Keywords

Customer Loyalty, Store Loyalty, Department Store, Organized Retailers.

Introduction

The fiercely competitive business environment of the 21^st century coupled with the increase of demanding and knowledge customers has presented one of the most important challenges to the marketers and that is developing a base of loyal customers. It’s because previous studies have highlighted the importance of customer loyalty and the benefits to a firm derived out of loyal customers. It was found that the attracting cost for a new customer was 6 to 8 times more than the cost to customer retention (Gruen, 1997). Hence the success of a business lies in developing a strong base of loyal customers.

In a retail business context, store loyalty means customers’ deeply held commitment to purchase merchandise from a retail store despite competitors’ efforts to attract their patronage and having the potential to encourage switching behavior. The loyal customers are emotionally attached to a particular retail store (Levy & Weitz, 2007). There are various benefits a firm can have from a strong base of loyal customers. The firm derives economic benefits (through increased purchases over time and lesser marketing expenditures to serve its customers), Consumer behaviour benefits (through WOM communication, referrals and customer voluntary performance) and HRM benefits (through customer co-operation/assistance in delivery process and less difficulty in serving loyal customers leading to increased employee retention) (Zeithaml et al., 2011).

The Indian retail sector has experienced a severe transition in the 21^st century with the increase in the share of organized retailing and the launch of new formats like supermarkets, hypermarkets, department stores, etc. The pace of organized retailing can be assessed from the fact that it took the organized retail a few decades to gain just a 2% share of the total retail market in 2002. But, due to the rapid growth of organized retailing in 2000 and beyond, the share of organized retailing jumped rapidly from 2% to 8% in just a span of 10 years from 2002 to 2012 with the the entry of leading corporate groups (India Retail Report, 2019; India Retail Report, 2013; Shoppers Stop Annual Report, 2003-04).

With the growing competition in organized retailing sector in the country, due to the entry of leading business groups like Tata, Birla, Reliance, Raheja etc. and launch of numerous e-commerce players, organized retailers (physical store-based) are finding it difficult to hold their customers for a long time from switching to competing retailers and make them loyal to them. Leading organized retailers especially department stores like Shoppers Stop, Pantaloons, Lifestyle, etc., from which customers have high expectation, have already adopted a relationship marketing approach and undertaken multiple initiatives to develop strong store loyalty. Levy & Weitz (2007) describes a ‘department store’ as a big general merchandise retailer that carries a huge variety and deep merchandise assortment which also offers a range of customer service from attentive shopping assistance, alterations, to home delivery. The variety of products ranges from apparel & fashion accessories, cosmetics, home furnishings, etc. and are organized into separate departments. These stores are distinctive in terms of the shopping experience, the level of services and the store atmospherics. They have made efforts in making the shopping experience great, rewarding customers for their loyalty through loyalty programs, making regular communication with each customer, sending store updates and personalized communication messages. However, according to Merrick et al. (2002), these stores are experiencing competitive pressures due to increased competition from discount stores, specialty stores and aggressive e-commerce players like Amazon. Today, these stores are not having exclusive and appealing merchandise to match consumer needs, especially of the youths.

Considering the above situation, its rationale to conduct a study on understanding customer loyalty towards department stores as only a solid base of loyal customers can guarantee the success of an organization. This paper attempts to make a comprehensive analysis of store loyalty towards the leading department stores with special reference to select customer demographics - age, gender, marital status and income.

Literature Review and Hypotheses Development

Store Loyalty

According to Pappu & Quester (2006) Store loyalty is

“The tendency to be loyal to a focal retailer as demonstrated by the intention to buy from the retailer as a primary choice”.

Loyalty creates different advantages and subsequently is helpful in creating and actualizing several marketing methods (Jacoby & Chestnut, 1978). Like, loyalty creates pool of customer for products and services of a firm (Oliver, 1997). Loyal customers take an interest in repurchasing, Word of mouth and are able, ready to pay higher price (Zeithaml et al., 1996). The efforts to keep up store loyalty are considered as a critical retailer methodology of customer retention and which results in sustainability and profitability (Wallace et al., 2004).

Sainy (2010) considered that impact of service quality and demographics factors on the loyalty of the customers in retail outlets. Age (two levels), gender, occupation (engaged in business or service) and high or low income and Departmental Retail store format was considered for the analysis. The study indicated positive effect of service quality on customer loyalty and demographics variable demonstrated a positive impact on customer loyalty. Customers’ purchasing preferences, related to demographic profiles was compared with the customer’s perceptions toward different retail formats (Shergil & Chen, 2008). There is significant impact of psychographic and dynamics of consumers on organised grocery and food retail store. The study also found that the consumer’s opinion, perception changes while purchasing things in various kinds of retail outlets. Housewives and workingwomen and are bound to do shopping in supermarkets (Prasad & Reddy, 2007).

Most of the studies on loyalty in marketing literature are emphasized on customer loyalty to a brand i.e. brand loyalty, from where the concept of store loyalty i.e. customer loyalty to a retail store has been derived. There are several definitions of loyalty proposed by different authors and researchers; however, there has been a debate over the concept of loyalty as researchers have different perspectives on loyalty. A group of researchers conceptualized customer loyalty in terms of behavioural measures – repeat purchase behaviour (Cunningham, 1961; East et al., 1995). This concept of loyalty was challenged by many researchers. They argued that mere repeat purchasing without attitudinal preference is ‘spurious loyalty’ and do not qualify for ‘sustainable loyalty’ (Jacoby & Kyner, 1973; Dick & Basu, 1994).

While examining differences in consumer dependent on Demographics, scholars found out that there is significant distinction between the behavior of men and women (Kolyesnikova et al., 2009). Women and men act in an unexpected way (Kolyesnikova et al., 2009) and the way they shop is evident and bring distinctions (e.g., Bakewell & Mitchell, 2004; Dholakia, 1999). For instance, women have more prominent proclivity for shopping and as compared to men women moves slowly in the stores, interacts with the store staff, check out products and qualities, price comparisons, communicating with staff, posing inquiries, trying out products before buying (Gąsiorowska, 2011). Studies have additionally discovered that perception of representative brand benefits differs from gender to gender. For instance, the brand personality measurements among men vary from women (Grohmann, 2009). Given the realities consumer shopping behavior varies from men to women. Along these lines, this study hence attempts to explore the role gender in the representative store loyalty. Examination of directing job of sex in the emblematic brand benefits–brand loyalty connections would assist retailers with formulating and executing gender related marketing strategies like segmentation, targeting, positioning to develop store loyalty.

According to the study, 'gender differences' is utilized to allude to the analyze and compare behavior of men and women with regards to social roles. Gender has been incorporated as a precursor in an extensive amount of studies, and various researchers have demonstrated that gender directs the impacts of satisfaction on loyalty (Mittal & Kamakura, 2001; Homburg & Giering, 2001; Das, 2015; Sharma et al., 2012). Gender has been found to direct the connections between perceived value or satisfaction and behavioral intentions in retail sector (Sharma et al., 2012). As per context of retail, there seems, by all accounts, to be an agreement that women and men vary in shopping style, perceptions and behaviors (Faqih, 2016; Babin et al., 2013; Borges et al., 2013; Mortimer & Clarke, 2011; Respectable et al., 2006).

Men are engaged in bigger groups and women are mainly in pair bonds (Melnyk et al., 2009; Gabriel & Gardner, 1999). Specifically, study has indicated that women are loyal to individuals, for example service employees, whereas men focus their loyalty on entities such as companies (Melnyk, 2014). The previous study has analyzed perceived innovativeness from the consumer’s point of view (Kunz et al. 2011; Boisvert & Ashill, 2011; Hubert et al., 2007; Kim et al., 2015; Pappu & Quester, 2016; Jin et al. 2015; Kim et al., 2018). Notwithstanding the developing significance of retailer innovativeness, few experimental investigations have concentrated on this idea and expected to see how innovativeness assumes a job on customer’s observations inside in food retailing (Anselmsson & Johansson, 2009; Lin et al. 2015; Lin, 2016).
After analyzing previous pieces of literature on loyalty, (Oliver, 1999) believed

“A strongly held commitment to repurchase a preferred brand consistently in future, in spite of situational influences and competitors’ marketing efforts of having the potential to prompt switching behavior”.

In a retailing context, store loyalty refers to ‘customers’ commitment to purchase merchandise from a retail store despite competitors’ efforts to attract their patronage. The loyal customers are emotionally attached to a particular retail store. The reasons for continuing patronizing a retailer go beyond the store convenience, low prices or the specific brands offered by the retailer (Levy & Weitz, 2007).

Multiple studies indicate store attributes to influence store choice and loyalty (Berry, 1969; Solgaard & Hansen, 2003; Bearden, 1977; Chang & Tu, 2005). Berry (1969) identified three attributes i.e. merchandise assortment and quality, sales staff, and store atmosphere influencing consumer’s store choice. In addition to these attributes, Solgaard & Hansen (2003) identified numerous store-related attributes - store layout, accessibility and cleanliness - significant for the consumer’s assessment of retail stores. Bearden (1977) identified attributes like price, merchandise assortment and quality, location, parking facilities, friendliness of sales staff, and store atmosphere influencing consumer’s store patronage. Chang & Tu (2005) found service offerings, activities, facilities, and convenience as the main factors having a significant impact on the satisfaction and loyalty of retail customers. Store prestige and trust developed by the store are significantly related to store loyalty (Konuk, 2019)

Effect of Age on Store Loyalty

In case our hypotheses get accepted i.e. (the impact of gender on store loyalty), at that point it is enticing to know if this impact is relentless over the customer's lifetime. Psychological research has yet various models have been seen and analyzed the various gender differences in connection to the functions of age.

Role of Gender in Western nations got liberal among the youthful ages traditionally (for example Neiss et al., 2009). In the event that the association of age and gender is to be inspected, age should in addition be melded as a variable with a direct effect on loyalty. Study has demonstrated that existing and old consumers are bound to repurchase a specific vehicle brand, and preferred lesser about other brands, dealers of automobile vehicles and variants throughout the buying process as compared to the youthful consumers (Lambert-Pandraud et al., 2005). Similar proof shows that the older consumers are bound to be loyal to the product they utilize for longer period of time (Lambert-Pandraud & Laurent, 2010).

Age directs the satisfaction of customer and loyalty relationship (Lambert-Pandraud & Laurent, 2010; Homburg & Giering, 2001). The study in the retail segment demonstrates that older customers don't utilize various retailers for their shopping of food as against the youthful consumers (Meneely et al., 2009) and customers with a constrained future time horizon are progressively faithful to their retailer selling grocery (Kuppleweiser & Sarstedt, 2014). Age has also been found to direct the relationship among satisfaction and loyalty covering six retail classifications (fashion-style, Cosmetics, electronic gadgets, telecom, jewellery and retail chains) (Sharma et al., 2012). In light of every one of these outcomes, older customers are relied upon to have better store loyalty than their more youthful customers. It was identified that Older Generation Y customers’ expectations for services varies by type of stores, and expectations levels, perception towards service quality and service was linked to satisfaction of retailer’s and store loyalty (Jin Ma & Niehm, 2006)

Since attributes and personality associated with each store may not be the same as perceived by the customers, it may be assumed that customer loyalty also varies with the store. Hence the following hypothesis is developed:

H1: Store loyalty significantly varies from store to store to which the customers are associated.

Store Loyalty and Customer Demographics

The core of all market segmentation is consumer demographics because many consumption behaviors and attitudes are directly related to demographics. Product needs often vary with customers like age, gender, marital, income, ethnicity, etc (Schiffman & Kanuk, 2007). Previous studies have found that there is an association of Customer demographics with their loyalty towards a brand or firm. Patterson (2007) found an impact of age & gender on loyalty and satisfaction towards service products. Oyewole (2001) found a significant influence of marital status on customer loyalty. Sasikala (2013) found an association of age, gender, marital and income with customer loyalty. Sinha et al. (2002) found store loyalty dependent on the store as well as shopper-related variables like age, income, etc. Previous studies have inspected the impact of consumer demographics on choice of grocery retail format. Zeithaml (1985) study looked at the impacts of five demographic factors (women working status, gender, marital status, Income, age) on supermarket shopping variables (for example visit to supermarket stores week after week, shopping time, and money spent). The study stressed that adjustments in the family (for example number of working women, male, and widowed, divorced and singles) would drive changes in grocery patronage in the USA.

Fox et al. (2004) analyzed the impact of demographics on various format choices between grocery markets, mass merchandisers, and Pharma retails. The study demonstrated that income, household size, and qualification impact consumer’s format choices

Charlton (1973) stated that developed countries household with a high level of store loyalty is with low-income group and lowest store loyalty is with higher income households. In contrast, we also found that the presence of a employed wife in the household tends to decrease store loyalty.

Charlton (1973) proposed that store loyalty is to a great extent is a negative characteristic, possessed of necessity instead of choice, because of time, income and mobility constraints. Certain retail chains (Spencers, Imprints, Sainsburys) seem to have developed piece of the pie for food and groceries effectively by promoting store loyalty, especially among higher income groups where customarily store loyalty has been low. As it were, the job of the retail chain in promoting store loyalty might be substantially more dynamic than was beforehand the situation. These points recommend that specific high-income group do pick a procedure of high store loyalty, maybe with pressures on time as contributory factor.

Past studies have stated that customer satisfaction prompts higher estimation of a firm (Askoy et al., 2008), by ascend in income flow and future growth and development (Malshe & Agarwal, 2015). According to study of retail, customer satisfaction has been exhibited to be key for retention of the customer (Pappas et al., 2014), which indicates store loyalty (Hsu et al., 2010). Customer satisfaction has been exhibited to be a significant indicator of customer loyalty (Oliver, 1999, Zeithaml, 2000). The evidence shows that a loyal, satisfied customer enhances their purchase intensity from the retail store (Anderson & Sullivan, 1993), and spread positive word of mouth (Anderson, 1996).

According to Carman (1970) income was unfavorably related with First Store Loyalty (Tate, 1961; Enis & Paul, 1970; Dunn & Wrigley, 1984). Carman prescribed that loyalty towards a store rose up out of a lifestyle. Enis & Paul, and Tate, battled that store loyalty within the less affluent was the result of impediments in transport time, stock management and access to alternative stores. McGoldrick & Andre (1997) have exhibited that the customers with higher First Store Loyalty will have better income. Regarding age, Mason (1991) and East et al. (1995) indicated that the under-45 age group demonstrated higher First Store Loyalty as compared to other age groups. Mason (1996) stated that 65+ age are least loyal.

Hypotheses

Following hypotheses have been developed for the study based on the earlier studies:

H2: Store loyalty significantly depends on age groups. H3: Store loyalty significantly depends on gender.

H4: Store loyalty significantly depends on marital status. H5: Store loyalty significantly depends on income groups.

Objectives of the Study

1. To analyze store loyalty across leading department stores in the national capital region of Delhi.

2. To analyze store loyalty across customer demographics- age, gender, marital status and income.

Research Methodology

The study was descriptive based on data collected from retail store customers. The primary data was collected with the help of a structured questionnaire developed after a thorough literature review and pilot study. A five-item customer loyalty scale was developed after thoroughly studying the research works and views of Oliver (1999), Zeithaml, Berry & Parasuraman (1996) and reviewing the loyalty scale developed by Hayes (2011).The five items in the loyalty scale were analyzed with a 5 point Likert scale, in which ‘1’ was for strongly disagree and ‘5’ was for strongly agree. For checking the reliability of the loyalty scale developed in this study Cronbach’s Alpha test was used.

The data was collected from 287 respondents, who were over 18 years and purchased in one of the five leading department stores- Shoppers Stop, Westside, Pantaloons, Globus, and Lifestyle. The respondents were asked to select a retail store where they shop relatively regularly and felt fairly most associated. The geographical area of the study is the National Capital Region (NCR) of Delhi. The convenience and mall intercept sampling technique was used for this study. Statistical analysis of the collected data was done with the help of SPSS 20 version software. For descriptive analysis, Mean and Standard deviation were used. For testing the hypotheses developed in the study, independent sample t-test and One-way ANOVA statistical tool was used. Tukey HSD was used to conduct Post-hoc analysis to understand whether the means of two specific groups were significantly different or not.

Results and Discussion

As shown in the above Table 1, almost three fourth of the respondents in the sample belong to the age group of 18 to 35 years, and just over 6% fell in the older age group i.e. above 45 years. Male and female respondents made up 61% and 39% of the total respondents respectively. Unmarried and married respondents were almost the same in number in the sample Over 65% of respondents had monthly income of over Rs. 50,000, with the highest proportion belonging to the Rs 50,001 – 75,000 groups. In the sample, the highest proportions of the respondents (30.7%) were customer’s pantaloons store. It was followed by Shoppers Stop (21.3%), Globus (18.1%), Lifestyle (16%) and Westside (13.9%).

Table 1 Respondents’ Demographic Profile
Age
	Frequency	Percent
18-25yrs	108	37.6
26-35 yrs	106	36.9
36-45yrs	54	18.8
>45yrs	19	6.6
Total	287	100.0
Gender
MALE	175	61.0
FEMALE	112	39.0
Marital
married	139	48.4
unmarried	148	51.6
Income
	Frequency	Percent
Up to Rs 25,000	31	10.8
Rs25,001 to Rs50,000	68	23.7
Rs 50,001 to Rs 75,000	78	27.2
Rs 75,001 to Rs 1 lac	48	16.7
>Rs 1 lac	62	21.6
Total	287	100.0
store
	Frequency	Percent
Shoppers Stop	61	21.3
pantaloons	88	30.7
globus	52	18.1
lifestyle	46	16.0
westside	40	13.9
Total	287	100.0

Reliability Test

For checking the reliability of the loyalty scale developed in this study Cronbach’s the alpha test was used. The five items in the loyalty scale were considered for the test and the value of ‘Cronbach alpha’ was 0.848. This alpha value indicates a high reliability of the internal consistency of the questionnaire (Hair et al., 2006).

Hypothesis Testing

The results of the testing of the hypotheses developed in the study are shown in Table 2. Statistical tools used to test hypotheses were One-way ANOVA and independent sample t-test. A 95% confidence interval is taken in the study and hence the alpha value considered for hypothesis testing is 0.05. A significance value of more than 0.05 means acceptance of set null hypothesis and rejection of the alternate hypothesis. Out of the nine hypotheses, only one alternate hypothesis (H4) is rejected. The details of the hypotheses testing are mentioned in further sections.

Table 2 Summary Table of Hypotheses Testing Results
Alternate Hypotheses Developed in the study	Test	Result
H1: Store loyalty significantly varies from store to store to which the customers are associated.	One-way ANOVA	Accepted
H2: Store loyalty significantly depends on age groups.	One-way ANOVA	Accepted
H3: Store loyalty significantly depends on gender.	Independent sample t-test	Accepted
H4: Store loyalty significantly depends on marital status.	Independent sample t-test	Rejected
H5: Store loyalty significantly depends on income groups.	One-way ANOVA	Accepted

Store Loyalty across Leading Department Stores

As shown in the ANOVA Table 3, F=12.350 and associated Significance value = 0.000 (95% confidence interval considered) which is less than the significance level of 0.05. It indicates acceptance of the alternative hypothesis H1 i.e. Store loyalty significantly varies from store to store to which the customers are associated

Table 3 ANOVA Test for Hypothesis 1
Loyalty	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	20.994	4	5.248	12.350	0.000
Within Groups	119.839	282	0.425
Total	140.833	286

An inspection of the descriptive Table 4 indicates that the total loyalty mean of all respondents taken at a time was fair with a mean a score of 3.60 and there was a range in customer loyalty of respondents associated with different stores. Shoppers stop was ranked the best store in terms of store loyalty (loyalty mean = 4.07) followed by Westside (loyalty mean = 3.63), pantaloons (loyalty mean = 3.51), globus (loyalty mean = 3.47) and lastly lifestyle store (loyalty mean = 3.24).

Table 4 Descriptives for Hypothesis 1
	N	Mean	Std. Deviation
Shoppers Stop	61	4.07	0.47
Pantaloons	88	3.51	0.69
Globus	52	3.47	0.68
Lifestyle	46	3.24	0.78
Westside	40	3.63	0.61
Total	287	3.60	0.70

The Post-hoc analysis with Tukey (see Appendix Table A1) found that loyalty of respondents associated with Shoppers Stop was significantly higher than any another store in the study i.e. Westside, Pantaloons, Globus, and Lifestyle. The loyalty of respondents associated with Westside was found to be significantly higher than only one store i.e. Lifestyle, but was not significantly different from those associated with Pantaloon and Globus. The loyalty of respondents associated with Pantaloons, Globus, and Lifestyle stores was not significantly different from one another.

Store Loyalty across Age Groups

As shown in above ANOVA Table 5, F=3.891and associated significance value = 0.009 which is less than the significance level of 0.05 means acceptance of the alternative hypothesis, H2 i.e. Store loyalty significantly depends on age groups.

Table 5 ANOVA Test for Hypothesis 2
Loyalty	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	5.579	3	1.860	3.891	0.009
Within Groups	135.254	283	0.478
Total	140.833	286

An inspection of the mean Table 6, indicates that the store loyalty among older respondents were higher than the younger respondents. The loyalty of above 45 years age group was the highest (Mean = 4.00) followed by 36-45 years age group (Mean = 3.71), 26-35 years age group (Mean 3.58) and lastly 18-25 years age group (Mean = 3.47).

Table 6 Descriptives for Hypothesis 2
Loyalty	N	Mean	Std. Deviation
18-25yrs	108	3.4722	0.70959
26-35 yrs	106	3.5849	0.70896
36-45yrs	54	3.7185	0.64955
>45yrs	19	4.0000	0.58878
Total	287	3.5951	0.70173

The Post-hoc analysis with Tukey (shown in appendix Table A2) found that significant difference in-store loyalty was there between only two out of the four groups. The store loyalty of the oldest age group was significantly different than that of the youngest age group. The store loyalty of the oldest age group (45 yrs and above) was found to be significantly higher than the loyalty of the youngest group (18-25 years age group). The three age groups i.e. 18 to 25 years, 26 to 35 years and 36 to 45 years groups were not found to be significantly different in in-store loyalty.

Store Loyalty between Male and Female Customers

As shown in the above independent sample t-test Table 7, t= 2.072 and associated significance value = 0.039 which is less than the significance level of 0.05 means the rejection of the null hypothesis and acceptance of alternative hypothesis H3 i.e. store loyalty significantly depends on gender.

Table 7 Independent Samples T-Test for Hypothesis 3
		Levene's Test for Equality of Variances		t-test for Equality of Means
		F	Sig.	t	df	Sig. (2- tailed)	Mean Difference	Std. Error Difference	95% Confidence Interval of the Difference
									Lower	Upper
Loyalty	Equal variances assumed	0.241	0.624	2.072	285	0.039	0.17493	0.08443	0.00874	0.34111
	Equal variances not assumed			2.084	241.216	0.038	0.17493	0.08394	0.00957	0.34029

An inspection of the mean Table 8 indicates that the store loyalty of females (Mean = 3.70) was significantly higher than the males (Mean = 3.52).

Table 8 Group Statistics for Hypothesis 3
Gender		N	Mean	Std. Deviation	Std. Error Mean
Loyalty	MALE	175	3.5269	0.70476	0.05327
	FEMALE	112	3.7018	0.68655	0.06487

Store Loyalty of Married and Unmarried customers

As shown in above independent sample t-test Table 9, t= 1.770 and associated significance value = 0.078 which is more than the set significance level of 0.05 indicates the acceptance of the null hypothesis and rejection of alternative hypothesis H4 i.e. Store loyalty significantly depends on marital status. In other words, there is no significant difference in store loyalty among married and unmarried customers.

Table 9 Independent Samples Test for Hypothesis 4
		Levene's Test for Equality of Variances		t-test for Equality of Means
		F	Sig.	t	df	Sig. (2- tailed)	Mean Difference	Std. Error Difference	95% Confidence Interval of the Difference
									Lower	Upper
Loyalty	Equal variances assumed	0.313	0.576	1.770	285	0.078	0.14618	0.08258	-0.01636	0.30872
	Equal variances not assumed			1.773	284.989	0.077	0.14618	0.08243	-0.01607	0.30843

An inspection of the mean Table 10 indicates that the store loyalty of married customers (Mean = 3.67) was not significantly higher than the unmarried customers (Mean = 3.52).

Table 10 Group Statistics for Hypothesis 4
Marital		N	Mean	Std. Deviation	Std. Error Mean
Loyalty	Married	139	3.6705	0.67839	0.05754
	Unmarried	148	3.5243	0.71805	0.05902

Store Loyalty across Income Groups

As shown in above ANOVA Table 11, F= 8.05 and associated significance value = 0.000 which is lesser than the significance level of 0.05 means the rejection of the null hypothesis and acceptance of alternative hypothesis H5 i.e. Store loyalty significantly depends on income groups.

Table 11 Anova Test for Hypothesis 5
Loyalty	Sum of Squares	Df	Mean Square	F	Sig.
Between Groups	14.447	4	3.612	8.059	0.000
Within Groups	126.386	282	0.448
Total	140.833	286

An inspection of the mean Table 12, indicates that the store loyalty means among lower- income groups were lower than loyalty means of the higher income groups. While the highest income group (above Rs 1 lac) was found to be the most loyal group (Mean = 3.96), the least income group was the least loyal group (Mean = 3.26).

Table 12 Descriptives for Hypothesis 5
Loyalty
Rs (INR)	N	Mean	Std. Deviation	Std. Error	95% Confidence Interval for Mean		Minimum	Maximum
					Lower Bound	Upper Bound
Upto Rs 25000	31	3.2645	0.63956	0.11487	3.0299	3.4991	2.20	4.60
Rs25001 to Rs50000	68	3.3971	0.75823	0.09195	3.2135	3.5806	2.00	4.80
Rs 50001 to Rs 75000	78	3.5846	0.64043	0.07251	3.4402	3.7290	2.20	4.80
Rs 75001 to Rs 1 lac	48	3.6333	0.67456	0.09736	3.4375	3.8292	2.00	4.60
>Rs 1 lac	62	3.9613	0.60905	0.07735	3.8066	4.1160	2.20	4.80
Total	287	3.5951	0.70173	0.04142	3.5136	3.6767	2.00	4.80

The Post-hoc analysis with Tukey (shown in appendix Table A3) found the highest income group (above Rs 1 lac) was significantly higher than all the other groups except Rs75,001-Rs 1 lac group. The lower-income groups were not significantly different from one another in-store loyalty.

Findings and Conclusion

The finding of the study revealed that store loyalty significantly varied with the stores to which the respondents were associated. Shoppers Stop was ranked the best department store in terms of customer loyalty to the store followed by Westside, Pantaloons, Globus and lastly Lifestyle store. The Post-hoc analysis found that loyalty of respondents associated with Shoppers Stop was significantly higher than any other store in the study i.e. Westside, Pantaloons, Globus, and Lifestyle. The loyalty of respondents associated with Westside was found to be significantly higher than only one store i.e. Lifestyle, but was not significantly different from those associated with Pantaloon and Globus. The difference in-store loyalty might have occurred because these stores have their attributes and multiple studies have found store attributes to influence store choice and loyalty (Berry, 1969; Solgaard & Hansen, 2003; Bearden, 1977; Chang & Tu, 2005; Sinha & Banerjee (2004) as well as lead to the development of the store personality (Martineau, 1958).

The study also revealed that there was a significant impact of age, gender and income on customer loyalty towards the stores. The store loyalty among older respondents was higher than the younger respondents. While the oldest age group i.e. over 45 years was found to be the most loyal, the youngest group i.e. 18-25 years age group was found to be the least loyal towards the stores. Moreover, the Post-hoc analysis with Tukey found that the store loyalty of the oldest age group (45 yrs and above) was significantly higher than the loyalty of the youngest group (18-25 years age group). The first three age groups in the range of 18 to 45 years were not found to be significantly different in their store loyalty. This finding is also supported by previous studies that age has an impact on customer loyalty (Patterson, 2007; Sasikala, 2013) and older shoppers are more loyal than younger ones (East et al., 1995; Anic & Radas, 2006).

The study found that Customer loyalty significantly depends on gender. The store loyalty of female customers was significantly higher than that of male customers. This is supported by previous studies that females tend to shop more and are relatively more loyal (Oderkerken- Schroder et al., 2001; Stan, 2015). Lastly, the study revealed that Customer loyalty significantly depends on income. The store loyalty of lower-income groups was lower than that of the higher income groups. While the highest income group (above Rs 1 lac) was found to be the most loyal, the least income group was the least loyal group. The Post-hoc analysis found that the highest income group (above Rs 1 lac) was significantly higher than all the other groups except 75K- 100K groups. The lower-income groups were not significantly different from one another in- store loyalty. The above finding is also supported by previous studies that customers with more income tend to shop more (Anic & Radas, 2006; Zeithaml, 1985, East et al., 2000). As Price is the important determinant of customer satisfaction Hunneman et al. (2015) and change in satisfaction level has a significant relationship loyalty and store loyalty (Pee et al., 2018; Bhat & Singh, 2017). Overall, the findings i.e. gender, age has relationship with the store loyalty are also consistent with (Sinha et al., 2002; Vasudeva & Chawla, 2019) supports our finding that store loyalty is dependent on store-related variables as well as shopper-related variables.

From the above findings, it is quite clear that department stores must strive hard to develop strong customer loyalty for their success as the retailing business environment has become fiercely competitive and there are significant differences in-store loyalty based on customer demographics.

Managerial Implications, Limitations and Scope for Further Research

The analysis done in this study has managerial implications for the retailing firms involved in operating department store format. The findings provide a deep insight into understanding the level of customer loyalty towards the department stores and across demographics. This study could influence the marketing managers of department stores, especially Pantaloons, Globus, Lifestyle and Westside to redesign their marketing strategies to differentiate their stores from others and develop strong customer loyalty. They must pay due to attention to improve the loyalty of the younger age groups (18-35 years) as it makes most of the purchase in organized retail outlet (India Retail Report, 2013). Moreover, appropriate marketing strategies focusing on improving the loyalty of male customers and lower-income groups must be developed.

This study has a few limitations as it cannot be perfect. One limitation that study has is the non-availability of certain data which is there in most of the cases. There was not a hundred percent response rate as there were some customers who were not willing to fill the questionnaire. Few limitations were connected to financial resources and also had time constraint. The respondents across the country couldn’t be contacted and hence data couldn’t be collected from them. Response biases couldn’t be ruled out completely. Further research could be carried out more comprehensively by considering a larger sample and by covering other regions of India to have a broader understanding of customer loyalty across the department stores and demographics. More demographic variables could be added to future studies. Also, further research could be the focus on comparing customer loyalty across different retail formats.

Appendices

Appendix Table A1 Multiple Comparisons for Hypothesis 1
Dependent Variable: Loyalty Tukey HSD
(I) store	(J)store	Mean Difference (I-J)	Std. Error	Sig.	95% Confidence Interval
					Lower Bound	Upper Bound
shoppers stop	pantaloons	0.55976*	0.10861	0.000	0.2616	0.8579
	Globus	0.59578*	0.12304	0.000	0.2580	0.9336
	lifestyle	0.82972*	0.12730	0.000	0.4802	1.1792
	westside	0.43885*	0.13263	0.009	0.0747	0.8030
pantaloons	shoppers stop	-0.55976*	0.10861	0.000	-0.8579	-0.2616
	Globus	0.03601	0.11402	0.998	-0.2770	0.3491
	lifestyle	0.26996	0.11861	0.156	-0.0557	0.5956
	westside	-0.12091	0.12431	0.867	-0.4622	0.2204
globus	shoppers stop	-0.59578*	0.12304	0.000	-0.9336	-0.2580
	pantaloons	-0.03601	0.11402	0.998	-0.3491	0.2770
	lifestyle	0.23395	0.13195	0.391	-0.1283	0.5962
	westside	-0.15692	0.13710	0.783	-0.5333	0.2195
lifestyle	shoppers stop	-0.82972*	0.12730	0.000	-1.1792	-0.4802
	pantaloons	-0.26996	0.11861	0.156	-0.5956	0.0557
	Globus	-0.23395	0.13195	0.391	-0.5962	0.1283
	westside	-0.39087*	0.14093	0.046	-0.7778	-0.0039
westside	shoppers stop	-0.43885*	0.13263	0.009	-0.8030	-0.0747
	pantaloons	0.12091	0.12431	0.867	-0.2204	0.4622
	Globus	0.15692	0.13710	0.783	-0.2195	0.5333
	lifestyle	0.39087*	0.14093	0.046	0.0039	0.7778

Appendix Table A2 Multiple Comparisons for Hypothesis 2
Dependent Variable: Loyalty Tukey HSD
(I) age	(J) age	Mean Difference (I-J)	Std. Error	Sig.	95% Confidence Interval
					Lower Bound	Upper Bound
18-25yrs	26-35 yrs	-0.11268	0.09452	0.632	-0.3570	0.1316
	36-45yrs	-0.24630	0.11522	0.144	-0.5441	0.0515
	>45yrs	-0.52778*	0.17199	0.013	-0.9723	-0.0833
26-35 yrs	18-25yrs	0.11268	0.09452	0.632	-0.1316	0.3570
	36-45yrs	-0.13361	0.11558	0.655	-0.4323	0.1651
	>45yrs	-0.41509	0.17223	0.077	-0.8602	0.0300
36-45yrs	18-25yrs	0.24630	0.11522	0.144	-0.0515	0.5441
	26-35 yrs	0.13361	0.11558	0.655	-0.1651	0.4323
	>45yrs	-0.28148	0.18440	0.423	-0.7580	0.1951
>45yrs	18-25yrs	0.52778*	0.17199	0.013	0.0833	0.9723
	26-35 yrs	0.41509	0.17223	0.077	-0.0300	0.8602
	36-45yrs	0.28148	0.18440	0.423	-0.1951	0.7580

Appendix Table A3 Multiple Comparisons for Hypothesis 5
Dependent Variable: Loyalty Tukey HSD
(I) income (J) income		Mean Difference (I-J)	Std. Error	Sig.	95%           Confidence Interval
					Lower Bound	Upper Bound
Up to Rs 25,000	Rs25,001 to Rs50,000	-0.13254	0.14508	0.892	-0.5309	0.2658
	Rs 50,001 to Rs 75,000	-0.32010	0.14214	0.164	-0.7103	0.0701
	Rs 75,001 to Rs 1 lac	-0.36882	0.15425	0.121	-0.7923	0.0547
	>Rs 1 lac	-0.69677*	0.14726	0.000	-1.1011	-0.2925
Rs25,001               to Rs50,000	Up       to     Rs 25,000	0.13254	0.14508	0.892	-0.2658	0.5309
	Rs 50,001 to Rs 75,000	-0.18756	0.11107	0.443	-0.4925	0.1174
	Rs 75,001 to Rs 1 lac	-0.23627	0.12621	0.335	-0.5828	0.1102
	>Rs 1 lac	-0.56423*	0.11756	0.000	-0.8870	-0.2415
Rs 50,001 to Rs 75,000	Up       to     Rs 25,000	0.32010	0.14214	0.164	-0.0701	0.7103
	Rs25,001 to Rs50,000	0.18756	0.11107	0.443	-0.1174	0.4925
	Rs 75,001 to Rs 1 lac	-0.04872	0.12281	0.995	-0.3859	0.2885
	>Rs 1 lac	-0.37667*	0.11391	0.009	-0.6894	-0.0639
Rs 75,001 to Rs 1 lac	Up       to     Rs 25,000	0.36882	0.15425	0.121	-0.0547	0.7923
	Rs25,001 to Rs50,000	0.23627	0.12621	0.335	-0.1102	0.5828
	Rs 50,001 to Rs 75,000	0.04872	0.12281	0.995	-0.2885	0.3859
	>Rs 1 lac	-0.32796	0.12871	0.083	-0.6813	0.0254
>Rs 1 lac	Up       to     Rs 25,000	0.69677*	0.14726	0.000	0.2925	1.1011
	Rs25,001 to Rs50,000	0.56423*	0.11756	0.000	0.2415	0.8870
	Rs 50,001 to Rs 75,000	0.37667*	0.11391	0.009	0.0639	0.6894
	Rs 75,001 to Rs 1 lac	0.32796	0.12871	0.083	-0.0254	0.6813

Author Details

Mujibur Rahman, School of Business, Galgotias University, Email Id: rahmandel2@gmail.com

Md. Chand Rashid, Associate Professor, School of Business, Galgotias University, Plot No.2, Sector 17-A, Yamuna Expressway, Gautam Buddh Nagar, Greater Noida, Uttar Pradesh 201310, INDIA, Email Id: mcrashidkhan@gmail.com

Jitender Kumar*, Assistant Professor, School of Business Studies, Sharda University, Plot No. 32-34, Greater Noida and Research scholar, Indian Institute of Management, Rohtak. Email Id: jitender.kumar1@sharda.ac.in

Ashish Gupta*, Corresponding Author, Assistant Professor- Marketing Area, Indian Institute of Foreign Trade, New Delhi, IIFT Bhawan, B-21, Qutab Institutional Area, New Delhi 110 016, INDIA, Email Id: ashishgupta@iift.edu

Corresponding Author (*) Ashish Gupta- Assistant Professor, Indian Institute of Foreign Trade, New Delhi, India, Email: ashishgupta@iift.edu & Jitender Kumar*, Assistant Professor, School of Business Studies, Sharda University, Plot No. 32-34, Greater Noida and Research scholar, Indian Institute of Management, Rohtak Email Id: jitender.kumar1@sharda.ac.in

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