Maximization Paradox: Result of Believing in an Objective Best

Abstract

The results from four studies provide reliable evidence of how beliefs in an objective best influence the decision process and subjective feelings. A belief in an objective best serves as the fundamental mechanism connecting the concept of maximizing and the maximization paradox (i.e., expending great effort but feeling bad when making decisions, Study 1), and randomly chosen decision makers operate similar to maximizers once they are manipulated to believe that the best is objective (Studies 2A, 2B, and 3). In addition, the effect of a belief in an objective best on the maximization paradox is moderated by the presence of a dominant option (Study 3). The findings of this research contribute to the maximization literature by demonstrating that believing in an objective best leads to the maximization paradox. The maximization paradox is indeed the result of believing in an objective best.

Keywords

maximization paradox maximizer belief in an objective best decision making

Maximization has been one of the most important and commonly used terms in the decision literature since Simon’s (1955) seminal work. Simon (1955, 1956, 1957) proposed an important distinction between maximizing and satisficing as decision-making strategies. Maximizing entails seeking the best outcome and requires an exhaustive search of all possibilities, whereas satisficing entails seeking what is “good enough” until a threshold of acceptability is reached. Despite its importance and widespread usage, fundamental questions remain concerning how maximization actually operates. Although researchers have established a number of theories regarding maximization (e.g., Bruine de Bruin, Parker, & Fischhoff, 2007; Iyengar, Wells, & Schwartz, 2006; Nenkov, Morrin, Ward, Schwartz, & Hulland, 2008; Parker, Bruine de Bruin, & Fischhoff, 2007; Rim, Turner, Betz, & Nygren, 2011; Schwartz et al., 2002), recent experimental work has begun to challenge commonly held assumptions about maximization (e.g., Ma & Roese, 2014; Polman, 2010; Shiner, 2015; Weaver, Daniloski, Schwarz, & Cottone, 2015). Most past work has assumed that maximizing means achieving absolute standards or the best outcomes in an objective sense (Easterlin, 1974; Schwartz et al., 2002; Simon, 1955, 1956, 1957). Recent work has argued that the concept of maximization is more complex than was previously assumed and includes an aspect of the self (Weaver et al., 2015).

This article focuses on the maximization paradox and proposes an alternative perspective to understand how maximization actually operates. The maximization paradox is initially derived from observations of maximizers. Schwartz et al. (2002) divided people into maximizers and satisficers based on Simon’s classic theory. Shortly thereafter, various studies found that maximizers are less happy and less optimistic than satisficers (Bruine de Bruin et al., 2007; Polman, 2010; Purvis, Howell, & Iyer, 2011). The result of the Maximization Scale was consistently positively correlated with regret and negatively correlated with happiness (Parker et al., 2007; Polman, 2010; Purvis et al., 2011; Schwartz et al., 2002). Moreover, maximizers invested more time when making their decisions (Chowdhury, Ratneshwar, & Mohanty, 2009; Dar-Nimrod, Rawn, Lehman, & Schwartz, 2009; Gigerenzer & Gaissmaier, 2011; Ma & Roese, 2014; Misuraca & Teuscher, 2013; Schwartz et al., 2002), explored more options, and made more comparisons among the choices (Iyengar et al., 2006; Nenkov et al., 2008; Patalano, Weizenbaum, Lolli, & Anderson, 2015; Schwartz et al., 2002), but they felt more negatively about what they had chosen (Chowdhury et al., 2009; Dar-Nimrod et al., 2009; Iyengar et al., 2006; Schwartz et al., 2002; Sparks, Ehrlinger, & Eibach, 2012). Research describes this phenomenon as the maximization paradox (e.g., Dar-Nimrod et al., 2009; Polman, 2010; Schwartz, 2004).

There are some theoretical interpretations of the maximization paradox. Polman (2010) argued that the maximization paradox occurs because maximizers not only maximize their likelihood of realizing a positive outcome (e.g., obtaining a good job offer) but, in so doing, also maximize their likelihood of realizing a negative outcome (e.g., experiencing rejection in searching for a job). Dar-Nimrod et al. (2009) described the maximization paradox as a pattern whereby maximizers tend to sacrifice resources to attain additional options, which ultimately reduces their satisfaction (Dar-Nimrod et al., 2009). Iyenagr and colleagues (2006) argued that compared with satisficers, maximizers invest more heavily in gathering information from external sources, thereby incurring search costs, and fixate more on realized and unrealized options, thereby incurring opportunity costs. As a result, no matter how well they do, maximizers feel worse than satisficers. We believe that these interpretations provide possible but insufficient interpretations of the maximization paradox.

We are concerned with the fundamental reason that maximizers consistently attempt to maximize their chances, sacrificing resources and investing heavily, but satisficers do not. The answer may relate to a deeper explanation of the maximization paradox. Many studies have suggested that maximizing is pursued to achieve absolute standards, that is, the best outcomes in an objective sense, whereas satisficing is pursued to seek a “good enough” option that satisfies a threshold of acceptability (Easterlin, 1974; Schwartz et al., 2002; Simon, 1955, 1956, 1957). However, these works have not answered the fundamental question of why maximizers and satisficers seek differently; instead, they have simply described the phenomenon. Nevertheless, this does not mean that there is an absence of related work in the literature. Our concern on the issue derives primarily from Weaver et al. (2015), for whom the concept of maximization is more complex than previously assumed and includes an aspect of the self. We believe that this concept does not simply include the self; rather, the “self” plays a critical role in maximization. Maximizers consistently attempt to maximize their chances and invest heavily because they believe that an objective best exists. They expend considerable effort in seeking the objective best that is indeed in their mind. We attempt to further clarify the maximization paradox by manipulating the belief that the best is either objective or subjective. This work addresses an important gap in the maximization literature. Prior theoretical and experimental work has fully examined the objective decision process (which involves considerable effort) and subjective outcomes (affective responses) but has largely ignored the role of decision makers’ belief in an objective decision process and subjective outcomes, which we consider as the primary distinction between maximizers and satisficers, and therefore the essential reason for the maximization paradox. This omission is striking because decisions cannot be made absent decision makers’ beliefs; that is, they either believe that the best is objective (which likely characterizes maximizers) or that the best is subjective (which likely characterizes satisficers). This article attempts to fill this gap by identifying what types of beliefs maximizers and satisficers hold and how beliefs affect their decision process and subjective outcomes differently. In so doing, we propose an alternative perspective on the maximization paradox.

If people believe that the best is objective or that there must be a correct choice in every decision regardless of their own preference, then they have a belief in an objective best. A belief in an objective best differs from the objective best per se. To be specific, a belief that the best is objective can be separated from the issue of whether or not there exists an objectively best option. In other words, what is most important for a belief in an objective best is not being the best or obtaining the best but believing that there is an objective best. We assume that maximization is seeking the objective best (Schwartz et al., 2002; Simon, 1955, 1956, 1957) not only in an objective sense, as prior research has suggested, but also in the maximizer’s belief. The belief that there is an objective best motivates people to expend considerable efforts to identify it. People are more likely to regret their choice when they have difficulty finding the best for the reason that no one option actually stands out as better than the others.

The Present Research

We are concerned with whether belief in an objective best plays an important role in connecting the concept of maximizing to the maximization paradox, that is, expending more effort but feeling more regretful. We are also concerned with the situation in which we manipulate the belief that the best is either objective or subjective among randomly chosen decision makers. What would the outcome be in such a situation? In this article, we hypothesize that the fundamental mechanism under the maximization paradox is believing in an objective best.

The present research tests three hypotheses. Expanding on the idea that maximizing entails achieving the best outcomes in an objective sense (Schwartz et al., 2002; Simon, 1955, 1956, 1957), this study initially hypothesizes that the maximization paradox appears for maximizers because they believe that the best is objective (Hypothesis 1). It establishes the baseline of the current study, for which maximizers and satisficers have different beliefs concerning what the best is, and the belief in an objective best mediates the relationship between a maximizing tendency and the maximization paradox. This hypothesis is tested in Study 1. Building on the findings that maximizers who seek the best in an objective sense take more time in the decision-making process (e.g., Chowdhury et al., 2009; Schwartz et al., 2002) and the maximizing mind-set increases regret and dissatisfaction (Ma & Roese, 2014), we hypothesize that belief in an objective best leads to the maximization paradox for randomly chosen decision makers (Hypothesis 2). That is, a belief that the best is objective rather than subjective leads to more time spent in the decision-making process but feeling more regretful about the decision outcome. This hypothesis is tested in Studies 2A and 2B. In Studies 2A and 2B, we manipulated the belief that the best is objective or subjective among randomly chosen decision makers to provide further evidence about whether beliefs truly affect people’s decision-making process and subjective feelings. In Study 3, we test the moderating effect of the presence of a dominant option on the relationship between a belief in an objective best and the maximization paradox. We hypothesize that the presence of a dominant option eliminates the effect of belief in an objective best on the maximization paradox (Hypothesis 3).

Study 1

We assume that the maximization paradox appears among maximizers because they believe that the best is objective. Study 1 tests whether a belief in an objective best serves as the fundamental mechanism that connects maximizing to the maximization paradox. In this study, participants were asked to select the best course from 10 given courses, and then they indicated their belief in an objective best and their regret about their selections. After a 10-min distraction, they were asked to complete the Maximization Scale. We predict that maximizers and satisficers have different beliefs about the best and that a belief in an objective best mediates the relationship between a maximizing tendency and the maximization paradox.

Method

Participants

A total of 110 undergraduates (61 females, 49 males; M_age = 20.44 years, SD = 2.04) participated in this study.¹ The participants received monetary payment as compensation and gave their informed consent.

Procedure and materials

Course selection task

Participants read the following instructions:

On the next page, you will see ten courses (labeled Course A to J). Your task is to select the best course (you can select one course) among the given courses. When you make your decision, press the letter key (any key from A to J) on the keyboard to select your course. Please press Enter to start.

On the next page, participants saw a table with 10 courses that varied along six dimensions: instructor quality, potential relevance to goals, topic of interest, amount of work, convenience of meeting time and location, and peer evaluations. Rather than showing participants absolute values for each dimension (e.g., 10 hr of homework every week), relative values were used on three levels (e.g., preferred, ok, or burdensome for amount of work; see Figure 1 for further details). The materials for this course selection task were based on Patalano and Wengrovitz (2007) and Patalano et al. (2015). Ten courses were created with proximate scores according to our pretest (listed in the far right column in Figure 1). This construction allowed us to create a decision context involving substantial trade-offs. The duration from pressing Enter to pressing the letter key was recorded as the decision time.

Figure 1.

Ten courses for the course selection task.

Belief in an objective best

After participants completed the course selection task, they were asked to rate “I believe that in this decision task, the best is objective” and “In a limited set of courses, there must be one which is objectively better than the others” on a scale from 1 (strongly disagree) to 7 (strongly agree). We combined the two items into one measure (Cronbach’s α = .81, M = 4.4, 95% confidence interval [CI] = [4.18, 4.68]). Higher scores indicate more beliefs in an objective best.

Regret

Participants then rated “How regretful are you about your choice?” on a scale from 1 (not at all) to 7 (very much). After rating their beliefs in an objective best and regret, participants completed a 10-min unrelated distractor task.

Maximization Scale

Finally, participants completed the Maximization Scale (Schwartz et al., 2002), which was used to divide maximizers from satisficers. The scale contains 13 items (e.g., “When I am in the car listening to the radio, I often check other stations to see if something better is playing, even if I am relatively satisfied with what I’m listening to,” “I often find it difficult to shop for a gift for a friend,” and “I never settle for second best”). Each item was rated from 1 (strongly disagree) to 7 (strongly agree). The scale had a Cronbach’s alpha of .73. Individual items were averaged to create a composite maximizing score (M = 4.14, 95% CI = [3.99, 4.29]). Higher scores indicate likely maximizers. Finally, a maximizer group (score above the median, n = 56) and a satisficer group (score below the median, n = 54) were suggested.

Pilot study

A pilot study was conducted to determine the relative values assigned to different courses to create a trade-off context. A total of 48 participants not involved in any of the main studies were given six course selection dimensions (consistent with the dimensions described above). They were asked to allocate 100 points among the six dimensions. The more points they allocated to a given dimension, the more important the participants thought the dimension was. The average points for each dimension were then calculated and divided by 100 to determine the weight assigned to each dimension (see the bottom line in Figure 1).

Results

We first examined whether maximizers and satisficers differed in their decision time, belief in an objective best, and regret. As illustrated in Table 1, compared with satisficers, maximizers spent more time selecting their courses (M_maximizers = 104.17 s, M_satisficers = 76.85 s), felt more regretful (M_maximizers = 3.39, M_satisficers = 2.80), and were more likely to believe that the best was objective (M_maximizers = 4.77, M_satisficers = 4.07).

Table 1.

Decision Time, Belief in an Objective Best, and Regret of Maximizers and Satisficers (Results of Study 1).

	Maximizers		Satisficers		t(108)	p	d
	M	95% CI	M	95% CI	t(108)	p	d
Decision time	104.17	[90.17, 120.81]	76.85	[67.33, 86.71]	2.844	.004	0.54
Regret	3.39	[3.00, 3.77]	2.80	[2.41, 3.20]	2.098	.038	0.39
Belief in an objective best	4.77	[4.41, 5.11]	4.07	[3.76, 4.39]	2.844	.005	0.53

Note. Decision time was displayed in seconds. CI = confidence interval.

The findings based on maximizers and satisficers provided initial support for our hypothesis. Furthermore, we used bootstrap analyses with 5,000 samples to test the mediating effect of beliefs in an objective best in the relationship between a maximizing tendency and the decision time, as well as between a maximizing tendency and regret. As predicted, we found that belief in an objective best mediated the relationship between a maximizing tendency and the decision time (Figure 2a), as well as the relationship between a maximizing tendency and regret (Figure 2b), which explains why maximizers were more likely to spend time but feel regretful, or more likely to encounter the maximization paradox. With decision time as the dependent variable, indirect effect = 0.16, bootstrapped 95% CI = [12.81, 27.57]. With regret as the dependent variable, indirect effect = 0.07, bootstrapped 95% CI = [0.02, 0.51].

Figure 2.

Results of Study 1: Belief in an objective best mediates the relationships (a) between maximizing tendency and decision time and (b) between maximizing tendency and regret.

Discussion

The findings of Study 1 provide preliminary evidence for the different beliefs maximizers and satisficers hold regarding a best and statistical mediation, consistent with a pathway from a maximizing tendency to belief in an objective best to decision time and to regret. We further manipulate belief in an objective best to test our other hypotheses regarding whether a manipulated belief in an objective best also leads to the maximization paradox.

Study 2A

The aim of this study is to provide causal evidence for the impact of belief in an objective best on the maximization paradox. In other words, creating a belief in an objective best can make people act like maximizers. The hypothesis to be examined is that manipulating beliefs that the best is objective rather than subjective leads to longer decision time and more regret. In this study, participants were asked to complete an objective or subjective manipulation and then to choose the best picture among five. Unlike Study 1, in which all options were shown on one single page, each of the pictures in Study 2 was shown on its own page. In addition, no further information from different dimensions was shown beyond the picture per se.

Method

Participants and design

A total of 113 (59 females, 51 males, three unreported; M_age = 20.73 years, SD = 1.97) undergraduates participated in this study.² The participants received monetary payment as compensation and gave their informed consent. Three participants were excluded because they did not follow our instructions, and two others were excluded because of computer recording errors. The final sample consisted of 108 participants.

The participants were randomly assigned to one of the two groups for a single-factor (belief: objective vs. subjective) between-subjects design (objective group: n = 53, and subjective group: n = 55). The dependent variables were decision time and regret.

Procedure and materials

In this study, participants were informed that they were to participate in two unrelated experiments. In the first part, they completed a manipulation of belief content. In the second part, they chose the best picture among five, indicated their regret concerning their choice, and answered questions about the control variables.

Manipulation of belief content

Participants were randomly assigned to the objective or subjective group to manipulate their belief in an objective or subjective best. They had 3 min to read a material arguing that beauty was objective (for the belief in an objective best group) or subjective (for the belief in a subjective best group). The reading materials for each group were two paragraphs of discussions from famous philosophers. The reading material to manipulate belief in an objective best was from Phaedo (Plato) and Art as Object of Taste (David Hume), with the main idea that “beauty is objective.” The reading material to manipulate belief in a subjective best was from Critique of the Power of Judgment (Immanuel Kant) and Art as Object of Taste (David Hume), with the main idea that “beauty is subjective.” They were then given 10 min to write an essay of approximately 200 words to support the argument they had read. The manipulation was adapted from White, Lehman, and Cohen (2006) and Ma-Kellams, Spencer-Rodgers, and Peng (2011). This manipulation was tested in a pretest described below.

Picture selection task

Participants completed a picture selection task on a computer immediately after the writing activity. They were asked to choose one best picture from the five given pictures. These were five prize-winning pictures from the Spectacular Landscapes Competition held by the Society of International Nature & Wildlife Photographers.

The pictures were shown randomly. One picture was shown at a time. Participants had three choices for each picture: DELETE, PENDING, or SELECT. If they pressed the DELETE button, the picture would no longer appear. If they pressed the PENDING button, the picture would appear in the next round after all the other pictures were displayed in the current round. If they pressed the SELECT button, the task would end, and the selected picture would be their final selection. Participants could press the SELECT button only once in the whole process. The duration from seeing the first picture to pressing the last button was recorded as the decision time.

Regret

Participants then rated “How regretful are you about your choice?” on a scale from 1 (not at all) to 7 (very much).

Control variables

In addition to the rating of regret, participants were also asked to rate how happy they were and how difficult the task was on a scale from 1 (not at all) to 7 (very much). Mood and perceived difficulty served as control variables to show that a belief in an objective best did not create a halo effect of negativity or influence the perception of the task, in turn influencing the rating of regret (Ma & Roese, 2014). Finally, participants were thanked and debriefed.

Pretest

The manipulation was pretested among 54 participants not involved in any of the main studies. After the manipulation of belief in an objective best or subjective best, pretest participants were asked to rate “What kind of belief do you hold on beauty?” on a scale from 1 (subjective) to 7 (objective). As predicted, participants in the objective group reported believing that beauty was objective more than those in the subjective group did, objective group: M = 3.81, 95% CI = [3.25, 4.43]; subjective group: M = 2.21, 95% CI = [1.64, 2.89]; t(52) = 3.608, p = .001, Cohen’s d = 0.89. These results suggested that our manipulation of belief content was successful.

Results

Preliminary analyses

No participants correctly guessed the connection between the two parts. Analyses of the control variable showed no main or interaction effect on participants’ mood or perceived difficulty (ps > .25).

The effects of different beliefs on decision time and regret are shown in the top half of Table 2. The t tests were conducted to compare the different effects of beliefs in an objective or subjective best on decision time and regret. Participants with beliefs in an objective best (M = 56.53 s) spent significantly more time on the decision-making process than their counterparts (M = 44.24 s). Participants with belief in an objective best (M = 2.36) reported more regret than their counterparts (M = 1.85). The results suggested that beliefs in an objective best led to the maximization paradox. These data provided evidence on the role of beliefs in the decision process and subjective feelings.

Table 2.

Effects of Belief on Decision Time and Regret (Results of Study 2).

		Objective		Subjective		t	p	d
		M	95% CI	M	95% CI	t	p	d
Small assortment size (Study 2A)	Decision time	56.53	[48.81, 65.71]	44.24	[39.46, 50.01]	2.56	.013	0.48
	Regret	2.36	[2.04, 2.70]	1.85	[1.54, 2.11]	2.42	.017	0.45
Large assortment size (Study 2B)	Decision time	187.12	[153.24, 227.43]	139.52	[118.72, 162.77]	2.1	.038	0.41
	Regret	2.81	[2.38, 3.26]	2.15	[1.81, 2.51]	2.43	.017	0.46

Note. Decision time was displayed in seconds. Degree of freedom in Study 2A is 106, in Study 2B is 104. CI = confidence interval.

Study 2B

In Study 2A, participants made their decisions from a small assortment size (five pictures). According to the relevant literature, assortment size could influence the decision process and regret, but the question of whether and how large assortments impede people’s choices remains controversial (Chernev, Böckenholt, & Goodman, 2015; Iyengar & Lepper, 2000; Scheibehenne, Greifeneder, & Todd, 2010). The purpose of Study 2B was to examine whether beliefs in an objective best still lead to the maximization paradox with a large assortment size. In Study 2B, we replicated the procedure conducted in Study 2A but changed the materials of the decision task from five to 30 pictures.

Method

Participants and design

A total of 106 (56 females, 49 males, 1 unreported, M_age = 20.63 years, SD = 2.10) undergraduates participated in this study (see Note 2). The participants received monetary payment as compensation and gave their informed consent.

The participants were randomly assigned to one of the two groups for a single-factor (belief: objective vs. subjective) between-subjects design (objective group: n = 52, and subjective group: n = 54). The dependent variables were decision time and regret.

Materials and procedure

The procedure of Study 2B was the same as that conducted in Study 2A. The only difference was that participants were asked to choose one best picture among 30 (not five) pictures. Thirty prize-winning pictures from the Spectacular Landscapes Competition held by the Society of International Nature & Wildlife Photographers were used as the decision options.

Results

Preliminary analyses

No participants correctly guessed the connection between the two parts. All participants wrote their essays in support of the argument they had read. Analyses of control variables showed no main or interaction effect on participants’ mood or perceived difficulty (ps > .2).

The bottom half of Table 2 shows that participants in the objective group (M = 187.12 s) required significantly more time in the decision-making process than those in the subjective group (M = 139.52 s) but experienced more regret (M = 2.81) than those in the subjective group (M = 2.15). The maximization paradox also appeared with a larger assortment size.

Discussion

The results of Studies 2A and 2B further support the findings of Study 1 and extend it in important respects. First, unlike measuring belief in an objective best for maximizers and satisficers in Study 1, belief in an objective or subjective best was manipulated in Studies 2A and 2B. The results indicate that manipulating belief in an objective best leads average decision makers to spend more time in the decision process and to feel more regretful about decision outcomes than in the case of belief in a subjective best. Thus, Study 2 provides causal evidence for the impact of belief in an objective best on the maximization paradox.

In addition, Studies 2A and 2B extend results of Study 1 by using a new way to present information. In Studies 2A and 2B, participants made their decisions depending on their own criteria for and judgment of the options, rather than depending on finite given dimensions with objective evaluations from external information.

Furthermore, Studies 2A and 2B show that the effect of belief in an objective best is robust across assortment size. Consistent with prior research (Chernev et al., 2015; Inbar, Botti, & Hanko, 2011), a larger assortment size produces a longer decision time and higher level of regret. However, irrespective of how large the assortment size is, the role of beliefs in the decision-making process and in subjective feelings remains stable.

Study 3

The purpose of this study was twofold. The first objective was to replicate and generalize the results of Study 2, using a different manipulation of belief content, and a different scenario. The second objective was more substantive. Thus far, the previous studies all created ambiguity regarding which choice was best. In Study 1, no clearly dominant option was given; thus, participants had to make a trade-off among the given dimensions of courses. Similarly, all pictures in Study 2 were high-level prize-winning pictures of which it was difficult to determine the best. If one option was better on all the objective criteria, would the phenomenon we found in the previous studies still occur? In Study 3, we attempt to examine whether the presence of a dominant option serves as a moderator between belief in an objective best and the maximization paradox. We hypothesize that belief in an objective best leads to the maximization paradox only when the objective attributes create ambiguous trade-offs across choice options.

Method

Participants and design

A total of 138 (67 females, 71 males; M_age = 21.04 years, SD = 2.06) undergraduates participated in this study.³ Three participants were excluded because they did not follow our instructions. The participants received monetary payment as compensation and gave their informed consent. The final sample consisted of 135 participants.

Participants were randomly assigned to one of the four conditions of a 2 (belief: objective vs. subjective) × 2 (presence of a dominant option: yes vs. no) between-subjects design. Decision time and regret served as the dependent variables in this study.

Procedure and materials

The study was presented as two separate parts. In the first part, participants completed the belief in an objective or subjective best manipulation. In the second part, they chose the best laptop among five options, indicated their regret, and answered questions about the control variables.

Manipulation of belief content

All participants were given 5 min to recall and describe in writing a past decision they had made in which the best choice was objective or subjective. This manipulation was tested in a pretest described below.

Laptop selection task

Participants completed a laptop selection task on a computer immediately after the manipulation of belief content. They were asked to choose the best laptop among five options. On the next page, they saw a table with five laptops (labeled A-E) characterized by nine objective attributes: CPU, hard disk, memory, GPU, weight, standby time, warranty scope, appearance, and after-sales services (these attributes were determined by a pilot study described below). Consistent with Study 1, relative values were used in three levels (e.g., good, fair, poor for CPU). This design was inspired by Dijksterhuis, Bos, Nordgren, and van Baaren (2006). In the no-dominant-option group, the five laptops varied in a small range after endowing different weights to the nine attributes according to our pilot study (described below), which meant that ambiguous trade-offs were created across different choice options. In the one-dominant-option group, one laptop had the highest score according to all of the objective attributes, which means that it was clearly the dominant option among the five options. The laptops and attributes were shown in random order. The duration from pressing Enter to pressing the letter button (similar to the procedure described in Study 1) was recorded as the decision time.

Regret

Participants then rated “How regretful are you about your choice?” on a scale from 1 (not at all) to 7 (very much).

Control variables

Participants were also asked to rate how happy they were and how difficult the task was on a scale from 1 (not at all) to 7 (very much).

Pretest

This pretest tested the manipulation of belief content. The manipulation was pretested among 79 participants not involved in the main studies. After completing the belief in an objective or subjective best manipulation, pretest participants were asked to rate “What kind of belief do you hold on best?” on a scale of 1 (subjective) to 7 (objective). As predicted, participants in the objective group reported believing the best was objective more than those in the subjective group, objective group: M = 4.32, 95% CI = [3.73, 4.92]; subjective group: M = 2.21, 95% CI = [2.59, 3.38]; t(52) = 3.85, p < .001, Cohen’s d = 0.80. These results suggested that our manipulation of belief content was successful.

Pilot studies

Two pilot studies were conducted for Study 3. The first was to determine the attributes to be used in Study 3, and the second was to determine the relative values assigned to different laptops to create a trade-off context. In the first pilot study, a total of 32 participants not involved in any of the main studies completed an open-ended questionnaire asking them to list all attributes they would consider when buying a laptop. The nine attributes that were mentioned the most by the participants were chosen as the attributes in our main study. The second pilot study was similar to that for Study 1. A total of 48 participants not involved in any of the main studies were given nine attributes for laptops (consistent with the attributes described above). They were asked to allocate 100 points among the nine attributes. The weight assigned to each attributes was as follows: CPU: 0.19, hard disk: 0.11, memory: 0.15, GPU: 0.12, weight: 0.09, standby time: 0.10, warranty scope: 0.06, appearance: 0.09, and after-sales services: 0.07. We then created five laptops based on the results of this pilot study. The average score for each laptop in the no-dominant-option condition was: 2.17 (Laptop A), 2.17 (Laptop B), 2.11 (Laptop C), 2.11 (Laptop D), and 2.03 (Laptop E). The average score for Laptops B to E in the one-dominant-option condition was the same as in the no-dominant-option condition, but we changed Laptop A into the dominant option, and made it scored the highest in all nine attributes. The average score for Laptop A in the one-dominant-option group was 3 (i.e., a full mark).

Results

Preliminary analyses

No participants correctly guessed the connection between the two parts. Analyses of the control variables showed no main or interaction effect on participants’ mood or perceived difficulty (ps > .25). Participants’ choices were also significantly affected by the presence of a dominant option. As illustrated in Figure 3, participants selected diverse laptops in the no-dominant-option condition, χ²(4, N = 67) = 7.85, p = .10, but most participants chose the dominant option (Laptop A) in the one-dominant-option condition, χ²(4, N = 68) = 64.06, p < .001. These results suggested that our manipulations of no-dominant-option and one-dominant-option conditions were successful.

Figure 3.

Results of Study 3: Proportions for each choice under the no-dominant-option condition and one-dominant-option condition.

A 2 (belief: objective vs. subjective) × 2 (presence of a dominant option: yes vs. no) ANOVA of decision time revealed a significant main effect of the presence of a dominant option, F(1, 131) = 54.15, p < .001, η² = 0.29. Participants spent less time when the dominant option was shown (M_{one-dominant-option} = 26.48 s, M_{no-dominant-option} = 66.30 s). More important, as illustrated in Figure 4a, there was an interaction between the presence of a dominant option and belief, F(1, 131) = 5.14, p = .025, η² = 0.04. As predicted, a belief in an objective best led to a longer decision time only when there was no dominant choice (no-dominant-option condition: M_objective = 74.88 s, M_subjective = 57.45 s, p = .024; one-dominant-option condition: M_objective = 23.11 s, M_subjective = 30.06 s, p > .25). The main effect of belief was not significant (F < 1, p > .25).

Figure 4.

Results from Study 3: (a) Decision time and (b) regret with belief and the presence of a dominant option as independent variables.

Similarly, an ANOVA of regret also revealed a significant main effect of the presence of a dominant option, F(1, 131) = 39.275, p < .001, η² = 0.23. Participants’ rating of regret decreased with the presence of a dominant option (M_{one-dominant-option} = 1.24, M_{no-dominant-option} = 2.43). An interaction between the presence of the dominant option and belief was also found, F(1, 131) = 4.50, p = .036, η² = 0.03. As expected, participants with beliefs in an objective best felt more regretful in the absence of a dominant option (M_objective = 2.79, M_subjective = 2.06, p = .007) than in the presence of a dominant option (M_objective = 1.2, M_subjective = 1.27, p > .25). The main effect of belief was marginally significant, F(1, 131) = 3.022, p = .084, η² = 0.02. Participants with beliefs in an objective best felt more regret than their counterparts (M_objective = 1.99, M_subjective = 1.67, see Figure 4b).

Discussion

In Study 3, the moderating effect of the presence of a dominant option was found. As predicted, belief in an objective best only led to the maximization paradox when the objective attributes created ambiguous trade-offs across choice options, but the presence of a dominant option eliminated the effect of the belief in an objective best.

The results of this study also extended the findings of Studies 2A and 2B. In Studies 2A and 2B, we manipulated the belief that the best is objective or subjective in the context of beauty, which means that the manipulation context was consistent with the selection task. In Study 3, we found that the effect of belief in an objective best could also occur when the belief was formed in an area other than the current choice setting. That is, we manipulated belief in a context other than choosing the laptops, but the effect continued in the context of choosing laptops.

General Discussion

This article explores the important role of belief in an objective best in the maximization paradox. Across four studies, controlled laboratory settings were used with three different scenarios and two different ways to manipulate beliefs in an objective best. Substantial and robust influences of belief in an objective best on the decision process and subjective feelings were found.

Study 1 demonstrates that belief in an objective best serves as the fundamental mechanism that connects maximizing and the maximization paradox, that is, devoting greater effort but feeling more regretful. Studies 2A and 2B show that randomly chosen decision makers spend more time on the decision-making process and feel more regret about the decision outcome once they believe that the best is objective. Furthermore, Study 3 demonstrates that belief in an objective best leads to the maximization paradox only when the objective attributes created ambiguous trade-offs across choice options but not in situations in which a clearly dominant option existed.

Introducing belief to interpret the maximization paradox, we proceed a step further into the nature of the maximization paradox, exploring how maximization operates in comparison with prior research.

First, the finding provides an alternative interpretation of Polman’s (2010) contention. Polman interpreted the paradox as maximizing the likelihood of a positive outcome and maximizing for the likelihood of a negative outcome. Our experiments fixed the number of choices and found that participants felt more regret as long as we manipulated their belief that the best is objective, even if they were not allowed to search for more options. Thus, maximizing positive and negative outcomes may not be the essential reason for the maximization paradox. Maximizers’ exhaustive search of all possibilities in an effort to find the best (see Schwartz et al., 2002; Simon, 1955, 1956, 1957) results from their belief there is the best option in an objective sense, but they do not know what it is. Thus, irrespective of what decision they make, they will feel regret. Here, the key leading to the maximization paradox is the belief in an objective best.

Second, the finding also provides an alternative interpretation of the argument of Dar-Nimrod et al. (2009). Dar-Nimrod et al. described the maximization paradox as a pattern whereby maximizers tend to sacrifice resources to attain more options, which ultimately reduces their satisfaction. In our experiment, regardless of whether individuals were maximizers or satisficers, once they held a belief in an objective best, they felt more regretful. The key is that satisficers also felt more regret when they held a belief in an objective best. Thus, suggesting that believing in an objective best is the underlying reason of regret.

Third, the opinion of Iyengar et al. (2006) is also expanded. Iyengar et al. argued that maximizers invest heavily, which incurs more costs. Hence, maximizers feel worse than satisficers irrespective of how well they do. As to our understanding, maximizers feel worse not because of the costs per se of making a bad choice but because they believe that there are costs of having not identified the objective best.

Would belief in an objective best simplify our decision process in some particular situation? We contend that when given a specific decision-making standard (e.g., choosing a laptop with the longest standby time), the answer is yes. In such situations, a belief in an objective best could make us focus only on the attributes with which we are concerned, without confounding our own preferences in the decision. However, in real life, we often need to make trade-offs among different attributes, rather than depending on a single attribute. Ultimately, no one is willing to buy a laptop with the longest standby time but the poorest CPU, hard disk, and memory. Prior research also suggests that maximizers attempt to maximize gains on all attributes and make more compensatory trade-offs (Mao, 2016). Thus, it seems that the effect of a belief in an objective best may even be enhanced in real life. In our studies, we provided information from a fixed number of attributes to participants holding beliefs in an objective and subjective best. However, in the real world, if one believes that the best is objective, he or she may consider more attributes to find one option that is objectively better on the whole. Conversely, if one believes that the best is subjective, he or she may focus only on the attributes that meet his or her own preference. Ultimately, a belief in an objective best would make our decision easier in a limited range of circumstances, but in reality, such a belief may lead us to devote even more resources searching for information and alternatives.

Taken together, the results offer insight into the fundamental interpretation of the maximization paradox. That is, a belief in an objective best serves as the key for understanding the maximization paradox, as well as for understanding maximizers. A belief in an objective best motivates people to identify that objective best. They expend considerable effort pursuing it and struggle to find the objective best in a trade-off situation but generally feel regret regardless of their decisions. The maximization paradox is actually the result of believing in an objective best.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by Tsinghua University Initiative Scientific Research Program (2015THZWYY10).

Supplemental Material

The supplemental material is available online.

Notes

References

Bruine de Bruin

Parker

A. M.

Fischhoff

(2007). Individual differences in adult decision-making competence. Journal of Personality and Social Psychology, 92, 938-956.

Chernev

Böckenholt

Goodman

(2015). Choice overload: A conceptual review and meta-analysis. Journal of Consumer Psychology, 25, 333-358.

Chowdhury

T. G.

Ratneshwar

Mohanty

(2009). The time-harried shopper: Exploring the differences between maximizers and satisficers. Marketing Letters, 20, 155-167.

Dar-Nimrod

Rawn

C. D.

Lehman

D. R.

Schwartz

(2009). The maximization paradox: The costs of seeking alternatives. Personality and Individual Differences, 46, 631-635.

Dijksterhuis

Bos

M. W.

Nordgren

L. F.

van Baaren

R. B.

(2006). On making the right choice: The deliberation-without-attention effect. Science, 311, 1005-1007.

Easterlin

R. A.

(1974). Does economic growth improve the human lot? Some empirical evidence. Nations and Households in Economic Growth, 89, 89-125.

Faul

Erdfelder

Lang

A. G.

Buchner

(2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175-191.

Gigerenzer

Gaissmaier

(2011). Heuristic decision making. Annual Review of Psychology, 62, 451-482.

Inbar

Botti

Hanko

(2011). Decision speed and choice regret: When haste feels like waste. Journal of Experimental Social Psychology, 47, 533-540.

10.

Iyengar

S. S.

Lepper

M. R.

(2000). When choice is demotivating: Can one desire too much of a good thing? Journal of Personality and Social Psychology, 79, 995-1006.

11.

Iyengar

S. S.

Wells

R. E.

Schwartz

(2006). Doing better but feeling worse: Looking for the “best” job undermines satisfaction. Psychological Science, 17, 143-150.

12.

Roese

N. J.

(2014). The maximizing mind-set. Journal of Consumer Research, 41, 71-92.

13.

Ma-Kellams

Spencer-Rodgers

Peng

(2011). I am against us? Unpacking cultural differences in ingroup favoritism via dialecticism. Personality and Social Psychology Bulletin, 37, 15-27.

14.

Mao

(2016). When one desires too much of a good thing: The compromise effect under maximizing tendencies. Journal of Consumer Psychology, 26, 66-80.

15.

Misuraca

Teuscher

(2013). Time flies when you maximize—Maximizers and satisficers perceive time differently when making decisions. Acta Psychologica, 143, 176-180.

16.

Nenkov

G. Y.

Morrin

Ward

Schwartz

Hulland

(2008). A short form of the Maximization Scale: Factor structure, reliability and validity studies. Judgment and Decision Making, 3, 371-388.

17.

Parker

A. M.

Bruine de Bruin

Fischhoff

(2007). Maximizers versus satisficers: Decision-making styles, competence, and outcomes. Judgment and Decision Making, 2, 342-350.

18.

Patalano

A. L.

Weizenbaum

E. L.

Lolli

S. L.

Anderson

(2015). Maximization and search for alternatives in decision situations with and without loss of options. Journal of Behavioral Decision Making, 28, 411-423.

19.

Patalano

A. L.

Wengrovitz

S. M.

(2007). Indecisiveness and response to risk in deciding when to decide. Journal of Behavioral Decision Making, 20, 405-424.

20.

Polman

(2010). Why are maximizers less happy than satisficers? Because they maximize positive and negative outcomes. Journal of Behavioral Decision Making, 23, 179-190.

21.

Purvis

Howell

Iyer

(2011). Exploring the role of personality in the relationship between maximization and well-being. Personality and Individual Differences, 50, 370-375.

22.

Rim

H. B.

Turner

B. M.

Betz

N. E.

Nygren

T. E.

(2011). Studies of the dimensionality, correlates, and meaning of measures of the maximizing tendency. Judgment and Decision Making, 6, 565-579.

23.

Scheibehenne

Greifeneder

Todd

P. M.

(2010). Can there ever be too many options? A meta-analytic review of choice overload. Journal of Consumer Research, 37, 409-425.

24.

Schwartz

(2004). The paradox of choice: Why more is less. New York, NY: HarperCollins.

25.

Schwartz

Ward

Monterosso

Lyubomirsky

White

Lehman

D. R.

(2002). Maximizing versus satisficing: Happiness is a matter of choice. Journal of Personality and Social Psychology, 83, 1178-1197.

26.

Shiner

R. L.

(2015). Maximizers, satisficers, and their satisfaction with and preferences for reversible versus irreversible decisions. Social Psychological & Personality Science, 6, 896-903.

27.

Simon

H. A.

(1955). A behavioral model of rational choice. Quarterly Journal of Economics, 69, 99-118.

28.

Simon

H. A.

(1956). Rational choice and the structure of the environment. Psychological Review, 63, 129-138.

29.

Simon

H. A.

(1957). Models of man, social and rational: Mathematical essays on rational human behavior in society setting. New York, NY: Wiley.

30.

Sparks

E. A.

Ehrlinger

Eibach

R. P.

(2012). Failing to commit: Maximizers avoid commitment in a way that contributes to reduced satisfaction. Personality and Individual Differences, 52, 72-77.

31.

Weaver

Daniloski

Schwarz

Cottone

(2015). The role of social comparison for maximizers and satisficers: Wanting the best or wanting to be the best? Journal of Consumer Psychology, 25, 372-388.

32.

White

Lehman

D. R.

Cohen

(2006). Culture, self-construal, and affective reactions to successful and unsuccessful others. Journal of Experimental Social Psychology, 42, 582-592.

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