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A new research domain known as the Quantified Self has recently emerged and is described as gaining self-knowledge through using wearable technology to acquire information on self-monitoring activities and physical health related problems. However, very little is known about the impact of time window models on discovering self-quantified patterns that can yield new self-knowledge insights. This paper aims to discover the self-quantified patterns using multi-time window models.

This paper proposes a multi-time window analytical workflow developed to support the streaming k-means clustering algorithm, based on an online/offline approach that combines both sliding and damped time window models. An intervention experiment with 15 participants is used to gather Fitbit data logs and implement the proposed analytical workflow.

The clustering results reveal the impact of a time window model has on exploring the evolution of micro-clusters and the labelling of macro-clusters to accurately explain regular and irregular individual physical behaviour.

The preliminary results demonstrate the impact they have on finding meaningful patterns.

The purpose of this paper is to find out tourism movement patterns via the tracking of tourists with the help of positioning systems like GPS in the rural area of the Lake Constance destination in Germany. In doing so past, present and future of tourist tracking is illustrated.

The tracking is realized via common smartphones extended by an app, with dedicated sensors like position loggers and a survey. The three different approaches are applied in order to compare and cross-check results (triangulation of data and methods).

Movement patterns turned out to be diverse and individualistic within the rural destination of Lake Constance and following an ants trail in sub-destinations like the city of Constance. Repeat visitors and first-time visitors alike always visit the bigger cities and main day-trip destinations of the Lake. A possible prediction tool enables new avenues of governing tourism movement patterns.

The tracking techniques can be developed further into the direction of “quantified self” using gamification in order to make the tracking app even more attractive.

An algorithm-based prediction tool would offer new perspectives to the management of tourism movements.

Further research is needed to overcome the feeling of invasiveness of the app to allow tracking with that approach.

This study is original and innovative because of the first-time use of a smartphone app in tourist tracking, the application on a rural destination and the conceptual description of a prediction tool.

The purpose of this paper is to expand current knowledge about the recent trend of wearable technology to assess both its potential in the work environment and the challenges concerning the utilisation of wearables in the workplace.

After establishing exclusion and inclusion criteria, an independent systematic search of the ACM Digital Library, IEEE Xplore, ScienceDirect and Web of Science databases for relevant studies was performed. Out of a total of 359 articles, 34 met the selection criteria.

This review identifies 23 categories of wearable devices. Further categorisation of the devices based on their utilisation shows they can be used in the work environment for activities including monitoring, augmenting, assisting, delivering and tracking. The review reveals that wearable technology has the potential to increase work efficiency among employees, improve workers’ physical well-being and reduce work-related injuries. However, the review also reveals that technological, social, policy and economic challenges related to the use of wearable devices remain.

Many studies have investigated the benefits of wearable devices for personal use, but information about the use of wearables in the work environment is limited. Further research is required in the fields of technology, social challenges, organisation strategies, policies and economics to enhance the adoption rate of wearable devices in work environments.

Previous studies indicate that occupational stress and injuries are detrimental to employees’ health; this paper analyses the use of wearable devices as an intervention method to monitor or prevent these problems. Introducing a categorisation framework during implementation may help identify which types of device categories are suitable and could be beneficial for specific utilisation purposes, facilitating the adoption of wearable devices in the workplace.

Institutional and commercial web profiles that provide biobibliographic information about researchers are used for promotional purposes but also as information sources. In the latter case, the profiles' (re)presentations of researchers may be used to assess whether a researcher can be trusted. The article introduces a conceptual framework of how trust in researchers may be formed based on how the researchers' experiences and achievements are mobilized on the profiles to tell a multifaceted story of the “self.”

The framework is an analytical product which draws on theories of trust as well as on previous research focused on academic web profiles and on researchers' perceptions of trust and credibility. Two dimensions of trust are identified as central to the theoretical construction of trust, namely competence and trustworthiness.

The framework outlines features of profile content and narrative that may influence the assessment of the profile and of the researcher's competence and trustworthiness. The assessment is understood as shaped by the frames of interpretation available to a particular audience.

The framework addresses the lack of a trust perspective in previous research about academic web profiles. It provides an analysis of how potential trust in the researcher may be formed on the profiles. An innovative contribution is the acknowledgement of both qualitative and quantitative indicators of trustworthiness and competence, including the richness of the story told about the “self.”

The competition in the academe has always been tough, but today, the academe seems to be more like an industry than an academic community as academics are evaluated through quantified and economic means.

This article leans on Heidegger’s thoughts on the essence of technology and his ontological view on being to show the dangers that lie in this quantification of researchers and research.

Despite the benefits that information systems (ISs) offer to people and research, it seems that technology has made it possible to objectify researchers and research. This has a negative impact on the academe and should thus be looked into especially by the IS field, which should note the problems that exist in its core. This phenomenon of quantified academics is clearly visible at academic quantification sites, where academics are evaluated using metrics that count their output. It seems that the essence of technology has disturbed the way research is valued by emphasising its quantifiable aspects. The study claims that it is important to look for other ways to evaluate researchers rather than trying to maximise research production, which has led to the flooding of articles that few have the time or interest to read.

This paper offers new insights into the current phenomenon of quantification of academics and underlines the need for critical changes if in order to achieve the academic culture that is desirable for future academics.

This chapter, based on a sociological approach, addresses the ethical issues of surveillance research from the perspective of the profound transformations that science and innovation are undergoing, as part of a broader shift from modern to post-modern society, affecting also other major social institutions (such as government, religion, family, and public administration). The change occurring in the science and technology system is characterised by diminishing authority, uncertainty about internal mechanisms and standards, and a declining and increasingly difficult access to resources. Such changes, also related to globalisation and new digital technologies, have transformed the way research is conducted and disseminated. Research is now more open and its results more easily accessible to citizens.

Scientific research is also put under increased public scrutiny, while, at the same time, public distrust and disaffection towards science is rising. In such a context, it is more important than ever to make sure that research activities are not compromised by fraudulent and unethical practices. The legitimate expectations of citizens to enjoy their rights, including the ability to protect their private sphere, are growing. Scientific and technological development is deeply interrelated with the widespread awareness of these rights and the possibility of exercising them, but it produces also new risks, while a widespread sense of insecurity increases. The digital revolution, while improving people’s quality of life, offers at the same time new opportunities for crime and terrorism, which in turn has produced a demand to strengthen security systems through increasingly advanced and intrusive surveillance technologies. Misconduct in the field of surveillance may not only undermine the quality of research, but also further impair society’s trust in research and science as well as in the State and its institutions.

This paper aims to address which resources provided by an entrepreneurial ecosystem (EE) are necessary for deep technology entrepreneurship.

The authors used a novel approach known as necessary condition analysis (NCA) to data on EEs and deep-tech startups from 132 countries, collected in a global innovation index and Crunchbase data sets. The NCA makes it possible to identify whether an EEs resource is a necessary condition that enables entrepreneurship.

Necessary conditions are related to political and business environment; education, research and development; general infrastructure; credit; trade; diversification and market size; and knowledge absorption capacity.

The results show that business and political environments are the most necessary conditions to drive deep-tech entrepreneurship.

Policymakers could prioritize conditions that maximize entrepreneurial output levels rather than focusing on less necessary elements.

Some resources require less performance than others. So, policymakers should consider allocating policy efforts to strengthen resources that maximize output levels.

Studies on deep-tech entrepreneurship are scarce. This study provides a bottleneck analysis that can guide the formulation of policies to support deep-tech entrepreneurship, as it allows to identify priority areas for resource allocation.

Representations of time are commonly used to construct narratives in visualisations of data. However, since time is a value-laden concept, and no representation can provide a full, objective account of “temporal reality”, they are also biased and political: reproducing and reinforcing certain views and values at the expense of alternative ones. This conceptual paper aims to explore expressions of temporal bias and politics in data visualisation, along with possibly mitigating user approaches and design strategies.

This study presents a theoretical framework rooted in a sociotechnical view of representations as biased and political, combined with perspectives from critical literacy, radical literacy and critical design. The framework provides a basis for discussion of various types and effects of temporal bias in visualisation. Empirical examples from previous research and public resources illustrate the arguments.

Four types of political effects of temporal bias in visualisations are presented, expressed as limitation of view, disregard of variation, oppression of social groups and misrepresentation of topic and suggest that appropriate critical and radical literacy approaches require users and designers to critique, contextualise, counter and cross beyond expressions of the same. Supporting critical design strategies involve the inclusion of multiple datasets and representations; broad access to flexible tools; and inclusive participation of marginalised groups.

The paper draws attention to a vital, yet little researched problem of temporal representation in visualisations of data. It offers a pioneering bridging of critical literacy, radical literacy and critical design and emphasises mutual rather than contradictory interests of the empirical sciences and humanities.

This study aims to offer novel insights on how industrial marketing might contribute to bringing innovations to market in the peculiar case of health care. This study aims at shedding first light on how the alignment between dissemination and exploitation activities might contribute to bringing to market innovations developed by public–private partnerships funded by the European Commission (EC).

The theoretical development comes from an inductive research design based on the 42-month pan-European H2020 research project NESTORE aimed at developing an integrated portfolio of innovations for the healthy aging of European citizens.

This study advances the theory and practice of industrial marketing in health care by conceptualizing an actionable method to align dissemination and exploitation activities within EC-funded projects, facilitating that innovations will go to market. The method is composed of five phases. First, an external analysis to define market opportunities and users’/stakeholders’ needs. Second, an internal analysis to identify the most promising exploitable outputs. Third, scenarios crystallization to define the most suitable scenarios (business models) to bring the selected exploitable outputs to market. Fourth, exploitation and dissemination alignment through the identification and involvement of the most relevant stakeholders. Fifth, scenario refinement and business plan.

This study is relevant because many EC-funded projects still fail to move innovations from labs to market, thus limiting the benefits for the European citizens and the competitiveness of Europe with respect to the USA and China. Although this relevance, past studies overlooked the peculiar context of EC-funded innovation projects, privileging pharmaceutical and biomedical companies. This study advance theory and practice of industrial marketing in health care.