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This study aims to investigate the impact of technologies on the knowledge transfer process. In particular, the authors aim to analyze the topic of knowledge brokers and the relationship between broker and digital tools in the knowledge transfer process in the sport context. The study developed, therefore, aims to investigate the creating of this environment for knowledge transfer and knowledge sharing between man and machine, looking to improve the planning of technical sports projects of the clubs.

This paper presents a qualitative approach aimed at analyzing how platforms and the players’ agents can be useful tools in the knowledge transfer process. The research was conducted through a survey with a structured questionnaire via e-mail to 64 managers at the head of clubs playing in the Italian Series B basketball in the 2021–2022 championship. The total number of questions administered is 21.

The results demonstrate how sports directors, for the construction of a technical sports project, in addition to learning off the pitch by interactions with media, fans, pressure management, leadership skills, positive attitude, tolerance, understanding of other opinions, background and cultures, see the athletes’ agents as the main stakeholder of the managers. The research resulted, by the clubs’ managers, in both formal learning and informal-type learning. Informal learning, by far the most frequently used and most important in the general learning process of executives, is identified in the use that executives make of information available on digital platforms and of the fiduciary relationships that management has with players’ agents.

The results demonstrate the valuable opportunities for executives, coaches, managers and clubs to strategically manage learning and knowledge sharing. Improving and managing knowledge-sharing strategies would help increase knowledge, not only of the sports directors but also of the entire club, thus improving the absolute quality of the game within the Italian basketball divisions. The authors have developed an innovative framework regarding the construction of a “typed sports technical project”, and the authors have identified a series of crucial phases capable of determining the creation of a new roster of athletes.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

It has been demonstrated that AI-powered, data-driven tools’ usage is not universal, but deeply linked to socio-cultural contexts. The purpose of this paper is to display the need of adopting situated lenses, relating to specific personal and professional learning about data protection and privacy.

The authors introduce the results of a case study based on a large educational intervention at a fully online university. The views of the participants from degrees representing different knowledge areas and contexts of technology adoption (work, education and leisure) were explored after engaging in the analysis of the terms and conditions of use about privacy and data usage. After consultation, 27 course instructors (CIs) integrated the activity and worked with 823 students (702 of whom were complete and correct for analytical purposes).

The results of this study indicated that the intervention increased privacy-conscious online behaviour among most participants. Results were more contradictory when looking at the tools’ daily usage, with overall positive considerations around the tools being mostly needed or “indispensable”.

Though appliable only to the authors’ case study and not generalisable, the authors’ results show both the complexity of privacy views and the presence of forms of renunciation in the trade-off between data protection and the need of using a specific software into a personal and professional context.

This study provides an example of teaching and learning activities that supports the development of data literacy, with a focus on data privacy. Therefore, beyond the research findings, any educator can build over the authors’ proposal to produce materials and interventions aimed at developing awareness on data privacy issues.

Developing awareness, understanding and skills relating to data privacy is crucial to live in a society where digital technologies are used in any area of our personal and professional life. Well-informed citizens will be able to obscure, resist or claim for their rights whenever a violation of their privacy takes place. Also, they will be able to support (through adoption) better quality apps and platforms, instead of passively accepting what is evident or easy to use.

The authors specifically spot how students and educators, as part of a specific learning and cultural ecosystem, need tailored opportunities to keep on reflecting on their degrees of freedom and their possibilities to act regarding evolving data systems and their alternatives.

This paper aims to assess whether the current eResearch Knowledge Centre’s (eRKC) research support practices align with researchers’ requirements for achieving their research objectives. The study’s objectives were to assess the current eRKC research support services and to determine which are adequate and which are not in supporting the Human Sciences Research Council (HSRC) researchers.

This study uses interviews as part of the qualitative approach. The researcher chose to use interviews, as some aspects warranted further explanation during the interview. The interviews were scheduled using Zoom’s scheduling assistant. The interviews were semi-structured, guided by a flexible interview procedure and supplemented by follow-up questions, probes and comments. The research life cycle questions guided the interviews. The data obtained were coded and transcribed using MS Excel. The interview data were analysed, using NVivo, according to the themes identified in the research questions and aligned with the theory behind the study. Pre-determined codes were created in line with the six stages of the research life cycle and applied to group the data and extract meaning from each category. Interviewee responses were assigned to groups in line with the stages of the research life cycle.

The current eRKC research support services are aligned with the needs of HSRC researchers and highlight services that could be expanded or promoted more effectively to HSRC researchers. It proposes a new service, data analysis, and suggests that the eRKC could play a more prominent role in research impact, research data management and fostering collaboration with HSRC research divisions.

This study is limited to assessing the eRKC’s support practices at the HSRC in Pretoria, South Africa. A more comprehensive study is needed for HSRC research services, capabilities and capacity.

Assessment of eRKC followed a comprehensive interviewee schedule that followed Raju and Schoombee’s research life cycle model.

Zoom’s scheduling assistant may have generated Zoom fatigue and reduced productivity. Technical issues, losing time, communication gaps and distant time zones may have affected face-to-face interaction.

eRKC research support practices are rare in South Africa and most parts of the world. This study bridges the gap between theory and practice in assessing eRKC research support practices.

Data science promises new opportunities for organizational decision-making. Data scientists arguably play an important role in this regard and one can even observe a certain “buzz” around this nascent occupation. This paper enquires into how data scientists construct their occupational identity and the challenges they experience when enacting it.

Based on semi-structured interviews with data scientists working in different industries, the authors explore how these actors draw on their educational background, work experiences and perception of the contemporary digitalization discourse to craft their occupational identities.

The authors identify three main components of data scientists’ occupational identity: a scientific mindset, an interest in sophisticated forms of data work and a problem-solving attitude. The authors demonstrate how enacting this identity is sometimes challenged through what data scientists perceive as either too low or too high expectations that managers form towards them. To address those expectations, they engage in outward-facing identity work by carrying out educational work within the organization and (paradoxically) stressing both prestigious and non-prestigious parts of their work to “tame” the ambiguity and hype they perceive in managers’ expectations. In addition, they act upon themselves to better appreciate managers’ perspectives and expectations.

This study contributes to research on data scientists as well as the accounting literature that often refers to data scientists as new competitors for accountants. It cautions scholars and practitioners alike to be careful when discussing the possibilities and limitations of data science concerning advancements in accounting and control.

Self-regulated learning (SRL) is crucial for successful learning and lifelong learning in today’s rapidly changing world, yet research has shown that many learners need support for SRL. Recently, learning analytics has offered exciting opportunities for better understanding and supporting SRL. However, substantial endeavors are still needed not only to detect learners’ SRL processes but also to incorporate human values, individual needs and goals into the design and development of self-regulated learning analytics (SRLA). This paper aims to examine the challenges that lifelong learners faced in SRL, their needs and desirable features for SRLA.

This study triangulated data collected from three groups of educational stakeholders: focus group discussions with lifelong learners (n = 27); five teacher interviews and four expert evaluations. The groups of two or three learners discussed perceived challenges, support needs and willing-to-share data contextualized in each phase of SRL.

Lifelong learners in professional development programs face challenges in managing their learning time and motivation, and support for time management and motivation can improve their SRL. This paper proposed and evaluated a set of design principles for SRLA.

This paper presents a novel approach for theory-driven participatory design with multistakeholders that involves integrating learners, teachers and experts’ perspectives for designing SRLA. The results of the study will answer the questions of how learners’ voices can be integrated into the design process of SRLA and offer a set the design principles for the future development of SRLA.

Uncertainty management (UM) in projects has been a point of attention for researchers for many years. Research on UM has mainly been aimed at uncertainty analyses in the front-end and managing uncertainty in the construction phase. In contrast, UM components in the design phase have received less attention. This research aims to improve knowledge about the key components of UM in the design phase of large road projects.

This study adopted a literature review and case study. The literature review was used to identify relevant criteria for UM. These criteria helped to design the interview guide. Multiple case study research was conducted, and data were collected through document study and interviews with project stakeholders in two road projects. Each case's owners, contractors and consultants were interviewed individually.

The data analysis obtained helpful information on the involved parties, process and exploit tools and techniques during the design phase. Johansen's (2015) framework [(a) human and organisation, (b) process and (c) tools and techniques)] was completed and developed by identifying relevant criteria (such as risk averse or risk-taker, culture and documentation level) for each component. These criteria help to measure UM performance. The authors found that owners and contractors are major formal UM actors, not consultants. Empirical data showed the effectiveness of Web-based tools in UM.

The studied cases were Norwegian, and this study focussed on uncertainties in the project's design phase. Relevant criteria did not cover all the criteria for evaluating the performance of UM. Qualitative evaluation of criteria allows further quantitative analysis in the future.

This paper gave project owners and managers a better understanding of relevant criteria for measuring UM in the owners and managers' projects. The paper provides policy-makers with a deeper understanding of creating rigorous project criteria for UM during the design phase. This paper also provides a guideline for UM in road projects.

This research gives a holistic evaluation of UM by noticing relevant criteria and criteria's interconnection in the design phase.

When improving business processes, process analysts can use data-driven methods, such as process mining, to identify improvement opportunities. However, despite being supported by data, process analysts decide which changes to implement. Analysts often use process visualisations to assess and determine which changes to pursue. This paper helps explore how process mining visualisations can aid process analysts in their work to identify, prioritise and communicate business process improvement opportunities.

The study follows the design science methodology to create and evaluate an artefact for visualising identified improvement opportunities (IRVIN).

A set of principles to facilitate the visualisation of process mining outputs for analysts to work with improvement opportunities was suggested. Particularly, insights into identifying, prioritising and communicating process improvement opportunities from visual representation are outlined.

Prior work focuses on visualisation from the perspectives – among others – of process exploration, process comparison and performance analysis. This study, however, considers process mining visualisation that aids in analysing process improvement opportunities.

This study aims to provide a systematic and complete knowledge map for use by researchers working in the field of research data. Additionally, the aim is to help them quickly understand the authors' collaboration characteristics, institutional collaboration characteristics, trending research topics, evolutionary trends and research frontiers of scholars from the perspective of library informatics.

The authors adopt the bibliometric method, and with the help of bibliometric analysis software CiteSpace and VOSviewer, quantitatively analyze the retrieved literature data. The analysis results are presented in the form of tables and visualization maps in this paper.

The research results from this study show that collaboration between scholars and institutions is weak. It also identified the current hotspots in the field of research data, these being: data literacy education, research data sharing, data integration management and joint library cataloguing and data research support services, among others. The important dimensions to consider for future research are the library's participation in a trans-organizational and trans-stage integration of research data, functional improvement of a research data sharing platform, practice of data literacy education methods and models, and improvement of research data service quality.

Previous literature reviews on research data are qualitative studies, while few are quantitative studies. Therefore, this paper uses quantitative research methods, such as bibliometrics, data mining and knowledge map, to reveal the research progress and trend systematically and intuitively on the research data topic based on published literature, and to provide a reference for the further study of this topic in the future.

This study aims to describe and evaluate various visual and creative tools for supporting the in-depth biographical interview aimed at analyzing educational communities and their stakeholders.

Researching educational spaces today requires new ways of understanding, analyzing and studying. The complex characteristics, functions and realities demand research that responds to educational singularities. It is a matter of deeply understanding the educational phenomenon's peculiarities. For these purposes, instruments and research paradigms are needed to extract data and reach information saturation regarding the data obtained from the proposed objects of study. With this in mind, the following paper suggests reflecting on data collection tools that can complement the interview and biographical-narrative research approach. The authors highlight the use of photo-elucidation, the biogram-based timeline, the organigram and the flight of the geese, all of which are instruments endowed with a visual character that allows a deeper understanding of the object studied.

The main contribution of this paper is to unpack the uses and applications of four visual tools that support the interview technique. First, photo-elucidation is presented as a sensory strategy to stimulate the narrative during the dialogical exchange of the interview. Next, the timeline is described as a visual concretization of the traditional biogram widely used in educational research. Next, the authors unravel the uses of the organizational chart in educational research, which, due to its nature and utility, provides a glimpse of the organizational functioning of an institution and is particularly suitable for research in institutional frameworks. Finally, the tool known as the flight of the geese is presented. This tool is recommended for use in educational leadership and teamwork studies due to its simplicity and high representativeness of the hierarchy of roles and functions.

Researching educational spaces today requires new ways of understanding, analyzing and studying. The complex characteristics, functions, and realities demand research that responds to educational singularities. It is a matter of deeply understanding the educational phenomenon's peculiarities. For these purposes, instruments and research paradigms are needed to extract data and reach information saturation regarding the data obtained from the proposed objects of study. With this in mind, the following paper invites us to reflect on data collection tools that can complement the interview and biographical-narrative research approach. The authors highlight the use of photo-elucidation, the biogram-based timeline, the organigram, and the flight of the geese, all of which are instruments endowed with a visual character that allows a deeper understanding of the object studied.