Archive - October 2018
Events
News
October 10, 2018
Read Dr. Aziz Guergachi's article discussing "The Impacts of Entrepreneurship on Wealth Distribution" in the Journal of Statistical Physics (external link)
Abstract
Using mathematical statistical mechanics methods, this paper shows that decisions to heavily promote entrepreneurship beyond a certain threshold in a society would lead to an increase in the society’s Gini coefficient, and thus to more economic inequalities. More specifically, we show that, in a heterogeneous society made up of both entrepreneurs (Es) and ordinary agents (OAs), economic inequalities reach a minimum at an optimal ratio of ‘Es to OAs’. When dealing with a purely homogeneous society made up of entrepreneurs only or ordinary agents only, economic inequalities would decrease as trading activities intensify among the society’s agents. In particular, ideologies that consist in flattening the wealth/income of citizens (as it was recommended, for example, by communist regimes in the last century) to reduce economic inequalities through strict government interventions, may not lead to positive outcomes. We also show that introducing a little heterogeneity into a purely homogeneous society will help reduce economic inequalities in this society. Thus, a society that is composed of ordinary agents only will see its economic inequalities decrease if a number of entrepreneurs join this society. Vice-versa, a society of entrepreneurs only will have its inequalities reduced if some ordinary agents join this society and engage the pre-existing entrepreneurs in trading activities; one could think of southern San Francisco Bay Area, Silicon Valley, as a concrete example of such a situation. To encourage ordinary agents become entrepreneurs, governments could design and implement tax-incentive policies for their respective societies. While such tax-incentive policies would help increase the number of entrepreneurs in the targeted society, they would also have unintended consequences: the society’s middle class gets depleted at equilibrium, and the inequalities that result from implementing the aforementioned policies will be uniformly bigger than the ones that result from an equal tax redistribution policy. The paper concludes with a discussion section that raises a number of questions about socio-economic phenomena and explains how these phenomena can be accounted for using physics laws and principles.
October 17, 2018
This recent article published by Dr. Farid Shirazi in the International Journal of Information Management (external link) discusses a big data analytics model for customer churn prediction in the retiree segment.
Abstract
Undoubtedly, the change in consumers’ choices and expectations, stemming from the emerging technology and also significant availability of different products and services, created a highly competitive landscape in various customer service sectors, including the financial industry. Accordingly, the Canadian banking industry has also become highly competitive due to the threats and disruptions caused by not only direct competitors, but also new entrants to the market.
The primary objective of this paper is to construct a predictive churn model by utilizing big data, including the structured archival data, integrated with unstructured data from sources such as online web pages, the number of website visits and phone conversation logs, for the first time in the financial industry. It also examines the effect of different aspects of customers’ behavior on churning decisions. The Datameer big data analytics tool on the Hadoop platform and predictive techniques using the SAS business intelligence system were applied to study the client retirement journey path and to create a churn prediction model. By deploying the above systems, we were able to uncover a wealth of data and information associated with over 3 million customers’ records within the retiree segment of the target bank, from 2011 to 2015.