A methodology for analysing and evaluating narratives in annual reports: a comprehensive descriptive profile and metrics for disclosure quality attributes

There is a consensus that the business reporting model needs to expand to serve the changing information needs of the market and provide the information required for enhanced corporate transparency and accountability. Worldwide, regulators view narrative disclosures as the key to achieving the desired step-change in the quality of corporate reporting. In recent years, accounting researchers have increasingly focused their efforts on investigating disclosure and it is now recognised that there is an urgent need to develop disclosure metrics to facilitate research into voluntary disclosure and quality [Core, J. E. (2001). A review of the empirical disclosure literature. Journal of Accounting and Economics, 31(3), 441–456]. This paper responds to this call and contributes in two principal ways. First, the paper introduces to the academic literature a comprehensive four-dimensional framework for the holistic content analysis of accounting narratives and presents a computer-assisted methodology for implementing this framework. This procedure provides a rich descriptive profile of a company's narrative disclosures based on the coding of topic and three type attributes. Second, the paper explores the complex concept of quality, and the problematic nature of quality measurement. It makes a preliminary attempt to identify some of the attributes of quality (such as relative amount of disclosure and topic spread), suggests observable proxies for these and offers a tentative summary measure of disclosure quality

The KINDRA project. Sharing and evaluating groundwater research and knowledge in Europe

Groundwater knowledge and research in the European Union is often scattered and non-standardised, because of different subjects involved and different approaches from Member States. The Horizon2020 project KINDRA has conducted an EU-wide assessment of existing groundwater-related practical and scientific knowledge based on a new Hydrogeological Research Classification System, identifying more than 280 keywords related to three main categories (namely Operational Actions, Research topics and Societal Challenges) to be intersected in a 3D-diagram approach. The classification is supported by a web-service, the European Inventory of Groundwater Research, which acts not only as knowledge repository but also as a tool to help identify relevant researchm topics, existing research trends and critical research challenges. The records have been uploaded during the project by 20 national experts from National Associations of Geologists, under the umbrella of the European Federation of Geologists. The total number of metadata included in the inventory at the end of the project are about 2300, and the analysis of the results is considered useful for producing synergies, implementing policies and optimising water management in Europe. By the use of additional indicators, the database content has been analysed by occurrence of keywords, type of document, level of innovation. Using the three-axes classification, more easily understandable by 2D diagrams as bubble plots, occurrence and relationship of different topics (main categories) in groundwater research have been highlighted. This article summarizes the activities realized in relation to the common classification system and to the metadata included in the EIGR, showing the distribution of thecollected information in different categories and attributes identified by the classification

Ewé: a web-based ethnobotanical database for storing and analysing data

Ethnobotanical databases serve as repositories of traditional knowledge (TK), either at international or local scales. By documenting plant species with traditional use, and most importantly, the applications and modes of use of such species, ethnobotanical databases play a role in the conservation of TK and also provide access to information that could improve hypothesis generation and testing in ethnobotanical studies. Brazil has a rich medicinal flora and a rich cultural landscape. Nevertheless, cultural change and ecological degradation can lead to loss of TK. Here, we present an online database developed with open-source tools with a capacity to include all medicinal flora of Brazil. We present test data for the Leguminosae comprising a total of 2078 records, referred to here as use reports, including data compiled from literature and herbarium sources. Unlike existing databases, Ewé provides tools for the visualization of large datasets, facilitating hypothesis generation and meta-analyses. The Ewé database is currently available at www.ewedb.com

Knowledge Cartography for Controversies: The Iraq Debate

In analysing controversies and debates—which would include reviewing a literature in order to plan research, or assessing intelligence to formulate policy—there is no one worldview which can be mapped, for instance as a single, coherent concept map. The cartographic challenge is to show which facts are agreed and contested, and the different kinds of narrative links that use facts as evidence to define the nature of the problem, what to do about it, and why. We will use the debate around the invasion of Iraq to demonstrate the methodology of using a knowledge mapping tool to extract key ideas from source materials, in order to classify and connect them within and across a set of perspectives of interest to the analyst. We reflect on the value that this approach adds, and how it relates to other argument mapping approaches

Application of artificial neural network in market segmentation: A review on recent trends

Despite the significance of Artificial Neural Network (ANN) algorithm to market segmentation, there is a need of a comprehensive literature review and a classification system for it towards identification of future trend of market segmentation research. The present work is the first identifiable academic literature review of the application of neural network based techniques to segmentation. Our study has provided an academic database of literature between the periods of 2000-2010 and proposed a classification scheme for the articles. One thousands (1000) articles have been identified, and around 100 relevant selected articles have been subsequently reviewed and classified based on the major focus of each paper. Findings of this study indicated that the research area of ANN based applications are receiving most research attention and self organizing map based applications are second in position to be used in segmentation. The commonly used models for market segmentation are data mining, intelligent system etc. Our analysis furnishes a roadmap to guide future research and aid knowledge accretion and establishment pertaining to the application of ANN based techniques in market segmentation. Thus the present work will significantly contribute to both the industry and academic research in business and marketing as a sustainable valuable knowledge source of market segmentation with the future trend of ANN application in segmentation.Comment: 24 pages, 7 figures,3 Table

A Correlation Framework for Continuous User Authentication Using Data Mining

Merged with duplicate records: 10026.1/572, 10026.1/334 and 10026.1/724 on 01.02.2017 by CS (TIS)The increasing security breaches revealed in recent surveys and security threats reported in the media reaffirms the lack of current security measures in IT systems. While most reported work in this area has focussed on enhancing the initial login stage in order to counteract against unauthorised access, there is still a problem detecting when an intruder has compromised the front line controls. This could pose a senous threat since any subsequent indicator of an intrusion in progress could be quite subtle and may remain hidden to the casual observer. Having passed the frontline controls and having the appropriate access privileges, the intruder may be in the position to do virtually anything without further challenge. This has caused interest'in the concept of continuous authentication, which inevitably involves the analysis of vast amounts of data. The primary objective of the research is to develop and evaluate a suitable correlation engine in order to automate the processes involved in authenticating and monitoring users in a networked system environment. The aim is to further develop the Anoinaly Detection module previously illustrated in a PhD thesis [I] as part of the conceptual architecture of an Intrusion Monitoring System (IMS) framework

A Business Model Research Schema

This paper suggests a schema for business model research that has the potential to progress the research, in a structured manner, from conceptual to theoretical. It draws on the scientific and business research literature to identify the types of research necessary to further knowledge and promotes the inductive-deductive model of research. The importance of conducting empirical research to evaluate current conceptualisations of business models and developing a theory of business models is stressed. An important aspect of any research agenda is the creation of a general classification of domain objects that can serve a wide range of current and future uses. Classification literature relating to the biological, behavioural, organisational and social sciences has been referenced in this paper in support of this claim. Existing classifications of business models are evaluated, determining that the only classifications that have been proposed to date are typologies and that no general taxonomy of business models currently exists