Qweh

International Journal of Management and Technology, Vol. 1 No. 1 (January, 2011) Copyright © Mind Reader Publications ISSN No. 0976-0924 www. ijmt. yolasite. com Towards an understanding of the youth’s perception of, and response to, mobile advertising in an emerging market An exploratory study Justin Henley Beneke Bus. Sc. (Hons) M. Bus. Sc, Cape Town School of Management Studies Faculty of Commerce University of Cape Town E-mail: Justin. [email protected] ac. za INTRODUCTION & BACKGROUND

The expansion of the global market, as well as the abundance and convergence of new technologies, has created new advertising opportunities for marketers (Bamba & Barnes, 2007). Together with this, technological advances, a shift towards advertising philosophies supporting one-to-one marketing and interactivity, and the increase of mobile penetration rates and mservice usage, have facilitated emergence of a direct marketing channel: mobile marketing (Karjaluoto, Lehto, Leppaniemi & Mustonen, 2007).

We Will Write a Custom Essay Specifically
For You For Only $13.90/page!


order now

Bamba & Barnes (2007) describe mobile marketing as “using a wireless medium to provide consumers with time-and-location-sensitive, personalized information that promotes goods, services and ideas, thereby benefiting all 1 Justin Henley Beneke stakeholders. ” Mobile marketing has been categorized into two models, the push-model and pull-model campaign. The latter refers to information which is requested by and sent to consumers, whilst the former refers to unsolicited communication, initiated by the marketer, and which in turn raises the issue of consumer’s permission and privacy (ibid).

The development of mobile technology has been a long journey of innovation and which is constantly evolving and updating as a result of consumers’ changing needs (Bamba & Barnes, 2007). Today, mobile penetration rates have reached staggering levels. It was estimated that the number of mobile phones worldwide hit the 4 billion mark in 2008, with year-on-year penetration growth estimated to reach 61% in 2008 (ITU, 2008). Approximately 67. 86% of South Africans personally own, rent or make use of a mobile phone (AMPS, 2009).

These high penetration rates have provided marketers with the opportunity to use mobile phones to deliver advertisements for products and services (Tsang et al. , 2004). It is predicted that the financial impact of mobile marketing will reach $24 billion by 2013 from just US $1. 8 billion in 2007, as more companies discover the benefits this new medium offers (Yaniv, 2008). It is estimated that globally 1. 5 billion users received SMS advertisements in 2008 (Yaniv, 2008).

This figure indicates the potential that exists for mobile advertising to become, if used in the right way, one of the most powerful, unique, best–targeted advertising mediums to reach customers (Leppaniemi & Karjaluoto, 2005). The Mobile Marketing Association (2008) reported that 70% of participants were very open to the concept of mobile marketing as the idea of an interactive, innovative and personal media channel was more appealing than traditional and digital media.

Jun and Lee (2007) speculate that mobile advertising will become the most important communication medium for marketers, the value of which is estimated to be in the hundreds of billions of dollars. Soon, it will be unusual for a company not to incorporate and align mobile advertising with its traditional marketing mix (Jun & Lee, 2007). Short Message Services (SMS) has become the new “buzzword” in the transmission of business to consumer mobile advertising, as there is no alternative which is as cheap and easy to use which works with all phones across all networks (Okazaki, 2005).

SMS exceeded all initial expectations and has gone on to become consumers’ preferred mobile service, with cell phone users worldwide sending more than 10 billion SMS messages each month (Carroll, 2007). 36% of South African adults, sixteen years and older, send SMS’s daily or weekly (Vodacom, 2008). 2 Towards an understanding of the youth’s perception.. Over 20 million “Please Call Me” messages are sent to more than 2. 5 million unique users’ everyday (ibid). By sponsoring this service, advertisers are provided with the opportunity to reach a mass market at a low cost (Lonergan, 2008).

As a result, mobile marketing has been dubbed the “7th mass media” (ibid). Multi-Media Services (MMS) builds on the successful foundations of SMS but allows for richer data content. However, due to varying mobile devices and phone capabilities, it is yet to have the same reach of SMS (Marketing Mix, 2008). Due to its ubiquitous nature, the mobile phone as a communication tool has one of the most extensive reaches (67%) in South Africa, compared to any other medium (Radio 94%, Outdoor 90%, Television 84%, Newspaper 48%, Magazine 40%, Internet 8% & Cinema 6%) as per 2009 AMPS data.

Mobile advertising allows the marketer to transcend the traditional communication “time-space paradigm” boundaries through the availability, interactivity, frequency and speed of communication provided by mobile devices (Scharl, Dickenger & Murphy, 2005). One of the strongest benefits of mobile advertising is the ability of the mobile device to replicate all the elements of traditional media to the consumer in one device as it can reach consumers in a multitude of new ways (Jun & Lee, 2007).

Mobile advertising provides the option of supporting both unique one-to-one and mass communication with consumers, incorporating personalized information based on time, location and preferences (Scharl et al, 2005). As cynicism and distrust of advertising and marketing efforts increase (Anderberg & Morris, 2006), it is necessary to explore new and innovative means to communicate with consumers. Consumers are living within a media saturated environment, with mass media estimated to occupy 70% of a consumer’s day, thus limiting the effectiveness of advertising (Newell & Meier, 2007). This has led to “advertising clutter”, most prevalent in raditional mass media, resulting in marketers moving their advertising focus towards less cluttered mediums, such as mobile advertising (ibid). Due to the high levels of control consumers possess over mobile advertising offers, it is perceived to be a medium that is less cluttered with unsolicited messages compared to that of traditional media. This allows the company opportunities to be innovative and can result in a competitive advantage to those brands that implement such a campaign successfully (ibid). However, due to the highly personal nature of the mobile phone, care must be taken when approaching customers with advertising.

It is vital that consumers are in control, have explicitly 3 Justin Henley Beneke given permission and are only receiving timely, relevant and personalized advertising (Yaniv, 2008). Excessive volumes of advertising and a lack of perceived control or value from such advertising has lead to a negative attitude towards mobile advertising and a general consumer perception of cynicism towards mobile advertising (Krishnamurthy, 2001). Due to the high reach of mobile phones, their low cost and high retention rates, expectations are high that this industry will succeed (Kondo, Jian & Shahriar, 2008).

The mobile channel (especially SMS), possesses the benefits of being immediate, customized, automated, direct, reliable, personal, discreet as well being a direct call to action that is far more impressive than any other channel (ibid). Special features of the mobile channel include its mobility, reachability, direct marketing capabilities, interactivity, two-way communication, branding opportunities, viral-marketing potential, timeliness and personalisation, the possibilities of this communication channel are immense (Karjaluoto et al, 2007).

The current literature all focuses on one common theme, that of the power of mobile advertising. Despite the harsh realities of the economic crisis putting pressure on advertising budgets, it has been claimed that the time to engage customer’s attention with something, new, different, and effective is now (Marketing Mix, 2008). Academics and practitioners agree that mobile advertising is a particularly effective marketing tool in reaching the youth market (Scharl et al, 2005). The youth have been found to be open to trying new and different things and are seen to be innovators in adopting new technologies (Kumar & Lim, 2008).

Like all forms of advertising, it is more effective to have a targeted campaign and the youth market proves to have the greatest potential for mobile advertising campaigns. RESEARCH STATEMENT Despite the proliferation of mobile advertising campaigns, as well the “glory and attention” paid to it, there is a lack of empirical studies in academic literature concerning the effectiveness of mobile advertising and the factors contributing to its success (Drossos et al, 2007; Leppaniemi & Karjaluoto, 2005; Dickenger et al, 2004; Bamba & Barnes, 2007). This research aims to fill the gap, specifically in the South African context.

As mobile advertising has the potential to be one of the most powerful advertising mediums, if used in the right manner (Leppaniemi & Karjaluoto, 2005), it is appropriate to study its potential for success. The aim of this study is to provide 4 Towards an understanding of the youth’s perception.. insights to mobile advertisers, particularly retailers who seek to efficiently manage the opportunities that mobile technology may offer them, with the emphasis on push marketing via SMS and MMS. METHODOLOGY RESEARCH DESIGN Our sample frame was limited to English-speaking consumers located in the Western Cape, specifically the Cape Town area.

Although the main respondents of the study were residents of Cape Town, the city’s metropolitan and international community are similar to South African major cities. Three focus groups were conducted over a period of one week. The focus group made use of open-ended questions which covered members’ previous experience with mobile advertising; their attitudes toward advertising in general and toward mobile advertisements in particular, as well as their opinion of what factors would influence the latter. A quantitative survey was then conducted. Person-to-person and computer-assisted (online) methods were used to obtain 250 responses.

Questionnaires were completed by hand at a major university and a small number of high schools. In order to randomise the technique, every third student walking past the questionnaire distribution point was approached to assist with the study. This approach proved beneficial, as it is one of the more effective ways to enlist cooperation and convey instructions clearly, which resulted in the respondents following the questionnaire’s instructions accurately. A web site was setup to host the questionnaire for the computer-assisted component of the empirical research.

Once respondents had completed a questionnaire, their responses were stored on the website and extracted at the end of survey window. COMPOSITION OF SAMPLE The final sample size comprised a total of 250 respondents. However, the demographics of these respondents did not perfectly reflect the South African population. The majority of respondents were white females between the ages of 16 and 25, who earn an average monthly income/allowance of less than R1000 (however the largest proportion of respondents, 44%, preferred not to divulge their monthly income).

Students with a low average monthly income/allowance represent the largest proportion of the sample, which is to be expected as 5 Justin Henley Beneke these characteristics generally define the youth market. The results of this study may therefore not be accurately extrapolated to the entire South African population in this segment. FINDINGS GENERAL OVERVIEW Five point Likert scales were used to measure responses to the variables used within this study. The questionnaire has been included in the appendix, in which the scale items may be seen. The most popular measure of central tendency is the mean.

Table 1 shows the means for each item, as well as the means for the average of each factor (averages in bold). “Average Content”, “Average Personalisation”, “Average Attitudes towards Advertising”, “Average Knowledge”, “Average Incentive” and “Average Purchase Intention” are variables which have means that can be rounded up/down to 3. This represents “Neutral” responses in the questionnaire and therefore little information can be gleaned from these figures. All other variables display a greater degree of skewness in the distribution of the data which allows one to make tentative conclusions.

This implies that the data deviates from a normal distribution. The Lilliefors test of normality resulted in p-values of less than 0. 01 for all variables which allows one to reject the null hypothesis that states that the data is normal at the 1% significance level. “Average Interactivity” has a mean of 2 (rounded down) which represents “Disagree” and is skewed to the right. This suggests that consumers do not value features within the mobile advertisement that allows them to respond or have further communication with the advertiser. “Average Innovativeness” has a mean of 4 (rounded up), representing “Agree”, and is skewed to the left.

This indicates that consumers like new and different things and therefore may be open to new forms of communication, such as mobile advertising. Although “Average Knowledge” has a mean of 3 (rounded down), the two items which comprise the factor have been answered differently. “Knowldg1” and “Knowldg2” have means of 4 and 3 respectively which imply that consumers agree that they understand the applications on their mobile phones well, however they do not necessarily consider themselves experts on the latest mobile phone technology in comparison to their friends. Average Control” has a mean of 4 (rounded down) and is skewed to the left. Consumers therefore appear to value having control over the content and access to 6 Towards an understanding of the youth’s perception.. their personal information as well as their participation in mobile advertising campaigns. “Average SPAM” also has a mean of 4 (rounded up) and is skewed to the left suggesting that consumers have a fear of SPAM and are concerned that mobile advertising will result in SPAMMING. Average Attitudes towards Mobile Advertising” has a mean of 2 (rounded down) and is skewed to the right which provides us with preliminary evidence that negative attitudes concerning mobile advertising exist. “Average Attention” has a mean of 2 (rounded down) and is skewed to the right, indicating that little attention is paid to mobile advertisements. This is confirmed by figure 1 which shows that the majority of respondents read mobile advertisements occasionally or ignore them completely. “Average Ad Source” has a mean of 4 (rounded up) and is skewed to the left.

The source of the advertisement is important to consumers as they believe that they are more likely to read the mobile advertising message if the advertiser is familiar to and trusted by the consumer. “Average Involvement” in the mobile advertisement has a mean of 2 (rounded down) and is skewed to the right. Consumers do not appear to put a great deal of effort into reading and evaluating the mobile advertisement. Figure 2 shows that the majority of respondents only read about a quarter of the mobile advertisement whilst the second highest proportion of respondents does not read them at all.

WHAT RESPONDENTS GENERALLY DO WHEN THEY RECEIVE A MOBILE ADVERTISEMENT 120 100 80 60 40 20 0 Ignore it Completely Read it Read it After Read it when I Read it Right Occassionally Accumulating Get Time Away too Many of Them Figure 1: Attention Paid to the Mobile Advertisement 7 Justin Henley Beneke HOW MUCH OF THE MOBILE ADVERTISEMENT IS READ 80 70 60 50 40 30 20 10 0 Not At All Read About a Quarter of the Message Read About Read About Half the Three-Quarters Message of the Message Read the Whole Message Figure 2: Involvement in the Mobile Advertisement High variances were observed on some items.

This indicates that these items were answered differently by respondents. For example, the item “Content2” has a variance of 1. 8719, suggesting that respondents did not answer the question in the same way and that answers varied around the mean. This indicates that there is a possibility of differences existing among respondents. “Attitudes towards Mobile Advertising” has a relatively low variance (0. 61), indicating that respondents did not answer questions pertaining to this construct differently. This suggests that most respondents have a negative attitude towards mobile advertising.

ESTABLISHING CORRELATIONS Scatterplots were constructed to ascertain whether relationships between two variables might exist (Keller & Warrack, 2003). Figure 3 depicts a moderate, positive relationship between “Average Content” and “Average Attitude towards Mobile Advertising”, which is confirmed by a moderately high and positive correlation coefficient of 0. 40580. Moderate, positive relationships also exist between “Average Interactivity”, “Average Personalisation”, “Average Attitude towards Advertising in General”, “Average Innovativeness” and the dependent variable, “Average Attitude towards Mobile Advertising” (figures 4-7).

These relationships are confirmed by correlation coefficients of 0. 36008, 0. 45460, 0. 37432 and 0. 29252 respectively. 8 Towards an understanding of the youth’s perception.. Scatterplot: Ave Content vs. Ave AttMA Ave AttMA = 1. 3371 + . 31391 * Ave Content Scatterplot: Ave Interact vs. Ave AttMA Ave AttMA = 1. 6830 + . 25151 * Ave Interact Correlation: r = . 40580 5. 0 4. 5 4. 0 3. 5 Correlation: r = . 36008 5. 0 4. 5 4. 0 3. 5 Ave AttMA 1. 0 1. 5 2. 0 2. 5 3. 0 3. 5 4. 0 4. 5 5. 0 5. 5 Ave AttMA 3. 0 2. 5 2. 0 1. 5 1. 0 0. 5 0. 5 3. 0 2. 5 2. 0 1. 5 1. 0 0. 5 0. 5 1. 0 1. 5 2. 0 2. 5 3. 0 3. 5 . 0 4. 5 5. 0 5. 5 Ave Content 0. 95 Conf. Int. Ave Interact 0. 95 Conf. Int. Figure 3: “Attitude towards Mobile Advertising” vs. Advertising” vs. “Content” Scatterplot: Ave Person vs. Ave AttMA Ave AttMA = 1. 2396 + . 32283 * Ave Person Figure 4: “Attitude towards Mobile “Interactivity” Scatterplot: Ave AttAd vs. Ave AttMA Ave AttMA = 1. 3233 + . 32114 * Ave AttAd Correlation: r = . 45460 5. 0 4. 5 4. 0 3. 5 5. 0 4. 5 4. 0 3. 5 Correlation: r = . 37432 Ave AttMA 3. 0 2. 5 2. 0 1. 5 1. 0 0. 5 0. 5 Ave AttMA 1. 0 1. 5 2. 0 2. 5 3. 0 3. 5 4. 0 4. 5 5. 0 5. 5 3. 0 2. 5 2. 0 1. 5 1. 0 0. 5 0. 5 1. 1. 5 2. 0 2. 5 3. 0 3. 5 4. 0 4. 5 5. 0 5. 5 Ave Person 0. 95 Conf. Int. Ave AttAd 0. 95 Conf. Int. Figure 5: “Attitude towards Mobile Advertising” vs. Advertising” vs. “Personalisation Figure 6: “Attitude towards Mobile “Attitude toward Advertising in General” 9 Justin Henley Beneke Scatterplot: Ave Innov vs. Ave AttMA Ave AttMA = 1. 0782 + . 32366 * Ave Innov Scatterplot: Ave Knowldg vs. Ave AttMA Ave AttMA = 2. 0979 + . 05970 * Ave Knowldg Correlation: r = . 29252 5. 0 4. 5 4. 0 3. 5 5. 0 4. 5 4. 0 3. 5 Correlation: r = . 06742 Ave AttMA 3. 0 2. 5 2. 0 1. 5 1. 0 0. 5 0. 5 Ave AttMA 1. 0 1. 2. 0 2. 5 3. 0 3. 5 4. 0 4. 5 5. 0 5. 5 3. 0 2. 5 2. 0 1. 5 1. 0 0. 5 0. 5 1. 0 1. 5 2. 0 2. 5 3. 0 3. 5 4. 0 4. 5 5. 0 5. 5 Ave Innov 0. 95 Conf. Int. Ave Knowldg 0. 95 Conf. Int. Figure 7: “Attitude towards Mobile Advertising” vs. Advertising” vs. “Innovativeness” Figure 8: “Attitude towards Mobile “Knowledge” Figure 8 suggests that there is no relationship between consumers’ “Knowledge” of mobile phone technology and their “Average Attitude towards Mobile Advertising”, as the correlation coefficient of 0. 06742 is close to zero. Figure 9 illustrates a moderate negative relationship (r=0. 267) between “Average Control” and “Average Attitude towards Mobile Advertising”. Similarly, figure 10 shows a weak negative relationship (r=-0. 1856) between “Average SPAM” and “Average Attitude towards Mobile Advertising”. 10 Towards an understanding of the youth’s perception.. Scatterplot: Ave Control vs. Ave AttMA Ave AttMA = 3. 9216 – . 3886 * Ave Control Scatterplot: Ave Spam vs. Ave AttMA Ave AttMA = 2. 9341 – . 1649 * Ave Spam Correlation: r = -. 3267 5. 0 4. 5 4. 0 3. 5 3. 0 2. 5 2. 0 1. 5 1. 0 0. 5 2. 0 Correlation: r = -. 1856 5. 0 4. 5 4. 0 3. 5 Ave AttMA 2. 5 3. 0 3. 5 4. 4. 5 5. 0 5. 5 Ave AttMA 3. 0 2. 5 2. 0 1. 5 1. 0 0. 5 0. 5 1. 0 1. 5 2. 0 2. 5 3. 0 3. 5 4. 0 4. 5 5. 0 5. 5 Ave Control 0. 95 Conf. Int. Ave Spam 0. 95 Conf. Int. Figure 9: “Attitude towards Mobile Advertising” vs. Advertising” vs. “Control” Figure 10: “Attitude towards Mobile “SPAM” The relationship between the construct “Average Attitude towards Mobile Advertising” and the construct “Average Attention” paid to mobile advertising is strong and positive, with a correlation coefficient of 0. 70001 (figure 11). The relationships depicted in figure 12 and 13 are moderate and positive.

The correlation coefficient between “Average Attention” and “Average Involvement” variables is 0. 48934, whilst the correlation coefficient between “Average Involvement” and “Average Purchase Intention” variables is 0. 45442. Finally, the correlation coefficient of 0. 53278 (figure 14) indicates that a moderate to fairly high, positive relationship between “Average Attitude towards Mobile Advertising” and “Average Purchase Intention” exists. This allows us to make a tentative finding that mobile advertising is a successful sales generating tool in South Africa.

Further data analysis will later explore whether these relationships are in fact causal or merely spurious correlations. 11 Justin Henley Beneke Scatterplot: Ave AttMA vs. Ave Attent Ave Attent = . 16034 + . 90972 * Ave AttMA Scatterplot: Ave Attent vs. Ave Involve Ave Involve = 1. 2694 + . 43071 * Ave Attent Correlation: r = . 70001 5. 0 4. 5 4. 0 3. 5 5. 5 5. 0 4. 5 4. 0 Correlation: r = . 48934 Ave Involve Ave Attent 3. 5 3. 0 2. 5 2. 0 1. 5 1. 0 0. 5 0. 5 3. 0 2. 5 2. 0 1. 5 1. 0 0. 5 0. 5 1. 0 1. 5 2. 0 2. 5 3. 0 3. 5 4. 0 4. 5 5. 0 1. 0 1. 5 2. 0 2. 5 3. 0 3. 5 4. 0 4. 5 5. Ave AttMA 0. 95 Conf. Int. Ave Attent 0. 95 Conf. Int. Figure 11: “Attitude towards Mobile Advertising” vs. “Involvement” “Attention” Figure 12: “Attention” vs. Scatterplot: Ave Involve vs. Ave PI Ave PI = 1. 5587 + . 42723 * Ave Involve Scatterplot: Ave AttMA vs. Ave PI Ave PI = 1. 1966 + . 57296 * Ave AttMA Correlation: r = . 45442 4. 5 4. 0 3. 5 3. 0 4. 5 4. 0 3. 5 3. 0 Correlation: r = . 53278 Ave PI 2. 5 2. 0 1. 5 1. 0 0. 5 0. 5 Ave PI 1. 0 1. 5 2. 0 2. 5 3. 0 3. 5 4. 0 4. 5 5. 0 5. 5 2. 5 2. 0 1. 5 1. 0 0. 5 0. 5 1. 0 1. 5 2. 0 2. 5 3. 0 3. 5 4. 0 4. 5 5. 0 Ave Involve 0. 5 Conf. Int. Ave AttMA 0. 95 Conf. Int. Figure 13: “Involvement” vs. “Purchase Intention” Figure 14: “Attitude towards Mobile Advertising” vs. “Purchase Intention” 12 Towards an understanding of the youth’s perception.. CONSUMER PERCEPTIONS AND TENDENCIES The figures below represent questions included in the questionnaire that were not used for statistical analysis, but still revealed results of interest. The majority of respondents indicated that they would never like to receive mobile advertisements, which suggests that strong negative attitude towards mobile advertising exist.

The largest proportion of the remaining respondents indicated that only weekdays are preferred (see figure 15). On these days of the week, consumers prefer receiving mobile advertisements in the afternoon or early evenings. PREFERRED TIMES 120 100 80 60 40 20 0 TO RECEIVE MOBILE ADVERTISEMENTS Figure 15: Preferred Times to Receive Mobile Advertisements 36% of respondents consider mobile advertisements to be SPAM when they receive advertisements 2-3 times a week, with a further 24% having the more extreme view that receiving mobile advertisements even once a week is SPAM (see figure 16).

Respondents indicated that they prefer as minimal communication as possible from mobile advertisers. These findings confirm the literature which states that 2-3 times a week is the appropriate frequency of sending advertising messages. Respondents were not very willing to provide personal information. This is indicated by the fact that, only 49% of respondents were prepared to provide the highest recorded type of information, 13 Justin Henley Beneke gender (see figure 17). Although respondents are not very willing to provide personal nformation; gender, age, email address, cell phone number and name were the most commonly cited pieces of information that consumers feel comfortable giving to advertisers. Interestingly, only 30% of consumers are prepared to provide their cell phone number which could prove to be problematic in initiating a mobile advertising campaign. This further supports the finding that strong negative attitudes exist towards mobile advertising. As per figure 17, consumers particularly dislike giving out their bank details, income levels, landline numbers and address.

This confirms the literature which suggests that consumers are more willing to give low concernlevel personal information (demographic, occupation and lifestyle information) as opposed to high concern level personal information (financial data and personal identifiers). These findings confirm previous literature on privacy issues surrounding mobile advertising where consumers have a strong fear of SPAM and are highly concerned about losing control of the access and use of their personal information.

MESSAGE FREQUENCY AT WHICH CONSUMERS REGARD MOBILE ADVERTISING AS SPAM 9% 11% 36% 2-3 Times a Week Once a Week 3-6 Times a Week 20% 2-3 Times a Day Once a Day 24% Figure 16: Message Frequency at which Consumers Regard Mobile Advertising as SPAM 14 Towards an understanding of the youth’s perception.. PERCENTAGE OF RESPONDENTS WHO ARE WILLING TO PROVIDE PERSONAL INFORMATION 60% 50% 40% 30% 20% 10% 0% 45% 24% 49% 38% 18% 0% 23% 13% 2% 3% 3% 29% 20% 30% Figure 17: Personal Information Consumers are Willing to Provide Figure 18 indicates that respondents are more trusting of recommendations from family and friends.

They are more likely to buy a product if the mobile advertisement were forwarded by friends and family. Consumers’ distrust of advertisers and trust of family and friends, as well as the ease with which consumers can forward messages via SMS, implies that mobile advertising could be used to establish successful word-of-mouth campaigns. Marketers need to harness the viral potential of mobile advertising. I WOULD BE MORE LIKELY TO BUY A PRODUCT IF THE MOBILE ADVERTISEMENT WERE FORWARDED TO ME BY FAMILY OR FRIENDS 15% 9% 14% Strongly Disagree Disagree Neutral Agree 21% 41% Strongly Agree

Figure 18: The Viral Potential of Mobile Advertising 15 Justin Henley Beneke Although almost all respondents indicated that their handsets are equipped to receive an MMS, the majority of respondents would prefer not to receive mobile advertisements containing sound, images and video clips (as indicated in figure 19). This is contrary to literature and could be an indication of consumers’ fear of SPAM (consumers are unwilling to receive any mobile advertisements even if it contains sound, images and video clips) and the low technology adoption rates in SA.

However, more research would be needed in order to confirm these tentative findings. I PREFER TO RECEIVE MOBILE ADVERTISMENTS THAT CONTAIN SOUND, IMAGES AND VIDEO CLIPS MORE THAN PLAIN TEXT ADVERTISEMENTS 70 60 50 40 30 20 10 0 Strongly Disagree Disagree Neutral Agree Strongly Agree Figure 19: Consumers Preferred Type of Mobile Advertisement CONCLUSIONS Despite the success of mobile advertising indicated by the positive relationship between consumers’ attitudes towards mobile advertising and purchase intentions, negative attitudes towards mobile advertising currently exist amongst the youth in South Africa.

This finding confirms that of Van der Waldt et al (2009). Therefore, it can be deemed to be unsuccessful in generating sales at present in South Africa and will only be effective in the future if these attitudes are addressed and changed. In order to convert these into positive attitudes, marketers need to address the critical underlying factors which influence consumers’ attitudes towards mobile advertising. Statistical analysis confirmed the mobile advertising literature and identified six predictors of “Attitudes towards Mobile Advertising”: “Content”, “Personalisation”, 6 Towards an understanding of the youth’s perception.. “Attitude towards Advertising in General”, consumers’ level of “Innovativeness”, consumer’s lack of “Control” and fear of “SPAM”. Privacy issues, specifically “Control”, emerged as the most important and significant aspect of mobile advertising for consumers. It is evident that consumers want more control over the access to and use of their personal information and their participation in mobile advertising campaigns. Therefore, the less control consumers have, the more negative their attitude towards mobile advertising.

The “Content” of the mobile message is the second-most influential predictor of “Attitude towards Mobile Advertising”. Evidently, consumers value helpful, informative, creative and entertaining mobile advertisements. Following conventional wisdom, “Attitude towards Advertising in General” is an important factor affecting consumer attitudes towards mobile advertising. The more positive a consumer’s “Attitude towards Advertising in General”, the more positive their “Attitude towards Mobile Advertising” will be. Finally, “Personalisation” is an influential predictor of “Attitudes towards Mobile Advertising”.

This implies that consumers value mobile messages that are tailored to their preferences and habits, time and location. A SUGGESTED FRAMEWORK FOR MOBILE MARKETERS Based on the research conducted, the importance of positive attitudes towards mobile advertising is evident. However, marketers need to realise that despite the many benefits associated with mobile advertising in reaching the youth, mobile advertising may not be as effective due to the current negative attitudes that exist in the South African youth market.

Therefore mobile marketers should consider our five golden rules (5 P’s) when formulating mobile advertising campaigns in order to create positive attitudes towards mobile advertising: • • • • • Give power to the consumer Be private with the use of consumer’s personal information Be punchy with the message content Be personalised Be polite when communicating 17 Justin Henley Beneke Figure 20: The 5 P’s of Successful Mobile Advertising In order for consumers to have more control over the terms of the relationship, marketers need to ‘give power to the consumer’.

Marketers should therefore only use permission-based campaigns in which explicit authorisation must be obtained from them before communication can commence. A clear, free-of-charge opt-out feature must also be included in the mobile advertisement to allow consumers to terminate their participation easily and at any time. If the power lies in consumers hands they would be less afraid of the sale and abuse of their personal information. This in turn would decrease their fear of SPAM and also protect the credibility of mobile advertising as a marketing medium.

Marketers should ‘be private with the use of consumer’s personal information’ thereby transferring more control to the consumer. Marketers need to view the exchange of personal information as a “social contract” between consumers and the company. The use, access and distribution of this information should be protected and respected at all times to refrain from 18 Towards an understanding of the youth’s perception.. violating this implicit “social contract”. Research indicated that only low concern-level personal information should be requested: gender, age, email address, cell phone number and name.

Bank details, income levels, landline numbers and address should not be asked so as to circumvent the creation of negative attitudes towards mobile advertising or raising consumer suspicion. Literature, focus groups and statistics confirmed that consumers particularly fear the sale of their personal information and this should be avoided by companies so as to respect consumers’ confidentiality. Furthermore, the respect of consumers’ privacy would increase consumers’ trust and decrease their fear of SPAM. Due to the limited number of characters in a mobile advertisement it is crucial for marketers to ‘be punchy with the message content’.

The messages must be creative and entertaining as well as informative in order to captivate consumers’ attention and keep them open to future communication. This can be done through the use of humour, graphics, sound and video clips. However, findings show that consumers are unwilling to receive this type of content at this point in time. Despite this, marketers should not dismiss this aspect of mobile advertising completely. As mobile technology is diffusing and advancing rapidly, this aspect could possibly be temporary and could prove to be an important determinant of attitudes in the near future.

Content should also be varied to keep them interested and avoid large defection rates of consumers opting-out of the campaign. Effective content would not only encourage participation in the campaign but also curb consumers’ fear of SPAM. Communication would be desired and welcomed rather than being considered unwanted, unsolicited messages which are forced onto them. Furthermore, by using punchy content, mobile advertising has the potential to go viral, as it is one of the easiest and cheapest mediums to pass on advertisements.

Findings have also indicated that consumers will be more willing to buy an advertised product if it is forwarded by friends or family. In order for marketers to obtain consumers’ attention they need to offer consumers something of value. To do this, messages need to ‘be personalised’. By sending relevant and targeted messages, marketers can decrease irritation levels and fear of SPAM among consumers and prevent consumers from being overwhelmed by excessive amounts of unnecessary messages. Marketers should tailor their advertisements to consumers’ profiles (past purchasing behaviour and 9 Justin Henley Beneke demographics), preferences, habits and interests. Additional customisation can be achieved through the latest in mobile technology, location-based advertising in which messages are sent according to the consumer’s proximity to the advertiser’s store. Personalisation is critical as consumers apply a great deal of selectivity in terms of the attention paid to commercial stimuli and have a higher level of awareness of stimuli that meet their needs and interests. Not only can marketers tailor their message content but they can also tailor their target audience.

Although no differences in attitudes towards mobile advertising existed among different demographic groups within our sample frame (age, race, gender, occupation or income) research suggested that the more innovative an individual, the more positive their attitude towards mobile advertising. Therefore, marketers should try to identify and target innovators and opinion leaders amongst the youth market as they are more open to trying new things and are thus more accepting of a new medium such as mobile advertising.

Due to the intense fear of SPAM inherent in the majority of consumers it is imperative to ‘be polite when communicating’ with consumers. Message frequency needs to be limited to 1-3 times a week to avoid consumers being inundated with mobile advertising. Otherwise mobile advertising would be considered as SPAM, resulting in negative attitudes developing. Youth prefer that messages are sent in the afternoon and early evening on weekdays only. It is important to bear these in mind as they affect the primary predictors of “Attitude towards Mobile Advertising”.

By following these 5 guidelines marketers will maximise the probability of sending the right message to the right person at the right time. This should assist in transforming current negative attitudes towards mobile advertising among the youth market in SA into positive attitudes. It is important for marketers to note that whilst mobile advertising is believed to have more benefits than traditional media it should not be used in isolation. It should rather form part of an integrated marketing campaign and should be complementary in nature. This complementary role is particularly important as this new medium is still in ts infancy in South Africa. 20 Towards an understanding of the youth’s perception.. The five guidelines will aid in obtaining consumers’ attention and involvement in mobile advertisements, thereby allowing marketers to capitalise on the potential of mobile advertising to be a successful medium to target the youth of South Africa. LIST OF REFERENCES Anderberg, J. and Morris, J. (2006), “Authenticity and transparency in the advertising industry: An interview with John Morris”. Journal of Management Development, Vol. 25, No. 10, pp. 1021-1023 Bamba, F. and Barnes, J. 2007), “SMS advertising, permission and the consumer: a study”. Business Process Management Journa, Vol. 13, No. 6. pp. 815-829 Barnes, S. J. (2003), “Wireless digital advertising: nature and implications”. International Journal of Advertising, Vol. 21 No. 3, pp. 399-420 Barwise, P. and Strong, C. (2002), “Permission-Based Mobile Advertising”. Journal of Interactive Marketing, Vol. 16, No. 1, pp. 14-24 Bauer, H. , Reichardt, T. , Barnes, S. and Neumann, M. (2005), “Driving Consumer Acceptance of Mobile Marketing: A Theoretical Framework and Empirical study”. Journal of Electronic Commerce Research, Vol. No. 3, pp. 181-197 Bellman, S. , Johnson, E. and Lohse, G. (2001), “To Opt-In or Opt-Out? It Depends on the Question”. Communications of the ACM, Vol. 44, No. 2 Carroll, A. , Stuart, B. and Scornavacca, E. (2007), “Consumer perceptions and attitudes towards SMS advertising: recent evidence from New Zealand”. International Journal of Advertising, Vol. 26, No. 1, pp. 79–98 21 Justin Henley Beneke Carter, E. (2007), “Mobile Marketing and Generation Y African-American Mobile Consumers: The issues and the opportunities”. International Journal of Mobile Marketing, Vol. 3, No. , pp. 62-66 Casal, C. (2002), “Regulating Spam: Opting in or opting out? ” Centre for Technology, Policy and Industrial development, Vol 4, No. 2, pp. 42-48 Dickenger, A and Haghirian, P. (2004), “An Investigation and Conceptual Model of SMS Marketing”. Proceedings of the 37th Hawaii International Conference on System Sciences. Hawaii, USA: IEEE Drossos, D. , Giaglis, G. , Lekakos, G. , Kokkinaki, F. and Stavraki, M. (2007), “Determinants of Effective SMS Advertising: An Experimental Study”. Journal of Interactive Advertising, Vol. 7, No. 2 Elliot, M. T. and Speck, P. S. 1998), “Consumer Perception of Advertising clutter and its impact across various media”. Journal of Advertising Research, Vol. 38, No. 1, Pp. 29 – 41 Hanley, M. and Becke, M. (2008), “Cell Phone Usage and Advertising Acceptance among college students”. International Journal of Mobile Marketing, Vol. 3, No. 1, pp. 67-80 Hanley, M. , Becker, M. and Martinsen, J. (2006), “Factors Influencing Mobile Advertising Acceptance: Will Incentives Motivate College Student to Accept Mobile Advertisement? ”. International Journal of Mobile Marketing. Vol. 1, No. 1, pp. 50-58 Jin, C and Villegas, J. 2008) “Mobile Phone Users’ Behaviours: The Motivation Factors of the Mobile Phone User”. International Journal of Mobile Marketing. Vol. 3, No. 2, pp. 4-14 Jun, J. and Lee, S. (2007), “Mobile Media and its Impact on Consumer Attitudes towards Mobile Advertising”. International Journal of Mobile Marketing. Vol. 2 No. 1 pp. 50-58 22 Towards an understanding of the youth’s perception.. Karjaluoto, H. , Lehto, H. , Leppaniemi, M. and Mustonen, T. (2007), “Insights into the Implementation action of Mobile Marketing Activities”. International Journal of Mobile Marketing, Vol. 2, No. 2, pp. 10-20 Kondo, F.

N, Jian, Z. N. and Shahriar, A. (2008), “Gradual Changes in Repeat Customers’ Adoption Behaviour toward Responses to Mobile Direct Mail Coupon Promotions”. International Journal of Mobile Marketing, Vol. 3, No. 2, pp. 15-24 Krishnamurthy, S (2001), “A Comprehensive Analysis of Permission Marketing”. Journal of Computer-Mediated Communication, Vol. 6, No. 2 Ktoridou, D. , Epaminonda, E. , and Kaufmann, H. (2008), “Technological challenges and consumer perceptions of the use of Mobile Marketing: Evidence from Cyprus”. International Journal of Mobile Marketing. Vol. 3. No. 2 Kumar, A. & Lim, H. 2008), “Age Differences in Mobile Service Perceptions: Comparison of Generation Y and Baby Boomers”. Journal of Service Marketing, Vol. 22, No. 7, pp. 568-577 Leppaniemi, M and Karjaluoto, H (2005), “Factors influencing consumers’ willingness to accept mobile advertising: a conceptual model”. International Journal of Mobile Communications, Vol. 3, No. 3, pp. 197-212 Leppaniemi, M. and Karjaluoto, H. (2008), “Mobile Marketing: From Marketing Strategy to Mobile Marketing Campaign Implementation”. International Journal of Mobile Marketing, Vol. 3, No. 1, pp. 50-61 Maneesoonthorn, C. and Fortin, D. 2006), “Texting Behaviour and Attitudes toward Permission Mobile Advertising: An Empirical Study of Mobile Users’ Acceptance of SMS for Marketing Purposes”. International Journal of Mobile Marketing, Vol. 1, No. 1, pp. 66-72 23 Justin Henley Beneke Marketing Mix (2008), The Marketer’s Guide to Mobile, Vol. 26, No. 11/12 Milne, G. and Rohm, A. (2000), “Consumer Privacy and Name Removal Across Direct Marketing Channels: Exploring Opt-In and Opt-Out Alternatives”. Journal of Public Policy and Marketing, Vol. 19 No. 2, pp. 238-249 Mobile Marketing Association (2008) URL: [Accessed 11 May] Newell, . J. and Meier, M. 2007), “Desperately Seeking Opt-In: A field report from a Student-Led Mobile Marketing Initiative”. International Journal of Mobile Marketing, Vol. 2, No. 2, pp. 5357 Okazaki, S. (2005), “Mobile advertising adoption by multinationals: Senior executives’ initial responses”. Journal of Internet Research, Vol. 15 No. 2, pp. 160-180 Petty, D (2000), “Marketing without Consent: Consumer Choice and Costs, Privacy, and Public Policy”. American Marketing Association, Vol. 19 No. 1, pp. 42-53 Phelps, J. , Nowak, G and Ferrel, E. (2000), “Privacy Concerns and Consumers Willingness to Provide Personal Information”.

Journal of Public Policy and Marketing, Vol. 19, No. 1, pp. 27-41 Rohm, J. and Sultan, F. (2006), “An Exploratory Cross-market Study of Mobile Marketing Acceptance”. International Journal of Mobile Marketing, Vol. 1, No. 1, pp. 4-12 Sadeh, N. (2002), M-Commerce: Technologies, Services, and Business Models,New York: John Wiley & Sons Inc 24 Towards an understanding of the youth’s perception.. Scharl, A. , Dickenger, A. and Murphy, J (2005), “Diffusion and Success Factors of Mobile Marketing”. Electronic Commerce Research and Applications, Vol. 4, pp. 159-173 Shavitt, S. , Lowrey, P. nd Haefner, J. (1998), “Public Attitudes towards Advertising: more favourable than you might think”. Journal of Advertising Research, Vol. 38, No. 4, pp 7 – 22 Siau, K. and Shen, Z. (2003), “Building Customer Trust in Mobile Commerce”, Communications of the ACM. Vol. 46, No. 4, pp. 91-94 Stewart, D. , and Pavlou, P. (2002), “From Consumer Response to Active Consumer: Measuring the Effectiveness of Interactive Media”. Journal of the Academy of Marketing Science, Vol. 30, No. 4, pp. 376 – 396 Taylor, A. S. and Harper, R. (2001), “Talking Activity: Young People and Mobile Phones”.

Proceedings of the CHICHI 2001 Workshop: Mobile Communications: Understanding Users, Adoption & Design, Seattle, WA Tsang, M. M; Ho, S and Liang, T. (2004), “Consumer Attitudes Toward Mobile Advertising, an Empirical Study”. International Journal of Electronic Commerce, Vol. 8, No. 3, pp. 65-78 Vatanparast, R. (2007), “Piercing the Fog of Mobile Advertising”. The Sixth International Conference on Mobile Business ICMB 2007 July. Toronto, Ontario, Canada Vatanparast, R. , and Asil, M. (2007), “Factors Affecting the use of Mobile Advertising”. Journal of Mobile Marketing, Vol. 2.

No. 2 Vodacom, (2008), “The Mobile Media Solution Guide: The 7th Mass Media Channel”. Marketing Mix. Vol. 26. No. 11 pp. 11-19 Yaniv, G. (2008), “Sold on Mobile Marketing: Effective Wireless Carrier Mobile Advertising and How to Make it Even More So”. International Journal of Mobile Marketing, Vol. 3, No. 2, pp. 86-91 The author would like to acknowledge, and state his thanks for, the intellectual contribution of three Bus. Sc. Marketing Honours students in compiling this paper – G. Cumming, A. Stevens and M. Versfeld. 25 Justin Henley Beneke Table 1: Descriptive Statistics

Variable Content1 Content2 Content3 Ave Content Interct1 Interct2 Ave Interact Person1 Person2 Person3 Person4 Ave Person AttAd1 AttAd2 Ave AttAd Innov1 Innov2 Ave Innov Knowldg1 Knowldg2 Ave Knowldg Control1 Control2 Control3 Control4 Ave Control Spam1 Spam2 Ave Spam AttMA1 AttMA2 AttMA3 AttMA4 Ave AttMA Attent1 Attent2 Attent3 Ave Attent AdSourc1 AdSourc2 Ave AdSourc Involve1 Involve2 Ave Involve Incent1 Incent2 Incent3 Ave Incent PI1 PI2 Ave PI Descriptive Statistics Valid N Mean Minimum Maximum Variance 250 3. 192000 1. 000000 5. 000000 1. 553349 250 3. 340000 1. 000000 5. 000000 1. 71888 250 2. 696000 1. 000000 5. 000000 1. 770667 250 3. 076000 1. 000000 5. 000000 1. 020975 250 2. 419355 1. 000000 5. 000000 1. 415209 250 2. 508000 1. 000000 5. 000000 1. 407566 250 2. 463678 1. 000000 5. 000000 1. 252202 250 3. 608000 1. 000000 5. 000000 1. 628851 250 3. 020080 1. 000000 5. 000000 1. 706424 250 3. 260000 1. 000000 5. 000000 1. 606827 250 3. 283401 1. 000000 5. 000000 1. 542819 250 3. 292870 1. 000000 5. 000000 1. 211398 250 3. 321285 1. 000000 5. 000000 1. 117659 250 2. 778226 1. 000000 5. 000000 1. 175913 250 3. 049755 1. 000000 5. 000000 0. 830046 250 3. 775100 1. 00000 5. 000000 0. 672312 250 3. 791165 1. 000000 5. 000000 0. 880083 250 3. 783133 1. 000000 5. 000000 0. 499027 250 4. 120482 1. 000000 5. 000000 0. 869018 250 2. 740000 1. 000000 5. 000000 1. 261446 250 3. 430241 1. 000000 5. 000000 0. 779265 250 4. 020000 1. 000000 5. 000000 1. 087952 250 4. 128514 1. 000000 5. 000000 0. 818826 250 4. 440000 1. 000000 5. 000000 0. 568675 250 4. 076000 1. 000000 5. 000000 0. 865687 250 4. 166129 2. 250000 5. 000000 0. 431761 250 3. 674699 1. 000000 5. 000000 1. 175304 250 3. 983936 1. 000000 5. 000000 0. 778858 250 3. 829317 1. 000000 5. 000000 0. 74453 250 2. 678715 1. 000000 5. 000000 0. 924888 250 1. 976000 1. 000000 5. 000000 0. 979341 250 2. 384000 1. 000000 5. 000000 1. 008578 250 2. 172000 1. 000000 5. 000000 0. 970297 250 2. 302679 1. 000000 4. 500000 0. 610926 250 2. 228000 1. 000000 5. 000000 1. 060257 250 2. 173387 1. 000000 5. 000000 1. 291343 250 2. 364000 1. 000000 5. 000000 1. 903116 250 2. 255129 1. 000000 4. 666667 1. 031798 250 3. 564000 1. 000000 5. 000000 1. 074201 250 3. 676000 1. 000000 5. 000000 1. 023116 250 3. 620000 1. 000000 5. 000000 0. 953414 250 2. 377510 1. 000000 5. 000000 0. 998048 250 2. 104000 1. 00000 5. 000000 0. 872675 250 2. 240755 1. 000000 5. 000000 0. 799377 250 3. 508000 1. 000000 5. 000000 0. 997928 250 2. 984000 1. 000000 5. 000000 1. 124241 250 3. 252000 1. 000000 5. 000000 1. 024594 250 3. 248000 1. 000000 5. 000000 0. 679882 250 2. 588000 1. 000000 5. 000000 0. 925960 250 2. 444000 1. 000000 4. 000000 0. 753880 250 2. 516000 1. 000000 4. 000000 0. 706570 Std. Dev. Skewness Kurtosis Lilliefors 1. 246334 -0. 38175 -0. 81603 p < 0. 01 1. 368169 -0. 53785 -0. 94293 p < 0. 01 1. 330664 0. 23217 -1. 10274 p < 0. 01 1. 010433 -0. 41147 -0. 39284 1. 189626 0. 35201 -0. 4343 p < 0. 01 1. 186409 0. 11173 -1. 11363 p < 0. 01 1. 119019 0. 19350 -0. 90991 1. 276265 -0. 90357 -0. 21338 p < 0. 01 1. 306302 -0. 20087 -1. 05166 p < 0. 01 1. 267607 -0. 49983 -0. 80076 p < 0. 01 1. 242103 -0. 41457 -0. 67945 p < 0. 01 1. 100635 -0. 80199 -0. 13533 1. 057194 -0. 46768 -0. 29504 p < 0. 01 1. 084395 -0. 00472 -0. 89234 p < 0. 01 0. 911069 -0. 24495 -0. 53248 0. 819946 -0. 53038 0. 16360 p < 0. 01 0. 938127 -0. 71806 0. 35150 p < 0. 01 0. 706418 -0. 38783 0. 29433 0. 932211 -1. 32255 1. 76093 p < 0. 01 1. 123141 0. 35545 -0. 44119 p < 0. 1 0. 882760 -0. 49249 0. 18689 1. 043049 -0. 89638 0. 05848 p < 0. 01 0. 904890 -0. 88043 0. 16993 p < 0. 01 0. 754105 -1. 38027 1. 96908 p < 0. 01 0. 930423 -0. 81555 0. 22901 p < 0. 01 0. 657085 -0. 38638 -0. 71940 1. 084114 -0. 44746 -0. 51343 p < 0. 01 0. 882530 -0. 60460 0. 02283 p < 0. 01 0. 880030 -0. 27165 -0. 62975 0. 961711 -0. 08087 -0. 65163 p < 0. 01 0. 989617 0. 80019 -0. 16452 p < 0. 01 1. 004280 0. 27393 -0. 69440 p < 0. 01 0. 985037 0. 38571 -0. 78499 p < 0. 01 0. 781618 0. 22605 -0. 75735 1. 029688 0. 48748 -0. 70128 p < 0. 01 1. 136373 0. 1371 -0. 85437 p < 0. 01 1. 379535 0. 88739 -0. 58751 p < 0. 01 1. 015774 0. 54108 -0. 74791 1. 036437 -0. 92515 0. 26205 p < 0. 01 1. 011492 -0. 95795 0. 61243 p < 0. 01 0. 976429 -1. 03238 0. 78850 0. 999024 0. 64622 0. 01201 p < 0. 01 0. 934171 0. 83391 0. 61539 p < 0. 01 0. 894079 0. 67835 0. 25655 0. 998963 -0. 54607 -0. 14126 p < 0. 01 1. 060302 0. 09319 -0. 83181 p < 0. 01 1. 012222 -0. 35864 -0. 63267 p < 0. 01 0. 824550 -0. 24224 -0. 03148 0. 962268 -0. 07515 -0. 83065 p < 0. 01 0. 868262 0. 11801 -0. 63783 p < 0. 01 0. 840577 -0. 17856 -0. 74021 26