/colour

Offer5

I use grocery apps due to offers like money back in

case order not delivered on time

Source: Author’s own presentation

11 Empirical Result and discussion

This study examines the impact of offers and attitude of grocery app on intention to use.

Before employing documenting the regression outcome, we present descriptive statistics and

reliability of these constituent variables (offers, attitude and intention) in table 3. The result is

obtained based on 416 responses. It is observed that offer has highest mean (3.23) followed by

intention (3.21) and use (3.20). Further, the reliability of intention is high (0.92) comparatively

amongst constituent variables. For any construct the reliability has to be more than 0.6 which

is considered as the benchmark which is found in case of each considered variable. Table 4

encapsulates the degree of association (correlation) amongst offers, attitude and intention. We

observe that there is evidence of positive correlation amongst constructs. Interestingly,

intention and attitude are highly correlated (0.869) while followed by offers and attitude

(0.338). The least correlation is witnessed between attitudes and offers (0.338).

Table 3. Descriptive Statistics and Reliability

Offers

Mean

Std. Deviation

Mean

Reliability

Offer2

416

3.68

1.314

.822

Offer1

416

3.27

1.385

3.23

Offer4

416

3.07

1.198

Offer3

416

3.05

1.145

Offer5

416

2.91

1.176

Valid N (listwise)

416

Intention

Mean

Std. Deviation

Mean

Reliability

Intent1

416

3.55

1.363

.92

Intent4

416

3.38

1.195

3.21

Intent3

416

3.03

1.154

Intent2

416

2.81

1.247

Valid N (listwise)

416

Attitude

Mean

Std. Deviation

Mean

Reliability

Att3

416

3.41

1.401

0.91

Att2

416

3.19

1.369

3.20

Att1

416

3.05

1.440

Att4

416

2.90

1.271

Valid N (listwise)

416

Source: Author’s own presentation

Table 4.Correlations Matrix of considered variables

Intention

Offers

Attitude

Pearson Correlation

Intention

1.000

.242

.869

Offers

.242

1.000

.338

Attitude

.869

.338

1.000

Sig. (1-tailed)

Intention

.000

Offers

.000

Attitude

.000

Intention

416

Offers

416

Attitude

416

Source: Author’s own presentation

Table 5 furnishes the results obtained from multiple regressions in which model summary and

coefficients are considered. Overall, the model is fit as jointly the beta of both independent

variables is significant. Further, considering the impact, it is found that offers affect negatively

to the intention to use as its coefficient is negative. It infers that each unit of offers decreases

the intention by 0.065 units. Further, attitude also affects the intention positively and

significantly. It is documented that each unit of attitude increases the intention by 0.94 units.

Referring to the most significant variable, we notice that attitude is more important variable

then offers as its standard beta is high (0.889).

Table 5. Results obtained from multiple regressions Model Summary

Model

Square

Adjusted R Square

Std. Error of the Estimate

.871a

.758

.757

.592

As regards with variation of intention by both independent variables (offers and attitudes), it is

noticed that its R-squared is 87.1% .

Table 6. Results of Significance

Model

Unstandardized

Coefficients

Standardized

Coefficients

Sig.

95.0% Confidence

Interval for B

Std.

Error

Beta

Lower

Bound

Upper

Bound

(Constant)

.406

.107

.000

.196

.616

Offers

-.065

.028

-.059

.023

-.120

-.009

Attitude

.947

.027

.889

.000

.893

1.001

Source: Author’s own presentation

Further, R-squared is also computed to determine the corrected goodness of fit. Table 6 shows

the adjusted R-squared is 75.7% which adjusts the number of terms. Following is an equation

considered for this study: Intention = 0.406-0.065 offers+ 0.947 attitude.

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