Abstract— The combination of business forecasting, Top Management Team (TMT) and Fuzzy Inference System is rarely seen in the literature. Drawing on the Upper-Echelon perspective, we investigated the power of Top Management Team (TMT) composition to forecast firm performance. A Multi Input – Multi Output Adaptive Neuro-Fuzzy Inference System (ANFIS) approach was used in two dimensions, Cross-section and Time Series forecasting. Six input performance enablers were used to forecast a multifaceted firm performance. Two stage analysis was applied, and the results provide empirical evidence of the power of TMT to forecast the firm’s performance. This study represents a promising new way for future extension in this field currently understudied, including the possibility of introducing a firm’s pre-defined bins or categories classification methods rather than an exact figure forecasting. Also, it is suggested that firm’s performance forecasting should be obtained from one region as opposite to multiple regions. This may reduce errors associated with disparities between different regions in terms of overall economic context and TMT composition governance.
— ANFIS, Top management team, firm performance, forecasting.
Yousif I. Alhosani is with the Engineering Management and Innovation, University of Sharjah and École de technologie supérieure, UAE (e-mail: firstname.lastname@example.org).
Constantine J. Katsanis is with Construction Engineering Department, École de technologie supérieure, Montreal, Canada (e-mail: Constantine.Katsanis@etsmtl.ca).
Sabah Alkass is with the College of Engineering, United Arab Emirates University, Al Ain, UAE (e-mail: email@example.com).
Cite: Yousif I. Alhosani, Constantine J. Katsanis, and Sabah Alkass, " Predicting Firm Performance and the Role of Top Management Team (TMT): A Fuzzy Inference Approach," International Journal of Innovation, Management and Technology vol. 8, no. 2, pp. 144-150, 2017.