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The purpose of this paper is to better understand the data practices, influences and needs of researchers at a major public research institution.

This paper is based on the results of a pre-tested, web-based survey of University of Kansas faculty, staff, researchers and graduate students.

Influences on data practices and data needs vary with the research methodology and academic discipline of the researcher.

Academic libraries may need to adjust the services they offer to meet the varying needs of researchers in differing disciplines using differing methodologies.

This study adds to the developing literature describing research data management.

Inspired by objective hermeneutics (Oevermann, 1984, 1996, 1999; Oevermann et al., 1979; Weller, 2010; Wohrab-Sahr, 2003) and qualitative validation (Adcock and Collier, 2001; Martis, 2006; Maxwell, 1992), the authors present this essay with the aim of proposing an objective hermeneutic approach to qualitative validation.

In order to develop this approach, the authors consider the contributions of Martis (2006) and Maxwell (1992) about theoretical–empirical validity, Adcock and Collier's propositions (2001) regarding the conceptualization and evaluation of phenomena through specific levels, tasks and stages of validation and the principles of objective hermeneutic interpretation proposed by Wohlrab-Sahr (2003).

Three main contributions are considered: theoretical–empirical validity (Martis, 2006; Maxwell, 1992); levels of validation – theoretical framework, systematized concept, indicators and results (Adcock and Collier, 2001); stages of validation – content validity, convergent validity and nomological validity (Adcock and Collier, 2001); and principles of objective hermeneutic interpretation – sequential interpretation, mental–experimental explanation of possible interpretations, preservation rule, literal character of interpretation, totality, reflection about knowledge used in the analysis and group of interpreters (Wohrab-Sahr, 2003). These contributions were related to establishing a framework that illustrates the proposed objective hermeneutic approach to qualitative validation.

The authors intend to offer to the scope of organization studies an alternative for validation, so that the voices of the researched can be heard. Furthermore, the authors seek to guide researchers as to how to respect and protect what is heard, in order to avoid any invasion of others' discourse.

This chapter considers the challenges and potentials of using so called big data in communication research. It asks what lessons big data research can learn from digital ethnography, another method of gathering digital data.

The chapter first takes on the task of clearly defining big data in the context of communication and media studies. It then moves on to analyse and critique processes associated with the dealings of big data: datafication and dataism. The challenges of data-driven research are juxtaposed with qualitative perspectives on research regarding data gathering and context. These thoughts are further elaborated in the second part of the chapter where the lessons learned in digital ethnography are linked to challenges of big data research.

It is proposed that by including the materialities of contexts and transitions between material and mediated realms, we can ask more relevant research questions and gain more insights compared to a purely data-driven approach.

This chapter encourages researchers to reflect upon their relations to the object of study and the context in which data was produced through human/human–technical interaction.

This chapter contributes to debates about qualitative and quantitative research methods in communication and media studies. Moreover, it proposes that methods which are in the widest sense used in the never-ending digital field benefit from the mutual consideration of both qualitative and quantitative approaches.

The purpose of this paper is to analyse the metrics provided by Publons about the scoring of publications and their relationship with impact measurements (bibliometric and altmetric indicators).

In January 2018, 45,819 research articles were extracted from Publons, including all their metrics (scores, number of pre and post reviews, reviewers, etc.). Using the DOI identifier, other metrics from altmetric providers were gathered to compare the scores of those publications in Publons with their bibliometric and altmetric impact in PlumX, Altmetric.com and Crossref Event Data.

The results show that: there are important biases in the coverage of Publons according to disciplines and publishers; metrics from Publons present several problems as research evaluation indicators; and correlations between bibliometric and altmetric counts and the Publons metrics are very weak (r<0.2) and not significant.

This is the first study about the Publons metrics at article level and their relationship with other quantitative measures such as bibliometric and altmetric indicators.

Since the field of healthcare was a latecomer to the quality movement, knowledge transfer has generally flowed in one direction, from industry to healthcare. However, organisations can also be enriched by healthcare. In particular, this paper aims to show industry that important lessons can be learned regarding how teamwork is generally managed within healthcare.

To identify the useful lessons that healthcare can teach industry, the authors started with a brainstorming session among the members of the research team to pin‐point the lessons based on their experience with healthcare and industrial environments. Afterwards, an exhaustive review of the relevant literature from the last ten years was carried out.

Industrial organisations need to develop teamwork frameworks focused on involving every employee in cross‐disciplinary, empowered and trained teams. Moreover, from a team perspective, special care must be shown when defining clear roles, focusing on end clients, formulating shared objectives and facilitating internal communications.

The ten lessons from healthcare teamwork best practices believed to be the most important are given in the paper. Although some of these lessons may not be completely new concepts for industrial organisations, the paper shows how healthcare develops, spreads and applies these concepts in the real world.

The paper summarises, in ten useful lessons for organisations, healthcare's best teamwork practices in the literature.

The purpose of this study was to determine if Systems Development Methodologies (SDMs) are being utilised effectively in the development of Learning Management Systems (LMSs) in South Africa. With e-learning being a critical component of modern educational systems, it has become essential to ensure that LMSs of a high standard are being developed. In the field of SDMs, much research has been done and the value of SDMs is proven and documented. To enhance the chances of developing LMSs of outstanding quality, it is crucial that SDMs are applied efficiently, as they can have a significant impact on the development process.

A positivistic research approach was followed. By utilising a survey as the main research method, quantitative data were generated. By statistically analysing the dataset, meaningful results were obtained.

This study shed some light on how LMS procurement and development is being done in South Africa and revealed that the use of open-source systems currently exceeds the use of proprietary systems. The results of the research showed that SDMs (e.g. Rapid Application Development) are being used effectively in the development of e-learning systems. Strong relationships exist between many of the SDM factors identified (e.g. performance expectancy and the perceived support of the methodology) and the quality and productivity of the development process. This, in turn, has a strong influence on the impact SDMs have on the quality of LMSs.

The study made a contribution to the discipline of information systems and, more specifically, LMSs, by providing insights with regard to the factors affecting the use and effectiveness of SDMs in developing LMSs. As far as could be ascertained, this study generated the first empirical data on the procurement and development of LMSs in South Africa.

This paper aims to investigate the ethical challenges within same-day delivery (SDD) operations in the gig economy, focusing on promoting fairness and justice for independent contractors by applying Rawlsian justice principles.

Adopting a philosophical and theoretical methodology, the authors synthesize insights from business ethics, corporate governance and Rawlsian ethical theories. This study critically examines the application of these theories within SDD business models through a comparative analysis of seminal and contemporary ethical discussions. Importantly, the authors reverse the traditional antecedents, decisions and outcomes framework to start with outcomes, offering a novel methodological execution that enhances the study’s approach to ethical research.

The analysis identifies pronounced ethical deficiencies in treating SDD contractors, emphasizing the need for systemic reforms. The study proposes a series of hypotheses to rectify these issues, including recommendations for enhancing algorithmic transparency, ensuring equitable compensation and fortifying worker protections. These proposed changes advocate for restructuring corporate policies to foster a fairer SDD business environment.

By interweaving Rawlsian ethical principles with practical corporate responsibilities specific to the gig economy, this paper enriches the discourse on business ethics. It introduces a novel framework for analyzing the ethical treatment of gig workers, proposing actionable strategies that bridge theoretical ethics with real-world applications. This approach advances academic understanding and guides industry practices toward more ethical and sustainable models.

The purpose of this paper is to explore the current literature on data governance in scientific and practice-oriented publications, and to provide a comparative analysis of the activities reported for data governance. Data have become a key organisational asset and data governance both a necessary and critical activity.

A comprehensive literature review is conducted in order to identify the published material that reflects the current state of knowledge. A systematic procedure was followed that identified 61 publications that explicitly mention data governance activities. Open coding techniques were applied to conduct content analysis, resulting in the identification of 591 concepts. A critical analysis also identified gaps in the literature.

The analysis identified 120 data governance activities which are understood as: “action” plus “area of governance” plus “decision domain” (e.g. define data policies for data quality). The authors define and present a data governance activities model based on the analysis. The analysis also shows a higher volume of data governance activities reported by practice-oriented publications that are associated with the “implement” and “monitor” actions of the areas of governance across the decision domains compared with scientific publications, whereas The authors found that the scientific publications focus more on defining activities. The results contribute to identifying research gaps and concerns on which ongoing and future research efforts can be focused.

This paper is of interest to both academics and practitioners, as it helps them understand the activities associated with a data governance programme. Current literature fails to provide a comprehensive understanding of the data governance activities that are required when considering a data governance programme. Therefore, the proposed model for data governance activities can be used to give insights into these activities.

To the knowledge of the authors, this study is the first to explicitly consider data governance activities from both an academic and practice-oriented perspective.