Accounting & Finance

To accomplish this mission, the Accounting Program has articulated a number of program objectives. These include the need to

• Design, develop and deliver programs that impart to students skills, abilities, and knowledge appropriate to their backgrounds and professional career aspirations
• Maintain currency in the accounting curriculum
• Support student professional development activities especially for students from families attending university for the first time
• Promote faculty development
• Encourage and support intellectual contributions in the accounting and business disciplines
• Conduct outreach to various stakeholders of the Accounting Program
• Maintain faculty participation in and service to the academic, business, and accounting professional communities 
• Explore and develop international relationships 
• To enhance diversity and improve value-added nature of accounting programs, increase number and support of first-generation accounting students 
• Add value by placing our students in highly regarded firms

These objectives enhance the accounting program’s ability to provide a challenging educational environment in which to prepare and support our students to be successful in accounting careers; to encourage our faculty to develop professionally and intellectually; and to promote overall participation in activities that support the University and the professional community.

Learning Goals	Learning Objectives
LG1: Analyze and design data measures and develop decision models, analytics and reporting systems to support the achievement of business and stakeholders’ goals
	LO1: Use analytical techniques to extract and transform data into information useful for businesses and stakeholders’ decision making
	LO2: Design systems, including reporting systems, and decision models to support managers’ and stakeholders’ decision making
	LO3: Understand how risks relate to organizations’ and their stakeholders’ goals and how controls act to reduce risks
	LO4: Analyze and evaluate decision models’ strengths and weaknesses
	LO5: Develop skills and knowledge related to the integration of technology in accounting and business
LG2: Understand accounting as a discipline requiring professional judgment and knowledge of standards and best practices
	LO6: Demonstrate the ability to recognize and analyze ethical dilemmas in a business
	LO7: Demonstrate the ability to evaluate critically business and stakeholders’ models and corresponding systems designs

Learning Goals	Learning Objectives
LG1: Expose students to the professional accounting environments, including to its risks, reporting, regulatory processes and professional ethics standards
	LO1: Use professional standards and other codifications from professional bodies to analyze complex business and accounting situations and recommend viable solutions
	LO2: Analyze professional ethical situations using appropriate professional standards and recommend defensible solutions
LG2: Demonstrate the ability to use effective oral and written communication to express clearly ideas about accounting in a professional manner and tone
	LO3: Be able to articulate an accounting issue in writing that is clear, concise and logical
	LO4: Be able to orally communicate an accounting issue in a coherent and effective manner
LG3: Demonstrate an ability to conduct an accounting or accounting-related project which adds value to the profession or a potential client or firm
	LO5: Identify a subject area of accounting to research, perform a literature review, identify theories and frameworks to use, and formulate research questions
	LO6: Appropriately test research questions by investigating sources of data and collecting relevant data
	LO7: Summarize research findings and prepare conclusion

Dion Bongaerts (Rotterdam School of Management); [email protected]
Thomas Breuer (University of Applied Sciences Vorarlberg); [email protected]
Hans-Peter Burghof (University Hohenheim); [email protected]
Pascal Gantenbein (University of Basel); [email protected]
Stefan Morkoetter (University of St. Gallen); [email protected]
J. Austin Murphy (Oakland University); [email protected]
Daniel Rösch (University of Regensburg); [email protected]
Simone Westerfeld (University of St. Gallen); [email protected]

2015 Conference in Basel, Switzerland

2014 Conference in Rochester, Michigan

2013 Conference in Basel, Switzerland

2011 Conference in Rochester, Michigan

Information Asymmetry
One of the research project derived from my dissertation, titled “Investment Decision, Limited Liability, and Consumption Preference,” was published by GRP International Journal of Business and Economics in 2012 (Vol. 1, No. 3). This paper investigates the friction between borrowers and lenders. The topic of friction between the borrower and the lender is of special interest in helping to explain the collapse of the U.S. housing market.

Systematic Risk
During the 2010 academic year, I co-authored with accounting colleague at Oakland University and industry expert and published “Systematic Risk Estimation: OLS v. State-space Methods” at International Research Journal of Applied Finance (Vol. III, Issue 7, July, 2012). We proposed a new approach in estimating systematic risk in the stock market.

From the 2011 academic year onward, I have been collaborating with colleagues in finance and an external banking industrial expert on a series of bond risk projects. “An Empirical Analysis of Segmented Pricing of Bond Systematic Risk” was published at the Credit and Capital Markets (Kredit and Kapital, Vol. 3, 2014); “An Empirical Examination of Ex-ante Estimates of the Market Risk Premium” was published at The Journal of Investing (Vol. 23 No. 2, 2014); “Systematic Risk and Yield Premiums in the Bond Market” was published by The Journal of Credit Risk in 2015 (Vol. 11, No.2). All these papers are produced by utilizing Citigroup proprietary corporate bond data. The collaboration with the industry creates research synergies between academia and the business world, the findings from our studies not only contribute to provide more advanced empirical evidence to the theories of credit and business risks; but also shed lights on business environment and industry understanding of their specific risk factors.

Credit Risk
In 2010 academic year, I have also published a credit risk paper with two accounting colleagues at Oakland University. “New Risk Analysis Tools with Accounting Changes: Adjusted Z-score” was published at The Journal of Credit Risk (Vol. 8 No.1, Spring, 2012) and it discusses necessary adjustments in bankruptcy Z-score in the presence of earnings management.

Liquidity Risk
In the liquidity risk area, I have co-authored with department’s colleagues and outside colleague, and published two papers on Review of Accounting and Finance. The manuscript titled “The Role of CEO Inside Debt Holdings in Corporate Pension Funding Status” was published in 2015 (Vol. 14, No.3) and had also received the honor of Highly Commended Paper in the 2016 Emerald Literati Network Awards for Excellence. Another study titled “Liquidity and Corporate Governance: Evidence from Family Firms” was published in 2016 (Vol. 15, No.2). Both research on liquidity risks have considerable implications to the business world.

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In brief:
Managers face an ethical dilemma between altruism and financial incentives in the allocation of scarce resources to philanthropic activities like corporate social responsibility (CSR) activities. For this matter, we develop arguments for the positive role of managerial efficiency that can influence the outcome of CSR activities. Using a newly developed measure of managerial efficiency, we demonstrate that, on average, managerial efficiency enhances Corporate Social Performance (CSP). However, we find that efficient managers are more likely to put efforts on product related CSR activities not to environment-related CSR activities. Overall, we conclude even for the altruistic decisions, efficient managers do better job. Our findings cast a new light on that our conventional view on the profit oriented managers who does not care about social value. Often, less business oriented people are assigned to the positions that have tasks of making decisions on CSR or sustainability. Then chances are resources are wasted with less trained managers in CSR activities without any social benefits.

Impact of Corporate Social Responsibility Activity on Corporate Social and Financial Performance
Over the past few decades, corporate social responsibility (CSR) activities have become increasingly essential to a firm’s operation. The importance of CSR goes beyond the philanthropic endeavors, and expands to a firm’s strategic and business case for CSR (e.g., economic oriented CSR). For example, customer loyalty tends to be significantly stronger toward corporations that incorporate CSR. Moreover, assets of an international network of CSR-focused investors, Principles for Responsible Investment, increased to a total of $59 trillion in the fiscal year 2015. To match this growing demand for CSR in recent years, more managers of many U.S. firms have begun allocating resources to CSR more than ever before. However, even for top managers such as the chief executive officer (CEO), who has the most control over resource allocation, it is difficult to pursue CSR because most CSR investment is frequently denigrated or criticized due to limited evidence that such spending has a positive influence on the firm’s long-term profitability or survival. Moreover, CEOs are confronted by the dilemma in CSR investment when they deal with acute conflicts and competitions among different stakeholders. For example, corporate pressure on suppliers can violate human rights by pushing down workers’ compensation of suppliers, mishandled labor relations can cause discrimination lawsuits, or a large-scale industrial dump can cause irreversible environmental damage. In such cases, business ethics can give some guidance in resolving the outright conflicts. Therefore, as powerful and final decision makers, most CEOs constantly calibrate their decisions to align with socially acceptable ethical standards. Obviously, investment in CSR is one area that involves business ethics. Considering the importance of business ethics in CSR investment, a long-standing concern is whether CSR activities provide financial gain to the firm. Often, the Corporate Social Performance (CSP),¹ which is rated by independent third-party agencies, through the lens of corporate financial performance (CFP) such as accounting earnings. The findings from prior studies on the relationship between CSP and CFP, however, are mixed. Such a lack of conclusive evidence may be attributable to the seemingly contradictory incentives that drive CSR. That is, the managerial incentives that precipitate CSR spending are encapsulated in a wide spectrum, dominated on one extreme by purely profit-oriented motivations and dominated on the other by altruistic motivations. Another reason for the mixed finding of the relation between CSP and CFP is that CFP does not work as a proxy to capture the effect of CSP beyond direct monetary benefits. Accordingly, understanding the underlying managerial motivations of various CSR and their consequences is important to shed light on the relation between CSP and CFP.

The Role of Managerial Efficiency to Enhance the Corporate Social Responsibility Performance
We investigated whether managerial efficiency plays a role in the execution of CSR and the achievement of high CSP, and how managerial efficiency influences the relationship between CSP and CFP. The productrelated CSR activities (e.g., long-term quality programs or notable innovation) are an example of relatively more strategic or economic-oriented activities that are expected to provide signal product quality to consumers, contrasting with purely profit-oriented business behavior producing products of lower quality with fewer costs. To test our research questions, we consider CSR activities when they are rated by Kinder, Lydenberg, and Domini (KLD) Research and Analytics, Inc. We use the CSR rating score published by KLD to measure CSP from 2003 to 2011. The KLD CSP score is composed of seven areas (environment, product, labor relations, diversity, community, corporate governance, and humanities). For managerial efficiency, we use the measure quantified by Demerjian et al. (2012).² For the empirical proxy of CFP, we use Total Q.

We find that managerial efficiency does not significantly affect the level of aggregated CSP, which is measured by the net total KLD CSR rating score. However, further analyses document that the moderating role of managerial efficiency appears for product-related CSR. On the other hand, we find that there is no moderating role of managerial efficiency on environment-related CSR. These results suggest that managerial efficiency is working in places related to product CSR issues to enhance CSP, not in environmental issues. With respect to the role of managerial efficiency in the link between CSP and CFP, we find that the link is stronger for firms with high managerial efficiency. When we consider the differential effect of managerial efficiency on two different types of CSP, we observe a similar moderating role of managerial efficiency on product-related CSP to generate high long-term benefits. These differential effects of managerial efficiency to capitalize CSP into CFP suggest that the degree of managerial efficiency is one of the important managerial characteristics to drive, choose, and execute CSR to generate future benefits. Overall, our results imply that degree of managerial efficiency can be an ex ante indicator of whether engaging in CSR is value creating or not.

Our findings address the importance of managerial ability to incorporate resources to produce positive outcome even with philanthropic spending such as CSR. Most of sustainability office positions are held by nonbusiness major professionals but mostly trained in sociology area. This is mainly because they are more tuned or educated what is important for society and comply with social norms. However, with limited resources, there is a logistical dilemma they face for which they are less trained. Using accounting and financial information along with measures for CSP and Managerial Efficiency, we document the importance of managerial education for future leaders using accounting and financial aspects of CSR activities.

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¹ Unlike CSR, which refers to a firm’s programs or investment regarding social issues, CSP represents the overall quality of such CSR-related investments as judged by a third-party rating agency or organization in lieu of stakeholders’ assessments, because each stakeholder has a limit to accessing and evaluating the full range of CSR activities. In addition, in contrast to CSR’s nature as a onetime commitment, CSP is cumulative and composed of continual CSR investment. ² Demerjian, P., B. Lev, & S. McVay. (2012). Quantifying managerial ability: A new measure and validity tests. Management Science, 58, 1229–1248.

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I. Current Status

1. Data
   1. Course-specific, using traditional data types.
   2. Ad hoc and “little” for problems addressed within the course, e.g. Accountants worksheet, Master Budget, Amortization schedules, etc.
   3. Leveraged research databases, used mainly in MAcc.: Mergent, Edgar, Compustat, CRSP, Audit Analytics
2. Analytics:
   1. Usually course-specific as needed to solve course-specific problems (not necessarily resulting in progression of skills across programs. Excel is main tool for analysis, with smattering of Access, and course-specific software (e.g. ACL software and its associated data).
   2. Little use and coordination of upstream course material in both Accounting (e.g. in financial accounting sequence ACC 2000->ACC 3100->CC 3110->ACC 4010) and in SBA-required courses, especially the 6-credit-hours of Probability and Statistics, and the Mathematics (Linear Algebra and Calculus). Exception: MIS 2000 (a MS Office/Workstation skills course, soon to be prereq. for ACC 2000).
   3. Limited skills in processing and analyzing non-traditional, perhaps “non-accounting” data, e.g. survey data, social media data, image and video data, and blockchain data.
   4. Limited skills in visualization and dashboard KPI’s.

II. Preliminary Envisioned D&A Environment for Accounting Programs

1. Data:
   1. ERP package or Industry data source (e.g. HCUP dats) with realistic simulated data possibly seeded with errors and anomalies, e.g., MS Dynamics 360 for hypothetical steel manufacturer. (Integration of ERP data with “cleaned” external data sources, including leveraging research databases, and identifying, obtaining, cleaning and processing non-traditional data.
   2. Relational, non-relational, non-traditional data modeled using MS BI Desktop or equivalent Excel capabilities, e.g. Get & Transform, Power Query, Power Pivot, and Visualization tools.
   3. Admin and maintenance issues, faculty training, course coordination issues for above.
2. Analytics:
   
   1. Excel (See II.a).(3) above), Excel Plug-ins, SAS, R
   2. Simulation, e.g. @Risk
   3. Visualization and Dashboard “reporting”, e.g. Tableau
   4. Identify and coordinate a designed progression of skills sets

III. Advise and Support

1. Public Accounting Firms training approaches to these issues
2. Corporate/Managerial approach to these issues
3. Database acquisition, administration and maintenance thereof

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In brief:
Drones and robots are augmenting, assisting, and in some cases, replacing human workers in almost every industry. The common assumption that drones and robots threaten primarily manual human tasks is not entirely correct – although these types of tasks are often the initial target for mechanical automation, more white collar routine jobs are now facing robotic disruption. For example, robots are now augmenting and even replacing human financial analysts at certain money management firms. It is time to discuss this highly probable robotic enhancement to our profession, to visualize the Dronnovation of accounting….

The accounting and auditing profession could soon become fun, appealing to millennials and innovative accountants alike, all due to drones (non-fixed wing Unmanned Ariel Vehicles) and robots (mechanical or software automation of processes). Like many professions, the fields of accounting and auditing as they are currently being practiced stand to soon be disrupted by recent innovations in drones and robotics (Deloitte 2015). Computers have already become ubiquitous in business, and in the future drones and robots of all kinds will too.¹ Soon there will be the Dronnovation² of accounting.

What is the Dronnovation of accounting? Quite simply, the application and evolution of the most recent innovations of drones and robotics in the domains of accounting and auditing. The innovation of drones and robots in accounting = Dronnovation³. Dronnovation consists of potentially three aspects - the drone, the mechanical robot, and the software robot (or bot), or two aspects – a robotic drone and the software bot. The goal of Dronnovation is not to replace the accountant, but to find ways that drones and robots can assist and support the accountant (Davenport and Kirby 2016a, 2016b). Drones are better at inspecting, observing, and monitoring than humans and robots are better at crunching numbers, lifting heavy objects, and working tirelessly 24/7 (Rus 2015; Simonite 2016). Ultimately, with Dronnovation the automated routine data collection procedures and data analysis applications converge in a cloud based real time monitoring and auditing system that is supervised and utilized by the accountant who will focus on higher risk judgmental tasks.

Drones

Software Robots (bots)
Software robots (bots), or robotic process automatons, are already being utilized by many business industries. According to the Deloitte (2015) survey of global business leaders⁴, automation is a top priority now. Executives anticipate that automation could deliver value for clerical and spreadsheet processes that are repetitive and rules based. Many transactional processes, data manipulation, and data analysis tasks can be automated by bots. According to the Deloitte study, 91% of the executives anticipate that accounts payable transactions will be automated, followed by 55% for travel and expense, 36% for fixed assets, 27% for general ledger, 18% for financial reporting, and 9% for both payroll and payment cards. In fact, most of the anticipated areas for future automation exist in accounting, where robotic processes could reduce costs and improve the quality of routine tasks. In this survey, accountants are envisioned to be managing and monitoring the bots, and examining exceptions that are outlier events using judgment in higher risk decision situations. The accountant will be focusing on those transactions that require nuanced human analysis and not the routine high volume transactions. Although bots are expected to improve the efficiency, timing, accuracy, and consistency of many data accounting processes, automation benefits from mechanical robots and small drones are also highly feasible. Although the PwC study focuses primarily on bots, the physical or mechanical aspect of accounting and auditing should not be ignored either. Drones and robots could be the accounting digital assistants of the near future, completing the more predictable and mundane accounting tasks, both physical and mental. What follows is a broad discussion of the future of accounting, transformed by an integration of drones and robotics - Dronnovation.

The three steps towards the Dronnovation of Accounting
Research and practice suggest that automation of a manual process should be undertaken incrementally (Alles at al 2008, Appelbaum and Nehmer 2017). The optimal process for technology use has been suggested to be one of augmentation – “starting with what humans do today and figuring out how that work could be deepened rather than diminished by a greater use of machines” (Davenport and Kirby, June 2015). This integration approach to automation may already be observed in the accounting profession with personal income tax filing and reporting (Dhar 2017). Fifty years ago preprinted tax returns were filled in manually by typewriter after the numbers were totaled by hand or calculator. This was followed with the use of basic spreadsheets for calculations, but the reports themselves were still completed manually. Then followed initial offerings by commercial software providers, minus electronic filing. Then filing became electronic, offered in the software and eventually directly with the IRS. As the technology replaced more of the manual tasks for individual and CPA filers, tax preparation services were hired mainly for more complex returns. Now less complex returns may be handled by Artificial Intelligence (AI) data robots (Dhar 2017). In fact, recently a major tax filing service provider announced that it would be preparing and filing returns with an AI application. However, less predictable personal and business returns still require nuanced human judgment (Davenport and Kirby, June 2015). As seen with tax services, the integration and eventual automation of manual and routine thought processes in a profession entails several steps, and is illustrated here:

Figure 1: the integration steps towards automation of a manual tasks (adopted from Davenport and Kirby 2015)
Integration of manually directed automation tools to assist the work task	⇒	Augmentation of the work task with semi-automated tools	⇒	Work task is heavily automated, with human monitoring and analysis of the resulting big data

The accounting profession, with its requirements for inventory validation, transactions and events monitoring, and asset
evaluation, which can be physically challenging tasks in some environments and circumstances, stands on the brink of
drone and robot augmentation. Once the profession begins utilizing drones and robots, the possibilities are endless: drones
and robots can start as a solution for specific problems, and evolve to sophisticated information collectors as virtual
accounting assistants. The Dronnovation of accounting is envisioned as follows, with inventory and asset observation
serving as illustrations:

Figure 2: The Dronnovation of Accounting
First Phase: The accounting drone extension		Second Phase: The Botmentation of Accounting		Third Pase: The Dronnovation of Accounting

¹ In the article “The Robots are Coming”, Foreign Affairs July/August 2105 issue, on page 15 author Daniela Rus states “Computers have already achieved ubiquity in human society. In the future, robots will too.”
² This is a term created by the authors
³ This article focuses primarily on drones but includes some discussion of robotics. Deloitte has issued an informative discussion of robotics in their 2015 white paper “The Robots are Coming.”
⁴ See “The Robots are Coming”, released by Deloitte in 2015.

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I. Dimensions of Risk Issues and Big Data Healthcare

1. Patient level: temporal from small one-off incident to episodic to chronic to W2T
2. Healthcare Providers level: from fee-for-service to bundled payments to capitation
3. 3rd Party Payer level, including government (e.g. CMS), risk-sharing (e.g. ACO’s)
4. System level: sustainability, continuum from single paper to “market-based” solutions

II. Examples of our Research

1. (with Professor Vijayan Sugumaran)
   
   Use of Technology in Remote Monitoring and Pain Management for Patients with Sickle Cell Disease
   Joseph Callaghan, Vijayan Sugumaran
   
   
   • Sickle cell disease (SCD) is a chronic genetic disease that affects, in the United States, Primarily African Americans
   • Self-care management is an important part of living with any chronic illness
   • Recognizing the cues to an evolving SCD-related acute paid episode (i.e. a VOC event) and responding appropriately is important
   • Information technology may facilitate self-care management, improve outcomes and reduce costs associated with the treatment of SCD
   • Research Objective - Examine the use of Patient-Reported Outcomes (ePRO) and Actigraphy (AG) devices and their impact on SCD patient behavior, outcomes and costs
     
     • First Phase: Gather information from both devices to discover possible associations between measures gathered and subsequent VOc events requiring traditional treatments
     • Second Phase: Intervene using telemedicine techniques to treat patients earlier or when indicated facilitate traditional treatment modes
2. “Machine Learning of Treatment/Billing Patterns Using HCUP Data.” (with Professor Liang Fu)
   1. HCUP Data (on rent currently), ICD codes > Procedure codes > Risk-adjusted APR-DRG codes > Billing (under different regimes)
   2. Statistically fit then apply to hold-out data and system for updating “model” based on continually provided forecast errors, i.e. machine learning.