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This work aims to present existing management system standards (MSSs) published by the International Organization for Standardization (ISO) through a bibliometric analysis, thereby outlining their academic research status and highlighting their relation to the Sustainable Development Goals (SDGs) as well as to environmental, social and governance (ESG) themes.

The study firstly retrieves a preliminary set of MSSs standards from ISO and filters it in accordance with certain exclusion/inclusion criteria. Secondly, a bibliometric search is performed in the database Scopus. Thirdly, performance analysis is conducted to quantitatively measure the scientific output in academia, and science mapping of co-occurrences of keywords is applied to identify related topics. Thereby, the standards’ relationships to sustainability are outlined. Eventually, the work discusses future research opportunities.

The findings reveal that whereas research on MSSs focuses predominantly on only a few standards by now, there are actually numerous further standards that address sustainability-relevant topics, which are getting increasing attention among scholars as measured by the number of publications. Therefore, an action plan for future research is derived. Moreover, the findings support the argument of integrating MSSs to cover a broad range of corporate sustainability issues.

The paper connects the concepts of MSSs and sustainability, an upcoming research branch yet characterized by shortage of academic studies (given that research continues to focus on a few standards such as ISO 9001, ISO 14001 and ISO 45001). The work therefore opens up the line for more in-detail research on less known but nevertheless sustainability-relevant ISO MSSs.

This article describes the interviews the authors conducted in late 2021 with 19 researchers at the Department of Classical Philology and Italian Studies at the University of Bologna. The main purpose was to shed light on the definition of the word “data” in the humanities domain, as far as FAIR data management practices are concerned, and on what researchers think of the term.

The authors invited one researcher for each of the official disciplinary areas represented within the department and all 19 accepted to participate in the study. Participants were then divided into five main research areas: philology and literary criticism, language and linguistics, history of art, computer science and archival studies. The interviews were transcribed and analysed using a grounded theory approach.

A list of 13 research data types has been compiled thanks to the information collected from participants. The term “data” does not emerge as especially problematic, although a good deal of confusion remains. Looking at current research management practices, methodologies and teamwork appear more central than previously reported.

Our findings confirm that “data” within the FAIR framework should include all types of inputs and outputs humanities research work with, including publications. Also, the participants of this study appear ready for a discussion around making their research data FAIR: they do not find the terminology particularly problematic, while they rely on precise and recognised methodologies, as well as on sharing and collaboration with colleagues.

Data protection requirements heavily increased due to the rising awareness of data security, legal requirements and technological developments. Today, NoSQL databases are increasingly used in security-critical domains. Current survey works on databases and data security only consider authorization and access control in a very general way and do not regard most of today’s sophisticated requirements. Accordingly, the purpose of this paper is to discuss authorization and access control for relational and NoSQL database models in detail with respect to requirements and current state of the art.

This paper follows a systematic literature review approach to study authorization and access control for different database models. Starting with a research on survey works on authorization and access control in databases, the study continues with the identification and definition of advanced authorization and access control requirements, which are generally applicable to any database model. This paper then discusses and compares current database models based on these requirements.

As no survey works consider requirements for authorization and access control in different database models so far, the authors define their requirements. Furthermore, the authors discuss the current state of the art for the relational, key-value, column-oriented, document-based and graph database models in comparison to the defined requirements.

This paper focuses on authorization and access control for various database models, not concrete products. This paper identifies today’s sophisticated – yet general – requirements from the literature and compares them with research results and access control features of current products for the relational and NoSQL database models.

Although scholars argue that artificial intelligence (AI) represents a tool to potentially smoothen the bullwhip effect in the supply chain, only little research has examined this phenomenon. In this article, the authors conceptualize a framework that allows for a more structured management approach to examine the bullwhip effect using AI. In addition, the authors conduct a systematic literature review of this current status of how management can use AI to reduce the bullwhip effect and locate opportunities for future research.

Guided by the systematic literature review approach from Durach et al. (2017), the authors review and analyze key attributes and characteristics of both AI and the bullwhip effect from a management perspective.

The authors' findings reveal that literature examining how management can use AI to smoothen the bullwhip effect is a rather under-researched area that provides an abundance of research avenues. Based on identified AI capabilities, the authors propose three key management pillars that form the basis of the authors' Bullwhip-Smoothing-Framework (BSF): (1) digital skills, (2) leadership and (3) collaboration. The authors also critically assess current research efforts and offer suggestions for future research.

By providing a structured management approach to examine the link between AI and the bullwhip phenomena, this study offers scholars and managers a foundation for the advancement of theorizing how to smoothen the bullwhip effect along the supply chain.

This study aimed to analyze the strategies and challenges related to technology transfer (TT) in technology transfer offices (TTOs), specifically regarding actions to offer technologies in their portfolios.

The qualitative research used a multiple case study based on interviews with TTO managers from seven Brazilian public Science and Technology Institutions (STIs): University of São Paulo (USP), State University of Campinas (UNICAMP), Paulista State University (UNESP), Federal University of Minas Gerais (UFMG), Federal University of Paraná (UFPR), Federal Technological University of Paraná (UTFPR) and Oswaldo Cruz Foundation (FIOCRUZ).

STIs that invest more resources in their portfolio’s active offering and marketing are more successful in TT than STIs with a passive strategy. Although this active strategy has grown in importance, there is a disparity among Brazilian TTOs as some are still passive in commercializing their intellectual property. This research also highlights the need for clear policies to overcome obstacles related to legal uncertainty for researchers who wish to undertake projects as entrepreneurs using the intellectual property of STIs.

The results of this study cannot be generalized since its conclusions are limited to the studied institutions. However, the outcomes indicate some interesting matters for managers of STIs, public policymakers and TT researchers.

Literature on marketing and innovation related to TT between research institutions and companies in developing countries is still limited. Thus, this research contributes to generating knowledge in the field and improving TTOs.

The current paper sought to assess health research institutions in transferring knowledge from health research findings into decision and policy making in Malawi. The study employed both a qualitative and a multi-case study approach. Data was gathered through interviews. The study's participants were purposefully chosen directors of research institutions, public universities, and the ministry of health. Few research institutions compile a list of organisations that might benefit from their health research findings, and even fewer libraries have databanks or repositories. Policymakers rarely receive actionable messages from research institutions. Researchers are short on communication skills as well as time to transfer research findings into usable formats. Research centres including libraries should provide an opportunity for interacting and enhancing the use of research evidence. Individuals, research groups, institutions must all develop stakeholder interaction structures. Structures should define incentives and advancement opportunities for those working in health research institutions.

This study reviews and discusses the accounting literature that analyzes the role of auditors and enforcers in the context of fraud.

This literature review includes both qualitative and quantitative studies, based on the idea that the findings from different research paradigms can shed light on the complex interactions between different financial reporting controls. The authors use a mixed-methods research synthesis and select 64 accounting journal articles to analyze the main proxies for fraud, the stages of the fraud process under investigation and the roles played by auditors and enforcers.

The study highlights heterogeneity with respect to the terms and concepts used to capture the fraud phenomenon, a fragmentation in terms of the measures used in quantitative studies and a low level of detail in the fraud analysis. The review also shows a limited number of case studies and a lack of focus on the interaction and interplay between enforcers and auditors.

This study outlines directions for future accounting research on fraud.

The analysis underscores the need for the academic community, policymakers and practitioners to work together to prevent the destructive economic and social consequences of fraud in an increasingly complex and interconnected environment.

This study differs from previous literature reviews that focus on a single monitoring mechanism or deal with fraud in a broadly manner by discussing how the accounting literature addresses the roles and the complex interplay between enforcers and auditors in the context of accounting fraud.

The UN Sustainable Development Goals (SDGs) provide a framework to achieve sustainable development and fulfilling these Goals will take an unprecedented effort by all sectors in society. Many universities and businesses are using the Goals within their strategies and sustainability reporting. However, this is difficult as there is currently no standard methodology to map the 17 goals, 169 targets and 232 indicators. Work at the University of Leicester has focused on developing a robust methodology to map a higher education institution's (HEI's) research contribution to the Goals. We have integrated this unique methodology into an automated software tool to measure a university's academic contribution to the Goals using mathematical text mining techniques. Our ability to quickly and effectively map institutions' research contributions has boosted our ambitions and efforts to develop software to map the full operations of an HEI or business.

The advancement of a profession depends on factors such as firm education, training programmes and vibrant professional associations. The purpose of this study is to provide baseline information on archives and records management (ARM) professionals from Africa, including their views on education and training programmes. Related studies have been limited to investigating the experiences of graduates from a few institutions within a limited jurisdiction. Similar studies have not been conducted by African-based ARM associations.

This study’s survey approach was administered electronically. Two surveys explored themes through 10 research questions in three categories: background information; characteristics of the education; and types of courses and extent covered during the study.

The two surveys had 107 and 179 respondents, respectively, domiciled in 19 African countries. In both studies, about 75% of the respondents had an undergraduate- or master-level qualification. Between 69% and 87% of the respondents from the first and second surveys, respectively, had completed their educational programmes within their home countries. There was varied sentiment on the types of courses and level of coverage within their studies. Legal and technology aspects were less covered in the curriculum than core subjects.

To the best of the author’s knowledge, this study is the first with findings from ARM respondents across several African countries. It provides insight into the demographics and educational programmes. This study’s unique contribution provides baseline data for more detailed and nuanced studies that will explore data and investigate patterns within and among individual countries on the continent.

The purpose of this study was to investigate trust within human-AI teams. Trust is an essential mechanism for team success and effective human-AI collaboration.

In an online experiment, the authors investigated whether trust perceptions and behaviours are different when introducing a new AI teammate than when introducing a new human teammate. A between-subjects design was used. A total of 127 subjects were presented with a hypothetical team scenario and randomly assigned to one of two conditions: new AI or new human teammate.

As expected, perceived trustworthiness of the new team member and affective interpersonal trust were lower for an AI teammate than for a human teammate. No differences were found in cognitive interpersonal trust and trust behaviours. The findings suggest that humans can rationally trust an AI teammate when its competence and reliability are presumed, but the emotional aspect seems to be more difficult to develop.

This study contributes to human–AI teamwork research by connecting trust research in human-only teams with trust insights in human–AI collaborations through an integration of the existing literature on teamwork and on trust in intelligent technologies with the first empirical findings on trust towards AI teammates.