The research inherited four factors from the research model of Nor, Nazarie, and Yusoff (2013): (1) Trust Propensity, (2) Testimonials, (3) Experience in Online Purchasing, (4) Financial Perceived Risk and based on the interview, the study developed two more factors: (5) Product Perceived Risk and (6) Time Perceived Risk.
An Giang University Journal of Science – 2019, Vol 6, 26 – 38 FACTORS INFLUENCING CUSTOMER’S TRUST WHEN PURCHASING ON FACEBOOK SOCIAL NETWORK Tran Thi My Phuong1 An Giang University Information: Received: 10/06/2018 Accepted: 14/09/2018 Published: 02/2019 Keywords: Trust, trust propensity, testimonials, risk ABSTRACT Trust is the key element for the success of trading on Facebook, therefore, finding the factors influencing trust of customers is necessary The research inherited four factors from the research model of Nor, Nazarie, and Yusoff (2013): (1) Trust Propensity, (2) Testimonials, (3) Experience in Online Purchasing, (4) Financial Perceived Risk and based on the interview, the study developed two more factors: (5) Product Perceived Risk and (6) Time Perceived Risk After surveying 200 customers, the research shows that Trust Propensity affects the most positively to Online Trust and Financial Perceived Risk affects negatively to Online Trust The study implicates to help management build their customers’ trust as well as offers a particular reality in an e-commerce research field INTRODUCTION majority of Internet users are not confident to make a purchasing decision on Facebook According to Gefen (2000), Harn, Khatibi and Ismail (2006), lack of trust is a major barrier in an online purchase This can be explained that Facebook users are unlimited and there has been no legal organization regulating trading activity on it It is easy for a person to cheat customers out of money on Facebook Purchasing online has been developing dramatically in all corners of the world due to its practical benefits such as help customers save time, compare prices, access new products easily, and save transportation cost as well as avoid traffic congestion Recently, a large number of customers has moved to shop on social networks, especially Facebook instead of buying on formal websites such as Vatgia.com or Lazada.vn Facebook is considered as a public house of oneseventh of world’s population and one- third of Vietnamese population (VNNIC, 2013) Individuals and businesses, therefore, are taking advantage of this medium to both sell products and keep in touch with their friends (Ranganathan & Ganapathy, 2002) Nevertheless, most of the studies focused on the traditional e-commerce and there are few types of researches conducted to examine factors that affect customer’s trust on Facebook This study aims to fill in this gap in order to help businesses increase their customer’s trust by some particular actions; besides, its results can reliably contribute to research of e-commerce field in general In spite of many advantages mentioned above, the LITERATURE REVIEW 26 An Giang University Journal of Science – 2019, Vol 6, 26 – 38 2.1 Trust and Online Trust orders or write testimonials about some certain products However, everything has its two sides, Facebook has some disadvantages for both sellers and buyers Trust has been identified differently among researchers Koufaris and Hampton-Sosa (2004) suggest that trust is the willingness to rely on a third party after the first interaction with it Another study conducted by Coulter and Coulter (2002) defined trust as a key factor to build longterm relationships between service representatives and their customers 2.3 Some typical researches Customer’s Trust on Online Many studies have been conducted to investigate factors that influence customers’ trust in an online purchase One of recent research is by Nor, Nazarie, and Yusoff (2013) They studied the factors influencing individuals’ trust in an online purchase through social network sites and the results discovered that (1) Trust propensity, (2) online purchasing experiences, (3) testimonials, and (4) money risk affect customers’ trust in online purchase The authors surveyed 129 customers who come from Malaysia, China, by sending emails and uploading the questionnaires on their individual Facebook accounts Especially, the research used the method of multiple regression analysis to test the relation of the factors and discovered that testimonials have the strongest effect on customer’s trust In other words, good comments and feedbacks which come from old customers are advantageous for attracting new customers and building stable relations among existing customers In the Internet shopping platform, online trust is also the willingness of a consumer to be defenseless to the actions of an Internet business and based on the hopes that he or she will be treated agreeably, regardless of the ability of the consumer to regulate or control the Internet business (Lee & Turban, 2001) Meanwhile, Hui and Kejin (2009) defined online trust as a process including requirement, attitude, intention, and purchase behavior From various definitions, trust shows an important role in online shopping Without trust, customers are not confident enough to make online purchasing decision and businesses can not establish sustainable relationships with their customers 2.2 Social Networks (SNs) SNs is the top of Internet applications which allows users to create profiles and keep contact with friends who are already registered on the site Some of the examples are MySpace, Facebook, Friendster and Twitter In Vietnam, Facebook has about million users (Comscore, 2012) and becomes a phenomenon in the youngsters even the elderly and the kids One of the special functions of Facebook is that users can upload their photos and make their information visible to their friends This enables them to communicate more effectively and make friends unlimitedly In terms of e-commerce, sellers find it easy to describe the products and services, and convenient to reply customer’s questions on Facebook, while buyers think it easy to approach new products from their favorite Facebook stores, easy to place Moreover, Gefen (2000) also studied the role of familiarity and trust in an e-commerce context He analyzed the relations of five factors: (1) familiarity, (2) trust propensity, (3) trust, (4) inquiring, and (5) purchasing The results show that both familiarity with an Internet vendor and its processes as well as trust in the vendor influenced purchasing intension Therefore, it is necessary to concentrate on building trust by increasing familiarity Moreover, the study proved that familiarity is primarily people's disposition to trust that influenced their trust in the venders In addition, another important research was conducted by Kim et al (2007) on “A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and 27 An Giang University Journal of Science – 2019, Vol 6, 26 – 38 their antecedents” This study focused on developing a theoretical framework which describes the trust-based decision-making process that a consumer uses when purchasing on the Internet and on examining the model which use Structural Equation Modeling method The study results show that online trust and perceived risk affect customer’s purchasing decisions strongly factors mentioned and repeated in most of the researches are Trust Propensity, Online Purchasing Experience, Testimonials, and Perceived Risks This inspires the author to implement a study to survey the factors influencing customer’s online trust when purchasing on Facebook In Vietnam, the number of research on online trust has been increasing Tran Minh (2012) studied “Factors affecting customer trust in online shopping in Vietnam” The author proposed a research model including four factors affecting trust in online shopping: (1) Privacy Perceptions, (2) Security Protection, (3) Perceived Risks, and (4) Perceived Benefits The study used convenience sampling and purposing sampling to select 216 Vietnamese students and office workers who used to shop online by electronic payments The results proved that Perceived Risks and Privacy Perceptions have strong impacts on online trust This is explained that in a developing country like Vietnam, customers are not familiar with online shopping Therefore, they tend to care about risks rather than profits 3.1 Research methodology Research methodology and hypothesis The study was implemented by combining quantitive and qualitative research methodology After reviewing a wide range of national and international papers and researches related to online trust, the author conducted six focus interviews with six customers who had purchased on Facebook in order to compare the previous results to the reality and to find out new factors An online questionnaire was prepared and developed based on the previous results and focus interviewed results The study used convenience sampling method which allows reaching the responders who are available conveniently to participate in the study and targeted Facebook users who had purchased on Facebook All of 38 dependent and independent variables were measured by Likert scales Furthermore, Nguyen Mai Trang and Nguyen Ngoc Bich Tram (2014) studied about the factors affecting actual use of Facebook in Vietnam by examining six factors: (1) Social Identity, (2) Altruism, (3) Telepresence, (4) Perceived ease of use, (5) Perceived usefulness, and (6) Perceived encouragement There were 363 Facebook users in Ha Noi, Da Nang, and Ho Chi Minh City taking part in the survey The results indicated that Perceived ease of use, Perceived usefulness, and Perceived encouragement influence directly on the actual use of Facebook 3.2 Research hypothesis Trust propensity was mentioned in several types of researches on e-commerce According to McKnight and Chervany (2002), trust propensity or disposition to trust can be defined as “general willingness based on extended socialization to depend on others” and concluded that those who have a strong belief in human’s good characteristic may have a high level of trust propensity This finding leads to the first hypothesis of the study: In conclusion, the above research overview indicates that in Vietnam most of the studies concentrated on online purchasing intention or Facebook-using behavior while many researchers in the world have investigated online trust popularly and profoundly in different sides The Hypothesis 1: Trust propensity influences positively on customers’ trust when purchasing on Facebook Testimonials play an important role in online shopping Testimonials are sentences spoken or 28 An Giang University Journal of Science – 2019, Vol 6, 26 – 38 written about some feelings of customers after they experienced the products or services with a hope that they can recommend or prevent other customers from buying a particular product or service In social networks, customers can write their testimonials publicly or send a message privately (Dwyer, Hiltz & Passerini, 2007) That is the reason why businesses on Facebook try to gather more and more positive testimonials about their product or service to enhance their customers’ trust Therefore, the second hypothesis is suggested such as phone numbers, home address, e-mail address, and debit or credit card numbers which are attractive to financial frauds (March, 2006) Therefore, the fourth hypothesis is proposed Hypothesis 4: Financial risk influences negatively on customers’ trust when purchasing on Facebook Product risk is another widespread issue that every customer concerns before making a purchasing decision Product risk involves both quality and quantity In terms of quantity, customers receive more or fewer items than they order In terms of quality, customers receive products that are not matched to the ones they order, namely they may be damaged or defective and they may have different color or size In another word, product risk is the loss that customers get when the provided products are not matched to the ones that they expect (Horton, 1976) Therefore, the fifth hypothesis is proposed Hypothesis 2: Testimonials influence positively on customers’ trust when purchasing on Facebook Jiang, Chen and Wang (2008) researched on the relation between knowledge, trust in online purchasing and online buying intention of customers The results pointed out that knowledge are related positively to trust in online purchasing In the words, those who have awareness of online shopping tend to trust and be willing to shop online because they can identify risk in online transactions The third hypothesis is given Hypothesis 5: Product risk influences negatively on customers’ trust when purchasing on Facebook Despite the convenience of online shopping, a loss of time may occur in all stages such as making inquiries, ordering products, paying the bills, receiving products, even asking for refund Roselius (1971) confirmed in his research that time loss was considered as an additional risk of products and services Therefore, the sixth hypothesis is proposed Hypothesis 3: Experience in online purchasing influences positively on customers’ trust when purchasing on Facebook Purchasing online involves a wide range of risks in which financial risk is the most concerned Most of the cases, the customers lose their money by sending money in advance and not receive their ordered products or receive dissatisfied ones Moreover, the customers have to disclose their personal information to the sellers Hypothesis 6: Time risk influences negatively on customers’ trust when purchasing on Facebook 29 An Giang University Journal of Science – 2019, Vol 6, 26 – 38 Figure Research Model Research results 4.1 Scale descriptions is a measure of internal consistency on the closely level that the variables of the scale correlate with each other in order to eliminate the inappropriate variables According to Nguyen Dinh Tho (2013), a good reliability scale must have Cronbach’s Alpha coefficient from 0,70 to 0,80 However, the Cronbach’s Alpha coefficient of scale from 0,6 upward are accepted Furthermore, the condition to carry out Exploratory Factors Analysis (EFA) is that the variables must have corrected item-total correlation greater than 0,3 (Nunnally and Burnstein, 1994) The data was collected from 200 respondents who have been purchasing on Facebook and 38% are male Most of them are from 22 to 35 years old The majority have been buying online for a year (accounting for 39%), for more than one year (accounting for 26,5%), and for a month (accounting for 20,5%) 4.2 Cronbach’s Alpha analysis The Cronbach’s Alpha coefficient is used to evaluate the reliability of the scale In addition, it Table Results of Cronbach’s Alpha Analysis Variables Trust Propensity Items Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted prop1 0,595 0,832 prop2 0,693 0,806 prop3 0,745 0,791 prop4 0,644 0,818 prop5 0,603 0,830 => Cronbach’s Alpha of the scale Testimonials 0,847 test1 0,643 0,788 test2 0,532 0,819 test3 0,571 0,810 test4 0,734 0,762 test5 0,656 0,783 30 An Giang University Journal of Science – 2019, Vol 6, 26 – 38 Variables Items Corrected Item-Total Correlation => Cronbach’s Alpha of the scale Online Purchasing Experience 0,827 ex1 0,632 0,885 ex2 0,687 0,873 ex3 0,753 0,857 ex4 0,769 0,854 ex5 0,803 0,846 => Cronbach’s Alpha of the scale Financial Risks 0,888 Fin1 0,702 0,889 Fin2 0,699 0,890 Fin3 0,753 0,878 Fin4 0,811 0,865 Fin5 0,797 0,868 => Cronbach’s Alpha of the scale Product Risks Cronbach's Alpha if Item Deleted 0,900 Pro1 0,807 0,802 Pro2 0,263 0,922 Pro3 0,832 0,795 Pro4 0,769 0,813 Pro5 0,780 0,812 => Cronbach’s Alpha of the scale 0,864 Pro1 0,844 0,891 Product Risks Pro3 0,861 0,885 (After deleting Pro2) Pro4 0,771 0,915 Pro5 0,808 0,903 => Cronbach’s Alpha of the scale Time Risks 0,922 Time1 0,739 0,890 Time2 0,745 0,890 Time3 0,784 0,886 Time4 0,787 0,887 Time5 0,734 0,891 Time6 0,753 0,889 Time7 0,781 0,886 Time8 0,286 0,926 31 An Giang University Journal of Science – 2019, Vol 6, 26 – 38 Variables Corrected Item-Total Correlation Items => Cronbach’s Alpha of the scale Time Risks (After deleting Time8) 0,906 Time1 0,740 0,917 Time2 0,767 0,914 Time3 0,793 0,912 Time4 0,793 0,913 Time5 0,730 0,918 Time6 0,774 0,914 Time7 0,774 0,914 => Cronbach’s Alpha of the scale Trust 0,926 trust1 0,623 0,901 trust2 0,831 0,857 trust3 0,871 0,847 trust4 0,660 0,894 trust5 0,761 0,873 => Cronbach’s Alpha of the scale 0,898 In the process of verifying reliability, Pro2 and Time8 were deleted because they both have Corrected Item-Total Correlation less than 0.3 The remaining 36 variables have Cronbach’s Alpha coefficient of the constituent larger than 0.7; this means that the variables have closely connected each other in the same factor The observing variables in the same factors have itemtotal correlation greater than 0.3; therefore all of them were put into Exploratory Factors Analysis (EFA) 4.3 Exploratory Factor Independent Variables Cronbach's Alpha if Item Deleted Analysis Risks, Online Purchasing Experience, Trust Propensity, Testimonials Among them, Test2, which belongs to Testimonials, had loading coefficient of less than 0.5 so it was removed from the scale Then, another EFA was conducted in which KMO test coefficient had a value of 0.840 > 0.5 showing the suitability of the analysis to the data (Nguyen Dinh Tho, 2013) Bartlett's Test of Sphericity is 4006.98 with Sig = 0.00 < 5% This asserts that variables closely connected each other (Nguyen Dinh Tho, 2013) Cumulative Variance is 71.293 > 50% In other words, the first factor can explain 71.29% of the variation of data (Gerbing and Anderson, 1988) Moreover, Eigenvalue coefficient is greater than one on The analysis result shows that the independent variables gather in groups and have loading coefficients larger than 0.5 There are six factors grouped: Time Risks, Financial Risks, Product 32 An Giang University Journal of Science – 2019, Vol 6, 26 – 38 Table Rotated Component Matrixa after deleting Test2 Component time4 849 time3 847 time6 827 time2 824 time7 823 time1 817 time5 786 fin4 864 fin3 857 fin5 850 fin1 791 fin2 791 ex5 845 ex4 819 ex3 803 ex2 781 ex1 739 pro1 906 pro3 901 pro5 892 pro4 841 prop3 829 prop4 780 prop2 724 prop1 656 33 An Giang University Journal of Science – 2019, Vol 6, 26 – 38 prop5 642 test4 832 test5 757 test1 729 test3 595 Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization a Rotation converged in iterations 4.4 Exploratory Factor Dependent Variables Analysis on In conclusion, after conducting Exploratory Factor Analysis, six independent variables and one dependent variable remain as before KMO Measure of Sampling Adequacy is 0.833 > 0.5 This means that the test is essential Bartlett's Test of Sphericity is 653.509 with Sig = 0.00< 5% (0.05) showing that the variables correlate closely each other Cumulative of Variance is 71,148 >50% 4.5 Examining the reliability of the scale after removing Test2 This step aims at re-examining to ensure the scale is still reliable after removing Test2 Fortunately, the result makes certain that Cronbach’s Alpha of the scale get value 0.819 and reliabilities of all items are larger than 0.5 The matrix does not rotate because only one dependent factor was extracted Table Cronbach’s Alpha after Removing Test2 Variable Testimonials Items Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted test1 0,643 0,771 test3 0,546 0,823 test4 0,764 0,715 test5 0,631 0,776 => Cronbach’s Alpha of the scale 4.6 The result of Pearson Coefficient Analysis 0,819 Correlation All of the Sig values are smaller than 5% This means that the Pearson Correlation Coefficient Analysis results are significant in statistics The table shows value from -0.310 to +1, that means the variables are relevant to each other and can be used in regression analysis After encoding the average value of dependent and independent variables, the author analyzes the Pearson correlation in order to find out the variables that are relevant to each other and to remove irrelevant or fewer relevant ones 34 An Giang University Journal of Science – 2019, Vol 6, 26 – 38 Table Correlation TRUST Pearson Correlation TRUST TIME FIN PROP PRO EX TEST -.250** -.310** 551** -.254** 512** 475** 000 000 000 000 000 000 100 -.249** 184** 088 003 160 000 009 217 966 -.240** 227** -.159* -.096 001 001 025 177 -.086 362** 558** 226 000 000 083 116 244 101 489** Sig (2-tailed) TIME FIN PROP PRO EX TEST Pearson Correlation -.250** Sig (2-tailed) 000 Pearson Correlation -.310** 100 Sig (2-tailed) 000 160 Pearson Correlation 551** -.249** -.240** Sig (2-tailed) 000 000 001 Pearson Correlation -.254** 184** 227** -.086 Sig (2-tailed) 000 009 001 226 Pearson Correlation 512** 088 -.159* 362** 083 Sig (2-tailed) 000 217 025 000 244 Pearson Correlation 475** 003 -.096 558** 116 489** Sig (2-tailed) 000 966 177 000 101 000 000 ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed N = 200 4.7 Regression analysis 51.8% of the variation of the dependent variable Sig value of F test < 0.05 shows that the model is statistically significant at significance level 5% In addition, VIF coefficients of all factors are < implying that multi-collinearity does not influence much on regression results Regression analysis was conducted between TRUST and six independent variables (1) Trust Propensity (PROP), (2) Testimonials (TEST), (3) Online Purchasing Experience (EX), (4) Time Risks (TIME), (5) Financial Risks (FIN), (6) Product Risks (PRO) All regression coefficients (β) are statistically significant since Sig β < 5% There are three regression coefficients taking negative sign corresponding to risk factors that affect negatively TRUST All the six hypotheses were therefore accepted The research’s linear regression equation is as following: TRUST =β0 + β1 * PROP + β2 * TEST + β3 * EX β4 ATIME- β5 FIN- β6 PRO With R2 of 0.518 indicating that the independent variables in the regression model can explain 35 An Giang University Journal of Science – 2019, Vol 6, 26 – 38 Table Estimates of Coefficientsa Unstandardized Coefficients B Standardized Coefficients Std Error (Constant) 2.039 280 TIME -.122 037 FIN -.082 PROP Beta Collinearity Statistics t Sig Tolerance VIF 7.281 000 -.172 -3.263 001 874 1.144 038 -.113 -2.156 032 886 1.128 229 065 227 3.512 001 582 1.718 PRO -.161 037 -.229 -4.393 000 892 1.121 EX 280 046 352 6.069 000 722 1.385 TEST 175 059 193 2.958 003 571 1.751 a Dependent Variable: TRUST RESEARCH IMPLICATIONS can attract For this reason, it is essential for those who business on Facebook to invest in collecting valuable testimonials from their clients In addition to improving product’s quality, online sellers need to spend time taking care of their customers such as asking about how they feel about the products if they have any suggestions for increasing the product’s quality, or how to serve them better By talking to customers, businesses can both keep track of their demand and pick out valuable feedbacks to build online customer’s testimonials corner which is the best proof for a quality product Trust propensity influences positively and most strongly on customer’s trust People who have high trust propensity feel easy to trust in something they intend to buy Therefore, online shops are encouraged to observe meticulously in order to know their groups of customers who have a high trust propensity to their products or services In addition, online purchasing experience affects customers’ trust supportively when they shop on Facebook This result reminds online businesses enabling customers to approach online shopping process For instance, shop owners can simplify the purchasing steps, create more payment channels, and arrange the easy-to-shop appearance Once customers online transactions several times, they will get some certain experience and may become loyal customers of the stores on Facebook The research result also proves that financial risks influence negatively and the most sharply on customer’s trust Problems such as losing money, losing bank account information, or being charged exorbitantly mostly always disturb customers To avoid them, firstly, business managers need to disclose different types of payment such as by cash on delivery (COD), bank account, delivery companies, electronic money, or charging mobile phone cards Each group of customers will be suitable for each type of payment Secondly, opening various bank accounts enables customers Testimonials include purchasers’ feedbacks, comments, or suggestions about products or services that they used The better testimonials online businesses have, the more customers they 36 An Giang University Journal of Science – 2019, Vol 6, 26 – 38 to choose the one they have, therefore, they not have to pay any fees for a different bank Furthermore, all of the charges related to products should be listed down clearly to avoid misunderstanding when paying In the same way, the products should be checked considerately so that the customers not have to pay another fee to return or exchange products Last but not least, any information of customers must be secured absolutely researches will overcome these limitations and could focus on the differences between customer’s trust in purchasing on Facebook and other e-commerce websites REFERENCES Comscore (2012) Introduction of Online Video Measurement Service in Taiwan, Vietnam, Indonesia and the Philippines Retrieved from http://www.comscore.com/Insights/Press_ Releases/2012/8/comScore_Announc es_Introduction_of_Online_Video_Measurem ent_ Service_in_Taiwan_Vietnam _Indonesia_and_the_Philippines The second risk in online shopping is product risk including defected products, wrong size, wrong quantity, wrong color or products not meet enough characteristics and utilities as advertised Product risks reduce customers’ trust especially at the first time they deal with an online shop For this reason, shops on Facebook need to be truthful to advertise their products, not to blow up some features or functions that their products cannot fulfill Likewise, salespeople need to give useful advice and introduce the products in details to customers before setting up an order Coulter, K S & Coulter, R A (2002) Determinants of Trust in a Service Provider: The Moderating Role of Length of Relationship Journal of Services Marketing, 16, 35- 50 Dwyer, C., Hiltz, S R & Passerini, K (2007) Trust and Privacy Concern Within Social Networking Sites: A Comparison of Facebook and MySpace AMCIS 2007 proceedings, 339 Time risk is also specially noted since it affects negatively customer’s trust in online shopping Businesses on Facebook need to be professional in updating new products, answering customer’s questions, and shipping an order in order not to let customers wait for a long time Gefen, D (2000) E-commerce: the role of familiarity and trust International Journal of Management Science, 28, 725-37 Gerbing, D W., & Anderson, J C (1988) An updated paradigm for scale development incorporating unidimensionality and its assessment Journal of marketing research, 186-192 Nevertheless, the research has some unavoidable limitations Firstly, the sample size is not big enough for generalization Secondly, the questionnaires were delivered online, so the responders were not explained clearly some complicated questions Thirdly, the research surveyed only the customers who purchased on Facebook at least once and so it cannot compare to people who have never bought anything on Facebook or to people who buy online on other websites except Facebook Finally, the adjusted R2 is only 0.518 which indicates the appropriate level of the model is 51.8% In other words, there are some necessary variables which have not put in the model yet The author expects that further Harn, A C P., Khatibi, A & Ismail, H B (2006) E-Commerce: A Study on Online Shopping in Malaysia Journal Social Science, 13, 231-242 Hoang Trong & Chu Nguyen Mong Ngoc (2008) Research data analysis with SPSS Ho Chi Minh City: Hong 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Marketing Intelligence & Planning, 24, 746761 Tran Minh (2012) Factors influence on customer’s trust when purchasing online in Vietnam (Unpublished master thesis) University of Economics, Ho Chi Minh City McKnight, D.H & Chervany, N.L (2002) What trust means in e-commerce customer relationships: an interdisciplinary conceptual typology International Journal of Electronic Commerce, , 35–59 Vietnam E-Commerce and Information Technology Agency (2013) E-Commerce Report 2013 Vietnam: Ministry of Industry and Trade Vietnam Internet Network Information Centre (2013) Vietnamese Internet Resources Report 2013 Vietnam: Ministry of Information and Communications Nguyen Đinh Tho (2013) Research methodology in business Ho Chi Minh City: Labor and Society Publisher 38 ... survey the factors influencing customer’s online trust when purchasing on Facebook In Vietnam, the number of research on online trust has been increasing Tran Minh (2012) studied ? ?Factors affecting... perceived risk affect customer’s purchasing decisions strongly factors mentioned and repeated in most of the researches are Trust Propensity, Online Purchasing Experience, Testimonials, and Perceived... disposition to trust that influenced their trust in the venders In addition, another important research was conducted by Kim et al (2007) on “A trust- based consumer decision-making model in electronic