Pacific B usiness R eview I nternational

A Refereed Monthly International Journal of Management Indexed With THOMSON REUTERS(ESCI)
ISSN: 0974-438X
Imapct factor (SJIF): 6.56
RNI No.:RAJENG/2016/70346
Postal Reg. No.: RJ/UD/29-136/2017-2019
Editorial Board

Prof. Mahima Birla
(Editor in Chief)

Dr. Khushbu Agarwal

Ms. Asha Galundia
(Circulation Manager)

Editorial Team

Mr. Ramesh Modi

A Refereed Monthly International Journal of Management

Exploring the Influence of Trust on E-Tail Customer Loyalty


Dr. Jogi Mathew

Associate Professor

Department of Management studies

Christ University, Hosur Road, Banagalore, India

Contact No:- +91 9845133217



Online retail business is prospective business format for the next generation having high growth potential currently. The growth potential of the online retail business in India has attracted leading international players like Amazon, eBay etc and their entry would increase competition in this business segment. A loyal customer is steady with the company particularly in making regular purchases and has a good perception towards the company. A loyal customer will recommend other prospective purchasers to the e-tail firm through word of mouth. The analysis result apparent from the data concluded that Customer loyalty is directly influenced by Trust. Trust takes in to consideration the previous experience and will ultimately lead to customer loyalty. When trust goes beyond a certain level it will become commitment. Customer satisfaction along with trust is an indicator of customer loyalty. For further research, a qualitative analysis has good scope for research to get e-tail customers feedback using in-depth analysis.

Keywords: Customer satisfaction, Customer trust, Customer loyalty, E-tailing, Customer commitment.

Introduction to e-tailing

Retail is one of the most dynamic industries in the world today. E-commerce is the promising segment which is expected to be the next thrust area for retail expansion in India. These days’ retailers explicitly offer their customers an opportunity to shop using multiple channels by offering a variety including physical stores, catalogue stores, call centres, and e-commerce sites (Rangaswamy & van Bruggen, 2005). Online shopping is estimated as the fastest growing area involving internet usage (Forsythe & Shi, 2003), and has recorded phenomenal growth rates, in comparison to the past decade, and is continuing to rise, and the accomplishments have exceeded those achieved utilizing traditional channels. According to Turban (2006), e-tailing is when retailing is conducted online, utilizing the internet. Wang (2002) has provided an exhaustive definition of e-tailing by explaining it as the selling of goods and services to the consumer market using the internet.

The E-Tail Revolution in India

Indian Railway Catering and Tourism Corporation, a division of the Indian Railways, was innovated the application of e-commerce in India. The success story of online ticket booking was on a large scale motivated other business players to try out this technique for expanding their e-businesses, to increase sales volumes and thereby to attain high profits. Though online shopping is present since 2000, it has attained popularity only with the advent of deep discount model by Flipkart in 2007. In continuation, other portals like Amazon, eBay, Jabong, etc. are actively targeting Indian consumer for the expanding their business.

Ambareesh Murty, country manager of eBay India, concurs, ‘Online marketplaces help create trade between metros and Tier II and III cities by bridging the demand and supply gap.’ The online retail industry was booming very strongly in the last two decades. With the probable expansion in the e-commerce industry, online Retail is anticipated to reach USD 70 billion by 2020 from USD 3 Billion in 2014 (IBEF, 2016). As per the analysis results of Boston Consulting Group (BCG, 2015) in days to come internet retailing will pose a challenge to the brick and mortar shops in few years. The expected growth of e-tailing market is to spread out to over US$ 100 billion by 2020 from the existing figures of US$ 3.5 billion in 2014. The boom of e-commerce industry in the country, the internet retailing is geared up to expand four times and touch USD 14.5 billion by 2018.

Drivers of E-Tail Growth in India

It’s interesting to notice that the initial responses of many established retailer players were slow, or even timid, but years later, the Internet is now a remarkable part in their competitive strength (Weltevreden & Boschma, 2008). As Keen, Wetzels, de Ruyter, and Feinberg, (2004) explained ‘fears that the Internet will take over the (traditional) retail, at least at this point in time, overblown and exaggerated’. The acceptable view is that an efficient and well formed internet channel aids in the performance of retailers, and thereby it helps to protect their position on the high street (Wolk & Skiera, 2009). According to Kedar Gavane director of comScore ‘The online channel is playing an increasingly important role in connecting retailers with potential customers in India. The rapid growth of online coupon sites suggests that consumers in India are looking for deals, highlighting the need for online retailers to adopt effective marketing and pricing strategies.’

As per the information of Google, India has more than 100 million internet users in the country and at least half of this figure could be a strong prospect for internet retailing. In 2012, India had more than 900 million mobile subscriptions and 380 million mobile phone users. By the year 2020, mobile phone users are expected to increase to 600 million (Technopak, 2013). The typical Internet consumer of the twentieth century is young, professional, and well off with high disposable income and higher education (Palumbo and Herbig, 1998). One of the interesting facts is that 54% of the Indians are below 25years. On-line retailing is currently providing retailers with ample source of individualized customer information, that allows them to embark on effective one-to-one marketing (Frow & Payne, 2009) which has a real contribution to improved organizational performance (Warrington, Gangstad, Feinberg, & de Ruyter, 2007).

Zeithaml (2002) was of the opinion that the success of e-tailing relies on the efficient web site design, facilitating effective shopping and prompt delivery. There has been much proof to suggest that the Internet mostly supports the larger retailer as it facilitates them to progress their ‘business efficiencies’, and in the process, offer even lower prices (Burt & Sparks, 2003). Internet market places even have the capacity to reduce search costs for price and product related information (Bhatt & Emdad 2001). Cash-on–delivery is the most favourite payment mode with more than 30 percent of buyers choosing for it in India (IBEF, 2016).

Need for the study

The study takes in to account the evolution of the Indian customer who transformed from the weekly hats, mela’s and mandi’s to the trendy and modern e-tailing. The modern customers look out is not just on the offerings of the online retailer but even the intangible factors which gives him an experience. It is interesting realization that the increase in customer satisfaction essentially do not lead to customer loyalty. The rationale behind the study is to find out the variables accountable for making a supermarket customer loyal and which in the process also retains them. The currently available studies are based on conceptual understanding and don’t have an empirical backup. Added to this the number of empirical studies in the Indian context are very less connecting the variables of online retailer customer loyalty this is the research gap identified. On account of these, this study is expected to contribute literature by filling the gap of information in the Indian retail market and specifically about the Bangalore online retailer.

Conceptual framework

Customer loyalty is defined as ‘a deeply held commitment to re-buy or re-patronize a preferred product or service consistently in the future, despite situational influences and marketing efforts having the potential to cause switching behaviour’ (Oliver, 1997, p. 392). The association between customer loyalty and company’s profitability had been determined (Reichheld, &Teal, 1996). A loyal Customer will help the e-tail to bring new customers through word of mouth with out any extra cost. Customer loyalty was an incident that marketers depict to their customers, preferably about value creation (Kumar & Shah, 2004). Satisfaction, trust, commitment and retail employee’s co-operation were strong influencers of customer loyalty (Ranaweera & Prubho, 2003).

Review of literature

Customer Loyalty

The organizations dealing with e-tail have given undue importance to customer loyalty and even policies to retain the customer. ‘Customer loyalty can be a double edged sword. In general, it was believed that it is five to 10 times more expensive to acquire a new customer than obtain repeat business from an existing customer’ (Kumar & Shah, 2004). As a result of this taking care of a loyal customer has not only become a key concern but even an inevitable action to have a long term organizational success. ‘It is commonly known that there is a positive relationship between customer loyalty and profitability’ (Bowen & Chen, 2001). Rajan (2009) observes that ‘loyal customers cost less to serve, pay more than other customers and attract more customers through word of mouth’. True customer loyalty occurs when the customer ultimately becomes a brand ambassador for the organization, without any other extra benefits.

The Impact of Customer Commitment on Customer Loyalty

Commitment was an after effect of behavioral, attitudinal and emotional impact on consumers (Du Plessis, 2010). Morgan and Hunt (1994) defined commitment as ‘an ongoing relationship with another that is as important as to warrant maximum efforts at maintaining it’. Whenever commitment is more, the customer is ready to overcome barriers on the way and these results in continued patronage (Dick & Basu, 1994). Articles authenticate that trust by the side of commitment was a strong antecedent of loyalty (Floh & Treiblmaier, 2006; Ball, Coelho, & Macha´s, 2004). Having these inputs the following hypotheses had been constructed:

H1: Customer commitment has a positive relationship with customer loyalty.

The Impact of Customer Trust on Customer Commitment

Mayer et al. (1995) define trust as ‘the willingness of a party to be vulnerable to the actions of another party based on the expectation that the other will perform a particular action important to the trust or, irrespective of the ability to monitor or control that other party’. Trust was optimistically connected to customer commitment (Eakuru & Mat, 2008). Several studies explained customer trust which significantly was related to customer commitment statistically (Lancastre & Lages, 2006). Trust was explained as an important indicator of commitment (Coote, Forrest, & Tam, 2003). Numerous studies report remarkable relationships connecting trust and commitment (Palmatier, Dant, & Grewal, 2007; Lohtia, Bello, Yamada, & Gilliland, 2005). Therefore, it is hypothesized that:

H2: Customer trust has a positive relationship with customer commitment.

The Impact of Customer Trust on Customer Loyalty

The reputation of trust and its effect in clearing up loyalty was complemented by authors (Chaudhuri & Holbrook, 2001; Sirdeshmukh, Singh, & Sabol, 2002). The relationship from customer trust to customer loyalty is a direct and effective one. Many researches have suggested that customers’ trust is a significant role in building long-term relationship and achieving customer loyalty (Chu, 2009). Corbitt, Thanasankit, and Yi (2003) had strongly emphasized a strong positive influence of trust on customer loyalty. The inferences will aid in generating the hypothesis:

H3: Customer trust has a positive relationship with customer loyalty.

The Impact of Consumer Satisfaction on Customer Trust

The customer satisfaction was indirectly related through customer trust to customer loyalty (Songsom & Trichun, 2012). Here the tasks of the firms were to reduce the gap and thereby build the trust of the customers. In this process the customers will be loyal to the offerings as well as the e-tail firm. Previous research studies had shown that constructs of trust and satisfaction had a strong influence and were positively correlated (Yoon, 2002). According to Danesh, Nasab, and Ling (2012) customer satisfaction had a straight and valid involvement with customer trust. Customer satisfaction was a key antecedent of trust acquired by the organization with an intention of providing service (Kennedy, Ferrell, & LeClair, 2001). On account of the facts given the following hypothesis is formed:

H4: Customer satisfaction has a positive influence with customer trust.

Model of the study

Figure 1. The proposed conceptual framework

The proposed model is developed using the inputs from the theoretical concepts. The detailed review of literature was giving insights on each constructs which are a part of this proposed conceptual model. There is a well knit relationship being established from the literature which connects all the constructs which are a part of this model. The proposed model (Figure 1) displays the factors which will lead to customer loyalty.

Objectives of the study

To empirically validate a model linking customer satisfaction, customer trust, customer commitment and customer loyalty. The major intend of the study is to ascertain the influence of customer trust, customer commitment and customer satisfaction on customer loyalty.

Sampling procedure

Bangalore population is 9,588,910 according to the Indian 2011 Census. In it the urban population is 8,719,939 and from the population only people with the age of 18 and above years are only coming under the sample. The research study has used convenience sampling for data collection. According to Pruzek and Boomsma, (1984) sample size of 400 was the requirement. The study was conducted in a period of six months (2017 December to 2018 May). The size of response was 500 customers in Bangalore.

Questionnaire design

The reason for using an existing questionnaire is that it will be more reliable as it is used more and already validated and accepted. The research tool is a structured questionnaire and the data collection is a combination of survey and personal interview. The questionnaire which is adopted is based on a 5 point rating scale ( Likert scale) which ranges from strongly disagree to strongly agree. To measure Customer satisfaction and Customer loyalty the items were adopted from (Reddy, Reddy, & Azeem, 2011) for Customer trust (Li, 2011) and for Customer commitment. Table- 1 shows the Profile of respondent’s.

Table 1. Profile of respondents

















Self employed



Household work






Educational Status

10 th std






Under graduate



Post Graduate



Annual Income

Not applicable



< 1 lakh



1 to 2 lakhs



3 to 4 lakhs



4 to 5 lakhs



Reliability and Validity

The overall reliability Cronbach’s alpha coefficient is 0.924 (a value which is adequately above 0.7). The item wise Cronbach Alpha for reliability for each construct is (Customer satisfaction 0.879, Customer trust 0.770, Customer commitment 0.851 and Customer loyalty 0.820) shown in Table-2.

Table 2. Reliability and Validity Constructs of the Measurement Model



Standardized Loadings

Cronbach Alpha


Customer satisfaction

CS1: I truly enjoyed by coming to this e-tail website

CS2: I am satisfied with this e-tail website

CS3: I think the choice to come to this e-tail website was a good one






Customer trust

CT1: e-tail website gives me a feeling of confidence

CT2: I have faith in my e-tail website

CT3: e-tail website enjoys my confidence






Customer commitment

CC1: If products are cheaper at another e-tail website than at my e-tail website, then I go to the other e-tail website (r)

CC2: If my e-tail website is not nearly, then I go to the other e-tail website (r)

CC3: If I intend to go to e-tail website, it is easy to make me change my mind. so that I in fact go to another e-tail website (r)






Customer loyalty

CL1: I recommend this e-tail website to my friends and family

CL2: I would like to buy from this e-tail website only

CL3: I would like to visit this e-tail website again and again






The results shows the composite reliability of all the construct are greater than 0.70. The findings reveal that the constructs are all reliable. Convergent validity assessment done bases of two criteria: the factor loadings of the indicators and the average variance extracted (AVE) for each factor (Fornell & Larcker, 1981). AVE value for each construct should be greater than 0.50 (Hair, Ringle, & Sarstedt, 2011). Table 2 shows AVE values more than 0.5(Customer satisfaction 0.720, Customer trust 0.602, Customer commitment 0.713 and Customer loyalty 0.738).

Assessing Overall Structural Model Fitness

Based on factor loading (regression coefficients) and estimate of reliability of each item within the factor and observing the values such of CMIN, RMSEA, GFI and the final as part of CFA, the final observed item under each of the latent (unobserved) construct or factor is provided in Table -3.

Table 3. Goodness-of-fit Indices for Structural Model

Fit Indices

Accepted Value

Model Value

Absolute Fit Measures

Chi-square/df (χ2/df)

< 3


GFI (Goodness of Fit Index)

> 0.9


RMSEA (Root Mean Square Error of Approximation)

< 0.10


Incremental Fit Measures

AGFI (Adjusted Goodness of Fit Index)

> 0.80


NFI (Normed Fit Index)

> 0.90


CFI (Comparative Fit Index)

> 0.90


IFI (Incremental Fit Index)

> 0.90


RFI (Relative Fit Index)

> 0.90


Parsimony Fit Measures

PCFI (Parsimony Comparative of Fit Index)

> 0.50


PNFI (Parsimony Normed Fit Index)

> 0.50


With respect to RMSEA, values less than 0.05 indicate good fit and values as high as 0.10 represent reasonable errors of approximation in the population. In our hypothesized model (Table 3) the RMSEA is found to be 0.037 which is less than 0.10 indicating the model to be in reasonably good fit.

Structural Model Hypotheses Testing

The standardized regression weights (the beta coefficient) which is a part of path regression analysis outcomes are depicted in Table 4. Single headed arrows or paths are used to identify casual relationships present in the model, with the variable at the tail of the arrow being the cause of the variable at that point. These symbolize the regression coefficients. This regression result is analyzed alike the ordinary linear regression result.

Table 4. Standardised regression weights for customer loyalty


Standardized regression coefficients β





0.629 (β1)





0.781 (β2)





0.735 (β3)


7. 592



0.837 (β4)




Accordingly, the standard loadings (also referred as regression coefficients) are given along with the Z-statistics and p-values in Table 4. The same results obtained through regression equation are put in the form of a pictorial representation in Figure 2 for better understanding of those hypotheses whether having statistical significance (p<0.05).

Figure 2. Pictorial Representation of resultant model with statistical significance hypotheses

It is observed that there is a significant (Table 4 with a Z – value of 6.271and p-value less than 0.05) influence of commitment (COMM) on customer loyalty (LOYAL). Thus, H1 is accepted that customer commitment has a positive relationship with customer loyalty. The direct path regression coefficient (β2) between trust (TRST) and commitment (COMM) is 0.781. It is seen that there is a significant (Table 4 with a Z – value of 8.274 and p-value less than 0.05) influence of trust (TRST) on commitment (COMM). Thus, H2 is accepted that customer trust has a positive relationship with customer commitment.

It is observed that there is a significant (Table 4 with a Z – value of 7.592 and p-value less than 0.05) influence of Trust (TRST) on Customer Loyalty (LOYAL). Similarly, the direct path regression coefficient between trust (TRST) and customer loyalty (LOYAL) is 0.735 (β3). Thus, H 3 is accepted that customer trust has a positive relationship with customer loyalty. Building a strong customer trust would definitely ensure higher customer loyalty. The regression coefficient is 0.735 (β3) indicate that an additional one unit effort of having better customer trust, one would expect an increase of 0.735 units in customer loyalty with other things fixed or constant.

The direct path regression coefficient (β4) between customer satisfaction (CUSTSAT) and trust (TRST) is 0.837 and between trust (TRST) and loyalty (LOYAL) is 0.735 (β3). It is seen that there is a significant (Table 4 with a Z – value of 9.658 and p-value less than 0.05) influence of customer satisfaction (CUSTSAT) on Trust (TRST). Thus, we accept H 4 Customer satisfaction has a positive influence with customer trust.


According to the findings of the research study customer satisfaction has indirect relationship with loyalty, satisfaction alone is not a strong indicator of customer loyalty. Satisfaction is necessary but is not the construct adequate for producing customer loyalty (McIlroy & Barnett, 2000; Sivadas & Baker-Prewitt, 2000; Dick & Basu, 1994). A loyal customer will recommend other persons to utilize e-tailing as a purchase option. This recommendation happens in the form of positive word of mouth. The positive word of mouth is of great importance in continuing the customer subscription and contributing to profits. It is seen that there is a significant influence of customer satisfaction on Trust. Trust is dependent on previous experience and it will ultimately lead to customer loyalty.

The more of trust towards the e-tail in due course leads to customer loyalty intentions. When trust goes beyond a certain level it will become commitment. Lots of research works have proven about the existence of trust and commitment relationship. McIlroy and Barnett, (2000) says that ‘in a business context loyalty has come to describe a customer’s commitment to do business with a particular organization, purchasing their goods and services repeatedly, and recommending the services and products to friends and associates’. The analysis result shows that commitment is having a positive effect on loyalty. Customer satisfaction is not a major influencer of customer loyalty whereas trust is placed as a central coordinator of customer loyalty (Liao, & Wu, 2009). Considering any customer, loyalty is about showing positive attitude and thereby suitable behaviour which is connected to the extent of re-purchasing loyalty to any brand in the later days to come (Chu, 2009).


Valdani, (2009) clarified that organizations are important due to the presence of the consumer who has to be taken care. Online shopping provides fast, convenient, money saving and remarkable shopping experience. Changes in the life style of the customer will lead to difference in preferences. The research results indicate that mere customer satisfaction would not significantly influence or retain the loyalty of customers in the long run. The research is giving a warning as well as highlighting the advantages of creating trust towards e-tail which will lead to customer loyalty. The research result shows that customer satisfaction has indirect effects through trust or commitment on customer Loyalty.

This study gives inputs to the management about the customer’s satisfaction levels related to experience with the e-tail. Satisfied customer need not essentially be loyal or be retained. The study is giving a warning as well as highlighting the advantages of creating trust towards e-tail which will lead to customer loyalty. Suggestions for further research are a qualitative analysis has good scope in the research in order to get e-tail customers feedback as result of an in-depth analysis. This could give a detailed and in- depth suggestions regarding the expectations and aspirations of the customers in various dimensions.


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