User Satisfaction with Wearables

This study investigates user satisfaction with wearable technologies. It proposes that the integration of expectation confirmation theory with affordance theory sheds light on the sources of user’s (dis)confirmation when evaluating technology performance experiences and explains the origins of satisfaction ratings. A qualitative and quantitative analysis of online user reviews of a popular fitness wristband supports the research model. Since the band lacks buttons and numeric displays, users need to interact with the companion software to obtain the information they need. Findings indicate that satisfaction depends on the interaction’s quality, the value of digitalizing physical activity, and the extent to which the informational feedback meets users’ needs. Moreover, the results suggest that digitalizing physical activity has different effects for different users. While some appreciate data availability in general regardless of their accuracy, those who look for precision do not find such quantification useful. Thus, their evaluative judgments depend on the wearable system’s actual performance and the influence that the feedback has on their pursuit of their fitness goals. These results provide theoretical and practical contributions to advance our understanding of wearable technologies

Using big data for customer centric marketing

This chapter deliberates on “big data” and provides a short overview of business intelligence and emerging analytics. It underlines the importance of data for customer-centricity in marketing. This contribution contends that businesses ought to engage in marketing automation tools and apply them to create relevant, targeted customer experiences. Today’s business increasingly rely on digital media and mobile technologies as on-demand, real-time marketing has become more personalised than ever. Therefore, companies and brands are striving to nurture fruitful and long lasting relationships with customers. In a nutshell, this chapter explains why companies should recognise the value of data analysis and mobile applications as tools that drive consumer insights and engagement. It suggests that a strategic approach to big data could drive consumer preferences and may also help to improve the organisational performance.peer-reviewe

Big data and Sentiment Analysis considering reviews from e-commerce platforms to predict consumer behavior

Treballs Finals del Màster de Recerca en Empresa, Facultat d'Economia i Empresa, Universitat de Barcelona, Curs: 2019-2020, Tutor: Javier Manuel Romaní Fernández ; Jaime Gil LafuenteNowadays and since the last two decades, digital data is generated on a massive scale, this phenomenon is known as Big Data (BD). This phenomenon supposes a change in the way of managing and drawing conclusions from data. Moreover, techniques and methods used in artificial intelligence shape new ways of analysis considering BD. Sentiment Analysis (SA) or Opinion Mining (OM) is a topic widely studied for the last few years due to its potential in extracting value from data. However, it is a topic that has been more explored in the fields of engineering or linguistics and not so much in business and marketing fields. For this reason, the aim of this study is to provide a reachable guide that includes the main BD concepts and technologies to those who do not come from a technical field such as Marketing directors. This essay is articulated in two parts. Firstly, it is described the BD ecosystem and the technologies involved. Secondly, it is conducted a systematic literature review in which articles related with the field of SA are analysed. The contribution of this study is a summarization and a brief description of the main technologies behind BD, as well as the techniques and procedures currently involved in SA

Are HIV smartphone apps and online interventions fit for purpose?

Sexual health is an under-explored area of Human-Computer Interaction (HCI), particularly sexually transmitted infections such as HIV. Due to the stigma associated with these infections, people are often motivated to seek information online. With the rise of smartphone and web apps, there is enormous potential for technology to provide easily accessible information and resources. However, using online information raises important concerns about the trustworthiness of these resources and whether they are fit for purpose. We conducted a review of smartphone and web apps to investigate the landscape of currently available online apps and whether they meet the diverse needs of people seeking information on HIV online. Our functionality review revealed that existing technology interventions have a one-size-fits-all approach and do not support the breadth and complexity of HIV-related support needs. We argue that technology-based interventions need to signpost their offering and provide tailored support for different stages of HIV, including prevention, testing, diagnosis and management

Harnessing the power of the general public for crowdsourced business intelligence: a survey

International audienceCrowdsourced business intelligence (CrowdBI), which leverages the crowdsourced user-generated data to extract useful knowledge about business and create marketing intelligence to excel in the business environment, has become a surging research topic in recent years. Compared with the traditional business intelligence that is based on the firm-owned data and survey data, CrowdBI faces numerous unique issues, such as customer behavior analysis, brand tracking, and product improvement, demand forecasting and trend analysis, competitive intelligence, business popularity analysis and site recommendation, and urban commercial analysis. This paper first characterizes the concept model and unique features and presents a generic framework for CrowdBI. It also investigates novel application areas as well as the key challenges and techniques of CrowdBI. Furthermore, we make discussions about the future research directions of CrowdBI

“Gaining Control” Women’s Health on Period and Pregnancy Trackers

This project conducts a discourse analysis on four FemTech platforms: Clue, Flo, Ovia, and Sprout. It interrogate how these apps market their services and shape user attitudes about health. This analysis takes place in four sections: (1) visuals, (2) language, (3) services, and (4) terms of use and privacy. This project makes an argument for how FemTech replicates rather than mitigate disparities in the U.S healthcare system

Understanding the Association between Star Ratings and Review Helpfulness: The Perspectives of Expectation Confirmation Theory and Negativity Bias

Consisting of textual, multimedia, and numerical information elements, online consumer reviews (OCR) have been considered an essential information source of products for prospective consumers. Researchers have made significant efforts to comprehend how these information elements are associated with OCRs’ information value or helpfulness. However, there is a paucity of theoretical evidence on consumers’ perception and evaluation of star ratings and their information, even though star ratings as numerical information cues can imply multiple meanings. In this study, we leverage (1) expectation-confirmation theory to delineate star ratings as the extent of consumer satisfaction and (2) negativity bias to explain the relationship between star ratings and helpfulness. Using 45,621 reviews of 20 products across three categories, we empirically find that our theoretical approaches improve our understanding of the effect of star ratings on helpfulness. Therefore, this study contributes to the extant literature on OCRs by providing the theory-based evaluation of star ratings in relation to helpfulness

This other atmosphere: against human resources, Emoji, and devices

Frequently humans are invited to engage with modern visual forms: emoji, emoticons, pictograms. Some of these forms are finding their ways into the workplace, understood as augmentations to workplace atmospheres. What has been called the ‘quantified workplace’ requires its workers to log their rates of stress, wellbeing, their subjective sense of productivity on scale of 1-5 or by emoji, in a context in which HR professionals develop a vocabulary of Workforce Analytics, People Analytics, Human Capital Analytics or Talent Analytics, and all this in the context of managing the work environment or its atmosphere. Atmosphere is mood, a compote of emotions. Emotions are a part of a human package characterised as ‘the quantified self’, a self intertwined with - subject to but also compliant with - tracking and archiving. The logical step for managing atmospheres is to track emotions at a granular and largescale level. Through the concept of the digital crowd, rated and self-rating, as well as emotion tracking strategies, the human resource (as worker and consumer) engages in a new politics of the crowd, organised around what political philosopher Jodi Dean calls, affirmatively, ‘secondary visuality’, high circulation communication fusing together speech, writing and image as a new form. This is the visuality of communicative, or social media, capitalism. But to the extent that it is captured by HR, is it an exposure less to crowdsourced democracy, and more a stage in turning the employee into an on-the-shelf item in a digital economy warehouse, assessed by Likert scales? While HR works on new atmospheres of work, what other atmospheres pervade the context of labour, and can these be deployed in the generation of other types of affect, ones that work towards the free association of labour and life