This week we're discussing the high price of ownership and the cost of keeping doors open from chapters 8 and 9.

 

In your discussion:

1) Discuss the concept of ownership and its role in decision making.  This discussion should include your own unique examples and discussion of the information (not just a summary of the readings).

2) Discuss the concept of keeping doors open and its role in decision making.  This discussion should include your own unique examples and discussion of the information (not just a summary of the readings).

3) Find and discuss two scholarly journal articles to supplement your discussion. Be sure to thoroughly discuss each article and how it relates to your discussion.

MANAGEMENT SCIENCE informs Vol. 50, No. 5, May 2004, pp. 575–586
issn 0025-1909 ! eissn 1526-5501 ! 04 ! 5005 ! 0575 ® doi 10.1287/mnsc.1030.0148
© 2004 INFORMS Keeping Doors Open: The Effect of Unavailability on
Incentives to Keep Options Viable
Jiwoong Shin, Dan Ariely Massachusetts Institute of Technology, 38 Memorial Drive, Cambridge, Massachusetts 02142
{jishin@mit.edu, ariely@mit.edu} M any of the options available to decision makers, such as college majors and romantic partners, can become
unavailable if sufficient effort is not invested in them (taking classes, sending flowers). The question
asked in this work is whether a threat of disappearance changes the way people value such options. In four
experiments using “door games,” we demonstrate that options that threaten to disappear cause decision makers
to invest more effort and money in keeping these options open, even when the options themselves seem to be
of little interest. This general tendency is shown to be resilient to information about the outcomes, to increased
experience, and to the saliency of the cost. The last experiment provides initial evidence that the mechanism
underlying the tendency to keep doors open is a type of aversion to loss rather than a desire for flexibility.
Key words: options; aversion to loss; search
History: Accepted by Martin Weber, decision analysis; received March 12, 2002. This paper was with the
authors 8 months for 3 revisions. Introduction to close appear more attractive than doors that remain
open? And if so, will individuals overinvest just to
keep them open?
From a naive, rational perspective, one could expect
that the value of an option (having the ability to make
a choice) would be based solely on the expected utility of the outcomes it represents. From a psychological
perspective, however, there are two primary reasons
why the subjective value of an option can exceed its
expected value: a desire for flexibility and aversion
to loss.
Initial evidence for the value of flexibility was proposed by Brehm (1956), who showed that people are
willing to sacrifice consumption pleasure to increase
freedom of choice (see also Simonson 1990, Gilbert
and Ebert 2002). The desire for flexibility is not limited to humans; even pigeons exhibit it (Catania 1975).
Such preference for flexibility implies that individuals can get utility (pleasure) from simply “having the
right to choose” (keeping options open) prior to making a final choice.
Evidence for aversion to loss dates back to
Kahneman and Tversky (1979).1 The most relevant
application of this aversion to loss is the case Imagine a student who is uncertain about whether
he wants to become a computer programmer or a
poet. If he wants to keep both options available, he
has to keep taking classes in both majors. On the
other hand, keeping both options open has its own
cost. Double majoring implies that the student has to
divide his time and effort and take classes in both
fields—leading him to become proficient in both, but
an expert in neither. Along similar lines, consider a
person pursuing two potential relationships. As long
as this romantic decision maker spends sufficient time
with each of her potential romantic partners, she can
keep them both as viable future relationships. However, once she starts spending more time with one and
neglecting the other, the neglected party is likely to
move on and become unavailable. Given the possible
loss of the second romantic option, our enthusiastic
dater might try to spend at least some of her time
with her less-preferred partner, largely to maintain
the viability of the relationship. However, much like
the student with the double major, “keeping doors
open” has its costs, drawing valuable time and energy
away from the more promising relationship.
Double majoring and dating are just two examples
of cases where one must invest extra time and effort
to keep options available. The main questions asked
here are whether the threat of future unavailability
makes less-desirable options seem more appealing
and whether this causes individuals to overinvest in
these options. In other words, do doors that threaten 1 The general reluctance to give up (aversion to loss) is related to
loss aversion (Tversky and Kahneman 1991). However, this general
reluctance to give up does not require any comparison between the
gains and losses. General reluctance to give up can, therefore, be
regarded as a related phenomenon capturing the general human
tendency to try to avoid losses. For instance, the endowment effect
can be seen as related to both loss aversion and aversion to loss.
575 576 Shin and Ariely: Effect of Unavailability on Incentives to Keep Options Viable of endowment effect (Kahneman et al. 1990, 1991;
Bar-Hillel and Neter 1996; Carmon and Ariely
2000), showing that ownership, or even deliberation (Carmon et al. 2003), can increase attachment and hence valuations. Support for aversion
to loss was also provided in the context of risky
choice, in particular the rejection of a pair of mixed
gambles (Markowitz 1952, Williams 1966). Although
options for items are very different from the items
themselves—for example, the possibility of dating a
person is a very different experience from actually
dating that person—and although it is not possible to
own an option in the same way it is to own an item,
losing an option (opportunity loss) is closely related
to the loss of an item. Namely, the loss of an option
also implies the loss of the item. Based on this similarity in terms of loss and the large influence of loss
on decision making (Tversky and Kahneman 1991),
it can be argued that individuals will also experience
the general aversion to loss and a pseudo-endowment
effect for options. The general aversion to loss implies
that the utility that individuals get from simply having the “right to choose” (keeping options open) is not
a utility, but rather disutility or pain that can accompany the loss of options.
In summary, the current work asks two questions:
First, whether the threat of unavailability increases
the perceived value of an option; and second, if so,
whether the higher valuation comes from a desire for
flexibility or from aversion to loss. Four experiments
were designed to provide initial answers to these
questions. The Experiments: General Because all four experiments employ the same basic
design, it is simpler to first describe the overall
paradigm (the “game”) and provide more details
about specific differences as they pertain to the individual experiments.
The general structure of the game involved a
sequential search task (Camerer 1995, Ratchford
and Srinivasan 1993, Zwick et al. 2000), in which
respondents were faced with multiple alternatives,
each associated with a different payoff distribution.
Respondents playing the game faced a dilemma
similar to many real-life search tasks: They wanted to
maximize their earnings by finding the best alternative (payoff in this game is based solely on performance), yet search is costly. Thus, respondents had
to trade off the possible value of additional searching
against its cost to determine their stopping rule (Saad
and Russo 1996).
As a metaphor for “keeping options open,” we
created a computer game with three doors to three
rooms (for a schematic illustration of the game, see Management Science 50(5), pp. 575–586, © 2004 INFORMS Figure 1 Schematic Illustration of the “Door Game”
Main Screen: The Three Doors
Door
1 Door
2 Door
3 Door
1 Door
2 Door
3 Click Click Click Note. Respondents first encountered three doors to three rooms. Clicking
on any door opened that door, allowing the respondents to either click within
that room or move to another room. Clicking in a room resulted in a payoff
randomly sampled from the distribution of that room. Moving to a different
room cost the respondents a click. Respondents were given a total click budget, and the experiment was completed when the click budget was depleted. Figure 1). One door was red, another blue, and the
third green. By clicking with the mouse on one of
the doors (door-click), respondents opened that door
and entered the room. Once in the room, respondents
could either click in that room (room-click) or click
on a door to a different room (door-click). Each roomclick resulted in a payoff gain sampled randomly
from that room’s distribution, and each door-click
transferred the respondent to another room (without
a payoff). Respondents were given a click budget to
use on door- and room-clicks as they wished. Once
respondents used all their clicks, the game was over
and they were paid the sum of their door-click payoffs. Note that charging the respondent a click to
switch rooms created a switching cost. The total number of clicks was indicated clearly on the screen, in
terms of both how many clicks the respondent had
used and how many clicks they had left until the end
of the experiment.
The main manipulation of interest was the relationship between the actions of the player and door availability (option availability), which was varied on two
levels: constant availability and decreased availability. In
the constant-availability conditions, all three rooms
remained as viable options throughout the experiment, irrespective of the action of the respondent.
In the decreased-availability conditions, availability
depended on the action of the respondent. Every time
a respondent clicked either on a door or within a
room, the doors to the other two rooms were reduced
in size by 1/15 of their original width. A single Shin and Ariely: Effect of Unavailability on Incentives to Keep Options Viable 577 Management Science 50(5), pp. 575–586, © 2004 INFORMS door-click on a shrinking door revitalized it to its
original size and the process continued. Once the size
of a door reached zero, it was eliminated for the rest
of the game. With this shrinking factor, an option
(room) that was not clicked on within 15 clicks was
eliminated and was no longer visible or available.2
In sum, at each point, respondents had to decide
whether to remain with their current choice or to
continue searching while incurring switching costs.
In addition, respondents in the decreased-availability
condition also had to decide whether to invest in
options that threaten to disappear to maintain their
viability.
The analogy between the experimental game and
the examples presented earlier should be clear. The
three doors represent different academic or romantic
options. In the decreased-availability conditions, the
viability of an option is threatened when there is no
investment in, or attention to, that option. Moreover,
after a certain amount of neglect, options become
unavailable, a state that is irreversible. Experiment 1: Effect of
Decreased Availability Experiment 1 was designed to determine whether
the mere fact that options could become unavailable
would influence decision makers’ behavior. Our
hypothesis was that the decreasing-availability condition would cause respondents to invest in keeping
options viable. By providing an initial answer to the
question of whether people switch rooms more often
when there is a threat of disappearance, Experiment 1
served as a starting point for examining the possible
motivation to invest in keeping options open.
Method
Respondents. Advertisements were placed around
campus to recruit 157 respondents, including some
from within the computer lab where the experiment
took place. The experiment lasted about 15 minutes.
Respondents were randomly assigned to one of
the two option-availability conditions (constant and
decreased availability).
Design. The overall structure of the game was as
described in the general description of the game. For
this experiment, the expected value of each room-click
was 3¢, but the three rooms were associated with
three different distributions (Table 1). Door 1 was
highly concentrated around mean 3 (normal with
2 For a robustness test, we manipulated this visual saliency of
the disappearance of the doors in a separate experiment. The
results showed that there was no observable impact on the player’s
actions, suggesting that the effect of availability was not due to the
visual saliency that was used in this game. Table 1 Distributions of Payment in the Three Doors Across the Four
Experiments Experiment #
(clicks)
Experiment 1
(100) Experiment 2
(50) Experiment 3
(100) Experiment 4
(100) Manipulation
Option availability
Distribution
Average ¢/variance
Min ¢/Max ¢
Information level
Distribution
Average ¢/variance
Min ¢/Max ¢
Saliency of the cost
Distribution
Average ¢/variance
Min ¢/Max ¢
Reactivation
Distribution
Average ¢/variance
Min ¢/Max ¢ Door 1 Door 2 Door 3 Normal
3/2!25
0/7 Normal
3/0!64
1/5 Chi-square
3/10
−2/10 Normal
6/9
0/14 Normal
6/2!25
2/9 Chi-square
6/16
−4/19 Normal
10/9
4/18 Normal
10/2!25
6/13 Chi-square
10/20
0/20 Normal
2!5/1!25
−0!6/5!9 Normal
3/1!25
0!1/6!9 Normal
3!5/1!25
1!2/8!1 Note. Door 3 was a chi-square distribution with a degree of freedom, which is
larger than the expected mean by 2¢. We subtracted 2¢ from the distribution
to keep the same average, but encounter a few negative outcomes. For example, in Experiment 1, door 3 was a chi-square distribution with 5 degrees of
freedom, where we subtracted 2¢. variance 0.64); door 2 was symmetric around the same
mean, but much more diffused (normal with variance 2.25); and door 3 was highly skewed toward
high numbers (chi square with 3 degrees of freedom).
The payoff distributions across these three rooms
ranged from −2¢ to 14¢, with the lower numbers
being more frequent than the higher numbers (so that
the mean value was 3¢). Respondents were given
a total of 100 clicks in the experiment, which they
could allocate as they saw fit between switching
rooms (door-clicks) and getting payoffs within a room
(room-clicks).
Procedure. Upon arrival at the lab, respondents
were seated individually and given instructions for
the game. All respondents received instructions that
emphasized that their goal in the experiment was
to make as much money as possible and that the
amount they made would be paid to them at the
end of the experiment. In the decreased-availability
condition, respondents were also given the description of the rules governing the shrinking, revitalizing, and disappearance of the doors. The instructions
did not include any information about the different
payoff distributions of the three doors; respondents
had to learn about the distributions while playing
the game.
Results and Discussion
First, we compared how door-switching behavior
varied across the two conditions. A comparison of
the average number of room switches (door-clicks) Shin and Ariely: Effect of Unavailability on Incentives to Keep Options Viable 578 Management Science 50(5), pp. 575–586, © 2004 INFORMS revealed that switching was more likely to occur
in the decreased-availability condition !M = 16"70#
than in the constant-availability condition (M = 7"47;
t!156# = 7"82, p < 0"001).
Next, we examined how the tendency to switch
rooms in the two option-availability conditions
changed as a function of the total number of clicks
used (click number). Note that the click number is a
measure of both the learning and the expected value
of keeping options open, both reducing the motivation for switching. First, as the click numbers increase,
respondents have more experience, better estimation
of the distributions, and thus a reduced need to
explore the different options. Second, the expected
benefit of exploring different options is reduced with
the click number because the time horizon during
which this information can be used is reduced.
To analyze the effect of the click number, clicks
were divided into 10 blocks of 10 clicks each. An
overall 2 (option-availability) by 10 (block) ANOVA
revealed a significant main effect for option availability (F !1$ 1550# = 306"27, p < 0"0001), a significant main
effect for block (F !9$ 1550# = 5"61, p < 0"0001), and a
significant interaction effect between option availability and block (F !9$ 1550# = 3"82, p = 0"0001). As can
be seen in Figure 2, there was a decreased tendency
to switch rooms later in the game. However, even in
the last block of 10 clicks, more switching occurred
in the decreased-availability condition (M = 1"27)
than in the constant availability condition (M = 0"75;
F !1$ 155# = 8"23, p = 0"0047). More important, there
were interesting differences in how the tendency to
open other doors changed as a function of block in the
two conditions, as indicated by the interaction. In particular, while respondents in the constant-availability
condition switched the most during the first block,
respondents in the decreased-availability condition
switched the most during the second block—which Experiment 2: Effects of Knowledge
on the Desire to Keep Doors Open 1.5 Although the results of Experiment 1 suggest that
the respondents were willing to invest to keep their
options open, it remains unclear as to whether this
investment can be classified as an overinvestment. It
is possible, for example, that in the face of uncertainty,
the optimal strategy is to keep options open until
sufficient information about distribution accumulates.
Experiment 2 manipulated the level of knowledge
respondents had about the distributions, the logic
being that if the reason for keeping options available is lack of knowledge, providing respondents with
more information about payoff distributions should
eliminate, or at least substantially decrease, the difference in switching between the decreased- and
constant-availability conditions. On the other hand, if
the tendency to keep options open is caused by mechanisms such as preference for flexibility or aversion
to loss, providing additional information should not
influence the effects of option availability on room
switching. 1.0 Method 0.5 Respondents. Advertisements were placed around
campus to recruit 105 respondents, including some
from within the computer lab where the experiment
took place. Respondents were randomly assigned to
one of six conditions. Figure 2 Average Number of Door Switches for Decreased- and
Constant-Availability Conditions Within Each Block of
10 Clicks in Experiment 1
Decreased Availability 3.0 Constant Availability 2.5
# of switches was the first time they encountered a threat of option
elimination.
It is worth contrasting the behavior of the respondents to an optimal strategy benchmark, which in
this experiment was to select a single room and
remain there during the entire game, which would
have earned the highest possible payoff due to the
implicit opportunity cost of 3¢ for each room switch
(door-click). Relative to this standard, the respondents
in Experiment 1 gave up 11% of their profits (8%
in the constant-availability condition and 14% in the
decreased-availability condition) as a consequence of
switching rooms, which occurred on the average of
12 times per respondent. Note that in this experiment, respondents had to discover the underlying
payment distribution based on experience, and therefore had to switch to learn about the doors—that is,
payoffs. Accordingly, the reduction in payment cannot be taken as evidence of any irrational behavior.
Experiment 2 more carefully examined normative
expected behavior in such cases.
In summary, Experiment 1 showed a main effect for
option availability. Decision makers’ interests in alternative options seemed to increase when they were
threatened by their unavailability. D
C 2.0 0.0 BL-1 BL-2 BL-3 BL-4 BL-5 BL-6 BL-7 BL-8 BL-9 BL-10
Click Number (blocks) Note. Error bars are based on standard errors. Shin and Ariely: Effect of Unavailability on Incentives to Keep Options Viable
Management Science 50(5), pp. 575–586, © 2004 INFORMS Design and Procedure. The main manipulation in
Experiment 2 was a manipulation of information,
which was varied on three levels: no prior information,
practice information, and descriptive information, which
was crossed with the manipulation of option availability. The distributions of the three rooms had the
same mean value of 6¢ (Table 1), and respondents
were allocated 50 clicks rather than 100 clicks as their
clicking budget. The no-prior-information conditions
were a basic replication of Experiment 1. In these
two conditions (constant and decreased availability),
respondents did not get any prior information about
the distributions. They were simply given the opportunity to play the game. In the practice-information
condition, respondents played the same game twice,
first for 50 practice trials without getting paid, and
then for 50 real trials. Respondents were clearly
informed that the distributions associated with each
room were the same in the practice and real parts,
thus increasing their knowledge about these distributions for the real part of the experiment (the part for
which they got paid). Respondents in the descriptiveinformation condition were told that the averages
of the distributions of all three rooms were identical. They were also shown a graph in which the
means, skewnesses, and variance of each distribution were depicted. Although the respondents in the
descriptive-information condition knew the three distributions, they did not know which room corresponded to which distribution. Thus, if they were
not satisfied with the equal expected value across
the three rooms, they could have searched the three
rooms for their preferred distribution.
Results and Discussion
As in Experiment 1, the main dependent measure was
the frequency of room switches across the different
conditions, analyzed in a 2 (option-availability) by
3 (information) between-subjects ANOVA. The overall
ANOVA (Figure 3a) revealed a main effect for option
availability (F !1$ 99# = 56"66, p < 0"001), replicating
the main results of Experiment 1. The overall ANOVA
also revealed an effect for information (F !2$ 99# = 6"99,
p < 0"001), showing that the no-prior-information conditions induced more switching than did the other
two conditions (F !1$ 101# = 12"78, p < 0"001), which
were not different from each other (F !1$ 61# = 1"85,
p = 0"18). Finally, the analysis showed a nonsignificant interaction between option availability and information (F !2$ 99# = 1"32, p = 0"27), demonstrating that
the addition of information did not change the effect
of option availability on switching behavior; that is,
respondents with no prior information about the distributions exhibited the same reaction to the threat of
disappearance as respondents who had more information (either descriptive or practice) about these 579 distributions. There were a few respondents who
wanted to end the experiment as fast as possible, not
switching rooms at all. These respondents increased
the standard errors in general but most profoundly
when the mean switching was higher, which is the
decreased-availability condition.
While these results demonstrate that additional
information does not reduce the effect of option
availability, they do not rule out rational explanations
for the observed effect. For example, had respondents
needed 15 clicks per room to learn its payoff distribution, respondents in the decreased-availability conditions would have had to switch rooms at least six
times, while respondents in the constant-availability
conditions would have had to switch only twice. To
examine more carefully such possible explanations,
we constructed three other measures: pecking, elimination point, and click investment.
First, we examined pecking, the number of times
that respondents switched to another room, clicked
in that room once, and switched back (the result
remains the same if we define pecking as switching
to another room and switching back without clicking inside the room, or as a combined measure).
From the perspective of gaining information about
the payoffs, we could consider such pecking behavior
as an irrational overinvestment in keeping options
open because it provides little information (one
more sample) at a high cost (three clicks—one
for switching away, one for sampling the payoffs,
and one for switching back). ANOVA analysis
revealed that pecking behavior was more frequent
in the decreased-availability condition (M = 0"36)
than in the constant-availability condition (M = 0"07;
F !1$ 99# = 5"97, p = 0"016), suggesting that in the face
of a threat that options could become unavailable,
respondents showed “irrational” behavior more often.
More important, the effect of information on pecking was not significant (F !2$ 99# = 0"682, p = 0"508),
nor was the interaction between option availability
and information (F !2$ 99# = 0"435, p = 0"649), suggesting that the different amounts of information had
no effect on respondents’ overinvestment in keeping
options open.
In a second attempt to e...

 

Attachments:

• 1506954552-Scholarly article 2.pdf
• 1506954558-Ownership scholarly article 1.pdf