Suppose that this morning, when trying to stop the alarm, you accidentally dropped and shattered your beloved phone. After collecting the pieces of the phone (and yourself from the trauma), you realize that you now have to buy a new one. So, you head to the mall: in possession of all the information in the world, based on your preferences (after weighting all the important characteristics of the product), you choose the phone which maximizes your utility with respect to your budget constraint – your wallet. At least that is what the theory of consumer choice and rational decision theory suggest (in which an agent’s goal is to maximize their utility). While there are obvious advantages of this take on the decision theory, let’s see what a non-homo economicus does.
The first problem comes from lack of information. In the classical theory, all the choices are in a given pool, where the decision-maker can decide objectively, for the outcomes are known to them. Simon (1959) argues, however, that perception and cognition play a huge part in decisions. For instance, in different environments, we might perceive the same information in very different ways. Similarly, being savvy within the product category plays a huge role in decisions: maybe we are up-to-date with the new mobile phone trends, or perhaps you just gather information when you are actually planning on buying a new one. It may also be the case that your perceived knowledge can differ from objective knowledge (i.e. when you don’t know how lacking your knowledge really is).
In one of our previous blogs, we talked about the concept of “satisficing utility”; that is, we do not wish to maximize our utility, but rather we just want to keep ourselves “satisfied”. According to Simon, when one cannot reach their desired satisfaction, they turn to search behavior – trying to reach the desired point by searching for alternatives with greater levels of satisfaction.
A significant amount of research papers were dedicated to finding the “Holy Grail” of search behavior. A number of models were proposed, differing mainly in their perspective of the human decision-makers.
John D. Hey (1982) formulated some of the widely-known rules in search behavior. For example, he identified the reservation rule. It states that whenever the search for alternatives yields a price which is lower than some reservation price, it results in a sudden stop of the search, if the product requirements are met. However, there exists a number of rules that, after a number of searches, result in high prices (or to put it simply: after a bunch of unsuccessful search attempts), subjects just stop looking for alternatives and accept the most recent price. In other words – they give up. Perhaps, they realize that the cost of searching is greater than accepting a non-optimal price, or they just simply get tired of it.
Brucks (1985) found that the greater a-priori objective knowledge you have on the subject, the more effective you are in your search for new information. Based on their experimental method, they concluded that basic knowledge helps in prioritizing search for the relevant information, and subjects, who had previous experience, searched for less irrelevant alternatives than their counterparts. This supports Miyake and Norman (1979): “To ask a question, one must know enough to know what is not known”.
The following search behaviour model was designed by Punj and Staelin (1983), which describes the process of information search when buying a new car, Fig.1.
Based on the rational assumptions of this model, the outcome of the search behavior can be called effective when the cost savings from gaining information (e.g. finding lower-priced deals) outweigh the cost of searching (the latter can be interpreted as transaction costs).
Importantly, the search behavior can differ between fast-moving consumer goods and durable goods: indeed, it is not the same to buy an Apple iPhone, as opposed to just an apple. Some would argue that, when the potential risks of bad decisions are apparent, people want to take a safer route: when buying an iPhone, some people might search scrupulously for weeks. In contrast, buying a small item, like an apple, does not come with the same weight. In such a case, we might simply use heuristics to choose. For instance, last time the red ones were better than the greens, so I might just take a bunch of red apples – even though they are from a different producer, or even a completely different apple cultivar.
Regardless of the purchase at hand, whether it be a phone or an apple, search behaviour occurs in almost any of our decisions – it appears to be innate to humans and its existence is irrefutable.
Valence-Framing: Same Question, Different Answer
Mental Accounting: Our Cognitive Filters
References & Further readings
Girish N. Punj and Richard Staelin (1983): A Model of Consumer Information Search Behavior for New Automobiles. Journal of Consumer Research, Vol. 9, No. 4 (Mar., 1983), pp. 366-380
John D. Hey (1982): Search for Rules for Search. Journal of Economic Behavior & Organization Volume 3, Issue 1, March 1982, Pages 65-81
Merrie Brucks (1985): The effects of product class knwoledge on information search behavior. Journal of Consumer Research, Vol 12, No.1, pp. 1-16
Riitta Katila, Gautam Ahuja (2002): Something old, something new: a longitudinal study of search behavior and new product introduction. Academy of Management Journal Vol 45, No. 6, 1183-1194