The 2011-2016 Outlook for Chinese Recipe Bottled Soy Sauce in the United States by ICONGroup


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									 The 2011-2016 Outlook for Chinese Recipe
   Bottled Soy Sauce in the United States

                         Professor Philip M. Parker, Ph.D.
                       Chaired Professor of Management Science
                     INSEAD (Singapore and Fontainebleau, France)                                ©2010 ICON Group International, Inc.

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Neither ICON Group International, Inc. nor its employees or the author of this report can be held accountable for the
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                                          About the Author
Dr. Philip M. Parker is the Chaired Professor of Management Science at INSEAD where he has taught courses on
global competitive strategy since 1988. He has also taught courses at MIT, Stanford University, Harvard University,
UCLA, UCSD, and the Hong Kong University of Science and Technology. Professor Parker is the author of six
books on the economic convergence of nations. These books introduce the notion of “physioeconomics” which
foresees a lack of global convergence in economic behaviors due to physiological and physiographic forces. His
latest book is "Physioeconomics: The Basis for Long-Run Economic Growth" (MIT Press 2000). He has also
published numerous articles in academic journals, including, the Rand Journal of Economics, Marketing Science, the
Journal of International Business Studies, Technological Forecasting and Social Change, the International Journal
of Forecasting, the European Management Journal, the European Journal of Operational Research, the Journal of
Marketing, the International Journal of Research in Marketing, and the Journal of Marketing Research. He is also
on the editorial boards of several academic journals.

Dr. Parker received his Ph.D. in Business Economics from the Wharton School of the University of Pennsylvania
and has Masters degrees in Finance and Banking (University of Aix-Marseille) and Managerial Economics
(Wharton). His undergraduate degrees are in mathematics, biology and economics (minor in aeronautical
engineering). He has consulted and/or taught courses in Africa, the Middle East, Asia, Latin America, North America
and Europe.

                                          About this Series
The estimates given in this report were created using a methodology developed by and implemented under the direct
supervision of Professor Philip M. Parker, the Chaired Professor of Management Science, at INSEAD. The
methodology relies on historical figures across states. Reported figures should be seen as estimates of past and future
levels of latent demand.

Some of the methodologies and research approaches used in this report have benefited from the R&D Committee at
INSEAD, whose research support is gratefully acknowledged.                                                     ©2010 ICON Group International, Inc.

                     About ICON Group International, Inc.

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    Contents                                                                                         v

Table of Contents
1       INTRODUCTION                                                                             9
     1.1      Overview                                                                           9
     1.2      What is Latent Demand and the P.I.E.?                                              9
     1.3      The Methodology                                                                   10
        1.3.1   Step 1. Product Definition and Data Collection                                  11
        1.3.2   Step 2. Filtering and Smoothing                                                 12
        1.3.3   Step 3. Filling in Missing Values                                               12
        1.3.4   Step 4. Varying Parameter, Non-linear Estimation                                12
        1.3.5   Step 5. Fixed-Parameter Linear Estimation                                       13
        1.3.6   Step 6. Aggregation and Benchmarking                                            13
2       SUMMARY OF FINDINGS                                                                     14
     2.1   Latent Demand in The US                                                              15
3       FAR WEST                                                                                16
     3.1    Executive Summary                                                                   16
     3.2    Latent Demand by Year - Alaska                                                      18
     3.3    Cities Sorted by Rank - Alaska                                                      19
     3.4    Cities Sorted by Zipcode - Alaska                                                   20
     3.5    Latent Demand by Year - California                                                  22
     3.6    Cities Sorted by Rank - California                                                  23
     3.7    Cities Sorted by Zipcode - California                                               43
     3.8    Latent Demand by Year - Hawaii                                                      63
     3.9    Cities Sorted by Rank - Hawaii                                                      64
     3.10   Cities Sorted by Zipcode - Hawaii                                                   66
     3.11   Latent Demand by Year - Nevada                                                      68
     3.12   Cities Sorted by Rank - Nevada                                                      69
     3.13   Cities Sorted by Zipcode - Nevada                                                   70
     3.14   Latent Demand by Year - Oregon                                                      72
     3.15   Cities Sorted by Rank - Oregon                                                      73
     3.16   Cities Sorted by Zipcode - Oregon                                                   77
     3.17   Latent Demand by Year - Washington                                                  81
     3.18   Cities Sorted by Rank - Washington                                                  82
     3.19   Cities Sorted by Zipcode - Washington                                               89
4       GREAT LAKES                                                                             97
     4.1   Executive Summary                                                                    97
     4.2   Latent Demand by Year - Illinois                                                     99
     4.3   Cities Sorted by Rank - Illinois                                                    100
     4.4   Cities Sorted by Zipcode - Illinois                                                 113
     4.5   Latent Demand by Year - Indiana                                                     126
     4.6   Cities Sorted by Rank - Indiana                                                     127
     4.7   Cities Sorted by Zipcode - Indiana                                                  133
     4.8   Latent Demand by Year - Michigan                                                    139
     4.9   Cities Sorted by Rank - Michigan                                                    140
     4.10  Cities Sorted by Zipcode - Michigan                                                 148
     4.11  Latent Demand by Year - Ohio                                                        156
     4.12  Cities Sorted by Rank - Ohio                                                        157
     4.13  Cities Sorted by Zipcode - Ohio                                                     169
     4.14  Latent Demand by Year - Wisconsin                                                   181
     4.15  Cities Sorted by Rank - Wisconsin                                                   182
     4.16  Cities Sorted by Zipcode - Wisconsin                                                192                                            ©2010 ICON Group International, Inc.
    Contents                                                                                    vi

5       MID-ATLANTIC                                                                      202
     5.1    Executive Summary                                                             202
     5.2    Latent Demand by Year - Delaware                                              204
     5.3    Cities Sorted by Rank - Delaware                                              205
     5.4    Cities Sorted by Zipcode - Delaware                                           206
     5.5    Latent Demand by Year - District of Columbia                                  206
     5.6    Cities Sorted by Rank - District of Columbia                                  208
     5.7    Cities Sorted by Zipcode - District of Columbia                               208
     5.8    Latent Demand by Year - Maryland                                              209
     5.9    Cities Sorted by Rank - Maryland                                              210
     5.10   Cities Sorted by Zipcode - Maryland                                           216
     5.11   Latent Demand by Year - New Jersey                                            223
     5.12   Cities Sorted by Rank - New Jersey                                            224
     5.13   Cities Sorted by Zipcode - New Jersey                                         234
     5.14   Latent Demand by Year - New York                                              244
     5.15   Cities Sorted by Rank - New York                                              245
     5.16   Cities Sorted by Zipcode - New York                                           270
     5.17   Latent Demand by Year - Pennsylvania                                          296
     5.18   Cities Sorted by Rank - Pennsylvania                                          297
     5.19   Cities Sorted by Zipcode - Pennsylvania                                       312
6       NEW ENGLAND                                                                       327
     6.1   Executive Summary                                                              327
     6.2   Latent Demand by Year - Connecticut                                            329
     6.3   Cities Sorted by Rank - Connecticut                                            330
     6.4   Cities Sorted by Zipcode - Connecticut                                         335
     6.5   Latent Demand by Year - Maine                                                  340
     6.6   Cities Sorted by Rank - Maine                                                  341
     6.7   Cities Sorted by Zipcode - Maine                                               346
     6.8   Latent Demand by Year - Massachusetts                                          351
     6.9   Cities Sorted by Rank - Massachusetts                                          352
     6.10  Cities Sorted by Zipcode - Massachusetts                                       361
     6.11  Latent Demand by Year - New Hampshire                                          370
     6.12  Cities Sorted by Rank - New Hampshire                                          371
     6.13  Cities Sorted by Zipcode - New Hampshire                                       375
     6.14  Latent Demand by Year - Rhode Island                                           379
     6.15  Cities Sorted by Rank - Rhode Island                                           380
     6.16  Cities Sorted by Zipcode - Rhode Island                                        381
     6.17  Latent Demand by Year - Vermont                                                383
     6.18  Cities Sorted by Rank - Vermont                                                384
     6.19  Cities Sorted by Zipcode - Vermont                                             387
7       PLAINS                                                                            390
     7.1    Executive Summary                                                             390
     7.2    Latent Demand by Year - Iowa                                                  392
     7.3    Cities Sorted by Rank - Iowa                                                  393
     7.4    Cities Sorted by Zipcode - Iowa                                               397
     7.5    Latent Demand by Year - Kansas                                                401
     7.6    Cities Sorted by Rank - Kansas                                                402
     7.7    Cities Sorted by Zipcode - Kansas                                             405
     7.8    Latent Demand by Year - Minnesota                                             408
     7.9    Cities Sorted by Rank - Minnesota                                             409
     7.10   Cities Sorted by Zipcode - Minnesota                                          415
     7.11   Latent Demand by Year - Missouri                                              422                                       ©2010 ICON Group International, Inc.
    Contents                                                                               vii

     7.12      Cities Sorted by Rank - Missouri                                      423
     7.13      Cities Sorted by Zipcode - Missouri                                   429
     7.14      Latent Demand by Year - Nebraska                                      435
     7.15      Cities Sorted by Rank - Nebraska                                      436
     7.16      Cities Sorted by Zipcode - Nebraska                                   437
     7.17      Latent Demand by Year - North Dakota                                  440
     7.18      Cities Sorted by Rank - North Dakota                                  441
     7.19      Cities Sorted by Zipcode - North Dakota                               441
     7.20      Latent Demand by Year - South Dakota                                  443
     7.21      Cities Sorted by Rank - South Dakota                                  444
     7.22      Cities Sorted by Zipcode - South Dakota                               445
8       ROCKIES                                                                      446
     8.1   Executive Summary                                                         446
     8.2   Latent Demand by Year - Colorado                                          448
     8.3   Cities Sorted by Rank - Colorado                                          449
     8.4   Cities Sorted by Zipcode - Colorado                                       453
     8.5   Latent Demand by Year - Idaho                                             457
     8.6   Cities Sorted by Rank - Idaho                                             458
     8.7   Cities Sorted by Zipcode - Idaho                                          459
     8.8   Latent Demand by Year - Montana                                           461
     8.9   Cities Sorted by Rank - Montana                                           462
     8.10  Cities Sorted by Zipcode - Montana                                        463
     8.11  Latent Demand by Year - Utah                                              465
     8.12  Cities Sorted by Rank - Utah                                              466
     8.13  Cities Sorted by Zipcode - Utah                                           469
     8.14  Latent Demand by Year - Wyoming                                           473
     8.15  Cities Sorted by Rank - Wyoming                                           474
     8.16  Cities Sorted by Zipcode - Wyoming                                        475
9       SOUTHEAST                                                                    476
     9.1    Executive Summary                                                        476
     9.2    Latent Demand by Year - Alabama                                          478
     9.3    Cities Sorted by Rank - Alabama                                          479
     9.4    Cities Sorted by Zipcode - Alabama                                       483
     9.5    Latent Demand by Year - Arkansas                                         489
     9.6    Cities Sorted by Rank - Arkansas                                         490
     9.7    Cities Sorted by Zipcode - Arkansas                                      493
     9.8    Latent Demand by Year - Florida                                          496
     9.9    Cities Sorted by Rank - Florida                                          497
     9.10   Cities Sorted by Zipcode - Florida                                       512
     9.11   Latent Demand by Year - Georgia                                          528
     9.12   Cities Sorted by Rank - Georgia                                          529
     9.13   Cities Sorted by Zipcode - Georgia                                       535
     9.14   Latent Demand by Year - Kentucky                                         542
     9.15   Cities Sorted by Rank - Kentucky                                         543
     9.16   Cities Sorted by Zipcode - Kentucky                                      547
     9.17   Latent Demand by Year - Louisiana                                        551
     9.18   Cities Sorted by Rank - Louisiana                                        552
     9.19   Cities Sorted by Zipcode - Louisiana                                     556
     9.20   Latent Demand by Year - Mississippi                                      560
     9.21   Cities Sorted by Rank - Mississippi                                      561
     9.22   Cities Sorted by Zipcode - Mississippi                                   563
     9.23   Latent Demand by Year - North Carolina                                   567                                  ©2010 ICON Group International, Inc.
 Contents                                                                                   viii

     9.24   Cities Sorted by Rank - North Carolina                                    568
     9.25   Cities Sorted by Zipcode - North Carolina                                 575
     9.26   Latent Demand by Year - South Carolina                                    582
     9.27   Cities Sorted by Rank - South Carolina                                    583
     9.28   Cities Sorted by Zipcode - South Carolina                                 587
     9.29   Latent Demand by Year - Tennessee                                         591
     9.30   Cities Sorted by Rank - Tennessee                                         592
     9.31   Cities Sorted by Zipcode - Tennessee                                      596
     9.32   Latent Demand by Year - Virginia                                          602
     9.33   Cities Sorted by Rank - Virginia                                          603
     9.34   Cities Sorted by Zipcode - Virginia                                       607
     9.35   Latent Demand by Year - West Virginia                                     613
     9.36   Cities Sorted by Rank - West Virginia                                     614
     9.37   Cities Sorted by Zipcode - West Virginia                                  616
10      SOUTHWEST                                                                     618
     10.1   Executive Summary                                                         618
     10.2   Latent Demand by Year - Arizona                                           619
     10.3   Cities Sorted by Rank - Arizona                                           620
     10.4   Cities Sorted by Zipcode - Arizona                                        623
     10.5   Latent Demand by Year - New Mexico                                        627
     10.6   Cities Sorted by Rank - New Mexico                                        628
     10.7   Cities Sorted by Zipcode - New Mexico                                     630
     10.8   Latent Demand by Year - Oklahoma                                          632
     10.9   Cities Sorted by Rank - Oklahoma                                          633
     10.10 Cities Sorted by Zipcode - Oklahoma                                        636
     10.11 Latent Demand by Year - Texas                                              639
     10.12 Cities Sorted by Rank - Texas                                              640
     10.13 Cities Sorted by Zipcode - Texas                                           656
     11.1   Disclaimers & Safe Harbor                                                 672
     11.2   ICON Group International, Inc. User Agreement Provisions                  673                                   ©2010 ICON Group International, Inc.
 Summary of Findings                                                                                                     9


This study covers the latent demand outlook for Chinese recipe bottled soy sauce across the states and cities of the
United States. Latent demand (in millions of U.S. dollars), or potential industry earnings (P.I.E.) estimates are given
across some 11,700 cities in the United States. For each city in question, the percent share the city is of it’s state and
of the United States is reported. These comparative benchmarks allow the reader to quickly gauge a city vis-à-vis
others. This statistical approach can prove very useful to distribution and/or sales force strategies. Using econometric
models which project fundamental economic dynamics within each state and city, latent demand estimates are
created for Chinese recipe bottled soy sauce. This report does not discuss the specific players in the market serving
the latent demand, nor specific details at the product level. The study also does not consider short-term cyclicalities
that might affect realized sales. The study, therefore, is strategic in nature, taking an aggregate and long-run view,
irrespective of the players or products involved.

This study does not report actual sales data (which are simply unavailable, in a comparable or consistent manner in
virtually all of the cities in the United States). This study gives, however, my estimates for the latent demand, or the
P.I.E., for Chinese recipe bottled soy sauce in the United States. It also shows how the P.I.E. is divided and
concentrated across the cities and regional markets of the United States. For each state, I also show my estimates of
how the P.I.E. grows over time. In order to make these estimates, a multi-stage methodology was employed that is
often taught in courses on strategic planning at graduate schools of business.


The concept of latent demand is rather subtle. The term latent typically refers to something that is dormant, not
observable, or not yet realized. Demand is the notion of an economic quantity that a target population or market
requires under different assumptions of price, quality, and distribution, among other factors. Latent demand,
therefore, is commonly defined by economists as the industry earnings of a market when that market becomes
accessible and attractive to serve by competing firms. It is a measure, therefore, of potential industry earnings (P.I.E.)
or total revenues (not profit) if the United States is served in an efficient manner. It is typically expressed as the total
revenues potentially extracted by firms. The “market” is defined at a given level in the value chain. There can be
latent demand at the retail level, at the wholesale level, the manufacturing level, and the raw materials level (the
P.I.E. of higher levels of the value chain being always smaller than the P.I.E. of levels at lower levels of the same
value chain, assuming all levels maintain minimum profitability).

The latent demand for Chinese recipe bottled soy sauce in the United States is not actual or historic sales. Nor is
latent demand future sales. In fact, latent demand can be either lower or higher than actual sales if a market is
inefficient (i.e., not representative of relatively competitive levels). Inefficiencies arise from a number of factors,
including the lack of international openness, cultural barriers to consumption, regulations, and cartel-like behavior on
the part of firms. In general, however, latent demand is typically larger than actual sales in a market.

For reasons discussed later, this report does not consider the notion of “unit quantities”, only total latent revenues
(i.e., a calculation of price times quantity is never made, though one is implied). The units used in this report are U.S.
dollars not adjusted for inflation (i.e., the figures incorporate inflationary trends). If inflation rates vary in a
substantial way compared to recent experience, actually sales can also exceed latent demand (not adjusted for
inflation). On the other hand, latent demand can be typically higher than actual sales as there are often distribution
inefficiencies that reduce actual sales below the level of latent demand.

As mentioned in the introduction, this study is strategic in nature, taking an aggregate and long-run view, irrespective
of the players or products involved. In fact, all the current products or services on the market can cease to exist in
their present form (i.e., at a brand-, R&D specification, or corporate-image level) and all the players can be replaced                                                         ©2010 ICON Group International, Inc.
    Summary of Findings                                                                                               10

by other firms (i.e., via exits, entries, mergers, bankruptcies, etc.), and there will still be latent demand for Chinese
recipe bottled soy sauce at the aggregate level. Product and service offerings, and the actual identity of the players
involved, while important for certain issues, are relatively unimportant for estimates of latent demand.


In order to estimate the latent demand for Chinese recipe bottled soy sauce across the states and cites of the United
States, I used a multi-stage approach. Before applying the approach, one needs a basic theory from which such
estimates are created. In this case, I heavily rely on the use of certain basic economic assumptions. In particular, there
is an assumption governing the shape and type of aggregate latent demand functions. Latent demand functions relate
the income of a state, city, household, or individual to realized consumption. Latent demand (often realized as
consumption when an industry is efficient), at any level of the value chain, takes place if an equilibrium is realized.
For firms to serve a market, they must perceive a latent demand and be able to serve that demand at a minimal return.
The single most important variable determining consumption, assuming latent demand exists, is income (or other
financial resources at higher levels of the value chain). Other factors that can pivot or shape demand curves include
external or exogenous shocks (i.e., business cycles), and or changes in utility for the product in question.

Ignoring, for the moment, exogenous shocks and variations in utility across geographies, the aggregate relation
between income and consumption has been a central theme in economics. The figure below concisely summarizes
one aspect of problem. In the 1930s, John Meynard Keynes conj
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