Impulse buying behaviour at the retail checkout: an investigation of select antecedents

Abstract

The remarkable growth of the Indian retail landscape over the last decade is reflected in the proliferation of supermarkets, departmental stores and hypermarkets in India. Evolving consumption patterns, raising living standards has sparked a huge demand in the food and grocery retailing. Impulse buying is a time-tested tactic by which retailers grab customer’s attention and boost average purchase value. Prior research has deliberated extensively on impulse buying in the store and its determinants. However, little effort has been made to examine the impulse buying behaviour, particularly at the retail checkout. To bridge this gap, we conducted an empirical study in the leading food and grocery modern retail stores in selected Tier I and Tier II cities in the state of Karnataka, India. The data was collected from 385 respondents using a structured questionnaire. The responses were analysed using confirmatory factor analysis and multiple regression.
Our study shows that impulse buying at the store checkout area is minimal and sporadic for most of the product categories at the checkout. Impulse buying at the checkout is instigated by factors such as store environment, credit card availability, momentary mood, in-store promotion, offers and discounts and large merchandise. The study has important implications for retail stores by emphasising on the choice of merchandise offered for sale at the checkout area. Further, the investigation reveals that Indian shoppers are health-conscious and cautious about their purchase at the checkout rather than being
impulsive.

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Copyright © 2021 e Author(s). Published by Vilnius Gediminas Technical University
is is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unre-
stricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
*Corresponding author. E-mail: thiqbal34@gmail.com
Business: Theory and Practice
ISSN 1648-0627 / eISSN 1822-4202
2021 Volume 22 Issue 1: 69–79
https://doi.org/10.3846/btp.2021.12711
service encounters (Maister, 1985; Taylor, 1994; Van Riel
et al., 2012; Schimmel & Bekker, 2013; Weiss & Tucker,
2018; Ullal & Hawaldar, 2018; Hawaldar et al., 2019).
Waiting at the checkout area is usually alleged as an un-
productive time that does not create any value for the cus-
tomer (Nethravathi et al., 2020; Van Riel et al., 2012). e
checkout lane is anked by the attractive product displays
having a low cost, high margin to stimulate impulse buy-
ing (Nathanson, 2013). From the store’s perspective, wait-
ing at the checkout is an opportunity to raise additional
revenue (Weiss & Tucker, 2018; Ullal et al., 2020).
Pugliese (1998) reported about 69% of the magazines
bought as an impulse buy at the checkout counter and per-
ceived as a “want” by the customers in the U.S. A drop in
impulse buying of candies and magazines were observed
in Quincy, Massachusetts when the customers availed self-
checkout over staed counters (Vinish et al., 2021; Adams,
2006). Hilliard (2014) shared evidence of impulse buying
IMPULSE BUYING BEHAVIOUR AT THE RETAIL CHECKOUT:
AN INVESTIGATION OF SELECT ANTECEDENTS
Vinish PALLIKKARA 1, Prakash PINTO 2, Iqbal onse HAWALDAR 3*, Slima PINTO 4
1, 2, 4Department of Business Administration, St Joseph Engineering College, Mangaluru, Karnataka, India
3Department of Accounting & Finance, College of Business Administration, Kingdom University, Bahrain
Received 13 May 2020; accepted 3 August 2020
Abstract. e remarkable growth of the Indian retail landscape over the last decade is reected in the proliferation of su-
permarkets, departmental stores and hypermarkets in India. Evolving consumption patterns, raising living standards has
sparked a huge demand in the food and grocery retailing. Impulse buying is a time-tested tactic by which retailers grab
customer’s attention and boost average purchase value. Prior research has deliberated extensively on impulse buying in the
store and its determinants. However, little eort has been made toexamine the impulse buying behaviour, particularly at
the retail checkout. To bridge this gap, we conducted an empirical study in the leading food and grocery modern retail
stores in selected Tier I and Tier II cities in the state of Karnataka, India. e data was collected from 385 respondents
using a structured questionnaire. e responses were analysed using conrmatory factor analysis and multiple regression.
Our study shows that impulse buying at the store checkout area is minimal and sporadic for most of the product categories
at the checkout. Impulse buying at the checkout is instigated by factors such as store environment, credit card availability,
momentary mood, in-store promotion, oers and discounts and large merchandise. e study has important implications
for retail stores by emphasising on the choice of merchandise oered for sale at the checkout area. Further, the investiga-
tion reveals that Indian shoppers are health-conscious and cautious about their purchase at the checkout rather than being
impulsive.
Keywords: impulse buying, grocery retailing, in-store promotion, situational factors, external factors, retail checkout.
JEL Classication: D91, L21, L81, M31.
Introduction
Indian retail industry is the h-largest in the world and
is one of the most preferred, fast-growing global destina-
tion for retail space (FICCI, 2020; IBEF, 2019). e organ-
ised retailing share is anticipated to grab a market share of
22% by 2021, while the share of organised grocery stores
and departmental chain stores is expected to touch 18%
during the same period (Suneera, 2019). e modern food
and grocery retail in India largely comprise of supermar-
kets and hypermarkets formats and are fast expanding due
to evolving consumer preferences (Sandoval & Sawant,
2019). Most of the Indian department stores have shared
checkout at the entrance/exit area of the store (Pataskar,
2011; Fatima, 2013, p. 44). e eciency of the checkout
was observed to be poor in western Maharashtra, a highly
developed urban zone in India (Pataskar, 2011, p. 202).
Researchers in the past oen attributed checkout as a
compelling, unavoidable and common experience in retail

70 V. Pallikkara et al. Impulse buying behaviour at the retail checkout: an investigation of select antecedents
of items such as beer, aerated so drinks, candy bars, chips
and ice-creams by the American citizens at the checkout
aisles in the food retail stores. According to a study by
Nielsen in 2012, the impulse potential can be increased by
positioning items near the store entrance or exit (Hilliard,
2014). is argument is true in the case of Coca Cola
where more than 70% of its sales are through impulse buy-
ing as stated by the CEO Mr Muhtar Kent (Vinish et al.,
2020; Karmali, 2007). Placing confectionary items near the
checkout was eective in attracting small kids who pester
their parents for purchasing the same (Raju et al., 2015).
Impulse goods at the checkout generate good margins
without aecting sales of items displayed in other areas
of the store due to its exclusive placement near the billing
counter (Vinish et al., 2020; Eder, 2002; Iyer, 1989).
While impulse sales are a huge opportunity to boost
overall prot, Ghosh et al. (2010) advocate that custom-
ers visiting the stores expect fast and ecient billing sys-
tem, which could be a hindrance to impulse buying at
the checkout. According to Bettman (1979), the amount
of time available regulate the degree of information pro-
cessed. Iyer (1989) suggests that in the absence of time
pressure customers search for in-store queues and are
more likely to make an unplanned purchase in the con-
text of a grocery store. Beatty and Ferrell (1998) found a
positive relationship between the time available and the
prospect of making an impulse buy. However, we have
not come across any convincing evidence to conrm the
impact of the presence of time pressure (faster checkout)
or absence of time pressure on impulse buying behaviour
precisely at the checkout counter.
Prior work on impulse purchase was focused on an-
tecedents such as personal characteristics like shopping
enjoyment and impulse buying tendency (Beatty & Fer-
rell, 1998; Weun et al., 1998; Sharma al., 2010), optimum
stimulation level (Nethravathi et al., 2020; Sharma et al.,
2010), product-specic conceptualization and involve-
ment (Jones et al., 2003), and situational variables such as
time and money available (Beatty & Ferrell, 1998), point-
of-purchase signboards (Peck & Childers, 2006), product
display (Ghani & Kamal, 2010), point-of-purchase posters
featuring discount information (Zhou & Wong, 2003).
Store characteristics such as in-store atmosphere and
customer’s emotional state (Vinish et al., 2021; Sherman
etal., 1997), lighting, music and social factors such as sales-
people attire and approach, merchandise quality (Baker
et al., 1994), pricing and store image (Wheatley & Chiu,
1977), shopping satisfaction (Bitner, 1990) were found to
inuence store preferences, the volume of purchase made,
time and money spent in the store. Tauber (1972) suggest-
ed the need for socialising and peer group attraction as
the reasons for visiting the stores. Presence of social cues
and service quality drive favourable attitude towards the
store and shopping arousal (Hu & Jasper, 2006). Mohan
et al. (2013) explored the synergy among environmental
factors, individual factors and impulse buying behaviour.
Nonetheless, there exists limited research on the inuence
of the above factors on impulse buying behaviour at the
retail checkout in the Indian context. us, this study aims
to analyse the impulse purchase of merchandise displayed
at the store’s checkout area; assess the impact of situational
factors and external stimuli on the impulse purchase of
products displayed at the checkout.
1. Literature review
Retailers have well acknowledged the sales generated
through impulse buying (Clover, 1950), and hence it gave
rise to considerable research interest (cf. Stern, 1962; Kol-
lat & Willett, 1969; Rook, 1987; Peck & Childers, 2006;
Ali & Hasnu, 2013). Stern (1962) rened the meaning of
impulse buying and classied impulse buying mix as pure,
reminder, suggestion and planned. Exposure to in-store
stimuli such as POP displays, price-o sales promotions,
coupons and sampling, in-store siting, on-shelf product
placements and demonstrations can lead to impulse buy-
ing decisions signicantly (Abratt & Goodey, 1990). Kollat
and Willett (1967) contend that in-store stimuli remind
the customers of their present or future needs. Impulse
purchase involves the minimal expenditure of resources
like time, physical and mental eort, and money (Ullal
et al., 2020; Stern, 1962). A study by Abratt and Goodey
(1990) showed customers spend more money than in-
tended, which is against the views of Kollat and Willet
that “there is a strong tendency for actual expenditure to
approximate spending intentions”.
Raju et al. (2015) attributed higher impulse buying
behaviour among customers in oine stores due to the
gratication they derive through immediate possession or
consumption. Prior knowledge about new products com-
plemented by the desire for shopping pleasure and esteem
boost impulse buying intention and thus leading to buying
behaviour (Harmancioglu et al., 2009).
e determinants of impulse buying are classied as
store attributes, customer characteristics, situational fac-
tors and product features (Raju et al., 2015). is study
takes into consideration the impact of situational and ex-
ternal factors on impulse buying at the checkout area.
1.1. Situational factors
Belk (1975) described situations and recognised per-
sonal, environmental and social aspects of retail shop-
ping as situational variables. Situational factors such
as store environment, customer mood and impulsivity
trait could determine the intensity of consumption im-
pulse experienced (Dholakia, 2000). Substantial research
within social psychology indicates positive mood state of
customers enhance their sensation-seeking tendency and
weaken the prospect of systematic information process-
ing (see Schwarz & Bohner, 1996). Mischel and Mischel
(1983) claim that physical proximity could trigger posi-
tive memories associated with the product’s consumption
in the past and are likely to encourage the desire to buy.
Park et al. (1989) explored the eect of situational factor
“time available for shopping” on unplanned buying and

Business: eory and Practice, 2021, 22(1): 69–79 71
found a positive relationship between the two. According
to Beatty and Ferrell (1998) and Foroughi et al. (2014)
time and money availability are important situational fac-
tors inuencing the urge to buy impulsively and eventually
making an impulse purchase. Innovations such as credit
cards (Ullal etal., 2021; Omar & Kent, 2001; Bhakat &
Muruganantham, 2013; Bhuvaneswari & Krishnan, 2015),
availability of online stores 24 hours a day (Pradhan, 2016)
have induced impulse purchase.
Rook (1987) argued that perceived impulse buying in-
tensity and the ability to control the impulses vary among
customers. Kacen and Lee (2002) stated that independent
customers are more impulse buying oriented as compared
to dependent customers. “Highly impulsive buyers are
more likely to experience spontaneous buying; their shop-
ping lists are more “open” and receptive to sudden, unex-
pected buying ideas” (Rook & Fisher, 1995, p. 306). Bell et
al. (2011) point out the variation in pricing, variety, loca-
tion and store ambience among retail formats could lead
to disparity in in-store buying decisions. Pradhan (2016)
examined the factors persuading impulse buying in Kath-
mandu supermarkets and found reference groups (family
and friends) as one of the signicant attributes triggering
impulse purchase. Luo (2005) made a contrasting conclu-
sion about the behaviour of customers where their urge
to buy impulsively increased during the presence of peer
customers while it decreased during the presence of family
members. Based on the above discussion, we hypothesise:
H1: Situational factors contribute positively to impulse
buying at the retail checkout.
1.2. External stimuli
Applebaum (1951) was one of the early researchers who
suggested in-store stimuli such as display, pricing, sales
conversations and demonstrations as a catalyst for impulse
purchase by the customers. Bhakat and Muruganantham
(2013) mentioned lighting, layout, xtures, colour, sound,
odour, oor coverings and behaviour of sta inuencing
the retail store atmosphere. Youn and Faber (2000) de-
scribed external stimuli as specic triggers connected with
shopping and managed by marketers to entice customers
to purchase action. It includes dealing with shopping en-
vironment (i.e. Store ambience, size, design and format)
and marketing environments such as sales and advertising
activities (Bhakat & Muruganantham, 2013). Piron (1991)
points to four dimensions of stimuli connected with im-
pulse buying viz (1) response to marketing reminders
or recommendations (Stern, 1962), (2) manipulation of
store atmosphere (Kotler, 1974), POP display (see Shimp
& DeLozier, 1986) and product positioning (Berkman &
Gilson, 1986), (3) non-satisfactory or unavailable planned
purchases (Iyer & Ahlawat, 1987), and (4) customer-gen-
erated non-environmental persuaded stimulation.
Customers also face an urge to make an impulse pur-
chase when confronted with visual inducements such as
promotional oers (Ullal et al., 2021; Dholakia, 2000).
Buying impulses essentially activate with individual’s
sensation and perception determined by external stimuli
resulting in a sudden urge to buy (Rook & Hoch, 1985).
In large stores stimuli such as merchandise display, price,
store environment and the large variety form the key mo-
tives for an impulse purchase (Gupta et al., 2009). While
in small stores product price continued to be the prime
factor for an impulse purchase. Yu and Bastin (2010) de-
liberated on the role of store employees in motivating and
complementing customers, thus leading to impulse buy-
ing. Atulkar and Kesari (2018) and Husnain et al. (2019)
mentioned that friendly employees play an important role
in an impulse purchase. Badgaiyan and Verma (2015)
reected on family inuence on impulse buying. Social
interaction among customers and with their friends, rela-
tives during the shopping mostly inuence them to spend
more time in the store and make impulse buying decisions
(Baron et al., 1996). Lin and Chen (2012) concluded that
impulse buying tendency tends to be higher when the sus-
ceptibility to interpersonal inuence is more. Based on the
above and in line with (Bhakat & Muruganantham, 2013),
we hypothesise:
H2: External stimuli positively lead to impulse buying
at the retail checkout.
2. Methodology
2.1. Sample designing and data collection
We have followed a single-stage mall intercept survey
method to gather responses much like earlier studies (e.g.:
Beatty & Ferrell, 1998; Sharma et al., 2010; Mohan et al.,
2013). e respondents include both resident and tourist
customers the Indian state of Karnataka.
According to MSME-Development Institute (2016),
Karnataka is the “one of the most progressive and in-
dustrialized states in the country and is leading States in
driving India’s economic growth”. e state is popularly
hailed as Silicon Valley of India with a population of more
than 61 million with fourth highest FDI in the country
(KPMG, 2018). e state recorded IT exports worth US$
77.80 billion in the year 2018–19 (IBEF, 2020), and is the
4th largest technology cluster in the world (IBEF, 2018). In
terms of Human Development Index, the state shares the
nineteenth rank (Global Data Lab, 2019) in the country.
e NASSCOM-AT Kearney Report (2017) has identi-
ed four major cities in Karnataka viz. Bengaluru (leader
location), Mangaluru (challenger location), Hubballi-
Dharwad and Mysuru (aspirant location) for its business
potential. e study, therefore, considered a sample of
385 customers (convenience sampling method) visiting
the leading retail stores such as two supermarkets namely
Nilgiris and More, and two hypermarkets i.e. Big Bazaar
and Spar in leading Tier I (Bengaluru) and Tier II (Man-
galuru, Mysuru, Hubballi-Dharwad) cities in the state of
Karnataka, India.
e stores selected for the study have Pan India pres-
ence oering a wide range of branded merchandise such
as grocery, fruits and vegetables, bakery, meat, dairy

72 V. Pallikkara et al. Impulse buying behaviour at the retail checkout: an investigation of select antecedents
products, poultry, personal care and plastics. Big Bazaar
and Spar also oer larger products like textiles, electron-
ics, IT products besides oering products sold in More
and Nilgiris stores. Moreover, the stores have a unique
layout, large product display, checkout layout and num-
ber of counters, choice of products, oers and discounts,
trained sta and unique dress code, and are intended to
encourage customers’ emotions and purchase behaviour.
e study explores the inuence of situational and exter-
nal factors on the impulse buying behaviour of customers,
particularly at the store checkout area. e constructs and
the scale items used in this study are borrowed from the
literature study and modied to suit the present study.
2.2. Convergent and discriminant validity
Convergent and discriminant validities are two vital parts
of construct validity. e discriminant validity depicts
the construct that not only should correlate with related
variables, but it also should not correlate with dissimi-
lar and unrelated ones. Convergent validity illustrates by
what means the new scale is related to other variables and
other measures of the same construct (de Vet et al., 2011;
Streiner et al., 2015). e study examines the concurrent
validity of the respondents’ impulse buying behaviour
with situational and external factors, using convergent and
discriminant analysis.
Table 1 shows the convergent validity of the situational
factors with seven items. Convergent validity examines the
strength of the variables.
From Table 1, it is observed that there exists a strong
correlation between the variables of situational factors,
with p-value 0.000 < 0.005 at 1% signicance level.
Table 2. Discriminant validity of situational factors
Wilks’
Lambda F df1 df2 Sig.
Money availability .973 2.641 4 380 .034
Time availability .946 5.467 4 380 .000
Family inuence .932 6.904 4 380 .000
Social Inuence .921 8.125 4 380 .000
Store environment .857 15.916 4 380 .000
Credit card
availability .830 19.398 4 380 .000
Momentary Mood .857 15.868 4 380 .000
Table 1. Correlation between the variables of situational factors
Money
availability
Time
availability
Family
inuence
Social
Inuence
Store
environment
Credit card
availability
Momentary
Mood
Money
availability
Pearson
Correlation 1 .424** .334** .299** .235** .169** .385**
Sig. (2-tailed) .000 .000 .000 .000 .001 .000
N 385 385 385 385 385 385 385
Time availability
Pearson
Correlation .424** 1 .244** .252** .320** .224** .329**
Sig. (2-tailed) .000 .000 .000 .000 .000 .000
N 385 385 385 385 385 385 385
Family inuence
Pearson
Correlation .334** .244** 1 .472** .184** .245** .187**
Sig. (2-tailed) .000 .000 .000 .000 .000 .000
N 385 385 385 385 385 385 385
Social Inuence
Pearson
Correlation .299** .252** .472** 1 .277** .335** .325**
Sig. (2-tailed) .000 .000 .000 .000 .000 .000
N 385 385 385 385 385 385 385
Store
environment
Pearson
Correlation .235** .320** .184** .277** 1 .403** .311**
Sig. (2-tailed) .000 .000 .000 .000 .000 .000
N 385 385 385 385 385 385 385
Credit card
availability
Pearson
Correlation .169** .224** .245** .335** .403** 1 .269**
Sig. (2-tailed) .001 .000 .000 .000 .000 .000
N 385 385 385 385 385 385 385
Momentary
Mood
Pearson
Correlation .385** .329** .187** .325** .311** .269** 1
Sig. (2-tailed) .000 .000 .000 .000 .000 .000
N 385 385 385 385 385 385 385
** Correlation is signicant at the 0.01 level (2-tailed).

Business: eory and Practice, 2021, 22(1): 69–79 73
Table 2 presents that the independent variables of situ-
ational factors are signicant at 0.000 < 0.005. Hence, the
discriminant dimensions are highly signicant and show
a strong relationship.
Table 3 interprets the convergent validity of external
factors with eight items. e strength of the variables is
measured through convergent validity.
Table 3 shows a strong correlation between the vari-
ables of external factors, with p-value 0.000 < 0.005 at 1%
signicance level.
Table 4 shows that the independent variables of ex-
ternal factors are signicant at 0.000 < 0.005. Hence, the
discriminant dimensions are highly signicant and show
a strong relationship.
Table 3. Correlation between the variables of external factors
In-store
promotion
Oers &
discounts
Bonus
Packs
Large
merchandise
Product
placement
Peer
inuence
In-store
service
Friendly
employees
In-store
pro-
motion
Pearson
Correlation 1 .499** .450** .228** .334** .377** .247** .276**
Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000
N 385 385 385 385 385 385 385 385
Oers
and dis-
counts
Pearson
Correlation .499** 1 .680** .378** .357** .449** .325** .376**
Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000
N 385 385 385 385 385 385 385 385
Bonus
Packs
Pearson
Correlation .450** .680** 1 .470** .369** .480** .302** .367**
Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000
N 385 385 385 385 385 385 385 385
Large
mer-
chan dise
Pearson
Correlation .228** .378** .470** 1 .494** .397** .499** .435**
Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000
N 385 385 385 385 385 385 385 385
Product
place-
ment
Pearson
Correlation .334** .357** .369** .494** 1 .558** .447** .428**
Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000
N 385 385 385 385 385 385 385 385
Peer
inu-
ence
Pearson
Correlation .377** .449** .480** .397** .558** 1 .487** .421**
Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000
N 385 385 385 385 385 385 385 385
In-store
service
Pearson
Correlation .247** .325** .302** .499** .447** .487** 1 .765**
Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000
N 385 385 385 385 385 385 385 385
Friendly
emp-
loyees
Pearson
Correlation .276** .376** .367** .435** .428** .421** .765** 1
Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000
N 385 385 385 385 385 385 385 385
** Correlation is signicant at the 0.01 level (2-tailed).
Table 4. Discriminant validity of external factors
Wilks’
Lambda F df1 df2 Sig.
In-store promotion .914 8.897 4 380 .000
Oers and discounts .946 5.439 4 380 .000
Bonus Packs .899 10.658 4 380 .000
Large merchandise .898 10.823 4 380 .000
Product placement .908 9.590 4 380 .000
Peer inuence .924 7.822 4 380 .000
In-store service .919 8.399 4 380 .000
Friendly employees .944 5.609 4 380 .000

74 V. Pallikkara et al. Impulse buying behaviour at the retail checkout: an investigation of select antecedents
2.3. Reliability statistics for the impact of various
factors on impulse buying behaviour at the retail
checkout
e eect of various factors on impulse buying behaviour
among the respondents is measured through 15 variables
derived from the literature using a ve-point Likert scale.
Table 5. Reliability statistics
Cronbach’s
Alpha
Cronbach’s Alpha Based
on Standardized Items N of Items
0.863 0.865 15
The calculated Cronbach’s Alpha of 0.865 (refer
Table5) indicates that there is a very high level of internal
consistency for 15 items dened, which intern concludes
the scale used to measure factors on impulse buying is
behaviour is highly reliable.
3. Data analysis and ndings
3.1. Demographic prole
e sample consists of 36.1% of the respondents be-
longing to the age group of 31−40 years, 35.8% of the
respondents from the category 21−30 years, 22.3% of
the respondents belong to 41−50 years, 4.7% of the re-
spondents belong to >50 years and 1% of the respond-
ents below 20 years. Majority of the respondents are
women (54.5%) followed by men (45.5%). 61.6% of the
respondents are married, while 37.4% are unmarried, 1%
is widowed and none are divorced. Most of the respond-
ents (35.8%) visited More supermarket, 26.8% visited
Spar hypermarket, 26% visited Big Bazaar Supermarket
and 11.4% visited Nilgiris supermarket. 37.7% of the re-
spondents predominantly visited the store weekly, 33.8%
visited monthly, 9.9% visited occasionally and few (3.1%)
visited bi-monthly. Table 6 provides an analysis of the
data obtained from the survey.
3.2. Factor analysis of the variables inuencing
impulse buying behaviour
Factor analysis is conducted to describe the variability
among observed, correlated variables into a potentially
lower number of unobserved variables.
Kaiser-Meyer-Olkin (KMO) = 0.823 > 0.50 (refer Ta-
ble7), indicates that the sample size is sucient to con-
duct factor analysis.
Table 6. Demographic prole
  Count Percentage
Age
<20 years 4 1.00%
21−30 years 138 35.80%
31−40 years 139 36.10%
41−50 years 86 22.30%
>50 years 18 4.70%
Tota l 385 100.00%
Gender
Male 175 45.50%
Female 210 54.50%
Tota l 385 100.00%
Marital
Status
Single 144 37.40%
Married 237 61.60%
Divorced 0 0.00%
Widowed 4 1.00%
Tota l 385 100.00%
Store
visited
More Supermarket 138 35.80%
Nilgiris
Supermarket 44 11.40%
Big Bazaar
Hypermarket 100 26.00%
Spar Hypermarket 103 26.80%
Tota l 385 100.00%
Frequency
of visit
Week l y 145 37.70%
Fortnightly 60 15.60%
Monthly 130 33.80%
Bi-monthly 12 3.10%
Occasionally 38 9.90%
Tota l 385 100.00%
Table 7. KMO and Bartlett’s test
Kaiser-Meyer-Olkin Measure of Sampling
Adequacy 0.823
Bartlett’s Test of
Sphericity
Approx. Chi-Square 2150.057
Df 105
Sig. 0.000
Table 8. Total variance explained
Com-
ponent
Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings
Tota l % of
Variance
Cumulative
%Tota l % of
Variance
Cumulative
%Tota l % of
Variance
Cumulative
%
1 5.303 35.353 35.353 5.303 35.353 35.353 4.082 27.212 27.212
2 1.594 10.628 45.980 1.594 10.628 45.980 2.815 18.768 45.980
e Bartlett’s test p-value is 0.000 < 0.05, therefore
there exists a correlation between variables and thus fac-
tor analysis can be carried out.
Table 8 represents that the rst factor accounts for
35.35% of the variance. e second factor accounts for
10.62% of the variance. All the remaining factors are not
signicant.

Business: eory and Practice, 2021, 22(1): 69–79 75
e variables are loaded into two factors. Table 9 pres-
ents the same.
Table 9. Factor loadings for the inuencing factors
Factor Items included
Rotated
Component
matrix
Name
of the
factor
Percentage
Contri-
bution
Factor 1
Friendly
employees 0.742
External
factors 35.35%
In-store
service 0.737
Peer inuence 0.698
Oers and
discounts 0.697
Bonus Packs 0.694
Large
merchandise 0.687
Product
placement 0.640
In-store
promotion 0.509
Factor 2
Time
availability 0.709
Situa-
tional
factors
10.62%
Family
inuence 0.642
Money
availability 0.638
Social
Inuence 0.619
Momentary
Mood 0.592
Credit card
availability 0.474
Store
environment 0.468
e antecedents of impulse buying are classied into
external and situational factors. Among the two, the ex-
ternal factors emerged to be the leading determinant of
impulse buying behaviour at the retail checkout with the
factor loading 35.35%. Also, variables such as “friendly
employees” and “in-store service” under external factors
are found to highly inuence the impulse buying behav-
iour. Whereas in situational factors, “time availability” is
found to have highest bearing on the impulse buying be-
haviour.
3.3. Impact of situational and external factors on
impulse buying behaviour
Multiple regression analysis was performed by consider-
ing seven and eight factors concerning situational factors
and external factors as independent variables and impulse
buying behaviour “Make a spontaneous purchase at the
checkout area” as the dependent variable.
H1: Situational factors contribute positively to impulse
buying at the retail checkout.
Table 10. Inuence of situational factors on impulse buying
SL.
NO
Inde-
pen dent
Variables
Unstandardized
Coecients
Stan dar-
dized
Coe-
cients TSig.
BStd.
Error Beta
(Constant) 0.183 0.323 0.567 0.571
1Money
avail ability −0.074 0.061 −0.065 −1.226 0.221
2Time
avail ability −0.003 0.070 −0.002 −0.036 0.971
3Family in-
u ence 0.054 0.066 0.043 0.827 0.409
4Social in-
u ence 0.085 0.062 0.074 1.371 0.171
5Store en-
vi ron ment 0.197 0.062 0.162 3.170 0.002*
6
Credit
card avail-
ability
0.215 0.048 0.225 4.439 0.000**
7Momen-
tary Mood 0.318 0.063 0.257 5.008 0.000**
A. Dependent Variable: Make a spontaneous purchase at the
checkout area
Note: Signicant at: *0.05, ** 0.01 levels.
Table 11. Model summary
RR Square Adjusted R Square P-value
0.507 0.257 0.244 0.000**
Table 10 provides the standardised beta coecients
and p-value for the factors causing impulse buying be-
haviour. e result shows that among the seven factors,
three factors were statistically signicant, with a p-value
less than 0.05. ey are (1) “Store environment” (β =
0.162, p = 0.002), (2) “Credit card availability” (β = 0.225,
p = 0.000) and (3) “Momentary Mood” (β = 0.257, p =
0.000). Other factors have a low impact on impulse buying
behaviour. However, they are not statistically signicant.
Table 11 gives the adjusted R square value for impulse
buying behaviour. e overall impact of these factors on
the level of impulse buying was 24.4%. So, the hypothesis
H1 is accepted.
H2: External stimuli positively lead to impulse buying
at the retail checkout.
Table 12 provides the standardised beta coecients
and p-value for the factors causing impulse buying behav-
iour. e result shows that among the eight factors, three
factors were statistically signicant, with a p-value less
than 0.05. ey are (1) “In-store promotion” (β = 0.123, p
= 0.032), (2) “Oers and discounts” (β = 0.142, p = 0.041)
and (3) “Large merchandise” (β = 0.152, p = 0.016). Other
factors have a low impact on impulse buying behaviour.
However, they are not statistically signicant.

76 V. Pallikkara et al. Impulse buying behaviour at the retail checkout: an investigation of select antecedents
Table 13 gives the adjusted R square value for impulse
buying behaviour. e overall impact of these factors on
the level of impulse buying was 12.5%. So, the hypothesis
H2 is accepted.
4. Managerial implications
Retail checkout signicantly inuences the overall evalu-
ation of customer store service and shopping experience.
is study reveals some important ndings on impulse
buying at the retail checkout area. First, not all the prod-
uct categories at the checkout area receive the same atten-
tion and urge to buy impulsively. e results of the study
indicate that chocolates and personal care products are
oen bought by the customers impulsively, while other
product categories such as ready to eat foods, Tobacco
products, so drinks, batteries, kitchen accessories, sports
goods, stationery items and toys are rarely bought items.
Moreover, the shoppers are found to be health-conscious
by avoiding frequent purchases of tobacco products, so
drinks, ready to eat foods and chocolates. e results also
suggest that store managers need to carefully plan the
visual merchandising of the above product categories at
the checkout area to gain the attention of more buyers and
pursue them to impulse purchase.
Second, the regression analysis of situational construct
suggests that Indian shoppers are inuenced by store en-
vironment, momentary mood, and credit card availabil-
ity. Yoo et al. (1998) and Cottet et al. (2010) showed that
factors such as store design, lighting, colour, air quality,
music and decoration contribute to the pleasant mood
which in turn lead to impulse purchase behaviour. Credit
card companies encourage customers to shop more and
earn rewards. e increased usage of the credit cards by
customers aids the retailers to boost their revenue through
impulse sales. Retail stores should focus on cobranding
their stores with leading credit card companies as a sales
strategy.
ird, the in-store promotion, attractive oers and
discounts, and large merchandise have emerged to be
leading contributors to impulse buying under the exter-
nal factors. Indian Retailers continues to woo shoppers
by oering mouth-watering deals. is has heightened the
shoppers’ tendency to actively seek oers and discounts
at every point of purchase. us, last-minute sales can be
achieved by keeping the prices low, oering cashback and
deep discounts. Online players such as Amazon and Flip-
kart have been undercutting the prices to drive trac to
their websites. To stay competitive, oine retailers need to
consistently oer quality in-store service besides keeping
the prices low.
ough situational factors like money and time avail-
ability, family and social inuence are important anteced-
ents of impulse buying behaviour inside the store, our
study shows that these variables do not contribute to im-
pulse buying at the retail checkout in specic. is reects
weak impulse buying at the checkout, which is reected
in the purchase of two product categories out of ten cat-
egories available. Similarly, external factors such as bonus
packs, product placement, peer inuence, in-store service,
and friendly employees did not facilitate impulse buying
at the checkout. During the survey, it was observed that
the checkout area in the above stores is generally crowd-
ed and the shoppers were in a hurry to exit the billing
counter. e customers were also busily engaged in ob-
serving the queue movement, and the other lines at the
checkout, which validates Maister (1985) propositions
about the “e Psychology of waiting lines”. e interac-
tion between customers and employees were minimal at
the checkout area, as the billing sta were busy at their
work and other store stas were present near the aisles
managing the inventory. is also could have aected the
impulse buying at the checkout in specic.
Conclusions
Preceding studies on impulse buying in retail stores is
deeply ingrained in the western community and devel-
oped economies, while in developing countries is limited.
Moreover, the literature on impulse buying particularly at
the checkout area is very limited. e results of the study
will broaden the scope of impulse buying literature in In-
dia and other developing nations. Our study shows that
Table 12. Inuence of external factors on impulse buying
Sl
No
Independent
Variables
Unst an-
dardized
Coe cients
Stan-
dar-
dized
Coe-
cients tSig.
BStd.
Error Beta
(Constant) 0.835 0.327 2.554 0.011
1In-store pro-
motion 0.144 0.067 0.123 2.154 0.032*
2Oers and
discounts 0.191 0.093 0.142 2.047 0.041*
3Bonus Packs 0.168 0.094 0.128 1.794 0.074
4Large mer-
chandise 0.183 0.075 0.152 2.429 0.016*
5Product place-
ment 0.076 0.084 0.057 0.909 0.364
6Peer inuence 0.109 0.080 0.089 1.368 0.172
7In-store service 0.086 0.100 0.069 0.859 0.391
8Friendly
employees 0.026 0.091 0.022 0.285 0.776
a. Dependent Variable: Make a spontaneous purchase at the
checkout area
Note: Signicant at: *0.05, ** 0.01 levels.
Table 13. Model summary
RR Square Adjusted R Square P-Value
0.378 0.143 0.125 0.000**

Business: eory and Practice, 2021, 22(1): 69–79 77
impulse buying at the retail checkout is weak. Although
the prior research identied important determinants of
impulse buying in the store, our study shows that the In-
dian consumers are price and value-conscious and less im-
pulsive while waiting in the queue at the checkout area.
e customers oen make healthy product choices at the
checkout and are more focused on queue rather than on
the retail shelves at the checkout area. Researchers have ar-
gued in the past that the comparison of factors signicant
to impulse buying behaviour is limited. While the situ-
ational and external factors have a bearing on the impulse
buying behaviour at the checkout, our study hasn’t con-
sidered the impact of impulse buying tendency. Further
investigation could include this and bring out an integral
model on impulse buying behaviour.
Author contributions
Below are the authors’ contributions to this study:
– Vinish P wrote the rst dra of the article, validated
the research methodology, prepared the question-
naires, collected data, interpretated the result and
wrote the nal manuscript.
– Prakash Pinto validated the research methodology,
collected data, supervised the data analysis and in-
terpretation, revised the manuscript.
– Iqbal onse Hawaldar supervised and validated
the results and discussions and the nal manuscript
preparation.
– Slima Pinto collected data, conducted data analyses,
and interpreted the result.
Disclosure statement
e authors do not have any conict of interest.
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