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An overview of the current use of handwritten text recognition (HTR) on archival manuscript material, as provided by the EU H2020 funded Transkribus platform. It explains HTR, demonstrates Transkribus, gives examples of use cases, highlights the affect HTR may have on scholarship, and evidences this turning point of the advanced use of digitised heritage content. The paper aims to discuss these issues.

This paper adopts a case study approach, using the development and delivery of the one openly available HTR platform for manuscript material.

Transkribus has demonstrated that HTR is now a useable technology that can be employed in conjunction with mass digitisation to generate accurate transcripts of archival material. Use cases are demonstrated, and a cooperative model is suggested as a way to ensure sustainability and scaling of the platform. However, funding and resourcing issues are identified.

The paper presents results from projects: further user studies could be undertaken involving interviews, surveys, etc.

Only HTR provided via Transkribus is covered: however, this is the only publicly available platform for HTR on individual collections of historical documents at time of writing and it represents the current state-of-the-art in this field.

The increased access to information contained within historical texts has the potential to be transformational for both institutions and individuals.

This is the first published overview of how HTR is used by a wide archival studies community, reporting and showcasing current application of handwriting technology in the cultural heritage sector.

The purpose of this paper is to examine the influence of research evaluation policies and their interpretation on academics’ writing practices in three different higher education institutions and across three different disciplines. Specifically, the paper discusses how England’s national research excellence framework (REF) and institutional responses to it shape the decisions academics make about their writing.

In total, 49 academics at three English universities were interviewed. The academics were from one Science, Technology, Engineering and Mathematics discipline (mathematics), one humanities discipline (history) and one applied discipline (marketing). Repeated semi-structured interviews focussed on different aspects of academics’ writing practices. Heads of departments and administrative staff were also interviewed. Data were coded using the qualitative data analysis software, ATLAS.ti.

Academics’ ability to succeed in their career was closely tied to their ability to meet quantitative and qualitative targets driven by research evaluation systems, but these were predicated on an unrealistic understanding of knowledge creation. Research evaluation systems limited the epistemic choices available to academics, partly because they pushed academics’ writing towards genres and publication venues that conflicted with disciplinary traditions and partly because they were evenly distributed across institutions and age groups.

This work fills a gap in the literature by offering empirical and qualitative findings on the effects of research evaluation systems in context. It is also one of the only papers to focus on the ways in which individuals’ academic writing practices in particular are shaped by such systems.

The purpose of this paper is to describe and theorize the type of hate-love relationship to performance measurement systems (PMSs) that individual researchers tend to develop in academia. To this end, the paper draws upon Foucault’s writings on neoliberalism to analyse PMSs as neoliberal technologies holding certain qualities that can be expected to elicit such ambivalent views.

The paper is based on a qualitative interview study of researchers from three Swedish universities, who were asked to reflect upon questions related to three overall themes, namely, what it means to be a researcher in contemporary academia, the existence and use of PMSs at their universities and if/how such PMSs affected them and their work as researchers.

The empirical findings show that the hate-love relationship can be understood in terms of how PMSs are involved in three central moments of governmentality, where each such moment of governmentality tends to elicit feelings of ambivalence among researchers due to how PMSs rely on: a restricted centrifugal mechanism, normalization rather than normation and a view of individual academics as entrepreneurs of themselves.

Existing literature has provided several important insights into how the introduction and use of PMSs in academia tend to result in both negative and positive experiences and reactions. The current paper adds to this literature through theorizing how and why PMSs may be expected to elicit such ambivalent experiences and reactions among individual researchers.

The research carried out a bibliometric analysis of the literature on environmental sustainability from a demand perspective by analyzing the scientific contributions published in the last twenty years.

A bibliometric analysis was carried out to outline the scientific studies development, identifying the most discussed topics and those that would require future research. In total, 274 articles published between 1999 and 2021 were collected through the Web of Science database and analyzed with the SciMAT software.

By systematizing the literature results, the study revealed a steady growth in the number of publications and in the research areas, highlighting a substantial evolution of the research topic.

The study contribute for conceptual, methodological and thematic development of the topic, systematizing the results of existing studies and providing useful indications for the promotion of sustainable consumer habits.

The study attempts to bridge the gap in current literature by offering a holistic view on the role of consumer behavior in pursuing sustainability goals, identifying both the most treated areas and the emerging ones that can represent opportunities for future research.

The proliferation of (big) data provides numerous opportunities for service advances in practice, yet research on using data to advance service is at a nascent stage in the literature. Many studies have discussed phenomenological benefits of data to service. However, limited research describes managerial issues behind such benefits, although a holistic understanding of the issues is essential in using data to advance service in practice and provides a basis for future research. The purpose of this paper is to address this research gap.

“Using data to advance service” is about change in organizations. Thus, this study uses action research methods of creating real change in organizations together with practitioners, thereby adding to scientific knowledge about practice. The authors participated in five service design projects with industry and government that used different data sets to design new services.

Drawing on lessons learned from the five projects, this study empirically identifies 11 managerial issues that should be considered in data-use for advancing service. In addition, by integrating the issues and relevant literature, this study offers theoretical implications for future research.

“Using data to advance service” is a research topic that emerged originally from practice. Action research or case studies on this topic are valuable in understanding practice and in identifying research priorities by discovering the gap between theory and practice. This study used action research over many years to observe real-world challenges and to make academic research relevant to the challenges. The authors believe that the empirical findings will help improve service practices of data-use and stimulate future research.

Using the theory, construct, method, moderator (TCMM) format, this framework-based review critically analyses the mobile financial services (MFSs) field through a detailed synthesis and analysis of a sample of mainstream empirical research published in various scientific journals within the period 2009–2020.

The authors followed a three-step structured approach suggested by Webster and Watson (2002) to search for the literature to synthesise the global perspectives on MFSs and their associated applications and systems. The literature research resulted in the identification of 115 most relevant articles.

The authors identified three major categories or domains within the MFSs comprising the entire spectrum of digital financial services. To facilitate the literature analysis, TCMM is developed and proposed as an organising framework. Moreover, the authors also developed and presented the comprehensive framework of MFS domains and explicitly identified 14 different research themes for future research in MFSs.

Prior attempts to synthesise and analyse mainstream academic research in MFSs have been scant and limited to a specific MFS domain: mobile banking or mobile payment. The authors synthesised a more extensive body of knowledge and provided a global perspective on the MFS field. Unlike the past literature reviews which followed traditional frameworks such as antecedents, decisions and outcome (ADO); TCCM; and 6 W Framework (who, when, where, how, what and why), the authors developed and proposed TCMM as organising framework.

By envisioning the learning environment as an eco-social system, this study aims to map interrelated enablers of students’ sustainability-oriented learning (SoL) in the context of a university course at the interface of science and society.

A case-study approach was used to delineate what enables student learning in a university-wide transdisciplinary Master of Science course. A sample of 102 students, university and societal stakeholders participated to this study, by sharing their experiences and views through focus groups and questionnaires.

A main finding is the development of a configuration of six intertwined enablers that through their interplay help to cultivate students’ SoL, in the course under exploration.

This study paves the way for a re-orientation of how to explore learning in complex environments. It shows that adopting a relational, situated and systems approach is not only feasible but is also desirable to understand and guide learning practices in complex environments.

Agricultural workers represent an important part of the population exposed to high heat-related health and productivity risks. This study aims to estimate the heat-related productivity loss (PL) for moderate work activities in sun and shady areas and evaluating the economic cost locally in an Italian farm and generally in the whole province of Florence. Benefits deriving by working in the shade or work-time shifting were provided. Comparisons between PL estimated in Mediterranean (Florence, Italy) and subtropical (Guangzhou, China) areas were also carried out.

Meteorological data were collected during summers 2017–2018 through a station installed in a farm in the province of Florence and by two World Meteorological Organization (WMO)‐certified meteorological stations located at the Florence and Guangzhou airports. These data were used to calculate the wet-bulb globe temperature and to estimate the hourly PL and the economic cost during the typical working time (from 8 a.m. to 5 p.m.) and by advancing of 1 h and 2 h the working time. Significant differences were calculated through nonparametric tests.

The hourly PL and the related economic cost significantly decreased (p < 0.05) by working in the shade and by work-time shifting. Higher PL values were observed in Guangzhou than in Florence. The decrease of PL observed by work-time shifting was greater in Florence than in Guangzhou.

Useful information to plan suitable heat-related prevention strategies to counteract the effects of heat in the workplace are provided. These findings are essential to quantify the beneficial effects due to the implementation of specific heat-related adaptation measures to counter the impending effects of climate change.

With the aid of naturalistic simulations, this paper aims to investigate human behavior during manual and autonomous driving modes in complex scenarios.

The simulation environment is established by integrating virtual reality interface with a micro-simulation model. In the simulation, the vehicle autonomy is developed by a framework that integrates artificial neural networks and genetic algorithms. Human-subject experiments are carried, and participants are asked to virtually sit in the developed autonomous vehicle (AV) that allows for both human driving and autopilot functions within a mixed traffic environment.

Not surprisingly, the inconsistency is identified between two driving modes, in which the AV’s driving maneuver causes the cognitive bias and makes participants feel unsafe. Even though only a shallow portion of the cases that the AV ended up with an accident during the testing stage, participants still frequently intervened during the AV operation. On a similar note, even though the statistical results reflect that the AV drives under perceived high-risk conditions, rarely an actual crash can happen. This suggests that the classic safety surrogate measurement, e.g. time-to-collision, may require adjustment for the mixed traffic flow.

Understanding the behavior of AVs and the behavioral difference between AVs and human drivers are important, where the developed platform is only the first effort to identify the critical scenarios where the AVs might fail to react.

This paper attempts to fill the existing research gap in preparing close-to-reality tools for AV experience and further understanding human behavior during high-level autonomous driving.

This work aims to systematically analyze the inconsistency in driving patterns between manual and autopilot modes in various driving scenarios (i.e. multiple scenes and various traffic conditions) to facilitate user acceptance of AV technology.

A close-to-reality tool for AV experience and AV-related behavioral study. A systematic analysis in relation to the inconsistency in driving patterns between manual and autonomous driving. A foundation for identifying the critical scenarios where the AVs might fail to react.