Keywords

Retail, Consumer Behaviour, Mediation, Process Macro.

Introduction

According to (Agyekum, et al. 2015), the Indian retail industry was 883 US$, expected to be US$ 1.1 trillion by 2027 and US$ 2 trillion by 2032. The majority of 68% of the market is food and grocery, and 15% of lifestyle products in 2020. India is considered the quickest retail-growing and placed 73 in the United Nations Conference of Trade and Development in 2019 and 63 in World Bank Doing Business in 2020 (Ali et al. 2020). India is the world's fifth most preferred shopping destination. The online penetration in the retail industry is anticipated to increase from 4.7% in 2019 to 10.7% in 2024. India has invited US$ 4.11 billion FDIin between 2000 to 2022. Srivastava (2008); (Hayes, 2018) has focused that organized retail becoming part and parcel of Indian customers (Paromita Goswami, 2009) Focused on shifting consumers from the local Kirana stores to organized retail because of better customer service and cleanliness (Sharma, 2020) specifies that because of covid 2019, there is a shift in customer preference from regular independent stores to retail malls for convenience shopping (Hisam, et al. 2016) Emphasized the importance of service quality which attracts the consumer to the doorsteps of the retail store for purchase (Bawa, et al. 2013) has also emphasized the importance of value delivery to the customer in the long run despite the short-term benefits offered by the retailer. (Dineshkumar, 2012) has focused on customer engagement through word-of-mouth advertisement of their positive shopping experience with the retail store. Historically, India has been a country with Kirana Shops in retailing operations (Nagar-Haryana, 2012) defined retailing as any direct purchase of an individual consumer or end user. The organized retail business only emerged in the early 1990s. Until then, the unorganized sector controlled the industry. Customers need more choices in a seller's market with a restricted number of brands. The absence of educated labor, tax restrictions, and government regulations hindered the expansion of organized retailing in India at the time. Lack of customer knowledge and restrictions on foreign firms entering the market further slowed the rise of organized retailing. But in recent years, we are witnessing a change in the dimensions of retailing as an emergence of organized retailing. According to (Chattopadhyay, n.d.), since the arrival of major organized retailers, unorganized merchants' proportion of business and margins has decreased. This is primarily due to the rise in the income levels of the consumers. According to (Katole, 2012); (Agyekum et al., 2015) the study focused on the demographic factors of consumers in purchase decisions in retail. (Ramya, 2016) concluded perspectives on promotional efforts undertaken by the organized retail industry constitute a significant segment that all organized.

According to (Chattopadhyay, 2019), India's consumer market has been widely characterized as a pyramid, with a relatively tiny affluent class at the top with a hunger for luxury & high-end goods and services, a middle class in the center, and a large economically disadvantaged sector at the bottom. The Indian market's pyramid structure is gradually crumbling and being supplanted by an entirely new multifarious consumer class with a relatively big affluent class at the top, a massive middle class in the center, and a tiny economically disadvantaged sector at the bottom. Although having a vast and continually rising customer base, the market is complicated and Indian consumers' proclivity and ability to spend is determined by a particular combination of price and value.

Several physical, social, temporal, and demographical elements may be included when assessing a consumer's supermarket purchasing behaviour. According to (Jhamb & Kiran, 2012), the critical drivers of organized retail in India are infrastructure, economic growth, and changing customer demographics. The location of a retail store, managerial style, and proper employee pay all contribute to the performance of the retail company and are critical success criteria for retailers. So it becomes essential to know the consumer's perception to effectively position an organized retail store in today's world (Wahyuningsih & Dubelaar, 2020). According to their findings, to satisfy their clients, businesses must adequately define each group of consumers, whether they're passive, rational-active, or relationally reliant. This is because each of these three categories of consumers perceives their degree of pleasure differently. Because rational active & relational dependent consumers are susceptible to their sentiments and expectations, businesses must constantly communicate and improve their performance.

Literature Review

Data Analysis

Mediation analysis is to identify the direct and indirect relationship between the Independent variable (X) on (Y), the dependent variable in the presence of (M), and the mediation variable (Watson, 2013).

The simple mediation effect between store and hospitality with offers as mediation is shown in Figure 1 (Kane & Ashbaugh, 2017). The results show that the correlation between store and offers is .44, between offers and hospitality, is .47, and the direct relationship between store and hospitality is .63. This reflects that for the consumer, preferring hospitality plays a vital role in the store and offers (Hanaysha, 2018). Another study depicted that the employee focus on customer service also affects the customer revisit in the store Tables 1-7.

Table 1 Technology Model
Author(s)	Year	Topic	Findings
(Kumar et al., 2022)	2022	Adoption of Technology Applications in Organized Retail Outlets in India: A TOE Model	It focused on the use of technology to increase the customer base
(Chattopadhyay, 2019)	2019	A Comprehensive Study on Organized Retailing Concerning Customer Preferences and Customer Loyalty in Indian Context	Customers' Lifestyle affects the decision-making in their buying behavior.
(Behera, Mukti Prakash; Mishra, 2017)	2017	Impact of Store Location and The Layout on Consumer Purchase Behavior in Organized Retail	The store ambiance and its facilities attract consumers and enhance the shopping experience.
(Ramya, 2016)	2016	A Study On Customer Perception Towards Organised Retailing In Coimbatore City	Demographics play a vital role when purchasing from retail stores.
(Chaturvedi & Singh, 2013)	2013	Customers Perception and Shopping Motivation at Organized Retail Outlets	Preference is given to organized retail for its value in pricing and quality of products.
(Ghosh et al., 2010)	2010	Customer expectations of store attributes: A study of organized retail outlets in India	The study focused on the store layout, visual merchandising, and art and crafts that attract customers.
(Katole, 2012)	2012	An analysis of consumer purchase behavior in organized retail outlets	The consumer's tastes and preferences change according to their demographics, which the marketers should take care of.
(Ghosh et al., 2010)	2009	Customer expectations of store attributes: A study of organized retail outlets in India	The fast service and convenience in hances the customer's experience and their buying patterns in retail stores.

Table 2 Model's Summary
Model	R	R Square	Adjusted R Square	Std. The error in the Estimate
1	.867a	.751	.749	.41808
a. Predictors: (Constant), Offers, Store

Table 3 Coefficients
Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.	Collinearity Statistics
		B	Std. Error	Beta			Tolerance	VIF
1	(Constant)	.006	.124		.045	.964
	Store	.635	.040	.599	15.990	.000	.761	1.315
	Offers	.474	.045	.398	10.636	.000	.761	1.315
a. Dependent Variable: Hospitality

Table 4 Collinearity Diagnostics
Model	Dimension	Eigenvalue	Condition Index	Variance Proportions
				(Constant)	Store	Offers
1	1	2.935	1.000	.01	.01	.01
	2	.033	9.377	.42	.95	.09
	3	.031	9.657	.57	.04	.90
a. Dependent Variable: Hospitality

Table 5 Total Effects
	StoreI	OffersI
OffersI	0.436	0.000
CSI	0.841	0.474

Table 6 Two-Tailed Significance
	StoreI	OffersI
OffersI	.001	...
CSI	.001	0.001

Table 7 Path Analysis
			Estimate	S.E.	C.R.	P	Hypothesis Accepted/ Rejected
OffersI	<---	StoreI	.436	.051	8.599	***	Accepted
CSI	<---	StoreI	.635	.040	16.058	***	Accepted
CSI	<---	OffersI	.474	.044	10.682	***	Accepted

The value of the adjusted R square is .749, which implies that the model can explain 74% of the variables identified to get the model's validity.

(Johnston et al., 2018)The Variance Inflation (VIF) describes the collinearity between the independent variables. This is a concept in statistics. It denotes that any increase in the regression coefficient will lead to collinearity. VIF represents the type II error; the value is uniform but misleading the variable's coefficient. The (VIF) Variance, Inflation Factor value, is >2.5 is considered as there is multicollinearity between the variables. The above table shows the VIF value of store and offers is 1.315, respectively, < 2.5. Therefore it is considered that there is no multicollinearity issue in the model.

The value of a condition index of more than 15 is considered the presence of collinearity. The Condition index in the table is less than the threshold, reflecting that the model is good.

The above table describes that customer service plays a vital role in attracting customers to the store through offers mediating between hospitality and ambiance.

The above table concludes that customer service is essential between the offers and the store's ambiance. Therefore, offers alone will not be able to attract customers to the store.

H₁ The offers store ambiance impacts the offers provided by the store.

H₂ There is the significance of Customer service and store ambiance in presence of offers as mediation

H₃ There is a significant relationship offers as mediation between and Customer service and store ambiance

Run MATRIX procedure

***************** PROCESS Procedure for SPSS Version 4.2 *****************

Written by Andrew F. Hayes, Ph.D. www.afhayes.com

Documentation is available in Hayes (2022). www.guilford.com/p/hayes3

**************************************************************************

Model: 4

Y: CSI

X: StoreI

M: OffersI

Sample

Size: 236

**************************************************************************

OUTCOME VARIABLE:

OffersI

Model Summary

R R-sq MSE F df1 df2 p

.4892 .2393 .3764 73.6200 1.0000 234.0000 .0000

Model

coeff se t p LLCI ULCI

constant 1.4254 .1563 9.1191 .0000 1.1175 1.7334

StoreI .4359 .0508 8.5802 .0000 .3358 .5360

The above table describes that the store ambiance P is.000, which is <.05. It depicts a significant relationship between store and customer service in the presence of offers as a mediator.

**************************************************************************

OUTCOME VARIABLE:

CSI

Model Summary

R R-sq MSE F df1 df2 p

.8667 .7512 .1748 351.7968 2.0000 233.0000 .0000

Model

coeff se t p LLCI ULCI

constant .0056 .1240 .0448 .9643 -.2388 .2499

StoreI .6348 .0397 15.9898 .0000 .5565 .7130

OffersI .4738 .0445 10.6364 .0000 .3861 .5616

****************** DIRECT AND INDIRECT EFFECTS OF X ON Y *****************

The direct effect of X on Y

Effect se t p LLCI ULCI

.6348 .0397 15.9898 .0000 .5565 .7130

Indirect effect(s) of X on Y:

Effect BootSE BootLLCI BootULCI

OffersI .2066 .0371 .1353 .2827

In the direct relationship, the p-value is .00,>.05, and the indirect effect relationship is also significant. Therefore, the offer partially mediates between the store and customer services.

*********************** ANALYSIS NOTES AND ERRORS ************************

Level of confidence for all confidence intervals in the output:

95.0000

Number of bootstrap samples for percentile bootstrap confidence intervals:

5000

------ END MATRIX -----

Conclusion

The study has noticed the essential facts in consumer buying behavior in retail stores. The results from applying mediation analysis (SPSS AMOS 23) and process macro methods. It was noticed that discount offers and other lucrative pricing benefits can attract customers. The store facility layout, ambiance, and customer service also influence the consumer buying behavior pattern. This study has managerial implications for marketers to change their strategy from price factor to customer service factor to increase the footfall of the customers and their sales figures.

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Received: 22-Oct-2023, Manuscript No. AMSJ-23-14115; Editor assigned: 23-Oct-2023, PreQC No. AMSJ-23-14115(PQ); Reviewed: 29-Jan-2024, QC No. AMSJ-23-14115; Revised: 15-Apr-2024, Manuscript No. AMSJ-23-14115(R); Published: 03-May-2024