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Graphs are powerful tools which affect a reader’s impression and decision making. However, graphs in annual reports have a long tradition of being designed in order to give a more favourable impression of the company’s performance. The purpose of this paper is to add to the understanding of how large listed companies in Europe choose to use and misuse graphical representation.

This comprehensive study investigates annual reports of the top 50 European companies listed in the fortune 500 index. Company reports are analysed over a period of seven years resulting in 4,683 graphs. The authors investigate the development of the three major areas of impression management – selectivity, graphical measurement distortion and presentational enhancement – individually by company as well as collectively for the entire sample.

The main findings are that topics displayed, and how they are presented, significantly change over time and that graphs are much more likely to exaggerate positive trends than to understate them. Additionally, it can be found that longer time sequences (greater than five years) almost exclusively depict favourable trends (86 per cent) and graphical measurement distortions are applied on purpose for both key financial variables (KFV) as well as for non-KFV (around 30 per cent in all years).

The sample for this study are the biggest 50 companies in Europe. It is not clear, if these companies are a representative sample for all publicly traded companies in Europe. Further research is needed regarding small and medium size companies.

The findings show that companies primarily produce graphs in order to influence the perception of their stakeholders rather than to display the topics in accordance with the “true and fair view” principle that is requested by the IASB. However, standard setters like the IASB or the FASB have not yet released any particular information on how to use graphs correctly and avoid misleading information. This study should provide a solid base for further discussions in this regard as companies still use graphs to give a favourable impression of the company and deliberately misuse them in order to achieve this aim.

This study contributes to the research field of impression management by answering the quest for more longitudinal studies and offers an extended focus while examining not only KFV but all variables depicted in annual reports.

The Equal Pay Act 1970 (which came into operation on 29 December 1975) provides for an “equality clause” to be written into all contracts of employment. S.1(2) (a) of the 1970 Act (which has been amended by the Sex Discrimination Act 1975) provides:

Data visualizations in some form or another have served as decision-support tools for many centuries. In conjunction with advancements in information technology, data visualizations have become more accessible and more efficient to generate. In fact, virtually all enterprise resource planning and human resource (HR) information system vendors offer off-the-shelf data visualizations as part of decision-support dashboards as well as stand-alone images and displays for reporting. Plus, advances in programing languages and software such as Tableau, Microsoft Power BI, R, and Python have expanded the possibilities of fully customized graphics. Despite the proliferation of data visualization, relatively little is known about how to design data visualizations for displaying different types of HR data to different user groups, for different purposes, and with the overarching goal of improving the ways in which users comprehend and interpret data visualizations for decision-making purposes. To understand the state of science and practice as they relate to HR data visualizations and data visualizations in general, we review the literature on data visualizations across disciplines and offer an organizing framework that emphasizes the roles data visualization characteristics (e.g., display type, features), user characteristics (e.g., experience, individual differences), tasks, and objectives (e.g., compare values) play in user comprehension, interpretation, and decision-making. Finally, we close by proposing future directions for science and practice.

Analyses of organizational behavior traditionally use methods based on linear statistics. However, aspects of complex system behavior, such as market share performance, may be better modeled and understood using graphical approaches. These approaches can be used to clarify the relationships between variables found in psychological research and can provide a complement to traditional research representations that has particular value for the practitioner in organizations. This paper demonstrates how three‐dimensional graphs can be valuable tools for understanding, explaining, and communicating research results by using longitudinal performance data from the automotive industry as an illustration.

This study examines whether manipulation in attributes of corporate narrative disclosures and the use of graphical representations can bias non-professional investors' judgment towards firms' future performance, in an emerging market context.

The authors conduct three different experiments with a 2 × 2 between-subjects design, using accounting and finance senior undergraduate students to proxy for the non-professional investors.

Results show that simple (more readable) disclosures improve non-professional investors' judgment towards firms' future performance. In addition, it is found that non-professional investors are prone to a recency effect from the intentional ordering of narrative information, when using complex (less readable) narratives. However, no primacy effect is found, when using simple (more readable) disclosures. The results further provide evidence that the inclusion of graphical representations, along with the manipulated narrative disclosures, can moderate the recency effect of information order, when using less readable and complex narrative disclosures.

The results reveal that although the content of corporate disclosures can be objective, neutral and relevant, manipulation in textual features and the use of graphical presentations, can interact to impact how non-professional investors perceive and process the disclosed information. This study provides an Egyptian evidence regarding this issue, as the majority of prior studies concentrate on developed capital markets. In addition, it contributes to prior studies evaluating the appropriateness of the Belief Adjustment Model predictions about the effect of textual presentation order on decision-making, by providing evidence from an emerging market.

Results attempt to increase the awareness of investors and encourage them to use multiple sources of information to avoid the probable bias that can result from management's manipulation of narratives. In addition, the study could be of interest to regulators and standard-setters, where the results reveal the need for guidelines and regulations to guide the disclosure of narrative information and the use of graphical information in corporate reports.

To the best of the authors' knowledge, this is the first study to examine the effect of two impression management strategies in narrative disclosures (readability and information order), along with the use of graphical representations, on non-professional investors' judgment in an emerging market, like Egypt.

A distinction must be drawn between a dismissal on the one hand, and on the other a repudiation of a contract of employment as a result of a breach of a fundamental term of that contract. When such a repudiation has been accepted by the innocent party then a termination of employment takes place. Such termination does not constitute dismissal (see London v. James Laidlaw & Sons Ltd (1974) IRLR 136 and Gannon v. J. C. Firth (1976) IRLR 415 EAT).

This study surveyed the perceptions of users and preparers of Corporate Annual Reports (CAR) regarding graphical information (GI) disclosed in the CAR. Questionnaires were used and sent to (i) 120 selected users, and (ii) 489 CFO of non‐financial companies listed on the main board of Bursa Malaysia for the year 2002. It was found that users ranked GI as second after financial statements. The users of CAR utilized GI to evaluate company’s performance overtime, make comparison with other companies and assist in making investment decision. The KFV graphs preferred are sales, earnings, EPS, share price performance, and cash flow graphs. More than fifty percent of users believed that graphs disclosed in CAR are sufficient. The survey also revealed that 75.4 percent of Malaysian companies included graphs in their CAR. They disclosed sales, earning per share, shareholders fund, earnings, and net tangible assets. These variables were presented in bar, line, pie, and column. However, the most popular type of graph was bar. The perceived major users of GI are mainly financial analysts, potential investors and financial investors. The preparers indicated that the main reasons that hinder companies from disclosing GI in CAR are due to the sufficiency of the existing numerical and narrative disclosure, and inexistence of formal guideline regarding the construction of graphs. The findings also revealed that users were more aware of fundamental principle of graphs construction than the preparers based on the mean scores by both group on the criterion of good construction of graph. Overall, the survey evidenced that graphs are appreciated by both parties as an alternative way of communicating information in a more effective manner.

This chapter enquires into the contribution of two British writers, Herbert Somerton Foxwell and Henry Riverdale Grenfell, who elaborated upon the hints provided by Jevons towards a description of long waves in the oscillations of prices. Writing two decades after Jevons, they witnessed the era of high prices turning into the great depression of the last quarter of the nineteenth century, the causes of which they saw in the end of bimetallism. Not only did they take up Jevons’s specific explanation of the long fluctuations, but they also based their discussion upon graphical representation of data and incorporated in their treatment a specific trait (the superposition principle) of the ‘waves’ metaphor emphasized by the Manchester statisticians in the 1850s and 1860s. Their contribution is also interesting for their understanding of crises versus depressions at the time of the emergence of the interpretation of oscillations as a cycle, which they have only partially grasped – as distinct from the approach of later long wave theorists.

The construction industry produces voluminous quantitative data. Much of this data is created during the controls phase of projects and relates to cost, schedule, and administrative information. Recent storage and processing advances in computers as well as display capabilities afforded by computer graphics increase the opportunity to monitor projects fundamentally different from existing project control systems. However, changes in project control methods have been slow to evolve. The lack of a fundamental model of project control data representation contributes to the inadequate application and implementation of visual tools in project control methods. Difficulties associated with the graphical representation of data can be traced to the diversity of skills required in creating visual information displays. Owing to the reality that not all engineers/constructors possess these attributes in great strength, streamlining the process of how to best visualize data is important. Visual representations of data hold great potential for reducing communication difficulties fostered by industry fragmentation. However, without information structure, organization, and visual explanations, the massive amount of data available to project managers results in information overload. Therefore, improved information displays are needed to overcome the possibility of information overload with the capability of human perception. This paper discusses research to create a framework for visual representation of construction project data. Underlying visualization theory, the visual framework, and a detailed implementation are provided.

The latest financial crisis has stressed the need of understanding the world financial system as a network of interconnected institutions, where financial linkages play a fundamental role in the spread of systemic risks. In this paper we propose to enrich the topological perspective of network models with a more structured statistical framework, that of Bayesian Gaussian graphical models. From a statistical viewpoint, we propose a new class of hierarchical Bayesian graphical models that can split correlations between institutions into country specific and idiosyncratic ones, in a way that parallels the decomposition of returns in the well-known Capital Asset Pricing Model. From a financial economics viewpoint, we suggest a way to model systemic risk that can explicitly take into account frictions between different financial markets, particularly suited to study the ongoing banking union process in Europe. From a computational viewpoint, we develop a novel Markov chain Monte Carlo algorithm based on Bayes factor thresholding.