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This investigation aims to examine the differences and similarities between activity tracking technology users from two regions (the USA and Germany) in their intended privacy-related behavior. The focus lies on data handling after hypothetical discontinuance of use, data protection and privacy policy seeking, and privacy concerns.

The data was collected through an online survey in 2019. In order to identify significant differences between participants from Germany and the USA, the chi-squared test and the Mann–Whitney U test were applied.

The intensity of several privacy-related concerns was significantly different between the two groups. The majority of the participants did not inform themselves about the respective data privacy policies or terms and conditions before installing an activity tracking application. The majority of the German participants knew that they could request the deletion of all their collected data. In contrast, only 35% out of 68 participants from the US knew about this option.

This study intends to raise awareness about managing the collected health and fitness data after stopping to use activity tracking technologies. Furthermore, to reduce privacy and security concerns, the involvement of the government, companies and users is necessary to handle and share data more considerably and in a sustainable way.

This study sheds light on users of activity tracking technologies from a broad perspective (here, participants from the USA and Germany). It incorporates not only concerns and the privacy paradox but (intended) user behavior, including seeking information on data protection and privacy policy and handling data after hypothetical discontinuance of use of the technology.

Building on theoretical foundation of personal information management (PIM) in information science, this paper seeks to understand how activity tracker users manage their personal health information generated by their devices and to elucidate future activity tracking technology in support of personal health information management (PHIM). This paper aims to discuss this issue.

The authors conducted a web survey study with a specific group of activity tracker users – amateur runners. This survey collected both quantitative and qualitative data on participants’ engagement with activity tracking technology, their PHIM practices with the information generated by the technology and how their needs were being met by their activity tracking technology use and PHIM practices.

Amateur runners surveyed in this study exhibit long-term engagement and frequent interaction with activity tracking technology. They also engage in PHIM practices by using a range of PHIM tools and performing various PHIM activities. Furthermore, they use activity tracking technology and engage in PHIM practices to meet various health/fitness-related needs and information needs, while some of these needs such as performance needs and overarching needs are only partially met or unmet.

This research discusses amateur runners as power users of activity tracking technology, provides timely updates to PIM and PHIM research in light of a new type of personal health information, and generates design considerations for future activity tracking technology in support of PHIM. It also brings together previously disparate research regarding everyday life PHIM in information science, human–computer interaction and health informatics.

This paper aims to discuss research and design of learning activities involving activity tracking and wearable activity tracking technology.

Three studies are summarized as part of a program of research that sought to design new learning activities for classroom settings. The first used data from a qualitative interview study of adult athletes who self-track. The second used video excerpts from a designed learning activity with a group of fifth grade elementary students. The third study draws largely on quantitative assessment data from an activity tracking unit enactment in a rural sixth grade class.

Activity tracking appears to provide opportunities for establishing benchmarks and calibration opportunities related to intensity of physical activities. Those features of activity tracking can be leveraged to develop learning activities where elementary students discover features of data and how data are affected by different distributions. Students can show significant improvement related to statistical reasoning in classroom instructional units that centralize the use of self-tracked data.

As activity tracking is becoming a more ubiquitous practice with increased pervasiveness and familiarity with mobile and wearable technologies, this paper demonstrates a topical intersection between the information and learning sciences, illustrates how self-tracking can be recruited for instructional settings, and it discusses concerns that have emerged in the past several years as the technology related to activity tracking begins to be used for educational purposes.

The purpose of this article is to examine the ways in which self-tracking data have meaning and value in and after the life of the creator, including how such data could become part of the larger historical record, curated in an institutional archive. In doing so, the article expands upon existing shared interests among researchers working in the areas of self-tracking, human–computer interaction and archival science.

A total of 18 people who had self-tracked for six months or more were recruited for the study. Participants completed a survey which gathered demographic data and characteristics vis-à-vis their self-tracking behavior. In-person semi-structured interviews were then conducted to ascertain the beliefs of the participants regarding the long-term use and value of personal quantified-self data.

The findings reveal the value that people place on self-tracking data, their thoughts on proper modes for accessing their archive once it moves from the private to the public space, and how to provide fidelity within the system such that their experiences are represented while also enabling meaning making on the part of subsequent users of the archive.

Today’s quantified-self data are generally embedded in systems that create a pipeline from the individual source to that of the corporate warehouse, bent on absorbing and extracting insight from a totality of big data. This article posits that new opportunities for knowing and for design can be revealed when a public interest rationale is appended to rich personalized collections of small data.

Briefly reviews previous literature by the author before presenting an original 12 step system integration protocol designed to ensure the success of companies or countries in their efforts to develop and market new products. Looks at the issues from different strategic levels such as corporate, international, military and economic. Presents 31 case studies, including the success of Japan in microchips to the failure of Xerox to sell its invention of the Alto personal computer 3 years before Apple: from the success in DNA and Superconductor research to the success of Sunbeam in inventing and marketing food processors: and from the daring invention and production of atomic energy for survival to the successes of sewing machine inventor Howe in co‐operating on patents to compete in markets. Includes 306 questions and answers in order to qualify concepts introduced.

This study explores the drivers behind sports technology use and identifies the need for a new conceptualization of sports technology adoption. To address this issue, the authors create a new construct, “context-awareness,” with four dimensions: tracking, coaching, sharing and gamification.

The paper uses a mixed-method approach, including in-depth interviews and partial least squares structural equation modeling. The proposed model combines technology acceptance frameworks with the Sports Motivation Scale and a novel context-awareness scale. It is empirically tested with a diverse sample of 600 respondents to identify use-intention differences according to sports motivation and sport types.

The paper reveals group differences in sports type (dynamic vs nondynamic) and sports motivation (intrinsic vs extrinsic) regarding sports technology use. It also suggests that perceived technology characteristics mediate the relationship between context-aware features and intention to use.

This research introduces a new construct of “context-awareness” into the literature on new technology acceptance. The proposed model combines insights from information systems, sports science, sports marketing and sports medicine to explain the adoption of complex technology.

The purpose of this paper is to report the design and implementation of the enhanced participant-driven photo elicitation method in a qualitative interview study, to assess the performance of the method to investigate a research topic in everyday life health information behaviour and to provide insights on how to effectively use this method in future research.

The author embedded the enhanced participant-driven photo elicitation in a qualitative interview study to examine people’s everyday life health information behaviour with activity tracking technology. The author assessed the types of visual data collected by the method, categories of elicitation enabled by the method and how the method contributed to key research findings of the interview study.

The enhanced participant-driven photo elicitation generated rich, unique and meaningful data that would be otherwise difficult to collect through conventional qualitative interviews. The method also elicited explanation, rationalisation and reflection during the interviews, which enriched and triangulated key research findings. This work validated the benefits of the general photo elicitation method such as aiding participants’ recall of experiences, enriching research findings and improving research validity. It also demonstrated that the enhancement techniques used in this study could generate rich and even research data across interviews.

This paper describes the design and implementation of the enhanced participant-driven photo elicitation method to augment a qualitative interview study with activity tracker users. The author provides recommendations for researchers to take full advantage of the method in future everyday life health information behaviour research.

This study aims to characterize how ecosystem actors shape customer experience (CX). The study also proposes implications for managers and research regarding the customer ecosystem, its actors and actor constellations in the context of CXs.

A qualitative study is conducted among activity tracker users to identify how actors within their ecosystems shape CXs. Data include 28 in-depth interviews and ten self-reported diaries.

This study delineates six actor categories in the customer ecosystem shaping CX within and beyond the service. The number of actors and their importance to the focal customer in various actor constellations form individual-, brand- and socially driven ecosystems. These customer ecosystem types show how actors combine to drive CXs.

Researchers should shift their attention to experiences emerging in the customer’s lifeworld. A customer ecosystem highlights the customer-centered actor configuration emergent within the customer’s lifeworld. It is self-constructed based on the customer’s reference point.

Managers should aim to locate, monitor and join the customer’s lifeworld to gain more insight into how CXs emerge in the customer ecosystem based on customer logic.

Customers are not isolated actors simply experiencing service; rather, they construct idiosyncratic actor constellations that include various providers, social groups and peers.

This paper extends the theory on CXs by illustrating how the various actors and actor constellations forming the customer ecosystem shape CXs.

This paper presents a critical review of studies which map the urban environment using continuous physiological data collection. A conceptual model is consequently presented for mitigating urban stress at the city and the user level.

The study reviews relevant publications, examining the tools used for data collection and the methods used for data analysis and data fusion. The relationship between urban features and physiological responses is also examined.

The review showed that the continuous monitoring of physiological data in the urban environment can be used for location-aware stress detection and urban emotion mapping. The combination of physiological and contextual data helps researchers understand how the urban environment affects the human body. The review indicated a relationship between some urban features (green, land use, traffic, isovist parameters) and physiological responses, though more research is needed to solidify the existence of the identified links. The review also identified many theoretical, methodological and practical issues which hinder further research in this area.

While there is large potential in this field, there has been no review of studies which map continuously physiological data in the urban environment. This study covers this gap and introduces a novel conceptual model for mitigating urban stress.

Data-driven marketing is replacing conventional marketing strategies. The modern marketing strategy is based on insights derived from customer behavior information gathered from their facial expressions and neuro-signals. This study explores the potential for face recognition and neuro-marketing in modern-day marketing.

The study conducts an in-depth examination of the extant literature on neuro-marketing and facial recognition marketing. The articles for review are downloaded from the Scopus database, and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) is then used to screen and choose the relevant papers. The systematic literature review method is applied to conduct the study.

An extensive review of the literature reveals that the domains of neuro-marketing and face recognition marketing remain understudied. The authors’ review of selected papers delivers five neuro-marketing and facial recognition marketing themes that are essential to modern marketing concepts.

Neuro-marketing and facial recognition marketing are artificial intelligence (AI)-enabled marketing techniques that assist in gaining cognitive insights into human behavior. The findings would be of use to managers in designing marketing strategies to enhance their marketing approach and boost conversion rates.

The uniqueness of this study lies in that it provides an updated review on neuro-marketing and face recognition marketing.