End-user Acceptance of Online Shopping Sites in India

Bolar K; Shaw B

End-user Acceptance of Online Shopping Sites in India

Bolar K^1* and Shaw B²

T.A.Pai Management Institute, Manipal, Karnataka, India
IBS Hyderabad, IFHE Deemed University, India

Corresponding Author: Bolar K, T.A.Pai Management Institute, Manipal, Karnataka, India, Tel: 917893516364; Email: kartikeya.bolar@tapmi.edu.in

Received: June 10, 2015 Accepted: July 09, 2015 Published: July 11, 2015

Citation:Bolar K, Shaw B (2015) End-user Acceptance of Online Shopping Sites in India. J Internet Bank Commer 20:102.

Copyright: © 2015 Bolar K, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

Online shopping sites have recently gained momentum in India. Since the ecommerce industry is in infancy state, customer (end user) satisfaction with the online shopping is the prime concern because decreasing customer satisfaction leads to negative electronic word of mouth (eWOM) which is very severe for the business. Through a dataset gathered from 127 online shopping customers in with respect to online shopping sites in India, this study investigates the role of website quality, information integrity and perceived behavioral control on customers’ online experience, which in turn influences usage and satisfaction. One of the key results is that the online customer experience has a larger influence on satisfaction rather than usage.

Keywords

Online shopping site; Online customer experience; Research study; India

INTRODUCTION

The emergence of Internet has unexpectedly created the opportunities in various fields. Internet along with technology has paved a remarkable pathway in the world of electronic devices like computers, mobile and other related gadgets, one of them being e-commerce.

Online Shopping site uses Internet as a remote delivery channel for shopping services for seeking information and conducting transactions. Essentially it is an electronic customer interface. It specifically provides a unique combination of real-time processing and the convenience of location and time. But there are issues of concern to the customer like the loss of personal attention and security of information. Online Shopping sites can operate at different cumulative functional levels namely Informational, Communicative and Transactional. At the informational level, the site provides information about the different products and services. At the communication level there is interaction limited to email, static enquiries and information updates. At transactional level, selection of the product, making an order and payment transactions can be conducted. However value proposition to the customer at the transactional level of online shopping site is the highest. At the transactional level, there are various functionalities to be supported and other concerns associated with the functionalities emerge. For example, to provide mechanism of bill payment, coordination with the vendors’ information system or the bank has to be established.

According to the web source of Gartner Inc [1], the India ecommerce market will reach $6 billion in 2015 a 70 percent increase over 2014 revenue of $3.5 billion. According to a report of PwC India [2], E-commerce is relatively a novel concept. According to the report, e-commerce has taken significant strides in US and China however the industry in India is, still at its infancy. This is justified by the fact that the big players in the Indian E-commerce industry like Flipkart, Snap Deal and Amazon have been launched in the last few years (i.e Flipkart in 2007, Snap Deal in 2010 and Amazon in 2012). On the other hand, there is a trend of physical shopping malls growing in size as well as numbers in India according to a web report of Hindu Business line [3]. Under such circumstances, when the consumer has a choice of choosing the place from where shopping can be done, consumer satisfaction with the online shopping in India is the prime concern because decreasing customer satisfaction leads to negative electronic word of mouth (eWOM) which is very severe for the business.

Customer satisfaction in the context is the culmination of online customer experiences. Online customer experience is a perception that is left behind in the customer’s mind, formed by the amalgamation of the many pieces of sensory information taken in during the encounter with the online shopping sites. The positive and negative perceptions will mainly depend on the quality of the website and the information along with the feeling of control over the operations done through the website. The positive and negative perceptions can be understood in terms of the benefits and the costs involved while using the shopping sites. These perceptions are conceptualized as usefulness and ease of use. Customers tend to use the site frequently if a positive perception is created while shopping online. Thus the study of the determinants and the consequences of online customer experience find its relevance in academic as well in managerial perspective.

The objective of this study is to examine the role of quality of website and information, perceived control on customer experience which in turn influences the usage and satisfaction of online shopping sites.

In what follows, the review of literature on online customer experience is provided and theoretical foundations of the research model are developed. Then hypotheses are presented and tested. The research results and implications are discussed.

Literature Review

Online customer experience (OCE)

The term “Experience” in most of the studies refer to the number of years of exposure [4,5]. However, here OCE is referred to the subjective and qualitative measure of experience when exposed to an environment. OCE plays a significant role in converting a prospective customer to loyal customers. According to Rose et al. [6] OCE has been defined as “the takeaway impression formed by the people’s encounter with products and services and businesses”. According to the authors, the take away impression is a collection of perceptions which are a result of summing up sensory information during online interaction with the interface. According to Technology Acceptance Model (TAM) proposed by Davis [7], these perceptions are Perceived Usefulness (PU) and Perceived Ease of Use (PEOU). According to the author,PU is the degree of a person’s belief that using a particular technology improves their performance in the job, whereas PEOU being the degree of a person’s belief that a specific system would be free of effort. In the context of online shopping, the perception of customers build during the interaction plays an important role in the acceptance of online interface or shopping site.

The manifestation of OCE in terms of PU and PEOU can be justified as follows:

a. In the Cost Benefit Paradigm, PEOU can be considered as the cost and PU can be considered as the benefit. In the context of online interfaces, PEOU is the takeaway impression formed by the people when they encounter a online interface. If they encounter any problem, PEOU will be less and there is a possibility to have a higher cost over the benefit thereby an indication of negative experience.

b. Taking cue from motivation and hygiene theory proposed by Herzberg [8] for OCE, PEOU sets the hygiene condition wherein it sets the minimum requirement for having a positive experience. This also means that even if PEOU is witnessed, there is an indicate towards positive experience but not necessarily become a positive experience. PU on the other hand, sets the motivation condition wherein the benefit in terms of improved productivity, convenience sets the stage of having positive OCE. This also means that PU could be the manifestation of sufficient condition of positive OCE.

Information integrity and website quality

According to Bolar, the Website features and Information Integrity were considered as the determinants of the PU and PEOU. According to the author, these two were considered as the important aspects of the technology interface through which the customer develops perceptions about the Interface. Information Integrity in particular suggests that the integrity of the information is maintained if the information is accurate, complete, consistent, timely and precise. There are other studies that also validated the positive relationship between the system quality, output quality and the perceptions about the system or technology [9-12].

Perceived behavioral control

According to Venkatesh and Bala [11], self-efficacy is the belief of an individual concerning the ability to use a system or technology, whereas facilitating condition refers to the individuals’ belief related to the convenience of organizational resources and the support structure to assist the use of a system. There are studies that validate that self-efficacy and facilitating conditions are positive determinants of PEOU [11,13]. Both self efficacy and facilitating conditions are the two different aspects of perceived behavioral control. On the whole, perceived behavioral control is the construct reflecting the control over the object as perceived by the user of the object either due to inherent confidence in using it or having an external resource or support for using the same.

Usage and user satisfaction

There are many studies, which have validated the basic TAM, where in the PU and PEOU are considered as motivations determining the usage of technology [9,11]. According to Rose et al. [6], user satisfaction is different from customer experience. According to the authors, user satisfaction is the evaluation of accumulated customer experience. This suggests that the OCE is the positive determinant of user satisfaction.

Research Objectives

The objectives of the proposed research are as follows

1. To study the influence of quality of online shopping site, perceived behavioral control on OCE.

2. To study the influence of OCE on usage and user satisfaction.

THeoretical framework and development of hypothesis

To achieve these objectives, a research model was developed based on the conceptual framework. The conceptual framework builds on the theory of planned behavior (TPB). TPB is an extension of the Theory of Reasoned Action (TRA). TPB deals with those situations where the user does not have complete volitional control over the behavior. According to Ajzen [14], the extension to TRA is done by including Perceived Behavioral Control (PBC) as an antecedent to the Behavioral response which consists of beliefs related to possession of requisite resources and opportunities to carry out a behavior. However, in various studies on TAM which is incidentally based on TRA, it has been validated that PBC be treated as an antecedent to PEOU instead of behavioral response [11,13].

Noting the requisite changes required in the application of TPB, the research model is developed which relates user perceptions of online shopping site characteristics, PBC, OCE, usage and user satisfaction as shown in Figure 1.

Research hypothesis

According to Bolar [15], a positive perception is created in the mind of customers when the information provided on the website is accurate, current and well organized as per customer requirement. The customer should be able to get all the information from the website. This argument also finds support from various studies [11,13,16,17].

This forms the basis for formulating the following hypotheses

H1: Website quality positively influence perceived usefulness

H2: Website quality positively influence perceived ease of use

H3: Information integrity positively influence perceived usefulness

H4: Information integrity positively influence perceived ease of use

According to Venkatesh and Bala [11], a user gets motivation to interact with technology when the user is confident enough to use the technology as well as the resources provided by the website is helpful in performing their task. The utility of a system enhances if the person is able to use it effortlessly thus having a positive influence on perceived usefulness and perceived ease of use.

This forms the basis for formulating the following hypothesis:

H5: Perceived behavioral control positively influence perceived usefulness.

H6: Perceived behavioral control positively influence perceived ease of use.

According to Davis [9], the usage of the interface is influenced by user motivations of the technology. According to Rose et al. [6], a user is satisfied only when they can perceive the benefits and the usefulness of the technology. The usefulness with investing less time and free from effort adds to customer satisfaction.

This forms the basis for formulating the following hypothesis:

H7: Perceived usefulness positively influence usage.

H8: Perceived usefulness positively influence satisfaction.

H9: Perceived ease of use positively influence usage.

H10: Perceived ease of use positively influence satisfaction.

Data collection and methodology

The study was conducted in the context of Online Shopping sites in India. Online Shopping sites could be considered as one of the rising delivery channels for seeking information and conducting transactions. The survey research approach was undertaken. The Online shoppers constituted the sampling unit for the survey.

A structured questionnaire was designed for the purpose of collecting information and was administered online. Most of the items on the questionnaire were adapted from past literature. . The items of PU and PEOU were adapted from Davis [9]. The items for information integrity, website quality, self-efficacy facilitating condition were adapted from Bolar, Loiacono et al., Liao et al., Flowerday and Solmes, Palmer [15-19]. The items for customer satisfaction and usage were adapted from Venkatesh and Bala [11].

The online questionnaire was developed using Google Docs Form Application Template. The advantage of using Google Docs Form Application Template is that the responses are immediately stored along with a time stamp in a spreadsheet database which can be only accessed by the researcher who developed the questionnaire.

Initially, the link to the questionnaire was emailed to a mailing list of known people. They were also requested to forward the mail to the people whom they know who are using online shopping sites. Again the link to the questionnaire was e-mailed to mailing list provided by known people to whom link was sent initially giving their reference. This type of sampling is called snowball sampling which is often used in case of hidden populations where the sampling frame does not exist and there is a concern for individual privacy [20].

The content of the mail sent consisted of

1. A brief introduction of the researcher.

2. The description of the purpose of the research.

3. A request to submit responses at the link of online questionnaire.

A mailing list was developed from various forwards of emails sent to the researcher which often contains the list of email addresses of people unknown to the researcher. The content of the email had background information about the researcher, purpose of the mail so that the email was not treated as any forward or any spam mail.

Besides sending e-mails, the link of the questionnaire was also placed in various social networking sites like Facebook and Linkedin. Responses were also received offline on the paper-based questionnaire from known Internet users.

Information was received from 150 respondents over a period of two months. The responses were downloaded as an Excel spreadsheet document. The standard scores of all the study variables were calculated for all the 150 respondents. The respondents were filtered to 127 respondents based on standard scores so as to achieve the skewness and kurtosis of each variable within the range of ±2. This was done to remove outliers and achieve distribution close to normal. The profile of the 127 respondents is shown in Table 1.

From the profile data, it can be inferred that the typical respondent of this survey is a male youth with monthly family income above Rs. 30000 and with more than 2 years of Internet banking experience. The respondent had to provide their responses with respect to only one online shopping site which they use often. The breakup of the respondents with respect to the online shopping site for which they responded is shown in Table 2.

The breakup with respect to the Online Shopping sites is justified in the sense that Amazon, Flipkart and Snapdeal are the three major players in the Indian e-commerce sector.

The questionnaire was developed incorporating the descriptions about the constructs. The questionnaire was pretested at two stages. During the first stage, a pilot study was conducted with a group of doctoral scholars of a university with whom the researcher could interact and discuss the difficulties in answering and overall feedback on the questionnaire design. During the second stage, a quick sort procedure was carried out with two academicians and two industry experts to get consensus on the questions developed and the constructs to which they belong. Ambiguous questions were either removed or reworded. The vagueness of some relevant questions was reduced by supplementing it with additional information and instances.

The format and sequences of items in the questionnaire are suitably modified to reduce the common method bias in responses. Common method bias is systematic measurement error which can happen if the responses are not exactly the true responses of the respondents but due to the way the questionnaire items are sequenced. As discussed in Podsakoff et al. the problems of social desirability implicit theory and illusory correlations can be sources of common method bias. In this study, the questionnaire layout was developed based on the suggestions given by Podsakoff et al. [21] such as creating psychological separation between the predictor and the criterion variables. For instance, the questionnaire was divided into four sections namely A, B, C and D. Each section starts with explanation of the section and instructions to the respondents. The respondent cannot answer the questions of a particular section unless all the questions of the preceding section have received responses. However the respondent can go back to an earlier section and make changes in the earlier recorded responses. The layout of the questionnaire thus creates a psychological separation between the items of the predictor and criterion constructs and keeps the focus of the respondent on limited number of questions of a particular theme. This reduces the formation of implicit theory and illusory correlations. Apart from reducing common method bias, the Harmon’s single factor test was used to assess common method bias as suggested in Malhotra et al. [22]. According to Harmon’s single factor test, when a factor analysis is carried out using the questionnaire items, if a single factor emerges from unrotated factor solution then there is a likelihood of common method bias.

Exploratory Factor Analysis (EFA) was used in this research study to identify and validate the constructs. Factor scores were used in multiple regression analysis to test the Hypotheses stated earlier.

Data analysis and interpretation

As indicated in the research model, Information Integrity (II), Website Quality (WQ) and Perceived Behavioral Control (PBC) are proposed as the determinants of the Online Customer Experience. Similarly the Online Customer experience is proposed as the determinant of customer satisfaction and usage. Hence Information Integrity, Website Quality and Perceived Behavioral Control are considered to be at the same level. Similarly the Online Customer Experience which is manifested as Perceived Usefulness and Perceived Ease of Use is considered at another level. Customer satisfaction and usage are treated at the same level. Therefore, three factor analysis were conducted.

The items concerned with II, WQ, and self-efficacy and facilitating condition was subjected to the first factor analysis. The Kaiser-Meyer- Olkin (KMO), a measure of the sampling adequacy was 0.882 and the Barlett’s Test of sphericity was significant justifying the use of PCA. Three interpretable factors were obtained and suitably named as II, PBC and WQ. The factors obtained accounted for a total variance of 75.31% of which first factor accounts for 55.46 %, second factor 11.94 % and third factor explained 7.91% (Table 3).

The items concerned with PU and PEOU were subjected to the second factor analysis. The KMO was 0.892 and the Barlett’s Test of sphericity was significant justifying the use of PCA.

Two interpretable factors were obtained and suitably named as PEOU and PU. The factors obtained accounted for a total variance of 73.56% of which first factor accounts for 61.49 %, and the second factor 11.94 % (Table 4).

The items concerned with usage and customer satisfaction were subjected to the third factor analysis. The KMO was 0.87 and the Barlett’s Test of sphericity was significant justifying the use of PCA. Two interpretable factors were obtained and suitably named as Usage and Customer /User Satisfaction. The factors obtained accounted for a total variance of 77.26% of which first factor accounts for 61.48%, and the second factor 15.78% (Table 5).

The measure of internal consistency, coefficient alpha, was also computed for the items with the given factor. Coefficient (Cronbach) alpha for each of the factors was greater than 0.7 which is acceptable according to the recommendation from Nunnally [23].

Factor loadings below 0.4 were suppressed. The absence of cross loadings indicates discriminant validity i.e the items clearly belong to one factor and do not belong to the others. Similarly the high values of Coefficient alpha indicate convergent validity.

The hypothesis was tested using multiple linear regression analysis. The first six hypotheses were tested using two regression analysis, where the Independent variables were information integrity, website quality and perceived behavioral control in each regression analysis whereas the dependent variables were perceived ease of use and perceived usefulness respectively. The results of this regression analysis are shown in Table 6.

By examining the p-values given in the table and the sign of the estimates, it can be inferred that there are significant positive relationship between:

1. Perceived ease of use and information integrity at 1% significance level.

2. Perceived ease of use and website quality at 5% significance level.

3. Perceived ease of use and perceived behavioral control at 1% significance level.

4. Perceived usefulness and information integrity at 1% significance level.

5. Perceived usefulness and website quality at 1% significance level.

6. Perceived usefulness and perceived behavioral control at 1% significance level.

The other four were hypothesis were tested using two regression analysis, where the Independent variables were Perceived Ease Of Use and Perceived Usefulness in each regression analysis whereas the dependent variables were Usage and Satisfaction respectively. The results of this regression analysis are shown in Table 7.

By examining the p-values given in the table and the sign of the estimates, it can be

Inferred that there are significant positive relationship between

1. Usage and perceived ease of use at 1% significance level

2. Satisfaction and perceived ease of use at 1% significance level

3. Usage and perceived usefulness at 1% significance level

4. Satisfaction and perceived usefulness at 1% significance level

Discussion and Implications

Though all the hypothesis proposed were accepted there are some interesting observations in the results.

Relative importance of the determinants of online customer experience

When Perceived Ease of Use is considered as one of the manifestations of Online Customer Experience, it is referred as the hygiene condition or the necessary condition to have a positive feeling about the interface. Considering the relative importance of its determinants based on the comparison of standardized estimates, perceived behavioral control plays the most important role followed by Information Integrity and Website Quality. This indicates that the user wants support as well as confidence in order to be at ease while using the interface. Information Integrity is the next important aspect wherein the user wants to ensure that the transaction conducted by the user is not manipulated or misused in any way.

When Perceived Usefulness is considered as one of the manifestations of online customer experience, it is referred as the motivation to have a positive feeling about the interface. Considering the relative importance of its determinants based on the comparison of standardized estimates, web site quality plays the most important role followed by Information Integrity and Perceived behavioral control. This is justified in the sense the website quality in terms of appearance and interaction will definitely attract the user and the user feels gratified.

Relative influence of online customer experience on usage and satisfaction

Satisfaction is defined as the culmination of online customer experience. From the results it can be observed the influence of online customer experience is more on satisfaction compared to usage (as indicated by R2). This is justified as usage of the shopping site is based on the requirement and not necessarily always based on the customer experience. However satisfaction is purely an evaluation of the user based on the experience.

Limitations and future research directions

This study was conducted among Online shopping site users in India. The results of this study were obtained using cross-sectional data. End-user behavior to a particular interface may not remain the same at all times. For instance, a novice at the technology may become an expert at the same during some span of time. Hence, results from longitudinal studies may be more reliable and valid. Future studies may obtain longitudinal data while testing the research model. The sample size for this study is not adequate for using better analysis techniques such as structured equation modeling. A larger sample covering the responses with respect to interfaces of different online shopping sites, may yield more reliable and valid results.

Most of the responses in this study were obtained online. However it would be interesting to compare the results obtained based on the online responses with the results obtained based on the offline responses.

The role of user profile in the model can be an interesting addendum. In TAM, especially for the organizational setting, study has been conducted by Agarwal and Prasad [24].

Similarly Bolar [15] has tested the moderating role of the user demographics in the context of Internet banking.

Finally, the research model used in this study can be tested for mobile interfaces where the challenge is to provide optimum menu for limited screen space.

Conclusion

From the discussion of the results, the following conclusions can be made

1. In the context of e-commerce acceptance, user satisfaction with the shopping site turns out to be the better indicator of acceptance of the shopping site rather than the usage itself. This draws back the attention to the Information Systems Success Model proposed by Delone and Mclean [25] where they relate the net benefits to user satisfaction. Also in the other study by Ingham et al. [26], it was revealed that in the studies of e-commerce, the user motivations proposed in TAM influence the attitude of the user towards the shopping sites. Now the interesting proposition is to equate the meaning of customer satisfaction and attitude. Does the meaning of a better attitude towards a technology refer to high user satisfaction? If that is so, this proposes for the integration between the Information Systems Success Model and the Technology Acceptance Model wherein the customer satisfaction or attitude can be the bridge between two models.

2. Online customer experience can be understood to have two components wherein there is an experience of the hygiene condition in terms of perceived ease of use and there is an experience of the motivation condition in terms of perceived usefulness.

3. When it comes to serve the hygiene condition i.e. to ensure that the end-user is at ease, perceived behavioral control should be the variable of interest for the website designers and online retailers. This suggests that the online support and tracking feature should be provided in the shopping site so that the user gets confidence and thereby is at ease while using the shopping site.

4. When it comes to serve the motivation condition i.e. to keep the end-user coming back for more purchase to the shopping site, the website quality and information integrity are the variables of interest for the website designers and online retailers.