Decision Making Process - Essay Example

Decision Making Process The early economic theory was founded on an old psychological model describing individual behavior. The human conduct was thought to be the result of a decision making process in which the costs and benefits of choices are weighted to maximize utility. However, several economists in that era questioned the plausibility of this theorem. In fact viner (1925, 373-374 as cited in Camerer, Loewenstein & Prelec 2003 ) stated that: “Human behavior, in general, and presumably, therefore, also in the market place, is not under the constant and detailed guidance of careful and accurate hedonic calculations, but is the product of an unstable and unrational complex of reflex actions, impulses, instincts, habits, customs, fashions and hysteria.” The Inability to objectively measure utility clearly indicated that it cannot be independently used to predict behavior and decision outcomes. The realization of this fact led economists to abandon their old ideas. Jevons comments on the issue revealed his hesitation to believe that the human heart’s feelings may ever be measured by man. In his view, “it is from the quantitative effects of the feelings that we must estimate their comparative amount” (jevons, as cited in Camerer, Loewenstein & Prelec 2003). Economists established the importance of feelings in behavior prediction. They understood that feelings can only be assessed from behavior and realized the importance and need for direct measurement. Positing immeasurable feelings was an intermediate step. As soon as ordinal utility and revealed preference concepts were introduced in the 1940s, that redundant step was dismissed. While assuming a consistent behavior to avoid circularity, the revealed preference theory indicates that observed choices and unobserved preferences are similar. Thus, the theory becomes falsifiable as someone who prefers coke over Pepsi should not prefer to drink Pepsi when coke is available. Economists continued to avoid the messy reality underlying the utility theory by following the simple root offered by the ordinal utility and revealed preferences theories while cognitive details continued to be ignored in all later developed extensions, such as the expected, discounted and subjective expected utility and Bayesian updating. Economists maneuvered away from direct feelings measurement. Instead, they developed different mathematical models and techniques to help understand the decision making process. The advent of neuroscience changed everything and now, the latest technological developments are promising direct feelings and thoughts measurements. Latest findings in this field are now changing the scientific view of reality. New theories are emerging while the older concepts are being called into question. (Camerer, Loewenstein & Prelec 2003) Defining Neuroeconomics Paul J. Zak, of the Center for Neuroeconomics Studies, Claremont Graduate University, defines Neuroeconomics as “an emerging transdisciplinary field that uses neuroscientific measurement techniques to identify the neural substrates associated with economic decisions.” (zak). In this definition, the word economic is not restricted to financial matters but should be understood as broadly as possible to mean any human or animal decision process involving alternatives evaluation. One possible non-human classical example narrated by Paul was the ‘optimal foraging’ where an animal, for instance, elect to exert energy and move from his current location, characterized by good food quality and quantity, to another where the quality and quantity of food are not guaranteed. The human example narrated by Paul describes the decision making process involved when a man is to choose between a $100,000 per year job offer at Goldman Sachs with limited pay increase and advancement and a $40 000 per year job at a smaller company with good chances of pay increase and advancement but at the risk of being fired if not successful. As noted by Paul, Both the human and animal example can be expressed mathematically in terms of a constrained optimization problem. In the human case, one of the predictions established via the mathematical process indicates that the “safe” Goldman Sachs job will be elected by a person who is more risk adverse (Zak 2004). “Neuroeconomics is a natural extension of bioeconomics” (Hirshleifer 1985; Gheslin & Landa 1999; Hirshleifer &Zak 2004 act in Zak 2004) as the bioeconomics research programme developed human behavior prediction models on the bases of evolutionary biology. Behavioral economics, in which the human decision making process is modeled using cognitive psychology, is also considered to be a second ancestor of Neuroeconomics. (Camerer 2003 as cited in zak 2004). While bioeconomics and behavioral economics were focused on the causes of behavior and the effect of evolved psychologies on decision making respectively, Neuroeconomics research is focused “to discover proximate causes of choice behavior as they provide the most leverage when seeking to affect behavior through policy” (Zak 2004). As noted earlier, this field is not restricted to studying human behavior, in fact, Paul notes that the first paper of Neuroeconomics published in 1999 by Michael Platt and Paul Glimcher studied the decision making process of rhesus monkeys using an economic approach. He also notes the tremendous advantages offered by Neuroeconomics both to the ‘neuro’ and in ‘econ’ sides. Greg Berns of Emory University organized the first plenary meeting of Neuroeconomics in autumn 2003. The meeting was attended by professionals in neuroscience, economics and medicine, thus indicating the broad range of the discipline and its clinical applications (Zak 2004). Neuroeconomics research is currently being conducted in two main categories. The first is concerned with identifying the neural processes affecting decision making in cases where the standard economic model is appropriate, while the second is researching the anomalies or the cases that cannot be predicted by the standard model. Studies within the second category lead to the development of several new alternative models with different behavioral assumptions. The new models “predict decisions equally well and therefore the ‘true’ sources of behavior are unknown” (Camerer 2003 as cited in Zak 2004). Paul indicated that the first category research is headed by M.Ds and neuroscientists while the second category research is conducted by economists. However, he also notes that the two categories are defusing since, nowadays, the research team of any category include professionals from all relevant disciplines. The utility theory, Risk and the decision making process Utility in economics is considered as a “numerical measure of the individual preference or subjective value for an object” (Lee 2005). Although it is quite difficult to compare different objects, the utility of each object should reflect individual preferences. By using this approach, parsimonious principles, such as that of utility maximization can be used to investigate individual choices. Risk, on the other hand can be defined for situations where the outcome of a decision is uncertain as “a spread from the mean in the objective value of possible outcome” (Lee 2005). Based on this definition, we may conclude that a choice with a fixed outcome is risk free while a lottery paying $14 to $16 is less risky than a lottery paying $10 or $12 dollars. Solutions to risky decision making problems can be provided using the expected utility theory according to which “the utility of a choice is determined by summing the utility of each possible outcome weighted by its probability” (Bernoulli 1954 as cited in Lee 2005). It is quite difficult to precisely measure the amount of risk associated with a particular item, however, objective measurement, such as money, provides the necessary means to identify different choices. However, when the utility of a particular decision is proportional to its objective value, risk does not affect utility. This is an example of a risk-neutral decision making process and clearly such a process is indifferent to any combination of possible outcomes provided that the mean is maintained constant. In reality, humans and animals seek or avoid risk depending on individual preferences. Thus, the linear utility function does not reflect actual behavior. The relationship between the shape of the utility function and individual risk preference and acknowledged by Daniel Bernoulli in his paper published in 1738 (lee 2005). Bernoulli suggested the use of logarithmic function instead of the traditional linear function. This was inline with the common idea that a $100 would mean more to a middle class than to a millionaire. “Such observations have led to more complex shapes of utility functions4 and other elaborations of utility theory” (Friedman& Savage as cited in lee 2005). The observations also indicated that whenever potential losses are involved, both humans and animals tend to be risk-prone (Kahneman & Tversky 1979, Marsh& Kacelink 2002 as cited in Lee 2005) while risk adverse when potential gains are expected in case of humans or when their energy meets the daily metabolic requirement in the animals case (Caraco 1990, as cited in Lee 2005) The somatic-marker hypothesis A broad range of animal and human behavioral choices can be perfectly explained using different economic and psychological theories of decision making. However, “the neural basis for this fundamental aspect of life is only beginning to be understood” (Naqvi, Shiv & Bechara 2006) Antonio Damasio’s observation of ventromedial prefrontal cortex (vmPFC) damaged patients lead the way into the modern era of neuroscience. Such patients were found lacking in their ability to make advantageous decisions. Thus, they tend to make choices that often result in financial, social, family and friends losses. In addition, the patients were found unable to react normally to different emotional situations. On the basis of his observations, Damasio introduced his hypothesis which explains that “the primary dysfunction of patients with vmPFC damage was an inability to use emotions to aid in decision making, particularly decision making in the personal, financial, and moral realms” (Naqvi, Shiv & Bechara 2006). The somatic marker hypothesis is founded on this very same tent: “emotions play a role in guiding decisions, especially in situations in which the outcome of one’s choices, in terms of reward and punishment, are uncertain” (Naqvi, Shiv & Bechara 2006) The hypothesis was tested further by Damasio and his colleagues. They focused on using lesion studies to address the decision making role played by vmPFC. Several other experiments revealed that patients suffering from amygdala injuries demonstrated a similar decision making pattern as those suffering from vmPFC damage. The amygdala lesions patients demonstrated their tendency to make disadvantageous decisions. However, unlike their damaged vmPFC counterparts, they had impaired SCRs to receiving reward and punishment. This finding suggests that patients with damaged amygdala were unable to register the emotional impact of reward and punishment, thus, were unable to anticpate both the reward and punishment caused by the same behaviors in the future (Naqvi, Shiv & Bechara 2006). The reward related functions of vmPFC were investigated by Edmund Rolls and his colleagues, publishing their results in 2004 revealing that “vmPFC neurons respond to the receipt of various primary reinforcers, such as palatable foods. Furthermore, they found that responses to specific primary reinforcers were reduced by manipulations that diminished their value, such as feeding someone a palatable food to satiety. In addition, they found that vmPFC neurons respond to conditioned stimuli that predict the delivery of primary reinforcers. Functional imaging studies have extended these findings to humans” (Naqvi, Shiv & Bechara 2006). In 2003, Gottfried, O’Doherty, & Dolan conducted a functional magnetic resonance study through which they established that the “responses of the vmPFC to conditioned stimuli that predict primary reinforcers are reduced by devaluation of the specific primary reinforcer that they predict” (Naqvi, Shiv & Bechara 2006). The findings of this suggested a role played by the vmPFC in the future rewards prediction process based on stored information from past experiences. The results of the mutual lesion and physiological studies in rodents conducted in 2003 by Schoenbaum, Setlow, Saddoris, and Gallagher indicated the the vmPFC ability to “encode predictive reward value’’ is dependent on the condition of the amygdala. These findings are perfectly consistent with all results established through human lessons studies. Broadly speaking, the somatic-marker hypothesis establishes the required basis for understanding the complicated human decision making capacity in the moral, financial and social realms. It clearly indicates how this human ability is related to the basic motivation and homeostatic processes shared by all mammalian species. Furthermore, the theory serves to explain several other goal oriented processes integrating motivation and effects. Scientific Tools The most popular neuroscientific tools used nowadays are the brain imaging systems. In most cases, imaging studies are carried out by comparing the pictures obtained for different people performing an experimental task and a control task. By taking the difference between the images obtained during the experimental task and those obtained during the control task, a picture of the areas activated during the experimental task can be constructed. The images can be taken using one, or a combination of three basic methods. The Electro-encephalogram (or EEG) is perhaps the oldest methods used to obtain brain images. In EEG, the electrical activity synchronized to stimulus events or behavioral responses is measured by attaching electrodes to the scalp of the subject. The second method, positron emission topography (PET) scanning is similar to EEG. Here, the blood flow in the brain is measured to assess the extent of neural activities. The third, latest and most popular method of brain imaging is the functional magnetic resonance imaging (fMRI). Unlike the two older methods, fMRI keeps track of the changes in blood oxygenation and thus the activities within the brain. (Camerer, Loewenstein & Prelec 2003) It is important to appreciate both the advantages and disadvantages of all the methods described above. In case of the EEG, It is the only method directly measuring neural activities within the brain. The temporal resolution is excellent however; the offered spatial resolution is weak while the measurements are restricted to the outer portion of the brain. Although the resolution offered by EEG has been improved, however, a major advantage from an economic perspective is its small size and mobility which may enable measurements at any given location and time. The resolution offered by the PET and fMRI are far much better than that obtained using the EEG, however, they both exhibit poor temporal resolution due to their indirect approach for neural activity measurement. (Camerer, Loewenstein & Prelec 2003) By using brain imaging, we can arrive at some basic view of brain activates that can describe the general conduct of a neuron circuit. Scientists however were interested to go further and measure the activity of a single neuron. To conduct such measurements, tiny electrodes are inserted inside the brain to measure individual neuron electrical activities. Although this procedure is strictly restricted to animal studies, research conducted in the past few years revealed important and striking findings particularly in areas of basic emotional and motivational processes common to both humans and animals. However, the areas of high level processes such as language and consciousness in humans are yet to be explored. (Camerer, Loewenstein & Prelec 2003) Another tool employed in brain function studies, which is also restricted to animals, is the electrical brain stimulation method. In 1954, psychologists James Olds and Peter Milner discovered that “rats would learn and execute novel behaviors if rewarded by brief pulses of electrical brain stimulation (EBS) to certain sites in the brain. Rats (and many other vertebrates, including humans) will work hard for EBS. For a big series of EBS pulses, rats will leap over hurdles, cross electrified grids, and forego their only daily opportunities to eat, drink, or mate.” (Olds and Milner 1954 as cited in Camerer, Loewenstein & Prelec 2003) “Animals also trade EBS off against smaller rewards in a sensible fashion – e.g., they demand more EBS to forego food when they are hungry. Unlike more naturalistic rewards, EBS does not satiate. And electrical brain stimulation at specific sites often elicits behaviors such as eating, drinking” (Mendelson 1967 as cited in Camerer, Loewenstein & Prelec 2003) “or copulation” (Caggiula and Hoebel 1966 as cited in Camerer, Loewenstein & Prelec 2003). Human oriented studies are not only restricted to healthy humans, in fact, the study of mental conditions and chronic mental diseases, degenerative illnesses and developmental disorders offers valuable information. In most cases, illnesses are connected to specific brain areas (Camerer, Loewenstein & Prelec 2003) in some illness cases; a progression localized path was discovered in the brain. For instance, the “basal ganglia” is first affected by Parkinson’s disease before the rest of the cortex. Thus, “The early symptoms of PD therefore provide clues about what the basal ganglia do” (Lieberman, 2000 as cited in Camerer, Loewenstein & Prelec 2003). Valuable information were obtained through studies on localized brain damaged caused by accidents and strokes. The Damasio observation, described earlier is one example. Lastly, it is worth mentioning the new transcranial magnetic stimulation method (TMS) in which a pulse magnetic field is used to halt brain function temporarily in specified regions. The subject’s cognitive and behaviors are monitored resulting from the pulse magnetic disruptions are providing information about the control points of different neural functions. Theoretically speaking, TMS provides direct brain function information whereas imaging studies provide purely associational evidence. This can be interpreted as an advantage for TMS over imaging, however, this techniques is currently restricted to the cortex and is considered controversial due to possible short and long term side effects. (Camerer, Loewenstein & Prelec 2003) Advantages and Limitations It is widely believed that the expected benefits of Neuroeconomics are tremendous. From an economic point of view, the research conducted in Neuroeconomics will facilitate the development of social and economic behavior prediction models based on neurobiological findings. Such models will help answer different traditionally fundamental questions such as: “why do two individuals faced with the same information and incentives make different choices? Why does the same individual sometimes make choices that are inconsistent? How much is choice behavior affected by childhood development, if at all?”(Hoeck 2006) So far, instead of using individual or temporal variations in choices, average choices are the focal point of attention used to answer different economic queries. The model building follows what-if pattern while motivation data are being neglected in the process. The application of the economic model to policy follows a similar pattern. Restriction of extreme behaviors is the common theme. The average behavior is neglected. The study of Neuroeconomics presents a better understanding of the interpersonal variations in choices which are fundamental to effective public policy establishment and implementation. From a corporate perspective the biggest advantage that may be offered by Neuroeconomics is related to the marketing sector. A full understanding of the human decision making process can be translated into a revolution in the marketing sector, more customers and ultimately more profit. Those are the origins of the controversy. Many scientists involved in Neroeconomics research believe that nothing is proved so far despite the tremendous amount of data available from different MRI and EEG studies. Currently, the brain remains a mysterious system. Nobody can tell for sure what exactly the brain is doing even when the activities are restricted to certain areas. Many people believe that Neroeconomics and micromarketing are over rated while many others disagree. In reaction to such concerns, many scientists say that the kind of control currently debated is simply fictional. Scientists explain that the currently underway imaging research is not aimed to control peoples mind and end the choice but rather to provide data to be analyzed in context. Nevertheless, all prospects and future visions are exciting. Irrespective of the controversy created over the subject, such brain imaging studies are promising to help cooperates better advertise their products and services. Neuroscience will help advertisers understand what kind of advertisement works, thus leading to cheaper and more objective advertisement campaigns. Although the field of neuroscience and neuromarketing are not exactly perfect, however, they are objective in their approach. The level of objectiveness reached particularly by neuromarketing cannot be claimed by any other traditional marketing method. For example, there are many aspects of human nature are hidden and cannot be understood through external observation. This is particularly apparent in studies conducted on focal groups when sometimes a strong personality within the group influences the overall opinion or when the participants lie to tell others what they want to hear. It is a fundamental truth that everybody lies! But no one can lie to an MRI. The truth will always be shown in the picture. However, the real problem becomes how well can it be seen. (Hoeck 2006) Conclusion Economics, psychology, and neuroscience are converging into a single, unified field aimed at providing a theory of human behavior.In this enterprise, the method and the standard set by neuroscience is the final goal: a reconstruction of the process and mechanism that goes from a stimulus presented to the subject to his final action in response. Economics provides the conceptual structure and the object of the analysis. In this emerging view, people are seen as deciding among options on the basis of the relative desirability of each option. This is true when they are in isolation as well as when they are in strategic (interaction with few persons) and market (interaction with a large number) environments” (Glimcher and Rustichini n.d). Several researches on the subject describe the realization of desirability as an actual neurological signal generated with the brain. This means that, the desirability of each object is calculated within the brain framework. Thanks to the latest technological advancements, the means to measure and test this brain activity are now available. Works cited Camerer Colin, Loewenstein George, Prelec Drazen (2003) “Neuroeconomics: How neuroscience can inform economics”, Center for Advanced Study in Behavioral Sciences. Glimcher W. Paul (2003) “THE NEUROBIOLOGY OF VISUAL-SACCADIC DECISIONMAKING” Glimcher W. Paul & Rustichini Aldo (n.d) “Neuroeconomics: The Consilience of Brain and Decision” Hoeck E. Marcia (2006) “Neuromarketing- a special report” , Hoeck Associates, Inc. Lee Daeyeol (2005) “Neuroeconomics: making risky choices in the brain” Nature Publishing Group Naqvi Nasir, Shiv Baba & Bechara Antoine (2006) “The Role of Emotion in Decision Making A Cognitive Neuroscience Perspective” Association for Psychological Science, Vol 15 Viner, J. (1925) "The utility concept in value theory and its critics." Journal of Political Economy, 33, pp. 369-387. Zak J. Paul (2004) “Neuroeconomics”, The royal society Read More