Outstanding Dissertation Award

The SET Section periodically (usually annually) awards the SET Outstanding Dissertation Award. The award is to recognize outstanding dissertations in the fields of strategic and emerging technologies in the accounting discipline.

For the purposes of this award, Strategic and Emerging technologies include (among others):artificial intelligence (including cognitive computing, knowledge-based systems, neural networks, heuristic problem solving, expert systems, case-based reasoning, machine learning, natural language processing, intelligent databases, intelligent agents, and intelligent devices), information system security, image processing, communications technologies, wireless connectivity, the Internet of things, ERP systems, workflow technology, private networks, XBRL, XML, data mining, group technologies, continuous assurance services, big data, data analytics, text analytics, voice recognition, and interactive multimedia.

The winner of SET Outstanding Dissertation Award will be presented with a plaque at the Annual SET Section Business meeting, held at the American Accounting Association’s annual meeting.

An abstract of the winning dissertation will be published in the SET Newsletter and on the SETSection website.
An entry may be nominated either by the student who wrote the dissertation or by one or more members of their dissertation committee.
The entry cannot be simultaneously submitted for similar awards by other Sections of the AAA.
Submission requirements:

  • Dissertation topic dealing with strategic or emerging technologies in accounting.
  • Dissertation completed between January 1 and December 31 of the year preceding the award
  • Letter signed by the dissertation chairperson stating that the dissertation was completed and accepted by the degree granting institution during the above period
  • A nominating letter stating why the dissertation deserves special recognition
  • An extended abstract of the dissertation (in PDF format). The extended abstract should focus on the aim, motivation, and significance of the research; and include a summary of the methodology, statistical analysis (as appropriate), results, limitations, and future research questions.
  • The dissertation (in PDF format)

Call for Nominations for the 2016Award
Please send your nomination (as an attachment to an email) by 31 MARCH 2016 to the Chair of the committee for this award:
Professor Stewart Leech
University of Melbourne
Email: saleech@unimelb.edu.au

Members of the Dissertation Award Committee
Bachman Fulmer
Cal State Fullerton
Email: bachmanfulmer@outlook.com

Vasundhara Chakraborty
Monmouth University
Email: vasuchau@gmail.com

Previous winners of this award
(click on each name highlighted to see the abstract of their dissertation)

  • 2005 - Shirley Hunter, Murray State University, The impact of the Internet on the market valuation of emerging market firms: A longitudinal study, 1991--2001
  • 2006 - Mark Cecchini, University of Florida, "Quantifying the Risk of Financial Events Using Kernel Methods and Information Retrieval"
  • 2007 - Jia Wu, Rutgers University, "Continuous tests of details and analytical procedures in continuous auditing"
  • 2008 - MaciejPiechocki, Freiberg University of Technology, "XBRL Financial Reporting Supply Chain Architecture"
  • 2009 - Not given
  • 2010 - Frederik Gailly,Ghent University, "Operationalization of Business Ontologies: Representation, Formalization and Application"
  • 2011 - Dr.SunitaGoel, University at Albany, SUNY, "Qualitative Information in Annual Reports & the Detection of Corporate Fraud: A Natural Language Processing Perspective"
  • 2012 - Dr. Yong Bum Kim, Ramapo College - "Continuous Monitoring: Macro- and Micro-level Control"
  • 2013 - Danielle Lombardi, Rutgers University,"Using an expert system to de-bias auditor judgment: An experimental study."
  • 2014 - Jeff Reinking, University of Central Florida, "The Diffusion of Digital Dashboards: An Examination of Dashboard Utilization and the Managerial Decision Environment"
  • 2015 –Qi Liu,Rutgers University,“The Application of Exploratory Data Analysis in Auditing”