Determinants of Effective SMS Advertising: An Experimental Study

Dimitris Drossos, Geroge M. Giaglis, George Lekakos, Flora Kokkinaki, Maria G. Stavraki

Athens University of Economics and Business


Mobile advertising has become one of the most popular applications in mobile commerce, particularly in the form of text advertising through SMS (Short Messaging Service). However, in the study of mobile advertising little is known regarding the effectiveness of SMS advertising and the factors contributing to its success. This research investigates the significance of a number of factors associated with SMS advertising effectiveness through an experimental study. The findings indicate that incentive, interactivity, appeal, product involvement, and attitude toward SMS advertising in general directly influence attitude toward the advertisement, attitude toward the brand, and purchase intention. The results of the study suggest that a stronger focus on these factors is necessary to improve the effectiveness of SMS advertising campaigns.


SMS campaigns are proliferating around the world. In an empirical study of the state of interactive marketing in five large developed markets (United States, Japan, Germany, UK, and France) and two key emerging markets (China and Brazil), Barwise and Farley (2005) found that 19% of the participant firms were already using text messaging either as a direct response or as a “push” channel. Nevertheless, the academic literature is short of empirical studies investigating the importance of the factors that determine SMS advertising effectiveness.

In line with efforts to identify determinants of successful advertising campaigns in other media (e.g., Baltas 2003; Chittenden and Rettie 2003; Korgaonkar, Moschis, and Bellenger 1984; Stewart and Koslow 1989), this paper attempts to conceptualize and test factors that influence the effects of a mobile advertising campaign, with particular emphasis on push advertising via Short Messaging Service (SMS) text. In the next section, we identify the factors that may influence the effectiveness of SMS advertising and then develop a number of hypotheses that are tested experimentally in the remainder of the paper.

Prior Research on Mobile Advertising

Before we developed our hypotheses, we identified the factors that had the potential to influence mobile advertising effects.  To this end, we carefully reviewed the relevant mobile advertising and marketing literature. Initially, we retrieved 36 papers by querying the electronic text databases Business Source Premier, Elsevier’s ScienceDirect, Emerald (MCB), Kluwer, Wiley InterScience, and ACM (the Appendix provides the respective references). The keywords used were “mobile advertising,” “mobile marketing,” “wireless advertising,” and “wireless marketing.” The search was limited to scholarly journals, conference proceedings, and papers with full text access. Additional research, according to the same search criteria, yielded four additional papers, which were not accessible through the above databases. The Appendix includes the references to these papers as well.

Figure 1 presents the variables that were cited the most frequently with regard to SMS recipients’ cognitive, emotional, and behavioral responses. In much of the research, the focus was mainly on message and medium factors that could be experimentally manipulated. Consumer-related factors (e.g., attitude toward SMS advertising in general) were also used in our study due to empirical evidence suggesting that consumers have generally negative attitudes toward mobile advertising (Tsang, Ho, and Liang 2004).

Percentages of Factors Represented in Mobile Literature Research

Percentages of Factors Represented in Mobile Literature Research

Independent Variables

Location and Time

Location-based advertising is regarded as one of the most interesting opportunities mobile commerce has to offer because of its impact on the perceived informational utility of the location-aware advertisement. Various studies have empirically verified an increase in advertisement effectiveness through spatial advertising (Andersson and Nilsson 2000; Gopal and Tripathi 2006). Andersson and Nilsson (2000), for example, evaluated location-sensitive SMS campaign effectiveness based on traditional communication effect measures, and showed that SMS campaigns were effective and did have a positive impact especially on brand awareness and purchase intention. In the current research, ‘ad localization’ is considered as sending information to consumers based on their location, in order to convince them to visit a local store. Furthermore, consumer behavior theory points to the interdependence of time and location (Kang, Herr, and Page 2003). Targeting prospects at the right time and place actually implies minimum perceived effort for the prospect in buying the advertised product. Measuring actual time (for example, 11:00 p.m.) and location by distance (for example, 2 km from point of sale) seems inadequate to fully capture the notion of “right time and place.” Therefore, time and location have been examined under the umbrella of the perceived effort to buy the advertised product (Cronin, Brady, and Hult 2000).  It is therefore expected that:

H1: SMS advertisements lead to more positive attitudes toward the advertisement (Aad) and the brand  (Ab) and to more positive purchase intentions (PI) when the perceived effort to buy the advertised product is low.


Interactive elements of a mobile ad attempt to elicit cognitive responses by allowing the viewer to search for more information through the mobile device. By providing interactivity, the advertiser attempts to increase viewer involvement by creating a two-way communication in real time, instead of the usual one-way connection in media advertising (Lohtia, Donthu, and Hershberger 2003). This study regards interactivity as an objective medium characteristic and adopts the “communicator’s perspective” of interactivity, meaning that if a mobile ad allows for a reciprocal communication, then it is considered as more interactive than a comparable ad with no such feature (Hoffman and Novak 1996; Wu 2006). Sundar and Kim (2005) show that the level of interactivity is positively associated with ad and product attitudes. Thus, we hypothesize that:

H2: SMS advertisements that have an element of interactivity lead to more positive Aad and Ab and to more positive PI than SMS advertisements that have no interactive elements.


Individuals are interested in deriving some monetary benefit from direct marketing programs (Milne and Gordon 1993). In a Nokia-sponsored survey, conducted by HPI Research Group, almost nine out of ten participants (86%) agreed that there should be a trade-off for accepting advertisements on their mobile devices (Pastore 2002). Prior research proposes that price discounts are particularly effective in inducing effects, such as purchase acceleration and product trial (Shi, Cheung, and Prendergast 2005).  Previous studies have shown that retail price promotions change consumers’ purchase decisions and that retailers use price promotions more frequently to boost store sales (Chen, Monroe, and Lou 1998). We therefore hypothesize that:

H3: SMS advertisements that offer incentives lead to more positive Aad and Ab and to more positive PI than advertisements without incentives.

Ad Source (Credibility)

The term “ad source” is used to refer to traits of the communicator (whether an individual or a company), and includes expertise, trustworthiness, attractiveness, and power. Mackenzie and Lutz (1989) found that credibility strongly influences attitude toward the advertiser, which in turn is an important predictor of attitude toward the ad. Corporate credibility is defined as “the extent to which consumers believe that a firm can design and deliver products and services that satisfy customer needs and wants” and has been found to have direct positive effects on attitude toward the ad, the brand, and purchase intent (Choi and Rifon 2002). We focus on source expertise and trustworthiness and expect that:

H4: SMS advertisements from expert and trustworthy sources lead to more positive Aad and Ab and to more positive PI than SMS advertisements from less expert and trustworthy sources.


Message appeals are usually divided into rational and emotional ones (Johar and Sirgy 1991). Rational appeals are typically based on factual information and focus on product attributes. Emotional appeals, on the other hand, typically intend to create positive emotions and develop a brand personality. Emotional appeals have been found to be most effective when brand response involvement and advertising message involvement are low, whereas rational appeals are found to be relatively more effective when customers are highly involved with the brand and the advertisement (Baker and Lutz 2000). Johar and Sirgy (1991) have proposed that value-expressive advertising appeals are persuasive when the product is value-expressive, whereas utilitarian appeals are persuasive when the product is utilitarian. A series of studies by Shavitt (1990) yielded evidence about the attitude functions associated with different products, and showed that attitudes toward products that serve different functions respond to different types of advertising appeals. In this research, we assess SMS advertisements’ use of emotional appeals for a “feel” product of moderate involvement and we hypothesize that:

H5: SMS advertisements for a “feel” product that use emotional appeals lead to more positive Aad and   Ab and to more positive PI than SMS advertisements that use rational appeals.

Product Involvement

In light of our initial review of prior research on mobile advertising, there is a need for comparative research that explores whether mobile phone users react differently to diverse types of products. As Malhotra (2005) argues, “it is likely that the relative effect of cognition versus affect varies… across objects (e.g., perfumes vs. mutual funds)” (p. 480).  According to the FCB Grid (Ratchford 1987; Vaughn 1986), products differ in their “feel or think” nature. When individuals base their purchase decision mainly on how they feel about the product, then the product is characterized as “feel”; when the purchase decision is based mainly on thoughts, then the product is characterized as “think” (Ratchford 1987). As Laurent and Kapferer (1985) argue, the degree to which consumers process advertising communications and react to the message in an active or passive way depends on their involvement with the product. The Elaboration Likelihood Model (Petty and Cacioppo 1986) suggests that involvement affects motivation to process information. People with high product involvement may be more likely to explore more product-specific information. If advertisement arguments are strong, involved consumers may be more likely to form a positive attitude toward the advertised products. Due to the limited information quality that SMS advertisements can convey to consumers we expect that:

H6: Aad, Ab and PI will be less favorable when an SMS advertisement concerns a high-involvement product, compared to an advertisement for a low-involvement product taking into consideration both think and feel dimensions.

Attitude toward Mobile Advertising in General

The study of attitude toward advertising in general may be especially significant because it influences attitudes toward a specific ad, an important antecedent of brand attitudes (e.g., Alwitt and Prabhaker 1992; Mackenzie and Lutz 1989). Tsang, Ho, and Liang (2004) also found that consumers have generally negative attitudes toward mobile advertising unless they have specifically consented to receive the advertising messages. Thus, it is possible that attitudes toward specific mobile advertisements are influenced by attitudes toward advertising via cellular phones in general. We therefore expect that:

H7: Aad, Ab and PI for the advertised product will be less favorable when a consumer has a generally negative attitude toward mobile advertising, than when a consumer has a generally positive attitude toward mobile advertising.

Prior to the next section, it should be noted that ad relevance was not manipulated in our experiment but was controlled through pre-testing to choose products of moderate relevance to test hypotheses H1-H7. This was intentionally selected in order to avoid possible confounding problems via the selection of products that were of either low or high interest to the consumer.

Dependent Variables

The measures of effectiveness used in our study were attitude toward advertisement, brand, and purchase intention. Attitude toward the ad is a strong mediator of advertising effectiveness (Batra and Ray 1986; Homer 1990) and studies have shown a strong positive relationship between the ad and brand attitude, which in turn is positively related to purchase intention.

Figure 2 summarizes our conceptual model. We believe that consumer attitudes (Aad and Ab) and purchase intention (PI) are affected by each of the aforementioned ad characteristics (location and time, interactivity, incentive, appeal, ad source, appeal, and product involvement).

Conceptual Model: Factors Affecting Consumer Attitudes and Purchase Intention

Conceptual Model: Factors Affecting Consumer Attitudes and Purchase Intention



Management Science students from a large university located in Athens, Greece, participated in the experiment.  A student sample may be better than a sample taken from the general population in terms of predictive validity (Danaher and Mullarkey 2003). Ninety-seven students were randomly assigned to two groups of approximately equal size. Fifty students formed group 1, while the remaining forty-seven students formed group 2. Each group saw seven different SMS advertisements corresponding to the aforementioned manipulated variables. Among the 97 participants, 58 were female, while 39 were male. The majority of the participants were 19-23 years old (92.3%), while the remaining 7.2% were 24-28 years old. Mobile phone ownership reached 100%, with 69.1% of the participants using SMS one or more times per day. We also took into account previous experience with SMS advertising. Twenty-two of the participants stated that they had never received an SMS advertisement.


The participants read instructions indicating that they were to evaluate SMS advertisements for six fictitious products since prior familiarity with the advertised brands could potentially confound our results (Dahlen 2001). Each advertisement was described as permission-based and was shown via a mobile phone screen to increase external validity (Figure 3). All participants were asked to state their attitude toward mobile advertising in general prior to the evaluation of the SMS advertisements. Each participant belonged either in group 1 (N=50) or group 2 (N=47). Group 1 participants saw seven SMS advertisements. To be more illustrative, the first SMS message advertised the fictitious Goldy chocolate bar that could be bought in a store approximately five kilometers away from the experimental location. The second ad had no interactivity element, while the third ad informed the participant about the price of Goldy but used no price-off incentive. The fictitious product Delight instant coffee was employed to test ad source credibility, following the manipulation procedure of Goldberg and Hartwick (1990). Conversely, participants in group 2 could buy Goldy from a shop which was located just a few meters away (advertisement 1); could learn more about the new brand through an SMS reply (advertisement 2); and, in the third ad, could buy the chocolate bar with a price-off discount. The experimental conditions are illustrated in Table 1.

Illustration of an SMS Advertisement

 Illustration of an SMS Advertisement

In order to control other possible confounding effects, twenty-seven product categories were pre-tested for the “feel/think” nature of the product (following Ratchford 1987) and involvement. The categories of chocolate bar (moderate feel/moderate involvement) and instant coffee (moderate feel/moderate involvement) were selected to examine the effects of the independent variables, except for the product involvement conditions. The product categories of sun glasses (high feel/high involvement), laptop (high think/high involvement), CD-Recordable (moderate think/moderate involvement), and potato chips (moderate feel/moderate involvement) were selected to examine the possible effects of product involvement.

The arguments contained in the advertisements were also selected based on a preliminary study, where different arguments were tested for persuasiveness, comprehensibility, familiarity, and emotional versus rational appeal (following Petty and Cacioppo 1986). Arguments of equal persuasiveness, comprehensibility, and familiarity were selected to avoid confounding effects.

Experimental Conditions

 Experimental Conditions

Finally, the likelihood that participants would go through the information in the advertisements was not constrained to be either very high or low. Participants could choose to read the advertisement or not, according to their motivation. As such, these experiments were conducted under moderate elaboration conditions. Importantly, these are likely to be the conditions under which many recipients will receive advertisements in real life conditions.


Most of the constructs employed in this study were adapted from prior research. Table 2 provides the studies for the operationalization of the employed constructs.

Operationalization of the Employed Constructs

Operationalization of the Employed Constructs

Since this study attempted to shed light on the effects of a great number of factors, the authors intentionally selected reliable scales that incorporated few items in order to keep the data collection instrument as short as possible. Thus, six constructs were measured with a single-item.


Manipulation Checks

As anticipated, the participants in group 1 (M = 4.63, SD = 2.13) perceived buying the chocolate bar as more effortful (t = 6.03, df = 95, p < 0.001) than the participants in group 2 (M = 2.35, SD = 1.15). Moreover, group 1 respondents (M = 3.04, SD = 1.41) found the second SMS ad less interactive (t = -2.39, df = 95, p < 0.05) than group 2 respondents (M = 3.77, SD = 1.57). When the participants were asked to state if the offer provided any cost savings, the group 1 participants’ mean was 3.30 (SD = 1.35) and group 2 participants’ mean was 5.40 (SD = 1.33) (t = -7.7, df = 95, p < 0.001). The respondents in group 1 reported that the SMS advertisement’s appeal was indeed emotional (M = 3.08, SD = 1.2) while the respondents in group 2 reported a rational appeal (M = 4.08, SD = 0.9) (t = -4.5, df = 95, p < 0.001). In terms of product importance, the participants perceived the potato chips and the CD-R as products of lower involvement (Mpotato chips = 3.03, SD = 1.6 and MCD-R = 5.26, SD = 1.4) than the sun glasses and the laptop (Msun glasses = 5.95, SD = 1.28 and Mlaptop = 6.36, SD = 1.2) (tthink = -6.24, df = 96, p < 0.001 and tfeel = 16.38, df = 96, p < 0.001). Finally, the manipulation of credibility was also successful. The participants in group 2 perceived the advertiser as more credible (M = 4.7, SD = 0.92) than the participants in group 1 (M = 3.9, SD = 1.07) (t = -3.96, df = 95, p < 0.001).

Impact of Manipulated Variables on Advertising Effects

Table 3 denotes the t-values for the experimental conditions. Hypotheses were tested at the 5% significance level. Five out of the seven independent variables were found to have significant effects on the dependent variables.

Location and Time.  H1 was not supported (p > 0.05). In the presence of products of moderate involvement and arguments of moderate persuasiveness, SMS advertisements did not lead to more positive Aad and Ab, or to more positive PI when received closer to the selling point.

Interactivity. The direct effects of interactivity features were tested for a moderate feel product with modest persuasive arguments. The SMS ad prompted the consumer to send an SMS to learn more about the advertised chocolate. This specific interactive feature led to more negative attitudes toward the advertisement and the brand, and to more negative purchase intentions than SMS advertisements that did not have any interactive element.  Therefore, H2 was not supported.

Incentive.  H3 stated that SMS advertisements that offered incentives would lead to more positive attitudes toward the advertisement and the brand, and to more positive purchase intentions than advertisements without any incentives. H3 was partially supported, although the use of incentives for the specific product type did not positively influence attitude toward the brand.

Ad Source.  Unexpectedly, advertiser credibility did not seem to influence the dependent variables as predicted by H4. Although it is contradictory to the existing mobile advertising literature, it should be taken into account that all SMS advertisements manipulated in the experiment were perceived as permission-based. Permission-based marketing, as studied in the mobile advertising context, seems to have a moderating effect on source credibility (Tsang, Ho, and Liang 2004).

Appeal.  Even though the product employed in the advertisements was aimed at satisfying a sensory need, respondents preferred the factual appeal. Thus, H5 was not supported, and in fact, the results were significant in the opposite direction.

Product Involvement.  While examining the “think and feel” product dimensions related to the dependent variables, H6 was partially supported. The “feel” importance dimension did not result in any significant relationship, although intense systematic (central) information processing for low versus high “think” products concluded in partial support of the sixth hypothesis.

Differences in Attitudes and Purchase Considerations between Experimental Conditions

 Differences in Attitudes and Purchase Considerations between Experimental Conditions

General Attitude toward SMS advertising.  The results revealed significant direct effects of general attitudes toward SMS advertising on the dependent variables (Table 4). Thus, H7 was partially supported. In addition, we tested whether general attitude toward SMS advertising interacted with any of the above variables manipulated in this experiment. Responses of general attitude toward SMS advertising were divided into two groups based on a median split. Changes in the relationships between the independent and dependent variables in the presence of general attitude toward SMS advertising were examined using ANOVA. To support the hypothesis that general SMS advertising attitudes moderate these relationships, we needed to see significant changes in attitudes and purchase intentions among the interaction term measures. However, the moderator effects were not significant at p < 0.05.

Main Effects of General Attitude toward Mobile Advertising
on Attitudes and Purchase Intentions

Main Effects of General Attitude toward Mobile Advertising on Attitudes and Purchase Intentions


The results from our experiment offer insight into the effects of location and time, interactivity, incentives, ad source credibility, appeal, product involvement, and attitude toward mobile advertising in general, on the effectiveness of mobile text advertisements. In accordance with the specific experimental settings under which our research took place, the following paragraphs summarize and reflect on our findings for each of the seven factors tested.

Location and Time

The location of the SMS advertisement recipient did not affect the dependent variables significantly. Although location-based advertising has been heralded as one of the most promising opportunities in mobile commerce because of its impact on perceived informational utility, our research did not reveal any main direct effects. However, interdependence may still exist between location and the remaining manipulated variables. This issue calls for further research.


Contrary to our expectations, the use of interactive messages led to negative attitudes and purchase intentions for the particular product category studied. Research on interactivity has been rather inconclusive (Liu and Shrum 2002). Some studies on online web advertisements found interactivity as a strong cue aiding the persuasive function of the online ads (Sundar and Kim 2005), while others have concluded that interactivity has a negative effect on advertising effectiveness (Bezjian-Avery, Calder, and Iacobucci 1998). Our experimental conditions showed a negative influence of interactivity. One explanation for this could be the use of the chocolate bar in tests of the interactivity variable. A chocolate bar belongs to the self-satisfaction FCB quadrant (Lepkowska-White, Brashear, and Weinberger 2003) and the pre-test results showed a moderate purchase importance. In the absence of a unique selling proposition (USP), since the experimental conditions employed arguments of moderate persuasiveness to avoid confounding effects, the interactivity feature showed negative direct effects. Additionally, the participants of the second group in our experiment had to send an SMS to find out more information about the advertised product. Sending an SMS implies some additional monetary cost for a low-cost product, and this could have negatively affected the dependent variables. Thus, it is essential to explore the nature of mobile interactivity and determine the conditions in which interactivity may be useful in an advertising context.


As expected, we confirmed that the use of incentives in SMS advertisements led to more positive attitudes and purchase intentions.  This is in line with similar research in Internet advertising, where most web surfers look for incentives to read an advertisement before they click on it (Lohtia, Donthu, and Hershberger 2003). In most cases, the presence of promotional information, such as price reductions or discounts in banner advertisements, is associated with higher click-through-rates (Hupfer and Grey 2005). Additionally, in accordance with the mobile literature (e.g., Barwise and Strong 2002), our research supports that users expect a reward for receiving SMS advertisements. Moreover, the use of incentives alleviates the effects of negative attitudes toward SMS advertising on the dependent variables. The work of Tsang, Ho, and Liang (2004) provides further support for our research.

Ad Source (Credibility)

Surprisingly, the source of the advertisement did affect the dependent variables significantly. A possible rationale is that the perceived uncertainty and privacy cost effects on mobile advertising communications may occur when providing personal data to opt-in databases and not during a permission-based SMS communication, as was the case of our test. Permission-based marketing may alleviate the negative effects of a non-reputable advertiser, at least within the context of an uncluttered advertising medium as in our case (where nearly 76.3% of the respondents had received few, if any, SMS advertisements before). Research in this area is at an embryonic stage and calls for further research to determine the effects of source credibility as mobile advertising clutter grows.


The use of rational appeals led to more positive attitudes and purchase intentions than emotional appeals, despite the fact that testing was performed on a “feel” product. Although several studies on online environments have demonstrated that the use of emotional appeals in different product categories exhibit higher effects (e.g., Drossos, Vrehopoulos, and Ferles 2006), in the mobile context participants responded more favorably to the informative content strategy. While mobile devices are perceived as ideal for convenient anytime shopping, their small screens and low-resolution displays render the development of graphic applications a challenge. In the absence of sound, image, and motion that could effectively convey and demonstrate the product’s ability to satisfy a sensory need, text advertisements may be ineffective in producing an influential emotional appeal. Instead, the quality of information may play a more crucial role.

Product Involvement

Attitudes and buying intentions were less favorable when the SMS advertisement concerned a high-involvement product, compared to an advertisement for a low-involvement product. In contrast to the web, the mobile environment is likely to affect attitudes and purchase intentions for high involvement “think” products negatively because of its inherent limitation in enabling information search. However, there could be a significant increase in the frequency of impulse purchases, especially in low value, low involvement product categories (Kannan, Chang, and Whinston 2001).

Attitude toward Mobile Advertising in General

As expected, attitudes and buying intentions were less favorable when a consumer had a negative attitude toward mobile advertising in general. Our data suggest that respondents hold negative attitudes about receiving mobile advertisements. The mean overall attitude score was just 2.81 on a seven-point Likert scale. Given the unique nature of mobile phones, agencies and managers should examine the features of their opt-in database to effectively target consumers.

Limitations and Future Research

Our contribution is an empirically-validated framework, which is clearly lacking in the majority of existing research regarding the potential and critical success factors of mobile advertising. The validity and generalization of our results are of course limited by a number of factors. We have chosen to base our study on student attitudes. Although this seems like a logical decision given the participation of this age group to mobile advertising campaigns, our findings would be more helpful if we had examined a more representative sample.

Moreover, while identifying the factors that influence mobile advertising, we could not capture the relative importance (weight) of each factor and constituent variable on the campaign’s success. Although interdependence may exist between the manipulated variables, our experimental design did not allow us to conclude about their interaction effects.

Furthermore, this paper has based its findings on products of moderate involvement and arguments of moderate persuasiveness. Different results may appear when employing different product categories and argument qualities.

On issues of future research, our paper offers some potential research avenues. Two significant research questions emerge as a direct consequence of the work presented here. On the one hand, research could be directed toward identifying the clusters of consumers that are more positively inclined toward SMS advertisements. On the other hand, investigating the interaction of the aforementioned message characteristics through a full factorial experimental design could elicit a more precise picture of correlates of successful SMS advertising campaigns.


Aalto, Lauri, Nicklas Göthlin, Jani Korhonen, and Timo Ojala (2004), “Bluetooth and WAP Push Based Location-aware Mobile Advertising System,” in Proceedings of the 2nd International Conference on Mobile Systems, Applications, and Services, Boston, MA.

AAdvani, Rajiv and Khaled Choudhury (2001), “Making the most of B2C Wireless,” Business Strategy Review, 12 (2), 39-49.

Alwitt, Linda F. and Paul R. Prabhaker (1992), “Functional and Belief Dimensions of Attitudes to Television Advertising: Implications for Copytesting,” Journal of Advertising Research, 32 (5), 30-42.

Andersson, Annica and Johanna Nilsson (2000), Wireless Advertising Effectiveness: Evaluation of an SMS Advertising Trial, Master’s Thesis in Marketing, Stockholm School of Economics Andersson.

Baker, William E. and Richard J. Lutz (2000), “An Empirical Test of an Updated Relevance-Accessibility Model of Advertising Effectiveness,” Journal of Advertising, 29 (1), 1-14.

Balasubramanian, Sridhar, Robert A. Peterson, and Sirkka L. Jarvenpaa (2002), “Exploring the Implications of M-commerce for Markets and Marketing,” Journal of the Academy of Marketing Science, 30 (4), 348-361.

Baltas, George (2003), “Determinants of Internet Advertising Effectiveness: An Empirical Study,” International Journal of Market Research, 45 (4), 505-513.

Barnes, Stuart J. (2002a), “Wireless Digital Advertising: Nature and Implications,” International Journal of Advertising, 21 (3), 399-420.

— (2002b), “Under the Skin: Short-range Embedded Wireless Technology,” International Journal of Information Management, 22 (3), 165-179.

Barwise, Patrick (2001), “TV, PC, or Mobile? Future Media for Consumer e-Commerce,” Business Strategy Review, 12 (1), 35-42.

— and Colin Strong (2002), “Permission Based Mobile Advertising,” Journal of Interactive Marketing, 16 (1), 14-24.

— and John U. Farley (2005), “The State of Interactive Marketing in Seven Countries: Interactive Marketing comes of Age,” Journal of Interactive Marketing, 19 (3), 67-80.

Batra, Rajeev and Michael L. Ray (1986), “Affective Responses Mediating Acceptance of Advertising,” Journal of Consumer Research, 13 (2), 234-249.

Berkowitz, Eric N. and John R. Walton (1980), “Contextual Influences on Consumer Price Responses: An Experimental Analysis,” Journal of Marketing Research, 17 (3), 349-358.

Bezjian-Avery, Alexa, Bobby Calder, and Dawn Iacobucci (1998), “New Media Interactive Advertising vs. Traditional Advertising,” Journal of Advertising Research, 38 (4), 23-32.

Chen, Shih-Fen S., Kent B. Monroe, Yung-Chien Lou (1998), “The Effects of Framing Price Promotion Messages on Consumers’ Perceptions and Purchase Intentions,” Journal of Retailing, 74 (3), 353-372.

Chittenden, Lisa and Ruth Rettie (2003), “An Evaluation of e-mail Marketing and Factors Affecting Response,” Journal of Targeting, Measurement and Analysis for Marketing, 11 (3), 203-217.

Choi, Sejung Marina, and Nora J. Rifon (2002), “Antecedents and Consequences of Web Advertising Credibility: A Study of Consumer Response to Banner Advertisements,” Journal of Interactive Advertising, 3 (1) (accessed on 3/15/2006).

Crichard, Mark (2003), “Privacy and Electronic Communications,” Computer Law & Security Report, 19 (4), 299-303.

Cronin, J. Joseph, Michael Brady, and G. Tomas M. Hult (2000), “Assessing the Effects of Quality, Value, and Customer Satisfaction on Consumer Behavioral Intentions in Service Environments,” Journal of Retailing, 76 (2), 193-218.

Dahlen, Micael (2001), “Banner Advertisements through a New Lens,” Journal of Advertising Research, 41 (4), 23-30.

Danaher, Peter J. and Guy W. Mullarkey (2003), “Factors Affecting Online Advertising Recall: A Study of Students,” Journal of Advertising Research, 43 (3), 252-267.

De Reyck, Bert and Zeger Degraeve (2003), “Broadcast Scheduling for Mobile Advertising,” Operations Research, 51 (4), 509-517.

Drossos, Dimitris, Adam Vrehopoulos, and Ioannis Ferles (2006), “Predicting the “Click-Through Rate Performance of Banner Advertisements on the Web,” in Proceedings of the 35th European Marketing Academy Conference, Athens, Greece.

Funk, Jeffrey L. (2005), “The Future of the Mobile Phone Internet: An Analysis of Technological Trajectories and Lead Users in the Japanese Market,” Technology in Society, 27 (1), 69-83.

Goldberg, Marvin E. and Jon Hartwick (1990), “The Effects of Advertiser Reputation and Extremity of Advertising Claim on Advertising Effectiveness,” Journal of Consumer Research, 17 (2), 172-179.

Gopal, Ram D. and Arvind K. Tripathi (2006), “Advertising via Wireless Networks,” International Journal of Mobile Communications, 4 (1), 2-16.

Haghirian, Parissa, Maria Madlberger, and Andrea Tanuskova (2005), “Increasing Advertising Value of Mobile Marketing – An Empirical Study of Antecedents,” in Proceedings of the 38th Hawaii International Conference on System Sciences, Hawaii, 1-10.

Heinonen, Kristina and Tore Strandvik (2003), “Consumer Responsiveness to Mobile Marketing,” Center for Information and Communication Research at the Stockholm School of Economics, (accessed on 01/10/2005).

Hoffman, Donna L. and Thomas P. Novak (1996), “Marketing in Hypermedia Computer-Mediated Environments: Conceptual Foundations,” Journal of Marketing, 60 (July), 50-68.

Homer, P.M. (1990), “The Mediating Role of Attitude toward the Ad: Some Additional Evidence,” Journal of Marketing Research, 27 (1), 78-86.

Hristova, Nataliya and Gregory O’Hare (2004), “Ad-me: Wireless Advertising Adapted to the User Location, Device and Emotions,” in Proceedings of the 37th Hawaii International Conference on System Sciences, Hawaii.

Hupfer, Maureen and Alex Grey (2005), “Getting Something for Nothing: The Impact of a Sample Offer and User Mode on Banner Ad Response,” Journal of Interactive Advertising, 6 (1) (accessed on 3/15/2006).

Johar, J. S. and M. Joseph Sirgy (1991), “Value-expressive versus Utilitarian Advertising Appeals: When and Why to Use Which Appeal,” Journal of Advertising, 20 (September), 23-33.

Jones, Andrew (2002), “Wireless Marketing: The Linking Value of Text Messaging,” International Journal of Advertising & Marketing to Children, 3 (2), 39-44.

Kaasinen, Eija (2003), “User Needs for Location-Aware Mobile Services,” Personal and Ubiquitous Computing, 7 (1), 70-79.

Kang, Yong-Soon, Paul M. Herr, and Christine M. Page (2003), “Time and Distance: Asymmetries in Consumer Trip Knowledge and Judgments,” Journal of Consumer Research, 30 (3), 420-429.

Kannan, P. K., Ai-Mei Chang, and Andrew Whinston (2001), “Wireless Commerce: Marketing Issues and Possibilities,” in Proceedings of the 34th Hawaii International Conference on System Sciences, Hawaii.

Kavassalis, Petros, Ntina Spyropoulou, Dimitris Drossos, Evangelos Mitrokostas, Gregory Gikas, and Antonis Hatzistamatiou (2003), “Mobile Marketing: Framing the Market Inquiry,” International Journal of Electronic Commerce, 8 (1), 55-7.

Kerckhove, Anne (2002), “Building Brand Dialogue with Mobile Marketing,” International Journal of Advertising & Marketing to Children, 3 (4), 37-42.

Korgaonkar, Pradeer K., George P. Moschis, and Danny N. Bellenger (1984), “Correlates of Successful Advertising Campaigns,” Journal of Advertising Research, 24 (1), 47-53.

Laurent, Gilles and Jean-Noël Kapferer (1985), “Measuring Consumer Involvement Profiles,” Journal of Marketing Research, 12 (February), 41-53.

Lepkowska-White, Elzbieta, Tomas G. Brashear, and Marc G. Weinberger (2003), “A Test of Ad Appeal Effectiveness in Poland and the United States,” Journal of Advertising, 32 (3), 57-67.

Leppäniemi, Matti, Heikki Karjaluoto, and Jari Salo (2004), “The Success Factors of Mobile Advertising Value Chain,” EBusiness Review, 4, 93-97.

Leung, Chi Hong, Yuen Yan Chan, and Candy Suk Ching Chan (2003), “Analysis of Mobile Commerce Market in Hong Kong,” in Proceedings of the 5th International Conference on Electronic Commerce, Pittsburgh: Pennsylvania.

Lichtenstein, Donald R. and William O. Bearden (1989), “Contextual Influences on Perceptions of Merchant-supplied Reference Prices,” Journal of Consumer Research, 16 (1), 55-66.

Liu, Scott S. and Patricia A. Stout (1987), “Effects of Message Modality and Appeal on Advertising Acceptance,” Psychology and Marketing, 4 (3), 167-187.

Liu, Yuping and L. J. Shrum (2002), “What Is Interactivity and Is It Always Such a Good Thing? Implications of Definition, Person, and Situation for the Influence of Interactivity on Advertising Effectiveness,” Journal of Advertising, 31 (4), 53-.

Lohtia, Ritu, Naveen Donthu, and Edmund K. Hershberger (2003), “The Impact of Content and Design Elements on Banner Advertising Click-through Rates,” Journal of Advertising Research, 43 (4), 410-418.

Long, Ju, Andrew B. Whinston, and Kerem Tomak (2002), “Calling All Customers,” Marketing Research, 14 (3), 28-35.

Mackenzie, Scott B. and Richard J. Lutz (1989), “An Empirical Examination of the Structural Antecedents of Attitude toward the Ad in an Advertising Pretesting Context,” Journal of Marketing, 53 (2), 48-65.

Malhotra, Naresh K. (2005), “Attitude & Affect: New Frontiers of Research in the 21st Century,” Journal of Business Research, 58 (4), 477-482.

Malloy, Alisha D., Upkar Varshney, and Andrew P. Snow (2002), “Supporting Mobile Commerce Applications using Dependable Wireless Networks,” Mobile Networks and Applications, 7 (3), 225-234.

Milne, George R. and Mary Ellen Gordon (1993),”Direct Mail Privacy-efficiency Trade-offs within an Implied Social Contract Framework,” Journal of Public Policy & Marketing, 12 (2), 206-215.

Muehling, Darrel D. (1987), “An Investigation of Factors underlying Attitude-toward-advertising-in-general,” Journal of Advertising, 16 (1), 32-40.

Okazaki, Shintaro (2004), “How do Japanese Consumers Perceive Wireless Advertisements? A Multivariate Analysis,” International Journal of Advertising, 23 (4), 429-454.

Pastore, Michael (2002) “Incentives Still Key to Mobile Advertising” (accessed on 05/20/2006).

Petty, Richard E. and John T. Cacioppo (1986), Communication & Persuasion: Central & Peripheral Routes to Attitude Change, New York: Springer-Verlag.

Petty, Ross D. (2003), “Wireless Advertising Messaging: Legal Analysis and Public Policy Issues,” Journal of Public Policy & Marketing, 22 (1), 71-82.

Ranganathan, Anand and Roy H. Campbell (2002), “Advertising in a Pervasive Computing Environment,” in Proceedings of the 2nd  ACM International Workshop on Mobile Commerce, 28 (September), 10-14.

Ratchford, Brian T. (1987), “New Insights about the FCB Grid,” Journal of Advertising Research, 27 (4), 24-38.

Ratsimor, Olga, Tim Finin, Anupam Joshi, and Yelena Yesha (2003), “eNcentive: A Framework for Intelligent Marketing in Mobile Peer-to-peer Environments,” in Proceedings of the 5th International Conference on Electronic Commerce, Pittsburgh: Pennsylvania.

Saari, Timo, Niklas Ravaja, Jari Laarni, Marko Turpeinen, and Kari Kallinen (2004), “Innovation, Management & Strategy: Psychologically Targeted Persuasive Advertising and Product Information in E-commerce,” in Proceedings of the 6th International Conference on Electronic Commerce, Delft: The Netherlands.

Scharl, Arno, Astrid Dickinger, and Jamie Murphy (2005), “Diffusion and Success Factors of Mobile Marketing,” Electronic Commerce Research and Applications, 4 (2), 159-173.

Shavitt, Sharon (1990), “The Role of Attitude Objects in Attitude Functions,” Journal of Experimental Social Psychology, 26 (March), 124-148.

Shi, Yi-Zheng, Ka-Man Cheung, and Gerard Prendergast (2005), “Behavioural Response to Sales Promotion Tools,” International Journal of Advertising, 24 (4), 467-486.

Stewart, David W. and Scott Koslow (1989), “Executional Factors and Advertising Effectiveness: A Replication,” Journal of Advertising, 18 (3), 21-32.

Sundar, S. Shyam and Jinhee Kim (2005), “Interactivity and Persuasion: Influencing Attitudes with Information and Involvement,” Journal of Interactive Advertising, 5 (2) (accessed on 3/15/2006).

Tsang, Melody M., Shu-Chun Ho, and Ting-Peng Liang (2004), “Consumer Attitudes toward Mobile Advertising: An Empirical Study,” International Journal of Electronic Commerce, 8 (3), 65-78.

Varshney, Upkar (2001), “Location Management Support for Mobile Commerce Applications,” in Proceedings of the 1st International Workshop on Mobile Commerce, Rome: Italy.

— (2003), “Location Management for Mobile Commerce Applications in Wireless Internet Environment,” ACM Transactions on Internet Technology, 3 (3), 236-255.

— and Ron Vetter (2001), “A Framework for the Emerging Mobile Commerce Applications,” in Proceedings of the 34th Hawaii International Conference on System Sciences, Hawaii.

— and — (2002), “Mobile Commerce: Framework, Applications and Networking Support,” Mobile Networks and Applications, 7 (3), 185-198.

Vaughn, Richard (1986), “How Advertising Works: A Planning Model Revisited,” Journal of Advertising Research, 26 (February/March), 57-66.

Watson, Richard T., Leyland F. Pitt, Pierre Berthon, and George M. Zinkhan (2002), “U-commerce: Expanding the Universe of Marketing,” Journal of the Academy of Marketing Science, 30 (4), 333-347.

Wu, Guohua (2006), “Conceptualizing and Measuring the Perceived Interactivity of Websites,” Journal of Current Issues and Research in Advertising, 28 (Spring), 87-104.

Yuan, Soe Tsyr and Chiahsin Cheng (2004), “Ontology-based Personalized Couple Clustering for Heterogeneous Product Recommendation in Mobile Marketing,” Expert Systems with Applications, 26 (4), 461-476.

Yuan, Soe Tsyr and Eva Tsao (2003), “A Recommendation Mechanism for Contextualized Mobile Advertising,” Expert Systems with Applications, 24 (4), 399-414.

Zaichkowsky, Judith Lynne (1985), “Measuring the Involvement Construct,” Journal of Consumer Research, 12 (3), 341-352.

Appendix: Retrieved References for Mobile Advertising Studies

Retrieved References for Mobile Advertising Studies

About the Authors

Dimitris Drossos is a Ph.D. Candidate in the Department of Management Science and Technology at the Athens University of Economics and Business and currently teaches e-marketing at the Technological Educational Institute of Patras. He is currently doing research on mobile advertising, as well as m-commerce technologies and services.

Dr. George M. Giaglis is an Associate Professor of eBusiness at the Athens University of Economics and Business. His main research interests lie in the areas of mobile and wireless applications and services; ubiquitous, pervasive, and wearable information systems; business process modeling and simulation; and information systems evaluation. He has published more than 100 articles in leading journals and international conferences. Since 2001, he has been the Director of the ISTLab Wireless Research Center (

Dr. George Lekakos is an Adjunct Lecturer at the Department of Management Science and Technology, Department of Computer Science, University of Cyprus. Dr. Lekakos’ research interests are in the area of personalized and adaptive systems, human-computer interaction, and machine learning. He has published more than 30 papers in international journals and conferences, and he is the co-editor of books and conference proceedings.

Dr. Flora Kokkinaki is an Assistant Professor in the Department of Marketing and Communication at the Athens University of Economics and Business. Her research interests include attitude theory and consumer decision-making. She has published in the British Journal of Psychology, the British Journal of Social Psychology, and the Journal of Economic Psychology.

Maria G. Stavraki is a Ph.D. Candidate in the Department of Marketing and Communication at the Athens University of Economics and Business. Her research interests include consumer behavior and affective processes in attitude change.