Use of a controlled experiment and computational models to measure the impact of sequential peer exposures on decision making

It is widely believed that one's peers influence product adoption behaviors. This relationship has been linked to the number of signals a decision-maker receives in a social network. But it is unclear if these same principles hold when the pattern by which it receives these signals vary and when peer influence is directed towards choices which are not optimal. To investigate that, we manipulate social signal exposure in an online controlled experiment using a game with human participants. Each participant in the game makes a decision among choices with differing utilities. We observe the following: (1) even in the presence of monetary risks and previously acquired knowledge of the choices, decision-makers tend to deviate from the obvious optimal decision when their peers make similar decision which we call the influence decision, (2) when the quantity of social signals vary over time, the forwarding probability of the influence decision and therefore being responsive to social influence does not necessarily correlate proportionally to the absolute quantity of signals. To better understand how these rules of peer influence could be used in modeling applications of real world diffusion and in networked environments, we use our behavioral findings to simulate spreading dynamics in real world case studies. We specifically try to see how cumulative influence plays out in the presence of user uncertainty and measure its outcome on rumor diffusion, which we model as an example of sub-optimal choice diffusion. Together, our simulation results indicate that sequential peer effects from the influence decision overcomes individual uncertainty to guide faster rumor diffusion over time. However, when the rate of diffusion is slow in the beginning, user uncertainty can have a substantial role compared to peer influence in deciding the adoption trajectory of a piece of questionable information

Ranking Influential Nodes of Fake News Spreading on Mobile Social Networks

Online fake news can generate a negative impact on both users and society. Due to the concerns with spread of fake news and misinformation, assessing the network influence of online users has become an important issue. This study quantifies the influence of nodes by proposing an algorithm based on information entropy theory. Dynamic process of influence of nodes is characterized on mobile social networks (MSNs). Weibo (i.e., the Chinese version of microblogging) users are chosen to build the real network and quantified influence of them is analyzed according to the model proposed in this paper. MATLAB is employed to simulate and validate the model. Results show the comprehensive influence of nodes increases with the rise of two factors: the number of nodes connected to them and the frequency of their interaction. Indirect influence of nodes becomes stronger than direct influence when the network scope rises. This study can help relevant organizations effectively oversee the spread of online fake news on MSNs

Measuring Social Influence in Online Social Networks - Focus on Human Behavior Analytics

With the advent of online social networks (OSN) and their ever-expanding reach, researchers seek to determine a social media user’s social influence (SI) proficiency. Despite its exploding application across multiple domains, the research confronts unprecedented practical challenges due to a lack of systematic examination of human behavior characteristics that impart social influence. This work aims to give a methodical overview by conducting a targeted literature analysis to appraise the accuracy and usefulness of past publications. The finding suggests that first, it is necessary to incorporate behavior analytics into statistical measurement models. Second, there is a severe imbalance between the abundance of theoretical research and the scarcity of empirical work to underpin the collective psychological theories to macro-level predictions. Thirdly, it is crucial to incorporate human sentiments and emotions into any measure of SI, particularly as OSN has endowed everyone with the intrinsic ability to influence others. The paper also suggests the merits of three primary research horizons for future considerations

AI in marketing, consumer research and psychology: A systematic literature review and research agenda

This study is the first to provide an integrated view on the body of knowledge of artificial intelligence (AI) published in the marketing, consumer research, and psychology literature. By leveraging a systematic literature review using a data-driven approach and quantitative methodology (including bibliographic coupling), this study provides an overview of the emerging intellectual structure of AI research in the three bodies of literature examined. We identified eight topical clusters: (1) memory and computational logic; (2) decision making and cognitive processes; (3) neural networks; (4) machine learning and linguistic analysis; (5) social media and text mining; (6) social media content analytics; (7) technology acceptance and adoption; and (8) big data and robots. Furthermore, we identified a total of 412 theoretical lenses used in these studies with the most frequently used being: (1) the unified theory of acceptance and use of technology; (2) game theory; (3) theory of mind; (4) theory of planned behavior; (5) computational theories; (6) behavioral reasoning theory; (7) decision theories; and (8) evolutionary theory. Finally, we propose a research agenda to advance the scholarly debate on AI in the three literatures studied with an emphasis on cross-fertilization of theories used across fields, and neglected research topics

What Airbnb Reviews can Tell us? An Advanced Latent Aspect Rating Analysis Approach

There is no doubt that the rapid growth of Airbnb has changed the lodging industry and tourists’ behaviors dramatically since the advent of the sharing economy. Airbnb welcomes customers and engages them by creating and providing unique travel experiences to “live like a local” through the delivery of lodging services. With the special experiences that Airbnb customers pursue, more investigation is needed to systematically examine the Airbnb customer lodging experience. Online reviews offer a representative look at individual customers’ personal and unique lodging experiences. Moreover, the overall ratings given by customers are reflections of their experiences with a product or service. Since customers take overall ratings into account in their purchase decisions, a study that bridges the customer lodging experience and the overall rating is needed. In contrast to traditional research methods, mining customer reviews has become a useful method to study customers’ opinions about products and services. User-generated reviews are a form of evaluation generated by peers that users post on business or other (e.g., third-party) websites (Mudambi & Schuff, 2010). The main purpose of this study is to identify the weights of latent lodging experience aspects that customers consider in order to form their overall ratings based on the eight basic emotions. This study applied both aspect-based sentiment analysis and the latent aspect rating analysis (LARA) model to predict the aspect ratings and determine the latent aspect weights. Specifically, this study extracted the innovative lodging experience aspects that Airbnb customers care about most by mining a total of 248,693 customer reviews from 6,946 Airbnb accommodations. Then, the NRC Emotion Lexicon with eight emotions was employed to assess the sentiments associated with each lodging aspect. By applying latent rating regression, the predicted aspect ratings were generated. With the aspect ratings, , the aspect weights, and the predicted overall ratings were calculated. It was suggested that the overall rating be assessed based on the sentiment words of five lodging aspects: communication, experience, location, product/service, and value. It was found that, compared with the aspects of location, product/service, and value, customers expressed less joy and more surprise than they did over the aspects of communication and experience. The LRR results demonstrate that Airbnb customers care most about a listing location, followed by experience, value, communication, and product/service. The results also revealed that even listings with the same overall rating may have different predicted aspect ratings based on the different aspect weights. Finally, the LARA model demonstrated the different preferences between customers seeking expensive versus cheap accommodations. Understanding customer experience and its role in forming customer rating behavior is important. This study empirically confirms and expands the usefulness of LARA as the prediction model in deconstructing overall ratings into aspect ratings, and then further predicting aspect level weights. This study makes meaningful academic contributions to the evolving customer behavior and customer experience research. It also benefits the shared-lodging industry through its development of pragmatic methods to establish effective marketing strategies for improving customer perceptions and create personalized review filter systems

Uncovering the Dynamic, Cognitive, and Linguistic Strategies of Misinformation

Les mentides, la manipulació o la informació falsa no són res de nou. Totes han existit durant segles des que el flux i el contingut de la informació ha estat una font de poder. Tot i això, a l'era de les plataformes socials, el mecanisme ha canviat. Si bé encara hi ha emissors d'informació institucionals, competeixen amb altres fonts d'informació que depenen de la viralitat a través de la xarxa per a la difusió d'informació. En aquesta competència, els continguts tradicionals i els creats institucionalment pateixen un desavantatge: no juguen amb les mateixes regles. El contingut que es desvia dels codis deontològics i estilístics dels proveïdors d'informació fiable aprofita diverses heurístiques psicològiques per tornar-se més viral. Per exemple, es basen en l'evocació emocional (llenguatge sentimental i apel·lació als valors morals) i es basen en estils que requereixen menys esforç cognitiu per ser processats (en termes de complexitat gramatical i lèxica). En aquesta tesi doctoral, exploro com les fonts de desinformació aprofiten les heurístiques psicològiques per definir les seves eleccions estratègiques. Més específicament, la tesi es compon de tres estudis: (1) Ús del processament del llenguatge natural per a una exploració quantitativa sobre com les diferents categories d'informació falsa (clickbait, teories de conspiració, fake news, discurs d'odi, pseudociència i rumors) difereixen en termes de sentiment, apel·lació a la moralitat, llegibilitat i diversitat lèxica; (2) Mitjançant anàlisis de xarxes i processament de llenguatge natural, una demostració d'estratègies d'isomorfisme de fonts d'informació falsa cap a fonts confiables amb l'objectiu d'imitar actors d'alt estatus a l'ecosistema d'informació; i (3) una anàlisi dinàmica de notícies falses versus fonts fiables que informen sobre la pandèmia de Covid durant 2020 i 2021. En general, els resultats indiquen que hi ha diferències estructurals significatives entre diferents categories d'informació falsa i entre fonts d'informació fiables (per exemple, les notícies falses són, de mitjana, 18 vegades més negatives, 12 vegades menys diverses lèxicament, un 50% més apel·lants a la moralitat i un 13% més fàcils de processar que les notícies fàctiques). A més, presento evidència sobre com les fake news, el clickbait i els rumors fan servir una estratègia d'imitació cap a fonts fiables amb l'objectiu de ser percebuts com a proveïdors d'informació legítims i d'alt estatus. A més, mostro com es van comportar les fonts de notícies fiables i falses durant la pandèmia de Covid, revelant una reacció inicial convulsa seguida d'una estratègia de desinformació per crear caos i ambigüitat en canviar constantment entre temes. Finalment, discuteixo les implicacions dels resultats de la tesi per a les plataformes de xarxes socials, l'ecosistema mediàtic, les elits polítiques i els usuaris d'Internet.Las mentiras, la manipulación o la información falsa no son nada nuevo. Todas han existido durante siglos desde que el flujo y el contenido de la información ha sido una fuente de poder. Sin embargo, en la era de las plataformas sociales, el mecanismo ha cambiado. Si bien los emisores de información institucionales aún existen, compiten con otras fuentes de información que dependen de la viralidad a través de la red para la difusión de información. En esta competencia, los contenidos tradicionales y los creados institucionalmente sufren una desventaja: no juegan con las mismas reglas. El contenido que se desvía de los códigos deontológicos y estilísticos de los proveedores de información confiable aprovecha diversas heurísticas psicológicas para volverse más viral. Por ejemplo, se basan en la evocación emocional (lenguaje sentimental y apelación a los valores morales) y se basan en estilos que requieren menos esfuerzo cognitivo para ser procesados (en términos de complejidad gramatical y léxica). En esta tesis doctoral, exploro cómo las fuentes de desinformación aprovechan las heurísticas psicológicas para definir sus elecciones estratégicas. Más específicamente, la tesis se compone de tres estudios: (1) Uso del procesamiento del lenguaje natural para una exploración cuantitativa sobre cómo las diferentes categorías de información falsa (clickbait, teorías de conspiración, fake news, discurso de odio, pseudociencia y rumores) difieren en términos de sentimiento, apelación a la moralidad, legibilidad y diversidad léxica; (2) Por medio de análisis de redes y procesamiento de lenguaje natural, una demostración de estrategias de isomorfismo de fuentes de información falsa hacia fuentes confiables con el objetivo de imitar a actores de alto estatus en el ecosistema de información; y (3) un análisis dinámico de noticias falsas versus fuentes confiables que informan sobre la pandemia de Covid durante 2020 y 2021. En general, mis resultados indican que existen diferencias estructurales significativas entre distintas categorías de información falsa y entre fuentes de información confiables (por ejemplo, las noticias falsas son, en promedio, 18 veces más negativas, 12 veces menos diversas léxicamente, un 50 % más apelantes a la moralidad y un 13 % más fáciles de procesar que las noticias fácticas). Además, presento evidencia sobre cómo las fake news, el clickbait y los rumores emplean una estrategia de imitación hacia fuentes confiables con el objetivo de ser percibidos como proveedores de información legítimos y de alto estatus. Además, muestro cómo se comportaron las fuentes de noticias confiables y falsas durante la pandemia de Covid, revelando una reacción inicial convulsa seguida de una estrategia de desinformación para crear caos y ambigüedad al cambiar constantemente entre temas. Finalmente, discuto las implicaciones de los resultados de la tesis para las plataformas de redes sociales, el ecosistema mediático, las élites políticas y los usuarios de Internet.Las mentiras, la manipulación o la información falsa no son nada nuevo. Todas han existido durante siglos desde que el flujo y el contenido de la información ha sido una fuente de poder. Sin embargo, en la era de las plataformas sociales, el mecanismo ha cambiado. Si bien los emisores de información institucionales aún existen, compiten con otras fuentes de información que dependen de la viralidad a través de la red para la difusión de información. En esta competencia, los contenidos tradicionales y los creados institucionalmente sufren una desventaja: no juegan con las mismas reglas. El contenido que se desvía de los códigos deontológicos y estilísticos de los proveedores de información confiable aprovecha diversas heurísticas psicológicas para volverse más viral. Por ejemplo, se basan en la evocación emocional (lenguaje sentimental y apelación a los valores morales) y se basan en estilos que requieren menos esfuerzo cognitivo para ser procesados (en términos de complejidad gramatical y léxica). En esta tesis doctoral, exploro cómo las fuentes de desinformación aprovechan las heurísticas psicológicas para definir sus elecciones estratégicas. Más específicamente, la tesis se compone de tres estudios: (1) Uso del procesamiento del lenguaje natural para una exploración cuantitativa sobre cómo las diferentes categorías de información falsa (clickbait, teorías de conspiración, fake news, discurso de odio, pseudociencia y rumores) difieren en términos de sentimiento, apelación a la moralidad, legibilidad y diversidad léxica; (2) Por medio de análisis de redes y procesamiento de lenguaje natural, una demostración de estrategias de isomorfismo de fuentes de información falsa hacia fuentes confiables con el objetivo de imitar a actores de alto estatus en el ecosistema de información; y (3) un análisis dinámico de noticias falsas versus fuentes confiables que informan sobre la pandemia de Covid durante 2020 y 2021. En general, mis resultados indican que existen diferencias estructurales significativas entre distintas categorías de información falsa y entre fuentes de información confiables (por ejemplo, las noticias falsas son, en promedio, 18 veces más negativas, 12 veces menos diversas léxicamente, un 50 % más apelantes a la moralidad y un 13 % más fáciles de procesar que las noticias fácticas). Además, presento evidencia sobre cómo las fake news, el clickbait y los rumores emplean una estrategia de imitación hacia fuentes confiables con el objetivo de ser percibidos como proveedores de información legítimos y de alto estatus. Además, muestro cómo se comportaron las fuentes de noticias confiables y falsas durante la pandemia de Covid, revelando una reacción inicial convulsa seguida de una estrategia de desinformación para crear caos y ambigüedad al cambiar constantemente entre temas. Finalmente, discuto las implicaciones de los resultados de la tesis para las plataformas de redes sociales, el ecosistema mediático, las élites políticas y los usuarios de Internet

AI in Marketing, Consumer Research & Psychology: A Systematic Literature Review and Research Agenda

This study is the first to provide an integrated view on the body of knowledge on artificial intelligence (AI) published in the marketing, consumer research, and psychology literature. By leveraging a systematic literature review (SLR) using a data-driven approach and quantitative methodology (including bibliographic coupling), this study provides an overview of the emerging intellectual structure of AI research in the three bodies of literature examined. We identified eight topical clusters: (1) memory and computational logic; (2) decision making and cognitive processes; (3) neural networks; (4) machine learning and linguistic analysis; (5) social media and text mining; (6) social media content analytics; (7) technology acceptance and adoption; and (8) big data and robots. Furthermore, we identified a total of 412 theoretical lenses used in these studies with the most frequently used being: (1) the unified theory of acceptance and use of technology; (2) game theory; (3) theory of mind; (4) theory of planned behavior; (5) computational theories; (6) behavioral reasoning theory; (7) decision theories; and (8) evolutionary theory. Finally, we propose a research agenda to advance the scholarly debate on AI in the three literatures studied

The Democratization of News - Analysis and Behavior Modeling of Users in the Context of Online News Consumption

Die Erfindung des Internets ebnete den Weg für die Demokratisierung von Information. Die Tatsache, dass Nachrichten für die breite Öffentlichkeit zugänglicher wurden, barg wichtige politische Versprechen, wie zum Beispiel das Erreichen von zuvor uninformierten und daher oft inaktiven Bürgern. Diese konnten sich nun dank des Internets tagesaktuell über das politische Geschehen informieren und selbst politisch engagieren. Während viele Politiker und Journalisten ein Jahrzehnt lang mit dieser Entwicklung zufrieden waren, änderte sich die Situation mit dem Aufkommen der sozialen Online-Netzwerke (OSN). Diese OSNs sind heute nahezu allgegenwärtig – so beziehen inzwischen $67\%$ der Amerikaner zumindest einen Teil ihrer Nachrichten über die sozialen Medien. Dieser Trend hat die Kosten für die Veröffentlichung von Inhalten weiter gesenkt. Dies sah zunächst nach einer positiven Entwicklung aus, stellt inzwischen jedoch ein ernsthaftes Problem für Demokratien dar. Anstatt dass eine schier unendliche Menge an leicht zugänglichen Informationen uns klüger machen, wird die Menge an Inhalten zu einer Belastung. Eine ausgewogene Nachrichtenauswahl muss einer Flut an Beiträgen und Themen weichen, die durch das digitale soziale Umfeld des Nutzers gefiltert werden. Dies fördert die politische Polarisierung und ideologische Segregation. Mehr als die Hälfte der OSN-Nutzer trauen zudem den Nachrichten, die sie lesen, nicht mehr ($54\%$ machen sich Sorgen wegen Falschnachrichten). In dieses Bild passt, dass Studien berichten, dass Nutzer von OSNs dem Populismus extrem linker und rechter politischer Akteure stärker ausgesetzt sind, als Personen ohne Zugang zu sozialen Medien. Um die negativen Effekt dieser Entwicklung abzumildern, trägt meine Arbeit zum einen zum Verständnis des Problems bei und befasst sich mit Grundlagenforschung im Bereich der Verhaltensmodellierung. Abschließend beschäftigen wir uns mit der Gefahr der Beeinflussung der Internetnutzer durch soziale Bots und präsentieren eine auf Verhaltensmodellierung basierende Lösung. Zum besseren Verständnis des Nachrichtenkonsums deutschsprachiger Nutzer in OSNs, haben wir deren Verhalten auf Twitter analysiert und die Reaktionen auf kontroverse - teils verfassungsfeindliche - und nicht kontroverse Inhalte verglichen. Zusätzlich untersuchten wir die Existenz von Echokammern und ähnlichen Phänomenen. Hinsichtlich des Nutzerverhaltens haben wir uns auf Netzwerke konzentriert, die ein komplexeres Nutzerverhalten zulassen. Wir entwickelten probabilistische Verhaltensmodellierungslösungen für das Clustering und die Segmentierung von Zeitserien. Neben den Beiträgen zum Verständnis des Problems haben wir Lösungen zur Erkennung automatisierter Konten entwickelt. Diese Bots nehmen eine wichtige Rolle in der frühen Phase der Verbreitung von Fake News ein. Unser Expertenmodell - basierend auf aktuellen Deep-Learning-Lösungen - identifiziert, z. B., automatisierte Accounts anhand ihres Verhaltens. Meine Arbeit sensibilisiert für diese negative Entwicklung und befasst sich mit der Grundlagenforschung im Bereich der Verhaltensmodellierung. Auch wird auf die Gefahr der Beeinflussung durch soziale Bots eingegangen und eine auf Verhaltensmodellierung basierende Lösung präsentiert

The Role of Ethical Evaluation of Corporate Social Responsibility in the Perception of Corporate Hypocrisy, the Intention of Opinioned Communication and Behavior toward a Firm

Corporate hypocrisy refers to publics\u27 negative perception of CSR (Corporate Social Responsibility) as a result of ethical attribution of CSR to normative ethics, and thus can be a useful indicator of the disappointing and ineffective role of CSR programs geared toward raising publics\u27 goodwill toward a firm. However, scant scholarly effort has been made to explore the concept of corporate hypocrisy in relation to corporate issues and crises, publics\u27 ethical orientation, cultural and national influence, and polarized sentiments toward global business in the media landscape. These aspects collectively constitute the unpredictable, uncontrollable public opinion, in particular the opinion of the socially minded general public, and these aspects thus generate a turbulent business arena across the globe. To fill this void, this dissertation concurrently conducted two sets of research: one used a survey methodology on a real company\u27s CSR case and the other used an experimental method. First, Study 1 aimed to investigate how the perception of corporate hypocrisy connects publics\u27 ethical attribution of CSR to subsequent positive/negative opinioned communication intention and pro-firm behavioral intention. With special attention to deontology and consequentialism in normative ethics of philosophy, the current study was to empirically test a theoretical model of perceived corporate hypocrisy with two causal antecedents (i.e., the evaluation of self-orientation and other-orientation in CSR), and the mediating role of corporate hypocrisy between such antecedents and subsequent publics\u27 communication and behavioral intention toward a firm. Personal ethical orientation was suggested to moderate effects of corporate hypocrisy on dependent measures. Moreover, to explore the cultural and national effect in the theoretical model, this study compared U.S. and Korean data. To this end, a survey using a real company CSR case was conducted via Internet with a convenient sample (n = 603; the U.S.=406, Korea=256), including the general population (n=456) and a Northeastern university\u27s student and alumni population (n=147). Structural equation modeling (SEM) was used to empirically test the hypothesized mediation model of corporate hypocrisy. The results indicate several key issues regarding the role of ethics on the strategic CSR communication. First, this study found sound measurement reliability and validity of the proposed four-item scale of four dimensions in ethical CSR evaluation (i.e., self-interested motives, self-interested outcomes, altruistic motives and altruistic outcomes). Further, this study also proposed a self-developed seven-item scales for deontology and consequentialism with acceptable reliability and validity as indicators of personal ethical orientation in the context of public\u27s ethical judgment of global business practices. The current study also found significant mediation effects of corporate hypocrisy between ethical CSR evaluation and publics\u27 communication and behavioral intention based on positive and negative opinions formed through CSR evaluation. Also, as assumed, personal ethical orientation and cultural/national difference were found to significantly moderate the role of corporate hypocrisy on dependent measures. Study 2 aimed to test the theoretical validity of the attitudinal and behavioral influence of personal ethical orientation (i.e., deontology vs. consequentialism) and media framing of CSR approach (i.e., self-oriented CSR vs. other-oriented CSR); an experiment study (n=603) was conducted online for study 2. For the U.S. samples, the university student and alumni population was recruited (n= 347), and for the Korean samples, the general population (n=256) was recruited via an online survey system. Study 2 also found significant effects of personal ethical orientation and media framing. Deontological publics were more influenced by media framing of CSR approach rather tha n consequentialist publics; more significant was the differing interaction effect across nationalities. The Korean samples were more prone to be affected by media framing of CSR approach depending on their ethical orientation than the U.S. samples. To summarize, across the findings of the two studies, deontological publics showed more ethically idealistic and rigorous traits whereas consequentialist publics displayed a more pragmatic and business-friendly inclination in CSR judgment. This result highlighted the role of virtue ethics perceived from corporate motives and outcomes of CSR, which can play a part in forming publics which have certain opinions toward global business and its CSR activities. Also, the findings indicated that these ethical traits can be related to the cultural and national background of publics targeted in the global market; thus CSR strategy should take the ethical and cultural traits of target publics into account. Limitations and suggestions for future research were discussed with implications for both public relations scholarship and practices

Building consumer-brand relationship through mobile marketing

In an extremely competitive Era, in which the need of value creation for the clients emerge, brands appear to be a fundamental asset for companies and the emotional relationships that are built with consumers are their fundamental source of differentiation. The new interactive media that born of technology and allow new ways for customers and brands to communicate seem to promote that relationship. A research in Generation Y (people aged between 18 and 35 years old) in Portugal was made using an online survey being obtained 238 valid answers. The objective of this research was the analysis of the impact of mobile marketing (use of mobile phones as marketing communication media) in the strength of consumer-brand relationship. The interaction with brands through mobile devices do not originate in the respondents perspective positive consumer-brand relationships, however it was obtained for a specific group of consumers. The brand experience that is felt along the interaction is a factor that influences the strength of consumer-brand relationship, as also the value of communication – it was proved that emotional communications are associated with stronger consumer-brand relationships. The tool of interaction is also an influencer factor, pull-based mobile marketing actions empowered the consumer-brand relationship more than push-based mobile marketing actions. The research also allowed to conclude that the strength of consumer-brand relationship has influence in future interactions intentions with the brand, namely in services that imply the providing of personal data.Numa Era de competitividade em que a necessidade de criação de valor para o cliente urge, as marcas afiguram-se como os principais activos de uma empresa e as relações emocionais que criam com os consumidores são a sua principal fonte de diferenciação. As novas formas de interação entre marcas e consumidores derivadas das novas tecnologias dão indícios de fomentar e fortalecer essa relação. Foi realizada uma investigação junto da Geração Y (jovens entre os 18 e 35 anos) em Portugal através de um inquérito online de onde foram obtidas 238 respostas válidas. O objetivo desta investigação era a análise do impacto do mobile marketing (uso de telemóveis enquanto meio de comunicação em marketing) na relação consumidor-marca. A interação com as marcas através dos dispositivos móveis não deu origem a relações consumidor-marca extremamente positivas em termos absolutos, no entanto, para um nicho de consumidores foi possível verificar o contrário. A experiência de marca sentida aquando da interação revelou-se um factor com influência na força da relação, assim como o valor da comunicação – comunicações emocionais originam relações consumidor-marca mais fortes. A forma de interação é também factor influenciador, sendo que as ações de comunicação pull parecem aumentar a força da relação em comparação com as ações push. A investigação permitiu também concluir que força da relação influencia as intenções de interação futuras com a marca, nomeadamente através de serviços que implicam o fornecimento de dados pessoais do cliente