Recent research in the fields of economics and psychology has begun to illuminate a strange pattern that initially seems to contradict economic theory. Paradoxically, it is now believed that individuals can have too much choice, and in modern Western society, this is often the case.
Richard Easterlin revealed evidence in 1974 that although income per person has climbed in the United States for almost a century, average reported happiness was uncorrelated. In fact, average reported happiness decreased for part of that time period. What could explain this phenomenon? We now have a greater variety of consumer goods and services to choose from than at any other time in human history. We have more wealth and more ability to take leisure time than our great grandparents had. We can walk into a grocery store and choose from hundreds of different salad dressings, hundreds of different cereals, hundreds of different cars with customizable features, etc. Why has this not increased our utility?
Microeconomic theory states that an economic agent will seek the bundle of two goods found at the theoretical point where that consumer’s indifference curve for those two goods is tangent to his/her budget constraint. The indifference curve is assumed to be a continuous function composed of an infinite set of bundles of those two goods in different proportions. In reality, a consumer cannot buy a fifth of an apple or 17% of a car. A consumer’s indifference curve for any two goods is actually composed of discrete points. The probability that the optimal tangency bundle exists is very low and the consumer will likely have to settle for a sub-optimal bundle that is on a lower utility curve than the optimal bundle. Theoretically, as the number of choices (bundles in the set) increases, the indifference curve becomes more continuous and the probability of the optimal bundle being available increases. Even if the optimal bundle is still not available, each additional bundle added may be closer to the optimal bundle than the next best alternative. If it is not closer, the consumer would simply choose the bundle that provides the highest utility level, which would be the same as before the addition of that last bundle. In this model the consumer is unharmed by increased choice.
Thus, this paper will look closely at a vast array of literature published in regards to what the authors have chosen to call the “choice overload” phenomenon. We’ll begin by looking at the crucial role of opportunity cost and the implications of it while decision making. It will reveal that opportunity cost is an essential piece of evidence in the debate about “too many choices”. The decision making process will have to be explored with the help of Brenner and Michalos, two giants in the growing field of “choice” research. We look into Brenner’s insights into the decision making process which he calls direct and derived evaluations—literally multiple levels of decisions stemming from one. The link between the surging opportunity costs consumers face with products and the decision making process is bridged with Michalos’ work on risk evaluations. Consumers or any decision makers have a certain level of risk for every decision they make—increasing as alternatives rise. He argues consumers will tend to make decisions with the status quo, and reduce the “perceived” risk as it’s shared with everyone else. Richard Thaler calls this the Endowment Effect, which leads to a discussion on whether people artificially reduce choices by following the “crowd” regardless of the options available. Further research into risk and choice overload leads us into a fascinating concept called Loss Aversion by Bernoulli (1976); People are more likely to protect their losses rather than pursue their gains. This concept puts choice overload in perspective—the less choice, the less opportunity cost and the more willingness to overlook particular gains brought about by increasing choices. Later the paper will focus on two different classes of decision makers, maximizers and satisficers. The former being the classical economics version of an ideal decision maker and the latter the realistic decision maker who chooses based on satisfaction—not evaluations of alternatives.
Finally, and most important question in this paper is whether people are happy with choices or not? Another paper published by Michalos (1981) looks specifically into the relationship between expectations, achievement and happiness. The overriding conclusion of his paper is that people with a high achievement-expectations gap, tend to be less happy. This paper will link this with the choice overload theory which says that more choices increase expectations, which may widen the achievement-expectations gap—making people less happy.
Opportunity Cost and the Decision Making Process
In classical economics, the theory of opportunity cost is foundational and started with John Stuart Mill in 1848 (Thornton, 2007)). Dr. Mark Thornton in his paper, Richard Cantillon and the Discovery of Opportunity Cost, outlines the historical evolution of opportunity cost in the field of economic thought. Every decision an individual makes involves some form of opportunity cost—the cost of forfeiting all reasonable alternatives. The opportunity cost is highest when the number of reasonable alternatives is great, which tends to be especially problematic for the modern day consumer.
Every consumer is bombarded with a number of different alternatives to products and services. As the visible number of alternatives increase for a specific product, while increasing competitive welfare for the consumer—it also produces a larger opportunity cost. The difficulty in making a choice is greater and whether the consumer appreciates it in regards to enhanced product quality is questionable. Although free market economics clearly endorses more competition to increase consumer welfare, the trade off between the negative psychological effects of opportunity cost are being researched. For example, if a consumer is choosing between two TVs, both being reasonable alternatives with competitive features, the opportunity cost is forfeiting the value of one TV. However, realistically a consumer is choosing between hundreds of TVs within a dozen stores, with different prices and different features—causing a much larger opportunity cost.
In a paper published in the Journal of Consumer Research, On Decisions that Lead to Decisions: Direct and Derived Evaluations of Preference, Lyle Brenner argues that the opportunity cost in decision making is broken down in a sequential pattern (Brenner, 2004). A direct evaluation is the first stage in the process, which is based on factors such as location, store, price, etc. The second stage is a derived evaluation, which is based on factors such as quality, options and future alternatives to the product. Thus a modern day consumer actually has an even larger opportunity cost than ever before—direct and derived alternatives (Brenner, 2004). For example, there isn’t a singular opportunity cost for the purchase of a TV, but a multidimensional one. There are direct evaluations of stores, locations and sales, and derived evaluations on options, future alternatives and quality. The emerging question is whether or not consumers follow this process outlined by Brenner or not? His research concludes that many consumers simply stop at direct evaluations when it comes to following the status quo—a group influenced decision. An individual decision, not based on group influence, was found to be derived (Brenner, 2004). However, many more decisions were found to be group influenced, thus more individuals preferred direct evaluations. This characteristic of the decision making process hinted at the fact that individuals preferred a less complex decision making process, even though a derived decision could mean a better quality product.
The implication of Brenner’s research follows suit with previous work done by Alex C. Michalos from the University of Guelph during the early 70s and 80s. In Michalos’ paper The Cost of Decision Making, he defines production costs, implementation costs and failure costs in the decision making process for all individuals. Production is the creation of the decision, implementation is the delivery of the decision and failure is the cost associated with making the “wrong” decision (Michalos, 1970). Michalos says the risk of “failure” is fixed, however production and implementation costs of decision making are variable—which makes them the most difficult part in the process. Thus, decision makers often try to “insure” their production and implementation decisions to reduce responsibility of failure costs. The costs involved in insuring their losses are called planning costs—where over-planning and under-planning are both equally detrimental to an individual (Michalos, 1970). Similarly to Brenner, those that under-plan may simply be following the status quo and spreading responsibility of loss, where-as those that over-plan risk an individual loss. Thus, consistent with Brenner, most people prefer the status quo decision making process as losses are perceived to be less. The only negative implication of under planning and receiving a successful result is the estimated value of success cost—where success will be shared with the status quo or group (Michalos, 1970). Thus, as research implies, many decisions are based on the risk of loss rather than the probability of gains.
Loss Aversion and Framing
The phrase “losses loom larger than gains” is a summary of basic behavioural decision making theory. The foundation of this idea was laid by Daniel Bernoulli in an essay published back in 1738. He formally developed the concept of risk aversion by offering test subjects lotteries or sure payments. He found that people are likely to take payments lower than the expected value of the lottery because they are risk averse. This tendency to choose certainty over uncertainty is fairly obvious. The psychological aversion to loss has become widely know and is used in both marketing strategies and incentive schemes.
Kahneman and Tversky (1983) described how someone can frame a problem as either a gain or a loss in order to produce a desired result. 132 undergraduate test subjects were asked to complete a questionnaire including the following:
Question 1. Would you accept a gamble that offers a 10% chance to win $95 and a 90% chance to lose $5?
Question 2. Would you pay $5 to participate in a lottery that offers a 10% chance to win $100 and a 90% chance to win nothing?
The two questions are essentially asking the same thing, but by framing the $5 as a cost rather than a potential loss, the effectiveness of the technique was revealed. 55 of the respondents (41.7%) had differing answers to these two questions. Of those respondents, 42 answered Question 1 negatively, and answered Question 2 positively.
Framing is such an effective tool that it is used whenever possible. In an example used by Thaler (1980), lobbyist for the credit card industry pushed for a change in the way credit card fees are communicated. By wording the cost of a cash transaction as a cash discount from the “normal” credit card cost rather than a credit card surcharge on top of the normal cash cost, consumer behaviour can be influenced. Since losses loom larger than gains, people are more willing to forgo a discount than to pay extra.
A framing example involving incentive schemes was described in the article “The Behaviourist Visits the Factory: Increasing Productivity Using Simple Framing Manipulations” by Tanjim Hossain and John A. List in 2009. The attempt to increase productivity in a Chinese manufacturing factory was more successful when the incentive was framed as a loss rather than a gain. One group of workers in the factory were told that they would receive a bonus payment at the end of the week if their average productivity increased to a certain level. Another group was given an identical bonus at the start of the week and told that if their productivity did not reach the same target as given to the first group, their bonuses would be deducted from the next pay cheque. This is another case where two problems are essentially the same, but one is framed as a gain and the other as a loss. As is expected, both incentive schemes increased the productivity of the test subjects, but after correcting for increased defects, the workers given the loss incentive were 1% more productive than the workers given the gain incentive.
In 1980 Richard Thaler first used the term “endowment effect” when describing the observation that people tend to prefer the status quo to change. This can be explained by the idea that in every transaction something is lost and something is gained. The loss of the current state has a greater effect than the gain of the new state and so the transaction should come with a premium to overcome this inertia.
Kahneman and Tversky (1983) described an exercise that showed this endowment effect well. A group was asked to imagine that they work in an environment with two specific characteristics and then asked if they would like to be transferred to a job with a different set of characteristics; one worse and one better than the current job. A second group was given the same two imaginary employment options, but with the opposite starting position. The result was that the majority of each group chose to stay with their endowed position instead of making the change.
When a consumer is evaluating choices available, there are many comparisons to be made. As the number of choices increases, the comparisons to be made between each choice grows exponentially and can quickly become daunting. While Stereo M is marginally better in a way than Stereo B and Stereo F, Stereo H is slightly better in two characteristics, but far worse in another. The endowment effect has been shown to confound even when only two options are available, but each additional option amplifies its strength.
Valence Loss and Possession Loss
A 2007 article by Brenner, et al. expanded the concept of loss aversion by defining two types of loss. A possession loss is the loss of a possession, regardless of whether that loss is desirable or not. For example, loss of a painful memory and loss of a car are both possession losses. A valence loss is a negative change, regardless of whether something was physically gained or given up. Valence loss aversion (VLA) and possession loss aversion (PLA) are the forces influencing a person to avoid valence losses and possession losses respectively. When a decision involves trading an undesirable item for another undesirable item, the two forces have opposite effects; VLA reinforces the endowment effect while PLA pushes the person to make the trade.
Satisfaction and Happiness, Gap between Expectations and Achievement
In Satifaction and Happiness (1979), Michalos conducts a mass survey at the University of Guelph in order to research the relationship between expectations, aspirations and satisfaction. The results at the time revealed that individuals that had a large gap between their expectations and their overall satisfaction, were frustrated and unhappy—where as others whom were satisfied with not achieving were happier (Michalos, 1979). The implications of this study are very relevant today as the relationship between choice alternatives and decision satisfaction are very conflicting. As mentioned earlier, the cost of decision making when alternatives are many are very large. During the production and implementation process of decision making, there is much variability and dissatisfaction due to the risk of failure costs which is fixed (Michalos, 1970). Thus, when options increase and expectations grow—dissatisfaction with choice is inevitable and could lead to un-happiness. For example when someone chooses between TVs, they are firstly choosing between stores, sales and location as direct evaluation and then deriving choices based on options, price, quality and future alternatives—increasing expectations. However, without a research institute to secure a “perfect” TV and not being an expert, the satisfaction received from the decision and the expectations from every other alternative may not have the customer feeling very happy. Later in this paper we will discuss the possible role of sales people and if decisive ones make a consumer feel better than indecisive ones.
Maximizing and Satisficing
The categorization of people into maximizers and satisficers is concept that most directly explains why consumers are negatively affected by increased choice. Maximizers exert large amounts of time and effort evaluating all options before making a choice in an effort to find the best possible decision. Satisficers have a certain subjective expectation in mind when they begin to evaluate the choices available and simply choose the first option that meets the standard. If the choice can be changed, the satisficer can simply evaluate each new option against the original choice. “A satisficer thus often moves in the direction of maximization without ever having it as a deliberate goal.” (Schwartz, et al, 2002).
In an age with a sea of choices for nearly every product and service, maximizers have great difficulty simply evaluating every option. The next step, choosing the best, is unnecessarily taxing. Ironically, while a maximizer seeks to find the optimal good or service, maximizing is not the optimal strategy to follow in order to be happy.
Iyengar and Lepper (2000) explained that “the more options there are, the more likely one will make a nonoptimal choice, and this prospect may undermine whatever pleasure one gets fro one’s actual choice.” They conducted an experiment that found consumers were more likely to buy exotic jams or gourmet cookies when they had 6 options than when they had 24 or 30 options, respectively.
Schwartz (2000) suggested three ways that an increased number of choices could be detrimental. “First, there is the problem of gaining adequate information about the option to make a choice. Second, there is the problem that as options expand, people’s standards for what is an acceptable outcome rise. And third, there is the problem that as options expand, people may come to believe that an unacceptable result is their fault, because with so many options, they should be able to find a satisfactory one.”
Paradox of Choice and General Arguments/Modern Examples, Newspapers
Recently, the idea of choice overload was taken main stream by Barry Schwartz in his book Paradox of Choice-Why More is Less (2005). Schwartz mentions many of the same authors above but also includes brilliant anecdotal references to it in various environments. This field of study is clearly a mix between psychology and economics, and Schwartz outlines studies in both fields (Shwartz, 2005). Another author that has made headlines with her research in this field is Sheena Iyengar in her book The Art of Choosing (2009). In one of her debuts on the Globe and Mail she reveals an example of how shoppers in one of her studies had an increase in purchases when their choices were low compared to when choices were high (Houpt, 2010).
The authors of this paper see the choice overload phenomenon happening for many “speculative” investors in the stock market. With recent literature in finance and economic journals by Thaler and Ritter, and the outspoken opinion of investments giants like Warren Buffet: the argument is heavy against market efficiency. One of the gruelling facts about the stock market which makes it inefficient is the presence of mass speculators who make decisions based on hear-say, status quo or extreme interpretations. These speculative investors could very well be encountering the choice overload phenomenon (using direct evaluations or satisficing) in making investment decisions. Firstly the investor has to make a direct evaluation on a specific stock amongst hundreds of other stocks and looking for factors such as industry, business news, price history etc. Events such as news or price history can have a significant impact on decisions, and as Brenner says, most people stop at direct evaluations. The second step which is even more tedious is looking at a derived evaluation of the stock based on financial statements (cash flow, income statement), management, and company history—compared to hundreds of different alternatives. Thus one can clearly see that speculation is almost inevitable for everyday investors compared fund managers who have access to millions of dollars worth of resources. However, even fund managers can fall victim to the choice overload phenomenon. As discussed earlier with Michalos, the risk of decision making is extremely large for specific positions of interest such as fund managers. The fund managers are evaluated heavily every fiscal quarter and their actions are compared to other fund managers—hence making a decision with the status quo is less risky than being wrong alone.
Another possible example of the choice overload phenomenon is the presence of sales people in many different industries. In an article published in the Journal of Personal Selling and Sales Management, Increasing Sales by Getting Salespeople to Work Smarter (1988), it reveals relationship is the biggest factor in successful sales—not product knowledge. How can this be related to the choice overload phenomenon? Since consumers are not experts in all product groups, sales people were created to help educate the customer on all possible alternatives. Yet sales people are far more effective when they lower possible alternatives and literally make the decision for consumers (Surjan, Weitz, & Sujan, 1988). Thus, the presence of salespeople helps consumers deal with choice overload—regardless of accurate product knowledge.
Finally the relationship between choice overload and happiness is complex, and research mentioned above suggests that happiness decreases as choices increase in the form of the achievement expectations gap (Michalos, 1979). An interesting example that has yet to be researched thoroughly could prove a living example of choice overload is Bhutan and its Gross National Happiness Index (Thinley Y. Jigmi, 2004). Perhaps the only surviving closed economy in the world which tries extremely hard to preserve the traditional values of Tibetan Buddhism has created a Gross National Happiness (GNH) Index for citizens. Bhutan remains economically very frugal compared to other nations, but its unique political and social landscape virtually eliminates the headache of all modern choices for its people. The government works to provide all the necessary benefits for its people and upholds dress codes—eliminating even fashion choices. The irony remains that a government that intentionally creates a choice-less atmosphere for its people also creates a GNH index—very significant to the majority of capitalist economies around the world. Furthermore research on happiness in different countries by Carol Graham in her book, Happiness Around the World: The Paradox of Happy Peasants and Miserable Millionaires, suggests that communist Cuba is one of the happiest places in the world (Graham, 2009)—much higher than the United States. Cuba certainly has limitations of choices compared to the United States—even in choosing one’s career. Thus, the relationship between choice overload and happiness certainly should be explored in depth.
The dissatisfaction experienced by modern consumers seems to be linked to the overwhelming burden of constantly making decisions from enormous sets of options. We are told by advertisers every day that we can have the best of everything, but no one actually has the time or ability to figure out exactly what is best. The market is filled with very similar products. By attempting to maximize utility a consumer may waste time needlessly and eventually be less happy than before the decision was made.
The basic microeconomic model described earlier requires certain assumptions. Consumers are required to know their preferences precisely and be able to evaluate any set of options immediately. In fact, predicting how a product will benefit a life relative to another product is impossible to do.
With so much emphasis placed on finding “the perfect car”, “the best TV”, and “the most delicious bread”, solace is found in knowing that “good enough” is actually the best.
Amrito Bhattarai lives in Canada and is General Manager at a Credit Counseling Company.