Dr. Sherwood L Lambert

This paper intersects the delineation of responsibilities for information systems (IS) functions between cloud service users (CSUs) and cloud service providers (CSPs) specified in the Committee of Sponsoring Organizations of the Treadway Commission (COSO) (2021) “Enterprise Risk Management for Cloud Computing” with control activities in the most recent ISACA Control Objectives for Information Technologies (COBIT) “2019 Governance Management Objectives Practices Activities.” This intersection helps CSUs and CSPs understand their responsibilities for information technology (IT) control activities when establishing service level agreements (SLAs). In addition, it advises CPAs on internal control over financial reporting (ICFR) under Sarbanes-Oxley when performing annual financial statement audits for publicly traded CSUs and CSPs. Furthermore, it informs CPAs on CSPs’ IT control responsibilities when conducting third-party System and Organization Controls (SOC) engagements for CSPs under Statement on Standards for Attestation Engagements 18 (SSAE 18).
Data Availability: Data are available from the public sources cited in the text.
JEL Classifications: G31; G32; G33; M21.

This study evaluates tax service fees from 2003 to 2020, considering the impact of partisan politics on the level of fees paid. We review the major tax provisions as they impact the level of corporate taxation and the potential cost of tax minimisation strategies. The results find that the lowest average yearly tax fees occurred (2017-2020) after Republican President Trump enacted a major reduction in corporate tax rates to 21% from 2017 to the present. During Republican President Bush's last six years (2003-2008), the average yearly tax fees were higher than during Democratic President Obama's eight-year term (2009-2016). The results suggest that while the political party and the partisan nature of tax policy would seem to impact the costs for tax services, the largest impact comes from actions taken by specific presidents in tax policy.

We propose a generalized, practitioner-oriented operating-leverage model for predicting operating income using net sales, cost of sales, depreciation, and SG&A. Prior research links operating income directly to these items; hence, our model includes all aggregate revenues and expenses that comprise operating income. Prior research finds that the cost of sales is “much less” sticky than depreciation and SG hence, we use the cost of sales as a proxy for the total variable costs and depreciation and SG&A as proxies for the sticky fixed costs. We introduce a new adjustment to the textbook operating-leverage model so that the ratio of sales to the cost of sales remains constant for the reference and forecast periods. Inspired by prior research, we adjust depreciation and SG&A for cost stickiness. We find that using our generalized operating-leverage model improves the forecast accuracy of next-quarter and next-year operating income predictions compared to predictions made using textbook operating leverage, which is a special case of our model.

Blockchain and cloud computing continue to emerge and evolve as important technologies for data management. This has strategic implications for data stored in enterprise resource planning (ERP) systems. We use manufacturing bills of materials (MBOMs) as an example of critical data in ERP. MBOMs define the complex product structures of manufacturing enterprises. We survey five alternatives for storing, controlling, and auditing MBOMs in ERP: Oracle Blockchain Table; Oracle Blockchain Platform Enterprise Edition; Microsoft Azure SQL Database Ledger; SAP HANA Blockchain Ledgers; and IBM Blockchain Platform. We also consider cloud computing without blockchain technologies. We analyze the advantages and disadvantages of each alternative by its effect on the management of MBOMs. Although we use MBOMs in our illustrations, many of the concepts discussed also apply to other critical data stored in ERPs. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: G31; G32; G33; M21.

Both professionals and academics have called for changes to the accounting curriculum over the past 20 years, and more recent research (e.g., Albring & Elder, 2020) has asked schools to share not only their curriculum changes but also the motivations for these changes. This paper responds to these calls by not only providing the results of and rationale for an accounting curriculum change but also sharing the research and processes that supported the change. The six-step process employed in this paper was used to review and revise the Master of Accountancy (MAcc) curriculum at a mid-size Florida university with a strong emphasis on career preparation and student success on the CPA Exam. The results and resources presented include benchmarking curriculum analyses (e.g., tracks offered, number of courses by type, required versus elective courses), techniques for sharing benchmark information with stakeholders, and internal and external stakeholder surveys. Although some resources may be of immediate use “as-is,” it is more likely that schools will be able to enhance, refine, or alter the processes to align with the particular needs and objectives of their stakeholders.

We study the effects of the three recessions during 1990-2009 on analysts' next-year EPS forecasts. We find 10 of the 17 forecast-year/forecasted-year pairs studied have the expected inverse relationship between utilization of fundamental signals and forecast error rates when the forecast and forecasted years are outside the recessions' period ranges. Similarly, we find this inverse relationship exists for 2006-2007 and 2007-2008 that are wholly within The Great Recession timeframe. These results are consistent with an inverse relationship existing during periods of extended economic growth or prolonged recession that span the forecast reference year and the realization of the next-year, forecasted EPS. For 1991-1992 when the Gulf War Recession affected the 1991 fundamental signals, and 2001-2002 when the 9/11 Recession affected the 2001 fundamental signals, we find both forecast error rate and efficient utilization of the fundamental signals decreased. We find comparable results for analysts' long-term earnings growth forecasts.

This paper uses just the items in Compustat to develop a proxy for operating leverage and studies operating leverage as a fundamental signal for predicting future earnings. The evidence indicates operating leverage is not relevant in predicting next-year EPS change but is a significant and positive predictor of long term growth in earnings, with the condition that earnings are positive in the current year and in the long-term future year. With this condition imposed, operating leverage is significant in predicting longterm growth in earnings in thirteen-of-fourteen years tested with average p-value 0.017 for the fourteen-years tested. All fourteen yearly coefficients were positive, indicating a robust, direct relationship to long-term growth. Other fundamental signals were developed and studied for free-cash flows, market share, and debt-to-assets, and evidence indicates that these three along with operating leverage significantly contribute to the explanatory/predictive power of models previously developed using the expert guidance of security analysts. In addition, evidence is consistent with the macroeconomic recessions that began during 2001 and near the end of 2007 having substantially affected the relevance of many of the studied fundamental signals during 2000 and 2006 in predicting next-year earnings changes.

Purpose – To the authors’ knowledge, this paper is the first to use Detail I/B/E/S to study directly the timeliness of security analysts’ next-year earnings-per-share (EPS) estimates relative to the SEC filings of annual (10-K) and quarterly (10-Q) financial statements. Although the authors do not prove a causal relationship, they provide evidence that the average time from firms’ filings of 10-Ks and 10-Qs to the release of analysts’ annual EPS forecasts during short timeframes (for example, 15-day timeframe from a 10-K’s SEC file date) subsequent to the 10-K and 10-Q filing dates significantly shortened with XBRL implementation and then remained relatively constant following implementation.

Design/methodology/approach – Using filing dates hand-collected from the SEC website for 10-Ks during 2009-2011 and filing dates for 10-Ks and 10-Qs during 2003-2014 input from Compustat along with analysts’ estimated values for next year EPS, actual estimated next year EPS realized and estimate announcement dates in Detail I/B/E/S, the authors study the days from 10-K and 10-Q file dates to announcement dates and the per cent errors for individual estimates during per- and post-XBRL eras.

Findings – The authors find that analysts are announcing next-year EPS forecasts significantly more frequently and in significantly shorter time in zero to 15 days immediately following 10-K and 10-Q file dates post-XBRL as compared to pre-XBRL. However, the authors do not find a significant change in forecast accuracy post-XBRL as compared to pre-XBRL. Research limitations/implications – Because this study uses short timeframes immediately following the events (filings of 10-Ks and 10-Qs), the relationship between 10-Ks and 10-Qs with and without XBRL and improved forecast timeliness is strengthened. However, even this strengthened difference-in-difference methodology does not establish causality. Future research may determine whether XBRL or other factors cause the improved forecast timeliness the authors’ evidence.

Practical implications – This improved efficiency may become critical if financial statement reporting expands as a result of new innovations such as Big Data and continuous reporting. In the future, users may be able to electronically connect to financial statement data that firms are maintaining on a perpetual basis on the SEC website and continuously monitor and analyze the financial statement data dynamically in real time. If so, then unquestionably, XBRL will have played a critical role in bringing about this future innovation.

Originality/value – Whereas previous studies have utilized Summary IBES data to assess the impact of XBRL on analyst forecasts, the authors use Detail IBES to study the effects of XBRL adoption directly by measuring days from 10-K and 10-Q file dates in Compustat to each estimate’s announcement date recorded in IBES and by computing the per cent error using each estimate’s VALUE and ACTUAL recorded in Detail IBES. The authors are the first to evidence a significant shortening in average days and an increase in per cent of 30-day counts in the zero- to 15-day timeframe immediately following the fillings of 10-K s and 10-Qs.

This case addresses the critical topic in education of developing students' skills and capabilities associated with enterprise-level business intelligence systems and associated internal control concerns. The experiences of using a business intelligence,task-based activity in an interdisciplinary curriculum model are presented and discussed. Pedagogically, the task-based activity enhances perceived learning for both accounting and IS disciplines indomain (internal controls and IS development), communication (comprehension and creation), and critical thinking skills. Additionally, students appreciate the realism and active learning associated with the task-based activity delivered in an interdisciplinary curriculum model. The design of the task-based activity as a teaching resource allows other instructors, based on their requirements, to develop a lesson plan around using the activity as written, or focusing on the any of the many aspects of controls or technology presented.

Purpose – This paper aims to develop a set of tactical electronic business solutions for the electronic credit card issuing industry.

Design/methodology/approach – Specifically, a strategic credit card issuing (SCCI) model is developed to analyze e-business in the credit card issuing industry. Second, a set of tactical solutions is derived on the basis of the SCCI model. Third, pattern analysis is conducted on the basis of data collected from dominant credit card issuing companies to further investigate the implementation status on these electronic business solutions in the credit card issuing industry.

Findings – The findings show that three categories of electronic business solution items can be classified. The average variability of electronic business implementation patterns for business-to-business, business-to-customer and business-to-internal in each company shows a variety of electronic business strategies implemented by these dominant companies.

Originality/value – The results will help managers and executives when they make strategic and tactical decisions on electronic business in the credit card issuing industry.