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Environmental, social and governance (ESG) factors have become increasingly important in investment decisions, leading to a surge in ESG investing and the rise of sustainable investment assets. Nevertheless, challenges in ESG disclosure, such as quantifying unstructured data, lack of guidelines and comparability, rampantly exist. ESG rating agencies play a crucial role in assessing corporate ESG performance, but concerns over their credibility and reliability persist. To address these issues, researchers are increasingly utilizing machine learning (ML) tools to enhance ESG reporting and evaluation. By leveraging ML, accounting practitioners and researchers gain deeper insights into the relationship between ESG practices and financial performance, offering a more data-driven understanding of ESG impacts on business communities.

The authors review the current research on ESG disclosure and ESG performance disagreement, followed by the review of current ESG research with ML tools in three areas: connecting ML with ESG disclosures, integrating ML with ESG rating disagreement and employing ML with ESG in other settings. By comparing different research's ML applications in ESG research, the authors conclude the positive and negative sides of those research studies.

The practice of ESG reporting and assurance is on the rise, but still in its technical infancy. ML methods offer advantages over traditional approaches in accounting, efficiently handling large, unstructured data and capturing complex patterns, contributing to their superiority. ML methods excel in prediction accuracy, making them ideal for tasks like fraud detection and financial forecasting. Their adaptability and feature interaction capabilities make them well-suited for addressing diverse and evolving accounting problems, surpassing traditional methods in accuracy and insight.

The authors broadly review the accounting research with the ML method in ESG-related issues. By emphasizing the advantages of ML compared to traditional methods, the authors offer suggestions for future research in ML applications in ESG-related fields.

Jumpstart Our Business Startups Act 2012 (the JOBS Act) was passed in 2012. JOBS Act enables emerging growth companies (EGCs) to go public without being subject to the full vigorous range of regulations applicable to publicly traded companies. The purpose of this paper is to study financial performance, Tobin’s Q-ratio and value relevance of EGCs.

The sample includes 620 IPOs during the period from April 5, 2009 to April 5, 2015. The analyses use firm-quarter observations.

The results show that EGCs have both lower financial performance, and a lower Tobin’s Q-ratio compared to the financial performance and Tobin’s Q-ratio of non-EGCs. Moreover, the value relevance of accounting information for EGCs is lower than the value relevance of accounting information for non-EGCs.

This study contributes to the accounting regulation literature by documenting the inferior market performance and financial information quality of EGCs, i.e., the unintended consequences of the JOBS Act.

The purpose of this study is to examine the impact of goodwill impairment losses on bond credit ratings.

The authors use regression analysis to examine the relationship between goodwill impairment losses and bond credit ratings.

The empirical results show a negative relationship between the amount of goodwill impairment losses and bond credit ratings, suggesting that firms with goodwill impairment losses receive lower credit ratings. The authors perform various additional tests, including subsamples in good or bad market time, changes analysis, first time goodwill impairment firms vs subsequent impairment and the two-stage least squares regression analysis to address potential endogeneity issues. The main results persist.

This paper links and contributes to two streams of literature: goodwill impairment in accounting literature and bond credit ratings in finance literature. Whether a firm’s goodwill impairment losses affect the firm’s bond credit rating remains an interesting question that has not been examined previously. To the best of the authors’ knowledge, this is the first study that directly examines the relationship between goodwill impairment losses and bond ratings at the firm level.

The purpose of this paper is to examine the impact of career concerns on CEOs’ use of expectations management to meet or beat analysts’ quarterly earnings forecasts. The authors posit that early career-stage CEOs are less (more) likely to use expectations management than are late career-stage CEOs if the market views expectations management as an opportunistic strategy (efficient process) due to reputational capital concerns.

The authors obtain data for CEO career stages and CEO compensation from ExecuComp, analyst earnings forecasts from the detailed I/B/E/S database, financial statement data from quarterly Compustat and stock returns from the daily CRSP database over the period 1992–2013.

The results are consistent with the opportunistic hypothesis and early-stage CEOs seeking to build reputational capital by avoiding the perception of engaging in an inefficient managerial strategy. The authors find robust evidence that late career-stage CEOs are more likely to engage in expectations management than early career-stage CEOs. Furthermore, the authors show that late career-stage CEOs tend to employ expectations management to boost the value of their equity-based compensation.

The findings have important implications because the authors document a different implication of the “horizon problem” related to CEOs’ opportunistic forecasting behavior and the manipulation of analysts’ forecasts for CEOs who are approaching retirement.

The results have practical implications for analysts who provide earnings forecasts for firms whose CEOs are in early or late career stages and for investors who use such analysts’ forecasts in firm valuation models.

The authors contribute to the literature on expectations management by documenting how reputational incentives of CEOs affect the likelihood that managers engage in expectations management. The authors show that an important managerial incentive to engage in expectations management is CEO career concerns. Furthermore, the authors show that CEOs who are in early stages of their careers choose not to engage in expectations management due to the market’s perceived degree of opportunism pertaining to this strategy.

The author discusses the paper by Ordyna (2020) and suggests a few areas for improvement. First, the author could think more about the financing scheme of the acquisition including hybrid debt securities. Second, the author could consider forecast reputation, the timing and frequency of earnings guidance. Third, the author may consider the difference-in-differences research design and identification strategy. Other model designs, robustness checks and alternative measures of key variables are discussed.

The paper aims to examine whether or not firms voluntarily filing in XBRL (eXtensible Business Reporting Language) format enjoy a lower cost of capital. XBRL, or “interactive data” as the US Securities and Exchange Commission refers to it, is an information format that enables electronic exchange of standardized business and financial information.

The authors investigate whether voluntary adoption of XBRL impacts cost of equity capital using a sample of US firms participated in the SEC Voluntary Filer Program, each matched with a pair of non-XBRL filers (matched by two-digit SIC code, same fiscal yearend, and close total assets in the same year). The authors measure firm-specific cost of equity capital at the fiscal year of last voluntary XBRL filing, using the PEG ratio model proposed by Easton, Gode and Mohanram, and Hou et al.

The results show that cost of equity capital is significantly and negatively associated with XBRL adoption. The magnitude of the coefficient on XBRL suggests that firms voluntarily adopting XBRL are associated with an average reduction in cost of equity capital by 17-20 basis points (conditional on different cost of capital measures).

There is a research limitation due to the sample of voluntary XBRL adopters as of self-selection bias. The authors address this issue by using the Heckman two-stage regression procedure.

The study provides evidence on the economic consequence of XBRL adoption in that it benefits shareholders by reducing the cost of equity capital. The evidence should provide regulators like the SEC more incentives to mandate the XBRL standard and motivate companies to adopt the standard as well.

By showing that voluntary XBRL adopters are associated with lower cost of equity capital, the study provides timely and relevant empirical evidence to the economic consequences of voluntary adoption of XBRL. It also contributes to the limited empirical research on the economic consequences of new information technology and highlights the importance of institutional regulation in shaping the outcomes of new financial reporting format.

Nowadays, organizations have to resist the rising competition more effectively than their competitors and take a step closer to excellence in offering the product to customer demands. To do this, organizations need agile leaders in order to implement agility principles and practices. Especially in the health sector, health managers must be agile because of the specific characteristics of health services. From this view, this chapter aims to develop a theoretical agile leadership model in healthcare organizations. First, the authors define agile leadership and its sub-dimensions based on previous literature. Then, the antecedents and outcomes of agile leadership have been analyzed. “Drivers of agile leadership,” “organizational factors affecting agile leadership” and “individual factors affecting agile leadership” are identified as the antecedents of agile leadership. “Organizational outcomes” and “individual outcomes” are determined as the outcomes of agile leadership in the health sector.

The purpose of this paper is to enhance the understanding on the electrodeposition of various lead (Pb)‐free solder alloys, so that new studies can be carried out to solve processing issues.

The paper reviews the available reports on the electrodeposition of tin (Sn)‐based solder systems and identifies the challenges in this area.

Compositional control remains a major challenge in this area, where the achievement of desired composition for binary and ternary alloys is subjected to uncertainties. The use of chelating agents in the bath and optimization of parameters can assist the achievement of near‐desired alloy composition. Acidic plating baths are preferred due to their compatibility with photoresists but oxidation of stannous ions causes poor bath stability. Antioxidants, reducing agents and low oxygen overpotential anodes can suppress the oxidation rate and increase the lifespan of plating baths. Apart from chelating agents and antioxidants, various categories of additives can be added to improve quality of deposits. Surfactants, grain refiners and brighteners are routinely used to obtain smooth, fine‐grained and bright deposits with good thermo‐mechanical properties.

The paper provides information on the key issues in electrodeposition of Pb‐free solder alloys. Possible measures to alleviate the issues are suggested so that the electrodeposition technique can be established for mass production of a wider range of solder alloys.

How do organizations respond to negative feedback regarding their innovation activities? In this chapter, the authors reconcile contradictory predictions stemming from behavioral learning and from the escalation of commitment (EoC) perspectives regarding persistence under negative performance feedback. The authors core argument suggests that the seemingly contradictory psychological processes indicated by these two perspectives occur simultaneously in decision makers but that the design of organizational roles and reward systems affects their prevalence in decision-making tasks. Specifically, the authors argue that for decision makers responsible for an individual project, responses given to negative performance feedback regarding a project are dominated by self-justification and loss-avoidance mechanisms predicted by the EoC literature, while for decision makers responsible for a portfolio of projects, responses to negative performance regarding a project are dominated by an under-sampling of poorly performing alternatives that behavioral learning theory predicts. In addition to assigning decision-making authority to different organizational roles, organizational designers shape the strength of these mechanisms through the design of reward systems and specifically by setting more or less ambiguous goals, aspiration levels, time horizons of incentives provided, and levels of failure tolerance.