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When improving business processes, process analysts can use data-driven methods, such as process mining, to identify improvement opportunities. However, despite being supported by data, process analysts decide which changes to implement. Analysts often use process visualisations to assess and determine which changes to pursue. This paper helps explore how process mining visualisations can aid process analysts in their work to identify, prioritise and communicate business process improvement opportunities.

The study follows the design science methodology to create and evaluate an artefact for visualising identified improvement opportunities (IRVIN).

A set of principles to facilitate the visualisation of process mining outputs for analysts to work with improvement opportunities was suggested. Particularly, insights into identifying, prioritising and communicating process improvement opportunities from visual representation are outlined.

Prior work focuses on visualisation from the perspectives – among others – of process exploration, process comparison and performance analysis. This study, however, considers process mining visualisation that aids in analysing process improvement opportunities.

We highlight two mechanisms of limited attention for expert information intermediaries, i.e., analysts, and the effects of such limited attention on the market price discovery process. We approach analysts' limited attention from the perspective of day-to-day arrival of information and processing of tasks. We examine the attention-limiting role of competing tasks (number of earnings announcements and forecasts for portfolio firms) and distracting events (number of earnings announcements for non-portfolio firms) in analysts' forecast accuracy and the effects of such, on the subsequent price discovery process. Our results show that competing tasks worsen analysts' forecast accuracy, and competing task induced limited attention delays the market price adjustment process. On the other hand, distracting events can improve analysts' forecast accuracy and accelerate market price adjustments when such events relate to analysts' portfolio firms through industry memberships.

The article reveals a need for greater understanding and use of corporate intellectual capital (IC) information within two connected capital market areas. Firstly with regard to the conceptualisation and valuation process these capital market agents (analysts and fund managers) conduct. Secondly, within the capital market agents' own value creation chain. The concept of the value creation chain is combined with an analysis of the barriers faced by capital market agents represented by fund managers and analysts. These barriers are proposed to comprise knowledge, uncertainty, ownership and management problems. In addition, cultural pressures within analyst and fund manager communities are viewed as contributors to information barriers. Such problems are exacerbated by additional market induced problems of severe time constraints and conflicts of interest.

The study proposes competence models for the roles of process owners, process analysts and industrial engineers based on qualitative research.

The research methodology is a combination of a questionnaire survey and interviewing in Czech companies, which develop the process approach. The proposed competence models can be utilized during business process management (BPM) implementation while appointing process owners, analysts and industrial engineers and their further development.

This paper emphasizes the role of human factor and presents research results concerning most important BPM roles and their competencies.

There is lack of research (a research gap) in the field of BPM roles, what they do and what they should do.

A system of competence models is thus a tool for human resource management and should increase the success rate of BPM projects. Another possible utilization is in higher education in business administration.

Another possible utilization is in higher education in business administration.

It proposes competence models for the roles of process owners, process analysts and industrial engineers based on qualitative research.

Discusses the qualitative analysis of a case study of analyst‐client communications using grounded theory and themed analyses. Describes in detail the interaction that took place between an analyst and a client in a public sector agency in Tasmania, Australia. Uses a theatrical metaphor to give a representation that encompasses chronological and contextual aspects, providing an immediacy that enables the reader to appreciate how the interaction developed over time. Using concepts derived from the use of grounded theory techniques, demonstrates how these concepts and themes operated in this particular case. Concludes with a general discussion of themes and contextual influences as they occur in the case of the student assistance scheme and other cases studied by the author.

In the backdrop of emerging market setting of India, this study aims to attempt to identify how Institutional investors use sell side analyst outputs for their decision-making processes in light of inherent biases in their forecasts and recommendations. The study also conceptualizes the role of internal buy side teams in the process and try to figure out the key attributes and services provided by sell side analysts, which provide maximum value to the investors.

The study is centered upon in-depth semi-structured interviews of ten institutional investors from top Indian asset management companies covering a wide range of topics tied back to theoretical explanations. The data collected was transcribed, coded and analyzed using content analysis to ensure a systematic synthesis of point of view.

The findings show that internal analyst teams of institutional investors play a dominant role in terms of validation of sell side analysts’ outputs (given the inherent biases in sell side analyst forecasts). Further, the engagement of sell side analysts by the investors are determined not only through profitable recommendations but also on the basis of soundness of the investment rationale along with other services provided. Finally, this study puts into perspective, the critical role of analyst industry knowledge and access to company management (as opposed to analyst pedigree and forecast accuracy) for institutional investors decision-making.

The findings of the paper have profound implications for various stakeholders such as companies, sell side analysts, policy makers, researchers and students of finance in terms of detailed understanding of investment processes of institutional investors in the context of emerging markets like India, which have a different legal and regulatory set-up compared to developed markets. The authors also provide a critical perspective through an intriguing paradox that exists between finance theory and its relevance for actual practitioners.

To the best of the authors’ knowledge, this is the first study in India which look inside the “black box” of institutional investors and their decision-making process, especially with respect to how they use sell side outputs.

The purpose of this paper is to systematise the current state of research on the association between companies’ corporate social responsibility (CSR) engagement and financial analysts’ company assessment. Additionally, it aims to identify fruitful directions for future research that contribute to a further exploration of the link between CSR and financial analysts.

This study reviews and synthesises existing research on CSR and financial analysts. Based on the research question, “What is the relationship between CSR engagement and financial analysts’ metrics?,” the authors conduct a systematic literature review. The authors search three major databases and use an extensive search term to ensure exhaustive coverage of the field. The paper then systemises the current state of research and identifies knowledge gaps and potential directions for future research.

The review of existing research shows that several studies confirm a positive link between CSR performance and analyst coverage, suggesting that external monitoring through analysts incentivises companies to enhance their CSR engagement. Further, results indicate that a company’s involvement in “sin” industries is linked to lower analyst coverage. Besides, a higher level of CSR disclosure is positively associated with analyst forecast accuracy, thus indicating that the provision of CSR-related information is linked to an enhanced information environment. High levels of CSR performance are associated with more positive recommendations from analysts. However, recent surveys and interview studies on analysts’ perceptions of CSR fail to uniformly support an increasing interest in CSR.

For a better understanding of the link between CSR engagement and financial analysts, two fruitful directions for future research are observed. First, future research designs should clearly differentiate between CSR disclosure and CSR performance and take account of interdependencies between them. Second, studies should address behavioural insights into how analysts process information and the influence of individual analyst characteristics on the link between CSR engagement and an analyst’s assessment of a company.

This study is the first to review the literature on the relationship between CSR and financial analysts. The association between CSR and financial analysts is particularly interesting given the pivotal role financial analysts play as information intermediaries in financial markets. This study delivers an in-depth understanding of existing studies and their theoretical underpinnings. Based on the existing literature, this paper develops innovative directions for future research.

Financial analysts' forecasts serve as a proxy for market earnings expectations, and research provides mixed evidence of the relation between financial analysts' expertise and forecast accuracy. The judgment and decision-making (J/DM) literature suggests that those with more expertise will not perform better when tasks exhibit either extremely high or extremely low complexity. Expertise is expected to contribute to superior performance for tasks between these two extremes. Using archival data, this research examines the effect of analysts' expertise on forecasting performance by taking into consideration the forecasting task's complexity. Results indicate that expertise is not an explanatory factor for forecast accuracy when the forecasting task's complexity is extremely high or low. However, when task complexity falls between these two extremes, expertise is a significant explanatory variable of forecast accuracy. Both results are consistent with our expectations.

Both the SEC (Securities and Exchange Commission) and the popular press have routinely criticized firms for the complexity of their financial disclosures. This study aims to investigate how financial analysts respond to the tone complexity of firm disclosures.

Using approximately 20,000 earnings conference call transcripts of S&P 1,500 firms between 2005 and 2015, the authors first calculate the abnormal negative tone, the measure of tone complexity; then use such tone measure in econometric models to examine analyst forecast behavior. The authors also test the robustness of the results under different model specifications, tone word lists and alternative tone measure calculations.

Consistent with the notion that analysts respond to the information demand from investors and incur more costs and effort to analyze firm disclosure when the tone is more complex, the authors find that higher tone complexity is positively and significantly associated with more analyst following, longer report duration, more forecast revisions, larger forecast error and larger forecast dispersion. In addition, the authors find that tone complexity has a long-term impact on analyst following but has a limited long-term impact on analyst report duration, analyst revision, forecast error and dispersion.

This study complements existing literature by highlighting the information role of financial analysts and by providing evidence that analysts incorporate the management tone disclosed during conference calls to adjust their forecasting behaviors. The results can be used by policymakers as evidence and support for further improving firm communication from a new dimension of disclosure tone.

The current paper aims to understand whether fair value accounting (FVA) affects analysts’ loan approval decisions and default risk judgments.

This study focusses on three issues: unrealized gain or loss resulting from FV measurement recognized in other comprehensive income (OCI), recognition of assets at FV or historical cost and the disclosure or non-disclosure of the FV of collateral assets. It uses an experiment carried out with a sample of 29 CFA analysts.

The results show that all three issues have a significant effect on analysts’ judgment and decision-making in processing FV estimates.

The paper extends knowledge on how financial analysts perceive FV estimates and disclosure and may help the accounting standard boards assess the challenges facing analysts when they apply professional judgments in interpreting FV measurements and disclosures. Moreover, it offers fresh views to the debate on the decision usefulness of FVA, particularly relevant in the post-implementation review of IFRS 13.