Development Of Taxonomy Research Articles

Negotiating pricing and payment terms for insurance covered mHealth apps: a qualitative content analysis and taxonomy development based on a German experience

BackgroundGermany was the first country worldwide to offer mobile digital health applications (mHealth apps, “DiGA”) on prescription with full cost coverage by statutory health insurances. Especially statutory health insurances criticize the current pricing and payment regulations in Germany due to “free and non-transparent” pricing in the first year and lack of cost use evidence. The study consists of two parts: The first part evaluates interests of digital health application providers and statutory health insurances in Germany to identify overlaps and divergences of interests. The second part includes the development of a comprehensive pricing and payment taxonomy for reimbursable mHealth apps in general.MethodsBoth parts of the study used the input from 16 expert interviews with representatives of digital health application providers and statutory health insurances in Germany. In part one the authors conducted a qualitative content analysis and in part two they followed the taxonomy development process according to Nickerson et al. (2013).ResultsA value based care model is expected to bring the greatest benefit for patients while statutory health insurances welcome the idea of usage based pricing. The final pricing and payment taxonomy consists of four design and negotiation steps (price finding, payment prerequisites, payment modalities, composition of negotiation board).ConclusionsAs healthcare resources are scarce and thus need to be optimally allocated, it is important to implement pricing and payment terms for reimbursable mHealth apps that result in the greatest benefit for patients. To the best of the authors’ knowledge, there has been no structured study yet that examines alternative pricing strategies for reimbursable mHealth apps.The developed pricing and payment taxonomy for reimbursable mHealth apps serves as planning and decision basis for developers, health policy makers and payers internationally.

A SYNTHESIS OF THE DETERMINANTS OF SUCCESSFUL INTERCULTURAL COMMUNICATION IN ORGANISATIONS

Organisations exist, function and develop through communication. Intercultural communication is a specific communication activity in which the parties involved represent different cultures. The current context, dominated by globalisation, multiculturalism, internationalisation and digitalisation, underlines the importance of studying intercultural communication in an organisational context. The aim of this paper is to develop a comprehensive synthesis of the factors that influence the effectiveness of intercultural communication in organisations and to propose research hypotheses for future studies in this area. The methodology used to conduct this study includes the methods of analysis, synthesis, induction (for logical connections), deduction (for identifying theories from the literature), abduction (for identifying causes and factors and building hypotheses) and hierarchical classification (for grouping factors in the three-level taxonomy). The analysis of the factors mentioned in the literature on the effectiveness of intercultural communication in organisations has led to the development of a three-level taxonomy that groups them into five categories: management-related factors, group factors, individual factors, cultural factors and communication factors. This systematic and clarifying approach suggests linkages and directions for research as well as lines of action for practitioners to ensure sustainable development of multicultural organisations and increase the chances of success of intercultural communication in different organisational contexts. The novelty of the paper lies in the fact that the existing literature does not propose a systemic view of the factors that influence intercultural communication outcomes. Most of the identified research presents comparative, descriptive approaches to the characteristics of intercultural communication in specific cultural contexts.

Bridging academia and industry in the era of Industry 4.0 by means of the triple helix: The PLANET4 initiative

Practical Learning of Artificial Intelligence on the Edge of Industry 4.0 (PLANET4) is a cross-disciplinary initiative funded by the European Commission under the Erasmus+ program that embodies the triple helix model of collaboration between academia, industry, and administration. It aims to bridge the gap between academic teaching and practical applications in the context of Industry 4.0. PLANET4 focuses on developing hard skills in artificial intelligence, industrial Internet of things, and cloud and edge computing, along with the soft competencies required to manage changes in the industrial ecosystem. It involves three phases: (1) training needs analysis, taxonomy development, and workshop design; (2) collection of best practices and training material design; and (3) implementation of the PLANET4 learning course. This paper presents the materialization of these phases into a blended learning course, highlighting the integration of the triple helix model and the European Commission’s support for academia-industry collaboration with the aim of improving education quality and promoting Industry 4.0 innovation in Europe.

A Systematic Review of Evidence-based General Competency Models: Development of a General Competencies Taxonomy

A Systematic Review of Evidence-based General Competency Models: Development of a General Competencies Taxonomy

Species of the Sections Hedysarum and Multicaulia of the Genus Hedysarum (Fabaceae): Taxonomy, Distribution, Chromosomes, Genomes, and Phylogeny.

The genus Hedysarum L. (Fabaceae) includes about 200 species of annual and perennial herbs distributed in Asia, Europe, North Africa, and North America. Many species of this genus are valuable medicinal, melliferous, and forage resources. In this review, we consider the taxonomic history of the genus Hedysarum, the chromosomal organization of the species from the sections Hedysarum and Multicaulia, as well as phylogenetic relationships between these sections. According to morphological, genetic, and phylogenetic data, the genus Hedysarum is divided into three main sections: Hedysarum (= syn. Gamotion), Multicaulia, and Stracheya. In species of this genus, two basic chromosome numbers, x = 7 (section Hedysarum) and x = 8 (sections Multicaulia and Stracheya), were determined. The systematic positions of some species within the sections are still uncertain due to their morphological similarities. The patterns of distribution of molecular chromosomal markers (45S rDNA, 5S rDNA, and different satellite DNAs) in karyotypes of various Hedysarum species made it possible to determine their ploidy status and also specify genomic relationships within the sections Hedysarum and Multicaulia. Recent molecular phylogenetic studies clarified significantly the taxonomy and evolutionary development of the genus Hedysarum.

Archetypes of blockchain-based business models in enterprise networks

AbstractMany enterprises are currently engaged in developing blockchain-based business models. Enterprise networks offer a variety of potential applications for blockchain solutions as they benefit from transparency and security as well as automation of handling data, material, and financial flows along their supply chains. Despite profound potentials, the indicated business models are still in their early stages and need further investigation. To provide an overview of existing blockchain-based business models in the context of enterprise networks, the underlying paper designs a multidimensional taxonomy and identifies several archetypes of blockchain-based businesses. For the taxonomy development, data from 101 blockchain start-ups serves as a basis for empirical validation. Using hierarchical clustering and the k-means method, seven archetypes that sharpen the understanding of how blockchain solutions affect business models in enterprise networks and enable new business models are derived. The proposed work results are intended to be applied in future research and practice to classify and assess the integration of blockchain solutions into existing business models and to support developing new ones that leverage emerging technological capabilities.

HISTORY OF THE ERMINE MOTH (LEPIDOPTERA: YPONOMEUTIDAE) STUDY IN THE RUSSIAN FAR EAST AND ADJACENT COUNTRIES

As a result of the analysis of the history of the family Yponomeutidae study the three conditional stages were outlined mainly based on the used research methods. The first stage, which began in the first half of XVIII century and ended at the beginning of the XX century, covers the period from the first descriptions with illustrations of larva nests and the external features of the preimaginal and imaginal stages to the use of genital characters in the species identification. From the latter the second stage starts and ends before the introduction of the molecular genetic method for study of taxonomic diversity. During this stage the study of the ermine moths were expanded to comparative morphological research, elucidation of the homology of genital structures based on their functional morphology and development of taxonomy based on phylogenetic analyses. The third stage begins from the end of XX century, when researchers started to use molecular markers to solve taxonomic problems in the group. According to the results of many years of research, the fauna of yponomeutid moths has been studied in Russia and adjacent countries very unevenly and, in general, insufficiently. Currently, the species diversity of ermine moths in the Russian Far East is 38 species from 10 genera, significantly inferior to that of China (70 species of 17 genera) and less to that in Japan (46 species of 16 genera). However, the species diversity of ermine moths in the Russian Far East exceeds the known diversity of this group in Korea (25 species from 10 genera).

Consumer proactive empowerment: A systematic review and taxonomy development

Consumer proactive empowerment: A systematic review and taxonomy development

When East meets West: The politicization of kei pou (qipao) or cheongsam in Hong Kong

When East meets West: The politicization of kei pou (qipao) or cheongsam in Hong Kong

Enhancing strategy for Industry 4.0 implementation through maturity models and standard reference architectures alignment

PurposeA maturity model for Industry 4.0 (I4.0 MM) with influencing factors is designed to address maturity issues in adopting Industry 4.0. Standardisation in I4.0 supports manufacturing industry transformation, forming reference architecture models (RAMs). This paper aligns key factors and maturity levels in I4.0 MMs with reputable I4.0 RAMs to enhance strategy for I4.0 transformation and implementation.Design/methodology/approachThree steps of alignment consist of the systematic literature review (SLR) method to study the current published high-quality I4.0 MMs, the taxonomy development of I4.0 influencing factors by adapting and implementing the categorisation of system theories and aligning I4.0 MMs with RAMs.FindingsThe study discovered that different I4.0 MMs lead to varied organisational interpretations. Challenges and insights arise when aligning I4.0 MMs with RAMs. Aligning MM levels with RAM stages is a crucial milestone in the journey toward I4.0 transformation. Evidence indicates that I4.0 MMs and RAMs often overlook the cultural domain.Research limitations/implicationsFindings contribute to the literature on aligning capabilities with implementation strategies while employing I4.0 MMs and RAMs. We use five RAMs (RAMI4.0, NIST-SME, IMSA, IVRA and IIRA), and as a common limitation in SLR, there could be a subjective bias in reading and selecting literature.Practical implicationsTo fully leverage the capabilities of RAMs as part of the I4.0 implementation strategy, companies should initiate the process by undertaking a thorough needs assessment using I4.0 MMs.Originality/valueThe novelty of this paper lies in being the first to examine the alignment of I4.0 MMs with established RAMs. It offers valuable insights for improving I4.0 implementation strategies, especially for companies using both MMs and RAMs in their transformation efforts.

Breaking the chains of traditional finance: A taxonomy of decentralized finance business models

Recently, the looming bankruptcy of Credit Suisse, which ultimately led to its merger with UBS, has intensified the discussion surrounding the need for more transparent and democratic financial markets. Decentralized finance (DeFi) represents a departure from traditional financial intermediation by leveraging blockchain technology and smart contracts. Despite its growing importance, limited research has been conducted on the business models of DeFi services. This study aims to address this gap by examining the business models of various DeFi services, identifying key drivers of innovation, differentiation, and value creation. Using a rigorous taxonomy development framework, we identify 12 dimensions and 47 characteristics that operationalize business models in DeFi. Our findings contribute to a better understanding of the transformation of financial services through blockchain technology and provide valuable insights for DeFi entrepreneurs, investors, and policymakers.

Development and Application of an Attribute-Based Taxonomy on the Benefits of Oral Anticoagulant Switching in Atrial Fibrillation: A Delphi Study.

Patients with atrial fibrillation (AF) often switch between oral anticoagulants (OACs). It can be hard to know why a patient has switched outside of a clinical setting. Medication attribute comparisons can suggest benefits. Consensus on terms and definitions is required for inferring OAC switch benefits. The objectives of the study were to generate consensus on a taxonomy of the potential benefits of OAC switching in patients with AF and apply the taxonomy to real-world data. Nine expert clinicians (seven clinical pharmacists, two cardiologists) with at least 3years of clinical and research experience in AF participated in a Delphi process. The experts rated and commented on a proposed taxonomy on the potential benefits of OAC switching. After each Delphi round, ratings were analyzed with the RAND Corporation/University of California, Los Angeles (RAND/UCLA) appropriateness method. Median ratings, disagreement index, and comments were used to modify the taxonomy. The resulting taxonomy from the Delphi process was applied to a cohort of patients with AF who switched OACs in a population-based administrative health dataset from 1996 to 2019 in British Columbia, Canada. The taxonomy was finalized in two Delphi rounds, reaching consensus on five switch benefit categories: safety, effectiveness, convenience, economic considerations, and drug interactions. Safety benefit (a switch that could lower the risk of adverse drug events) had three subcategories: major bleeding, intracranial hemorrhage (ICH), and gastrointestinal (GI) bleeding. Effectiveness benefit had four subcategories: stroke and systemic embolism (SSE), ischemic stroke, myocardial infarction (MI), and all-cause mortality. Real-world OAC switches revealed that more OAC switches had convenience (72.6%) and drug interaction (63.0%) benefits compared to effectiveness (SSE 22.0%, ischemic stroke 11.1%, MI 3.1%, all-cause mortality 10.1%), safety (major bleeding 24.3%, GI bleeding 10.6%, ICH 48.5%), and economic benefits (12.1%). The Delphi-based taxonomy identified five criteria for the beneficial effects of OAC switching, aiding in characterizing real-world OAC switching.

Create the Taxonomy for Unintentional Insider Threat via Text Mining and Hierarchical Clustering Analysis

The unintentional activities of system users can jeopardize the confidentiality, integrity, and assurance of data on information systems. These activities, known as unintentional insider threat activities, account for a significant percentage of data breaches. A method to mitigate or prevent this threat is using smart systems or artificial intelligence (AI). The construction of an AI requires the development of a taxonomy of activities. The literature review focused on data breach threats, mitigation tools, taxonomy usage in cybersecurity, and taxonomy development using Endnote and Google Scholar. This study aims to develop a taxonomy of unintentional insider threat activities based on narrative descriptions of the breach events in public data breach databases. The public databases were from the California Department of Justice, US Health and Human Services, and Verizon, resulting in 1850 examples of human errors. A taxonomy was constructed to specify the dimensions and characteristics of objects. Text mining and hierarchical cluster analysis were used to create the taxonomy, indicating a quantitative approach. Ward’s agglomeration coefficient was used to ensure the cluster was valid. The resulting top-level taxonomy categories are application errors, communication errors, inappropriate data permissions, lost media, and misconfigurations.

Význam buku lesního ve střední Evropě v období klimatické změny: přehled současných poznatků

In the period of ongoing global climate change, ecosystems, including Central European forests, face significant challenges such as summer droughts and heat waves, which increase the climate risks also for the European beech (Fagus sylvatica L.), an important and dominant broadleaved tree species in this region. This article provides a comprehensive review of current knowledge on the adaptation strategies of European beech in response to changing climatic conditions, highlighting its ecological demands, development of taxonomy, ecological and economic importance and exploring its resilience, growth characteristics, and challenges such as water regime, pests, diseases, and the impact of climate change. A key finding is that despite the various stressors affecting European beech, adaptive management and the use of mixed forest stands can significantly contribute to its conservation and sustainable use. The importance of integrating the genetic diversity and adaptive capacity of European beech into forestry practices is emphasised. The review of 203 studies highlights the need for further research focused on understanding the interactions between European beech and a changing climate in order to develop more effective strategies for its conservation and sustainable management in the future.

Development of a spatial dimension-based taxonomy for classifying the defect patterns in a wafer bin map

A wafer bin map (WBM) represents the locational information of defective chips on the wafer. The spatial correlation of defects on the wafer provides crucial information for the root cause diagnosis of defects in wafer fabrication. The spatial correlation is classified as a defect pattern for efficient diagnostics. A defect pattern taxonomy should be defined in advance for coherent classification of defect patterns. Various taxonomies are used in previous studies, but they share common limitations in that the differentiation among defect patterns is unclear, the set of predefined defect patterns is insufficient, and they cannot accommodate newly-emerged defect patterns. A concept of spatial dimension-based defect pattern taxonomy and its development procedure are proposed. Defect patterns are defined by three spatial dimensions, namely, Shape, Size, and Location. The development procedure is applied to a major NAND flash memory semiconductor manufacturer for two years. Results show that spatial dimension-based taxonomy can improve the performance of the defect pattern classification system by alleviating common existing limitations. Moreover, meaningful defect patterns for diagnostics are retained through the engineers’ involvement in the development procedure.

Hosting and Integrating a Hawaiian Language Taxonomy in the British Museum’s Collection Database

With more than 2.5 million catalogue records the British Museum’s digital collection database is one of the largest museum databases in the world, constituting a primary point of access to the collections both internally and externally. But its recording systems, developed over multiple generations, contain problematic data in a structure dominated by a single language. This article focuses on efforts to transform a portion of the data within the structural complexities. In 2021, a Hawaiian language research group was formed at the British Museum. Named Keaukānaʻi, this group supports the development and integration of a new taxonomy in ʻōlelo Hawaiʻi (Hawaiian language) for describing Hawaiian ancestral treasures physically at the museum. The authors reflect on the work initiated to deconstruct taxonomical violence, and to build a new path forward for hosting, integrating and centering an indigenous language and associated knowledge at the British Museum. The article presents key steps while also discussing the challenges and limitations encountered.

Taxonomy development for term standardization in activity resulting from medication review processes: a Delphi study.

Medication review (MR) is the systematic assessment of a patient's medications for safety and effectiveness by a healthcare professional. The language used to describe MR activity, such as stopped medicine and increased dose, should be consistent across studies to assist researchers compare how different services operate and identify their mechanism of impact. To develop an international taxonomy of standardized terms and activity definitions related to medication reviews. This was a three-stage Delphi-based consensus study with international medication review experts. A systematic review provided MR activity terms for the survey. Experts rated their consensus on each activity term and its definition on a Likert scale and provided written feedback. The consensus was 75% panel agreement. At each stage, consensus elements were retained, and feedback was used to revise definitions. Seven experts were recruited for the study (response rate 15.2%) from four countries: the United Kingdom (n = 4), New Zealand (n = 1), Australia (n = 1), and Malaysia (n = 1). The following terms achieved consensus: the term Medication as a descriptor for MR terms; discontinue medication, start medication, dose increase, dose decrease, dosage form change, and medication safety and efficacy monitor to describe MR activity; Educate to describe the delivery of healthcare professionals and patients/carers education. Standardized medication review activity terms and definitions have been selected for universal adoption in all future MR research to facilitate a meaningful comparison of process evaluations within different settings.

Knowledge and ICT based networks: towards a taxonomy

Abstract Purpose The article proposes a taxonomy of knowledge-based and information and communication technology (ICT) networks based on a systematic literature review. The specific objectives focus on (1) presenting knowledge-based and ICT network models, indicating their theoretical context (trends); (2) identifying proposals for knowledge-based network models in the literature (based on SLR); (3) developing a taxonomy of knowledge-based network models; and (4) indicating the directions of their development. Design/methodology/approach The systematic literature review (SLR) methodology was used, which allows not only for a formalized and objectified synthesis of the existing scientific achievements or for the evaluation of previous research. In addition, the “snowball” method was used, and its application was supported by the use of the ResearchRabbit tool. In addition, the taxonomy method (typological analysis, typological approach) was used. Findings The results of SLR were presented: a list of selected types of knowledge-based and ICT networks along with a discussion of the results, and the author’s proposals for a taxonomy of knowledge-based and ICT networks were presented along with a synthetic description of the leading models. The directions of their development were also indicated. Practical implications (*if any, optional). The practical usefulness of the proposal contained in the study is related to the possibility of using the proposed concept to evaluate various types of network models, which will enable the formulation of diagnostic findings and conducting comparative and dynamic research in the field of analysis and evaluation of knowledge-based and ICT-based network models. Originality/value The added value of the article is related to the development of a proprietary taxonomy of knowledge- and ICT-based networks and, consequently, to the organization and systematization of models of these networks. This taxonomy is a valuable tool for organizing and categorizing information systematically. When it comes to knowledge and ICT-based networks, a taxonomy can help classify and understand the different types and components involved in starting point division into network models that were created as a result of the virtualization process and models that were created as a result of exchange processes and the flow of intangible assets. The added value is also related to the practical usefulness of the developed taxonomy.

Privacy, Security, and Legal Issues in the Health Cloud: Structured Review for Taxonomy Development.

Privacy in our digital world is a very complicated topic, especially when meeting cloud computing technological achievements with its multidimensional context. Here, privacy is an extended concept that is sometimes referred to as legal, philosophical, or even technical. Consequently, there is a need to harmonize it with other aspects in health care in order to provide a new ecosystem. This new ecosystem can lead to a paradigm shift involving the reconstruction and redesign of some of the most important and essential requirements like privacy concepts, legal issues, and security services. Cloud computing in the health domain has markedly contributed to other technologies, such as mobile health, health Internet of Things, and wireless body area networks, with their increasing numbers of embedded applications. Other dependent applications, which are usually used in health businesses like social networks, or some newly introduced applications have issues regarding privacy transparency boundaries and privacy-preserving principles, which have made policy making difficult in the field. One way to overcome this challenge is to develop a taxonomy to identify all relevant factors. A taxonomy serves to bring conceptual clarity to the set of alternatives in in-person health care delivery. This study aimed to construct a comprehensive taxonomy for privacy in the health cloud, which also provides a prospective landscape for privacy in related technologies. A search was performed for relevant published English papers in databases, including Web of Science, IEEE Digital Library, Google Scholar, Scopus, and PubMed. A total of 2042 papers were related to the health cloud privacy concept according to predefined keywords and search strings. Taxonomy designing was performed using the deductive methodology. This taxonomy has 3 layers. The first layer has 4 main dimensions, including cloud, data, device, and legal. The second layer has 15 components, and the final layer has related subcategories (n=57). This taxonomy covers some related concepts, such as privacy, security, confidentiality, and legal issues, which are categorized here and defined by their expansion and distinctive boundaries. The main merits of this taxonomy are its ability to clarify privacy terms for different scenarios and signalize the privacy multidisciplinary objectification in eHealth. This taxonomy can cover health industry requirements with its specifications like health data and scenarios, which are considered as the most complicated among businesses and industries. Therefore, the use of this taxonomy could be generalized and customized to other domains and businesses that have less complications. Moreover, this taxonomy has different stockholders, including people, organizations, and systems. If the antecedent effort in the taxonomy is proven, subject matter experts could enhance the extent of privacy in the health cloud by verifying, evaluating, and revising this taxonomy.

How to establish digital health ecosystems from the perspective of health service-organizations: A taxonomy developed based on expert interviews conducted as modified Delphi approach.

Digital health ecosystems may be the next revolution in improving citizens' well-being, health delivery, data management, and health system processes, but solutions have not yet been broadly established. Reasons could be that health service-organizations have misaligned interests or lack capabilities. This study investigates reasons from a multi-health-service-organization perspective, differentiating between payers, insurers, healthcare providers, and innovators, detailing the expected value-adds, preferred participation roles, and required capabilities including a rating assessment. Findings are based on a taxonomy development methodology, which combines a literature review with semi-structured qualitative expert interviews, conducted using a modified Delphi approach. Interviews were thematically analysed. In total, 21 experts across the four health service-organization groups were interviewed. The capability taxonomy includes a total of 16 capabilities, categorized in three themes: 'Health market', 'organizational', and 'technology and informatic'. Providers expect a value-add from strengthening their health process economics through efficiency gains but reveal the largest capability gaps, especially in 'interoperability' and 'platform'. Innovators' 'technology and informatic' capabilities complement well with those of payers for the 'health market'. We present a health service-organization-specific three-stage approach for establishing digital health ecosystems. Payers and insurers should address their 'technology and informatic' capability gaps, using technical enablers or forming new entities to reduce dependencies from legacy information technology systems. Innovators should clarify their monetization models and create positive awareness for their services, possibly entering the market directly. Providers must address interoperability issues and may require incentives to encourage their participation. Findings suggest governmental policymakers to prioritize three health policy initiatives.