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This study aims to examine whether Chinese firms increase their concerns about analysts’ earnings forecasts following the split-share structure reform (SSR) in 2005, which removed trading restrictions on approximately 70% of the shares of listed firms.

Using data from 2002 to 2019, the authors empirically test the association between meeting or beating analysts’ earnings expectations and the implementation of SSR.

The authors find that firms are more inclined to meet analysts’ earnings expectations after the introduction of SSR. Further analysis shows that firms guide analysts to walk their forecasts down by manipulating third-quarter earnings, suggesting enhanced value relevance between analysts’ forecasts and third-quarter earnings management in the postreform period.

The findings reveal an undesirable side effect of SSR and suggest that policymakers and regulators should consider and carefully manage the complex relationships between firms and analysts.

In contrast to prior studies that predominantly focus on the positive effects of the reform, this study reveals the side effects of SSR and provides new evidence on the mechanisms of meeting or beating analysts’ earnings 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.

This study investigates the influence of nonfinancial 8-K disclosures released during the earnings announcement window on the abnormal trading activities of individual investors.

We employ regression analysis in this empirical study to examine the impact of nonfinancial 8-K filings on individual investors' abnormal trading activities.

Our results reveal that individual investors exhibit higher levels of abnormal trading activities when firms release nonfinancial 8-Ks during the (0,1) window of earnings announcements. This effect is observed for both buyer-initiated and seller-initiated transactions and is particularly pronounced for firms reporting an operating loss. Negative sentiment in 8-Ks significantly intensifies such effect. Additionally, we find that buy-sell consensus increases significantly with concurrent nonfinancial 8-Ks. This suggests that 8-Ks may reduce information noise, leading individuals to trade with greater conviction.

Our study examines the joint influence of nonfinancial 8-Ks and earnings announcements on individual investors' trading activities, thereby providing a novel perspective on the mechanisms through which 8-K filings affect individual investors' trading behaviors.

In this study, we examine the influence of a firm’s environmental, social, and governance (ESG) performance on analysts’ stock recommendations and earnings forecast accuracy in the Chinese context.

We take a textual analysis approach to analyst research reports issued between 2010 and 2019, and differentiate between two distinct analyst categories: “sustainability analysts,” which refer to those more inclined to incorporate ESG information into their analyses, and “other analysts.”

Our evidence indicates that sustainability analysts tend to be significantly more likely than others to provide positive stock recommendations and demonstrate enhanced accuracy in forecasting earnings for companies with superior ESG performance. Our additional analyses reveal that this finding is particularly prominent for analysts who graduated from institutions emphasizing the protection of the environment, those recognized as star analysts, those affiliated with ESG-oriented brokerages, and forecasts made by analysts in the later part of the sample period. Our findings further indicate that sustainability analysts exhibit a more pronounced negative response when confronted with a negative ESG event.

In general, the evidence from this study reveals the interplay between ESG factors and analyst behavior, offering valuable implications for both financial analysts and sustainable investment strategies.

This study aims to investigate whether mandated disclosure of engagement quality review hours provides new information that affects investors’ decision-making.

In 2014, Korean authorities mandated that audit engagement quality review hours must be disclosed in their audit reports. Using this unique field setting in Korea, this study presents empirical evidence of the policy initiative’s effect on earnings reliability by examining both pre- and post-implementation periods.

Following the initial disclosure of engagement quality review hours in 2014, the authors observe that the capital market’s valuation of quarterly earnings surprises, measured by earnings response coefficients (ERCs), was significantly lower for firms with high levels of abnormal engagement quality review hours than for other firms. This paper also finds that the observed association between engagement quality review hours and ERCs in the postregulation period hinges on the probability of earnings management, proxied by discretionary accruals and just meeting or beating analyst earnings forecast.

This paper suggests that the policy mandating disclosure of engagement quality review hours provides original information that the market considers relevant for appraising the reliability of reported earnings.

This paper aims to examine whether firms meeting or just beating an earnings benchmark engage in tone management in earnings conference calls to complement earnings management in the UK context. It also investigates whether the audience tone in beating or just meeting earnings fails to predict future performance.

This study was performed using a sample of non-financial UK firms listed in the FTSE 350 index over the period 2010–2015.

The findings show that firms that exercise more earnings management to meet or just beat earnings are positively associated with the abnormal tone during earnings conference calls. The outcomes also reveal that the audience’s tone of firms meeting or just beating an earnings benchmark fails to predict future performance. This confirms the effectiveness of the tone management in managing the perception of audience.

This study highlights the need for increased accountability by firms on earnings conference call. It also supports academics and practitioners in understanding the management discretion used in reporting and communication during the earnings conference call. Overall, the results of this study are beneficial for regulators, policymakers and professionals, regarding confirming the need for the earnings conference calls to be regulated.

To the best of the authors’ knowledge, this is the first study that examines the association between earnings management and tone management in the UK earnings conference calls. It adds to the existing literature by examining the self-serving behaviour of managerial tone during earnings conference calls within a sitting in which meeting or just beating a benchmark is used. Unlike several studies that explain the behaviour of tone as a signalling strategy, this study reveals that the tendency of impression management behaviour can explain the tone management.

The purpose of this study is to examine the impact of cross-ownership on corporate digital innovation and their specific mechanisms. Cross-ownership, who hold equity in two or more companies simultaneously, have two different types of governance effects in the capital market: governance synergistic effects and competitive collusion effects.

This paper uses a panel model, selecting A-share company data from 2011 to 2021 in China. In total, 23,853 valid data were obtained, which came from the CSMAR database and Wind database. For some missing data, they were manually supplemented by consulting the company's annual report and Sina Finance. Data processing was conducted using EXCEL and Stata16.0 software.

The results show that cross-ownership promote corporate digital innovation by leveraging governance synergies. Further grouping tests show that the synergistic effects of cross-ownership are significant in non-state-owned, high-tech, weakly competitive and higher analyst attention enterprises. Mechanism testing shows that cross-ownership can empower corporate digital innovation in three ways: reducing information asymmetry, alleviating financing constraints and improving corporate governance.

The conclusion of this paper provides new empirical evidence for a comprehensive understanding of the role of cross-ownership in corporate development, enriches the economic consequences research of chain institutional investors in China and broadens the research perspective of corporate digital innovation. It also provides important references for the digital transformation of enterprises and the healthy development of the capital market.

Business analytics (BA) is a new frontier of technology development and has enormous potential for value creation. Information systems research shows ample evidence of its positive business impacts and organizational performance. However, there is limited understanding of how decision-makers or users of BA outcomes actually engage with data analysts in the process of data-driven insight generation and how they improve their understanding of business environments using BA outcomes. To aid this engagement and understanding, this study investigates the interaction between decision-makers and data analysts when they attempt to uncover data capacities and business needs and acquire business insights from BA tools.

This study employs an interpretive field study with thematic analysis. The authors conducted interviews with 31 participants who all relied on BA in their daily decisions. The study participants were engaged in different BA roles, including data analysts and decision-makers. They validated the applicability and usefulness of our findings through a focus group with eight practitioners, including decision-makers and data analysts from the same companies.

This study proposes a process model of data-driven sensemaking and sensegiving based on Weick’s sensemaking framework. The findings exhibit that decision-makers are engaged in sensemaking by identifying areas of focus, determining BA scope, evaluating generated insights and turning BA into action. The findings also show that data analysts engage in sensemaking by consolidating data, data understanding, preparing preliminary outcomes and generating actionable reports. This study shows how sensemaking processes and sensegiving activities work together over time through immediate enactment, selection and decision cycles.

This study is a first attempt to understand interactions in the context of BA using the perspective of sensemaking and sensegiving.

COVID-19 and its accompanying lockdowns were arguably the most traumatic events of our times. This paper investigates the impact of COVID-19 on market efficiency.

I analyze all publicly traded U.S. equities for 2014–September 2021, using intraday data from TAQ, TRACE, I/B/E/S and Capital IQ and daily data from CRSP, Thomson Reuters, Compustat, CRSP-Compustat Merged Database and FRED, using a controlled contrast between absolute abnormal returns for relevant halfhours versus absolute abnormal returns in control halfhours, measured by the negative of the coefficient of the fixed effect of the interaction between the indicator variable, and as the case may be, ticker and/or time period of interest, in the regression of halfhour-level absolute abnormal returns on tickers, months and interactions.

Using two separate objective, systematic, independent and ordinal per se measures of market efficiency based upon market reactions separately to key developments and earnings announcements, I find that U.S. equities markets were statistically and economically significantly less efficient during the first two-three months of the COVID-19 lockdowns.

Efficient capital markets provide substantial social benefits and are a sine qua non for the democratization of markets and the protection of investors, and constitute a critical mission of regulatory bodies such as the U.S. Securities and Exchange Commission (SEC) and the U.S. Financial Industry Regulatory Authority (FINRA).

The impact on market efficiency provides one critical input into the social cost-benefit analysis of public health policy and that of government interventions in general.

There has been no previous work done on the systematic and objective characterization of the impact of COVID-19 and associated lockdowns on market efficiency.