Decision making

Decision making



Decision making

Introduction

A great number of studies on human decision-making and judgment have been made in the field of social science, and a variety of methodologies have been researched. Understanding the human decision-making process and the modelling of the decision-making process is one of the goals of this discipline. Studies on decision-making can be classified into two categories: the study of decision modelling and the study of decision process tracing. Decision modelling studies the human decision-making mechanism and tries to build models that predict human decisions. (O'Connor, W. Remus and K. Lim, 2005, 76-89)

This field has been researched under the name of expert systems in the discipline of management, and the findings are abundant. Examples of findings include the development of new algorithms for building decision-making models and the development of methodologies for a knowledge base. In the past, studies were focused on modelling that resembled expert decisions and judgment. However, using enormous amounts of real data, recent studies have rigorously investigated the modelling of rules and associations. The application of these results has been expanded to a variety of areas, such as finance (e.g., bankruptcy prediction and stock price index prediction), marketing, account auditing, credit rating, and venture investment decision-making, (O'Connor, W. Remus and K. Lim, 2005, 76-89)

Decision process tracing, the other paradigm of study for human decision-making, focuses on the process of judgment and decision-making. To measure the predictive validity of human judgment, this research has introduced various methods for the analysis of the decision-making process these methods include probability scoring rules, log transformation, and the lens model. In probability scoring rules, mean probability scores (MPS) are viewed as efficient tools for measuring the level of uncertainty Einhorn and suggested log transformation to classify types of human decision strategies. The lens model, proposed by Brunswick and developed by Tucker, describes decision-making behaviour in terms of linearity and non-linearity. This model also provides the tools to measure the predictive validity of the linear and non-linear parts of decision-making behaviour. The effectiveness of the lens model has been verified by various empirical studies. (O'Connor, W. Remus and K. Lim, 2005, 76-89)

Literature review

Decision process tracing

The analytical framework needed to understand the human decision-making process was borrowed from studies on human judgment in the cognitive psychology discipline. The decision-making process is a major branch of decision-making studies. Finding the key factors affecting the decision-making process has been a core research topic of previous studies. As a consequence of this research, types and characteristics of decision-making behaviour and measuring methods and/or models have been developed For instance, mean probability scores (MPS) were considered a useful method to measure predictive accuracy . MPS is a function of squares of the deviation score between predicted values and actual outcome values

The decision-making model is mainly applied to classification and/or prediction problems. Most classification researchers have used hit ratio for the performance evaluation criterion. They have also used statistical models, such as regression analysis, discriminate analysis, and logistic analysis, which are based on linear ...