This paper examines how managerial discretion and judgment in revenue recognition affect earnings and revenue value relevance. Specifically, the purpose of this paper is to assess…
Abstract
Purpose
This paper examines how managerial discretion and judgment in revenue recognition affect earnings and revenue value relevance. Specifically, the purpose of this paper is to assess the impact of lifting the objective-price constraint in revenue recognition on the value relevance of earnings and revenue by examining firms’ contemporaneous returns-earnings/revenue relation before and after the implementation of Accounting Standards Update (ASU) 2009-13. In addition, this paper examines how the change in earnings value relevance is conditioned by agency costs, corporate governance, information environment, and audit quality. This paper further examines whether earnings, revenue, and accruals quality change after the objective-price constraint is lifted.
Design/methodology/approach
This paper employs a difference-in-differences research design to examine whether earnings and revenue value relevance are enhanced or lowered more for a list of 107 US firms that applied selling price estimates in revenue recognition under ASU 2009-13 than for a list of 107 matched US firms that did not apply selling price estimates. Sub-sample analyses are employed to examine how agency costs, corporate governance, information environment, and audit quality condition the change in value relevance. Additional analyses examine the changes in earnings, revenue, and accruals quality using accruals, revenue accruals, discretionary revenue, absolute abnormal accruals, earnings/revenue predictability, and smoothness.
Findings
The empirical results suggest that lifting the objective-price constraint in revenue recognition improves earnings and revenue value relevance for positive earnings and that the effect of information usefulness dominates that of managerial opportunism. Change in the earnings value relevance is conditioned by the level of corporate governance, information environment, and audit quality. Evidence of no significant reduction in the earnings/revenue/accruals quality corroborates the main findings.
Research limitations/implications
The findings lend support to the new revenue standard (ASU 2014-09) that continues the use of the estimates of selling price in revenue recognition.
Originality/value
This study provides some of the first evidence that managerial judgment exercised in revenue recognition through the use of selling price estimates (i.e. lifting the objective-price constraint in revenue recognition) enhances earnings and revenue value relevance while such benefit does not come at a cost of reduced earnings/revenue/accruals quality.
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Anthony Chen and Hung-Yuan (Richard) Lu
In this study, the authors extend upon Brockman et al. (2008), who provide evidence that managers opportunistically accelerate bad news prior to share repurchases, but provide…
Abstract
Purpose
In this study, the authors extend upon Brockman et al. (2008), who provide evidence that managers opportunistically accelerate bad news prior to share repurchases, but provide limited evidence that managers withhold good news until after repurchases. The authors examine management forecasts surrounding share repurchases in periods when companies must disclose detailed repurchase information. The authors argue these disclosures increase managers' legal and reputation risks of accelerating bad news, but have a lesser effect on delaying good news.
Design/methodology/approach
First, the authors examine whether managers alter the information released to the market before buying back shares by comparing managerial forecasts made within 30 days before the beginning of a repurchasing period with those made outside of this window. Second, the authors examine whether managers are more likely to provide good news forecasts, in terms of both magnitude and frequency, after buying back shares. Lastly, the authors examine the impact of CEO stock ownership on managerial forecasting behavior surrounding share buybacks.
Findings
Consistent with the authors’ hypotheses and contrary to Brockman et al. (2008), the authors find limited evidence that the likelihood or magnitude of bad news forecasts is greater in the period before share buybacks. Instead, the authors document that the frequency and magnitude of good news forecasts increase in periods following share buybacks and that these associations are positively moderated by managerial equity incentives. The authors also find that the withholding of good news is associated with lower average repurchase prices and greater repurchase volume. The authors further show that, when litigation risk is greater, managers are less likely to accelerate bad news prior to repurchases and more likely to withhold good news until after. Overall, the study results are consistent with managers balancing the benefits of opportunistic repurchase behavior with the costs.
Originality/value
This study contributes to the management forecast and share repurchase literatures by providing evidence consistent with managers opportunistically releasing earnings forecasts in the period after buying back shares. Most importantly, the authors show that after the rule revision, managers refrain from actively disclosing bad news that carry higher legal costs. Instead, they opt for the omission of good news to repurchase stocks at lower prices. The study results reconcile the conflicting evidence of Brockman et al. (2008) and Ge and Lennox (2011).
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Hung-Yuan (Richard) Lu and Vivek Mande
This study aims to examine whether banks are compliant with the Financial Accounting Standards Board’s standard Accounting Standards Update (ASU) 2010-06 requiring disaggregated…
Abstract
Purpose
This study aims to examine whether banks are compliant with the Financial Accounting Standards Board’s standard Accounting Standards Update (ASU) 2010-06 requiring disaggregated fair value hierarchy information. It also identifies institutional and firm-specific factors that are associated with compliance or non-compliance.
Design/methodology/approach
Using quarterly reports of banks for the first quarters of 2009 (pre- ASU 2010-06) and 2010 (post- ASU 2010-06), we hand-collect information on disclosures about fair values from the footnotes. Using a logistic regression with compliance/non-compliance as the dependent variable, we examine factors associated with compliance/non-compliance.
Findings
Results show that 23 per cent of banks do not comply with ASU 2010-06 and that the non-compliant banks tend to be small, lack effective internal controls and are more likely to be audited by non-specialist auditors.
Research limitations/implications
This study only considers one type of non-compliance with ASU 2010-06, i.e. whether or not firms provide disaggregated fair value hierarchy information. There may be other forms of non-compliance that the authors do not examine because of the difficulties involved in objectively defining non-compliance.
Practical implications
The findings suggest firms may need to increase training for internal personnel and hire high-quality auditors for ensuring compliance with fair value accounting rules. The authors also suggest that smaller firms may find compliance to be onerous and recommend additional research to examine whether smaller firms should be exempted from some or all of the fair value rules.
Originality/value
This study provides some of the first evidence on the level of compliance with mandated fair value disclosures.
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Although prior research documents that analysts sometimes herd their forecasts, very few studies investigate how investors’ judgments are influenced by their perceptions of the…
Abstract
Although prior research documents that analysts sometimes herd their forecasts, very few studies investigate how investors’ judgments are influenced by their perceptions of the likelihood of analyst herding. I conduct an experimental study to investigate the conditions under which investors’ assessments of uncertainty about future earnings are influenced by their perceptions of the likelihood of analyst herding. As expected, and consistent with motivated reasoning, the results show that the temporal order of analyst forecasts influences investors’ estimates of the likelihood of analyst herding and investors’ uncertainty judgments when analyst forecasts are preference-inconsistent but not when analyst forecasts are preference-consistent. This study provides a potential explanation for the mixed findings of prior research in regard to investors’ reactions to the likelihood of analyst herding. In addition, this study extends research on investors’ credulity by providing evidence that motivated reasoning and skepticism may serve as a mechanism that contributes to that credulity.
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Yen-Chun Wu, Mark Goh, Chih-Hung Yuan and Shan-Huen Huang
The purpose of this paper is to investigate the state of logistics management research in Asia. The study focuses on the research agenda, the topics of interest, and the extent of…
Abstract
Purpose
The purpose of this paper is to investigate the state of logistics management research in Asia. The study focuses on the research agenda, the topics of interest, and the extent of research collaboration in logistics theory building and knowledge specific to Asia.
Design/methodology/approach
This study uses a mixed methods approach namely, content analysis drawn from the articles found in six well-recognized peer-reviewed logistics management related journals from 2003 to 2013, followed by social network analysis which is applied on the selected articles to provide a structure of the collaboration relationship.
Findings
Initial findings suggest that there are some scholars in Asia who are instrumental in research collaboration and in building a body of knowledge on logistics management focused on Asia. More co-production of knowledge from deeper and tightly knit industry-academic collaboration is needed to progress this domain. Most of the published work use an empirical instrument drawn from the resource-based view to explore firm level supply chain collaboration and strategy. This suggests a positivist research tradition within logistics. There is a shortage of studies conducted on the supply chain as a network of enterprises.
Research limitations/implications
The review of the articles is limited to six logistics specific journals and the authors only concentrate on logistics management research focused on Asia. The contributions from the other journals may have been missed. More collaboration at the institutional, national, and international levels is called for especially on cross-collaboration between practice and theory.
Practical implications
Though the analysis is restricted to 260 articles found in six journals, this paper can shed light on the research needs from different perspectives and facilitate the progress of logistics management research in Asia.
Originality/value
This is the first paper to discuss the state of logistics management research collaboration in Asia, and provides an overview of the research issues, topics, and approaches undertaken thus far. Through this work, this study hopes that it will encourage greater research collaboration between industry and academia, and academics themselves.
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Yujie Cheng, Hang Yuan, Hongmei Liu and Chen Lu
The purpose of this paper is to propose a fault diagnosis method for rolling bearings, in which the fault feature extraction is realized in a two-dimensional domain using scale…
Abstract
Purpose
The purpose of this paper is to propose a fault diagnosis method for rolling bearings, in which the fault feature extraction is realized in a two-dimensional domain using scale invariant feature transform (SIFT) algorithm. This method is different from those methods extracting fault feature directly from the traditional one-dimensional domain.
Design/methodology/approach
The vibration signal of rolling bearings is first transformed into a two-dimensional image. Then, the SIFT algorithm is applied to the image to extract the scale invariant feature vector which is highly distinctive and insensitive to noises and working condition variation. As the extracted feature vector is high-dimensional, kernel principal component analysis (KPCA) algorithm is utilized to reduce the dimension of the feature vector, and singular value decomposition technique is used to extract the singular values of the reduced feature vector. Finally, these singular values are introduced into a support vector machine (SVM) classifier to realize fault classification.
Findings
The experiment results show a high fault classification accuracy based on the proposed method.
Originality/value
The proposed approach for rolling bearing fault diagnosis based on SIFT-KPCA and SVM is highly effective in the experiment. The practical value in engineering application of this method can be researched in the future.
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Alberto Rosi, Marco Mamei and Franco Zambonelli
The key purpose of this paper is to overview the many issues related to the integration of social sensing and pervasive sensing in the support of adaptive context-aware services…
Abstract
Purpose
The key purpose of this paper is to overview the many issues related to the integration of social sensing and pervasive sensing in the support of adaptive context-aware services.
Design/methodology/approach
From the analysis of existing proposals and prototypes, the authors found out that the process of integrating social and pervasive sensing can follow a limited number of approaches, which enables the authors to properly frame the proposals existing in the literature (and/or available as prototype infrastructures) according to a simple taxonomy, which is very useful to make the survey much more effective than a simple list of systems and proposals.
Findings
The taxonomy shows that, when integrating social sensing with pervasive sensing, it is possible, at one extreme, to exploit social network as a mere source of information and have such information flow towards the infrastructure supporting the execution of pervasive computing services. At the other extreme, it is possible exploiting a social network as an infrastructure for the integration, by having data from pervasive devices flow towards social networks. In between the extremes, different means can consider to have social networks and pervasive infrastructures converge towards each other to enable the integration of social and pervasive sensing.
Originality/value
Besides introducing the main concepts related to social sensing and framing the key approaches that can be undertaken to pursue the integration with traditional pervasive sensing, the authors go further discussing open issues and key research challenges behind their seamless integration.