Identification of factors influencing building initial trust in e-commerce

Abstract

Nowadays, consumer trust is identified as one of the most important factors in electronic commerce (e-commerce) growth. This has led much research to investigate the role of trust in e-commerce and determine the factors which influence trust in this area. This paper explores factors which are engaged in building initial consumer trust in online shopping when a consumer wants to buy from a website for the first time. For developing the model and determining factors, data collection is conducted using questionnaire distribution for 325 respondents. After that, the validity of the proposed model is confirmed with Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). In EFA, variables are categorized into 6 factors and then using CFA which is based on Structural Equations Model (SEM) the relationship between variables and factors is investigated. The results of research show that factors of Product Characteristics, Security & Reputation, Website Design Quality, Support, Purchase Characteristic, and Advertising are effective factors for building initial trust. In this study the statistical population is students of Damghan University.

Headnote

Abstract

Nowadays, consumer trust is identified as one of the most important factors in electronic commerce (e-commerce) growth. This has led much research to investigate the role of trust in e-commerce and determine the factors which influence trust in this area. This paper explores factors which are engaged in building initial consumer trust in online shopping when a consumer wants to buy from a website for the first time. For developing the model and determining factors, data collection is conducted using questionnaire distribution for 325 respondents. After that, the validity of the proposed model is confirmed with Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). In EFA, variables are categorized into 6 factors and then using CFA which is based on Structural Equations Model (SEM) the relationship between variables and factors is investigated. The results of research show that factors of Product Characteristics, Security & Reputation, Website Design Quality, Support, Purchase Characteristic, and Advertising are effective factors for building initial trust. In this study the statistical population is students of Damghan University.

Keywords

E-commerce, E-trust, Initial trust, Online shopping.

...

(ProQuest: ... denotes non-US-ASCII text omitted.)

Introduction

Regarding the development of information technology in the modern world, many activities are done in a way different from before. This development also affects business and economic exchanges and creates a new economic ecosystem and electronic marketplace which is named electronic commerce (e-commerce). There are different meanings of e-commerce in the literature. Simply stated, e-commerce is buying and selling via the Internet (Chaffey, 2002). Generally, e-commerce is buying, selling, transforming, and trading products, services, or information via computer networks especially the Internet (Fathian & Molanapor, 2011). E-commerce is beneficial for several reasons. For example, it provides convenient access to products that may not otherwise be accessible, which is particularly important in rural areas. It is an efficient way of entering into transactions, both for consumers and e-retailers. Further, e-commerce has made possible low value cross-border transactions on a scale that was previously unimaginable (Svantesson & Clarke, 2010).

E-commerce business models can generally be categorized in different models one of which is B2C (Business to Consumer). In B2C model, a customer can view a product and order the same. In this model, in addition to business organizations, online shopping websites are useful and are growing day by day at an unprecedented rate and the volume of transactions in e-marketplaces is expanding. This development in e-commerce and especially in the volume of transactions in online shopping websites is related to consumer trust, and the future of e-commerce depends on trust (Lee & Turban, 2001; Wang & Emurian, 2005). In e-commerce, trust is a critical issue (Yoon & Ocenna, 2015) because consumers face the challenge of buying online from an unfamiliar merchant a product or service that they cannot actually see or touch (Hong & Cho, 2011). Trust plays a central role in helping consumers overcome perceptions of risk and insecurity (McKnight, Choudhury & Kacmar, 2002; Mayer, Davis & Schoorman, 1995; Pavlou, 2003) and provides expectations of successful transactions (Schurr & Ozanne, 1985). Thus, trust building is still attracting the attention of information sciences researchers nowadays (Jai, Cegielski & Zhang, 2014). In this paper, factors which affect building consumer initial trust when they want to buy in online shopping websites for the first time are considered and a new model for the detection and categorization of these factors is presented.

This paper is organized as follows: Literature review section describes various factors which have been introduced in relation to trust in the literature and reviews different papers. In Initial trust section the conception of initial trust is explained. In Research methodology section the problem and model with all its variables are presented and research methodology is described. Then the analysis of extracted data from the questionnaire is investigated in Data analysis section and finally the Conclusion section describes the final results of the model.

Literature review

Because of the rapid development of e-commerce in modern business, e-commerce is a necessity for entering the business world. Nowadays e-commerce is rapidly penetrating into organizations and has profound impacts on businesses as well as the ordinary lives of people (Jafarzadeh & Aghabarar, 2013). E-commerce provides a unique environment in which trust has an outstanding importance. Therefore, it is important to understand how to promote consumer trust in online shopping. In addition, because of the absence of human touch and communication in e-commerce, comparing the situation of traditional transaction with real environment when consumers give their satisfaction of products by experiencing them physically, trust has a basic role in e-commerce.

The lexical meaning of trust in dictionaries is assured reliance on the character, ability, strength, or truth of someone or something. In spite of this meaning, trust is perhaps one of the most highly challenging terms whose meaning is hardly agreed upon by researchers within diverse academic disciplines (Hong & Cho, 2011). Trust in marketing involves a consumer's perceived reliability on the brand, products, or services of a merchant (Flavian, Guinaliu & Gurrea, 2006). Generally trust is defined 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 trustor, irrespective of the ability to monitor or control that other party (Chai & Kim, 2010; Mayer, Davis & Schoorman, 1995).Trust is a governance mechanism in exchange relationships characterized by uncertainty, vulnerability, and dependence (Bradach & Eccles, 1989; Jarvenpaa, Tractinsky & Vitale, 2000). Because trust is a key determinant of long term orientation in buyer-seller relationships (Ganesan, 1994), it has become crucial for online merchants to build consumers' trust. Often the definition of trust is followed by introducing three characteristics that are the main characteristics of trust (especially electronic trust). These characteristics include ability (or competence), benevolence, and integrity. Besides these factors, some researchers add predictability, too. Competence in the context of e-commerce may include good product knowledge, fast delivery, and quality customer service among others. Benevolence according to Mayer, Davis & Schoorman, 1995, refers to the extent to which a trustee is believed to want to do good to the trustor, aside from an egocentric profit motive. Integrity is the belief that the trusted party adheres to accepted rules of conduct, such as honesty and keeping promises (Gefen, 2002). Also predictability indicates the perceived reputation of vendor to service consumer continuously (Rahimnia, Amini & Nabizadeh, 2011).

There are several papers in the literature with the subject of investigation of trust in e-commerce. Among these papers some researchers consider external and contextual factors such as demographic variables. For example, these variables can be seen in the papers of Lee and Turban and Corritore et al. (Lee & Turban, 2001; Corritore, Kracher & Wiedenbeck, 2003). Some others such as Wang and Emurian (2005) investigate factors which are related to design and content of shopping websites as the main factors affecting trust. Some researchers such as Hemphill (2002) present suitable legal infrastructure in e-commerce as a necessity to build consumer trust. Some researches investigate the role of security and privacy factors in e-trust such as Thaw, Mahmood & Dominic (2009) and Wang et al. (2012). Other researchers consider the four mentioned characteristics of e-trust in the literature such as Gefen (2002) and Yu, Balaji & Khong (2015). Table 1 describes different papers in e-trust in the literature.

Regarding the studied variables of different papers about trust in the literature, it is seen that there are few papers that investigate factors affecting initial trust and in each paper only some groups of variables are considered. In this research with regard to a few models about the conception of initial trust for purchasing in shopping websites for the first time, using several models and different papers in the literature, a new model is presented to identify and categorize effective factors of building initial trust in e-commerce. It is notable that in this proposed model in addition to different factors mentioned in the literature, advertising policies that are less heeded in the previous studies are introduced and investigated.

Initial trust

Various papers on trust imply the importance and complexity of trust conception in e-commerce. This has led researchers to investigate different factors that are engaged in trust in different levels. Regarding the literature, these levels can be categorized into 3 Levels. In level 1 there are some factors such as personal factors which are related to the intention of a consumer to connect with Internet vendors. Level 2 is about factors that should be considered for building initial trust of consumers such as characteristics about shopping websites, security, privacy, etc. Another level can be related to stability of trust of consumers during the time. It should be noted that there are some researchers in the literature who have categorized different factors (Mc Knight, Choudhury & Kacmar, 2002) in some levels.

The concentration of this study is on level 2 which is building initial trust. About the difference of factors in level 2 and 3 it is notable that in level 2 the customer is searching and investigating different websites to select a good website for shopping. Therefore, initial trust begins when a person does not have firsthand knowledge and decides to rely on his/her propensity to trust others or institutional cues (Susanto & Chang, 2014). But in level 3 customers have bought at least one time from a specific online shopping website and factors in this level cause a customer to shop from the mentioned website for the next time and this process builds consumer Loyalty (Kim, Jin & Swinney, 2009; Dehdashti Shahrokh, Oveisi & Timasi, 2013). The factors in this level are generally related to the process of shopping in the website and the quality of after sale services of websites such as the behaviors of vendor for refunding or changing the commodity, receiving the purchased goods through the Internet on time, lack of complexity in the shopping process, etc. All these variables in level 3 will be investigated after or during the shopping process. It is remarkable that the conception of initial trust is different from online purchase intention because according to the studies of Nazari, Hajiheidari & Nasri (2012) and Ganguly et al. (2010), trust is a factor which influences online purchase intention.

Research method

The current study is an applied and descriptive one which is specifically Structural Equations Model (SEM). As stated earlier, this research only discusses factors which affect initial trust when the consumer wants to connect with an Internet store after making a decision to shop. For this purpose 27 variables which are effective factors in initial trust are detected and investigated. The variables are described in Table 2. The main question of this research may be worded as follows:

what are the effective factors which influence building the initial trust of consumers?

To test the mentioned variables of this research a questionnaire was employed. At first, by studying different papers and books, numerous variables for designing the questionnaire were collected. After detection of key variables, the final questionnaire was designed. The questionnaire is divided into two sections. The first section with five questions is about the demographic attributes of respondents, and the second section consisting of 27 questions is related to the goal of research. These questions are measured on 1 (strongly disagree) to 5 (strongly agree) point Likert scale. Thus, the first section's questions are about the statistical population of interest for our study, and they ask for respondents to provide information on their gender, age, education, the number of online shopping experience, and the level of access to the Internet. Other questions follow the main question of the paper.

The reliability shows the stability of measures in different conditions (Nunnally, 1978). To determine the amount of error in every construct, the Cronbach's alpha test was applied. The constructs with a higher Cronbach's alpha are more reliable in terms of internal compatibility among variables. There are different definitions for interpreting Cronbach's alpha. In this research, the Cronbach's alpha was 0.925, which was close to Brown's recommendation and more than Nunnally's standard. Therefore, the reliability of the measures is satisfactory.

In order to examine the validity of conception of the questionnaire, some experts and professors of universities investigated and confirmed the variables of the questionnaire. Also, investigation of the validity of questionnaire was checked using exploratory factor analysis and confirmatory factor analysis. The results are explained in the next section.

To choose the statistical population of the study regarding the aim of research, the two following conditions are considered. At first avoiding invalid data from questionnaires, the questionnaires of study were distributed among students of Damghan University, because students are familiar with Internet and online shopping (Olfat, Khosravani & Jalali, 2011; Hasangholipor et al., 2013). To explain the second condition, it can be said that to follow the purpose of the research and identify the factors affecting building initial trust in buying for the first time from a website, in addition to viewpoints of people who had Internet shopping experience, the opinions of people who hadn't any experience are also necessary. By investigating these two groups of people, we can help managers and owners of online shopping websites attract customers to do their first shopping. Thus, in this research the limitation of having Internet shopping experience is not considered. The size of population in this study is 3500 students, and according to Morgan table, 350 people have been selected using simple random sampling. 325 usable questionnaires were returned. The demographic profile of the respondents is shown in Table 3.

Data analysis

After gathering data from questionnaires, exploratory factor analysis was used to guide the process of grouping factors into their component or to check that the proposed grouping structure is consistent with the data. IBM SPSS Statistics version 22 was used for data analysis. The first output of SPSS exploratory factor analysis is Kaiser-Meyer measure of sampling adequacy and Bartlett's test. The value of KMO should be greater than 0.5 to show if the sample is adequate and suitable for conducting factor analysis. In this paper, the value of KMO is 0.924 which is greater than 0.5 which indicates that this sample survey is appropriate for further conducting factor analysis.

Principal Component Analysis (PCA) was used for extraction of the variables whose measure in the communalities table and in the extraction column is less than 0.5. The extraction column shows the amount of variance that is common with the other variables' variance. In other words, the variance and effects on variance of a particular variable by all factors are shown in the communality table (Gaur & Gaur, 2006). Variables with more than 50% (more than 0.5) common variance with the other variables are suitable for factor analysis and should not be omitted (HabibporGetabi & SafariShali, 2006). EFA results show that variables with numbers of 25, 26 and 27 have very low extraction value compared with others and should be omitted from the model in this step. Table 4 shows the results of exploratory factor analysis. According to the results, 24 variables were categorized into 6 groups.

After extracting 6 factors using exploratory factor analysis, confirmatory factor analysis (CFA) with Lisrel 8.8 was used to test the measurement model and establish convergent and discriminate validity of the constructs. Convergent validity means the extent to which the measures for a variable act as if they are measuring the underlying theoretical construct because they share variance (Schwab, 1980). In Figure 1 standardized solutions of confirmatory factor analysis are shown. In this figure standardized factor loadings indicate the effect of each factor on variable's variance.

In Figure 2 t-values of confirmatory factor analysis are shown. According to this figure, because all t-values are more than 1.96, all determined paths in the model are significant (Mohammadi & Amiri, 2014). In other words, six extracted factors from exploratory factor analysis describe variance of their variables.

Table 5 shows the overall model fit indices for CFA. It also shows the recommended values of each measure. As shown, all measures satisfied the recommended values, except for the X and GFI. However, the X is sensitive to large sample sizes, especially for cases in which the size exceeds 200 respondents (Hair et al., 1998). The GFI at 0.84 was slightly below the 0.9 benchmark, but it exceeds the recommended value of 0.80 suggested by Etezadi-Amoli and Farhoomand (1996). One may conclude that the index is marginally acceptable (Suh & Han, 2003). Therefore, there is a reasonable overall fit between the model and the observed data.

Conclusion

Regarding the importance of e-commerce in modern business world, many researchers have investigated various factors related to e-commerce. Among these factors, consumer trust is a significant factor for propagating e-commerce. In this paper, using different models and various papers in the literature, a new model for factors which affect the building of initial trust in e-commerce is proposed. In this model, at first 27 variables were extracted, then using exploratory factor analysis 6 general groups of variables were gained, and 3 variables from 27 variables were omitted. After that confirmatory factor analysis to test the measurement model was done. The results of CFA confirmed the proposed model of this paper.

Comparing this model with others in the literature, it can be said that the results of this paper are in conformity with the results of other papers. Factors such as perceived vendor reputation and perceived site quality as factors affecting initial trust which were investigated in Mc Knight, Choudhury and Kacmar (2002) are two factors affecting initial trust in this paper. Also, in the study of Susanto and Chang (2014) in addition to the mentioned factors, security and privacy are introduced as important factors in initial trust which the results of this paper confirm. Besides these factors, advertisement, Product Characteristics, Purchase Characteristic, and Support are factors which are introduced and tested in this paper as effective factors on initial trust. In addition to resolutions of current studies in the literature about initial trust, the results of this paper confirm the results of research about e-commerce so that the factors that are investigated in this paper are introduced as effective factors in e-commerce in previous studies such as Lee and Turban (2001), Gefen (2002), Kim et al. (2005), Wang & Emurian (2005), Liao, Palvia & Lin (2006), Thaw, Mahmood & Dominic (2009), Khodadadhoseini, Shirkhodaei & Kordnaeij (2010), Wang et al. (2012), and Chang, Cheung & Tang (2013).

In addition, in the literature, the advertising factor is not investigated as an effective factor in initial trust and is less heeded in the field of e-commerce. In this paper, this factor with 3 variables of Online advertising, Advertising in other media, and Satisfaction and good evaluation of past consumers is identified as one of the six effective factors in building initial trust.

According to significant coefficient of the six factors, it is clear that these groups are not independent from each other. Thus, it is recommended that managers and owners of shopping websites consider all six groups together for designing shopping websites. Also, it is recommended that managers notice advertisements especially in virtual social networks as an important variable to build initial trust. Because of the dependency of these six groups of variables, the investigation of these factors can be done using system dynamics model for future work. System dynamics is efficient for showing the relationship of all variables better.

References

References

Bradach, J.L. & Eccles, R.G. (1989). "Price, authority and trust: From ideal types to plural forms". Annual Review of Sociology, 15, 97-118.

Chaffey, D. (2002). E-Business and E-commerce Management. London, Prentice-Hall.

Chai, S. & Kim, M. (2010). "What makes bloggers share knowledge? An investigation on the role of trust". International Journal of Information Management, 30(5), 408-415.

Chang, M.K.; Cheung, W. & Tang M. (2013). "Building trust online: Interactions among trust building mechanisms". Information & Management, 50, 439-445.

Corbitt, B.J.; Thanasankit, T. & Yi, H. (2003). "Trust and e-commerce: a study of consumer perceptions". Electronic Commerce Research and Applications, 2, 203-215.

Corritore, C.L.; Kracher, B. & Wiedenbeck, S. (2003). "On-line trust: concepts, evolving themes, a model". International Journal of Human-Computer Studies, 58, 105-125.

DehdashtiShahrokh, Z.; Oveisi, N. & Timasi, S.M. (2013). "The Effects of Customer Loyalty on Repurchase Intention in B2CE-commerce- A Customer Loyalty Perspective". Journal of Basic and Applied Scientific Research, 3(6), 636-644.

Etezadi-Amoli, J. & Farhoomand, A.F. (1996). "A structural model of end user computing satisfaction and user performance". Information & Management, 30(2), 65-73.

Fathian, M. & Molanapor, R. (2011). Electronic commerce. Tehran. Atinegar. (In Persian)

Flavian, C.; Guinaliu, M. & Gurrea, R. (2006). "The role played by perceived usability, satisfaction and consumer trust on website loyalty". Information & Management, 43(1), 1-14.

Ganesan, S. (1994). "Determinants of long-term orientation in buyer-seller relationships". Journal of Marketing, 58(2), 1-19.

Ganguly, B.; Dash, S.B.; Cyr, D. & Head, M. (2010). "The effects of website design on purchase intention in online shopping: the mediating role of trust and the moderating role of culture". International Journal of Electronic Business, 8(4/5), 302-330.

Gaur, A.S.; Gaur, S.S. (2006). Statistical Methods for Practice and Research. London, SAGE Publications Inc.

Gefen, D. (2002). "Reflections on the Dimensions of Trust and Trustworthiness among Online Consumers". ACM Special Interest Group on Management Information Systems, 33(3), 38-53.

Ghalandari, K. (2012). "The Effect of E-Service Quality on E-Trust and E-Satisfaction as Key Factors Influencing Creation of E-Loyalty in E-Business Context: The Moderating Role of Situational Factors". Journal of Basic and Applied Scientific Research, 2(12),12847-12855.

HabibporGetabi, K. & SafariShali, R. (2006). Comprehensive Manual for Using SPSS in Survey Researches. Tehran, Motefakeran-Loyeh. (In Persian)

Hair, J.F.J.; Anderson, R.E.; Tatham, R.L. & Black, W.C. (1998). Multivariate Data Analysis with Readings. NewJerwey, Prentice Hall.

Hasangholipor, T.; Amiri, M.; Fahim, F. & Ghaderiabed, A. (2013). "The effect of customer characteristics on their willingness to accept internet shopping". Information Technology Management, 5(4), 67-84. (In Persian)

Hassanein, Kh. & Head M. (2004). "The Influence of Product Type on Online Trust". 17thBled Electronic Commerce Conference eGlobal, Bled, Slovenia.

Hemphill, T.A. (2002). "Electronic commerce and consumer privacy: Establishing online trust in the US digital economy". Business and Society Review, 107(2), 221-239.

Hong, l. B. & Cho, H. (2011). The impact of consumer trust on attitudinal loyalty and purchase intentions in B2C e-marketplaces: Intermediary trust vs. seller trust. International Journal of Information Management, 31(5), 469- 479.

Jafarzadeh, A. & Aghabarar, F. (2013). "Trust in E-commerce". Academic Journal of Research in Business and Accounting, 1(5), 46-52.

Jai, L., Cegielski, C. & Zhang, Q. (2014). "The Effect of Trust on Customers' Online Repurchase Intention in Consumer-to-Consumer Electronic Commerce". Journal of Organizational and End User Computing, 26(3), 65-86.

Jarvenpaa, S.L.; Tractinsky, N. & Vitale, M. (2000). "Consumer trust in an Internet store". Information Technology and Management, 1(1), 45-71.

KhodadHoseini, S.H.; Shirkhodaei, M. & Kordnaeij, A. (2010). "Factors influence customer trust in e-commerce (B2C Model)". Modarres Human Sciences, 13(2), 93-118.(In Persian)

Kim, D.J.; Song, Y.I.; Braynov, SB. & Rao, HR. (2005). "A multidimensional trust formation model in B-to-C e-commerce: a conceptual framework and content analyses of academia/practitioner perspectives". Decision support systems, 40, 143-165.

Kim, J.; Jin, B. & Swinney, J.L. (2009). "The role of retail quality, e-satisfaction and e-trust in online loyalty development process". Journal of Retailing and Consumer Services, 16, 239-247.

Lee, M.K.O. & Turban, E. (2001). "A trust model for consumer internet shopping". International Journal of Electronic Commerce, 6(1), 75-91.

Liao, C.; Palvia, P. & Lin, H. (2006). "The roles of habit and web site quality in e-commerce". International Journal of Information Management, 26, 469-483.

Mayer, R.C.; Davis, J.H. & Schoorman, F.D. (1995). "An integrative model of organizational trust". Academy of Management Review, 20(3), 709-734.

McKnight, D.H. &Chervany, N.L. (2002). "What trust means in e-commerce customer relationships: An interdisciplinary conceptual typology". International Journal of Electronic Commerce, 6(2), 35-59.

McKnight, D.H.; Choudhury, V. & Kacmar, C. (2002). "The impact of initial consumer trust on intentions to transact with a web site: a trust building model". Strategic Information Systems,11, 297-323.

Miremadi, A.; Hassanian-Esfahani, R. & Aminilari, M. (2013). "A New Trust Model for B2C E-Commerce Based on 3D User Interfaces". 7th International Conference on e-commerce in Developing Countries with focus on E-security, Kish Island, Iran.

Mohammadi, A. & Amiri, Y. (2014). "Identify and explain the factors influence the acceptance of IT innovations in government organizations with structural equation modelling approach". Information Technology Management, 5(4), 195-218.(In Persian)

Nazari, M.; Hajiheidari, N. & Nasri, M. (2012). "The effect of B2C shopping website attributes on customer internet purchase intention using conjoint analysis technique". Business Management, 4(4), 127-146. (In Persian)

Nunnally, J.C. (1978). Psychometric Theory. New York. McGraw-Hill.

Olfat, L.; Khosravani, F. & Jalali, R. (2011). "Identification of factors influence internet shopping and prioritize them using Fuzzy ANP". Business Management, 3(7), 19-36. (In Persian)

Pavlou, P.A. (2003). "Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model". International Journal of Electronic Commerce, 7(3), 101-134.

Rahimnia, F.; Amini, M. & Nabizadeh, T. (2011). "Provide a framework for the process of building e-trust in and e-commerce development". 6th national conference on e-commerce and economy, Tehran, Iran. (In Persian)

Safa, N.S. & Ismail, M.A. (2013). "A customer loyalty formation model in electronic commerce". Economic Modelling, 35, 559-564.

Schurr, P.H.; & Ozanne, J.L. (1985). "Influences on exchange processes: Buyers' preconceptions of a seller's trustworthiness and bargaining toughness". Journal of Consumer Research, 11(4), 939-953.

Schwab, D.P. (1980). "Construct validity in Organizational behavior". Research in Organizational Behavior, 2, 3-43.

Shankar, V.; Urban, G.L. & Sultan, F. (2002). "Online trust: A stakeholder perspective, concepts, implications, and future direction". Journal of Strategic Information Systems, 11, 325-344.

Suh, B. & Han, I. (2003). "The impact of customer trust and perception of security control on the acceptance of electronic commerce". International Journal of Electronic Commerce, 7(3), 135-161.

Susanto, H.T.A. & Chang, Y. (2014). "Determinants of Initial Trust Formation in Electronic Commerce Acceptance in Indonesia". IEEE Conference on Systems, Process and Control (ICSPC 2014), Kuala Lumpur, Malaysia.

Svantesson, D. & Clarke, R. (2010). "A best practice model for e-consumer protection". Computer law and security review, 26(1), 31-37.

Thaw, Y.Y.; Mahmood, A.K. & Dominic, D.D. (2009). "A Study on the Factors That Influence the Consumers' Trust on E-commerce Adoption". International Journal of Computer Science and Information Security, 4(1&2), 153-159.

Wang, R.; Wang, S.; Wu, T.Z. & Zhang, X. (2012). "Customers E-trust for Online Retailers: A Case in China". 8thInternational Conference on Computational Intelligence and Security, Guangzhou, China.

Wang, Y.D. & Emurian H.H. (2005). "An overview of online trust: Concepts, elements, and implications". Computer in Human Behavior, 21(1), 105-125.

Yoon, H.S. & Occena, L.G. (2015). "Influencing factors of trust in consumer-to-consumer electronic commerce with gender and age". International Journal of Information Management, 35(3), 352-363.

Yu, P.L.; Balaji, M.S. & Khong, K.W. (2015). "Building trust in internet banking: a trustworthiness perspective". Industrial Management & Data Systems, 115(2), 235-252.