Associate Editor: Kai R. Larsen

University of Colorado, Boulder

Term: January 1, 2021 – December 31, 2022

Research Interests

I am a design science researcher using Natural Language Processing and Machine Learning to solve methodological and information overload problems faced by researchers in the behavioral sciences. For example, I create search engines, taxonomies, ontologies, and other tools that improve our ability to integrate and extend behavioral knowledge.

My current interests include:

  • psychometric constructs; what they are, how their operationalization drives correlations and research conclusions, and how we can use machine learning to shortcut the psychometric process
  • literature review and meta-analysis methodological innovations
  • ontologies, taxonomies, and evaluations of semantic spaces and document collections
  • research validities and their use in quantitative and qualitative research as well as design science

Methodological interests and qualifications

In addition to design science work, I am comfortable managing manuscripts that develop methodological innovations blending machine learning and traditional quantitative and qualitative methods, especially as focus moves from hypothesis testing to evaluating the validity of models and methods. Empirically, my expertise resides at the individual level of analysis rather than at the industry or market levels and associated econometric approaches.

Personal preferences in editing and reviewing:

  • I like research relevant to the IS discipline, but that is also relevant for one or more additional fields. Research that develops methodological innovations is likely to perk my interest
  • I like papers that display creative effort in validating the steps of a research process
  • I do not believe that employing the latest techniques in deep learning neural networks necessarily means that an article is novel or exciting to an IS audience, but may be interested if such algorithms are employed in contexts not accessible to the traditional machine learning algorithms, and yield substantial behavioral implications
  • I may request access to data to myself validate surprising results