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Developing cybersecurity awareness (CSA) is becoming a more and more important goal for modern organizations. CSA is a complex sociotechnical system where social, technical and organizational aspects affect each other in an intertwined way. With the goal of providing a holistic representation of CSA, this paper aims to develop a taxonomy of factors that contribute to organizational CSA.

The research used a design science approach including a literature review and practitioner interviews. A taxonomy was drafted based on 71 previous research publications. It was then updated and refined in two iterations of interviews with domain experts.

The result of this research is a taxonomy which outline six domains for importance for organization CSA. Each domain includes several activities which can be undertaken to increase CSA within an organization. As such, it provides a holistic overview of the CSA field.

Organizations can adopt the taxonomy to create a roadmap for internal CSA practices. For example, an organization could assess how well it performs in the six main themes and use the subthemes as inspiration when deciding on CSA activities.

The output of this research provides an overview of CSA based on information extracted from existing literature and then reviewed by practitioners. It also outlines how different aspects of CSA are interdependent on each other.

In pursuit of objectives, under the European Green Deal, to channel capital flows to sustainable activities, the EU Taxonomy offers clarity, labelling real economic activities as “sustainable”, based on technical screening criteria. This study of disclosure experiences aims to explore the role of co-evolutionary relationships in the Taxonomy’s effectiveness.

Co-evolution theory implies a dynamic interplay among sustainable finance stakeholders (SFSs), through adjustment to, impact on and operationalisation of the Taxonomy. Corporate disclosure experiences, including those of financial institutions and related SFS experiences, may reveal co-evolutionary processes. With significant Undertakings for Collective Investment in Transferable Securities (UCITS) and Alternative Investment Funds (AIFs), Irish SFSs provide contextual insight. Semi-structured interviews with a purposive sample of Irish SFSs capture inaugural corporate Taxonomy disclosure experiences.

A thematic analysis reveals six co-evolutionary processes that facilitate Taxonomy implementation in pursuit of policy objectives: [1] cross-functional reporting; [2] iterative pre-empting and addressing compliance issues; [3] regulation as a catalyst for co-evolution; [4] advanced capacity building; [5] stakeholder adaptation and [6] graduated use of ESG data. Implications for sustainability policy development and management are significant.

Whilst limited to just one EU jurisdiction, given limited prior empirical evidence for sustainable finance regulations from co-evolutionary perspectives, this study highlights a catalytic, yet precautionary role for co-evolution in their transformation effectiveness. As such, they must take account of their potential to stimulate co-evolution and to nurture it in pursuit of their policy objectives.

The findings of this study add to a small, but growing body of academic literature on the Taxonomy Regulation, which suggests that a co-evolutionary lens is important for gaining a comprehensive understanding of its early-stage dynamics. From an implementation perspective, the qualitative data reveals actionable implications for regulators and policymakers, such as building capacity, better anticipation of outcomes and investment in data infrastructure.

Unlike existing analyses of disclosures, this study offers a co-evolutionary lens on Taxonomy contributions to sustainable development through qualitative accounts.

The purpose of this paper is to propose a taxonomy of artificial intelligence (AI) literacy to support AI literacy education and research.

This study makes use of the facet analysis technique and draws upon various sources of data and information to develop a taxonomy of AI literacy. The research consists of the following key steps: a comprehensive review of the literature published on AI literacy research, an examination of well-known AI classification schemes and taxonomies, a review of prior research on data/information/digital literacy research and a qualitative and quantitative analysis of 1,031 metadata records on AI literacy publications. The KH Coder 3 software application was used to analyse metadata records from the Scopus multidisciplinary database.

A new taxonomy of AI literacy is proposed with 13 high-level facets and a list of specific subjects for each facet.

The proposed taxonomy may serve as a conceptual AI literacy framework to support the critical understanding, use, application and examination of AI-enhanced tools and technologies in various educational and organizational contexts.

The proposed taxonomy provides a knowledge organization and knowledge mapping structure to support curriculum development and the organization of digital information.

The proposed taxonomy provides a cross-disciplinary perspective of AI literacy. It can be used, adapted, modified or enhanced to accommodate education and learning opportunities and curricula in different domains, disciplines and subject areas.

The proposed AI literacy taxonomy offers a new and original conceptual framework that builds on a variety of different sources of data and integrates literature from various disciplines, including computing, information science, education and literacy research.

Published in June 2020, the European Union (EU) Taxonomy Regulation is an important tool for the reorientation of capital flows toward sustainability, establishing a classification system that enables investors to identify green economic activities. Confronted by the reporting demands of this regulation, companies are caught in a sustainability economic revolution. This study seeks primarily to understand firms’ responses to the EU taxonomy, and whether they recognize value creation opportunities by aligning market and nonmarket strategies with the taxonomy goals. For that, we conducted expert interviews and adopted a conceptual framework based on institutional theory, dynamic capabilities view and nonmarket strategy research. Our findings indicate that most firms respond reactively, while firms with sustainability-driven business models tend to respond in an anticipatory way, and firms with high greenhouse gas (GHG) emissions and low taxonomy eligibility in a defensive way. We also find evidence for mimetic isomorphism related to the influence of consulting and auditing services. Further, high levels of uncertainty, ambiguity and lack of clarity has a great impact on firms’ responses and motives. Finally, this study highlights the EU taxonomy considering a paradigmatic shift toward sustainability, which is not recognized by most firms. To this end, we find that most companies have not identified opportunities arising from nonmarket integration and, rather, see the taxonomy only as an extra regulation to be compliant with. Hence, we argue that it is crucial that firms contextualize the taxonomy within its larger institutional paradigmatic shift to capture the importance of going beyond mere compliance.

Competency-based human resource management (CBHRM) is a key component of all organisations but needs to be regularly reviewed and evaluated to ensure the quality of healthcare professionals. One common taxonomy of competency domains for health professions is from Englander et al., where this paper aims to conduct a large-scale analysis based on topic modelling to investigate the extent to which the competency framework for the healthcare sector is applied in the German job market of health professions.

The quantitative NLP analysis of a dataset consisting of 3,362 online job advertisements of nurses and doctors was scraped from a German job portal. The data was pre-processed according to Miner et al. For the analysis, the authors applied unsupervised (e.g. HDP, LDA) and supervised (BERTopic) methods and content analysis. Based on the extracted topics a word list was created and these words were coded to existing dimensions of the competency framework of Englander et al. or new dimensions were created.

Comparing methodologies, HDP (unsupervised) and BERTopic (supervised) were the best performing while the BERTopic algorithm outperforms HDP. For the doctor dataset 46% of one main dimension was identified but with an overall coverage of 69%, for the care dataset is weaker with 30.8% but an overall coverage of 100%. Additionally, the taxonomy was enhanced with supplementary competencies of “personality/characteristics” and “leadership” as well as two facets of job description which are “place of work” and “job conditions”.

On the one hand selected dimensions of the taxonomy could be clearly identified but on the other hand, there is a documented gap between the taxonomy and the competencies advertised. One cause may lie in the NLP algorithms but applicants may also have the same difficulties when reading the OJAs. Thus, practitioners should carefully review OJAs regarding better separating explicit competencies they are searching for. For the scientific development of new competency frameworks, our data-driven approach exemplified an extension of a given taxonomy.

This study is part of a series aimed at improving the city's environment, as fully restoring the past soundscape is hardly feasible. The initial study aims to uncover the city's sound characteristics, including iconic sounds that have shaped the city's environment for decades, contributing to its status as Indonesia's second most popular tourist destination. This stage is critical for informing policymaking to carefully manage and enhance the urban acoustic environment in alignment with the preserved culture.

The city's sound profile was examined using standard urban sound taxonomies. The study used quantitative methods, including (1) sound pressure level (SPL) measurements and sound recordings, (2) in situ surveys and (3) memory-based surveys. The first set of data were compared to current standards and standard urban sound taxonomies, while the second set was analysed to determine the median rating score for determining the soundscape dimensions. The third data set was used to identify the specific acoustic aspects inherent in Yogyakarta.

Yogyakarta's acoustic environment was bustling, with traffic noise and human activities dominating the soundscape, surpassing the standard levels. Many sounds not classified in standard urban sound taxonomies were present, showing the diverse nature of urban sound classification, particularly in a cultural and traditional city like Yogyakarta. The memory-based survey unveils Yogyakarta's two most remarkable soundmarks, “gamelan” and “andong”, which support the findings of prior studies. The in situ survey rated the city's acoustic environment as eventful, pleasurable and generally appropriate, emphasising the presence of cultural sounds unique to Yogyakarta, even though they are not fully audible in the current environment.

The standard sound taxonomies used in urban areas need to be adjusted to include the unique sounds produced by cultural and traditional activities in developing countries. The ordinates and subordinates of the taxonomies also need to be updated. When cultural and daily activities are massively seen in a particular city, the sounds they produce can be recalled exclusively as the city's signature. It is urgent to implement policies to safeguard the few remaining soundmarks before they disappear entirely.

Drawing on institutional theory analytical perspectives of theorisation and translation, this study aims to explore the institutionalisation of eXtensible Business Reporting Language (XBRL) in Indonesia from a regulatory and filer perspective.

The Indonesian capital market offers a unique case of the integration of XBRL regulatory reporting between multiple regulators and a transfer from capital market regulation to state-level regulation. This study uses semi-structured interviews with key actors employed with Indonesian XBRL-regulatory bodies and listed companies (filers).

External pressures, monitoring issues and tensions in the implementation process were instrumental in the theorisation and translation of XBRL in Indonesia. Specifically, the findings show that choices made with respect to XBRL regulation and implementation created tensions between XBRL reporting fulfilling a monitoring purpose and serving stakeholders’ interests. The findings also indicate that the Indonesian approach to XBRL regulation and implementation had distinct characteristics compared to XBRL implementation in other jurisdictions.

This study emphasises the necessity for robust regulatory support and strict enforcement to navigate the complexities and tensions arising from a multi-regulatory approach. Additionally, it stresses the importance of firms’ readiness and expertise in XBRL as more sophisticated implementation strategies are considered.

Using the analytical lens of theorisation and translation, the study provides a deeper understanding of how a globally diffused accounting technology was institutionalised and legitimised in a developing country. Specifically, this study explains why a conversion approach to XBRL implementation was favoured and how XBRL implementation and reporting were managed and coordinated between different Indonesian regulators.

Develop a comprehensive framework for assessing the knowledge organization systems (KOSs), including the taxonomy of Wikipedia and the ontologies of Wikidata, with a specific focus on enhancing management and retrieval with a gender nonbinary perspective.

This study employs heuristic and inspection methods to assess Wikipedia’s KOS, ensuring compliance with international standards. It evaluates the efficiency of retrieving non-masculine gender-related articles using the Catalan Wikipedian category scheme, identifying limitations. Additionally, a novel assessment of Wikidata ontologies examines their structure and coverage of gender-related properties, comparing them to Wikipedia’s taxonomy for advantages and enhancements.

This study evaluates Wikipedia’s taxonomy and Wikidata’s ontologies, establishing evaluation criteria for gender-based categorization and exploring their structural effectiveness. The evaluation process suggests that Wikidata ontologies may offer a viable solution to address Wikipedia’s categorization challenges.

The assessment of Wikipedia categories (taxonomy) based on KOS standards leads to the conclusion that there is ample room for improvement, not only in matters concerning gender identity but also in the overall KOS to enhance search and retrieval for users. These findings bear relevance for the design of tools to support information retrieval on knowledge-rich websites, as they assist users in exploring topics and concepts.

Sustainability has become an integral part of the real estate industry, alongside advancing globalization and demographic development. Due to real estate's influence on greenhouse gas emissions throughout its life cycle, both the regulatory and legal requirements concerning the sustainability of real estate are growing and, as a result of social responsibility, the interest of tenants and investors in sustainable real estate. However, criteria for measuring the ecological sustainability of a real estate investment in the purchase process in order to reduce the risk of including “stranded assets” in the portfolio are missing. This paper aims to address the need to integrate the issue of carbon stranding into existing sustainability rating tools.

Existing tools are examined based on defined criteria to determine whether they are suitable for purchasing a property before suitable tools for purchase are compared. Strengths and weaknesses are identified, which are to be remedied with the scoring tool. Taxonomy regulation is integrated into the existing valuation basis as a legal regulation.

The result is a scoring tool that enables real estate companies to measure and evaluate the ecological sustainability performance of a property during the acquisition process, taking into account the three aspects of sustainability and considering them when determining an appropriate purchase price in line with market conditions. Moreover, the developed tool helps to minimize the risk of acquiring a stranding asset.

The environmental, social and governance (ESG) framework employed in this study does not incorporate governance considerations. While the analysis extensively evaluates the building's environmental and social aspects, it does not extend to examining the governance practices of the companies involved. Thus, the assessment is confined solely to the physical attributes of the property without accounting for broader corporate governance factors.

The developed scoring tool represents a valuable tool for the real estate industry, offering insights into sustainability performance during property acquisitions and providing a structured framework for decision-making. By addressing both certification and taxonomy regulation requirements, the tool contributes to the industry's evolution toward more sustainable and environmentally responsible real estate practices.

In response to the growing importance of sustainability in the real estate industry, this paper introduces a novel scoring tool for evaluating the sustainability of real estate investments during the acquisition process.

This study aims to investigate the reality of relationship banking (RB) in the small and medium enterprise (SME) context, specifically how banks organize activities, define SMEs and manage the SME–banking relationship.

Using qualitative methods, this study uses a case study approach, conducting in-depth interviews with relationship managers from major New Zealand banks. The data are analyzed using thematic analysis with a process- and mechanism-oriented lens.

The study identifies bank criteria for defining SMEs, considering factors such as business complexity, owner/manager ethnicity and business lending. Banks divide their activities into personal and business banking, with the latter further classified as micro-, small- and medium-sized businesses based on borrowing amounts. Three types of RB emerge, namely, micro-business (online/many-to-many) relationship model (RM), small-business RM (one-to-many) and medium-sized business (one-to-one) RM. This study presents a taxonomy of business banking relationship management models that capture the structure and dynamics of the three RB levels.

Interviews may introduce biases or limited perspectives. Findings specific to New Zealand may not universally apply. Future research could explore different regions and assess the impact of these RB models on SMEs’ financial outcomes and satisfaction with banking services.

Findings assist banks in organizing activities and managing SME relationships. Taxonomy aids in categorizing companies and determining appropriate management models. Consequently, tailored services can be provided based on SME needs, offering customized financial packages.

RB models prioritizing ethnicity consideration and personalized services contribute to enhanced financial inclusion for SMEs, thereby fostering broader socioeconomic growth and development, partly through the provision of tailored financial packages. Additionally, relationship managers specializing in specific industries can offer valuable insights and assistance to SMEs, fostering mutual trust and collaboration.

To the best of the author’s knowledge, this is the first study to hypothesize, investigate, identify and provide evidence for three RB levels in SMEs. The presented taxonomy contributes to the literature on the SME–bank relationship by providing a structured framework for effective SME relationship management. Insights can help banks develop strategies and practices for serving SMEs, ultimately contributing to their growth and success.