Shmueli, G., and O. Koppius, "Predictive Analytics in Information Systems Research", ERN Economics of Networks eJournal, vol. 2, issue 56, 2010.

Shmueli, G., and O. Koppius, "Predictive Analytics in Information Systems Research", MIS Quarterly, vol. 35, issue 3, pp. 553-572, 2011. MISQ-Predictive-Analytics-in-IS-Shmueli-Koppius -2011.pdf (303.74 KB)

Kenett, R. S., and G. Shmueli, "Rejoinder: Helping authors and reviewers ask the right questions: The InfoQ framework for reviewing applied research", Statistical Journal of the IAOS, vol. 32, issue 1, pp. 33-35, 2016.

Kenett, R. S., and G. Shmueli, "Rejoinder: On Information Quality", JRSS A, vol. 177, issue 1, pp. 35-38, 2014.

Kenett, R. S., and G. Shmueli, "A special issue on: Actual impact and future perspectives on stochastic modelling in business and industry", Applied Stochastic Models in Business and Industry, vol. 31, issue 1, pp. 1-2, 2015.

Shmueli, G., T. P. Minka, J. B. Kadane, S. Borle, and P. Boatwright, "A Useful Distribution for Fitting Discrete Data: Revival of the COM-Poisson", Journal of The Royal Statistical Society, Series C (Applied Statistics), vol. 54, issue 1, pp. 127-142, 2005. JRSS-COM-Poisson.pdf (278.49 KB)

Shmueli, G., and O. Koppius, "The Challenge of Prediction in Information Systems Research", Working Paper RHS 06-152: Smith School of Business, University of Maryland, 2009.

Minka, T. P., G. Shmueli, J. B. Kadane, S. Borle, and P. Boatwright, "Computing with the COM-Poisson Distribution", Technical Report #776: Dept. of Statistics, Carnegie Mellon University, 2003.

Kenett, R. S., and G. Shmueli, From Quality to Information Quality in Official Statistics: Indian School of Business, 04/2014.

Kenett, R. S., and G. Shmueli, "On Information Quality", Working Paper RHS 06-100: Smith School of Business, University of Maryland, 2011.

Shmueli, G., and O. Koppius, "Predictive Analytics in Information Systems Research", Working Paper RHS 06-138: Smith School of Business, University of Maryland, 2010.

Shmueli, G., T. P. Minka, J. B. Kadane, S. Borle, and P. Boatwright, "Using Computational and Mathematical Methods to Explore a New Distribution: The v-Poisson", Technical Report #740: Dept. of Statistics, Carnegie Mellon University, 2001.