Los smartphones se han convertido en una parte integral en la vida de las personas, encontrándose en constante evolución y actualización como efecto de las necesidades y preferencias cambiantes de los consumidores. Por tal motivo, el presente estudio busca identificar cuáles son los factores que influyen en la intención de compra de smartphones en adultos jóvenes. Para ello, se aplicó el método de investigación cuantitativo para probar hipótesis, basándose en un análisis estadístico, junto con un enfoque explicativo. La elección de la muestra es no probabilística por conveniencia, teniendo un tamaño de 452 personas. Así mismo, la técnica de recolección de datos utilizada fue el cuestionario, también denominado encuesta. Esta investigación empleó el análisis de regresión lineal múltiple y recopiló datos válidos de 361 encuestados (adultos jóvenes que cumplan con el perfil). Los resultados del análisis mostraron que la marca, características del producto, necesidades sociales y el precio son los factores que guardan relación significativa con la intención de compra de smartphones, mientras que la conveniencia e influencia social no influyen en la misma. En tal sentido, este estudio analiza cada variable relacionada con la intención de compra de smartphones proponiendo un modelo, el cual incorpora nuevos factores en base a lo estudiado, permitiendo conocer su relación con la intención de compra. Así mismo, estos resultados aportan a que las empresas entiendan y conozcan al consumidor al que se dirigen, pudiendo ofrecerle el producto que están buscando. / Smartphones have become an integral part of people's lives, are constantly evolving and updating as a result of the changing needs and preferences of consumers. Therefore, the present study seeks to recognize which are the factors that influence the purchase intention of smartphones in young adults. For this purpose, the quantitative research method was applied to test hypotheses, based on the statistical analysis, along with an explanatory approach. The sample is non-probabilistic for convenience, having a size of 452 people. Likewise, the data collection technique used was a questionnaire, also denominated survey. This investigation used a multiple linear regression analysis and collected valid data from 361 respondents (young adults who meet the profile). The results of the analysis showed that the brand, product characteristics, social needs and the price are the factors that are significantly related to the intention to buy smartphones, while convenience and social influence have no impact on it. In this sense, the study examines each variable relating to the purchase intention of smartphones, proposing a model, which incorporates new factors founded on what has been studied, allowing to notice its relation to the purchase intention. Furthermore, these outcomes contribute to enterprises comprehend and get to know their target consumers, being able to offer them the product they are looking for. / Tesis / PE

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[pt] Nesta dissertação são avaliados os antecedentes da confiança móvel para a sua construção. É proposto um modelo que incorpora normas subjetivas, fatores interativos, utilitários e hedônicos relacionados ao contexto do comércio móvel e seus efeitos sobre a atitude e intenção de compra. Os dados da amostra de 433 consumidores brasileiros foram coletados em um levantamento online e analisados por meio de modelagem de equações estruturais. Os resultados obtidos sugerem que fatores utilitários e diversão exercem forte efeito sobre a construção da confiança móvel e que este efeito é transferido para a atitude e intenção de comprar por meio de dispositivos móveis. A força do efeito da Confiança em relação à Atitude, neste estudo, é capaz de explicar 49 porcento da variância observada na Atitude, reforçando efeito mediador entre a Confiança dos consumidores e a intenção de compra por meio de dispositivos móveis. / [en] The present study evaluates the antecedents of mobile trust for its construction. A model that assembles subjective norms, interactive, utilitarian and hedonistic factors concerning the mobile commerce and its effects regarding the purchase intention. The data sample was collected from an online survey with 433 Brazilian consumers and the data was analyzed through a structural equation modeling. The results suggest that utilitarian factors and entertainment exert a strong effect in the construction of 0mobile trust and that this effect is transferred to the attitude and the purchase intention to buy through mobile devices. The effect of the force of Trust regarding Attitude in this study is able to explain the 49 percent variance observed in the Attitude, reinforcing the mediating effect between the Consumer trust and the purchase intention through mobile devices.

Natural language processing and Machine learning are subjects undergoing intense study nowadays. These fields are continually spreading, and are more interrelated than ever before. A case in point is text classification which is an instance of Machine learning(ML) application in Natural Language processing(NLP).Although these subjects have evolved over the recent years, they still have some problems that have to be considered. Some are related to the computing power techniques from these subjects require, whereas the others to how much training data they require.The research problem addressed in this thesis regards lack of knowledge on whether Machine learning techniques such as Word2Vec, Bidirectional encoder representations from transformers (BERT) and Support vector machine(SVM) classifier can be used for text classification, provided only a small training set. Furthermore, it is not known whether these techniques can be run on regular laptops.To solve the research problem, the main purpose of this thesis was to develop two separate conversational interfaces utilizing text classification techniques. These interfaces, provided with user input, can recognise the intent behind it, viz. classify the input sentence within a small set of pre-defined categories. Firstly, a conversational interface utilizing Word2Vec, and SVM classifier was developed. Secondly, an interface utilizing BERT and SVM classifier was developed. The goal of the thesis was to determine whether a small dataset can be used for intent classification and with what accuracy, and if it can be run on regular laptops.The research reported in this thesis followed a standard applied research method. The main purpose was achieved and the two conversational interfaces were developed. Regarding the conversational interface utilizing Word2Vec pre-trained dataset, and SVM classifier, the main results showed that it can be used for intent classification with the accuracy of 60%, and that it can be run on regular computers. Concerning the conversational interface utilizing BERT and SVM Classifier, the results showed that this interface cannot be trained and run on regular laptops. The training ran over 24 hours and then crashed.The results showed that it is possible to make a conversational interface which is able to classify intents provided only a small training set. However, due to the small training set, and consequently low accuracy, this conversational interface is not a suitable option for important tasks, but can be used for some non-critical classification tasks. / Natural language processing och maskininlärning är ämnen som forskas mycket om idag. Dessa områden fortsätter växa och blir allt mer sammanvävda, nu mer än någonsin. Ett område är textklassifikation som är en gren av maskininlärningsapplikationer (ML) inom Natural language processing (NLP).Även om dessa ämnen har utvecklats de senaste åren, finns det fortfarande problem att ha i å tanke. Vissa är relaterade till rå datakraft som krävs för dessa tekniker medans andra problem handlar om mängden data som krävs.Forskningsfrågan i denna avhandling handlar om kunskapsbrist inom maskininlärningtekniker som Word2vec, Bidirectional encoder representations from transformers (BERT) och Support vector machine(SVM) klassificierare kan användas som klassification, givet endast små träningsset. Fortsättningsvis, vet man inte om dessa metoder fungerar på vanliga datorer.För att lösa forskningsproblemet, huvudsyftet för denna avhandling var att utveckla två separata konversationsgränssnitt som använder textklassifikationstekniker. Dessa gränssnitt, give med data, kan känna igen syftet bakom det, med andra ord, klassificera given datamening inom ett litet set av fördefinierade kategorier. Först, utvecklades ett konversationsgränssnitt som använder Word2vec och SVM klassificerare. För det andra, utvecklades ett gränssnitt som använder BERT och SVM klassificerare. Målet med denna avhandling var att avgöra om ett litet dataset kan användas för syftesklassifikation och med vad för träffsäkerhet, och om det kan användas på vanliga datorer.Forskningen i denna avhandling följde en standard tillämpad forskningsmetod. Huvudsyftet uppnåddes och de två konversationsgränssnitten utvecklades. Angående konversationsgränssnittet som använde Word2vec förtränat dataset och SVM klassificerar, visade resultatet att det kan användas för syftesklassifikation till en träffsäkerhet på 60%, och fungerar på vanliga datorer. Angående konversationsgränssnittet som använde BERT och SVM klassificerare, visade resultatet att det inte går att köra det på vanliga datorer. Träningen kördes i över 24 timmar och kraschade efter det.Resultatet visade att det är möjligt att skapa ett konversationsgränssnitt som kan klassificera syften, givet endast ett litet träningsset. Däremot, på grund av det begränsade träningssetet, och konsekvent låg träffsäkerhet, är denna konversationsgränssnitt inte lämplig för viktiga uppgifter, men kan användas för icke kritiska klassifikationsuppdrag.

This thesis presents an activity mode intent recognition approach for safe, robust and reliable control of powered backbone exoskeleton. The thesis presents the background and a concept for a powered backbone exoskeleton that would work in parallel with a user. The necessary prerequisites for the thesis are presented, including the collection and processing of surface electromyography signals and inertial sensor data to recognize the user’s activity. The development of activity mode intent recognizer was described based on decision tree classification in order to leverage its computational efficiency. The intent recognizer is a high-level supervisory controller that belongs to a three-level control structure for a powered backbone exoskeleton. The recognizer uses surface electromyography and inertial signals as the input and CART (classification and regression tree) as the classifier. The experimental results indicate that the recognizer can extract the user’s intent with minimal delay. The approach achieves a low recognition error rate and a user-unperceived latency by using sliding overlapped analysis window. The approach shows great potential for future implementation on a prototype backbone exoskeleton.

Bakgrund: Eftersom användning av sociala medier har blivit vanligt har företag förändrat sättet att kommunicera från traditionell marknadsföring till influencer marketing. Det innebär att företagen använder opinion leaders, influencers eller kändisar, som frivilligt marknadsför varumärken på sociala medier. En influencer eller en så kallad opinion leader är någon som påverkar människors köpintention och köpbeslut genom sina sponsrade inlägg. Företag ger erbjudanden till influencers som betalda samarbeten för att rekommendera företagets produkter eller varumärken på sociala medier. Men sponsrade inlägg och samarbeten med influencers betraktas inte som reklam av konsumenterna. Det uppfattas som genuina rekommendationer eftersom influencer ses som expert inom ett område. De som följer influencers mest och studien kommer fokusera på är unga kvinnor. Metod: I denna studie utfördes en kvalitativ undersökning i form av semistrukturerade intervjuer. Tolv intervjuer genomfördes med unga kvinnor i åldrarna 20-29 år. Studien har genom dessa intervjuer undersökt vilken attityd unga kvinnliga konsumenter har på influencers och influencer marketing. Uppsatsen har en abduktiv ansats som utgångspunkt. Resultat: Studiens resultat indikerar att unga kvinnor har en reserverad och kluven attityd gentemot influencers. Detta berodde på tidigare erfarenheter där kvinnorna känt sig lurade samt upplever avsaknad genuinitet från influencers. Respondenternas attityder till betalda samarbeten och inlägg påverkas av mängden samarbeten, vilket påverkade om influencers uppfattades trovärdigt. Längre och mer konsistent samarbeten uppskattas mer och uppfattas mer genuint av respondenterna. Influencers som är mer relaterbara eller erbjuder rolig underhållning är två viktiga aspekter för att respondenterna valde att följa majoriteten av de influencers de följer. Ytterligare var det flertal respondenter som nämnde “inspiration” och att det var en anledning till att de använde dem plattformarna de gjorde samt följde specifika influencers. / Background: As the use of social media has become common, companies have changed the way of communicating from traditional marketing to influencer marketing. This means that companies use opinion leaders, influencers or celebrities, who voluntarily promote brands on social media. An influencer or a so-called opinion leader is someone who influences people's purchase intent and purchase decision through their sponsored posts. Companies give offers to influencers as paid collaborations to recommend the company's products or brands on social media. However, sponsored posts and collaborations with influencers are not considered advertising by consumers. It is perceived as genuine recommendations because the influencer is seen as an expert in a field. Those who follow influencers the most and the study will focus on are young women. Method: In this study, a qualitative study was carried out in the form of semi-structured interviews. Twelve interviews were conducted with young women aged 20–29. Through these interviews, the study has investigated the attitude of young female consumers towards influencers and influencer marketing. The essay has an abductive approach as a starting point. Conclusion: The study results indicate that young women have a reserved and ambivalent attitude towards influencers. This was due to previous experiences where the women felt deceived and experienced a lack of authenticity from influencers. Respondents' attitudes towards paid collaborations and posts are affected by the number of collaborations, which affected whether influencers were perceived as credible. Longer and more consistent collaborations are more appreciated and perceived more genuinely by the respondents. Influencers who are more relatable or offer fun entertainment are two important aspects why respondents chose to follow most of the influencers they follow. Furthermore, several respondents mentioned “inspiration” and that it was a reason why they used the platforms they did and followed specific influencers.

Esta investigación se realizó a partir de la necesidad de conocer el entorno del social commerce, comercio a través de las redes sociales, el cual se ve potenciado por el incremento del uso de plataformas digitales y comercio electrónico debido a la pandemia por la COVID – 19. El objetivo principal es determinar si existe relación entre la confianza en el social commerce y la intención de compra en los usuarios del rango etario entre 18 a 34 años que residen en Lima Metropolitana, durante el segundo semestre del 2020. Para lo cual, se mantuvo un enfoque en la plataforma Facebook, ya que es la que tiene mayor participación en el país y audiencia de diferentes edades. Se estudió la influencia de la confianza en el social commerce sobre la intención de compra a través de las siguientes dimensiones: familiaridad, búsqueda de información, presencial social y confianza. Se realizó una investigación cualitativa a través de la búsqueda de fuentes y entrevista a expertos; y una investigación cuantitativa mediante la ejecución de 400 encuestas, la cual mantiene una escala Likert. En el análisis de la investigación se halló que la confianza en el social commerce a través de Facebook está relacionada a las dimensiones expuestas, las cuales tienen una influencia positiva sobre la intención de compra. Esta investigación es de valor para empresas, agencias de medios, emprendedores o personas afines que buscan potenciar su alcance y ventas a través de esta red social. / This research was carried out based on the need to know the social commerce environment in Peru, which is enhanced by the increase in the use of digital platforms and e-commerce due to the COVID-19 pandemic. The main objective is to determine if there is a relationship between trust in social commerce and purchase intention in users aged from 18 to 34 years old, residents in Lima Metropolitana, in the second half of 2020. The focus was maintained on the Facebook platform, since it is the one with the highest participation in the country and audience of different ages. The influence of trust in social commerce on purchase intention was studied through the following dimensions: familiarity, information seeking, social presence and trust. A qualitative research was carried out by searching for information sources and interviewing experts; and a quantitative investigation through the execution of 400 surveys, which maintains a Likert scale. In the analysis of the research, it was found that trust in social commerce through Facebook is related to the exposed dimensions, which have a positive influence on the purchase intention. This research is valuable for companies, media agencies, entrepreneurs or related people who are looking to boost their reach and sales through this social networking site. / Tesis

Considering the current skepticism surrounding the impact and efficacy of nonprofit and nongovernmental organizations, some believe that a unique category of innovator known as the social entrepreneur may be society’s best hope for bringing innovative, scalable, and systemic solutions to bear on the world’s most intractable problems. Social entrepreneurs, as defined by Ashoka, have a unique set of characteristics that determine not only how they move within the world of social change-making but also how they communicate their ideas and mission to the public. This exploratory study reviewed how social entrepreneurs currently use documentary film and visual media in their communications strategy and public relations practice, what that tells us about the emerging culture of social entrepreneurs, and whether documentary, as defined by John Grierson, is an appropriate tool for these organizations. The author interviewed three founders, three communications professionals, and three filmmakers associated with social entrepreneurial organizations and observed a course for student filmmakers learning to make documentaries for social entrepreneurs. The findings of this study suggested that social entrepreneurs used documentary film as a communications tool when it aligned with their stated missions and goals but that cost, time, and control were significant barriers to implementation. Additionally, social entrepreneurs in all phases of development exhibited a unique set of cultural characteristics that interacted with the intent, content, and effect of their films in both positive and negative ways. The author also noted three distinct levels of filmmaker involvement with social entrepreneurial organizations that impacted the intent, content, and effect of their respective films. These levels of involvement are described as collaborative, independent, and interdependent. While the author offers some provocative observations about the role of documentary in social entrepreneurial organizations, this study remains exploratory in nature. She suggests several additional avenues of research that may further the scholarly conversation and continue to shed light on documentary film as communication for and by social entrepreneurs.

Communication with customers is a major part of customer experience as well as a great source of data mining. More businesses are engaging with consumers via text messages. Before 2020, 39% of businesses already use some form of text messaging to communicate with their consumers. Many more were expected to adopt the technology after 2020[1]. Email response rates are merely 8%, compared to a response rate of 45% for text messaging[2]. A significant portion of this communication involves customer enquiries or support messages sent in both directions. According to estimates, more than 80% of today’s data is stored in an unstructured format (suchas text, image, audio, or video) [3], with a significant portion of it being stated in ambiguous natural language. When analyzing such data, qualitative data analysis techniques are usually employed. In order to facilitate the automated examination of huge corpora of textual material, researchers have turned to natural language processing techniques[4]. Under the light of shared statistics above, Billogram[5] has decided that support messages between creditors and recipients can be mined for predictive maintenance purposes, such as early identification of an outlier like a bug, defect, or wrongly built feature. As one sentence goal definition, Billogram is looking for an answer to ”why are people reaching out to begin with?” This thesis project discusses implementing unsupervised clustering of support messages by benefiting from natural language processing methods as well as performance metrics of results to answer Billogram’s question. The research also contains intent recognition of clustered messages in two different ways, one automatic and one semi-manual, the results have been discussed and compared. LDA and manual intent assignment approach of the first research has 100 topics and a 0.293 coherence score. On the other hand, the second approach produced 158 clusters with UMAP and HDBSCAN while intent recognition was automatic. Creating clusters will help identifying issues which can be subjects of increased focus, automation, or even down-prioritizing. Therefore, this research lands in the predictive maintenance[9] area. This study, which will get better over time with more iterations in the company, also contains the preliminary work for ”labeling” or ”describing”clusters and their intents.

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