Search results

The integrated reporting framework seeks to connect a firm’s financial and non-financial performance in a single report by displaying how different forms of capital contribute to the firm’s value creation. Drawing on impression management and incremental information approaches, the purpose of this paper is to examine how the content and semantic properties of intellectual capital disclosure (ICD) found in integrated reports is associated with firms’ performance.

All reports by European listed firms from 2011 to 2016 available via the integrated reporting emerging practice examples database are analysed. Content analysis is used to assesses the quality of ICDs, whereas a regression analysis tests the variation in semantic properties of ICDs according to firms’ performance.

ICDs in integrated reports are mainly discursive, with a backward looking orientation and a limited focus on human capital. On average, more than half of each ICD is conveyed in a positive tone. As the optimistic tone in firms’ ICDs increases, so too does their non-financial performance measured in terms of environmental, social and governance aspects. This finding supports the incremental information approach.

This paper contributes to the current literature on ICDs by introducing new evidence on firms’ motivations for non-financial disclosures in integrated reports. By taking a more comprehensive theoretical approach, namely, testing both impression management and incremental information hypotheses, this research extends on prior studies which tested similar relationships in integrated reports but focussed only on the impression management hypothesis.

This paper aims to investigate the effect of voluntary non-financial reporting on the evaluation of audit risk from the auditors’ viewpoint in a post-crisis period. Furthermore, this paper analyses whether auditors perceive that voluntary non-financial reporting impacts audit risk differently for old clients as compared with new clients.

This study is conducted on a sample of Italian audit firms through a paper-based questionnaire. Both Big4 and non-Big4 audit firms have been included in the sample.

Results show that integrated reporting is perceived to be the most relevant reporting method and intellectual capital statement the least relevant. Surprisingly, empirical findings over the sample period show that auditors do not perceive statistically significant differences between old and new clients.

Auditors can identify opportunities to adapt their assessment model to include voluntary non-financial report information. Moreover, they can use different assessment models regarding the research variables in the case of new and old clients.

Empirical findings highlight the growing role of voluntary non-financial reporting in the auditors’ perception of their client’s audit risk. All the observed voluntary non-financial reporting forms, except for intellectual capital, are considered as relevant by auditors in the evaluation of their client’s audit risk when compared to an indifference point. In addition, findings reveal that female auditors perceive a reduced gap in the relevance between integrated reports and intellectual capital reports compared to their counterparts.

Voluntary non-financial reporting aims at fairly reporting a firm’s non-financial performance. In particular, integrated reporting (IR) displays in a single report the contribution of different forms of capital to the firm’s value creation. Drawing on both legitimacy and voluntary disclosure theory, the main purpose of this study is to examine the extent to which a company’s environmental, social, and governance (ESG) performance affects the content and semantic properties of intellectual capital disclosure (ICD) found in IRs.

To test theoretical hypotheses, content and tone analysis is used to assess the disclosure strategy associated with ICD, whereas a regression analysis tests the variation in semantic properties of ICD according to firms’ ESG performance. A total of 79 reports by European listed firms from 2011 to 2016 were downloaded via the Integrated Reporting Emerging Practice Examples Database and analyzed.

Results show that ESG performance contributing more to optimistic ICD tone is governance, although in mixed ways. Integrating vision and strategy positively contributes to ICD tone, whereas information on poor treatment of shareholders’ rights tends to be manipulated and associated with an optimistic tone of the ICD. Moreover, eco-efficient product innovation and healthy and safe job conditions play a positive role in enhancing optimistic ICD tone.

This chapter contributes to the current literature on voluntary disclosure by introducing new evidence on the disclosure strategy in IR. By analyzing the effect of the single dimensions of ESG performance on ICD tone, this study extends respectively ESG literature.

The issue investigated in this work is relative to the features of the information sub‐systems supporting specific university administrative processes (accountancy, personnel management, student services). This paper attempt: to develop a benchmarking model; and apply the suggested model to a group of Italian universities.

While the literature analysis has been useful to achieve the first goal, the empirical methodology of case studies has been employed for both the objectives. It means that there has been a full commitment of the involved universities also in the theoretical phase of the work.

Two types of specific results are expected through the application of the suggested benchmarking model. The first is the pertinent position of each university in respect with some observed features of the information sub‐systems. The second is the identification of possible trends that are widespread within the selected universities.

Generalization of the benchmarking trends is not possible, because trends arise from a limited group of universities.

The universities involved in the project have discovered the importance of benchmarking as a means of improving their processes and systems.

This paper represents a first attempt at developing a model to compare the condition of the administrative information systems in a selected group of Italian universities.

This study aims to bring awareness to the developing of fault detection systems using the data collected from sensor devices/physical devices of various systems for predictive maintenance. Opportunities and challenges in developing anomaly detection algorithms for predictive maintenance and unexplored areas in this context are also discussed.

For conducting a systematic review on the state-of-the-art algorithms in fault detection for predictive maintenance, review papers from the years 2017–2021 available in the Scopus database were selected. A total of 93 papers were chosen. They are classified under electrical and electronics, civil and constructions, automobile, production and mechanical. In addition to this, the paper provides a detailed discussion of various fault-detection algorithms that can be categorised under supervised, semi-supervised, unsupervised learning and traditional statistical method along with an analysis of various forms of anomalies prevalent across different sectors of industry.

Based on the literature reviewed, seven propositions with a focus on the following areas are presented: need for a uniform framework while scaling the number of sensors; the need for identification of erroneous parameters; why there is a need for new algorithms based on unsupervised and semi-supervised learning; the importance of ensemble learning and data fusion algorithms; the necessity of automatic fault diagnostic systems; concerns about multiple fault detection; and cost-effective fault detection. These propositions shed light on the unsolved issues of predictive maintenance using fault detection algorithms. A novel architecture based on the methodologies and propositions gives more clarity for the reader to further explore in this area.

Papers for this study were selected from the Scopus database for predictive maintenance in the field of fault detection. Review papers published in this area deal only with methods used to detect anomalies, whereas this paper attempts to establish a link between different industrial domains and the methods used in each industry that uses fault detection for predictive maintenance.