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Dr. Nicholas Danks

Associate Professor (School Office Trinity Business School)


 Composite Overfit Analysis Framework
 Computational Validity
 DAGifying SEM

Details Date
Track Chair and Scientific Advisory Board member at 2022 International Conference on Partial Least Squares Structural Equation Modeling at Babe"-Bolyai University, Faculty of Economics and Business Administration, Cluj-Napoca, Romania September 6 - 9, 2022
Track Chair at the 2022 International Conference on Service Science and Innovation (ICSSI 2022) at National Sun Yat-sen University, Kaohsiung, Taiwan. November 17 - 19, 2022
Education Track Chair at the Special Interest Group on Decision Sciences and Analytics Pre-ICIS workshop
Member of Scientific Advisory Board to the 2022 International Conference on Partial Least Squares Structural Equation Modeling
Language Skill Reading Skill Writing Skill Speaking
Afrikaans Fluent Fluent Fluent
Chinese Basic Basic Medium
English Fluent Fluent Fluent
Details Date From Date To
Reproducibility Team Member for the Informs Journal of Data Science 01/03/2022
Scientific Advisory Board Member for the 2022 International Conference on Partial Least Squares Structural Equation Modeling 01/08/2020
Member of Analytics Institute of Ireland 01/09/2021
Academy of Marketing (UK) 01/07/2022
Association for Information Systems (AIS) 01/07/2022
Miloš Fišar, Ben Greiner, Christoph Huber, Elena Katok, Ali I Ozkes, Management Science Reproducibility Collaboration, Reproducibility in Management Science, Management Science, 2024, Journal Article, PUBLISHED
Valdez, A., Kojan, L., Danks, N.P., and Ray, S., Structural Equation Modeling in HCI Research using SEMinR, CHI EA '23: Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, CHI Conference on Human Factors in Computing Systems 2023, Hamburg, April 2023, edited by ACM , (553), 2023, pp1 - 3, Conference Paper, PUBLISHED  DOI
Danks, N.P., Ray, S., Shmueli, G., The Composite Overfit Analysis Framework: Assessing the Out-of-sample Generalizability of Construct-based Models Using Predictive Deviance, Deviance Trees, and Unstable Paths, Management Science, 2023, Journal Article, ACCEPTED
Chaouali, W., Danks, N., Hey chatbot, why do you treat me like other people? The role of uniqueness neglect in human-chatbot interactions, Journal of Strategic Marketing, 2023, Journal Article, PUBLISHED  DOI
Marko Sarstedt, Nicholas P. Danks, Prediction in HRM research-A gap between rhetoric and reality, Human Resource Management Journal (UK), 2021, Journal Article, PUBLISHED  TARA - Full Text  URL
Danks, N.P., The Piggy in the Middle: The Role of Mediators in PLS-SEM-based Prediction, Data Base for Advances in Information Systems, 52, (SI), 2021, p24 - 42, Journal Article, PUBLISHED  TARA - Full Text  URL
George Franke, Marko Sarstedt, Nicholas P. Danks, Assessing measure congruence in nomological networks, Journal of Business research, 130, (June), 2021, p318 - 334, Journal Article, PUBLISHED  TARA - Full Text
Heyam Abdulrahman Al Moosa, Mohamed Mousa, Walid Chaouali, Samiha Mjahed Hammami, Harrison McKnight, Nicholas Patrick Danks, Using humanness and design aesthetics to choose the "best" type of trust: a study of mobile banking in France, International Journal of Retail & Distribution Management, 2021, Journal Article, PUBLISHED  TARA - Full Text
Ray, S., Danks, N.P., and Calero Valdez, A., 'SEMinR: Domain-specific language for building, estimating, and visualizing structural equation models in R', V2.3.1, CRAN, The Comprehensive R Archive Network, 2021, -, Software, PUBLISHED  TARA - Full Text  URL  URL  URL
Nicholas Danks, Soumya Ray, Validity and Reproducibility Of Computational Research: A Teaching Agenda, SIG-DSA, Hyderabad, India, 12/12/2020, 2020, Conference Paper, PRESENTED

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Hair, J.F., Hult, G.T.M., Ringle, C.M., Sarstedt, M., Danks, N.P., Ray, S., Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook, Germany, Springer , 2021, Book, PUBLISHED


Award Date
William R. Darden Award for Best Methodological Paper at the Academy of Marketing Science Annual Conference, Vancouver, Canada (2019) May 29 - 31, 2019
Best Methodological Paper Award at the 2022 International Conference on Partial Least Squares Structural Equation Modeling Sep 6 - 9, 2022
Trinity Business School Teaching Excellence Award 2023
Trinity Business School Teaching Excellence Award 2022
Trinity Business School Research Excellence Award 2022
Structural Equation Modeling (SEM) is now a dominant methodology in business and management, life sciences, and social science research - both in academic and industrial contexts. My primary research focus is on the rigorous and statistically correct use of SEM for scientific research. I am particularly interested in quantitative research methods and machine learning for explanatory models. To this end my work introduces predictive methodology to traditionally explanatory methods and finds opportunities for the intersection of these to supplement the scientific conclusions that can be drawn from research. To this end I generate new statistical methods, and refine existing methods in SEM (and in particular Partial Least Squares - PLS). My research therefore lies at the intersection of methodology and practice. In addition, I also research the use of computational statistics as a field and how these modern computational methods can be applied to solve imminent business and social challenges. This research is focused on ensuring that the progress in computational statistics is supported by the appropriate frameworks to ensure computational validity, reproducibility, and open access. I am a co-author and the primary maintainer of SEMinR, an open-source package for the R Statistical Environment for the estimation and evaluation of PLS path models. I publish in journals such as Managment Science (ABS 4*, FT50), Human Resource Management Journal (ABS4*), Decision Science (ABS3), Journal of Business Research (ABS3), and The Database for ACM (ABS2).