Gender and DSS design: the research implications. - Philip L. Powell; Johnnie E. V. Johnson (Decis. Support Syst., 1995)

Exploring Decision Makers' Use of Price Information in a Speculative Market. - Johnnie E. V. Johnson; Owen Jones; Leilei Tang (Manag. Sci., 2006)

Identifying winners of competitive events: A SVM-based classification model for horserace prediction. - Stefan Lessmann; Ming-Chien Sung; Johnnie E. V. Johnson (Eur. J. Oper. Res., 2009)

Towards a methodology for measuring the true degree of efficiency in a speculative market. - Stefan Lessmann; Ming-Chien Sung; Johnnie E. V. Johnson (J. Oper. Res. Soc., 2011)

A new methodology for generating and combining statistical forecasting models to enhance competitive event prediction. - Stefan Lessmann; Ming-Chien Sung; Johnnie E. V. Johnson; Tiejun Ma (Eur. J. Oper. Res., 2012)

Time is money: Costing the impact of duration misperception in market prices. - Tiejun Ma; Leilei Tang; Frank McGroarty; Ming-Chien Sung; Johnnie E. V. Johnson (Eur. J. Oper. Res., 2016)

Probabilistic forecasting with discrete choice models: Evaluating predictions with pseudo-coefficients of determination. - Ming-Chien Sung; David C. J. McDonald; Johnnie E. V. Johnson (Eur. J. Oper. Res., 2016)

Bridging the divide in financial market forecasting: machine learners vs. financial economists. - Ming-Wei Hsu; Stefan Lessmann; Ming-Chien Sung; Tiejun Ma; Johnnie E. V. Johnson (Expert Syst. Appl., 2016)

It takes all sorts: A heterogeneous agent explanation for prediction market mispricing. - Valerio Restocchi; Frank McGroarty; Enrico H. Gerding; Johnnie E. V. Johnson (Eur. J. Oper. Res., 2018)

To what extent can new web-based technology improve forecasts? Assessing the economic value of information derived from Virtual Globes and its rate of diffusion in a financial market. - Lawrence Green; Ming-Chien Sung; Tiejun Ma; Johnnie E. V. Johnson (Eur. J. Oper. Res., 2019)

Improving prediction market forecasts by detecting and correcting possible over-reaction to price movements. - Ming-Chien Sung; David C. J. McDonald; Johnnie E. V. Johnson; Chung-Ching Tai; Eng-Tuck Cheah (Eur. J. Oper. Res., 2019)

Can deep learning predict risky retail investors? A case study in financial risk behavior forecasting. - Alisa Kim; Yaodong Yang 001; Stefan Lessmann; Tiejun Ma; Ming-Chien Sung; Johnnie E. V. Johnson (Eur. J. Oper. Res., 2020)

Comparing the effectiveness of deep feedforward neural networks and shallow architectures for predicting stock price indices. - Larry Olanrewaju Orimoloye; Ming-Chien Sung; Tiejun Ma; Johnnie E. V. Johnson (Expert Syst. Appl., 2020)

Are the least successful traders those most likely to exit the market? A survival analysis contribution to the efficient market debate. - Tiejun Ma; P. A. F. Fraser-Mackenzie; Ming-Chien Sung; A. P. Kansara; Johnnie E. V. Johnson (Eur. J. Oper. Res., 2022)

Turning the heat on financial decisions: Examining the role temperature plays in the incidence of bias in a time-limited financial market. - Luis Felipe Costa Sperb; Ming-Chien Sung; Tiejun Ma; Johnnie E. V. Johnson (Eur. J. Oper. Res., 2022)