Structural Model for the Adoption of Online Advertising on Social ...

Structural Model for the Adoption of Online Advertising on Social Network in Vietnam 1

Thanh D. Nguyen1, Thi H. Cao1,2, and Nghia D. Tran1

HCMC University of Technology, 2 Saigon Technology University [email protected], [email protected], [email protected] users, only has about 0.04% enterprise users [38]. With the hurricane development of Web 2.0, OA is significantly changing in SN, according to StrongMail in 2012, marketing trend in 2013 that is renovating toward online. The trends of OA on SN in 2014 are video on Facebook, ads on Twitter and Google+... Hence, a potential OA on SN market are being crestfallen by VN enterprises.

Abstract—Social network is strongly expanding in all over the globe, it is being an indispensable part of the online world, so social network advertising is a potential market for the business propensity. Hence, researches on the adoption models of online advertising on social network are essential work. This study proposes a structural model of online advertising on social network adoption to overcome the limitations of previous study. The concepts in the model were analyzed by linear structural model. The research results illustrated that have the relationships between entertainment, irritation, credibility, and interactionsocial, attitude toward online advertising, and online advertising on social network adoption.

2010 96 95

93 95

97 97 79

Keywords—Adoption; structural model; online advertising; social network, Vietnam.

62 59

74 58 40

I. INTRODUCTION According to the Ministry of Information and Communications in 2013, Vietnam (VN) was ranked 18th among the world's top 20 Internet countries, and compared to countries, Asia and Southeast Asia, the VN’s rank was respectively 8th and 3rd with approximately 36% population use the Internet. The VN Government in 2012 had set a target for 2020 will be rated from 55% to 60% population use the Internet. Besides that, the revenue of the VN advertising market in 2012 was about $970 million, including online advertising (OA) roughly $60 million, inflating up to $100 million in 2013 [36]. According to VN Advertising Association in 2012, it is approximately 85% market share of advertising on television, followed by newspapers, only about 1% market share on OA, a relatively modest number.

52

57 56 40

32 35

50

57

36

20 17

23

Figure 1. The percentage of the users use online application Source: Kantar [15]

Up to now, several models of cognitive value and attitude toward OA have been studied by many authors (e.g., Brown & Staymen [3]; Ducoffe [9]...). Although there are many studies on Information Technology adoption (e.g. Davis [6], [7]; Venkatesh et al. [33], [34]; Pham et al. [27], Nguyen et al. [23], [24]…), and also OA adoption (e.g., Zeng et al. [40]; Soares et al. [29]; Kelly et al. [16]...), there are not many researches on OA on SN adoption, especially in a potential market as VN. Besides that, Nguyen et al. [25] had researched on the adoption of OA on SN in VN, the research results illustrated that the structural factors, namely entertainment, communication, irritation, credibility, and interaction-social affect to attitude toward OA; and attitude toward OA affect to OA on SN adoption. Notwithstanding, the study results are still limited, seeing the potential correlation relationships of the independent factors, such as irritation always contrast with credibility in OA, but the model did not show the relationships among these factors. On the other hand, the research did not provide the impact of independent factors on OA on SN adoption, and also did not explain beauteous parameters.

Up to 2012, it had got roughly 300 social networks (SN) in the world [39]. According to E-Marketer’s forecasting in 2011, the OA on SN revenue in the world would be about $10 billion in 2013, the revenue of the largest SN - Facebook is about $6.72 billion. Besides that, according to Divine in 2012, SN is new methods of the business marketing strategies in the world. According to Vinalink in 2012, VN has got 22 in 28 kinds of SN in the globe. Most of online users in VN use SN (the 1st ranking is news reading). The SN users rate up significantly in 2013 compared with 2011, it was followed by portal and e-mail users (Figure 1). However, this potential market has not been respected by enterprises. According to the top 100-SN in VN, the numbers of user have been ranked in order Facebook, Zing Me, Google+, Go, Yume... Although Facebook has approximately 12 million

c 978-1-4799-3080-7/14/$31.00 2014 IEEE

2011

38

II.

RESEARCH MODEL AND HYPOTHESIS

A. Theoretical Basis Overview Ducoffe [9] proposed model of cognitive value and attitude toward OA, the research had confirmed research of Brown & Staymen [3] about attitude toward advertising being the emotional response to advertising. Then, Brackett & Carr [2] inherited Ducoffe [9], and added 2 factors being reliability and demographics. Besides that, Sukpanich & Chen [32]; Cho & Hongsik [5] confirmed the interactions affect to cognitive value and attitude toward advertising. Next, Zhang & Wang [41] continued inheritance Ducoffe [9], and added interactive element. Recently, Soares et al. [29] also proposed SN role in the interactive from marketing to social, Chandra et al. [4] applied the model of Ducoffe [9], Zeng et al. [40]; Kelly et al. [16] referenced Cho & Hongsik [5] to study about attitude toward OA on SN. Some theories of Information Technology (IT) adoption such as Theory of Rational Action (TRA) [1], [12] was studied from the perspective of social psychology to identify elements of the trend-conscious behavior. Technology Acceptance Model (TAM) [6], [7] based on TRA to establish relationships among variables to explain the user behavior on the acceptance and use new technology. Unified Theory of Acceptance and Use of Technology (UTAUT) developed by Venkatesh et al. [33], [34] to the acceptance and use behavior new IT, this theory has been referenced in most of research on the acceptance and use IT. Most of related research models had studied about the technology adoption in general. Besides that, there are also extensive researches on attitude toward advertising and OA. However, there are not many studies about OA on SN adoption. On the other hand, the relevant researches have not shown adequate all factors that affect SN adoption, the relationships of interrelated factors, not only in VN and also in the globe. Thus, the study about the structural model for the OA on SN adoption is very essential work. B. Model and methodology Based on the theoretical models and previous related research. These components in the structural model for the OA on SN adoption are proposed as follows: (1) Habit (HA) is the extent in which people having the inclination to perform the behavior automatically. According to Venkatesh et al. [34], the role of habit is described as the different basic process that affects to technology use. (2) Entertainment (EN) is the emotional level that gives the SN users to see the ad. According to McQuail [21], entertainment denotes the ability to meet consumer demand for recreational, aesthetic satisfaction, emotional liberation... Ducoffe [9] also found that accountability position in OA has a positive impact on the consumer perceived and attitude. (3) Credibility (CR) is the trust level of the users for OA on SN. MacKenzie & Lutz [19] suggested that the trust level of consumer in the advertisement message, and the trust in the origin and poster of advertisement influence on OA. (4) Irritation (IR) is the

discomfort level that OA gives the SN users. According to Ducoffe [9], advertising caused irritation, offensive or outrageous, so consumers often feel the effects of unwanted and annoyed from this advertisement. Irritation lessens the effectiveness of advertising, causing a feeling of annoyance for consumers. (5) Interaction (IN) is the level of interplay between users and different types of OA on SN Sukpanich & Chen [32] provided the interactive confirmation with 3 groups: “human-human”, “human-message” and “humancomputer”. For OA disunited into 3 types of Interaction: “computer”, “content” and “human”. Thus, these studies showed that the interaction factor affect to the user attitude toward advertising. (6) Social role (SO) is the level of impact that society gives users, which affect to attitude toward OA. According to Soley & Reid [30], consumer perceptive reflection is influenced by society and culture of advertising. Korgaonkar et al. [18] noted that OA is as well as other advertising forms, making the message with the high interaction with the social community, from influential individuals in social that strongly impact to attitude of advertising users. (7) Attitude toward OA (ATA) is a positive or negative attitude in the subjective perspective of SN users. According to Mehta [22], attitude toward advertising affect on the success of any form of public advertising, and has ability to predict the tendency to accept or not usage. (8) OA on SN adoption (ASA) is acceptance of OA on SN or intention to buy advertised products on SN in the future. According to MacInnis & Stayman [20], the purchasing intention is customer reaction with productive incentives to create react positively or negatively to advertising, and the level of consumer intention to purchase a product due to the positive or negative attitude advertising. Research hypotheses are formulated according to 4 groups: (1) Relationships among the independent factors: H1a: There are 2-dimensional correlation with inverse proportions between HA, EN, CR, IN elements and IR element. H1b: There are 2-dimensional correlation with the proportions between HA, EN, CR, IN elements and SO element. (2) Effects on attitude toward OA: H2a: EN has a positive impact on ATA. H2b: IR has a negative impact on ATA. H2c: CR has a positive impact on ATA. H2d: IN has a positive impact on ATA. H2e: SO has a positive impact on ATA. (3) Effects on OA on SN adoption: H3a: HA has a positive impact on ASA. H3b: EN has a positive impact on ASA. H3c: IN has a positive impact on ASA. H3d: SO has a positive impact on ASA. (4) Attitude toward OA affects OA on SN adoption: H4: ATA has a positive impact on ASA.

2014 International Conference on Advances in Computing,Communications and Informatics (ICACCI)

39

In order to test the model and all hypotheses which were proposed, information was collected using a structured survey with a set of all scales referring to the different variables identified in the model (see Table II). According to the literature review, data were collected by a survey using convenient sampling. The questionnaires were delivered using Google Docs, E-mail, SN, forums… and sent directly print hard copies to respondents who have used SN in Vietnam. A total of 320 respondents was obtained, 280 was finally usable (40 invalid respondents). All scales were scored on a 7-point Likert scale anchored with strongly disagree (1) to strongly agree (7), with 31 indicators. The data were then analyzed by Structural Equation Modeling (SEM) techniques with SPSS and AMOS softwares.

H1a’: There are 2-dimensional correlation with inverse proportions between HA, EN, CR, IN-SO elements and IR element. H1b’: There are 2-dimensional correlation with the proportions between HA, EN, CR elements and IN-SO element. The hypotheses H2d, H2e, H3c, and H3d are restated: H2d-e: SO-IN has a positive impact on ATA. H3c-d: SO-IN has a positive impact on ASA. TABLE I.

ALL VARIABLES IN F ACTOR ANALYSIS

Observed variables

RESEARCH RESULTS

Consequently, the hypotheses H1a and H1b are restated:

40

1. IN-SO

Sign in SN for product information Help to reach product easier Click into product links Knowing trends from many sectors Awareness high level about product Be interested in using the product What similar others buying Products with individual characteristics

0.757 0.754 0.735 0.704 0.661 0.660 0.570 0.560

0.790 0.765 0.750 0.749 0.686 0.683 0.664 0.651

0.776 0.770 0.726 0.722

0.884 0.879 0.816 0.800

0.814 0.799 0.791 0.781

0.841 0.818 0.760 0.609

2. EN

Cronbach alpha = 0.921; Average Variance Extracted = 0.715

EN2 EN1 EN4 EN3

OA on SN is pleasing OA on SN is fun to use OA on SN is enjoyable OA on SN is is exciting

3. IR


IR2 IR1 IR3 IR4

OA on SN is annoying OA on SN is irritating OA on SN is confusing OA on SN is deceptive

4. CR


CR2 CR1 CR4 CR3

5. HA

B. Exploratory and Confirmatory Factor Analysis After eliminating one item that is ATA4 of attitude toward OA (ATA) element in reliability analysis (Cronbach alpha) due to the correlation-item of ATA factor < 0.60. The composite reliability of constructs ranges from 0.784 to 0.921. Next, eliminating IN6 item of interaction (IN) element in the 1st Exploratory Factor Analysis (EFA) due to the factor loading < 0.50. Then, the 2nd EFA with 26 observed variables which are grouped according to each factor as proposing model. However, there is a factor has been loaded from the observed variations of the IN and social role (SO) element, the authors propose a new name for this factor called “Interactionsocial” (IN-SO). For this reason, IN-SO component means that the interaction in terms of social to attitude toward OA. As a result, the coefficient Cronbach alpha of IN-SO is 0.902.

IN4 IN2 IN3 SO1 IN1 SO3 SO2 SO4

HA1 HA3 HA2

OA on SN is credible 0.823 0.838 OA on SN is believable 0.811 0.786 Use OA on SN as a reference for purchasing 0.741 0.784 OA on SN is trustworthy 0.551 0.515 Cronbach alpha = 0.834; Average Variance Extracted = 0.731 Using SN has become a habit 0.798 0.831 Be addicted to use SN 0.738 0.814 Must use SN 0.700 0.667


6. ATA

A. Data Characteristics Gender: there are considerable difference with 59% male and 41% female. Age: 18-23 age group is the majority - 39%; 24-29 age group accounted for 29%, the other age groups have a relatively low rate. This shows that most of the respondents are young people, under 30 years-old. Education: there are nearly 60% of respondents in university degree, about 21% of respondents in graduate degree, and percentage of the others is lower. Therefore, the majority of survey participants have the relatively higher education. Job Position: as regards the staff, student, low level management, and middle level management is by far the highest at nearly 39%, followed by the latter at 32%, 15% and 11% respectively. Experience: 1-5 years amounted to the highest percentage - 41%; 6-10 years is 21%; 17% of respondents do not have experience. In general, respondents have little experience who interest OA on SN. Statistics from the survey results show that, in VN, the percentage of Facebook users account for the majority of the 73%; followed by Zing Me and Google+ at 10% and 9% respectively... These rates are consistent with the usage situation and the popularity of SN in Vietnam and the world.


ATA2 Like to look at OA on the Internet ATA3 Like to look at OA on SN ATA1 Important part in my buying decision

7. ASA

III.

Factor loading EFA CFA

ASA1 Intend to research about OA in the future ASA3 Will look OA on SN in future ASA2 Share OA information for the friends

0.709 0.702 0.698

0.802 0.790 0.537

0.862 0.858 0.857

0.779 0.713 0.642


On the one hand, EFA results are presented in Table I. On the other hand, coefficient Kaiser Meyer Olkin (KMO) is 0.918 (significant at p = 0.000), so it shows that EFA of the independent components being appropriate. The Total Variance Extracted (VA) is 69.12% should explain roughly 69% of the data variance. Besides that, ASA’s coefficient KMO is 0.727 (p = 0.000), so the ASA’s VA is 78.36% should well explain the data variance.


Hence, after EFA, the final measurement scales of the study model include 7 components: IN-SO, EN, IR, CR, HA, ATA, and ASA with 29 observed variables. Confirmatory Factor Analysis (CFA) are conducted to assess and refine the measurement scales. The CFA on the overall measurement model yields the following measures: Chi-square (F2)/dF = 2.015; TLI = 0.914; GFI = 0.882; CFI = 0.925; RMSEA = 0.060 (p = 0.000). The CFA loading of all items ranges from 0.515 to 0.838. The Average VA of constructs varying between 0.506 and 0.731 (> 0.50) which are accomplished scales. Therefore, the measurement scales for all constructs are satisfactory. C. Structural Model The structural model estimation was then conducted using ML estimation. The indexes for the model showed adequate fit with F2/dF = 1.637; TLI = 0.946; GFI = 0.903; CFI = 0.954; RMSEA = 0.048 (p = 0.000). The standardized path coefficients are presented in Table II. Interestingly, IR has the relationships with HA, EN, CR, and IN-SO where γ coefficients are –0.222; –0.638; –0.327, and –0.330 (p < 0.001) respectively. Thus, there are 2dimensional correlation with inverse proportions between HA, EN, CR, IN-SO elements and IR element, and so the hypothesis H1a’ is supported. On the other hand, HA has the correlative relationships with CR, IN-SO, and EN with γ coefficients are 0.707; 0.441, and 0.462 (p < 0.001) respectively; EN has the correlative relationships with IN-SO and CR with γ coefficients are 0.886 and 0.728 (p < 0.001); CR has a correlative relationship with IN-SO with coefficient γ is 0.548 (p < 0.001). Hence, there are 2-dimensional correlation with the proportions between HA, EN, CR elements and IN-SO element, and so the hypothesis H1b’ is supported. As the results, support the positive effect of SN and IN-SO on ATA with γ coefficients = 0.339 and 0.362 (p < 0.001), that support H2a and H2d-e. In other side, IR and CR have the effect on ATA with γ coefficients = –0.082 (p = 0.375) and 0.081 (p = 0.190), but the path from IR and CR to ATA are nonsignificant at p = 0.05, hence, the relationships of the concepts are not achievable as the expected about theoretical, and so the hypotheses H2b and H2c are not supported. Besides that, EN and IN-SO have the positive effect on ASA with γ = 0.208 (p = 0.007) and 0.194 (p = 0.038), which in turn H3b and H3c-d are supported. Although HA has an impact on ASA with γ = –0.154 (p = 0.027), but γ < 0, so HA has a negative effect on ASA, thus, the hypothesis H3a is not supported. Finally, ATA has strongly positive effect on ASA with γ = 0.676 (p < 0.001), which supports H4. In addition, the coefficient determination (R2) of the ATA and ASA are 0.603 and 0.858, so all variables should should explain approximately 60% of attitude toward OA and 86% of OA on SN adoption.

TABLE II. H

1

2

H1a’

H1b’

ANALYSIS OF HYPOTHESIZED RELATIONSHIPS

Relationships

Estimate

HA l IR EN l IR

–0.222

***

–0.638

***

CR l IR IN-SO l IR

–0.327

***

–0.330

***

HA l CR HA l IN-SO

0.707

***

0.441

***

HA l EN EN l IN-SO

0.462

***

0.886

***

EN l CR CR l IN-SO

0.728

***

0.548

***

3

H2a

EN

4

H2b

IR

5

H2c

CR

6

H2d-e

7

H3a

HA

8

H3b

EN

9

H3c-d

10

H4

IN-SO

IN-SO ATA

o o o o o o o o

p-value

Result

Supported

Supported

ATA

0.399

***

Supported

ATA

–0.082

0.375

Rejected

ATA

0.081

0.190

Rejected

ATA

0.362

***

Supported

ASA

–0.154

0.027

Rejected

ASA

0.208

0.007

Supported

ASA

0.194

0.038

Supported

ASA

0.676

***

Supported *** p < 0.001

D. Bootstrap Analysis Bootstrap method is used to test the model estimates with the quantity of reduplicate samples [28]. In this research, the quantity of repeat samples is N = n*2 = 560. The Bootstrap estimate result is calculated with difference (CR) that are illustrated in Table III, with |CR| < 2 so the difference is very minor and not statistically significant (p > 0.05). Hence, the model estimates in this study are reliable. TABLE III. Relationships

BOOTSTRAP ANALYSIS RESULT ML

Bootstrap Bias

|CR|

EN o ATA

0.399

0.097

0.394

–0.005

1.250

2

IR o ATA

–0.082

0.119

–0.088

–0.006

1.200

3

CR o ATA

0.081

0.076

0.086

0.005

1.667

4

IN-SO o ATA

0.362

0.101

0.362

0.000

0.000

5

HA o ASA

–0.154

0.083

–0.161

–0.007

1.750

6

EN o ASA

0.208

0.112

0.199

–0.009

1.800

7

IN-SO o ASA

0.194

0.104

0.196

0.002

0.500

8

ATA o ASA

0.676

0.161

0.689

0.013

1.857

1

SE

Mean

Generally, the analysis results showed that the hypotheses H1a’ and H1b’ are supported by all independent factors have 2dimensional correlation, according to which, HA, EN, CR, and IN-SO have correlation through each others in positive and have correlation with IR in negative. In addition, the research results also provided that 5 hypotheses (H2a, H2d-e, H3b, H3d-c, and H4) are supported, and 3 hypotheses (H2b, H2c, and H3a) are not supported. In summary, Figure. 2 illustrates the adjusted model for online advertising on social network


41

adoption, including the presentation of all paths of the model and also all hypotheses (non-significant paths appear as dashed arrows).

Habit H3a Entertainment

H3b H2a

H1b’

H1a’

H2b

Irritation

(ATA)

H4

(ASA)

H2c H2d-e

Credibility

H3c-d

Interaction-Social

Figure 2. Online Advertising on Social Network Adoption - Adjusted Model

IV.

RESULT DISCUSSIONS

The analysis results illustrated that these factors, namely HA, EN, CR, IN-SO, and IR have 2-way relationships with each other, the relationships have contributed to the explanation of attitude toward OA and OA on SN adoption with high compared previous relevant researches. Besides that, ATA is strongly affected by EN with coefficient γ is 0.399, the impact value better than the studies of Ducoffe [9] (γ = 0.263); Chandra et al. [4] (γ = 0.001) and not statistically significant (p = 0.979), which indicates the SN users more interested in entertaining of OA on SN in VN. On the other hand, EN also affects ASA (γ = 0.208), while previous studies had not shown this relationship. This result shows that in OA on SN, entertaining of OA samples has an important role. Meanwhile, IN-SO affects ATA (γ = 0.362), so the interaction-social has considerable influence on attitude toward OA. In addition, INSO also shows to be linked to ASA. According to research findings, CR and IR can not affect much ATA, and HA has nonsignificant impact to ASA, shown by the concerning hypotheses are not supported. This finding demonstrates that consumers are not concerned about the irritation, credibility, and habit of OA on SN. In fact, OA on SN in VN has not been interested much by the enterprises, a part of the causes belong to business leaders who do not participate much SN that should not be precautionary how to use this information channel. Besides that, it does not have training center specializing in the SN in VN, so advertising strategists do not have in-depth knowledge in this field, and also with concerns about the high risks according to the users [35]. More than that, in the data collection process, most respondents agreed that the irritation of OA on SN causing the consumers have a negative attitude toward OA, there should be measures to minimize the irritation of OA for the users. Finally, ATA affect ASA with a high coefficient γ (0.676), which evidences that, if user has a positive attitude toward OA, they will almost accept

42

OA on SN. These results have shown that the research model being consistent in the context in VN. Research results can contribute to the theories of OA on SN adoption, not only in Vietnam but also in the world. Although there are 3 hypotheses were rejected, not for the reason that the research model reduces the explaining about OA on SN adoption. Because of the model explanatory is preeminent on attitude toward OA (R2 = 0.603) and OA on SN (R2 = 0.858). On the other hand, the research results also externalize the relationships of elements that in the study of Nguyen et al. [25] had not manifested. Therefore, the research model not only contributes to the knowledge basis for scientific researches on the adoption of OA on SN, but also accommodates the information for businesses in the planning of advertising strategies in VN. V.

CONCLUSIONS

The research results accommodates that all scales of independent variables, attitude toward OA, and OA on SN stabilize reliability. Exploratory factor analysis provides 4 factors called habit, entertainment, credibility, and irritation are extracted in accordance with the proposed model. Interaction and social role elements are extracted into 1 factor and named interaction-social, so 13 initial hypotheses are reduced to 11 hypotheses (hypotheses H2d and H2e reset to H2d-e; hypotheses H3c and H3d reset to H2c-d). Confirmatory factor analysis indicates that measurement scales for all variables are satisfactory, the model scales achieve distinguishing worth. The linear structural model shows that these factors, namely entertainment, habit, credibility, and the irritation, and interaction-social have relationships through mutual; attitude toward OA is directly influenced by entertainment and interaction-social, and not significantly affected by the credibility and irritation; entertainment, interaction-social, and attitude toward OA have direct impact on OA of SN adoption. Although only 8 out of 11 proposed hypotheses of the research model are supported, research findings also explain the relatively consummate attitude toward OA and OA on SN adoption, the parameters in verification of the model are very high. Interestingly, the Bootstrap analysis result shows that the estimate of study model can be reliability. Therefore, the study has shown the correlation between the elements and OA on SN adoption of the structural model in VN, which the study of Nguyen et al. [25] could not achieve. Although structural model for the adoption of OA on SN is not achieved the expectations set out yet, which can assess the impact of each factor to OA on SN adoption at different levels. Besides that, the research result is also the knowledge basis of scientific researches on the adoption of OA on SN. However, research findings are still some limitations, so in subsequent study, the scopes will be expanded, the scales will be revised more appropriate than with the development situation of OA on SN in VN and also the world, new relationships among the elements will be added in the study model.


REFERENCES [1] [2]

[3]

[4]

[5] [6]

[7]

[8]

[9]

Ajzen I., Fishbein M., Understanding Attitudes and Predicting Social Behavior, Englewood cliffs, NJ: Prentice Hall, 1980. Brackett L.K., Carr B.N., “Cyberspace Advertising vs. other Media: Consumer vs. Mature Student Attitudes,” Journal of Advertising Research, vol. 41 (5), pp. 23-33, 2001. Brown S.P., Stayman D.M., “Antecedents and Consequences of Attitude Toward the Ad: A Meta-analysis,” The Journal of Consumer Research, vol. 19, pp. 34-51, 1992. Chandra B., Goswami S., Chouhan V., “Investigating Attitude Towards Online Advertising on Social Media - An Empirical Study,” Management Insight, vol. 8 (1), pp. 1-12, 2013. Cho C.H., Hongsik J.C., “Why do People Avoid Advertising on the Internet?,” Journal of Advertising, vol. 33 (4), pp. 89-97, 2004. Davis F.D., “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Quarterly, vol. 13 (3), pp. 319-340, 1989. Davis F.D., “User Acceptance of Information Technology: System Characteristics, User Perceptions and Behavioural Impacts,” International Journal of Man-Machine, vol. 38, pp. 475-487, 1993. Divine M., “Social Networking: Vietnamese Enterprise are being indifferent,” Workshop on the Role of Social Network in the Enterprise, French Cultural Centre, Hanoi, 2012. Ducoffe R., “Advertising Value and Advertising on the Web,” Journal of Advertising Research, vol. 36 (5), pp. 21-35, 1996.

[10] E-Marketer, “Market Research on Digital Media, Internet Marketing, Advertising & Marketing on Facebook in the World,” 2011. http://www.emarketer.com [11] Eze C.U., Lee H.C., “Consumers Attitude Towards Advertising,” International Journal of Business and Management, vol. 7 (13), pp. 94108, 2012. [12] Fishbein M., Ajzen I., Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research, Addison-Wesley, 1975. [13] Haghirian P., Madlberger M., “Consumer Attitude Toward Advertising via Mobile Devices - An Empirical Investigation among Austrian Users,” ECIS 2005 Proceedings, Regensburg, Germany, 2005. [14] Hoffman D.L., Novak T.P., “Marketing in Hypermedia Computer Mediated Environments: Conceptual Foundation,” Journal of Marketing, vol. 60 (3), pp. 50-68, 1996. [15] Kantar Media Vietnam, “Net Insights Report 2011,” 2012. http://www.slideshare.net [16] Kelly L., Kerr G., Drennan J., “Avoidance of Advertising in Social Networking Sites: The Teenage Perspective,” Journal of Interactive Advertising, vol. 10 (2), pp. 16-27, 2010. [17] Ko H., Cho C.H., Roberts M.S., “Internet Users and Gratifications: A Structural Equation Model of Interactive Advertising,” Journal of Advertising, vol. 34 (2), pp. 57-70, 2005. [18] Korgaonkar P., Silverblatt R., Oleary B., “Web Advertising and Hispanics,” Journal of Consumer Marketing, vol. 18 (2), pp. 134-152, 2001. [19] MacKenzie, S.B., Lutz, R.J., “An Empirical Examination of the Structural Antecedents of Attitude Toward the Ad in an Advertising Pretesting Context,” The Journal of Marketing, pp. 48-65, 1989. [20] MacInnis D.J., Stayman D.M., “Focal and Emotional Integration: Constructs, Measures, and Preliminary Evidence,” Journal of Advertising, vol. 22 (4), pp. 51-66, 1993. [21] McQuail D., Mass Communication Theory: An Introduction, Sage Publication, London, 1983. [22] Mehta A., “Advertising Attitudes and Advertising Effectiveness,” Journal of Advertising Research, vol. 40 (3), pp. 67-71, 2000. [23] Nguyen T.D., Nguyen D.T., Cao T.H. “Acceptance and Use of Information System: E-learning based on Cloud Computing in Vietnam,” Information and Communication Technology, pp. 139-149, Springer Berlin Heidelberg, 2014.

[24] Nguyen T.D., Nguyen T.M., Pham Q.T., Misra, S. “Acceptance and Use of E-Learning Based on Cloud Computing: The Role of Consumer Innovativeness,” Computational Science and Its Applications, pp. 159174, Springer International Publishing, 2014. [25] Nguyen T.D, Tran N.D., Pham C.M. “Proposing the Online Advertising on Social Network Adoption Model in Vietnam,” Journal of Development Science and Technology, vol. 16 (Q3), pp. 5-18, 2013. [26] Ministry of Information and Communications, The utilization of the Internet in Vietnam, 15 years of Internet activity in Vietnam, Hanoi, 2013. [27] Pham L., Cao N.Y., Nguyen T.D., Tran P.T. “Structural Models for EBanking Adoption in Vietnam,” International Journal of Enterprise Information Systems, vol. 9 (1), pp. 31-48, 2013. [28] Schumacker, R.E., Lomax, R.G., A Beginner’s Guide to Structural Equation Modeling, Lawrence Erlbaum, London, 2006. [29] Soares A.M., Pinho J.C., Nobre H., “From Social to Marketing Interactions: The Role of Social Networks,” Journal of Transnational Management, vol. 17 (1), pp. 45-62, 2012. [30] Soley L.C., Reid L.N., “Satisfaction with the Informational Value of Magazine and Television Advertising,” Journal of Advertising, vol. 12 (3), pp. 27-31, 1983. [31] Strong Mail System, “2013 Marketing Trends Survey,” 2012. http://www.strongmail.com [32] Sukpanich N., Chen L., “Interactivity as the Driving Force behind eCommerce,” AMCIS 2000 Proceedings, p. 244, Long Beach, CA, USA, 2000. [33] Venkatesh V., Morris M., Davis F., “User Acceptance of Information Technology: Toward a Unified View,” MIS Quarterly, vol. 27, pp. 425478, 2003. [34] Venkatesh V., Thong J.Y., Xin X., “Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology,” MIS Quarterly, vol. 36 (1), pp. 157-178, 2012. [35] Vinalink Media, “Top 100 social networks in Vietnam,” Workshop on the Role of Social Network in the Enterprise, French Cultural Centre, Hanoi, 2012. [36] Vietnam Advertising Association, “Overview of the Advertising Market in Vietnam,” Vietnam Advertising Association Conference, Hanoi, 2012. [37] Vietnam Government, “Planning and Developing of National Telecom up to 2020,” Decision 32/2012/QD-TTg, Hanoi, 2012. [38] We Are Social, “Situation of Social Network in the World,” 2011 http://wearesocial.net [39] White D.S., “All Things Marketing, Social Media Growth from 2006 to 2012,” 2013. http://dstevenwhite.com [40] Zeng F., Huang L., Dou W., “Social Factors in User Perceptions and Responses to Advertising in Online Social Networking Communities,” Journal of Interactive Advertising, vol. 10 (1), pp. 1-13, 2009. [41] Zhang P., Wang C., “An Empirical Study on Consumer’s Perceived Value and Attitude Toward Advertising,” Global Information Technology and Management World Conference, Anchorage, AK, USA, 2005.


43