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# A conjoint analysis of the Japanese salmon market

Yuko Kusakabe

University of Rhode Island

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Kusakabe, Yuko, "A conjoint analysis of the Japanese salmon market" (1992). Open Access Dissertations. Paper 3815.

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# A conjoint analysis of the Japanese salmon market

Kusakabe, Yuko, Ph.D.

University of Rhode Island, 1992

U.M.I

300 N. Zeeb Rd.
Ann Arbor, MI 48106
A CONJOINT ANALYSIS OF THE JAPANESE SALMON MARKET

BY

YUKO KUSAKABE

A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE
REQUIREMENTS FOR A DEGREE OF
DOCTOR OF PHILOSOPHY
IN
ECONOMICS - MARINE RESOURCES

UNIVERSITY OF RHODE ISLAND

1992
# A Conjoint Analysis of the Japanese Salmon Market

## Abstract

Given the heterogeneous nature of salmon products, the conventional demand approach which treats salmon as a homogeneous product does not explain sufficiently why the salmon market in Japan is evolving the way it is. This study presents empirical measures of Japanese salmon buyers' preferences for salmon products as a function of product attributes. The relative contribution of individual attributes to the product's overall preference was estimated through two model specifications; two-limit Tobit and rank-order logit. Both models estimated the buyer's preference function reasonably well even though different salmon buyers were surveyed at different points in time. Results from respective model specifications show strong consistency in terms of signs and magnitude for key variables such as price and quality. Changes in buyers' preferences over time indicate the increased importance of quality in the buyer's decision. Marginal effects of variables such as price and quality on preference are evaluated.
Acknowledgment

I would like to express sincere gratitude to my major advisor, Dr. James Anderson for his immeasurable help, support, guidance, and friendship throughout this long process. He was instrumental in its completion. Gratitude is extended to other members of my dissertation committee: Dr. James Opaluch, Dr. Nikhilesh Dholakia for their helpful comments and insights. Special thanks go to the faculty of the Department of Resource Economics, especially department chairman Dr. Thomas Weaver for his continuous support all through my academic endeavors.

My thanks also go to John Gauvin for his love and patience for reading my thesis countless number of times and provided very helpful comments. Great thanks go to my fellow graduate students, especially to my good friend Priscilla Brooks.

A special appreciation is expressed to my parents for their continuous and unconditional love and supports.
# TABLE OF CONTENTS

## Chapter 1. Introduction

1.1 Statement of Problem.................. 1

1.2 Objectives and Method of Analysis......... 3

## Chapter 2. Background

2.1 An Overview of Japan's Salmon Supply......... 5

2.2 Prospects for Japanese Domestic Salmon
Production.................................. 7

2.3 Imports of Salmon...................... 8

2.4 Implications of Increased Supply........ 16

2.5 Summary of the Changes in Japan's Salmon
Supply.................................... 22

2.6 Consumption of Salmon in Japan........ 23

2.7 General Trends in Salmon Consumption........ 25

2.8 Household Level Consumption................ 27

2.9 Changes in the Consumption of Salmon........ 29

2.10 Summary of the Salmon Consumption in
Japan.................................... 33

2.11 Distribution System in the Japanese Salmon
Market.................................... 35

2.12 The Route Through Wholesale Markets........ 36

2.13 Routes Which Bypass Wholesale Markets........ 39

2.14 Difference in Distribution by Species and
End Use.................................. 40

2.15 Summary of the Distribution of Salmon........ 42

## Chapter 3. Theory

3.1 Consumer Utility Theory of a Multi-
Attribute Product...................... 44

3.2 Techniques for Estimating the Demand for
Non-Market Goods.................... 45

3.3 Overview of the Conjoint Analysis........ 48

3.4 Development of Conjoint Analysis........ 49

3.5 Advantages and Shortcomings of Conjoint
Analysis................................ 49

## Chapter 4. Method and Procedure

4.1 Experimental Design.................. 52

4.2 Survey Procedures.................. 60
Chapter 5. Model Estimation

<table><tr><td>5.1</td><td>Introduction</td><td>64</td></tr><tr><td>5.2</td><td>General Model Specification</td><td>64</td></tr><tr><td>5.3</td><td>Statistical Specification for Dependent Variable</td><td>68</td></tr><tr><td>5.4</td><td>Limited Dependent Variable, Censored Regression</td><td>69</td></tr><tr><td>5.5</td><td>Two-Limit Tobit Model</td><td>70</td></tr></table>

Chapter 6. Result

<table><tr><td>6.1</td><td>Introduction</td><td>74</td></tr><tr><td>6.2</td><td>Self-Explicated Measure</td><td>75</td></tr><tr><td>6.3</td><td>Variable Selection for Data Pooling</td><td>80</td></tr><tr><td>6.4</td><td>Overall Result</td><td>83</td></tr><tr><td>6.5</td><td>Comparison among Attribute Levels</td><td>88</td></tr><tr><td>6.6</td><td>Marginal Effect</td><td>94</td></tr><tr><td>6.7</td><td>Summary</td><td>102</td></tr></table>

Chapter 7. Summary, and Future Research Direction

Appendix 108

Bibliography 109
LIST OF TABLES

TABLE

<table><tr><td>2.1A</td><td>Japanese Imports of Fresh Salmon by Country (1980-1990)</td><td>12</td></tr><tr><td>2.1B</td><td>Estimated Percentage Share of Wild-caught and Cultured Salmon in Japan's Fresh Salmon Imports</td><td>12</td></tr><tr><td>2.2A</td><td>Japanese Imports of Frozen Salmon by Country (1980-1990)</td><td>14</td></tr><tr><td>2.2B</td><td>Estimated Percentage Share of Wild-Caught and Cultured Salmon in Japan's Frozen Salmon Imports</td><td>14</td></tr><tr><td>2.3A</td><td>Japanese Imports of Cured Salmon by Country (1983-1990)</td><td>15</td></tr><tr><td>2.3B</td><td>Estimated Percentage Share of Wild-Caught and Cultured Salmon in Cured and Smoked Salmon Imports</td><td>17</td></tr><tr><td>2.4</td><td>Japanese Imports of Salmon by Product Type</td><td>17</td></tr><tr><td>2.5</td><td>List of Salmon Products Available at Retail Level</td><td>24</td></tr><tr><td>4.1</td><td>A Listing of the Attributes and Attribute Levels</td><td>54</td></tr><tr><td>4.2</td><td>Fractional Factorial Design Matrix for the Experiment</td><td>57</td></tr><tr><td>4.3</td><td>A Sample of the Hypothetical Product Profiles</td><td>59</td></tr><tr><td>5.1</td><td>A List of Explanatory Variables Used in the Estimation</td><td>65</td></tr><tr><td>5.2</td><td>Average Wholesale Prices of Salmon by Species and Product Type Used as Base Prices</td><td>67</td></tr><tr><td>6.1</td><td>Weighted Average of the Direct Evaluation of Attributes in the Self-Explicated Measure</td><td>77</td></tr><tr><td>6.2</td><td>Weighted Average of the Direct Evaluation of Attribute Levels in the Self-Explicated Measure Scores</td><td>79</td></tr></table>
<table><tr><td>6.3</td><td>Two-Limit Tobit Model with Separate Intercept and Coefficients for 1988 and 1989 Survey Years</td><td>82</td></tr><tr><td>6.4</td><td>The Results of Conjoint Analysis; Two-Limit Tobit Model</td><td>84</td></tr><tr><td>6.5</td><td>The Results of Conjoint Analysis; Rank-Order Logit Model</td><td>85</td></tr><tr><td>6.6</td><td>Wald Test for Coefficient Change Over 1988 and 1989 Survey Year in the Partially Pooled Model for Two-Limit Tobit</td><td>86</td></tr><tr><td>6.7</td><td>Mean Spearman Rank-order Correlation Coefficient between Observed and Predicted Ranks</td><td>89</td></tr><tr><td>6.8</td><td>The Marginal Effects Estimated at Mean Value of X in the Two-limit Tobit Model</td><td>96</td></tr></table>
LIST OF FIGURES

FIGURES

<table><tr><td>2.1</td><td>Japanese Salmon Supply 1976-1990.</td><td>6</td></tr><tr><td>2.2</td><td>Japanese Imports of Salmon by Product Type 1980-1991.</td><td>9</td></tr><tr><td>2.3</td><td>Japanese Imports of Fresh and Frozen Salmon in 1988 Quantity.</td><td>10</td></tr><tr><td>2.4</td><td>Japanese Imports of Salmon, Estimated Share of Wild and Cultured Salmon 1980-1990.</td><td>18</td></tr><tr><td>2.5</td><td>Carry Over Inventory of Frozen Salmon 1976-1990.</td><td>19</td></tr><tr><td>2.6</td><td>Average Wholesale Price of Frozen Chum and Sockeye Salmon (1985-1990).</td><td>21</td></tr><tr><td>2.7</td><td>Annual Consumption of Salmon by Region in 1990.</td><td>26</td></tr><tr><td>2.8</td><td>Apparent Consumption of Salmon in Japan 1976-1990.</td><td>28</td></tr><tr><td>2.9</td><td>Japanese Household Consumption of Salmon 1976-1990.</td><td>30</td></tr><tr><td>2.10</td><td>Per Capita Consumption of Salmon at Overall and the Household Level.</td><td>32</td></tr><tr><td>2.11</td><td>Share of Food Expenditure on Selected Food Categories.</td><td>34</td></tr><tr><td>2.12</td><td>Distribution of Salmon in Japan.</td><td>37</td></tr><tr><td>6.1</td><td>Effect of Price Deviation From Average Market Price on Sockeye Salmon from Canada and Alaska.</td><td>98</td></tr><tr><td>6.2</td><td>Effect of Quality Changes on Sockeye Salmon From Canada and Alaska.</td><td>100</td></tr><tr><td>6.3</td><td>Effect of Price Deviation From Market Price on Salmon Species.</td><td>101</td></tr></table>
# Chapter 1. Introduction

## 1.1 Statement of the Problem

Japan ranks as the top salmon consuming countries in the world. During the period between 1976 and 1990, Japan's total supply of salmon increased markedly from 129,778 MT to 416,768 MT. The consumption of salmon in Japan represented approximately 37 percent of the world's production of salmon in 1990 (Ministry of Agriculture, Forestry, and Fishery of Japan 1990; FAO 1990). This increase in supply of salmon did not happen as a linear expansion.

The rise of aquaculture worldwide, coupled with Japan's dwindling operations in the high-seas, is changing the whole outlook of Japanese salmon market. There have been significant changes in terms of the product forms in which salmon is imported, the share of cultured salmon in the market, and the presence of new suppliers. Imports of fresh salmon have been increasing rapidly in recent years, though salmon is still primarily imported frozen. The share of cultured salmon (fresh and frozen) increased to approximately 16 percent in 1990. Japan is now importing salmon from an increasingly diversified assortment of suppliers. Countries such as Chile, New Zealand, and Australia have recently joined the arena.

These changes in the market are inevitably reflected in the way salmon is consumed. Salmon is consumed in an increasingly diversified selection of product types and
market outlets. As the market has gone through these
changes, salmon products have become increasingly more
differentiated, not only by such factors as species and
size, but also by method of catch, whether farmed or wild-
caught, country or region of origin, and product form. This
increasing array of salmon products is filling different and
new market niches.

Observing these changes in the market motivates a list
of questions such as; Is the cultured salmon replacing wild-
caught salmon or is it filling a newly developed segment of
the market not captured by wild-caught salmon?; Is cultured
salmon considered a good substitute for wild-caught salmon
or it is considered distinctively different product?; Why
is that certain cultured salmon command, on average, higher
prices than many other salmon in the market?; How does the
product being cultured, as opposed to wild-caught, influence
the buyer's purchase decision, other things being equal?

A conventional demand approach which treats salmon as a
homogeneous product does not provide a sufficient basis to
answer these questions and is therefore unable to explain
fully why the Japanese salmon market is evolving the way it
is. The conventional aggregate demand approach ignores real
differences between salmon products and is thus of limited
use in developing an accurate picture of the Japanese salmon
market or Japanese buyer behavior. Questions such as
whether farmed salmon is a perfect substitute for wild-
caught salmon can only be answered by understanding what
## 1.2 Objectives and Method of Analysis

This research embraces the heterogeneous nature of salmon. Salmon is a heterogeneous product differentiated with respect to attributes such as species, origin, flesh color, fat content, size, price, and such. The focus of this research is to elicit buyer's preference structure for salmon in terms of his/her valuation of individual attributes of the product. Buyers preference function is expressed as a function of product attributes. How individual attributes such as product origin or quality influence buyer's overall preference for the product will be estimated.

Available market data only provide average price of salmon broken down by species and product type (fresh, frozen, salted) as if they were homogeneous in all other attributes. Therefore, despite the fact that salmon is widely traded in the market, the buyer's valuation of individual attributes can not be estimated using available market data. The primary data for this research was collected through a survey of salmon buyers in Japan.

A technique called conjoint analysis is used to estimate buyer's valuation of individual attributes of the product from his/her overall valuation of the product. The three principle objectives of this research are:
1) to provide a thorough overview of Japanese salmon market,
2) to estimate Japanese salmon buyer's preference structure
as a function of product attributes,

3) to estimate how salmon buyer's preferences have changed
over time.

This study will also extend previous efforts in
econometric techniques used for the analysis. The model is
developed in the framework of qualitative/limited dependent
variable instead of through ordinary least squares which is
biased and inconsistent when dependent variables are limited
or censored.

Information obtained through conjoint analysis
concerning how each product attribute contributes to the
buyer's preference for the product is useful to the industry
as well as researchers. The information can be used to
differentiate products through product design or through
effective marketing strategies. It can also be used to
evaluate the profitability of targeting a certain segment of
the market. More fundamentally, it will provide insights as
to why the salmon market is evolving the way it is, which
has intrinsic value to both researchers and observers.
# Chapter 2. Background

## 2.1 An Overview of Japan's Salmon Supply

Japan currently obtains salmon and trout from four sources: 1) high-seas fishery; 2) its coastal fishery based on hatchery-returned salmon; 3) domestic aquaculture; and 4) imports. Domestic production (high-seas, coastal, and aquaculture) constituted approximately 60 percent of Japan's total salmon supply in 1990 (Gyogyo Yoshokugyo Seisan Tokei Nenpou 1990; Japanese Imports of Marine Products Statistics 1991).

Figure 2.1 illustrates the changes in supply sources from 1976 to 1990. During this period, Japan's total supply of salmon increased markedly from 129,778 MT to 416,768 MT.<fnref n="1" /> This substantial increase in overall supply of salmon is largely attributable to the increase in coastal landings of hatchery-returned salmon and imports. The shift in supply sources took place after 1976 when 200 mile Exclusive Economic Zones were established in many parts of the world. Japan's high seas fishery has declined steadily since then and it now faces a complete phase-out in 1992. Confronted with the changes in international water boundaries, the Japanese government extended its efforts in hatchery programs significantly. As a result, Japan's coastal catch based on hatchery salmon returns has increased significantly

<footnote n="1">¹ The number is for domestic production and imports, not including a balance of inventory at the beginning and the end of the year.</footnote>
<figure><img src="image_3.png" /><figcaption>FIGURE 2.1: JAPANESE SALMON SUPPLY
1976-1990</figcaption></figure>

SOURCE: STATISTICS AND INFORMATION
BUREAU, MINISTRY OF AGRICULTURE,
FORESTRY AND FISHERY, TOKYO, JAPAN
from 39,434 MT in 1976 to 195,656 MT in 1990 (Gyogyo Yoshokugyo Seisan Tokei Nenpou 1990). Imports, which were insignificant prior to 1976, accounted for 169,981 MT in 1990 which was roughly 40 percent of Japan's total salmon supply (Japanese Imports of Marine Products Statistics 1991). Although still minimal, production of aquaculture salmon accounted for 23,608 MT in 1990 (Gyogyo Yoshokugyo Seisan Tokei Nenpou 1990).

## 2.2 Prospects for Japanese Domestic Salmon Production

Japan's high-seas salmon fishery employs motherships, drift gill-nets, and long-line gear operating within a designated area under the International North Pacific Fisheries Convention (INPFC) and bilateral agreements with the USSR. Due to economic infeasibility, the use of motherships was curtailed in 1989. The land-based fleet operation also faces a complete phase-out from the USSR Exclusive Economic Zone (EEZ) in 1992. Japan-USSR joint ventures, however, may provide access for Japanese vessels to salmon stocks within the EEZ of the USSR after 1992.

The coastal fishery is entirely dependent on returning hatchery-raised salmon. Although hatchery programs involve several species of salmon, chum salmon is the dominant species. The coastal catch of chum salmon has increased significantly from 39,434 MT in 1976 to 195,656 MT in 1990. Coho salmon is the most successful species for aquaculture production in Japan. Aquaculture production of coho salmon
has increased significantly from 72 MT in 1978 to 23,608 MT in 1990, which constituted about 6 percent of the total supply in 1990. Preliminary numbers indicated that the aquaculture production amounted to 26,000 mt in 1991. Efforts in aquaculture production have been expanded to other species of salmon as well.

## 2.3 Imports of Salmon

Imports of salmon are flourishing partly due to the decreasing high-seas quota for Japan and relatively favorable exchange rate for yen. Imports of salmon increased from 3,684 MT in 1976 to 169,981 MT in 1990 and declined slightly to 153,604 MT in 1991 constituting roughly 40 percent of Japan's total salmon supply in these years. A close look at trends in imports reveals ongoing changes in the Japanese salmon market.

Figure 2.2 illustrates Japanese imports of salmon by product type during 1980-1991.<fnref n="2" /> Although salmon is primarily imported frozen (about 94% of total imports in 1991), an increase in fresh salmon imports is apparent in recent years. Imports of fresh salmon increased markedly from 14 MT in 1980 to 8,993 MT in 1990. This trend can be seen even more clearly by expressing the import quantity in terms of an index based on 1988 quantities (Figure 2.3). This increase in fresh salmon imports also signifies a shift

<footnote n="2">² Note: The quantity of fresh and cured salmon imports is plotted on the separate axis from frozen salmon because of the difference in quantity.</footnote>
<figure><img src="image_4.png" /><figcaption>FIGURE 2.2: JAPANESE IMPORTS OF SALMON BY PRODUCT TYPE 1980-1991</figcaption></figure>

SOURCE: JAPANESE IMPORTS OF MARINE PRODUCTS (STATISTICS)
<figure><img src="image_5.png" /><figcaption>FIGURE 2.3: INDEX OF JAPANESE IMPORTS OF FRESH AND FROZEN SALMON
(BASED ON 1988 QUANTITIES)</figcaption></figure>

SOURCE: JAPANESE IMPORTS OF MARINE PRODUCTS (STATISTICS)
from wild-caught salmon to cultured salmon.

Table 2.1A illustrates Japan's imports of fresh salmon by country from 1980 to 1991. Table 2.1B illustrates the estimated percentage share of wild-caught and cultured salmon in fresh salmon imports.<fnref n="3" /> The table also shows the shares of the United States and Norway as representative suppliers of wild and cultured salmon respectively. Despite some fluctuation from year to year, it is obvious that the respective shares of wild and cultured salmon have reversed within the past decade. The share of the wild-caught salmon decreased from approximately 88 percent of total fresh salmon imports in 1980 to 4 percent in 1991. In other words, cultured salmon represented 96 percent of Japan's imports of fresh salmon in 1991.

Also interesting is a shift in key suppliers. Although fluctuating somewhat over time, the U.S. was the leading supplier of fresh salmon to Japan until 1984 when Norway took over the lead. Other European and Scandinavian nations then entered the arena. As other more recent salmon producing countries such as Chile, New Zealand, and Australia have entered the competition, the shares of the U.S., Canada, and some European nations have dropped

<footnote n="3">³ Import statistics are not separated by wild versus cultured salmon. Although some imports from the U.S. are known to be cultured salmon, they are assumed to be minimal. Since 1985, 95% of Canada's fresh salmon exports are assumed to be cultured, while all frozen exports from Canada are assumed to be wild. The share of wild-caught salmon is calculated as the aggregate of imports from U.S., Canada (only until 1985 for fresh salmon), R. Korea, N. Korea, China and USSR.</footnote>
<table><caption>TABLE 2.1A: JAPANESE IMPORTS OF FRESH SALMON BY COUNTRY (1980-1991)</caption><thead><tr><th></th><th>1980</th><th>1981</th><th>1982</th><th>1983</th><th>1984</th><th>1985</th><th>1986</th><th>1987</th><th>1988</th><th>1989</th><th>1990</th><th>UNIT: KG<br>1991</th></tr></thead><tbody><tr><td colspan="14" style="text-align: left; font-weight: bold;">FRESH/CHILLED SALMON</td></tr><tr><td>U.S.</td><td>6,039</td><td>37,757</td><td>205,555</td><td>1,272,389</td><td>4,509</td><td>146,133</td><td>115,411</td><td>264,499</td><td>908,360</td><td>749,810</td><td>370,473</td><td>357,395</td></tr><tr><td>CANADA*</td><td>565</td><td>543</td><td>124</td><td>136</td><td>907</td><td>4,082</td><td>8,771</td><td>25,473</td><td>211,905</td><td>863,613</td><td>435,451</td><td>849,561</td></tr><tr><td>R. KOREA</td><td>5,977</td><td>427,544</td><td>5,024</td><td>5,737</td><td>67,797</td><td>68,557</td><td>79,858</td><td>19,890</td><td>5,355</td><td>245</td><td></td><td></td></tr><tr><td>NORWAY</td><td>1,735</td><td>28,630</td><td>33,443</td><td>77,540</td><td>179,002</td><td>280,672</td><td>587,733</td><td>1,006,482</td><td>2,127,824</td><td>4,872,440</td><td>4,161,583</td><td>4,313,647</td></tr><tr><td>U.K.</td><td></td><td></td><td></td><td>194</td><td></td><td>4,491</td><td>2,076</td><td>16,994</td><td>94,401</td><td>374,286</td><td>404,746</td><td>496,902</td></tr><tr><td>SWEDEN</td><td></td><td>57</td><td>307</td><td>362</td><td></td><td></td><td>3,978</td><td>23,122</td><td></td><td>2,849</td><td>1,712</td><td>5,318</td></tr><tr><td>IRELAND</td><td></td><td></td><td></td><td></td><td>6,516</td><td></td><td></td><td>17,971</td><td>43,864</td><td>5,271</td><td>53,050</td><td></td></tr><tr><td>DENMARK</td><td></td><td></td><td></td><td></td><td></td><td>1,961</td><td>1,945</td><td>28,094</td><td>113,419</td><td>7,200</td><td>29,621</td><td></td></tr><tr><td>ICELAND</td><td></td><td></td><td></td><td></td><td></td><td></td><td>3,740</td><td>417</td><td>290,367</td><td>75,282</td><td>3,264</td><td></td></tr><tr><td>CHILE</td><td></td><td></td><td></td><td></td><td></td><td>11,356</td><td>7,738</td><td>64,232</td><td>36,303</td><td>672,464</td><td>728,679</td><td></td></tr><tr><td>NEW ZEALAND</td><td></td><td></td><td></td><td></td><td></td><td>52,497</td><td>190,764</td><td>244,522</td><td>445,247</td><td>667,037</td><td>822,947</td><td></td></tr><tr><td>AUSTRALIA</td><td></td><td></td><td></td><td></td><td>4,367</td><td></td><td>1,164</td><td>177,423</td><td>282,984</td><td>829,905</td><td>1,363,654</td><td></td></tr><tr><td>OTHERS**</td><td>0</td><td>0</td><td>408</td><td>361</td><td>96</td><td>605</td><td>154</td><td>1,120</td><td>630</td><td>5,263</td><td>63,704</td><td>2,023</td></tr><tr><td>TOTAL</td><td>14,316</td><td>494,531</td><td>244,861</td><td>1,356,719</td><td>252,301</td><td>515,423</td><td>863,795</td><td>1,670,902</td><td>3,907,087</td><td>7,848,097</td><td>7,742,907</td><td>8,993,011</td></tr></tbody></table>

* SINCE 1985, 95% OF THE CANADA'S FRESH EXPORTS ARE ASSUMED TO BE CULTURED.

** OTHERS INCLUDES BELGIUM, FRANCE, NETHERLAND, FINLAND, CHINA AND USSR

<table><caption>TABLE 2.1B: ESTIMATED PERCENTAGE SHARE OF WILD-CAUGHT AND CULTURED SALMON IN JAPAN'S FRESH SALMON IMPORTS</caption><thead><tr><th></th><th>1980</th><th>1981</th><th>1982</th><th>1983</th><th>1984</th><th>1985</th><th>1986</th><th>1987</th><th>1988</th><th>1989</th><th>1990</th><th>UNIT: %<br>1991</th></tr></thead><tbody><tr><td>U.S.</td><td>42.18</td><td>7.63</td><td>83.95</td><td>93.78</td><td>1.79</td><td>28.35</td><td>13.36</td><td>15.83</td><td>23.25</td><td>9.55</td><td>4.78</td><td>3.97</td></tr><tr><td>NORWAY</td><td>12.12</td><td>5.79</td><td>13.66</td><td>5.72</td><td>70.95</td><td>54.45</td><td>66.04</td><td>65.82</td><td>54.46</td><td>59.54</td><td>53.75</td><td>47.97</td></tr><tr><td>WILD</td><td>87.88</td><td>94.20</td><td>86.05</td><td>94.22</td><td>29.01</td><td>41.65</td><td>22.61</td><td>17.02</td><td>23.40</td><td>9.56</td><td>5.61</td><td>3.98</td></tr><tr><td>CULTURED</td><td>12.12</td><td>5.80</td><td>13.95</td><td>5.76</td><td>70.99</td><td>58.35</td><td>77.39</td><td>82.98</td><td>76.60</td><td>90.44</td><td>94.39</td><td>96.02</td></tr></tbody></table>

SOURCE: JAPANESE IMPORTS OF MARINE PRODUCTS (STATISTICS), JAPAN MARINE PRODUCTS IMPORTERS ASSOCIATION
significantly. In 1991, Norway's share represented approximately 48 percent of total fresh salmon imports, while the share of the U.S. represented 4 percent. Chile, New Zealand, and Australia combined represented about 33 percent of Japanese fresh salmon imports.

An increase in aquacultured salmon is also apparent in frozen salmon imports. Table 2.2A illustrates Japanese imports of frozen salmon by country during 1980-1991. Table 2.2B illustrates the estimated percentage share of wild and cultured salmon during the same time period. In 1980, virtually all frozen salmon were wild-caught. Imports of frozen cultured salmon have increased since 1988. In 1991, cultured salmon represented approximately 17 percent of total frozen salmon imports. The U.S. has been by far the largest supplier of frozen salmon to Japan. At its peak in the recent decade, the U.S. share represented nearly 89 percent of total Japanese frozen salmon imports. As imports of frozen cultured salmon increased in recent years, however, the share of the U.S. has decreased accordingly. The U.S. share amounted to 63 percent in 1991. Chile became the largest supplier of frozen cultured salmon in 1990. Its share constituted about 12 percent of the Japan's total frozen salmon imports in 1991.

Table 2.3A illustrates Japan's imports of cured salmon by country. Since 1988, imports of smoked salmon have been recorded independently. While imports of salted salmon have decreased in recent years, imports of smoked salmon have
<table><caption>TABLE 2.2A: JAPANESE IMPORTS OF FROZEN SALMON BY COUNTRY (1980-1981)</caption><thead><tr><th></th><th>1980</th><th>1981</th><th>1982</th><th>1983</th><th>1984</th><th>1985</th><th>1986</th><th>1987</th><th>1988</th><th>1989</th><th>1990</th><th>1991</th><th>UNIT: KG</th></tr></thead><tbody><tr><td colspan="14">FROZEN SALMON</td></tr><tr><td>U.S.A.</td><td>33,018,732</td><td>60,212,220</td><td>93,063,233</td><td>86,669,438</td><td>80,271,219</td><td>102,400,793</td><td>95,893,773</td><td>94,310,551</td><td>105,478,018</td><td>103,282,777</td><td>115,599,896</td><td>90,660,628</td><td></td></tr><tr><td>CANADA</td><td>2,640,973</td><td>5,157,988</td><td>10,833,946</td><td>3,837,041</td><td>5,177,689</td><td>9,847,777</td><td>15,086,699</td><td>9,428,636</td><td>11,332,199</td><td>19,482,287</td><td>18,976,641</td><td>17,853,645</td><td></td></tr><tr><td>U.S.R.</td><td>1,990,644</td><td>2,546,132</td><td>644,906</td><td>254,490</td><td>1,363,017</td><td>1,505,434</td><td>778,593</td><td>2,998,386</td><td>1,239,847</td><td>2,632,201</td><td>4,064,775</td><td>3,798,476</td><td></td></tr><tr><td>R. KOREA</td><td>5,600</td><td>359,944</td><td>1,356,963</td><td>1,922,536</td><td>1,982,374</td><td>437,835</td><td>290,959</td><td>554,467</td><td>16,600</td><td>28,778</td><td>37,016</td><td></td><td></td></tr><tr><td>N. KOREA</td><td>1,673,891</td><td>3,001,703</td><td>1,500,949</td><td>1,188,030</td><td>1,660,919</td><td>779,336</td><td>1,103,285</td><td>546,714</td><td>111,047</td><td>692,520</td><td></td><td>1,080</td><td></td></tr><tr><td>CHINA</td><td>14,820</td><td>60</td><td>9,212</td><td>56,086</td><td>109,628</td><td>157,317</td><td>227,439</td><td>355,669</td><td>2,892,841</td><td>3,105,409</td><td>1,663,135</td><td>1,046,543</td><td></td></tr><tr><td>NORWAY</td><td></td><td>181</td><td></td><td></td><td></td><td></td><td>5,303</td><td>305,459</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>SWEDEN</td><td></td><td></td><td></td><td></td><td></td><td></td><td>201</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>ICELAND</td><td></td><td></td><td></td><td></td><td></td><td></td><td>1,000</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>FINLAND</td><td></td><td></td><td></td><td></td><td></td><td></td><td>1,741</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>NETHERLAND</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>U.K.</td><td></td><td></td><td>2,585</td><td></td><td></td><td>148</td><td></td><td>7,000</td><td></td><td>14,608</td><td></td><td>1,326,149</td><td>880,660</td><td></td></tr><tr><td>DENMARK</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>497</td><td></td><td>55,765</td><td></td><td>95,168</td><td>58,460</td><td></td></tr><tr><td>CHILE</td><td>5,411</td><td>51,402</td><td>33,020</td><td></td><td></td><td>3,718</td><td>33,544</td><td>20,047</td><td>969,679</td><td>4,374,327</td><td>11,870,088</td><td>17,061,493</td><td></td></tr><tr><td>NEW ZEALAND</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>55,156</td><td>617,249</td><td>519,154</td><td>813,413</td><td>871,930</td><td></td></tr><tr><td>AUSTRALIA</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>181,194</td><td>31,434</td><td>150,983</td><td></td><td></td></tr><tr><td>OTHERS*</td><td>1,260</td><td>43,000</td><td>17,577</td><td>3,687,031</td><td>2,412,991</td><td>984</td><td>0</td><td>7,230</td><td>74,636</td><td>1,201,490</td><td>21,177</td><td>5,420</td><td></td></tr><tr><td>TOTAL</td><td>39,331,100</td><td>71,341,409</td><td>107,478,188</td><td>97,847,816</td><td>92,977,945</td><td>115,482,043</td><td>113,427,698</td><td>109,020,382</td><td>129,255,597</td><td>141,134,937</td><td>161,454,172</td><td>143,812,258</td><td></td></tr></tbody></table>

* OTHERS INCLUDE MOROCCO, MEXICO, PANAMA, SURINAM, BELGIUM, TRINIDAD ARGENTINA, TUNISIA, NAMIBIA, FR. GERM. ITALY, GREECE, BRAZIL, AND ST P. MQ

* PARTICULARLY LARGE IMPORTS IN "OTHERS" CATEGORY ARE DUE TO THE IMPORTS FROM THE FOLLOWING COUNTRIES:
TAIWAN 3687012 KG IN 1983. TAIWAN: 2412811 KG IN 1984. ST P. MQ 1137594 KG IN 1989.

<table><caption>TABLE 2.2B: ESTIMATED PERCENTAGE SHAPE OF WILD-CAUGHT AND CULTURED SALMON IN JAPAN'S FROZEN SALMON IMPORTS</caption><thead><tr><th></th><th>1980</th><th>1981</th><th>1982</th><th>1983</th><th>1984</th><th>1985</th><th>1986</th><th>1987</th><th>1988</th><th>1989</th><th>1990</th><th>1991</th><th>UNIT: %</th></tr></thead><tbody><tr><td>U.S.A.</td><td>83,95</td><td>84,40</td><td>86,59</td><td>88,58</td><td>86,33</td><td>88,67</td><td>84,54</td><td>86,51</td><td>81,60</td><td>73,18</td><td>71,60</td><td>63,04</td><td></td></tr><tr><td>CHILE</td><td>0,00</td><td>0,01</td><td>0,06</td><td>0,03</td><td>0,00</td><td>0,00</td><td>0,03</td><td>0,02</td><td>0,77</td><td>3,10</td><td>7,35</td><td>11,86</td><td></td></tr><tr><td>WILD</td><td>100,00</td><td>99,93</td><td>99,93</td><td>96,14</td><td>97,29</td><td>99,86</td><td>99,76</td><td>98,94</td><td>91,48</td><td>89,49</td><td>87,49</td><td>82,27</td><td></td></tr><tr><td>CULTURED</td><td>0,00</td><td>0,07</td><td>0,07</td><td>3,96</td><td>2,71</td><td>0,14</td><td>0,24</td><td>1,06</td><td>8,52</td><td>10,51</td><td>12,51</td><td>17,00</td><td></td></tr></tbody></table>

SOURCE: JAPANESE IMPORTS OF MARINE PRODUCTS (STATISTICS), JAPAN MARINE PRODUCTS IMPORTERS ASSOCIATION
<table><caption>TABLE 2.3A: JAPANESE IMPORTS OF CURED SALMON BY COUNTRY (1983-1991)</caption><thead><tr><th></th><th>1983</th><th>1984</th><th>1985</th><th>1986</th><th>1987</th><th>1988</th><th>1989</th><th>1990</th><th>UNIT: KG<br>1991</th></tr></thead><tbody><tr><td colspan="10"><strong>CURED SALMON</strong></td></tr><tr><td>U.S.A.</td><td>6,798</td><td>695,414</td><td>1,209,940</td><td>351,597</td><td>207,660</td><td>302,593</td><td>121,643</td><td>144,173</td><td>232,447</td></tr><tr><td>CANADA</td><td>120,786</td><td>562,702</td><td>743,038</td><td>676,485</td><td>455,910</td><td>499,386</td><td>437,488</td><td>385,031</td><td>239,396</td></tr><tr><td>R.KOREA</td><td></td><td></td><td></td><td>22,890</td><td>50,700</td><td></td><td></td><td>250</td><td></td></tr><tr><td>N.KOREA</td><td>16,734</td><td>9,375</td><td>36,716</td><td>3,016</td><td>2,775</td><td></td><td></td><td></td><td></td></tr><tr><td>NORWAY</td><td></td><td>158</td><td>152</td><td></td><td></td><td>8,817</td><td>6,621</td><td></td><td></td></tr><tr><td>OTHERS*</td><td>0</td><td>0</td><td>90,915</td><td>0</td><td>0</td><td>218</td><td>1,943</td><td>1,590</td><td>2,286</td></tr><tr><td>SUBTOTAL</td><td>144,318</td><td>1,267,649</td><td>2,080,761</td><td>1,053,988</td><td>717,045</td><td>811,014</td><td>567,695</td><td>531,044</td><td>474,129</td></tr><tr><td colspan="10"><strong>SMOKED SALMON</strong></td></tr><tr><td>NORWAY</td><td></td><td></td><td></td><td></td><td></td><td>26,521</td><td>21,455</td><td>52,866</td><td>62,162</td></tr><tr><td>SWEDEN</td><td></td><td></td><td></td><td></td><td></td><td>3,970</td><td>288</td><td>356</td><td>703</td></tr><tr><td>DENMARK</td><td></td><td></td><td></td><td></td><td></td><td>2,604</td><td>11,884</td><td>10,021</td><td>7,783</td></tr><tr><td>U.K.</td><td></td><td></td><td></td><td></td><td></td><td>9,658</td><td>20,526</td><td>22,615</td><td>10,408</td></tr><tr><td>IRELAND</td><td></td><td></td><td></td><td></td><td></td><td>720</td><td>974</td><td>310</td><td>774</td></tr><tr><td>NETHERLAND</td><td></td><td></td><td></td><td></td><td></td><td>305</td><td>405</td><td>103</td><td>303</td></tr><tr><td>BELGIUM</td><td></td><td></td><td></td><td></td><td></td><td>107</td><td></td><td>98</td><td>113</td></tr><tr><td>FRANCE</td><td></td><td></td><td></td><td></td><td></td><td>292</td><td>1,479</td><td>594</td><td></td></tr><tr><td>FR GERM</td><td></td><td></td><td></td><td></td><td></td><td>817</td><td>743</td><td>203</td><td></td></tr><tr><td>CANADA</td><td></td><td></td><td></td><td></td><td></td><td>85,814</td><td>87,348</td><td>151,538</td><td>1,700</td></tr><tr><td>U.S.</td><td></td><td></td><td></td><td></td><td></td><td>5,183</td><td>8,667</td><td>14,034</td><td>201,570</td></tr><tr><td>NEWZEALAND</td><td></td><td></td><td></td><td></td><td></td><td>1,385</td><td>1,733</td><td>479</td><td>21,677</td></tr><tr><td>OTHERS**</td><td></td><td></td><td></td><td></td><td></td><td>500</td><td>3,303</td><td>364</td><td>17,737</td></tr><tr><td>SUBTOTAL</td><td></td><td></td><td></td><td></td><td></td><td>137,876</td><td>158,805</td><td>253,581</td><td>324,930</td></tr><tr><td><strong>TOTAL</strong></td><td><strong>144,318</strong></td><td><strong>1,267,649</strong></td><td><strong>2,080,761</strong></td><td><strong>1,053,988</strong></td><td><strong>717,045</strong></td><td><strong>948,890</strong></td><td><strong>726,500</strong></td><td><strong>784,625</strong></td><td><strong>799,059</strong></td></tr></tbody></table>

* OTHER INCLUDES CHINA, DENMARK, FRANCE, NEWZEALAND, CHILE, AND U.K.

** OTHER INCLUDE SWITZERLAND, AUSTRALIA, R.KOREA, BRAZIL, CHILE, AND CHINA

SOURCE: JAPANESE IMPORTS OF MARINE PRODUCTS (STATISTICS), JAPAN MARINE PRODUCTS IMPORTERS ASSOCIATION
shown steady increases. Cured cultured salmon, which had virtually no place in Japanese imports prior to 1987, represented approximately 12 percent of total cured salmon imports in 1991 (Table 2.3B).

The share of cultured salmon has increased in every part of the Japanese market. Table 2.4 summarizes Japanese imports of salmon by product type between 1980-1991. Estimated shares of wild and cultured salmon in Japan's total salmon imports during the same period is illustrated in Figure 2.4. Imports of wild-caught salmon fluctuated from year to year depending largely on the level of harvest in that particular year, while imports of cultured salmon increased consistently. Although wild-caught salmon represented a dominant share, cultured salmon imports appear to have driven overall imports. Within a decade, cultured salmon increased from virtually zero to approximately 21 percent of Japanese salmon imports.

## 2.4 Implications of Increased Supply

Figure 2.5 illustrates the carry over inventory of frozen salmon from 1976 to 1992.<fnref n="4" /> Despite relatively large fluctuation year to year, tendency of inventories to increase over time can be observed. Approximately 76,349 MT

<footnote n="4">⁴ Inventory of salmon is categorized as frozen and salted. Since frozen salmon can be processed salted later on, in order to avoid possible double counting, only frozen salmon inventory is used here. Inclusion of salted salmon inventories, however, does not change overall trends in inventory.</footnote>
<table><caption>TABLE 2.3B: ESTIMATED PERCENTAGE SHARE OF WILD-CAUGHT AND CULTURED SALMON IN CURED AND SMOKED SALMON IMPORTS</caption><thead><tr><th></th><th>1980</th><th>1981</th><th>1982</th><th>1983</th><th>1984</th><th>1985</th><th>1986</th><th>1987</th><th>1988</th><th>1989</th><th>1990</th><th>UNIT:%<br>1991</th></tr></thead><tbody><tr><td>WILD</td><td></td><td></td><td></td><td>100.00</td><td>99.99</td><td>99.99</td><td>100.00</td><td>100.00</td><td>94.11</td><td>90.56</td><td>88.58</td><td>87.84</td></tr><tr><td>CULTURED</td><td></td><td></td><td></td><td>0.00</td><td>0.01</td><td>0.01</td><td>0.00</td><td>0.00</td><td>5.89</td><td>9.44</td><td>11.42</td><td>12.16</td></tr></tbody></table>

<table><caption>TABLE 2.4: JAPANESE IMPORTS OF SALMON BY PRODUCT TYPE</caption><thead><tr><th></th><th>1980</th><th>1981</th><th>1982</th><th>1983</th><th>1984</th><th>1985</th><th>1986</th><th>1987</th><th>1988</th><th>1989</th><th>1990</th><th>UNIT:KG<br>1991</th></tr></thead><tbody><tr><td>FRESH</td><td>14,316</td><td>494,531</td><td>244,861</td><td>1,356,719</td><td>252,391</td><td>515,423</td><td>863,795</td><td>1,670,902</td><td>3,907,087</td><td>7,848,097</td><td>7,742,607</td><td>8,993,001</td></tr><tr><td>FROZEN</td><td>39,331,100</td><td>71,341,409</td><td>107,478,188</td><td>97,847,816</td><td>82,977,945</td><td>115,482,043</td><td>113,427,698</td><td>109,020,382</td><td>129,255,597</td><td>141,134,937</td><td>161,454,172</td><td>143,812,258</td></tr><tr><td>CURED</td><td>0</td><td>0</td><td>0</td><td>144,318</td><td>1,287,649</td><td>2,080,761</td><td>1,053,988</td><td>717,045</td><td>948,880</td><td>726,500</td><td>784,628</td><td>799,059</td></tr><tr><td>TOTAL</td><td>39,345,416</td><td>71,835,940</td><td>107,723,049</td><td>99,348,853</td><td>94,497,985</td><td>118,078,227</td><td>115,345,481</td><td>111,408,329</td><td>134,111,574</td><td>149,709,534</td><td>169,981,404</td><td>153,604,328</td></tr></tbody></table>

SOURCE: JAPANESE IMPORTS OF MARINE PRODUCTS (STATISTICS). JAPAN MARINE PRODUCTS IMPORTERS ASSOCIATION
<figure><img src="image_6.png" /><figcaption>FIGURE 2.4: JAPANESE IMPORTS OF SALMON ESTIMATED SHARE OF WILD AND CULTURED SALMON 1980-1991</figcaption></figure>

SOURCE: JAPANESE IMPORTS OF MARINE PRODUCTS (STATISTICS)
<table><caption>FIGURE 2.5: CARRY-OVER INVENTORY OF FROZEN SALMON 1976-1992</caption><thead><tr><th></th><th>1976</th><th>1978</th><th>1980</th><th>1982</th><th>1984</th><th>YEAR</th><th>1990</th><th>1992</th></tr></thead><tbody><tr><td>0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>40</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>20</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

SOURCE: STATISTICS AND INFORMATION BUREAU, MINISTRY OF AGRICULTURE, FORESTRY, AND FISHERY
of frozen salmon alone was carried over to 1991 from 1990.
The carry over inventory to 1992 has further increased to
77,753 MT. Frozen salmon inventories used to be reduced
during the months when there was no harvest of wild-caught
salmon. However, with increased imports of cultured salmon
from diversified sources, salmon is now brought into Japan
any time of the year, which has contributed to the marked-
build-up of inventories.

Figure 2.6 illustrates monthly average wholesale prices
of frozen chum and sockeye salmon at the Tokyo Central
Wholesale Market from 1985 to 1990. (These two species
constituted about 65 percent of the total frozen salmon
handled in Tokyo Central Wholesale Market in 1991.) Despite
some price differences between the two species, an overall
downward trend in wholesale prices is apparent. Observation
of Figure 2.5 and Figure 2.6 suggests a rather strong
inverse relationships between inventory level and wholesale
prices of frozen chum and sockeye salmon. Wholesale price
fluctuation is caused by many factors such as inventory,
expected and actual harvest, overall supply of salmon, the
U.S. and European salmon market, exchange rates, and other
seafood and meat prices. Rigorous analysis of time trend of
price fluctuation is not within the scope of this study.
Here, general market conditions for salmon in Japan are
provided as background information to better understand the
analysis of salmon buyers' preference structure.
<figure><img src="image_7.png" /><figcaption>FIGURE 2.6: AVERAGE WHOLESALE PRICE OF FROZEN CHUM AND SOCKEYE SALMON (1985-1990)</figcaption></figure>

SOURCE: ANNUAL REPORT OF THE DAKOTA CENTRAL WHOLESALE MARKET
## 2.5 Summary of the Changes in Japan's Salmon Supply

The establishment of 200-mile Exclusive Economic Zones has changed the supply sources of salmon for Japan. The changes can be characterized by declining high-seas catch, rapidly increasing imports, and increased coastal salmon catch resulting from the return of hatchery-raised salmon. Aquaculture production has also shown a significant increase.

During the period from 1976 to 1990, Japan's total supply of salmon increased more than three-fold from 129,778 MT to 416,768 MT. This large increase in overall supply of salmon is mostly attributable to the increase in coastal catch of hatchery returned salmon and imports.

During the same period, the share of cultured salmon in Japan's imports increased from virtually zero to approximately 16 percent. The share of cultured salmon has further increased to 21 percent in 1991. Although salmon is primarily imported frozen, imports of fresh salmon increased markedly. Cultured salmon now constitutes the majority of Japan's fresh salmon imports. An increase in cultured salmon is also apparent in frozen salmon imports. Japan is importing salmon from an increasingly diversified assortment of suppliers as new competitors have joined the arena. This increase in overall supply of salmon has caused inventory build-up over time, which in turn has created downward pressure on wholesale salmon prices.
## 2.6 Consumption of Salmon in Japan

Before discussing the trends in salmon consumption, some brief background information concerning how salmon is consumed in Japan may be helpful. Table 2.5 lists the various salmon products available in Japan. Salmon is usually sold in retail stores as skin-on slices called *kirimi*. Slices are fresh, frozen, salted, or marinated in different sauces. Salted salmon is by far the most prevalent product form in which salmon is consumed. Salted salmon slices with varying degree of saltiness are usually available.

Smoked salmon has gained popularity in recent years. Although its estimated share represents merely 10 percent of the total salmon consumption, it is nonetheless considered the most rapidly growing salmon product in Japan, based on the results of the survey conducted by the author in 1989. Annual production is estimated at about 6,000 - 6,500 MT, valued at about 25 billion yen (U.S. Embassy, 1991). Smoked salmon is largely a gift item. In addition to smoked salmon, dry salted whole salmon is widely used as gift item.

Contrary to common belief, the practice of eating raw salmon was not widely accepted until recently. Encouraged by increased supply of farm raised fresh salmon, the sushi/sashimi consumption of raw salmon is now increasing. There are many other secondary products in which salmon is consumed such as frozen breaded salmon slices/nuggets, salmon flakes in air tight container, or canned salmon.
<table><caption>Table 2.5: List of Salmon Products Available at Retail Level</caption><thead><tr><th></th><th></th></tr></thead><tbody><tr><td>A. Kirimi, skin-on slices (portioned fillet)</td><td>1) Fresh*<br>2) Salted**<br>3) Brined ***<br>4) Marinated with various Sauce****</td></tr><tr><td>*</td><td>The word "fresh" is used equivalent to "non-salted" in Japan and it includes pre-frozen. Although not prevalent, steak cut form is also available.</td></tr><tr><td>**</td><td>Mild, medium, and heavy salt products are available.</td></tr><tr><td>***</td><td>Brined salmon is recently introduced for better control of the consistency of the product's salt content.</td></tr><tr><td>****</td><td>Some of the sauce used for marinating salmon are soy bean paste, rice wine lee, soy sauce, and malted rice.</td></tr><tr><td>B. Smoked Salmon*</td><td>Cold smoked salmon is most prevalent. Fillet, blocks, and slices of various size packages are available.</td></tr><tr><td>C. Skinned Salmon Fillet/Loin for Raw Consumption (sushi/sashimi)</td><td>D. Low-Value Products<br>1) Breaded Frozen Salmon Nuggets/Slices<br>2) Salmon Flakes in Air Tight Container<br>3) Dehydrated Salmon Flakes with Sea Weed and Other Seasonings in Packages<br>4) Salmon Paste Products</td></tr><tr><td>E. Canned Products</td><td>1) Canned Salmon in Oil or Water<br>2) Flavored Canned Salmon</td></tr><tr><td>F. Gift Products</td><td>1) Whole Dry Salted Salmon<br>2) Smoked Salmon Fillet</td></tr></tbody></table>

In addition to the product listed above, there are some specialty products whose demand is rather limited in certain regions. Some retail stores sell heads and collars of salmon for pot dishes.
(For more details, please refer to Kusakabe and Anderson, 1989).

Prior to 1960, consumption of salmon was limited to the northern part of Japan where salmon is harvested. The market has recently been expanding southward due to improvements in transportation methods, diminishing differences in regional dietary habits, and advertising campaigns (Nasaka, 1986). However, there remain some regional differences in salmon consumption as well as in preferences for certain species of salmon.

Figure 2.7 illustrates annual household consumption of salmon by region<fnref n="5" />. Regions are ordered from north to south. It is apparent that the consumption of salmon remains higher in the north. There are also some regional differences in preference for certain species of salmon. The chum salmon market is northward from Tokyo. Higher valued salmon species such as sockeye are preferred in the south west metropolitan areas including Osaka and Nagoya (U.S. Embassy, 1991).

Although salmon is consumed year-around, there are some seasonal patterns in consumption. In general, consumption increases toward the end of the year. This is considered partly because the chum salmon run, which takes place during fall, makes up about 50 percent of the total Japanese salmon supplies. Most people strongly associate salmon with this

<footnote n="5">⁵ Consumption of salmon here is an aggregate quantity of fresh (including pre-frozen) and salted salmon slices purchased by the household for home consumption.</footnote>
<figure><img src="image_8.png" /><figcaption>FIGURE 2.7: ANNUAL CONSUMPTION OF SALMON BY REGION IN 1990</figcaption></figure>

SOURCE: STATISTICS BUREAU MANAGEMENT AND COORDINATION AGENCY, JAPAN
domestic harvest season. Salmon consumption usually peaks
in the month of December. This is due to the widely
established gift giving practices in Japan. Smoked salmon
and dry salted whole salmon are one of the most sought after
items for the winter gift season. (Kusakabe and Anderson,
1989; Wessells, 1990).

## 2.7 General Trends in Salmon Consumption

Figure 2.8 illustrates a notable increase in the apparent consumption of salmon in Japan from 1976 to 1990. Apparent consumption is calculated as carry-over inventory from the previous year, plus domestic production and imports, minus inventories at year's end<fnref n="6" />. Over this period, the apparent consumption of salmon has increased significantly from 136,770 MT to 415,183 MT. The apparent consumption in 1990 represented approximately 37 percent of the world's production of salmon (FAO 1990).

Given a minimal growth in population during this
period, trends in per capita consumption of salmon, which
was calculated simply as apparent consumption divided by
population, are highly correlated with trends in apparent
consumption. Per capita consumption of salmon has increased
from about 1.21 kg in 1976 to 3.36 kg in 1990.

<footnote n="6">⁶ Domestic production is in live weight, the majority of imports is frozen head-off dressed form, and the inventory is frozen and salted form. Because of these difference in product forms and resulting yield, apparent consumption is a rough estimate of the actual quantity of salmon consumed.</footnote>
<figure><img src="image_9.png" /><figcaption>FIGURE 2.8: APPARENT CONSUMPTION OF SALMON IN JAPAN 1976-1990</figcaption></figure>
Behind this impressive overall increase in salmon
consumption, there are numerous changes in the way salmon is
consumed. A close look at trends in salmon consumption at
household level unveils some of these changes.

## 2.8 Household Level Consumption

The *Annual Report on the Family Income and Expenditure Survey* (Statistics Bureau Management and Coordination Agency, Japan, 1990) records household-level consumption and expenditures on various items including seafood.

Consumption of salmon is recorded by the two product forms in which salmon is mainly consumed: salted and fresh/frozen product. Salmon in these product forms represented 8.4 percent of total seafood consumption at the household level in 1990 (Annual Report on the Family Income and Expenditure Survey, 1990).

Figure 2.9 illustrates annual household level
consumption of salmon from 1976 to 1990. Salted salmon
consumption increased up until 1983. Despite some
fluctuation, salted salmon consumption has been decreasing
since that time. Consumption of fresh salmon, in contrast,
increased rather notably from 1988 to 1990.

## 2.9 Changes in the Consumption of Salmon

By dividing the household consumption of salmon by the
average number of people per household, per capita
consumption of salmon at the household level was calculated.
Per capita consumption of salmon at the household level is then contrasted with per capita consumption of salmon at the overall level in Figure 2.10. This sheds a different light on salmon consumption in Japan. Although apparent consumption is at best an approximation of actual consumption, it is obvious that the discrepancy between home consumption of salmon and overall salmon consumption increased significantly during 1976-1990 period. This discrepancy may be caused by the diversification of salmon products and market outlets. In other words, household consumption of salmon in salted form, which is the main salmon outlet, is no longer representative of the Japanese salmon market as a whole.

Salmon is consumed in increasingly diversified product forms such as smoked, sushi/sashimi, marinated with different spices and sauces, or prepared in a ready-to-eat form. Salmon is also consumed in restaurants more frequently. Consumption of salmon in these product forms is mixed with other products and categorized as smoked seafood products, prepared foods, or dining out. The trend in total at-home and away-from-home salmon consumption, therefore, cannot be clearly isolated and identified.

Expenditure on dining out and prepared foods, however, increased significantly during the period from 1976 to 1990. Annual household expenditures on dining out increased from
84,240 yen in 1976 to 168,630 yen in 1990.<fnref n="7" /> During the same period, expenditures on ready-to-eat foods increased from 31,730 yen to 79,719 yen.<fnref n="8" /> Figure 2.11 illustrates the percentage share of household average monthly food expenditure on seafood, meat/poultry, dining-out, and prepared foods. While the share of expenditure on seafood and meat/poultry showed a slight decrease during this period, the share of dining-out and ready-to-eat foods showed considerable increase. Expenditures on dining-out now commands the highest proportion of household food expenditures, around 16 percent.

## 2.10 Summary of Salmon Consumption in Japan

The apparent consumption of salmon in Japan increased significantly from 136,770 MT in 1976 to 415,183 MT in 1990. At the household level, however, an equivalent increase in salmon consumption was not observed. Consumption of salted salmon, the form in which salmon is consumed most prevalently, increased until 1983, but decreased afterward. Fresh salmon consumption in the household showed a rather notable increase in recent years.

The discrepancy in salmon consumption trends at the overall level and at the household level in part seems to imply that salmon is consumed in increasingly diversified

<footnote n="7">⁷ Dining out expenditure includes school lunches in addition to expenditure on meals and beverages in restaurants.</footnote>

<footnote n="8">⁸ Ready-to-Eat foods include packed lunch, prepared main and side dishes in ready-to-eat form.</footnote>
<table><caption>FIGURE 2.11: SHARE OF FOOD EXPENDITURE ON SELECTED FOOD CATEGORIES</caption><thead><tr><th></th><th>PERCENT</th><th>YEAR</th><th></th></tr></thead><tbody><tr><td>18</td><td></td><td>1976</td><td></td></tr><tr><td>16</td><td></td><td>1978</td><td></td></tr><tr><td>14</td><td></td><td>1980</td><td></td></tr><tr><td>12</td><td></td><td>1982</td><td></td></tr><tr><td>10</td><td></td><td>1984</td><td></td></tr><tr><td>8</td><td></td><td>1986</td><td></td></tr><tr><td>6</td><td></td><td>1988</td><td></td></tr><tr><td>4</td><td></td><td>1990</td><td></td></tr><tr><td>2</td><td></td><td></td><td>MEAT/POULTRY</td></tr><tr><td>0</td><td></td><td></td><td>READY-TO-EAT</td></tr><tr><td>• FISH/SHELLFISH</td><td></td><td></td><td></td></tr><tr><td>• DINING-OUT</td><td></td><td></td><td></td></tr></tbody></table>

SOURCE: STATISTICS BUREAU MANAGEMENT AND COORDINATION AGENCY, JAPAN
product forms and market outlets. As a result, salted
salmon consumption, which is the most prevalent form in
which salmon is consumed, no longer represents the Japanese
salmon market as a whole.

The trend in total at-home and away-from-home salmon
consumption cannot be clearly isolated and identified
because diversified salmon products are now aggregated in
the composite category such as dining out and ready-to-eat
food. Expenditures on dining out and ready-to-eat foods
showed a significant increase from 1976 to 1990.

2.11 Distribution System in the Japanese Salmon Market

The distribution system in Japan typically consists of
two types of wholesale markets, one at the ports where fish
are landed and the other in cities where the majority of
fish is consumed. (These wholesale markets are referred to
as the producer wholesale market and the consumer wholesale
market, respectively.) Domestically-caught salmon as well
as imports are routed through these wholesale markets.
There are, however, many other channels which by-pass
wholesale markets. How salmon are routed depends on
species, type of salmon, product form, and intended end use.
It also depends on market condition, and the participant's
affiliations, financial arrangements, and product
specializations.
## 2.12 The Route Through Wholesale Markets

Figure 2.12 illustrates the basic distribution flows of salmon in Japan. Domestically-caught salmon are transported to the nearby wholesale markets. Wholesale markets at the ports (producer wholesale markets) are generally run by local fishermen's cooperatives.<fnref n="9" /> In the markets, salmon are sold to processors, retailers, and shippers through auctions, bidding, and bargaining.

In addition to the domestic landings of salmon, imported frozen salmon is supplied to the producer wholesale markets by importers.<fnref n="10" /> These salmon are purchased mainly for further processing. In the producer wholesale market not only fresh but frozen and processed salmon are also sold. Except for those consumed locally, the majority of salmon are transported to distant cities through the hands of shippers. Salmon are distributed all over Japan according to demand in the different markets and regional preferences for salmon.

In cities, the other type of wholesale markets (consumer wholesale market) is run by licensed wholesalers under the control of prefecture or city government. As of 1990, there were 505 consumer wholesale markets in cities

<footnote n="9">⁹ There were 340 producer wholesale markets in Japan as of 1986.</footnote>

<footnote n="10">¹⁰ Importers include trading companies, large fishery companies, wholesalers, processors, and some supermarket chains.</footnote>
<figure><img src="image_10.png" /><figcaption>Figure 2.12:</figcaption></figure>
throughout Japan.<fnref n="11" /> Salmon products from the producer wholesale markets are brought into the consumer wholesale markets by shippers. In addition, a large portion of salmon imports (fresh and frozen) are directly supplied to the consumer wholesale markets by importers. Primary and secondary processors also supply salmon products directly to the consumer wholesale markets. These domestic and imported salmon products are sold to retailers, processors, restaurants, catering services, small/medium supermarkets, and other wholesale markets through the hands of primary and secondary wholesalers.<fnref n="12" />

Salmon are sold in different ways in the wholesale market depending on product type. Fresh salmon is usually sold by auction. This is because there is high quality variance and a need to distribute highly perishable products quickly. Primary wholesalers' commissions are fixed at 5.5 percent of the sales price. Frozen and salted salmon are sold instead by negotiated prices. This is because processing costs are set and purchase prices are generally known.

<footnote n="11">¹¹ Out of 505 consumer wholesale markets, 55 are located in cities with population greater than 20,000 and thus referred to as central wholesale markets. The rest are referred to as local wholesale markets.</footnote>

<footnote n="12">¹² Authorized buyers such as large volume retailers, supermarkets, and local wholesale markets can purchase salmon directly from primary wholesalers.</footnote>
## 2.13 Routes Which Bypass Wholesale Markets

There are many channels which bypass wholesale markets. One of the out-of-market routes is through in-house processing. Many large trading houses and fishing companies have in-house processing plants or affiliated processing companies. They have their own distribution networks and facilities. A large portion of frozen salmon imported by those companies are processed in-house. Processed salmon products are then directly distributed to supermarket chains, catering services, and restaurants in addition to wholesale markets. The vertical integration of this sort tends to reduce the flow through wholesale markets.

There are several other out-of-market channels. Importers frequently distribute frozen salmon directly to processors for further processing. Importers also sell frozen salmon directly to large supermarket chains. Supermarket chains usually have their own distribution stations in major cities. Certain types of processing such as cutting a whole salmon into portions and tray-packing them take place in these distribution stations. The larger the supermarket chains, the higher the extent to which out-of-market channels are used. Large supermarket chains also import some of the salmon themselves. Brokers may be involved in any of these transactions through out-of-market channels.

Out-of-market channels exist not only for imported products but also for domestic salmon as well. Large
supermarkets and consumer cooperatives may purchase salmon directly from fishermen's cooperatives without going through wholesale markets.

The degree to which salmon products are routed through wholesale markets varies significantly depending on product type. According to the report published by Japan Marine Product Importers Association in 1992, fresh/chilled salmon and frozen salmon are distributed in 1990 as follows:

<table><thead><tr><th></th><th>Fresh</th><th>Frozen</th></tr></thead><tbody><tr><td>Wholesale Market</td><td>52.8%</td><td>39.2%</td></tr><tr><td>Large volume Retail Store</td><td>27.0%</td><td>7.8%</td></tr><tr><td>Out-Market Broker</td><td>16.6%</td><td>26.9%</td></tr><tr><td>Processor</td><td>0.4%</td><td>22.7%</td></tr><tr><td>In-house Processing</td><td>3.2%</td><td>3.3%</td></tr><tr><td>Restaurants</td><td>-</td><td>0.1%</td></tr></tbody></table>

Source: Yunyu Suisanbutsu Kokunai Chousa, 1992

The above report is based on the result of the mail survey of twenty-seven member companies of the association.

However, the report states that imports of farmed salmon are believed to be largely handled by non-member companies. The actual proportion of fresh salmon routing through the wholesale market is considered higher than the above number indicates.

## 2.14 Difference in Distribution by Species and End Use

There are four different outlets for salmon products: retail market, gift market, restaurants, and industrial use. Salmon are routed differently by species and intended end use. Differences in distribution, however, vary year to year.
year depending on overall salmon market conditions, scarcity or abundance of certain species, and relative price differences among salmon species.

The retail outlet is the largest of the four outlets for salmon. Retail stores include neighborhood fish stores, convenience stores, supermarkets, and department stores.<fnref n="13" /> The most common product form of salmon sold at retail stores is skin-on portioned fillets called kirimi (fresh and salted). The majority of domestic fall chum salmon, imported frozen sockeye salmon, and coho salmon are processed into this product form and sold at supermarket and retail stores alike. Frozen king salmon processed into kirimi and steaks are also sold at supermarkets and upscale retail stores such as department stores. A growing number of frozen aquacultured salmon (domestic coho, Chilean coho, and sea-trout) are routed to this outlet as well. Fresh imported salmon (wild-caught and aquacultured) are also sold at supermarket and upscale retail stores. They are not usually processed salted.

Typical gift items of salmon are smoked salmon and salted whole salmon (aramaki). Although the majority of frozen salmon is imported head-off, about 10 percent of frozen sockeye salmon are imported in head-on form. These salmon are processed into dry salted whole salmon and sold at department stores and supermarkets as year end gift

<footnote n="13">¹³ Large fish processing companies have contracted retail booths in department stores, malls, and some supermarkets to sell fresh, frozen, and processed seafood.</footnote>
items. Silver bright domestic chum salmon of large size are
processed and distributed in the same way. Troll-caught
frozen sockeye and chinook salmon are processed smoked and
distributed through supermarkets, specialty stores, and
department stores as gift items. Frozen Atlantic salmon and
sea-trout are also used for smoking.

Fresh domestic and imported salmon are also distributed
to restaurant outlets. A special niche for fresh Atlantic
salmon has been cultivated in the restaurant sector.
Restaurants are a major outlet for smoked salmon in addition
to the gift market. Some frozen and processed salmon are
also routed to restaurants.

Lower grade salmon of various species are used for
flakes, nuggets, and other processed salmon products. Most
pink salmon, domestic as well as imported, are used for
canning and box lunches.

2.15 Summary of the Distribution of Salmon

Wholesale markets are the core of the distribution
system of seafood in Japan. There are 340 producer
wholesale markets and 505 consumer wholesale markets located
throughout Japan. Due to improvements in processing
technology and transportation, however, channels which
bypass these wholesale markets have developed. Increases in
imports of salmon have also contributed to the product flow
which bypass wholesale markets. Large supermarket chains
and processors linked directly to importers utilize out-of-
market routes effectively. The vertical integration of
salmon importers also reduces the flow through wholesale
markets.

How salmon are routed depends on species, type of
salmon, product form, and intended end use. Routing also
changes year to year depending on overall market conditions,
scarcity or abundance of certain species, and the relative
price differences among salmon species.
# Chapter 3. Theory

## 3.1 Consumer Utility Theory of a Multi-attribute Product

A theoretical foundation for the multi-attribute product approach and demand as a function of the product attributes can be found in the work of Lancaster (1966). Lancaster pointed out the limitations of conventional consumer theory which treats goods as generic and homogenous. As a result, conventional consumer theory fails to provide any basis for consumer reactions to quality variations in goods. Lancaster suggested that the good, per se, does not give utility to the consumer; it possesses characteristics, and these characteristics give rise to utility. In other words, the preference or utility of the consumer is a function of the product's attributes. The concept can be expressed as the following general relationship; Preference = f (Attributes). This simple relationship provides the basis for the research to elicit a buyer's preference structure for multi-attribute product.

Salmon is not a homogeneous, generic product. Salmon can be viewed as a composite of attributes such as species, origin, flesh color, fat content, size, and price. Within attribute category, there are several subclasses of characteristics. For example, within the attribute "flesh color", several shades of color exist from pale pink to deep red. These subclasses of characteristics are called levels of the attribute. Salmon are described as combinations of
these attributes at different levels.

When choosing among multiattribute alternatives, a consumer is seeking an attribute mix which gives him/her the highest utility. A consumer's preference for the product in question is the totality of the utility he/she derives from individual attributes of the product.

In reality, the consumer's valuation of individual attributes is unobservable. Available market data never fully identify the attributes of the product. Data only quantify price and quantity of the products as if they were homogeneous. Therefore, despite the fact that salmon is widely traded in the market, the buyer's valuation of individual attributes cannot be estimated using available market data.

## 3.2 Techniques for Estimating the Demand for Non-Market Goods

Several methods for estimating demand for non-market goods can be applied to quantify the buyer's valuation of product attributes. Options include hedonic price models, the contingent valuation method, and conjoint analysis.

Hedonic price models take into account the existence of differentiated products. Hedonic price models assume that implicit (hedonic) prices can be viewed as a function of the attributes of which a good is composed (Freeman, 1979). For example, housing prices often reflect characteristics of the house, location, and some environmental amenity the house
location can offer. As long as specific attributes and price of the house are known, implicit prices for each house attribute can be estimated.

This type of data are largely unavailable for salmon. In general, salmon market data offers only average prices for different species of salmon. On some occasions, prices are further broken down by fresh and frozen, country of origin, size, and method of catch. These data are for the most part incomplete and available only for a limited number of species. Moreover, product attributes such as quality, fat content, flesh color, appearance, and farmed vis-a-vis wild-caught are not available in market data. This stringent data requirement makes estimating buyer's valuation of individual attributes of salmon products using hedonic price methods impossible.

The contingent valuation (CV) technique uses survey questions to elicit an individual's preference for non-market goods by finding out what they would be willing to pay for a specified change in the goods/services in question (Mitchell and Carson 1989). The contingent valuation technique circumvents the absence of a market by presenting consumers with a hypothetical market in which they have the opportunity to buy the good in question. Hypothetical bids are elicited from respondents regarding their willingness to pay, or willingness to accept compensation for specified changes in goods and services in question. Since an individual's willingness to pay/accept is expressed in terms
of a dollar amount, the contingent valuation technique can
be susceptible to biases induced by the respondents'
adoption of strategic behavior. Other possibilities of bias
include how survey questions are framed, information biases,
and the lack of a definable general standard of accuracy
(Michell and Carson 1989).

Conjoint analysis, like contingent valuation
techniques, uses survey questions to elicit buyers'
preferences for multi-attribute products. One conceptual
difference between conjoint measures and contingent
valuation is that the price of the good is treated as simply
another component of the product in conjoint analysis.
Instead of putting a dollar amount on a hypothetical
product, respondents simply order the hypothetical product
described as a bundle of attributes including price, from
the most preferred to the least, and/or assign metric scores
which represent the respondent's preference for the product.
Respondents are generally more comfortable providing
qualitative rankings or ratings of attribute bundles (which
include price), rather than dollar valuation of the same
bundles as in contingent valuation. In treating price as
simply another attribute, the conjoint approach minimizes
biases that can arise in open-ended contingent valuation
studies when respondents are presented with the unfamiliar,
and often unrealistic, task of putting prices on non-market
goods (Mackenzie 1990).
### 3.3 Overview of the Conjoint Analysis

Conjoint analysis is classified as a "decompositional" approach, since the technique takes a buyer's overall evaluation of a product and decomposes it into a buyer's evaluation of individual components of the product. Through careful experimental design, combinations of attributes at different levels are generated, which constitute hypothetical product profiles. Through survey measures, primary data are collected on buyer's preferences for each product profile. Since product profiles are pre-specified in terms of levels of different attributes, the data thus obtained constitute respondent valuation of different combinations of attributes in the product. The researcher then can use a variety of statistical methods to estimate the relative contribution of individual levels of attributes to the respondent's overall evaluation of the product.

Technical details of conjoint analysis are discussed in the experimental design and survey procedure sections.

Suppose that consumers are comparing Product A and B which are described as:

A: fresh sockeye salmon, gill-netted in Alaska, with silvery skin, deep red flesh color, high fat content, 4-6 lbs, priced at $4.15/lb,

B: fresh Atlantic salmon, cultured in Chile, with bright silver skin, pink red flesh, high fat content, 6-9 lbs, priced at $3.75/lb.

From the buyer's overall evaluation of Product A and B, conjoint analysis allows researchers to estimate, among other things, how much sockeye, as opposed to Atlantic
salmon, contributes to the buyer's preference for the product, and how aquacultured as compared to wild ocean-caught influences the buyer's preference for the product.

## 3.5 Development of Conjoint Analysis

Although the foundation of conjoint measurement goes back to work by Luce and Tukey in 1964, the first detailed consumer-oriented application of conjoint analysis was done by Green and Rao in 1971. Since then, numerous theoretical and empirical contributions have been made to the advancement of this technique (Green and Rao 1971; Green and Wind 1975; Johnson 1974; Green and Srinavasan 1978). Anderson and Brooks (1986) first applied this approach to seafood in the analysis of the salmon market in New England. (Anderson and Bettencourt 1991; Machenzie 1990, Manalo 1990)

## 3.6 Advantages and Shortcomings of Conjoint Analysis

Conjoint analysis introduces relatively realistic settings for the buyer's evaluation of the product, corresponding to the real-life choices the buyer faces among products which have multiple attributes. Using conjoint measurements, a researcher can make inferences about buyer preferences based upon actual behavior rather than upon self-reporting.

Another advantage of using conjoint analysis is that it permits analysis of a heterogeneous product market. Through careful experimental design, it also allows a researcher to
circumvent the statistical problem of multicollinearity and thus to separate out the effect of certain factors which in reality always occur simultaneously. Conjoint analysis also allows one to test a new product which has not yet appeared on the market.

The primary weaknesses of conjoint analysis are the cost and time involved in developing a well-designed experiment and conducting the experiment. Another weakness is the limitation on the number of factors which can be incorporated into the experiment because of the limitation on the number of factors a respondent can consider at one time. (This will be discussed further in Section 4.1.) Since a conjoint study is usually based on cross-sectional data at a given point in time, the estimated parameters are essentially static and the model may not forecast changes of market conditions or changes in consumer preference structure well. (For more detail about advantages and shortcomings of conjoint analysis, refer to Anderson and Bettencourt, 1991.)

A similar approach to modeling consumer preferences among multiattribute alternatives is the compositional approach. In compositional approach, consumers directly evaluate each attribute component of the product rather than evaluating a complete product as a composite of attributes. For example, buyers evaluate the importance of an attribute category such as species, origin, and method of catch. Buyers then evaluate the preference of each level of
attributes within a category, such as coho, king, sockeye, chum, Atlantic, and pink. Based on the consumer's reported valuation of attributes and attribute levels, the total utility of a multiattribute product is expressed as a weighted sum of attributes and attribute level valuations. Although conjoint measurement was used for this research, for comparison, one of the compositional approaches called self-explicated utility measure was added to the experimental procedure.
# Chapter 4. Method and Survey Procedure

## 4.1 Experimental Design

Designing a conjoint analysis experiment involves selection of: 1) relevant attributes and attribute levels, 2) a data collection method, 3) a method for constructing stimulus sets, 4) a stimulus presentation method, and 5) a measurement scale for the dependent variable. The design of the questionnaire will be explained following the steps listed above.

The attributes and attribute levels should be relevant to the potential buyers. The attributes selected should also be manageable in number. A larger number of attributes leads to a larger number of combinations to be tested, which then leads to a potentially overwhelming amount of information respondents have to consider at one time. In the extreme, this may cause an information overload on the part of a respondent. The ranges of attribute levels, on the other hand, should cover the entire representative domain. If the selected attributes are continuous variables (such as price), levels of attributes should be far enough apart to be considered as realistically distinct (Green and Srinivasan 1978, Heiner 1983).

Attributes and attribute levels for our experiment were chosen based on a *priori* knowledge of the Japanese market, a literature review of the Japanese trade press and seafood industry newspapers/magazines, a similar study done by
Anderson and Brooks (1986) of the New England salmon market, and discussions with several Japanese seafood traders in Boston. Wholesale price information from the Tokyo Central Wholesale Market was used to select price levels. The selected attributes and the levels of each attribute are listed in Table 4.1. There are 12 attributes with the number of levels ranging from 2 to 8 per attribute.

Data collection procedures in conjoint analysis employ variations of two basic methods: the two-factor-at-a-time procedure and the full-profile procedure. In the former procedure, as the name suggests, a respondent compares the combinations of two attributes at one time. Since only two factors are compared at one time, this method is relatively inefficient in terms of the amount of information collected per unit of respondent time. However, in the event of large numbers of attributes and attribute levels, this method presumably reduces the amount of information a respondent has to consider at one time.

The full-profile procedure, on the contrary, utilizes a complete set of factors. With this procedure, respondents evaluate hypothetical products which are described as a complete set of attributes. The full-profile method is much more efficient in terms of the amount of information collected per unit of respondent time. It also reflects a more realistic setting for the buyer's purchase decision.

A major limitation to this approach is the possibility of information overload on the part of the respondent. The
<table><caption>TABLE 4.1: A LISTING OF THE ATTRIBUTES AND ATTRIBUTE LEVELS</caption><thead><tr><th>ATTRIBUTE</th><th>LEVELS</th></tr></thead><tbody><tr><td>A. SPECIES</td><td>COHO<br>KING<br>SOCKEYE<br>CHUM<br>PINK<br>ATLANTIC</td></tr><tr><td>B. ORIGIN</td><td>CANADA<br>ALASKA<br>JAPAN<br>NORWAY<br>NEW ZEALAND<br>CHILE<br>WESTCOAST U.S. (NOT INCLUDING ALASKA)</td></tr><tr><td>C. METHOD</td><td>SEINE<br>GILL NET<br>TROLL<br>FARMED</td></tr><tr><td>D. TYPE</td><td>FRESH<br>FROZEN<br>SALTED</td></tr><tr><td>E. QUALITY</td><td>LOW QUALITY<br>MED QUALITY<br>HIGH QUALITY</td></tr><tr><td>F. COLOR</td><td>PALE PINK<br>PINK RED<br>DEEP RED</td></tr><tr><td>G. FAT CONTENT</td><td>LOW FAT<br>MED FAT<br>HIGH FAT</td></tr><tr><td>H. APPEARANCE</td><td>DARK/ MARKED<br>SILVERY SKIN/ SOME SCALE LOSS<br>BRIGHT SILVER/ MINIMAL SCALE LOSS</td></tr><tr><td>I. FORM/SIZE</td><td>STEAK<br>FILLET<br>HEAD-ON 1-2KG<br>HEAD-ON 2-3KG<br>HEAD-ON 3-4KG<br>HEAD-ON 4KG+<br>HEAD-OFF 1-2KG<br>HEAD-OFF 2-3KG<br>HEAD-OFF 3-4KG<br>HEAD-OFF 4KG+</td></tr><tr><td>J. SUPPLY</td><td>SEASONAL<br>YEAR ROUND</td></tr><tr><td>K. PRICE</td><td>PRICE DIFFERENCE</td></tr></tbody></table>
amount of information a respondent can include in his
judgement at one time is presumably limited. When too much
information is presented to the respondent, respondents are
tempted to simplify the task by ignoring variations in what
they perceives as less important factors. Results thus
obtained can be biased and may not reflect true buyer
preference structure (Green and Srinivasan, 1978).

The full-profile method was used for this experiment.
The targets of the survey were Japanese salmon importers
who, by profession, are involved in evaluating salmon
products which are composites of a large number of
attributes. For this reason, it was presumed that a twelve
attribute description profile would not create an
information overload for them. Moreover, in order to avoid
possible information overload, the number of products which
respondents had to evaluate at one time was reduced to a
minimum. (This will be discussed later in this chapter.)

If all possible combinations of attributes and
attribute levels were considered (full factorial design),
this would have resulted in a 7 * 6² * 4³ * 3⁵ * 2 or
7,838,208 possible products. Experiments involving this
large number of possible combinations are infeasible. With
the assumption of minimum interaction among attributes,
however, a fraction of combinations can be used which allows
estimation of parameters. The technique most commonly used
to choose a fraction of combinations from all possible
combinations is called fractional factorial design which
utilizes orthogonal arrays. With this design, the
contribution of each attribute taken separately (main
effect) can be estimated without trial of every possible
combination. A matrix designed with orthogonal arrays is
independent, which allows researchers to avoid
multicollinearity. Table 4.2 shows the fractional factorial
design for 7 * 6² * 4³ * 3⁵ * 2 attribute combinations. This
experiment was designed using one of the basic plans of the
asymmetric factorial design devised by Addelman (1962).
(For more detail, refer to Addelman, 1962.)

The matrix thus designed is used to assign attribute
levels in order to construct hypothetical product profiles.
Since occurrence of the levels of attributes is balanced
regardless of whether a certain combination exists in the
real world, product profiles generated by orthogonal design
include unrealistic products. For example, a product such
as wild caught Pacific salmon in Norway does not exist
because of the biological boundaries of the species and
biological/economic limitations of aquaculture.

The potential problem of including highly unrealistic
(non-representative) stimuli in conjoint experiment has been
studied by many researchers (Green and Srinivisan 1990;
Green 1984; Huber and McCann 1982; Cattin and Wittink 1982;
Goldberg 1984). Despite the potential problem, little
empirical evidence has been found to support the hypothesis
that unrealistic combinations of attributes have a
deleterious impact on consumer judgements in conjoint
<table><caption>TABLE 4.2: FRACTIONAL FACTORIAL DESIGN MATRIX FOR THE EXPERIMENT</caption><thead><tr><th></th><th>2</th><th>3</th><th>3</th><th>3</th><th>3</th><th>4</th><th>4</th><th>4</th><th>6</th><th>6</th><th>7</th></tr></thead><tbody><tr><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>2</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>2</td><td>2</td><td>1</td><td>2</td><td>2</td><td>1</td><td>5</td></tr><tr><td>3</td><td>0</td><td>0</td><td>0</td><td>0</td><td>2</td><td>2</td><td>1</td><td>2</td><td>1</td><td>1</td><td>2</td><td>0</td></tr><tr><td>4</td><td>0</td><td>1</td><td>1</td><td>2</td><td>0</td><td>0</td><td>1</td><td>1</td><td>1</td><td>0</td><td>1</td><td>1</td></tr><tr><td>5</td><td>0</td><td>1</td><td>1</td><td>2</td><td>1</td><td>1</td><td>0</td><td>1</td><td>0</td><td>2</td><td>2</td><td>1</td></tr><tr><td>6</td><td>0</td><td>1</td><td>1</td><td>2</td><td>2</td><td>2</td><td>2</td><td>0</td><td>2</td><td>1</td><td>0</td><td>3</td></tr><tr><td>7</td><td>0</td><td>0</td><td>2</td><td>1</td><td>0</td><td>0</td><td>2</td><td>2</td><td>2</td><td>0</td><td>2</td><td>4</td></tr><tr><td>8</td><td>0</td><td>0</td><td>2</td><td>1</td><td>1</td><td>1</td><td>1</td><td>0</td><td>1</td><td>2</td><td>0</td><td>6</td></tr><tr><td>9</td><td>0</td><td>0</td><td>2</td><td>1</td><td>2</td><td>2</td><td>0</td><td>1</td><td>0</td><td>1</td><td>1</td><td>2</td></tr><tr><td>10</td><td>1</td><td>0</td><td>1</td><td>1</td><td>0</td><td>1</td><td>0</td><td>1</td><td>1</td><td>1</td><td>0</td><td>4</td></tr><tr><td>11</td><td>1</td><td>0</td><td>1</td><td>1</td><td>1</td><td>2</td><td>2</td><td>2</td><td>0</td><td>0</td><td>1</td><td>6</td></tr><tr><td>12</td><td>1</td><td>0</td><td>1</td><td>1</td><td>2</td><td>0</td><td>1</td><td>0</td><td>2</td><td>2</td><td>2</td><td>2</td></tr><tr><td>13</td><td>1</td><td>1</td><td>2</td><td>0</td><td>0</td><td>1</td><td>1</td><td>2</td><td>2</td><td>1</td><td>1</td><td>0</td></tr><tr><td>14</td><td>1</td><td>1</td><td>2</td><td>0</td><td>1</td><td>2</td><td>0</td><td>0</td><td>1</td><td>0</td><td>2</td><td>5</td></tr><tr><td>15</td><td>1</td><td>1</td><td>2</td><td>0</td><td>2</td><td>0</td><td>2</td><td>1</td><td>0</td><td>2</td><td>0</td><td>0</td></tr><tr><td>16</td><td>1</td><td>0</td><td>0</td><td>2</td><td>0</td><td>1</td><td>2</td><td>0</td><td>0</td><td>1</td><td>2</td><td>1</td></tr><tr><td>17</td><td>1</td><td>0</td><td>0</td><td>2</td><td>1</td><td>2</td><td>1</td><td>1</td><td>2</td><td>0</td><td>0</td><td>1</td></tr><tr><td>18</td><td>1</td><td>0</td><td>0</td><td>2</td><td>2</td><td>0</td><td>0</td><td>2</td><td>1</td><td>2</td><td>1</td><td>3</td></tr><tr><td>19</td><td>0</td><td>0</td><td>2</td><td>2</td><td>0</td><td>2</td><td>0</td><td>2</td><td>2</td><td>2</td><td>0</td><td>1</td></tr><tr><td>20</td><td>0</td><td>0</td><td>2</td><td>2</td><td>1</td><td>0</td><td>2</td><td>0</td><td>1</td><td>1</td><td>1</td><td>1</td></tr><tr><td>21</td><td>0</td><td>0</td><td>2</td><td>2</td><td>2</td><td>1</td><td>1</td><td>1</td><td>0</td><td>0</td><td>2</td><td>3</td></tr><tr><td>22</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>2</td><td>1</td><td>0</td><td>0</td><td>2</td><td>1</td><td>4</td></tr><tr><td>23</td><td>0</td><td>1</td><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>1</td><td>2</td><td>1</td><td>2</td><td>6</td></tr><tr><td>24</td><td>0</td><td>1</td><td>0</td><td>1</td><td>2</td><td>1</td><td>2</td><td>2</td><td>1</td><td>0</td><td>0</td><td>2</td></tr><tr><td>25</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>2</td><td>2</td><td>1</td><td>1</td><td>2</td><td>2</td><td>0</td></tr><tr><td>26</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>1</td><td>2</td><td>0</td><td>1</td><td>0</td><td>5</td></tr><tr><td>27</td><td>0</td><td>0</td><td>1</td><td>0</td><td>2</td><td>1</td><td>0</td><td>0</td><td>2</td><td>0</td><td>1</td><td>0</td></tr><tr><td>28</td><td>0</td><td>1</td><td>1</td><td>1</td><td>1</td><td>3</td><td>1</td><td>3</td><td>3</td><td>3</td><td>0</td><td>0</td></tr><tr><td>29</td><td>0</td><td>1</td><td>1</td><td>1</td><td>2</td><td>0</td><td>1</td><td>2</td><td>1</td><td>5</td><td>4</td><td>5</td></tr><tr><td>30</td><td>0</td><td>1</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>4</td><td>5</td><td>2</td></tr><tr><td>31</td><td>0</td><td>1</td><td>2</td><td>0</td><td>1</td><td>1</td><td>0</td><td>2</td><td>0</td><td>3</td><td>4</td><td>3</td></tr><tr><td>32</td><td>0</td><td>1</td><td>2</td><td>0</td><td>2</td><td>2</td><td>3</td><td>0</td><td>3</td><td>5</td><td>5</td><td>1</td></tr><tr><td>33</td><td>0</td><td>1</td><td>2</td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>1</td><td>4</td><td>3</td><td>3</td></tr><tr><td>34</td><td>0</td><td>0</td><td>0</td><td>2</td><td>1</td><td>1</td><td>1</td><td>0</td><td>1</td><td>3</td><td>5</td><td>4</td></tr><tr><td>35</td><td>0</td><td>0</td><td>0</td><td>2</td><td>2</td><td>2</td><td>0</td><td>1</td><td>0</td><td>5</td><td>3</td><td>6</td></tr><tr><td>36</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td><td>0</td><td>3</td><td>2</td><td>3</td><td>4</td><td>4</td><td>2</td></tr><tr><td>37</td><td>1</td><td>1</td><td>2</td><td>2</td><td>1</td><td>2</td><td>3</td><td>2</td><td>0</td><td>4</td><td>3</td><td>4</td></tr><tr><td>38</td><td>1</td><td>1</td><td>2</td><td>2</td><td>2</td><td>0</td><td>1</td><td>0</td><td>3</td><td>3</td><td>4</td><td>6</td></tr><tr><td>39</td><td>1</td><td>1</td><td>2</td><td>2</td><td>0</td><td>1</td><td>0</td><td>1</td><td>1</td><td>5</td><td>5</td><td>2</td></tr><tr><td>40</td><td>1</td><td>1</td><td>0</td><td>1</td><td>1</td><td>2</td><td>0</td><td>0</td><td>1</td><td>4</td><td>4</td><td>0</td></tr><tr><td>41</td><td>1</td><td>1</td><td>0</td><td>1</td><td>2</td><td>0</td><td>3</td><td>1</td><td>0</td><td>3</td><td>5</td><td>5</td></tr><tr><td>42</td><td>1</td><td>1</td><td>0</td><td>1</td><td>0</td><td>1</td><td>1</td><td>2</td><td>3</td><td>5</td><td>3</td><td>6</td></tr><tr><td>43</td><td>1</td><td>0</td><td>1</td><td>0</td><td>1</td><td>2</td><td>1</td><td>1</td><td>3</td><td>4</td><td>5</td><td>5</td></tr><tr><td>44</td><td>1</td><td>0</td><td>1</td><td>0</td><td>2</td><td>0</td><td>0</td><td>2</td><td>1</td><td>3</td><td>3</td><td>1</td></tr><tr><td>45</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>3</td><td>0</td><td>0</td><td>5</td><td>4</td><td>3</td></tr></tbody></table>

<table><thead><tr><th></th><th>2</th><th>3</th><th>3</th><th>3</th><th>3</th><th>4</th><th>4</th><th>4</th><th>6</th><th>6</th><th>7</th></tr></thead><tbody><tr><td>46</td><td>1</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>3</td><td>0</td><td>1</td><td>5</td><td>3</td><td>3</td></tr><tr><td>47</td><td>1</td><td>1</td><td>0</td><td>0</td><td>2</td><td>1</td><td>1</td><td>1</td><td>0</td><td>4</td><td>4</td><td>1</td></tr><tr><td>48</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td><td>2</td><td>3</td><td>3</td><td>5</td><td>3</td></tr><tr><td>49</td><td>1</td><td>1</td><td>1</td><td>2</td><td>1</td><td>0</td><td>0</td><td>1</td><td>3</td><td>5</td><td>4</td><td>4</td></tr><tr><td>50</td><td>1</td><td>1</td><td>1</td><td>2</td><td>2</td><td>1</td><td>3</td><td>2</td><td>1</td><td>4</td><td>5</td><td>6</td></tr><tr><td>51</td><td>1</td><td>1</td><td>1</td><td>2</td><td>0</td><td>2</td><td>1</td><td>0</td><td>0</td><td>3</td><td>3</td><td>2</td></tr><tr><td>52</td><td>1</td><td>0</td><td>2</td><td>1</td><td>1</td><td>0</td><td>1</td><td>2</td><td>0</td><td>5</td><td>5</td><td>0</td></tr><tr><td>53</td><td>1</td><td>0</td><td>2</td><td>1</td><td>2</td><td>1</td><td>0</td><td>0</td><td>3</td><td>4</td><td>3</td><td>5</td></tr><tr><td>54</td><td>1</td><td>0</td><td>2</td><td>1</td><td>0</td><td>2</td><td>3</td><td>1</td><td>1</td><td>3</td><td>4</td><td>2</td></tr><tr><td>55</td><td>0</td><td>0</td><td>2</td><td>2</td><td>2</td><td>2</td><td>2</td><td>2</td><td>2</td><td>0</td><td>0</td><td>6</td></tr><tr><td>56</td><td>0</td><td>0</td><td>2</td><td>2</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>2</td><td>1</td><td>5</td></tr><tr><td>57</td><td>0</td><td>0</td><td>2</td><td>2</td><td>1</td><td>1</td><td>3</td><td>1</td><td>3</td><td>1</td><td>2</td><td>4</td></tr><tr><td>58</td><td>0</td><td>0</td><td>0</td><td>1</td><td>2</td><td>2</td><td>3</td><td>0</td><td>3</td><td>0</td><td>1</td><td>5</td></tr><tr><td>59</td><td>0</td><td>0</td><td>0</td><td>1</td><td>2</td><td>2</td><td>2</td><td>1</td><td>2</td><td>2</td><td>2</td><td>1</td></tr><tr><td>60</td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>1</td><td>0</td><td>2</td><td>0</td><td>1</td><td>0</td><td>3</td></tr><tr><td>61</td><td>0</td><td>1</td><td>1</td><td>0</td><td>2</td><td>2</td><td>0</td><td>1</td><td>0</td><td>0</td><td>2</td><td>4</td></tr><tr><td>62</td><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>3</td><td>2</td><td>3</td><td>2</td><td>0</td><td>6</td></tr><tr><td>63</td><td>0</td><td>1</td><td>1</td><td>0</td><td>1</td><td>1</td><td>2</td><td>0</td><td>2</td><td>1</td><td>1</td><td>2</td></tr><tr><td>64</td><td>1</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td><td>2</td><td>0</td><td>3</td><td>1</td><td>0</td><td>4</td></tr><tr><td>65</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>2</td><td>0</td><td>1</td><td>6</td></tr><tr><td>66</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>2</td><td>3</td><td>2</td><td>0</td><td>2</td><td>2</td><td>2</td></tr><tr><td>67</td><td>1</td><td>0</td><td>1</td><td>2</td><td>2</td><td>0</td><td>3</td><td>1</td><td>0</td><td>1</td><td>1</td><td>6</td></tr><tr><td>68</td><td>1</td><td>0</td><td>1</td><td>2</td><td>0</td><td>1</td><td>2</td><td>2</td><td>3</td><td>0</td><td>2</td><td>5</td></tr><tr><td>69</td><td>1</td><td>0</td><td>1</td><td>2</td><td>1</td><td>2</td><td>0</td><td>0</td><td>2</td><td>2</td><td>0</td><td>0</td></tr><tr><td>70</td><td>1</td><td>1</td><td>2</td><td>1</td><td>2</td><td>0</td><td>0</td><td>2</td><td>2</td><td>1</td><td>2</td><td>1</td></tr><tr><td>71</td><td>1</td><td>1</td><td>2</td><td>1</td><td>0</td><td>1</td><td>3</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td></tr><tr><td>72</td><td>1</td><td>1</td><td>2</td><td>1</td><td>1</td><td>2</td><td>2</td><td>1</td><td>3</td><td>2</td><td>1</td><td>3</td></tr><tr><td>73</td><td>0</td><td>0</td><td>1</td><td>1</td><td>2</td><td>1</td><td>2</td><td>1</td><td>0</td><td>2</td><td>0</td><td>5</td></tr><tr><td>74</td><td>0</td><td>0</td><td>1</td><td>1</td><td>0</td><td>2</td><td>0</td><td>2</td><td>3</td><td>1</td><td>1</td><td>1</td></tr><tr><td>75</td><td>0</td><td>0</td><td>1</td><td>1</td><td>1</td><td>0</td><td>3</td><td>0</td><td>2</td><td>0</td><td>2</td><td>3</td></tr><tr><td>76</td><td>0</td><td>0</td><td>2</td><td>0</td><td>2</td><td>1</td><td>3</td><td>2</td><td>2</td><td>2</td><td>1</td><td>4</td></tr><tr><td>77</td><td>0</td><td>0</td><td>2</td><td>0</td><td>0</td><td>2</td><td>2</td><td>0</td><td>0</td><td>1</td><td>2</td><td>6</td></tr><tr><td>78</td><td>0</td><td>0</td><td>2</td><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>3</td><td>0</td><td>0</td><td>2</td></tr><tr><td>79</td><td>0</td><td>1</td><td>0</td><td>2</td><td>2</td><td>1</td><td>0</td><td>0</td><td>3</td><td>2</td><td>2</td><td>6</td></tr><tr><td>80</td><td>0</td><td>1</td><td>0</td><td>2</td><td>0</td><td>2</td><td>3</td><td>1</td><td>2</td><td>1</td><td>0</td><td>5</td></tr><tr><td>81</td><td>0</td><td>1</td><td>0</td><td>2</td><td>1</td><td>0</td><td>2</td><td>2</td><td>0</td><td>0</td><td>1</td><td>4</td></tr></tbody></table>
analysis (Moore and Holbrook 1990).

However, pre-testing of the survey instrument with Japanese traders in Boston strongly indicated that the inclusion of these unrealistic products undermines a respondent's confidence and cooperation with the survey. In order to circumvent this problem, highly unrealistic product profiles were deleted. The matrix shown in Table 4.2 is not the minimum size experiment for 7 * 6² * 4³ * 3⁵ * 2 attribute combinations. A larger matrix was designed in order to allow for exclusion of highly unrealistic product profiles while still retaining the properties of the factorial design. From the 81 profiles of salmon products created by the original factorial design, 27 unrealistic profiles were deleted, resulting in 54 profiles to be tested. Although the deletion of any profile from a fractional factorial design makes the attributes somewhat correlated, the presence of inter-attribute correlation per se does not violate any assumptions of conjoint analysis (Green and Srinivasan 1990).

Hypothetical salmon products thus designed were presented to the respondents using cards which included terse attribute-level descriptions. An example of a profile card can be found in Table 4.3. Cards are used to facilitate product comparisons. Although visual aids may help respondents to visualize products, pictures may also convey other information which is not intended. This precluded the use of pictorial presentations for the survey.
<table><caption>TABLE 4.3: A SAMPLE OF THE HYPOTHETICAL PRODUCT PROFILES</caption><tr><td>SPECIES:</td><td>KING SALMON</td></tr><tr><td>ORIGIN:</td><td>CANADA</td></tr><tr><td>METHOD:</td><td>FARM RAISED</td></tr><tr><td>TYPE:</td><td>FRESH</td></tr><tr><td>QUALITY:</td><td>MEDIUM QUALITY</td></tr><tr><td>FLESH COLOR:</td><td>PINK RED</td></tr><tr><td>FAT CONTENT:</td><td>HIGH</td></tr><tr><td>APPEARANCE:</td><td>BRIGHT SILVER SKIN/MINIMAL SCALES LOSS</td></tr><tr><td>FORM/SIZE:</td><td>HEAD-OFF/4KG+</td></tr><tr><td>SUPPLY:</td><td>SEASONAL AVAILABILITY</td></tr><tr><td>PRICE:</td><td>1400 YEN/KG</td></tr></table>
Since a relatively large number of attributes were used for describing hypothetical products, product profile cards were divided into subgroups and only 6 product profiles were presented to each respondent. With only 6 profiles evaluated by each respondent, a minimum of nine interviews with salmon buyers was necessary in order to complete all 54 cards. This segmentation of the full design across individual respondents is commonly used in conjoint experiments (Green and Srinavasan 1990.)

Both metric and non-metric scales were employed for the measurement of the respondent's product preference. When profiles of various hypothetical products were presented to respondents, respondents not only rank ordered the products but also assigned numerical values which represented their preference for each product profile. The main advantage of employing metric scales is the increased information content potentially present in these scales.

## 4.2 Survey Procedures

The survey described above was conducted in Japan on two different occasions: March and April, 1988 and November 1989. Respondents were chosen from the member list of the Japan Marine Products Importers Association. A total of 79 firms were included in the list, and each was listed with the primary seafood products it imported. Fifty-six firms from the list imported salmon as one of their primary products. Because of travel logistics and time constraints,
those headquartered in Tokyo were targeted (51 firms out of 56).

The salmon import division of each firm was contacted. In 1988, out of 24 traders contacted, 15 traders completed the survey. Imports of salmon are handled by a relatively small number of large firms in Japan. The 15 firms surveyed in 1988 represented approximately 60 percent of Japan's salmon imports in 1988.<fnref n="3" /> In 1989, out of 46 traders contacted, 29 traders completed the survey. The 29 firms surveyed in 1989 represented about 65-70 percent of Japanese salmon imports in 1989. In addition to the traders, 12 surveys in 1988 and eight surveys in 1989 were completed by buyers for large retail stores, such as supermarket chains and department stores.

The survey was conducted using in-person interviews. The questionnaire was four pages long and took about 20-30 minutes to administer. It consisted of three parts: 1) description of respondent's firm; 2) self-explicated utility measure; and 3) conjoint measure.

In the first part, general descriptive information on the respondent's firm was collected. Information collected includes: quantity of salmon the firm imported in that particular year; the percentage breakdown of imports by country of origin; characteristics of salmon currently

<footnote n="3">³ The percentage was calculated from total Japanese imports of salmon in 1987 (published by the Ministry of Finance) and the aggregate of the each company's salmon import quantity.</footnote>
imported for their dominant market outlets. These firm characteristic variables are not included in the preference function.

In the self-explicated utility part, the respondents evaluated attributes and levels of attributes directly. Respondents were asked to rate selected salmon attributes such as species, country of origin, quality, fat content, size, and price in terms of its relative importance for their purchasing decision. Each attribute was rated on the scale of 0 to 100, where 100 is the most important and 0 the least important. In order to learn the relative importance of different attributes, the most important attribute was assigned 100 points. Using this as a point of reference, the remaining attributes were scored. The same score could be placed on more than one attribute.

The respondent was then asked to evaluate the levels of each attribute in terms of its relative preference (within the same attribute category) on the scale of 0 to 10, where 10 is the most preferred and 0 the least. The respondent rated, for example, coho, king, sockeye, chum, pink, and Atlantic salmon respectively on a scale of 0-10. The same score could be used for different attribute levels more than once. While evaluating levels of an attribute, the rest of the attributes were assumed to be held constant. These self-reported attribute importance and preference ratings will be compared with the results of the conjoint analysis.

A total of 54 salmon profile cards were divided into 9
groups of six profiles. In the conjoint part, these six hypothetical salmon product profiles were presented to the respondent. The respondent was asked to evaluate all six product profiles and order them from the most to least preferred.

When the ranking of six products was completed, a respondent was further asked to place scores on each product profile using a scale of 0 to 100, where 100 is the most preferred and 0 the least. Prior to rating, 100 points were assigned to the product composed of the combination of attributes which the respondent described as most preferred in the self-explicated part. This was done in order to establish a ceiling of the preference scoring. This ideal product varied among respondents. The respondent placed scores on each hypothetical salmon profile relative to the 100 point product.

The rankings and scores thus obtained reflect the respondent's relative preference of the products and are used as dependent variables in our model. Different statistical procedures are required to deal with rankings and scores respectively as dependent variables, which will be discussed in the next chapter.
# Chapter 5. MODEL ESTIMATION

## 5.1 Introduction

Through in-person interviews of the Japanese salmon buyers, the preference rankings and scores of the hypothetical salmon products were obtained. The rankings and scores reflect the respondent's relative preference for the products and are used as dependent variables and regressed against product attribute levels. Different statistical procedures are required to deal with rankings and scores respectively as dependent variables, because one is scaled metrically and the other non-metrically. The statistical software package LIMDEP (Greene, 1990) was used.

## 5.2 General Model Specification

Table 5.1 shows the list of explanatory variables used in the estimation. Preference scores and rankings were used for the dependent variable and regressed against product attribute levels as explanatory variables. Except for price, all the other variables are dummy variables with 1 representing the presence of the level, and 0 its absence. Price is the only continuous variable.

Since there are relatively large price differentials among different species of salmon, using one continuous price across all salmon species introduces inconsistency as to how the respondent perceives price when evaluating hypothetical products. The same 790 yen/kg price is likely
<table><caption>TABLE 5.1: A LIST OF EXPLANATORY VARIABLES USED IN THE ESTIMATION</caption><thead><tr><th>VARIABLES</th><th>NOTES</th></tr></thead><tbody><tr><td>COHO</td><td>EXCEPT PRICE, ALL THE OTHER</td></tr><tr><td>KING</td><td>VARIABLES ARE DUMMY VARIABLES</td></tr><tr><td>SOCKEYE</td><td>WHERE 1 REPRESENTS PRESENCE OF</td></tr><tr><td>CHUM*</td><td>THE LEVEL, 0 ITS ABSENCE</td></tr><tr><td>PINK</td><td></td></tr><tr><td>ATLANTIC</td><td>* MARKED DUMMY VARIABLES ARE OMITTED</td></tr><tr><td>CANADA</td><td>FROM EACH ATTRIBUTE CATEGORY IN THE</td></tr><tr><td>ALASKA</td><td>REGRESSION</td></tr><tr><td>JAPAN*</td><td></td></tr><tr><td>NORWAY</td><td></td></tr><tr><td>NEW ZEALAND</td><td></td></tr><tr><td>CHILE</td><td></td></tr><tr><td>WESTCOAST U.S. (NOT INCLUDING ALASKA)</td><td></td></tr><tr><td>SEINE</td><td></td></tr><tr><td>GILL NET</td><td></td></tr><tr><td>TROLL</td><td></td></tr><tr><td>FARMED*</td><td></td></tr><tr><td>FRESH</td><td></td></tr><tr><td>FROZEN*</td><td></td></tr><tr><td>SALTED</td><td></td></tr><tr><td>LOW QUALITY</td><td></td></tr><tr><td>MED QUALITY*</td><td></td></tr><tr><td>HIGH QUALITY</td><td></td></tr><tr><td>PALE PINK</td><td></td></tr><tr><td>PINK RED*</td><td></td></tr><tr><td>DEEP RED</td><td></td></tr><tr><td>LOW FAT</td><td></td></tr><tr><td>MED FAT*</td><td></td></tr><tr><td>HIGH FAT</td><td></td></tr><tr><td>DARK/ MARKED</td><td></td></tr><tr><td>SILVERY SKIN/ SOME SCALE LOSS*</td><td></td></tr><tr><td>BRIGHT SILVER/ MINIMAL SCALE LOSS</td><td></td></tr><tr><td>STEAK</td><td></td></tr><tr><td>FILLET</td><td></td></tr><tr><td>HEAD - ON 1-2KG</td><td></td></tr><tr><td>HEAD - ON 2-3KG</td><td></td></tr><tr><td>HEAD - ON 3-4KG</td><td>FOR REGRESSION, 3-4KG AND 4KG+</td></tr><tr><td>HEAD - ON 4KG+</td><td>CATEGORIES WERE COMBINED FOR HEAD-ON</td></tr><tr><td>HEAD - OFF 1-2KG*</td><td>AND HEAD-OFF</td></tr><tr><td>HEAD - OFF 2-3KG</td><td></td></tr><tr><td>HEAD - OFF 3-4KG</td><td></td></tr><tr><td>HEAD - OFF 4KG+</td><td></td></tr><tr><td>SEASONAL</td><td></td></tr><tr><td>YEAR ROUND*</td><td></td></tr><tr><td>PRICE DIFFERENCE</td><td>PRICE DIFFERENCE BETWEEN LISTED PRICE IN THE PRODUCT PROFILE AND THE BASE PRICES CALCULATED FOR EACH SPECIES OF SALMON AND FOR EACH PRODUCT TYPE (FRESH/FROZEN/SALTED) USING THE AVERAGE WHOLESALE PRICE OF TOKYO CENTRAL WHOLESALE MARKET ADJUSTED FOR ESTIMATED CIF PRICE</td></tr></tbody></table>
to have different implications depending on whether it is
for sockeye salmon or pink salmon.

In order to circumvent this problem, the base price was
calculated for each species of salmon by product type
(fresh/frozen/salted). Table 5.2 shows the list of the base
prices. Those prices were calculated using the average
wholesale prices of salmon obtained from the *Annual Reports
of the Tokyo Central Wholesale Market* for 1988 and 1989¹.
The average wholesale prices were then adjusted by the
common conversion factor for CIF (Cost, Insurance, and
Freight) price since respondents are importers rating the
product profile as products to purchase for their business
use. Through the conversion, frozen sockeye and pink salmon
both priced at 790 yen/kg are now registered at -400 yen/kg
for sockeye salmon and +210 yen/kg for pink salmon
respectively. This conversion more appropriately captures
the price effect as a respondent perceives it when he/she is
evaluating the hypothetical products. Instead of one
continuous price across all salmon species, the price
deviation from these base prices was included in the
regression as a price variable. All other things being

<footnote n="1">¹ The Tokyo Central Wholesale Market reports certain species and product types of salmon only in an aggregate fashion. For example, frozen king and Atlantic salmon are aggregated in "other species" of salmon in frozen form category. The average price was used for both king and Atlantic salmon. Since Atlantic salmon is usually not processed salted, the price of Atlantic salmon in salted form cannot be obtained in the annual wholesale report. It was calculated using the average price differences between frozen and salted product for other species of salmon.</footnote>
<table><caption>TABLE 5.2: AVERAGE WHOLESALE PRICES OF SALMON BY SPECIES AND PRODUCT TYPE USED AS BASE PRICES</caption><thead><tr><th rowspan="2">SPECIES/PRO TYPE*</th><th colspan="3">1988</th><th colspan="3">1989</th></tr><tr><th>FRESH</th><th>FROZEN</th><th>SALTED</th><th>FRESH</th><th>FROZEN</th><th>SALTED</th></tr></thead><tbody><tr><td>COHO</td><td>990</td><td>1,233</td><td>1,315</td><td>756</td><td>950</td><td>1,040</td></tr><tr><td>PINK</td><td>1,489</td><td>757</td><td>815</td><td>1,138</td><td>712</td><td>642</td></tr><tr><td>SOCKEYE*</td><td>1,719</td><td>1,492</td><td>1,666</td><td>1,363</td><td>1,305</td><td>1,584</td></tr><tr><td>KING*</td><td>1,719</td><td>1,365</td><td>1,644</td><td>1,363</td><td>1,160</td><td>1,450</td></tr><tr><td>CHUM</td><td>837</td><td>968</td><td>1,008</td><td>659</td><td>610</td><td>844</td></tr><tr><td>ATLANTIC*</td><td>1,719</td><td>1,365</td><td>1,503</td><td>1,363</td><td>942</td><td>1,101</td></tr></tbody></table>

* The Tokyo Central Wholesale Market reports certain species and product types of salmon only in an aggregate fashion. Fresh sockeye, king, and Atlantic salmon are aggregated in "other species of salmon" category. Frozen king and Atlantic salmon are also aggregated.

The average price was used for the species aggregated. Since Atlantic salmon is usually not processed salted, the price of Atlantic salmon in salted form cannot be obtained in the annual wholesale reports. It was calculated using the average price differences between frozen and salted product for other species of salmon.

SOURCE: ANNUAL REPORT OF THE TOKYO CENTRAL WHOLESALE MARKET (SEAFOOD)
equal, the higher the price is from the base price (which represent the average price importers are expected to pay for a given product), the less preferred the product. A negative sign is expected on the coefficient for this price variable.

### 5.3 Statistical Specification for Dependent Variables

As mentioned before, different statistical procedures are required to deal with rankings and scores respectively as a dependent variables. A ranking is ordinal-scaled when it represents a simple ordering such as Product A is preferred to Product B. Given the ordinal nature of the dependent variable, ranking as a function of various attribute levels should be developed in a discrete choice model. In the usual multinominal logit model, only the most preferred alternative will be utilized in the estimation. However, the survey data obtained consist of a complete set of ranks. Rank-order logit, a variation of a multinomial logit model which incorporates all ranking information, was used for the estimation. The use of this greater information is expected to enhance the estimation of parameters. LIMDEP's regression procedure for a discrete choice model for observed rank-order data was used, which is based on the model developed by Beggs, Cardell, and Hausman (1981).

Scores, on the other hand, are interval scaled, wherein the distance between any two numbers on the scale has
meaning. In other words, it represents not only preference ordering, but also the intensity of the respondent's preference for the products. Respondents can use equal scoring to indicate indifference between products. Given a larger amount of information, scoring is expected to outperform ranking in terms of specifying a respondent preference function.

## 5.4 Limited Dependent Variable, Censored Regression

The preference scores obtained from the survey are limited between 0 and 100, and otherwise continuous within limits. When the value of the dependent variable is censored within a certain range, a value beyond the specified range will be transformed to a value at the limit (Greene 1984). For example, the preference scores below 0 are transformed to 0, while values above 100 are transformed to 100. Therefore, once outside the observable range, there is no distinction in relative distance of the values from the limit of the range we can observe. When data are censored, the sample data thus becomes the mixture of discrete limit observations and continuous non-limit observations. If we estimate the regression equation by ordinary least squares based only on the values we can observe, the residual would be correlated with explanatory variables and thus the estimator would be biased and inconsistent (Maddala 1990).

The work of Tobin (1958) first introduced this type of
censored regression model in the estimation of demand for household durable goods. Household expenditures on durable goods can be observed only when there is positive expenditure. Expenditure data is censored at zero. The suggested method to incorporate qualitative differences between limit and non-limit observations is to use the maximum likelihood estimator by making some specific assumptions about the distribution of the disturbance term. This specification incorporates the probability that the observation takes on the limit value. Amemiya (1973) has provided proof that maximization of the likelihood function with respect to the unknown parameter leads to estimators that are consistent and asymptotically normal.

There are, however, some other consistent estimators of censored regression. Heckman (1976, 1979) and Hartley (1976) treated the censored regression in the framework of an omitted explanatory variable. The method is essentially based on predicting the missing observations and then using least squares based on the predicted data and the complete observations. This two-step procedure is considered inefficient compared to maximum likelihood estimation (Kmenta 1986).

## 5.5 Two-Limit Tobit Model

The scoring of hypothetical salmon products obtained through the survey is restricted by both an upper and lower limit. This two-limit censored regression model requires an
extension of the basic Tobit model. The two-limit
specification was developed by Rosett and Nelson (1975) to
illustrate that a two-limit Tobit model using just the
number of observations at the limits and non-limit will give
consistent estimates of the parameters. Nakamura and
Nakamura (1983) also applied two-limit censored regression
in the analysis of work behavior of married women. Instead
of maximum likelihood, however, Nakamura and Nakamura used a
variant of a Heckman procedure.

A two-limit censored regression model is derived below
following the notation of Maddala. Define a latent non-
observable variable $y_i^*$, such that the model is defined as
follows;

$$
y_i^* = \beta'x + e \tag{5.1}
$$

where $\beta$ is a $k \times 1$ vector of unknown parameters, $x$ is a $k \times 1$ vector of explanatory variables and $e$ residuals. If we denote by $y_i$, the observed dependent variable,

$$
\begin{align*}
y_i &= L_{1i} & \text{if } y_i' \le L_{1i}, \\
y_i &= y_i' & \text{if } L_{1i} \le y_i' \le L_{2i}, \\
y_i &= L_{2i} & \text{if } y_i' \ge L_{2i} \tag{5.2}
\end{align*}
$$

where $L_{1i}$ and $L_{2i}$ are respectively lower and upper limit. In this model, they are 0 and 100.

The likelihood function for this model is given by

$$
L(\beta, \sigma | y_i, x_i, L_{1i}, L_{2i}) = \prod_{y_i=L_{1i}} \Phi\left(\frac{L_{1i} - \beta'x}{\sigma}\right) \prod_{y_i=y_{i*}} \frac{1}{\sigma} \Phi\left(\frac{y_i - \beta'x}{\sigma}\right) \prod_{y_i=L_{2i}} \left(1 - \Phi\left(\frac{L_{2i} - \beta'x}{\sigma}\right)\right) \quad (5.3)
$$
where $\Phi$ represents the cumulative distribution function and
$\phi$ the density function of the standard normal distribution.
For convenience, define the following:

$$ \Phi_i = \Phi\left(\frac{y_i - \beta'x_i}{\sigma}\right) = \frac{1}{(2\pi)^{\frac{1}{2}}} e^{-\frac{1}{2\sigma^2} (y_i - \beta'x_i)^2} \quad (5.4) $$

$$ \Phi_i = \Phi\left(\frac{y_i - \beta'x_i}{\sigma}\right) = \int_{-\infty}^{\frac{y_i - \beta'x_i}{\sigma}} \frac{1}{(2\pi)^{\frac{1}{2}}} e^{-\frac{t^2}{2}} dt \quad (5.5) $$

Also denoting $\Phi(L_{1i}-\beta'x_i/\sigma)$ and $\Phi(L_{2i}-\beta'x_i/\sigma)$ by $\Phi_{1i}$ and $\Phi_{2i}$ respectively, with corresponding definitions for $\phi_{1i}$ and $\phi_{2i}$, the log-likelihood function is given by:

$$ \log L = \sum \log \Phi_{1i} - \sum \frac{1}{2\sigma^2} (y_i - \beta'x_i)^2 + \sum \log (1 - \Phi_{2i}) \quad (5.6) $$

Maximization is obtained by equating the partial derivatives of the log-likelihood function with respect to $\beta$ and $\sigma^2$ to zero.

$$ \frac{\partial \log L}{\partial \beta} = \frac{\Phi_{1i} x_i}{\Phi_{1i}} + \frac{1}{\sigma^2} \sum (y_i - \beta' x_i) x_i - \frac{\Phi_{2i} x_i}{1 - \Phi_{2i}} = 0 \quad (5.7) $$

$$ \frac{\partial \log L}{\partial \sigma^2} = -\frac{1}{2\sigma^2} \sum \frac{\beta'x_i \Phi_{1i}}{\Phi_{1i}} + \sum \frac{1}{2\sigma^2} + \frac{1}{2\sigma^4} \sum (y_i - \beta'x_i)^2 + \frac{1}{2\sigma^2} \sum \frac{\beta'x_i \Phi_{2i}}{1 - \Phi_{2i}} = 0 \quad (5.8) $$

Since these equations are non-linear in $\beta$, the estimation of
the parameters involves an iterative procedure such as the
Newton-Raphson method. The two-limit Tobit procedure in
LIMDEP was used for estimation of our model, which utilizes
OLS estimators as initial values and Newton-Raphson method
as an iterative procedure.
# Chapter 6. Results of Conjoint Analysis

## 6.1 Introduction

Fifteen importers and twelve large retail store buyers participated in the survey in 1988. Twenty-nine importers and eight large retail store buyers participated in the survey in 1989. Out of the total of 64 surveys, three were unusable. In addition, two respondents did not complete the self-explicated measure task, two did not complete ratings of hypothetical products, and two only partially completed the ratings. The rest of the respondents each provided ratings of six hypothetical products. When evaluating hypothetical products, respondents voluntarily provided ratings of additional products by changing one of the attribute levels of the hypothetical products. Respondent sometimes claimed, for example, that the product he rated 30 (on the scale of 0 to 100) would be rated 75 if the quality attribute changes from low to high with all other attributes being the same. The new product with altered attributes levels were included in the respondent ratings as if he evaluated seven (6+1) hypothetical products. The ideal product the respondent described in the direct ratings of individual attributes prior to rating hypothetical products, was also incorporated into the data. This has resulted in a total of 416 rating observations.

Preference ratings and rankings were used as dependent variables and regressed against product attribute levels in
two model specifications: two limit Tobit and rank-order
logit. The relative contributions of individual attributes
to the product's overall preference were estimated through
these model specifications. Results will be discussed in
terms of the model's ability to predict the respondents'
actual evaluation of the product, comparison among different
attribute levels within the same attribute category, and the
impact of changes in attribute levels on the overall
preference for the products.

6.2 Self-Explicated Measure

Prior to the analysis of the regression results, the
respondents' direct evaluation of the product attributes and
attribute levels in the self-explicated measure are
summarized. This self-stated preference for individual
attributes may not necessarily agree with the regression
results. Montgomery (1986) reported the discrepancy between
self-explicated and conjoint measures in the importance of
salary for the college graduates' choice of job. In the
direct evaluation of job attributes, college graduates who
participated in the survey claimed low importance of the
salary in their choice of potential job. The importance
weights derived from conjoint analysis, however, indicated
that the salary was the most important attribute which
influenced the college graduate's choice of job. Although
the agreement is neither sufficient nor necessary, the self-
explicated measure provides an important benchmark for
comparison with the conjoint results.

Table 6.1 shows the mean value of the respondent's direct evaluation of attributes. Attributes were rated in terms of the importance each respondent places on the attributes when respondent is evaluating the product for purchase. Overall weighted average ratings indicate that price and quality are considered as the most important attributes in the product choice, followed closely by flesh color. There are some differences in ratings between importers and large retail store buyers. T-tests were conducted to test the significance level of the differences. The results of the T-test is also included in Table 6.1.

Large retail buyers placed significantly more importance on country of origin, method of catch, flesh color, fat content, supply consistency, and less importance on price and species than importers. This may have resulted from the fact that large retail stores usually carry many species of salmon year-round and that attributes such as origin and method of catch are used to differentiate products for sale at the retail level. Flesh color and fat content are also more important at the retail level. Given that large retail stores are closer to the consumers than importers on the distribution hierarchy, different importance placed on the price is consistent to the prior expectation.

T-test were also conducted to test the significance level of the difference between 1988 survey and 1989 survey.
<table><caption>TABLE 6.1: WEIGHTED AVERAGE OF THE DIRECT EVALUATION OF ATTRIBUTES IN THE SELF-EXPLICATED MEASURE</caption><thead><tr><th></th><th>IMPORTER</th><th>RETAILER</th><th>SURV88</th><th>SURV89</th><th>AVERAGE TOTAL</th><th>T-TEST TRDRTL</th><th>T-TEST SURV88/89</th></tr></thead><tbody><tr><td>NUM</td><td>43</td><td>19</td><td>26</td><td>36</td><td>62</td><td></td><td></td></tr><tr><td>SPECIES</td><td>86.43</td><td>71.06</td><td>75.63</td><td>85.94</td><td>81.55</td><td>3.053 **</td><td>-2.191 *</td></tr><tr><td>ORIGIN</td><td>56.55</td><td>75.56</td><td>57.29</td><td>65.56</td><td>62.15</td><td>-2.582 *</td><td>-1.200</td></tr><tr><td>METHOD</td><td>57.50</td><td>75.83</td><td>63.13</td><td>62.92</td><td>63.08</td><td>-2.480 *</td><td>0.030</td></tr><tr><td>TYPE</td><td>78.29</td><td>79.41</td><td>77.92</td><td>79.12</td><td>78.6</td><td>-0.158</td><td>-0.183</td></tr><tr><td>QUALITY</td><td>94.29</td><td>98.33</td><td>95.83</td><td>95.28</td><td>95.52</td><td>-1.701</td><td>0.250</td></tr><tr><td>APPEARANCE</td><td>81.90</td><td>89.17</td><td>85.00</td><td>83.47</td><td>84.13</td><td>-1.693</td><td>0.381</td></tr><tr><td>FLESH COLOR</td><td>87.26</td><td>93.61</td><td>87.92</td><td>90.00</td><td>89.14</td><td>-2.312 *</td><td>-0.811</td></tr><tr><td>FAT</td><td>72.14</td><td>85.83</td><td>81.46</td><td>72.78</td><td>76.44</td><td>-2.960 *</td><td>2.007 *</td></tr><tr><td>SIZE</td><td>66.90</td><td>74.17</td><td>66.46</td><td>70.83</td><td>69.02</td><td>-1.108</td><td>-0.714</td></tr><tr><td>FORM</td><td>66.55</td><td>73.33</td><td>67.71</td><td>69.17</td><td>68.57</td><td>-0.934</td><td>-0.215</td></tr><tr><td>PRICE</td><td>97.38</td><td>91.11</td><td>95.00</td><td>95.83</td><td>95.46</td><td>2.306 *</td><td>-0.328</td></tr><tr><td>SUPPLY</td><td>57.56</td><td>78.89</td><td>71.67</td><td>58.86</td><td>64.19</td><td>-2.666 **</td><td>1.708</td></tr></tbody></table>

Significance for t-test is indicated as follows;

* p < 0.05

** p < 0.01
The result is also included in Table 6.1. In general, importance ratings between two survey years showed strong consistency. Only species and fat content attributes showed significantly different ratings between 1988 survey and 1989 survey.

Table 6.2 shows the mean value of the respondent's direct evaluation of individual attribute levels. The attribute levels were rated in terms of preference among different levels within an attribute. High quality, bright silver skin, and the price of 580 yen/kg (the lowest price level presented) uniformly received the score of 10 (on the scale of 0 to 10) in the ratings of individual attribute levels. The ideal product, composed simply by combining attribute levels with highest average ratings, is described as; sockeye salmon from Canada, troll caught, frozen, high quality, with bright silver skin, deep red flesh color, high fat content, in head-off/2-3kg size, available year-round, at the price of 580 yen/kg.

Significant differences in preference among different levels of attribute were observed between importers and large retail store buyers. Retail store buyers significantly preferred chum salmon, and year-round supply. Given that majority of chum salmon supply comes from domestic production (rather than imports), and that retail stores carry salmon year-round, those difference in preference ratings between importers and large retail store buyers conform to prior expectations. Importers rated
<table><caption>TABLE 6.2: WEIGHTED AVERAGE OF THE DIRECT EVALUATION OF ATTRIBUTES LEVELS IN THE SELF-EXPLICATED MEASURE</caption><thead><tr><th></th><th></th><th>IMPORTERRETAILER</th><th>SURV88</th><th>SURV89</th><th>AVERAGE TOTAL</th><th>T-TEST TRDRTL</th><th>T-TEST SURV88/89</th></tr></thead><tbody><tr><td rowspan="6">SPECIES</td><td>COHO</td><td>6.68</td><td>6.72</td><td>6.13</td><td>7.06</td><td>6.67</td><td>-0.07</td><td>-1.47</td></tr><tr><td>KING</td><td>6.00</td><td>7.17</td><td>7.13</td><td>5.86</td><td>6.38</td><td>-1.33</td><td>1.54</td></tr><tr><td>ATL</td><td>4.98</td><td>4.31</td><td>5.09</td><td>4.59</td><td>4.79</td><td>0.72</td><td>0.60</td></tr><tr><td>CHUM</td><td>4.05</td><td>7.44</td><td>6.11</td><td>4.40</td><td>5.12</td><td>-4.90 **</td><td>2.64 *</td></tr><tr><td>SOCK</td><td>9.43</td><td>9.50</td><td>9.35</td><td>9.51</td><td>9.44</td><td>-0.19</td><td>-0.45</td></tr><tr><td>PINK</td><td>3.88</td><td>4.00</td><td>4.16</td><td>3.77</td><td>3.92</td><td>-0.15</td><td>0.52</td></tr><tr><td rowspan="7">ORIGIN</td><td>TROUT</td><td>5.79</td><td>3.70</td><td>5.33</td><td>5.24</td><td>5.51</td><td>2.42</td><td>0.09</td></tr><tr><td>CAND</td><td>8.22</td><td>9.29</td><td>8.78</td><td>8.37</td><td>8.54</td><td>-1.82</td><td>0.75</td></tr><tr><td>BRIS</td><td>6.65</td><td>7.63</td><td>6.59</td><td>7.15</td><td>6.97</td><td>-1.34</td><td>-0.83</td></tr><tr><td>COOK</td><td>7.44</td><td>8.29</td><td>8.00</td><td>7.50</td><td>7.71</td><td>-1.62</td><td>1.01</td></tr><tr><td>JAP</td><td>6.00</td><td>7.92</td><td>6.06</td><td>6.77</td><td>6.55</td><td>-1.84</td><td>-0.74</td></tr><tr><td>NZ</td><td>3.94</td><td>3.08</td><td>4.12</td><td>3.52</td><td>3.64</td><td>0.86</td><td>0.67</td></tr><tr><td>CHILE</td><td>5.29</td><td>4.18</td><td>3.94</td><td>5.63</td><td>4.79</td><td>1.06</td><td>-1.86</td></tr><tr><td rowspan="4">METHOD</td><td>NRY</td><td>5.46</td><td>5.11</td><td>5.63</td><td>5.21</td><td>5.32</td><td>0.37</td><td>0.48</td></tr><tr><td>WCA</td><td>6.28</td><td>6.00</td><td>7.20</td><td>5.58</td><td>6.23</td><td>0.31</td><td>2.04 *</td></tr><tr><td>SEINE</td><td>6.84</td><td>6.93</td><td>6.95</td><td>6.81</td><td>6.86</td><td>-0.13</td><td>0.24</td></tr><tr><td>GILL</td><td>5.87</td><td>7.00</td><td>6.73</td><td>5.84</td><td>6.22</td><td>-1.70</td><td>1.44</td></tr><tr><td rowspan="3">TYPE</td><td>TROLL</td><td>9.26</td><td>9.82</td><td>9.41</td><td>9.44</td><td>9.42</td><td>-1.13</td><td>-0.07</td></tr><tr><td>FARM</td><td>7.35</td><td>5.09</td><td>6.02</td><td>7.12</td><td>6.63</td><td>3.23 *</td><td>-1.69</td></tr><tr><td>FRH</td><td>7.23</td><td>6.69</td><td>7.23</td><td>6.94</td><td>7.06</td><td>0.59</td><td>0.34</td></tr><tr><td rowspan="4">QUALITY</td><td>FRZ</td><td>9.08</td><td>9.17</td><td>9.29</td><td>8.97</td><td>9.11</td><td>-0.22</td><td>0.82</td></tr><tr><td>SALT</td><td>5.56</td><td>7.00</td><td>6.33</td><td>5.71</td><td>5.99</td><td>-1.43</td><td>0.68</td></tr><tr><td>LOW</td><td>1.55</td><td>0.89</td><td>1.08</td><td>1.53</td><td>1.35</td><td>1.43</td><td>-1.03</td></tr><tr><td>MED</td><td>5.58</td><td>5.33</td><td>5.42</td><td>5.56</td><td>5.5</td><td>0.45</td><td>-0.29</td></tr><tr><td rowspan="3">SKIN</td><td>HIGH</td><td>10.00</td><td>10.00</td><td>10.00</td><td>10.00</td><td>10</td><td></td><td></td></tr><tr><td>DARK</td><td>2.43</td><td>1.88</td><td>2.09</td><td>2.38</td><td>2.26</td><td>1.05</td><td>-0.62</td></tr><tr><td>SILV</td><td>6.93</td><td>7.29</td><td>7.04</td><td>7.03</td><td>7.03</td><td>-0.91</td><td>0.04</td></tr><tr><td rowspan="3">FLESH</td><td>BS</td><td>10.00</td><td>10.00</td><td>10.00</td><td>10.00</td><td>10</td><td></td><td></td></tr><tr><td>PALE</td><td>2.40</td><td>2.89</td><td>3.04</td><td>2.21</td><td>2.57</td><td>-0.78</td><td>1.42</td></tr><tr><td>PINK</td><td>6.80</td><td>7.56</td><td>7.67</td><td>6.59</td><td>7.04</td><td>-1.49</td><td>2.27 *</td></tr><tr><td rowspan="3">FAT</td><td>RED</td><td>9.63</td><td>9.33</td><td>9.71</td><td>9.41</td><td>9.54</td><td>0.52</td><td>0.56</td></tr><tr><td>LOW</td><td>4.23</td><td>3.78</td><td>3.67</td><td>4.38</td><td>4.09</td><td>0.85</td><td>-1.45</td></tr><tr><td>MED</td><td>8.30</td><td>7.50</td><td>8.33</td><td>7.85</td><td>8.07</td><td>1.66</td><td>1.07</td></tr><tr><td rowspan="4">FORM</td><td>HIGH</td><td>9.39</td><td>9.56</td><td>9.52</td><td>9.38</td><td>9.43</td><td>-0.46</td><td>0.42</td></tr><tr><td>HON</td><td>7.93</td><td>8.50</td><td>8.88</td><td>7.56</td><td>8.12</td><td>-1.05</td><td>2.58 *</td></tr><tr><td>HOFF</td><td>9.60</td><td>9.61</td><td>9.38</td><td>9.76</td><td>9.6</td><td>-0.04</td><td>-1.34</td></tr><tr><td>STK</td><td>1.36</td><td>1.83</td><td>1.21</td><td>1.63</td><td>1.36</td><td>-0.51</td><td>-0.52</td></tr><tr><td rowspan="5">SIZE</td><td>FILT</td><td>4.65</td><td>4.76</td><td>3.46</td><td>5.58</td><td>4.7</td><td>-0.10</td><td>-1.99</td></tr><tr><td>1-2</td><td>5.45</td><td>4.50</td><td>5.50</td><td>5.03</td><td>5.23</td><td>1.21</td><td>0.66</td></tr><tr><td>2-3</td><td>9.10</td><td>7.89</td><td>8.17</td><td>9.12</td><td>8.72</td><td>2.00</td><td>-1.68</td></tr><tr><td>3-4</td><td>7.78</td><td>8.61</td><td>8.29</td><td>7.85</td><td>8.03</td><td>-1.48</td><td>0.83</td></tr><tr><td>4-5</td><td>4.72</td><td>6.11</td><td>6.33</td><td>4.30</td><td>5.16</td><td>-1.52</td><td>2.36 *</td></tr><tr><td rowspan="4">PRICE</td><td>KG5+</td><td>3.36</td><td>2.64</td><td>4.14</td><td>2.88</td><td>2.4</td><td>0.69</td><td>0.96</td></tr><tr><td>580</td><td>10.00</td><td>10.00</td><td>10.00</td><td>10.00</td><td>10</td><td></td><td></td></tr><tr><td>790</td><td>8.98</td><td>9.36</td><td>8.82</td><td>9.18</td><td>9.05</td><td>-1.28</td><td>-0.48</td></tr><tr><td>1000</td><td>7.83</td><td>6.73</td><td>6.52</td><td>8.15</td><td>7.45</td><td>-1.30</td><td>-0.30</td></tr><tr><td rowspan="5">SUPPLY</td><td>1190</td><td>5.81</td><td>6.22</td><td>6.26</td><td>6.33</td><td>1)</td><td></td><td>2)</td></tr><tr><td>13/14</td><td>3.78</td><td>4.18</td><td>4.88</td><td>3.35</td><td>3.61</td><td></td><td></td></tr><tr><td>16/1700</td><td>1.33</td><td>2.07</td><td>1.05</td><td>1.79</td><td>1.43</td><td></td><td></td></tr><tr><td>20/2100</td><td>0.15</td><td>0.73</td><td>0.14</td><td>0.41</td><td>0.3</td><td></td><td></td></tr><tr><td>YEAR</td><td>7.18</td><td>9.41</td><td>8.35</td><td>7.50</td><td>7.86</td><td>-3.31 *</td><td>1.35</td></tr><tr><td>SEASN</td><td>6.88</td><td>7.18</td><td>6.17</td><td>7.50</td><td>6.97</td><td>-0.32</td><td>-1.53</td></tr></tbody></table>

1) Since Importers and large retail store buyers face different price range, t-test between importers and retailers on price is not meaningful.

2) Respondents evaluated different range of price in 1988 and 1989. T-test on price between 1988 and 1989 (except 580, 790, AND 1000 yen/kg which were used for both survey years), therefore, is not meaningful.

Significance for t-test is indicated as follows:

* p < 0.05

** p < 0.01
farmed products significantly higher than larger retail
store buyers. The difference may be due partly to the
relatively poor image domestic (Japanese) farmed coho has
compared with the farmed salmon from Norway, Canada or Chile
handled by importers. Difference in preference may have
also resulted from the fact that importers distribute salmon
through many market channels. Although farmed salmon has
made a significant inroads into the retail sector specially
through supermarket outlets, salted salmon is still the
dominant product form. Farmed salmon was usually not
processed into salted products.

Individual attribute levels which showed significant
preference changes between the two survey years are chum
salmon, origination from west coast U.S., pink red flesh
color, and Head-on product form, and 4-5kg size category.
In general, however, individual attribute level ratings were
strongly consistent between two survey years.

6.3 Variable Selection for Data Pooling

The survey data used for the analysis is from two
separate time periods. Given a relatively small sample size
in each survey year, it is desirable to pool the data if it
is appropriate. The result of the direct ratings in the
self-explicated measure which indicated strong consistency
between two survey years also supported this approach. In
the two-limit Tobit specification, a dummy variable for 1989
survey year and its product with each attribute level were
included in the regression. This is to allow the intercept
and slope coefficients to differ from 1988 to 1989 survey
period. The variance of the error term, however, was
assumed to be the same in both survey years. A Wald test
was conducted to test the significance level of the
difference in coefficients for 1988 and 1989. A Wald test
is asymptotically equivalent to an F test, applied to the
model which is nonlinear in the parameters. The test
statistic has an unknown small-sample distribution but is
distributed asymptotically as a Chi-square ($\chi^2$) with degrees
of freedom equal to the number of restrictions being tested
(Kennedy).

Table 6.3 shows the results of the estimation and tests
of the significance of difference in coefficients between
two survey years. Variables which did not show significant
difference between two survey years were pooled together.
However, since pooling of one variable affects the remainder
of the variables in the model, pooling of variables was made
iteratively. Variables were pooled until significance level
of the difference (between coefficients in 1988 and 1989) is
$p < 0.2$.

The variables which showed noticeable differences
between 1988 and 1989 are sockeye salmon, seine, high fat
content, steaks form, head-on 3/4kg+, head-off 2/3kg, and
price. These eight variables were allowed to have different
coefficients for 1988 and 1989, while other variables were
pooled together for two survey years. The dummy intercept
<caption>TABLE 6.3 : TWO-LIMIT TOBIT MODEL WITH SEPARATE INTERCEPT AND COEFFICIENTS FOR 1988 AND 1989 SURVEY YEARS</caption>

MAXIMUM LIKELIHOOD ESTIMATES

<table><thead><tr><th colspan="2">LOG-UKELIHOOD</th><th colspan="2">-1453.1</th><th colspan="2">WALD TEST</th></tr><tr><th>VARIABLES</th><th>COEFFICIENT</th><th>STD. ERROR</th><th>CHI-SQ</th><th>SIGNIFICANCE</th><th></th></tr></thead><tbody><tr><td>ONE</td><td>-11.6365</td><td>34.2419</td><td></td><td></td><td></td></tr><tr><td>COHO88</td><td>17.2945</td><td>16.6894</td><td></td><td></td><td></td></tr><tr><td>COHO89</td><td>29.3312</td><td>13.2354</td><td>0.3192</td><td>0.5721</td><td></td></tr><tr><td>KING88</td><td>13.3841</td><td>14.0998</td><td></td><td></td><td></td></tr><tr><td>KING89</td><td>23.3986</td><td>9.8354</td><td>0.3408</td><td>0.5594</td><td></td></tr><tr><td>SOCKEYE88</td><td>-5.6719</td><td>17.1215</td><td></td><td></td><td></td></tr><tr><td>SOCKEYE89</td><td>32.7319</td><td>11.3137</td><td>3.4831</td><td>0.0620</td><td></td></tr><tr><td>ATLANTIC88</td><td>18.3058</td><td>17.5865</td><td></td><td></td><td></td></tr><tr><td>ATLANTIC89</td><td>37.8565</td><td>14.9009</td><td>0.7178</td><td>0.3989</td><td></td></tr><tr><td>PINK88</td><td>-27.5825</td><td>15.6037</td><td></td><td></td><td></td></tr><tr><td>PINK89</td><td>-6.7871</td><td>9.2281</td><td>1.3139</td><td>0.2517</td><td></td></tr><tr><td>CANADA88</td><td>21.3232</td><td>9.8952</td><td></td><td></td><td></td></tr><tr><td>CANADA89</td><td>13.1100</td><td>7.4706</td><td>0.3260</td><td>0.5680</td><td></td></tr><tr><td>NRY88</td><td>-3.7146</td><td>16.3739</td><td></td><td></td><td></td></tr><tr><td>NRY89</td><td>-5.9376</td><td>11.0866</td><td>0.0044</td><td>0.9471</td><td></td></tr><tr><td>ALASKA88</td><td>3.8313</td><td>10.5346</td><td></td><td></td><td></td></tr><tr><td>ALASKA89</td><td>2.9210</td><td>7.4605</td><td>0.0050</td><td>0.9437</td><td></td></tr><tr><td>NZ88</td><td>3.2904</td><td>19.5409</td><td></td><td></td><td></td></tr><tr><td>NZ89</td><td>18.0076</td><td>14.4140</td><td>0.3916</td><td>0.5314</td><td></td></tr><tr><td>CHILE88</td><td>-9.2977</td><td>16.1667</td><td></td><td></td><td></td></tr><tr><td>CHILE89</td><td>4.4615</td><td>10.8336</td><td>0.5042</td><td>0.4777</td><td></td></tr><tr><td>WESTCOAST88</td><td>-10.8414</td><td>12.3343</td><td></td><td></td><td></td></tr><tr><td>WESTCOAST89</td><td>4.4667</td><td>8.2867</td><td>1.0099</td><td>0.3149</td><td></td></tr><tr><td>SEINE88</td><td>-2.2474</td><td>14.5837</td><td></td><td></td><td></td></tr><tr><td>SEINE89</td><td>19.2126</td><td>9.8929</td><td>0.6234</td><td>0.3642</td><td></td></tr><tr><td>GILL88</td><td>-2.9247</td><td>11.7772</td><td></td><td></td><td></td></tr><tr><td>GILL89</td><td>4.1613</td><td>7.9259</td><td>0.2492</td><td>0.6176</td><td></td></tr><tr><td>TROLL88</td><td>13.3810</td><td>13.5184</td><td></td><td></td><td></td></tr><tr><td>TROLL89</td><td>19.8498</td><td>8.8946</td><td>0.0028</td><td>0.9578</td><td></td></tr><tr><td>FRESH88</td><td>11.3484</td><td>8.2076</td><td></td><td></td><td></td></tr><tr><td>FRESH89</td><td>10.2904</td><td>8.0445</td><td>0.0106</td><td>0.9174</td><td></td></tr><tr><td>SALTED88</td><td>0.2581</td><td>9.3372</td><td></td><td></td><td></td></tr><tr><td>SALTED89</td><td>5.8871</td><td>8.4673</td><td>0.2439</td><td>0.6214</td><td></td></tr><tr><td>QUALITY88</td><td>3.9160</td><td>9.4539</td><td></td><td></td><td></td></tr><tr><td>QUALITY89</td><td>-21.7182</td><td>6.5180</td><td>4.9860</td><td>0.0258</td><td></td></tr><tr><td>QUALITY88</td><td>23.7360</td><td>8.0603</td><td></td><td></td><td></td></tr><tr><td>QUALITY89</td><td>8.6887</td><td>8.1915</td><td>2.1992</td><td>0.1081</td><td></td></tr><tr><td>DARK88</td><td>-7.7458</td><td>10.4319</td><td></td><td></td><td></td></tr><tr><td>DARK89</td><td>-7.4494</td><td>6.7549</td><td>0.0006</td><td>0.9610</td><td></td></tr><tr><td>BTSILVER88</td><td>-5.8896</td><td>10.8397</td><td></td><td></td><td></td></tr><tr><td>BTSILVER89</td><td>2.8550</td><td>8.6661</td><td>0.4510</td><td>0.5018</td><td></td></tr><tr><td>PALE88</td><td>14.8135</td><td>8.9263</td><td></td><td></td><td></td></tr><tr><td>PALE89</td><td>5.5652</td><td>6.6062</td><td>0.6656</td><td>0.4146</td><td></td></tr><tr><td>DEEPRED88</td><td>18.2571</td><td>8.2225</td><td></td><td></td><td></td></tr><tr><td>DEEPRED89</td><td>6.1919</td><td>6.3343</td><td>1.5852</td><td>0.2080</td><td></td></tr><tr><td>LFAT88</td><td>-2.9296</td><td>9.0508</td><td></td><td></td><td></td></tr><tr><td>LFAT89</td><td>-5.5334</td><td>6.2455</td><td>0.0562</td><td>0.8127</td><td></td></tr><tr><td>HFAT88</td><td>17.8284</td><td>9.2597</td><td></td><td></td><td></td></tr><tr><td>HFAT89</td><td>7.0732</td><td>6.7574</td><td>0.8835</td><td>0.3472</td><td></td></tr><tr><td>STEAK88</td><td>35.4559</td><td>23.7633</td><td></td><td></td><td></td></tr><tr><td>STEAK89</td><td>-0.3759</td><td>17.2058</td><td>1.4933</td><td>0.2217</td><td></td></tr><tr><td>FILLET88</td><td>10.8323</td><td>24.3562</td><td></td><td></td><td></td></tr><tr><td>FILLET89</td><td>8.4484</td><td>16.6426</td><td>0.0066</td><td>0.9354</td><td></td></tr><tr><td>HEADON1/288</td><td>26.3564</td><td>23.7167</td><td></td><td></td><td></td></tr><tr><td>HEADON1/289</td><td>14.4632</td><td>18.0738</td><td>0.1594</td><td>0.6897</td><td></td></tr><tr><td>HEADON2/388</td><td>46.0953</td><td>25.4393</td><td></td><td></td><td></td></tr><tr><td>HEADON2/389</td><td>16.2201</td><td>17.8579</td><td>0.8044</td><td>0.3698</td><td></td></tr><tr><td>HEADON3/4+88</td><td>23.6326</td><td>21.0039</td><td></td><td></td><td></td></tr><tr><td>HEADON3/4+89</td><td>2.6467</td><td>15.3535</td><td>0.6516</td><td>0.4195</td><td></td></tr><tr><td>HEADOFF2/388</td><td>55.8531</td><td>27.6775</td><td></td><td></td><td></td></tr><tr><td>HEADOFF2/389</td><td>32.3625</td><td>20.0503</td><td>0.4672</td><td>0.4943</td><td></td></tr><tr><td>HEADOFF3/4+88</td><td>11.3207</td><td>26.1833</td><td></td><td></td><td></td></tr><tr><td>HEADOFF3/4+89</td><td>6.2477</td><td>18.1222</td><td>0.0255</td><td>0.8732</td><td></td></tr><tr><td>SEASONAL88</td><td>11.2524</td><td>7.1724</td><td></td><td></td><td></td></tr><tr><td>SEASONAL89</td><td>7.3054</td><td>4.9524</td><td>0.2050</td><td>0.6507</td><td></td></tr><tr><td>PRICEDIF88</td><td>-0.0414</td><td>0.0058</td><td></td><td></td><td></td></tr><tr><td>PRICEDIF89</td><td>0.0201</td><td>0.0094</td><td>3.7443</td><td>0.0530</td><td></td></tr><tr><td>TRADER</td><td>-8.1372</td><td>4.2953</td><td></td><td></td><td></td></tr><tr><td>SURV88</td><td>25.4046</td><td>40.9742</td><td></td><td></td><td></td></tr><tr><td>SIGMA</td><td>30.3661</td><td>1.3701</td><td></td><td></td><td></td></tr></tbody></table>
term for the year of the survey was insignificant in the
original specification with all the attribute variables with
separate coefficients for 1988 and 1989. However, in order
to capture the cumulative effect of those variables which
were pooled together, the dummy intercept for the year of
the survey was left in the model.

The preliminary run with the data combined for 1988 and
1989 showed overall agreement between the two-limit Tobit
and the rank-order logit. (The result of the estimation is
in Appendix B.) Although the Wald test was conducted in the
two-limit Tobit model, the same variables are pooled for
1988 and 1989 in the rank-order logit model. This is to
retain comparability of the result between the two model
specifications.

6.4 Overall Results

The model with variables partially pooled for 1988 and
1989 was regressed through two specifications; the two-limit
Tobit and the rank-order logit. The results are summarized
in Table 6.4 and Table 6.5. The separate coefficients are
listed for 1988 and 1989 for eight selected variables. Wald
tests were conducted for those eight variables in the
partially pooled model for two-limit Tobit. The result of
the Wald test is shown in Table 6.6.

Despite the intertemporal difference among responses by
importers, the model estimated the buyer's preference
function reasonably well. Higher performance was expected
<table><caption>TABLE 6.4: THE RESULTS OF CONJOINT ANALYSIS
TWO-LIMIT TOBIT MODEL</caption><caption>MAXIMUM LIKELIHOOD ESTIMATES<br>LOG-LIKELIHOOD -1459.6</caption><thead><tr><th rowspan="2">VARIABLES</th><th colspan="2">COEFFICIENT</th><th colspan="2">STD. ERROR</th></tr><tr><th>1988</th><th>1989</th><th>1988</th><th>1989</th></tr></thead><tbody><tr><td>ONE</td><td>-19.9058</td><td></td><td>18.4771</td><td></td></tr><tr><td>COHO</td><td>30.2398</td><td></td><td>9.9538</td><td></td></tr><tr><td>KING</td><td>24.2880</td><td></td><td>7.8417</td><td></td></tr><tr><td>SOCKEYE</td><td>11.7484</td><td>28.8643</td><td>11.2843</td><td>10.7004</td></tr><tr><td>ATLANTIC</td><td>34.2341</td><td></td><td>11.2850</td><td></td></tr><tr><td>PINK</td><td>-9.4564</td><td></td><td>7.8955</td><td></td></tr><tr><td>CANADA</td><td>16.5789</td><td></td><td>5.9076</td><td></td></tr><tr><td>NRY</td><td>-3.9388</td><td></td><td>9.1985</td><td></td></tr><tr><td>ALASKA</td><td>3.9282</td><td></td><td>6.1068</td><td></td></tr><tr><td>NZ</td><td>15.9820</td><td></td><td>11.5896</td><td></td></tr><tr><td>CHILE</td><td>0.3042</td><td></td><td>8.9515</td><td></td></tr><tr><td>WESTCOAST</td><td>-0.4882</td><td></td><td>6.8836</td><td></td></tr><tr><td>SEINE</td><td>-1.7189</td><td>16.1429</td><td>9.8155</td><td>8.2220</td></tr><tr><td>GILL</td><td>-3.0059</td><td></td><td>6.6095</td><td></td></tr><tr><td>TROLL</td><td>15.7391</td><td></td><td>6.9557</td><td></td></tr><tr><td>FRESH</td><td>10.1983</td><td></td><td>4.8403</td><td></td></tr><tr><td>SALTED</td><td>3.0488</td><td></td><td>5.3117</td><td></td></tr><tr><td>LQUALITY</td><td>1.0233</td><td>-20.3174</td><td>7.5386</td><td>5.9388</td></tr><tr><td>HQUALITY</td><td>13.7826</td><td></td><td>4.8900</td><td></td></tr><tr><td>DARK</td><td>-5.9010</td><td></td><td>5.6005</td><td></td></tr><tr><td>BTSILVER</td><td>1.0902</td><td></td><td>5.6890</td><td></td></tr><tr><td>PALE</td><td>9.6574</td><td></td><td>5.2970</td><td></td></tr><tr><td>DEEPRED</td><td>9.6926</td><td></td><td>5.0202</td><td></td></tr><tr><td>LFAT</td><td>-5.3496</td><td></td><td>5.0927</td><td></td></tr><tr><td>HFAT</td><td>18.3550</td><td>8.5126</td><td>7.3891</td><td>5.9908</td></tr><tr><td>STEAKS</td><td>27.4260</td><td>5.5677</td><td>14.7570</td><td>13.8865</td></tr><tr><td>FILLET</td><td>9.3129</td><td></td><td>12.9022</td><td></td></tr><tr><td>HEADON1/2</td><td>19.2961</td><td></td><td>13.8340</td><td></td></tr><tr><td>HEADON2/3</td><td>29.1831</td><td></td><td>13.9700</td><td></td></tr><tr><td>HEADON3/4+</td><td>21.4284</td><td>6.2568</td><td>12.5886</td><td>12.2378</td></tr><tr><td>HEADOFF2/3</td><td>58.2845</td><td>33.4898</td><td>16.8725</td><td>16.6569</td></tr><tr><td>HEADOFF3/4+</td><td>9.2352</td><td></td><td>13.9820</td><td></td></tr><tr><td>SEASONAL</td><td>8.9753</td><td></td><td>4.0886</td><td></td></tr><tr><td>PRICEDIF</td><td>-0.0373</td><td>-0.0239</td><td>0.0049</td><td>0.0080</td></tr><tr><td>TRADER</td><td>-6.8740</td><td></td><td>4.1670</td><td></td></tr><tr><td>SURVEY89</td><td>30.2371</td><td></td><td>8.3745</td><td></td></tr><tr><td>SIGMA</td><td>30.9546</td><td></td><td>1.3961</td><td></td></tr></tbody></table>
<table><caption>TABLE 6.5: THE RESULTS OF CONJOINT ANALYSIS
RANK-ORDER LOGIT MODEL</caption><caption>MAXIMUM LIKELIHOOD ESTIMATES</caption><thead><tr><th rowspan="2">VARIABLES</th><th colspan="2">COEFFICIENT</th><th colspan="2">STD. ERROR</th></tr><tr><th>1988</th><th>1989</th><th>1988</th><th>1989</th></tr></thead><tbody><tr><td>COHO</td><td>1.7221</td><td></td><td>0.4722</td><td></td></tr><tr><td>KING</td><td>1.5010</td><td></td><td>0.3629</td><td></td></tr><tr><td>SOCKEYE</td><td>0.6628</td><td>1.3272</td><td>0.5326</td><td>0.5243</td></tr><tr><td>ATLANTIC</td><td>1.1570</td><td></td><td>0.4760</td><td></td></tr><tr><td>PINK</td><td>-0.3109</td><td></td><td>0.3639</td><td></td></tr><tr><td>CANADA</td><td>0.9984</td><td></td><td>0.2785</td><td></td></tr><tr><td>NRY</td><td>-0.0300</td><td></td><td>0.4264</td><td></td></tr><tr><td>ALASKA</td><td>0.1146</td><td></td><td>0.2895</td><td></td></tr><tr><td>NZ</td><td>0.5943</td><td></td><td>0.5093</td><td></td></tr><tr><td>CHILE</td><td>-0.6114</td><td></td><td>0.4325</td><td></td></tr><tr><td>WESTCOAST</td><td>-0.3543</td><td></td><td>0.3156</td><td></td></tr><tr><td>SEINE</td><td>-0.1269</td><td>0.1478</td><td>0.3976</td><td>0.3565</td></tr><tr><td>GILL</td><td>-0.1158</td><td></td><td>0.3134</td><td></td></tr><tr><td>TROLL</td><td>0.1565</td><td></td><td>0.3273</td><td></td></tr><tr><td>FRESH</td><td>-0.0943</td><td></td><td>0.2291</td><td></td></tr><tr><td>SALTED</td><td>-0.0496</td><td></td><td>0.2317</td><td></td></tr><tr><td>LQUALITY</td><td>-0.9827</td><td>-20.3174</td><td>0.3414</td><td>0.2832</td></tr><tr><td>HQUALITY</td><td>1.2077</td><td></td><td>0.2227</td><td></td></tr><tr><td>DARK</td><td>-0.2515</td><td></td><td>0.2493</td><td></td></tr><tr><td>BTSILVER</td><td>-0.1310</td><td></td><td>0.2716</td><td></td></tr><tr><td>PALE</td><td>0.2620</td><td></td><td>0.2308</td><td></td></tr><tr><td>DEEPRED</td><td>0.5762</td><td></td><td>0.2140</td><td></td></tr><tr><td>LFAT</td><td>-0.1804</td><td></td><td>0.2198</td><td></td></tr><tr><td>HFAT</td><td>0.9404</td><td>0.6802</td><td>0.3218</td><td>0.2684</td></tr><tr><td>STEAKS</td><td>0.6597</td><td>0.1425</td><td>0.6051</td><td>0.5586</td></tr><tr><td>FILLET</td><td>0.1668</td><td></td><td>0.5090</td><td></td></tr><tr><td>HEADON1/2</td><td>0.6910</td><td></td><td>0.5892</td><td></td></tr><tr><td>HEADON2/3</td><td>1.6889</td><td></td><td>0.5619</td><td></td></tr><tr><td>HEADON3/4+</td><td>1.1655</td><td>0.0176</td><td>0.4623</td><td>0.4835</td></tr><tr><td>HEADOFF2/3</td><td>2.1688</td><td>1.1908</td><td>0.6662</td><td>0.6427</td></tr><tr><td>HEADOFF3/4+</td><td>0.7000</td><td></td><td>0.5439</td><td></td></tr><tr><td>SEASONAL</td><td>0.6493</td><td></td><td>0.1934</td><td></td></tr><tr><td>PRICEDIF</td><td>-0.0016</td><td>-0.0013</td><td>0.0002</td><td>0.0004</td></tr><tr><td>TRADER</td><td>-2.0642</td><td></td><td>0.1950</td><td></td></tr><tr><td>SURVEY89</td><td>0.1326</td><td></td><td>0.3690</td><td></td></tr></tbody></table>
<table><caption>TABLE 6.6: WALD TEST FOR COEFFICIENT CHANGE OVER 1988 AND 1989 SURVEY YEAR IN THE PARTIALLY POOLED MODEL TWO-LIMIT TOBIT</caption><caption>MAXIMUM LIKELIHOOD ESTIMATES<br>LOG-LIKELIHOOD -1459.6</caption><thead><tr><th rowspan="2">VARIABLES</th><th colspan="2">COEFFICIENT</th><th colspan="2">WALD TEST</th></tr><tr><th>1988</th><th>1989</th><th>CHISQ</th><th>SIGNIF. LEVEL</th></tr></thead><tbody><tr><td>ONE</td><td>-19.9058</td><td></td><td></td><td></td></tr><tr><td>COHO</td><td>30.2398</td><td></td><td></td><td></td></tr><tr><td>KING</td><td>24.2880</td><td></td><td></td><td></td></tr><tr><td>SOCKEYE</td><td>11.7484</td><td>28.8643</td><td>2.0518</td><td>0.1520</td></tr><tr><td>ATLANTIC</td><td>34.2341</td><td></td><td></td><td></td></tr><tr><td>PINK</td><td>-9.4564</td><td></td><td></td><td></td></tr><tr><td>CANADA</td><td>16.5789</td><td></td><td></td><td></td></tr><tr><td>NRY</td><td>-3.9388</td><td></td><td></td><td></td></tr><tr><td>ALASKA</td><td>3.9282</td><td></td><td></td><td></td></tr><tr><td>NZ</td><td>15.9820</td><td></td><td></td><td></td></tr><tr><td>CHILE</td><td>0.3042</td><td></td><td></td><td></td></tr><tr><td>WESTCOAST</td><td>-0.4882</td><td></td><td></td><td></td></tr><tr><td>SEINE</td><td>-1.7189</td><td>16.1429</td><td>3.2553</td><td>0.0712</td></tr><tr><td>GILL</td><td>-3.0059</td><td></td><td></td><td></td></tr><tr><td>TROLL</td><td>15.7391</td><td></td><td></td><td></td></tr><tr><td>FRESH</td><td>10.1983</td><td></td><td></td><td></td></tr><tr><td>SALTED</td><td>3.0488</td><td></td><td></td><td></td></tr><tr><td>LQUALITY</td><td>1.0233</td><td>-20.3174</td><td>7.2242</td><td>0.0072</td></tr><tr><td>HQUALITY</td><td>13.7826</td><td></td><td></td><td></td></tr><tr><td>DARK</td><td>-5.9010</td><td></td><td></td><td></td></tr><tr><td>BTSILVER</td><td>1.0902</td><td></td><td></td><td></td></tr><tr><td>PALE</td><td>9.6574</td><td></td><td></td><td></td></tr><tr><td>DEEPRED</td><td>9.6926</td><td></td><td></td><td></td></tr><tr><td>LFAT</td><td>-5.3496</td><td></td><td></td><td></td></tr><tr><td>HFAT</td><td>18.3550</td><td>8.5126</td><td>1.7757</td><td>0.1827</td></tr><tr><td>STEAKS</td><td>27.4260</td><td>5.5677</td><td>3.7944</td><td>0.0514</td></tr><tr><td>FILLET</td><td>9.3129</td><td></td><td></td><td></td></tr><tr><td>HEADON1/2</td><td>19.2961</td><td></td><td></td><td></td></tr><tr><td>HEADON2/3</td><td>29.1831</td><td></td><td></td><td></td></tr><tr><td>HEADON3/4+</td><td>21.4284</td><td>6.2568</td><td>2.9586</td><td>0.0854</td></tr><tr><td>HEADOFF2/3</td><td>58.2845</td><td>33.4898</td><td>3.4626</td><td>0.0628</td></tr><tr><td>HEADOFF3/4+</td><td>9.2352</td><td></td><td></td><td></td></tr><tr><td>SEASONAL</td><td>8.9753</td><td></td><td></td><td></td></tr><tr><td>PRICEDIF</td><td>-0.0373</td><td>-0.0239</td><td>2.6216</td><td>0.1054</td></tr><tr><td>TRADER</td><td>-6.8740</td><td></td><td></td><td></td></tr><tr><td>SURVEY89</td><td>30.2371</td><td></td><td></td><td></td></tr><tr><td>SIGMA</td><td>30.9546</td><td></td><td></td><td></td></tr></tbody></table>
for the two-limit Tobit model given that the score was used
for the dependent variable (rather than rankings) and that
the score potentially contains more information regarding
the intensity of the respondent's preference. The signs and
relative magnitude of the coefficients, although they are
not directly comparable due to different regression
procedures, are strongly consistent between two-limit Tobit
and rank-order logit models. These results are also
generally comparable to the self-explicated result, which
indicates the robustness of the estimation.

With lack of measure of the "goodness of fit" in the
qualitative response model analogous to R² in the
conventional linear regression model, two-limit Tobit and
rank-order logit models were evaluated on the basis of its
ability to predict respondent's actual responses in the
survey. One of the nonparametric statistics called Spearman
rank-order correlation coefficient (Siegel and Castellan)
were used to measure the association between buyer's
valuation of product predicted through two model
specifications and buyer's actual valuation of the products
obtained in the survey. To calculate the Spearman
correlation coefficient the variables has to be at least in
an ordinal scale (Siegel and Castellan).

The predicted scores estimated through two-limit Tobit
were transformed to ranks, establishing the common base to
compare the predictive performance of two-limit Tobit and
rank-order logit. Spearman correlation coefficients were
calculated between actual rankings and predicted rankings
estimated through two-limit Tobit and through rank-order
logit model respectively. The coefficient is bounded by
zero and one, where 1 indicates perfect association. Table
6.7 shows the mean value of the Spearman correlation
coefficient which was computed for each respondent. The
mean value of the Spearman coefficient is 0.6763 for the
two-limit Tobit, which is significant at p < 0.2 level, and
0.7224 for rank-order logit, which is significant at p < 0.1
level.

## 6.5 Comparison among Attribute Levels

In order to avoid perfect multicollinearity, one level
of attribute was omitted from each attribute category. The
coefficient of variables, therefore, should be interpreted
relative to the omitted level of the attribute. The same
should apply for the interpretation of the t-statistics.
The omitted variables from each attribute category are chum,
Japan, farmed, frozen, medium quality, silver skin, pink red
flesh color, medium fat content, head-off 1-2kg, and year-
round supply.

It should also be noted that when there are two or more
sets of dummy variables in a regression, the comparison of
the coefficients within a category is made relative to all
other sets of dummy variables represented by omitted
variables (Pindyck). For example, the coefficients on low
and high fat content is relative to medium fat content where
<table><caption>TABLE 6.7: MEAN SPEARMAN RANK-ORDER CORRELATION COEFFICIENT BETWEEN OBSERVED AND PREDICTED RANKS</caption><thead><tr><th></th><th>TWO-LIMIT<br>TOBIT</th><th>RANK-ORDER<br>LOGIT</th></tr></thead><tbody><tr><td>AVERAGE</td><td>0.6763</td><td>0.7224</td></tr><tr><td>TRADER</td><td>0.6866</td><td>0.7261</td></tr><tr><td>RETAILER</td><td>0.6489</td><td>0.7125</td></tr><tr><td>SURVEY88</td><td>0.6581</td><td>0.6778</td></tr><tr><td>SURVEY89</td><td>0.6872</td><td>0.7490</td></tr></tbody></table>
all the other characteristics are fixed at omitted dummy
variables described above (such as chum, Japan, farmed,
frozen, and so forth.)

The sign of the coefficient for the price variable
conformed to prior expectations for both two-limit Tobit and
rank-order logit models. It was negative and highly
significant in terms of contribution to the buyer's overall
product preference. The price coefficients were significant
for both survey years. The difference between 1988 and 1989
was insignificant (p < 0.105) as the Wald test indicated.

The results of the two-limit Tobit and rank-order logit
model were also consistent for quality variables which are
the other key variable with the highest importance ratings
in the self-explicated measure. The coefficient for high
quality displayed the expected sign and a significant
difference from medium quality (which is the omitted
variable from quality category) in terms of the contribution
to the product overall preference. The 1989 model revealed
significantly more negative preference for low-quality
products compared to 1988 (p < 0.0072). Observations and
anecdotal evidence indicating that end products which were
previously made with low quality salmon were using better
quality salmon in 1989 because of increased supply, seem to
support these buyer preference changes regarding low-quality
product.

The two-limit Tobit and the rank-order logit model show
consistent results regarding the relative preference among
different species of salmon. Both models indicate that coho, king, sockeye, and Atlantic salmon are, for the most part, significantly preferred to chum salmon, which is the omitted dummy variable from species category. Pink salmon is less preferred to chum salmon, though the differences between chum and pink are insignificant.

Separate coefficients for 1988 and 1989 are estimated for sockeye salmon. Both models exhibit a favorable preference change over time for sockeye salmon. However, the insignificant difference between sockeye salmon and chum salmon in 1988 is not consistent with the results from the direct evaluation of species in self-explicated measure.

Canada is the only country of origin which is significantly preferred to Japan. All the other origins for salmon are insignificantly different from Japan (which is an omitted dummy variable in the country of origin category). Two-limit Tobit and rank-order logit are consistent with each other in the relative preference among different origins of the product.

The Tobit model indicates that troll-caught is significantly preferred to farmed among different methods of catch. The result is consistent with the indication of the respondent's direct ratings in the self-explicated measure. The rank-order logit model, on the other hand, showed no significant differences among any methods of catch in terms of contribution to the buyer's overall preference for the product. Increased preference was observed for seine which
is inconsistent with the result from the direct ratings in
the self-explicated measure. The preference change for
seine, however, was only significant at p < 0.071 level.

Both models indicate that fresh product is
significantly preferred to frozen product, while salted
product is insignificantly different from frozen. This
result does not concur with the respondent's direct ratings
of product type where frozen is strongly preferred. When
comparing product type attributes holding other
characteristics constant, importers may prefer frozen, since
the vast majority of the product handled by importers is
frozen. However, importers move different products through
many market channels. In evaluating individual hypothetical
products, fresh/frozen/salted product type differences may
not hinder a buyers' overall preference for the product.

No significant differences were detected among all
skin color/appearance attributes in both Tobit and rank-
order logit models. The Attribute for flesh color, however,
exhibited expected differences in preference. The estimates
indicate that pale flesh color was not acknowledged as a
significant disadvantage compared to pink red fresh color.
However, deep red flesh color was found to be a significant
advantage over pink red flesh color in both models. The
result of the relative preference among skin color and flesh
color is consistent between two-limit Tobit and rank-order
logit.

The sign of the coefficient for fat content variables
conform to prior expectations, though the difference between
low fat and medium fat was insignificant. The results were
consistent between two-limit Tobit and rank-order logit
models. The preference change over time displays some
decrease in the contribution of high fat content to the
product's overall preference. The Tobit model indicates
that in 1989, high fat is not significantly preferred to
medium fat content.

Both Tobit and logit models indicate that 2-3 kg size
category in both head-on and head-off product form are
significantly preferred to head-off/1-2 kg size, which is
the omitted product form/size. Some preference changes are
observed in steak form product, head-off/2-3kg, and head-
on/3-4kg+ products. The significance level of these
preference changes, however, are low as Wald test indicated.
The result from the direct evaluation of attribute level
also shows some unfavorable preference change regarding
head-on/large size category.

Seasonal availability is significantly preferred to
year-round supply for both Tobit and rank-order logit.
Intercept terms for importers is negative and highly
significant in rank-order logit model. Tobit model also
shows a negative coefficient for importer dummy, though the
level of significance was low. The dummy variable for
survey year 1989 was left in the model to capture the
cumulative effect of the variables which was pooled together
for 1988 and 1989. The coefficient for survey year 1989 was
significant in the Tobit model, though it is not a case in
logit model.

6.6 Marginal Effects

The coefficient in Tobit model does not directly
represent a change in preference with respect to a change in
attribute levels. The estimated coefficients have to be
adjusted incorporating the probability factor for the
marginal effects. However, the comparison of the
coefficients among attribute levels presented in the
previous section is still valid because when adjusting for
the probability factor, the same scale factor applies to all
of the slopes in the model (Greene), leaving the relative
impacts among attribute levels intact. The marginal effects
of attribute levels in the two-limit Tobit model can be
formulated following the notation of Greene.

Expected value of Y in the two-limit (doubly censored)
Tobit model is formulated as;

$$
E[y] = L \text{Prob}[y=L] + U \text{Prob}[y=U] + E[y^*|L<y<U] \text{Prob}[L<y^*<U] \tag{6.1}
$$

Let

$$
l = \frac{L - \beta'x}{\sigma}, \quad u = \frac{U - \beta'x}{\sigma},
$$

$$
\Phi_l = \Phi(l), \Phi_u = \Phi(u), \Phi_l = \Phi(l), \Phi_u = \Phi(u) \tag{6.2}
$$

Then,
$$E[y] = U + L\Phi_{1} - U\Phi_{u} + (\Phi_{u} - \Phi_{1})\beta'x + \sigma(\Phi_{1} - \Phi_{u}). \quad (6.3)$$

The derivative with respect to x is;

$$\frac{\partial E[y]}{\partial x} = (\Phi_u - \Phi_l) \beta \quad (6.4)$$

This is equal to $\text{Prob} [L < y' < U | B$, the parameter vector scaled by the probability in the uncensored region.

The value of the above equation will vary with the values of x. The marginal value (which is a partial derivatives of the expected value of y with respect to x) is usually calculated at the mean value of x. The marginal effects estimated at mean value of x in the two-limit Tobit model is presented in Table 6.8.

The computation of partial derivatives is useful when the variable in question is continuous. The model being estimated, however, is composed of virtually all dummy variables except one for price. For the models with dummy variables, partial derivatives is not meaningful. Expected value of preference score was calculated by changing one attribute level from zero to one at a time while holding other attribute level constant. This change in expected value of preference score associated with a change in attribute level can be considered as the approximate measure of the marginal effect. Although all the permutations can not be covered, subsequent figures illustrate some of the
<table><caption>TABLE 6.8: THE MARGINAL EFFECTS ESTIMATED AT MEAN VALUE OF X IN THE TWO-LIMIT TOBIT MODEL</caption><thead><tr><td>VARIABLES</td><td>MARGINAL EFFECT</td></tr></thead><tbody><tr><td>CONSTANT</td><td>-15.3650</td></tr><tr><td>COHO</td><td>27.1060</td></tr><tr><td>KING</td><td>21.8440</td></tr><tr><td>SOCK88</td><td>10.4880</td></tr><tr><td>SOCK89</td><td>26.5640</td></tr><tr><td>ATL</td><td>30.2900</td></tr><tr><td>PINK</td><td>-8.5064</td></tr><tr><td>CANADA</td><td>15.0850</td></tr><tr><td>NRY</td><td>-3.5874</td></tr><tr><td>ALASKA</td><td>3.6836</td></tr><tr><td>NZ</td><td>14.0750</td></tr><tr><td>CHILE</td><td>0.4309</td></tr><tr><td>WCU.S.</td><td>-0.5533</td></tr><tr><td>SEINE88</td><td>-2.0088</td></tr><tr><td>SEINE89</td><td>13.9710</td></tr><tr><td>GILL</td><td>-2.8752</td></tr><tr><td>TROLL</td><td>13.9260</td></tr><tr><td>FRESH</td><td>9.2078</td></tr><tr><td>SALTED</td><td>2.5563</td></tr><tr><td>LQUAL88</td><td>0.9526</td></tr><tr><td>LQUAL89</td><td>-17.9040</td></tr><tr><td>HAUAL</td><td>12.2220</td></tr><tr><td>DARK</td><td>-5.4742</td></tr><tr><td>BSIL</td><td>1.0092</td></tr><tr><td>PALE</td><td>8.5122</td></tr><tr><td>DRED</td><td>8.5417</td></tr><tr><td>LFAT</td><td>-5.1843</td></tr><tr><td>HFAT88</td><td>16.0210</td></tr><tr><td>HFAT89</td><td>7.4230</td></tr><tr><td>STK88</td><td>22.6430</td></tr><tr><td>STK89</td><td>2.9992</td></tr><tr><td>FILT</td><td>6.6102</td></tr><tr><td>HON2</td><td>15.6250</td></tr><tr><td>HON3</td><td>24.2730</td></tr><tr><td>HON4588</td><td>17.3460</td></tr><tr><td>HON4589</td><td>3.9900</td></tr><tr><td>HOF388</td><td>49.9130</td></tr><tr><td>HOF389</td><td>27.7700</td></tr><tr><td>HOF45</td><td>6.4148</td></tr><tr><td>SEASN</td><td>7.9341</td></tr><tr><td>PDIF88</td><td>-0.0334</td></tr><tr><td>PDIF89</td><td>-0.0207</td></tr><tr><td>TRDER</td><td>-6.2526</td></tr><tr><td>SURV89</td><td>26.3200</td></tr></tbody></table>
approximate marginal effect of product attributes. The slope represents approximated marginal effect, which varies according to the different value of x.

Figure 6.1 illustrates an effect of price deviation from average market price on the product from Canada and Alaska. Other product attributes are set as; sockeye salmon, gillnetted, frozen, high quality, bright silver skin, deep red flesh color, high fat content, head-off/2-3kg size, with seasonal supply. Only price and country of origin were changed incrementally, allowing to isolate effect of price deviation on the product from different country of origin.

Price deviation, $O$, indicates that the product is priced at ongoing average market price. Negative and positive deviations from the average is plotted across $x$ axis. Figure 6.1 illustrates that as price deviation from average market price increases, its marginal effect on the product's overall preference increases. Price deviation, however, does not affect the product from different country of origin equally. Effect of price change on preference is higher for the product from Alaska than the product from Canada. These differential impact of price between Canada and Alaska increases as price positively deviate further from the average, represented by the increasing gap between the two lines in Figure 6.1. The approximated effect of 100 yen increase in price above average market price on the score (which is the proxy for preference) is about 0.569 for
<figure><img src="image_11.png" /><figcaption>FIGURE 6.1: EFFECT OF PRICE DEVIATION FROM AVERAGE MKT PRICE ON SOCKEYE SALMON FROM CANADA AND ALASKA</figcaption></figure>
product from Canada and 0.9069 for product from Alaska.

The same product were compared in terms of the effect of quality changes. The result is illustrated in Figure 6.2. Expected score is positively related to quality. Marginal effect of quality change on preference can be approximated by the slopes, which increases as quality changes from high to low. Impact of quality change on preference is higher for product from Alaska than from Canada.

The effect of price deviation on various salmon species were calculated in the similar fashion as above and illustrated in Figure 6.3. It is obvious from the figure that the price increase does not affect different species of salmon uniformly. Price change does not affect preference of high valued species (such as sockeye, coho, Atlantic, and king) as much as for chum and pink salmon. Marginal effects of price on chum and pink salmon (which are approximated by the slopes) increase at increasing rate. The figure also indicates that for respondent to be indifferent between, for example, king and sockeye or coho, other things being equal, the price difference should be around 200 yen/kg. Price difference between chum and pink salmon in order for the respondent to be indifferent about the choices is around 400 yen/kg. These price differences seem larger than the actual price difference among the different species in the market. In the actual market, however, price may not fully adjust to the indifference levels compared here. Difference in
<figure><img src="image_12.png" /><figcaption>FIGURE 6.2: EFFECT OF QUALITY CHANGES ON SOCKEYE SALMON FROM CANADA AND ALASKA</figcaption></figure>
<figure><img src="image_13.png" /><figcaption>FIGURE 6.3: EFFECT OF PRICE DEVIATION FROM MARKET PRICE ON SALMON SPECIES</figcaption></figure>
marginal effect of price on various species of salmon are
consistent with prior expectation and observations in the
current Japanese salmon market.

6.7 Summary of the Results

The focus of this research is to elicit a buyer's preference structure for salmon in terms of his valuation of individual product attributes. The relative contribution of individual attributes to the product's overall preference was estimated through two model specifications; two-limit Tobit and rank-order logit. Although it could be further refined, the model estimated the buyer's preference function reasonably well despite survey data from different salmon buyers at different points in time. The Spearman rank-order correlation coefficient indicated reasonable "goodness of fit" in terms of the models' ability to predict buyers actual responses.

The signs and relative magnitude of the coefficients are strongly consistent between two-limit Tobit and rank-order logit models for the key variables. Although there are some discrepancies for other less important variables, the results are, for the most part, consistent between two-limit Tobit and rank-order logit. Results from respective model specifications are also generally comparable to the self-explicated results, which underscores the robustness of the estimation. In general, the results of the conjoint analysis on buyers' preference structure generally confirmed
the intuition and observations of the current Japanese
salmon market.

Buyers' preference structure change over time was
tested for the time period between early 1987 and late 1988.
Significant changes in preference during this period were
observed for the attribute for low quality. Effect of low
quality on buyer's overall preference for the product is
significantly more negative in 1989. Buyers' preference
change toward low-quality product seems to be supported by
observations in the current salmon market in Japan. Except
this change toward low-quality attribute, little change was
observed in salmon buyer's preference structure over the
period of time. Estimated preference structure seems stable
over the period the surveys were undertaken.

Marginal effect of an incremental change in attribute
levels on a product's overall preference was calculated.
Given that the model being estimated consists mostly of
dummy variables, approximated marginal effect were
calculated by changing one attribute level from zero to one
at a time while holding other attribute levels constant.
The approximates of marginal effects were plotted to
illustrate the effect of price deviations from the average
market price on such attributes as species of salmon and
country of origin. Changes in price and quality affect
marginal preference scores of different species and origin
differently. Differential marginal effect on various
species and country of origin are consistent with prior
expectations and observations in the current Japanese salmon market.
# Chapter 7. Summary and Future Research Direction

This is the first time the Japanese salmon market has been analyzed in terms of buyer's preference of salmon as a function of product attributes. The results of the conjoint analysis on buyers' preference structure generally confirmed the intuition and observations of the current Japanese salmon market. Although the model can benefit from further refinement, this type of information on the structure of buyer preference sheds a new light on the conventional demand approach.

The analysis was based on the cross-sectional survey data collected at two different points in time. A review of import statistics indicates that the year the survey was conducted coincided with the beginning of the advent of cultured salmon in Japan. If additional data is collected, a clearer pattern of preference change over time may emerge.

On the subject of data collection, some adjustments in methods and refinements in techniques might increase the value of this type of information. Insufficient data on large retail stores such as supermarkets did not allow for separate analyses of buyer preferences in that sector. If the data base was extended, the question such as whether significant differences in buyer preferences exist in various market segments and for different product uses could be addressed. Differences in buyer preference between retail sector and growing restaurant sector would be a
logical extension of this research. Moreover, importers
surveyed distribute salmon through many market channels. A
questionnaire might be formulated to capture the preference
of salmon specific to a certain market outlet rather than
the general case.

Scoring hypothetical products on the scale of 0-100
was an efficient way to collect information per respondent
time and the task was plausible and easy for the respondents
to understand. This scaling lacks definable general
standards, however, and precision is compromised. Large
variance was observed in the way respondents assign scores
on the hypothetical products. Some respondents assigned
zeros to a number of products they were evaluating, while
another assigned 30 to what were claimed to be totally
unacceptable products. Uniformity of standards across the
board would be preferable and should be established.
Preference scores can be linked to a term which appeals to
the reality of the respondents such as likelihood to
purchase. Some linkages should also be established between
the preference score and the quantity of salmon respondents
are willing to purchase given a profile of the salmon
product. That information could be incorporated into the
conventional demand function. Comparative work could be
done by combining some of the techniques of the contingent
evaluation such as obtaining information on willingness to
pay to change a certain attribute of the product to a
certain level.
As more was learned about the salmon market and as the Japanese market evolved further, some of the questionnaire formats became less than completely realistic. In order to maintain compatibility and continuity of techniques to describe buyer preference between two survey years, however, the questionnaire format was kept the same. The Japanese salmon market has probably become even more dynamic and differentiated since our survey was conducted. If the survey were to be repeated, some adjustments would be needed to better accommodate current market conditions while maintaining basic compatibility with the previous survey results intact.

The information generated through this study can be used in the framework of optimal product design by incorporating cost of operation data. The information is particularly useful for salmon aquaculture where certain product attributes can be modified to better fit the market demand, although some attributes could be optimized in capture fisheries through selective fishing techniques and modification of fishing practices to some degree. Salmon growers could certainly select attribute combinations that maximize profits subject to the cost of providing that attribute mix. The cost/benefit tradeoffs will be an interesting and potentially important extension of this research.
APPENDIX: THE RESULTS OF THE ESTIMATE WITH 1988 AND 1989 D POOLED TOGETHER IN TWO-LIMIT TOBIT

MAXIMUM LIKELIHOOD ESTIMATES

LOG-LIKELIHOOD -1471.2

<table><thead><tr><th>VARIABLES</th><th>COEFFICIENT</th><th>STD. ERROR</th></tr></thead><tbody><tr><td>ONE</td><td>-19.6269</td><td>19.1764</td></tr><tr><td>COHO</td><td>31.0856</td><td>9.8152</td></tr><tr><td>KING</td><td>24.8334</td><td>8.0325</td></tr><tr><td>SOCKEYE</td><td>18.7648</td><td>9.4190</td></tr><tr><td>ATLANTIC</td><td>36.6137</td><td>11.4314</td></tr><tr><td>PINK</td><td>-9.0873</td><td>8.0173</td></tr><tr><td>CANADA</td><td>17.4395</td><td>6.1411</td></tr><tr><td>NRY</td><td>-0.1153</td><td>9.3673</td></tr><tr><td>ALASKA</td><td>2.8488</td><td>6.2895</td></tr><tr><td>NZ</td><td>18.2115</td><td>11.8535</td></tr><tr><td>CHILE</td><td>-0.5430</td><td>9.2735</td></tr><tr><td>WESTCOAST</td><td>-0.7060</td><td>7.0595</td></tr><tr><td>SEINE</td><td>12.8983</td><td>7.7326</td></tr><tr><td>GILL</td><td>-0.3834</td><td>6.8098</td></tr><tr><td>TROLL</td><td>16.2048</td><td>7.1829</td></tr><tr><td>FRESH</td><td>9.8238</td><td>4.9793</td></tr><tr><td>SALTED</td><td>2.6694</td><td>5.5044</td></tr><tr><td>LQUALITY</td><td>-15.6756</td><td>5.4726</td></tr><tr><td>HQUALITY</td><td>14.6679</td><td>5.0411</td></tr><tr><td>DARK</td><td>-4.3647</td><td>5.7825</td></tr><tr><td>BTSILVER</td><td>0.8075</td><td>5.8393</td></tr><tr><td>PALE</td><td>11.6983</td><td>5.4460</td></tr><tr><td>DEEPRED</td><td>11.8738</td><td>5.1608</td></tr><tr><td>LFAT</td><td>-5.1134</td><td>5.3097</td></tr><tr><td>HFAT</td><td>12.3641</td><td>5.6630</td></tr><tr><td>STEAKS</td><td>18.3142</td><td>14.0501</td></tr><tr><td>FILLET</td><td>12.9223</td><td>13.6835</td></tr><tr><td>HEADON1/2</td><td>22.6442</td><td>14.5881</td></tr><tr><td>HEADON2/3</td><td>34.7422</td><td>14.7497</td></tr><tr><td>HEADON3/4+</td><td>14.3821</td><td>12.4238</td></tr><tr><td>HEADOFF2/3</td><td>50.7708</td><td>16.4764</td></tr><tr><td>HEADOFF3/4+</td><td>15.6806</td><td>14.8420</td></tr><tr><td>SEASONAL</td><td>9.1812</td><td>4.2176</td></tr><tr><td>PRICEDIF</td><td>-0.0317</td><td>0.0048</td></tr><tr><td>TRADER</td><td>-4.4274</td><td>4.2961</td></tr><tr><td>SURVEY89</td><td>18.5309</td><td>3.6480</td></tr><tr><td>SIGMA</td><td>32.1254</td><td>1.4499</td></tr></tbody></table>
Bibliography

Addelman, Sydney. "Orthogonal Main-Effect Plans for Asymmetrical Factorial Experiments". *Technometrics* 4(1962): 21-46.

Addelman, Sydney. "Symmetrical and Asymmetrical Fractional Factorial Plans". *Technometrics* 4(1962): 47-58.

Amemiya, Takeshi. "Tobit Models: A Survey". *Journal of Econometrics*, 24 (1984): 3-61.

Anderson, James L. "Current and Future Market for Salmon in the United States". in Aquaculture International - Congress Proceedings. Congress held in Vancouver, British Columbia, Sept. 6-9, 1988. Vancouver, B.C.: Aquaculture International Congress. 1988.

Anderson, James L. and S. U. Bettencourt. "A Conjoint Approach to Model Product Preferences: The New England Market for Fresh and Frozen Salmon". *Marine Resource Economics* 8(forthcoming).

Anderson, James L. and P. Brooks. "Conjoint Analysis of the New England Salmon Market". Prepared for Department of Fisheries and Oceans. Vancouver, British Columbia. Canada. 1987.

Anderson, James L. and Y. Kusakabe. "Analysis of the Japanese Salmon Market". Economic and Commercial Analysis Report No. 56. Department of Fisheries & Ocean. Ottawa, Ontario. Canada. 1989.

Beggs S., S. Cardell and J. Hausman. "Assessing the Potential Demand for Electric Cars". *Journal of Econometrics* 16(1981): 1-19.

Cattin, Philippe and Dick R. Wittink. "Commercial Use of Conjoint Analysis: A Survey". *Journal of Marketing*, 46(1982): 44-53.

Freeman, Myrick A. The Benefits of Environmental Improvement Theory and Practice. Washington D.C.: Resources for the Future. 1979.

Goldberg, Stephen M., Paul E. Green, and Yoram Wind. "Conjoint Analysis of Price Premiums for Hotel Amenities". *Journal of Business*. 57(1984): S1111-S1132.
Green, Paul E. "Hybrid Models for Conjoint Analysis: An Expository Review". Journal of Marketing Research, XXI (1984): 155-69.

Green, Paul E., Kristiaan Helsen, and Bruce Shandler. "Conjoint Internal Validity Under Alternative Profile Presentations". Journal of Consumer Research. 15 (1988): 392-97.

Green, Paul E. and Vithala R. Rao. "Conjoint Measurement for Quantifying Judgmental Data". Journal of Marketing Research, VIII (1971): 355-63.

Green, Paul E. and V. Srinavasan. "Conjoint Analysis in Marketing: New Development with Implications for Research and Practice". Journal of Marketing, October (1990): 3-19.

____________________. "Conjoint Analysis in Consumer Research: Issues and Outlook". Journal of Consumer Research, 5 (1978): 103-123.

Green, Paul E. and Yoram Wind. "New Way to Measure Consumers' Judgements". Harvard Business Review, 53 (1975): 107-117.

Greene, William H. Econometric Analysis. New York: MacMillian Publishing Co. 1990a.

____________________. Limdep Ver. 5.1/386. New York, NY: Econometric Software, Inc. 1990b.

Hartley, M.J. "The Estimation of Markets in Disequilibrium: The Fixed Supply Case". International Economic Review 17 (3): 687-99.

Heckman, J. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models". Annals of Economic and Social Measurement V (1976): 475-92.

____________________. "Sample Selection Bias as a Specification Error". Econometrica. 47 (1979): 153-61.

Heiner, Ronald A. "The Origin of Predictable Behavior". American Economic Review. 73 (9): 560-595

Huber, Joel and John McCann. "The Impact of Inferential Beliefs on Product Evaluations". Journal of Marketing Research. 19 (1982): 324-33.
Japan Marine Products Importers Association. Japanese
Imports of Marine Products (Statistics). Tokyo, Japan.
1980-1990.

Johnson, Richard M. "Trade-Off Analysis of Consumer
Values". *Journal of Marketing Research*, XI (1974): 121-
127.

Kmenta, Jan. *Elements of Econometrics*. New York: Collier
MacMillian Co. 1986.

Kennedy, Peter. *A Guide to Econometrics*. Cambridge,
Massachusetts. The MIT Press. 1985.

Kikuchi, A. "Salmon Consumption at the Household Level in
Japan". M.S. Department of Agriculture and Resource
Economics. Oregon State University. 1987.

Kusakabe, Yuko and J.L. Anderson, "The Japanese Seafood
Market: Salmon". Economic and Commercial Analysis
Report No. 21. Department of Fisheries & Ocean.
Ottawa, Ontario. Canada. 1989.

Lancaster, Kelvin J. "A New Approach to Consumer Theory".
*Journal of Political Economy*. 74(1966): 132-57.

Luce, R. Duncan and John W. Tukey. "Simultaneous Conjoint
Measurement: A New Type of Fundamental Measurement".
*Journal of Mathematical Psychology*, 1(1964): 1-27.

Maddala, G.S. *Limited-Dependent and Qualitative Variables
in Econometrics*. New York: Cambridge University Press.
1990.

Maddala, G.S. *Econometrics*. New York: McGraw-Hill Book Co.
1977.

Mackenzie, John. "Conjoint Analysis of Deer Hunting".
*Northeastern Journal of Agricultural and Resource
Economics*, 10(1990): 109-117.

Manalo, Alberto B. "Accessing the Importance of Apple
Attributes: An Agricultural Application of Conjoint
Analysis". *Northeastern Journal of Agricultural and
Resource Economics*, 10(1990): 118-124.

Mitchell, Robert C. and Richard T. Carson. *Using Surveys to
Value Public Goods: The Contingent Valuation Method*.
Washington, D.C.: Resources for the Future. 1989.
Montgomery, David B. "Conjoint Calibration of the Customer/Competitor Interface in Industrial Markets". Industrial Marketing: A German-American Perspective. Klaus Backlaus and David T. Wilson, eds. Berlin: Springer-Verlag, 297-319.

Moore, William L. and Morris B. Holbrook. "Conjoint Analysis on Objects with Environmentally Correlated Attributes: The Questionable Importance of Representative Design". Journal of Consumer Research. 16(1990): 490-97.

Nakamura, Alice and Masao Nakamura. "Part-Time and Full-Time Work Behavior of Married Women: A Model with A Doubly Truncated Dependent Variable". Canadian Journal of Economics, XVI(1983): 229-257.

Nasaka, Y. "Salmonid Programs and Public Policy in Japan". submitted to the World Salmonid Conference, Portland, Oregon, Oct. 1986.

Pagan, Adrian and Frank Vella. Diagnostic Tests for Models Based on Individual Data: A Survey. Journal of Applied Econometrics, IV(1989): S29-S59.

Pindyck, Robert S. and Daniel L. Rubinfeld. Econometric Models and Economic Forecasts. New York: McGraw-Hill Book Co. 1990.

Rosett, Richard N. and Forrest D. Nelson. "Estimation of the Two-Limit Probit Regression Model". Econometrica, 43(1975): 141-146.

Siegel, Sydney and John Castellan, Jr. Non-Parametric Statistics for the Behavioral Sciences. New York: McGraw-Hill Book Co. 1988.

Statistics Bureau Management and Coordination Agency. Annual Report on the Family Income and Expenditure Survey. Japan. 1990.

Statistics and Information Bureau, Ministry of Agriculture. Forestry and Fishery. Gyogyo-Yoshokuqyo Seisan Tokei Nempo (Annual Statistics on Domestic Fisheries Production). Tokyo, Japan. 1989.

Tobin, James. "Estimation of Relationships for Limited Dependent Variables". Econometrica, 26(1958): 24-36.

Tokyo Central Wholesale Market, Annual Report of Tokyo Central Wholesale Market (Seafood). 1987.