Examination of Web Assurance Features on E-Commerce Website and Their Impact on Web Assurance

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Examination of Web Assurance Features on E-Commerce Website and Their Impact on Web Assurance

    1. Anil Kumar T V

      Doctoral Research Scholar,

      Dept. of management studies, Pondicherry University, Puducherry, India

      Dr. Victor Anandkumar

      Associate Professor,

      Dept. of management studies, Pondicherry University, Puducherry, India

      Abstract Given the impersonal nature of E-commerce, web assurance is inevitable element on E-commerce websites. This research listed out some of the web assurance features adopted by popular E-commerce websites in India and found out the impact of this features on developing web assurance in the mind of online shopper. It emphasizes the importance of the web assurance features in E-commerce arena.

      KeywordsE-commerce, web assurance, web assurance features.

      1. INTRODUCTION

        With the boom in information technology, falling prices of personal computers and robust infrastructure, number of internet users have grown from meager 0.1% in 1998 to 19.19% in 2014 of the total Indian population i.e. 243,198,922 users, which is more than the total population of Canada [4]. Due to this digital revolution, E-commerce sector in India has become four times its size, from 3.8 billion dollar in 2009 to 17 billion dollar in 2014, growing at a CAGR of 37%. The sector is expected to cross the 100 billion dollar mark within the next five years, contributing over four percent to Indias GDP [5]. Web assurance is important element for any E- commerce websites. It has a major impact on the purchasing decision of a consumer. Even though some major dominated E-commerce vendors are getting the benefit of web assurance by using some features on their website some vendors are not aware about these. The purpose of this research is to examine the web assurance features adopted by some reputed e- commerce websites in the Indian context and assess the impact of these features on web assurance.

      2. CONCEPTUAL BACKGROUND

        1. Web assurance

          Assurance is said to be something said or done to inspire confidence [1]. While E-commerce is expected to become the dominant means by which business will conduct transactions, it is also predicted that Internet based fraud may become the largest type of white-collar crime. Therefore, it is essential to improve E-commerce security, build trust between the participants, and provide assurance [3]. Assurance can be given by the particular vendor or consumers or third party. For example, Privacy policy statement by vendor, Reviews and

          rankings is given by consumers and Third party assurance seals adopted by vendor. Online shoppers are given assurances about the vendor, products and online transaction by these features.

        2. Role of web assurance in online buying process

          Trust is the one of important construct in the measurement web site quality. People are worried of numerous risks on E- commerce and reluctant to do online business because of incidents of online fraud and abuse cases happened in this business. A primary obstacle preventing consumers from purchasing goods and services online is their lack of trust in online retailers. Many online retailers are new and relatively unknown to consumers, with the distance and impersonal nature of online shopping making it even more difficult for consumers to assess the trustworthiness of online store [2]. Online shoppers are more comfortable use E-commerce websites with the effect of these web assurance features and they are feeling secured in terms of privacy and security and transaction integrity. The role of web assurance comes to importance at this circumstance. E-commerce assurance is an area which has not been researched much; consequently, there are very few journals which discuss e-commerce assurance models and propose robust models [8].

        3. Types of web assurance feature on E-commerce websites

        There are number of web assurance features are adopted by E-commerce websites. One way of classifying these feature based on the source of the assurance. It could be classified into three, internally provided assurance (self assurance), externally provided assurances (third party assurance) and social proof which is provided consumers and other interested people. Internally provided assurances are provided and managed by the online vendor that not verified by an independent source. Examples of those are privacy policy statement, security policy statement and so on. Externally provided assurances involve a certificate and are provided by a third party organization only after an independent evaluation of the retailers e commerce related activities. Some of the examples of third party assurance seals are BBBOnline, Truste and so on. Customers reviews and ratings are considered to be social proof.

        Based on the functions served by web assurance seals, web assurance seal can be classified in to three. That are

        transaction security assurance (for example, verisign), consumer privacy assurance (for example, Truste) and transaction integrity assurance (for example, BBBOnline) [11]. A privacy assurance function is used to alleviate online consumers' perceived risk of leaking personal identification information. A security assurance function reassures online consumers that the online vendor uses a special protocol (e.g., HTTPS) to secure online transactions and a secured database to protect their personal information. A transaction-integrity assurance function guarantees fair business practices and business transactions before, during, and after the online transaction [11].

        Another way of classifying the web assurance is based on the object of assurance. It may be classified into three. Those are assurance about the vendor, assurance about the product and assurance about the process.

      3. RESEARCH METHODOLOGY

        This research is enhanced with primary data. An online questionnaire survey has been conducted in the second quarter of the year 2016 and a total of 71 questionnaires were coded and analyzed using SPSS. Convenient sampling technique has been selected for sampling. The inclusion criterion for selecting sample is people who have online shopping experience. Among the respondents 74 percent were male and 26 percent were female. 14 different web assurance features are selected from some reputed E-commerce websites and underwent exploratory factor analysis for data reduction. Scale reliability was evaluated using Cronbachs alpha (coefficient alpha) coefficient on SPSS. Nunally (1978) recommends an alpha value of 0.7 is acceptable for exploratory research. All the five constructs have good Cronbachs alpha coefficient value in this model. The items which are measuring web assurance have been chosen from previous study [9]. Web assurance level is measured by the items developed by Bonson Ponte, et al (2015).

        FINDINGS

        There are two kinds of statistical analysis strategy followed for this study. Descriptive statistics is used to explain the variables and multivariate analysis is used to inference the data and results. The result of descriptive statistics revealed that among these features on the website, as per the mean value Track your order, Replacement guarantee Customer review Return policy Customer care link are influencing more on creating positive feel on the mind of online shoppers. Surprisingly, Social network links and third party seals are least effective features in this list. Based on the variance and standard deviation, track your order has the least variation. That means online shoppers have a very similar perception about this feature.

        o test any significant difference in independent variables depends on demographic variables; appropriate t test and ANOVA were used. The result of independent sample t test shows that there is no significant impact of gender of the shopper on the influence of web assurance features on web assurance. The result of ANOVA shows that the online experience of the online shopper has significant impact on tangible evidence assurance features with the values of

        F=4.222 and p=.009. No other category of web assurance features have been significantly impacted by online experience. Post doc results tell that shoppers have less than one year experience are thinking differently on this. Another ANOVA results show that frequently purchased product of shopper has significant impact on self assurance features with the values of F=.726 and p=.049.

        By Exploratory factor analysis, it has been found that there are four different factors which are giving web assurance to the mind of online consumer. These factors are named as Product assurance and customer care link, Third party assurance, Self assurance and Tangible evidence. The feature, social network link has been deleted from the list due to low factor loading to all factors. Customer care link is closely associated with product assurance features like customer review rating and replacement guarantee. The KMO value was found to be 0.76. It shows the degree of common variance among the variables is high, so the factor analysis can proceed. Bartletts test of sphericity shows that significant value p is 0.000 which is less than 0.05, says there are relationships between the variables.

        All the features have its own importance in building web assurance. The effect of these features on web assurance has been checked by regression analysis with the help SPSS software. Adjusted R Square value in the model was calculated and it is found to be .485. The regression results revealed that there is a significant impact of product assurance features and customer care link and self assurance features on web assurance with the values of B=.398 and sig=.001 and B=.262 and sig=.005 respectively. But the results show that there is no significant impact of third party assurance seals and tangible evidence features on web assurance.

        Table 1: Regression output

      4. DISCUSSION AND CONCLUSTION

        This study emphasizing the importance of web assurance features which are used by some reputed E-commerce vendors websites. It gives intimation to new online vendors which are not adopted so-called web assurance features on their websites that the ability of these features to build assurance in the mind of online customers and create purchase intention. In the e-commerce context, studies have confirmed the relationship between trust and purchase intention. Trust is one of the predictors of online purchase intention in the context of E-commerce [9].

        Based on the research conducted in developed countries, the underlying belief is that third party web assurance features were very important for building web assurance. But here in India e-commerce is in nuance stage. This research result reveals that online shoppers are assured more by some other web assurance features like return policy, track your order, replacement guarantee and so on. It is giving a clue to the Indian researchers to think about the validity of web quality measurements which are used in India. This research indicated that the customers tend to rely more on consumer reviews than the information given by the vendor itself.

      5. LIMITATION AND FUTURE RESEARCH DIRECTION

This studies limitation provides direction to the future research. This study included web assurance features which are exclusively used for building web assurance. But some other factors on the website are also positively influencing the web assurance. For example, visual appeal, ease of use, response time and so on. Future studies may conduct including these factors. This study concentrated on young Indian online shoppers only. So the future study could be done with all age categories of online shoppers. The sample size of the study is 71 because of the time constraint. A study with improvised sample size may get better generalized idea in this context.

REFERENCES

  1. Wichers, David R., Joel E. Sachs, and Douglas J. Landoll. "What Color is Your Assurance." In Seventeenth National Computer Security Conference, pp. 11-14. 1994.

  2. Cook, D. P., & Luo, W. (2003). The Role of Third-Party Seals in Building Trust Online. E-Service Journal, 2(3), 7184. http://doi.org/10.2979/ESJ.2003.2.3.71

  3. Yanyan, W. (2014). Research on e-commerce security based on risk management perspective. International Journal of Security and Its Applications, 8(3), 153162. http://doi.org/10.14257/ijsia.2014.8.3.17

  4. Kalia, P., Kaur, N., & Singh, T. (2015). Internet Marketing and B2C E- Commerce: The Indian Scenario. Innovation Management, Excel India Publishers, Delhi, India, 127-134.

  5. Kapoor, Rana. (n.d). TFurter of e-commerce: Uncovering Innovation (p. 5). Assocham. Retrieved from http://www.assocham.org/upload/event/recent/event_1113/Background

    _Paper_Future_of_e-Commerce_web.pdf

  6. Hatcher, L. (1994). A Step-by-Step Approach to Using the SAS® System for Factor Analysis and Structural Equation Modeling. Cary, N.C.: SAS Institutte, Inc.

  7. Mathur, N. (2015). Perceived Risks towards Online Shopping An Empirical Study of Indian Customers, 3(2), 296300.

  8. Mayayise, T., & Osunmakinde, I. O. (2014). E-commerce assurance models and trustworthiness issues: an empirical study. Information Management & Computer Security, 22(1), 7696.

    http://doi.org/10.1108/IMCS-01-2013-0001

  9. Bonsón Ponte, E., Carvajal-Trujillo, E., & Escobar-Rodríguez, T. (2015). Influence of trust and perceived value on the intention to purchase travel online: Integrating the effects of assurance on trust antecedents. Tourism Management, 47, 286302.

    http://doi.org/10.1016/j.tourman.2014.10.009

  10. Kerkhof, P., & van Noort, G. (2010). Third party Internet seals. Reviewing the effects on online consumer trust consumer trust. Encyclopedia of E-Business Development and Management in the Global Economy, 701708. http://doi.org/10.4018/978-1-61520-611- 7.ch069

  11. Hu, X., Wu, G., Wu, Y., & Zhang, H. (2010). The effects of Web assurance seals on consumers initial trust in an online vendor: A functional perspective. Decision Support Systems, 48(2), 407418. http://doi.org/10.1016/j.dss.2009.10.004

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