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The purpose of this paper is to investigate the extent to which Chinese firms voluntarily extend the standard XBRL taxonomy to disclose more detailed financial information; and second, to identify and test corporate governance factors that may be associated with voluntary taxonomy extensions in eXtensible Business Reporting Language (XBRL)‐based reporting.

Using a sample of 114 firms that are listed on the Shanghai Stock Exchanges, the authors compared their XBRL‐based financial reports of 2008 and 2009 with the standard XBRL taxonomy. Multiple regression tests were performed to examine the effects of corporate governance factors and firm characteristics on XBRL taxonomy extensions.

The results indicate a high level of voluntary taxonomy extension in Chinese firms' XBRL reports. The extent of such extension is associated with the percentage of independent directors, combined CEO/chair of the board position, and firm size. It is also associated with audit firm size, in that companies audited by Big Four firms tend to have lower level of taxonomy extension. However, the direction of the result is opposite to what the authors expected.

This paper highlights the effects of corporate governance factors on Chinese firms' decisions to extend XBRL standard taxonomy and, in doing so, to disclose more financial information. Future research may consider using longitudinal data and alternative corporate governance factors to validate and extend the results.

It is an unanswered question as to whether and why firms extend standard XBRL taxonomies and disclose additional voluntary information. This paper fills the gap by investigating this issue in the context of the Chinese capital market.

Prior research established a seven dimensional taxonomy of financial ratios. The purpose of this paper is to identify the extent to which the previously identified relationships have changed, and if appropriate, to establish an entirely new taxonomy of manufacturing industry financial ratios.

The authors used principle component analysis (PCA) to identify factor patterns for 58 financial ratios over the ten-year period 2004-2013. The validity of employing PCA was confirmed using the Kaiser-Meyer-Olkin measure of sampling adequacy and Bartlett’s test of sphericity.

This study identified four additional financial analysis factors beyond the seven established by prior research. Notably, a separate cash flow factor did not surface as was the case in earlier work but an entirely new factor (current position) was identified.

This paper leaves to future research to establish the precise causes for the changes to the taxonomy of financial ratios and how to best utilize the new set of factors for financial analysis research.

This paper identifies changes in financial ratio relationships to guide future researchers in selecting appropriate ratios for their studies.

This study substantially improves and extends prior work in two areas. First, it utilizes advanced statistical methodologies and computing technologies that were unavailable to previous researchers. Second, it investigates not only the current taxonomy of manufacturing industry financial ratios, but also its stability over a recent ten-year period.

The aim of this paper is to present an online framework for building a domain taxonomy, called TaxoLine, from Web documents automatically.

TaxoLine proposes an innovative methodology that combines frequency and conditional mutual information to improve the quality of the domain taxonomy. The system also includes a set of mechanisms that improve the execution time needed to build the ontology.

The performance of the TaxoLine framework was applied to nine different financial corpora. The generated taxonomies are evaluated against a gold-standard ontology and are compared to state-of-the-art ontology learning methods.

The experimental results show that TaxoLine produces high precision and recall for both concept and relation extraction than well-known ontology learning algorithms. Furthermore, it also shows promising results in terms of execution time needed to build the domain taxonomy.

This paper aims to extend the knowledge of eXtensible Business Reporting Language (XBRL) to synthesize what 20 years of accounting and business literature on XBRL suggests about the effective improvement from its implementation in financial reporting.

A systematic literature review and bibliometric analysis of 142 articles resulted in the identification of 5 primary research streams: adoption issues; financial reporting; decision-making processes, market efficiency and corporate governance; audit and assurance issues; and non-financial reporting.

The results reveal a scarcity of studies devoted to explicating the consequences of XBRL implementation on financial reporting outside the SEC’s XBRL mandate and listed companies’ contexts. Also, some papers’ results question the usefulness of the language on the decision-making process. The overall lack of literature concerning the impact of XBRL on financial statement preparers, especially with reference to SMEs, is evident. Moreover, the consequences on corporate governance choices and the relevant internal decision-making processes are rarely debated.

The findings are useful for users of companies’ financial disclosure policies, particularly for regulators who manage XBRL implementation in countries where XBRL has not yet been adopted as well as for others working in specific areas of financial disclosure, such as non-financial reporting and public sector financial reporting.

This study differs from previous literature on XBRL as it focuses on a wider period of analysis and offers a unique methodology – combination of bibliometric and systematic review – as well as a business perspective for deepening XBRL.

The Securities Exchange Commission mandated eXtensible Business Reporting Language (XBRL) filing data provide immediate availability and easy accessibility for both academics and practitioners. To be useful, this data should provide information for decisions, specifically, investment decisions. The purpose of this study is to examine whether the XBRL database can be used with models, developed in previous studies, predicting the directional movement of earnings. The study does not attempt to examine the validity of these models, but only the ability to use the data in the analysis of financial statements based on these models.

The study analyzes New York Stock Exchange companies’ XBRL data using a two-step logistic regression model. The model is then used to arrive at the directional movement of earnings between current and subsequent quarters. Additional models are created by dividing the sample into industry membership.

The results classified companies as realizing an increase or a decrease in earnings. The final model indicated a significant ability to predict earnings changes, on average about 65 per cent of the time, for the entire model, and 71 per cent, for the industry-based models (higher than those of previous studies based on COMPUSTAT). The investment strategy created average quarterly return between 2.8 and 10.7 per cent.

The originality of this study is in the way it examines the quality of XBRL data, by examining whether findings from prior research which relied on traditional databases (such as COMPUSTAT) still hold using XBRL data. The use of XBRL allows not only easier and less-costly access to the data but also the ability to adjust the models almost immediately as current information is posted, thus providing a much more relevant tool for investors, especially small investors.

The purpose of this paper is to examine the potential for eXtensible Business Reporting Language (XBRL) to go beyond static reporting. A taxonomy structure of information is developed for providing a knowledge base and insights for an XBRL taxonomy for integrated reporting (IR).

Design Science (DS) research, as a pragmatic exploratory research approach, is embraced to create a new “artefact” and thematic content analysis is used to analyse IR in practice.

Using XBRL for IR allows a shift from static and periodic reporting to more relevant and dynamic corporate disclosure for stakeholders, who can navigate and retrieve customised disclosure information according to their interest by exploiting the multidimensionality of IR and overcome some of its criticisms. The bi-dimensional taxonomy structure the authors’ present allows users to navigate disclosure from two different perspectives (content elements (CE) and capitals), display specific themes of interest, and drill down to more detailed information. Because of its evidence-based nature and levels of disaggregation, it provides flexibility to preparers and users of information. Additionally, the findings demonstrate the need to codify sector-specific information for the CE, so that to direct the efforts toward the development of sector-specific taxonomy extensions in developing an XBRL taxonomy for IR.

The limitations of DS research are, first, the artefact design and, second, its effects in practice. The first limitation stems from the social actors’ perspective taken into account to develop the taxonomy structure, which derives from the analysis of the reporting practices rather than a pluralistic approach and dialogic engagement. The second limitation relates to the XBRL taxonomy development process because, since the study is limited to the “design” phase being codification and structuring the knowledge base for an XBRL taxonomy, there is a need to develop a taxonomy in XBRL and then apply it in practice to empirically demonstrate the potential and benefits of XBRL in the IR context.

The taxonomy structure is targeted at entities interested in designing an XBRL taxonomy for IR. This is a call for academics and practitioners to explore the potential of technology to improve corporate disclosure and open up new projections for resurging themes on intellectual capital (IC) reporting with prospects for IC “fourth-stage” research focused on IC disclosure.

This is an interdisciplinary research employing the DS approach, which is rooted in information systems research. It is the first academic study providing pragmatic results for using XBRL in the context of IC and IR.

In this study, research problem has been designed as a fleet-based optimization problem. This paper aims to present fleet modelling with risk taxonomy. Fleet modelling has been assumed as strategic multi-criteria decision-making problem to capacity building. Capacity building risk management is an essential element within the scope of its strategy to ensure sustainable corporate performance. Optimization is a fundamental target in aviation business’ strategy and management since the manager make decisions in their multi-interrelated criteria environment. Also, aviation is a highly regulated sector, and its operational and business procedures have certain limits by both national and international authorities. For this reason, companies implement risk management for strategic optimization while performing operations in compliance with the legislation. Risk management with capacity building and resource dependency perspective applied for strategic optimization aims to capture opportunities and result in threats with minimum accidents and incidents.

The taxonomy and analytical hierarchy process (AHP) have been identified as methodologies in this research. The type of training in the high organizational performance of an approved training organization, strategy, resources and allocations with the corporate objectives, the amount and qualifications of the flight crew, their professionalism, maintenance team and licenses, hangar conditions and capacity, authority requirements and limits, region conditions, altitude and meteorology, student profile, together with a multi-criteria decision are to be considered. For each criterion, there are resources and thus resource dependence. In this study, the analytical network process method was used. In the construction of new taxonomy, specific criteria have been considered, and the analysis has been accomplished as multi-criteria decision-making problem because of the relationship and interaction between them. A number of professionals with high knowledge of the pilots and manager from Air Traffic Organization participated in the study.

The fleet modelling is both strategic and operational decision issue for training organizations. In this issue, there is a vital problem as which aircrafts should include fleet? Main criteria and sub-criteria are analyzed by AHP method and sorted according to their priorities and the fleet qualifications consisting of the most suitable aircraft/aircraft are presented. The finding and suggestions will contribute to establish sustainable organization in based on capacity building and resource dependency for managers. While analyzing main criteria, the important criteria which were found were strategic and then operational. After ordering main criteria, sub-criteria were analyzed and were multiplicated with their items. According to study findings, aircraft suitability for training model is the most important item. It follows respectively aircraft maintenance sustainability, cost of aircraft supply and faculty budget adequacy. However, operation characteristics of the square that is less important item was found. It was seen that the strategies used to manage dependencies used the bridge strategy. The results we obtained with the interviews with pilot managers are very significant in terms of resource dependence on the subject of fleet optimization. While first criterion is operational, it continues with strategic and financial criteria. After interviews with pilot managers, it was figured out that maintenance is also very important criteria. For managing this dependency, university has acquisitions, which is one of the strategy to manage dependency, rather than outsourcing. For this reason, maintenance criterion has lower importance than others. When thinking of other criteria, strategic and financial criteria have played an important role. University has tried to decrease dependency and increase sustainability.

Aircraft selection is a strategic decision of fleet modelling in both aviation business and also training organizations via influencing their corporate performance, operational performance, capacity building and their sustainability. There are some factors that limit the criteria, as research problem has been developed for approved training organizations not airlines. For this reason, our research is limited with fleet of training organizations. Our findings and suggestions may be useful for flight schools to managing their resource dependency and also to their capacity building. In this research, new taxonomy has been developed depending on training organizations’ qualifications. Airlines may improve this taxonomy to use in their decision-making process.

The fleets, which were established considering the taxonomy in this study, will be able to manage the risk of resource dependency more successfully. Pilot candidates will be able to provide a more ergonomic and higher quality education. This research and its findings will contribute to the development of organizations’ accurate and timely decision-making skills. Resource dependency may threat organizational sustainability in our research, New taxonomy and our holistic approach will support organizational efforts to achieve sustainable strategies.

New taxonomy to modelling fleet that has been developed in this research may provide contribution to approved training organizations for both managing resource dependency-based risks and to capacity building-related decision-making process. This research may serve organizations as strategic decision-making tool. And also this kind of study may contribute to improve sustainability of organizations and serve more good fleet for their pilot candidates. For these reasons, this research may create social implications, as both resource using and capacity building will make contribution for society and add value.

This research presents new risk taxonomy and criteria. Also new taxonomy and its criteria are analysed with AHP. It is thought that this research shows risk management-based approach for fleet modelling creates benefits for approved training organizations to using their limited sources effectively and efficiently. The article includes risk management and capacity building-related approach to decision-making. also, this research presents modeling which will contribute to the management field besides literature. In developing taxonomy process, the analysis has been conducted, based on expert opinions and referred to for these pairwise comparisons. Airlines managers and risk managers may examine their fleet modelling according to our taxonomy which is based on risk management.

The purpose of this paper is to analyse the process by which “analogue” corporate reports produced under a “paper paradigm” are translated into a machine language as required by digital reporting. The paper uses Austin and Searle’s linguistic speech act theory to examine how digitally translating reporting information into atomised data affects the infrastructure and practice of accounting.

Extensive interview and observation evidence focussed on the IFRS Foundation’s digital reporting project is analysed. An interpretive approach is informed by the concepts of L compatibility, illocution and perlocutionary acts which are drawn from speech act theory.

Two key sites of translation are identified. The first site concerns the translation of accounting standards, principles and practices into taxonomies for digital tagging. Controversies arise over the definition of accounting concepts in a site populated by accounting and IT-orientated experts. The second site of translation is in the routine production and dissemination of digital reports which impacts the L compatibility between preparers and users.

The paper highlights a previously unexplored field of translation in accounting and contributes a unique perspective that demonstrates that machine translation is no longer marginalised but is the “primary” text with effects on the infrastructure and practice of accounting. It extends speech act theory by applying it to the digital domain and in the context of translation between languages.

This study aims to identify a taxonomy of financial ratios derived from financial statements prepared using International Financial Reporting Standards (IFRS). The work first empirically establishes and then statistically validates the taxonomy of financial attributes captured in financial ratios. In 2005, the European Commission required that publicly traded companies in the European Union use IFRS as the basis for financial reporting. In the same year, Australia adopted IFRS as a basis for financial reporting. Since then, 120 countries and reporting jurisdictions have adopted IFRS as the basis for financial reporting. Given that IFRS predominate in the financial reporting world, it seems essential to establish and validate IFRS-based ratio attributes. Only then can reliance upon and comparability of these ratios be warranted (Altman and Eisenbeis, 1978). Using principle component analysis, the authors empirically identify nine stable attributes (factors) for ratios drawn from IFRS-based financial statements from 84 counties. The findings provides an empirical basis to formulate testable hypotheses regarding the predictive and descriptive utility of financial ratios draw from IFRS-based financial statements.

The paper begins with a broad category of IFRS-based financial ratios, 50, found in practice and research, including income statement, balance sheet, cash flow, profitability and liquidity measures. Then, a sample of companies from the manufacturing sector is segmented using IFRS as a basis of financial statement reporting. Next, principal component analysis, a method of factor analysis, is applied to empirically identify factors and financial attributes captured in financial ratios used in research inquiry and financial analysis.

The authors find that the financial attributes captured by IFRS-based ratios go well beyond the traditional measures of profitability, liquidity and solvency. The authors identify nine factors that are interpretable and stable over the period, 2011-2015: asset relationship, asset turnover, capital structure, expense insight, fixed asset usage, inventory turnover, liquidity, profitability margin and performance return. Interestingly, the authors did not find a separate cash flow factor. Most importantly, the results corroborate that IFRS-based ratios are consistent and comparable, despite innate country differences that have been shown to influence the application, interpretation and use of IFRS.

The efforts are limited to the manufacturing sector. The financial attributes may be different in service, distribution and retail sectors. Also, limiting the effort are the ratios selected in this study. A broader range of ratios may widen the identification of unique stable factors over time.

The findings provide a basis for research and analysis efforts regarding the validity, comparability and stability of IFRS-based financial ratios. Most importantly, the results corroborate that IFRS-based ratios are consistent and comparable, despite innate country differences that have been shown to influence the application, interpretation and use of IFRS. The findings should be of interest to international and national financial reporting standard setters, investors and analysts.

An empirically evidenced classification system for IFRS-based financial ratios has yet to be determined based on a financial statements across a wide breadth of countries and reporting jurisdictions. Identification of stable interpretable factors, financial attributes, has been limited. The first is that inquiry has been limited to domestic-based, such as US Generally Accepted Accounting Principles, financial ratios. The second is inquiry has been limited to IFRS-based financial ratios within a specific country.

The European Union (EU) aims to become climate-neutral by 2050. Achieving this requires targeted measures and strategies. One of the instruments of the EU is the EU taxonomy, a classification system with the purpose of creating a common definition of what economic activities are deemed sustainable. The paper aims to examine how the EU taxonomy can affect the Norwegian construction industry, property owners and facilities management (FM) providers.

The research is based on a document analysis and interviews with main stakeholders within the financial sector, construction and real estate (RE) sector, authorities, environmental organisations and businesses related to FM and RE.

The findings show that different stakeholders share largely similar attitudes towards the taxonomy, although some differ in their opinions. This paper finds that there are high levels of uncertainty and confusion associated with the taxonomy, which can be said to be a major obstacle for successful implementation. Several stakeholders show concerns related to the fact that Norway lacks definitions and regulations on which the taxonomy is based. The requirements for new buildings and existing buildings are considered stricter than the current practice in the Norwegian construction and RE industry, while the requirements for renovation are considered more achievable. The uptake of the EU taxonomy will impact the FM and the urban FM practices and standards for the procurement of services, and the integration of environmental, social and governance (ESG) policies must be developed.

The research presented in this paper was conducted at a time when the EU taxonomy was a relatively unknown concept in the Norwegian construction and RE industry. FM providers were not interviewed in this study.

This research is one of the first studies to be conducted on this topic in Norway and represents the first meeting between the EU taxonomy and the industry. The discussion underpins the relevance of adjusting and updating FM standards to today’s knowledge about ESG principles.

The paper shows the viewpoint of the Norwegian stakeholders involved in the construction and RE industry. This gives valuable information about the challenges that the industry needs to overcome.