Computer-Mediated Advertising as a Correlate of Buying Behavior Among Youths From South-East Nigeria

This study examined the correlation between exposure to computer-mediated adverts and the buying behavior of youths from Enugu State. The correlational survey was used for the study, while a sample of 385 was selected through a multistage sampling technique. In the analysis of the result, simple percentages were used to achieve the research objectives, while the Pearson correlation coefficient (r) was used to test the hypotheses raised. The result showed a strong positive correlation between the engagement in computer-mediated communication (CMC) and exposure to computer-mediated adverts (r = .815, n = 362, p < 005). The findings also showed a strong negative correlation between the format of computer-mediated advertising (CMA) and the duration of viewing (r = −.241, n = 362). Finally, the researcher found a strong positive correlation between exposure to CMA and buying decision (r = −.666, n = 362, p < 005). The researcher concludes that the level of engagement in CMA correlates exposure and eventual purchase likelihood. The researcher recommends, among others, that efforts aimed at reaching youths through CMC should also incorporate their level of engagement.

interactivity, and computer intelligence allow advertisers to expand the boundaries of advertising beyond brand awareness and exposure. Although some scholars (e.g., Bahr, & Ford, 2011;Dehkordi et al., 2012;Fagerstrøm & Ghinea, 2010) refer to CMA as e-marketing, the crux of the matter is that the emergence of the internet has resulted to changes in advertising. Luk et al. (2002) posit that CMA helps to market products and services through interactive and colorful catalogs and provides the audience with current and available information. According to the trio, such advertising also allows the audience to make both local and international purchases as there are numerous websites designed to promote sales and to maintain relationships with customers. Zheng and Yeqing (2002) hold that CMA is less annoying than usual advertising.
The overall goal of CMA is to communicate products qualities to the target consumers and eventually influence their buying behavior. This implies that the essence of CMA 938701S GOXXX10.1177/2158244020938701SAGE OpenAsogwa research-article20202020 1 Federal University Oye-Ekiti, Nigeria is to promote marketing of products. Todorova (2015) posits that marketing communications represent the voice of the company and its brands-they are the means by which the company can establish a dialogue and build a relationship. Fill and Jamieson (2006) corroborates that all organizations, irrespective of size, commercial, government, charities, educational and other not-for-profit organizations, need to communicate with a range of stakeholders.
Knowledge of the buying behavior of consumers is an ever-interesting area in advertising because marketers are usually interested in explaining and predicting consumer behavior. Munthiu (2009) avers that the decision of purchasing an item does not immediately trigger motivation, perception, learning, memory, personality, and attitude are fundamental drivers in the unfolding of the decision process that presupposes the consumer's covering of five stages: problem recognition, information search, evaluation of alternatives, purchase decision, and postpurchase behavior. Although many factors such as income level, education level, gender, location, among others, have been identified as essential to buying behavior, age is said to play a critical role in deciding what to buy. Evidence in the literature (e.g., Khan & Chawla, 2015;Singh & Dalal, 1999) points to the fact that age is a pivotal variable that determines buying decision. Also, there is empirical evidence suggesting that computermediated communication is most common among the youth. For example, the Dunahee and Lebo (2016) reported that at least 90% of respondents ages 18 to 24 years engage in computer-mediated communication daily. In Nigeria, youth are people between the ages of 18 and 35 years. This is contained in the National Youth Policy and Strategic Plan of Action of the Federal Government of the Federal Republic of Nigeria (2001) as cited by Gever (2015). Therefore, this study adopted the theory of reasoned action to examine the correlation between CMA and buying behavior of youths from Enugu State.

The Problem
Although computer-mediated communication is an attractive area for 21st-century scholars, studies on CMA are still emerging. Much of the literature on advertising has focused on conventional media like radio, TV, newspaper, and magazine. Studies (e.g., Benek et al., 2011;S. Kumar, 2013) have also shown that youth and children influence family buying decisions. This implies that knowledge of the relationship between exposure to CMA and buying decision of youth could also offer an insight into buying decisions of the family. Khan and Roni (2013) corroborate that the youth market is one of the most appealing and attractive markets because they are considered to have more pull (power) in their crucial family decisions and purchases. There is also evidence suggesting that people of young age take part in computer-mediated communication most, hence are likely to be exposed to computer-mediated adverts. Although it may be tempting to conclude that most youths are exposed to computer-mediated adverts because they are engaged in computer-mediated communication, such an assumption may lack empirical proof. Advertisers are aware of youth technology culture and have taken advantage of it. Moreno (2018) notes that youth are key stakeholders in advertising. This makes it essential to understand the relationship between computer-mediated adverts exposure and eventual purchase likelihood.

Objectives of the Study
The general objective of this study is to determine the relationship between computer-mediated adverts and the buying decision of youth from Enugu State. Specifically, the researcher sought to achieve the following: 1. To ascertain the relationship between engagement in computer-mediated communication and exposure to computer-mediated adverts among youths from Enugu State. 2. To discover the relationship between format of computer-mediated advert and estimated viewing duration. 3. To examine the relationship between exposure to computer-mediated adverts and buying behavior.

Research Hypotheses
This study tested the following hypotheses: Hypothesis 1: There is a significant statistical relationship between engagement in computer-mediated communication and exposure to computer-mediated adverts among youths from Enugu State. Hypothesis 2: There is a significant statistical relationship between the format of the computer-mediated advert and estimated viewing duration. Hypothesis 3: There is a significant statistical relationship between exposure to computer-mediated adverts and buying behavior.

Computer-Mediated Adverts Format
As stated earlier, CMA describes messages about products or services which are made available to the receivers through new communication technologies. December (1996) says that it is referred to a situation in which commercial messages are created, exchanged, and perceived through networked telecommunications systems that facilitate encoding, transmitting, and decoding messages. Deshwal (2016) describes CMA as a type of mass communication which is based on the traditional form of advertising but develops its communication strategies in correlation with the new technical and medium-based requirements. CMA could reach the receivers through different mediated devices like the laptop computer, the desktop, mobile phone, an iPad, a tablet, among other devices that posses the ability to process, store, and retrieve messages. Computer-mediated adverts may appear in different formats like video which shows the features of the product and draw people in with sound and motion. The format could also be in the form of the image which guides people to the destination of the websites or applications through high-quality visuals. Farace et al. (2020) in their study found that the visual component is essential in stimulating purchase. Interestingly, computer-mediated advertisements include visual and motion formats. The format could equally be regarding collection which encourages shopping by displaying items from products catalog. Also, computermediated adverts could be informed of the carousel which reveals up to 10 images or videos within a single advert with each having its individual like. There is also slideshow format which uses motion, sound, and text to tell the story about the advert on connection speed. V. Kumar et al. (2017) add that computer-media advertising is now critical in 21st-century marketing. Appiah (2006) reported that computer-mediated communication users were more likely to have confidence that a site was targeting them, regard a site more positively, and rate the product more favorably when the site has audio/video testimonials than they were when the site is made up of either text/picture testimonials or no testimonials. Appiah's study implies that video format was most effective in influencing buying behavior. Germelmann et al. (2020) in their study reported that advertising medium is essential in determining advertising effectiveness. Their result suggests that computer-mediated adverts may play a role in consumer behavior.

Youth and Buying Behavior
The buying behavior of youth is an interesting area because of the influence they exact in the buying decision of families. Khan and Roni (2013) found that youth market is one of the sought-after markets because they are regarded to have more influence on their main family buying decisions. Therefore, a critical center of firm's marketing actions is toward these young consumers, and they place more attention on the determinants of buying behavior and brand choice of their obsession with new technologies. Chandwani et al. (2015) reveal 10 major steps (under pre-, intra-, and postpurchase behavior) identified for youth while purchasing. According to Chandwani et al., these factors include budget analysis; brand preferences or brand loyalty; usage or purpose, or requirement; specifications of the product; products available; products or brands comparison; product availability in stores; final purchase; consumption; satisfaction or dissatisfaction. Khan and Roni (2013) hold that today's youths are positively disposed to technology. Khan and Roni add that as a result of youth's fast adoption curve and orientation toward technology and innovative feature, this age group has become an area of significant interest to the marketers. The assertion of Khan and Roni is critical to the current study because it has shown that new communication technologies are common among youth, thus making it appropriate to investigate the correlation between exposure to computer-mediated adverts and buying behavior. Literature focusing on new media and advertising abound. Kalia and Ashutosh (2016) did a study on effects of online advertising on consumers and found that although different types of internet advertisements appear on the website, respondents express preference rectangular banner advertisements and skyscraper ads which are in vertical format.
Mohammed and Alkubise (2012) investigated the influence of online adverts on a sample in Jordan. The results revealed that internet skills, income, internet usage per day, the content of advertisement, and the location advertisement are essential factors that impact on the effectiveness of an online advertisement. However, two notable findings emerged: The first was the critical considerable role of website language and the second and maybe most importantly was the impact of other people opinions on the effectiveness of an online advertisement. Mathew et al. (2013) investigated the influence of web advertising on consumers in Maiduguri, Metropolis. The study discovered that a majority (100 [71.94%]) of the respondents said their disposition toward web advertising was positive. A minority (39 [28.06%]) of the respondents said that their disposition toward web advertising was negative. A total of 102 (73.38%) respondents said their attitude toward web advertising was informative. The study also found that a majority (42 [30.22%]) of the respondents said web advertising influences them to use some of the products and services. Afzal and Khan (2015) did a study on the effect of mediated and conventional advertisement on consumer buying behavior of branded garments. It was reported that the content of the advertisement, design, quality, previous buying experience of the consumer, and the loyalty of consumer toward the brand are critical factors that influence consumer buying behavior and affect the direct impact of online and conventional advertisement on consumer buying behavior through their strong mediating effect.
Aday and Yener (2014) investigated many factors that might influence the young consumer's behavior at the point of sale. The researchers revealed those factors, namely, packaging, labels, production, best before dates, and ingredients, among others.
Hayta (2013) did a study to know the influence of social media on the buying behavior of youth in Turkey and found that social media tools create a statistically significant difference on the purchasing behavior of consumers according to their age groups and educational status. This is because Hayta found that participant attitudes toward buying behaviors and social media relations cause a significant difference in educational level, t(686) = 6.666, p > .01. Fatima and Lodhi (2015) studied the impact of advertisement on buying behaviors of the consumers in Pakistan. The results showed that advertisement is very useful in creating the awareness among the people, but they are failed to build strong perceptions in the mind of consumers. Both of these variables such as consumer awareness and consumer perceptions will motivate the consumer to buy a particular product, as there is a positive relationship present in between them.
Van Berlo et al. (2020) in a study reported that familiarity with brand significantly moderates the impact that adolescents playing advergames has on their ability to recognize the commercial aim of advergames. Their result also revealed that smartphone attachment triggers recognition of the commercial objective of advergames among the sample examined. Schnack et al. (2020) conducted a study to ascertain to determine shopping behavior of consumers with the utilization of 153 different categories of shopping trips. The researchers made use of observation research approach and the result showed that shopping behavior of consumers was determined by virtual stimulation. Devereux et al. (2020) did a study to examine the features of social media posts from small from that stimulate engagement from the consumers. The researchers conducted the study in Australia. Their social media posting of companies reveal their value of their online activities. The results of the researchers also revealed that the consumers were more interested in engaging with Facebook posts of companies than any other social media platform.
From the studies reviewed, it can be seen that the concept of CMA has not received substantial attention in the literature. Rather, most of the previous studies focused on online advertising, which is just one aspect of CMA because even mobile phone advertising is part of CMA. And mobile phone advertising does not necessarily make use of the internet, thus not part of online advertising. Also, adverts in video games are also part of CMA but not part of online advertising. Therefore, CMA is broader in scope.

Theoretical Framework
This study found expression on the theory of planned behavior. Ajzen postulated the theory in 1986. The fundamental postulation of the theory is to explain human behavior. According to the theory, individual's intention to carry out an action at anytime is determined by the intention that the person has in mind. Behavior intention determined by three factors, namely, an individual's attitude toward behavior, subjective norms, and perceived behavioral control (PBC; Ajzen, 1991). In the views of Ajzen (1985), intention is "a person's readiness to perform a given behavior." Attitude defines the evaluation of a person concerning a behavior which can be positive or negative. subjective norms describe the opinion that a person's role model have about an issue. On its parts, PBC explains how less demanding or challenging it is for a person to engage in an action. Theory of planned behavior is considered useful as a framework for studies related to advertising. Zhang et al. (2018) made use of the theory to examine how young people in China react to green advert messages. Their results showed that the theory is an appropriate framework for examining issues related to adverting. Therefore, the researcher made use of the theory to explain the influence of computer-mediated adverts on youth in South-East Nigeria.

Method
The design that was used in this study was correlational survey. The design was deemed most suitable because it helped the researcher to determine the relationship between exposure to computer-mediated adverts and buying behavior of youth. The population of this was made up of all the youths from Enugu State aged 18 to 35 years. According to the National Bureau of statistics (2012), the total number of youth from Enugu State is 1,300,664.
The sample size of this study was made up of 385 youth. This was determined using the Australian calculator as provided by the National Statistical Service (NNS). The confidence level was 95% precision level of 0.05, and estimated variance of 5% was used. The researcher adopted the multistage sampling technique for this study.
First, the researcher considered the three senatorial zones in Enugu State as clusters. They are Enugu East, Enugu West, and Enugu North. At this stage, the researcher used purposive sampling to select one local government from each of the senatorial zones. Awgu from Enugu West, Nsukka from Enugu North, and Udi from Enugu East were selected. To sample the individual respondents, the researcher adopted simple random sampling by visiting the local government headquarters of the selected local government areas. Only those within the age bracket of 18 to 35 years were selected. Such persons also reported they were new media users. The questionnaire was used as the instrument of data collection. The reliability of the questionnaire was determined through a test-retest approach. To do this, initial copies of the questionnaire were administered to 20 persons in Nsukka; after 2 weeks, the same questionnaire was administered to the same respondents. The Guttman scale of coefficient of reproducibility was used to measure reliability of consistence of the instrument as shown below: . .
The calculation yielded 0.85 (85%), which was considered very high. The analyses were done using correlational analyses. In doing so, the Statistical Package for Social Sciences (SPSS 22. version) was used. The results were presented in tables.

Results
A total of 385 copies of the questionnaire were administered to the respondents, but only 362 copies representing 94% were retrieved and found useful. The sample was 52% male and 48% female. Also, average mean number of years that the respondents had been engaging in computer-mediated communication was 8 (range = 4-12 years). The device most commonly used for computer-mediated communication was the smartphone (95%). The frequency of engagement in computer-mediated communication was daily for most (82%) of the respondents. The motivation for was as follows: information exchange (83%), entertainment (67%), education (54%), and avoidance of boredom (41%). Overall, the respondents were asked to rate the level of on a trio of high level, medium level, and low level, and the result showed that most (72%) reported high level, 16% reported medium level, and 12% reported low level. Table 1 shows the result of the correlation between engagement in computer-mediated communication and exposure to computermediated adverts.
The result from the table above suggests that respondents who reported high-level engagement in CMC also reported full exposure to CMA. Also, respondents who reported lowlevel engagement in CMC also reported no exposure to CMA while medium-level engagement respondents reported glancing at CMA. Table 2 showed the cross tabulation between format of CMA and viewing duration. The result from the table above suggests that most of the respondents view CMA from image format and they do so within 0 to 5 min. Cumulatively, more than half of the respondents view the image format of CMA, followed by video and text. Table 3 shows the cross tabulation between Exposure to CMA and buying behaviour. The result from the table above revealed that most of the respondents who reported full exposure to CMA also reported that it influences their buying behavior. This is followed by those who reported glancing at such advert. Overall, of 64.1% of respondents who reported

Test of Hypotheses
The following hypotheses have been tested in this study: Hypothesis 1: There is no significant statistical relationship between engagement in computer-mediated communication and exposure to computer-mediated adverts among youths from Enugu State. Table 4 shows cross tabulation between engagement in computer-mediated communication and exposure to computer-mediated adverts. The result from the table above measured the relationship between the level of engagement in computer-mediated communication and exposure to computer-mediated advert using Pearson correlation coefficient. Preliminary analysis was performed to ensure no violation of the assumptions of normality, linearity, and homoscedasticity. There was a strong positive correlation between the two variables, r = .815, n = 362, p < 005, with a high level of engagement in CMC associated with exposure to CMA. Therefore, the first null hypothesis is rejected, and the researcher concludes that there is a significant statistical relationship between engagement in CMC and exposure to CMA among youths.

Hypothesis 2:
There is no significant statistical relationship between format of computer-mediated advert and estimated viewing duration. Table 5 shows correlation between format of computermediated advert and estimated viewing duration. The result from the table above measured the relationship between the format of the computer-mediated advert and estimated duration of exposure using Pearson correlation coefficient. Preliminary analyses were performed to ensure no violation of the assumptions of normality, linearity, and homoscedasticity. There was a strong negative correlation between the two variables, r = −.241, n = 362, p < 005. This implies that as the CMA format changes, it negatively affects the duration of exposure. Therefore, the second null hypothesis is rejected and the researcher concludes that there is no significant statistical relationship between the format of the computer-mediated advert and estimated viewing duration.

Hypothesis 3:
There is no significant statistical relationship between exposure to computer-mediated adverts and buying behavior. Table 6 shows the relationship between exposure to computer-mediated adverts and buying behaviour. The result from the table above measured the relationship between exposure to CMA and buying behavior using Pearson correlation coefficient. Preliminary analyses were performed to ensure no violation of the assumptions of normality, linearity, and homoscedasticity. There was a strong positive correlation between the two variables, r = −.666,  -tailed) .000 N 362 362 Note. CMA = computer-mediated advertising. **Correlation is significant at the .01 level (one-tailed).  n = 362, p < 005. This implies that exposure to CMA positively affects buying behavior. Therefore, the third null hypothesis is rejected, and the researcher concludes that there is no significant statistical relationship between exposure to computer-mediated adverts and buying behavior.

Discussion of Findings
This study investigated exposure to computer-mediated advert through computer-mediated communication and the buying decision of youth from Enugu State, Nigeria. The result of this study showed respondents who reported highlevel engagement in CMC also reported full exposure to CMA. The result of the hypothesis tested also showed a strong positive correlation between engagement in CMC and exposure to CMA (see Tables 1 and 4). The result of this study is consistent with that of Kalia and Ashutosh (2016). Also, the result of this study showed that the most preferred CMA format was the image format and this is viewed for 0 to 5 min. The result of the hypothesis testing showed a strong negative correlation between CMA format and viewing duration. This implies that as the format changes, the view duration also changes. Overall, the result showed a significant correlation between the format of CMA and viewing duration. This result is contrary to the study of Giordano et al. (2015). Finally, the result of this study showed that most of the respondents who reported high engagement in CMC also reported that it correlates their buying decision. The result of the hypothesis testing also showed a strong positive correlation between both variables. This finding is consistent with previous studies (e.g., Aday & Yener, 2014;Fatima & Lodhi, 2015;Hayta, 2013) focusing on CMC and buying behavior. This result has revealed two broad implications. First, it has shown that the level of engagement in CMC may not necessarily be the same among all youths as may be assumed. While some youths are likely to be highly engaged in CMC, others may be moderately involved. Such level of involvement has implications for behavior change.
Therefore, the relevance of this result is beyond advertisers as other groups like political parties, change agents, social workers, media practitioners, and so on wishing to plan and implement behavior change communication through CMC could find the result of this study beneficial. Also, Scholars from journalism and media studies could also leverage on the result of this study for the purposes of understanding the interface between the level of engagement in CMC and behavior change. Theoretically, this result has implications on the theory of planned action. The underlying assumption of the theory is that consumers act on a behavior based on their intention to create or receive a particular outcome. Hence, the result showed that higher engagement in CMC correlates exposure to CMA and eventual purchase likelihood; it can be argued that those youths who are engaged in CMC do so to achieve particular objectives and information on products could be part of it. This is more so that the result of this study showed that information is top on the motivation for engagement in CMC.

Conclusion
This study has shown the correlation between CMA and buying decision of youths in Enugu State. The result proves that the level of engagement in CMC is an essential consideration in understanding the exposure to CMA and ultimately purchases likelihood. This study has practical and scholarly contributions. Practically, the result of this study has shown that knowledge of the motivation for engagement in CMC as well as the level of engagement is cardinal for reaching 21st-century youth via CMC. Therefore, anybody or groups of persons who are interested in reaching youth via CMC or even understanding their engagement behavior must pay close attention to the level of engagement. Therefore, advertisers, political parties, health workers, and journalists could find this information beneficial. Scholarly, this result has added to the body of knowledge on youth participation in CMC. The study has also expanded literature in the study of advertising and purchase likelihood. Based on the result of this study, the research recommends as follows: Campaigns aimed at understanding and reaching the youth via CMC should pay close attention to their level of engagement in CMC. Advertisers should use more of image format as doing this may lead to longer duration of viewership. Finally, the message should be created in a manner that it can be effectively understood between 0 and 5 min of viewing.

Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.  -tailed) .000 N 362 362 Note. CMA = computer-mediated advertising. **Correlation is significant at .05 level of significance.