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The purpose of this paper is to explore the evolution of greenhouse gas (GHG) reporting quality and to determine whether the evolution of reporting quality is linked with the type of information reported based on the “search”, “experience”, and “credence” typology.

The method is based on the content analysis of GHG reporting in 245 sustainability reports by 45 oil and gas companies between 1998 and 2010. The content analysis disclosure index developed links GHG reporting requirements with seven quality dimensions. The information associated with each item on the content analysis index is classified as “search”, “experience” or “credence”. Statistical analysis is used to determine whether any significant change occurred in either overall GHG reporting quality or in the quality of reporting in any of the individual dimensions of quality over the period of the study.

GHG reporting quality has not improved significantly between 1998 and 2010. The quality of reporting is not the same in each of the seven dimensions of quality and this can be explained by information typology.

This paper provides the first longitudinal analysis of the quality of GHG reporting. The methodology developed advances current measures of reporting quality by linking reporting requirements with particular quality dimensions. The results show that the type of information is important in terms of quality evolution and that this can dictate the measures required to improve quality.

The purpose of this paper is to develop a method for information classification. The proposed method draws on established standards, such as the ISO/IEC 27002 and information classification practices. The long-term goal of the method is to decrease the subjective judgement in the implementation of information classification in organisations, which can lead to information security breaches because the information is under- or over-classified.

The results are based on a design science research approach, implemented as five iterations spanning the years 2013 to 2019.

The paper presents a method for information classification and the design principles underpinning the method. The empirical demonstration shows that senior and novice information security managers perceive the method as a useful tool for classifying information assets in an organisation.

Existing research has, to a limited extent, provided extensive advice on how to approach information classification in organisations systematically. The method presented in this paper can act as a starting point for further research in this area, aiming at decreasing subjectivity in the information classification process. Additional research is needed to fully validate the proposed method for information classification and its potential to reduce the subjective judgement.

The research contributes to practice by offering a method for information classification. It provides a hands-on-tool for how to implement an information classification process. Besides, this research proves that it is possible to devise a method to support information classification. This is important, because, even if an organisation chooses not to adopt the proposed method, the very fact that this method has proved useful should encourage any similar endeavour.

The proposed method offers a detailed and well-elaborated tool for information classification. The method is generic and adaptable, depending on organisational needs.

This paper aims to review key content, architecture, and metadata model decisions and strategies in creation of a publication portal (on DVD to start), based on a 30+ year series of flagship reports from the World Bank.

The paper describes and analyzes key considerations and aspects of the project, including content architecture, content analysis, DTD selection, retrospective conversion, vendor management, design of metadata architectures, use of automated profiling methods, user‐information behavior, and search architectures supporting complex content architectures. It includes the challenges of applying an institutionally based taxonomy required to express subject‐matter responsibilities and relationships within the World Bank.

The team learned that the metadata behavior and architecture (inheritance, relationships, variations) are more complex than simple links between parent and child objects. The project also reinforced the importance of comprehensive and dynamic topic taxonomy for classifying content that is both historical and current. The approach to defining classes for each full report (parent) will be likely to change, given what has been learned. The team would recommend that parts be classified and the sum of the part classes be assigned to the whole report. As a result of this exploratory work, the Bank's approach to classification and indexing of report series is changing from a top‐down to a bottom‐up inheritance.

The study provides insights into both general and World Bank‐specific challenges in creating a publication portal and derives some best practices for content architecture, metadata architecture, and use of automated profiling methods.

Since the early years of the Cold War, two countervailing trends have been present in the treatment of officially held information in the United States. On the one hand, as the foundations of U.S. information policy were being set after World War II, wartime practices were remade and made permanent in a crisis atmosphere, with the establishment of a classification system (essentially the same one used to this day) by executive order, as well, as the passage of the Atomic Energy Act in 1946 and the National Security Act in 1947. However, even as the practice of official secrecy took root, the United States took the lead in formalizing standards of openness by statute, beginning with the 1946 passage of the Administrative Procedures Act and culminating in the passage (and 1974 strengthening) of the Freedom of Information Act. This article traces the development of U.S. information policy since World War II and describes the impact of official secrecy on decision making and democratic practice more generally.

The purpose of this study is to construct a gray relational model based on information diffusion to avoid rank reversal when the available decision information is insufficient, or the decision objects vary.

Considering that the sample dependence of the ideal sequence selection in gray relational decision-making is based on case sampling, which causes the phenomenon of rank reversal, this study designs an ideal point diffusion method based on the development trend and distribution skewness of the sample information. In this method, a gray relational model for sample classification is constructed using a virtual-ideal sequence. Subsequently, an optimization model is established to obtain the criteria weights and classification radius values that minimize the deviation between the comprehensive relational degree of the classification object and the critical value.

The rank-reversal problem in gray relational models could drive decision-makers away from using this method. The results of this study demonstrate that the proposed gray relational model based on information diffusion and virtual-ideal sequencing can effectively avoid rank reversal. The method is applied to classify 31 brownfield redevelopment projects based on available interval gray information. The case analysis verifies the rationality and feasibility of the model.

This study proposes a robust method for ideal point choice when the decision information is limited or dynamic. This method can reduce the influence of ideal sequence changes in gray relational models on decision-making results considerably better than other approaches.

This paper aims to study the effect of new regulatory requirements on disclosure through a longitudinal study. The empirical setting is offered by the risk reporting in the management commentaries of Italian listed companies. In this setting there is an evolution from a voluntary disclosure environment toward a regulated one, with the gradual introduction of new reporting requirements.

This paper uses the content analysis method to investigate the narrative risk disclosure. Non‐parametric statistics are used to test the hypotheses.

It is found that even when new mandatory disclosure is introduced, managers exploit discretion and do not change their disclosure policy, continuing to withhold relevant information to external users. Before and after the introduction of new regulation, managers' behaviour appears in line with self‐interest to protect themselves from litigation and competitive costs, as well as from possible decreases in the firm's value.

The study provides a longitudinal study, covering changes from a voluntary disclosure environment to a regulated one. The paper provides evidence that the management incentives do not change in the presence of new disclosure regulation.

This paper, for the first time, classifies narrative information into complementary and supplementary. For the purpose of the paper, complementary narrative information is defined as that information which refers to specific numbers presented in the statutory accounts (profit and loss and balance sheet). Non‐specific narrative information is classified as supplementary. Having made the distinction and provided reasons for such a distinction the study investigates the extent of complementary narrative commentaries on numbers from the statutory accounts. The study also investigates which company‐specific characteristics are associated with the extent of complementary narrative commentaries. An index consisting of 46 items which must be reported in the statutory accounts was used to measure the extent of complementary narrative commentaries in the annual reports of 170 listed UK companies. The findings suggest that, on average, the companies comment on 39.9% of the numbers appearing in their statutory accounts. Using the Ordinary Least Squares (OLS) regression model, the results indicate that company size, gearing, profitability, liquidity ratio, the presence of exceptional items, and substantial institutional investment are significantly associated with the extent of complementary narrative commentaries. However, auditor type, directors’ share ownership, and the proportion of non‐executive directors are not significantly associated with the extent of complementary narrative commentaries. The research has important implications for accounting regulators, users of annual reports and future research into the usefulness narrative information provided in annual reports.

On his first full day in office, President Obama issued a Memorandum on Transparency and Open Government (White House, 2009a) committing his Administration to create an unprecedented level of openness in government and indicating his belief that government should be transparent, participatory, and collaborative. This chapter examines the Obama Administration through June 2010, and looks at how closely the administration is hewing to its promises, in the context of the legacy of secrecy it inherited.

This research has been conducted with a view to creating a framework to integrate risk management based on building information modeling (BIM) information.

In this research, all the information related to the construction of a residential project including 3D, 4D and 5D BIM models and the execution and control phases information was collected, and the risk list was determined for each activity accordingly.

The present study has suggested a framework for risk management in order to optimize project changes.

The lack of integration between 3D, 4D and 5D modeling besides execution information is a fundamental problem in many projects. The gap between these two groups of information will lead to improper management and late decisions, eventually imposing unforeseen delays and cost overruns. Risk management by the means of adopting a new approach has been addressed in recent studies using new methods, such as BIM and its associated technologies, some of which were mentioned in the review of theoretical literature in this research.

The purpose of this paper is to analyse the environmental scanning practices and information sources used by large companies as well as by small and medium‐sized enterprises (SMEs), the latter being relatively absent from scientific scrutiny. In doing so, it endeavours to contribute to a better understanding of the scanning and information‐gathering behaviour of SMEs, in order to develop measures to overcome their potential disadvantages in this respect.

Data were obtained from 165 Portuguese firms. Respondents were required to evaluate their use of 11 different environmental scanning practices and 12 information sources. For data analysis, the variables were classified using principal component analysis. Subsequently, the retained components and variables underwent a one‐way variance analysis.

Results indicate that smaller firms do not scan as broadly and as frequently as their larger counterparts. Although external information sources are used equally by larger and smaller enterprises, in general there is also a positive relationship between the exploitation of information sources and firm size.

Findings are taken from the Portuguese context, with its own idiosyncratic economic structure and climate. Generalisations should therefore be made with caution.

As the “size effect” influences the propensity for environmental scanning, SMEs are urged to adopt inter‐firm strategies in order to achieve a critical mass. The importance of building scanning and information networks among SMEs must be highlighted.

Research on environmental scanning in SMEs and comparative studies of the firm size effect have been relatively scarce. The findings reveal that firm size matters, insofar as the use of different scanning practices and information sources mostly augments with increasing firm size.