Keywords

Customer Behavior, FMCG, Brand Affect, Brand Performance, Switching Cost, Brand Loyalty.

Introduction

Market penetration in metropolitan areas has reached saturation. Given the sophisticated tastes and high level of customer awareness, the metropolitan markets are currently a haven for marketers looking to make a profit. Due to their rapid growth and unexplored potential, rural markets, on the other hand, offer marketers better opportunities. Through technology parks and info parks situated in remote Keralan hamlets, the level of literacy and job prospects, particularly in the I.T. sector, are rising. The population in rural markets thus earns more money and competes with their metropolitan counterparts, increasing demand. Rural communities now have better logistics and infrastructure development, including new roads and bridges, drainage systems, drinking water systems, and health initiatives. A trend of reverse migration from urban to rural regions seeking a tranquil lifestyle is currently occurring in Kerala as a result of considerable developments in communication, automobiles, and greater consumer affordability. The rail and road expansion has increased the mobility of rural populations of Cochin as well as neighboring districts of Cochin, allowing them to live in rural and suburban areas and commute to and from jobs. These consumers had a higher level of knowledge and a stronger desire to keep up with the purchasing habits of urban consumers since they commuted to metropolitan areas for employment, residence, or study.

Rural markets benefit most from the usage of Fast-Moving Consumer Goods because these goods can quickly reach all of these villages. Fast Moving Consumer Goods (FMCG) refers to relatively quickly moving products that the consumer uses directly. They impact every element of human existence. It is the most significant potential market in the world, raising the market's revenue level and likely expanding soon. With a total market value of more than US$ 44 billion, the FMCG industry in India ranks fourth in terms of economic size. Strong MNC participation, a well-established logistics chain, fierce competition between organized and unorganized groups, and minimal operating costs are its defining characteristics. According to Kashyap & Raut (2005), the FMCG segment in India is the most appealing market The growth in the commercial scenario of the rural customers has helped FMCG firms in enlarging their market to the different localities of the country, which brought numerous concerns due to highly uncertain customer profiles, stiff competition, inconsistent brand loyalty, and rising customer expectations. To combat these issues, marketers must investigate customer behavior or the criteria they choose to select the particular FMCG brand. Consumerism in FMCG products has thus made way for fresh study in this broad field.

The ability to distinguish a company's goods from its rivals through branding has become a critical business strategy. By focusing on one or more of the branding objectives, such as product identification, recurring business (loyalty), and improving new products, branding is used in this situation to provide a competitive advantage. A brand should be managed in terms of comprehensive marketing. Activities are planned so that they add value to the brand. (Mohammed et al., 2017) Managers have understood the value of branding and the advantages of keeping existing clients rather than seeking new ones. Companies have comprehended the importance of brand loyalty as a tactical tool for competitive advantage. A consumer's relationship with a brand is measured by brand loyalty. Brand loyalty refers to a customer's continued use of a favorite brand (Ball et al., 2004). Customers are adopting brands that meet their needs rather than being loyal to a specific brand. In contrast to Jacoby's composite model, which pioneered the idea of measuring brand loyalty as an attribute in 1971, the notion of brand loyalty as a crucial component of a brand management strategy arose in the 1950s. This measurement paradigm combined the consumer behavioral dimensions, kicking off a boom in brand loyalty studies. The current study aims to comprehend how different factors related to consumer behavior affect brand loyalty. It explores the relationship of brand affect, switching cost, and brand performance outcomes on customer behavior, emphasizing the linking role of brand loyalty.

Literature Review

Market share and price premiums have been tightly correlated with brand equity (Aaker, 1996). These results depend on numerous facets of brand loyalty, which eventually impact brand profitability. Brand-loyal customers are willing to pay a higher price for a brand because they believe it offers unique benefits that rival products cannot match. This distinctiveness may result from a brand trust or brand affect. Similarly, brand loyalty increases market share when customers consistently buy the same product, regardless of external factors. In conclusion, higher customer loyalty may lead to better brand performance outcomes like a bigger market share and a higher price. This loyalty can then be assessed based on the brand's perceived quality and the emotions or affect it creates. Research by Chaudhuri & Holbrook (2001) has demonstrated the potential value of brand loyalty in determining brand performance outcomes. The relationship between a firm and its customers is significantly influenced by brand affect, which in turn influences consumer brand loyalty, perceived initially as repurchase intention. The study by Mallik (2021) contributed to our understanding of how customers think about product awareness and consumption. The study concluded that consumers are willing to transfer to another brand if they discover better promotional offers that fit their budget and result in higher quality, lower cost, and more quantity. Brand loyalty encouraged additional customer visits, which was closely tied to firms’ profitability (Hyun-Ah et al., 2005). Brand loyalty thus inspires positive businesses (Kotler et al., 2022).

One of the most crucial areas of marketing is customer behavior, which aids marketers in comprehending consumer psychology pertaining to a specific brand. Despite the fact that the research on consumer behavior is in its infancy, scholars have conducted many studies to gain a better understanding of consumers. According to Hobbs (2019), consumers' preferences and food-buying habits vary. The current study aimed to identify some of the variables that affect rural customers' choices when it comes to buying FMCGs. The variables used in the study to understand customer behavior are brand affect, brand performance, and switching cost.

According to Chaudhuri and Holbrook (2001), brand affect is the ability of a product or service to cause the typical consumer to feel positive as a result of using it. Brand affect is as widely researched in marketing literature as brand trust (Iglesias et al., 2011). Findings by Kabadayi & Kocak Alan (2012) indicate that brand affect and brand trust are essential factors in establishing brand loyalty. The relationship between brand affect and brand trust is strong. Based on these studies, the following hypothesis has been proposed.

H₁: The brand affect of the particular brand is positively associated to brand loyalty

An enterprise's financial success is measured by brand performance (Lai et al., 2010). The idea of brand performance describes how powerful a company's brand is in the marketplace. It is a significant outcome of corporate operations and broad business objectives. Brand performance influences brand loyalty in various ways, including purchase and attitude loyalty. Prior studies found a considerable link between brand loyalty and an organization's financial performance (Tsai et al., 2010 and Unurlu & Uca, 2017) It is believed that brand performance and loyalty have a favorable and significant link in light of these research results. Hence the following hypothesis has been proposed.

H₂: The brand performance of the particular brand by rural customer is positively related to brand loyalty

According to the research of Lee et al. (2001) on mobile telecommunication service, the expense a customer incurs when changing service providers—a cost they would not have paid had they stayed loyal to their existing service providers—is known as the switching cost. Switching costs, therefore, are thought to play a role in maintaining relationship with a particular brand (Colgate and Lang, 2001). Switching costs may also be correlated with perceived risk, which is the belief among consumers that using another company's goods or services may have unfavorable effects. Studies in theory and practice demonstrate the critical role switching costs play in safeguarding a firm's current clients and acquiring a competitive edge. As a result, businesses now focus on marketing initiatives that manipulate this cost (Burnham et al., 2003).

Brand loyalty is used in marketing literature to describe a particular form of switching cost. The minimal price difference required before consumers who favor one brand transfer to a rival brand is how brand loyalty is typically defined in terms of switching costs. Prior research has shown that switching cost is a significant factor in winning brand loyalty (Aydin et al., 2005, Jones et al., 2002, Lee et al., 2001). In light of the above literature, the following hypothesis has been proposed.

H₃: Brand switching cost of a particular brand is positively linked to brand loyalty

One of the fundamental components of brand value is brand loyalty, which is defined as "the extent to which consumers buy a particular brand." Brand loyalty describes consumers' psychological attachment and behavioral tendencies to a specific brand in addition to their future purchases of the same goods. The frequency of purchases serves as the foundation for behavioral brand loyalty research, which emphasizes the significance of a particular brand. According to Khadka and Maharjan (2017), acquiring new customers is more expensive than keeping existing ones, hence loyal clients are a company's most valuable asset. Customer loyalty is essential to a brand's long-term success. Based on the thorough literature review and hypothesis development, the following conceptual model was proposed.

Brand affect, brand performance, and switching cost are the independent variables, and brand loyalty is the dependent variable in the study. The model predicts that all the considered independent variables have a notable impact on brand loyalty.

Research Methodology

The current study poses the following question: How do different factors related to consumer behavior affect the perception of brand loyalty among the users of FMCG products? Therefore, the objective of the research is to study the relationship and impact of different consumer behavior (brand affect, brand performance, and switching cost) based factors on the brand loyalty perception of the customers. The sampling technique chosen for this research will be convenience sampling. A well-structured questionnaire containing 12 close-ended questions was administered to customers to collect primary data pertinent to the study’s objectives. A total of 150 consumers with previous experience making purchases on online shopping sites are chosen as the sample. In the study, all variables were measured and analyzed from November to March 2022. Most of the questions are constructed using the Likert scale, ranging between 1-strongly Agree; 2-Agree;3-Neutral;4-Disagree; 5-Strongly Disagree. The questionnaire was circulated via Google forms online. The data were analyzed using the SPSS software. In order to find the relationship and influence between variables, the linear regression method is used. The reliability of internal consistency was determined using Cronbach's alpha. Descriptive statistics were used in data analysis.

Results and Discussion

The demographic profile of the 150 consumers is given in Table 2. Among the 150 consumers,54.7% are male, and the rest are female. According to the report, 58% of the respondents lie between the age group of 18-25, 38.7% lie between the age group of 26-35 and the rest, 3.3%, lie in the age group of 36-45.

Demography	Frequency	Percentage (%)
Gender	Male	54.7
	Female	45.3
Age (in years)	18-25	58
	26-35	38.7
	36-45	3.3

Table 2: Demographic profile of the consumers.

The reliability statistics of variables are calculated with SPSS, and results are given in Table 3. If the reliability value is above 0.6, it is said to be reliable. Here the values are all above 0.6. Hence it can be said that all the variables are reliable in nature.

Variables	Cronbac h's Alpha	N of items
Brand Loyalty	0.805	2
Brand affect	0.864	3
Brand Performance	0.805	2
Switching Cost	0.805	2

Table 3: Reliability statistics of each variable.

The data is interpreted from the Regression Analysis technique, which was used to check the impact of performance, switching cost, and brand affect on brand loyalty. To examine the proposed hypothesis, multiple linear regression is applied using enter method. The unstandardized regression coefficient for predicting brand loyalty from brand performance and switching cost are 0.566 and 0.344, respectively; the standardized coefficients are 0.556 and 0.272. The summary of these results is presented in table 4, 5, and 6.

Model	R	R2	Adjusted R2	Standard error of the estimate
1	.732a	.535	.532	.72243
2	.760b	.578	.573	.69051

The R-value indicates the degree of association between the dependent and independent variables. A value greater than 0.4 is considered for further examination. Here both models have values greater than 0.4, which is good. R² shows the total variation for the dependent variable that the independent variable could explain. Using the R² from the results of step-by-step regression analysis (table 4), we can say that R² =0.535 indicates that 53.5% of the variance in brand loyalty is predicted by switching costs alone. Likewise, 57.3% of the variance in brand loyalty is predicted by both switching costs and brand performance. Thus, the models are effective enough to determine the relationship between the variables.

Generally, a 95% confidence level or 5 % significance level is chosen for the study. Here the switching cost and brand performance are significant with a sig value below 0.01, that is, 0.000. Therefore, the results are significant. In addition, considering the model's inaccuracy, a F ratio greater than 1 indicates an efficient model. In table 5, F values are greater than 1, which is good. ANOVA and coefficients of models are illustrated in tables 5 and 6, respectively. Here all the beta values are positive, which shows that all the controlled variables have a significant influence on the measured variable. i.e., brand loyalty as the p value is less than 0.005. (Table 6)

Model		Sum of squares	Degree of freedom	Mean Square	F	Sig.
1	Regression	88.951	1	88.951	170.436	0.000b
	Residual	77.242	148	0.522
	Total	166.193	149
2	Regression	96.102	2	48.051	100.776	0.000c
	Residual	70.091	147	0.477
	Total	166.193	149

Table 5: ANOVAa (Summary Of regression analysis)

Regression equation: Y=a+b1*1+b2*2, where Y is the dependent variable. Following is the regression equation obtained from the regression analysis:

Brand loyalty=0.277+0.566*Switching cost+0.344*brand performance.

Therefore, when there is unit variation in switching cost, the variation in brand loyalty is 0.566. When there is unit variation in brand performance, the amount of the variation is 0.344.

Models		Unstandardized Coefficients		Standardized Coefficients Beta	T Value	Significance
		Beta	Standard Error
1	Constant	0.786	0.186		4.217	0.000
	Switching cost	0.744	0.057	0.732	13.055	0.000
2	Constant	0.277	0.221		1.249	0.214
	Switching Cost	0.566	0.071	0.556	7.935	0.000
	Brand Performance	0.344	0.089	0.272	3.873	0.000

Table 6: Coefficients.

Table 7 shows the minimum value, maximum values, mean and standard deviation of the variables in the study. Switching cost has the highest mean of 3.1, indicating it plays a vital role in this study and for the respondents. As the variables are measured using a 5point Likert scale ranging from 1= strongly disagree to 5= strongly agree, the minimum and maximum values reflect this. Also, the standard deviation of variables is low.

Variable	N	Minimum	Maximum	Mean	Standard Deviation
Brand Loyalty	150	1.00	5.00	3.0933	1.0561
Brand performance	200	1.00	5.00	3.0650	1.1935
Brand Affect	150	1.00	5.00	3.0933	1.0561
Switching cost	150	1.20	5.00	3.100	1.0380
Valid N (listwise)	150

Table 7: Descriptive statistics of the variables.

The p-value for the relationship between brand affect and brand loyalty is more than 0.001. Hence H₁ is rejected at a significance level of 1%. But the p values for the effect of brand performance and brand loyalty as well as switching cost and brand loyalty were less than 0.001, indicating that H₂ and H₃ are accepted at a significance level of 1%. (Table 8). Thus multiple regression predicts brand loyalty from the two antecedents switching cost and brand performance as the ‘sig’ is less than 0.01.

Hypothesis	P value	Accepted/Rejected
H1: Brand Affect → Brand loyalty	0.1	Rejected
H2: Brand Performance → Brand loyalty	0.00	Accepted
H3: Switching Cost→ Brand loyalty	0.00	Accepted

Table 8: Hypothesis testing result.

Conclusion

Brand Loyalty gives businesses powerful and competitive tools to battle rivals in the marketplace. From the current study, it has been concluded that brand switching cost and brand performance has been positively related to brand loyalty. In contrast, brand affect has a negative impact on brand loyalty. Thus, the current study concludes that switching costs and brand performance are predictors of brand loyalty in the FMCG sector in rural Cochin. In contrast, Chaudhuri & Holbrook (2001) discovered that brand affect and brand performance are two diverse attributes that work together to determine two distinct types of brand loyalty, namely attitudinal loyalty and purchase loyalty. These two types of brand loyalty respectively influence market share and relative price. Similarly, Kabadayi & Kocak Alan (2012) and Zhang et al., (2013) find a positive influence of brand affect on brand loyalty. Switching cost directly affects brand loyalty which supports the prior research by Aydin et al (2005) and Caruana (2003). In contrast, Sharma & Patterson (2000) concluded that perceived switching costs had a detrimental impact on consumer loyalty and trust. The current study is supported by Thompson and Sinha (2008), who demonstrated that product performance is positively and significantly affected by brand loyalty.

Limitation and future implication

The study was conducted in rural Cochin, and the findings may not apply to other regions of the nation. Also, the sample size is 150, which is a relatively small number. The responses of the respondents serve as the foundation for the data gathered, and the respondents' responses alone will determine how accurately the data is disclosed. Only FMCG product categories and customer behavior are highlighted in the study. Future studies can include other products as well, along with FMCGS, to understand customer behavior better. The determinants of consumer loyalty were formerly thought to be brand performance, affect, and switching costs. However, numerous additional factors might influence loyalty, including brand image, service quality, etc. Future research may broaden the data set, quantify the moderating impacts of the switching cost sub-dimensions and other variables, study the effects of all these variables on loyalty simultaneously, and extend the hypotheses and models created here to other market sectors.

Consumer brand loyalty appears to be diminishing in recent times due to a number of factors, including complex advertisements and widespread media assistance, product resemblance, effective promotional strategies that appeal to buyers’ impulse purchasing, general consumer fickleness in purchasing behavior, and the expansion of new products competing for display space and consumer interest. In the vast topic of consumer behavior, a study on why brand loyalty varies widely is significant. The causes for differences in brand loyalty are an essential subject of research in the large field of consumer behavior. Understanding the role of demographic factors in determining brand loyalty can help marketers rethink their marketing strategy to increase brand loyalty for their products, which has numerous benefits for marketers and organizations.

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Received: 16-Jun-2023, Manuscript No. AMSJ-23-13699; Editor assigned: 19-Jun-2023, PreQC No. AMSJ-23-13699(PQ); Reviewed: 25-Sep-2023, QC No. AMSJ-23-13699; Revised: 04-Oct-2023, Manuscript No. AMSJ-23-13699(R); Published: 10-Nov-2023