Mobile Technology and Advertising in Nigeria: The Emerging Complexities

Mobile Technology and Advertising in Nigeria: The Emerging Complexities

Chioma Ifeoma Agbasimelo, PhD
Department of Mass Communication, Nnamdi Azikiwe University Awka, Anambra State, Nigeria

DOI:  https://dx.doi.org/10.47772/IJRISS.2023.7729

Received: 31 May 2023; Accepted: 08 June 2023; Published: 18 July 2023

ABSTRACT                                                                                               

Mobile Technology offers advertisers an ever-growing global audience of “always on” multifunctional smartphone capability and instantaneous access to their contextual information. Location based, environmental, and behavioural data are increasingly being used to apply novel targeting and creative strategies for the development of new forecasting models. There is widespread dissemination and broad acceptance of mobile technology in the market place, as well as very promising opportunities for advertisers to engage with their customers in novel ways. Modern Technology has given consumers a wider range of options when it comes to how they consume media. Recently people spend more time on their smartphones, tablets and other mobile devices than they do on traditional media. In order to keep up with changing consumer habits companies adopt their advertising campaigns by adapting mobile technology strategies. The study was conducted to ascertain the emerging complexities of mobile technology in advertising. The study anchored on Technological Determinism Theory and The Theory of Planned Behaviour. The population comprises of mobile technology users. Online survey was used to solicit information. Purposive sampling method was used to gather data for the survey. The study revealed that consumers avoid mobile advertising due to perceived goal impediments, perceived intrusiveness, privacy concerns and ad irritation. The study also found out that in mobile advertising the boundaries between virtual and real life experiences is blurry. The study recommends that advertisers should bridge the boundaries between virtual and real life experiences in mobile advertising and that there is need for proper orientation for companies, advertisers and mobile technology users on the emerging complexities of mobile advertising.

Keywords: Mobile Technology, Advertising, Emerging complexities, Mobile Advertising, Virtual

INTRODUCTION

Mobile Technology is reshaping society, communications, and the global economy. With cell phones, smart phones and tablets now out numbering desktop computers, there has been a sea change in the way people access, use, and share information. Powerful mobile devices and sophisticated digital applications enable users to build businesses, access financial and health care records, communicate with public officials and complete online transactions. Globally, such devices and applications have helped reduce social equality, increased education levels, all of which spur national economic development.

This revolution is how consumers and businesses access information, and the far reaching consequences of such uses, represents a fundamental turning point in human history. For the first time, people are able to connect with one another in a relatively inexpensive and convenient manner around the clock. In both developed and developing countries, the growth in mobile technology has been accompanied by job creation and knowledge transfer, as well as deepened social and economic connections.

Mobile Technology offers advertisers an ever-growing global audience “of always on” multifunctional smartphone capability but also instantaneous access to their contextual information. Location based, environmental, and behavioural data are increasingly being used to apply novel targeting and creative strategies for the development of new forecasting models. In 2021 over 6 billion people worldwide had smartphone subscriptions (Statista, 2022^b). Not surprisingly, almost 60% of web traffic is accounted for by mobile devices (Stat Counter, 2022) Accordingly the evidence suggests that advertisers spend about two-thirds of their digital advertising budget on mobile advertising (eMarketer, 2019)

Mobile devices are highly individualized and important personal communication tools (Bacile, Ye & Swilley, 2014) and most users keep them within arm’s reach throughout the day, as well as nearby while they sleep. They have truly enabled consumers’ ubiquitous access to digital information, anytime and anywhere, which also means that mobile devices allow marketers to reach consumers more directly and constantly. Because consumers use their smartphones to conduct a host of activities, beyond just talking or texting, advertisers also have new opportunities for targeting their communications. People surf the web on their mobile devices and use various mobile applications (apps) many of which facilitate the delivery of advertising content. Today, social media sites such as Facebook, Twitter, and YouTube attract hundreds of millions of consumers who access the sites using their mobile devices; in turn, these sites provide tremendous insights for advertisers, due to their analytic capabilities.

An important feature that is unique to mobile devices is their ability to support Location-based applications. Customers often use apps for quick access to Location-based information such as nearest highly rated restaurant (Grewal & Levy, 2016). At the same time, an indoor positioning system based on simple transmitters (eg., iBeacon) can alert firms when a person is within a pre-determined set of locations of interest, such as when a consumer is in close proximity to a display of detergent in a grocery store. At that moment, the grocery retailer or detergent manufacturer likely wants to provide alerts, advertisements, or coupons to grab this particular consumer’s attention and move her closer to a purchase. (or increase her loyalty or advocacy)

Firms across the spectrum thus are wrestling with various factors that affect their mobile advertising and marketing strategies. Along with their dynamically shifting abilities to target and deliver relevant content and promotions to current and potential customers, markets must take into account how their mobile strategies interact with or complement their overall advertising and marketing strategies. This study aims at analyzing the emerging complexities of mobile Technology and Advertising in Nigeria. Specifically reflecting on Binding virtual and real experiences through mobile technology and the unintended consequences of mobile technology in advertising.

Statement of the Problem        

Mobile Technology is reshaping society, communication, and the global economy. With cell phones, smartphones, and tablets now outnumbering desktop computers, there has been a sea change to the way people access, use and share information. Powerful mobile devices and sophisticated digital applications enable manufacturers and firms to advertise their products and services. Mobile advertising allows retailers, service providers, and manufactures to provide consumers with increasingly relevant offers. The success of such campaigns depends on an ever better understanding of environmental consumer and technological context variables; a strong focus on advertising goals, accounting for market factors related to the nature of stakeholders and market environment; and the use of appropriate mobile and as well as a research agenda to stimulate additional work. Amidst of these various benefits of mobile Technology Advertising has emerging complexities. This study aims at ascertaining the emerging complexities of Mobile Technology advertising.

Research Questions

The following research questions were formulated to strengthen the study.

1. What is the extent of enthusiastic usage of mobile Technology and Advertising amongst Anambra State residents?
2. What are the complexities of mobile Technology and Advertising in Anambra State?
3. What are the significant influence of mobile Technology and Advertising complexities on the residents?

Research Objectives

The following objectives guided the study:      

1. To find out the extent of enthusiastic usage of mobile technology and Advertising amongst Anambra state residents.
2. To find out the complexities of mobile Technology and Advertising in Anambra state.
3. To find out the significant influence of mobile Technology Advertising complexities on the residents of Anambra state.

LITERATURE REVIEW

Mobile Technology Advertising

The technological context for mobile advertising depends substantially on the size of the device. Mobile devices usually are equipped with a relatively small touchscreen (cf. laptops, desktops), though these screen sizes vary widely, from 38 mm on the Apple Watch to 12.9 in. on the iPad Pro. The smaller screen sizes increase search costs, compared with Internet access through a desktop or laptop (Ghose, Goldfarb, and Han 2013), yet the mobility of the devices offers benefits that often justify these costs. The display size also limits the area available for advertising and dictates both the content and delivery mechanism for advertising (e.g., browser, app). Finally, consumers interact with mobile devices through touchscreens, and touch-based interactions differ from mouse interactions, as required on most traditional laptop or desktop computers. In particular, these touch-based interactions can prompt ownership effects (Brasel & Gips 2014) that may enhance advertising effectiveness.

Mobile advertising often is embedded in other content within a browser or an app. Thus, consumers might see a mobile ad on an advertiser’s website or app, or they could come in contact with the mobile advertisement through a third-party website or app (e.g., search engine, social network, news website). Such contextual factors may affect consumers’ level of involvement with the ad. According to the elaboration likelihood model (Petty&Cacioppo, 1986), advertising can affect brand attitudes through central or peripheral routes. Shankar and Balasubramanian (2009) propose that mobile display ads should target peripheral processing, by highlighting existing needs or potentially creating new needs for products and services that require only low consumer involvement.

However, in a large field experiment, Bart, Stephen, and Sarvary (2014) show that mobile display ads are most effective for higher-involvement, utilitarian products, because such ads may be the only ones that successfully initiate processing through a central processing route. With regard to the related technological context, a consumer searching on the advertiser’s site is likely to be more involved than somebody searching on a third-party site, so these context effects (related to how the ad was presented by an advertiser and accessed by a consumer) might help explain the varying findings in prior research, as well as determine consumers’ involvement.

Mobile devices might serve as either the first (and only) screen used by a consumer, or as a second screen in addition to a television or desktop screen. For example, while watching the latest episode of a televised drama series, some consumers tweet their reactions in real-time mode. Consequently, adver­tisers need to consider not just the mobile ad delivery mechanism but also

the content (context) with which con­sumers are involved on the first screen (e.g., television).

Consumer Context

Other major considerations for mobile ad effectiveness include the phase of the purchase decision process, the temporal dynamics of the choice task, and whether the consumer is multitasking. Furthermore, mobile apps are often inherently social, such that the consumer context comprises network effects.

The consumer journey consists of multiple stages, from need recognition and pre-purchase activities to purchase decisions and post-purchase activities (Puccinelli et al. 2009; Yadav et al. 2013). Mobile ads can stimulate consumers’ recognition of an unmet need or a purchase opportunity in their immediate vicinity. For example, a targeted ad for a store within walking distance may induce unplanned spending. In the pre-purchase stage, the consumer instead might be searching for product information through a search engine or review app (e.g., Yelp). Mobile advertisements may seek to draw a consumer into the store and away from competitor’s stores (Fong, Fang & Luo, 2015). In-store mobile ads may spark purchase behaviour. In the post-purchase phase, consumers often review their purchases on social media, where the advertiser in turn might place related, targeted mobile advertisements for the consumer’s friends to see alongside the review.

These phases also might relate to the temporal dynamics of consumer choice. For mobile marketers, consumers’ short- and long-term choices may compete and become conflicting goals (Dhar & Simonson, 1999; Fishbach & Shah, 2006), related to mental accounting (Thaler, 1985). That is, a consumer in the purchase stage likely weighs the trade-off between vices and virtues in the near and distant futures differently than a consumer in the need-recognition stage (Trope & Liberman, 2003). By considering these elements in combination, marketers can predict temporal changes in consumers’ advertising responses better and thereby capture more value from consumers.

However, the question of optimizing mobile advertising placements remains open. For example, when consumers are engaged in multiple tasks (e.g., checking their Facebook feed and considering advertisements for related products), if the primary task (engaging with Facebook) induces high arousal, it can lead to cognitive depletion that impairs their performance on the secondary task (processing a mobile ad) (Eysenck 1982; Fedorikhin & Patrick, 2010). In terms of both brand recall and attitudinal measures, the impact of a mobile advertisement can suffer when the prospective consumer is engaged in performing a task that triggers more arousal. Prior research mostly treats arousal as a generalized antecedent to attention (Maclnnis & Jaworski 1989; Petty & Cacioppo 1986), but separating and experimentally identifying the interaction of these two con­structs could provide an opportunity for studying the persua­siveness of mobile display ads. For example, literature that reveals behavioral consequences of affect (Andrade 2005; Rook & Gardner, 1993) identifies conditions that may account for the weak impact of display advertising in dual-task settings, such as when high involvement with the advertising channel lowers subsequent recognition of the advertised brand.

The example of a consumer who browses a Facebook feed and gets exposed to advertisements at the same time also suggests the need to consider network effects. Some consumers may be influenced by information about others’ decisions, and word-of-mouth (WOM) communications tend to exert more powerful influences on consumer decisions than firm-initiated communication (Herr, Kardes & Kim 1991).

Bridging Virtual and Real Experiences

The boundaries between virtual and real-life experiences have become increasingly blurry. Consumers often share their consumption experiences with others via social media and, in doing so, create virtual experiences for themselves as well as for others to relive. This development has largely been fueled by the wide and rapid adoption of smartphones, which has allowed consumers to take and share photos or broadcast live video streams in real time. Unsurprisingly, advertisers have largely wel­comed consumers taking over this role in their marketing communications by proactively sharing their experiences.

This line of study mainly focuses on consumers who are part of the experiences or the content they create about those experiences. However, the role of the environment in which experiences take place has been largely neglected. Many readers of this editorial will likely have been in the situation where they visited, for example, a shop, a restaurant, or a museum and felt the urge to take a picture and share it on social media. What are the situational factors that elicit such responses in some places and not others? How can advertisers actively design environments that inspire consumers to share their experiences with their social media followers? In this special section, Campbell, Colin, Sands & Montecchi (2022) tap into this phenomenon and investigate how real-life environments inspire consumers to generate and share user-generated content. They introduce a new term to describe this activity: “environment-cued indirect advertising.”

Campbell et al. (2022) neatly bring together the three distinct literatures of consumer-generated con­tent, experiential marketing, and retail atmospherics (the controllable characteristics of retail space) to enhance our understanding of how environments can be cued to generate indirect advertising. They find that brightness, colored lighting, and the number of colors present influence social media sharing. The authors also note that consumers are motivated to look good in the re-creation of an experience rather than during the experience itself. Consequently, to maximize indirect advertising, brand atmospherics needs to focus on mobile-device-based photo opportunities as well as the actual enjoyment of the experience.

Overall, their research underpins and throws further light on the importance of social media (in this case, Instagram) in many people’s lives. Many consumers are willing to lean forward and embrace opportunities that enable the coproduction of content with brands in pur­suit of self-presentation: the selfie. Their finding—that self-presentation, facilitated by mobile technology, appears to be more motivating to the creation of indir­ect advertising than the enjoyment of the actual experience.

Unintended consequences

Mobile advertising has anecdotally been praised to have revolutionized the advertising landscape. While it indeed offers novel applications, such as granular loca­tion targeting, in-app and cross-app advertising, synced advertising, and many more, it is also important for advertisers to understand that novel technological innovations can have unintended consequences. For example, Osinga, Zevenbergen & van Zuijlen (2019) have found that mobile banner ads do not increase online sales; instead, they have been found to increase offline sales. Research has also shown that using loca­tion-based mobile advertising (LBMA) can backfire by evoking negative consumer reactance when advertisers target consumers with a suboptimal combination of location, type of promotion, and/or type of product (Bernritter, Ketelaar & Sotgiu, 2021).

It is generally recognized that unintended conse­quences of mobile technology often become apparent when comparing mobile with other platforms.  Orimoloye et al. (2022) add to our understanding of unintended consequences by using clickstrearn data to compare mobile shoppers with con­sumers shopping via personal computers (PCs) or tab­lets. One of their key findings is that the frequency of completed orders and e-cart value is lowest for smart-phones, suggesting that smartphones might be an infer­ior shopping platform. They also find that reading customers’ online reviews does not positively affect con­version if consumers shop via smartphones, though it does so for tablets and PCs. Thus, while prominently displaying online reviews is a worthwhile endeavor on most platforms, it might not pay off on mobile plat­forms. As such,

their research indicates that the accepted norms for how non mobile platforms work do not necessarily apply to mobile platforms.

Another unintended consequence of advertising in the general advertising literature is ad avoidance. Ad avoid­ance has been an important topic in interactive media but has received less attention in the context of mobile. During the past two decades, interactive media research has attributed ad avoidance to a series of determinants from psychological, behavioral, and tactical perspectives. Scholars found consumers avoid online ads due to perceived goal impediment (Cho, 2004), perceived intrusiveness (Edwards, Li & Lee, 2002), privacy concerns (Segijn, Voorveld & Vakeel, 2021), ad irrita­tion (Baek & Morimoto, 2012), and attention-getting tactics (Campbell et al 2017), among others.

Ad avoidance is especially relevant to mobile devi­ces because up to 90% of mobile users perceive tar­geted ads as annoying and irritating, resulting in almost $150 billion ad spending wasted (Ogury, 2019). More recent research on LBMA reveals that loca­tion congruence attenuates the effect of intrusiveness on negative attitudes toward mobile ads (Ketelaar et al. 2018). Similarly, a study combining LBMA and media multitasking found that multitasking consumers, com­pared with single-tasking consumers, are more likely to avoid LBMA. Multitasking consumers tend to per­ceive ads from closer stores to be more intrusive and thus avoid them (Choi, Choi & Song 2021).

Schmidt & Maier (2022) address mobile ad avoidance from a new perspective: incidental exposure to embedded, as opposed to fixed, mobile banner ads. They show that ad avoidance on mobile phones works differently from that on desktops. In an experimental setting, the authors measured partici­pants’ gaze time using eye tracking while observing their scrolling actions via viewport logging. Their results sug­gest that while mobile users often ignore ads through the widely known “banner blindness” phenomenon, they also interact with their devices to actively scroll embedded mobile ads out of their focus of attention to their periphery.

Technology Acceptance Model

TAM’s theoretical background stems from the theory of reasoned action (TRA) (Fishbein & Ajzen, 1975) and the theory of planned behavior (TPB) (Ajzen, 1991). TRA posits that users’ beliefs determine attitudes and intentions, which then influence actual behaviours. TPB elaborates on TRA by adding the construct of perceived behaviour control as an independent determinant of intentions and behaviours. On the basis of these theories, TAM was developed to account for technology use in the workplace (Davis, 1989). TAM assumes that two basic beliefs – perceived usefulness and perceived ease of use – are the primary reasons for adopting technology. Perceived usefulness re­fers to “the degree to which a person believes that using a particular system would enhance his or her job performance” (Davis, 1989, p. 320) whereas perceived ease of use refers to “the degree to which a person believes that using a particular system would be free of effort” (Davis, 1989, p. 320). Individuals are likely to adopt new technologies when they perceive those technologies to be useful and easy to use.

Thus, TAM predicts that these perceptual beliefs are positively related to attitudes toward information technologies, which then determine intention to use and actual behaviour. TAM studies have provided consistent results of perceptions of usefulness and ease of use for attitudes toward the Web (Venkatesh & Davis, 2000) and e-commerce (Kleijnen et al., 2004: McCloskey, 2003-2004). Accord­ing to TAM, perceived usefulness increases when consumers feel that mobile technology is easy to use which, in turn, affects positive attitude formation. Conversely, acceptance of mobile technologies may decrease if consumers do not perceive the usefulness of new technologies based on a perception of being easy to use.

Technological Determinism Theory

This theory believes that technology is an autonomous force that changes the society. It provides an explanation for many changes that could be observed through the new media technology in the society. Technological Determination states that media technology shapes how we as individuals in the society think feel, act and how the society operates as we move from one technological age to another. We learn, feel and think the way we do because of the messages we receive through the current technology that is available. The medium is the message (McLuhan, 1962) the theory envisaged a world of media explosion and revolution in which the new electronic media have formed unified groups radically altered the way people think, feel and act. The new media effects have permeated every nook and cranny of the society, so much that it is now difficult to challenge the postulations of 1962 by the Canadian Media Researcher Marshal McLuhan.

METHODOLOGY

This study adopted the survey research design with questionnaire as research instrument since it involves studying a large population. According to Ohaja (2003) whenever the major sources of primary data for a study are the views of members of the public or any particular group, a survey will be called for. The suitability of the survey method was informed by the need to collect data from Anambra State residents within the stratified towns in the three senatorial sections of the State.

The population for this study comprised of 4,177,828 people according to the National Population Commission 2006 Census which has been currently projected to about 5,527,800 people in 2016. The study population includes adults residing in Awka, Nnewi and Onitsha.

A sample size of four hundred (400) respondents was selected as a representative sample for the study. This sample size is based on the population of the study area which is determined by applying Taro Yamane’s formula for selecting sample size.

This study adopted multistage sampling approach. In the first stage the stratified sampling method was used to divide Anambra State into three senatorial zones. They are: Anambra North, Anambra Central and Anambra South senatorial zones. The second stage involved selecting the local government areas used in each senatorial zone. The hat and draw simple balloting method was used to choose one local government from each senatorial zone. The purposive sampling method was used in selecting one town from each of the local government areas representing the three senatorial zones. The proportionate stratified sampling was used to arrive at the number of respondents selected from each of the three state strata of the population.

DATA PRESENTATION AND ANALYSIS

For the distribution of questionnaire, the researchers employed both physical distribution and online survey methods. Out of 400 respondents that were evaluated based ion either physical issuance of questionnaire or online survey, 360 copied were validly filled thus, forming the basis for data analysis.

Demographic variables

Table 1: Age Distribution

Table above shows 270 respondents (75%) fall within the age bracket of 18-25 years. The implication is that the respondents are active users of Mobile Technology. Secondly, it shows the most mobile technology users are within the ages of 18-25years.

Table 2: Gender

The above Tables shows the major users of Mobile Technology under study comprised of male respondents than female with varying significant percentage scores of 79 – 21% respectively.

Table 3: Preference of social media

Table 3 shows that YouTube and Instagram use for mobile advertising is relatively high respectively. It shows that respondents make relative use of all the social media platforms under study.

Table 4: Extent of enthusiastic usage of Mobile Technology in advertising

Differences on the extent of enthusiastic use of the social media platforms indicate ‘Great extent’ of YouTube (98%) and Instagram (95%) against the use of Facebook (53%) among the respondents. The implication is associated with easy use of YouTube and Instagram for advertisement. It enables online activities such as uploading of pictures, video and audio materials by advertisers, firms and organizations. On the other hand, Facebook has a significant reduction among the respondents.

Table 5: Influence of perceived benefits Mobile Technology Advertising amongst Anambra state residents

All respondents agreed to positive benefits of Mobile Technology Advertising

Table 6: Perceived Benefits of Mobile Technology Advertising

Table 6 shows that significant scores of 45% for users of Instagram believes that mobile technology advertising has global audience. On the other hand, the significant scores of 52% shows that YouTube has benefits of increased visual content which helps in mobile advertising.

Table 7: Significant Influence of Mobile Technology Advertising Complexities

The responses of significant score of 320 respondents (89%) indicate that there are perceived complexities associated with Mobile Technology Advertising

Table 8: Perceived Complexities of Mobile Technology Advertising

For users of Instagram, Ad Irritation and perceived Intrusiveness are significant complexities associated with mobile Technology Advertising. This finding supports the position of Baek & Morimoto, 2012 and Edwards, Li & Lee, 2002 that consumers avoid online ads due to ad irritation and perceived intrusiveness. For users of YouTube 75% believe that mobile ad avoidance is caused by ad irritation and perceived intrusiveness, YouTube users also indicated that 40% of its users believe that Mobile technology causes virtual and real life problem. For users of Facebook there is reduction on ad avoidance due to ad irritation and perceived intrusiveness, 20% of the users indicated privacy concerns as one of the complexities of mobile technology advertising.

DISCUSSIONS

Summarily, the analyses make the following findings:

1. The study found that active mobile technology users are within the age bracket of 18-25 years. However, other ages are Internet-friendly but at varying degree of usage.
2.  On the basis of preference, the study found that YouTube and Instagram are mostly used against Facebook. The degree of preference is affected by different factors such as content and interactivity.
3. All respondents agreed to the complexities of mobile technology advertising. Most Instagram and YouTube users agreed that complexities of mobile advertising are caused by Ad Irritation and Perceived Intrusiveness. In the case of Facebook there is a reduction on ad avoidance due to ad irritation and perceived intrusiveness while privacy concerns constitute a problem. Virtual and real life blurry.
4. For benefits, the findings show that YouTube has a significant advantage of increased visual content ads. Instagram has significant global audience. Regrettably, the findings also show that Facebook ad has reduced global audience, it is best used for building up relationships.

CONCLUSION/RECOMMENDATIONS

Based on the findings of the study, the following recommendations are proffered:

1. The advertisers should bridge the boundaries between virtual and real life experiences in mobile advertising.
2. There is need for proper orientation for companies, advertisers and mobile technology users on the emerging complexities of mobile technology advertising
3. APCON should have a strict regulation to guide mobile technology advertising in order to have a check on the activities of advertisers, companies, organizations and mobile Technology users.
4. Mobile Technology advertisers should engage in proper packaging and placement of ads to avoid Ad irritation, perceived intrusiveness and privacy invasion.
5. Mobile technology advertisers should deliver timely and relevant messages to consumers in order to avoid creating negative first time impression on potential customers

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