University of Groningen Faculty of Economics and Business Master of Science in Marketing Management
Master Thesis
The relationship between use of personalization on social media advertising
and purchase intentions: Moderating roles of influencer identification,
credibility and product fit
Author: Paraskevi Georganta
E-mail: p.georganta@student.rug.nl
Student number: S4067142
March 1st, 2021
1
Acknowledgement
One year ago, while I was preparing myself for my new adventure in Groningen, I remember feeling so enthusiastic and motivated for this year. I had never expected that this year was going to be that crazy not only for students, but for the whole world. A lot of things changed throughout this year and we had to change our habits, our way of living, and adapt to a new situation. Apart from the consequences of this situation, I decided to focus on the positive things that happened during this year. Nevertheless, it was a year that will stay in my mind and I will never forget. The most important accomplishment of this year was my decision to come to the Netherlands and study at the University of Groningen. Without any doubt, it was a great learning and life experience which broaden my horizons and gave me important tools, which will be very useful for my future career and life. I am grateful for having the opportunity to be part of the Master’s in Marketing Management and I am very excited for what is next to come.
First and foremost, I would like to express my appreciation for my supervisor Dr. Judith de Groot. Her professionalism, her continuous support, and her critical feedback made this challenging process an authentic learning experience. Where my eyes were seeing obstacles, hers were seeing solutions. I would like to thank my family for their love and support. They were always by my side when I needed it and without them, I could not be able to be here today. To my grandmother, Eftychia, wherever she may be, who could be very happy with her granddaughter’s accomplishments. To my boyfriend, Christos, who was my biggest supporter during this journey and believed in me at times that I did not believe in myself. He was always mentally by my side at times he could not be psychically close. I could never forget my friends, my old and new ones, for always having my back. It is said that friends are the family that we select, and I agree with this. I would like to thank my “old” friends Vaso, Sevi, Kona, Marina, Nela for their long-duration phone calls, video calls, and their patience to bear with me. Last but not least, I would like to express my gratitude for having met my “new” friends Bahar, Laura, Pablo, Zarifa, and Ze in Groningen. Even though we met under conditions of uncertainty, we managed to create deep relationships and we had a lot of moments of joy and happiness to remember. I will cherish all the lovely moments we’ve had throughout the year, and I am looking forward to those that come in the future.
Thank you,
2
Abstract
Over the last years, organizations spend a lot of time and budget on social media context. Companies and marketers have shifted their attention towards advertising on social media intending to design successful strategies, to attract more and more consumers to purchase the advertised products and services. Some of these strategies include the use of personalization and social media influencers. Thus, this study investigated the effect of personalization and social media influencers related to social media advertising that could predict the purchase intention of the consumers. Firstly, the study examined if personalized advertisements lead to higher purchase intentions. Further, the study assessed the interaction effect of social media influencers between personalization and purchase intentions. The findings of the study demonstrated that the use of personalization in advertisements on a social media environment could significantly affect consumers’ intention to buy the advertised product. Finally, this study showed that the interaction between the use of personalization and social media influencers was not significant and the social media influencers proved to not lead to higher purchase intentions. Therefore, marketers and organizations should effectively strategize their advertising on social media by considering the factor of personalization for increasing the buying behavior of the consumers.
3 Index
1.Introduction... 5
2.Literature review ... 8
2.1 The importance of consumer’s purchase intentions ... 8
2.2 The relationship between personalization and purchase intention ... 9
2.3 Social media influencers in the personalization- purchase intention relationship: the moderating roles of identification, credibility, and product-fit ... 10
2.3.2. The role of influencer’s credibility ... 12
2.3.3. The role of influencer’s product-fit ... 13
2.4 Conceptual model ... 14
3. Research Method ... 15
3.1 Participants and sampling strategy ... 15
3.1.1 Excluding criteria ... 16 3.1.2 Sample size ... 16 3.2 Procedure... 17 3.3 Scenario ... 17 3.4 Measures ... 19 3.4.1 Dependent Variable ... 19 3.4.2 Independent Variables ... 19 3.5 Plan of Analysis ... 20 3.5.1 Hypotheses ... 20 4. Results ... 21
4.1 Validity and Reliability ... 21
4.1.1 Personalization ... 23
4.1.2 Source’s Identification ... 23
4.1.3 Source’s Credibility ... 23
4.1.4 Source’s Product-fit ... 24
4.1.5 Purchase Intention ... 24
4.2 Relationship between the use of personalization, social media influencers, and purchase intention ... 24
4.2.1 Hypothesis 1: The more a consumer perceives the advertisement as personalized, the stronger is the intention to purchase a product ... 25
4.2.2 Hypothesis 2: Ad personalization will especially increase purchase intentions the more a consumer is identified with the social media influencer ... 26
4 4.2.4 Ad personalization will especially increase purchase intentions the higher is the
perceived fit between the influencer and the product. ... 27
5
The relationship between use of personalization and purchase intentions on
social media advertising: Moderating roles of influencer identification,
credibility, and product fit
1.Introduction
Online advertising has become an integral part of daily life and is considered such an important tool for consumers, marketers, and companies. On the one hand, consumers have become more resistant to advertising due to the great number of advertisements they are exposed to every day (Fransen et al., 2015). On the other hand, marketers and companies are in pursuit of effective media through which they would interact and communicate with customers. More specifically, due to the rapid development of the internet, marketers are trying to find techniques to target advertising more precisely, for improving the sales performance and satisfy customer needs (Lee et al., 2017). The latest findings show that social media usage is one of the most popular online activities. More specifically, it is estimated that 3.6 billion people are using social media worldwide, a number that is projected to increase to almost 4.41 billion in 2025 (Statista, 2020). Therefore, advertisements on social media have gained great popularity and high amounts of budget are allocated to these mediums (Ashley & Tuten, 2015).
The growth of social media has completely transformed the way people interact, communicate, and engage with each other. Social media compared to more traditional advertising media (email or direct email), have a highly interactive nature, making social media an exclusive environment for marketers to engage with consumers (Tyler et al., 2019). The vast number of social media users depicts the importance of these mediums for consumers. As of July 2020, more than half of all the people on Earth use social media. The latest data show that 3.6 billion people across the planet use social media today, amounting to almost 51 percent of the total global population (Statista, 2020). Accordingly, the number of people who use social media outweighs the number of those who do not use it. The latest numbers indicate that nearly two-thirds (65 percent) of the world's total population now uses social media. As a result, marketers, and businesses can take advantage of social media's opportunities and create content, communicate, deliver, and exchange ideas and offers with their audience.
6 to actually purchase products (Alalwan et al., 2017; Duffett, 2015; Kapoor et al., 2017; Shareef et al., 2017). To start with, social media are considered communication platforms as people share personal information, images, photos, and videos. The post of all this information on social media could influence other users’ opinion or could affect the opinion of other people (Alp & Öğüdücü, 2018). In reality, evidence has shown that social media has the potential to influence consumers' choices by impacting consumers' decisions, as well as the business decisions of managers (Power & Phillips-Wren, 2011). This happens due to the fact that the decision-maker turns to the online community to obtain the information needed (Power & Phillips-Wren, 2011). Through social media, marketers can understand consumers' purchasing behavior and gain insight into how consumers feel the way that they do about certain brands (Rockendorf, 2011). These opportunities allow marketers to communicate with the consumer through marketing messages and maintain the brand's presence in online marketplaces (Evans & McKee, 2010). Indeed, designing social media advertisements in a way that will be done effectively and attractively, is becoming challenging for marketers (Alalwan, 2018). In line with Tuten and Solomon (2017), one of the social media's basic aims is to shape the consumer's decision-making process. It is therefore crucial for marketers to understand how consumers respond to advertising towards social media, and how advertising through social media could help companies motivate customers to purchase products and services advertised in an online environment.
7 as one of the most significant marketing strategies (Adobe Systems Inc., 2014). Over the years, the interest in personalization in online advertising has grown considerably (Boerman et al., 2017). Therefore, the use of personalization in advertisements might shed light on the effectiveness of online advertising.
In the online industry, personalization in advertisements has become more common amongst others because it may increase the effectiveness of the advertisement (Aguirre et al., 2015). Personal data, such as visited websites, read articles, videos watched, click-through responses, and made purchases, are used to create a personalized ad (Boerman et al., 2017). The different types of information used for the level of personalization include age, gender, location (Aguirre et al., 2015), education level (Tucker, 2014), interests (Aguirre et al., 2015; Tucker, 2014), online shopping behavior (Bleier & Eisen beiss, 2015), and search history (Van Doorn & Hoekstra, 2013) of the active users of social media. The effectiveness of online advertisements has been measured in different ways, including click-through intention and behavior, purchase intention and behavior, brand recall, and perceived relevance of the advertisement (Boerman et al., 2017). The present study focuses on consumers’ purchase intentions as a key outcome measure for ad effectiveness.
As the usage of social media advertising is increasing, advertising tools are increasing as well. One of such tools is the use of social media influencers when promoting products or services, which has been coined as influencer marketing. Influencer marketing can be said to be one of the fastest-growing marketing strategies in reaching new consumers with the help of online media (Kadekova & Holiencinova, 2019). Social media influencers are considered important elements in promoting products and services in different areas of business and marketing (Dhanesh & Duthler, 2019). Evidence has shown that advertising through social media influencers could influence consumers’ buying behavior and more specifically the behavior of the desired group that marketers target, instead of targeting the whole population (Lagree et al., 2019). More specifically, social media influencers produce recommendations, by which they build customers’ reliability and purchase intentions. In line with this, companies use social media influencers for proposing or promoting their products or services in order to influence consumers’ purchase intentions. Therefore, social media influencers may be a key general attribute for understanding consumers’ purchase intention.
8 consumers’ purchase intentions, and further on the relationship between personalization and social media influencers on consumer’s purchase intentions. Prior evidence, as mentioned above, has proved the importance of both personalization and influencers on the purchase intention separately, but there is no study that combines the attributes of personalization and social media influencers on the social media environment. Understanding the moderating role of social media influencers on personalization and consumers' purchase intentions will contribute to integrate the growing literature on the effectiveness of ad personalization on social media. More specifically, literature could acknowledge the role of other attributes and their potential influence on the effectiveness of advertising in the social media environment (Aguirre et al., 2015). Furthermore, understanding the relative contribution of the role of influencers and personalization on customers’ purchase intention can provide business, marketers, and advertising companies valuable information regarding the budget allocated to social media advertising. Research on this topic suggests that influencer marketing may improve businesses' financial performance, which uses social media influencers in advertising campaigns (Erdogan et al., 2001). Taking into account the wide increase of personalization and social media influencers in the advertising field, it would be interesting to understand not only how personalization affects consumers' purchase intentions, but also how influencers could strengthen or weaken the relationship between personalization and customers' purchase intentions.
2.Literature review
2.1 The importance of consumer’s purchase intentions
9 Research has shown that consumer’s intention to purchase has a considerable effect on their actual purchase decisions and is an indicator for marketers. Considered that purchase intentions include the likelihood that the consumers will voluntarily buy a certain product, it is one of the most important key predictors for actual purchasing behavior (de Magistris & Gracia, 2008). Companies more and more realize the importance of purchase intention, as it is closely related to the ultimate goal, which is to increase sales and maximize profits (Hosein, 2012). Furthermore, marketing practitioners use purchase intentions as an input for sales and market share forecasts not only for existing but also for new products (Goyal, 2014). Therefore, purchase intentions are a tool that can assist managers in their marketing decisions related to advertising and promotional strategies.
2.2 The relationship between personalization and purchase intention
Personalization has been described as a marketing strategy that is focused on the customer aiming to deliver the right content to the right person at the right time, to maximize direct and future business opportunities (Tam & Ho, 2006). Similarly, other scholars have described personalization as advertising which is customized to each individual's characteristics, interests, and tastes (Hoy & Milne, 2010; Kelly, Kerr, & Drennan, 2010; Sundar & Marathe, 2010).
Personalized advertisements offer marketers the opportunity to target their audience and this is the reason why personalized advertisements have become such a widely used tool. When it comes to the personalization of advertising, marketers take advantage of consumers' data and create offers and promotional strategies tailored to the customers. Such data include information from websites, articles, videos, as well as everything searched for with a search engine (Ham, 2017). Moreover, targeting advertisements enables marketers to customize a company's marketing activities more accurately and responsibly to the individual customers' likings (Camilleri, 2018).
10 buying, website browsing, tastes, and choices which are tested and matched to similar patterns to create consumers' profiles (Wedel & Kannan, 2016).
Regarding personalization in the social media context, several studies have demonstrated that personalized advertisements can have an effect on social media platforms (Taylor, Lewin & Strutton, 2011; Tran, 2017). The study of Li (2016), showed that personalized advertisements lead to a positive impact on consumers likening and also lead to favorable effects. Previous research has found that a personalized advertisement could attract consumers’ attention and increase the chances of buying the advertised product or service (Ansari & Mela, 2003). Based on the above literature the present study hypothesizes that:
H1: The more a consumer perceives the advertisement as personalized, the stronger is the intention to purchase a product.
2.3 Social media influencers in the personalization- purchase intention
relationship: the moderating roles of identification, credibility, and product-fit
Another important aspect of social media advertising is the social media influencers. Social media influencers attract thousands or millions of followers as they share daily content to their platforms (Instagram, YouTube, Tik Tok) and they focus on a specific type of interest (Chapple & Cownie, 2017). More specifically, Instagram is considered to be the most used platform by social media influencers, due to the sense of immediacy that is generated and because of its creation of communities (Casaló et al., 2020). Different definitions have been used over the years to describe social media influencers. Social media influencers are described as "a new type of independent third-party endorser who shapes audience attitudes through blogs, tweets, and the use of other social media" (Freberg et al., 2011). According to De Veirman et al., (2017), social media influencers are opinion leaders because of the communication created between them and the people who follow them.11 significant effect on consumers’ purchase behavior. Prior research proposes that the attributes of influencers could lead to positive purchase intentions and buying behavior from the consumers (Hakimi et al., 2011). Prior evidence has demonstrated that influencers, who own video channels, positively affect consumers’ purchase intentions for products they promote to their videos (Lee & Watkins, 2016). Thus, social media influencers are a valuable asset for ad effectiveness.
Social media influencers are deemed important in relation to the effectiveness of personalization because they enable consumers to identify with a person (Djafarova & Rushworth, 2017), they could be used as a credible source (Ohanian, 1990) and they could be aligned with the product promoted (Kamins, 1990). Although both personalization and social media influencers are considered important factors on social media, there is no evidence regarding the possible effect of both these attributes on the social media environment. The presence of social media influencers on social media platforms might provide an explanation for the (in)effectiveness of personalization on purchase intentions. The following sections will highlight the importance of these three key influencers' attributes (identification, credibility, product-fit) to the personalization- purchase intention relationship.
The Elaboration Likelihood Model (Petty & Cacioppo, 1986) may help to understand the moderating effect of social media influencers on the personalization-purchase intention relationship. This model assumes that when consumers do not have strong pre-existing attitudes about a certain topic, (which happens mostly for not famous products that have been advertised), then consumers have a higher possibility to be persuaded by easily accessible and peripheral cues. Due to the fact that some people rely strongly on the opinion of reference groups, there is a higher possibility to be affected by peripheral routes. Personalization could function as such an external cue that activates heuristic decision making ("The company knows what I like, so they must care for me”), which can also be connected to the self-congruency theory (Sirgy, 1982). By using personalization as a cue to trigger heuristic decision-making in the shape of something related to the self-concept of the individual. Accordingly, the attitudes about how others think and act, as depicted by influencers, might also provide such cues.
12 intentions. We could draw the connection that the use of personalization will most likely result in a higher intention to purchase the product, with the presence of an influencer.
2.3.1. The role of influencer’s identification
Research on influencer marketing has underlined the social media influencer’s identification to play a significant role in the advertising effectiveness (Basil, 1996). Kelman (1961) suggested the three processes of social influence which are compliance, identification, and internalization. The phenomenon of identification exists when an individual adopts an attitude or behavior from another person and more specifically when this attitude or behavior is related to a fulfilling self-defining relationship with that person (Kelman, 1961).
Prior research has shown that when consumers feel that they share specific elements with influencers such as interests, values, or characteristics, then consumers have a higher possibility to adopt influencers’ attitudes and behaviors (Cialdini, 1993; Kelman, 2006). The explanation behind this is that identification derives from the extent to which one individual believes that they have things in common with another individual (Hoffner & Buchanan, 2005). In more detail, influencers could be relatable and approachable, making their audience feel like they have a friendship (Djafarova & Rushworth, 2017). Furthermore, the audience's ability to make comments on posted content and to start a conversation with the influencers enhances the feeling that the influencers have similarities with the followers (Schmidt, 2007). In line with the above statements, Basil (1996) suggested that consumers have a higher chance of accepting products promoted by influencers, who they could identify themselves with, and consequently positively affect advertising effectiveness. Given the fact that personalization results in the proper fit between consumers' preferences and the advertised product (Bleier & Eisenbeiss, 2015), we expect that ad personalization will prompt consumers to be more motivated to buy the product when they can identify themselves with the influencers. Therefore, we expect the following hypothesis to be:
H2: Ad personalization will especially increase purchase intentions the more a consumer is identified with the social media influencer
2.3.2. The role of influencer’s credibility
13 expertise and knowledge to understand the product or service (Ohanian, 1990). More specifically, source credibility is made up of different components consisting of the communicator's trustworthiness, attractiveness, and expertise (Ohanian, 1990). Building on these attributes, prior research has supported that expertise has a positive influence on purchase intention (Till & Busler, 2003). Accordingly, an endorser who is perceived as trustworthy and expert has a higher chance that the message will be accepted by the audience (Metzger, 2003). Additionally, influencers who are perceived as experts tend to be more persuasive (Aaker & Myers, 1987) and capable of affecting consumer purchase intention (Ohanian, 1991). Relatively, influencers who are considered as high in expertise and trustworthiness are perceived as more influential on their followers’ behaviors. In line with these findings, other scholars have stated the influencer’s ability to affect consumers' purchase decisions, as well as they, are considered to be reliable information sources (De Veirman et al., 2017; Djafarova & Rushworth, 2017). Prior research has also supported the attitude that influencers’ characteristics such as expertise and trustworthiness have positive effects on the purchase behavior of the consumers (Lafferty et al., 2002; Lee & Koo, 2015).
Building on the Elaboration Likelihood Model (Petty & Cacioppo, 1986), we stated above that personalization and influencers could function as an external cue that activates heuristic decision making. More specifically, when a personalized advertisement is depicted to the social media user, then there is a possibility that the consumer will rely on the influencer's credibility and therefore be willing to purchase the advertised product. In line with this reasoning, a moderating role of source credibility on the personalization-purchase intention relationship is hypothesized:
H3: Ad personalization will especially increase purchase intentions the more a social influencer is perceived as credible by the consumer.
2.3.3. The role of influencer’s product-fit
14 Furthermore, several studies have stated that in situations when influencers’ expertise matches the product/service promoted, then this will improve the purchase intention of the consumers (Till & Busler, 2000; Fink et al., 2004).
Except for the important role of influencers' product fit on consumers' purchase intentions, it would be meaningful to stress the effect on the personalization-purchase intention relationship. Similarly, with an influencer's credibility, the extent of the influencer's product fit is perceived by the consumers could also act as a cue. Based on this, a consumer will rely on the fit between the personalized product advertised on social media and the influencer, for deciding to buy the product. In line with this reasoning, a moderating role of source product-fit on the personalization-purchase intention relationship is hypothesized:
H4: Ad personalization will especially increase purchase intentions the higher is the perceived fit between the influencer and the product
2.4 Conceptual model
The present study aims to investigate the relationship between personalized advertisements and consumers’ purchase intention, and the moderating role of social media in this relationship. This research seeks to provide a comprehensive understanding of consumers’ purchase intention through personalized advertisements and social media influencers. Social media influencers are assumed to affect the personalization- purchase intention relationship through three specific influencer aspects, that is, identification, credibility, and product-fit. Figure 1 shows the proposed conceptual model and hypotheses.
15
3. Research Method
This study examined if personalized advertisements on social media affect consumers’ purchase intentions and, whether the use of social media influencers can strengthen or weaken this relationship. The research design of the study followed a cross-sectional method. The dependent variable of the study was the consumers' purchase intentions and the independent variable was the perceived personalization towards advertisements. Independent variables were also the influencers' identification, credibility, and product-fit, which were the hypothesized moderators in this relationship.
3.1 Participants and sampling strategy
The target group of this research was Instagram users, therefore those not familiar with the platform were excluded from participating. The reason behind selecting this social advertising medium is because of its popularity. Despite the rapid penetration among consumers and the wide usage of Instagram in marketing, there has been little evidence that examines this advertising medium. Specifically, there is limited research that examines the factors that enhance consumers’ purchase intentions towards Instagram advertising.
Participants for this study were gathered by convenience sampling. Convenience sampling (also known as Haphazard Sampling or Accidental Sampling) is a type of nonprobability or nonrandom sampling. In this sampling strategy, members of the target population meet specific requirements, such as easy accessibility, geographical proximity, availability at a given time (Dörnyei, 2007). One of the advantages of convenience sampling is its affordable price, easiness, and the availability of the subjects (Etikan et al., 2016) and were the main reason for selecting for this study. According to recent findings, people aged 18-34 tend to make purchases online in a higher volume than other age groups (Statista, 2019). Therefore, the majority of the participants were people from this age group. Taking into account that participants were asked to answer questions based on a scenario regarding personalization in advertisements and purchase intention through social media, they seemed to suit the purposes of the current study.
16 online study that was created via the software Qualtrics. All the respondents participated voluntarily in the study and did not get compensation for their participation.
3.1.1 Excluding criteria
In order to conduct the survey properly, two filter questions were asked at the start of the questionnaire. The first filter question asked whether or not the respondent was a user of the social media platform Instagram. If the respondent answered the question with "no" the respondent was directly directed to the end of the questionnaire. Because responses from someone not familiar with Instagram would be not representative and any valid results would not be possible to be drawn. The second filter question pertained was if the participant followed any influencers. If the response given was "no", the respondent was directly directed to the end of the questionnaire. The reason behind this elimination was the fact that participants who were not users of Instagram and did not follow any influencers, would not be aware of this type of advertisement presented on this social medium. If participants that did not know any influencers were allowed to proceed, it would introduce bias into the study. Therefore, the decision was to also exclude these participants in order not to impact the validity of the study. After the respondent answered that they were familiar with the Instagram platform and knew an influencer, they proceeded to the remainder of the questionnaire.
3.1.2 Sample size
To increase the reliability and validity of the outcomes of this study, we wanted to achieve a large number of participants. The number of participants was calculated based on the factor analysis rule of thumb. According to Pedhazur and Schmelkin (1990), 50 participants per factor was considered a minimum number for the study. Therefore, a minimum of 250 respondents was needed as there are five factors within the conceptual model.
17 remaining education lever was all below the 2.0% margin, equivalent to 2 or fewer respondents. Lastly, the majority of the respondents (52.6%) mentioned having an annual income less than €10,000, (27.6%) of them had an annual income between €10,000 and €19,999, (10.7%) of participants choose not to answer this question, while (4.6%) stated to have a salary every year between €20,000 and €29,999. The remaining participants were under a 2% margin.
3.2 Procedure
The survey started by introducing to the participants an informative text regarding the procedure of the survey. More specifically, this introduction message informed participants about the duration of the study and the survey's aim. Moreover, it was clearly stated that participation in the survey was voluntary and the data were treated anonymously. Following, participants were asked some demographic questions such as gender, age, education, ethnicity, and income level. Moreover, participants were asked about the usage of Instagram and whether they followed influencers on their Instagram account. For participants who were not users of Instagram or did not follow any influencers, that was the end of the survey because they could not relate to the study (n=83). For participants who were users of Instagram and were mentioning a follower, the following scenario was depicted in their survey.
3.3 Scenario
The scenario of the survey was inspired by a phenomenon that happens regularly to social media users. This phenomenon takes place when people face promoted advertisements on their social media feed, concerning products or services that they have searched about lately. Loftis, Geiger, and Imhoff (2001), stated that personalization is the company's ability to treat customers individually through messaging, targeted banner ads, or other personal transactions. Based on this definition, the author assumed that the promoted advertisements depicted on users' personal accounts after a conversation for this product or service describe a personalized advertisement. Therefore, this phenomenon is chosen for this study's scenario.
Participants were first asked to imagine that they were talking with their friends and had talked about the desire to buy a white pair of sneakers in the following way:
18 Figure 2 shows the pair of sneakers depicted in the survey. Participants then were asked to imagine that the next day, as they were scrolling down their Instagram account, they see their favorite influencer wearing the same pair of sneakers in the following way:
“The next day, as you are scrolling down your Instagram account, you see your favorite influencer wearing the same pair of sneakers”:
Figure 3 shows the influencer’s advertisement on Instagram. The first picture (figure 2) was shown in order to introduce participants to the product they searched online, while the second picture (figure 3) represented the product posted by a person on the Instagram medium. The two pictures aimed to make participants more engaged in the scenario and help them imagine their favorite influencer wearing the white pair of sneakers.
Figure 2: The pair of white sneakers Figure 3: The influencer’s Instagram post
Next, participants received questions regarding personalization, purchase intentions, and influencers. Finally, participants were asked if they wanted to comment on the scenario and the Instagram post. The study concluded by thanking participants and providing a form of contact if any information as required by participants. The questionnaire is shown in Appendix A.
19 among athletic footwear. More specifically, in a report of the analyst Powell (2020), it was found that the top-selling sneakers of 2019, were white. Based on these findings, the author assumed that the white pair of sneakers will be most suitable for the study.
3.4 Measures
3.4.1 Dependent Variable
The central dependent variable (consumer's purchase intention) was measured on a seven-point Likert-type scale (1=strongly disagree to 7=strongly agree). A 7-point Likert-type was chosen for all the variables because it is suggested that the number of response options should be at least five when constructing items (Maydeu-Olivares et al., 2017). Research also confirms that data from Likert items becomes significantly less accurate when the number of scale points drops below five or above seven. Johns, R. (2010). Moreover, it was found that 7-point scales resulted in stronger correlations with t-test results (Lewis, 1993). Based on the findings of Finstad (2010), seven-point Likert scales appear to be more suited to electronic distribution.
For measuring the dependent variable, four items were adapted from Duffett (2015) which were the following:
I will buy the shoes that are advertised on Instagram.
I desire to buy the shoes that are promoted in advertisements on Instagram.
I am likely to buy the shoes that are promoted on Instagram.
I plan to purchase the shoes that are promoted on Instagram.
3.4.2 Independent Variables
The independent variable personalization of advertisements was measured using three items adapted from Xu (2006) on a 7-point Likert-type scale ranging from 1 “strongly disagree” to 7 “strongly agree” including:
I feel that the Instagram advertisement displays a personalized message to me.
I feel that the Instagram advertisement is designed towards my needs.
The content of the Instagram advertisement is personalized.
20
[Influencer’s name] is the type of person I want to be like myself.
Sometimes I wish I could be more like [influencer’s name].
[Influencer’s name] is someone I would like to emulate.
I would like to do the kind of things [influencer’s name] does.
The moderator influencer’s credibility was assessed by using the trustworthiness and expertise subscales of the credibility scale by Ohanian (1990). Participants were asked to rate the influencer’s trustworthiness on four 7-point semantic differential scales: dishonest –honest, unreliable – reliable, insincere – sincere, and untrustworthy – trustworthy. Moreover, expertise was also measured with five 7-point semantic differential scales: not an expert – expert, inexperienced – experienced, unknowledgeable – knowledgeable, unqualified – qualified, and unskilled – skilled.
Finally, for the assessment of the moderator product-influencer fit, participants were asked to indicate the perceived fit between the presented product and influencer on a 7-point scale ranging from 1 “strongly disagree” to 7 “strongly agree”. The items structured by the author with the aim to combine the fit of the product with the influencer, and where the following:
The advertised pair of shoes is a product that suits [influencer’s name]. [Influencer’s name] is known for promoting these types of products.
The advertised pair of shoes and [influencer's name] seem to be a good match.
3.5 Plan of Analysis
The software that has been used to analyse the data from the questionnaire is SPSS, version 26. The first step of the analysis was to check the data for missing values, outliers. Then, the test is needed in order to test the validity and reliability of the sample and to check whether or not a sum variable may be computed. Factor analysis found that all items loaded to one factor. For the reliability analyses Cronbach's alpha value was above 0.7 (minimum value) and Cronbach's alpha if items deleted only went down for all the variables, meaning that no question should be deleted. Based on this, all items of the variables were computed to new variables. To test the hypotheses of this study, Linear Regression Analyses and model 4 of the PROCESS macro by Hayes (2013) was used in order to perform the moderation analysis.
3.5.1 Hypotheses
21 personalized advertisements, and purchase intention (H1). The moderation effects of a) influencers' identification on the relationship between personalization and purchase intention (H2), b) influencers' credibility on the relationship between personalization and purchase intention (H3), and c) influencers' product-fit on the relationship between personalization and purchase intention (H4) were tested with Hayes Macro, Process model 4. B-values, R2 and R2-change values, F-values, the indirect unstandardized B-values, and their confidence intervals were reported to provide a full picture of effect sizes in relation to the moderating analyses (Preacher & Kelly, 2011).
4. Results
In order to get a better perception of the data, an insight has been gained into the number of participants, means, standard deviations, minimum scores, maximum scores, and correlations among the independent and dependent variables used in this study. The descriptive statistics are shown in table 1.
Table 1. Descriptive Statistics
N Minimum Maximum M SD Gender 196 1.00 2.00 1.57 0.49 Age 196 18.00 53.00 27.11 5.94 Ethnicity 196 1.00 7.00 1.38 1.29 Annual Income 196 1.00 7.00 2.20 1.92 Education 195 1.00 5.00 2.23 0.76 Valid N 196
4.1 Validity and Reliability
22 Table 2. Validity and Factor analysis
Item 1 2 3 4 5
1. Personalization (α = .442)
I feel that the Instagram advertisement displays a personalized message to me.
0.815
I feel that the Instagram advertisement is designed towards my needs.
.0844
The content of the Instagram advertisement is personalized.
0.836
2. Influencer’s Identification (α =.146) [Influencer’s name] is the type of person I want to be like myself.
0.863
Sometimes I wish I could be more like [influencer’s name].
0.886 [Influencer’s name] is someone I would like
to emulate.
0.850
I would like to do the kind of things [influencer’s name] does.
0.771 3. Influencer’s Credibility (α =.001) dishonest –honest 0.815 unreliable – reliable 0.817 insincere – sincere 0.860 untrustworthy – trustworthy 0.833
not an expert – expert 0.789
inexperienced – experienced 0.845
unknowledgeable – knowledgeable 0.833
unqualified – qualified 0.872
unskilled – skilled 0.802
4. Influencer’s Product-Fit (α =.389) The advertised pair of shoes is a product that suits [influencer’s name].
0.805 [Influencer’s name] is known for promoting
these types of products.
0.814
The advertised pair of shoes and [influencer's name] seem to be a good match.
0.893
5. Purchase Intention (α =.067)
I will buy the shoes that are advertised on Instagram.
0.854
I desire to buy the shoes that are promoted in advertisements on Instagram.
0.879
I am likely to buy the shoes that are promoted on Instagram.
0.920
I plan to purchase the shoes that are promoted on Instagram.
0.867
23 Following the factor analysis, the internal consistency is calculated to test reliability. In order to check reliability, Cronbach’s alpha was calculated for all items of each construct. A construct was reliable if the alpha was 0.70 or higher. Table 3 shows an overview of the Cronbach alpha score of each construct. As shown in the table, all scales had an alpha level higher than .7, which concludes a good internal consistency. It shows that showing that the individual scale items measure the constructs good.
4.1.1 Personalization
The personalization consisted of three items introduced and validated by Xu (2006) “I feel that that the Instagram advertisement displays a personalized message to me”, “I feel that the Instagram advertisement is designed towards my needs”, and “The content of the Instagram advertisement is personalized”. The internal consistency for these three items was tested, Cronbach’s alpha returned as 0.77, (Table 3) which is above the minimum value of 0.70 Nunnally (1978) that allows us to combine items into one variable. A new variable “personalization” was computed based on this by adding the three items and then dividing them by 3 (M=5.39, SD=1.02).
4.1.2 Source’s Identification
The influencer’s identification consisted of four items introduced and validated by Hoffner and Buchanan (2005), “[Influencer’s name] is the type of person I want to be like myself”, “Sometimes I wish I could be more like [influencer’s name]”, “[Influencer’s name] is someone I would like to emulate”, and “I would like to do the kind of things [influencer’s name] does”. The internal consistency for these four items was tested, Cronbach’s alpha returned as 0.86 (Table 3). A new variable “Identification” was computed based on this by adding the four items and then dividing them by 4 (M=4.25, SD=1.29).
4.1.3 Source’s Credibility
24
4.1.4 Source’s Product-fit
The influencer’s product-fit consisted of three items introduced and validated which were “The advertised pair of shoes is a product that suits [influencer’s name]”, “[Influencer’s name] is known for promoting these types of products”, and “The advertised pair of shoes and [influencer’s name] seems to be a good match”. The internal consistency for these three items was tested, Cronbach’s alpha returned as 0.78 (Table 3). A new variable “product fit” was computed based on this by adding the three items and then dividing them by 3 (M=4.65, SD=1.28).
4.1.5 Purchase Intention
The purchase intention consisted of four items introduced and validated by Duffett (2015), “I will buy the shoes that are advertised on Instagram”, “I desire to buy the shoes that are promoted on advertisements on Instagram”, and “I am likely to buy the shoes that are promoted on Instagram”, “I plan to purchase the shoes that are promoted on Instagram”. The internal consistency for these four items was tested, Cronbach’s alpha returned as 0.90 (Table 3). A new variable “purchase” was computed based on this by adding the four items and then dividing them by 4 (M=4.30, SD=1.30).
Table 3. Reliability Statistics
Variables No of items Cronbach’s Alpha
Purchase Intentions 4 0.90
Personalization 3 0.77
Influencer’s Identification 4 0.86
Influencer’s Credibility 9 0.93
Influencer’s Product-fit 3 0.78
4.2 Relationship between the use of personalization, social media influencers, and
purchase intention
Hypothesis 1 examines whether the more a consumer perceives the advertisement as personalized, the stronger is the intention to purchase a product. This was tested through a Linear Regression Analysis.
25
4.2.1 Hypothesis 1: The more a consumer perceives the advertisement as
personalized, the stronger is the intention to purchase a product
Hypothesis 1 predicted that the more a consumer perceives the advertisement as personalized, the stronger is the intention to purchase a product. In order to analyse if there is a correlation between the values of personalization and purchase intention, a Linear Regression Analyses was conducted. The linear regression included personalization as the independent variable and purchase intention as the outcome variable. A significant regression equation was found. The results showed that personalization significantly explained purchase intention, R2=.02, F (1,194) =4.69, p<0.05 (Table 4). There is a positive relation between personalization and purchase intention (B=0.19, t (194) =2.16, p<0.05), which means that the more a consumer perceives the advertisement as personalized, the stronger is the intention to purchase the product. According to the findings of the estimated model, this variable shows a positive relationship with consumer's purchase intentions and is found significant at a 1% level of significance. The value of the coefficient explains that if there is 1 unit improvement in the response category of personalization, there may be 0.19 units improvement in the response category of purchase intentions. Therefore, Hypothesis 1 is supported.
Table 4. Regression Analyses
Variable Coefficient Std. Error t-Statistic Sig.
Constant (Purchase Intentions) 3.25 .49 6.57 .00
Personalization .19 .09 2.16 .03
R .15 R- Squared .02
Adjusted R-squared .01 F-statistic 4.69
26
4.2.2 Hypothesis 2: Ad personalization will especially increase purchase
intentions the more a consumer is identified with the social media influencer
Hypothesis 2 predicted that ad personalization will especially increase purchase intentions the more a consumer is identified with the social media influencer. Hayes Macro Process model 4 showed that the interaction effect is non-significant statistical (Table 5), = R2 =.00, F (1,192) = 0.01, p =.891. Indeed, the interaction term personalization*identification did not contribute significantly to the model (B=0.00, t (192) =0.13, p=.891). Therefore, the influencer's identification did not affect the relationship between personalization and purchase intention, hereby rejecting hypothesis 2.Table 5. Regression Analyses
Moderator Variable Model: Identification
Variable Coefficient Std. Error t-Statistic Sig.
Constant (Purchase Intentions) 2.26 1.69 1.33 .00
Personalization Identification Personalization*Identification .14 .24 .00 .30 .37 .06 0.49 0.63 0.13 .62 .52 .89 R .32 R- Squared .00
Adjusted R-squared .10 F-statistic 0.01
4.2.3 Hypothesis 3: Ad personalization will especially increase purchase
intentions the more a social media influencer is perceived as credible by the
consumer.
27 Table 6. Regression Analyses
Moderator Variable Model: Credibility
Variable Coefficient Std. Error t-Statistic Sig.
Constant (Purchase Intentions) 5.01 1.64 3.05 .00
Personalization Credibility Personalization*Credibility -.21 -.40 .09 .30 .35 .06 -0.71 -1.15 1.45 .47 .24 .14 R .20 R- Squared .01
Adjusted R-squared .04 F-statistic 2.11
4.2.4 Ad personalization will especially increase purchase intentions the higher is
the perceived fit between the influencer and the product.
Hypothesis 4 predicted that ad personalization will especially increase purchase intentions the higher is the perceived fit between the influencer and the product. Hayes Macro Process model 4 showed that the interaction effect is non-significant statistical (Table 7), = R2=.00, F (1,192) =1.99, p = .159. Indeed, the interaction term personalization*product fit did not contribute significantly to the model (B= 0.10, t (192) = 1.41, p=.159). Therefore, the influencer's product fit did not affect the relationship between personalization and purchase intention, hereby rejecting hypothesis 4.
Table 7. Regression Analyses
Moderator Variable Model: Product Fit
Variable Coefficient Std. Error t-Statistic Sig.
Constant (Purchase Intentions) 5.10 1.98 2.57 .01
Personalization Product fit Personalization*Product fit -.28 -.39 .10 .35 .40 .07 -0.80 -0.96 1.41 .42 .33 .15 R .25 R- Squared .00
28 The table below gives an overview of the results that are found while the hypotheses were tested (Table 8).
Table 8. Hypotheses Overview
Hypotheses Findings
H1: The more a consumer perceives the advertisement as personalized, the stronger is the intention to purchase a product.
Supported
H2: Ad personalization will especially increase purchase intentions the more a consumer is identified with the social media influencer.
Not Supported
H3: Ad personalization will especially increase purchase intentions the more a social media influencer is perceived as credible by the consumer.
Not Supported
H4: Ad personalization will especially increase purchase intentions the higher is the perceived fit between the influencer and the product.
29
5. Discussion
The present study examined the possibility of personalized advertisements leading to higher consumers’ purchase intentions. Except for this, the study aimed to assess whether the use of social media influencers affected the relationship between personalization and purchase intentions. In more detail, the present study aimed to understand if social media influencers could work as a significant tool for marketers and companies in order to affect consumers’ purchase intention when advertisements are tailored to the audience. The theoretical framework of the study was to analyse if the combination of the factor personalization and the factor social media influencers would lead to higher purchase intentions than solely using personalization.
To start with, the results found that that personalized advertisements significantly affected consumers’ purchase intentions which supported Hypothesis 1. More specifically, the findings of the study showed that the more consumers perceive the advertisement as personalized, the stronger were their intentions to buy the advertised product, which was a pair of white sneakers. This is in line with prior research, which suggests that a high fit of the personalized advertisements strengthens the consumers’ intention to purchase (van Doorn & Hoekstra, 2013). Personalization would also be connected to the self-congruency theory (Sirgy, 1982), and act as a peripheral cue to trigger heuristic decision making, which ultimately leads to higher purchase intentions. Therefore, the results of this analysis further prove the importance of the use of personalization in a social media context in order to achieve higher purchase intentions.
30 With regard to hypothesis 2, the study examined the moderating effect of influencer identification by the consumer. A previous study found social media influencer's identification to play a significant role in advertising effectiveness (Basil, 1996). In line with the above statement, Basil (1996) suggested that consumers have a higher chance of accepting products promoted by influencers, with who they could identify themselves with. Therefore, we expected that the more consumers identify themselves with the influencers, the higher will be the chance that the personalized advertisement will lead to a higher desire to purchase. The results towards identification showed that this influencers’ attribute was not proved to be a significant factor for increasing the buying intention when consumers experience personalized advertisements. So, hypothesis 2 ended by being unsupported, however, some interesting conclusions can still be drawn based on the outcomes provided by the analysis. In all, consumers will not be affected by the degree to which they identify themselves with the influencer depicted in the personalized ad, therefore resulting in higher purchase intention. An explanation for this finding may be that the advertised pair of sneakers may not lead the consumer to feel more similar to the influencer. This could be likely happening for example with a rich or famous influencer, whose influencer’s socioeconomic level is not similar to the consumer. As a result, the consumer could not identify the oneself with the influencer, and the intention to buy the pair of sneakers will not be higher. This outcome is in line with some respondents’ comments towards the scenario who mentioned that:
“An influencer advertises lots of products and due to the mass appeal, she probably could sell it easily. The problem is that many influencers rarely promote their style, and they just try to be "in fashion", so I cannot identify myself with her”.
31 The results from the analysis of this moderator showed that influencers’ credibility could not add to a higher purchase intention when someone experiences personalization. This outcome implies that consumers’ intention to buy something will not be affected by the fact of whether influencers are perceived as credible or not by social media's audience. An explanation may be that because of the frequency influencers promote different products on a weekly or a monthly basis, followers feel that is unrealistic to believe that all these products are so good in order to be promoted. For example, if the influencer chose by the participant, recently had promoted another pair of sneakers, then the participant may feel that the influencer's opinion is biased. Therefore, a consumer’s intention to buy the advertised pair of sneakers is not increased. As a result, hypothesis 3 is not supported. This finding corresponds to some participants’ comments who stated:
“When I see an advertisement of an influencer, my first thought is that they earn a lot of money from the promotions of products. That does not stimulate me to buy products that they promote. It makes the influencers less trustworthy”.
Finally, with regard to hypothesis 4, the study examined the moderating effect of an influencer's product-fit in the relationship between personalization and purchase intention. In a study by it was demonstrated that in situations when influencers’ expertise matches the product/service promoted, the purchase intention of the consumers will be increased (Till & Busler 2000; Fink et al. 2004). Moreover, a previous study has found that the effectiveness of an advertisement promoted by influencers is fully connected to the image and personality of the influencer's fit with the product promoted (Kamins,1990). Therefore, we expected that the higher the fit between the influencer and the product is, the higher will be the chance that the personalized advertisement will lead to a higher desire to purchase the product.
32 sneakers will be limited. The finding regarding product-fit is in line with the attitude of some comments at the survey mentioning that:
“I think that products are often not suited to people who advertise them”
Overall, on the one hand, our findings demonstrated that personalization could really affect consumers' intentions to buy the advertised products. On the other hand, the use of influencers showed to not add to a higher purchase intention when someone experiences personalization. The results yield an insignificant outcome for the moderation of influencers in the relationship between personalization and purchase intentions. In line with recipients' comments, we could conclude that consumers feel that the majority of influencers could not be trusted, because it's their job to promote and advertise products. Therefore, influencers do not act as a tool for enhancing consumers’ purchase intention to buy the advertised products.
5.1 Theoretical implications
This study is the first to investigate the underlying mechanism of how personalization in advertisements and social media influencers affect consumers’ purchase intentions via social media. Previous studies could either focused on personalization or social media influencers without considering combined these factors on the effect on consumers’ purchase intentions. Our findings build on the existing research, in the concepts of personalization, purchase intentions, and the use of influencers in the social media context. Further, this study builds on the existing literature to examine the possible relations between these concepts. Personalized advertisements leading to higher purchase intentions and social media influencers acting as a moderator between the concepts of personalization and purchase intentions. The influencers' attributes that were assessed in this study were identification, credibility, and product-fit.
33
5.2 Managerial Implications
This study provides useful insights firstly for companies and marketers that use the social media context in order to promote products and services. This study demonstrated that an effective strategy, which can enhance consumers’ intention to buy the advertised products, is through the use of personalization in the advertisements. As a result of this, companies and marketers should focus on promoting personalized advertisements in the online environment for increasing the possibility of their products being purchased. As proved, personalization could work as a strong tool in achieving higher purchase intentions, which is in line with previous studies (van Doorn & Hoekstra, 2013).
The study also provided some evidence for the use of social media influencers when used in the personalized advertisements. Although the interaction between personalization and social media influencers did not prove to successfully enhance the purchase intention, the study showed that the use of influencers when personalization is present, could not act as an effective tool. This finding could be proved such a significant advantage for the future of online personalized advertisements. Taking into account that the popularity of social media influencers is growing tremendously, it would be beneficial for marketers and companies to assess these results before investing large amounts of budget on these endorsers. A recent report in 2018, demonstrated that 39% of marketers intended to increase their budget spent on social media influencers. More specifically, the report showed that 19% of marketers had plans to invest more than $100,000 per campaign (Bevilacqua & Del Giudice,2018). Therefore, the findings of the study may shed some light on the trend of social media influencers. This is a finding the researchers did not manage to find analogues to the existing literature and could benefit marketers and companies when combined personalized advertisements promoted by influencers in the social media environment.
5.3 Limitations
34 Second, another limitation of the study was with regard to the influencers. During the study, participants were asked to name the influencer of their choice. The criterion of the free choice was determined by the fact that consumers have different people who are inspired by it. As proved, that was a bit confusing for a small percentage of respondents who were excluded from the survey because not stating an influencer. This could possibly be avoided by providing participants a fictional influencer, instead of asking them to name one. Another aspect that should be taken into account regarding the influencers was the fact that no distinction was made between the type of influencers (mega, macro, micro, nano-influencers). The type of influencer and the number of followers might be a significant factor that could probably explain the outcome.
Finally, another limitation of this study was with regard to the sample size. Although our sample reached the minimum levels sketched out by our theorization, the number of respondents proved to be smaller than the desired, specifically due to the excluding criteria included in the study. This could possibly have resulted in a different outcome.
5.4 Future research
The practical relevance of the research topic and the important findings documented in this study call for more research to shed further light on how to improve the effectiveness of online advertisements on social media. The results showed that personalization can significantly result in higher purchase intentions in the online environment, especially on Instagram which was the study presented. An interesting case would be to examine if the same results will be found on different social media platforms. Future research could focus on the social mediums of YouTube and Tok-Tok, for assessing whether personalization could enhance consumers’ purchase intentions in order to have a more rounded view with regards to personalized advertisements on social media.
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Reference List
Aaker, D. A., & Myers, J. G. (1987). Advertising management (3rd ed.). Prentice-Hall.
Abidin, C. (2016). Visibility labour: Engaging with Influencers’ fashion brands and #OOTD advertorial campaigns on Instagram. Media International Australia, 161(1), 86–100. https://doi.org/10.1177/1329878X16665177
Aguirre, E., Mahr, D., Grewal, D., de Ruyter, K., & Wetzels, M. (2015). Unraveling the personalization paradox: The effect of information collection and Trust-Building strategies on online advertisement effectiveness. Journal of Retailing, 91(1), 34–49. https://doi.org/10.1016/j.jretai.2014.09.005
Alalwan, A. A. (2018). Investigating the impact of social media advertising features on customer purchase intention. International Journal of Information Management, 42, 65–77. https://doi.org/10.1016/j.ijinfomgt.2018.06.001
Ansari, A., & Mela, C. F. (2003). E-Customization. Journal of Marketing Research, 40(2), 131–145. https://doi.org/10.1509/jmkr.40.2.131.19224
Ashley, C., & Tuten, T. (2015). Creative strategies in social media marketing: An exploratory study of branded social content and consumer engagement. Psychology & Marketing, 32(1), 15–27. https://doi.org/10.1002/mar.20761
Basil, M. D. (1996). Identification as a mediator of celebrity effects. Journal of Broadcasting & Electronic Media, 40(4), 478–495. https://doi.org/10.1080/08838159609364370 Belch, G., & Belch, M. (1995). Introduction to advertising and promotion: An integrated
marketing communications perspective, (3rd ed.). Richard D. Irwin.
Bevilacqua, J., & Giudice, E. (2018). Why brands need to utilize influencer marketing in 2018. St. Joseph Communications.
Bleier, A., & Eisenbeiss, M. (2015). The importance of trust for personalized online advertising. Journal of Retailing, 91(3), 390–409.
37 Boerman, S. C., Kruikemeier, S., & Zuiderveen Borgesius, F. J. (2017). Online behavioral
advertising: A literature review and research agenda. Journal of Advertising, 46(3), 363–376. https://doi.org/10.1080/00913367.2017.1339368
Camilleri, M. A. (2017). Market segmentation, targeting and positioning. Tourism,
Hospitality & Event Management, 69–83. https://doi.org/10.1007/978-3-319-49849-2_4
Casaló, L. V., Flavián, C., & Ibáñez-Sánchez, S. (2020). Influencers on instagram:
Antecedents and consequences of opinion leadership. Journal of Business Research, 117(July 2018), 510–519. https://doi.org/10.1016/j.jbusres.2018.07.005
Chapple, C., and F. Cownie. (2017). An investigation into viewers’ trust in and response towards disclosed paid-for-endorsements by YouTube lifestyle vloggers. Journal of Promotional Communications 5: 110–36
Cialdini, R. (1993). Influence: The psychology of influence. William Morrow & Co.
Cohen, J. (2001). Defining Identification: A Theoretical Look at the Identification of
Audiences With Media Characters. Mass Communication and Society, 4(3), 245–264. https://doi.org/10.1207/s15327825mcs0403_01
Colliander, J., & Dahlén, M. (2011). Following the fashionable friend: The power of social media. Journal of Advertising Research, 51(1), 313–320. https://doi.org/10.2501/jar-51-1-313-320
de Magistris, T., & Gracia, A. (2008). The decision to buy organic food products in southern italy. British Food Journal, 110(9), 929–947.
https://doi.org/10.1108/00070700810900620
De Veirman, M., Cauberghe, V., & Hudders, L. (2017). Marketing through instagram influencers: The impact of number of followers and product divergence on brand attitude. International Journal of Advertising, 36(5), 798–828.
38 Dhanesh, G. S., & Duthler, G. (2019). Relationship management through social media
influencers: Effects of followers’ awareness of paid endorsement. Public Relations Review, 45(3), 101765. https://doi.org/10.1016/j.pubrev.2019.03.002
Djafarova, E., & Rushworth, C. (2017). Exploring the credibility of online celebrities’ instagram profiles in influencing the purchase decisions of young female users. Computers in Human Behavior, 68, 1–7. https://doi.org/10.1016/j.chb.2016.11.009 Dörnyei, Z. (2007). Research methods in applied linguistics. Oxford University Press.
Duffett, R. G. (2015). Facebook advertising’s influence on intention-to-purchase and purchase amongst millennials. Internet Research, 25(4), 498–526.
https://doi.org/10.1108/intr-01-2014-0020
Erdogan, B. Z. (1999). Celebrity Endorsement: A Literature Review. Journal of Marketing Management, 15(4), 291–314. https://doi.org/10.1362/026725799784870379 Erdogan, B. Z., Baker, M. J., & Tagg, S. (2001). Selecting Celebrity Endorsers:The
Practitioner’s Perspective. Journal of Advertising Research, 41(3), 39–48. https://doi.org/10.2501/jar-41-3-39-48
Erz, A., & Heeris Christensen, A.-B. (2018). Transforming Consumers Into Brands: Tracing Transformation Processes of the Practice of Blogging. Journal of Interactive
Marketing, 43(69), 69–82. https://doi.org/10.1016/j.intmar.2017.12.002
Etikan, I. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1.
https://doi.org/10.11648/j.ajtas.20160501.11
Evans, D., & McKee, J. (2010). Social media as the next trend in social business marketing social media as the next trend in solar business marketing. International Journal of Innovative Technology and Exploring Engineering, 8(11S), 760–763.
