Journal of International Fisheries
vol.20，2021▶Article ◀

Consumer Preference for Cultchless Unspawned Oysters in Japan Using aContingent Valuation Method and Analytic Hierarchy Process
Hiroki Wakamatsu†, Tsutom Miyata＊ and Ryutaro Kamiyama（Japan Fisheries Research and Education Agency／＊Japan International ResearchCenter for Agricultural Science）
E-mail：†hwakamatsu@affrc.go.jp【abstract】
Demand for oysters has seen a significant rise in oyster bars in Japan, which haverecently gained popularity among consumers. This study undertakes a consumer
preference study to compare a new brand of cultchless unspawned oysters, “Amakoro,”with conventional oysters. We survey the willingness to pay (WTP) for both oyster types
as well as consumers’ evaluation of the oysters’ appearance, flavor, taste, and texture.
Based on a contingent valuation method and analytic hierarchy process, we analyze theextent to which each factor of consumers’ tastes explains WTP. The results show thatin terms of appearance, Amakoro is preferred over the conventional oyster, which is
positively correlated to WTP. The conventional oyster is inelastic to any type of taste
factor but has a robust value. In addition, the results show that WTP largely depends
on the characteristics of location and frequency of visits to oyster bars.
【keywords】
AHP, consumer preference, CVM, Japan, oyster

1．Introduction
The Great East Japan Earthquake and collateral tsunamis inflicted critical damage
to all aquaculture facilities for oysters, Crassostrea gigas, in Miyagi Prefecture. The
Japanese government immediately initiated a plan to recover the damaged facilities,
including the oyster-processing factories. However, even after the production facilities
were recovered, oyster sales in Miyagi declined and their production reached one-fourthof that before the earthquake, owing to labor shortage and other reasons (Tohoku
Regional Agricultural Administration Office (2014)). In addition, the production ofshelled oysters requires cumbersome shell-shucking labor. Thus, staffing constraint
and high wage rates make the production of shelled oysters less profitable (Yoshio- 19 -

Hiroki Wakamatsu, Tsutom Miyata and Ryutaro Kamiyama

Okuda, sales head in Miyagi Fisheries Cooperative, personal communication, February
2, 2014). However, the production of unshelled oysters can circumvent this shucking
process, thereby possibly saving labor power and cost, while increasing profitability(Kamiyama and Miyata (2021)).
To improve profit structure, Miyagi Prefecture and Japan’s Ministry of Agriculture,
Forestry and Fisheries launched a project after the earthquake to introduce a brandnew, high-quality oyster. Before the earthquake, the oyster industry in Miyagi focusedon shelled raw oysters. However, considering the increased demand for oysters in oyster
bars and restaurants in Japan, the production of unshelled oysters is expected to
improve the profit structure.
The “Amakoro oyster” is a new oyster brand with new properties of being cultchless(1)and unspawned(2). This oyster is smaller, sweeter, and more pure-tasting thanconventional oysters(3). While conventional oysters are produced in two or three years,
Amakaro oysters are produced within one year. Consequently, the Amakoro producers
can save one- or two-year running cost for production. In addition, cultchless type of
products cut costs for oyster producers because the shells do not have to be removed toship out the oysters to the market. Conventional oysters are cultured as an
agglomeration, similar to a big ball, and they need to be separated into individual
oysters during harvesting. Amakoro oysters are separated before they are cultured,
which makes the shape of the oyster shell balanced compared with the cultch oyster.
Estimation of the added value of cultchless unspawned oysters helps the oyster
industry to develop a variety of oysters in the future. A marketer should understandthe purchasing factors preferred by consumers, to anticipate an effective promotion forrestaurants, such as oyster bars.
Literature exists on consumer preference for conventional oysters (Cheng and Capps(1988)), but it is limited to home consumption. No study has targeted consumption in
the dining industry. However, as demand for this new oyster type is not addressed in
the literature, it is necessary to analyze the estimation not only for the industry but
also toward its academic contribution. Grabowski et al. (2003) examined whether US
consumers prefer the taste of native oysters or the non-native ones. However, as theirfindings were limited to quality measures between the two oyster types, it is unclear if
preference in taste is directly connected to willingness to pay (WTP). While WTP has
been measured in many studies, the literature on WTP for oysters is limited (Alfnes etal. (2006), Johnston and Roheim (2006), Nguyen et al. (2015), Quagrainie and Engle(2006), Wirth et al. (2007)). Although Nguyen et al. (2015) measured WTP for oysters- 20 -

Consumer Preference for Cultchless Unspawned Oysters in Japan Using a Contingent
Valuation Method and Analytic Hierarchy Processcompared to other seafood, the contingent valuation method (CVM) cannot decompose
the total value into the WTP of purchasing factors or quality measures, such as taste,
appearance, flavor, and texture. To estimate marginal WTP, each evaluation parameter
needs to be collected separately by survey and considered in the regression analysis.
The discrete choice experiment (DCE) is a popular method to estimate consumers’
WTP by decomposing purchasing factors. Since the DCE approach requires the settingof attributes and levels in its experimental design, it is unsuitable for this study because
it is difficult for consumers to understand levels of an oyster’s quality measure.
Moreover, people’s sensory evaluation of food is generally difficult to apply inquantitative research because the evaluation consists of several sensory factors, suchas taste, appearance, flavor, and texture. Even though the evaluation can be quantified(such as using a 5-point Likert scale), the importance/priority across factors is difficult
to weigh. We employ an analytic hierarchy process (AHP) in this study to obtain people’s
evaluation, which can quantify consumers’ evaluation while considering the weights ofpurchasing factors (Saaty (1977)).
We targeted customers in oyster bars and surveyed consumer preference forcultchless unspawned oysters over their conventional rivals at oyster bars in Japan. We
used Amakoro oysters as an example of new cultchless unspawned oysters. This study
has a twofold approach: we first calibrate consumers’ subjective evaluations for
Amakoro and Kamaishi oysters (as control) to build quality indicators using an AHP.
Thereafter, we adopt a CVM to investigate how WTP is attributed to the AHP indicatorsand other socio-demographics.

2．DataTo investigate consumer preference in oyster bars, we conducted survey research at
the oyster bars of Humanweb Inc.－the largest oyster bar company in Japan. For
comparison, as Amakoro oysters are distributed in summer, we used oysters from
Kamaishi, which are a major oyster brand traded in summer. We had both Amakoro
and Kamaishi oysters delivered to oyster bars and asked Humanweb’s customers totaste and compare them.
The survey was undertaken at five oyster bars around the Greater Tokyo area as
most oyster bars (21 out of 30 Humanweb bars in Japan) are located in the region(Humanweb, October 27, 2015, www.oysterbar.co.jp/shop). The survey is attached inAppendix B. We surveyed 150-200 respondents (30-40 at each bar) but managed to- 21 -

Hiroki Wakamatsu, Tsutom Miyata and Ryutaro Kamiyama

Table 1

Age and Gender of Respondents

Age/Gender

Male

FemaleTotal (%)

10s

0

1

1 (1)

20s

3

30

33 (30)

30s

11

18

29 (27)

40s

18

14

32 (29)50s

64

10 (9)

60s

2

0

2 (2)

70s or older

2

0

2 (2)

Total

42

67

109 (100)

Figure 1

Frequency of Oyster Bar Visits Per Yearobtain only 127 respondents(4). Upon filtering irrational and invalid responses, theeffective sample size was 109.
Table 1 tabulates the composition of respondents in terms of age and gender. Basedon random extraction of the sample from oyster bars in Tokyo, it is evident that those
aged in their 20s, 30s, and 40s comprise 86% of all the respondents, which indicatesthat oyster bars are popular among the younger age group. Regarding gender, there are
more female customers than males in the younger age groups, while the proportion ofmales increases with customers’ age.
Figure 1 shows the number of visits made by the respondents to oyster bars per year.
Most consumers visit oyster bars once every two to four months. On the other hand, a
few consumers visit oyster bars more than once per month (12 times/year). It follows
that most consumers do not visit oyster bars very often.
- 22 -

Consumer Preference for Cultchless Unspawned Oysters in Japan Using a Contingent
Valuation Method and Analytic Hierarchy Process

3．Method
We first calibrate consumers’ evaluation of both oysters via the AHP, and then, we
analyze their WTP, including AHP indicators, other control variables, and dummy
variables in the CVM. Accordingly, we first explain AHP theoretically and practically,followed by the CVM.
3-1．Analytic Hierarchy Process
The AHP was developed by Saaty in the 1970s to quantify various choices to set
priorities (Saaty (1977)). It is applied in a variety of fields as it enables researchers toquantify any type of comparable target via a pairwise comparison method. A goal andtargets for evaluation have to be set, such as Amakoro and Kamaishi oysters, todetermine priorities based on evaluation criteria, and subsequently, to judge the targets.
Figure 2 outlines this study’s AHP structure.

Goal

Evaluation
Criteria

Choose the best oyster

Appearacne

Alternatives

FlavorAmakoroFigure 2
Table 2

Taste

TextureKamaishiAHP Hierarchical Structure

Importance of Evaluation Criteria

Table 3

Importance of Alternatives- 23 -

Hiroki Wakamatsu, Tsutom Miyata and Ryutaro Kamiyama

The weighted evaluation for each criterion is calculated using either the geometricmean or eigenvector approach. We employed the geometric mean method because it iseasier to calculate and generates consistent results if the number of factors is less than
five (Manabe (2000)). This study uses four factors for the evaluation. Although the
eigenvector method is more accurate, pairwise comparisons are assumed to beconsistent (Saaty (1988)). The eigenvector method has larger errors while those of thegeometric mean method are relatively small and have an invariant property in pairwise
comparison (Dijkstra (2013)).
Following Saaty (1988), we designed pairwise comparisons for both the evaluation
criteria (Table 2) and alternative choices (Table 3). The actual design is attached inAppendix B, and the survey is written in Japanese (please contact the author for the
English version). Let a and b denote sets of evaluations: a ={1, 3, 5, 7} and b = {1, 3}.
The weights are the values of the geometric mean of each row divided by their sum,𝑛√∏𝑗 𝑎𝑖𝑗𝑛, where n is the number of variables in the row. We obtained four weights in∑𝑖 √∏𝑗 𝑎𝑖𝑗

the evaluation criteria table and two weights in the alternative table. In addition, we
obtained the weighted values for each alternative by multiplying each weight of thealternative by each weight of the evaluation criteria. The sum of the weighted values
was the general AHP value for each alternative.
3-2．Contingent Valuation Method
We developed a WTP estimation model for Amakoro and Kamaishi oysters based on
survey-stated preferences. The CVM is utilized in various fields, including
environmental evaluation and marketing of a new commodity (Carson et al. (2001),
Johnston and Roheim (2006), Loureiro and Lotade (2005), Loureiro et al. (2002), Lusk
and Schroeder (2004), Murphy et al. (2005)). In the CVM, consumers are asked to state
their preference for the target, which sometimes creates bias due to the lack of apayment obligation (Murphy et al. (2005), Nape et al. (2003), Ehmke et al. (2008)).
Kallas and Gil (2012) used a payment-card format method to obtain the WTP of
respondents in their study, where the combination of AHP and CVM was first applied
to agro-food products. However, the WTP in this method may be biased by the range of
product prices that researchers arbitrarily set (Freeman (2003)). Because estimating
the price of a brand-new product is considered difficult, we decided to choose anothermethod.
- 24 -

Consumer Preference for Cultchless Unspawned Oysters in Japan Using a Contingent
Valuation Method and Analytic Hierarchy Process

In this study, we collected consumer preference using an open-ended question
approach, which generates strong bias when respondents are unfamiliar with theevaluation target and do not have a base price (homegrown value) in mind (Cummings

et al. (1995), Rutström (1998)). For shopping, consumers are confronted with choices
across many aspects of commodities, including price, quantity, quality, and competition.
Thus, consumers are not used to open-ended pricing without alternatives (Freeman(2003)). In the CVM, private goods that are familiar to consumers generate relatively
less hypothetical bias (Murphy et al. (2005)). This study surveyed customers in oyster
bars by asking them to consume both oyster types for free and state their WTP. In thisway, the customers were already in the oyster bar and had already made their choicesfrom the menu, it more or less reduced hypothesis bias while we did not verify if every
single customer checked the menu and price before they responded to our survey. In
addition, most customers visited the oyster bar more than once, according to Figure 1.
Thus, we tried to reduce hypothetical bias; however, we could not eliminate it. Therefore,
the estimated WTP for oysters may be affected by some hypothetical bias, and we
focused on the difference in the WTP for Kamaishi and Amakoro oysters and estimatedall the factors, except for the base price (constant). To get more truthful values, an
incentive-compatible method, such as the auction method or market data, is desirable.

4．Econometric Model
We developed our econometric model for the stated preference for oysters within a
CVM framework. The responses in values are obtained using the open-ended question
method, which can simply be interpreted as WTP or compensating surplus (Freeman(2003)). The following linear model is developed accordingly:
𝑊𝑇𝑃𝑖 = 𝒒𝒊 𝜷 + 𝒛𝒊 𝜸 + 𝜀𝑖(1)where q is a vector of quality variables, including AHP indexes (appearance, flavor,
taste, and texture), types of oysters (Kamaishi as a reference), and interaction terms
between AHP indexes and the dummy of Amakoro oysters; and z is a vector of dummy
variables, including gender (female), age (young and old age groups), and bar locations;
Yokohama, Futakotamagawa, and Ikebukuro, as control variables, as shown in Table 4.
We pooled the WTP of both Amakoro and Kamaishi oysters and treated it as panel
data, by regarding Amakoro and Kamaishi as the same oyster belonging to Crassostrea

gigas. Thus, the panel data consist of two dimensions: individuals and species. This is
not ordinary cross-sectional and time-point panel data, but we apply panel data
- 25 -

Hiroki Wakamatsu, Tsutom Miyata and Ryutaro Kamiyama

Table 4

Variables for Regression

Description
1 if the oyster is from Kamaishi, 0 otherwise

Mean(Std. Dev)
0.50 (0.50)

Weighted AHP index for appearance

0.08 (0.07)

Flavor

Weighted AHP index for flavor

0.08 (0.09)

Taste

Weighted AHP index for taste

0.03 (0.03)

TextureWeighted AHP index for texture

0.04 (0.03)

Appearance if Kamaishi =0, 0 otherwise

0.06 (0.08)

Amakoro×Flavor

Flavor if Kamaishi =0, 0 otherwise

0.05 (0.07)

Amakoro×Taste

Taste if Kamaishi =0, 0 otherwise

0.01 (0.03)

Amakoro×Texture

Texture if Kamaishi =0, 0 otherwise

0.02 (0.03)

1 if the respondent is female, 0 otherwise

0.61 (0.49)

Youth (39 years or
less)Elder (60 years or
more)Consumption Pattern

1 if the respondent is under 39 years, 0
otherwise
1 if the respondent is 60 years or more, 0
otherwise

0.13 (0.34)

Frequency of visit

The number of oyster bar visits per year

5.35 (5.94)

1 if the respondent is surveyed in Ikebukuro,
0 otherwise
1 if the respondent is surveyed in
Futakotamagawa, 0 otherwise
1 if the respondent is surveyed in
Yokohama, 0 otherwise

0.23 (0.42)

Variables
Kamaishi
Quality Criteria
Appearance

Interaction
Amakoro×Appearance

Socio-demographics
Female0.58 (0.50)

Location dummy
Ikebukuro
Futakotamagawa
Yokohama

0.11 (0.31)
0.22 (0.42)* The number of observations is 218.

analysis, which is developed to keep a random-sampling assumption for repeatedsamples (Baltagi (1995), p191). This study adopts the random effects model, as the fixed
effect model drops invariant sociodemographic variables across the type of oysters due
to a collinearity problem (Greene (2003), p118). To choose the model, the Lagrange
multiplier (LM) test is conducted and rejected, and thus a random effects model is- 26 -

Consumer Preference for Cultchless Unspawned Oysters in Japan Using a Contingent
Valuation Method and Analytic Hierarchy Processadopted(5). However, heteroskedasticity did not exist, according to the result of theBreusch–Pagan test, and no disparity was found across ordinary, robust, andbootstrapped standard errors. Consequently, the estimation result was not robust
because of the insufficient sample size, rather than because of the data measurement
error.

5．Results
5-1．Analytic Hierarchy Process
The values of the AHP indicators for each evaluation criterion are shown in Figure 3.
The appearance of the Amakoro oysters is highly evaluated compared with that of
Kamaishi. This is probably because Amakoro oysters have relatively deep-cupped shells,
while Kamaishi oysters have barely cupped and flattened shells. This makes Amakorooysters puffed, whereas Kamaishi oysters are flat. Respondents prefer puffed oyster toflattened ones. Other than appearance, they have almost the same value as the other,although the flavor of Amakoro oysters is slightly stronger than that of Kamaishi, while
the other criteria are slightly lesser than those of Kamaishi oysters. The aggregated
AHP indicator is higher for Amakoro by 0.044 points. In the AHP, inconsistency is
discussed because it affects decision-making. However, in regression analysis, asinconsistency is treated as an error term, unbiased estimates will be obtained unless a
sufficient sample size is collected. We probed the consistency of the regression results,
regardless of whether the inconsistency of the AHP indicators generated bias in the
regression results.
5-2．Contingent Valuation Method
Table 5 presents the result of the open-ended CVM, as well as responders’ WTP for
Amakoro and Kamaishi oysters, evaluated in yen. Both standard deviations are small,and the variance of these preferences is relatively small. However, the standard
deviation of the price difference between Amakoro and Kamaishi oysters (Difference =Amakoro – Kamaishi) is larger than the mean value. As mentioned above, the listed
price for Kamaishi oysters is approximately 550 yen, which is 80 yen below the CVM
result. There is always a problem of hypothetical bias in CVM studies; however, byemploying real customers of oyster bars as participants in this study, we successfully
reduced overall hypothetical bias because the stated average price is lower than thelisted price.
- 27 -

Hiroki Wakamatsu, Tsutom Miyata and Ryutaro Kamiyama

Figure 3

AHP Indexes by Each Factor of Amakoro and Kamaishi

Note: Summed values of respective indexes are shown as Aggregated
AHP index. Respective quality criteria are the broken values of
AHP Indexes range between 0.03 to 0.11. The broken values of
Amakoro (Kamaishi) are, 0.11 (0.05) in appearance, 0.1 (0.09) inflavor, 0.03 (0.04) in taste, and 0.04 (0.05) in texture.

Table 5

Surveyed Open-ended Stated Preference (WTP)
Mean

Std. Dev.

Min. Price

Max. Price

Amakoro

411.8

160.2

100

950

Kamaishi

470.7

136.4

150

880

Difference

-58.9

114.4

-400

300

Figure 4 presents the histograms for prices of Kamaishi and Amakoro oysters. Someparticipants bid 600 yen or more for the Kamaishi oysters, which may be a hypotheticalbias but is negligible when averaged.
5-3．Regression Analysis
Table 6 presents the results of the ordinary least squares and random effects model
estimation. The LM test for random effects rejected the null hypothesis that the- 28 -

Consumer Preference for Cultchless Unspawned Oysters in Japan Using a Contingent
Valuation Method and Analytic Hierarchy Process

Figure 4

Histograms of WTP for Kamaishi and Amakoro oysters

variance across entities is zero, and we adopted the random effects model. The results
indicate that the WTP for Amakoro oysters is attributable to appearance and texture,
while that for Kamaishi has an invariant value to quality measures because thecoefficients of quality in the main effects (for Kamaishi) are insignificant. However, theKamaishi dummy is significant, and instead, it plays a role in the base price only for
Kamaishi oysters. Accordingly, regardless of the quality evaluation, consumers have aconstant WTP for Kamaishi oysters. While the consistency of the AHP indexes (C.I.)
indicates that some participants’ AHP index was inconsistent, we conducted arobustness check and found that inconsistent indexes did not affect our results (SeeAppendix A).
Conversely, for the Amakoro results, an insignificant coefficient and many significant
interaction variables of quality make the WTP for Amakoro dependent on quality
measures. In addition, the estimated magnitude in the quality criteria is large.
Moreover, in this study, we introduced dummy variables to treat the heterogeneity of
the location of restaurants, considering a variety of customers’ characteristics andoyster prices in oyster bars. The variable became significant and controlled forheterogeneity across oyster bars. We set the base as the Ginza and Hamamatsucho
areas, since they are located close to each other and their target clientele are business- 29 -

Hiroki Wakamatsu, Tsutom Miyata and Ryutaro Kamiyama

people. The post-estimation equality tests between the WTP of Ikebukuro and those ofother locations show a significant difference. Age dummies were not found to havesignificant relationships with WTP, but the frequency of visits had a significant
correlation to WTP; the WTP for oysters increased as customers visited oyster bars
more frequently. The averages of the predicted values (𝑦̂=Xb) of all the participants are
406 yen per Amakoro oyster and 471 yen per Kamaishi oyster.
Table 6

Estimation Results of the Ordinary Least Squares (OLS) and Random-Effect
Model
OLS

Variables
Kamaishi
Quality Criteria
Appearance
FlavorTaste
TextureInteraction
Amakoro×Appearance
Amakoro×Flavor
Amakoro×Taste
Amakoro×Texture
Socio-demographics
FemaleYouth (age 39 or less)
Elder age 60 or older
Consumption Pattern
Frequency of visit
Location dummy
Ikebukuro
Futagotamagawa
Yokohama
Constant
Adjusted R-squared

Std.
Err.

Estimates

***

124.6

375.33

**

477.6
329.1
499.3
477.3

-376.82-252.69
212.35-774.73

567.3
505.7
729.8
823.5

1211.391066.88992.381633.91

Estimates
380.78-234.70-269.84
407.42-978.33
1075.961148.56918.741802.55

Random Effects

**

**

Std.
Err.
**

152.5
339.9
263.4
408.2
368.9

**

**

581.4
582.6
877.1
802.4

47.83
-25.13
3.00

**

24.0
23.8
31.6

49.12
-23.06
5.80

5.47

***

1.8

5.63

**

2.3

28.5
36.5
28.4
97.8

131.8321.92-44.54
96.13
0.28

***

36.5
44.4
30.9
108.9

133.2522.20-41.57
89.43
0.28

26.1
26.7
30.8

Note: This study regards statistical significance level at 5% or more, and excludes
the 10% level from the result. ** and *** denote significance levels at 5%
and 1%, respectively. The four quality criteria are the AHP index values that
range from 0.03 to 0.11, as shown in Figure 3.

- 30 -

Consumer Preference for Cultchless Unspawned Oysters in Japan Using a Contingent
Valuation Method and Analytic Hierarchy Process

Amakoro’s AHP indexes for quality criteria range from 0.07 to 0.63 (appearance), 0.08
to 0.56 (flavor), and 0.08 to 0.45 (texture). Thus, upon multiplying the respective
significant estimates, the ranges of Amakoro’s estimated WTP for the respective criteria
are 84.8-736.1 yen (appearance), 85.4-597.5 yen (flavor), and 130-735.3 yen (texture).(6)6．Discussion
This study adds a new finding to existing literature that has not evaluated oysters
with respect to price and the quantified quality measure. Both aspects have been
considered in this study. The quality measure in price provides stakeholders with more
useful marketing and production strategies.
To answer the research question posed in the Introduction section, we investigatedwhether consumers would accept the new cultchless unspawned oysters at oyster bars.
We found that the consumer preference for the Amakoro oysters was attributed to someof the quality measures, while Kamaishi oysters were invariant to the quality measure.
Thus, consumers who found value in the qualities of the Amakoro oysters might haveshown higher WTP for them, despite the Kamaishi oysters being superior to the
Amakoro oysters at least in terms of size (Figure 5). Thus, despite the qualities of theKamaishi oysters not being as satisfactory as those of the Amakoro oysters, consumers
might have had a solid WTP for Kamaishi oysters.
However, Amakoro oysters have a cost advantage. As Kamaishi oysters are spawned
and commonly take two to three years to produce, they cost more than Amakoro oysters.
For future research, a benefit–cost analysis is necessary if cultchless unspawned oyster
is more profitable than the conventional 2-3-year oysters.

Figure 5

Amakoro Oysters (Left-hand Side of Plate) and Kamaishi Oysters (Right-handSide of Plate)- 31 -

Hiroki Wakamatsu, Tsutom Miyata and Ryutaro Kamiyama

Are consumers willing to pay for Amakoro oysters at the commercial level? According
to our result, the answer is in the affirmative, if 412 yen makes commercial sense. The
WTP for Kamaishi oysters is estimated at 470 yen in this study, but they are sold forapproximately 550 yen in oyster bars. Accordingly, paying 412 yen for Amakoro oysters
seems acceptable, especially considering that the price of oysters is approximately 500
yen (Yusuke Tobiki, Personal communication, May 14, 2015).
According to the regression analysis results, while no sociodemographic factors, suchas gender or age correlate with the WTP, customers who frequent oyster bars tend to
be willing to pay more for oysters as their frequency of visits increases. The estimation
result shows that one visit results in an increase of 5.6 yen per oyster, and the mean
visit frequency is 5 times per year. Thus, 25 yen per oyster can be added for repeat
customers. However, customers who visit less frequently prefer cheaper oysters. Thus,
discount coupons for less-frequent customers may be a strategy to make them consume
more oysters. The results also indicate that the appearance and texture of the Amakorooyster attract customers. Although texture cannot be detected unless the oysters are
consumed, appearance is an easy way to differentiate and promote Amakoro oysters. A
new cultchless unspawned oyster is evaluated 58 yen lower than conventional famous
oysters. Therefore, besides the appearance, tasting service is desirable for such newoysters to survive as a fixed menu in the bar, as their texture can be differentiated fromconventional oysters.
Since this study aimed to compare a specific brand with another, the result and its
interpretation is limited only to the specific brands. For a more general implication, it
is necessary to compare the relationship between cultchless unspawned and ordinary
oysters. Thus, further studies would provide a more general interpretation for Japan’s
oyster industry.
One of the limitations of this study is the size difference. The size of the Kamaishi
oyster is two to three times larger than that of the Amakoro oyster; however, we did notinclude oyster sizes in our AHP design, which may not typify consumer preference if
the size is an important purchasing factor.
Note(1) The cultchless oyster, which is also called the single-seed oyster, is separated from ahatchery, set on an oyster shell (cultch), and grown in clusters separately.
(2) Ordinary oysters are delivered after spawning season due to size limitations, but the
production process of Amakoro oysters is adjusted so that they can be delivered before- 32 -

Consumer Preference for Cultchless Unspawned Oysters in Japan Using a Contingent
Valuation Method and Analytic Hierarchy Process
the spawning season.
(3) Kahoku Shinpo. (2015) “Debut of “Amakoro oyster”, symbol of recovery,” Kahoku Sinpo,
Kahoku Sinpo Publishing, Miyagi, July 14, 2015 (in Japanese).
(4) In 2015, 1,500 Amakoro oysters were due to be delivered to Humanweb oyster bars, but
owing to timing delays during the harvest, only 150 were delivered.
(5) The Hausman test was not effective, as the chi-square value became negative, probably
because the lack of samples enlarged the variance in the regression.
(6) Significance levels above 5% are considered in this discussion. The linear combinationof the main effect and Amakoro interaction terms are tested, and the chi-square test
significant probabilities are 0.3% for appearance, 2% for flavor, 1% for taste, and 12%
for texture.

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[Acknowledgments] This study was sponsored by Japan’s Agriculture, Forestry and
Fisheries Council as part of a project for developing research on reforming the production
system in fisheries and aquaculture. All the necessary costs related to this study were
provided by this project. We thank the council for this support. We also appreciate thecooperation of Humanweb Inc. Lastly, we thank the anonymous reviewers and interviewees
in this study for providing useful comments and information.

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