Smartphones Adoption and Usage of 50+ Adults in the United Kingdom

This is an Accepted Manuscript of a book chapter published by Routledge in Jyoti Choudrie, Sherah Kurnia, and Panayiota Tsatsou, eds., Social Inclusion and Usability of ICT-enabled Services, on October 2017, available online at: https://www.routledge.com/Social-Inclusion-and-Usability-of-ICT-enabled-Services/Choudrie-Kurnia-Tsatsou/p/book/9781138935556. Under embargo until 30 April 2019.Peer reviewedFinal Accepted Versio

Investigating the adoption and use of smartphones in the UK : a silver-surfers perspective

Copyright and all rights therein are retained by the authors. All persons copying this information are expected to adhere to the terms and conditions invoked by each author's copyright. These works may not be re-posted without the explicit permission of the copyright holdersSmart phones are innovations that currently provide immense benefits and convenience to users in society. However, not all members of society are accepting and using smart phones; more specifically, for this research study silver-surfers or older adults (50+) are a demographic group displaying such an attitude. Currently, there is minimal knowledge of the reasons for older adults adopting and using smartphones. Bearing this in mind, this research study aims to investigate the adoption and usage behaviours of silver-surfers. For this purpose, the conceptual framework applied to this research draws factors from the following theories: Unified Theory of Acceptance and Use of Technology (UTAUT), the Diffusion of Innovations theory (DoI), and TAM3 (Technology Acceptance Model). From the online survey of 204 completed replies it was found that observability, compatibility, social influence, facilitating conditions, effort expectancy and enjoyment are important to the adoption and use of smartphones within silver-surfers. The contributions of this research are an identification and understanding of the factors that encourage or inhibit smartphone use within the older adult population. Second, this research can inform the design of computing devices and applications used for silver-surfers. Finally, this research can enlighten policy makers when forming decisions that encourage adoption and use of smartphones among silver surfersFinal Published versio

A behavioral choice model of the use of car-sharing and ride-sourcing services

There are a number of disruptive mobility services that are increasingly finding their way into the marketplace. Two key examples of such services are car-sharing services and ride-sourcing services. In an effort to better understand the influence of various exogenous socio-economic and demographic variables on the frequency of use of ride-sourcing and car-sharing services, this paper presents a bivariate ordered probit model estimated on a survey data set derived from the 2014-2015 Puget Sound Regional Travel Study. Model estimation results show that users of these services tend to be young, well-educated, higher-income, working individuals residing in higher-density areas. There are significant interaction effects reflecting the influence of children and the built environment on disruptive mobility service usage. The model developed in this paper provides key insights into factors affecting market penetration of these services, and can be integrated in larger travel forecasting model systems to better predict the adoption and use of mobility-on-demand servicesStatistic

iSEA: IoT-based smartphone energy assistant for prompting energy-aware behaviors in commercial buildings

Providing personalized energy-use information to individual occupants enables the adoption of energy-aware behaviors in commercial buildings. However, the implementation of individualized feedback still remains challenging due to the difficulties in collecting personalized data, tracking personal behaviors, and delivering personalized tailored information to individual occupants. Nowadays, the Internet of Things (IoT) technologies are used in a variety of applications including real-time monitoring, control, and decision-making due to the flexibility of these technologies for fusing different data streams. In this paper, we propose a novel IoT-based smartphone energy assistant (iSEA) framework which prompts energy-aware behaviors in commercial buildings. iSEA tracks individual occupants through tracking their smartphones, uses a deep learning approach to identify their energy usage, and delivers personalized tailored feedback to impact their usage. iSEA particularly uses an energy-use efficiency index (EEI) to understand behaviors and categorize them into efficient and inefficient behaviors. The iSEA architecture includes four layers: physical, cloud, service, and communication. The results of implementing iSEA in a commercial building with ten occupants over a twelve-week duration demonstrate the validity of this approach in enhancing individualized energy-use behaviors. An average of 34% energy savings was measured by tracking occupants’ EEI by the end of the experimental period. In addition, the results demonstrate that commercial building occupants often ignore controlling over lighting systems at their departure events that leads to wasting energy during non-working hours. By utilizing the existing IoT devices in commercial buildings, iSEA significantly contributes to support research efforts into sensing and enhancing energy-aware behaviors at minimal costs

Magic mirror on the wall: Selfie-related behavior as mediator of the relationship between narcissism and problematic smartphone use

Objective: Recent research has suggested that problematic smartphone use is associated with several psychological factors and that mobile apps and smartphone-related behavior (i.e. selfi e behavior) may encourage the development of problematic smartphone use. However, little is known about how the interplay between dysfunctional personality characteristics and selfi e-related behavior can infl uence problematic smartphone use. The aim of this study was to examine the relationship between narcissism and problematic smartphone use, as well as the mediating role of selfi e-related behavior in this relationship among young men and women. Method: In the current study, a total of 627 undergraduate students (283 males and 344 females) completed a cross-sectional survey. A structural equation model was tested separately for males and females in order to evaluate the associations between narcissism, selfi e-related behavior and problematic smartphone use. Results: The results showed that greater narcissism was related to increased selfi e-related behavior, which in turn were positively associated with problematic smartphone use both for males and females. However, selfi e-related behavior mediated the relationship between narcissism and problematic smartphone use only for females. Conclusions: The study provides fresh insight into our understanding of the psychological mechanisms underlying problematic smartphone use, which may inform prevention and treatment interventions

Effect of Values and Technology Use on Exercise: Implications for Personalized Behavior Change Interventions

Technology has recently been recruited in the war against the ongoing obesity crisis; however, the adoption of Health & Fitness applications for regular exercise is a struggle. In this study, we present a unique demographically representative dataset of 15k US residents that combines technology use logs with surveys on moral views, human values, and emotional contagion. Combining these data, we provide a holistic view of individuals to model their physical exercise behavior. First, we show which values determine the adoption of Health & Fitness mobile applications, finding that users who prioritize the value of purity and de-emphasize values of conformity, hedonism, and security are more likely to use such apps. Further, we achieve a weighted AUROC of .673 in predicting whether individual exercises, and we also show that the application usage data allows for substantially better classification performance (.608) compared to using basic demographics (.513) or internet browsing data (.546). We also find a strong link of exercise to respondent socioeconomic status, as well as the value of happiness. Using these insights, we propose actionable design guidelines for persuasive technologies targeting health behavior modification

Multifaceted companion devices: applying the new model of media attendance to smartphone usage

This study inspects the relationship between outcome expectations, habit strength, and smartphone usage by attempting to validate the new model of media attendance (NMMA) (LaRose and Eastin, 2004) , a social-cognitive theory of uses and gratifications. The fast adoption rate of smartphones, and their inherent characteristics as convergent, always-on, always-connected devices, warrant a closer look into user habitualization of this medium. Using a sample of 481 smartphone users selected from a larger panel, we were able to support the NMMA, although surprisingly no significant effect of habit strength on smartphone usage was found. While some uncertainties connected to the method are noted, this suggests a more complex reality, in which habitualization of a convergent media device does not necessarily implicate a significant rise in usage

Daily Stress Recognition from Mobile Phone Data, Weather Conditions and Individual Traits

Research has proven that stress reduces quality of life and causes many diseases. For this reason, several researchers devised stress detection systems based on physiological parameters. However, these systems require that obtrusive sensors are continuously carried by the user. In our paper, we propose an alternative approach providing evidence that daily stress can be reliably recognized based on behavioral metrics, derived from the user's mobile phone activity and from additional indicators, such as the weather conditions (data pertaining to transitory properties of the environment) and the personality traits (data concerning permanent dispositions of individuals). Our multifactorial statistical model, which is person-independent, obtains the accuracy score of 72.28% for a 2-class daily stress recognition problem. The model is efficient to implement for most of multimedia applications due to highly reduced low-dimensional feature space (32d). Moreover, we identify and discuss the indicators which have strong predictive power.Comment: ACM Multimedia 2014, November 3-7, 2014, Orlando, Florida, US

The role of an omnipresent pocket device : smartphone attendance and the role of user habits

Smartphones are convergent, always-on pocket devices that have taken up an important role in the life of their users. This warrants a closer look into how this medium is used in every-day situations. Are goal-oriented incentives the main drive for smartphone usage, or do habits play a critical role? This study with 481 Belgian smartphone users attempts to describe the precedents of smartphone attendance by validating the model of media attendance (MMA), a social-cognitive theory of uses and gratifications (LaRose & Eastin, 2004). We surprisingly did not find evidence for a significant effect of habits on smartphone usage. We suggest two explanations. First, we suggest some uncertainties concerning the MMA methodology. Second, we suggest a more complex reality in which several habitual use patterns are shaped, dependent on user, context and device. This warrants a more in-depth study, using more advanced measures for smartphone usage and habit strength