2013-28
Product lifecycle and choice of transportation modes:
Japan’s evidence of import and export
Hideki Murakami Yukari Matsuse
KojiMukaizawa Yushi Tsunoda

Product lifecycle and choice of transportation modes: Japan’s
evidence of import and export
Hideki MURAKAMI* ,Yukari MATSUSE,
Koji MUKAIGAWA and Yushi TSUNODA
Abstract
Here we test the hypothesis that commodities at their peak valuation aretransported by air and those at their birth and maturity are shipped by sea, and thatshippers would choose air for transporting high-valued commodities. We empiricallyinvestigated how the product lifecycle of commodities is reflected by shippers’ choices of
air transportation rather than seaborne transportation. We also assumed that thecommodities that achieved substantial innovation in their lifecycles would be moved by
air transportation so that these commodities could reach the targeted markets asquickly as possible to avoid the opportunity costs that might be generated by missed
business chances. We constructed two unbalanced panel data of 18 commodities (thecase of import) and 14 commodities (the case of export) for 24 years from Japan’s custom,demographic, and international statistics. By estimating structural equation systems
that consisted of commodity-specific import/export and import/export air ratio functions,
we found that the product lifecycle of cargo outgoing from Japan exactly matched the
upward and downward move of the air ratio, whereas since incoming commodities are
raw materials that have little to do with product lifecycle or matured phase in theirlifecycle stage, the peak of commodities’ valuations and the use of air transportation
were not necessarily synchronized.

Key words: product lifecycle, modal choice, structural equations
1. Introduction
Japan has experienced several economic phases over the past 20 years, including
the “bubble” economy (around the year 1990), followed by a long-term recession thatwas described as a “lost twenty years” including a “deflation-spiral,” the “inflation of
crude oil (early in 2008)” and the “Lehman shock in 2008” during which many
companies that had led industries in Japan went bankrupt or re-organized. During this“lost twenty years,” stock prices fell and the Japanese yen became stronger with time.

* The corresponding author, Professor of Transportation Economics, Graduate School ofBusiness, Kobe University, Japan. Email: hidekim@panda.kobe-u.ac.jp

These trends were followed by an increase in Japanese companies’ foreign investments
in Asian countries such as China, Thailand, Indonesia, and Vietnam, and by the
re-location of some companies’ headquarters and/or factories in foreign countries.
During the same period, Japan’s economy became dependent on imports rather thanexports, and its international trading balance became negative due to the increase inimports, especially from East Asian countries.
In accord with these shifts of Japanese economic activities from domestic tointernational markets, manufacturers and their relevant companies had to constructinternational logistics systems which have played important roles in their supply chain
management: some companies have relegated the operation of their international
logistics or supply chain management (SCM) to third-party logistics providers, whileother companies have internalized these operations. For example, Toyota Motor Corp.
manufactures and assembles car parts that are commonly used over its product lineup
such as wire harnesses, brake pedals, and antennas, in Vietnam. The in-process goods
are then imported into Japan to finalize the cars’ assemblies.1 It is commonly known
that some manufacturers relegate these logistics activities to the logistics-service
providers (LSPs) that originate in shipping companies, freight forwarders, and airlines.
Air freighters such as FedEx and UPS have constructed high-quality SCM systems
called integrators, but not many manufacturers that produce middle-or lower-quality
goods use integrators; instead, in light of the valuations of their cargo, they use LSPs.
In any case, regardless of whether a manufacturer chooses an LSP or an
integrator, the manufacturer must decide which transportation mode to use fortrans-ocean and/or trans-continental exports or imports, by negotiating with LSPs.
Focusing on Japan’s case, the transportation modes for international export/import arelimited to air and seaborne transportation, since Japan has no land-based link to thecontinents.
The shippers must bear higher expenditures when they need to have products
shipped quickly, since short-time delivery needs the speed afforded by airtransportation, which generally costs more than sea shipping. According to traditional
international trade theories such as the Heckscher–Ohlin model, a commodity withcomparative cost competitiveness is exported to a foreign country. In such a case, it isnatural to expect that this commodity will be exported by sea in order to take advantage
of comparatively low tariff rates. However, it is possible for the generalized cost of
seaborne transportation to exceed that of air transportation due to the opportunity costsof missing business chances, high interest rates, and high insurance costs that1

The author’s interview at Toyota Motor Vietnam, Hanoi, Vietnam in July 2008.

accompany long voyages. Shippers may thus choose air transportation when thegeneralized cost of air transportation is cheaper than that of seaborne transportation. If
we think of shippers’ choices of air or seaborne transportation based on the idea ofgeneralized costs mentioned above, the valuation of a commodity is not the absolutedeterminant of air or seaborne transportation.
In this paper we reduce the idea of a product lifecycle to the overtime changes inthe valuations of commodities, and we then analyze whether the product lifecycles
match the changes in air ratios for the cases of import and export. The methodologically
outstanding features of our analyses are having bridged the following three ideas: theidea of ordinary export/import functions, the air ratio that is much concerned withconditional factors demanded of air transportation, and the idea of the product lifecycle.
We regressed the air-ratio variable on cargo-valuation dummy variables as well as othervariables common for supply and factor demand scenarios.
The cargo valuation variables are a series of dummy variables, and “peak year
dummy” takes the value 1 when a certain type of commodity is at its peak valuation,and the “one-year post-peak dummy” takes the value 1 for the next year of the peak year.
The series of peak year dummies consists of five types: two years before, one year before,
the peak, one year after, and two year after the peak. By estimating and testing the
hypothesis of the coefficients of these dummies, we can approximate how long eachstage of the product lifecycle lasts for exports and imports in Japan’s case. In thefollowing section we review previous studies of the pricing (i.e., freight rate) theory ofcargoes and product lifecycle management. In Sections 3 and 4 we demonstrate our
empirical model and the dataset, respectively, and in Section 5 we carry out theeconometric analysis based on the models and data in Section 3. We also evaluate theempirical results, and in Section 6 we summarize the contributions and limitations of
our study.
2. Literature review of cargo pricing theory and product lifecycle management
The pricing rule for air and seaborne cargoes is explained by traditional
microeconomics theory. Benathan and Walters (1969) showed that the price elasticity ofcargo demand could be derived by multiplying the “price elasticity of a commodity in a
destination market” by the “freight rate that traffic can bear.” The freight rate that
traffic can bear is the generalized cost of transportation divided by the valuation of the
cargo. That study implied that the prices of cargoes are determined by theprice-discrimination rule and the handling costs of commodities.
Klepper (1996) developed a model that explained the industry’s evolution from its

birth to maturity and theoretically showed the mechanism underlying how the productlifecycle takes place and is terminated. He pointed out that the size of the firms play animportant role in the next innovation; e.g., a large firm that had sufficient budget would
supply products with lifecycles. Miyashita (2009) stated, based on the results of his several
empirical studies, that shippers chose seaborne logistics only, or both seaborne and air in acomplementary manner, or air only. He bridged these modal choice behaviors with the
product lifecycle theory.

Before Miyashita (2009), Miyashita (1988) in an early study assumed that thenominal price indices include the time trend while actual price indices convey a cyclicalmovement of prices. He also assumed that while the small amount of high valuation andtime-sensitive goods was transported by air, the large amount of low-valuation goods
are more commonly moved by a seaborne service. In this sense, Miyashita (1988)
assumed that each commodity or bundle of commodities followed a different lifecycle
track. Figure 1 illustrates that cargo valuations change cyclically for certain cases(except for medicines) that show an exponential trend only (dotted line). We thus
partially accept and partially do not Miyashita’s contentions as we survey thetime-series dimension of our dataset. In this paper, we will assume Klepper’s idea thatthe commodities of large industries follow the product lifecycles. We then highlight thecharacters of lifecycles of specific commodities, and we test the hypothesis that thecommodities at their peak valuation are transported by air and those at their birth andmaturity are shipped by sea.
Fig. 1. Time series changes in commodities’ valuations (import case).
3
2
Pharmacy1Motor/Engine

0-1

88 90 92 94 96 98 00 02 04 06 08 10

Automobile
Aircraft-2-3
The vertical axis shows the standardized (mean=0) valuations. The horizontal axis
shows the fiscal years.

In addition, although Miyashita (1988) stated that the air ratio itself has acharacteristic of a cyclical change in a particular level between 0 and 1, Figure 2 showsthat the air ratio (see Section 3) also has both cyclical and time-trend characteristics(especially medicine with positive trend and motor with negative trend).
Fig. 2. Changes in the air ratio with/without trend (import case).
0.95
0.85

Pharmacy

0.75

Motor/Engine
Aircraft

0.65
0.55
88 90 92 94 96 98 00 02 04 06 08 10

The virtual axis shows the standardized valuations. The horizontal axis shows the
fiscal years.

In summary, we have four categories concerning the relationship between
commodity valuations and the air ratio (Table 1).
Table 1. Classification of commodity samples with/without trend or cycle
Trend

Cycle

No cycle

Pharmacy (air ratio),

Pharmacy (valuation)

Engines (valuation, air ratio)
No Trend

Aircraft (air ratio, valuation)
Automobile (valuation)

Commodities indifferent of peaks/off-peaks such as gold precious stones are omitted from the present
analysis. The words in parentheses at the top-left partition indicate the air ratio of pharmacy changes
with cycles and trends. Engines’ air ratio and valuation also change with cycles and trends.

Regarding the commodities in Table 1, we can imply that air and seaborne service
are substitutes for commodities with cycles and no trend, and complement forcommodities with both cycles and trend. In this case, the up-slope trend is caused bytechnical progress and/or increases in individual income or the GDP. Considering thesefacts regarding commodities’ characteristics, we will have to incorporate the idea ofcommodity-specific analyses into our empirical models such as commodity-fixed effects.
Vernon (1966)’s product lifecycle theory followed by Vernon (1979 consists of threestages: new product, maturing product, standardized product. Miyashita (1994) added

one more stage to this theory: rationalized product. He empirically studied the systems
of inter-regional cargo flows by associating the idea of product differentiation with the
air ratio. However, the relationships between the peak of the air ratio and the productlifecycle were not analyzed. Here we try to analyze how and to what extent the productlifecycle will be reflected by the air ratio for commodities. We do not perform an
origin/destination-specific analysis, in order to maintain a sufficient number of samples
in a sense of statistics.
3. The model
In this section, we first construct the export/import air ratio functions together
with traditional export/import functions.

The definition of the air ratio () is asfollows:,
where ACVand SCV,(1)

are the commodity valuations that are exported/imported by airor sea. The determinants of this air ratio can be approximated by deriving theconditional factor demand, because both air and seaborne services are input demands ofshippers. Assuming that competitive Japanese shippers (here, importers) minimize
their costs subject to a certain fixed amount of cargo, the conditional factor demands canbe obtained by taking the first order condition of Lagrange function (Eq. (2)) in terms of
inputs ( ′ ) and a Lagrange multiplier, and a second-order condition such that the

Hessian matrix composed of the second-order differentiated terms is positive definite.
min

,⋯,

The conditional factor demands for(2)

can be written in the generalized form:,

where Q is the cargo traffic, and

∗

∑

,

and

,

∑

(3)

are the input prices. The plus and minus

in the parentheses are expected signs assuming that an input is a substitute for theothers. In our study,

andservices, that is, ACV

and SCV , and the determinants of the air ratio will be Q,

andare assumed to be the valuations of air and seaborne. In the case of exports, the air ratio function is similar to that of imports; it is aconditional factor demand function from the viewpoint of other countries. Next, we will
specify the sign ofin the air ratio function. Again,=(1)’

and if we assume that the production technology follows the Cobb-Douglas form, such
as:

∗

(4)

From the first-order condition of Lagrange function (Eq. (2)), we obtain:
and

(5)

The conditional factor demands that we obtain by the first-order condition of Eqs. (2)and (4) are as follows:
and

(6)

Substituting Eqs. (5) and (6) into Eq. (1)’, we obtain:

(7)

/

where

is the ratio of air/sea cargo valuations/

Taking the derivative of Eq. (7) with respect to

,

⁄

.

, we obtain:

>0

1

(8)

Therefore, the sign of air valuation variable is positive in the air-ratio function.
Our import and export functions are constructed by following ordinary
microeconomic theory. The import function can be derived by assuming that Japan
maximizes its utility subject to the budget constraint in each year. The explanatory
variables are imported commodities’ prices, domestic prices, income (the nation’s buying
power), and the exchange rate as a control variable. The import function of general form
goes as follows:,
whereis the imported cargo of commodity i in year t,

year t deflated by the retail price index,
the U.S. Dollar in year t,
retail price index, andis Japan’s GDP inis the Japanese yen in year t,

isis the price of domestic goods in year t deflated by theis that of foreign goods in year t. “k” denotes either importor export, and here “k” means import. As for. As for(9),, we used the import price index for, we prepared Japan’s retail price index and Nikkei stock price index,

and used the one better fitted from the statistical viewpoint.
In Eq. (9), the sign ofcannot be specified if we take the logarithm, since one

is in the denominator and the other is in the numerator. Therefore, this is the empiricalissue.
The typical export function can be derived just by replacing Japan’s “J” with world’s“W”, and here “k” means the export.
,
In Eq.(10),

(10)

,

is the “system-wide” GDP in the world exempting Japan in year t.

Japan used to export goods mainly to the U.S. and Europe, and has more recently been
exporting to China and South-East Asian countries (Fig. 3).
Fig. 3. Changes in total valuations of commodities exported from Japan
18
16
14
12
10
8
6
4
2
0

China
EW AsiaEU
US

The vertical axis indicates U.S. dollars (billion) and the horizontal axis is fiscal
years. Source: Ministry of the Treasury, Japan.

The GDPs of Japan’s “long-run” trading partners have moved almost the same ways,
but China has shown a different growth rate curve (Fig. 4).

The correlations among

these countries or regions’ GDP grows rates are shown in Table 2.
Fig. 4. GDP growth rates of each country/region
14
9
4
-1

OED
EAS
JPN
USA
CHN

-6
OED, OECD countries; EAS, Eastern Asia; JPN, Japan; USA, the United States;
CHIN, China. Source: World Bank.

Table 2. Correlation coefficients among countries/regions’ GDP growth rates

OED

EAS

JPN

USA

CHN

OED

1.000

EAS

0.648**

1.000

JPN

0.783**

0.902**

1.000

USA

0.88１**

0.293

0.446*

1.000

CHN-0.0680.068-0.159

0.060

1.000

**: significant at 1% level, *: at 5% level. Abbreviations are explained in Fig.
4.

With this replacement, Eq. (10) will be Japan’s supply function to the world.
The modified version of Eq. (10) is as follows:
,

(11)

,

be a numeraire. Eq. (6) will be rewritten as follows:

and again let,
Unlike Eq. (9), the sign of

(12)

,

will be specified as being negative if we take thelogarithm.
When Japan’s shippers think of trading goods with foreign countries, they haveto consider which transportation mode they choose, air or seaborne. Following thissimultaneous decision-making by shippers, we construct system-equation models thatgo as follows:(1) System of import function
ln(

)=
∑

(13)

∑

+

ln

+

∑

(14)

(2) System of export function
ln(
ln

)=α

α

α

α
+

α
∑

∑

+ε

(15)

∑
where

μ

is the dummy variable that denotes the product lifecycles.

when the valuation of commodities was at its peak,the valuation of commodities was peak,
five

(16)
takes 1

takes 1 for one-year before

takes 1 for one-year after, etc. We havevariables, and subscript τ starts with −2 and ends with 2.

is thecommodity-specific fixed effect dummy variable, and “m” denotes the type of commodity
such as pharmaceuticals, semi-conductors, etc.
4. The data
We collected the data from Japan’s custom classification statistics maintained by
the Ministry of the Treasury. Retail price indices, standardized by the average ofsamples, were obtained from World Economic Outlook Databases (IMF). The dataset ofexports is the unbalanced panel data of 14 commodities for a 24-year period. The
number of sample observations should thus be 336, but the data of chemical powder forthe years 1988–89, 1992–93 and 2011 and those of nonferrous junk materials for 1988,
1994, and 1995–96 are unavailable, so the number of whole sample observations is 327.
The commodities used here were the ones classified by five-digit category in the custom
classification. The dataset of imports is also the unbalanced panel data of 18
commodities for 24 years. The total sample observation should be 432, but the 1998 dataof the pulp and paper industry are missing. The number of sample observation is thus
431. Table 3 is the descriptive statistics of continuous variables.
Table 3. Descriptive statistics of continuous variables
Variables

Average

S.D.

Minimum

Maximum

MedianImport air ratio

0.374

0.299

0.008

0.991

0.301

Export air ratio

0.377

0.348

0.007

0.999

0.226

Import cargo volume (000t)

59191.1

152700.5

3.1834928.8

1173.4

Export cargo volume (000t)

51623.6

121044.3

0.1651568.2

535.1

Import reference price (air/sea, Yen)

118.5

450.7

0.8

5641

9.6

Export reference price (air/sea, Yen)

364.2

1833.00.001

19431.8

15.0

Net GDP (Billion yen)
Nikkei price index (Yen)
Exchange rate (Yen against USD)
Total population (000)

47

3.6

38.2

52.4

47.5

16937.1

6545.29426.734579.8

16394.3

114.2

15.7

79.8

144.8

113.9

126280.1

1628

122745128057126926

Import price index (Yen)

96.5

14

79.6

133

93.8

Export price index (Yen)

101.4

23.5

37

137.5

103.7

S.D.: standard deviation.

5. Empirical results

Firstly we estimated simultaneous equations (13) and (14) by generalized
two-stage least squares (G2SLS) detecting that there exists heteroscedasticity.2 The
result is shown in Table 4.
Table 4. Estimated results for cargo import and air ratio functions

Log ofDummy
variablesofCargo import function
Variables
CoefficientsJapan's GDP
2.028
Yen/USD−0.057
Import Price Index (nominal)−0.236
Nikkei stock prices
0.315
Fat of animal origin−1.937
Pharmacy
3.590
Essential/cosmetic oils
−1.776
Chemical powder−4.695
Leather/Leather goods
2.645
Strings for clothes
5.412
Cotton clothes
6.073
Wool clothes
2.862
Silk clothes
2.524
Synthetic fibers
3.521
Precious/semi-precious stones−0.258Motors/engines−2.509Pulp/paper products−5.258
Cars/car parts−4.157
Airplane/airplane parts−5.729Ship/ship parts−2.092
Constant−4.608t-ratio
4.095−0.426−1.3414.257−35.983
46.376−14.816−165.680
41.701152.430
86.14768.21232.30799.555−5.207−19.145−69.281−60.806−139.700−17.938−1.901t-test***6.683−13.185
5.626
0.475
0.937
0.679
−1.894−2.528−9.93316.007

***
***
***

***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
*

Import air ratio function
Log ofDummy
variablesofCargo valuation ratio (air/sea)
Import cargo volume
Japan's GDP
Two year before the peak
One year before the peak
Peak year of commodity's valuation
One year after the peakTwo years after the peakFat of animal origin
Pharmacy

0.217−0.436
1.369
0.042
0.072
0.045
−0.120−0.179−0.770
3.985

*
**
***
***

We carried out the heteroscedasticity test for both export and import cases. The
Breusch and Pagan chi-square value of import function, export function, import air
ratio function and export air ratio function are 191.90(22),145.37(16),427.39 (22), and159.20(16), respectively. The degrees of freedom are in parentheses, and all the null
hypotheses of homoscedasticity were rejected at 1% level.
2

Essential/cosmetic oils
Powder
Leather/Leather goods
Strings for clothes
Cotton clothes
Wool clothes
Silk clothes
Synthetic fibers
Precious/semi-precious stones
Nonferrous metals
Motors/engines
Automobiles /car parts
Ship/ship parts
Post Lehman Brothers shock
Constant

0.796−1.267
3.197
1.790
3.535
3.763
3.230
2.347
1.965
1.160
1.033
−0.471−1.138−0.169−6.4047.157−10.871
12.751
5.175
10.14912.224
11.6228.364
27.29514.04314.953−3.965−6.341−3.840−6.689

***
***
***
***
***
***
***
***
***
***
***
***
***
***
***

G2SLS estimation, R-Square of import function=0.991, R-Square of import air ratio function=0.920, n=431.
The benchmark of the fixed effect dummy variable is meat. t-test results:*** is significant at 1%, ** at 5%,
and * at 10% level.

The import function shows the correct sign, although the exchange rate and theexport price index are not significant. The air ratio function also shows comprehensive
results. It tells that in the case of imports, Japanese industries tend to use seaborne
transport. The parameter of cargo-valuation ratio shows a positive sign as is fixed in Eq.
(8). We have five dummy variables of commodity valuation, and the first three are notstatistically significant. This result means that high valued commodities are notnecessarily transported by air in the case of imports. In addition, the fourth and thefifth dummy variables (that is, one year after the peak and two years after the peak)indicate that as the commodities become matured or standardized, they are transported
by sea.
Our next interest is in the case of exports. Table 5 indicates the estimated resultsof cargo export function and export air ratio function.
Table 5. Estimated results of export and air ratio functions
Cargo export function
Variables
Log ofDummy
variablesof

Coeff.

t-ratiot-testExport price index (deflated by average of RPI)

−1.558−5.040***Japanese yen/USD

0.504

2.523

**

Japan’s GDP

2.405

4.422

***

Raw fish

4.346

19.868

***

Meat

5.680

16.896***

Pharmacy

10.09129.897

Chemical Powder−0.420−1.291

Strings for clothes

4.781

13.903***

Pearl

10.69632.361***

Nonferrous metals

6.272

18.644***Motors/Engines

6.272

18.644***

Pulp/Paper products

2.422

7.081

***

Audio Apparatus

10.22830.035***

Loud speakers, microphone

12.35334.184***Semi-conductors

11.66933.593

***

Gold

3.970

11.343***−15.456−3.521***

Export cargo volume

0.918

7.370

***

Cargo valuation ratio (air/sea)

0.109

4.332

***

Two years before the peak

0.141

0.830

One year before the peak

0.255

2.209

**

Peak year of commodity's valuation

0.350

2.442

**

One year after the peak

0.242

2.528

**

Two years after the peak

0.959

0.723

Raw fish−4.129−7.672***Meat−5.724−9.566***

Pharmacy−6.904−6.019***Strings for clothes−4.411−8.425***

Pearl−7.239−5.998***Nonferrous metals−4.787−7.031***

Motors/engines−4.787−7.031***

Pulp/paper products−1.996−7.991***

Audio Apparatus−7.248−5.948***

Loud speakers, microphone−9.673−6.372***Semi-conductors−7.910−5.556***Gold−0.760−1.732*

Constant***

Export air ratio function
Log ofDummy
variablesofConstant***−9.161−8.978G2StLS estimation, R-Square of export function =0.985, R-Square of export air ratio function =0.739,
n=327. The benchmark of fixed effect dummy variable is junk/scrap of metallic/mineral. T-test
results:*** is significant at 1%, ** at 5%, and * at 10% level.

The positive sign of Japanese yen/US dollar means that as the Japanese yen is
weaker against the US dollar, the export increases. Contrary to the case of imports,
Japanese shippers tend to export by air. Also contrary to the parameters of the dummy
variables of imported cargo valuations, the shippers choose air transportation one year
before the peak of their cargo values, the peak year, and followed by one year after the
peak. Therefore, commodities at their peak or adjacent to peak valuations in theirproduct lifecycle tend to be transported by air.
Figure 5 shows the changes in the coefficients of valuation dummy variables forboth import and export cases. It is apparent that the lifecycle of export cargoes changes
on a single-year basis, and it appears that the lifecycle of export cargo from the births ofcommodities to the maturities continues beyond five years. The import cargoes (dottedline) have relatively short lifecycles, and even in the time of highest validation, they are
not always transported by air. If we regard these import cargoes as matured and/or
standardized commodities, it is natural to think that they already experienced or did
not have a high-valuation phase. The more these commodities lost their value, the morethey were transported by sea. In addition, it is inferred from the idea of product lifecyclethat these matured commodities may not be traded since they may not stand even theprice of the seaborne mode’s low fares, and then their production is ceased.
Fig. 5. Lifecycle of cargo valuation and choice of air/seaborne transportation.
0.3
0.2
Export0.1

Import0-0.1

2 years
before1year
beforePeak year
in value

1 yearafter

2 yearsafter-0.2
The vertical axis shows the coefficients of the series of cargo valuation variables.

6. Conclusion

The empirical contribution of this paper is that we demonstrated that the morecargoes were imported to Japan, the less they were transported by air, whereas the
opposite result was obtained in the case of exports. In addition, the outstanding featureof this paper is that we showed the relationship between the idea of product lifecycle
and air ratios. We approximated the idea of product lifecycle to the overtime-increase
and decrease in cargoes’ valuations. We found that the product lifecycle of cargo
outgoing from Japan exactly matched the upward and downward move of the air ratio(the bold line in Fig. 5). On the other hand, the product lifecycle of incoming cargos were
not in line with the changes in air ratio. As we mentioned above, since incoming cargos
have been transported by sea, we can regard them as matured and/or standardizedcommodities, as we can see in Table 4. If so, these commodities have no peak valuation.
Therefore, their product lifecycle changes were not synchronized with the changes in air
ratio, and the more matured these commodities were, the more they are transported bysea (dotted line in Fig. 5).
From the national economic perspective, it is implied that the high-techindustries would choose air transportation; these industries are better located adjacent
to international (cargo) hub-airports. In addition, since shippers choose air or seaborne
service depending on the phase of the product lifecycle of their commodities, it would bebetter for airports and seaports to collaborate in order to facilitate shippers’ choices andminimize shippers’ transaction costs when they export or import.
Our analysis might be useful for the cases of other island countries such as
Australia, New Zealand, Taiwan, the Philippines, etc.

Of course, our study has thefollowing limitation: we did not perform an origin/destination-specific analysis.
Although the sample number will decrease if we do so, the estimated results maychange between countries and economy blocks. Therefore, our results might beunderstood as “on average” analyses between Japan and other countries. We willcontinue our study to address this limitation.
References

Breusch, T.S. and A.R. Pagan (1979). "Simple test for heteroscedasticity and randomcoefficient variation". Econometrica Vo.47, No.5, pp.1287–1294.
Klepper, S. (1996), “Entry, Exit, Growth, and Innovation over the Product Life Cycle”,

American Economic Review, Vol.86, No.3, pp.562-583.
Miyashita, K., (1988), Kaiun (Maritime Transport), Koyo Publishing.

Miyashita, K., (1994), Nihon no Kokusai Butsuryu System (Japan’s international

logistics system), Chikura Publishing (in Japanese).
Miyashita, K.(2009), “Structural Change in the International Advanced Logistics”,

Asian Journal of Shipping and Logistics, Vol.25, No.1, pp.121-138.
Vernon, R. (1966), ‘‘International Investment and International Trade in the ProductCycle’’, Quarterly Journal of Economics, Vol. 80.
Vernon, R. (1979), ‘‘The Product Cycle Hypothesis in a New International Environment’’,

Oxford Bulletin of Economics and Statistics, Vol. 41.
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