AN INVESTIGATION OF ONLINE DISPLAY ADVERTISING AND ITS EFFECT ON CONSUMER BEHAVIOURAL RESPONSES IN GHANA

📄 Item Type: Project Material| 📋 55 pages| 📚 1–5 chapters| Amount: ₦5,000

AN INVESTIGATION OF ONLINE DISPLAY ADVERTISING AND ITS EFFECT ON CONSUMER BEHAVIOURAL RESPONSES IN GHANA

📄 Project Material 📋 55 pages 📚 Chapters 1–5 💾 MS-Word & PDF

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AN INVESTIGATION OF ONLINE DISPLAY ADVERTISING AND ITS EFFECT ON CONSUMER BEHAVIOURAL RESPONSES IN GHANA

CHAPTER ONE

INTRODUCTION

1.1 Background of study

Because of its unrivaled reach, targeting, information richness, and interactivity, the internet has earned a special place as a preferred medium of choice in modern advertising since its inception (McCoy et al., 2012; Nihel, 2013; Liu & Mattila, 2017). More importantly, the massive increase in the number of internet users and the amount of time they spend online over the last decade (Souiden et al., 2017) demonstrates the internet's importance and potential as a relevant advertising medium. In 2018, it is estimated that half of the world's population is online (i.e., using the internet) (Internet World Statistics, 2018). As a result, in order to create relevance among, reach out to, connect with, and keep brands in front of their customers and target segments, several firms and businesses have not only established an online presence, but have also shifted the majority of their marketing strategies online and are stepping up their online advertising efforts (Kim, 2018).

As a result, Internet advertising (online advertising) has grown at an exponential rate, challenging the dominance of traditional media like television and print, and has grown to become a significant portion of the total advertising market (Belanche et al., 2017; Liu-Thompkins, 2019). Online advertising, for example, accounted for 41% of global ad spending in 2017, totaling $209 billion (Kafka & Molla 2017). The global market for online advertising, which is dominated by search and display advertising, is expected to reach $265 billion by 2020, according to projections (Companiesandmarkets.com, 2014; IAB, 2016). This thesis' focus is on online display advertising (ODA), which refers to graphical ads of various formats that are hosted on social networking sites, news sites, blogs, and commercial websites, among other places (Chapelle et al., 2014), and that internet users or website visitors see alongside other content. ODA currently accounts for 49.7% of the online advertising market and is expected to reach $222.3 billion by 2022, making it the fastest-growing segment of the industry (eMarketer, 2018). Marketers/advertisers and web publishers are responding by investing heavily in display advertising (Hof, 2013; Fridgeirsdottir & Najafi-Asadolahi, 2018). Because most display ads include mechanisms that allow users to click through, they have a high likelihood of being clicked on. Furthermore, internet-targeting technologies enable businesses to tailor their ODA to customers based on their previous browsing history and personal information, among other factors (Sridhar et al., 2016). All of these are strong indicators of online display advertising's continued growth and relevance in today's market from an industry standpoint.

The growing popularity of online display advertising poses some challenges for marketers and advertisers, the most significant of which is the perception of clutter in advertising. The internet has a high advertising density due to its ubiquitous nature (Ha & McCann, 2008; Goldfarb, 2014). Users are exposed to torrents of ODAs on every visit to the internet, competing for their attention on the medium, causing them to pay selective attention to ads and avoid them (Rejn-Guardia & Martinez-Lopez, 2014). Furthermore, the rapidly changing online advertising landscape, driven by new and evolving technology-enabled features, as well as the consistent emergence of diverse ODA formats ranging from static banners to interactive audio-visual ads (Li & Lo, 2015), makes it difficult for advertisers to decide which formats will produce the best results for their campaigns (de Pelsmacker & Neijens, 2012; Belanche et al., 2017). Because ODAs can both appeal to and irritate consumers depending on a variety of ad-related and consumer-related factors (Brajnik & Gabrielli, 2010; Janssens et al., 2012), marketers and advertisers are battling to stand out from the sea of online advertising to not only capture, but also hold, consumer attention for the purposes of elaborating advertising content, which may translate into increased sales (Kuisma et al., 2010; Nihel, 2013). As a result, there is a growing need to understand consumer reactions and responses to online display advertising in order to provide relevant indicators and actionable knowledge on how businesses can use it to better achieve their marketing objectives.

1.2 Statement of problem

Advertisers are struggling to stand out among the clutter, capture consumer attention, and generate favorable reactions in a saturated media environment where consumers are overwhelmed with advertisements and are gaining more control over their advertising exposure. As a result, there is a growing need for marketers and advertisers to learn which types of advertising work best in online environments (Bright & Daugherty, 2012; Hoban et al., 2015). There has been a steady stream of research on online advertising over the last two decades. The possible antecedents of online display advertising effectiveness, as well as approaches for assessing the efficacy of online display ads, have emerged as a timely focus of academic research aimed at providing insights that may suggest strategic ways to enhance positive online advertising effects while reducing negative outcomes (Martn-Santana & Beerli-Palacio, 2012; Lambrecht & Tucker,).

1.3 Objective of study

The following are primary objectives of this study:

1.     To determine the relationship between online display advertising (ODA) and consumer behavioural responses.

2.     To examine the intervening role of consumer attitude toward online advertising in the relationships between ODA and behavioural responses.

3.     To examine the likely variations in consumer behavioural responses based on the nature of the advertised brand.

1.4 Research question

The following research question guides this study:

1. What is the relationship between online display advertising (ODA) and consumer behavioural responses?

2. What is the intervening role of consumer attitude toward online advertising in the relationships between ODA and behavioural responses?

3. What are the likely variations in consumer behavioural responses based on the nature of the advertised brand?

1.5 Significance of study

This research is useful in a variety of ways, both in terms of practical and theoretical developments. The efficiency of online advertising has been the subject of a long debate in the advertising literature, with recent studies yielding inconclusive results. As a result, several academics have called for more research into the antecedents and measures of online display advertising effectiveness, as well as how to improve user responses to online display ads (Martin-Santana & Beerli-Palacio 2012). (Bleier & Eisenbess, 2015). As a result, the current study is intended to make theoretical and practical contributions, which will be reviewed briefly next. 

1.5 Scope of study

This study focuses on investigating online display advertising and its effect on consumer behavioural responses in Ghana

1.7 Limitation of study

Finance,inadequate materials and time constraint were the challenges the researchers encountered during the course of the study.

1.8 Definition of terms

Online Display Advertising: Online display advertising is a form of online keyword advertising that promotes a brand message visually using text, logos, videos, photographs, or other graphics.

Consumer Behaviour: Consumer behaviour is the study of individuals, groups, or organizations and all the activities associated with the purchase, use and disposal of goods and services, and how the consumer's emotions, attitudes and preferences affect buying behaviour.

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