Measuring Impulse buying behavior through Customer Satisfaction - A Retailer Perspective in FMCG sector

ABSTRACT

The core success of every business lies in the quality of services provided by the marketer, which is the forebearer for customer satisfaction, provoking impulsiveness in buying behavior Taking this as its core issue, this study mainly focuses on the retailer’ perspective towards service quality in the Fast Moving Consumer Goods (FMCG) sector and its impact on impulse buying behavior through customer satisfaction. For this purpose, 526 customers in the western region of Tamilnadu, India were selected through a convenience sampling technique. Tools such as structural equation modeling and correlation along with the decision tree analysis were employed and the outcome illustrated that no remarkable affiliation found amid the location of the store, reliability and empathy and the retailer’s service quality but customer satisfaction performed as a moderator between retailer’s service quality and the impulse buying behavior. Retailers are suggested to have a good customer relationship management through reliability and empathy for retaining the valuable customers as they have more knowledge towards brand preference.

Keywords:
Customer experience; perception; price; service quality; switching behavior

RESUMO

O sucesso central de toda empresa se baseia na qualidade dos serviços do profissional de marketing, e esse é o precursor da satisfação do cliente, que provoca impulsividade no comportamento de compra. Tendo isso como questão central, esta pesquisa enfoca principalmente a perspectiva do varejista em relação à qualidade do serviço no setor de FMCG e seu impacto no comportamento de compra por impulso por meio da satisfação do cliente e, para isso, 526 clientes na região oeste de Tamilnadu, Índia, foram selecionados por meio da técnica de amostragem por conveniência. Foram empregadas ferramentas como modelagem de equação estrutural, correlação e análise de árvore de decisão, e o resultado ilustrou que não foi encontrada nenhuma afiliação notável entre a localização da loja, a confiabilidade e a empatia e a qualidade do serviço do varejista, mas a satisfação do cliente atuou como moderador entre a qualidade do serviço do varejista e o comportamento de compra por impulso. Sugere-se que os varejistas tenham um bom gerenciamento do relacionamento com o cliente por meio de confiabilidade e empatia para reter os clientes valiosos, pois eles têm mais conhecimento sobre a preferência pela marca.

Palavras-chave:
Experiência do cliente; percepção; preço; qualidade do serviço; comportamento de troca

1. INTRODUCTION

Currently, the retail industry in India is witnessing dramatic growth, and the FMCG sector has seen an incredible transformation due to the proliferation of competitors and technology. This situation made it all the more critical for retailers to satisfy -a forerunner for the creation of spontaneity in purchase among the customers. This spontaneity is created through products and services (Miralam et al., 2019) and earned customer experience (Arviana & Syah, 2022), and customer value (Prasasthan & Navaprabha, 2013) (Wang, 2022) which are the basic philosophies for every marketer-“satisfying the customer’s needs and wants to earn profits”. Many earlier studies witnessed the subsistence of satisfaction based impulsive buying behavior practices among Indian customers. For instance, Hindustan Unilever LTD brought about impulsiveness in their customers through a mix of marketing and product strategy (Jayde, 2019); Customers of the Big Bazaar retail outlet in India have impulsive and spontaneous behavior created by good price and sales motivation (Harshith, 2019); 68 percent of the customers (female dominated) in D-mart, Osia, Big Bazaar, and Reliance Fresh preferred impulse buying owing to their shopping experience, a store’s floor merchandising, and the employees approach (Pandya, 2021). As a milestone, the report published in FeedVisor in the year 2021about the customers of M/s and Amazon highlighted that 49 percent of the total customers under the age of 27-40 preferred buying when the products were first listed on the platform, strongly indicating the impulsiveness of the customer. Still there exists a complexity in understanding the preference of the customers by the retailers and it is due to the heterogeneity idea that the customers have in their purchasing behavior.

But, this impulsive buying will not be permanent, and dissatisfaction, if any,in micro level (Sands et al., 2020) may lead toa switching mood among the customers despite having social, emotional and quality benefit through the product. Hence, it is very decisive for the marketer to detain the brand and the consumer demeanor (Sunardi et al., 2023) and any happening may result in damaging the market share and prosperity (Fernandas et al., 2020). This is also accepted by (Marva and Astini, 2023) who highlighted that enhanced quality in service yields better satisfaction and, in contra, inferior quality may lead to a worse level of customer satisfaction-and the sustainability of any business rests with the satisfaction level of the customers (Widodo et al., 2023) which is the soleantecedent for the impulsiveness in the buying behavior through loyalty.Hence many early studies have given importance to measuring the quality of service.

Initially, service quality was measured through parameters like Tangibility, Reliability, Responsiveness, Assurance, and Empathy (Parasuraman et al., 1988); (Firmansyah et al., 2023) and later, these parameter is applied to measure the customer satisfaction (Aruldoss et al., 2023; Ngaliman et al., 2019; Widodo et al., 2023). In addition, many researchers have measured service quality through various factors like usefulness, convenience, design, and security/privacy (Yum and Yoo, 2023); convenience, reliability, ease of use, fulfillment, and security in the banking sector (Nigatu et al., 2023) and particularly in the fast moving consumer sector, the service quality is measured by Reliability, Responsiveness, Assurance, Empathy and Tangibility (Sharma, 2021); perception in quality was examined through the word of mouth with the marketing mix (4Ps) (Khalil, 2021)of quality of object, quality of process, quality of infrastructure, quality of interaction, and quality of atmosphere (Zeneldin et al., 2014); studied the customer satisfaction through the FMCG products (Mishra and Mishra, 2022). Hence it is obvious that impulsiveness in buying is mainly depending upon the service quality followed by the customer satisfaction in the FMCG sector.

In other words, impulsiveness is intangible in character and could be measured only through there tention rate of customers, with this retention rate depending on the perceived service quality from the retailers. Singh et al. (2023) pointed out that client retention in any business is directly related to the service superiority and this withholding is resolute in the fundamental business plan of the company to gain trust and belief of the customer which in turn yield long term success. This conviction could be earned by the marketer only through continuous and consistent quality in services which enhance the impulsive buying behavior among the customers and the profit (Ali et al., 2021). Predominantly, in FMCG commodities, customers consistently seek out new products that the market has made available Selvi and Padmashri, 2023) and it is mandatory for the manufacturers to advance the features of the product as per the customer requirements (Lone and Bhat, 2023) and not be bothered about the price in the case of quality products (Andari, et al., 2023) as there is a constructive alliance between the brand equity and the operation of the business in the market (Mohan and Sequeira, 2016).

The above discussion is clearly informed about the present status of the retailers, who should remain attentive through proper understanding about their customers (Puccinelli et al., 2009) and in the FMCG sector, retailers must grasp customer preferences through their experience, as perceived shopping value plays a significant role in strengthening purchase intention, but large number of companies have not bothered about the customer value and experience and hence their improvement in the business were in trouble and in fact satisfaction mainly depended on the experience (Ray et al, 2020),which will turn on loyalty and create impulsiveness in the buying process only when the service providers solved the problems that have been raised by the customers (Manyanga et al., 2022).

Taking all the above, this study is unique as it considers various indispensable dimensions such as location, reliability, empathy, and customer satisfaction under a retailer’s service quality(RETSERVQ) that can precisely measure impulsiveness among the customers-customer satisfaction is considered as a moderator between the retailer’s service quality and the impulse buying behavior so as to ascertain whether the service quality in the FMCG sector directly induces the impulsiveness or through the customer satisfaction. Therefore, the following research questions were put forth for this study.

1. Whether the customer’sexperiences with the location, individual attention, and reliability of retailers in FMCG sector creates positive satisfaction?

2. Does a retailer’s service quality enhance customer satisfaction?

3. Whether customer satisfaction enhances impulse buying behavior in the FMCG sector?

As this study mainly focuses on the retailer’s perspective towards impulsiveness, the outcome will surely help the retailers to redefine a new phase in their business strategy for providing the products and services that align the inimitable needs and wants of the customers in the FMCG sector and thereby inducing the impulsiveness among them.

2. LITERATURE REVIEW

This section has the outcomes of various prior works that facilitated the overall understanding about the current topic of the study. The seven hypotheses as detailed below are:

2.1 Location and Service quality in FMCG sector

(Pugazhenthi, 2010), in a study about customer loyalty and choice of retailer in the FMCG sector, acknowledged that female customers preferred only the location of the store for their purchases, while men preferred location along with ambience, display, and availability of the products in the outlet. Hariyadi et al. (2018) identified hat the location and the distance of the retail outlet significantly influenced the repurchasing intention among the customers and this is substantiated by (Dey and Sharma, 2017) who informed that the place of purchase was very important and that customers were preferring neighborhood or nearby stores for purchasing FMCG products in Agartala city.

Bahri (2018) revealed that location, service, and product quality have significantly influenced the purchasing decision through customer satisfaction particularly - the management has to give importance to the parking area of the departmental store. Aronkar and Chaturvedi (2019) underlined that there is a strong relationship between store location - and the product quality-on the loyalty of customers. In addition, a retailer’s personality partially mediated the customer reactions and the retailer’s service quality (Rashid & Rokada, 2023). The above outcome shows the importance of the retail outlet’s location, and its impact on the customer buying behavior but whether the same mentality rests with the customer of this study and to test the relationship, the following hypothesis was framed.

H ₁ : Location of the outlet positively affects the retailer’s service quality in the FMCG sector

2.2 Reliability and Service Quality in FMCG sector

While reviewing the past literature about the impact of reliability on the retailer’s service quality, there was no direct study found, but many researchers have attempted to study the impact of reliability on the service quality through SERVQUAL among the dimensions. But, to provide lucidity to the audience, the following reviews were submitted.

Kumar et al. (2012) , in a study about retail service quality in organized retailing, established that reliability does not have a noteworthy relationship with customer satisfaction through retailer service quality but this outcome has a contradictory result with the findings of (Silva et al., 2022) who reported that reliability has a significant association with customer satisfaction through service quality in the Mini super market. Ngaliman et al. (2019) demonstrated the direct effect of reliability on customer satisfaction through service quality in the delivery services. Rashid and Rokada (2019) found that reliability in the grocery retail positively influences the customer satisfaction through service quality in terms of commitment of promises and delivery. Yuen and Chan (2010) enlightened that physical aspects, reliability, and problem solving have positively related to the loyalty among the customers in the retail sector, but this result was found in opposition to the findings of (Venkatesha and Govindappa, 2018) who found that reliability has no significant impact on the retailer’soverall service quality. To have the real position of the reliability of the retailer on the impulsive buying behavior in FMCG sector, the following alternative hypothesis is formulated.

H ₂ : Reliability positively influences the retailer’s service quality in the FMCG sector

2.3 Empathy and Retailers Service Quality in FMCG sector

Bahadur et al., (2018) recognized that the employees were the prime stakeholders in delivering empathy to the customer, in orderto showthe customer a business which enhances customer satisfaction and loyalty. In fact (Wei et al., 2022) particularly pointed out that even service failure could be forgiven by the customer if they were given treatment individually-installing customers on repurchase intention.

Rashid and Rokada (2019) revealed that theem ployee’s friendly and healthy empathetic behavior played a significant role in the grocery retail service quality. (Bove, 2019) established that empathy in services reduces anti-social behavior, revenge, and discrimination thereby enhancing ethical behavior among the employees. It is compulsory for the retailers to continuously endorse service quality through empathy and to confirm this situation, the following hypothesis is provided.

H ₃ : Empathy positively influences the retailer’s service quality in the FMCG sector

2.4 Customer Satisfaction and Retailer’s Service Quality in FMCG

Venkateswaran and Sundaram (2021) reported that retail service quality, and the store service quality, were increasing customer satisfaction which, in turn, created patronage intention among the customers. Kawa and Zdrenka (2023) identified the factors that create values among the customers through the e-retailing business and found that communication; convenience, reception experience, and the convenience in returning the article have satisfied the customers in turn built loyalty among them.

Sung et al. (2023) found that trust generated by the marketers through their behavior in online platform, helps reduce perceived risk and uncertainty in the purchase process. Similarly (Maqsood & Javed, 2019) emphasized that compatibility and customer satisfaction could be enhanced only through effective after-sales service and strong customer relationships, and this consistently encourages customers’ impulsive buying behavior. (Rajalakshmi & Golden, 2023) highlighted that factors like product quality, product value, and awareness were the key influencers for the customer satisfaction in the dairy industries. To identify the relationship between the retailer’s service quality and the customer satisfaction, the following alternative hypothesis is framed for this study.

H ₄ : There is a positive relationship between the retailer’s service quality in the FMCG sector and the customer’s satisfaction

2.5 Impulsive Buying Behavior and Service Quality in FMCG sector

Hashmi et al. (2019) clearly stated that information quality, service quality, and system quality have significantly and positively affected the online impulse buying behavior. Susanti (2022) found that competitive prices and good service quality in the minimarket sector have an significant impact on the impulse buying behavior of which (Husnain & Akhtar, 2016) highlighted that branding has a noteworthy impact on the impulse buying behavior.

Ahmed et al. (2014) explained that impulse buying behavior is mostly determinedby the attractive color, packaging, and labeling of the product. Vinish et al. (2020) realized that staff members and their skills played an important role in creating the impulse buying behavior among the female shoppers in the case of apparel industries, despite store’s ambience and layout. This study mainly focuses on customers’ impulsive buying behavior from a retailer’s perspective which is a incomparable study with the previous research undertaken from the retailers perspective and hence the following hypothesis is considered.

H ₅ : There is a positive impact of factors under retailer’s service quality and the impulse buying behavior in FMCG sector

2.6 Demographic profile and the Switching practice among the customers in FMCG sector

Verma et al. (2023) ; Kumar (2014) reported that the demographic profile of the customers influencing the decision making and buying behavior in preferring the FMCG products; particularly age, education, and occupation played an important role the decision making process. (Chen et al., 2021) confirmed that the impulse buying decision is influenced mainly by the parents and the spouses of the purchaser, other than companions in the grocery shopping, and this buying behavior mainly depend upon the retailer’s internal characteristics, atmosphere, and relationship with the customers.

Vinayagamoorthy and Kannan (2015) revealed momentous difference existed among the socio-demographic sketch of the customers and impulsiveness in buying action and, it is also seen that there was a weak association that existed between the consumer’s lifestyle, fashion involvement, and post decision stage with impulse buying behavior. Rani and Catherine (2023) told that discounts, offers, and other related promotions made the customer have impulse buying behavior through the demographic profile mainly the age and the psychographic factors. (Bogomolova et al.,2019) indicated that majority of new to store purchases mainly depend on store stimuli such as price promotions, stock outs, and, particularly display, however, no difference noticed between new and returning customers in retail purchases in terms of their demographic characteristics

Zhao et al. (2021) have proved that product pricing and packaging of the product significantly influenced the consumer’s buying decision process by pointing out that high pricing in the competitive market may lead to lose the customers permanently.(Guha,2023) revealed that there is a significant difference noticed between the male and female regarding impulse buying behavior and it is the emotion that played a good role in the impulse buying behavior and, sometimes, friends and family members may influence it among the college going students in Kolkata.

H ₇ : Demographic profile positively induced the switching mood among the customers of FMCG sector

This is the research primarily focusing on the customer’s impulsive buying behavior, through service quality in the retailer’s perspective and earlier research works were available but those work mainly concentrated on the customer satisfaction and loyalty and there is no direct study about the impact of a retailer’s service quality on impulsive buying behavior. As a milestone, another effort, which have not attempted so far, was taken to study the mediating role of customer satisfaction between the retailer’s service quality and the impulsive buying behavior. This is actually an exclusive research gap to be filled, and a special hypothesis was framed.

H ₆ : Customer satisfaction positively mediates a retailer’s service quality and impulse buying behavior in the FMCG sector

A consolidated framework of the hypotheses framed for this study is given in Table 1 below for easy understanding.

Table 1
Framework of the Hypothesis

Hypotheses	Description
H1	Location of the outlet positively affecting the retailer’s service quality in FMCG sector
H2	Reliability positively influencing the retailer’s service quality in FMCG sector
H3	Empathy positively influencing the retailer’s service quality in FMCG sector
H4	There is a positive relationship between the retailer’s service quality in FMCG sector and customer’s satisfaction
H5	There is a positive impact of factors under retailer’s service quality and the impulse buying behavior in FMCG sector
H6	Customer satisfaction positively mediating retailer’s service quality and the impulse buying behavior in FMCG sector
H7	Demographic profile positively inducing the switching mood among the customers of FMCG sector

. Based on the research gap of this study and with the construct selected, the following theoretical model is considered (Figure 1).

Figure 1
Hypothetical Model

3. OBJECTIVES OF THE STUDY

The following objectives were taken up for this study based on the conceptual model.

1. To establish an idiosyncratic study with unique factors under retailers service quality on the impulse buying behavior in the FMCG sector.

2. To investigate the association among the factors that influence the retailer’s service quality.

3. To identify the impact of the factors under the retailer’s service quality on the impulse buying behavior of the customers.

4. To scrutinize the mediating role of customer satisfaction between the retailers’s service quality and impulse buying behavior.

5. To spot the demographic variable that manipulating the switching practices of brand among the consumers.

4. RESEARCH METHODOLOGY

This study is basically of a quantitative and descriptive nature, and the factors considered were explored through the self-conducting questionnaire-data collection is done by two methods 1) interview method among the illiterate respondents 2) getting the opinion duly filled by them and the respondents were informed about purpose of the survey. The opinion was obtained through 5 point Likert scale ranging from 1- strongly disagrees to 5 -strongly agree. Since the population is unknown, the minimum requirement of the sample size is 384 but, based on the geographic area of the study, which constitutes 10 districts, a total of 650 samples were considered and selected through the convenience sampling method.

Here, the researcher wants to justify the representation of the geographic area and the population considered for this study. India is the second largest nation in the world, with a high population and possessed of 29 states of which, Tamil Nadu in the southern part hasa huge population, with unity in diversity. Even though they didn’t share a culture, this study found no difference in the using of FMCG products as a whole on a PAN India basis. Hence it is believed that conducting research in this selected jurisdiction would definitely represent the population of the entire country. This is the reason for selecting the western region of Tamil Nadu for this study.

Next, the questionnaire was distributed to these selected 650 respondents and the opinion was obtained from them. But it is seen that only 586 questionnaires were received, of which only 526were found to be in the reusing stage for the analysis purpose, with 80.9 %. Before conducting the actual survey, a pilot study was conducted with 150 samples to validate the consistency of the questionnaire and the value was found as 0.70 percent.

The following tools were employed in this study for the purpose noted against each.

Table 2
Details of analysis and purpose

Analysis tool	Purpose	To which Hypothesis
1.Structural Equation Modeling	To assess the goodness of fit of the model	H1- H6
2. Percentage analysis	To calculate the percentage of participation of the respondents and their demographic characters.	NA
3. Karl Pearson Correlation analysis	To find the association among the factors that influencing retailers service quality, customer satisfaction and the impulse buying behavior	H1- H5
4. Compare mean test	To investigate the association between demographic variables and the factors taken up for study.	H7
5. Decision Tree analysis	To find the decision of the consumers in purchasing the FMCG product along with the factors that influencing in such decision	H7
6. K mean cluster analysis	To identify the switching mentality of the customer those who were purchasing the FMCG product.	H7

4.1 Structural Equation Modeling

Any complex analysis through the multiple points of data could be done only through structural equation modeling through a path analysis. Through this method, multiple processes of the system are possible. It identifies the relationship of factors through measurement and structural equation which enable the researcher to have keen results on their objectives. This method’s aim is to lessen the difference that occurs between observed and expected covariance matrices. At last, validation of any model through path analysis is possible only through this technique.

The opinion collected through the questionnaire encompasses well-defined factors, and when the latent variable structure is known, the analysis proceeds directly with the confirmatory factor analysis (CFA) through AMOS by considering constructs like location, reliability, empathy and customer satisfaction as the exogenous and observed constructs, with the retailers service quality considered as the endogenous and a latent one in the first order level, and, in turn, the retailer’s service quality (RETSERVQ) as the exogenous factors, with the impulse buying behavior as the endogenous factor in the second order level.

Path analysis with the above factors was done by considering the customer satisfaction as the moderator between the retailer’s service quality and the impulse buying behavior and diagram obtained is represented in figure 2 below:

Figure 2
Structural Equation Modeling through AMOS

Theoretically, the items in each constructs which have factor loading with more than 0.5 (Hair et al., 2009 apudByrne, 2016); and factor with loading more than 0.4 Stevens (2002) apud (Cheung et al., 2023) may be considered for validation, and the rest of the factors having value lower than 0.4 should be deleted during the assessment and validation process. In the Figure 1 above, the following factors were found with the value less than the prescribed limit for validation. The details of the assessment of the model are given in Table 3 below:

Table 3
Measurement Model Assessment

Sl. No.	Variables (item ) Number	Factor label	Loading Value	Status
Cycle 1
01.	Empathy 1(EMP1)	Empathy	0.19	Deleted
Cycle 2
02.	Empathy 2( EMP2)	Empathy	0.27	Deleted
Cycle 3
03.	Location 1( LOC1)	Location	0.41	Deleted

The confirmatory factor report for every construct is given in Table 4 below:

Table 4
CFA Validation Report

Factors	Label	Standardized Factor Loading	Cronbach Alpha Value	R2	AVE	CR
Location	LOC1	Deleted	0.755	*	0.44	0.76
	LOC2	0.56		0.32
	LOC3	0.72		0.52
	LOC4	0.68		0.46
	LOC5	0.68		0.46
Reliability	REL1	0.58	0.838	0.34	0.58	0.76
	REL2	0.82		0.67
	REL3	0.76		0.58
	REL4	0.85		0.72
Empathy	EMP1	Deleted	0.734	*	0.50	0.74
	EMP2	Deleted		*
	EMP3	0.73		0.53
	EMP4	0.72		0.52
	EMP5	0.63		0.40
Customer Satisfaction	CS1	0.85	0.899	0.72	0.69	0.90
	CS2	0.78		0.61
	CS3	0.88		0.77
	CS4	0.82		0.67
Impulse buying behavior	IMP1	0.53	0.836	0.28	0.51	0.84
	IMP2	0.62		0.38
	IMP3	0.75		0.56
	IMP4	0.82		0.67
	IMP5	0.82		0.67

• (Source: Survey Data)

The Average value extracted (AVE) and the Composite reliability value are found within the threshold limit as prescribed in the earlier research (Ahmed et al., 2016). At the same time, the AVE value for the “Location” is found as 0.44 (<0.5) but the Composite reliability value found with the value 0.76 which is (>0.70) and hence it is accepted as per Fornell and Larcker (1981) . Discriminant validity was further verified and the result is given in Table 5 below. The outcome confirmed there are no issues in the validity as the square root of the factor’s Average Variance Extracted (AVE) value (in the diagonal of each factor) is greater than the correlation value between the factors of this study.

Table 5
Discriminant Validity

Factors	Location	Reliability	Empathy	Customer Satisfaction	Impulse Buying Behavior
Location	0.663
Reliability	0.037	0.762
Empathy	-0.06	0.161	0.707
Customer Satisfaction	-0.018	0.256	0.095	0.831
Impulse Buying Behavior	0.141	-0.013	0.21	0.325	0.714

• Source: Survey data

The path analysis after assessing the model by deleting the factors which have not met the criteria is given in figure 3 below:

Figure 3
Structural Equation Modeling through AMOS

The goodness of fit indices obtained is given in Table 6 below:

Table 6
Goodness of fit indices for the model

Sl. No.	Index	Value	Sl. No.	Index	Value
01.	CMIN/Degree of Freedom	2.695	07.	TLI	0.924
02.	GFI	0.925	08.	RMR	0.045
03.	AGFI	0.904	09.	SRMR	0.041
04.	NFI	0.900	10.	RFI	0.885
05.	IFI	0.935	11.	RMSEA	0.057
06.	CFI	0.935	12.	FMIN	0.842

• Source: Survey data

From the result in Table 2 above, the CMIN/df value wasfound as 2.695which indicated the better fit of the model. The GFI value (0.925) showed that the model accounted for92.5 percent of variance in the observed data through variance and covariance. This outcome is substantiated through the value of AGFI which is found as (0.904) which explained90.4 percent of the variance. The IFI value (0.935) confirms an improvement of 93.5 percent from the baseline model and the CFI value (0.935) authenticated a 93.5 percent improvement over the base modelThe RMR value indicated an average discrepancy of 4.5 %. Additionally, the FMIN value (0.842) showed the minimum discrepancy in the model. The RMSEA value of 0.057, below than the threshold limit of 0.08, exhibited good and, overall fit with the data that is obtained from customers who prefer in purchasing the FMCG products through retailers. Also, the maximum likelihood estimates result revealed is detailed underneath.

The standard regression weight and the status of the hypothesis of this research is detailed in Table 7 below:

Table 7
Regression weights (Standardized)

Hypothesis	Critical Path	Estimate	C.R.	Decision
H1	Location	🡐	RETSERVQ	0.047	0.548	Rejected
H2	Reliability	🡐	RETSERVQ	0.496	1.236	Rejected
H3	Empathy	🡐	RETSERVQ	0.097	1.459	Rejected
H4	Customer Satisfaction	🡐	RETSERVQ	0.551	1.935**	Supported
H5	Impulse Buying Behavior	🡐	RETSERVQ	-0.026	-0.476	Rejected
H6	Impulse Buying Behavior	🡐	Customer Satisfaction	0.210	1.978*	Supported

• Source: Survey data

The above values represented the output of the SEM of Analysis through regression weights and the result confirmed that the relationship between location, reliability, empathy were not statistically significant but customer satisfaction has a positive and noteworthy relationship with the RETSERVQ (Retailers Service Quality) at p≤0.01 as the value of the critical ration is more than (>) 1.96 .

The direct, indirect and the total effects of the factors that influencing the purchasing of FMCG among the customers was analyzed and given in Table 8 below:

Table 8
Standardized Direct, Indirect and Total Effects

Factors	Direct Effect		Indirect Effect		Total Effect
	IBB	RETSERVQ	IBB	RETSERQ	IBB	RETSERVQ
Location	0.000	0.036	0.000	0.000	0.000	0.036
Reliability	0.000	0.794	0.000	0.000	0.000	0.794
Empathy	0.000	0.217	0.000	0.000	0.000	0.217
Customer Satisfaction	0.053	0.406	0.000	0.000	0.053	0.406
Impulse buying behavior	0.000	-0.036	0.000	0.021	0.000	-0.015

• (IBB- Impulse Buying Behavior; RETSERVQ- Retailers Service Quality)
• Source: (Survey Data)

The impact of the exogenous factors on the endogenous one proved that increase in one unit of independent factors increases the retailers service quality to the tune of 2.7 % (Location); 79.4 % (Reliability ); 21.7 % ( empathy); customer satisfaction (40.6 %) and at the same time, the direct impact of RETSERVQ on the impulse buying behavior is found negative (-0.015) but when moderating through customer satisfaction, it is seen that the service quality through satisfaction improves the impulse buying behavior towards FMCG product at 2 %.

4.2. Descriptive Statistics

In this section, the summary of the demographic characteristics of the customers are analyzed and given in Table 9 below:

Table 9
Demographic profile of the respondents

Sl.No.	Characteristics	Category	Number of Respondents (n=526)	Percentage
01.	Gender	Male	152	28.9 %
		Female	374	71.1 %
02.	Age	Up to 20 years	74	14.1 %
		21- 30 years	105	20.0 %
		31-40 years	201	38.1 %
		41-50 years	75	14.3 %
		Above 50 years	71	13.5 %
03.	Marital Status	Married	379	72.1 %
		Unmarried	147	27.9 %
04.	Educational Qualification	Illiterate	46	8.7 %
		School level	78	14.8 %
		Under Graduate	246	46.8 %
		Post Graduate	144	27.4 %
		Others	12	2.3 %
05.	Family type	Single	271	51.5 %
		Joint	255	48.5 %
06.	Monthly Income	< Rs.20000/=	268	51.0 %
		Rs.20000/= to Rs. 40000/=	174	33.0 %
		> Rs.40000/=	84	16.0 %
07.	Purchasing outlet for FMCG	Kirana Stores	83	15.8 %
		Super Market	152	28.9 %
		Shopping Mall	139	26.4 %
		Departmental stores	149	28.3 %
		Others	3	0.6 %
08.	Frequency of purchase	Daily	63	12.0 %
		Weekly	162	30.8 %
		Fortnightly	35	6.7 %
		Monthly	262	49.8 %
		Rarely	4	0.7 %
09.	Switching the brand in FMCG	Yes	174	33.1 %
		No	352	66.9 %

• Source: Survey data

The demographic profile results highlighted that the maximum participants of this study were found to be female (71.1 %) and the maximum respondents were found under the age group of 31-40 years (38.1 %). Regarding marital status, it is found that the maximum respondents were found to be married (72.1 %) and 46.8 percent of the total population were held an undergraduate degree. It is also seen that most of the respondents were living singly (51.5 %) despite their marital status. Maximum customers had a monthly income to the tune of less than Rs.20000/= and 28.9 percent of the total population were purchasing the FMCG products in the super market and 30.8 percent of the customers have informed that they were purchasing on weekly basis.

Any growth in business is mainly depending upon the customers who are loyal with the company but even a small favor by the competitor makes this loyal customer to think about the switching pattern and those customers could be retained only through surprise promotional activities. In this study, customers were asked about their switching mentality in case of any problem with the existing FMCG and found that 33.1 percent of the total population informed that they were having the habit of switching to other brands.

4.3 Karl Pearson Correlation Analysis

In view to find the linear relationship between two continuous variables or factors, this technique was used. The main objective of finding the relationship among the factors is to determine the strength and direction of the factors taken up in the research along with prediction and forecasting for the decision-making process (Shoeber et al., 2018). Simply, it is an important diagnostic tool for the determination of association between the factors. The result of the correlation analysis of this study is detailed in Table 10:

Table 10
Correlation Analysis

	Inter Correlation
	Mean	SD	F1	F2	F3	F4	F5
Location	3.26	0.82	1	0.037	-0.060	-0.018	0.141*
Reliability	3.45	0.78		1	0.161**	0.256**	-0.013
Empathy	3.37	0.97			1	0.095*	0.210*
Customer Satisfaction	3.20	0.84				1	0.325**
Impulse Buying Behavior	3.49	0.72					1

• ** 1 % level significance; *5 % level significance
• Source: Survey Data

The outcome has to bear out that constructs like location, reliability, empathy and customer satisfaction were optimistically interrelated at 1 % and 5 %level of significance. There was seen weak to moderate correlation among the factors (R =+0.095 to +0.325) and the result is corroborated with the findings of (Schober et.al., 2018). The maximum association rest with “Customer satisfaction” and “Impulse Buying behavior” (r=-0.325**) followed by “Reliability” with “Customer satisfaction”(r=0.256**) and the lowest correlation was found between “Empathy” and the “Customer Satisfaction” with the value of (r=0.095*) at5 % level of significance. Through the R² value, 98 % variation was shown by the location with impulse buying behavior followed by empathy with 96 % towards impulse buying behavior; 89.5 % variation by the customer satisfaction towards the impulse buying behavior which revealed that total variability yet to be explained due to the inter linkage factors considered in this study.

4.4 Compare Mean Test

In order to find the association amid the demographic variables of the customers and the factors that influencing the Retailer Service Quality (RETSERVQ) and the impulse buying behavior, paired sample “t” test and one way ANOVA (“F” test) is conducted with the following result in Table 11 below:

Table 11
Compare Mean Test

Factors	Location	Reliability	Empathy	Customer Satisfaction	Impulse Buying Behavior
Paired Sample “t” test
Gender	81.525**	88.377**	73.428**	73.698**	125.376**
Marital Status	82.342**	91.051**	76.461**	76.249**	128.834**
Family type	81.471**	89.066**	74.558**	73.052**	125.585**
Switching pattern	81.546**	87.552**	73.735**	72.729**	124.125**
One Way ANOVA test
Age	1.562	1.505	1.291	4.106**	4.741**
Educational Qualification	3.560**	0.780	0.547	9.308**	1.837
Monthly Income	3.232*	1.105	0.871	4.841**	1.840
Type of purchasing outlet	2.695*	3.917**	0.556	3.690**	5.731**
Frequency of Purchase	4.837**	2.226	0.985	1.712**	1.734

• Source: Survey data

The result revealed that demographic variables like gender, marital status, family type and the switching pattern among the customers were found to be statistically significant with all the factors like location, reliability, empathy, customer satisfaction, and impulse buying behavior at 1 % level of significance but the result of one way ANOVA confirmed that there is a significant relationship found between the age and the customer satisfaction and impulse buying behavior; educational qualification with the location, customer satisfaction and impulse buying behavior; monthly income with the location and the customer satisfaction; type of purchasing outlet with all the factors except with the empathy and frequency of purchasing of FMCG with the location and the customer satisfaction at 1 % and 5 % level of significance.

4.4 Decision Tree Analysis

This is a statistical method where the decision-making process for a particular product could be represented based on the opinion of the respondents. In simple, it supports the strategic decision making process both for individual and for the organization but more to the marketers. In this study, the decision tree analysis is carried out and the flow chart obtained through the analysis is depicted in figure 4.

Figure 4
Decision Tree Analysis

The main aim of the decision tress analysis is to find what are the demographic factors of the consumers taken as a predictor for switching the brand of the FMCG and from the result revealed through CHAID (Chi Square Automatic Interaction Decision) method, it is noticed that the primary predictor for switching the brand of FMCG among the customers is the marital status and, it is seen that 45 percent of the married respondents and 2 percent of the unmarried respondents have given consent in switching over to the other brand of FMCG. The immediate next predictor in switching the brand in FMCG among the married category is monthly incomewhere 64.6 percent of the respondents who have the monthly income above Rs.40000/= and 49.3 percent of the respondents who have a monthly income ranging from Rs.20001/= to Rs. 40000/= have given consent in switching over the brand in case of dissatisfaction with the performance of the product. The immediate next predictor for those who have switched over to the other brand of FMCG based on the monthly income ranging from Rs.20001/= to Rs. 40000/= is the age and the chi-square result proved the remarkable bond existed between the demographic profile in all the nodes from Node 0 (root node) to Node 9 (terminal node). The classification result referred in Table 12 below also confirmed that 67.2 percent of the total population who have consented for switching the brand and 82.4 percent of the total customers who have not consented for switching the brand.

Table 12
Risk Analysis and classification matrix

Classification				Risk
Observed	Predicted			Estimate	Std. Error
	Yes	No	Percent Correct	0.226	0.018
Yes	117	57	67.2 %
No	62	290	82.4 %
Overall Percentage	34.0 %	66.0 %	77.4 %

• Growing Method: CHAID Dependent
  Variable: Switching practice

Also, the risk for the marketers, as resulted from this decision tree analysis, is (0.226) which revealed that the risk estimate and the overall correct classification rate are no longer consistent with each other-the expected risk estimate by the marketer is 0.226 (22.6 %) if the overall correct classification rate is 77.4 %.

In view to finding the similarities and the differences among the customers based on their switching mentality, k means cluster analysis is done to find the relationship between and among the factors considered under retailers service quality and with the impulse buying behavior. The result of the analysis is given in Table 13 below:

Table 13
K Means Cluster Analysis (k=3)

Final Cluster Centers				Number of Cases in each Cluster	ANOVA result
					Mean	“F” value
Z Score	Cluster
	1	2	3
Location	-0.38152	-0.12673	0.46324		34.381	39.412**
Reliability	0.28331	-0.00808	-0.25694		13.307	13.965**
Empathy	-0.87149	0.58876	0.31001		103.822	171.097**
Customer Satisfaction	-0.20831	0.87204	0-.54886		93.503	144.683**
Impulse Buying Behavior	0.41016	0.43391	-0.75157		83.340	121.641**
Distances Between the Final Cluster Centers
Cluster 1		1.857	1.966	176	Minimum Distance between Initial Centers
Cluster 2	1.857		1.978	161
Cluster 3	1.966	1.978		189
Total Sample size				526	6.079

• Total Iteration: 10; Number of clusters: 3; Method: Iterate and Classify
• **- Significance at 1 % level
• Source: Survey Data

From the above table, it is noticed that the “F” value of “Empathy” (103.822) found high followed by the customer satisfaction (93.503) which is the main source for the greatest separation between the 3 clusters formulated above. It is also seen that 176 customers in the cluster 1 were found as the most switching mentality persons towards FMCG product followed by 161 customers in the cluster 2 and 189 customers in the cluster 3 who were the least bothered persons in switching to other FMCG brand.

The Euclidean distance proved that customers in cluster 2 have equal similarity to cluster 1 and 3 as the distance found very short among the clusters. Large number of customers were found in the cluster 3 which revealed that customers with switching mentality were occupied this cluster.

5. RESULTS AND DISCUSSION

This is the study done to identify the forming of impulse buying behavior among the consumers-those who are purchasing the FMCG products through their satisfaction from the retailer’s perspective and hence the parameters such as location of the store, reliability, empathy and customer satisfaction were considered under retailer’s service quality and the impact of this service quality was analyzed directly through customer satisfaction as the moderator as satisfaction is the forerunner of impulse buying behavior.

Initially, the model fit was validated through structural equation modeling, followed by descriptive statistics. The findings indicated that the majority of respondents were female, which may be attributed due to the nature of the product used by them (i.e) FMCG, since women were responsible in planning of purchasing these products particularly grocery items.

Regarding the validation of the hypothesis, the path analysis of the structural equation modeling proved an insignificant relationship amongthe location with the retailer’s service quality (RETSERVQ) which found against the findings of (Faria and Carvalho, 2022) who proved that store design moderated the customer satisfaction and commitment in the retail industry and (Hunneman et al., 2023) who underscored that location invariably affects the store sales mainly the distance between the residence and the retail outlet and hence the hypothesis (H₁) was not validated as expected.

Regarding the association between reliability and the retailer’s service quality, the findings of this study confirmed that there is no significant association which is not parallel with the outcome of (Sung et al., 2023), that highlighted the role of positive influence of trust and reliability on the purchase intention, and hence the hypothesis (H₂) is rejected. Also, this study showed that there is no significant association between empathy and the retailer’s service quality which found controversy with the findings of (Wei et al., 2022) who informed that empathy mediating the consumer forgiveness and the repurchase intention which meant that if the retailers have a good empathy with the consumer, their sales will not be affected even if the consumers found fault in them because of their forgiveness level. However, in this study, this is totally opposite and hence the hypothesis (H₃) has not validated and got rejected.

But it is the customer satisfaction that have the positive association with the retailer’s service quality and also moderating the retailer’s service quality with the impulse buying behavior thereby corroborated with the findings of (Pornpitakpan et al., 2017) who identified that the good sales person’s retail service quality yields great impulse buying behavior and it is the customer satisfactory mood mediates the repurchase intention based on the retailer’s service quality and (Maqsood and Javed , 2019) who explained that satisfaction through price of the product and the quality have significantly influenced the impulse buying behavior and this price and quality mainly depend upon the retailer’s service quality and hence the hypotheses (H₄ and H₆) are supported, rejecting the hypothesis (H₅)

Regarding the impact of the demographic profile of the consumers on their switching habit to other brands of FMCG, the result of the decision tree analysis proved that the demographic profile marital status followed by income, type of family, and age have found as a momentous predictor for their switching mood to other brand which substantiated the findings of (Unika, 2020), and hence it is concluded that the socio- demographic characteristics of the customers/consumers have an inducement in switching to other brand of FMCG and this findings substantiated the result of (Nathiya and Kasthuri, 2021) who informed that demographic profile like income, age, gender, and education played a noteworthy role in brand awareness of FMCG products and hence the hypothesis (H₇) is accepted.

A summary of the hypothesis is given in Table 14 below:

Table 14
Summary of the Hypothesis

Hypothesis	Description	Result
H1	Location of the outlet positively affecting the retailer’s service quality in FMCG sector	Rejected
H2	Reliability positively influencing the retailer’s service quality in FMCG sector	Rejected
H3	Empathy positively influencing the retailer’s service quality in FMCG sector	Rejected
H4	There is a positive relationship between the retailer’s service quality in FMCG sector and customer’s satisfaction	Supported
H5	There is a positive impact of factors under retailer’s service quality and the impulse buying behavior in FMCG sector	Rejected
H6	Customer satisfaction positively mediating retailer’s service quality and the impulse buying behavior in FMCG sector	Supported
H7	Demographic profile positively inducing the switching mood among the customers of FMCG sector	Supported

• Source: survey data

The above results have provided the answers to the research questions of the study in such a way that the customers have satisfied with the retailer’s service quality particularly in selling the FMCG products in the selected geographical area and this service quality has enhanced the satisfaction level and it moderated the effect of retailer’s service quality with the impulse buying behavior among the customers and created repurchase intention through this impulsiveness because of the trust and reliability they have with the retailers.

PRACTICAL IMPLICATIONS

Now-a-days, consumers in both urban and rural area have a wide awareness towards the brand of FMCG (Dhanaraj, 2020) through promotional activities done through the social media and this is mainly due to the improvement in the technology (Ganesha and Sinnoor, 2019). Hence there is a chance of switching over to the other brand (Ramachandran, 2013). To retain the customers/consumers, it is mandatory for the retailers to have a good service quality in terms of reliability and trust, showing empathy, and having excellent customer relationships-this alone creates loyalty, and leads to repurchase intention. But the present scenario noticed with the marketers of this study area is not satisfactory and they should concentrate on the factors under service quality-but one doubt here is: even though there is no association between location, reliability, and empathy, consumers have satisfied with the retailer’s service quality and have their impulse buying behavior. But the decision tree analysis result proved that the socio-demographic characters of the purchaser initiated a significant function in switching behavior and hence it is compulsory for the retailers to focus on the empathy in service quality based on age, marital status, income, and educational level so that they could hold the customers in their hand in this competitive market.

7. LIMITATIONS AND SCOPE FOR FUTURE RESEARCH

As this study is focused on the retailer’s service quality based on location, reliability, empathy and customer satisfaction, and the impact of RSQ on the impulse behavior directly and through customer satisfaction as the moderator, the sample size and the area selected is very small. The result would be appreciable if the study is done through cross section analysis with other state or with other country too. While doing the future research, additional factors may also be considered for getting the precise results which will be useful to the universal audience in this domain.

ACKNOWLEDGEMENT

I would to acknowledge the support of all in successfully completing this manuscript.

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• DATA AVAILABILITY STATEMENT
  The dataset that supports the results of this study will be available upon request to author(s).
• FINANCIAL SUPPORT
  There is no financial support obtained from any sources for this manuscript.

Edited by

• Editor-in-chief:
  Márcia D’Angelo

• Associate Editor:
  Emerson Mainardes

Data availability

The dataset that supports the results of this study will be available upon request to author(s).

Publication Dates

• Publication in this collection
  01 June 2026
• Date of issue
  2026

History

• Received
  14 Dec 2023
• Reviewed
  08 May 2024
• Accepted
  20 June 2024