Perceptions and Recall of Advertising Content Presented on Mobile Handled Devices

Suzanne Altobello Nasco, Gordon C. Bruner II

Southern Illinois University


With the advancements in mobile phone technology and the increase in consumer use of wireless devices to access the internet, there is a need to explore the inevitable effect of these factors on mobile advertising. In this project, we presented commercial content on wireless devices, designed to represent various modality combinations (text, audio, and pictures) to test hypotheses based on cognitive load theory. Results showed that modality significantly affected subjects’ perceptions toward and recall of the commercial content. However, modality did not affect perceptions of the mobile device itself, or influence behavioral intentions and attitudes toward mobile advertising on wireless devices. Behavioral intentions to use mobile devices were significantly predicted by consumer perceptions of content and of the device. Marketers can use these results to design more effective ads to be presented on mobile devices.


The nearly universal presence of mobile phones has affected many facets of our daily lives. The rise of this “third screen” (relative to television screens and computer screens, e.g., Cuneo 2005) presents opportunities and challenges for advertisers seeking to utilize the mobile medium to reach consumers. The knee-jerk reaction might be to deliver the same content as has been used with the older screens, but this would probably be a mistake (Donaton 2006).  What is the best form to use when designing advertising content to appear on wireless devices and what is the effect of these different presentation formats on consumers’ perceptions of the commercial content and perceptions of the device itself? What predicts behavioral intentions toward using mobile devices to obtain commercial content?

In addition to these practical questions that marketers seek answers to are some fundamental psychological questions as well. Namely, how much information presented on wireless devices can individuals effectively process? The ubiquity of wireless devices leads individuals to multi-task across environments, thus, the constraints of working memory are likely to play a strong role in information processing of content presented on wireless devices. The theory of cognitive load could lend insight into the best way to present information to consumers, as this theory examines the effect of limitations of human working memory capacity on one’s ability to process information (Sweller 1988).

These practical and theoretical questions are examined in this study by presenting commercial content to consumers on a wireless device in a variety of presentation formats. We combined current technological capabilities of handheld devices with the theoretical concept of cognitive load in order to establish the foundation for our presentational design and research hypotheses. Findings from our study can be used by marketers to understand the best combination of presentation formats to create mobile ads that would enhance comprehension of the commercial message and improve attitudes toward mobile content and mobile devices.


Computer-based multimedia environments consisting of pictures (animation) and words (textual or audio-presented narration) offer a potentially powerful venue for improving consumer experiences. All multimedia messages deliver information to the user, but they are not equally successful in promoting understanding. Even though web pages can display text, audio, graphics and animation with little difficulty, the challenge is to design multimedia messages that promote learning (retention of information and recall), while simultaneously appealing to the individual’s preferences and not over-taxing the individual’s cognitive capacity.

These are practical issues to address because marketers wanting to utilize “the third screen” must make decisions about how to present the ads to consumers. With regard to the format for audio and video, several alternatives exist. Additionally, practitioners would typically want people to attend to their messages and process them properly. It is reasonable to ask if consumers have a preference for the modality in which advertising content is received on a mobile device. Beyond preference, it is reasonable to ask about contrasting effects of the different formats on consumers’ product-related attitudes and intentions.

Modality Effects Relevant to Mobile Advertising

The internet, in general, and the ability to connect to the internet via wireless handheld devices offer consumers a unique combination of traditional communication modalities, such as TV, print, and radio. Current mobile technology can allow marketers to present mobile advertising information via an auditory channel (e.g., someone calling a mobile phone and speaking directly to the consumer), a text channel (e.g., using SMS technology to send a short message to the consumer on their wireless device), or other visual channels that incorporate multimedia (e.g., sending a picture or video directly to the consumer on their wireless device). Moreover, the interactive nature of wireless devices allows consumers to customize these information modalities depending on personal preference and device capabilities (Lewis 1996).

Past research on modality has mostly focused on traditional media formats. Different types of media (through various modality combinations) have been shown to differentially affect attention, vividness, comprehension, and decision-making. Seminal research by Chaiken and Eagly (1976) found that comprehension of an easy message did not differ as a function of whether the message was presented in written, auditory, or video form, however, comprehension of a difficult message was best in written form. Jacoby, Hoyer, and Zimmer (1983) found similar results: print messages were better comprehended than television or audio messages. Conversely, research by Liu and Stout (1987) found that pictures and words, or pictures alone, were more effective than words alone in enhancing message recall and inducing positive thoughts and attitudes. Few researchers have examined these implications in a mobile advertising environment in particular, so predictions regarding directionality of various modalities on attitudes remain speculative. However, extending this research into the mobile environment, we hypothesize that favorable attitudes toward the content presented on the mobile device should be highest when multiple modalities are used to present the message (e.g., pictures and text, pictures and audio).

H1: Mobile advertising content presented in multiple formats (text with pictures, audio with pictures) will result in higher consumer involvement in and higher perceived importance of the ad content than mobile advertising content presented in single formats (text only, audio only).

In addition to the number of modalities possible in an interactive environment, technology capabilities also allow marketers to present visual information in a dynamic or static form. On the internet or mobile devices, this distinction translates into the ability to present pictures one at a time or to present pictures in video form. Past research by Singer (1980) found that the movement in television’s audio-visual messages creates visual variation and, hence, increases attention to the moving images. Therefore, in an interactive environment, we may find that consumers are more involved in content that is presented dynamically.

H2: Mobile advertising content presented dynamically will result in increased involvement than mobile advertising content presented statically.

In a multimedia environment, we may find that modalities interact to influence perceptions of the content. Although no published research speaks to this issue in a mobile advertising context, we specifically designed our study to examine the interactive effects of text, audio, and pictures (static vs. dynamic) on consumer perceptions.

Recall is also important to marketers, as consumers should recall advertising content at the point of purchase when making the decision to purchase a product. Past research has shown that textual information is better recalled than auditory information due to the enhanced ability to rehearse a text message (i.e., re-read) than an auditory one. For example, Sewell and Moore (1980) found that recall of a list of words was better when presented in text form than in audio form. Therefore, extending this research into the present project, we hypothesize that consumers’ recall of the information presented in a mobile ad should be highest in the print conditions.

H3: Mobile advertising content presented in text format will result in better recall than mobile advertising content presented in auditory formats.

Cognitive Load Theory and Mobile Advertising

Other research that pertains to advertising on mobile devices concerns consumer memory capacity, rather than consumer preference or attention. Human memory is composed of two parts: long-term memory and short-term (or working) memory. Long term memory is conceptualized as a permanent repository for knowledge and skills acquired via learning; working memory is used to organize incoming stimuli for further information processing, acting like a filter for long-term memory storage. Long-term memory has potentially unlimited storage capacity, while working memory is limited in its processing capacity, capable of holding only about seven information elements at any one time (Miller 1956). Due to this limited capacity, all mental activities impose a “cognitive load” on the individual. Cognitive load theory (Sweller 1988; Sweller, Van Merriënboer, and Paas 1998) addresses the limitations of working memory, in terms of both capacity to store and ability to process incoming information, and it provides guidelines for minimizing working memory overload. Initially, working memory was considered a unitary construct, but modern conceptualizations divide working memory into a “visual-spatial scratch pad” to hold and process visual information and a “phonological loop” to hold and process auditory information (Baddeley 1992).

Related to the visual field specifically, cognitive load research has found that if two messages presented simultaneously as pictorial and textual information are redundant (meaning either can be understood in isolation), presenting individuals with only one visual message is superior to presenting two redundant visual messages. For example, if individuals are trying to learn about how to use a product, they could be presented with a diagram or could read the instructions in text format. If the text merely translates the diagram into words, research by Chandler and Sweller (1991) found that subjects presented with both the diagram and the text performed worse on subsequent tasks than subjects who only viewed the diagram. Extending this idea to mobile advertising suggests that an advertisement presented on mobile device with both pictures and text that describes the pictures should be less effective than a mobile ad presented as just text.

H4: Mobile advertising content presented as two visual pieces of redundant information (e.g., pictures with text) will result in more negative perceptions and lower recall than mobile advertising content presented as one visual source (e.g., text).

Because visual and auditory working memory processors are separate, effective working memory may be increased by using both processors rather than either memory stream alone (Paivio 1986; Penney 1989).  Research based on this dual processor idea has shown that people are better able to understand and process two messages if they are communicated via different modes (e.g., reading one message while listening to another) than if two messages are presented in the same modality at the same time (e.g., listening to both messages or reading both messages) (Allport, Antonis, and Reynolds 1972; Frick 1984).

Although the dual processor effect is specific to learning two separate messages, we may be able to extend such thinking to a multimedia context. A mobile advertisement has the ability to be presented via one mode (e.g., an ad presented through SMS text messaging or an ad presented as an auditory recording) or via two modes (e.g., an ad presented through visual and auditory channels, such as pictures with a sound file). If the dual processor effect extends to mobile advertising, then ads that utilize dual modes will be more effective than those that utilize a single mode.

H5: Mobile advertising content presented across dual modes (e.g., a visual plus an auditory mode) will result in higher involvement, higher perceptions of importance and better recall of ad content than mobile advertising content presented across a single mode (e.g., visual only or auditory only).

Care must be taken by marketers, however, when utilizing dual modes. This is especially true if the modes are competing, rather than complementary. When words are presented on-screen in text format they must be processed through the visual system; any animation or pictures that are on-screen at the same time as the text must also be processed visually. In this situation, the text is competing with the animation for visual attention, causing a split attention effect. However, when words are presented as narration, they are processed in the auditory channel, thus freeing visual capacity that can be devoted to processing the animation more deeply and resulting in complementary modalities. Consequently, past research has found that learners processing pictures with narration (audio) displayed better performance on subsequent transfer tasks than learners processing pictures with text (Mayer and Moreno 2002; Mousavi, Low, and Sweller 1995). Hypothesis 6 extends this work in complementary versus competing processing modes to the domain of mobile advertising.

H6: Mobile advertising content presented in two complementary modes (e.g., pictures with audio) will result in higher involvement, higher perceptions of importance and better recall of ad content than mobile advertising content presented in competing modes (e.g., pictures with text).

Predicting Behavioral Intentions toward Mobile Devices for Commercial Content

Even though the evidence shows that redundancy and split attention increase cognitive load and reduce task performance, the research on cognitive load theory does not address a person’s preference for or perceptions of redundant information. In a multimedia context, it is possible that consumers have come to expect more dynamic media for entertainment value. Therefore, if a mobile phone can present video with audio, consumers may actually prefer redundant information rather than simply reading an SMS message presenting a mobile ad. Thus, behavioral intentions to use a wireless device to obtain commercial content should be higher for dynamic ads than static ads. In addition, recent research has found that including affective measures with cognitive measures provide much better prediction of intentions to use a wireless device than using cognitive factors alone (Bruner and Kumar 2005; Kulviwat et al. 2007).

H7: Mobile advertising content presented dynamically will result in higher behavioral intentions to use a mobile device than mobile advertising content presented statically.

H8: Cognitive and affective reactions to using a mobile device to obtain advertising content should significantly predict behavioral intentions to use a mobile device, over the effect of cognition alone on behavioral intentions.



Participants were 116 college students recruited from an introductory marketing course at a large public university in the midwestern United States. Participants received extra credit toward their course grade in exchange for participation.

Design and Content

All participants viewed one of six different presentations of an advertisement on a mobile device. To address the aforementioned hypotheses, we employed a 3 by 2 between-subjects design. The first factor was related to what participants saw on the mobile device screen and consisted of three levels: no pictures, multiple static pictures (i.e., photos presented in slide show mode), or streaming pictures (i.e., video). To create the levels for this factor, we downloaded a 30-second car commercial from a subscription-based advertising website (available from the first author upon request). From that primary video, we captured 10 still pictures from the video for the “static pictures” condition. In the “no picture condition”, the mobile device screen was black and in the “static pictures” condition, the 10 still pictures from the commercial appeared sequentially for 3 seconds each in the center of the screen (simulating a slideshow). In the “streaming pictures” condition, the full commercial video appeared in the center of the screen. In the latter two conditions, Microsoft Media Player was used to present the commercial content.

The second factor consisted of two levels and related to whether the participants heard audio to accompany what they saw (factor 1) or whether they read text that appeared on the screen. For the “audio only” condition, we stripped the 30-second audio track from the original video, saved it as a .wav file, and presented it to participants on the handheld device using Microsoft Media Player. For the “text only” condition, we transcribed the audio and presented the script in the center of the mobile device screen (black letters on a white background). When text was presented, along with pictures (either static slideshow or streaming video), the text appeared on the bottom of the mobile device screen, simulating a “closed-captioning” type of screen. Thus, participants were randomly assigned to and experienced one of the following six conditions: read the text script of the commercial with no pictures (n = 21), heard the audio track only of the commercial with no pictures (n = 18), read text of the commercial while viewing the 10 still pictures presented sequentially (n = 20), heard audio while viewing the 10 still pictures presented sequentially (n = 19), viewed the text of the commercial script while viewing the video (n = 20), or viewed the original commercial video (heard audio with video, n = 18).

Because these conditions were created specifically for this study to test hypotheses related to modality, all audio, text, and picture files had to be saved to a memory card and loaded onto a mobile device. At the time the data were collected, cell phones that could show streaming video content from an external memory card were not available. Therefore, instead of using a mobile phone as the handheld device, we used a Toshiba Pocket PDA (model e740) with an external memory card slot that had a similar screen size (2.25 inches by 3 inches), weight (6 ounces), and visual appearance to prototype models being developed by cellular phone companies at the time this study was designed (see Figure 1 for photo of device). Respondents participated in the study in experimental sessions of two to seven people; all participants in a session were in the same condition to simplify instructions regarding how to use the mobile device.

Toshiba Pocket PDA


Participants signed up for a one hour experimental session as part of a larger study exploring the effects of content presentation using various modalities on mobile devices. Upon entering a small conference room, each participant was given a folder consisting of survey materials and a PDA. The experimenter then held up a PDA and demonstrated how to use it. Headphones were provided with each PDA in the audio conditions and the experimenter demonstrated how to use the stylus to play a sample 10-second Windows Media Player system file. Each participant was encouraged to play the sample file several times, if necessary, to properly adjust the volume of his/her headset using the stylus.

Once the demonstration was over, the experimenter fielded any questions concerning operation of the device before proceeding. Participants were then instructed to use the stylus to click on the “begin” button on the mobile device screen to view the commercial content. Participants could only view the commercial one time on the PDA. Following the commercial presentation, all participants completed a series of questions.

Dependent Variables

The questionnaire assessed participants’ reactions to the content of the information presented (i.e., the commercial), as well as their reactions to the mobile device itself (i.e., the PDA). Attitudes toward using the mobile device and behavioral intentions of using a mobile device in the future were also measured. (See Appendix 1 for questionnaire items related to perceptions of content and device; see Appendix 2 for items related to attitudes and behavioral intentions.)

Perceptions of Commercial Content. In assessing perceptions toward the content, we measured personal involvement toward and perceptions of the importance of using a mobile device to advertising information. To measure involvement in receiving the commercial content, respondents reported their agreement with four statements that assessed their interest in and diligence in attending to the advertising information. To measure importance of receiving commercial content, we modified some items from Zaichkowsky (1985) to examine the extent to which obtaining ad information on the mobile device was perceived as positive by respondents. Participants rated their agreement with nine adjectives regarding the ad content received on the mobile device.

Perceptions of the Mobile Device. To assess perceptions of the mobile device itself, we asked participants to assess their overall affective experience with the device, the perceived usefulness of the device, and their perception of overall value of such a device. To measure overall affective experience, we asked participants to rate their level of agreement with six items regarding the extent to which receiving commercial information of this type on the mobile device generated positive emotions. To measure cognitive reactions toward the perceived usefulness of the mobile device, we used items suggested by Lund (1999). Our participants reported their agreement with five statements referring to whether the mobile device would help them be more effective. To measure the perceived value of wireless devices, we asked participants to rate their agreement with three statements regarding the value, relevance, and quality of wireless devices to obtain such content.

Attitudes and Behavioral Intentions toward the Mobile Device. To measure attitudes toward using a mobile device to obtain commercial advertising information, we used four items suggested by Bagozzi, Baumgartner, and Yi (1992). Participants assessed their attitudes on semantic differential scales anchored by the following descriptors: bad/good, negative/positive, unpleasant/pleasant, and unfavorable/ favorable.  To measure participants’ behavioral intentions to use a mobile device in the future to obtain commercial information, we asked this item right after receiving the commercial information (to measure specific intentions toward mobile advertising) and at the end of the study to measure overall likelihood of using a mobile device in the future (to measure general intentions toward mobile devices).

Recall of Commercial Content. At the end of the study (after all content, device, and demographic questions), we inserted a measure of recall regarding the commercial content. Respondents completed the recall phase approximately 15 minutes after viewing/hearing the commercial. We created five questions that asked respondents to name the car manufacturer mentioned in the ad, to name the country mentioned in the ad, to identify the car feature that was not mentioned in the ad, to identify the color of an item in the ad, and to identify the single number mentioned in the ad. Responses to these items were presented in multiple choice format, thus creating an “aided recall” measure, rather than an unaided recall measure.



The 116 participants were almost evenly distributed by gender, with 48% male (n = 56) and 51% female (n = 59), with one participant not reporting gender. The average age of participants was 22.52 years (SD = 4.54). Eighty-seven percent of respondents (n = 100) currently owned a mobile phone (with 65% of the sample reporting an average monthly cell phone bill less than $60). Only 30% of respondents (n = 35) reported currently using their phones to receive any sort of multimedia content.

Reliability of Scales

Exploratory factor analyses were conducted for all multi-item scales used in the study. See Appendices 1 and 2 for internal consistency measures, represented by Cronbach’s alpha. The items all loaded on their respective factors and the items from each of the six scales demonstrated high internal consistency, with alphas for all six scales greater than .83. Therefore, for each of the six scales, a single, averaged index was created with higher numbers representing more positive perceptions and attitudes. These indexes were used as dependent variables in subsequent analyses.

Perceptions of the Commercial Content

To assess the effects of modality on consumer perceptions toward the commercial content, the involvement and importance indices were used as dependent variables in a multivariate analysis of variance, with pictures and audio/text as between-subjects factors with three and two levels, accordingly. No significant main effects emerged, but the pictures by audio/text interaction was significant, Wilks’ L = .898, F (4, 218) = 3.007, p < .02.

A similar pattern of means emerged for both perception indices across modality conditions: when no pictures of the commercial were seen, perceptions of involvement in and importance of commercial content were significantly higher for the text only condition (Mtext only – involvement = 4.18 and Mtext only – importance = 3.79) than for the audio only condition (Maudio only – involvement = 3.04 and Maudio only – importance = 2.97), Wilks’ L= .940, F (2, 109) = 3.46, p < .04. However, when pictures accompanied the audio track or text conditions, the reverse occurred. For the static and streaming pictures conditions, perceptions of importance and involvement were higher in the audio conditions compared to the text conditions, although these simple effects tests did not reach statistical significance. See Figure 2 for graphs of both involvement and importance indexes across conditions.

Perceptions of Involvement and Importance by Modality

Perceptions of Involvement and Importance by Modality

Perceptions of Involvement and Importance by Modality

To specifically test Hypothesis 1, we created a contrast comparing the text only and audio only conditions to the remaining four multiple format conditions for both perception indexes. Neither contrast was significant (both t‘s < .40). To test Hypothesis 2, we created a contrast comparing the two streaming pictures (video) conditions to the two static pictures conditions for both perception indexes. Again, neither contrast was significant (both t‘s < .60).

Recall of Commercial Content and Perceptions of the Mobile Device

Hypotheses 3 through 6 relate specifically to recall (H3) and to recall and perceptions (H4, H5, and H6). To create a single recall index, we simply summed the number of correct answers to the five recall questions. As this was a formative index, a measure of internal consistency is not relevant (Diamantopoulous and Winklhofer 2001). The values for the index ranged from zero to five and, across all participants, the average number of items correctly recalled from the commercial was 3.05 (SD = 1.37). The recall index was used as the dependent variable in an analysis of variance, with pictures and audio/text as the independent factors. The pictures main effect and the pictures by audio/text interaction were not significant, but the audio/text main effect was significant, F (1, 116) = 9.35, p < .004. The pattern of means supports Hypothesis 3: respondents had better recall of the commercial content in the text conditions (M = 3.41, SD = .169) than for the audio conditions (M = 2.67, SD = 1.78), regardless of the picture condition. See Figure 3 for a graph of recall effects.

Recall of Commercial Content by Modality

Recall of Commercial Content by Modality

Hypotheses 4 (related to the effect of two visual pieces of information versus one visual piece on recall) and 5 (related to the effect of dual modes versus single modes on recall) were not supported (both t’s < 1.4). To test Hypothesis 6, we created a contrast pairing the two text plus picture conditions against the two audio plus picture conditions, with recall as the dependent variable. The contrast was marginally significant, t (110) = 1.69, p < .1, but the means were in the opposite direction with the competing modes (text and pictures) showing higher recall (M = 3.3) than the complementary modes (audio and pictures) (M = 2.79).

Hypotheses 4 through 6 also predicted the effect of modality on perceptions of the mobile device itself. Thus, we performed a MANOVA with the affective, usefulness, and value indices as dependent variables and the pictures and audio/text factors as the independent variables. Perceptions of the device were not affected by the modality presentations of the commercial content: the audio/text main effect, the picture main effect, and the pictures by audio/text interaction were not significant, Wilks’Ls = .994, .966, and .914, respectively; all F‘s not significant.

Since the hypotheses were generated a priori, we examined the significance of the three contrasts across the three device perception indexes, even though the overall MANOVA was not significant. Hypothesis 4 was not supported, but Hypotheses 5 and 6 were marginally significant for the value index. Specifically, advertising content presented across dual modes (audio plus static pictures and audio plus streaming pictures) led to higher perceptions of the value of using wireless devices to access commercial content, compared to single modes (visual only or audio only), t (102) = 1.88, p < .065. Also, advertising content presented in complementary modes (e.g., information presented via both visual and audio modes) led to higher perceptions of the value of using wireless devices to access commercial content, compared to competing modes (e.g., two pieces of information presented visually), t (102) = 1.89, p < .062.

Attitudes and Behavioral Intentions toward using a Mobile Device to obtain Commercial Content

Participants’ attitudes toward the device were not significantly different across the pictures or audio/text factors (both main effects and interaction were not significant). Similarly, the variation in modality presentation of commercial content did not affect either specific or general behavioral intentions to use a mobile device in the future. To test Hypothesis 7, we performed the same contrast as Hypothesis 2, but with general behavioral intention as the dependent variable. The contrast was not significant.

To examine Hypothesis 8, we ran a hierarchical regression predicting general behavioral intention from two cognitive measures (the value of wireless devices and the perceived usefulness of wireless devices to obtain commercial content) and two affective measures (the affective/emotional perception of commercial content on wireless devices and the attitude toward using a wireless device to obtain commercial content). The cognitive measures significantly predicted 58.5% of general behavioral intention, F (2, 106) = 73.4, p < .001. Both cognitive measures were significant predictors of intention (usefulness index: B = .615, t = 6.89, p < .001; value index: B = .504, t = 4.91, p < .001).

Support for Hypothesis 8 was specifically found in the significant improvement of predicting behavioral intention with affective measures included in the model. The affect and attitude indexes combined to predict an additional 5.3% of variance in intention, F change (2, 102) = 7.49, p < .002. Both affect indexes were significant predictors (attitude index: B = .252, t = 2.95, p < .005; affect index: B = .304, t = 2.29, p < .025), along with the usefulness index (B = .503, t = 5.64, p < .001). However, with affect indexes in the model, the perceived value of the wireless web no longer significantly predicted behavioral intention to use a mobile device to obtain commercial content. See Table 1 for hierarchical regression results.

Regression Results Predicting General Behavioral Intentions toward the Wireless Device from Cognitive and Affective Measures

Regression Results Predicting General Behavioral Intentions toward the Wireless Device from Cognitive and Affective Measures


Table 2 presents an overview of the hypotheses, findings, and brief conclusions from our research. Taking our hypotheses together, in the context of mobile advertising, cognitive load theory may not be adequate to explain recall and perceptions of commercial content. While the theory was important in helping to guide the development of our unique experimental conditions, many of the ideas regarding redundancy and split attention do not apply to interactive mobile content to the same extent as they do in educational design. The strength and primary contribution of our research is that our conclusions can speak directly to mobile content designers and providers, whereas other communication research may not be as appropriate for the mobile landscape. Our creative experimental design is one of the first of its kind that we know of to design specific mobile content across various modalities and to present it to consumers on wireless handheld devices to test specific learning hypotheses.

Our first hypothesis tested the assumption that multiple modes (e.g., pictures with text or pictures with audio) were superior to single modes (e.g., text only or audio only) on consumer involvement in and perceived importance of the commercial content. That hypothesis was not supported, suggesting that at this time enhanced multimedia presented on mobile devices may not be necessary. Greater movement in the pictorial dimension of the ad design did not affect a consumer’s involvement in attending to the mobile ad, nor affect a consumer’s perceived importance of the mobile ad content.

The hypothesis regarding dynamic pictures versus static pictures (H2) was also not significant, suggesting that, in mobile advertising contexts, a slideshow display of static pictures is just as effective as streaming video for the time being. Creators of mobile content can use this information to guide design of mobile ads, as our research suggests that content receivers don’t necessarily perceive much, if any, difference between static pictures and streaming videos. Thus, content providers do not need to allocate as much bandwidth or internal memory of mobile devices to present commercial content (as would be required with a video presentation.

We found that perceptions of the commercial content and recall of the advertising information presented on a mobile device varied as a function of whether pictures were present or not: when pictures were absent, presenting an ad as text only (as in an SMS-type message) was superior in recall and perceptions to presenting an ad as an audio file, whereas when pictures were present, accompanying those pictures with an audio file was better perceived and better recalled than accompanying the pictures with text. The superiority of text to audio (in the absence of pictures) on recall has been supported in basic psychological research (c.f., Chaiken and Eagly 1976; Jacoby, Hoyer, and Zimmer 1983). The implication here is that if content providers of mobile ads cannot accompany the ad with photos, they should present the ad in text-only format, rather than audio.

The detrimental effects of visual redundancy on recall found in cognitive load research and tested in hypothesis 4 were not supported here. Although we did not find enhanced recall in the visual redundancy conditions, neither did we find detrimental effects of visual redundancy. This is similar to research in the communication literature that has found that the addition of redundant pictures to text improves recall in newspaper (Prabu and Kang 1998) and television media (Lang 1995). It is important to remember though, that this hypothesis only relates to visual redundancy; when pictures were present, our respondents preferred audio accompaniment to text (see H3).

Likewise, the superiority of using dual modes (visual and audio) to present information found in previous dual-processing research was not supported for our recall measure in H5. However, dual modes were superior in enhancing consumer perceptions of the value of mobile devices to obtain commercial content. Therefore, if a mobile content provider wants to raise consumers’ perceptions of the value of the device, it should present commercial content in dual modes, with the caveat that the dual mode presentation will not necessarily enhance recall for the content.

Hypothesis 6 predicted that complementary modes are preferred over competing modes. This hypothesis was marginally supported for both recall and perceptions of value, but the recall effects were in the opposite direction. Namely, participants who received content information over competing modes (two visual pieces of information) demonstrated better recall than participants who received complementary modes. This is also supported in the redundancy findings in H4. Perceptions of value, though, were enhanced in complementary mode conditions (and consistent with the dual mode findings in H5). These findings suggest that the best type of multimedia presentation of commercial content may depend on the goal of the advertiser (e.g., recall versus attitude change).

Hypotheses 7 and 8 related to behavioral intentions to use a mobile device to obtain commercial content and will be of interest to mobile content providers. We found that dynamic content did not lead to higher behavioral intentions, compared to static content. As dynamic content is more costly to present, this finding (combined with H2) suggests that, at the time our data were collected, consumers may not have expected full streaming content presented over wireless handheld devices (as is expected with other media, such as television or computer internet media).

Almost two-thirds of the variability in behavioral intentions to use a mobile device to obtain commercial content was predicted in our project. In addition, the inclusion of scales that measured emotional reactions to the device significantly enhanced predictions, relative to cognitive measures alone. This result confirms previous work by Kulviwat and colleagues (2007), which found that affect measures (capturing pleasure and arousal) significantly improved a model predicting intentions to use handheld devices, compared to a model with just cognitions (such as perceived usefulness, ease of use, and relative advantage of handheld devices). Together, these studies suggest that affect is an important component for consumers to consider when using their mobile devices. It also implies that content providers should consider emotional responses of consumers when designing commercial content to be presented over wireless devices.

Even though these results may appear complex, one thing is very clear for practitioners: it would be a mistake to merely replicate the form of advertisements presented on TV and the computer monitor. Mobile advertising is a new medium and, as such, requires an understanding of new rules of what works and what does not.  Although this was suspected, we now have some empirical evidence to guide marketers in what to do or not do. Generalizations of our findings are shown in Table 2.

Summary of Research Hypotheses, Results, and Conclusions

 Summary of Research Hypotheses, Results, and Conclusions

Limitations and Future Directions

We did not find as many modality effects as expected in this project and one possibility is that we did not consider individual differences in modality preferences; it is possible that consumers with certain personality traits will always desire full multimedia. Coupey and Sandgathe (2000) argue that, because interactive media has the potential for customization, more emphasis should be placed on person factors that influence how consumers want to receive information and how they process such customized messages. While the present project does not speak to person factors, future research on customizability within the mobile advertising environment should examine the effects of personality variables on preference across modalities.

Our research also does not address whether consumers want to receive commercial content over their wireless devices, nor do we know how customers will perceive the mobile device (or the mobile service provider) if they receive mobile advertising content without consent. In our research, it does appear that the commercial content presentation did not adversely affect perceptions of the device or intentions to use such as device in the future. Admittedly, this finding could be due to the fact that respondents’ attitudes toward the device were relatively high for all participants across all conditions (the lower bound of the 95% confidence interval for this index was greater than the midpoint value for the index (4) for all conditions). As a majority of our participants had never used a wireless handheld device to obtain interactive content prior to their participation in our study, our results might have been affected by the novelty of the experience. Also, we did not survey respondents prior to participation regarding their interest in cars or for whom car buying was particularly salient at the time of their participation. However, since we were not examining car purchase intentions or perceptions of the brand presented in the mobile ad specifically, this limitation is not likely to have influenced perceptions toward the device.

To determine the robustness of our findings, we also suggest field tests where consumers would experience noise and distractions typical of mobile device usage. In our project, participants sat in a relatively quiet environment and focused on just one task. Thus, the external validity of our results needs to be explored further. Similarly, our respondents were all young cell phone users. We don’t know if our findings extend to older users of cell phones (e.g., Baby boomers). Finally, it is possible that our findings are specific to advertising content. Future studies should examine whether our results hold across other types of content that can be presented on mobile devices, such as news, sports, or weather information.


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Appendix 1: Perceptions of Commercial Content and Mobile Device

Perceptions of Commercial Content and Mobile Device

Appendix 2: Attitudes and Behavioral Intentions

Attitudes and Behavioral Intentions

About the Authors

Suzanne Altobello Nasco (Ph.D., University of Notre Dame) is an Assistant Professor of Marketing at Southern Illinois University. Her research interests span a variety of topics in consumer decision-making, such as sports marketing, mature consumer choices for services, and consumer perceptions of content presented on mobile/wireless devices.

Gordon C. Bruner II (Ph.D., University of North Texas) is a Full Professor in the Marketing Department at Southern Illinois University.  He is the lead author of the Marketing Scales Handbook series.  Apart from his work with psychometric scales, his research in recent years has focused on the nexus of consumers and technology.