Facebook advertising’s influence on intention-to-purchase and purchase amongst Millennials

Internet Research

ISSN : 1066-2243

Article publication date: 3 August 2015

The purpose of this paper is to investigate the influence of behavioural attitudes towards the most popular social medium in the world, Facebook, amongst Millennials in South Africa (SA), and to determine whether various usage and demographic variables have an impact on intention-to-purchase and purchase perceptions.


Quantitative research was conducted by means of a survey among a sample of over 3,500 respondents via self-administered structured questionnaires in SA. A generalised linear model was used to analyse the data.

The results confirm that advertising on Facebook has a positive influence on the behavioural attitudes (intention-to-purchase and purchase) of Millennials who reside in SA. The usage characteristics, log on duration and profile update incidence, as well as the demographic influence of ethnic orientation also resulted in more favourable perceptions of Facebook advertising.

Research limitations/implications

Research on Facebook advertising was only conducted in SA, whereas other emerging countries warrant further investigation to establish if they share the slight positive sentiment towards intention-to-purchase and purchase. This inquiry only provides a “snap shot” of behavioural attitudes, usage and demographic factors towards social media advertising, whereas future research could consider the development of cognitive, affective and behavioural attitudes towards Facebook advertising by employing longitudinal and qualitative research designs.

Practical implications

Organisations and managers should consider that their existing Facebook advertising strategies may only have a limited effect on intention-to-purchase and purchase in SA. However, certain usage characteristics, namely the more time spent logged on to Facebook and the greater frequency of profile update incidence, as well as the demographic variable, namely black and coloured Millennials, resulted in more favourable behavioural attitudes towards Facebook advertising. Hence, organisations and managers should be prepared to alter or adapt their Facebook advertising tactics accordingly when targeting the notoriously fickle Millennials.


This investigation found that Facebook advertising has a nominal positive influence on behavioural attitudes among Millennials, which is in congruence with the communications of the effect pyramid model that was established through traditional advertising research. This paper also makes a noteworthy contribution to attitudinal research in emerging countries where there is a dearth of research in social media advertising.

  • Social media
  • South Africa
  • Millennials
  • Behavioural attitudes
  • Facebook advertising
  • Intention-to-purchase

Duffett, R.G. (2015), "Facebook advertising’s influence on intention-to-purchase and purchase amongst Millennials", Internet Research , Vol. 25 No. 4, pp. 498-526. https://doi.org/10.1108/IntR-01-2014-0020

Emerald Group Publishing Limited

Copyright © 2015, Authors. Published by Emerald Group Publishing Limited. This work is published under the Creative Commons Attribution (CC BY 3.0) Licence. Anyone may reproduce, distribute, translate and create derivative works of the article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licenses/by/3.0/legalcode .

1. Introduction

Technological innovation has grown at an unprecedented rate over the past couple of decades, especially in terms of online social media platforms. Accordingly, Millennials (born between 1982 and 1994) have been exposed to an explosion of online technological applications since their advent, as these have been incorporated into nearly every facet of their daily existence. In fact, this cohort has not experienced the world without digital interactive technology. Moreover, technology diversification drives universal homogeneity among Millennials, resulting in a hypothetical global cohort that purportedly displays analogous attitudes and behaviour ( Lingelbach et al. , 2012 ; Moore, 2012 ). Yet, many articles have characteristically concentrated on the social media attitudes and usage of Millennials who reside in developed countries with unhindered access to social media and information technology. Hence, Bolton et al. (2013) maintain that social media attitudes and usage may differ among Millennials from emerging countries when compared to their wealthier counterparts owing to technological infrastructure and different cultures. Nonetheless, Millennials’ social media usage are of particular interest to organisations and managers’ since it may provide an indication of how these consumers will behave in the future, as well as what their perceptions are towards their brands ( Bolton et al. , 2013 ). Consequently, this study aims to establish if Facebook advertising is effective at realising the top communication of effects pyramid objectives, intention-to-purchase and purchase (the behavioural attitude), among the Millennial cohort.

Social media has become an imperative conduit for global marketing communications and is commanding a larger share of advertising budgets, especially to reach the younger generation. Therefore, the value of advertising on social media such as Facebook, Youtube, LinkedIn, Twitter and others is of great interest to organisations, managers and academics ( Saxena and Khanna, 2013 ). Much academic research has explored the attitudes and perceptions of online advertising ( Shu and Chuang, 2011 ; Jalilvand and Samiei, 2012 ; Blasco-Arcas et al. , 2014 ; Hsu et al. , 2014 ) and more recently, social media ( Maxwell, 2013 ; Persuad, 2013 ; Tham et al. , 2013 ; He and Zha, 2014 ; McCarthy et al. , 2014 ). There is also consensus that online advertising can be appraised via elements such as brand awareness, product recall and attitudinal and behavioural changes ( Bannister et al. , 2013 ; Barreto, 2013 ; Hudson and Thal, 2013 ).

However, Bolton et al. (2013) believes that previous research on social media among Millennial users results in more questions than answers. Bolton et al. (2013) suggest that prior research predominantly focused on US social media users, disregarding other emerging regions with rapidly growing Millennial populations, where the use of social media and its determinants might differ considerably. Accordingly, this study focused on social media users in South Africa (SA), where nearly 25 per cent of the population are deemed to be Millennials ( Statistics South Africa (SA), 2012 ). Furthermore, Bolton et al. (2013) noted that a majority of studies focused on student populations whose behaviour may change as they progress though the different stages of their life cycle. A broad spectrum of the Millennial cohort was surveyed, which comprised of young working adults and individuals who were still seeking employment from both rural and urban regions. Moreover, participants from both advantaged (suburbs) and disadvantaged (townships) communities were also included, instead of only utilising a student population. Bolton et al. (2013) also questioned whether there were noticeable differences among Millennial subgroups in their use of social media. Thus, the influence of a range of usage characteristics and demographic factors within the Millennial subgroups were also investigated in this study. Furthermore, Facebook revenue from advertising has grown by 59 per cent during the past year to over $5.4 billion in 2014 ( Facebook, 2014a ), which is testament to the shift from traditional media advertising to digital interactive media advertising by organisations. It is estimated that Millennials will have a combined purchasing power of $2.45 trillion world wide by 2015. It can be assumed that social communications in the form on online reviews, posts and word-of-mouth (WOM) will play a large part in driving purchase decisions ( Priyanka, 2013 ). Therefore, it is imperative that organisations have a complete understanding of the behavioural attitudes of this target market, especially in terms of usage characteristics and demographic factors that can be identified by Facebook Insight metrics ( Facebook, 2014b ) so that they can use their marketing communications budgets effectively by targeting those Millennials that yield the greatest behavioural response.

2. Literature review

2.1. social media background.

The rapid growth of social media platforms has permanently altered the way that numerous consumers interact with each other and organisations. Hence, this has changed the way that organisations attract and retain prospective consumers ( Leung et al. , 2015 ). Previously, marketers would create captivating advertising messages and purchase space in the mass media in the hope that consumers would become aware of and develop a preference to and purchase the brand. Social media has irrevocably altered marketing communications by shifting ways in which consumers select, share and appraise information. With the advent of social media, traditional media such as television and newspapers have lost uninterrupted viewership and readership, and their influence as advertising channels may have been weakened. The speed of online communication and numerous information sources make advertising on traditional sources less relevant. Furthermore, marketers quickly realised the influence of social community in terms of interactivity that comprises of personalised sections, shopping experiences, greater convenience and widespread information search ( Chandra et al. , 2012 ; Patino et al. , 2012 ; He and Zha, 2014 ).

Consequently, marketers are increasing their social media budgets with digital interactive advertising forecasted to reach $138 billion in 2014, a growth rate of nearly 15 per cent in comparison to 2013 ( eMarketer, 2014a ). Furthermore, the Middle East and Africa are predicted to have the highest social media advertising spend growth (64 per cent) in 2014 ( eMarketer, 2014c ). Business-to-consumer (B2C) ecommerce revenue is expected to reach $1.5 trillion in 2014 (an increase of 20 per cent), with growth primarily coming from emerging markets ( eMarketer, 2014b ). Current figures reveal that the largest online social medium in the world is Facebook, with 1.32 billion active members, and it is also the largest social commerce site that accounts for 85 per cent of all orders from social media ( Facebook, 2014a ; Shopify, 2014 ). The aforementioned evidence necessitates research into behavioural attitudes towards Facebook in an emerging country, namely, SA, which will be of interest to managers and their organisations.

2.2. Facebook marketing communication efficacy

The world wide adoption of mobile phones has driven Facebook’s mobile impetus, as the number of consumers that access the internet via mobile is closing the gap on computer-based online users. World Wide Worx indicated that there are 9.4 million active Facebook users in SA (making it the largest social medium in the country), with 87 per cent accessing Facebook via mobile devices such as cell phones and smartphones ( Wronski and Goldstruck, 2013 ). Additionally, 93 per cent of companies in SA use Facebook, with two-thirds using this platform as a core part of their marketing campaigns, and 47 per cent for customer lead generation ( Wronski and Goldstruck, 2013 ). Few studies have determined whether social media advertising is effective when accessed via mobile devices, which is examined in this paper. A review of Facebook’s global advertising performance indicated that click-through rates had improved by 20 per cent from 2011 to 2012 ( AYTM, 2012 ). Furthermore, the cost per click had risen by over a quarter and the cost per thousand increased by more than half. However, Greenlight (2012) found that 44 per cent of consumers did not ever click on Facebook advertisements, 31 per cent rarely did, 10 per cent often did and 3 per cent clicked regularly. While Associated Press and CNBC (2012) reported that over eight out of ten Facebook users never or seldom viewed Facebook advertisements or their sponsored content. However, Reuters and Ipsos (2012) revealed that one in five Facebook users had purchased products as a result of advertisements and/or comments that they viewed on Facebook. This rate increased to nearly 30 per cent who were aged 18-34. Facebook and ComScore (2012) disclosed that 4 per cent of consumers bought something within a month after being exposed to earned brand impressions from a retailer. The exposure also increased consumers’ intention-to-purchase. RichRelevance (2013) revealed that consumers who made purchases, owing to Facebook advertising, were double in comparison to Pinterest and Twitter. Facebook also had the greatest income per session. Bannister et al. (2013) found that the attitudes of US college students towards Facebook advertising were largely negative or indifferent. Respondents disclosed that Facebook advertisements were predominantly uninformative, irrelevant, uninteresting, and would, therefore, not generally click on them. Moreover, a majority of college students stated that they would not make a purchase owing to Facebook advertising. Persuad (2013) used a controlled experiment among 96 young adults to explore the impact of interactivity and product involvement on respondents’ attitudes towards brands on Facebook and their intention-to-purchase. No significant results were found for interactivity, product involvement or intention-to-purchase. However, the study revealed that high levels of interactivity on Facebook were positively correlated to intention-to-purchase and favourable attitudes towards the brand. The divergent results of Facebook’s marketing communication efficacy warrant additional investigation.

2.3. Millennials cohort

Millennial (Echo boomers, Generation Y, hip-hop, kwaito or Facebook generation) consumers are the children of the Baby Boomers or Generation X ( Dotson and Hyatt, 2005 ; Berndt, 2007 ). Most of the discussion is based on international studies, with some commentary on Millennial consumers in SA, although cohort research is deemed to be transnational. Millennial consumers enjoy communication, since they are self-expressive and support freedom of speech, as well as accept change and are even deemed to be trendsetters ( Lingelbach et al. , 2012 ; Moore, 2012 ; Bolton et al. , 2013). Millennials are always connected and connect with one another via the latest technologies ( Goldenberg, 2007 ). The black Millennials cohort encompasses a significant portion of the South African market, especially those who are studying at tertiary institutions, as they represent a particularly lucrative target market owing to the fact that higher education is correlated with increased earning potential ( Bevan-Dye et al. , 2012 ). Most Millennial members would have first encountered computers as toddlers and embraced the interconnectedness of the internet, mobile devices and social media social network sites (SNS) as part of their interactive world. The duo of interconnectivity and being tech savvy reveals the huge influence of Millennials’ predisposition to connect continuously and easily to multiple social network channels that are embraced for purchase decisions and to initiate electronic WOM ( Noble et al. , 2009 ).

Africa has experienced exponential internet growth over the past decade, with only 4.5 million internet users at the start of 2001 that grew to over 167 million in June 2012 ( Internet World Stats, 2012 ). A primary reason for this massive expansion in internet usage is owing to the increasing number of internet-enabled mobile and smart phone users, as mentioned in prior text. This new found connectivity has permitted more Africans to join the online world, while many are also joining SNS that allow them to interact with people around them and across the globe. SNS is the most popular online activity, with nearly 60 per cent of African users favouring it above all other online activities. Facebook is the dominant SNS, however, owing to the proliferation of smartphones, it is probable that Twitter will also gain favour as its usage has directly begun to increase exponentially ( Digital Fire, 2012 ). Two-thirds of South Africans are 30 years old or younger and a little under 25 per cent (over 13 million individuals) are deemed to constitute the Millennials cohort ( Statistics SA, 2012 ). However, less than 20 per cent of advertising budgets are directed at these young consumers in SA, yet Millennials spend over R100 billion per annum, which makes them a lucrative target market ( Levin, 2013 ). JWT Intelligence (2012) revealed that Millennials display a high propensity for SNS shopping-related activities: 63 per cent of Millennial online users have requested advice from friends about brands on Facebook, six out of ten were more probable to buy a brand based on recommendations received via Facebook, and 57 per cent had displayed a status update on their Facebook page about a brand. Barreto (2013) employed eye-tracking experiments among 20 undergraduates to establish whether they perceived advertisements on Facebook. The research confirmed that Facebook advertisements resulted in lower attention levels in comparison to the recommendations of friends. Yaakop et al. (2013) examined the cognitive interactivity (awareness and knowledge) and advertising avoidance (negative sentiment towards social network advertising (SNA)) influence on attitudes towards Facebook among 357 undergraduate students. The study revealed that both cognitive interactivity and advertising had significant influence on attitudes towards Facebook advertising, thereby revealing both negative and positive attitudes towards Facebook advertising. Hence, owing to these conflicting findings, it is necessary to further explore Millennials’ attitudes towards Facebook advertising.

2.4. Attitudes and hierarchy response model

Belch and Belch (2012) assert that there are three attitudinal stages or components, which are encapsulated in the tricomponent attitude model: cognitive component (an individual’s beliefs regarding an object), affective component (an individual’s feelings towards the object that may be positive or negative) and the behavioural component (an individual’s readiness to respond to the object in the form of behaviour).

Lavidge and Steiner (1961) diverged from prior early hierarchy response model development, since they believed that immediate sales was an insufficient factor of advertising effectiveness, even if it was measurable. They posited that advertising was an enduring investment, which was mainly owing to the long-term nature of advertising effects that resulted in the development of the hierarchy-of-effects model. Hence, it was inconceivable that consumers moved from a stage of total disinterest to eager purchasers; but instead moved through a sequence of steps until purchase. These steps are as follows: unawareness of the brand’s existence, awareness, knowledge of what the brand offers (awareness and knowledge form the cognitive attitude component), consumers like the brand (a favourable affective attitude), consumers prefer the brand over others (a favourable affective predisposition) and have a desire to purchase the brand and conviction that it would be a wise purchase that leads to purchase intent, and finally culminating in the actual purchase (behavioural attitude component). The steps of the hierarchy-of-effects model are analogous to the communications of effect pyramid (also known as the purchase funnel) that was mentioned in prior text. It becomes progressively more difficult to achieve the upper level stages and, hence, the number of prospective consumers decreases as they progress through the latter stages of the pyramid ( Safko, 2010 ; Belch and Belch, 2012 ).

Chandra et al. (2012) conducted research into attitudes towards SNA among undergraduate and postgraduate students. The study found that social media advertising aided the purchase decision and resulted in more competitive prices, but held unfavourable attitudes in terms of various cognitive (information) and affective (enjoyment, entertainment value and authenticity) components (lower level pyramid activities). Powers et al. (2012) agreed with the aforementioned sentiments and disclosed that over 20 per cent of consumers believed that social media was important for their final purchase decision; while another 20 per cent stated that it helped them to decide what to purchase. Hudson and Hudson (2013) used a case study research design to explore the influence of social media (Facebook and Twitter) on music festival consumer decisions. The research confirmed that consumers were actively engaged with the companies after purchase (the top purchase funnel echelon), thereby facilitating brand development. Smith (2013) determined that Facebook users who indicated having favourable experiences with an organisation’s brand content led to an increased probability of executing a higher level communications of effect pyramid action, whereas Yadav et al. (2013) surmised that products, which require a high effort and strong social component have a strong influence on purchase decisions in terms of computer-mediated social environments. Edwards (2011) found that companies, which employed social media, enhanced the elements of the purchase funnel such as awareness, consideration and purchase, while Carrillat et al. (2014) suggested that Facebook messages must be entertaining to have a positive impact on attitudes. Hence, this study seeks to confirm whether Facebook advertising has a positive effect on the top two levels of the communications of effect model. Table I provides an overview of recent Facebook marketing communications studies, which investigated the upper communications of effect pyramid levels, namely intention-to-purchase and purchase.

In summary, there have been a number of recent studies that assessed behavioural attitudes towards SNA, but these were predominantly conducted in more developed nations; utilised students as the research population; used relatively small sample sizes; and few explored the effect of usage characteristics and demographic factors on Facebook advertising.

3. Research objectives

Consequently, this empirical investigation seeks to expound upon the following research objectives: first, to determine whether advertising on Facebook has an influence on the behavioural attitudinal component of Millennials in an emerging country such as SA. As discussed in prior text, advertising achieves communication activities in a similar manner to a pyramid, by initially attaining lower hierarchy response marketing communication objectives such as awareness and knowledge. Thereafter, companies seek to attain and move consumers to higher hierarchical level objectives such as liking, preference and intention-to-purchase until the ultimate purchase. However, this model was based on traditional advertising, whereas this research focuses on new digital interactive media to determine consumers’ behavioural attitudes as they pass the upper echelons of the aforementioned model. Consequently, this research is important for managers, since a majority of organisations have invested significant portions of their promotion budgets on Facebook marketing communications, and need to establish if advertising on Facebook has a positive impact on the aforementioned behavioural attitudes. This empirical study is also important for academics and researchers, since, as mandated by Bolton et al. (2013) and Okazaki and Taylor (2013) , there is a dearth of social media advertising usage and attitude research among Millennials in emerging countries and, accordingly, this will contribute to attitude theory. Additionally, Facebook’s growth has begun to reach saturation in many first-world countries; whereas it is steadily growing at an incremental rate in many emerging countries. Facebook use has grown by almost 40 per cent over the past year in SA ( Wronski and Goldstruck, 2013 ). Furthermore, a number of studies have yielded divergent behavioural attitudinal responses. Bannister et al. (2013) , Kodjamanis and Angelopoulos (2013) , Maxwell (2013) and Persuad (2013) suggest that attitudes towards Facebook marketing communications were mainly negative or indifferent, whereas Chandra et al. (2012) , Mir (2012) , Leung et al. (2015) and Rohm et al. (2013) found a largely positive behavioural predisposition. Accordingly, the research questions (RQ) for the first objective are:

RQ1. Does Facebook advertising have an effect on intention-to-purchase among South African Millennials?

RQ2. What impact does advertising on Facebook have on purchase amid Millennials in SA?

Second, to establish if usage factors, which include how Facebook is accessed (as mentioned previously, 87 per cent of Facebook users in SA access this social medium via mobile phones; Wronski and Goldstruck, 2013 ), length of usage, log on duration, log on frequency and profile update incidence, have an influence on Millennials’ intention-to-purchase and purchase perceptions of advertising on Facebook. This research objective is of interest to both managers and academics, since it will provide insight into Millennials’ social media usage characteristics, and whether these affect their behavioural attitudes. Ultimately, this objective will provide a greater understanding of Millennials’ future consumer behaviour. Moreover, little research has been conducted to determine if the various usage characteristics have an influence on the impact of Facebook advertising behavioural attitudes among Millennial users, which will add to the conceptual framework of attitudinal research in social media. Chandra et al. (2012) determined that more frequent social media users exhibited a favourable attitude towards SNA, as it assisted with buying decisions; Punj (2011) found that internet usage levels influenced belief-behavioural responses; and Taylor et al. (2011) established that many social media users utilise SNS as part of their everyday routine, which may result in an elevated prospect of consumers perceiving SNA more favourably. Therefore, the RQ for the second objective are as follows:

RQ3. What influence do South African Millennial usage variables have on intention-to-purchase owing to Facebook advertising?

RQ4. Do usage characteristics of Millennials in SA have an impact on purchase as a result of Facebook advertising?

Third, to determine if demographic factors (gender, age and ethnic orientation) have an impact on Millennials’ intention-to-purchase and purchase perceptions of Facebook advertising. This objective will reveal whether there are noticeable differences within Millennial subgroups, as mandated by Bolton et al. (2013) , with regard to their attitudes towards Facebook advertising. Additionally, the ethic orientation analysis is of particular interest to managers and academics owing to the well-known injustices of the past that took place in SA, which resulted in a substantial economic divide. Furthermore, few studies have investigated the effect of demographic factors, especially age (within a particular cohort) and ethnic orientation, on attitudinal research. Ruane and Wallace (2013) established that Facebook yielded favourable behavioural attitudinal responses among Millennial women; while Punj (2011) determined that different demographic characteristics influenced behavioural activities; and Wang and Sun (2010) revealed that ethnic factors had an impact on behavioural responses. Hence, the RQ for the third objective include the following:

RQ5. Do demographic factors have an effect on intention-to-purchase among South African Millennials owing to Facebook advertising?

RQ6. What effect do demographic variables have on purchases that are attributable to advertising on Facebook amongst Millennials in SA?

4. Methodology

4.1. research design.

A research design is a plan, structure and strategy of investigation, which is conceived to obtain answers to RQ or problems. A research design is a procedural plan that is adopted by the researcher to answer questions validly, objectively, accurately and economically ( Kumar, 2011 ). Descriptive research is concerned with the current status of the phenomena to acquire a better understanding of the existing situation, but disregards the cause of the research problem ( Tustin et al. , 2005 ). As implied by its name, this research method describes the characteristics of groups and people ( Zikmund and Babin, 2007 ). Descriptive research typically takes a cross-section of a population, in this instance Millennials who reside in the Western Cape, and reveals their predisposition at a given point in time (behavioural attitudes towards Facebook advertising) on which the research can be built. Survey methods are typically associated with descriptive research ( Hair et al. , 2009 ). A measurement instrument (typically a questionnaire) is employed to take a snap shot (cross-section) of independent (usage characteristics and demographic factors) and dependent (intention-to-purchase and purchase) variables of a given research population by means of a sample at a given point in time. The main advantage of a survey is its capability of collecting a large quantity of data ( Bhattacherjee, 2012 ), whereas the main disadvantages are its high cost and that fieldworkers should be well trained ( Maree, 2007 ). Hence, structured self-administered questionnaires were distributed on a face-to-face basis to collect the required data for this study.

4.2. Sampling

Young adults (Millennials) are the predominant users of online digital applications such as SNS ( Du Chenne, 2011 ; Smith, 2012 ; Bolton et al. , 2013 ; Wronski and Goldstruck, 2013 ). Students were selected to investigate attitudes towards SNA and attitudes by a majority studies ( Molnár, 2011 ; Orpana and Tera, 2011 ; Vanden Bergh et al. , 2011 ; Bannister et al. , 2013 ; Persuad, 2013 ). Yet, the researcher believed that it was imperative to select a sample that included a broader spectrum of Millennials, as mandated by Bolton et al. (2013) owing to the consumer behavioural changes that occur as young adults pass though the phases of their natural life cycle. Hence, the research population comprised of young employed individuals, students and young adults who were still seeking employment. The unemployment rate in SA is in the region of 30 per cent, and is much higher among young adults (up to 50 per cent) ( Statistics SA, 2012 ). Furthermore, young adults were surveyed in both rural and urban areas, which encompassed wealthy suburbs and disadvantaged township communities to ensure a representative sample.

A sample frame is a record of all the sample units that are available for selection at a given stage in the sampling process ( Martins et al. , 1996 ; Zikmund, 2003 ; Aaker et al. , 2004 ). The Western Cape was selected to collect data, which represents a little over 11 per cent of the South African population ( Statistics SA, 2012 ). The study utilised a quasi-probability sample in the form of a multi-stage sampling technique, whereby, as mentioned in prior text, the Western Cape was selected from the nine provinces in SA. Various geographic areas (clusters), which included suburban (characteristically wealthier areas) and townships (which includes informal settlements) in both urban and rural locations, were identified by means of a map. Thereafter, commercial and community organisations (sports clubs, youth groups, churches and other local groups), as well as tertiary education institutions, were randomly selected via listings in a regional telephone directory. Next, these organisations were telephoned to obtain approval to carry out the empirical research and to ascertain whether there were an adequate number of Millennials to survey. Systematic sampling is a process whereby a random starting place is determined, followed by every k th element being selected by moving through the sample frame ( Maree, 2007 ; Bhattacherjee, 2012 ). This sampling technique was used to survey participants in the aforementioned organisations, with every third participant invited to voluntarily partake in the research.

4.3. Design of research instrument and data collection

A self-administered survey allows respondents to complete a survey instrument on their own, which has the benefits of eliminating interviewer bias, the ability to reach large research populations and attain an acceptable response rate ( Denscombe, 2010 ; Burns and Bush, 2012 ; Haydam and Mostert, 2013 ). The main disadvantage of self-administered questionnaires is the low-response rate if disseminated via mail, e-mail or online ( Bhattacherjee, 2012 ), however, to counteract this drawback, the researcher administered the questionnaires on a face-to-face basis. Another disadvantage is that it may be difficult to obtain large quantities of information from respondents if the research instrument was too long or complex (Blumberg et al. , 2011). However, the researcher assured respondents that the questionnaire took no longer than ten minutes to complete and the face-to-face administration once again ensured a high-survey participation rate in spite of no incentive being offered. Two pre-screening questions were asked in order to identify possible respondents, hence only respondents who used Facebook and had noticed advertising on Facebook qualified to participate in the study. However, respondents did not need to identify or list any of the companies and their brands that were featured in the advertisements, and no distinction was made between the different forms of Facebook advertising, since the main object of the research was only to evaluate the behavioural impact of Facebook advertising on Millennials’ attitudes.

The first section of the research instrument comprised of five multiple-choice questions that asked respondents about their Facebook usage characteristics in terms of access, period of usage, usage frequency, log-in duration and profile update. The second section focused on the two dimensions of the behavioural attitudes, namely intention-to-purchase and purchase, owing to exposure to Facebook advertising. The nine-item scale that was used to measure intention-to-purchase was largely adapted from Putrevu and Lord (1994) , Taylor and Hunter (2002) and Wu et al. (2008) , and was employed to measure this construct using a five-point Likert scale that ranged from strongly disagree to strongly agree. The nine-item scale that was used to assess purchase was mainly adapted from Martinez-Lopez et al. (2005) , Patwardhan and Ramaprasad (2005) and Hamidizadeh et al. (2012) with a five-point Likert scale also being utilised. The last section of the questionnaire consisted of three multiple-choice questions on the demographic physiognomies that included gender, age and population group. Pre-test and pilot studies are used to survey a small subset of the population to determine whether the research instrument and method to collect data are relevant, reliable and valid ( Du Plooy, 2009 ; Bhattacherjee, 2012 ). The questionnaire was pre-tested among 100 respondents to check the reliability of the scales, wording and question order and the ability of respondents to understand the meaning of the questions. Some of the questions were reworded and a couple of the Likert scale statements were tweaked. Subsequently, a pilot study of an additional 100 respondents was conducted to check that other research elements were well-organised, and also to double check that the research questionnaire was optimal, especially in terms of scale reliability. The primary research was conducted by 22 students (reading for their bachelor marketing degree at the Cape Peninsula University of Technology, and who received six months of rigorous training and practical application by the head of research of the marketing department), who were sent to the various locations to conduct the empirical survey on a face-to-face basis. A total of 3,521 useable questionnaires were collected over a three-month period from April to June 2013.

4.4. Data analysis

Data analysis typically entails the editing and reduction of data into more manageable portions in order to create summaries, detect patterns and apply statistical methods with the express purpose of interpreted data to answer the RQ at hand ( Blumberg et al. , 2011 ; Bhattacherjee, 2012 ). The data were captured and examined via statistical software known as SPSS (version 21). However, all of the questionnaires were first meticulously examined in terms of correctness and completeness to establish whether they should be incorporated in the statistical analysis – the Likert scale statements were organised in such a manner that alternated positive and negative statements so as to circumvent participants from choosing a single column. These questions were reversed via SPSS before the reliability of the responses was established for the measurement scales. Reliability signifies the internal consistency of the items that were developed to measure a specific construct with a high level of reliability, in other words, the intention-to-purchase and purchase measurement scales. The coefficient mechanism that was used to determine reliability is known as Cronbach’s α , and reliability estimates of 0.7 and above are deemed to be acceptable ( George and Mallery, 2003 ; Hair et al. , 2009 ; Maree, 2007 ). Hence, items that are negatively worded in the scales must have their scores reversed; otherwise they would have an adverse effect on Cronbach’s α result ( Field, 2009 ). Simple descriptive statistical analysis measures (means, standard deviations, frequencies and non-parametric standardised tests) were employed to provide a basic description of the results ( Tables II, III and IV ). Validity refers to the extent to which an instrument measures the construct that it is supposed to measure ( Blumberg et al. , 2011 ; Bhattacherjee, 2012 ). To ensure validity, existing measurement scales, as mentioned in prior text, were adapted and then tested before being utilised to assess the constructs. Furthermore, Pearson’s correlation coefficient analysis ( Tables III and IV ) was used to examine and measure the linear strength of relationships between quantitative variables ( Maree, 2007 , Field, 2009 ). Analysis of variance (ANOVA) is utilised when two independent variables or more need to be compared to an individual quantitative score ( Maree, 2007 ). ANOVA used Wald’s χ 2 and was conceptualised as a Generalised Linear Model (GLM) to establish if there were significant differences between the usage characteristics and demographic factors (predictor variables) and behavioural attitude components (dependent variables). The post-ad-hoc Bonferroni pairwise comparison was utilised to establish where the differences were, so that the findings could be interpreted conclusively ( Field, 2009 ; Bhattacherjee, 2012 ).

The survey included 3,521 members of the Millennials cohort in the Western Cape. Facebook was accessed by a majority of respondents (64.5 per cent) via both PC and mobile device; over 60 per cent logged on to Facebook everyday; spent one (58.5 per cent) to two (22.8 per cent) hours per log on; and more than 72 per cent updated their profile at least of once a week. The sample included a slight majority of females (54.8 per cent); and the ethnic groups accurately portrayed the ethnicity of the Western Cape, including primarily black (35.2 per cent) and coloured (36.4 per cent) ethnic groups ( Statistics SA, 2012 ). Table II offers a full overview of the usage characteristics and demographics of Millennials respondents that use Facebook.

As previously mentioned, the respondents’ behavioural attitude towards Facebook advertising was computed by nine-item scales for each of the hierarchy response levels ( Tables III and IV ).

Cronbach’s α was 0.843 for the Facebook advertising intention-to-purchase scale ( Table III ) and 0.742 for the Facebook advertising purchase scale ( Table IV ), which indicated good internal consistencies. A non-parametric one-sample bi-nominal standardised test was utilised to determine if there was a significant difference. The test showed that for both of the nine-item scales, there was a significant difference at p < 0.001 and p < 0.05, with the exception of one item in the intention-to-purchase scale. Pearson’s correlation coefficient analysis ( Tables III and IV ) showed a positive medium ( r > 0.3) to strong ( r > 0.5) relationship between a majority of the variables for the intention-to-purchase and purchase measurement scales, but there was weak positive correlation between a minority of the variables, especially in terms of the negatively reversed variables that were recoded.

The GLM ANOVA, as discussed in prior text, was used since the data contains a different number of observations for certain independent variables, which can be seen by the larger standard errors (an example of this is the low number of respondents that logged on to Facebook at least once a month). Van Schalkwyk (2012) discloses that the GLM takes this into consideration and “normalises” the outcomes. Tables V and VI show the effect in terms of Wald χ 2 test, which is based on the Bonferroni correction pairwise post hoc test among the estimated marginal means.

The Wald χ 2 test revealed that there was a significant difference at p < 0.001 for intention-to-purchase ( M =2.94, SD=0.805) because of Facebook advertising. No significant differences were found for access, length of usage, log on frequency, gender and age, whereas Bonferroni correction pairwise comparisons of estimated marginal means disclosed the significant difference between the next variables.

Log on duration ( p < 0.001): respondents who logged on for 1 hour ( M =2.82, SE=0.033) resulted in lower intention-to-purchase levels in comparison to those who logged on for two hours ( M =2.98, SE=0.039).

Profile update incidence ( p < 0.001): respondents who updated their Facebook status daily ( M =3.06, SE=0.041) resulted in greater intention-to-purchase compared to those who updated once a week ( M =2.93, SE=0.044), two to four times a month ( M =2.81, SE=0.050) and once a month ( M =2.81, SE=0.042); those who updated their Facebook status two to four times a week ( M =2.98, SE=0.043) showed an increase in intention-to-purchase compared to those who updated it two to four times a month ( M =2.81, SE=0.050) and once a month ( M =2.81, SE=0.042).

Ethnic group ( p < 0.001): white respondents ( M =2.79, SE=0.041) exhibited lower intention-to-purchase levels than black ( M =3.01, SE=0.035) and coloured ( M =2.96, SE=0.037) respondents.

The Wald χ 2 test disclosed that there was a significant difference at p < 0.001 for purchase ( M =2.94, SD=0.656), which was caused by Facebook advertising. No significant differences were found for access, length of usage, log on frequency, age, gender and race; however, Bonferroni correction pairwise comparisons of estimated marginal means showed significant difference amongst the following variables.

Log on duration ( p < 0.001): respondents who logged on for one hour ( M =2.85, SE=0.027) exhibited lower purchase levels compared to those who remained logged on for two hours ( M =3.01, SE=0.032) and four hours ( M =3.06, SE=0.056).

Profile update incidence ( p < 0.001): respondents who updated their Facebook status daily ( M =3.07, SE=0.034) resulted in higher purchase incidence in comparison to those who updated once a week ( M =2.97, SE=0.036), two to four times a month ( M =2.88, SE=0.041) and once a month ( M =2.86, SE=0.035); those who updated their Facebook status two to four times a week ( M =3.01, SE=0.035) showed increased intention-to-purchase levels compared to those who updated two to four times a month ( M =2.88, SE=0.041) and once a month ( M =2.86, SE=0.035).

In summary, a comparison between the usage characteristics ( Tables V and VI ) reveals that log on duration and profile update incidence show the largest degree of influence on Facebook advertising intention-to-purchase and purchase, whereas access, length of usage and log on frequency had little effect on the behavioural attitudinal component. A comparison between the demographic factors ( Tables V and VI ) shows that ethnicity displayed the greatest amount of influence on Facebook advertising intention-to-purchase and had some effect on purchase, but not at a significant level. Gender also had some impact on Facebook advertising purchase, but again not at a significant level, whereas gender had little effect on intention-to-purchase. The demographical variable age had no influence on Facebook advertising intention-to-purchase and purchase. A more detailed discourse on the effect of usage characteristics and demographical factors on Facebook advertising intention-to-purchase and purchase ensue in the following section.

6. Discussion and implications

6.1. key findings.

The first objective of this study was to establish if Facebook advertising had a favourable impact on the behavioural attitudes of Millennials in SA. The analysis indicates that Facebook advertising has a positive attitudinal influence on intention-to-purchase and purchase among Millennials, although at a marginal level, which supports the communications of the effect pyramid model. These findings are in agreement with a number of authors: Leung et al. (2015) revealed that a positive experience with Facebook would lead to a favourable attitude towards the Facebook page, which increased the consumers’ intention-to-purchase; Yang (2012) reported that advertising messages provided by Facebook enhances consumers’ attitudes towards brand and purchase intentions, while advertising messages that were provided by organisations had a greater impact than those sent by friends; and eMarketer (2012) found that consumers who were exposed to both paid and earned media could assist organisations with purchase consideration and brand liking/preference. These results could also be explained by the fact that Facebook has a diverse range of interactive and elements such as walls newsfeeds, albums, blogs, discussion forums and so forth, which enable organisations to generate relations with consumers. Therefore, with the longstanding exposure of Facebook applications, incentives and interaction, consumers tend to establish more favourable brand attitudes and greater purchase intentions pertaining to brand advertising on this platform ( Rau et al. , 2008 ). Ha and Janda (2014) postulated that positive attitudes had an influence on online behavioural intentions. However, Hudson and Thal (2013) disclosed that marketers were not effectively interacting with consumers who used social media. The research suggested that organisations focus on an array of consumer decision stages, instead of information and knowledge (cognitive) and purchase (behavioural) stages. Maxwell (2013) also revealed that many online consumers conduct research on the internet and SNS, but still favour purchasing products and brands at retailer stores.

The second objective of the research was to determine if certain usage characteristics had an effect on Millennials behavioural attitudes towards Facebook advertising. The research revealed that advertising on Facebook was most effective when Millennials spent two or more hours on Facebook per log-in session, which is a logical perception, as they would have more opportunity to interact with the advertising. Young adults have a high propensity towards multi-tasking and mobile devices, which enable them to be continuously on the move, while accessing the internet; SNS; television; and communication via text, graphics and verbally; as well as searching for consumer-related information to make purchase decisions ( Crosman, 2008 ).

This study confirmed that Millennial members who update their profile on Facebook more prolifically facilitated increased positive behavioural attitudes. This is a reasonable notion, since increased activity on Facebook should lead to greater activity with other elements such as advertising. This finding is also congruent with Chandra et al. (2012) who found that regular users displayed a positive attitude towards SNA, since it aided purchasing decisions.

No significant differences were revealed in terms of length of usage, log on frequency and how Facebook was accessed. This is an unexpected result, since Wronski and Goldstruck (2013) disclosed that almost nine out of ten Facebook users access Facebook via mobile phones. Facebook mobile advertising was launched in 2012 and received click-through rates of up to 13 times greater than other advertisements on Facebook ( Bischoff, 2012 ). Dynamic Logic (2012) indicated that intention-to-purchase was almost four times higher for mobile advertising that resulted in higher average click-through rates. Hence, it is apparent that Millennials in SA have divergent sentiments in comparison to their international counterparts.

The third objective of this investigation was to examine whether particular demographic factors had an impact on Millennials behavioural attitudes towards Facebook advertising. This investigation discovered that the white population group exhibited lower levels of intention-to-purchase compared to the black and coloured ethnic groups. Internet access has grown significantly among the coloured (35.7 per cent) and black (29.4 per cent) ethnic groups in recent years, but they are still catching up to the white (70.3 per cent) ethnic group ( Statistics SA, 2012 ). The proliferation of the black middle class, categorised as the Black Diamonds by TNS Research Surveys and the UCT Unilever Institute of Strategic Marketing ( Olivier, 2007 ), has resulted in greater spending power (R400 billion per annum), with the monthly income of black households increasing by 34 per cent since 2004. SA’s black middle class has risen by nearly 250 per cent from 1.7 million in 2004 to 4.2 million in 2012 ( Shevel, 2013 ). Consequently, a large proportion of black middle class young adults have gained internet access over the past decade, whereas many white young adults grew up with the internet and, subsequently, had more exposure and experience to SNS advertising.

No significant differences were found in terms of age and gender having an impact on Millennials’ intention-to-purchase and purchase perceptions of Facebook advertising. Bannister et al. (2013) reported that women had a slightly more positive attitude to Facebook advertising, whereas Taylor et al. (2011) found that young adults (aged 19-24 years old) maintained the most positive attitudes to SNS advertisements. Hence, it is apparent that there are not many noticeable differences within the South African Millennial cohort besides ethnic orientation.

6.2. Implications for theory

Attitudes towards advertising have been broadly researched over the past few decades and it was found that consumers’ attitudes towards advertising have a direct influence on attitudes towards the brand that impacts intention-to-purchase and purchase. Additionally, attitudes towards advertising have also been deemed to be an efficient measure of advertising effectiveness ( Yoo et al. , 2010 ). The appropriateness of traditional advertising theories to online advertising has been an area of interest to academics and advertising scholars since the arrival of online advertising. Traditional methods continue to be applicable to the environment of online advertising, as the basic objectives of online advertising are inclined to be comparable to the objectives of traditional advertising, and theoretical models created for traditional advertising have effectively been transferred to online advertising ( Rodgers and Thorson, 2000 ). From both an academic and marketing practitioner perspective, the hierarchy-of-effects model has received extensive attention as a detailed explanation of how advertising works, and hence is a base for measuring advertising effectiveness ( Yoo et al. , 2010 ). Although, little research has been conducted concerning the effects of SNA in terms of this recognised theoretical framework. Consequently, this study attempted to assess the effects of SNA within the framework of the hierarchy-of-effects model. The results reveal that advertising on Facebook has a favourable impact on behavioural attitudes among Millennials, but at a minimal level, which supports the communications of effect pyramid model that was developed via traditional advertising research. This model posits that it becomes increasingly more challenging to accomplish the higher level hierarchical objectives, namely intention-to-purchase and purchase; consequently, the number of potential consumers decline as they move up the pyramid. A more positive attitude towards advertising is correlated to more favourable advertising judgments in terms of entertainment, information and acceptance, which result in greater advertisement recall and higher purchase intention ( Wang and Sun, 2010 ). Stevenson et al. (2000) disclosed that an unfavourable attitude towards online advertising was related to low purchase intention, whereas Wolin et al. (2002) proposed that a favourable attitude towards online advertising usually resulted in more recurrent online purchasing and greater online spending. Mir (2012) revealed that a positive attitude towards social media advertising influences consumers’ advertising clicking behaviour and, consequently, has an impact on their online purchasing behaviour, which is congruent with the findings of Wolin et al. (2002) and Wang and Sun (2010) . Furthermore, Powers et al. (2012) disclosed that over 20 per cent of consumers believed that social media was important for their final purchase decision and Moore (2012) found that Millennial consumers purchase brands online with greater frequency in comparison to prior generations. Hence, it can be concluded that advertising on Facebook adheres to the same notions of traditional advertising in terms of the communications of effect pyramid model. This study has made a valuable contribution to attitudinal research and theory development among Millennials.

This inquiry found that log on duration and profile update incidence had an influence on South African Millennials’ intention-to-purchase and purchase perceptions of advertising on Facebook, whereas how Facebook was accessed, length of usage and log on frequency had no influence. Punj (2011) established that internet usage frequency affected behavioural activities; and Taylor et al. (2011) observed that many consumers use SNS to overcome boredom or to use up time between activities; they also frequently use SNS as part of their everyday routine. This habitual activity may increase the prospect that consumers would perceive would SNA positively, since it may provide an added diversion and an extra means of form of time structuring, which is in consensus with the results of this investigation. Wang and Sun (2010) determined that ethnic variables had an influence on behavioural attitudinal responses; and Jordaan et al. (2011) advocate that different ethnic groups in SA should be investigated to establish whether there was a difference in terms of online intent and purchase. Consequently, this study found that ethnic orientation had a positive impact on the behavioural attitudes of black Millennials in SA, but no effect on age and gender. These results make a noteworthy contribution to the theoretical framework of attitudinal research in SNS marketing communications, since there is a dearth of research on the effect of abovementioned usage and demographic factors on the upper levels of communications of effect pyramid model.

6.3. Managerial implications

In terms of the first RQ, this inquiry showed that Facebook advertising had a marginal, but a significant positive attitudinal effect on intention-to-purchase amongst South African Millennials. Maxwell (2013) also concluded that brands are needed to create stimulating content, interaction and advocacy via their social conduits in order to establish relationships that would instigate intention-to-purchase. Persuad (2013) found that high levels of interactivity on Facebook were positively correlated to intention-to-purchase and favourable attitudes towards the brand. Barreto (2013) determined that Facebook advertising resulted in lower purchase consideration levels in comparison to the WOM by friends. Hence, marketers should attempt to stimulate interactivity and WOM by proactively endorsing the sharing of marketing communication content between Facebook users by linking it to competitions, discounts, giveaways and other sales promotions, which would stimulate an increase in behavioural activities. Marketing should consider the use of the pre-roll video, which is incorporated into flash banner advertisements that increased purchase intent by up to four times in comparison to simple static banner, rich and video advertisements ( Millward Brown, 2012 ). Hence, South African organisations and managers should take the aforementioned findings into consideration in an attempt to increase purchase intent levels among Millennials.

Vis-à-vis the second research, this investigation revealed that advertising on Facebook resulted in a diminutive, but noteworthy favourable attitudes towards purchase among the Millenial cohort. Marketers should take into consideration that cheap costs, fast service, high quality and an “experience” are important factors that influence Millennials’ purchase considerations. Facebook advertisements that are connected to a physical in store promotion may actively draw SA Millennials who are not inclined to make online purchases to the actual store to purchase. Facebook’s location point tracking systems can also be used to display local stores’ promotions based on the interests of the Millennials’ location. Chandra et al. (2012) revealed that SNS assists in making the final purchase decision and resulted in lowing prices. However, it should be noted that Millennials have generally not yet established enduring consumer behaviour patterns and do spend freely, since many are students or unemployed who have limited resources, with 45 per cent agreeing that they purchase brands on sale as opposed to their preferred brands, which would dampen their purchase sentiments ( Symphony, 2013 ). This finding vindicates the decision by South African organisations and managers to spend large percentages of their advertising budgets on Facebook marketing communications.

In respect of the third and fourth research questions, this study determined that Facebook advertising had the greatest influence on behavioural attitudes on Millennials who spent longer periods of time on the SNS. However, this survey confirmed that nearly six out of ten Millennials spent one hour or less on Facebook per log on session, which is detrimental to marketing communication efforts. Therefore, organisations and managers should attempt to incorporate a selection of Facebook’s vast array of social plugins and apps to keep the young consumer entertained on the SNS for a longer period of time, which will, in turn, lead to a positive influence on purchase decisions. Advertisements on Facebook should be changed regularly to prevent advertising wear out, especially those that are directed at Millennials who easily become bored with a static digital environment that they frequent on a daily basis. Also concerning the third and fourth research questions, this investigation established that Millennials who regularly updated their Facebook profile resulted in favourable behavioural attitudes. South African organisations and managers could use the metrics that are available on Facebook to target the most active users, as well as Facebook’s apps and social plugins in their marketing communications that could have an influence on their profile updating incidence ( Facebook, 2014b ). Marketers should also consider the use of Facebook applications, including contests, games, photo up-loaders, virtual gifting and other interactive tools, which permit organisations to create branded experiences and sharing among Facebook friends that would increase behavioural activities ( Stokes, 2013 ). The researcher expected that Facebook advertising accessed by mobile devices would deliver more favourable behavioural attitudes than desktops. However, no difference was found, nevertheless organisations and managers still need to consider mobile marketing as an online purchasing resource owing to the rapid adoption rate of mobile devices. Furthermore, the more mobile friendly and the easier advertisements on Facebook are to access, the greater the outcome will be when Millennials want to purchase products of a particular brand. With reference to the fifth research question, this study revealed that black and coloured ethnic groups displayed more favourable purchase intent tendencies than their white counterparts, however, not in terms of the sixth research question, namely purchase. Nevertheless, black young adults represent a potentially profitable target market, because in recent years the black middle class consumers spend in SA has surpassed their white counterparts ( Petzer and De Meyer, 2013 ), which has also received increased exposure to Facebook advertising that should be exploited by savvy organisations and managers. Carrillat et al. (2014) indicate that Facebook marketing communication messages must be entertaining to have a favourable effect on attitudes. The use of humorous and creative advertisements is more likely to stimulate interaction with Millennials that may result in behavioural activities across different cultural groups. Facebook Insights provides data on usage and demographic information in terms of how users have interacted with an organisation’s Facebook page and marketing communications ( Facebook, 2014b ). Hence, marketers could increase their efficiency in targeting Millennials by using the usage and demographic factors identified in this study, which resulted in the most favourable behavioural attitudes.

SNS is a rapidly growing marketing communication tool, but it is up to marketers to recognise that the expectations, needs and wants of Millennial consumers are continually changing and hence this should be taken into consideration when using SNA to favourably influence this cohort’s behavioural predisposition.

6.4. Conclusion

Many organisations hold the mistaken belief that they can simply establish a Facebook page and post-content occasionally that will result in an incremental increase in sales. However, this is far from the truth, as social media must become a fundamental part of the organisation’s overall marketing communication strategy and activities in order for it to yield full potential. Furthermore, Millennial consumers have tremendous purchase power and influence on the other cohorts, so their media usage and attitudes towards various media are important to organisations and their brands. A thorough knowledge of this cohort will allow marketers to increase their marketing communication efficiency. This research has generated important new insights about a relatively new topic, specifically in terms of the African context, which is of benefit to organisations that utilise or intend to use Facebook social media as a marketing communication platform, and to academics who are scholars of attitudinal theory development. The study specifically provides valuable insights into the behavioural attitudes of South African Millennials towards Facebook advertising, as well as several usage characteristics and demographic variables that have a favourable influence on intention-to-purchase and purchase perceptions, which have received limited prior empirical investigation. Advertisements should be carefully created to be interactive and stimulating in order to appeal to Millennials who are notoriously fickle and difficult to reach. Furthermore, Hadija et al. (2012) proposed that organisations and managers must also understand what consumers and prospective consumers are doing on SNS such as Facebook; hence, should be prepared to alter or adapt their SNA strategies owing to changes that occur in the environment, and as a result of consumer feedback and academic research in order to increase the effectiveness. This study has assisted to reduce the aforementioned mandated academic-practitioner gap.

7. Limitations and directions for future research

This investigation has some limitations and also lends itself to additional research. The inquiry did not take the various types of Facebook advertising into consideration; therefore, it is suggested that further research should be conducted to determine whether there was a difference in attitudinal effectiveness between the various advertising forms. Only the behavioural attitude and a single SNS was surveyed, whereas future studies could examine other attitude components, as well as other widely used SNS such as YouTube, Google+, LinkedIn and Twitter. Cognitive and affective attitudes warrant further research, since consumers’ first need to become aware and be informed of an organisation’s products and develop favourable emotional bonds before they can progress to behavioural activities. Like this study, surveys, which constituted a cross-section of attitudes were previously used in cognitive and affective attitudinal research. Hence, a longitudinal approach would yield more complete results, as inferred by Kalampokis et al. (2013) and Schoen et al. (2013) . This study utilised quantitative data, as have past inquiries on cognitive and affective attitudinal components, whereas qualitative research would provide greater insight into Millennials’ attitudes. Future research could also take other countries into consideration, since a developing country with a diverse and rich culture such as SA, may differ from other developing nations.

               Table I
               Summary of recent Facebook media literature that investigated behavioural attitudinal research

Summary of recent Facebook media literature that investigated behavioural attitudinal research

               Table II
               Facebook usage characteristics and demographics

Facebook usage characteristics and demographics

               Table III
               Facebook (FB) advertising intention-to-purchase scale

Facebook (FB) advertising intention-to-purchase scale

               Table IV
               Facebook (FB) advertising purchase scale

Facebook (FB) advertising purchase scale

               Table V
               Effect of usage characteristics and demographics on Facebook advertising intention-to-purchase

Effect of usage characteristics and demographics on Facebook advertising intention-to-purchase

               Table VI
               Effect of usage characteristics and demographics on Facebook advertising purchase

Effect of usage characteristics and demographics on Facebook advertising purchase

About the author

Dr Rodney Graeme Duffett is a Senior Lecturer at the Faculty of Business, Cape Peninsula University of Technology (CPUT), Cape Town, South Africa. He is currently reading for the Doctor Technologiae Degree in Marketing at CPUT. He has published in African Journal of Business Management , Southern African Business Review and Journal of Contemporary Management . His research interests focus on any form of e-advertising, social media and black economic empowerment in the advertising industry. Dr Rodney Graeme Duffett can be contacted at: [email protected]

Aaker, D.A. , Kumar, V. and Day, G.S. ( 2004 ), Marketing Research , 8th ed., John Wiley , New York, NY .

Associated Press and CNBC ( 2012 ), “Is there a problem with Facebook advertising?”, available at: www.emarketer.com/Article.aspx?R=1009065 (accessed 1 July 2013).

AYTM ( 2012 ), “Facebook marketers find better payoff with sponsored stories”, available at: www.emarketer.com/Article/Facebook-Marketers-Find-Better-Payoff-with-Sponsored-Stories/1009109 (accessed 1 July 2013).

Bannister, A. , Kiefer, J. and Nellums, J. ( 2013 ), “ College students’ perceptions of and behaviours regarding Facebook advertising: an exploratory study ”, The Catalyst , Vol. 3 No. 1 , pp. 1 - 20 .

Barreto, A.M. ( 2013 ), “ Do users look at banner ads on Facebook ”, Journal of Research in Interactive Marketing , Vol. 7 No. 2 , pp. 119 - 139 .

Belch, G.E. and Belch, M.A. ( 2012 ), Advertising and Promotion: An Integrated Marketing Communication Perspective , 9th ed., McGraw-Hill , New York, NY .

Berndt, A. ( 2007 ), “ Media habits among generation Y consumers ”, Proceedings of the 19th Annual Conference of the Southern African Institute of Management Scientists, Johannesburg, 19-21 September , pp. 3 - 16 .

Bevan-Dye, A.L. , Garnett, A. and de Klerk, N. ( 2012 ), “ Materialism, status consumption and consumer ethnocentrism amongst black generation Y students in South Africa ”, African Journal of Business Management , Vol. 6 No. 16 , pp. 5578 - 5586 .

Bhattacherjee, A. ( 2012 ), Social Science Research: Principles, Methods, and Practices , USF Tampa Bay Open Access Textbooks , Tampa, FL .

Bischoff, W. ( 2012 ), “Mobile advertising now on Facebook in South Africa”, available at: www.bizcommunity.com/Article/196/12/78197.html (accessed 10 April 2014).

Blasco-Arcas, L. , Hernandez-Ortega, B. and Jimenez-Martinez, J. ( 2014 ), “ The online purchase as a context for co-creating experiences. Drivers of and consequences for customer behaviour ”, Internet Research , Vol. 24 No. 3 , pp. 211 - 242 .

Blumberg, B. , Cooper, D.R. and Schindler, P.S. ( 2011 ), Business Research Methods , 3rd ed., McGraw-Hill , London .

Bolton, R.N. , Parasuraman, A. , Hoefnagels, A. , Migchels, N. , Kabadayi, S. , Gruber, T. , Loureiro, Y.K. and Solnet, D. ( 2013 ), “ Understanding Generation Y and their use of social media: a review and research agenda ”, Journal of Service Management , Vol. 24 No. 3 , pp. 245 - 267 .

Burns, A.C. and Bush, F.R. ( 2012 ), Basic Marketing Research , 3rd ed., Pearson Education , Upper Saddle River, NJ .

Carrillat, A.F. , d’Astous, A. and Grégoire, E.M. ( 2014 ), “ Leveraging social media to enhance recruitment effectiveness: a Facebook experiment ”, Internet Research , Vol. 24 No. 4 , pp. 86 - 123 .

Chandra, B. , Goswami, S. and Chouhan, V. ( 2012 ), “ Investigating attitude towards online advertising on social media – an empirical study ”, Management Insight , Vol. 8 No. 1 , pp. 1 - 14 .

Crosman, P. ( 2008 ), “ Attracting young investors – financial firms are embracing mobile technology, Web 2.0 tools and social networking principles to reach Gen X and Gen Y ”, Wall Street and Technology , Vol. 26 , p. 16 .

Denscombe, M. ( 2010 ), The Good Research Guide , 3rd ed., McGraw-Hill , Berkshire .

Digital Fire ( 2012 ), “Social media marketing in Africa”, available at: www.bizcommunity.com/Article/196/16/73947.html (accessed 3 July 2013).

Dotson, M.F. and Hyatt, E.M. ( 2005 ), “ Major influence factors in children’s consumer socialisation ”, Journal of Consumer Marketing , Vol. 22 No. 3 , pp. 35 - 42 .

Du Chenne, S. ( 2011 ), “ High on aspiration, but cynical ”, AdReview , Vol. 28 , April , pp. 48 - 51 .

Du Plooy, G.M. ( 2009 ), Communication research: Techniques, Methods and Applications , Juta , Cape Town .

Dynamic Logic ( 2012 ), “Mobile video bumps up health brand metrics”, available at: www.emarketer.com/Article.aspx?R=1009490 & ecid=a6506033675d47f881651943c21c5ed4 (accessed 4 July 2013).

Edwards, S.M. ( 2011 ), “ A social media mindset ”, Journal of Interactive Advertising , Vol. 12 No. 1 , pp. 1 - 3 .

eMarketer ( 2012 ), “Social media key influencer in multi-exposure purchase path”, available at: www.emarketer.com/Article.aspx?R=1008845 & ecid=a6506033675d47f881651943c21c5ed4 (accessed 4 July 2013).

eMarketer ( 2014a ), “Digital ad spending worldwide to hit $137.53 billion in 2014”, available at: www.emarketer.com/Article/Digital-Ad-Spending-Worldwide-Hit-3613753-Billion-2014/1010736/8 (accessed 7 April 2014).

eMarketer ( 2014b ), “Global B2C ecommerce sales to hit $1.5 trillion this year driven by growth in emerging markets”, available at: www.emarketer.com/Article/Global-B2C-Ecommerce-Sales-Hit-15-Trillion-This-Year-Driven-by-Growth-Emerging-Markets/1010575 (accessed 7 April 2014).

eMarketer ( 2014c ), “Social ad spending per user remains highest in North America”, available at: www.emarketer.com/Article/Social-Ad-Spending-per-User-Remains-Highest-North-America/1010505 (accessed 7 April 2014).

Facebook ( 2014a ), “Company info”, available at: https://newsroom.fb.com/company-info / (accessed 6 August 2014).

Facebook ( 2014b ), “Platform”, available at: https://newsroom.fb.com/Platform (accessed 3 March 2014).

Facebook and ComScore ( 2012 ), “Can Facebook go beyond earned media success?”, available at: www.emarketer.com/Article/Facebook-Go-Beyond-Earned-Media-Success/1009127 (accessed 30 June 2013).

Field, A. ( 2009 ), Discovering Statistics using SPSS , 3rd ed., Sage , London .

George, D. and Mallery, P. ( 2003 ), SPSS for Windows Step by Step: A Simple Guide and Reference , 4th ed., Allyn & Bacon , Boston, MA .

Goldenberg, B. ( 2007 ), “ The rise of the digital client ”, Customer Relationship Management , Vol. 11 , p. 12 .

Greenlight ( 2012 ), “Facebook sponsored advertisements – 44% of people say they would ‘never’ click on them”, available at: www.bizcommunity.com/Article/196/12/75429.html (accessed 10 April 2014).

Ha, H. and Janda, S. ( 2014 ), “ The effect of customized information on online purchase intentions ”, Internet Research , Vol. 24 No. 4 , pp. 124 - 165 .

Hadija, Z. , Barnes, S.B. and Hair, N. ( 2012 ), “ Why we ignore social networking advertising ”, Qualitative Market Research: An International Journal , Vol. 15 No. 1 , pp. 19 - 32 .

Haigh, M.M. , Brubaker, P. and Whiteside, E. ( 2013 ), “ Facebook: examining the information presented and its impact on stakeholders ”, Corporate Communications: An International Journal , Vol. 18 No. 1 , pp. 52 - 69 .

Hair, J.F. , Bush, R.P. and Ortinau, D.J. ( 2009 ), Marketing Research , McGraw Hill/Irwin , New York, NY .

Hamidizadeh, M.R. , Yazdani, N. Tabriz, A.A. and Latifi, M.M. ( 2012 ), “ Designing and validating a systematic model of e-advertising ”, International Journal of Marketing Studies , Vol. 4 No. 2 , pp. 130 - 149 .

Haydam, N. and Mostert, T. ( 2013 ), Marketing Research for Managers , African Paradigms Marketing Facilitators , Cape Town .

He, W. and Zha, S. ( 2014 ), “ Insights into the adoption of social media mashups ”, Internet Research , Vol. 24 No. 2 , pp. 21 - 42 .

Hsu, M. , Chuang, L. and Hsu, C. ( 2014 ), “ Understanding online shopping intention: the roles of four types of trust and their antecedents ”, Internet Research , Vol. 24 No. 3 , pp. 106 - 139 .

Hudson, S. and Hudson, R. ( 2013 ), “ Engaging with consumers using social media: a case study of music festivals ”, International Journal of Event and Festival Management , Vol. 4 No. 3 , pp. 206 - 223 .

Hudson, S. and Thal, K. ( 2013 ), “ The impact of social media on the consumer decision process: implications for tourism marketing ”, Journal of Travel & Tourism Marketing , Vol. 30 Nos 1-2 , pp. 156 - 160 .

Internet World Stats ( 2012 ), “Internet users and population statistics for Africa”, available at: www.internetworldstats.com/stats1.htm (accessed 28 June 2013).

Jalilvand, M.R. and Samiei, N. ( 2012 ), “ The impact of electronic word-of-mouth on a tourism destination choice: testing the theory of planned behaviour (TPB) ”, Internet Research , Vol. 22 No. 5 , pp. 591 - 612 .

Jordaan, Y. , Ehlers, L. and Grove, J.M. ( 2011 ), “ Advertising credibility across media channels: perceptions of generation Y consumers ”, Communicare , Vol. 30 No. 1 , pp. 1 - 20 .

JWT Intelligence ( 2012 ), “Women’s influence on purchase decisions on the rise”, available at: www.emarketer.com/Article.aspx?R=1008807 (accessed 29 June 2013).

Kalampokis, E. , Tambouris, E. and Tarabanis, K. ( 2013 ), “ Understanding the predictive power of social media ”, Internet Research , Vol. 23 No. 5 , pp. 544 - 559 .

Kodjamanis, A. and Angelopoulos, S. ( 2013 ), “ Consumer perception and attitude towards advertising on social networking sites: the case of Facebook ”, Proceedings of International Conference on Communication, Media, Technology and Design, Famagusta, 2-4 May , pp. 53 - 58 .

Kumar, R. ( 2011 ), Research Methodology , Sage , Pretoria .

Lavidge, R.J. and Steiner, G.A. ( 1961 ), “ A model of predictive measurement of advertising effectiveness ”, Journal of Marketing , Vol. 25 No. 6 , pp. 59 - 62 .

Leung, X.Y. , Bai, B. and Stahura, K.A. ( 2015 ), “ The marketing effectiveness of social media in the hotel industry: a comparison of Facebook and Twitter ”, Journal of Hospitality & Tourism Research , Vol. 39 No. 2 , pp. 147 - 169 .

Levin, J. ( 2013 ), “Youth marketing”, available at: www.bizcommunity.com/Article/196/347/88005.html (accessed 2 July 2013).

Lingelbach, D. , Patino, A. and Pitta, D.A. ( 2012 ), “ The emergence of marketing in Millennial new ventures ”, Journal of Consumer Marketing , Vol. 29 No. 2 , pp. 136 - 145 .

McCarthy, J. , Rowley, J. , Ashworth, C.J. and Pioch, E. ( 2014 ), “ Managing brand presence through social media: the case of UK football clubs ”, Internet Research , Vol. 24 No. 2 , pp. 43 - 75 .

Maree, K. ( 2007 ), First Steps in Research , Van Schaik , Pretoria .

Martinez-Lopez, F.J. , Luna, P. and Martinez, F.J. ( 2005 ), “ Online shopping, the standard learning hierarchy, and consumers’ internet expertise ”, Internet Research , Vol. 15 No. 3 , pp. 312 - 334 .

Martins, J.H. , Loubser, M. and Van Wyk, H. ( 1996 ), Marketing Research: A South Africa Approach , Unisa , Pretoria .

Maxwell, J. ( 2013 ), “ Demystifying the online shopper 10 myths of multichannel retailing ”, PWC’s Multichannel Retail Survey , January , pp. 3 - 35 .

Millward Brown ( 2012 ), “Rich display and video ads boost purchase intent”, available at: www.marketingmag.com.au/news/rich-display-and-video-ads-boost-purchase-intent-14282/ #.U85FBBGKBMs (accessed 8 August 2014).

Mir, I.A. ( 2012 ), “ Consumer attitudinal insights about social media advertising: a South Asian perspective ”, The Romanian Economic Journal , Vol. 15 No. 45 , pp. 265 - 288 .

Molnár, G. ( 2011 ), “Social technographics profiles of students at University of Pecs”, master dissertation, University of Pecs, Pécs.

Moore, M. ( 2012 ), “ Interactive media usage among Millennial consumers ”, Journal of Consumer Marketing , Vol. 29 No. 6 , pp. 436 - 444 .

Noble, S.M. , Haytko, D.L. and Phillips, J. ( 2009 ), “ What drives college-age generation Y consumers? ”, Journal of Business Research , Vol. 62 No. 6 , pp. 617 - 628 .

Okazaki, S. and Taylor, R.T. ( 2013 ), “ Social media and international advertising: theoretical challenges and future directions ”, International Marketing Review , Vol. 30 No. 1 , pp. 56 - 71 .

Olivier, D. ( 2007 ), “ South Africa poised to become a loyalty marketing gem ”, Journal of Consumer Marketing , Vol. 24 No. 3 , pp. 180 - 181 .

Orpana, J. and Tera, J. ( 2011 ), “Facebook marketing – what do users think of it?”, bachelor thesis University of Applied Sciences, Turku.

Patino, A. , Pitta, D.A. and Quinones, R. ( 2012 ), “ Social media’s emerging importance in market research ”, Journal of Consumer Marketing , Vol. 29 No. 3 , pp. 233 - 237 .

Patwardhan, P. and Ramaprasad, J. ( 2005 ), “ Rational integrative model of online consumer decision making ”, Journal of Interactive Advertising , Vol. 6 No. 1 , pp. 2 - 13 .

Persuad, C. ( 2013 ), “The effects of interactivity and involvement on users’ attitude toward and perception of brands and purchase intent on Facebook”, master thesis, Louisiana State University, Baton Rouge, LA.

Petzer, D.J. and De Meyer, C.F. ( 2013 ), “ Trials and tribulations: marketing in modern South Africa ”, European Business Review , Vol. 25 No. 4 , pp. 382 - 390 .

Powers, T. , Advincula, D. , Austin, M.S. , Graiko, S. and Snyder, J. ( 2012 ), “ Digital and social media in the purchase decision process ”, Journal of Advertising Research , Vol. 52 No. 4 , pp. 479 - 489 .

Priyanka, S. ( 2013 ), “ A study of online advertising on consumer behaviour ”, International Journal of Engineering and Management Science , Vol 3 No. 4 , pp. 461 - 465 .

Punj, G. ( 2011 ), “ Effect of consumer beliefs on online purchase behaviour: the influence of demographic characteristics and consumption values ”, Journal of Interactive Marketing , Vol 25 No. 3 , pp. 134 - 144 .

Putrevu, S. and Lord, R.K. ( 1994 ), “ Comparative and noncomparative advertising: attitude effects under cognitive and affective involvement conditions ”, Journal of Advertising , Vol. 23 No. 2 , pp. 77 - 90 .

Rau, P.L.P. , Gao, Q. and Ding, Y. ( 2008 ), “ Relationship between the level of intimacy and lurking in online social network services ”, Computers in Human Behaviour , Vol. 24 No. 6 , pp. 2757 - 2770 .

Reuters and Ipsos ( 2012 ), “Can Facebook go beyond earned media success?”, available at: www.emarketer.com/Article/Facebook-Go-Beyond-Earned-Media-Success/1009127 (accessed 1 July 2013).

RichRelevance ( 2013 ), “On Facebook, retailers tackle how best to drive sales”, available at: www.emarketer.com/Article/On-Facebook-Retailers-Tackle-How-Best-Drive-Sales/1009793 (accessed 2 July 2013).

Rodgers, S. and Thorson, E. ( 2000 ), “ The interactive advertising model: how users perceive and process online ads ”, Journal of Interactive Advertising , Vol. 1 No. 1 , pp. 26 - 49 .

Rohm, A. , Kaltcheva, V.D. and Milne, G.R. ( 2013 ), “ A mixed-method approach to examining brand-consumer interactions driven by social media ”, Journal of Research in Interactive Marketing , Vol. 7 No. 4 , pp. 295 - 311 .

Ruane, L. and Wallace, E. ( 2013 ), “ Generation Y females online: insights from brand narratives ”, Qualitative Market Research: An International Journal , Vol. 16 No. 3 , pp. 315 - 335 .

Safko, L. ( 2010 ), The Social Media Bible: Tactics, Tools & Strategies for Business Success , 2nd ed., Wiley , Hoboken, NJ .

Saxena, A. and Khanna, U. ( 2013 ), “ Advertising on social network sites: a structural equation modelling approach ”, Vision , Vol. 17 No. 1 , pp. 17 - 25 .

Schoen, H. , Gayo-Avello, D. , Metaxas, P.T. , Mustafaraj, E. , Strohmaier, M. and Gloor, P. ( 2013 ), “ The power of prediction with social media ”, Internet Research , Vol. 23 No. 5 , pp. 528 - 543 .

Shevel, A. ( 2013 ), “Black Diamonds outshine whites”, available at: www.bdlive.co.za/national/2013/04/28/black-diamonds-outshine-whites (accessed 20 November 2013).

Shopify ( 2014 ), “Facebook is no. 1 for social commerce”, available at: www.emarketer.com/Article/Facebook-No-1-Social-Commerce/1010721 (accessed 7 April 2014).

Shu, W. and Chuang, Y. ( 2011 ), “ The perceived benefits of six-degree-separation social networks ”, Internet Research , Vol. 21 No. 1 , pp. 26 - 45 .

Smith, K.T. ( 2012 ), “ Longitudinal study of digital marketing strategies targeting Millennials ”, Journal of Consumer Marketing , Vol. 29 No. 2 , pp. 86 - 92 .

Smith, S. ( 2013 ), “ Conceptualising and evaluating experiences with brands on Facebook international ”, Journal of Market Research , Vol. 55 No. 3 , pp. 357 - 374 .

Statistics South Africa (SA) ( 2012 ), Census 2011: In Brief, Statistics , Statistics SA , Pretoria .

Stevenson, J. , Bruner, G. and Kumar, A. ( 2000 ), “ Webpage background and viewer attitudes ”, Journal of Advertising Research , Vol. 40 No. 1 , pp. 29 - 34 .

Stokes, R. ( 2013 ), eMarketing: The Essential Guide to Marketing in a Digital World , 5th ed., Quirk Education , Cape Town .

Symphony ( 2013 ), “Digital-first Millennials put a premium on value engagement”, available at: www.emarketer.com/Article/Digital-First-Millennials-Put-Premium-on-Value-Engagement/1009946 (accessed 1 July 2013).

Taylor, D.G. , Lewin, J.E. and Strutton, D. ( 2011 ), “ Friends, fans, and followers: do ads work on social networks ”, Journal of Advertising Research , Vol. 51 No. 1 , pp. 258 - 275 .

Taylor, S.A. and Hunter, G.L. ( 2002 ), “ The impact of loyalty with e-CRM software and e-services ”, International Journal of Service Industry Management , Vol. 13 No. 5 , pp. 452 - 478 .

Tham, A. , Croy, G. and Mair, J. ( 2013 ), “ Social media in destination choice: distinctive electronic word-of-mouth dimensions ”, Journal of Travel & Tourism Marketing , Vol. 30 , pp. 144 - 155 .

Tustin, D.H. , Ligthelm, A.A. , Martins, J.H. and Van Wyk, H. ( 2005 ), Marketing Research in Practice , Unisa , Pretoria .

Van Schalkwyk, D. ( 2012 ), Quantitative Statistics , CPUT , Cape Town .

Vanden Bergh, B.G. , Lee, M. , Quilliam, E.T. and Hove, T. ( 2011 ), “ The multidimensional nature and brand impact of user-generated as parodies in social media ”, Interactive Journal of Advertising , Vol. 30 No. 1 , pp. 103 - 131 .

Wang, Y. and Sun, S. ( 2010 ), “ Assessing beliefs, attitudes, and behavioural responses toward online advertising in three countries ”, International Business Review , Vol. 19 No. 1 , pp. 333 - 344 .

Wolin, L.D. , Korgaonkar, P. and Lund, D. ( 2002 ), “ Beliefs, attitudes and behaviour towards web advertising ”, International Journal of Advertising , Vol. 21 No. 1 , pp. 87 - 113 .

Wronski, M. and Goldstruck, A. ( 2013 ), SA Social Media Landscape , World Wide Worx & Fuseware , Johannesburg .

Wu, S.I. , Wei, P.L. and Chen, J.H. ( 2008 ), “ Influential factors and relational structure of internet banner advertising in the tourism industry ”, Tourism Management , Vol. 29 No. 1 , pp. 221 - 236 .

Yaakop, A. , Anuar, M.M. and Omar, K. ( 2013 ), “ Like it or not: issue of credibility in Facebook advertising ”, Asian Social Science , Vol. 9 No. 3 , pp. 154 - 163 .

Yadav, M.S. , de Valck, K. , Hennig-Thurau, H. , Hoffman, D.L. and Spann, M. ( 2013 ), “ Social commerce: a contingency framework for assessing marketing potential ”, Journal of Interactive Marketing , Vol. 27 No. 4 , pp. 311 - 323 .

Yang, T. ( 2012 ), “ The decision behaviour of Facebook users ”, Journal of Computer Information Systems , Vol. 52 No. 3 , pp. 50 - 59 .

Yoo, C.Y. , Kim, K. and Stout, P.A. ( 2010 ), “ Assessing the effects of animation in online banner advertising: hierarchy effects model ”, Journal of interactive advertising , Vol. 4 No. 2 , pp. 49 - 60 .

Zikmund, W.G. ( 2003 ), Business Research Methods , 7th ed., Thomson South-Western , Oklahoma, OK .

Zikmund, W.G. and Babin, B.J. ( 2007 ), Essentials of Marketing Research , 3rd ed., Thomson , Mason, OH .


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Untying the influence of advertisements on consumers buying behavior and brand loyalty through brand awareness: the moderating role of perceived quality.

\r\nJin Zhao

  • 1 School of Finance, Shanghai Lixin University of Accounting and Finance, Shanghai, China
  • 2 School of Management, Jiangsu University, Zhenjiang, China
  • 3 KUBEAC Department, University of Management and Technology, Sialkot, Pakistan
  • 4 Department of Accounting and Financial Management, University of Portsmouth, Portsmouth, United Kingdom

Consumer buying behavior is an important aspect in every marketing strategy to produce maximum output from the market. This study aims to determine how advertisement affects consumer buying behavior and brand loyalty by considering a mediator between brand awareness and the moderating role of perceived quality. For this purpose, this study targets the rising cosmetics industry. This study used the purposive sampling technique to collect data from 300 respondents with the help of an online survey method via Google doc. The partial least squares structural equation modeling PLS-SEM was applied to verify the hypotheses relationships. The findings have confirmed that advertisements substantially predicted brand awareness, brand loyalty, and consumer buying behavior. Furthermore, brand awareness partially mediated the association of advertisement with brand loyalty and consumer buying behavior. Also, perceived quality is significantly moderated on the association of brand awareness with brand loyalty and consumer buying behavior. Based on such findings, this study has contributed to the literature and provided new insights into the practical implications alongside the future roadmap of the survey.


Fashion Trends is changing rapidly in the international market ( Hur and Cassidy, 2019 ). Consumers are becoming increasingly brand conscious, and they value branded products to express their status symbol ( Turunen and Pöyry, 2019 ). The consumer desires fashion items that are like their culture. Brittian et al. (2013) found that women have a higher desire to use branded products compared to men. Naturally, the human being is always looking for unique and innovative things. Before brand awareness, women used to wear whatever was available to them ( Wei and Lu, 2013 ). Dörnyei (2020) showed that the emotions of having a unique product help the marketers establish market share by providing exceptional brand elements.

Furthermore, Oh et al. (2020) proposed that the word brand is not a new concept in marketing, rather in the modern era, it is a term exclusively used in the fashion industry. Nettelhorst et al. (2020) explained that marketers changed their mentality from what they want to what their customers want. The brand is an important asset for any business in our local setup because it can change people’s buying behavior. It can play a crucial role in enlarging any business ( Choi et al., 2017 ). There is fierce competition among companies to get a large market share. Rehman et al. (2017) demonstrated that it is very difficult for a company to differentiate its product when many competitors have similar attributes to their product. Jung et al. (2020) discussed why people agree to buy clothes at higher prices. The study found that the consumer’s thinking gets modified.

Similarly, Fazal-e-Hasan et al. (2018) showed that brands were considered highly valuable and helpful in building a relationship with customers. Scholz and Smith (2019) argued that a company’s financial aspect emphasizes the brand’s total value and grows successfully to serve the market. In the current globalizing and emerging markets age, business war depends on price and loyalty, attraction, and related matters ( Kim et al., 2019 ). Alalwan (2018) explained that impressive brand awareness attracts the consumer’s attention and insists they purchase again and again, which results in an increase in sales for a company.

Brand loyalty, brand image, psychical quality and top-of-the-mind brand, and brand recall are ways to measure brand awareness ( Sürücü et al., 2019 ). In the past, women did use expensive items, but the word branded was not clear. These expensive cosmetic items are included in luxuries, but no brand name was used ( Çifci et al., 2016 ). Historically, men and women were not involved in brands too much because of price constraints and their mindset. Through the opportunity to avoid it an early age, young and working-class individuals now confront it as brand slaves ( Han et al., 2015 ). They are always in search of unique designs and better quality. Chung et al. (2017) explained that the quality of any product is judged by price, which is the main reason for satisfaction and dissatisfaction. Before customers buy any brand, they do a lot of research.

Akrout and Nagy (2018) described quality as a key aspect in achieving a company’s wants and business success to grab a place in the global market. Priya et al. (2010) demonstrated that women are the most exclusive consumer for their direct purchase of 80% of total product sold. All types of consumers are highly affected by television advertisements. Nam et al. (2017) discussed how to search for information about brands, one requires internal and external data. Kim and Moon (2020) explained that advertisement and experience are a type of internal information. The data collected through the marketplace, peers, and family is external. The advertisement directly influences consumer awareness, which affects customer loyalty and consumer buying behavior, specifically in the fashion industry.

This study examines the functions of advertisement in building company success and its effect on consumers’ buying behavior and brand loyalty. The aim is to know how the brand is perceived, especially the buying behavior of young men and women. To reinstate a product as top-of-the-mind for consumers, organizations from all areas of the world spend huge amounts on advertisement ( Zhao and Yan, 2020 ). Given its effect on the sales and purchasing behavior of the organization, businesses are unable to decide how to make the most of their advertising and advertising communication ( Bagnied et al., 2020 ). Looking into prior studies, most of the researchers have examined the relationship between consumer purchase intention and social media advertisement ( Weismueller et al., 2020 ), personal factors of consumer buying behaviors ( Rehman et al., 2017 ), brand equity, brand association, and brand awareness on customer buying intentions ( Shanahan et al., 2019 ), social media advertising and customer purchase intention ( Alalwan, 2018 ), and brand awareness, image, physical quality, and employee behavior ( Sürücü et al., 2019 ) in the context of Western economies. Few empirical studies have investigated the impact of advertisement, brand awareness, brand loyalty, perceived quality, and consumer buying behavior in the context of developing countries ( Rehman et al., 2017 ; Rahman, 2018 ; Shareef et al., 2019 ). Therefore, to fill this research gap this study is conducted to measure the influence of advertisement on consumer buying behavior and brand loyalty and mediation of brand awareness in this relationship. In addition, it also explores the impact of brand awareness on consumer buying behavior and brand loyalty and the moderation of quality on their relationship. Therefore, this study has proposed the following research questions:

RQ1: What is the influence of advertisement on brand awareness, brand loyalty, and consumer buying behavior?

RQ2: Does brand awareness mediate the relationship between advertisement, brand loyalty, and consumer buying behavior?

RQ3: Does quality moderate the relationship between advertisement, brand loyalty, and consumer buying behavior?

Literature Review and Theoretical Support

Theoretical support.

This study used the theory of reasoned action to support this conceptual model. This theory is proposed by Ajzen (1991) . According to this theory, attitude toward behavior is one of the important predictors of behavioral intention ( Madden et al., 2016 ; Li et al., 2020 ). Attitude is defined as “an internal evaluation of an object such as [a] branded product.” Kaur and Hundal (2017) established that consumer attitude and behavior toward the advertisement affects consumer exposure, attention, and reaction to the individual advertisement through a variety of cognitive and affective processes. In consumer buying behavior research, attitude toward the advertisement, attitude toward brand loyalty, and brand awareness are commonly used constructs for predicting the effectiveness of marketing communications on different media ( Ayanwale et al., 2005 ; Alalwan, 2018 ).


An advertisement is a valuable tool to divert people’s attitudes positively and attract people toward a product ( Shareef et al., 2019 ). Advertisement is a mode of communication marketing through electronic or print media that persuade the customer to continue or adopt some action by paid content ( Cheah et al., 2019 ). According to Sofi et al. (2018) , it is a non-personal way of sharing information related to a product produced by a sponsor with the help of media. Similarly, Ayanwale et al. (2005) proposed that advertising is a paid, non-personal way in which concepts, products or services, ideas, and information are publicized through media (verbal, visual, and te’t) and identified promoter influence behavior. Zhang X. et al. (2020) described that in a company, to meet communication and marketing objectives, mass media plays a vital role and maximum information is provided to the target market about the product. Rehman et al. (2017) purported that the aim of advertising has popularity worldwide. Most companies are spending large amounts of money on advertisement to attract the customer to their products and services. Lichtenthal et al. (2006) summed up that such advertisement is a picture representing the whole story or in written form that the viewer cannot ignore, and it is beneficial for many advertising media.

Fennis and Stroebe (2020) identified that advertising is a promotional marketing strategy to attract people to a product or service. People are in favor of those brands with which they resonate emotionally. The medium can be chosen by your own choice. Some of the mediums are T.V., social media, magazines, and outdoor advertisements.

1. T.V. is the fastest medium of telecommunication for receiving and transmitting multi-colored images and pictures seen by people throughout the world regularly ( Masui et al., 2020 ).

2. Social Media: Most commonly used by the customers, marketers target their customers by posting links on social sites ( Zhou et al., 2021 ).

3. Magazines: Lee and Rim (2017) found that magazine advertisement has a huge impact on customers’ decision-making as the reader is interested in the magazine and forms a relationship with it.

4. Outdoor Advertisement: It includes billboards, posters, broachers, and banners ( Weismueller et al., 2020 ).

Repeated Exposure

Repetition of advertising increases product exposure to increase customer popularity ( Cox and Cox, 2017 ). In previous studies, researchers assessed that the repeating and selection of advertising methods should be in accordance with the product categorization, brand positioning, format, and advertising goals ( Green et al., 2008 ; Montoya and Horton, 2020 ). Prior studies have identified the various impacts of repeated advertising and supporting advertising appeals on brand purchase intention for distinct product classes ( Belanche et al., 2017 ; Wang et al., 2017 ). More exposure to advertising repetition develops a favorable customer mindset. As a consequence, it is more effective to repeat announcements of known goods compared to announcements of new ones ( Yang, 2018 ). Repeating ads enables marketers to inform customers about the goods and familiarize them with an advertised brand, which improves the likelihood of the products being purchased indirectly. Repeated exposure to advertising has a beneficial impact on customers’ purchasing decisions and helps them remember the brand’s goods ( Montoya et al., 2017 ).

Celebrity Endorsement

Advertisers also use celebrity endorsements in their advertisements to sway customer attitudes ( Gilal et al., 2020 ). Celebrities are people who are well-known among the general public for reasons other than their support of certain brands or goods ( Schimmelpfennig and Hunt, 2020 ). Advertisers’ employment of celebrity has a great impact on consumers’ attitudes about advertising ( Osei-Frimpong et al., 2019 ). Only when a well-known celebrity is supporting an advertisement will people buy the goods, regardless of whether or not they know anything about them. Popular celebrity endorsement affects buying intention more than unknown celebrity endorsement ( Yang, 2018 ). According to the experts who conducted the experiments cited above, celebrity endorsements have a favorable effect on customers’ purchasing intentions ( Zhang X. et al., 2020 ).

Sexual Appeals

Marketers’ goal was to make the commercial more glamorous and enticing to persuade customers to buy the goods by pushing its picture in their minds ( Wirtz et al., 2017 ). As a result, customers are more likely to buy the goods because of the advertisement’s sexual attractions. When words alone are not doing the job, sex appeal is often utilized in commercials to draw customers’ intention ( Black and Morton, 2015 ). Sexual appeal in advertising has a greater impact on women’s purchasing decisions and self-esteem. Using sexually explicit advertising reduces customers’ desire for product knowledge while increasing efficiency by influencing their purchasing decisions ( Gong and Shurtliff, 2020 ). The advertisements featuring attractive models attracted customers of the opposite sex and impacted their purchasing decisions ( Ekici et al., 2020 ). More and more image-based advertisements include sexual themes, and cosmetic product advertising is a good place for testing the impact of these themes on consumer advertising attitudes ( Vargas-Bianchi and Mensa, 2020 ).

Consumer Buying Behavior

Consumer behavior involves making a purchase decision based on available resources, i.e., effort, money, and time ( Chiang et al., 2016 ). Furthermore, Tsao et al. (2019) proposed a holistic view of consumer buying behavior. Consumer behaviors are those activities and processes in which individuals choose and utilize ideas, products, services, and experiences. Li et al. (2021) stated that consumer behavior analysis is another tool to examine the complexity of marketing operations. Meanwhile, Sumi and Kabir (2018) demonstrated that today’s consumers are kept in the dark about when and what they desire, all of which results in interactive advertising. Consumer behavior is a mixture of consuming and purchasing products and services ( Sundararaj and Rejeesh, 2021 ). Therefore, Anetoh et al. (2020) explored seven steps of consumer buying decision which needs recognition: search for information, pre-purchase, evaluation, purchase, consumption, post-consumption evaluation, and divestment.

Brand Loyalty

Brand loyalty describes a client’s connection with a brand ( Coelho et al., 2018 ). Brand loyalty is the tendency to be loyal to a brand, and loyalty demonstrates the consumer’s buying intention ( Atulkar, 2020 ). Additionally, Zhang X. et al. (2020) stated that a loyal consumer characterizes a basis for a price premium, a barrier to entry, protection against deleterious price accomplishment, and responding to competitors. The basic dimension of brand equity is brand loyalty. Similarly, the objective of brand management is brand loyalty. If the company needs to examine the strength and weaknesses of its consumer loyalty, whether the consumer is promoting its product more compared to competitors can be examined ( Coelho et al., 2019 ). Moreover, it is the attitude of the consumer on brand preferences from prior shopping experiences of a product summed up ( Bairrada et al., 2018 ). Furthermore, attitudinal loyalty is the degree of dispositional guarantees for some preferences linked with the brand whereas behavioral loyalty is the repeated buying intention of a consumer ( Diallo et al., 2020 ).

Brand Awareness

Brand awareness plays a significant role in creating consumer buying decisions by bringing three benefits: learning, consideration, and choice ( Foroudi, 2019 ). Sürücü et al. (2019) designate that brand awareness might be known by thickness and deepness. Thickness expresses how easily a brand name will arise in the customer’s mind while purchasing a product. Deepness means how quickly a customer identifies or recalls a brand. Brand awareness will be greater if a product at once possesses both brand thickness and brand deepness; customers will have thought of a definite product when they need to purchase a product ( Romaniuk et al., 2017 ). Furthermore, the brand name is the most vital part. Brand recall and brand recognition are the components of brand awareness. Brand recall means the customer can recall a brand name accurately when they see a product, and brand recognition means the capability of a customer to detect a brand whenever there is a brand sign ( Cheung et al., 2019 ). Brand awareness is a customer’s capability to recall or memorize brand information ( Romaniuk et al., 2017 ). Any product or service variation in the buying behavior is due to brand awareness related to any good or service.

Perceived Quality

This quality is possessed by an entity capable of specific or indirect desires ( Yang et al., 2019 ). Among handlers, it is the indication of the assured attributes in a product that create pleasure or frustration ( García-Fernández et al., 2018 ). Konuk (2018) express the quality of a product based on the foundation of performance, strength, consistency, advantages, and technology. It is based on consumers’ judgment and experience. Wang et al. (2020) explain the close link between product and service quality, company profitability, and customer gratification. The assessment of the benefits and strength of the client is service product quality. The chief aim of a lot of investigators is perceived quality ( Chi et al., 2020 ). Pooya et al. (2020) determine that perceived quality describes the buyer’s individual quality decisions about a brand’s whole fineness or advantage. The important element of consumers’ preferences and attitudes is the perceived quality, which is a significant issue in defining affective commitment.

Hypotheses Development

Advertisement and consumer buying behavior.

Advertisement is a source that convinces people to purchase the product at least once in their lives. Celebrities or personas used in ads may positively influence peoples’ buying intention ( Shanahan et al., 2019 ). Consumer buying behavior should be referred to as the choice to buy a product ( Sundararaj and Rejeesh, 2021 ). Advertisers are adapting different techniques to create purchase decisions through effective commercial messages. Additionally, market advertisers use celebrities in commercials to sponsor their product image ( Alalwan, 2018 ). The involvement of celebrities affects the buying intention of the consumer. This study shows that advertisements have a positive effect on consumer buying intention.

Consequently, Vargas-Bianchi and Mensa (2020) remarked that advertisement has a crucial role in the current age as it is an instrument to build society’s behavior regarding products. Ads help people to get information and make a purchasing decision. People’s psychological, emotional, and behavioral aspects are important while making a purchasing decision ( Wirtz et al., 2017 ). Consumer buying behavior can be predicted by relevant brand awareness in the market ( Alalwan, 2018 ). In conclusion, advertisement has a direct relation with consumer buying behavior. If advertisement increases, it will eventually lead toward an increase in buying intention of the consumer. Therefore, the following hypothesis is proposed:

H1: Advertisement substantially predicts consumer buying behavior.

Advertisement and Brand Loyalty

Nowadays, organizations aim to build strong customer relationships rather than provide only products or services to ensure customer loyalty ( Kwon et al., 2020 ). The process of introducing products to customers, making the product known, and selecting the product agreed upon by customers makes customers loyal to a brand ( Balakrishnan et al., 2014 ). Moreover, Ramaseshan and Stein (2014) explained that the degree of commitment when a customer purchases a product of a special brand is named loyalty. Prior researchers enlightened different factors that affect brand loyalty, but this study reveals five factors: easy usage, quality, brand awareness, brand image, and advertisement ( Tidwell et al., 1992 ; Iglesias et al., 2011 ; Hoewe and Hatemi, 2016 ).

Advertisement is one of the essential tools to increase the level of identification. Advertisement is a type of cost. According to Shanahan et al. (2019) it is not a cost if an advertisement lasts for a long period. Besides, every year millions of companies are generating revenue that results in brand loyalty and in making customers loyal to a special brand or firm. Consequently, Casteran et al. (2019) demonstrated that advertisement has a direct impact on brand loyalty. Thus, it is concluded that if advertisement spending is increased, there will be an increase in customer loyalty level. Moreover, the following hypothesis is assumed:

H2: Advertisement substantially predicts brand loyalty.

Advertisement and Brand Awareness

Rahman (2018) has commented that advertisement means attracting potential customers from the market. In contrast, Kanungo and Dutta (1966) have commented that advertisement means communicating with customers. In this regard, it will be essential to state that advertisement means attracting potential and existing customers from the market by creating awareness of the brand, product, or service ( Chang and Chang, 2014 ). Similarly, several prior research studies have stated that brand awareness can be predicted by the active marketing campaign of the brand, such as advertisement and promotional activities ( Wang and Yang, 2010 ; Lee et al., 2017 ). From this perspective, this study proposed the hypothesis:

H3: Advertisement substantially predicts brand awareness.

Brand Awareness as a Mediator

According to Foroudi (2019) , brand awareness is created to sell the product or service to the customer. Sundararaj and Rejeesh (2021) stated that brand awareness is a mandatory element of the overall knowledge system in the mind of the customer - how likely a customer is to recognize the brand under different situations, how frequently the brand name comes into the customer mind, and how much they like the brand. Moreover, Çifci et al. (2016) explored that customer’s ability to remember or recall brand information is called brand awareness. Li et al. (2021) summed up that it supports customers to make the best purchase decision where an exceedingly competitive market exists. Kanungo and Dutta (1966) showed that companies try to better use brand awareness by adapting marketing strategies to create awareness among customers. Cheung et al. (2019) identified that it has two aspects: width and depth. Width represents the outcomes when a customer makes a purchase decision when a brand name comes into their mind, and depth refers to the way customers can recall a brand.

According to Alalwan (2018) , when companies establish a new market or product, their core purpose is to focus on creating awareness among customers to get the best results, as brand awareness creates positive brand loyalty. Coelho et al. (2018) explored that brand loyalty is a customer’s past psychological attachment and affection to any brand. It can be measured by taking note of repeated purchases from the same brand. Moreover, Atulkar (2020) examined that to maintain and create a brand, companies must realize the increasing importance of unaided and aided awareness in customers and develop strategies related to it. Market communication should be made with different concerns on public relations and advertisement. Advertising options like radio, television, and social media create awareness.

Zhang H. et al. (2020) explained that a brand’s purchase intention depends upon searching information, problem arousal, comparing alternatives, post-purchase, and purchase behavior. The purchase intention of the customer consists of how much awareness he/she has about a brand. Marketers popularize products with the help of promotional activities to create awareness. When customers use and become aware of any brand, their personal experience will turn into brand loyalty ( Sürücü et al., 2019 ). That effect in purchasing the product again and again in case of a good experience refers to direct loyalty. Thus, we hypothesize:

H4: Brand awareness substantially mediates between advertisement and consumer buying behavior.

H5: Brand awareness substantially mediates between advertisement and brand loyalty.

Perceived Quality as a Moderator

In this section, this study discusses the modifying aspect of quality on the association of brand awareness and consumer buying behavior. There is an important relationship between brand awareness and perceived quality ( García-Fernández et al., 2018 ). Few researchers have explored the moderating role of perceived quality on the relationship between brand awareness and consumer buying behavior. It is further suggested that when the brand awareness is high, customer quality evaluation is also high ( Yang, 2018 ). In addition, Wang et al. (2020) explored that perceived quality will affect consumer buying intention and that quality will positively influence purchase intention.

Li et al. (2021) assert that a highly well-known brand will have a greater purchase desire than a less well-known brand. Furthermore, prior studies remarked that perceived quality and purchase intention are positively correlated ( Sürücü et al., 2019 ; Yang et al., 2019 ). Thus, there is a direct relationship between brand awareness and quality. Romaniuk et al. (2017) described that brand awareness has a significant and positive relationship with quality. Therefore, previous studies argued that higher awareness results in higher perceived quality ( Sürücü et al., 2019 ; Chi et al., 2020 ). Thus, the following hypothesis is predicted:

H6: Perceived quality substantially moderates the relationship between brand awareness and consumer buying behavior.

In this section, perceived quality has a moderating effect on the relationship between brand awareness and brand loyalty. Konuk (2018) explained that perceived quality is related to emotional value. Zhang H. et al. (2020) explained that the road map to brand loyalty is perceived quality. Moreover, Chang and Chang (2014) describes that brand quality is a limitation to measure brand excellence. Furthermore, Yang et al. (2019) elaborated that different people have different perspectives on the same product; when evaluating a product, their attitudes, values, and experiences are considered. Their attitude toward the product is important to measure quality, and feedback is obtained from people who use the product to assess the brand’s quality. Prior studies show that perceived quality will influence brand loyalty and trust and affect purchase behavior ( Pooya et al., 2020 ). Thus, perceived quality and brand loyalty are significantly and positively correlated, and brand loyalty will increase if the perceived quality is increased.

H7: Perceived quality substantially moderates the relationship between brand awareness and brand loyalty.

Theoretical Model

To identify the impact of advertisement on consumer buying behavior and brand loyalty, as well as the mediating role of brand awareness and moderating influence of quality, we have conceptualized this theoretical model. Figure 1 shows the research model for consumer buying behavior and brand loyalty.


Figure 1. Conceptual model.


The current study aims to determine how advertisement affects consumer buying behavior and brand loyalty by considering a mediating role of brand awareness and the moderating role of perceived quality. This study is quantitative and descriptive. However, this study followed deductive reasoning because the foundations of the study are linked with existing literature. Similarly, this study followed a cross-sectional design to gather data from respondents. A questionnaire survey technique was implemented to attain the online feedback of customer responses by using the purposive sampling technique.

Data Collection Procedure

The target population of the study was consumers of cosmetics brands. Therefore, this study has developed an online questionnaire by using Google docs. The link of the questionnaire has been spread over different social media platforms to gather responses. From this perspective, it can be stated that the present study has followed the purposive sampling method because it allows researchers to request respondents to spread the link to the questionnaire. When the responses of the questionnaire reached 328, the study compiled data in the SPSS file. However, twenty-eight questionnaires consist of empty responses and are considered invalid. Therefore, this study has employed analysis on the valid responses, which are 300 responses with a participation rate of 91%.

All the measures were adapted from earlier valid and reliable scales (See Appendix here). To measure the items, a 5-point Likert scale (5 demonstrating “strongly agree,” 4 signifying “agree,” 3 signifying “neutral,” 2 signifying “disagree,” and 1 demonstrating “strongly disagree”) was used.

The brand advertisement was measured using three dimensions, namely repeated exposure, celebrity endorsement, and sex appeal, adapted from the study of Kaur and Hundal (2017) . Each item has three measurement constructs. A sample item for repeated exposure is “repetition makes me remember the ad.” A sample item for celebrity endorsement is “products endorsed increases the loyalty of the customers.” A sample item for sexual appeal “sex appeal make the ad more attractive and attention-seeking.”

Brand awareness was assessed using a five-item scale adapted from the study of Sasmita and Mohd Suki (2015) . This scale was tested and validated by prior researchers ( Foroudi, 2019 ). A sample item is “I know how this particular product/brand looks.”

Brand loyalty was measured using a three items scale and adapted from the study of Sürücü et al. (2019) . This scale was widely accepted and used by previous researchers in the field of marketing ( Zhang S. et al., 2020 ). A sample item is “this brand would be my first choice.”

To measure consumer buying behavior, we adapted four items scale from the study of Sürücü et al. (2019) . This scale was tested and verified by existing studies ( Li et al., 2021 ). A sample item is “I mostly buy luxury brand goods for myself.”

Perceived quality was measured using a five items scale and adapted from the study of Shanahan et al. (2019) . A sample item is “this brand is of high quality.”

Profile of the Respondents

Table 1 show that most respondents were among the age group of 20–25, with a percentage of 79.3%. A further 13.7%, 4.7%, 1%, and 1% were from the age groups of 20–25, 26–30, 31–35, 36–40, and 40+, respectively. Regarding education, 1.3, 11, 51, 23.3, and 13.3% of respondents belonged to matric, intermediate, bachelors, masters, and MS/M.Phil., respectively. Likewise, 19.3, 4.3, 73, and 3.3% of respondents reported themselves as employed, unemployed, student, and others, respectively. Additionally, 16.3% were married, and 83.7%were unmarried. Similarly, 9% of respondents were users of MAC and 5.7, 19.3, 3, 7.7, 33.7, and 21.7% of respondents were users of Etude, L’OERAL, Avon, and Nivea, Dove, and others, respectively.


Table 1. Demographic information.

Measurement Model

The measurement model was analyzed through reliability and validity. Construct reliability was assessed using Cronbach’s alpha and composite reliability. Table 2 shows the values of Cronbach’s alpha and composite reliability for advertisement (0.888, 0.910), brand awareness (0.926, 0.945), consumer buying behavior (0.895, 0.927), brand loyalty (0.902, 0.939), and perceived quality (0.932, 0.949). According to Hair et al. (2014) , the values of Cronbach’s alpha should be >0.70 and the values of composite reliability should be >0.80. Therefore, the values of Cronbach’s alpha and composite reliability were acceptable and above the threshold value ( Sarstedt and Cheah, 2019 ). Moreover, construct validity was analyzed using average variance extracted AVE. The values of AVE were presented in Table 2 . The values of AVE for advertisement were (0.530), brand awareness (0.774), consumer buying behavior (0.761), brand loyalty (0.837), and perceived quality (0.787). Thus, all the values of validity fall within the range of the threshold value of 0.50 suggested by Sarstedt et al. (2011) . Furthermore, to check the multicollinearity issue, variance inflation test VIF was performed. The values of VIF were also shown in Table 2 . According to Hair et al. (2014) , the values of VIF must be lower than 5. Hence, the entire construct’s VIF were under the threshold value and there is no issue of multicollinearity in the data.


Table 2. Measurement model.

Discriminant Validity

Discriminant validity test was assessed using both criteria’s Fornell and Larcker (2018a) and Heterotrait-Monotrait HTMT ratio. The findings were shown in Tables 3 , 4 . As per criteria ( Fornell and Larcker, 2018b ), the square root of the AVE is called discriminant validity and must be higher than correlations values. Moreover, the values of the HTMT ratio should be less than 0.85. Thus, it is seen that the maximum achieved HTMT value was 0.599, and below the threshold value as suggested by Sarstedt et al. (2011) . Thus, all the measurement constructs were acceptable for structural model analysis.


Table 3. Fornell-Larcker criterion.


Table 4. Heterotrait-Monotrait ratio (HTMT) criterion.

Structural Model

The structural model was analyzed through Smart-PLS software and partial least squares structural equation modeling technique PLS-SEM was performed using the bootstrap method with 5000 sub-samples. This software was widely used and accepted in the field of management and social sciences studies ( Vinzi et al., 2010 ; Hair et al., 2014 ; Sarstedt et al., 2014a ; Cai et al., 2021 ). The fitness of the structural model was assessed through the standardized root mean square residual SRMR value. According to Sarstedt, Ringle, and Sarstedt et al. (2014b) a good structural model must have <0.080 SRMR value. Therefore, the value of SRMR was 0.070, which indicates an acceptable and adequate level of structural model fitness. Moreover, the structural model was also assessed using the value of the determination coefficient R 2 . As suggested by Chin (2010) , the desired R 2 should be greater than 0.1 or zero. Table 5 and Figure 2 shows that the structural model explained 23.6% variance in brand awareness, 29.9% in consumer buying behavior, and 35.9% in brand loyalty. Consequently, the values of R 2 were acceptable.


Table 5. Strength of model.


Figure 2. Structural model.

Additionally, for the predictive relevance of the model, the cross-validated redundancy measure (blindfolding) Q 2 test was performed. According to Götz et al. (2010) , the value of Q 2 must be >0.1 or zero. Table 6 explains that the values of Q 2 exceeded 0.1 and the positive predictive significance level of the model.


Table 6. Cross-validated redundancy.

Testing of Hypothesis

The results of the hypotheses were presented in Table 7 and Figure 3 . To test hypothesis H1, findings show that advertisement has a positive and significant impact on consumer buying behavior (β = 0.407, C.R = 9.216, p < 0.000). It means that if there is a more attractive advertisement about the brand, it will ultimately increase customers’ buying behavior. Therefore, H1 was accepted. Moreover, H2 results illustrate that advertisement has a positive and significant influence on brand loyalty (β = 0.420, C.R = 9.770, p < 0.000). Increased advertisement creates more brand loyalty among customers to satisfy their needs. Hence, H2 was supported. Moreover, H3 results indicate that advertisement has a positive and significant impact on brand awareness (β = 0.486, C.R = 11.085, p < 0.000). Hence, H3 was accepted. Furthermore, findings show that brand awareness has a positive and significant impact on consumer buying behavior (β = 0.087, C.R = 1.772, p < 0.047) and brand loyalty (β = 0.204, C.R = 4.333, p < 0.000). Additionally, this study also hypothesized that brand awareness plays a mediating role (indirect effect) on the relationship between advertisement, consumer buying behavior, and brand loyalty. The H4 findings illustrate that brand awareness positively and significantly mediates the relationship between advertisement and consumer buying behavior (β = 0.042, C.R = 1.723, p < 0.046). Therefore, H4 was accepted. Moreover, H5 results show that brand awareness positively and significantly mediates the relationship between advertisement and brand loyalty (β = 0.099, C.R = 3.801, p < 0.000). Thus, H5 was also supported.


Table 7. Structural model path coefficients.


Figure 3. Bootstrapping.

Moderation Analysis

To assess the moderating role of perceived quality in the relationship between brand awareness and consumer buying behavior, Table 8 results show that perceived quality has a positive influence on consumer buying behavior (β = 0.268, C.R = 6.046, p < 0.000) and also positively moderates the relationship between brand awareness and consumer buying behavior (β = 0.151, C.R = 3.386, p < 0.001). So, H6 was accepted. Meanwhile, H7 findings indicate that perceived quality has a significant impact on brand loyalty (β = 0.239, C.R = 4.867, p < 0.000) and significantly moderates the relationship between brand awareness and brand loyalty (β = 0.107, C.R = 3.298, p < 0.001). Thus, H7 was also supported.


Table 8. Moderation analysis.

This study aims to determine how advertisement affects consumer buying behavior and brand loyalty by considering a mediator between brand awareness and the moderating role of perceived quality. The study’s findings have revealed that advertising substantially predicted consumer behavior while brand loyalty mediated it, and perceived quality is moderated on their association. This study has confirmed that buying behavior is substantially predicted by advertisement and brand awareness. Similarly, Foroudi (2019) has confirmed that brand awareness is created by significant marketing campaigns of the companies, such as advertisements. It is also confirmed by the present study that advertisements are substantially linked to brand awareness in the cosmetics branding context. Furthermore, this study has also confirmed that brand awareness is significantly linked with consumer buying behavior. In this regard, Romaniuk et al. (2017) has commented that consumers create variation in their buying pattern due to significant brand awareness. However, several prior research studies have demonstrated that brand awareness attracts consumers toward the product or service and increases potential customers ( Kim et al., 2019 ; Shanahan et al., 2019 ). From this perspective, this study has concluded that brand awareness created by advertisements influences the buying behavior of cosmetics consumers.

Sofi et al. (2018) stated that advertisement substantially predicts consumer buying behavior, while such an association becomes stronger when advertisement actively produced positive outcomes. In the same sense, this study has proved the mediation effect of brand awareness between advertisement and consumer buying behavior. It implies that consumer buying behavior increases with an increase in an advertisement while such an increment becomes robust when brand association plays an active role. In contrast, this study has also confirmed the mediation effect of brand awareness between the association of advertisement and brand loyalty. In this regard, several prior research studies have stated that consumers become more loyal toward the brand when brand awareness substantially works ( Sasmita and Mohd Suki, 2015 ; Sürücü et al., 2019 ). Therefore, this study has concluded that consumers become more loyal and demonstrate constructive buying behavior because of the advertisement, and such association becomes robust based on brand awareness.

Furthermore, this study has found that perceived quality moderated the relationship between brand awareness, brand loyalty, and consumer buying behavior. In this regard, several prior research studies have stated that perceived quality attracts potential consumers from the market, and consequently, the company’s growth increases ( Akrout and Nagy, 2018 ; García-Fernández et al., 2018 ). However, this study has tested moderation of perceived quality which is statistically supported by the findings. Therefore, it is concluded that brand awareness increases loyalty and buying patterns and that when perceived quality is offered, brand awareness substantially predicts consumer buying behavior and brand loyalty.

Theoretical and Practical Implications

This study has contributed to the literature by evaluating the moderation effect of perceived quality on brand awareness with loyalty and consumer buying behavior. However, Teo et al. (2019) have confirmed that when a brand offers substantial-quality products and increased awareness in the market, it predicts the consumers’ higher purchasing behavior. It implies that perceived quality can be taken as a moderator. Therefore, this study has considered perceived quality as a moderator and tested empirically. Furthermore, the cosmetics industry is a growing industry worldwide and lacks research attention ( Amberg and Fogarassy, 2019 ). Therefore, this study has focused on the cosmetics industry to analyze the theoretical framework of the study. In this regard, this study has contributed to the literature of the cosmetics industry by stating that young people have a higher intention to demonstrate higher buying behavior. Therefore, managers have to focus on marketing campaigns focused on the younger population to produce a higher market share.

The findings of the study have confirmed that consumers preferred branded cosmetics products because they are more sensitive about their social standards. These consequences have important suggestions for international selling directors. With the increase in the quantity of cosmetics brands, brand managers and selling directors must evolve and understand the promotional activities from the Pakistani point of view. Outcomes would lead cosmetics product brand managers to develop policies to progress their branding decisions to gain a more competitive edge and stability of business through loyal customers. Consequences suggested that managers focus on brand awareness to increase consumer loyalty and consumer buying behavior by using promotional activities like advertisements. Teenagers are spending more time on social media sites like Facebook, Instagram, and Twitter, consequently, it will also be helpful for managers to create awareness in the mind of customers through social media. Meanwhile, to increase loyalty and consumer buying behavior, cosmetics product managers should pay more attention to building trust between their consumers by meeting or going beyond their expectations.

Limitation and Future Direction

The study’s findings are generalizable to the entire cosmetics industry, although this study has some limitations, just like other studies. For instance, one limit was due to the responses of the questions, which depended upon the Likert-type scale. Some people do not give a careful response, and others like to give careful answers. It means the presenter influenced the respondent’s reaction. Future research could be carried out in other sectors, including the telecom sector, banking sector, and textile sector, to show the cross-sector investigation of c consumer buying behavior and their outcome on performance, and the data should be collected using a mixed approach. Using this, the result might change. In the future, sample size should also be increased. Different promotional tools can be considered for further study to evaluate consumer behavior concerning perceived quality and brand awareness.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

The studies involving human participants were reviewed and approved by Ethics Committee of the Jiangsu University China. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

RB and MM proposed the research, analyzed the experimental results, and wrote the manuscript. JZ, FM, and AS designed and carried out the revision of this manuscript and extensively edited the manuscript. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Ajzen, I. (1991). The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50, 179–211. doi: 10.1016/0749-5978(91)90020-T

CrossRef Full Text | Google Scholar

Akrout, H., and Nagy, G. (2018). Trust and commitment within a virtual brand community: The mediating role of brand relationship quality. Inf. Manag. 55, 939–955. doi: 10.1016/J.IM.2018.04.009

Alalwan, A. A. (2018). Investigating the impact of social media advertising features on customer purchase intention. Int. J. Inf. Manage. 42, 65–77. doi: 10.1016/J.IJINFOMGT.2018.06.001

Amberg, N., and Fogarassy, C. (2019). Green Consumer Behavior in the Cosmetics Market. Resour 8:137. doi: 10.3390/RESOURCES8030137

Anetoh, J. C., Nnabuko, J. O., Okolo, V. O., and Anetoh, V. C. (2020). Sensory Attributes of Malt Drinks and Consumer Purchase Decisions. J. Food Prod. Market. 26, 317–343. doi: 10.1080/10454446.2020.1767748

Atulkar, S. (2020). Brand trust and brand loyalty in mall shoppers. Mark. Intell. Plan. 38, 559–572. doi: 10.1108/MIP-02-2019-0095

Ayanwale, A. B., Alimi, T., and Ayanbimipe, M. A. (2005). The Influence of Advertising on Consumer Brand Preference. J. Soc. Sci. 10, 9–16. doi: 10.1080/09718923.2005.11892453

Bagnied, M., Speece, M., and Hegazy, I. (2020). Attitudes toward Advertising and Advertising Regulation among College Students in Egypt. J. Int. Consumer Market. 33, 493–511. doi: 10.1080/08961530.2020.1833270

Bairrada, C. M., Coelho, A., and Lizanets, V. (2018). The impact of brand personality on consumer behavior: the role of brand love. J. Fash. Mark. Manag. An Int. J. 23, 30–47. doi: 10.1108/JFMM-07-2018-0091

Balakrishnan, B. K. P. D., Dahnil, M. I., and Yi, W. J. (2014). The Impact of Social Media Marketing Medium toward Purchase Intention and Brand Loyalty among Generation Y. Proc. Soc. Behav. Sci. 148, 177–185. doi: 10.1016/J.SBSPRO.2014.07.032

Belanche, D., Flavián, C., and Pérez-Rueda, A. (2017). User adaptation to interactive advertising formats: The effect of previous exposure, habit and time urgency on ad skipping behaviors. Telemat. Informat. 34, 961–972. doi: 10.1016/J.TELE.2017.04.006

Black, I. R., and Morton, P. (2015). Appealing to men and women using sexual appeals in advertising: In the battle of the sexes, is a truce possible? J. Market. Commun. 23, 331–350. doi: 10.1080/13527266.2015.1015108

Brittian, A. S., Toomey, R. B., Gonzales, N. A., and Dumka, L. E. (2013). Perceived Discrimination, Coping Strategies, and Mexican Origin Adolescents’ Internalizing and Externalizing Behaviors: Examining the Moderating Role of Gender and Cultural Orientation. Appl. Dev. Sci. 17, 4–19. doi: 10.1080/10888691.2013.748417

PubMed Abstract | CrossRef Full Text | Google Scholar

Cai, L., Murad, M., Ashraf, S. F., and Naz, S. (2021). Impact of dark tetrad personality traits on nascent entrepreneurial behavior: the mediating role of entrepreneurial intention. Front. Bus. Res. China 151:1–19. doi: 10.1186/S11782-021-00103-Y

Casteran, G., Chrysochou, P., and Meyer-Waarden, L. (2019). Brand loyalty evolution and the impact of category characteristics. Mark. Lett. 301, 57–73. doi: 10.1007/S11002-019-09484-W

Chang, W. Y., and Chang, I. Y. (2014). The Influences of Humorous Advertising on Brand Popularity and Advertising Effects in the Tourism Industry. Sustain 6, 9205–9217. doi: 10.3390/SU6129205

Cheah, J. H., Ting, H., Cham, T. H., and Memon, M. A. (2019). The effect of selfie promotion and celebrity endorsed advertisement on decision-making processes: A model comparison. Internet Res. 29, 552–577. doi: 10.1108/INTR-12-2017-0530

Cheung, M. L., Pires, G. D., and Rosenberger, P. J. (2019). Developing a conceptual model for examining social media marketing effects on brand awareness and brand image. Int. J. Econ. Bus. Res. 17, 243–261. doi: 10.1504/IJEBR.2019.098874

Chi, X., Lee, S. K., Ahn, Y., and Kiatkawsin, K. (2020). Tourist-Perceived Quality and Loyalty Intentions towards Rural Tourism in China. Sustain 12:3614. doi: 10.3390/SU12093614

Chiang, K.-P., Chan, A., and Milan, R. (2016). Social marketing and advertising appeals: On perception and intention to purchase condoms among college students. Int. J. Healthc. Manage. 11, 71–78. doi: 10.1080/20479700.2016.1266149

Chin, W. W. (2010). Bootstrap Cross-Validation Indices for PLS Path Model Assessment. Handb. Partial Least Squares 2010, 83–97. doi: 10.1007/978-3-540-32827-8_4

Choi, M., Park, M., Lee, H.-S., and Hwang, S. (2017). Dynamic modeling for apartment brand management in the housing market. Vilnius Gedim. Tech. Univ. 21, 357–370. doi: 10.3846/1648715X.2017.1315347

Chung, N., Song, H. G., and Lee, H. (2017). Consumers’ impulsive buying behavior of restaurant products in social commerce. Int. J. Contemp. Hosp. Manag. 29, 709–731. doi: 10.1108/IJCHM-10-2015-0608

Çifci, S., Ekinci, Y., Whyatt, G., Japutra, A., Molinillo, S., and Siala, H. (2016). A cross validation of Consumer-Based Brand Equity models: Driving customer equity in retail brands. J. Bus. Res. 69, 3740–3747.

Google Scholar

Coelho, A., Bairrada, C., and Peres, F. (2019). Brand communities’ relational outcomes, through brand love. J. Prod. Brand Manag. 28, 154–165. doi: 10.1108/JPBM-09-2017-1593

Coelho, P. S., Rita, P., and Santos, Z. R. (2018). On the relationship between consumer-brand identification, brand community, and brand loyalty. J. Retail. Consum. Serv. 43, 101–110. doi: 10.1016/J.JRETCONSER.2018.03.011

Cox, D., and Cox, A. D. (2017). Beyond First Impressions: The Effects of Repeated Exposure on Consumer Liking of Visually Complex and Simple Product Designs. J. Acad. Market. Sci. 30, 119–130. doi: 10.1177/03079459994371

Diallo, M. F., Moulins, J. L., and Roux, E. (2020). Unpacking brand loyalty in retailing: a three-dimensional approach to customer–brand relationships. Int. J. Retail Distrib. Manag. 49, 204–222. doi: 10.1108/IJRDM-03-2020-0115

Dörnyei, K. R. (2020). Limited edition packaging: objectives, implementations and related marketing mix decisions of a scarcity product tactic. J. Consum. Mark. 37, 617–627. doi: 10.1108/JCM-03-2019-3105

Ekici, N., Erdogan, B. Z., and Basil, M. (2020). The Third-Person Perception of Sex Appeals in Hedonic and Utilitarian Product Ads. J. Int. Consumer Market. 32, 336–351. doi: 10.1080/08961530.2020.1712294

Fazal-e-Hasan, S. M., Ahmadi, H., Mortimer, G., Grimmer, M., and Kelly, L. (2018). Examining the role of consumer hope in explaining the impact of perceived brand value on customer–brand relationship outcomes in an online retailing environment. J. Retail. Consum. Serv. 41, 101–111. doi: 10.1016/J.JRETCONSER.2017.12.004

Fennis, B. M., and Stroebe, W. (2020). The Psychology of Advertising. Psychol. Advert. 2020:9780429326981. doi: 10.4324/9780429326981

Fornell, C., and Larcker, D. F. (2018a). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. J. Market. Res. 18, 39–50. doi: 10.1177/002224378101800104

Fornell, C., and Larcker, D. F. (2018b). Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics. J. Market. Res. 18, 382–388. doi: 10.1177/002224378101800313

Foroudi, P. (2019). Influence of brand signature, brand awareness, brand attitude, brand reputation on hotel industry’s brand performance. Int. J. Hosp. Manag. 76, 271–285. doi: 10.1016/J.IJHM.2018.05.016

García-Fernández, J., Gálvez-Ruíz, P., Fernández-Gavira, J., Vélez-Colón, L., Pitts, B., and Bernal-García, A. (2018). The effects of service convenience and perceived quality on perceived value, satisfaction and loyalty in low-cost fitness centers. Sport Manag. Rev. 21, 250–262. doi: 10.1016/J.SMR.2017.07.003

Gilal, F. G., Paul, J., Gilal, N. G., and Gilal, R. G. (2020). Celebrity endorsement and brand passion among air travelers: Theory and evidence. Int. J. Hosp. Manag. 85:102347. doi: 10.1016/J.IJHM.2019.102347

Gong, Z. H., and Shurtliff, A. (2020). Effectiveness of Sexual Appeals in Print Advertisements?: A Dynamic Human-Centric Perspective. Innov. Advert. Brand. Commun. 2020, 117–135. doi: 10.4324/9781003009276-8

Götz, O., Liehr-Gobbers, K., and Krafft, M. (2010). Evaluation of Structural Equation Models Using the Partial Least Squares (PLS) Approach. Handb. Partial Least Squares 2010, 691–711. doi: 10.1007/978-3-540-32827-8_30

Green, M. C., Kass, S., Carrey, J., Herzig, B., Feeney, R., and Sabini, J. (2008). Transportation Across Media: Repeated Exposure to Print and Film. Media Psychol. 11, 512–539. doi: 10.1080/15213260802492000

Hair, J. F., Sarstedt, M., Hopkins, L., and Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. Eur. Bus. Rev. 26, 106–121. doi: 10.1108/EBR-10-2013-0128

Han, S. H., Nguyen, B., and Lee, T. J. (2015). Consumer-based chain restaurant brand equity, brand reputation, and brand trust. Int. J. Hosp. Manag. 50, 84–93.

Hoewe, J., and Hatemi, P. K. (2016). Brand Loyalty Is Influenced by the Activation of Political Orientations. Media Psychol. 20, 428–449. doi: 10.1080/15213269.2016.1202839

Hur, E., and Cassidy, T. (2019). Perceptions and attitudes towards sustainable fashion design: challenges and opportunities for implementing sustainability in fashion. Int. J. Fashion Design Technol. Educat. 12:1572789. doi: 10.1080/17543266.2019.1572789

Iglesias, O., Singh, J. J., and Batista-Foguet, J. M. (2011). The role of brand experience and affective commitment in determining brand loyalty. J. Brand Manag. 188, 570–582. doi: 10.1057/BM.2010.58

Jung, H. J., Choi, Y. J., and Oh, K. W. (2020). Influencing Factors of Chinese Consumers’ Purchase Intention to Sustainable Apparel Products: Exploring Consumer “Attitude–Behavioral Intention” Gap. Sustain 12:1770. doi: 10.3390/SU12051770

Kanungo, R. N., and Dutta, S. (1966). Brand awareness as a function of its meaningfulness, sequential position, and product utility. J. Appl. Psychol. 50, 220–224. doi: 10.1037/H0023340

Kaur, H., and Hundal, B. S. (2017). Impact of advertising strategies on the cognitive and behavioral component of attitude of women consumers. J. Asia Bus. Stud. 11, 413–433. doi: 10.1108/JABS-08-2015-0147

Kim, G., and Moon, I. (2020). Online banner advertisement scheduling for advertising effectiveness. Comput. Ind. Eng. 140:106226. doi: 10.1016/J.CIE.2019.106226

Kim, M.-Y., Moon, S., and Iacobucci, D. (2019). The Influence of Global Brand Distribution on Brand Popularity on Social Media. J. Int. Market. 27, 22–38. doi: 10.1177/1069031X19863307

Konuk, F. A. (2018). The role of store image, perceived quality, trust and perceived value in predicting consumers’ purchase intentions towards organic private label food. J. Retail. Consum. Serv. 43, 304–310. doi: 10.1016/J.JRETCONSER.2018.04.011

Kwon, J. H., Jung, S. H., Choi, H. J., and Kim, J. (2020). Antecedent factors that affect restaurant brand trust and brand loyalty: focusing on US and Korean consumers. J. Prod. Brand Manag. 30, 990–1015. doi: 10.1108/JPBM-02-2020-2763

Lee, E. B., Lee, S. G., and Yang, C. G. (2017). The influences of advertisement attitude and brand attitude on purchase intention of smartphone advertising. Ind. Manag. Data Syst. 117, 1011–1036. doi: 10.1108/IMDS-06-2016-0229

Lee, J., and Rim, H. (2017). Evolution of Corporate Social Responsibility: A Content Analysis of United States Magazine Advertising, 1980–2009. J. Promot. Manage. 24, 555–577. doi: 10.1080/10496491.2017.1380111

Li, C., Murad, M., Shahzad, F., Khan, M. A. S., Ashraf, S. F., and Dogbe, C. S. K. (2020). Entrepreneurial Passion to Entrepreneurial Behavior: Role of Entrepreneurial Alertness, Entrepreneurial Self-Efficacy and Proactive Personality. Front. Psychol. 11:1611. doi: 10.3389/FPSYG.2020.01611/BIBTEX

Li, X., Dahana, W. D., Ye, Q., Peng, L., and Zhou, J. (2021). How does shopping duration evolve and influence buying behavior? The role of marketing and shopping environment. J. Retail. Consum. Serv. 62:102607. doi: 10.1016/J.JRETCONSER.2021.102607

Lichtenthal, J. D., Yadav, V., and Donthu, N. (2006). Outdoor advertising for business markets. Ind. Mark. Manag. 35, 236–247. doi: 10.1016/J.INDMARMAN.2005.02.006

Madden, T. J., Ellen, P. S., and Ajzen, I. (2016). A Comparison of the Theory of Planned Behavior and the Theory of Reasoned Action. Personal. Soc. Psychol. Bull. 18, 3–9. doi: 10.1177/0146167292181001

Masui, K., Okada, G., and Tsumura, N. (2020). [Paper] Measurement of advertisement effect based on multimodal emotional responses considering personality. ITE Trans. Med. Technol. Appl. 8, 49–59. doi: 10.3169/MTA.8.49

Montoya, R. M., and Horton, R. S. (2020). Understanding the attraction process. Soc. Personal. Psychol. Compass 14:e12526. doi: 10.1111/SPC3.12526

Montoya, R. M., Horton, R. S., Vevea, J. L., Citkowicz, M., and Lauber, E. A. (2017). A re-examination of the mere exposure effect: The influence of repeated exposure on recognition, familiarity, and liking. Psychol. Bull. 143, 459–498. doi: 10.1037/BUL0000085

Nam, H., Joshi, Y. V., and Kannan, P. K. (2017). Harvesting Brand Information from Social Tags. J. Market. 81, 88–108. doi: 10.1509/JM.16.0044

Nettelhorst, S., Brannon, L., Rose, A., and Whitaker, W. (2020). Online viewers’ choices over advertisement number and duration. J. Res. Interact. Mark. 14, 215–238. doi: 10.1108/JRIM-07-2019-0110

Oh, T. T., Keller, K. L., Neslin, S. A., Reibstein, D. J., and Lehmann, D. R. (2020). The past, present, and future of brand research. Mark. Lett. 312, 151–162. doi: 10.1007/S11002-020-09524-W

Osei-Frimpong, K., Donkor, G., and Owusu-Frimpong, N. (2019). The Impact of Celebrity Endorsement on Consumer Purchase Intention: An Emerging Market Perspective. J. Market. Theory Pract. 27, 103–121. doi: 10.1080/10696679.2018.1534070

Pooya, A., Abed Khorasani, M., and Gholamian Ghouzhdi, S. (2020). Investigating the effect of perceived quality of self-service banking on customer satisfaction. Int. J. Islam. Middle East. Financ. Manag. 13, 263–280. doi: 10.1108/IMEFM-12-2018-0440

Priya, P., Baisya, R. K., and Sharma, S. (2010). Television advertisements and children’s buying behaviour. Mark. Intell. Plan. 28, 151–169. doi: 10.1108/02634501011029664

Rahman, R. (2018). Building brand awareness: The role of celebrity endorsement in advertisements. J. Glob. Scholars. Market. Sci. 28, 363–384. doi: 10.1080/21639159.2018.1509366

Ramaseshan, B., and Stein, A. (2014). Connecting the dots between brand experience and brand loyalty: The mediating role of brand personality and brand relationships. J. Brand Manag. 217, 664–683. doi: 10.1057/BM.2014.23

Rehman, F., Bin Md Yusoff, R., Bin Mohamed Zabri, S., and Binti Ismail, F. (2017). Determinants of personal factors in influencing the buying behavior of consumers in sales promotion: a case of fashion industry. Young Consum. 18, 408–424. doi: 10.1108/YC-06-2017-00705

Romaniuk, J., Wight, S., and Faulkner, M. (2017). Brand awareness: revisiting an old metric for a new world. J. Prod. Brand Manag. 26, 469–476. doi: 10.1108/JPBM-06-2016-1242

Sarstedt, M., and Cheah, J.-H. (2019). Partial least squares structural equation modeling using SmartPLS: a software review. J. Mark. Anal. 73, 196–202. doi: 10.1057/S41270-019-00058-3

Sarstedt, M., Henseler, J., and Ringle, C. M. (2011). Multigroup Analysis in Partial Least Squares (PLS) Path Modeling: Alternative Methods and Empirical Results. Adv. Int. Mark. 22, 195–218. doi: 10.1108/S1474-797920110000022012

Sarstedt, M., Ringle, C. M., and Hair, J. F. (2014a). PLS-SEM: Looking Back and Moving Forward. Long Range Plann. 47, 132–137. doi: 10.1016/J.LRP.2014.02.008

Sarstedt, M., Ringle, C. M., Smith, D., Reams, R., and Hair, J. F. (2014b). Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers. J. Fam. Bus. Strateg. 5, 105–115. doi: 10.1016/J.JFBS.2014.01.002

Sasmita, J., and Mohd Suki, N. (2015). Young consumers’ insights on brand equity: Effects of brand association, brand loyalty, brand awareness, and brand image. Int. J. Retail Distrib. Manag. 43, 276–292. doi: 10.1108/IJRDM-02-2014-0024

Schimmelpfennig, C., and Hunt, J. B. (2020). Fifty years of celebrity endorser research: Support for a comprehensive celebrity endorsement strategy framework. Psychol. Mark. 37, 488–505. doi: 10.1002/MAR.21315

Scholz, J., and Smith, A. N. (2019). Branding in the age of social media firestorms: how to create brand value by fighting back online. J. Market. Manage. 35, 1100–1134. doi: 10.1080/0267257X.2019.1620839

Shanahan, T., Tran, T. P., and Taylor, E. C. (2019). Getting to know you: Social media personalization as a means of enhancing brand loyalty and perceived quality. J. Retail. Consum. Serv. 47, 57–65. doi: 10.1016/J.JRETCONSER.2018.10.007

Shareef, M. A., Mukerji, B., Dwivedi, Y. K., Rana, N. P., and Islam, R. (2019). Social media marketing: Comparative effect of advertisement sources. J. Retail. Consum. Serv. 46, 58–69. doi: 10.1016/J.JRETCONSER.2017.11.001

Sofi, S. A., Nika, F. A., Shah, M. S., and Zarger, A. S. (2018). Impact of Subliminal Advertising on Consumer Buying Behaviour: An Empirical Study on Young Indian Consumers. Glob. Bus. Rev. 19, 1580–1601. doi: 10.1177/0972150918791378

Sumi, R. S., and Kabir, G. (2018). Factors Affecting the Buying Intention of Organic Tea Consumers of Bangladesh. J. Open Innov. Technol. Mark. Complex. 4:24. doi: 10.3390/JOITMC4030024

Sundararaj, V., and Rejeesh, M. R. (2021). A detailed behavioral analysis on consumer and customer changing behavior with respect to social networking sites. J. Retail. Consum. Serv. 58:102190. doi: 10.1016/J.JRETCONSER.2020.102190

Sürücü, Ö, Öztürk, Y., Okumus, F., and Bilgihan, A. (2019). Brand awareness, image, physical quality and employee behavior as building blocks of customer-based brand equity: Consequences in the hotel context. J. Hosp. Tour. Manag. 40, 114–124. doi: 10.1016/J.JHTM.2019.07.002

Teo, L. X., Leng, H. K., and Phua, Y. X. P. (2019). Marketing on Instagram: social influence and image quality on perception of quality and purchase intention. Int. J. Sports Mark. Spons. 20, 321–332. doi: 10.1108/IJSMS-04-2018-0028

Tidwell, P. M., Horgan, D. D., and Kenny, C. T. (1992). Brand character as a function of brand loyalty. Curr. Psychol. 114, 347–353. doi: 10.1007/BF02686791

Tsao, Y. C., Raj, P. V. R. P., and Yu, V. (2019). Product substitution in different weights and brands considering customer segmentation and panic buying behavior. Ind. Mark. Manag. 77, 209–220. doi: 10.1016/J.INDMARMAN.2018.09.004

Turunen, L. L. M., and Pöyry, E. (2019). Shopping with the resale value in mind: A study on second-hand luxury consumers. Int. J. Consum. Stud. 43, 549–556. doi: 10.1111/IJCS.12539

Vargas-Bianchi, L., and Mensa, M. (2020). Do you remember me? Women sexual objectification in advertising among young consumers. Young Consum. 21, 77–90. doi: 10.1108/YC-04-2019-0994

Vinzi, V. E., Trinchera, L., and Amato, S. (2010). PLS Path Modeling: From Foundations to Recent Developments and Open Issues for Model Assessment and Improvement. Handb. Partial Least Squares 2010, 47–82. doi: 10.1007/978-3-540-32827-8_3

Wang, J., Tao, J., and Chu, M. (2020). Behind the label: Chinese consumers’ trust in food certification and the effect of perceived quality on purchase intention. Food Control 108:106825. doi: 10.1016/J.FOODCONT.2019.106825

Wang, S., Kim, S., and Agrusa, J. (2017). A comparative study of perceptions of destination advertising according to message appeal and endorsement type. Asia Pacific J. Tour. Res. 23, 24–41. doi: 10.1080/10941665.2017.1394336

Wang, X., and Yang, Z. (2010). The Effect of Brand Credibility on Consumers’ Brand Purchase Intention in Emerging Economies: The Moderating Role of Brand Awareness and Brand Image. J. Glob. Market. 23, 177–188. doi: 10.1080/08911762.2010.487419

Wei, P. S., and Lu, H. P. (2013). An examination of the celebrity endorsements and online customer reviews influence female consumers’ shopping behavior. Comput. Human Behav. 29, 193–201. doi: 10.1016/J.CHB.2012.08.005

Weismueller, J., Harrigan, P., Wang, S., and Soutar, G. N. (2020). Influencer Endorsements: How Advertising Disclosure and Source Credibility Affect Consumer Purchase Intention on Social Media. Austral. Market. J. 28, 160–170. doi: 10.1016/J.AUSMJ.2020.03.002

Wirtz, J. G., Sparks, J. V., and Zimbres, T. M. (2017). The effect of exposure to sexual appeals in advertisements on memory, attitude, and purchase intention: a meta-analytic review. Int. J. Advert. 37, 168–198. doi: 10.1080/02650487.2017.1334996

Yang, W. (2018). Star power: the evolution of celebrity endorsement research. Int. J. Contemp. Hosp. Manag. 30, 389–415. doi: 10.1108/IJCHM-09-2016-0543

Yang, Z., Sun, S., Lalwani, A. K., and Janakiraman, N. (2019). How Does Consumers’ Local or Global Identity Influence Price–Perceived Quality Associations? The Role of Perceived Quality Variance. J. Market. 83, 145–162. doi: 10.1177/0022242918825269

Zhang, H., Xu, H., and Gursoy, D. (2020). The effect of celebrity endorsement on destination brand love: A comparison of previous visitors and potential tourists. J. Destin. Mark. Manag. 17:100454. doi: 10.1016/J.JDMM.2020.100454

Zhang, S., Peng, M. Y.-P., Peng, Y., Zhang, Y., Ren, G., and Chen, C.-C. (2020). Expressive Brand Relationship, Brand Love, and Brand Loyalty for Tablet PCs: Building a Sustainable Brand. Front. Psychol. 0:231. doi: 10.3389/FPSYG.2020.00231

Zhang, X., Jeong, E. H., Olson, E. D., and Evans, G. (2020). Investigating the effect of message framing on event attendees’ engagement with advertisement promoting food waste reduction practices. Int. J. Hosp. Manag. 89:102589. doi: 10.1016/J.IJHM.2020.102589

Zhao, J., and Yan, C. (2020). User acceptance of information feed advertising: A hybrid method based on sem and qca. Futur. Internet 12, 1–17. doi: 10.3390/FI12120209

Zhou, S., Barnes, L., McCormick, H., and Blazquez Cano, M. (2021). Social media influencers’ narrative strategies to create eWOM: A theoretical contribution. Int. J. Inf. Manage. 59:102293. doi: 10.1016/J.IJINFOMGT.2020.102293


Keywords : advertisement, brand awareness, brand loyalty, consumer buying behavior, perceived quality

Citation: Zhao J, Butt RS, Murad M, Mirza F and Saleh Al-Faryan MA (2022) Untying the Influence of Advertisements on Consumers Buying Behavior and Brand Loyalty Through Brand Awareness: The Moderating Role of Perceived Quality. Front. Psychol. 12:803348. doi: 10.3389/fpsyg.2021.803348

Received: 27 October 2021; Accepted: 09 December 2021; Published: 27 January 2022.

Reviewed by:

Copyright © 2022 Zhao, Butt, Murad, Mirza and Saleh Al-Faryan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Rehan Sohail Butt, [email protected] ; Majid Murad, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.


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