Storytelling advertising: A cognitive journey into emotions
A study on the effects of emotions in storytelling ad videos and the moderating role of source on Brand Attitudes and Sharing Intention
Raphael Perachi Vieira - 12441260 Master thesis
University of Amsterdam
Graduate School of Communication Persuasive Communication Science Supervisor Dr. Lotte Salome
26/06/ 2020 7500 words
Abstract
The current study extends literature by analyzing the effects of positive and negative storytelling advertisements while addressing the moderate effect of source on brand attitudes and sharing intentions. The research consists of a 2 (emotion type: positive vs. negative) × 2 (source: commercial brand vs non-profit organization) factorial between-subjects true experiment. The final sample of the online experiment consists of 192 participants, from 5 continents. The results show a nonsignificant effect of positive versus negative emotions on sharing intention and brand attitudes, reassuring the challenge to isolate positive and negative emotions from each other. Besides, the moderate effect of source is not supported. However, the study found an unexpected main effect of source on sharing intention and brand attitude, showing the emotional effect could have interfered in the study results. The study contributes to future research by suggesting
different approaches to effectively manipulate positive and negative emotions, since both can co-occur as two distinct dimensions. Additionally, it suggests the inclusion of emotional strength as a mediating variable.
Storytelling advertising: A cognitive journey into emotions Introduction
For decades, storytelling advertising has been used to empower brands in the marketplace (Chung, Choi, & Sohn, 2012). Storytelling advertising helps to build a relationship with
consumers (Simanjuntak, Napitupulu & Situmeang, 2016) by establishing passionate brand communities (Smith & Wintrob, 2013) for companies to be remembered (Kang, Hong &
Hubbard, 2020). Past research (Wentzel, Tomczak, & Herman, 2010; Woodside, Sood, & Miller, 2008) defined storytelling advertising, or narrative advertising, as “a form of advertising that communicates about a brand, a product, or a service in a story-like format” (Dessart, 2018, p. 289). In fact, storytelling is an accepted technique to raise the emotional power of advertising by stimulating consumers' emotions as they mentally combine stories with their own experiences (Escalas, 2006; Kang et al., 2020).
Therefore, emotion has been considered a predictor of advertising effectiveness and it has played a central role in advertisement (Chung et al., 2012; Poels & Dewitte, 2019). Emotion has been proven by neuroscience (Hamelin, Moujahid & Thaichon, 2017) as fundamental for rational thinking and behavior (Poels & Dewitte, 2019). It has played an important role into one’s
decision-making process (Guido, Pichierri & Pino, 2018; Poels & Dewitte, 2006) by raising consumers' awareness towards a product or an advertisement (Lewinski, Fransen & Tan, 2014; Mai & Schoeller, 2009).
Given the information above, Poels and De Witte (2019) proposed that society and the scientific domain still do not have profound knowledge on the impact of different types of emotions on actual advertising-related behavior (Zao & Ji, 2019). This seems to be a common
problem, as Guido, Pichierri and Pino (2018) indicated an absence of research on the sequence of elicit emotions on consumer behavior. In fact, Ferreira, Brandão, and Bizarrias (2017) pointed out that contrasting emotions, such as positive or negative, can influence consumers’ responses and impacts ad effectiveness (Kang et al., 2020). Several papers (Berkowitz, 2000; Diener, 1999; Laros & Steenkamp, 2005) showed positive and negative emotions are necessary while
experiencing different emotions. Thus, a deeper understanding of the impacts these emotions have could be an important indicator of consumer's attitude (Laros & Steenkamp, 2005).
Additionally, another relevant factor in storytelling effectiveness is the message source, or the storyteller. After being exposed to a message, the receiver is affected by the source (Chaiken, 1980; Hautz, Füller, Hutter & Thürridl, 2014). In fact, the message receiver entails observed or inferred characteristics of the storyteller, such as the source credibility (Hsieh, Hsieh & Tang, 2012). Thus, consumers tend to trust messages, or stories, created by peers more than the ones created by commercial marketers (Chatterjee, 2001). This research will analyse the effects of the source of an advertisement, more specifically a commercial brand and a non-profit organization, on consumers after the exposure to an emotional storytelling advertisement. Consequently, source credibility can be an important factor on the strength emotions play on the message receiver.
Ultimately, this study aims to build more knowledge on the effects of emotional
storytelling advertisement and analyse under which conditions these effects occur, focusing on two emotional dimensions (positive, negative). Likewise, this research addresses important gaps in previous literature and develops on the effects of source credibility, inspecting relevant differences between commercial brands and non-profit organizations. Additionally, society will
benefit as many marketers and communicators will be able to elaborate more in depth campaigns strategies for the marketing industry. On the other hand, the academic field will extend
knowledge by closing remaining gaps already described in literature. More specifically, this study aims to answer: What are the effects of emotion in a storytelling advertising video (positive/negative) on sharing intention and brand attitude? And to what extent is this effect influenced by type of source (commercial brand/non-profit organization)?
Theoretical framework Storytelling and Advertising
Previous studies showed stories have been embedded in human DNA and have been a part of human evolution for centuries (Moin, Hosany & O’Brien, 2020). As a fundamental part of human nature (Fisher, 1984), stories lead social life as individuals are exposed to it since birth (Van Laer, de Ruyter, Visconti & Wetzels, 2014). Everyone is able to tell a story as no
equipment is necessary (Senehi, 2002), only an audience of at least one person (Ryan, 1995). The process starts with a storyteller, or a sender. In this research, the storyteller can be
referenced as the brand or organization. Storytelling is a type of message sent to a receiver, in this study referred to as the consumer (Van Laer et al., 2014).
Therefore, extended literature claimed the main goal of a storyteller is to connect with the public (Jones, 2015). Aware of the power and tradition of storytelling, brands and organizations use this technique to advertise a product, adapting stories to connect and influence consumers (Merchant & Rose, 2013). However, storytellers are not only aiming to promote products or services to customers, but companies are endeavouring to establish strong connections (Sander &
Van Krieken, 2018) with the idea to “design brand experiences that stretch beyond mere products and price points” (Smith & Wintrob, 2013, p. 37). That’s the main reason why a storytelling advertising message is used.
Additionally, a number of authors recognized that the storytelling advertisement message is persuasive throughout life (Woodside et al., 2008). Stories are an emotional glue to connect with one another (Papadatos, 2006). Moreover, the storytelling message has been described as the “receiver’s consumption of the story through which he or she does not just read the story but also makes it readable in the first place” (Van Laer et al., 2014, p. 799). A recent study by Kakroo (2015) suggested a story, or narrative, with three major characteristics: (1) a plot,
defining the actions in a story, (2) a character, and (3) an attractive aesthetic. The latter relates to the “telling style” or rhetorical skills in a narrative to make a story more attractive. Likewise, a story can be identified by having central themes, a protagonist’s intention, behaviors to perform these intentions, and the results of such actions (Schank & Berman, 2002). Therefore, two important segments are described: First, chronology or the sequence of episodes, and secondly causality, or the affinity of story contexts and what motivates events to occur (Escalas, 1998). The majority of prior research has argued that an effective advertisement message stimulates consumers' emotions (Ho et al. 2013), influencing attitudes and behavioral responses (Lee et al., 2015; Meyers-Levy & Malaviya, 1999).
Several studies suggested humans, in this research the consumers or receivers of a story, recalled information in the form of events, experiences, incidents, and in the shape of stories rather than data and facts (Woodside, 2010). There is growing evidence that a lot of information is stored, indexed, and retrieved in the receiver’s brain in the form of stories (Lundqvist,
Liljander, Gummerus, & Van Riel, 2013; Schank, 1999). Accordingly, Weick (1995) stated a story receiver is not only purely reading the text, or viewing, but actually acting as an interpreter, consequently authoring how the story is being processed. De Certeau (1984, p. xxi) explained this process “makes the text habitable, like a rented apartment. It transforms another person’s property into a space borrowed for a moment by a transient”. These reflect the power of a story in the consumer’s brain, while absorbing the message and processing it. Given the above, the effects of storytelling advertisements are elicited by a phenomenon called narrative
transportation (Escalas, 2004; Gerrig 1994; Green & Brock 2000).
Narrative transportation theory. Commercials, or ads, are often used to tell stories (Woodside et al., 2008). Green and Brock (2000) stated transportation is an immersion into a text, leading to a cultivation of fewer negative thoughts, a more positive emotional response to a story, and consequently reducing counterargument (Kim, Ratneshwar & Thorson, 2017). All of these create a higher realism of experiences when the transported reader, the consumer, develops feelings of being lost, drowned, or absorbed into the story. As a result, “the traveler goes some distance from his or her world of origin, which makes some aspects of the world of origin inaccessible. The traveler returns to the world of origin, somewhat changed by the journey” (Gerrig, 1993, p. 11).
Therefore, consumers transported into the storytelling advertisement world may be less likely to disbelieve or counter argue the message. Likewise, the beliefs or attitudes of consumers may be influenced since the receiver is drowned to the brand’s world. This effect is crucial for this study, as it’s the brand’s final goal to penetrate the consumers brain to persuade them.
Emotions in storytelling advertising
A number of authors recognized that human beings are emotional creatures (Lund et al., 2018; Moin et al., 2020). Kleinginna and Kleinginna (1981, p. 371) defined an emotion as “a complex set of interactions among subjective and objective factors, mediated by neural/hormonal systems, which can (a) give rise to affective feelings of arousal, pleasure/ displeasure; (b)
generate cognitive processes such as emotionally relevant perceptual effects, appraisals, labeling processes; (c) activate widespread physiological adjustments to the arousing conditions; and (d) lead to behavior that is often, but not always, expressive, goal-directed, and adaptive”. This aligns with narrative transportation since the consumer dives into the world of a story, losing track of the real world.
Additionally, advertisers have been using images, text or background music to arouse emotions, in a creative way, on consumers since they are emotionally attached to a product (Mogaji, 2016). The public goes through the narrative process eliciting emotional responses (Kang et al., 2020). In short, emotions mediate the way advertisements are processed (Percy & Rosenbaum-Elliott, 2012). Therefore, how a consumer processes each emotion in the brain, during the narrative transportation effect, is that crucial to develop an effective emotional storytelling advertising message.
Cognitive appraisal theory of emotion. Lazarus (1991, 2001) explained emotion as a mental state of readiness arised from the cognitive appraisals that people have regarding
commercials (Friestad & Thorson, 1986; Srull, 1983, Bagozzi, Gopinath, & Nyer, 1999). In the model, emotions are activated by a cognitive appraisal, a stimulus such as the emotional
experience of a physiological response, where the narrative transportation effect can happen. Consequently, the consumer experiences the emotion and together with narrative transportation theory, the cognitive appraisal theory explains how emotional storytelling advertisements are absorbed and processed in the consumers brain (Kang et al., 2020). Finally, for all of these processes to occur, the consumer needs to identify with the message. This is explained by narrative empathy theory.
Narrative empathy theory. Keen (2006) disclosed the theory as the capability to appreciate, share, and interpret the cognitive, affective, experiential, and existential worlds of others (Moore & Hallenbeck, 2010, Charon, 2005). Empathy is a vicarious, spontaneous sharing of affect that can occur by watching someone else’s emotional state. Narratives promote
connection (Moore & Hallenbeck, 2010) as “we feel what we believe to be the emotions of others” (Keen, 2006, p. 208). Storytellers, and brands, normally rely on the central role of empathy to share a message and to influence consumers. The narrative transportation and empathy effects, with the stimulus of the emotional storytelling advertisements, help to explain the process consumers go through while watching an advertisement, experiencing the brand’s world. This is followed by the cognitive process of emotional appraisal, and the goal is for the consumer to emphatically relate to the message.
The effects of emotional advertising on attitudes towards the brand
Jeon, Franke, Huhmann, and Phelps (1999) argued that emotional appeals, such as emotional storytelling advertisements, aimed to provoke either negative or positive emotions. However, extensive research into the field of marketing has questioned the single bipolar
affective dimension view of positive and negative emotion as merely two opposites (Aaker et al., 1986; Edell & Burke, 1987). Huang (2001) proposed a dual unipolar affective dimension for emotions in marketing, where positive and negative emotion constituted separate emotional dimensions. This proposition makes sense, since the idea of positive and negative emotion being on opposite sides does not resonate since people can experience these emotions all together. This line of reasoning states advantages of “making possible a distinction between ambivalence and indifference” (Westbrook, 1987, p. 266), avoiding the difficulty in identifying emotional opposites (Aaker et al., 1986; Nyer, 1997), and “allowing positive and negative emotions to co-occur” (Edell & Burke, 1987, p. 427).
Additionally, Laros and Steenkamp (2005) argue the advantages of conceptualizing positive and negative emotions in separate dimensions: It keeps the model simple and to combine with a person’s attitude. On the contrary, the disadvantage is that the important distinctions among a wide range of different positive and negative emotions disappear (Lerner & Keltner, 2001). Ultimately, this study doesn’t aim to describe a wide variety of emotions, but rather proposes to isolate dimension's effects for consequences on attitudes towards the brand and sharing intention.
In the integrative behavior model, proposed by Fishbein (2000), an attitude is a predictor of an intention. In turn, behavioral intention is a predictor of the strength of an individual
willingness to perform a given behavior. As a result, with the effects of narrative transportation, cognitive appraisal theory, and narrative empathy, the consumer has a higher chance to absorb the information in the advertisement by emerging into its realms developing new attitudes or
reinforcing existing ones. This can lead to an intention to perform a given behavior, such as product purchase or sharing the video.
Thus, Laros and Steenkamp (2005), conceptualized positive emotions as contentment, happiness, love and pride while negative emotions included anger, fear, sadness and shame. Bessarabova, Turner, Fink, and Blustein (2015) pointed out that negative emotion is
counterproductive in consumer marketing and difficult to achieve the desired results, in this study’s case a positive brand attitude. On the other hand, positive emotional advertisement, when compared to negative emotional advertisement, results in better advertisement performances (Zheng, 2020, Dens & Pelsmacker, 2010). Finally, the argument assumes and argues that positive emotions will lead to positive attitudes towards the brand. The first hypothesis in this study states:
Hypothesis 1: Exposure to an emotional storytelling advertisement with positive emotions has a more positive effect on brand attitudes than a storytelling advertisement with negative emotions.
The effects of emotional advertising on sharing intention
Following the integrative behavior model, Heath, Bell and Sternberg (2001) found emotion as one of the most influential factors on consumers sharing intention of content.
Consumers are willing to share content if it appeals to their emotions (Kang et al., 2020, Berger & Milkman, 2012), a perfect fit for this study. For instance, research showed that highly arousing and positive videos were shared most often, followed by highly arousing and negative and/or disgusting videos. On the other hand, neutral, non-emotional, or low arousing videos were the
least likely to be shared online (Berger, 2011, Eckler and Bolls, 2011, Guadagno et al., 2013, Nelson-Field et al., 2013). Additionally, Botha and Reyneke (2013) indicated consumers with a positive, versus negative, emotional reaction tended to share more of the content they watched. Based on previous research, the second hypothesis of this study states that:
Hypothesis 2: Exposure to an emotional storytelling advertisement with positive emotions has a more positive effect on sharing intention than a storytelling advertisement with negative emotions.
Moderating effects of source
Several studies have found that the persuasive effect of any type of product information relied consequently on its source derogation (Chu, 2011, Lu et al., 2005, Pelling and White, 2009). Source refers to where the message originates (Berlo, 1960) and can have a strong impact on consumers (Chu, 2011, Lu et al., 2005). In the source credibility model, Hovland and Weiss (1951) stated the attitude of the audience towards the communicator (or source of the message, in this study the brand or
organization) was essential for the effectiveness of the message. In summary, when the consumer recognized the endorser of a video wanting to gain publicity, source
credibility was low. The public perceived the information could be manipulated (Chan & Zhang, 2019; Foreh & Grier 2003; Samman et al. 2009). However, the opposite also occurred, as consumers recognized the source embraced a social cause, source
credibility was higher (Trimble & Rifon, 2006).
non-profit as raising funds or creating awareness of social issues. As is widely known, commercial brands desire financial gain by selling products or services. Accordingly, sources in this study can be operationalized as non-profit organizations and commercial brands. Since hypothesis 1 and 2 state positive emotional storytelling advertising is a strong predictor of consumer brand attitudes and sharing intentions, this effect is even stronger when it is combined with the source of the story, playing a moderating role. Finally, hypothesis 3 and 4 are:
Hypothesis 3: The effect of a storytelling advertisement with positive emotions prevalence on brand attitude is more positive for a non-profit advertisement than for commercial advertisement.
Hypothesis 4: The effect of a storytelling advertisement with positive emotions prevailing on sharing intention is more positive for a non-profit advertisement than for commercial advertisement.
Methods Design
This empirical study used a 2 (emotion type in a storytelling ad: positive vs negative,) by 2 (source: non-profit vs commercial,) between-subjects true experimental design (see table 1). Participants were randomly assigned to one of the four experimental conditions. Ethical approval for this study was granted by the Ethics Committee representing ASCoR, the Amsterdam School of Communication Research, in the University of Amsterdam.
Participants
To test the hypotheses, an online experiment was conducted. A link with an invitation to participate in the online questionnaire was sent out via social media. The participants had to be older than 18 years, be able to read, listen and write in English and to have access to a
computer/cellphone with a sound system. The data was collected between May 27th and June 2nd of 2020.
A convenience sample approach was chosen since there were no funds available to spend in sampling, so this approach was the most reasonable and resourceful choice. This reduced the external validity, specially the population validity, as it won’t have a representative sample of the population (world). The web-based experiment impacted the internal validity, but this was the most suitable approach since the study was developed during the CoronaVirus pandemic. However, this decision also increased the external validity since the web-based experiment allowed participants to engage in the survey from their own environment, which created a more realistic setting to draw conclusions beyond the specific research context.
Finally, 264 respondents were invited to participate, but 29 drop-out. Out of the
remaining 235 participants, 43 participants were deleted from the data because of missing values. The final sample consisted of 192 participants (94 males, 97 females, 1 other) and the mean age was 33.30 (SD = 7.48) years.
Materials and manipulation
The experimental videos were real emotional storytelling ads, which increased the external validity to generalize results. A total of 20 emotional storytelling videos were taken out of YouTube and measured as more positive or negative (see pretest 1). After pretest 1, two videos were chosen, manipulated and retested (see pretest 2). Two videos were selected. The first video, from Coke - “Happiness starts with a smile” (Serviceplan group, 2015), shows a story of a man entering the subway and laughing out loud, without any reason, consequently creating a laugh atmosphere (see appendix C). The second video, by the ICRC - “The one gift Santa can’t deliver” (see appendix A), shows a story of a Santa Claus trying to reach a young girl who is in the middle of a war zone and bombs (International Committee of the Red Cross, 2018). Both videos can be found on YouTube by the name, increasing the replicability of this study. A second pretest was conducted to ensure the reliability of the final stimulus materials.
Emotion type in a storytelling ad. The manipulation of emotions was done by a pretest, which identified the different emotional variations in each video with a 7-point scale to rate the emotional strength between positive versus negative emotions (more details in pretest 1). Based on the mean of each emotion on the pre-tests, the video Coke “Happiness starts with a smile” (M = 6.6, SD = .59) was chosen. For the negative emotion, the ICRC “The one gift Santa can’t deliver” (M = 5.3, SD = 1.34) was chosen (more detail in pretest 2).
Source type. For the manipulation of source, four videos were created with a different logo edit at the end of the videos. The logos were from different commercial brands (KLM and Coke, see appendix B, D) and non-profit organizations (WWF and International Red Cross, see appendix B, D). Coke and ICRC were the original brands in the ad. KLM and WWF were chosen because the brand’s logos related to the original video and message, which increased the
measurement validity. KLM is a flight company and the Santa Video (negative emotion, see appendix A) tells a story of families living in war zones wanting to be reunited by travelling abroad. The WWF logo has a thankful message (see appendix D) and matches the happy aspect of the original Coke video. These logos/brands made it more realistic and compatible for the manipulation, increasing internal validity.
Pretest 1
The first pretest, among 46 participants, resulted in 31 valid responses computed between May 15th to May 17th of 2020. A total of 20 existing emotional storytelling ads (10 positive, 10 negative) were included in the first pretest, which contained 50% of commercial brand (ex: Google, Duracell, Johnnie Walker, Coke, McDonald’s, Fiber one, Tesla, Volskwagen, Mountain Dew, Amazon) and 50% of ads from non-profit organizations (Greenpeace, WWF, ICRC, Plastic People, Unicef, The Pillon Trust). The participants were randomly assigned, this eliminated rival explanations and increased internal validity, to 4 experimental groups with 5 videos each. The participants then answered questions and measurements (see appendix F).
The chosen positive ad, the Coke video (see appendix C), had the highest mean
difference between positive and negative emotion (Mdifference= 5.6) and the highest in the positive emotion mean average item (M = 6.60, SD = .59). The chosen negative ad, the International
Committee of the Red Cross (ICRC, see appendix A), had the highest mean difference between negative and positive emotion in the scale (Mdifference = 3.2) and it was the second highest in the negative emotion mean average item (M = 5.30, SD = 1.34). The first place in the negative emotion mean average had a lower mean difference.
Pretest 2
In the second pretest, a total of 6 valid responses were computed between May 21 to May 22th of 2020. Both videos, chosen on pretest 1, were duplicated in a video editor software. Two negative emotions videos, one with ICRC and KLM logo at the end (see appendix B), and two positive emotions videos, one with Coke and one with WWF logos at the end (see appendix D), were developed. The videos had the same length (1min 24sec) and four conditions were created. The same questions on pretest 1 were asked (see appendix F). As expected, the manipulated videos in the positive emotion/commercial condition (M = 6.50, SD = .07) and the positive
emotion/non-profit condition (M = 6.00, SD = .00) were seen as more positive. The manipulated videos in the negative emotion/commercial condition (M = 4.25, SD = 1.5) and the negative emotion/non-profit condition (M = 7.00, SD = .00) were also seen as more negative.
Procedure
For this study, the platform Qualtrics was used. The participants were informed about the ethics procedure and were given information about the study (see appendix G) and instructions (see appendix H), which increased the validity of the exposure. Further, the participants answered demographics questions such as age, gender, education and nationality. All the pages in the questionnaire were self-paced and consisted of 9 separate web pages.
The respondents were asked to watch one of four randomly assigned videos.
Additionally, the participants answered questions about their intention to share the video and attitudes towards the brand. Lastly, they answered the questions regarding the manipulation checks (see appendix E). People could not miss any of the questions due to forced response settings.
Measures
Attitudes toward the brand. The variable was measured using a five-item seven-point semantic differential scale presented by Spears and Singh (2012). Participants were asked to describe their overall feelings about the brand shown in the video they watched. Participants evaluated the video using the following anchor points: (1) unappealing/ (7) appealing, bad/good, unpleasant/pleasant, unfavorable/favorable, unlikeable/likable (see appendix I). An exploratory factor analysis with Varimax rotation indicated that the scale was unidimensional, explaining 83.40% of the variance. The 5-item scale also proved reliable (α = .95). The mean index of all the five items was computed together to create the continuous variable Attitudes Towards the Brand (M = 4.98, SD = 1.58).
Sharing intention. The variable was measured using a three-item seven-point likert scale (ranging from 1 = “strongly disagree” to 7 = “strongly agree”) presented by Choi, Bang. The items included “I will recommend this video to others”, “This video is worth sharing with others” and “I wish my friends and relatives would watch this video” (see appendix J). An exploratory factor analysis with Varimax rotation indicated that the scale was unidimensional, explaining 90.55% of the variance. The 3-item scale also proved reliable (α = .95). The mean
index of all the three items was computed to create the continuous variable Sharing Intention (M = 4.76, SD = 1.71).
Control variables. Gender was measured by giving the participant three options (male, female or other), while age was measure as an open question, nationality was divided by continents (“Asia”, “Australia”, “America”, “Europe” and “Africa”), while education was measured by the participants choosing the highest level of education accomplished or in current enrolment (“less than highschool”, “high school”, “associate’s degree”, “bachelors”,
“masters”, or “PhD or higher”).
Results Randomization checks
Age. In order to check if participants’ age was comparable over the emotion type
condition, a One-way ANOVA was conducted with emotion type (positive emotion vs. negative emotion) as an independent variable, and age as dependent variable. The ANOVA showed that participants’ mean age in the positive emotion condition (M = 32.64 years, SD = 6.48) was not significantly different from participants’ mean age in the negative emotion condition (M = 33.96 years, SD = 8.34), F(1, 190) = 1.51 p = .221.
The same procedure was conducted for source type (commercial vs. non-profit). The ANOVA showed that participants’ mean age in the commercial condition (M = 34.10 years, SD = 8.41) was not significantly different from participants’ mean age in the non-profit condition (M = 32.53 years, SD = 6.42), F(1, 190) = 2.11 p = .148.
Gender. In order to check if participants’ gender was comparable over the emotion type conditions (positive emotion vs. negative emotion), a chi-square test of independence was performed. Emotion type was the independent variable and gender was the dependent. The participants in each condition did not differ and the results were non-significant, Chi-squared (1, N = 191) = 0.64, p = .425, Phi = .06. There were no significant differences in the participants gender between both conditions groups.
Additionally, for source type (commercial vs. non-profit), a chi-square test of
independence was executed with the same procedure. The percentage of participants in each condition did not differ, results were non-significant, Chi-squared (1, N = 191) = 0.64, p = .423, Phi = -.06. No significant differences in participants' gender between both condition groups.
Education. In order to check if participants’ education was comparable over the emotion type conditions (positive emotion vs. negative emotion), a chi-square test of independence was performed. Emotion type was the independent variable and education dependent. The percentage of participants in each condition did not differ, results were non-significant, Chi-squared (1, N = 192) = 1.76, p = .779, Phi = .10. There were no significant differences in participant’s education level between both conditions groups.
For the source type conditions (commercial vs. non-profit), a chi-square test of independence was also performed with the same procedure. The percentage of participants in each condition did not differ, results were non-significant, Chi-squared (1, N = 192) = 3.16, p = .532, Phi = .13. There were no significant differences in participant’s education level between both conditions groups.
Nationality. In order to check if participants’ nationality was comparable over the emotion type conditions (positive emotion vs. negative emotion), a chi-square test of independence was performed. Emotion type as an independent variable and nationality as a dependent. The percentage of participants in each condition did not differ, results were
non-significant, Chi-squared (1, N = 192) = 0.52, p = .972, Phi = .05. There were no significant differences in participant’s nationality between both conditions groups.
For source type conditions (commercial vs. non-profit), a chi-square test of independence was also performed with the same procedure. The percentage of participants in each condition did not differ, results were non-significant, Chi-squared (1, N = 192) = 2.88, p = .579, Phi = .12. There were no significant differences in participant’s nationality between both conditions groups.
Therefore, all the control variables had the participant characteristics evenly distributed across all the conditions. Finally, there was no need to put any of the control variables as covariates in the main analysis.
Manipulation Check
Emotion type. In order to check if the manipulated variable emotion type was perceived as intended by the participants, a chi-square test of independence was performed with emotion type (positive, negative) as an independent variable and emotion effect (positive video, negative video) as the dependent. The emotion effect was measured asking the participants “How would you describe the video you just watched?” (see appendix E). In the positive emotional condition, 94 out of 96 people perceived the video as a positive. However, in the negative condition, only 55 out of 96 people perceived the video as a negative one, resulting in 41 people seeing the video as positive (see figure 1). This could impact the results as some people didn’t perceive it as a
negative video. However, the results of the Chi-square were significant, Chi-squared (1, N = 192) = 70.09, p < .001, Phi = .60, meaning that there were statistically significant differences in emotion type between the groups, showing the manipulation was effective as people perceived both videos differently.
Source type. In order to check if the manipulated variable source type (commercial vs. non-profit) was perceived as intended by the participants, a chi-square test of independence was performed with source type as an independent variable and source effect (commercial vs
non-profit) as a dependent. The participants were asked “Who is the maker of the video you watched” (see appendix E). In the commercial brand condition, 82 out of 87 participants recognized the video as coming from a commercial brand, while in the non-profit organization condition, 78 out of 86 people recognized the video coming from a non-profit organization (see figure 2). These numbers are good, showing the manipulation worked. Results were significant, as expected. Chi-squared (1, N = 192) = 70.09, p < .001, Phi = .60. There were significant differences in source between the groups, showing the manipulation was effective.
Main Analyses
A multivariate analysis of variance (MANOVA) was conducted to check the effects of H1, H2, H3 and H4. The test had 2 categorical independent variables (emotion type, positive/negative, and source type, commercial brand/non-profit organization) with 2 continuous dependent variables (sharing intention and brand attitude). Additionally, it should be noted that all the observations in this study were independent and there were no significant outliers.
Attitudes towards the brand. Hypothesis 1 stated that exposure to a storytelling ad with positive emotions has a more positive effect on brand attitudes than a storytelling ad with
negative emotions. A multivariate analysis of variance was carried out to assess the influence of exposure to a storytelling advertisement emotion type (positive vs negative) as the independent variable, in conjunction with the interaction effect of source type (commercial vs non-profit), and attitude towards the brand as a dependent variable. There was nonsignificant main effect of emotion type on attitudes towards the brand, F (1, 188) = 0.02, p = .887, so H1 was rejected. In other words, there were no significant differences in the mean of the participants who had seen the positive emotion video (M = 5.01, SD = 1.77) compared to those who had seen the negative emotion video (M = 4.95, SD = 1.39) on attitudes towards the brand. No effect of emotions on brand attitudes.
Furthermore, H3 stated the interaction effect, such as the effect of a storytelling ad with positive emotions on brand attitudes is more positive for a non-profit organization ad than for a commercial brand ad. There were no significant differences in attitudes towards the brand in the non-profit condition (M = 5.29, SD = 1.49) compared to the commercial brand (M= 4.66, SD = 1.61). The interaction effect was not significant, F (1, 188) = 0.00, p = .946, so H3 is rejected. No interaction effect of source and emotions on brand attitudes.
In addition, there was a significant but weak effect of source type on attitudes towards the brand, as F (1, 188) = 8.00, p = .005, Eta-squared = .04, but this effect was not theoretically expected in this study. Participants had more positive attitudes towards the brand when the source comes from a non-profit (M = 5.29, SD = 1.49) than a commercial brand (M = 4.66, SD = 1.61).
The assumption of equal variances in the population has been violated, Levene's F (3, 188) = 3.45, p = .018, thus we may not assume equal variances in the population, we have not met the assumption of homoscedasticity.
Sharing intention. Hypothesis 2 stated that exposure to a storytelling ad with positive emotions has a more positive effect on sharing intention than a storytelling ad with negative emotions. A multivariate analysis of variance was carried out to assess the influence of exposure to storytelling advertisement emotion type (positive/negative) as the independent variable, in conjunction with the interaction effect of source type (commercial/non-profit), on the dependent variable sharing intention. There was a non-significant main effect of emotion type on sharing intention, F(1, 188) = 0.00, p = .992, so H2 was rejected. There were no significant differences in the mean scores of participants who had seen the positive emotion video (M = 4.78, SD = 1.78) compared to those who had seen the negative emotion video (M = 4.75, SD = 1.64) on sharing intentions. No effects of emotions on sharing intentions.
Furthermore, H4 stated the interaction effect, such as the effect of a storytelling ad with positive emotions on sharing intention is more positive for a non-profit organization ad than for a commercial brand ad. Even though the results indicated in the predicted direction, there was no significant interaction effect on sharing intention in the non-profit condition (M = 5.18, SD = 1.59) compared to the commercial brand (M = 4.33, SD = 1.73), the interaction effect was not significant, F (1, 188) = 0.13, p = .718, so H4 is rejected. No interaction effects of source and emotion on sharing intention.
In addition, there was a significant but weak to moderate main effect for source type on sharing intention, as F(1, 188) = 12.57, p < .001, Eta-squared = .06, but this was not in the
theoretical construct. Participants have a higher sharing intention when the source comes from a non-profit (M = 5.18, SD = 1.59) than a commercial brand (M = 4.33, SD = 1.73).
The assumption of equal variances in the population has not been violated, Levene's F (3, 188) = 0.91, p = .435, thus we can assume equal variances in the population, we have met the assumption of homoscedasticity.
Conclusion and Discussion
This research aimed to answer what are the effects of emotional (positive, negative) storytelling advertising on brand attitudes and sharing intentions with the moderating role of source (commercial brand versus non-profit organization). Consequently, the purpose of the study was threefold. First, it aimed at gaining more insights into the effects of emotions in advertising and to close a gap in the academic field addressed in previous literature. Second, it examined under which conditions these effects occur by focusing on two categories of emotions: storytelling ads with positive emotions versus negative emotions. Third, it intended to clarify the processes underlying the effects of source after message exposure, while it investigated the main differences between commercial brands versus non-profit organizations. This research did not find a significant main effect of type of emotion in a storytelling advertisement on brand
attitudes and sharing intentions. Also, no significant interaction effect between emotion type and source type on brand attitudes and sharing intention.
With regards to the first and second hypothesis, the results showed there was no
significant effect of emotion type on the dependent variables (sharing intention, brand attitudes). However, past research showed negative emotions in an advertisement could lead to a positive
evaluations, and a more positive brand attitude (Deborah & Nicole, 2009). This could have been the case in this study since the values did not vary. This is proven by the Chi-square test
regarding the manipulation check of the emotion effect, where 41 participants, out of 96, perceived the negative emotional video as positive (see figure 1). The narrative transportation theory (Green & Brock, 2000) presented in this research could explain this since consumers were drowned into the story, cultivating fewer negative thoughts and a more positive emotional
response to the story. Consequently, the narrative empathy effect (Keen, 2006) could have raised the receiver’s empathy towards the little girl standing with Santa Claus in the negative emotional video. Both effects could have changed how people perceived the negative emotions, turning it into something positive, or relating to the story since the brand/organization proposed to take the girl home to her parents.
Besides that, Laros and Steenkamp (2005) stated positive/negative dimensions were the most popular conceptualizations by keeping the model simple and being a good indicator of one’s attitude. This was a perfect fit for this study since we measured attitudes. However, since the hierarchical study is from 2005, there could have been other ways to compare specific emotions, which could explain the lack of significant results. The disadvantages of the
positive/negative dimensions approach are that important distinctions among different emotions disappear (Lerner & Keltner, 2000), and more precise information about the way consumers feel is lost (Laros & Steenkamp, 2005). Therefore, the theoretical concepts present in this study are still valid, as emotions play a significant role in advertisement. Important distinctions between emotions, such as fear versus happiness, should be considered in future research when
Concerning the third and fourth hypothesis, regarding the interaction effects on sharing intention and brand attitudes, both were nonsignificant. The interaction effect could have been affected by the lack of precise isolation of positive versus negative emotion. Huang (2001) argued the presence of positive emotion does not exclude the absence of negative. As seen above, this could have played a significant role into the non significant interaction effects since both emotions can co-occur. However, there was a non-expected significant main effect of source on sharing intention and on brand attitudes, which demonstrated source type does play an important persuasive role. The participants were more willing to share videos and had higher positive attitudes coming from a source they trust, the non-profit organization. This unexpected significant result makes the argumentation regarding the isolation of emotions even stronger. Consequently, this data reinforces the source credibility model, proposed by Hovland and Weiss (1951), which stated the viewer recognized the intent of the endorser, and could have realized the information from the commercial brand could have been manipulated.
Finally, emotions are a complex variable to manipulate since it’s personal, but the results are reliable, replicable and have high external validity due to the similar real-world aspect of the stimulus material. Internal validity was lower, as emotions showed the difficulty to find reliable videos excluding one emotion from another, to make validity causal claims. This reinforces what Bessarabova, Turner, Fink, and Blustein (2015) point out: Negative emotion is counterproductive in consumer marketing and it’s difficult to achieve the desired results. Therefore, reinforcing Festinger (1962) argument: Negative emotion may induce peoples’ cognitive dissonance, which can lead to individual tension. In other words, the participant can react in different ways, such as
rejecting the message, explaining away, or avoid receiving the new information, which could have played a significant role in this study.
Limitations and future research
The use of real industry videos helped to increase the external validity of this study. Internal validity was also high, since the stimulus material had the same exact time duration during exposure. However, internal validity was hurt since the participants were at home, not a lab, which, on the other hand, increased the external validity with the real-world setting. Moreover, the sample was not evenly distributed, as the approach was a convenience sample. Additionally, even though the sample was widely diverse with participants from Europe and Americas, which increased the external validity, these nationalities and the highly educated level of participants are not a real representation of the world population, so ecological validity was lower. Future research could invest on a non-convenience sample including more nationalities and lower educated people to increase even more the validity of the results.
Another limitation was the unipolar dimension of emotion similar to the argumentation present in previous studies (Aaker et al., 1986; Edell & Burke, 1987; Westbrook, 1987; Nyer, 1997). The results emphasized the theoretical idea presented in this research questioning the bipolar affective dimension of positive and negative emotions as merely two opposites.
Moreover, the results confirm the theoretical line proposed by Huang (2001), mentioning a dual unipolar affective dimension for emotion in marketing, where both emotions could happen during a campaign and could co-occur. Emotions can’t be a binary option, as they are not extreme opposites, as this research shows. It is quite hard to eliminate and isolate an emotion from another one. This approach shows the challenges while manipulating and excluding one of
the emotions from the conditions, in order to make a reliable comparison. Many people
perceived the negative video as a positive one, with emotions co-occurring. This shows emotions are really personal, making it hard to manipulate. Future research should focus on stimulus materials that really exclude one emotion from another. One option could be a creation of an emotional advertisement with a specific storyline, same characters, actors and different brand logos. The difference could be to isolating the negative emotion from the positive by changing the final end of the same storyline. This could have been done in this research in case of extra funds and high sophisticated design materials.
Additionally, Nelson-Field, Riebe and Newstead (2013) argued that it is easier to develop low emotional strength materials than emotionally evocative. Zheng (2020, pg. 14) argued that “it is necessary to ensure enough emotional strength so that the advertisement has the
opportunity to attract consumers’ attention and emotional resonance”. Additionally, the strength of an audience’s emotional reaction could affect sharing intentions (Brown et al., 2010; Porter & Golan, 2006). Future research should focus on the mediating role of emotion strength, measured in an extensive list of emotions and values. The emotional advertisement effects would be mediated by the strength of the emotion felt, resulting in a higher or lower effect of emotions on the dependent variable. This is a big gap for future research. There was no data in the current study to know exactly how deeply people felt each emotion, or the strength of it to make assumptions.
Finally, despite the nonsignificant results, this study had no funds for sampling and materials. Still, the current research was able to reach a wide variety of age, ethnicity and gender of participants. Additionally, it had reliable measurements and valid manipulated materials. It
extended research into the persuasive knowledge domain, and it has challenged existing theories with a really complex and evergoing subject in human research: emotions. Besides, the present study was bold and audacious in this approach, dealing with a variety of research fields: Communication, advertisement, marketing, neuroscience, psychology, and human behavior.
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Figure 1.
Table 1
Source type
Emotion Type Commercial Brand Non-profit organization
Positive Condition 1 Condition 2
Appendix Appendix A
Appendix E
Appendix H
