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The paper aims to explore the life and contributions of one of the most influential management scholars (Herbert A. Simon), who is known as the founder and contributor to many scientific fields. Simon's interdisciplinary approach in conducting his research in management has made him a significant figure in many disciplines.

The paper is of a qualitative nature, and information is collected from the books and articles that are written by Simon as well as those who have been familiar with his work. This paper concentrates on Simon's contribution to the decision‐making theory and, more specifically, his insights into the process of decision making in real world situations. It explores the tenets of the classical and neoclassical approach to decision making and argues that because of Simon's work, attention was diverted from concentration on studying the organizational structure to the behavior of the decision makers during the process of making decisions. This new orientation brought more attention to the behavioral approach in studying decision making in organizations. Special attention is given to Simon's “bounded rationality” model and its relation to the process of decision making. This paper also deals with Simon's view on the role of intuition in decision making and explores the practicality of using his model in the real world.

Simon opened up a new world of scientific inquiry that its main focus is on the development of the most effective and realistic model for the decision makers to predict future outcomes.

The paper only concentrates on the core contribution of Herbert Simon's work on the decision‐making process. It does not indulge itself in Simon's related work in other disciplines such as computer science and artificial intelligence. In addition, this paper does not deal with the new developments in the theories of decision making. Future research could concentrate on the new discoveries concerning the ability of humans to construct thinking machines in order to improve productivity in organizations.

The paper examines the productive life of Herbert Simon and develops a realistic portrait of his core contributions to humanity (decision making). It involves the reader with the intricacies of the decision making process as it is examined and studied by Simon.

The purpose of this paper is to use Group Method of Data Handling (GMDH)-type artificial neural network to model the affecting factors of housing price in Isfahan city housing market.

This paper presents an accurate model based on GMDH approach to describing connection between housing price and considered affecting factors in case study of Isfahan city based on trusted data that have been collected from 1995 to 2017 for every six months. The accuracy of the model has been evaluated by mean absolute percentage error (MAPE), root mean square error (RMSE) and mean absolute error (MAE) in this case.

Due to the obtained value of MAPE, RMSE and MAE and also their interpretation, accuracy of modelling the factors affecting housing price in Isfahan city housing market using GMDH-type artificial neural network that has been conducted in this paper, is acceptable.

Due to limitation of reliable data availability about affecting factors, selected period is from 1995 to 2017. Accessing to longer periods of reliable data can improve the accuracy of the model.

The key point of this research is reaching to a mathematical formula that accurately shows the relationships between housing price in Isfahan city and effective factors. The simplified formula can help users to use it easily for analysing and describing the status of housing market in Isfahan city of Iran.

An accurate predictive model for forecasting urban housing price in Isfahan can be useful for sellers and owners to take more appropriate actions about housing supplying. Also, it can help urban housing planners and policymakers in managing of the housing market and preventing an urban housing crisis in Isfahan. The purpose of this paper is forecasting housing price in Isfahan city of Iran until 2022 using group method of data handling (GMDH).

This paper presents an accurate predictive model by applying the GMDH algorithm by using GMDH-Shell software for forecasting housing price in municipal boroughs of Isfahan city till the second half of 2022 based on creating time series and existing data. Alongside housing price, some other affecting factors have been also considered to control the forecasting process and make it more accurate. Furthermore, this research shows the housing price changes of boroughs on map using ArcMap.

Based on forecasting results, the housing price will increase at all boroughs of Isfahan till second half of the year 2022. Amongst them, Borough 15 will have the highest percentage of the price increasing (28.27%) to year 2022 and Borough 6 will have the lowest percentage of the price increasing (8.34%) to the year 2022. About ranking of the boroughs in terms of housing price, Borough number 6 and 3 will keep their current position at the top and Borough number 15 will stay at the bottom.

In this research, just few factors have been selected alongside housing price to control the forecasting process owing to limitation of reliable data availability about affecting factors.

The most remarkable point of this paper is reaching to a mathematical formula that can accurately forecast housing price in Isfahan city which has been rarely investigated in former studies, especially in simplified form. The technique used in this paper to forecast housing price in Isfahan city of Iran can be useful for other cities too.