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The aim of this study is to assess the mediating effect of source appearance (SA) and self-influencer congruence (SIC) on the relationship between visual content (VC) and customer engagement (CE) towards mobile advertisement.

This study uses a quantitative approach to test the proposed model based on the stimulus–organism–response (SOR) theory. The non-probability purposive sampling technique was used to collect data from Pakistani mobile users through a self-administered questionnaire.

The study results prove that VC alone cannot generate mobile users’ engagement. SA is the key in this regard, which has a relatively higher importance compared to SIC. Furthermore, the serial mediation effect of SA and SIC on CE shows that attractive sources are likely to induce higher SIC and subsequent CE.

The results reveal that without a pleasing SA and positive SIC, mobile users skip the ads by perceiving them to be irritating or interruptive. Mobile ads might cost relatively less, but the advertisers should understand the significance of the SA toward minimizing the mobile advertising skepticism.

Advertisers can enhance the user’s engagement on mobile devices by addressing both the SA and SIC in their VC. The combined effect of both the SA and SIC on CE has not been assessed before. Furthermore, this study has used the SOR mechanism to examine CE.

El objetivo general de esta investigación es evaluar el efecto mediador de la apariencia de la fuente (SA) y la congruencia del auto-influencer (SIC) en la relación entre el contenido visual (CV) y el compromiso del cliente (CE) hacia la publicidad móvil.

Este estudio utiliza un enfoque cuantitativo para probar el modelo propuesto basado en la teoría estímulo-organismo-respuesta (SOR). Se utilizó la técnica de muestreo intencional no probabilístico para recoger datos de usuarios de móviles paquistaníes mediante un cuestionario autoadministrado.

Nuestros resultados demuestran que el contenido visual por sí solo no puede generar el compromiso de los usuarios de móviles. La apariencia de la fuente es la clave a este respecto, que tiene una importancia relativamente mayor en comparación con la congruencia del auto-influencer. Además, el efecto de mediación en serie de SA y SIC en CE muestra que es probable que las fuentes atractivas induzcan un mayor SIC y el consiguiente compromiso del cliente.

Los resultados revelan que sin una SA agradable y una SIC positiva, los usuarios de móviles omiten los anuncios al percibirlos como irritantes o interruptores. Los anuncios para móviles pueden costar relativamente menos, pero los anunciantes deben comprender la importancia de la apariencia de la fuente para minimizar el escepticismo de la publicidad móvil.

Los anunciantes pueden mejorar la participación del usuario en los dispositivos móviles abordando tanto la AS como el SIC en sus contenidos visuales. Hasta ahora no se había evaluado el efecto combinado de la AS y el SIC en el CE. Además, este estudio ha utilizado el mecanismo del SOR para examinar el engagement del cliente.

本研究的总体目标是评估源外观（SA）和自我影响者一致性（SIC）对移动广告视觉内容（VC）和客户参与（CE）之间关系的中介效应。

本研究采用定量方法来检验基于刺激-有机体-反应（SOR）理论提出的模型。研究采用了非概率目的性抽样技术, 通过自填问卷的方式向巴基斯坦移动用户收集数据。

我们的研究结果证明, 仅靠视觉内容并不能引起移动用户的参与。在这方面, 源外观是关键, 与自我影响者一致性相比, 源外观的重要性相对更高。此外, SA 和 SIC 对 CE 的串联中介效应表明, 有吸引力的信息源可能会诱发更高的 SIC 和随后的客户参与。

研究结果表明, 如果没有令人愉悦的SA和积极的SIC, 移动用户就会认为广告具有刺激性或干扰性, 从而跳过广告。移动广告的成本可能相对较低, 但广告商应了解广告源外观对减少移动广告怀疑的重要性。

广告商可以通过在视觉内容中同时考虑广告联盟和广告投放中心这两个因素, 提高用户在移动设备上的参与度。之前从未有人评估过 “SA “和 “SIC “对消费者参与度的综合影响。此外, 本研究还使用了 SOR 机制来考察客户参与度。

The purpose of this study is to determine how sonic logo’s acoustic features (intensity, pitch and pace) based on melodic tunes with no voice orient the response of consumers, attract attention, elicit levels of pleasantness and calmness and transmit brand personality traits.

A within-subject experimental factorial design is applied to measure emotional arousal (indexed as electrodermal activity) and enhancement on perceptual processing (indexed as heart rate), as well as self-reported factors, namely, calmness/excitement, pleasantness and brand personality scales.

Results show a significant increase on electrodermal activity associated with fast-paced sonic logos and a decrease in heart rate in slow-paced long sonic logos. Also, fade-up, pitch-ascending fast sonic logos are defined as more exciting and descending-pitch sonic logos as more pleasant.

The use of sonic logos with no voice does limit its implications. Besides, the use of three variables simultaneously with 18 versions of sonic logos in a laboratory setting may have driven participants to fatigue; hence, findings should be cautiously applied.

First, sonic logos are best processed in a fade-up form. Second, fast pace is recommended to orient response, whereas slow pace is recommended to transmit calmness. Practitioners may opt for fast-paced sonic logos if the design is new or played in a noisy environment and opt for slow-paced sonic logos in already highly recognized sound designs.

To the best of authors’ knowledge, this study is the first to combine psychophysiological measures and self-reported scales in a laboratory experiment on how sonic logo’s acoustic features orient response, transmit emotions and personality traits.

This paper aims to investigate cross-gender effects of gender stereotypes in advertising. More specifically, it proposes that the negative effects found in studies of women’s reactions to stereotyped female portrayals should hold across gender portrayal and target audience gender.

In two experimental studies, the effects of stereotyped portrayals (vs non-stereotyped portrayals) across gender are compared.

The results show that advertising portrayals of women and men have a presumed negative influence on others, leading to higher levels of ad reactance, which has a negative impact on brand-related effects across model and participant gender, and for gender stereotypes in terms of physical characteristics and roles.

Whereas previous studies have focused on reactions of women to female stereotypes, the current paper suggests that women and men alike react negatively to stereotyped portrayals of other genders.

The results indicate that marketers can benefit from adapting a more mindful approach to the portrayals of gender used in advertising.

The addition of a cross-gender perspective to the literature on gender stereotypes in advertising is a key contribution to this literature.

The purpose of this study is to review and synthesize the literature on in-app advertising, identify gaps and propose future research directions.

The authors use a systematic literature review (SLR) approach, following the PRISMA guidelines, to investigate the current state of research in in-app advertising. The study uses 44 shortlisted articles from the Scopus and Web of Science databases. Using the Theory-Context-Characteristics-Methodology (TCCM) framework, the authors analyze the gaps in theory, context, characteristics and methods.

Using thematic analysis, the authors identify five main themes in the in-app advertising literature, namely, ad platform optimization; mobile app user psychology and behavior; ad effectiveness; ad fraud; and security, privacy and other user concerns. The findings show the need for empirical research, with a strong theoretical foundation in emerging ad formats of in-app advertising, user behavior and buy-side of in-app advertising.

This is a maiden study to conduct a domain-based SLR in the emerging field of in-app advertising using the TCCM framework. The authors highlight the key differences between in-app advertising and mobile web advertising. The authors propose theories in the advertising field that could be used in future empirical studies of in-app advertising.

El propósito de esta investigación es revisar y sintetizar la literatura sobre la publicidad en Apps, identificar lagunas y proponer futuras direcciones de investigación.

Utilizamos un enfoque de revisión sistemática de la literatura, siguiendo las directrices PRISMA, para investigar el estado actual de la investigación en publicidad en aplicaciones. El estudio utiliza 44 artículos preseleccionados de las bases de datos Scopus y Web of Science (WoS). Utilizando el marco Teoría-Contexto-Características-Metodología (TCCM), analizamos las lagunas en teoría, contexto, características y métodos.

Mediante un análisis temático, identificamos cinco temas principales en la literatura sobre publicidad en aplicaciones, a saber: optimización de plataformas publicitarias; psicología y comportamiento de los usuarios de aplicaciones móviles; eficacia publicitaria; fraude publicitario; seguridad, privacidad y otras preocupaciones de los usuarios. Nuestros hallazgos muestran la necesidad de investigación empírica, con una sólida base teórica en los formatos publicitarios emergentes de la publicidad en Apps, el comportamiento del usuario y el buy-side de la publicidad en Apps.

Se trata de un estudio pionero para realizar una revisión sistemática de la literatura basada en el dominio en el campo emergente de la publicidad en Apps utilizando el marco TCCM. Destacamos las principales diferencias entre la publicidad en aplicaciones y la publicidad en la web para móviles. Proponemos teorías en el campo de la publicidad que podrían utilizarse en futuros estudios empíricos sobre la publicidad en Apps.

本研究旨在回顾和总结有关应用内广告的文献, 找出差距并提出未来的研究方向。

我们采用系统性文献综述方法, 遵循 PRISMA 指南, 调查应用内广告的研究现状。研究使用了 Scopus 和 Web of Science (WoS) 数据库中的 44 篇入围文章。利用理论-背景-特征-方法（TCCM）框架, 我们分析了理论、背景、特征和方法方面的差距。

通过主题分析, 我们确定了应用内广告文献的五大主题, 即广告平台优化; 移动应用用户心理和行为; 广告效果; 广告欺诈; 安全、隐私和其他用户关注点。我们的研究结果表明, 有必要在应用内广告的新兴广告形式、用户行为和应用内广告买方等方面开展实证研究, 并奠定坚实的理论基础。

这是一项首次使用 TCCM 框架对新兴的应用内广告领域进行基于领域的系统性文献综述的研究。我们强调了应用内广告与移动网络广告的主要区别。我们提出了广告领域的理论, 可用于未来的应用内广告实证研究。

The purpose of this paper is the better understanding of the increasing relation between big data 2.0 and neuromarketing, particularly to influence election outcomes, along with a special aim to discuss some raised doubts about Trump’s presidential campaign 2016 and its ability to hijack American political consumers’ minds, and to direct their votes.

This paper combines deductive/inductive methodology to define the term of political neuromarketing 2.0 through a brief literature review of related concepts of big data 2.0, virtual identity and neuromarketing. It then applies a single qualitative case study by presenting the history and causes of online voter microtargeting in the USA, and analyzing the political neuromarketing 2.0 mechanisms adopted by Trump’s political campaign team in the 2016 presidential election.

Based on Trump’s political marketing mechanisms analysis, the paper believes that big data 2.0 and neuromarketing techniques played an unusual role in reading political consumers’ minds and helping the controversial candidate to meet one of the most unexpected victories in the presidential elections. Nevertheless, this paper argues that the ethics of using political neuromarketing 2.0 to sell candidates and its negative impacts on the quality of democracy are and will continue to be a subject of ongoing debates.

The marriage of big data 2.0 and political neuromarketing is a new interdisciplinary field of inquiry. This paper provides a useful introduction and further explanations for why and how Trump’s campaign defied initial loss predictions and attained victory during this election.

This paper aims to explore the recognition and success of different ways of branding native advertising in influencer marketing.

The data are evaluated using statistical tests, correlation and cluster analysis.

It was found that the higher the recognition rate of a post tagged in a particular way, the better the tagging method for influencer marketing on Instagram. Based on the findings of this study, word tag is recommended first because it is flexible and has one of the highest recognition rates.

The generalizability of the results across different regional settings requires further investigation.

Good labeling of native advertising leads to greater success.

This study can be used by marketing managers, advertisers and influencers to gain insight into the issue, as well as to better select the appropriate labeling method for their advertising content.

Este trabajo tiene como objetivo explorar el reconocimiento y el éxito de diferentes formas de branding de publicidad nativa en el marketing de influencers.

Los datos se evalúan mediante pruebas estadísticas, correlación y análisis de conglomerados.

Se encontró que cuanto mayor es la tasa de reconocimiento de un post etiquetado de una manera particular, mejor es el método de etiquetado para el marketing de influencers en Instagram. Basándose en los resultados de este estudio, se recomienda en primer lugar el etiquetado por palabras porque es flexible y tiene una de las tasas de reconocimiento más altas.

Un buen etiquetado de la publicidad nativa conduce a un mayor éxito.

Este estudio puede ser utilizado por directores de marketing, anunciantes e influencers para obtener información sobre el tema, así como para seleccionar mejor el método de etiquetado adecuado para su contenido publicitario.

La generalizabilidad de los resultados en diferentes entornos regionales requiere más investigación.

本文旨在探讨影响者营销中不同方式的品牌原生广告的识别和成功。

使用统计测试、相关性和聚类分析对数据进行评估。

研究发现, 以特定方式标记的帖子的识别率越高, Instagram上影响者营销的标记方式就越好。基于这项研究的结果, 首先推荐单词标签, 因为它很灵活, 而且有最高的识别率之一。

对原生广告进行良好的标注会带来更大的成功。

本研究可供营销经理、广告商和影响者使用, 以深入了解这一问题, 并更好地为其广告内容选择合适的标签方法。

研究结果在不同地区环境中的普适性需要进一步调查。

Prediction is a critical task in targeted online advertising, where predictions better than random guessing can translate to real economic return. This study aims to use machine learning (ML) methods to identify individuals who respond well to certain linguistic styles/persuasion techniques based on Aristotle’s means of persuasion, rhetorical devices, cognitive theories and Cialdini’s principles, given their psychometric profile.

A total of 1,022 individuals took part in the survey; participants were asked to fill out the ten item personality measure questionnaire to capture personality traits and the dysfunctional attitude scale (DAS) to measure dysfunctional beliefs and cognitive vulnerabilities. ML classification models using participant profiling information as input were developed to predict the extent to which an individual was influenced by statements that contained different linguistic styles/persuasion techniques. Several ML algorithms were used including support vector machine, LightGBM and Auto-Sklearn to predict the effect of each technique given each individual’s profile (personality, belief system and demographic data).

The findings highlight the importance of incorporating emotion-based variables as model input in predicting the influence of textual statements with embedded persuasion techniques. Across all investigated models, the influence effect could be predicted with an accuracy ranging 53%–70%, indicating the importance of testing multiple ML algorithms in the development of a persuasive communication (PC) system. The classification ability of models was highest when predicting the response to statements using rhetorical devices and flattery persuasion techniques. Contrastingly, techniques such as authority or social proof were less predictable. Adding DAS scale features improved model performance, suggesting they may be important in modelling persuasion.

In this study, the survey was limited to English-speaking countries and largely Western society values. More work is needed to ascertain the efficacy of models for other populations, cultures and languages. Most PC efforts are targeted at groups such as users, clients, shoppers and voters with this study in the communication context of education – further research is required to explore the capability of predictive ML models in other contexts. Finally, long self-reported psychological questionnaires may not be suitable for real-world deployment and could be subject to bias, thus a simpler method needs to be devised to gather user profile data such as using a subset of the most predictive features.

The findings of this study indicate that leveraging richer profiling data in conjunction with ML approaches may assist in the development of enhanced persuasive systems. There are many applications such as online apps, digital advertising, recommendation systems, chatbots and e-commerce platforms which can benefit from integrating persuasion communication systems that tailor messaging to the individual – potentially translating into higher economic returns.

This study integrates sets of features that have heretofore not been used together in developing ML-based predictive models of PC. DAS scale data, which relate to dysfunctional beliefs and cognitive vulnerabilities, were assessed for their importance in identifying effective persuasion techniques. Additionally, the work compares a range of persuasion techniques that thus far have only been studied separately. This study also demonstrates the application of various ML methods in predicting the influence of linguistic styles/persuasion techniques within textual statements and show that a robust methodology comparing a range of ML algorithms is important in the discovery of a performant model.

The pandemic has enhanced the global phenomenon of disinformation. This paper aims to study the false news concerning COVID-19, spread through social media in Spain, by using the LatamChequea database for a duration from 01/22/2020, when the first false information has been detected, up to 03/09/2021.

A quantitative analysis has been conducted with regard to the correlation between fake news stories and the pandemic state, the motive to share them, their dissemination in other countries and the effectiveness of fact checking. This study is complemented by a qualitative method: a focus group conducted with representatives of different groups within the society.

Fake news has been primarily disseminated through several social networks at the same time, with two peaks taking place in over a half of the said false stories. The first took place from March to April of 2020 during complete lockdown, and we were informed of prevention measures, the country’s situation and the origin of the virus, whereas the second was related to news revolving around the coming vaccines, which occurred between October and November. The audience tends to neither cross-check the information received nor report fake news to competent authorities, and fact-checking methods fail to stop their spread. Further awareness and digital literacy campaigns are thus required in addition to more involvement from governments and technological platforms.

The main limitation of the research is the fact that it was only possible to conduct a focus group of five individuals who do not belong to generation Z due to the restrictions imposed by the pandemic, although a clear contribution to the analysis of the impact of fake news on social networks during the COVID-19 pandemic in Spain can be seen from the privileged experiences in each of the fields of work that were identified. In this sense, the results of the study are not generalizable to a larger population. On the other hand, and with a view to future research, it would be advisable to carry out a more specific study of how fake news affects generation Z.

This research is original in nature, and the findings of this study are valuable for business practitioners and scholars, brand marketers, social media platform owners, opinion leaders and policymakers.