Nicholas Danks

王尼克


Contact Me:

nicholasdanks@iss.nthu.edu.tw

EDUCATION

PhD, Service Science, Institute of Service Science, National Tsing Hua University, Taiwan (current)

MBA, Business Administration, National Tsing Hua University, Taiwan

B. Com, Financial Accounting, University of South Africa, South Africa

RESEARCH INTEREST

  • Partial Least Squares Path Modeling (PLS-PM)

  • Predictive Methodology and Analytics

  • Programming

  • Technology Mediated Social Participation

  • Data Mining and Time Series Forecasting

Area of Interest: Marketing, Tourism & Hospitality, Statistical Methodology


Online Presence: ResearchGate

PUBLICATIONS

  1. Prediction-oriented model selection in partial least squares path modeling (Sharma, P., Sarstedt, M., Shmueli, G., Danks, N., Ray, S.) Decision Science Journal (Under Review)

  2. Predictions from PLS Models (Danks, N., Ray, S.). Book Chapter, Application of Partial Least Squares – Structural Equation Modeling (PLS-SEM) in Tourism and Hospitality Research, Emerald Publishing Group (In Press).

  3. Evaluating the Predictive Performance of Constructs in PLS Path Modeling (Danks, N., Ray, S., Shmueli, G.). Social Sciences Research Network Electronic Journal 2017. https://ssrn.com/abstract=3055222 or http://dx.doi.org/10.2139/ssrn.3055222

CONFERENCE PROCEEDINGS

  1. A Critical Review of PLS Path Modeling in Management Research and Ways Forward (Danks, N., Ray, S.). INFORMS 2018 International Meeting. Taipei, Taiwan.

  2. Evaluating the Predictive Performance of Constructs in PLS Path Modeling (Danks, N., Ray, S., Shmueli, G.). INFORMS 2018 International Meeting. Taipei, Taiwan.

  3. The Piggy in the Middle: The Role of Mediators in PLS Prediction (Danks, N., Ray, S., Shmueli, G.). 9th International Conference on PLS and Related Methods (PLS'17), Macau, China.

  4. Lost Gems: Predicting and Understanding Open-Source Module Abandonment (Ray, S., Danks, N., Chen, L.). AIS Special Interest Group on Open Research and Practice (SIGOPEN 2016). Dublin, Ireland.

  5. Visualizing and Analyzing Predictive PLS: A First Glimpse (Danks, N., Ray, S., Shmueli, G.). Taiwan Summer Workshop in Information Management (TSWIM 2016). Chiayi, Taiwan.

ONGOING PROJECTS

  1. Determining Predictive Validity and Accuracy of Composites in PLS Path Modeling

  2. SEMinR - Structural Equation Modeling estimation, simulation and prediction for both composite and common factor models using PLS Path Modeling

  3. Semiotics, causality and the use of conceptual modeling in academic literature

SOFTWARE DEVELOPMENT

  • SEMinR: Implementation of a Natural Syntax and Wrapper to combine functionality of PLS packages in R Statistical Environment and allow for easy model generation, evaluation and comparison.

GitHub CRAN

  • PLSpredict:Implementation of PLSpredict (Shmueli et al., 2016) in the R Statistical Environment (ongoing).

GitHub

AWARDS

    • Phi Tau Phi Academic Honor (2016)

    • IMBA Summa Cum Laude (2016)