Advertising creativity: Its influence on media response states towards the Hierarchy of effects

Abstract

The study investigates the influence of Advertising Creativity (AC) on Ad effectiveness in the context of Interactive Digital Media (IDM). The inquiry seeks to bridge a somewhat limited regard for AC in the context of IDM and provide insight into AC's place in audience communication processes as opposed to generally outcome-based perspectives. The study extends the process of AC effects towards the stages of the Hierarchy of Effects (HOE) by the inclusion of conditional media effects and media response states, which are major components of the Differential Susceptibility to Media Effects Model (DSMM), to elucidate dynamic audience processes especially in the context of interactive media. This study was limited to Filipino Millennials (born between 1980 and 1994) residing in the National Capital Region (NCR), Philippines. Data was collected from 326 respondents through a questionnaire survey, with PLS-SEM utilized for the analysis. The results show that AC effects occur through engaging immediate responses as manifested by the media response states at the time of exposure to ad stimuli rather than moderating relationships between conditional and response media effects, positively influencing all HOE stages. However, the strengths of these effects vary, with stages related to experiential responses such as Awareness, Learning/Memory, and Brand Liking reflecting more practical implications compared to more rationally involved HOE stages of accepting or rejecting ad claims and brand intentions. By its very nature, advertising is designed to disrupt original motivations and activities. Furthermore, media response is immediate upon introducing AC stimuli despite conditional dispositions. These results provide potential practical use in campaign development and conceptualization related to consumer demographics, as customized ad outputs addressing different audience traits or motivations can equate to higher production costs. Awareness, memory, and brand liking are posited to benefit the most from AC, allowing for better allocation of resources when developing outputs throughout campaigns. The study provides a practical view of AC's benefits to specific HOE stages enabling advertisers to develop strategies given the value and limitations of AC within integrated marketing campaigns keeping us abreast with the dynamic consumer processing of ad communications constantly developing in line with emerging media technology.

1. Introduction

Advertising Creativity (AC) has primarily enjoyed a place of centrality concerning determining advertising effectiveness [1,2,3]. This study focuses on the influence of AC on consumer behavior processes via the Hierarchy of Effects (HOE) towards the Ad and Brand responses in the context of emerging dynamic characteristics of interactive digital media. AC significantly stimulates positive consumer responses and has more substantial effects in high-involvement contexts [2]. This brings into question the expected effects of AC on consumer responses in contexts where the focus is often directed at other focal tasks [4] and unlikely to pay attention to and process ads, such as that of Interactive Digital Media (IDM) [5]. Given that the direction of the study is guided by effects, constructs, and mechanisms inherent in IDM, it is pertinent to include media communication effects and their role in ad processing. The understanding of the practical benefits or limitations of AC in the development of campaigns can provide industry professionals insights to take into consideration given brand objectives, resource allocation, and communication strategy.

Despite the popular notion of the role of creativity in determining effectiveness, there is still a noted limitation in the literature on creativity regarding the role of audience characteristics on consumer responses and the rapidly changing media landscape [3]. There is a need for further studies which involve the new dynamics of advertising processes in the context of emerging technological media situations, specifically IDM, and its effects on consumers. These dynamics, which include (a) new media and formats, (b) new consumer behaviors, and (c) extended effects of advertising [6], considered with AC is of significant consequence to inform our understanding of Advertising in today's inter-connected, computer-mediated, sphere of activity. Media studies in the age of new media technologies have generally been driven by the creation of knowledge towards understanding new human processes of perception, interpretation, and creation, which occur interactively with its characteristics. The primary motivations for IDM usage are highly personal-facilitating relationships, status-seeking, comparing oneself to idealized role models the desire for easily accessible, curated, and personalized entertainment [7], with digital advertising commonly seen as a distraction to primary intentions. Media communication research needs to keep abreast with new IDM technologies, highlighting possible effects on the cognitive processing of information [8]. The question of what effects can be expected in IDM contexts calls for further investigation. The current study seeks to address the following:

RQ₁ When and how does AC significantly affect Ad effectiveness as observed through HOE?

RQ₂ Does AC significantly affect media responses towards interactive digital ads?

RQ₃ Do responses in using IDM as affected by AC subsequently affect the levels of HOE?

RQ₄ In what stages of the HOE would the effects of AC be apparent?

The objective is to explore the influence of AC in the new dynamics of digital media and changing consumer behaviors. When and how does AC work in IDM considering media effects, and whether these contribute to consumer processing, ultimately leading to Ad effectiveness?

1.1. Review of related literature

1.1.1. Interactive Digital Media

Interactive Digital Media (IDM), driven by the digital component, affords easier production, duplication, and transmission differentiating it from traditional media. IDM as new digital media affords demassification, interactivity, and synchronicity [9] and has proven to enhance the effects of advertising at a phenomenal reduction of cost [9]. The ever-changing facets of technological characteristics, mediated by innovation and driven by competition, necessitate the continuous study of phenomena that emerge in their wake. Most apparent for advertising is the evolving consumer behaviors in this context [10]. This study recognizes digital ads as brand-initiated content distributed via networks such as the Internet to computer devices to reach and impact the audience. IDM and the Internet's unique aspect is interactivity with computer networks as bi-directional and addressable [11,12], thereby providing significant affordances to audiences.

1.1.2. Advertising creativity

There have generally been four approaches in empirically regarding AC: (1) a holistic perception of the creativity of an ad, (2) a single dimension regard of AC in the form of originality, (3) a bipartite assessment of AC through originality and appropriateness, and (4) the extension of the bipartite assessment combined with an additional dimension, often artistic value or production quality of the output [2]. The bipartite view presents AC as being (1) divergent, implying uniqueness, novelty, and originality; and (2) relevant, which grounds the view of AC as a function towards advertising's strategic goals as part of the marketing mix. Five factors account for divergence being achieved in advertising: (1) Originality, (2) Flexibility, (3) Elaboration, (4) Synthesis, and (5) Artistic Value [13]. Relevance connects the ad with brand strategy and consumer problem-solving abilities and goals [2]. Ads deemed appropriate are those seen as having a high level of fit and practicality as understood by consumers and how on-strategy the idea of the ad is [2].

1.1.3. The Hierarchy of effects

The Hierarchy of Effects (HOE) model reveals a systematic response process in individuals of which sequential stages may be culled for closer examination serving as a relevant model for describing the stages consumers go through when forming brand intentions and attitudes [5,13]. All HOE models share common characteristics, such as that they can be reduced into three broad stages: Cognitive, Affective, and Behavioral [14,15]. The current study is guided by Smith et al.'s (2008) five-stage HOE process, which was specifically developed for use in the context of AC to determine AC effectiveness:

Stage 1: Building brand awareness. As the first goal of advertising in HOE models, this stage is achieved by gaining consumer attention and interest, enabling cognitive resources to process the ad and the brand [16]. Brand awareness is instigated by attention and interest when consumers first encounter the ad. Stage 2: Learning and remembering ad claims. Ads associate brands with positive traits and dissociate them from negative traits. Upon exposure, consumers learn these associations and are represented in memory as brand-related beliefs. This learning stage suggests that consumer understanding or processing of ad claims at a deeper level makes claims more memorable [13]. Stage 3: Accepting/rejecting ad claims involves whether the information in ads is acknowledged or otherwise rejected by consumers in the context of the information's relation to their existing beliefs and values [13]. Persuasion is initially challenging as consumers are known to discount vested interest sources regarding ads [17]. AC may counteract this by providing positive experiences such as entertainment. Stage 4: Brand Liking. Brand preference is affected by a primary precursor of favorable consumer attitudes toward the brand as influenced by perceived entertainment value or affect transferred from more favorable ad attitudes [18]. Stage 5: Brand Intentions. Representing where the consumer moves from liking a brand to preference, brand intentions include the intent to recommend the advertised brand and the intent to purchase, with prior stages of the HOE working as a funnel for this to take effect. Creative ads produce high levels of liking and purchase interest, positively affecting brand attitudes and purchase intentions [19,20,10].

1.1.4. Media motivations, gratifications, and susceptibility

Various models and theories have been developed to investigate individual processes in media contexts. One such is the Uses & Gratifications Theory (UGT), from which several contemporary models have taken inspiration. The principal objectives of UGT inquiry include (1) an explanation of how people use media to gratify needs, (2) understanding the motives of media behavior, and (3) identifying functions or consequences that follow from needs, motives, and behaviors [21]. Built upon earlier individual-level media effects theories such as that of UGT, The Differential Susceptibility to Media Effects Model (DSMM) is a micro-level effect theory that bases its inferences on observations of individual users [22]. The media effects focused on within this model are referred to as the within-person modifications in cognitions, emotions, attitudes, beliefs, physiology, and behavior as consequences of media use, both short and long-term [22]. DSMM emphasizes two global features of media effects, of which the various theories can be categorized as Conditional Media Effects or Transactional Media Effects [23]. DSMM infers four related propositions [22]: (1) that media effects are conditional, (2) Media effects are indirect, (3) The differential-susceptibility variables have two roles; they act as predictors of media use and as moderators of the effect of media use on media response states, and (4) Media effects are transactional; they influence not only media use, but also the media response states, and differential-susceptibility variables. DSMM assumptions explain why some individuals are more susceptible to media effects than others, how and why media influence individuals, and how media effects can be enhanced or counteracted [22].

1.1.5. Conditional media effects: dispositional

Need for Cognition (NFC) reflects the extent individuals are more likely inclined towards effortful cognitive activities, which are seen as a moderator of media effects [22] and seen as a determinant of the type of messaging processing. Affective Empathy (AE). Affective empathy has been proposed to explain differences in individuals' responses to media content, with individuals high in trait affective empathy being more likely to experience state emotional responses [24]. Sensation Seeking (SS) is defined as “the seeking of varied, novel, complex and intense sensations and experiences, and the willingness to take physical, social, legal and financial risk for the sake of such experience” [24].

1.1.6. Transactional Media Effects: media response states

DSMM proposes that media effects are indirect, with the relationship between media use and media effects mediated by three response states, Cognitive, Emotional, and Excitative, originating from media use. Cognitive Response State (CRS) is based on the extent to which individuals, while using media, selectively attend to and invest cognitive faculties and efforts to understand and comprehend the content received [24,22]. Emotional Response State (ERS) refers to the experiential part of emotion as affected by internal or external stimuli. The DSMM places the emotional response rate as a state which encompasses all affectively-valenced reactions to media content (message, storyline, and vicarious affective reactions). Excitative Response State (EXRS) refers to the degree of physiological stimulation or arousal, such as activating the sympathetic nervous system in response to media [22]. This physiological arousal response significantly affects emotional processing; hence, it is an integral part of emotional responses.

The DSMM provides a framework for investigating not only the motivators or the effects or gratifications experienced by individuals in their media use but also considering the content they receive and how it may add to subsequent audience processes. Media and content choices of individuals are generally rational and directed toward specific goals and satisfactions [25,26]. Individuals consider specific needs regarding their media consumption [21], which can be addressed through content gratification. In determining the uses and gratifications of the Internet, Stafford et al. (2004) provide two general types, one of which is content gratification. It has been argued that knowing how a user came to a medium is less critical than understanding how the medium can hold the user [27,28]. Media properties as predictors involve the properties of media manifested through modality, content, and structural properties [23]. This feature is incredibly reliant on the content of the media, and in the case of advertising, AC weaved into the production and communication of the brand message.

1.2. Research framework

The study's framework has been developed from theoretical models regarding consumer behavior in advertising (HOE) and media communication (DSMM). This investigation considers concepts inherent in media communication studies, such as conditional media effects and the media response states, indicating the effects and audience processes upon ad exposure through IDM. The study hypothesizes that along this ad processing route via IDM, AC moderates transactional or response states of audiences, which may reflect on the stages of HOE. The operational framework (Fig. 1) illustrates that the hypotheses seek to find the effects AC as media use may have on the interaction between conditional media effects and media response effects. The paths indicate the testing of the influence of AC between these media effects and their sub-constructs towards the HOE. To identify when and where AC influences IDM effects, the measurement of the three sub-constructs of media Response states and their outcome interaction towards the different stages of the HOE will be made.

Fig. 1.

Operational framework.

1.3. Hypotheses

H₁–H₃:Advertising Creativity (AC) will positively moderate the relationship between Conditional Media Effects and Media Response State Effects.H₁, H₂, and H₃ propose that AC will have a positive moderating effect on the relationship between the Conditional media effects of the Need for Cognition (NFC), Sensation-Seeking (SS), and Affective Empathy (AE) to the Transactional media effects of Cognitive Response State (CRS), Emotional Response State (ERS), and Excitative Response State (EXRS). By positioning AC as a moderator, these hypotheses propose that audience response towards media is predicted by their conditional media effects with the relationship positively strengthened by AC. The response states can be seen as gratifications of the conditional states, which from a transactional effect perspective, places audiences in a favorable position to process brand messages and likely lead to ad effectiveness.

H1

AC will positively moderate the relationship between Need for Cognition (NFC) and Cognitive Response State (CRS). When consumers are exposed to AC, the effect of their NFC on CRS will be positively strengthened, compounding towards HOE. An individual who has a high level of NFC finds satisfaction in deliberating hard and for long hours, prefers complex to simple problems, and generally like doing things that require challenging their thinking abilities [29,30], which is related to their CRS towards stimuli on whether this need is gratified. This gratification places consumers in a more conducive state for the HOE stages to manifest. AC aligning with cognition is hypothesized to strengthen this relationship positively.

H2

AC will positively moderate the relationship between Sensation Seeking (SS) and Excitative Response State (EXRS). Sensation Seeking in individuals was found as a significant predictor and mediator of multitasking with media [31,32]; therefore, unfocused activity while engaged in digital media also indicates that users spend more time engaged in the media itself and that creative content leads to excitative responses which orient their attention to ad messages.

H3

AC will positively moderate the relationship between Affective Empathy (AE) and Emotional Response State (ERS). The appraisal of the ad stimuli and whether it elicits an emotional response is based on the cognition of the content of ad messages perceived as relevant to an individual's goals [33]. These conceptions may lead to arguments that emotional responses to ads may be highly subjective, undermining AC as the emotion elicited is evaluated or disregarded depending on the audience's preference in emotional experience [18]. found that emotion, which they construct as Positive Affect, was stimulated by exposure to creative ads.

Media Response States, as directly influenced by AC, will have significant and positive effects on the different stages of the HOE.

AC and HOE Stage 1: Awareness. AC is frequently linked to increased attention and interest [2]. Creative ads bring about a 'contrasting' effect, enabling them to stand out amongst the various clutter, attracting more attention [2,18] and holding it long enough for awareness to take. Attracting consumers' attention enables orienting cognitive resources toward processing [2]. Thus, it is hypothesized in this study that AC may lead to increased awareness.

H4

CRS will have a significant and positive relationship with HOE1.

H9

EXRS will have a significant and positive relationship with HOE1.

H14

ERS will have a significant and positive relationship with HOE1.

AC and HOE Stage 2 Learning and Remembering Ad Claims. The depth of consumer processing influences learning and memory regarding ad claims [34]. Creative ads are posited to attract higher levels of attention and interest which should facilitate a more careful understanding of the ad's claims [18].

H5

CRS will have a significant and positive relationship with HOE2.

H10

EXRS will have a significant and positive relationship with HOE2.

H15

ERS will have a significant and positive relationship with HOE2.

AC and HOE Stage 3: Accepting and Rejecting Ad Claims. A stage that may end the consumer journey may be a 'yielding' stage or acceptance of ad claims. As correlations between retention of message content and persuasion are typically low, this suggests that the cognitive reactions of consumers to the ad message (in the form of primary thoughts) were more significant to persuasion than merely learning ad claims [18]. These cognitive responses may be effectively guided to more favorable responses through AC as creative ads trigger consumers' sense-making equipment. This concept may be related to Need for Cognitive Closure (NCC), which refers to an individual's aversion to ambiguity and desire for firm answers to a question [18]. Because of its divergent nature, AC helps hold this curiosity regarding ads and creates open-mindedness, leading to lower levels of NCC towards favorable evaluation or acceptance of ad claims [18].

H6

CRS will have a significant and positive relationship with HOE3.

H11

EXRS will have a significant and positive relationship with HOE3.

H16

ERS will have a significant and positive relationship with HOE3.

AC and HOE Stage 4: Brand Liking. The affect transfer model states that in the context of AC, consumers' positive experience with output transfers to the brand and, therefore, brand liking. This suggests the role of AC in creating a positive experience for consumers to like the ad, which leads to a favorable evaluation of the brand [2]. Affective reactions play a major role in persuasion [18]. Through AC, ads are deemed more entertaining, increasing the probability of positive attitudes toward the ad and, subsequently, attitudes toward the brand.

H7

CRS will have a significant and positive relationship with HOE4.

H12

EXRS will have a significant and positive relationship with HOE4.

H17

ERS will have a significant and positive relationship with HOE4.

AC and HOE Stage 5: Brand Intention. This final stage of the HOE refers to the intent to recommend or intent to purchase the advertised brand and is highly dependent on the prior stages working as a funnel to take effect. Creative ads also produce high levels of liking and purchase interest, positively affecting brand attitudes and purchase intentions [19,20,35]. AC has been argued to signal product quality among consumers affecting quality perceptions and influencing brand intention [36].

H8

CRS will have a significant and positive relationship with HOE5.

H13

EXRS will have a significant and positive relationship with HOE5.

H18

ERS will have a significant and positive relationship with HO5.

2. Methodology

Following informed consent and age requirements limiting participants to be over 18 years of age, data was gathered from a cross-section of Filipino consumers residing in the National Capital Region (NCR) of the Philippines belonging to Generation Y. These are those born between 1980 and 1994 and are currently in the age range of 28–42. Gen. Y is numbered 25 million in the Philippines and is considered one of the largest generations in history, moving into its prime spending years.

To identify appropriate Ad stimuli, interviews were conducted with industry professionals consisting of copywriters, creative directors, chief creative officers, and chief executive officers. The key informants had an average of 25 years of experience in advertising. The KII recommendations are as follows:

• 1.Include outputs proven to have exhibited high AC regardless of product involvement category.
• 2.It would be appropriate to base ad stimuli on award-giving organizations' winners' lists.
• 3.The perspective of the target is critical in determining the AC level of ad outputs.

A self-report survey followed informed consent requirements and was limited to the specific generational cohort over 18 years old. To measure AC levels of 10 shortlisted video ads. The highest-scoring ad garnered a Divergence score of (4.54), a Relevance score of (4.38), and a total average score of (4.46) for AC. The 2-min video ad amassed 21 million views within two weeks of its release, garnered 98 million impressions, and has received numerous industry accolades.

AC measurement was guided by Smith et al. (2007) regarding the determinants and effects of creativity in advertising consisting of items for the bipartite dimensions of Divergence (flexibility, originality, synthesis, elaboration, and artistic value) and Relevance (ad to the consumer, brand to consumer, and ad to brand). The measurement of consumer responses through HOE is based on Smith et al. (2008) [13], culled from various works: MacInnis and Jaworski (1989) [34], Burke and Scrull (1988), Yang (2006), Ducoffe (1996), Smith et al. (2007) [16], and Smith and Swinyard (1983). Conditional and response effect states were assessed following a self-report survey method by Piotrowski and Fikkers (2020).

2.1. Sampling & statistical Treatment of data

The study employed a non-probability sampling method via a convenience sampling technique, with the survey disseminated to different NCR cities selected using random sampling via the fishbowl method. The online survey included a link to the Ad stimuli participants were to view and evaluate. A total of 384 responses were gathered and subjected to data cleansing before analysis. Investigation of response patterns and the detection of outliers (via statistical chart box and whisker function of Excel) was conducted. 39 responses were removed from the dataset bringing the final count of cases to 332 for analysis. The study utilized Partial Least Squares- Structural Equation Modeling (PLS-SEM) to elucidate relationships between the various variables of the model. PLS-SEM allows for the comparison between multiple response and explanatory variables [37], providing the researcher necessary understanding of the relationships between variables towards the development of appropriate recommendations for management.

3. Results

3.1. Measurement model evaluation internal consistency & convergent validity

Convergent validity was evaluated by considering the outer loadings and the Average Variance Extracted (AVE). An AVE value of at least 0.50 is recommended to indicate sufficient convergent validity [37]. The reliability and coefficient results are reported below (Table 1).

Table 1.

Reliability and validity coefficients.

Latent Variable	Cronbach α	CR (rho_a)	CR (rho_c)	AVE
AC	0.922	0.926	0.935	0.567
NFC	0.723	0.739	0.823	0.538
AE	0.777	0.787	0.848	0.520
SS	0.753	0.805	0.830	0.500
CRS	0.744	1.016	0.835	0.633
ERS	0.908	0.908	0.942	0.844
EXRS	0.912	0.914	0.939	0.793
HOE 1	0.844	0.857	0.889	0.618
HOE 2	0.930	0.933	0.942	0.671
HOE 3	0.938	0.941	0.948	0.668
HOE 4	0.938	0.941	0.950	0.732
HOE 5	0.904	0.905	0.954	0.913

The statements indicating the various constructs within the final model were evaluated for acceptable values for internal consistency through the assessment of Composite Reliability (rho_a & rho_c) and Cronbach's Alpha values. All statements yielded satisfactory composite reliability scores except for the CRS construct (rho_a = 1.016), which was over the acceptable threshold for internal consistency. Composite reliability values above 0.95, such as that for rho_a (Table 1), are generally undesirable [37]. However, these values occur when semantically redundant items exist [37]. Composite reliability is inclined to overvalue and indicates higher reliability approximations [37]. Rho _a is an alternative basis of reliability assessment as the more common criteria for measuring a construct's reliability is through Cronbach Alpha and rho_c [37], which both range from 0 to 1, and both have values over 0.70 as required for composite reliability of a construct [38]. The statements for the constructs yielded good internal consistency with Cronbach's alpha values above 0.70 (Table 1). All statements yielded sufficient value to indicate convergent validity, as all AVE values had values of at least 0.50 and above [37], indicating that, on average, the construct explains more than half of the variance of its indicators [37].

3.2. Discriminant validity

Cross-loading results of the indicators for each construct show that the various indicators’ outer loadings are higher than any other indicator on constructs it intends to measure. In terms of the Heterotrait-Monotrait Ratio (HTMT), almost all constructs have values (Table 2) lower than 0.85 (as recommended by Hair et al., 2017 as conservative) except for HOE1-EXRS (0.897) and HOE2-HOE1 (0.878). While the threshold of 0.85 is generally suggested, for conceptually similar constructs, the threshold may be adjusted to 0.90 [37]. The constructs in question, HOE1, HOE2, and EXRS, have some conceptual similarities, given that the three constructs are related to concepts of interest, attention, and arousal. Thus, the HTMT ratio values still fall below the threshold of 0.90 for conceptually similar constructs; therefore, discriminant validity is satisfied.

Table 2.

Discriminant validity heterotrait-monotrait ratio (HTMT).

	AC	AE	CRS	ERS	EXRS	HOE1	HOE2	HOE3	HOE4	HOE5	NFC	SS
AC
AE	0.203
CRS	0.379	0.204
ERS	0.762	0.289	0.445
EXRS	0.785	0.211	0.561	0.838
HOE 1	0.819	0.232	0.655	0.829	0.897
HOE 2	0.763	0.216	0.36	0.711	0.754	0.878
HOE 3	0.715	0.305	0.32	0.594	0.646	0.757	0.759
HOE 4	0.713	0.228	0.417	0.826	0.8	0.844	0.815	0.663
HOE 5	0.697	0.168	0.195	0.515	0.588	0.634	0.69	0.798	0.615
NFC	0.111	0.125	0.129	0.129	0.145	0.162	0.149	0.104	0.212	0.064
SS	0.19	0.156	0.144	0.125	0.207	0.189	0.167	0.207	0.146	0.087	0.243

PLS-SEM Structural Model Assessment.

All Variance Inflation factor (VIF) values fall below the recommended [37] threshold of 5.0 and are above 0.20, thus satisfying collinearity requirements (Table 3). Model fitting has yet to be widely accepted for use in PLS-SEM; as such, an alternative method for assessment can be utilized by considering R² values [37].The R² values for variables in the current model range from 0.15 to 0.71 (Table 4). For research that focuses on marketing issues, it is recommended that R² values of 0.75, 0.50, or 0.25 for endogenous variables can be respectively described as substantial, moderate, or weak. In the context of consumer behavior, an R² value of 0.20 is considered high [37]. R² values between 0.10 and 0.50 are good if most explanatory variables are statistically significant [39]. Given these considerations, the current R² values are acceptable.

Table 3.

Testing Collinearity among constructs- Inner VIF Values.

	CRS	ERS	EXRS	HOE1	HOE2	HOE3	HOE4	HOE5
AC	1.02	1.050	1.033
AE		1.034
CRS				1.427	1.427	1.427	1.427	1.427
ERS				2.399	2.399	2.399	2.399	2.399
EXRS				2.729	2.729	2.729	2.729	2.729
HOE 1
HOE 2
HOE 3
HOE 4
HOE 5
NFC	1.005
SS			1.033
AC x SS			1.011
AC x NFC	1.019
AC x AE		1.018

Table 4.

Coefficient of determination (R²).

	R-square	R-square adjusted
Cognitive Response State	0.158	0.15
Emotional Response State	0.512	0.508
Excitative Response State	0.537	0.532
HOE Stage 1	0.711	0.709
HOE Stage 2	0.527	0.522
HOE Stage 3	0.388	0.382
HOE Stage 4	0.641	0.638
HOE Stage 5	0.306	0.299

The path diagram and PLS estimations are shown below (Fig. 2) to give a visual representation of the interrelated variables and causal flow. Relevant values are supplied to highlight important relationships for context when particular findings in line with the hypotheses to be discussed.

Fig. 2.

Path Diagram and PLS Estimations

Note. Dashed lines represent insignificant paths, and continuous lines represent significant paths. Significance level (*p < .05, **p < .01, ***p < .001).

3.2.1. Respondent profile

The respondents (n = 332) were comprised of (52%) female and (48%) male Filipino consumers, with an average age of 32.2 (SD = 3.84). In terms of age group distribution, most respondents belonged to the 28 years and less than 31 age group (45%), followed by 31 years and less than 35 (26%), 35 years and less than 39 (21%), and finally, 39 years and less than 43 years of age (7%). The majority of the respondents represented the lower to upper middle class (45%), with the rest distributed among other income classes. Most of the respondents (98.19%) have attained at least a bachelor's degree or equivalent (n = 326). Respondents are reported to have above average to high conditional media effects of NFC (M = 3.88, SD = 0.33) and SS (M = 3.73, SD = 0.46) before stimulus exposure while scoring neutral for AE (M = 3.38, SD = 0.04). Most found the stimulus highly creative (M = 3.92, SD = 0.27). For media response states, most agreed to have these responses engaged: CRS (M = 3.76, SD = 0.25), EXRS (M = 3.86, SD = 0.16), and ERS (M = 4.02, SD = 0.17). For HOE stages, results show the stages of awareness (M = 3.79, SD = 0.34), learning and remembering ad claims (M = 3.74, SD = 0.20), brand liking (M = 4.07, SD = 0.23), and brand intentions (M = 3.46, SD = 0.01) were engaged across the majority with only accepting or rejecting ad claims stage emerging with neutral (M = 3.27, SD = 0.20) responses.

RQ 1

When and how does AC significantly affect Ad effectiveness as observed through the HOE?

RQ 2

Does AC significantly affect consumer media responses toward interactive digital ads?

To find out when or where AC has a significant effect on the different phases of communication processes towards HOE, the study sought to test where AC would have a significant effect on engaging and positively affecting ad effectiveness. The study's framework outlines that the audience's communication process starts with conditional media effects and, upon the introduction of AC as media use, moves towards media response states which subsequently affects the different indications of ad effectiveness through the various stages of the HOE. H₁, H₂, and H₃ are not supported as overall results (Table 5) show that AC does not have a positive moderating effect on the relationship between Conditional Media Effects and Response Media States. The moderating effect yielded non-significance with all at p > .05. Effect sizes (Table 6) for all hypothesized relationships were interpreted as having no effect regarding AC as a moderating construct towards the various Conditional and Response States as all effect sizes were at f² < 0.009, suggesting that the practical effect of AC happens elsewhere on the communication-ad effectiveness audience processing flow. Effect sizes of 0.005, 0.01, and 0.025 represent small, medium, and large effects in evaluating moderation effect sizes [37]. AC enters the process by its direct effect on the Media Response States, bringing about immediate media effects which consequently influence further stages of the process (HOE stages). This is indicated by the null hypothesis testing results where AC direct effects on the Media Response States of CRS, EXRS, and ERS all yielded statistically significant p-values all at p < .05 (Table 7), with substantial effect sizes for the direct effect of AC on the media response states of CRS (f² = 0.164), EXRS (f² = 1.083), and ERS (f² = 0.919) (Table 6).

RQ3

Does Consumer responses in using Interactive media as affected by Advertising Creativity subsequently affect the levels of the Hierarchy of Effects of Advertising?

To identify whether consumer responses to IDM subsequently affect the stages of ad effectiveness, the various media response states as influenced by AC were tested to see if there were positive and significant relationships with the HOE stages. The results show that the media response states as directly affected by AC have a significant and positive effect on HOE1: Building Brand Awareness. H₄, H₉, and H₁₄ are all supported with respective effect sizes at small (f² = 0.145), medium (f² = 0.249), and small (f² = 0.118). For HOE2 Learning and Remembering Ad claims, H₅ is not supported, while H₁₀ and H₁₅ are supported. The results for Hypotheses 6, 11, & 16 regarding HOE 3: Accepting/Rejecting Ad claims yielded that H₆ is not supported, while H₁₁ and H₁₆ are supported. For HOE4 Brand Liking, H₇ is not supported, while H₁₂ and H₁₇ are both supported. Finally, for HOE5 Brand Intention, the results indicate that H₈ and H₁₈ are not supported while H₁₃ is supported.

RQ 4

In what stages of the Advertising Hierarchy of effects would the effects of Advertising Creativity be apparent? The results show that AC influences all stages of HOE with the most impact on:

• ●HOE1: Awareness through AC's immediate effects on media response state EXRS on HOE1 (β = 0.443, t = 7.562, p < .001) with EXRS constituting a medium effect towards HOE1 (f² = 0.249).
• ●HOE2: Learning and remembering ad claims through AC's immediate effects on media response state EXRS on HOE2: (β = 0.477, t = 6.061, p < .001) with EXRS constituting a medium effect towards HOE2 (f² = 0.176).
• ●HOE4: Brand liking through AC's immediate effects on media response state ERS on HOE4 (β = 0.47, t = 8.287, p < .001) with ERS constituting a medium effect towards HOE4 (f² = 0.256).

Although apparent in all stages, AC effects are overall weaker for HOE stages of:

• ●HOE3: accepting/rejecting ad claims through AC's immediate effects on media response state EXRS on HOE3 (β = 0.442, t = 5.691, p < .001) with EXRS constituting a small effect towards HOE3 (f² = 0.117).
• ●HOE5: brand intention through AC's immediate effects on media response state EXRS on HOE5 (β = 0.489, t = 6.135, p < .001) with EXRS constituting a small effect towards HOE5 (f2 = 0.126).

Through AC's influence on the media response states, results show that all HOE stages are affected. Media response states EXRS and ERS emerge as primarily driving HOE outcomes as influenced by AC. CRS emerges in the study as most weakly affected by AC, subsequently having a diminished influence on HOE stages, with CRS having either no significant positive relationship or no effect on various HOE stages. All but one of the hypotheses concerning the CRS effect on HOE stages as influenced by AC are not supported. In answering RQ4, the results show that AC's effects are apparent in all HOE stages. AC effects have moderate effects on HOE1, HOE2, and HOE4, while AC weakly affects HOE3 and HOE5. While all HOE stages are affected positively, and in an impactful manner, it is most apparent with specific pairings of media response states. Negligible HOE outcomes stemming from AC influence media response states are seen for HOE stages 3 and 5.

Table 5.

Path coefficients and confidence interval.

Hypothesis	ß	M	SD	t	p	95% CI	Decision
Advertising Creativity as Moderator between Conditional Media Effects and Media Response States
H1: AC x NFC - > CRS	0.038	0.029	0.057	0.663	0.508	[-0.071, 0.149]	Not Supported
H2: AC x SS - > EXRS	0.042	0.038	0.035	1.201	0.230	[-0.021, 0.114]	Not Supported
H3: AC x AE - > ERS	0.03	0.026	0.052	0.578	0.563	[-0.061, 0.142]	Not Supported
Hierarchy of Effects Stage 1: Building Brand Awareness
H4: CRS - > HOE1	0.245	0.245	0.037	6.636	0.000	[0.168, 0.312]	Supported
H9: EXRS - > HOE1	0.443	0.444	0.059	7.562	0.000	[0.324, 0.552]	Supported
H14: ERS ->	0.286	0.285	0.051	5.556	0.000	[0.187, 0.387]	Supported
Hierarchy of Effects Stage 2: Learning and Remembering Ad claims
H5: CRS - > HOE2	−0.01	−0.01	0.05	0.208	0.835	[-0.111, 0.086]	Not Supported
H10: EXRS - > HOE2	0.477	0.478	0.079	6.061	0.000	[0.313, 0.622]	Supported
H15: ERS - > HOE2	0.299	0.3	0.069	4.33	0.000	[0.162, 0.435]	Supported
Hierarchy of Effects Stage 3: Accepting/Rejecting Ad Claims
H6: CRS - > HOE3	−0.031	−0.03	0.057	0.544	0.587	[-0.146, 0.078]	Not Supported
H11: EXRS - > HOE3	0.442	0.446	0.078	5.691	0.000	[0.283, 0.586]	Supported
H16: ERS - > HOE3	0.234	0.232	0.076	3.094	0.002	[0.084, 0.378]	Supported
Hierarchy of Effects Stage 4: Brand Liking
H7: CRS - > HOE4	0.004	0.006	0.046	0.089	0.929	[-0.088, 0.091]	Not Supported
H12: EXRS - > HOE4	0.381	0.381	0.063	5.996	0.000	[0.256, 0.503]	Supported
H17: ERS - > HOE4	0.47	0.469	0.057	8.287	0.000	[0.357, 0.578]	Supported
Hierarchy of Effects Stage 5: Brand Intentions
H8: CRS - > HOE5	−0.122	−0.12	0.056	2.18	0.029	[-0.231, −0.012]	Not Supported
H13: EXRS - > HOE5	0.489	0.489	0.08	6.135	0.000	[0.328, 0.641]	Supported
H18: ERS - > HOE5	0.148	0.148	0.085	1.742	0.082	[-0.017, 0.316]	Not Supported

Note. ß= Original Sample, M= Sample Mean, SD= Standard Deviation, t= T-statistics, p= p-value.

Table 6.

Effect Sizes (f²).

	CRS	ERS	EXRS	HOE1	HOE2	HOE3	HOE4	HOE5
AC	0.164	0.919	1.083
CRS				0.145	0	0.001	0	0.015
ERS				0.118	0.079	0.037	0.256	0.013
EXRS				0.249	0.176	0.117	0.148	0.126
NFC	0.009
AE		0.031
SS			0.01
AC x NFC	0.002
AC x AE		0.002
AC x SS			0.004

Note.f² ≥ 0.02, f² ≥ 0.15, and f² ≥ 0.35 represent small, medium, and large effect sizes, respectively.

Table 7.

Advertising creativity and media response states.

	ß	M	SD	t	p	95% CI
Advertising Creativity- > Cognitive Response State	0.376	0.382	0.046	8.182	0.000	[0.272, 0.456]
Advertising Creativity- > Excitative Response State	0.72	0.719	0.026	28.122	0.000	[0.665, 0.766]
Advertising Creativity- Emotional Response State	0.686	0.685	0.033	20.887	0.000	[0.618, 0.745]
Need for Cognition - > Cognitive Response States	0.089	0.103	0.063	1.415	0.157	[-0.201, 0.052]
Sensation Seeking - > Excitative Response States	0.071	0.08	0.037	1.923	0.055	[-0.092, 0.013]
Affective Empathy - > Emotional Response States	0.125	0.128	0.047	2.693	0.007	[-0.034, 0.019]

Note. ß= Original Sample, M= Sample Mean, SD= Standard Deviation, t= T-statistics, p= p-value.

4. Discussion

Advertising Creativity does not moderate the Relationship between Conditional Media Effects and Media Response States. AC effect on Ad effectiveness is initiated via immediate IDM effects at the Media Response Stage.

Studies on effect theories in the context of media entertainment uncover findings that counter the conditional/response relationship. In the context of media entertainment, people expose themselves to content inconsistent with their conditional states [23], which may be linked to selective exposure wherein individuals invest attention to new stimuli which derail original conditional media motivations. AC directly affects audiences at the time of exposure, which can overpower conditional media effects. While direct effects run counter to the technological affordances provided by IDM, the direct effects may be seen as immediate responses to the AC stimuli. Thus, NFC was revealed to be unrelated to CRS as this media response state is largely an outcome of exposure to the attention-grabbing stimuli that is AC. When highly arousing, unique stimuli are received, people tend to latch on to these new cues [23]. EXRS is based on physiological and mental arousal, which is an immediate outcome of stimuli received. Thus, SS was revealed to be unrelated to EXRS as this media response state is largely an outcome of the introduction of AC. The structural properties of media trigger an orienting reflex that instigates selective exposure [23], which is accompanied by stimulus-driven or transient attention [23]. Conditional media effects may have significance in the media use of individuals driven by their motivations. The introduction of AC to their IDM experience does not further these original intentions but initiate new responses. Results indicate that the conditional media effect of AE was unrelated to ERS as this media response state is, again, an outcome of the introduction of AC. In principle, advertising's main goal is to attract consumers' attention through the interruption of their activities, regardless of dispositions. By gaining attention and interest, creative ads arrest the original motivations of the IDM experience and institute immediate effects towards the ad stimuli at the moment of the experience, creating responses that may not have been initially aligned with the conditional dispositions of individuals when first engaging in IDM.

All Consumer responses in using IDM as affected by AC affect the levels of the HOE. These responses as uncovered, however, indicated varying effect strengths across HOE stages, revealing that not all pairings of media responses and HOE stages may be practical. Different consumer response dimensions will usually be more fitted to and appear at specific stages of the HOE. HOE Stage 1 is primarily affected by the media response state of EXRS with a medium effect followed by CRS and ERS with small effects for each. HOE Stage 2 is primarily affected by the media response state of EXRS with a medium effect followed by ERS with a small effect.

HOE Stages 1: awareness and 2: learning and remembering ad claims are stages dependent on the arousal, interest, and attention responses to ad messages as brought about by AC. Linked to increased attention and interest [2,16,18], AC brings about a 'contrasting' effect enabling ads to stand out and attract more attention, holding it long enough for awareness and learning to take. This is in line with the HOE stages, which involve attracting consumers' attention to enable their orienting cognitive resources toward processing [18]. HOE stages which revolve around attention, learning, memory, and subsequent evaluation, are largely influenced by engagement through heightened interest and arousal toward stimuli. The consumer response of learning and remembering ad claims refer to the ads associating brands with positively valued traits. As brands are more associated with positive traits as evaluated by consumers, the more favorably disposed the consumers will be toward purchase [35,18]. Emotions influence the selectivity of attention, motivating action and behavior, facilitating encoding and retrieval of information [40] and providing a conducive context to learning and retention of information. AC's ability to engage cognitive, emotional, and, more significantly, excitative responses enables the ad message to stand out from other ads, and involve the consumer more, positively affecting HOE1 and HOE2. The study identifies the HOE stages of awareness and attention and learning and remembering as stages that are generally most positively affected by the media response states CRS and EXRS as influenced by AC.

HOE Stage 4 is primarily affected by the media response state of ERS. The affect transfer model states that consumers' positive experience with the ad output generally transfers to the brand and, therefore, brand liking suggesting the significant role of AC in creating that positive experience, such as emotional responses and arousal, which eventually leads to a more favorable evaluation of the brand [2]. Pollay and Mittal (1993) propose that a factor influencing attitude toward ads is hedonic/pleasure which stems from consumers finding the ad stimuli beautiful, entertaining, and enjoyable [41]. This factor mainly manifests from emotional responses evoked by the ad stimuli. Creative ads lead to more favorable brand attitudes as these provide entertainment and evoke positive emotions and arousal leading to favorable evaluation. The favorable evaluation of the ad as a positive effect should transfer to the brand [2,13], leading to brand liking.

HOE Stages 3 and 5 are the least affected by all media response states. These stages are generally regarded as deliberate, higher-order cognitive processes which involve appraisals, interpretations, attributions, schemas, and strategies [15]. These stages differ from other stages as they involve transforming an individual's role from vicarious audience to decision-making consumer.

CRS has no significant and positive relationship with HOE stage 3: accepting or rejecting ad claims, and HOE stage 5: brand intention. Most respondents professed to have invested cognitive effort in evaluating the ad stimulus embedded in the instrument. However, as with most creative ads, the stimulus concentrates on a more emotional route, sacrificing rational information, which is needed for decision-making. Ads utilize different appeals, which have different effects depending on target audiences [42]. Ads with a more rational tone of appeal are designed to provide information through appeals of reasoning, thinking, and awareness [42]. The available research on AC generally supports its positive effect on immediate responses such as attention and signals such as perceived sender effort [5]. There are conflicting results regarding outcome responses such as brand intention [36,2]. Thus, AC's influence on CRS' effect on HOE3 and HOE 5 constitutes little to no contribution towards ad effectiveness.

EXRS has a significant and positive small relationship with HOE stage 3: accepting or rejecting ad claims, and HOE stage 5: brand intentions. This is weaker in comparison to its effects on other HOE stages. EXRS emerges as the best-performing media response state, with less strength toward its effects on HOE3 and HOE5. Ad content eliciting excitative responses leads audiences to perceive the content quality as favorable. As the quality of content is perceived as favorable through responses such as arousal, and excitement, the perceived intrusiveness of the ad is weakened, leading to more positive engagement [43] with ad messaging and claims. Heightened EXRS during exposure to ads indicates higher content quality delaying ad avoidance. Individuals are likelier to abandon immediate gratification in favor of long-term interests [43], such as the continuation of the excitative experience regarding the ad. This allows for the delay of closure and avoidance, allotting more time for the ad claims to be regarded and accepted. Compared to emotional responses, excitative responses yielded significant results toward brand intention. Arousal and excitement may be instigated through value/emotion-free content such as dynamic, active structures of the ad. The elements of the ad can take a formalistic approach, meaning non-representational forms. Moreover, their structure can illicit arousal and interest by engaging relevance or aesthetic perceptions. Non-representational or non-emotive content that excites or arouses audiences, such as textures and product/ad quality, are emotion-free yet add to the rational information processed by consumers leading to intention.

Unlike information-driven advertising, persuasive advertising relies more on emotions than logical mental processes. Like emotional response states, excitative responses are affected by stimuli that activate physiological and emotional arousal. This indicates that audiences with heightened excitative response states affected by advertising will be more likely to accept the advertising claims. Excitative responses are generally positive reactions to the stimuli received, holding attention. Thus, further processing of ad claims is longer, leading to an increased likelihood of acceptance. However, the lack of rational information to drive higher-order cognitive processes in HOE3 and HOE5, which involve appraisals, interpretations, attributions, schemas, and strategies, has likely contributed to EXRS' comparatively weaker effect on these HOE stages.

ERS effects on the Hierarchy of Effect stages of HOE stage 3: accepting or rejecting ad claims and HOE stage 5: brand intentions are at their weakest compared to the other HOE stages, with ERS having a weak effect on HOE stage 3 and no effect on HOE stage 5. The strength of the effect of emotional response states on the HOE stage of accepting or rejecting ad claims and brand intention in this study was small. Cognitive Experiential Self Theory (CEST) [15], which investigates the presence of sequential patterns of the HOE model concerning information processing from advertisements [15], proposes that two conceptual systems work in parallel and dynamically reinforce each other given a particular task. These are classified as the experiential and the rational systems. The experiential system is considered affective and related to rapid and crude processing. It is within this processing system that ERS can be placed. ERS, consistent with CEST, is a relatively basic and automatic associative process that is less deliberate than higher-order cognitive processes of the rational system. Given the lack of information contained in the ad stimulus utilized in the study to engage the rational processes, higher-order cognitive processing was engaged less towards brand intentions and accepting ad claims but directed towards the narrative, emotional aspect of the ad message.

Where does AC enter the advertising communication process? The results indicate that AC's effects enter the process by directly and immediately influencing media response states. The categorizing of immediate responses to advertising is based on the three main theoretical accounts: affect transfer, processing, and signaling [2]. Available findings have generally shown that AC is beneficial in terms of immediate responses such as attention [2,16], perceived sender effort [6,2], and positive affect [2]. Empirical support for these three theoretical accounts, as provided by Rosengren et al. (2020), further strengthens the immediate effect of AC on consumer responses.

On conditional-response media effects in the context of advertising. The DSMM posit that Conditional Media Effects as indicative of the susceptibility of individuals in their responsiveness to media [28]. However, the current study has uncovered that conditional media effects play a lesser role in media use as conceptualized through AC. Instead, results show that AC as media use, by its structural characteristics, can hijack the connection between dispositions and media responses. This misalignment begs for the critical consideration of the conditional-response relationship as consistent and predictable as conceptualized by DSMM [24]. To address this issue, Fikkers and Piotrowski (2020) recommend the consideration of the role of selection. As a media effect feature, selectivity is transactional and influences the investment of cognitive, excitative, and emotional faculties in individuals, leading toward heightened engagement.

5. Conclusion and recommendations

5.1. Conclusion

The study investigated where AC significantly affects outcome effectiveness through the HOE and in the context of IDM. In so doing, communication processes regarding media use are introduced and open new avenues of investigation. Including IDM may add further insight into AC's place in advertising. As IDM as a medium is positioned as having significantly different communication processes than traditional media, this study included media effects such as Conditional Media Effects and Media Response States to see whether AC influences these media communication processes.

5.2. Theoretical implications

In terms of AC as a representative of IDM and, therefore, a medium presented in the communication process of individuals. AC, through its ability to capture attention, create interest, and heighten arousal, has a disrupting effect on the online experience of audiences, subsequently bringing about immediate media response states. AC's immediate impact on media response states resulting in heightened HOE outcomes is primarily supported. Practical positive effects are apparent on HOE stages that are classified under an experiential, conceptual system given a particular task. For true ad effectiveness to lead to expected brand outcomes by advertisers, the rational system must likewise be engaged. The study shows that AC, as manifested in the stimuli presented to respondents, had lower outcomes of effects towards HOE stages which deal with the rational system. The study confirmed previous research lauding the AC and its contribution to the HOE. These insights contribute to theoretical discussion and exploration in several ways. At the forefront is the regard of dynamic media effects, which can influence consumer ad processes prior to outcome-based variables such as that of HOE. This opens up new inroads of study, taking into account media theory's place in advertising. The integration of DSMM components within the study can open new knowledge-generating inquiries exploring further concepts that could explain or predict how media responses can be augmented to serve campaign goals.

Also uncovered is that HOE is not necessarily linear, with all stage effects compounding towards final brand goals such as purchase intention. This non-linear outcome tie into the recommendation that researchers on AC must bear in mind that specific ad outputs may have different brand intentions in mind. Not all campaigns seek to sell but build awareness or consumer-brand relationships to set the stage for meaningful communication in further marketing and advertising efforts [44]. For example, the results indicate that respondents that found the stimuli creative nonetheless were neutral on the HOE stage 3 of accepting ad claims yet were positively affected by brand liking (HOE4). The current study investigated AC as output-based and data gathered from a singular advertising artifact. Advertising effectiveness may be better measured when moving away from the linear processes of HOE and towards a synthesis of marketing communications and integrated marketing communications [45]. Because consumers are exposed to a magnitude of information in the marketplace, a linear approach is limited in measuring advertising effects on consumers [46].

5.3. Managerial implications

The findings ground our expectations of AC as a powerful, albeit not all-encompassing, strategy toward brand goals. Current creative advertising outputs reaping awards in the country (as reflected on the 10 ad outputs evaluated in this study) share the common quality of being emotionally and story-driven, which is alluded to from conversations with the KIIs in the study who shared that today's creative ads do not look or feel like ‘ads.' Rational information, such as reasons to buy or value propositions, is not at the forefront of the content of current ad outputs deemed as creative. The deficit of rational cues to engage consumer decision-making towards brand intentions may be addressed in subsequent efforts to complete and support the experiential, conceptual system by engaging the rational conceptual system. As AC proved to be very effective regarding experiential HOE responses such as brand liking, it is this positive experience which may pave the way for advertisers to sustain conversations with consumers, as positive experience towards a brand can lead to a more conducive positive reception for other communications that are directed towards more information-driven reason to buy cues.

We must keep in mind that the evaluation of AC is hinged on the consumer perspective. Advertising is only deemed creative if the audience, based on their current contextual environment and psychographic traits, deems it so. The subjective nature of creativity is not a hindrance for AC and advertising in general, as specific outputs and messaging towards contemporary schemas, beliefs, lifestyles, and worldviews of the target market, niche markets, or specific consumer groups are always taken into consideration when conceptualizing advertising to bring about effectiveness.

The study provides potential practical use in campaign development and conceptualization as related to consumer demographics, as customized ad outputs addressing different audience traits or motivations can equate to higher production costs. Awareness, memory, and brand liking are posited to benefit the most from AC, allowing for better allocation of resources when developing outputs throughout campaigns. This practical view of AC's benefits to specific HOE stages provides actionable insights enabling advertisers to develop strategies given the value and limitations of AC within integrated marketing campaigns. It keeps us abreast with dynamic consumer processing of ad communications constantly developing in line with emerging media technology.

5.4. Recommendations and further research

By identifying the AC's objectives and its limitations in addressing some outcome stages of the HOE, other strategies may be developed and put into action, building on the immediate effects garnered. Such actions may be more rationally toned ad messaging, providing additional information for consumers to reach a purchase decision. It is recommended that AC be utilized to create brand awareness, allowing for attention through the advertising clutter and differentiating brands from its competitors, and fostering positive consumer-brand relationships to serve as a strong foundation for further marketing strategies through building recognition, trust, and preference. As the effect of AC is mainly manifested through its immediate effects on media response states, it is recommended that ad output is conceptualized and produced such that it will capture audience attention in the first seconds of exposure for all media response states to be engaged towards the HOE stages. Therefore, AC factors that illicit interest, arousal, and attention are recommended at the onset of advertising outputs. AC divergence factors may be in the best position to achieve this as AC relevance factors may be less immediate in their effects on audiences. Future studies may investigate AC in its different levels of Divergence and Relevance and whether specific configurations may be suitable for various marketing contexts. Integrating frameworks and theories from different media communications and advertising disciplines posits the current study's novelty. The potential for further knowledge creation should be exploited as cross-discipline research has many benefits, such as examining phenomena through alternative theoretical lenses.

5.5. Limitations

The study is limited to a cross-sectional online administered survey with data gathered and inferences made on the analysis relevant to the generational cohort of Y. Ad stimuli choice was limited to available data during the study. Only winners of advertising award organizations released in 2021 were taken into consideration.

Author contribution statement

Miguel Paolo l. Paredes: Conceived and designed the experiments; Analysed and interpreted the data; Wrote the paper.

Reynaldo A. Bautista Jr: Conceived and designed the experiments; Analysed and interpreted the data; Contributed reagents, materials, analysis tools or data.

Rayan P. Dui: Analysed and interpreted the data; Contributed reagents, materials, analysis tools or data.

Data availability statement

Data will be made available on request.

Additional information

No additional information is available for this paper.

Declaration of generative AI and AI-assisted technologies in the writing process

During the preparation of preparing this work, the author(s) used Grammarly & Microsoft Editor to identify grammar and clarity issues in the manuscript. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the publication's content.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.