Chia-Chun Wu 2* Assistant Professor Dept. of Information Management I-Shou University Kaohsiung, Taiwan






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Vol. 4, No.5, October 2014

Utilizing the Technology Acceptance Model to

Explore the Effects of Mobile Advertising on

Purchase Intention

Lisa Y. Chen1 Associate Professor Dept. of Information Management

I-Shou University Kaohsiung, Taiwan

Chia-Chun Wu2* Assistant Professor Dept. of Information Management

I-Shou University Kaohsiung, Taiwan

Mr. Ti-Lung Li3

Dept. of Information Management I-Shou University Kaohsiung, Taiwan

Abstract—The recent and rapidly expanding capabilities of

mobile devices present retailers with both challenges and opportunities. Mobile devices offer an unparalleled depth of potential interaction with consumers, enabling opportunities to increase sales and expand markets, by motivating retailers to integrate mobile solutions into their consumer-engagement strategies. This study identifies some key determinants of consumer attitudes related to mobile advertising and consumer purchase intentions, offering insights into the successful adoption of mobile advertising. This study investigated some of the influencing factors of consumer behaviors related to mobile advertising, such as perceived usefulness, perceived ease of use and the influence on purchasing intentions generated by mobile advertising. The technology acceptance model (TAM) was used for this research. A self-administered questionnaire was also used as a quantitative evaluation method for data collection. Correlation and multiple regression analyses were conducted to test the proposed model and hypotheses, utilizing a sample of 187 Taiwanese consumers. The results revealed that the interactions of mobile advertising have a positive influence on perceived usefulness and the perceived ease of use. Additionally, the perceived usefulness and the perceived ease of use of mobile advertising had positive influence on the attitudes toward mobile advertising. The attitudes of mobile advertising also had a positive influence on the consumers’ product purchasing intention. Some of the limitations of this study and directions for future research are also discussed.

Keywords-Mobile advertising; technology acceptance model; mobile advertising attitude; purchase intention


As consumers increasingly use their mobile devices to navigate, inform, and engage in real-time messaging, mobile advertising is becoming a proven channel for driving both brand engagement/interaction and response to effectively reach target markets. A successful mobile advertising campaign requires an integrated mobile marketing strategy, spanning promotion, sales, and customer service. A series of standalone advertisements on small screens is not adequate.

The advancement of mobile communication technologies has enabled a meteoric rise in the new medium of mobile advertising (Bakar & Bidin, 2014). Mobile communications provides information and services between individuals and corporations, enabling wireless network surfing to view real-time advertising messages and share such messages with others in an easy to use and highly interactive environment (Yang et al., 2013).

This study adopts TAM as the research model and, from the four perspectives of “Information”, “Interaction”, “Perceived Usefulness” and “Perceived Ease of Use”, analyzes the impact on mobile user purchase intention. This study also discusses the relevance and the causal relationship between the mobile advertising content and the interaction provided by mobile advertising service providers, and discusses, also, user attitudes toward mobile advertising and purchase intention. The aim of this study is to provide mobile advertising service providers with some guidance and suggestions for overall marketing direction and for service development strategies for launching mobile advertising campaigns.


A. Definition Mobile Advertising

Mobile advertising refers to advertising messages that appear on wireless devices. The Wireless Advertising Association (WAA) states that “when messages are sent by means of a non-fixed network to wireless communication devices such as a cell phone or PDA to achieve an advertisement push effect”, that this can be called mobile advertising. However, with the progress in wireless devices, the Short Message Service (SMS) is extending its multimedia support capabilities, by integrating images, sound, animation and text, into the Multimedia Messaging Service (MMS). MMS is, therefore, able to send and receive messages that are made up of text, sound, images and video to mobile phones that support the service. In addition, the Carat Interactive Company has, also, divided mobile advertising according to the


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transmission mode of either Push or Pull (Leppäniemi et al., 2005). Push actively sends messages to wireless users, and Pull displays ads based on web browsing activity.

The biggest advantage of mobile advertising relates to the “personalized”, “localized”, and “real-time” environment that is created. Business Insider (2014) pointed out that mobile advertising is growing rapidly and global mobile advertising spend is expected to grow with an average of 26% each year over the next five years.

Several major reasons why mobile advertising will grow and thrive via personalized mediums, direct responses, and interactive communications. These mechanisms attract younger groups, one-to-many communications, (opt-in), and positioning services, all of which find expression in mobile advertising’s “Environmental Interaction” function. Interactivity was defined as a message receiver’s feedback to message content and message source. Interactivity, therefore, compared to research on traditional and online advertising, focuses on mobile advertising and the “Interaction with the Media Environment” (McMillan, 1999).

B. Technology Acceptance Model

The Technology Acceptance Model (TAM) is the result of modifications by Davis et al. (1989) to the Theory of Reasoned Action (TRA) (Fishbein & Ajzen, 1975; Ajzen, 1988) and the Theory of Planned Behavior (TPB) (Ajzen, 1985). Other researchers Lee, et al. (2006), Hongwei et al. (2012) and Peslak et al. (2010) have addressed customer perceptions of mobile advertising, utilizing different models, but not from the approach of this study.

This study, with Davis et al. (1989)’s Technology Acceptance Model (see Fig. 1), first discusses the basic framework then extends that discussion to the Technology Acceptance Model II, which was re-proposed by Venkatesh and Davis in 2000 in order to cover the constructs “Perceived Usefulness” and “Intention to Use”. In 2008, Venkatesh and Bala further proposed the Technology Acceptance Model III, which introduced two new perceptions into Davis’ Technology Acceptance Model I: “Perceived Usefulness” (PU) and “Perceived Ease of Use” (PEOU).

*** Insert Fig. 1 Here ***

After modification, Venktesh’s Technology Acceptance Model II (see fig. 2) integrates two major key items: Social Influence Process (Subjective Norm, Spontaneity, and Impression) and Perception Promoting Process (Task Relevance, Output Quality, Outcome Accountability, and Perceived Ease of Use).

*** Insert Fig. 2 Here ***

After modification, the important conclusions of the Technology Acceptance Model II are as follows: 1. The relation between the Subjective Norm and Intention is adjusted by Experience and Spontaneity, and that only in mandatory usage and early experience can Subjective Norm significantly and directly affect Intention. 2. The relation between Subjective Norm and Usefulness is significantly adjusted by Experience,

but Impression directly affects Usefulness, instead of being adjusted by Experience. 3. Perceived Usefulness is subject to significant influence by Task Relevance, Output Quality and Outcome Accountability.

Venkatesh & Bala’s (2008) Technology Acceptance Model III (see fig. 3) includes two constructs: Personal Anchor and System Adjustment, and suggests that Experience and Voluntariness are significant disturbance variables. In addition, the variable Subjective Norm, which is not discussed in the original Technology Acceptance Model, is taken into consideration in the Technology Acceptance Model II and the Technology Acceptance Model III to discuss its impact on the use of new information technology. The conclusion is that the Subjective Norm has an influence on Intention to Use, Perceived Usefulness and Image.

*** Insert Fig. 3 Here ***

Wallace & Sheetz (2013) studied the model that is based on the technology acceptance model and operationalized the perceived usefulness construct according to the desirable properties of software measures. Their results suggested that both the perceived ease of use and perceived usefulness of a software measure can increase the likelihood of software measure use.

The perceived usefulness of a software measure can be measured by an assessment of the measure’s applicability throughout the life cycle, dependence on a particular programming language, ability to prescribe solutions or actions, and the validity of the software measure. In addition, the perceived ease of use of the software measure can also influence the perceptions of the measure's usefulness.

Lee & Lehto (2013) examined their study that was framed using the technology acceptance model to identify determinants affecting behavioral intention to use YouTube. Their conceptual framework included two proximal antecedents of behavioral intention as proposed by the TAM- perceived usefulness and perceived ease of use. Overall their findings suggested that YouTube may augment its function as a common channel for procedural learning and instruction.


This section describes the research method of this study and develops the research hypotheses, utilizing the variables from the section 2 literature review. The research framework is established based on those variables and operational definitions, and then, using the questionnaire as the research tool, empirical data was collected to test the research hypotheses. The four parts consisting of the Research Framework, Research Hypotheses, Research Design, as well as, the Data Statistics and Analysis Method are described as follows.

A. Research Framework and Hypotheses

As discussed in the section 2 literature review, this study adopted the technology acceptance model (TAM) proposed by Davis et al. (1989) as the basic theoretical framework (see fig. 4) to discuss whether “Information” and “Interaction” of


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mobile advertising will, through “Perceived Usefulness” and “Perceived Ease of Use”, affect Advertising Attitude.

*** Insert Fig. 4 Here ***

The TAM was adopted as the basic theory to explore the relationships between information, interaction, users’ perceived usefulness, perceived ease of use, and advertising attitude. Further, this study examined the relationships between the advertising attitudes and purchase intentions. The research hypotheses proposed are as follows:

H1a: Information of mobile advertising has a positive influence on perceived usefulness.

H1b: Information of mobile advertising has a positive influence on perceived ease of use.

H2a: Interaction of mobile advertising has a positive influence on perceived usefulness.

H2b: Interaction of mobile advertising has a positive influence on perceived ease of use.

H3: Perceived usefulness has a positive influence on advertising attitude.

H4: Perceived ease of use has a positive influence on advertising attitude.

H5: Advertising attitude has a positive influence on purchase intention.

B. Operationalization of Variables and Measurement

The questionnaire used in this study was adopted from previous studies and is assumed to be more reliable and persuasive than the researcher’s self-developed scales (Rudestam & Newton, 1995). The below shows the research variables and their operational definitions:

Information of mobile advertising is defined as accuracy of information provided by mobile advertising, and evaluating the correctness and real-timeliness of mobile advertising’s content (Bailey & Pearson, 1983; Doll & Torkzadeh, 1988; Zeithaml et al., 2002; Varnali et al., 2012). Interaction of mobile advertising is defined as the users’ autonomous right to use mobile advertising in mobile environment and the frequency of interaction with other users (McMillan & Hwang, 2002; Liang & Mackey, 2011).

Perceived usefulness is defined as the users’ feeling of the usefulness and efficiency of the purchase of mobile-advertising products through using the mobile advertising’s information and interaction. Perceived ease of use is defined as the degree of effort and proficiency required of the users to use mobile advertising (Davis, 1989; Suki & Suki, 2011). Advertising attitude is defined as the users’ reaction of identity (identification or disidentification) through mobile advertising (Bauer et al., 2005; Argyriou & Melewar, 2011). Purchase intention is defined as evaluating the intensity of the users’ willingness to buy the commodities marketed by mobile advertising and whether they prefer to buy such commodities (Dodds, 1991; Bian & Forsythe, 2012).

C. Data Statistics and Analysis Method

This study adopts average Taiwanese consumers as questionnaire respondents, who will, according to their own perceived actual state and feelings choose the closest answer to each option. In this study, the consumer questionnaire , consists of seven parts: comprising “Information of Mobile Advertising”, Interaction of Mobile Advertising”, “Perceived Usefulness”, “Perceived Ease of Use”, “Advertising Attitude”, “Purchase Intention “and “Basic Personal Data”.

After the questionnaires were returned, the data obtained from the samples were visually checked, numbered and recorded, and then analyzed with the appropriate statistical methods. This research adopted SPSS for Windows as the statistical package for the analysis of the questionnaire data. The analysis included descriptive statistics, reliability analysis, validity analysis, factor analysis, Pearson Correlation Coefficient analysis, as well as, Multiple Regression analysis.


The physical questionnaire was used to collect data from Taiwan’s mobile consumers. Random samples of 193 were returned and six questionnaires were invalidated, leaving 187 valid questionnaires. In this study, the questionnaires were based on the previous literatures, and 50 samples of pre-test questionnaires were issued to consumers for evaluation, resulting in the modification of the content of the questionnaire.

The hypothetical constructs were subjected to a reliability analysis; finding that the Cronbach’s α value of every variable in this questionnaire was greater than 0.7, suggesting that the questionnaire had a high reliability. The questionnaire was not completed until a consensus was reached on the questionnaire’s considerable degree of reliable validity. The demographic characteristics of study participants shown that 53% respondents are male with 46% have college degree. There are 38% with age range between 31-40 years old and majority of participant (34%) have at least 5 years work experience.

This study adopted the Pearson Correlation Analysis to discuss the correlation between the variables, and it was found that the coefficient of correlation between average consumer variables in this questionnaire ranged from between 0.431 and 0.715, suggesting a correlation between the variables and constructs in this questionnaire. The results of the correlation analysis of constructs are shown in Table 1.

***Insert Table 1 Here***

In this study, a multiple regression analysis was used to test the hypotheses, and it was found that all the hypotheses were supported. Table 2 shows the results of a regression analysis.

For H1a and H1b, this study adopted information of mobile advertising, which was measured as an independent variable, and perceived usefulness and perceived ease of use as dependent variables. As the results showed that, D-W=1.996 and 1.942 were close to 2, suggesting no autocorrelation; VIF is 1.000, indicated that colinearity was not serious. However, the multiple determination coefficient of H1a R2 =0.252, Adj- R2 =0.248, F=62.264, and β=0.502 (P=0.00<0.001) reached a significance level. The multiple determination coefficient of


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H1b R2 =0.213, Adj- R2 =0.208, F=49.971, and β=0.461 (P=0.00<0.001) also reached a significance level. The results indicated that information of mobile advertising had a positive influence on perceived usefulness and perceived ease of use.

For H2a and H2b, this study adopted interaction of mobile advertising, which was measured as an independent variable, and perceived usefulness and perceived ease of use as dependent variables. The results showed that D-W=1.968 and 1.975 were close to 2, suggesting no autocorrelation; VIF is 1.000, indicated that colinearity was not serious. However, the multiple determination coefficient of H2a R2 =0.424, Adj- R2 =0.421, F=136.351, and β=0.651 (P=0.00<0.001) reached a significance level. The multiple determination coefficient of H2b R2 =0.278, Adj- R2 =0.275, F=71.401, and β=0.528 (P=0.00<0.001) also reached a significance level. The results indicated that the interaction of mobile advertising had a positive influence on perceived usefulness and perceived ease of use.

For H3 and H4, perceived usefulness and perceived ease of use were measured as independent variables and advertising attitude as a dependent variable. The results showed D-W=1.948 and 1.998 were close to 2, suggesting no autocorrelation. VIF is 1.000, indicated that colinearity was not serious. However, the multiple determination coefficient of H3 R2 =0.376, Adj- R2 =0.372, F=111.366 and β=0.613 (P=0.00<0.001) reached a significance level, and the multiple determination coefficient of H4 R2=0.269, Adj- R2 =0.265, F=68.177, and β=0.519 (P=0.00<0.001) reached a significance level. The results indicated that both perceived usefulness and perceived ease of use had a positive influence on advertising attitude.

For H5, this study adopted advertising attitude which was measured as an independent variable and purchase intention as a dependent variable for H5. The results showed that D-W=1.961 was close to 2, suggesting no autocorrelation; VIF is 1.000, indicated that colinearity was not serious. However, the multiple determination coefficient of H5 R2 =0.512, Adj- R2 =0.509, F=193.868, and β=0.715 (P=0.001) reached a significance level. The results indicated that advertising attitude had a positive influence on purchase intention.

***Insert Table 2 Here***


With increasingly fierce market competition, informative advertising is becoming more and more important, with the goal to establish selective demand, i.e. the demand for a specific brand. This paper demonstrated that the construct “Mobile Advertising” can become a measurement indicator to establish selective demand. With knowledge of consumer attitudes, intentions and specific behavior profiles, it will be possible to design a mobile advertising strategy that is consistent with the significant consumer attributes. This will be conducive to providing direction and reference for mobile communication system service providers or for those who wish to use mobile advertising for marketing.

The research results demonstrated that Taiwan’s mobile consumers have a high sense of identity with the statement: “I

can exchange the experience using the mobile advertising”, with “I will dedicate more time to paying attention to information about the goods and services marketed by mobile advertising with a preference to purchase if mobile advertising product prices are within an acceptable range. Customers highly satisfied with mobile advertising will, through interaction with mobile advertising, recommend those products to relatives and friends, thereby promoting manufacturer’s sales and profits.

This study finds that mobile advertising can significantly affect purchase intention, especially in the competitive global economy. The quality and creativity of mobile advertising impacts the performance of product marketing. Improving the mobile advertising effect can positively affect sales performance and competitive strategies.

Consumer attitudes toward mobile advertising can, also, significantly affect consumers’ purchase intentions. Apart from the corporate image, attitudes toward mobile advertising are an important consideration of consumers. Positive consumer attitudes toward mobile advertising can increase the chances of successful product access to markets, increase market shares, boost a company’s marketing effort, positively enhance consumer product impressions, and thereby producing purchase intention and potentially increase a company’s profitability.

This study has, of course, limitations. Future research could expand and test relevant issues specific to every product class separately, for a more extensive and in-depth knowledge of the subject area. The research objective could be expanded to survey consumers worldwide, for a more representative research conclusion. However, this paper adopted TAM, and suggests that future research add in other influencing factors for analysis and comparison. Finally, it is suggested that future research develop a more thorough knowledge of mobile advertising communications to obtain more complete research results on the impact of mobile advertising on consumer behavior.

Figures and Tables


Variables Information of Mobile Advertising Interaction of Mobile Advertising Perceived Ease of Use Perceived Ease of Use Advertising Attitude Purchase Intention Information of Mobile Advertising 1.000 Interaction of Mobile Advertising 0.586** 1.000 Perceived Ease of Use 0.502** 0.651** 1.000 Perceived Ease of Use 0.461** 0.528** 0.755** 1.000 Advertisin g Attitude 0.552** 0.661** 0.613** 0.519** 1.000 Purchase Intention 0.431** 0.615** 0.597** 0.530** 0.715** 1.000 a. ** Significance Level: p<0.01


Vol. 4, No.5, October 2014 External  Variables  Perceived  Usefulness  (U)    Attitude  Toward  Using  (A)   Behavioral  Intention to  Use (BI)    Actual  System Use  Perceived  Ease of Use  (E)    Experience  Voluntariness                      Intention to  Use  Usage  Behavior  Perceived  Ease of Use  Subjective  Norm  Output  Quality  Image  Job  Relevance  Result  Demonstrability  Perceived  Usefulness 

Technology Acceptance Model

Output Quality                                       Perceived  Usefulness  Perceived  Ease of Use  Use  Behavior  Behavioral  Intention  Adjustment            Perceived  Enjoyment  Objective  Usability  Anchor                      Computer  Self‐efficacy  Computer  Playfulness  Computer  Anxiety  Perceptions of  External  Voluntariness  Experience  Subjective  Norm  Image  Job Relevance  Result  Demonstrabilit Technology Acceptance Model (TAM)    Mobile Advertising  Information  Interaction    Perceived  Usefulness  Perceived Ease of  Use  Advertising  Attitude  Purchase  Intention 



Variable F β t VIF H1a information of mobile advertising perceived usefulness 62.264 0.502 7.891*** 1.000 R2=0.252 , Adj-R2=0.248, , P=0.000, D-W=1.996 H1b information of mobile advertising perceived ease of use 49.971 0.461 7.069*** 1.000 R2=0.213 , Adj-R2=0.208 , P=0.000, D-W=1.942 H2a interaction of mobile advertising perceived usefulness 136.351 0.651 11.677*** 1.000 R2=0424 , Adj-R2=0.421, P=0.000, D-W=1.968 H2b interaction of mobile advertising perceived ease of use 71.401 0.528 8.450*** 1.000 R2=0.278 , Adj-R2=0.275, P=0.000, D-W=1.975

H3 usefulness perceived advertising attitude 111.366 0.613 10.553*** 1.000

R2=0.376 , Adj-R2=0.372, P=0.000, D-W=1.948

H4 ease of use perceived advertising attitude 68.177 0.519 8.257*** 1.000

R2=0.269 , Adj-R2=0.265, P=0.000, D-W=1.998

H5 advertising attitude purchase intention 193.868 0.715 13.924*** 1.000

R2=0.512 , Adj-R2=0.589, P=0.000, D-W=1.961

Figure 1. Framework of Technology Acceptance Model (TAM)

Figure 2. Technology Acceptance Model II

Figure 3. Technology Acceptance Model III

Figure 4. Framework of Research Model


The author would like to thank the Editor and anonymous reviewers for their valuable comments and suggestions to improve the quality of the manuscript.


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