*2.2. Defining and Measuring Reporting Quality*

The benefits of having a meaningful and measurable concept of "quality" are important to a wide range of disciplines, including computer science, social science, education, and accounting disclosure. The information might be described as "quality" if it is fit for the purpose intended. As we saw in the section above, the purpose intended for financial reporting and the accompanying non-financial reporting is primarily focused on meeting the needs of shareholders and financial market participants. We have also discussed how appropriate and useful information for these stakeholders cannot be assumed to be so for other stakeholders. However, the UK corporate governance code and the disclosure rules do state that the needs of these other stakeholders should be addressed to a degree, though perhaps not necessarily to a level that might be seen as sufficient or meaningful. In designing our ACD index, we have used both the Bribery Act and major non-governmental sources (UN, EITI, GRI) as guidance for what might be reasonable content for a company to address on this topic for it to be seen as meeting these broader information requirements in its annual report.

Another angle on quality in the information economics and accounting literature is the practical need for the provision of information to be collated at a reasonable cost, in a timely manner, and to be understandable. The IASB Conceptual Framework (2018, Section 2) puts these in a financial reporting context, and IASB (2022), a draft standard for sustainability financial disclosure, extends this to sustainability-related financial disclosures and, by implication, any other disclosure that would support such disclosure. Whilst the latter is beyond our sample period, it provides the clearest insight into the continuing mindset of corporate reporting.

Reporting quality has been examined by prior research across numerous dimensions, including the characteristics of information disclosed, the volume disclosed, the themes or topics covered, the type of information, and the language used [30] summarizes these. Most non-financial corporate reporting research approaches have used that draw on one or two of these dimensions to measure the "quality" of corporate sustainability, or subtheme, reporting in most cases. To assess quality (e.g., the range of themes addressed, measures of disclosure, time period, and credibility of disclosure), we would require a very comprehensive (compound) descriptive model with the added complexity of needing to weight each factor for relative importance—yet another factor that may vary by user group. Hence, quality in the field of CSR reporting is no less a complex concept being multifaceted and subjective [43,45–47,51–53].

#### *2.3. Credibility of Assessing Reporting Disclosure and Its Quality*

The difficulty of measuring the extent of corporate disclosure is one of the most important limitations encountered in disclosure studies [54]. The volumetric approach, which counts words, sentences, or pages in the report, indicates the importance of the reported items/themes to readers and, therefore, can be used as a measure of reporting quality [31]. Additionally, the unweighted disclosure indices, which have been used to assess corporate disclosure quantity under the assumption that all disclosed items/themes are equally important, have also been criticized. As a proxy of reporting quality, these approaches focus only on how much information is provided. Additionally, meaning-based or interpretive approaches, such as weighted thematic content analysis, have also been used as a measure to evaluate the quality of disclosure [33,52]. Thus, this has led to generally quantitative evaluations of what is disclosed and how it is disclosed by analyzing the content of the corporate report in terms of specific criteria and then weighting/scoring the criteria according to their perceived relative importance (e.g., [32,46,55,56]). Despite these concerns, weighted disclosure indices have been criticized as reflecting a bias towards a specific group of users [31], though the decision to use unweighted indices is no less a decision. Such studies apply content analysis to numeric but mostly non-numeric information [57]. By applying weighted thematic content analysis, these studies seek to evaluate the content of specific disclosed topics rather than simply count them [52]. Using content analysis, [50] examined corporate disclosure to assess the comparative positions and trends in corporate reporting (see, also, [30,44,47,58]).

It has often been considered that the amount of disclosure (i.e., number of disclosed items, pages, or words) is a sufficient measure of the quality of disclosure, despite the fact that many empirical studies have shown that the quality and quantity of disclosure are distinct from each other and that quality refers to the precision or accuracy of the disclosure (e.g., [18,29,30,32,59]). As a result, several studies have examined who is reporting, what is reported, how is reported, and how much is reported in the corporate social responsibility (CSR) reporting literature (see [30,42,60–63]). In addition, the narrative and graphical disclosures within UK annual reports (ARs) have offered a foundation for evaluating not just the quantity of disclosure but also the readability and reporting quality of these corporate documents [51,64]. Indeed, a report's breadth and visual format have established a framework for gauging the quality of CSR reporting [30].

Prior corporate non-financial reporting literature has focused on the number or type of disclosed items made in assessing the quality of CSR reports [33,38,44]. Many of these studies employ content analysis as a primary tool to analyze the content of these CSR reports (see, for example, [19,59,65–69]). This approach may include a number of words, sentences, phrases, pages, or items as well as assessing the readability or the proportional disclosure of good versus negative news [30]. To arrive at statistical conclusions on the quality of CSR reporting, these studies have often relied on content analysis to turn, usually, textual matter into quantitative metrics (e.g., [18,55,70,71]). A disclosure measure that seeks to measure reporting quality may provide a better result than a disclosure measure that just measures its quantity (see [19,30,31,47]).

Content analysis requires collecting relevant information by codifying and classifying both qualitative and quantitative information into pre-determined categories and sub-categories [27,30]. In our context, this is to identify trends and patterns in corporate reporting. Careful designing of the coding structure is paramount to avoid inaccurate results (i.e., the validity of inferences derived from data is determined by the integrity of the content analysis and the validity of the data collected, see [33]). Assessing reporting quality can also be incomplete if the scoring systems are based upon merely disclosure or non-disclosure (a 1/0 scale) since this would limit measuring and then assessing the themes covered, completeness, relevance, reliability, and other important features of corporate disclosure. Further, [57] asserts that the reliability of assessing reporting quality is dependent on shared meanings, which create the same referents independently of the coder (see [44]). Based on Krippendorff's [57] analysis, the reliability of measuring reporting quality is classified into three dimensions: (1) stability (the consistency exhibited over time by the same coder when analyzing the same content), (2) reproducibility (the degree to which different coders produce the same results when analyzing the same content), and (3) accuracy (whether the text is classified according to a standard or norm [57]. Finally, [53] emphasize that the scoring system is value loaded and depends on the prior knowledge of coders/assessors of corporate reporting. They also add that a training workshop of approximately 20 corporate reports (e.g., pilot study) is necessary to achieve accurate scores of reporting quality.

#### *2.4. Measures of Assessing Reporting Quality*

As the main objective of this research is to investigate the quantity and quality of corporate ACD, it is essential to review the common disclosure measures developed and used in the academic literature (e.g., [19,30,32,34,43,48,59,66,68,69,72]). As stated above, these measures are designed to scrutinize the non-financial, mostly textual, elements of

corporate reporting, usually analyzing and comparing the annual report of companies. Such assessment of reporting quality has primarily been conducted based on quantity or a checklist of themes/items or topics that seek to capture the volume and variety of corporate disclosure features. Much of the corporate disclosure literature has assessed corporate disclosure based on the volume of disclosure and the number of disclosed themes. There can be no quality without a level of quantity, but it is clear that a higher volume does not necessarily mean more meaningful content.

Studies have adopted the traditional approaches of content analysis (i.e., volumetric and interpretative) and scoring methods (i.e., unweighted and weighted disclosure index) (see, [27,30,31,34,35,66,68,73]) to the corporate reporting context. For instance, Michelon et al. (2015) assessed the quality of corporate disclosure using the quality model adopted by [35] to capture the quantity of information disclosed and the 'richness' of its content. This richness captures many quantitative and qualitative features in a specific type of disclosure. A further instance would be [19] assessing the quality of corporate disclosure using a scoring method with a minimum score of zero and a maximum of four, with zero for no disclosure and four being used for "truly extraordinary disclosures" (page 204). More recently, [31] developed a multidimensional quality model (MQM) to assess the quality of environmental disclosure and capture a broader set of assumed quality proxies (for example, high-level content, credibility, and communication of environmental disclosure).

We consider these metrics developed in the relatively well-researched reporting subcategory of environmental reporting and seek to apply them to ACD, a sub-category that has attracted much less research interest and a reporting segment where volume is much reduced compared to environmental issues. We categorize the different approaches to the assessment of corporate reporting into two groups: unidimensional measures and multidimensional measures. These are presented below in Section 3.3.

To conclude, previous academic literature has paid considerable attention to corporate sustainability and performance practices (e.g., [18,30,34,37,74,75]). Within sustainability reporting analysis, a few academic studies have addressed several ACD matters (e.g., [1,2,65,66,68,69,72,76]). These studies assessed both the quantity and quality of ACD practices using self-developed indexes and disclosure checklists based on sustainability reporting guidelines such as the Global Reporting Initiative (GRI) and Transparency International (TI) (see, [6,66,77], for example). Further research is needed to assess the response of companies to the pressure of regulation and international guidance mandating or encouraging them to disclose their anti-corruption practices. Hence, the current research aims to reduce this gap by addressing the research questions stated above. We develop a quality disclosure index and then, by applying metrics from the environmental accounting field to ACD reporting, seek to assess the merit of these metrics in this field firstly and, secondly, seek to use them to assess the impact of the UK Bribery Act 2010, on the quantity and quality of ACD practices of the large UK domiciled extractive companies.

#### **3. Research Methodology**

#### *3.1. Research Sample*

Our sample comprises the extractive firms listed in the UK FTSE 100 from 2003 to 2019. The FTSE 100 is one of the globe's best-known stock market indices and includes the largest 100 firms with a main listing on the London Stock Exchange. The UK is a suitable country for such an analysis as it has relatively high levels of CSR reporting practices [73]. As stated above, the extractive industry is a suitable purposive sample as it is one of several industries where the potential for corruption is seen to be high and, therefore, would be an appropriate subject for companies to address. We collected annual reports for the companies below for the time in the sample period that they were in the FTSE 100, an index re-assessed every three months. The sample period covers a good number of years pre and post the introduction of the UK Bribery Act. This sample included 10 companies, detailed in the table below, though not all firms could be included for all years of the study due to changes of domicile and for periods when they were not in the FTSE 100 index. Glencore is

deemed to be a continuation of Xstrata, a predecessor company. The sample is presented in Table 1.


**Table 1.** Companies included in the study.

Notes: Market Cap Market Capitalisation; B Billion.
