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This study aims to promote strategic maritime management as a new emerging discipline to foster research in strategic maritime issues.

An existing academic discipline maturity model is adapted by including four phases of dynamic evolutionary paths to evaluate the phase of maturity of a research discipline. The model is validated by means of two matured disciplines: strategic management and maritime economics.

It is found that the current research of strategic maritime management is at a phase of emergence of discipline and ready to move to the maturity phase. It is also found that the evolution of the path of strategic maritime management resembles the early evolution path of strategic management but lags 30 years behind. Future research directions of strategic maritime management can be referred to the research streams in the maturity phase of strategic management.

The adapted academic discipline maturity model brings in the longitudinal and dynamic perspectives of the evolution of an academic discipline, which helps maritime strategists identify gaps and opportunities and evaluate the appropriateness of applying a strategic management paradigm to a specific research topic.

The adapted academic discipline maturity model brings in the longitudinal and dynamic perspective of the evolution of an academic discipline, which helps maritime strategists define the gaps and opportunities in strategic maritime management research.

The population of internationally forcibly displaced people, which includes refugees and asylum seekers, is large and heterogeneous. To determine the varying reasons for and experiences during the migration journey, including exposure to violence and health- and integration-related needs, there is an urgent need to involve children with refugee backgrounds in research and development activities. This chapter describes a model for the child participatory approach developed at Barnafrid, a national competence centre on violence against children at Linköping University in Sweden. The model has been tested in the Long Journey to Shelter study, which investigated exposure to violence and its consequences on mental health and functional ability among forcibly displaced children and young adults. As part of this project, we conducted workshops with children (n = 36, aged 13–18 years) to design a questionnaire on exposure to community violence in the country of resettlement. Experiences recounted during the child participatory workshops indicated no problems involving newly arrived children with refugee backgrounds and Swedish-born adolescents in research activities. However, attention should be paid to proper preparatory work and the need for adjustments. We discuss the results in light of other studies on refugee child participation, the United Nations Convention on the Rights of a Child and diversity considerations.

The rapid rise of large language models (LLMs) has propelled them to the forefront of applications in natural language processing (NLP). This paper aims to present a comprehensive examination of the research landscape in LLMs, providing an overview of the prevailing themes and topics within this dynamic domain.

Drawing from an extensive corpus of 198 records published between 1996 to 2023 from the relevant academic database encompassing journal articles, books, book chapters, conference papers and selected working papers, this study delves deep into the multifaceted world of LLM research. In this study, the authors employed the BERTopic algorithm, a recent advancement in topic modeling, to conduct a comprehensive analysis of the data after it had been meticulously cleaned and preprocessed. BERTopic leverages the power of transformer-based language models like bidirectional encoder representations from transformers (BERT) to generate more meaningful and coherent topics. This approach facilitates the identification of hidden patterns within the data, enabling authors to uncover valuable insights that might otherwise have remained obscure. The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

This classification offers practical guidance for researchers, developers, educators, and policymakers to focus efforts and resources. The study underscores the importance of addressing challenges in LLMs, including potential biases, transparency, data privacy, and responsible deployment. Policymakers can utilize this information to shape regulations, while developers can tailor technology development based on the diverse applications identified. The findings also emphasize the need for interdisciplinary collaboration and highlight ethical considerations, providing a roadmap for navigating the complex landscape of LLM research and applications.

This study stands out as the first to examine the evolution of LLMs across such a long time frame and across such diversified disciplines. It provides a unique perspective on the key areas of LLM research, highlighting the breadth and depth of LLM’s evolution.

Due to the unknown location, size and timing of disasters, the rapid response required by humanitarian operations (HO) faces high uncertainty and limited time to raise funds. These harsh realities make HO challenging. This study aims to systematically capture the complex dynamic relationships between operations in humanitarian settings.

To achieve this goal, the authors undertook a systematic review of the extant academic literature linking HO to system dynamics (SD) simulation.

The research reviews 88 papers to propose a taxonomy of different topics covered in the literature; a framework represented through a causal loop diagram (CLD) to summarise the taxonomy, offering a view of operational activities and their linkages before and after disasters; and a research agenda for future research avenues.

As the authors provide an adequate representation of reality, the findings can help decision makers understand the problems faced in HO and make more effective decisions.

While other reviews on the application of SD in HO have focused on specific subjects, the current research presents a broad view, summarising the main results of a comprehensive CLD.

The paper attempts to address the following research questions (RQs): RQ1: What are the main research topics within PSS research? RQ2: What are future trends for PSS research?

Twenty years of research (1999–2018) on product-service systems (PSS) produced a significant amount of scientific literature on the topic. As the PSS field is relatively new and fragmented across different disciplines, a review of the prior and relevant literature is important in order to provide the necessary framework for understanding current developments and future perspectives. This paper aims to review and organize research contributions regarding PSS. A machine-learning algorithm, namely Latent Dirichlet Allocation, has been applied to the whole literature corpus on PSS in order to understand its structure.

The adopted approach resulted in the definition of eight distinct and representative topics able to deal adequately with the multidisciplinarity of the PSS. Furthermore, a systematic review of the literature is proposed to summarize the state-of-the-art and limitations in the identified PSS research topics. Based on this critical analysis, major gaps and future research challenges are presented and discussed.

On the basis of the results of the topic landscape, the paper presents some potential research opportunities on PSSs. In particular, challenges, transversal to the eight research topics and related to recent technology trends and digital transformation, have been discussed.

In identifying both the topics of interest and key limitations of the extant organizational security research, both opportunities for future research as well as some underlying challenges for conducting this research may be revealed.

To identify the leading organizational cybersecurity research topics of interest and their key limitations, the author conducted a topic modeling analysis of the organizational level studies published in the Association for Information Systems (AIS) senior scholars' “basket of eight journals” (Association for Information Systems, 2022) over the past five years.

Leading topics include (1) organizational security research concerns governance and strategic level decision-making and their role in shaping organizational security successes and failures, (2) cybercriminals and organizations' ability to monitor and detect them from both within and outside the firm; (3) cost, liability and security negligence, (4) organizations' innovation dispositions for security products and services and (5) organizational breach response efficacy; while key limitations of this study include the following: (1) scholars' ability to propose and assess strategic and operational level threat response recommendations, (2) their understanding how influence is formed and maintained among employees and groups and (3) their measurement instruments and models.

Organizations remained plagued by an ever-emerging set of threats to the security of their digital and informational assets. New threats are regularly discovered and remedies to existing threats are continually proven ineffective against these new threats. Providing an orientation to the current research on organizational security can help advance their security efforts.

This paper aims that privacy research is divided in distinct communities and rarely considered as a singular field, harming its disciplinary identity. The authors collected 119.810 publications and over 3 million references to perform a bibliometric domain analysis as a quantitative approach to uncover the structures within the privacy research field.

The bibliometric domain analysis consists of a combined directed network and topic model of published privacy research. The network contains 83,159 publications and 462,633 internal references. A Latent Dirichlet allocation (LDA) topic model from the same dataset offers an additional lens on structure by classifying each publication on 36 topics with the network data. The combined outcomes of these methods are used to investigate the structural position and topical make-up of the privacy research communities.

The authors identified the research communities as well as categorised their structural positioning. Four communities form the core of privacy research: individual privacy and law, cloud computing, location data and privacy-preserving data publishing. The latter is a macro-community of data mining, anonymity metrics and differential privacy. Surrounding the core are applied communities. Further removed are communities with little influence, most notably the medical communities that make up 14.4% of the network. The topic model shows system design as a potentially latent community. Noteworthy is the absence of a centralised body of knowledge on organisational privacy management.

This is the first in-depth, quantitative mapping study of all privacy research.

This paper provides a structured literature review of blockchain in accounting. The authors identify current trends, analyse and critique the key topics of research and discuss the future of this nascent field of inquiry.

This study’s analysis combined a structured literature review with citation analysis, topic modelling using a machine learning approach and a manual review of selected articles. The corpus comprised 153 academic papers from two ranked journal lists, the Association of Business Schools (ABS) and the Australian Business Deans Council (ABDC), and from the Social Science Research Network (SSRN). From this, the authors analysed and critiqued the current and future research trends in the four most predominant topics of research in blockchain for accounting.

Blockchain is not yet a mainstream accounting topic, and most of the current literature is normative. The four most commonly discussed areas of blockchain include the changing role of accountants; new challenges for auditors; opportunities and challenges of blockchain technology application; and the regulation of cryptoassets. While blockchain will likely be disruptive to accounting and auditing, there will still be a need for these roles. With the sheer volume of information that blockchain records, both professions may shift out of the back-office toward higher-profile advisory roles where accountants try to align competitive intelligence with business strategy, and auditors are called on ex ante to verify transactions and even whole ecosystems.

The authors identify several challenges that will need to be examined in future research. Challenges include skilling up for a new paradigm, the logistical issues associated with managing and monitoring multiple parties all contributing to various public and private blockchains, and the pressing need for legal frameworks to regulate cryptoassets.

The possibilities that blockchain brings to information disclosure, fraud detection and overcoming the threat of shadow dealings in developing countries all contribute to the importance of further investigation into blockchain in accounting.

The authors’ structured literature review uniquely identifies critical research topics for developing future research directions related to blockchain in accounting.