1,720,989 research outputs found
O impacto das capacidades sociais dos agentes conversacionais na experiência do consumidor
Get PDFVários são os estudos recentes relativos às aplicações da inteligência artificial e,
muitos deles, abordam como estas podem ter um impacto positivo na
otimização de processos no contexto empresarial. Para além disso, também são
apresentadas várias investigações sobre como a inteligência artificial
generativa tem alterado a forma como os agentes conversacionais se
liberalizaram junto dos utilizadores. Contudo, o estudo do efeito das
capacidades sociais nos chatbots enquanto estímulo da experiência do
consumidor continua a ser um objeto pouco explorado. Assim, a presente
investigação procurou analisar a empatia enquanto uma capacidade social
implementada nos agentes conversacionais dotados de inteligência artificial
generativa e como esta pode afetar a experiência do consumidor. Para tal,
foram criados dois cenários distintos, um em que o chatbot demonstrava altos
níveis de empatia e outro com baixos níveis de empatia, que foram aplicados a
uma amostra. Cada participante dessa amostra teve acesso a apenas um dos
cenários criados, sendo avaliadas a satisfação, lealdade e electronic word of
mouth, como variáveis dependentes, e a confiança, self-disclosure e apego
afetivo, como variáveis mediadoras. O estudo foi concluído com a confirmação
de duas das seis hipóteses, afirmando que a satisfação e o eWOM são
impactados positivamente quando a empatia é integrada no chatbot. Algumas
das limitações passaram pelo tipo de amostra escolhido, porém foi
demonstrado que empresas que querem seguir os desenvolvimentos
tecnológicos devem apostar na potencialização do uso da inteligência artificial
nas suas ferramentas, de modo a acompanharem as necessidades dos
consumidores.Several recent studies have focused on the applications of artificial intelligence,
and many of them discuss how these can positively impact process optimization
in a business context. Additionally, there are various investigations into how
generative artificial intelligence has changed the way conversational agents
have become widespread among users. However, the study of the effect of
social capabilities in chatbots as a stimulus for consumer experience remains an
underexplored topic. Therefore, the present research aimed to analyze empathy
as a social capability implemented in generative AI-powered conversational
agents and how it can affect consumer experience. To achieve this, two distinct
scenarios were created: one where the chatbot demonstrated high levels of
empathy and another with low levels of empathy. These scenarios were applied
to a sample, with each participant having access to only one of the created
scenarios. Satisfaction, loyalty, and electronic word of mouth (eWOM) were
evaluated as dependent variables, while trust, self-disclosure, and emotional
attachment were evaluated as mediating variables. The study concluded by
confirming two of the six hypotheses, asserting that satisfaction and eWOM are
positively impacted when empathy is integrated into the chatbot. Some
limitations included the type of sample chosen, but it was demonstrated that
companies aiming to keep up with technological advancements should invest
in enhancing the use of artificial intelligence in their tools to meet consumer
need
Balancing Privacy and Personalization: Analyzing Consumer Behavior when Using Intelligent Personal Assistants
Get PDFDissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Risk Analysis and ManagementNowadays, AI technology is developing at a rapid pace, changing the world and our daily lives
every day. Thus, understanding the impacts of these AI developments on their users' ethical
concerns and data privacy is essential. This study focuses on the role of Personalization in
determining whether the desire for personalized content can mitigate users' data privacy
concerns when using and disclosing information to Intelligent Personal Assistants (IPAs). To
address this question, a model was developed where Personalization was the independent
variable, and Risk Perception and Trust served as mediators. The dependent variables were
Willingness to Self-Disclose to IPAs and Intention to use IPAs. The results indicated that
Personalization significantly enhances users' intention to use IPAs and their willingness to
disclose personal information with it. Additionally, having access to personalized content can
reduce the perceived risk associated with IPAs and foster greater trust in these technologies.
These findings contribute to a deeper understanding of the trade-off users are willing to make
to access the benefits provided by IPAs while highlighting the critical role of personalization in
influencing user behavior and perceptions
Antecedentes do uso de redes sociais e seu impacto nas emoções negativas e no bem-estar dos indivíduos
Get PDFDissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Marketing IntelligenceA evolução tecnológica que temos assistido tem conduzido a alterações significativas no setor
produtivo e dos serviços, nos negócios e na gestão empresarial, na comunicação e interação
entre as pessoas, observando-se neste contexto um incremento do digital anunciado como
vantagem competitiva e facilitadora do acesso à satisfação das necessidades da economia e
da sociedade. Contudo a utilização excessiva da tecnologia pode produzir efeitos negativos na
vida e saúde dos utilizadores, sendo com este desígnio que desenvolvemos este estudo com
o objetivo de investigar as consequências emocionais negativas que o uso indiscriminado das
redes sociais pode gerar nos indivíduos e explorar a relação de algumas características
sociodemográficas e económicas com este tipo de comportamento. Para o efeito, a pesquisa
assentou fundamentalmente na revisão da literatura e na aplicação de um questionário aos
internautas construído com base na literatura da especialidade, sendo definida uma amostra
não probabilística por conveniência, obtendo-se 282 respostas válidas. Dos resultados do
estudo, ressaltam fundamentalmente as confirmações de que a idade dos utilizadores tem
influência na frequência de uso das redes sociais, o hábito de consumo de um grupo próximo
influencia positivamente as preferências de outros usuários das redes sociais, e a intensidade
de uso das redes sociais aumenta não apenas as emoções negativas sentidas pelo usuário,
mas também influencia negativamente o seu bem-estar
The Impact of Artificial Intelligence on Consumer Behaviour: The Introduction of Smart Mirrors in Retail Stores
Get PDFDissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Marketing IntelligenceThis research investigates how Artificial Intelligence impacts customer behaviour in the
retail industry, focusing on consumer perceptions and how these perceptions condition their
intents to use the technology. Innovative technologies, such as machine learning and
automation, have reshaped various industries. Smart Mirrors are an emerging innovative
solution in retail that blends digital and physical experiences. In order to better understand
customer’s behaviours towards Smart Mirrors, the present study includes two new variables
- Perceived Risk and Intention to do Word of Mouth – to the Technology Acceptance Model
(TAM), which serves as its theoretical foundation. For a deeper research, control variables
Privacy Concerns and Consumer Innovativeness were also examined to provide a deeper
analysis. Through a quantitative study using a convenience sample of Portuguese consumers
who frequently shop for clothing at mass market retail stores, data were collected via an
online survey distributed through social media, resulting in 299 valid responses. Regression
and ANOVA were used in the analysis, conducted through SPSS, to assess the relationships
between variables. Findings suggest that Perceived Usefulness is the most influential factor in
consumers’ attitudes and behavioural intention towards using smart mirrors. Attitude
Towards Using was confirmed as a mediator, indicating that Attitude Towards Using mediates
the relationship between the independent and the dependent variables. The study
emphasizes the importance of improving perceived usefulness and ease-of-use while
addressing privacy and security concerns. Furthermore, it highlights important limitations
related to sample size and data collection timing, recommending future research to
incorporate additional variables and to adopt mixed methods approach for broader
understanding of consumer adoption patterns
Pet Ownership Consumer Behavior: Investigating how pet characteristics and attachment levels shape product choices between dog and cat owners
Get PDFDissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Digital Marketing and AnalyticsIn Portuguese families, pets play a more active role, which will influence their owner’s
purchasing intentions. This study analyses how dimensions such as the type of pet (dog or
cat), the level of attachment between owner and pet, and the anthropomorphism level in
which the pet is perceived will influence the owner’s purchasing intentions, and how that will
have an influence in the anthropomorphic pet product industry. These anthropomorphic
products (those not essential to the pet’s survival, and usually associated with human
characteristics), are most likely to be purchased by those owners who have stronger bonds
and consequently higher attachment levels with their pets. Additionally, the level of
anthropomorphism was proven to be the same between cat and dog owners, which
contradicts the current literature. Finally, having a more active and playful pet was confirmed
to influence the owners' purchasing intention positively. The study uses a mixed-method
approach, where both in-depth interviews and a survey were conducted
The Impact of Recommendations Agents in consumers’ purchasing decisions and satisfaction
Get PDFDissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Digital Marketing and AnalyticsThis work explores the impact of recommendation agents on consumer purchasing decisions
and satisfaction. With the rise of Artificial Intelligence (AI), recommendation agents have
become a significant part of consumers' daily lives, offering product suggestions based on
analysis of customers' online behaviors. These agents simplify decision-making by reducing
information overload and personalizing the shopping experience. The research tries to
understand how RA helps consumers deal with choice overload and how it conditions the
purchase decision and satisfaction of online consumers. The main results of the research show
that, although we did not obtain significant results between the RA and the purchase intention
and satisfaction variables, we were able to verify that the participants who had AI assistance
had a lower choice overload, and a higher purchase intention and satisfaction compared to the
participants who did not have AI assistance. Furthermore, the research considers the differences
between maximizers and satisficers to try to understand how each group reacts to personalized
recommendations and a control variable, privacy concerns, to understand if users with AI are
more subject to online attacks than those without AI. The results of this study contribute to the
understanding of the strategic implications of RA in online retail and offer insights for future
research on this topic and on how companies can optimize their recommendation strategies to
better meet consumers' needs. To obtain this insight, this thesis was developed through
quantitative analytic research via an online questionnaire with 130 responses
How does consumer awareness of greenwashing influence their purchasing decision of circular products?
No full textDissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Marketing IntelligenceThe fashion industry, a significant contributor to environmental pollution, faces growing pressure to adopt sustainable practices. However, issues like greenwashing undermine consumer trust. Circular consumption provides a transparent pathway to sustainability, but consumer behavior remains influenced by factors such as environmental concern and green consumption confusion. This thesis investigates how consumer awareness of greenwashing impacts purchasing decisions for circular products. By testing a conceptual model that
integrates environmental concern and green consumption confusion, this research seeks to address a critical gap in understanding consumer behavior. Ultimately, this study offers insights into advancing the transition towards a more sustainable fashion industry
Impact of Recommender Agents used in Online Retail on Customer Satisfaction and Purchase Intention
Get PDFDissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Digital Marketing and AnalyticsTechnology has changed how consumers live their lives and make purchases, which has forced
businesses to adjust to a more competitive market environment. Artificial Intelligence (AI) is
one example of a disruptive technology that has revolutionised corporate processes and
offered creative ways to improve customer experiences. In contrast to conventional decisionmaking processes, this thesis examines the effects of AI-driven Recommendation Agents
(RAs), on online retail, with a special emphasis on customer satisfaction and purchase
intention. By evaluating customer data and forecasting their preferences, RAs use AI to
customise the online purchasing experience, which enhances decision-making and reduces
information overload. There is no empirical study on AI personalisation's substantial impact
on customer behaviour, despite the industry's increased investment in this area. To close this
gap, this study compares consumer responses when supported in making decisions by RAs vs
traditional techniques. The main study topic looks at how customer satisfaction and purchase
intention are affected by decision-making supported by RAs. Furthermore, the research
explores how factors like algorithm aversion, perceived decision autonomy, and trust affect
these results. This study attempts to advance knowledge of AI's revolutionary potential in
marketing and its function in promoting improved customer interactions by offering insightful
information about the strategic implications of RAs for online businesses. To accomplish the
intended objective, quantitative analytic research using an online questionnaire with 150
replies was used to develop this thesis
The Impact of Social Media Influencers on Consumer Engagement and Well-being - The Role of Consumer Attachment
No full textDissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Marketing IntelligenceNowadays, influencers are a proven fact. It is amazing how important they are as representatives of a
brand; how well-known they are and how much people identify with them. Presently, social media
platforms serve as platforms for businesses. The influence of online resources has changed how much
people intend to exercise during pandemics. Although the interest in exercise and a healthy lifestyle
has been growing for a while, it has accelerated since COVID 19. It became clear throughout the
lockdown that maintaining a healthy lifestyle was necessary. Given the number of digital influencers
present in Social Networks, it is necessary to direct the issue to a target niche – fitness influencers –
who are dedicated to sharing a healthy lifestyle, connecting the body with health and wellbeing. The
way a company is perceived online these days is challenging to completely control, but by picking the
right influencers, it is possible to make sure that they accurately represent the companies' values and
aid in attracting customers. This research will include both genders to determine if there are
differences in their behaviors. For this reason, this thesis focuses on a variety of topics, such as online
influencer marketing, social media influencers, fitness influencer, characteristics of a digital influencer,
consumer engagement, consumer attachment and well-being. The primary goal of this thesis is to
examine how the characteristics of social media influencers (such as credibility, informativeness,
similarity and enjoyability) affect well-being and engagement in the fitness sector. To achieve the
proposed goal, this thesis was developed through a quantitative analysis study via an online
questionnaire with 827 responses
O impacto da IA no comportamento dos consumidores em contexto de retalho: A influência dos agentes de recomendação personalizados
Get PDFDissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Digital Marketing and AnalyticsAtualmente, o desenvolvimento contínuo da tecnologia, em particular das tecnologias de
informação no mercado de consumo, provoca um conjunto de comportamentos diversos na
aquisição de produtos e serviços, no setor do retalho. Neste sentido, a evolução tecnológica
tem promovido a alteração da experiência do consumidor, devido à facilidade e rapidez do
processo de compra. Assim, a utilização da Inteligência Artificial (IA) tem sido uma das
estratégias adotadas pelas empresas de forma a dar resposta às necessidades do mercado,
através da utilização de algoritmos e análises de tendência para oferecer recomendações de
produto personalizadas, considerando as preferências individuais de cada consumidor. No
setor do retalho, a utilização das tecnologias de IA alterou a forma como as empresas
interagem com os seus clientes, estimulando uma melhor compreensão das suas
necessidades, comportamentos e intenções, com base na análise de fatores demográficos e
o histórico de consumo individual. Através da presente investigação, foi possível efetuar
uma revisão literária para obter uma compreensão relativamente ao impacto da IA no
comportamento dos consumidores, para identificar a capacidade de influência dos agentes
de recomendação personalizada na sua experiência de compra. Assim, efetuou-se uma
análise à perceção do consumidor considerando o conjunto de recomendações efetuadas
com base nas suas preferências individuais, permitindo a identificação da sua expectativa
relativamente à aplicação destas soluções. Além disso, foi possível analisar o impacto
provocado pelas recomendações de produto na experiência de compra do consumidor, de
forma a identificar potenciais estratégias que reforçam a relação com o cliente no setor do
retalho. Através da realização de um questionário, foi possível avaliar qual o impacto e a
influência da IA na experiência de compra dos consumidores, permitindo efetuar uma
recolha das percepções dos utilizadores relativamente à utilização dos agentes de
recomendação personalizada. Como tal, foi possível verificar que, embora as
recomendações efetuadas por IA sejam influentes, não foi possível evidenciar uma relação
causal direta entre os agentes de recomendação personalizada e a intenção de compra dos
consumidores. Ainda assim, verifica-se a importância de assegurar uma experiência de
consumo que considere a personalização e proteção de privacidade de forma a otimizar
todo o processo de compra online.Nowadays, the continuous development of technology, particularly information technologies
in the consumer markets, leads to several behaviors in consumption and acquisition of
products and services in the retail sector. Thus, technological evolution has led to a change
in the consumer experience regarding to the ease and speed of the purchasing process.
Consequently, the use of Artificial Intelligence (AI) has been one of the strategies adopted by
companies to meet market needs, through the utilization of algorithms and trend analysis in
order to offer highly personalized product recommendations concerning the individual
preferences. Hence, in the retail sector, the use of AI technologies has changed how
companies interact with their customers, fostering a better understanding of their needs,
behaviors and intentions, based on the analysis of demographic factors and individual
consumption historical data. In the present research, it was possible to observe a literary
analysis to gain an understanding of the impact of AI on consumer behavior, with the aim of
identifying the influence capacity of personalized recommendation agents on the customer's
purchasing experience. In this document, an analysis of consumer preferences was carried
out based on their individual experiences, allowing tje identification of their profile and
expectations. Furthermore, it was possible to analyze the impact caused by personalized
product recommendations on consumer's purchasing experience, to identify potential
strategies that strengthen the relationship with the customer in the retail sector. By aplying
a survey, it was possible to assess the impact and influence of AI on consumers' shopping
experiences, gathering user perceptions regarding the use of personalized recommendation
agents. Therefore, although AI-driven recommendations are influential, a direct causal
relationship between personalized recommendation agents and consumers' purchase
intentions could not be established. Nonetheless, ensuring a shopping experience that
considers both personalization and privacy protection remains essential to optimizing the
entire online shopping process
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