ADVERTISING IN NEW MEDIA: EXPLORING ADOPTION OF LOCATION-BASED MOBILE APPLICATION ADVERTISING

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1 ADVERTISING IN NEW MEDIA: EXPLORING ADOPTION OF LOCATION-BASED MOBILE APPLICATION ADVERTISING Haifeng Xu, Department of Information Systems, National University of Singapore, Singapore, Zhuolun Li, Department of Information Systems, National University of Singapore, Singapore, Abstract With the development of various mobile applications, more and more advertisements are embedded in these applications. In this study, we aim to investigate what factors influence people s adoption of location-based mobile application advertising (LMAA). Combining technology adoption literature and advertising literature, we develop a theoretical model which proposes that entertainment, informativeness, irritation, credibility and social norm are antecedents to attitude towards LMAA, which in turn influence people s intention to use it. We conducted a survey to empirically test the research model. 213 students from two large universities in China were recruited to complete the questionnaires. Our findings show that entertainment, informativeness, credibility and social norm are positively related to attitude towards LMAA, while irritation is negatively related to attitude towards LMAA. Moreover, attitude towards LMAA significantly affects people s intention to use it. This study has both theoretical and practical implications. It does not only propose a novel research model to explain the adoption of a new kind of advertising, but also provides insightful suggestions for practitioners to pay more attention to those factors which may greatly help them persuade individuals to accept advertisements on mobile applications. Keywords: mobile, advertising, location-based, entertainment, informativeness, irritation, credibility, social norm

2 1 INTRODUCTION Nowadays, advertising is playing an increasingly important role in modern commercial activities. Consumers are flooded by advertisements in a variety of media. Actually, the media carrying advertising are experiencing a tremendous evolution in recent years. Although traditional media like broadcast, television, short message service (SMS) and multimedia message service (MMS) are still major ways of advertising (Oh and Xu 2003; Tsang et al. 2004), mobile application advertising has emerged to become an important category of advertising. With the popularity of smart phone, consumers tend to treat mobile phone as a mobile personal computer rather than simply as a telephone. Different kinds of mobile applications are developed to run on mobile operating system. These applications include instant messaging (IM), word processor, Web browser, game, social network services (SNS) etc., making mobile phone similar to a light-weighted mobile computer. According to the statistics in 2010, Apple s App Store has 225,000 applications; Android Market has 70,000 applications; BlackBerry App World has 7,200 applications. Apple ios users have an average of 37 applications on their devices, compared to 22 for Android users and 10 for BlackBerry users. US iphone users download 60 applications a year. There were 81.9 million application users across the UK, France, Italy, Spain and Germany in April All these figures indicate that mobile application advertising is potential to be the next leading advertising channel in the future. However, as a new advertising medium, mobile application advertising is to some extent different from traditional mobile advertising and Internet advertising. It has characteristics which are owned either by mobile advertising or Internet advertising. Mobile technology, such as Global Positioning System (GPS), makes location-based service possible to be used in advertising. Location-based advertising refers to displaying advertising information to mobile phone users based on their location (Oh and Xu 2003). Meanwhile, embedding advertisements in applications provides a specific scenario, for example searching in a map or watching a video, which makes the advertisements appeared on the screen well-targeted to the consumers. Although there are numerous studies which have investigated individuals intention to accept mobile advertising or Internet advertising (Ducoffe 1996; Goh et al. 2009; Oh and Xu 2003; Tsang et al. 2004; Yang 2007), to our knowledge, few of them actually focused on individuals intention to accept advertisements embedded in mobile applications. Since advertisements are embedded in mobile applications, this type of new advertising is not only location-based, but also scenario-based. Because the advertisements only appear when mobile application is open, the application provides certain scenarios for users to see advertisements. Location-based and scenario-based are two characteristics which distinguish mobile application advertising from traditional mobile advertising and Internet advertising. Internet advertising like search engine advertising is scenario-based but not location-based, since the users position information is not available, while traditional mobile advertising such as permission-based SMS or MMS advertising is location-based but not scenario-based, because consumers behavior information is missing. However, mobile application advertising has features of both location-based and scenariobased technology, by which marketers are able to reach consumers better for more precise position and behavior information. This study aims to investigate what factors influence people s adoption of location-based mobile application advertising (LMAA). It provides a theoretical model to explain consumers intention to click mobile application advertising. We used survey as the methodology to validate the theoretical model. Research into mobile consumer behavior will greatly contribute to the existing information systems and marketing research. In addition, the results of this study help to provide guideline for practitioners to design mobile application advertisements.

3 2 THEORETICAL BACKGROUND 2.1 Attitude and Intention A series of behavioral theories including Theory of Reasoned Action (TRA) (Fishbein and Ajzen 1975), Theory of Planned Behavior (TPB) (Ajzen 1985), and Technology Acceptance Model (TAM) (Davis 1989) are related to the dependent variable in this study: intention to click mobile application advertising. Both of TRA and TPB argue that attitude is an important antecedent of behavioral intention. Fishbein defined attitude as a learned predisposition of human beings (1967). In the field of information systems research, recent studies have confirmed the rationality of employing these theories to investigate consumer attitude toward the adoption and use of mobile services (Pedersen 2005; Yang 2007). However, even though these theories could partially explain the consumer behavior pertaining to mobile advertising, they do not directly take into consideration factors that may affect the consumer attitude toward mobile advertising such as entertainment, informativeness, and irritation. Actually, in different context of advertising, these influencing factors may or may not be the same. Therefore, it is valuable for us to investigate what factors will affect individuals attitude toward mobile application advertising. Several mature advertising models have given some predictors of people s attitude toward advertising (Brackett et al. 2001; Ducoffe 1996), which will be further discussed in the following sections. 2.2 Advertising Model Numerous studies have been conducted to investigate consumers acceptance of advertising, including mobile and Internet advertising. Public attitude toward advertising is generally considered to be negative (Zanot 1984), because consumers usually find advertising information useless or even annoying. However, some researchers argued that Internet advertising might generate positive consumer attitude toward (Schlosser et al. 1999), due to the informativeness and entertainment of Internet advertising. First of all, mobile advertising may drive consumer irritative, since mobile is a personal device pertaining to privacy. In this case, permission-based advertising is believed to be helpful in reducing the degree of irritation of consumer. In permission-based advertising, only consumer who explicitly agree to accept advertising will received messages (Tsang et al. 2004). In our study, mobile application advertising is a new kind of permission-based advertising. Before consumers use the application, they will be asked if they are willing to give their location information. Second, Haghirian and Madlberger (2005) conducted empirical study of consumer attitude toward mobile advertising in Austria, while Marko et al. (2007) empirically investigated the drivers of consumer acceptance of mobile advertising in Finland. However, their studies may suffer from such limitation that mainly focusing on the most traditional form of mobile advertising, that is, SMS advertising. Comparing to MMS advertising and mobile application advertising, SMS advertising is considered to be lack of media richness while multimedia is proved to provide more entertainment for consumers. Furthermore, considering the unique characteristics of mobile, location-based advertising is proposed to take advantage of positioning technology. With location-based advertising, advertisers could reach consumers when they are most likely to make a purchase and deliver advertising messages contextually through the media on a geographically targeted basis (Oh and Xu 2003). That is, advertising information could be effectively targeted on potential consumer on the basis of geographical information, thus predictively resulting in 5 to 10 times higher click-through rates than traditional Internet advertising (Oh and Xu 2003). In addition, the popularity of smartphone and mobile application leads to an opportunity to provide scenario-based advertising. For example, after an individual watches the trailer of a new movie,

4 advertising information on this new movie is highly possible to attract consumer s attention to click or browse. To the best of our knowledge, there is no academic research which investigates mobile consumer behavior regarding to location-based application advertising. Therefore, we combine Ducoffe s and Brackett et al. s advertising models to explain users attitude toward location-based mobile application advertising. In Ducoffe s advertising value model, entertainment, informativeness and irritation are posited to compose the value of advertising (1996). In order to enhance the explanatory power, Brackett et al. integrated several advertising models (Ducoffe 1996; MacKenzie and Lutz 1989) and developed a new pragmatic model, adding credibility and relevant-demographic-variables as two new meaningful constructs (Brackett et al. 2001). As the flourishing of 3G mobile technology has promoted the convergent evolution between Internet services and mobile services (Pedersen 2005), these advertising models can also be applied in the mobile context with some adjustments. 3 RESEARCH MODEL AND HYPOTHESES The research model to explain intention to click mobile application advertising incorporates constructs from both TRA and existing advertising models (see Figure 1). Previous research has emphasized the importance of social norm in deciding consumer attitude toward advertising and intention to accept advertising (Ajzen 1985; Fishbein and Ajzen 1975). Prior studies have also proved the significance of advertising content in affecting attitude toward adverting and intention to accept advertising (Brackett et al. 2001; Ducoffe 1996; Oh and Xu 2003; Tsang et al. 2004). Therefore, constructs of advertising content and social norm are hypothesized to influence the attitude and intention in relation to mobile application advertising. Figure 1. Research Model 3.1 Attitude and Intention As suggested by TRA and TPB, customers positive attitude towards advertising will increase their intention to accept advertising (Ajzen 1985; Davis 1989; Fishbein and Ajzen 1975). On the one hand, positive attitude towards LMAA indicates that the user has seen the benefits of using LMAA. For example it can provide useful reliable and accurate information. On the other hand, positive attitude towards LMAA means that the user does not care a lot about the irritation of such advertising. Or at least, he/she believes the benefits that LMAA offers are much more than the disturbance of using it. Thus if a user has a positive attitude towards LMAA, it is highly likely that he/she has the intention to click it. Therefore, we hypothesize:

5 H1: Attitude towards location-based application advertising is positively related to intention to click location-based application advertising 3.2 Social Norm Social norm is defined as an individual's perception of behavior and behavior consequences by persons important to him/her (Fishbein and Ajzen 1975). Venkatesh and Davis (2000) indicated that people may choose to perform a behavior, even if they are not themselves favorable toward the behavior or its consequences, if they believe one or more important referents think they should, and they are sufficiently motivated to comply with the referents. Therefore, the behaviors or thoughts of people who are important to us or around us may determine our decision making or attitude towards other things. In our study, an individual is more likely to have a favorable attitude towards locationbased advertising if most important people around her have good impression on location-based advertising, and vice versa (Ajzen 1985; Fishbein and Ajzen 1975). Therefore, we hypothesize: H2: Positive social norm results in more favorable attitude towards location-based application advertising. 3.3 Entertainment Entertainment refers to the ability to arouse aesthetic enjoyment (Ducoffe 1996). Location-based mobile application advertising can meet the customer needs of entertainment and satisfaction by different types of content like music and video and under different circumstance such as gaming and microblogging. Both of the entertainment of application and advertisement influence users emotion when they are using the application and see the advertisement. If the application and advertisement are interesting, the user will be more favorable to the mobile application advertising. Therefore, we hypothesize: H3: Higher level of entertainment results in more favorable attitude towards location-based application advertising. 3.4 Informativeness Informativeness refers to the ability to effectively provide relevant information (Ducoffe 1996). Given the location-based support, personalized advertising such as location-sensitive advertising is possible to provide more relevant and timely information for customer to evaluate the advertising products, thus leading to a better score of advertising value and purchase intention. If an advertisement displayed is more relevant to what a user needs, the user will be more favorable to the mobile application advertising. Therefore, we hypothesize: H4: Higher level of informativeness results in more favorable attitude towards location-based application advertising. 3.5 Irritation Irritation refers to any offending effects that may go against what a user values (Ducoffe 1996). Irritation of location-based advertising may emerge when spam advertisement is sent to customers or when useful advertisement repeats constantly, thus resulting in reduction of advertising value and advertising effectiveness. As Ducoffe stated, customers are likely to perceive advertisement as irritating influence when annoying or insulting techniques are employed in advertising (Ducoffe 1996). If a user feels that the advertisement is annoying, he/she will be less favorable to the mobile application advertising. Therefore, we hypothesize: H5: Higher level of irritation results in less favorable attitude towards location-based application advertising.

6 3.6 Credibility Credibility could be considered to be the believability of source of information. Credibility is stated to have a direct relationship with value of advertising (Brackett et al. 2001). Practically, since locationbased advertising is a kind of permission-based advertising (Barwise and Strong 2002), customers are more ready to receive advertisements. Besides, customers are likely to be more trustful on the advertisement associated with mobile applications, because they have a favorable impression on the mobile application they are using. Therefore, we hypothesize: H6: Higher level of credibility results in more favorable attitude towards location-based application advertising. 4 RESEARCH METHODOLOGY 4.1 Questionnaire Design In order to test the hypotheses in the research model, we used survey methodology to collect data. The main section of the questionnaire begins with a clear definition of LMAA as a type of advertising that when people use mobile applications, location-sensitive advertisements embedded in the applications appear differently based on users location. Then in order to make subjects more deeply understand what LMAA is, two examples of LMAA (one is advertisement of a restaurant; the other is advertisement of a cinema) with advertisement pictures are presented in the questionnaire. Seven constructs in the research model are measured in the questionnaire. Formal definitions of these constructs are listed in Table 1. All of the items used to measure the constructs are adapted from prior studies to enhance validity. The survey items and sources can be found in Appendix A. These questions have also been modified to fit the context of the present study. In addition, in order to check whether the subjects answer the questions carefully, an extra reversed question is added to the questionnaire. The new item is I think LMAA will show me wrong information, which was opposite to the item CRD3 I think LMAA will show me credible information in meaning. If subjects give same or similar degree of agreement to these two statements, we may judge that they do not answer the questions carefully. Thus this case may be noise in the whole sample data. Seven-point Likert scales anchored from strongly disagree to strong agree are used to examine participants responses to the questions. At the end of the questionnaire, we put an open ended question to ask for the subjects feedback on the research topic or the questions in the questionnaire. Construct Definition (Abbreviation) Entertainment The ability to fulfil audience needs for escapism, diversion, aesthetic enjoyment, or (ENT) emotional release (Ducoffe 1996; Tsang et al. 2004) Informativeness The ability of advertising to inform consumers of product alternatives so that purchases (INF) yielding the greatest possible satisfaction can be made (Ducoffe 1996; Tsang et al. 2004) Irritation The tactics advertisers employ that make the experience of processing advertising (IRT) negative (Ducoffe 1996; Tsang et al. 2004) Credibility The extent to which the consumer perceives claims made about the brand in the (CRD) advertising to be truthful and believable (Brackett et al. 2001; MacKenzie and Lutz 1989; Tsang et al. 2004) Social Norm Also referred to subjective norm, the person s perception that most people who are (SN) important to him or her think he should or should not perform the behavior in question (Ajzen 1985; Fishbein and Ajzen 1975) Attitude A predisposition to respond in a favorable or unfavorable manner to a particular (ATT) advertising stimulus during a particular exposure occasion (MacKenzie and Lutz 1989) Intention to Click A person s relative strength of intention to perform a behavior (Fishbein and Ajzen (INT) 1975; Miller 2005). In this study, it is defined as users readiness to click LMAA. Table 1. Formal Definition of Constructs

7 4.2 Data Collection and description The survey was conducted in two large universities in China. The selection of China is because of its potential mobile application advertising market. The number of mobile application users is increasing rapidly in China. In China, most of the application downloading is free. Since people are more willing to download applications including advertisements if it is free, we can expect that LMAA would have a good market prospect in China. Moreover, previous studies indicated that university students were more likely to adopt new technologies, because of their high education level and pro-technology inclination (Lightner et al. 2002; Pijpers et al. 2001). Therefore, we translated the questionnaire into Chinese, and conducted survey among university students in China. Before we distributed the questionnaire, we asked every subject whether they owned a mobile phone and used or at least saw others use the mobile applications before. Only students meeting these requirements were recruited, because it is assumed that those who know nothing about mobile application or even do not have a mobile phone are less likely to understand what LMAA is. Since our study examines the users attitude towards LMAA, it is more appropriate to include those who have some basic knowledge about mobile phone and mobile application. A total of 213 students were recruited to participate in the survey. All the subjects were required to provide their individual information as well as mobile use history and then complete a questionnaire. As an incentive for their participation, each subject received a gift (e.g. stationery) upon completion. Table 2 shows the descriptive statistics of respondents characteristics. As can be seen from the table, the percentage of male respondents (48.4%, N=103) and female respondents (51.6%, N=110) is similar percent of subjects (N=181) are from 21 years old to 23 years old, and almost all of them are 4th year undergraduate students (30.0%, N=64) or master candidates (67.6%, N=144) percent of the respondents have more than 5 years mobile phone use experience, while 74.6 percent of them have used mobile application for more than 1 year. Since most subjects in our sample have rich mobile phone and mobile application use experience, their experience and familiarity with the mobile application will help them better understand LMAA and our questions. Furthermore, it is undoubted that they will be the potential users of LMAA. In addition, subjects are required to indicate the model of their mobile phone used now. Almost all of their mobile phones are smart enough to install mobile applications, which means as far as they want, they can immediately click LMAA. Variables Items Frequency Percent Gender Male Female yrs. old Age yrs. old yrs. old Above 26 yrs. old rd yr undergraduate Grade 4th yr undergraduate Master Candidate Below 5 yrs Mobile Phone Use 5-7 yrs History 8-10 yrs yrs Below 1yr yrs Mobile Application Use 3-4 yrs History 5-6 yrs Above 6 yrs Table 2. Descriptive Statistics of Respondents Characteristics (n=213)

8 5 DATA ANALYSIS AND RESULTS 5.1 Measurement model We randomly split the dataset into two independent samples (N=85 and N=128). We used the first sample (N=85) to conduct EFA test, while the second sample (N=128) to conduct CFA and SEM test. All statistical tests were carried out at a 5 percent level of significance. EFA with principal components analysis and varimax rotation was conducted by SPSS 16.0 to test the convergent and discriminant validity of the instrument. As rules of thumb, items loading on intended factors should be more than 0.5, while on unintended factors should be less than 0.4 to support the convergent and discriminant validity. In order to satisfy this requirement, we dropped both ENT1 and ATT4. In ENT1, we asked the respondents whether they would feel that LMAA is entertaining. However, after we translated it into Chinese, the subjects might understand this question as whether they think LMAA is a kind of entertainment, which was a little different in meaning from ENT2, ENT3, ENT4 and ENT5. On the other hand, ATT4, Overall, I like LMAA, was different from the other three items in format. Moreover, ATT4 described the general attitude towards LMAA, while the others were only measured from one certain aspect. After dropping these two items, we have the principal component analysis results with varimax rotation using SPSS 16.0 as Table 3. According to the rules of thumb, convergent and discriminant validity were supported. Therefore, we moved on to CFA test. Component Items ENT ENT ENT ENT IFO IFO IFO IFO IFO IRT IRT IRT CRD CRD CRD SN SN SN ATT ATT ATT INT INT INT

9 Eigenvalue Variance explained( %) Cumulative variance (%) Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 8 iterations. Table 3. Validity of Questions We used R to run CFA and Structural Equation Modelling (SEM) test on the other independent sample (N=128). Table 4 shows the standardized item loadings on each constructs. All the constructitem correlations are significant. In addition, every latent factor s Average Variance Extracteds (AVE) is greater than 0.5, which means a construct explains more than 50% of the item variance. Construct Item Std. Loading Z-value P(< z ) AVE ENT Entertainment ENT ENT ENT IFO IFO Informativeness IFO IFO IFO IRT Irritation IRT IRT CRD Credibility CRD CRD SN Social Norm SN SN ATT Attitude ATT ATT INT Intention INT INT Table 4. The Convergent Validity of the Measurement Model Table 5 reports the correlation among constructs. The diagonal elements are square roots of AVE. From Table 5, we can see that all the correlations among constructs are less than the square root of AVE. Therefore, discriminant validity of the model is confirmed in this study. In addition, the descriptive statistics in the table shows that the data are normally distributed, which is suitable for SEM analysis.

10 Mean S.D. Min. Max. ENT IFO IRT CRD SN ATT INT ENT IFO IRT CRD SN ATT INT Table 5. Descriptive Statistics and Factor Correlation Moreover, the results of goodness-of-fit assessment show that the measurement model fits the data well. Chi-square is with 231 degrees of freedom, p < CFI is TLI is SRMR is RMSEA is Both CFI and TLI are greater than 0.9, and SRMR is less than 0.05, indicating that the proposed model fits the data very well. Although RMSEA is in the interval from 0.05 to 0.08, we still think it is a reasonable fit. 5.2 Structural Model Since the measurement model was satisfactory, the structural model was next assessed to determine its explanatory power and the significance of the hypotheses. In structural model, Chi-square is with 236 degrees of freedom, p < CFI is TLI is SRMR is RMSEA is The results that CFI and TLI are greater than 0.9, while SRMR and RMSEA are in the range of imply that the research model fits the data reasonably well. The explanatory power of the structural model could be used to explain the amount of variance in the constructs (attitude and intention) for which the model could account. Constructs in our model could explain 78.2 percent of attitude and 64.8 percent of intention. Figure 2 shows the structural model. Each hypothesis corresponds to a path in the structural model. Figure 2. Structural Model All the hypotheses are supported in this study. Social norm, entertainment, informativeness, irritation and credibility are predictors of individuals attitude towards LMAA. The relationships between entertainment, informativeness, irritation, credibility and attitude towards LMAA are significant at α=0.05 level, while the relationship between social norm and attitude is significant at α=0.01 level. Individuals attitude towards LMAA greatly influences their intention to click LMAA, which is significant at α=0.001 level. Table 6 summarizes the results of hypotheses testing.

11 Hypothesis Standardized Coefficient t-value Supported H1:Attiude Intention *** Yes H2:Social Norm Attitude ** Yes H3:Entertainment Attitude * Yes H4:Informativeness Attitude * Yes H5:Irritation Attitude * Yes H6:Credibiltiy Attitude * Yes *p<0.05; **p<0.01; ***p<0.001 Table 6. Results of Hypothesis Testing 5.3 Control Variables In order to make sure the significant results were not due to covariation with control variables, we included control variables (gender, age, mobile phone experience, and mobile application experience) in the research model together with the 7 original constructs. The results showed that all of the control variables (gender, age, mobile phone experience, and mobile application experience) were not significant, and the significant hypotheses remained the same as in table 7. Moreover, the inclusion of the control variables did not significantly increase the explanation power of the structural model. Therefore, we concluded that the results of hypotheses tests were stable and independent of control variables. 6 DISCUSSION AND IMPLICATIONS 6.1 Discussion of Findings First of all, our findings indicate that entertainment significantly affects individuals attitude towards mobile application advertising. This is consistent with previous literature which shows that consumers are more likely to have a positive attitude towards MMS advertising than SMS advertising, because MMS contributes more entertainment to the value of advertising than SMS (Oh and Xu 2003). Second, we find support for the hypotheses that informativeness and credibility have positive effects on individuals attitude towards LMAA. That is, if LMAA can provide accurate and reliable information for consumers, consumers will think it is useful and are more willing to use it. Third, our results also provide evidence that irritation is negatively related to users attitude towards LMAA. Therefore, in order to let people adopt LMAA, LMAA should not interrupt users daily life. It should appear or pop up only when users have needs to use it. Forth, social norm appears to have the most predominant impact on attitude towards LMAA, followed by credibility and entertainment. The influence of social norm on attitude is consistent with the TPB model and literature on the subject. Finally, individuals intention to click LMAA is positively affected by their attitude towards LMAA. This result reinforces previous research involving the relationship between attitude and intention to use, and possibly imply that TRA and TPB are also valid and effective in the context of mobile application advertising. 6.2 Theoretical Implications Our study makes several theoretical implications. First, with the popularity of smart phone and the advancement of positioning technology, mobile application featuring location-based and scenariobased is expected to dominate advertising market in the future. However, so far there are not many studies investigating this kind of mobile application advertising. To the best of our knowledge, this is the first study which explores the adoption of location-based mobile application advertising. Second, we combine behavioral theories, such as TRA and TPB, and advertising models to construct a new model to explain the adoption of LMAA. We propose that intention to use LMAA is influenced by users attitude towards it, which is in turn affected by four most important constructs in advertising models. We also provide empirical evidence to support these hypotheses. Third, we add social norm

12 which is a focal construct in the technology adoption literature to the advertising model. We show that it can greatly influence users attitude towards LMAA together with other variables, such as entertainment, informativeness, irritation and credibility. 6.3 Practical Implications In addition to theoretical implications, our study also makes several practical implications. This project preliminarily investigated the potential factors influencing individuals attitude towards advertising and their intention to click it. The insight into mobile consumer behavior from this project may provide helpful suggestions for merchants who engaged in the mobile advertising. For instance, since social norm is regarded as the most important factor influencing individuals attitude, advertising companies should develop some strategies to encourage users to recommend the product to their friends. In addition, when they design applications, they have to focus on the dimensions of entertainment, informativeness, irritation and credibility. First, the application should be entertaining enough to stimulate people s interest. Second, the information it provides should be accurate and useful. Finally, we have to make sure that the advertising does not annoy the users. Otherwise it may lead to some negative effects on them. 7 LIMITATIONS AND FUTURE RESEARCH Although this study has both theoretical and practical implications, it also has some limitations as following. First, since we use survey to empirically test the model, some researchers may doubt whether the results can be generalized due to the relatively small sample size and subject selection. However, we believe that university students can be representatives of the whole population, because of their high education level and pro-technology inclination (Lightner et al. 2002; Pijpers et al. 2001). In addition, the sample size of 213 is also large enough to test proposed relationships. Second, the goodness-of-fit is not excellent in both measurement and structural model. Although it is still a reasonable data model fit, it will be better if RMSEA is less than However, CFI and TLI are quite good in measurement and structural model. Therefore, we still maintain that this research model is an appropriate model. Third, in our study, the dependent variable is intention to click LMAA. Nevertheless, intention to click LMAA does not equal to actual click behaviors. Some people who have high intention to click LMAA may not click it at last due to many other factors. Therefore, we plan to use actual LMAA click behavior as dependent variable, and investigate what other factors may impact the usage of LMAA in the future research. Finally, we only incorporate location-based information in our research model to investigate consumers attitude towards LMAA. However, as we mentioned in the introduction section, LMAA is not only location-based but also scenario-based. We acknowledge that scenario-based information inferred from the use of mobile application is also critical to further understand consumers attitude towards LMAA. For example, users irritation may be moderated by mobile applications where LMAA is embedded in. We plan to extend our existing research model by incorporating both location-based and scenario-based factors in future research. 8 CONCLUSION In recent years, mobile phone is becoming an increasingly important gadget in our daily life. At the same time that various mobile applications are developed, some companies have sensed the potential marketing importance of mobile application advertising. Because of the maturity of location based technology, LMAA, as a new source of advertising, has appeared in our smart phones. In this study, we empirically tested the relationships between application advertising design factors and individuals intention to click LMAA. We also added social norm as an important antecednent to attitude towards LMAA to the research model. The results of the study show that entertainment, informativeness, credibility and social norm are positively related to attitude towards LMAA, while irritation is negatively related to attitude towards LMAA. Moreover, attitude towards LMAA significantly influences people s intention to click it. Therefore, it is valuable for practitioners to pay more attention to these factors, which may greatly help them persuade individuals to accept the advertisements on mobile applications.

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14 Appendix A Survey Items Constructs and Items Entertainment ENT1 I would feel that LMAA is entertaining ENT2 I would feel that LMAA is enjoyable ENT3 I would feel that LMAA is fun to use ENT4 I would feel that LMAA is pleasing ENT5 I would feel that LMAA is exciting Informativeness IFO1 LMAA is a good source of product information IFO2 LMAA supplies relevant product information IFO3 LMAA is a good source of up-to-date product information IFO4 LMAA makes product information immediately accessible IFO5 LMAA is a convenient source of product information Irritation IRT1 I would feel that LMAA is annoying IRT2 I would feel that LMAA is irritating IRT3 I would feel that LMAA is intrusive Credibility CRD1 I will use LMAA as a reference for purchasing CRD2 I would like to trust LMAA CRD3 I think LMAA will show me credible information Social Norm SN1 I think people around me find I should use LMAA SN2 I think people around me will believe it is a good idea for me to use LMAA SN3 I think people around me would encourage me to use LMAA Attitude ATT1 I would feel that LMAA is attractive ATT2 I would feel that LMAA is appealing ATT3 I would feel that LMAA is impressive ATT4 Overall, I like LMAA Intention INT1 I am willing to click LMAA INT2 I expect to click LMAA in the future INT3 I expect that LMAA would make everything easier in the future Sources Ducoffe, R.H. Advertising Value and Advertising on the Web, Journal of Advertising Research(36), 1996, pp Oh L., and Xu H. Effects of Multimedia on Mobile Consumer Behavior: An Empirical Study of Location-based Advertising, International Conference on Information Systems, 2003, pp Ducoffe, R.H. Advertising Value and Advertising on the Web, Journal of Advertising Research(36), 1996, pp Tsang, M. M., Ho, S. C., and Liang, T.P. Consumer Attitudes toward Mobile Advertising: An Empirical Study, International Journal of Electronic Commerce, 2004, Spring, 8(3), pp Tsang, M. M., Ho, S. C., and Liang, T.P. Consumer Attitudes toward Mobile Advertising: An Empirical Study, International Journal of Electronic Commerce, 2004, Spring, 8(3), pp S.W. Campbell, A cross-cultural comparison of perceptions and uses of mobile telephony, New Media & Society 9 (4) (2007) pp Oh L., and Xu H. Effects of Multimedia on Mobile Consumer Behavior: An Empirical Study of Location-based Advertising, International Conference on Information Systems, 2003, pp Tsang, M. M., Ho, S. C., and Liang, T.P. Consumer Attitudes toward Mobile Advertising: An Empirical Study, International Journal of Electronic Commerce, 2004, Spring, 8(3), pp B. Suh, I. Han, The impact of customer trust and perception of security control on the acceptance of electronic commerce, International Journal of Electronic Commerce 7 (3) (2003) pp