A Cross-Cultural Study of Reference Point Adaptation:
Evidence from China, Korea, and the US
Hal R. Arkes
Department of Psychology, The Ohio State University, 240N Lazenby Hall, 1827 Neil Avenue, Columbus, Ohio 43210,
Paul Merage School of Business, University of California – Irvine, Irvine, CA 92617, firstname.lastname@example.org
The College of Business, Florida State University, 821 Academic Way, Tallahassee, FL 32306, email@example.com
Sonya S. Lim
The Kellstadt Graduate School of Business, DePaul University, 1 E. Jackson Blvd, Chicago, IL 60604, firstname.lastname@example.org
August 4, 2008
We examined reference point adaptation following gains or losses in security trading using
participants from China, Korea, and the US. In both questionnaire studies and trading experiments
with real money incentives, reference point adaptation was larger for Asians than for Americans.
Subjects in all countries adapted their reference points more after a gain than after an equal-sized loss.
When we introduced a forced sale intervention that highlighted a prior price change, Americans
showed greater adaptation toward the new price, whereas Asians showed less adaptation. We offer
possible explanations both for the cross-cultural similarities and the cross-cultural differences.
Keywords: Prospect theory; cross-cultural differences; reference point adaptation; mental accounting;
1 In a somewhat similar spirit, Strahilevitz and Loewenstein (1998) conjectured that " . . . adaptation to losses takes
longer than adaptation to gains and would therefore require a greater time interval to observe."
Prospect theory (Kahneman and Tversky 1979) is one of the—if not the—most prominent descriptive
theories of decision making under uncertainty. Although originally designed as a static model, it has been
widely applied to dynamic settings in economics and business research to understand work effort, brand
choices, capital budgeting, stock returns, trading volumes, and option exercises (e.g., Hardie, Johnson,
and Fader 1993; Keasey and Moon 1996; Heath, Huddart, and Lang 1999; Heath, Larrick, and Wu 1999;
Barberis and Huang 2001; Grinblatt and Han 2005; Mas 2006). An important premise of these
applications of prospect theory is that reference points shift over time, but only recently have scholars
started to explore systematically the dynamic properties of reference points. Furthermore, research that
examines such properties across different cultures is almost non-existent. Given the large body of
research showing that culture affects individual judgment and decisions, a primary purpose of this
manuscript was to ascertain whether reference point adaptation exhibits cross-cultural variation, and if so,
what are possible causes of this variation.
A natural hypothesis for the dynamics of reference point adaptation is that the reference point
moves in a manner consistent with the prior outcome, shifting upward following a gain and downward
following a loss. Using subjects from the US, Arkes, Hirshleifer, Jiang, and Lim (2008) found that
reference points adapt asymmetrically: such adaptation was significantly larger following a gain than
following a loss.1 They also found that when realization of the initial gain or loss was emphasized,
adaptation both to losses and gains appeared to be enhanced. Applying the measurement approach of
Arkes et al. to encompass both east-Asian and US subjects, we identify cross-cultural similarities and
differences in reference point adaptation. Our findings suggest that both westerners and easterners tend to
adapt more to prior gains than to their losses, but that eastern and western cultures differ in their tendency
to adapt to their prior outcomes due to their differences in loss aversion and in the tendency to expect
reversals in fortune.
Performing cross-cultural studies in this domain was motivated by recent research that has
documented important differences in several judgment and decision making phenomena across countries,
such as overconfidence (Yates, Lee, and Shinotsuka 1998), attribution of responsibility (Morris and Peng
1994), and risk preferences (Hsee and Weber 1999). The results of these studies suggest that previous
findings mostly generated in the United States may not generalize completely to other countries. In fact,
given the various cross-cultural differences enumerated above, we should expect substantial differences in
the way people from different cultures react to gains and losses by shifting their reference point.
Scholars have also used prospect theory to understand a number of anomalous stock market
phenomena, including excess volatility, the equity premium puzzle, the value effect, the disposition effect,
and IPO underperformance (e.g., Shefrin and Statman 1985; Bernartzi and Thaler 1995; Barberis and
Huang 2001; Barberis and Xiong 2008). There is evidence that the high equity premium, the value effect,
and the disposition effect are present outside the United States to varying extents (e.g., Fama and French
1998; Grinblatt and Keloharju 2001; Feng and Seasholes 2005; Dimson, Marsh, and Staunton 2007).
Understanding cross-cultural differences in reference point adaptation may also help us better understand
these variations in market behavior around the world.
2. Motivation and Literature Review
2.1. Prospect Theory
Kahneman and Tversky (1979) proposed prospect theory as an alternative to the normative theory of
expected utility maximization. Three main elements of prospect theory are most relevant to our research.
First, people derive utility from gains and losses relative to a reference point, while traditional utility
theory assumes that people derive utility from total wealth or consumption. Although the reference point
is generally one’s current wealth (Kahneman and Tversky, 1979), aspiration levels or norms can also
serve this function (Kahneman and Tversky, 1979, p. 286; Heath, Larrick, and Wu, 1999). Second, the
value function is concave in the domain of gains and convex in the domain of losses with a steeper slope
in the loss domain. The shape of the function captures “dual risk attitudes”: individuals tend to be risk
averse in the gain domain but risk seeking in the loss domain. Third, the effect of a loss on utility is much
larger than that of a gain of the same size ("loss aversion").
Kahneman and Tversky (1979) showed that prospect theory described the behavior of subjects in
the US as well as in European countries such as Sweden, and in Israel. Past studies suggested that losses
have an effect approximately 2 to 2.5 times that of a gain of the same size (e.g. Tversky and Kahneman,
1992). However, there is relatively limited research that assesses the magnitude of the loss aversion and
risk aversion among east-Asians, who tend to differ from westerners in several aspects of judgment and
decision making (e.g., Wright and Phillips 1980; Yates et al. 1989; Weber and Hsee 1998; Levinson and
Peng 2006). Thus, to measure reference point adaptation, we included an estimation of the loss aversion
and the exponent of the value function among east-Asians.
There are two prior studies somewhat related to this aspect of our study. Kachelmeier and
Shehata (1992) provided evidence consistent with the probability weighting function in prospect theory,
using high monetary incentives for Chinese subjects. Hsee and Weber (1999) examined choices over sure
versus risky outcomes in both gain and loss domains. They found that Chinese subjects are less risk-
averse than US subjects.
Our paper has a different goal from these two papers: to measure cross-cultural differences in
reference point adaptation across two different cultures and to explore the sources of such differences.
Our paper also differs in that we estimated the parameters of the value function as means of quantifying
2.2. Reference Point Adaptation in Prospect Theory
Prospect theory has most commonly been applied to static decision environments. When one applies this
model to more realistic dynamic settings such as stock trading, repeated bargaining and negotiation, work
efforts, and firm investments, it is important to understand how reference points are updated after such
individuals experience outcomes over time.
Consider the prospect theory value function depicted in Figure 1. If a loss has occurred, the
decision maker is at point L in Figure 1a. If a subsequent decision is to be made and the reference point
has not adapted to the initial loss, the decision maker will likely be risk seeking, in that a further loss will
cause only a small decrease on the y-axis, whereas a further gain will result in a larger increase. However
if the decision maker adapts fully to the initial loss, then Figure 1b depicts this situation. Now the
decision maker will be less risk seeking, because the “re-centering” of the origin of the graph on the
current state of affairs causes a loss to be more painful than it would have been in Figure 1a. Thus, if the
reference point does not budge following a loss, then the decision maker is likely to become risk seeking
and to try to recover the loss, leading to such phenomena as the sunk cost effect (Arkes and Blumer 1985)
or the disposition effect (Shefrin and Statman 1985). On the other hand, if the reference point adapts
downward following a loss, the decision maker is able to “make peace” with this loss and will be less
likely to “throw good money after bad.”
Figure 1a (left): No adaptation to the loss that has occurred at point L.
Figure 1b (right): Full adaptation to the loss that has occurred at point L.
There are a very few cross-cultural studies pertaining to the static aspects of prospect theory.
However, we know of no cross-cultural research on its dynamic aspects. There are a very few studies
testing the dynamic aspects of prospect theory using US subjects. Chen and Rao (2002) found that the
order in which two opposite events (gain/loss) occurred affected the subject's final affective state,
suggesting that a shift in the reference point occurred after the first event. Gneezy (2005) assumed that
subjects are most willing to sell when the current price is equal to the reference point, and showed that
assuming a stock’s peak price to be the reference point best explained subjects’ willingness to sell that
stock. Baucells, Weber, and Welfens (2007) estimated the reference point by asking subjects which
selling price would make them neither happy nor unhappy. Using a weighting function approach Baucells
et al. showed that the reference point is most heavily influenced by the first and the last observed stock
price. Both Gneezy (2005) and Baucells et al. (2007) focused on which price in the past price history had
a bigger influence on the current reference point, but they did not estimate the magnitude of reference
point adaptation after a gain or loss, which is the main focus of our study.
Arkes et al. (2008) estimated the changes in reference point location following stock trading gains
and losses using both questionnaires and real money incentives. They found that the reference point
adapts to prior gains to a greater extent than to prior losses using two main procedures. In their
Experiment 1, for example, subjects were asked to indicate the stock prices that would render the same
utility as that caused by a prior gain or loss. If the shape of the prospect theory value function remains
unchanged, the distance between the indicated stock price and the new reference point must be equal to
the distance between the prior stock price and the old reference point. Therefore, one can infer the change
in the reference point (“reference point adaptation”) from the indicated change in stock prices.
The second procedure is exemplified in their Experiment 6. Subjects purchased a stock at a
certain price and experienced either price appreciation or depreciation. Then subjects were informed of
the possible stock prices in the next trading period and offered a chance to sell the stock by stating their
minimum selling price. Using the Becker, DeGroot, and Marschak procedure (1964), Arkes et al.
obtained each subject's minimum selling price—the certainty equivalent of the gamble—and then solved
for the implied new reference point using the prospect theory value function. They then measured the
reference point adaptation by comparing the distance between the new reference point and the initial
reference point, which was assumed to be the purchase price.
Using either procedure, the primary result was that reference point adaptation was asymmetric;
adaptation following a gain was significantly greater than that following an equal-size loss. Also, when
subjects were forced to sell a stock and then repurchase it at the same price at which it had been sold
(Weber and Camerer 1998), Arkes et al. found that reference point adaptation was accelerated. The
authors hypothesized that this sale/repurchase intervention emphasized the new price following the prior
gain or loss, and thus facilitated the closing of the old “mental account” (Thaler 1985, 1999) that
encompassed that prior gain or loss. This would, in turn, cause more adaptation to the outcome, whether it
was a gain or loss.
2.3. Cross-Cultural Differences in Decision Making
Weber and Hsee (1998) and Hsee and Weber (1999) showed that Chinese are less risk-averse than
Americans in their financial decisions, but not in other domains such as medical and academic decisions.
Weber and Hsee (1998) found that the perception of the riskiness of financial investment options is lower
among Chinese than Americans, and argue that this difference in risk perception can explain cross-
cultural differences in risk preferences.
Hsee and Weber (1999) advanced the “cushion hypothesis” to account for cross-cultural
differences in risk perception in the financial domain. In collectivist cultures such as present in China, the
members of one’s social network can provide assistance to cushion financial losses. Thus Chinese
participants in this research might understandably perceive financial risks to be less than would
Americans due to this safety net. However members of one’s family or social network cannot provide the
same magnitude of assistance in medical or educational domains, so differences in risk perception
between Chinese and Americans were neither predicted nor found in these areas. In support of the
cushion hypothesis, Hsee and Weber (1999) found that when they controlled for social network variables
such as the number of people an individual could rely on for financial assistance, the cross-cultural
difference between the Chinese and Americans became non-significant.
To gain further insight into the sources of cross-cultural differences in risk-taking, Weber, Hsee,
and Sokolowska (1998) examined risk advice contained in national proverbs. They found that Chinese
proverbs seem to provide more risk-seeking advice than American proverbs, and that Chinese perceived
their proverbs to advocate greater risk-seeking than Americans perceived in their proverbs, but only for
financial and not for social risks.
Ji, Nisbett, and Su (2001) documented an important difference between Asians’ and Americans’
attitudes toward change. In five studies, Ji et al. (2001) showed that Chinese students were more likely to
predict change from an initial state than were Americans. In one experiment (Study 2) some of the
questions posed were economic, such as: “The global economy growth rates (annual percentage change in
real GDP) were 3.2%, 2.8%, and 2.0% for 1995, 1997, and 1999, respectively. . .” Subjects were asked to
predict the probability of the trend remaining the same, going up, and going down. Chinese subjects in
this study and others were more likely than Americans to predict that the current trend would reverse.
Thus, compared to Americans, Chinese subjects—or Asian subjects in general—might be more likely to
predict that gains would be followed by losses, and conversely. Any such difference would have
important implications for the valuation and willingness to continue holding a stock following an initial
In this paper, we employed the methods of Arkes et al. (2008) to pursue four goals. First, we
measured reference point adaptation among east-Asians to ascertain if the greater adaptation to gains than
losses was present across cultures, as was documented among US participants in Arkes et al. (2008).
Second, we examined if there is a cross-cultural difference in reference point adaptation between east-
Asians and Americans. Third, we ascertained whether the intervention of the sale and repurchase of a
stock accelerated reference point adaptation in the Asian culture, as was previously demonstrated in the
2 The exchange rate between the US dollar and Korea Won is close to the ratio of the purchasing powers of two
currencies. However, there is a discrepancy between the exchange rate and the purchasing power ratio for the US
dollars and China ¥. For instance, an equivalent McDonald meal or an hour of math tutoring costs roughly 2-3 times
more in the US than in China. Therefore, for the Chinese subjects we made an adjustment to their prize based on the
American sample. Finally, we explored the robustness of and possible explanations for the observed
cross-cultural variation in reference point adaptation.
3. Reference Point Adaptation Using a Questionnaire (Study 1)
In this questionnaire study we asked subjects to indicate a stock price today that would generate the same
utility as a previous stock price change. Assume that the first stock price P1 resulted in a level of utility
V(P1 – R0) which is a function of the difference between the first stock price P1 and the reference point R0.
Subjects indicate the price of the stock today P* that would generate the same utility as the previous price.
Assuming a constant shape of the prospect value function, we have V(P* – R1) = V(P1 – R0). Thus P* –R1
= P1 – R0. So the reference point adaptation R1 – R0 = P* – P1. That is, reference point adaptation can be
inferred from the subject’s indication of the stock price today that would generate the same utility as the
previous price change.
3.1. Research Participants
The participants were undergraduate students at Florida State University in the United States (81 subjects),
Nanjing University in China (89 subjects), and Korea University in Korea (81 subjects). The subjects
answered brief questionnaires in a classroom setting. All students voluntarily filled out the questionnaires
for a raffle prize within each class. The raffle prizes were adjusted to ensure a similar monetary incentive
across three countries from the perspective of an average subject. In the US, the prize was $20.
According to official exchange rates when the experiment was conducted, this amount was equivalent to
20,000 KRW (Korean Won), which served as the prize for our Korean subjects. The prize for our Chinese
participants was ¥80, which was the equivalent of $10 according to the official exchange rate. However
the three countries’ prizes were chosen to be similar in purchasing power, because the raffle prize could
pay for approximate 3-4 equivalent McDonalds meals in each country.2
relative price of a McDonald meal or payment for tutoring services in the two markets. This strategy ensured similar
incentives from the perspective of an average subject across all countries.
3.2. Questionnaires and Procedure
We conducted a questionnaire study where we asked two questions regarding reference point adaptation,
similar to those used in Arkes et al. (2008). In one question, subjects were asked to indicate the stock
price that would make them just as happy with the stock’s price this month as they were when they
learned the stock had risen from $30 to $36. In the other, they indicated the stock price that would make
them just as sad as when they learned the stock had dropped from $30 to $24 last month. To ensure that
original meanings were preserved during translation, the questionnaire was first translated into Chinese or
Korean by one person and then back-translated into English by a different person, and we made minor
corrections when there were discrepancies (Brislin 1986).
The US payoff numbers were multiplied by 1,000 in Korea, because one US dollar was about
1,000 KRW in Korea. In China, we opted to use the same US figures but in local currency. In other words,
we replaced $30 with ¥30, and so forth. In our later stock trading study, we also used the same practice to
reflect the fact that average Chinese stocks are traded around ¥20-¥30. For simplicity in reporting, we
later do not distinguish the numbers in $ from those in ¥, but refer to all of them in $, instead. The
reference point adaptation of Korean subjects was divided by 1,000 so that we could compare the results
3.3. Results and Discussion
We report the results in Table 1. Two observations from Asian countries (one from China, the
other from Korea) were deleted due to entry errors. Since we found no statistical difference between the
risk taking behaviors between Chinese and Koreans, we aggregated them into one factor, namely Asian
The responses to the two reference point adaptation questions yielded a finding similar to that of
Arkes et al. (2008): reference points adapted to gains to a greater extent than to losses of equal size. Table 1
shows that the implied adaptation to a $6 gain minus that to a $6 loss, calculated as ΔRP(G) − ΔRP(L), is
positive and statistically significant both in Asia and the US. Our evidence suggests that asymmetric
adaptation in reference points is a general phenomenon in individual decision making and can be
generalized across cultures.
Table 1. Reference point adaptation to gains and losses (Study 1)
Note. ΔRP(G), defined as R1 – R0 = P* – 36, measures the reference point adaptation to a $6 gain. ΔRP(L), defined as
R1 – R0 = 24 – P*, measures the reference point adaptation to a $6 loss. The t-stat tests whether the asymmetric
adaptation, ΔRP(G) − ΔRP(L), is different from zero.
[ΔRP(G) + ΔRP(L)]/2
ΔRP(G) − ΔRP(L)
Furthermore, we observe some cross-cultural variations in adaptation. First, Asians appear to adapt
more to prior outcomes than Americans, as measured by the average adaptation [ΔRP(G) + ΔRP(L)]/2. On
average, Asians adapt $5.18 to a $6 prior outcome while Americans adapt $3.10, a $2.08 difference.
Second, the asymmetric adaptation seems larger among Asians than among Americans. On average,
reference points adapt $1.94 more to gains than to losses among Asians, but only $1.07 among Americans.3
Using an ANOVA 2 (gain/loss) x 2 (cultures) design, we find evidence consistent with our
observations. First, the gain/loss factor is significant (F(1, 247) = 37.2, p < 0.01), suggesting that the
asymmetric adaptation exists across the two cultures. The culture factor is significant (F(1,247) = 29.9, p <
0.01), indicating greater adaptation among Asians than among Americans. The interaction term (gain/loss x
culture) is marginally significant (F(1,247) = 3.11, p = 0.079).
4. Reference Point Adaptation Using Real Money Incentives
The advantage of the questionnaire study (Study 1) is that the inference of reference point adaptation is
parameter-free; one needs no assumption about the parameters of the prospect theory value function.
However, a general criticism to questionnaire studies is the lack of a monetary incentive. Therefore, we
3 Arkes et al (2008) estimated that the asymmetry is equal to $1.73 for their US subjects, larger than our US estimate
of $1.07. We used a within-subject design instead of a between-subject design used by Arkes et al (2008), which
might have possibly reduced the asymmetry.
also studied individual reference point adaptation in experimental stock trading settings, in which
subjects’ trading profits were tied to monetary payoffs.
We followed the procedure employed by Arkes et al. (2008). Subjects purchased a share of stock
for $20. After the stock price moved up or down by $6, subjects were informed of the two equally-likely
future prices at which they would have to liquidate the stock. Before a coin flip determined the second-
period stock price, subjects were asked to indicate a minimum price at which they were willing to sell the
stock to the experimenter. Since the value of the certain payoff indicated by the minimum selling price
should be equal to the expected value of the future liquidation values, we could infer the new reference
point and the reference point adaptation.
4.1. Estimating Parameter Values (Study 2)
Since we need to equate the value of the certainty equivalent to the expected value of a risky gamble to
infer the reference point, we first estimated the loss aversion parameter (λ) and the exponent (α) in the
cumulative prospect theory value function (Tversky & Kahneman, 1992) for each culture.
The existing estimates for the loss aversion parameter (λ) and the exponent (α) are based on
experiments using western subjects. For instance Tversky and Kahneman (1992) estimated the loss
aversion parameter to be 2.25 and the exponent α to be 0.88 using US subjects. However, nowhere in the
existing literature are there such estimates for Asians subjects. Since these could differ from those for US
subjects, it is important that we estimate these values.
Our questionnaires followed Kahneman and Tversky (1979) and Tversky and Kahneman (1992).
We used the same range of hypothetical payoffs as the range of the real monetary payoffs used in our
stock trading experiment.
4.1.1 Research Participants
Part 1 of Study 2 was designed to estimate the loss aversion coefficient. It was run together with Study 1.
Thus, the participants and procedures were the same as described in Study 1, but the number of
observations differs slightly. Among our Korean subjects, three persons did not provide answers to the
loss aversion questions, and the data from one US subject were deleted due to a preposterous value
provided by that individual.
Part 2 of Study 2, which was designed to estimate the exponent of the value function (α), was run
online. We sent out e-mails to undergraduate students enrolled in selected business classes and also made
in-class announcements asking for participation. For the online survey, the raffle prize was three $20
prizes in the US, two $50 prizes in Korea, and three $20 prizes in China. Though the prize in the US is
smaller than that in Korea and China, the US subjects were given one extra credit for filling out the
survey, which served as an additional incentive. One hundred eighteen subjects from Florida State
University in the United States, 92 subjects from Sun Yat-Sen University in China, and 88 subjects from
Korea University in Korea participated in the online survey.
4.1.2 Questionnaires and Procedure
In Part 1 of Study 2, there were three questions for each subject, each asking for the size of the gain
prospect of a gamble that would make a participant indifferent between a sure outcome of zero and the
gamble. The three gambles differed in the magnitude of the loss prospect. As described in Study 1, the
numbers were converted into Korean currency of equivalent amounts by an approximate ratio based on
the exchange rates, and in China by changing the label of the currency. The questions in Part 1 were
adapted from Tversky and Kahneman (1992), and the loss aversion coefficient of an individual was
measured by the indicated gain prospect, X, divided by the corresponding loss prospect.
Part 1: Loss aversion
Option A: No gain or loss;
Option B: Win $X or lose $25/$50/$100 with equal probability of 50%
Indicate the dollar value of X that will make you indifferent between Options A and B:
Similarly, in Part 2, there were two pairs of questions per subject, one for the gain domain and one for the
loss domain, which estimated the exponent of the value function (α).
Part 2: Exponent
You are expected to give the dollar value of X to make option B just as attractive as option A. In
other words, please indicate the dollar value of X that will make you exactly indifferent between
the two options.
Option A: Win (Lose) $X for sure.
Option B: Win (Lose) $50/$100 or win (lose) nothing with equal probability of 50%
Indicate the dollar value of X that will make you indifferent between Options A and B: $______
Since the value of the sure outcome (Option A) must be equal to the expected value of the risky gamble
(Option B) when a subject is indifferent between the two options, the indicated amount X must satisfy
V(X) = 0.5V(0) + 0.5V(P), where P is equal to $50 or $100 depending on the question. Using the prospect
theory value function in Equation (1), the exponent α is equal to log(2)/log(P/X), where P refers to the
gain or loss prospect ($50 or $100) of the risky gamble.
4.1.3 Results and Discussion
Table 2 contains the mean loss aversion and the exponent estimates for each culture. The mean loss
aversion coefficient across the three loss prospects is 1.66 for Asia (1.69 for China, 1.61 for Korea) and
2.08 for the US. The estimates indicate that the US subjects are more loss averse than the Asians. Again,
we found no statistically significant differences between Chinese and Koreans, so they are aggregated
into an Asian culture group.
The alpha estimates from a pair of questions (one pertains to a gain of $50/$100 and the other a loss
of the same magnitude) were averaged for each subject, then across subjects within each culture. Some
subjects indicated certain payoffs that are equal to one of the possible payoffs of the gamble or greater
than the non-zero possible payoff, in which case we could not solve for α. 4
4 We only included subjects that have a pair of solvable alpha estimates for a given magnitude ($50 or $100). For
“All” average, we only include those that have both pairs of solvable answers.
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Our estimate of the alpha among Americans is 0.84, close to the estimate of 0.88 by Tversky and
Kahneman (1992). The mean alpha estimate is 0.97 for Asians. A lower loss aversion coefficient and a
higher exponent estimate of Asians compared to those of Americans are broadly consistent with the
findings of Weber and Hsee (1998) and Hsee and Weber (1999) that Asians are less risk averse compared
Table 2. Mean Parameter Estimates of the Value Function (Study 2)
Loss Aversion (λ)
Note: The loss aversion coefficient is defined as the reported amount of the gain prospect divided by the pre-
specified loss prospect ($25, $50, or $100) in a 50:50 gamble such that a subject is indifferent between the gamble
and a sure outcome of zero. The exponent of the value function (α) is defined as α = log(2)/log($50/X), or α =
log(2)/log($100/X), where X refers to the reported dollar amount that would make subjects indifferent between a
sure amount of X and a 50:50 gamble of a zero and a $50/$100 gain/loss. The α estimates for a gain and a loss
gamble of the same magnitude ($50 or $100) were averaged for each subject. The number of observations is in
We then proceeded to test reference point adaptation to outcome payoffs. As discussed previously,
we employed the experimental design of Arkes et al. (2008) to test whether (a) reference points adapt
faster to gains than to losses, and (b) a forced sale/repurchase event helps foster adaptation among Asian
subjects. Furthermore, we looked for possible cultural differences in these adaptation patterns.
4.2. Stock Trading Game with Monetary Incentive (Study 3)
4.2.1. Research Participants
The participants were 176 subjects from DePaul University, Florida State University, and The Ohio State
University in the US, 94 subjects from Sun Yat-Sen University in China, and 116 subjects from Yonsei
University in Korea. We recruited undergraduate business majors through e-mails, fliers, and in-class
announcements. The study occurred outside of class time.