Online ISSN 1347-4456 Print ISSN 1347-4464

ABAS: Annals ofBusiness Administrative
ScienceVol. 2, No. 1, January 2003

KONNO, Yoshinori

1

MIYAZAKI, Masaya

11

Suppliers' Performance and Parts Transactions with Customers

Inferring Competitors' Intention:
Using Content Analysis and Product Concept Trajectory

http://www.gbrc.jp© 2003 Global Business Research CenterAnnals of Business Administrative ScienceVol. 2, No. 1, January 2003

CHIEF EDITOR

Junjiro Shintaku

University of TokyoEDITORIAL BOARD

Makoto Abe
University of Tokyo
Takahiro Fujimoto University of Tokyo
Makoto Kasuya
University of Tokyo
Hotaka Katahira
University of Tokyo
Nobuo Takahashi University of Tokyo
Technical Editor: Maki Nishida, Global Business Research Center

Annals of Business Administrative Science is published quarterly in January, April,
July, and October, by Global Business Research Center, Marunouchi, Chiyoda-ku, Tokyo,
JAPAN. http://www.gbrc.jp

Annals of Business Administrative Science Vol.2, No.1 (January 2003)

Suppliers’ Performance andParts Transactions with Customers
Yoshinori KONNO
Graduate School of Economics, University of Tokyo
E-mail: konno@e.u-tokyo.ac.jp

Abstract: This paper investigates the relationship between suppliers’ performanceand their parts transactions with customers in Japanese automobile industry. We
generate a hypothesis focusing on supplier’s learning processes, and test it using
Japanese auto parts transactions data set during the period 1993-99. Results showthat suppliers who prove important to the main customer at the same time
maintaining business relationship with numbers of other customers, tend to surpass
other suppliers in their performance. In other words, we find how important it is for
suppliers to build stable business tie with the main customer and broaden
relationship with other various customers.
Keyword: Japanese automobile industry, parts transaction, supplier’s learning
process

1. Introduction

company at the same time maintaining businessThis paper aims to generate a hypothesis concerning

relationship with numbers of other customers tend to

the relationship between suppliers’ performance andsurpass other suppliers in their performance. We will

their parts transactions with customers in Japanesealso discuss its implication.

automobile industry, and test, though restrictively,

It has been said that Japanese automakers arethis hypothesis. Precisely, this paper will clarify that

inclined to have long-term stable parts transactions

suppliers who prove important to main customer car

relationship with restricted number of parts suppliers,

1

Konno“Keiretsu

a major role in the suppliers’ learning process. In fact,corporations” with very close relations of capital andit is commonly observed to have automakers

personnel. However, Japanese automobile industry

supervise suppliers on product management andof today has been struck by an unprecedented tide ofquality control. On the other hand, it is often seen

structural reform reflecting slowdown in automobile

among suppliers to receive technical experts fromdemand and sharp rise of yen. Suppliers are shifting

brotherly automakers or send their own men tofrom a structure depending on a specific automakercustomer automakers for training. Moreover, it isfor most of transactions and sales but trying to open

ever crucial for suppliers to gain information,

new business with other automakers. Nonetheless,directly and indirectly, through daily transactions,

recent new car development lead-time has become

about technical trend, rivals’ doings, and up-to-dateever shorter, while components technology isneeds of automakers and consumers. Alternatively,

innovating rapidly. Suppliers are needed to build

recently, Japanese top manufacturers are growing instrong cooperative relationship with automakers thantendency to involve main suppliers in the earliest

ever. In fact, not few suppliers station engineers instage of new technology development projects. Thus,

technical centers of closely related automakers toengaging in such co-development projects isestablish

essential for suppliers to access and accumulate

which

have

in

been

depth

described

informationassharingandvaluable technological know-how.

coordination of activities from an early stage of

Most important in learning from customers istechnological development.
From an economic point of view, it does seemthe relationship with the main customer, in this casecontradictory that suppliers are “broadening theautomaker. Virtually, suppliers’ contacts are most

scope

time,

frequent with main customers, and main customers’

specific

job priorities are higher. It is not uncommon that

automakers.” However, when we take particular note

product development projects aimed at mainon the suppliers’ learning process, both efforts arecustomers play a major role in building up new core

consistentpracticed

product or production system. Hence, learning fromsimultaneously. Hereafter, we will generate amain customers have much larger influence on the

hypothesis and conduct limited test of it.

supplier’s organizations than learning from otherofcustomers,”“strengthening

and

at

businessdesirable

the

ties

to

same
with

be

customers.

2. Generating Hypothesis

However, even when automaker B is the main

2.1. Regarded Important from Main Customer

customer for supplier A, this does not simply allow

Definitely, information, which is passed on fromsupplier A to draw significantly valuable information

automakers who are customers to their supplier, playfrom automaker B. Among Japanese manufacturers,2

Suppliers’ Performanceeach auto part is usually procured from more than

2.2. Customer Scope

one supplier. Automakers procure same parts from

Another thing that is import in suppliers’ learning

multiple suppliers, and in doing thus they refer to aprocess is to broaden the scope of customers. First,

list in which suppliers are minutely rated bybecause dealing with many numbers of automakers

competence and background. As for automakers,

would allow suppliers access to many different kinds

especially in co-development projects where highlyof information, compared to suppliers who limit theconfidential information needs to be shared,

number of customers. Additionally, developing andtendency is stronger to partner-up with suppliers

producingwhose main customers are themselves. This isautomakers will engage more numbers of test run

because suppliers whose main customer is anotherand improvement activities during product design

automaker might have the potential to lay priority on

and production design procedure, thus quite possibly

the other company and, may it not be intentional,

increase learning effect and experience effect of theleek confidential information to rival companies. In

supplier.

virtually

Second,fact, in our interviews, automakers would tie up withsame

experiencing

parts

for

numerous

different

customer

their main supplier whose main customers are

dealings would increase the ability of knowledge

themselves as well in co-development projects oftransfer

new technology. Therefore, as long as supplier A is

exceptions, it is not easy to develop, produce andnot treated as important supplier from company B, A

deliver auto parts to different automakers without

will hardly gain valuable information from B:

modification, even with same parts. Therefore, inAdvantages gained through learning from mainorder to transfer knowledge gained through dealings

customer will be reserved.

from one customer to another, it is critical to adapt

in

suppliers.

Generally,

with

some

On the contrary, when tight relationshipthe knowledge into different contexts. Such process

between makers and suppliers are maintained, ininvolves much questioning and learning-by-doing of

which both companies regard each other as main

“what can be used from knowledge already gained

partner, trust grows and opportunistic breach of

and what ought to be changed,” and more

information become unlikely: Information of higher

transactions

confidentiality can be exchanged. Thus, suppliers

opportunity in this matter.

offer

suppliers

more

learning

regarded important from main customers takeThird, we must consider learning bias. Whenadvantage of learning process compared with

suppliers are depending too much on transactions

suppliers that are not.

with specific automakers, suppliers are apt tooverestimate
because
3

the

their

own

opportunity

competence,
to

gain

naturally
objective

Konnoinformation needed to comprehend their competence

2.3. Mutually Complementing Relationship between

is scarce.

“Regarded Important from Main Customer” andMoreover, among various activities going on in“Customer Scope”

a firm, most are repeated and form patterns. ThroughWe further expect that, from discussions in Sections

continuous repetition, activities which proved to be

2.1

successful are selected and accumulated within thecustomers’ eyes and scope of customers are mutuallyfirm as “organizational routine”; such being standard

complementing: meeting either one alone would beprocedures,ofinsufficient. In other words, suppliers are able tocommunication, various know-how, and so on.

merit through learning process only when both

Generally speaking, in auto parts transactions,priorities are high in main customer’s eyes, andsuppliers repeat problem-solving in effort to meetbusinessthe demands of customer automakers, to accumulate

maintained.

computerprograms,

patternand 2.2,

suppliers’ importance inrelation

with

many

customers

main

are

successful cases and form routine. Routine allows

We consider that enhanced learning processes

higher efficiency of operation, however, if the

improve suppliers’ ability. Thus, from above

suppliers’ learning opportunities are reserved to few

discussion, we can derive a hypothesis: Suppliers

customer dealings, it would bias learning process.

who remain highly important to main customer

This is because the supplier might put too muchautomaker at the same time maintaining businessstrength on learning the knowledge and experience

relationship with numbers of other customers, tend

useful in dealing with the main customer alone andto surpass other suppliers in their performance.

neglect other learning. Likewise, learning bias mightoccur in “basic corporate behavior principles.”

3. Data Analysis

Suppliers who restrict business to specific limited

3.1. Sample and Data

numbers of customers in a long term may possiblyThis paper will test the hypothesis presented in

narrow down and get stuck to one idea of what they

Section 2, though quite restrictively, on Japaneseregard as business opportunity.

auto parts transactions during the period 1993-99,

Thus, we believe that suppliers’ learning

utilizing logistic regression analysis method.

process is improved through business relations with

We here treat parts transaction as the unit ofvariety of automakers.

analysis. That is, we analyze each delivery of parts
from supplier to automaker as individual transaction.
We referred to IRC Co., Shuyo Jidosha Buhin 200
Hinmoku no Seisan Ryutsu Chosa of 1993 and 1999
to attain data. Nine Japanese car companies are4

Suppliers’ Performancecovered: Toyota, Nissan, Honda, Mitsubishi, Mazda,

Indeed, “continuity of parts transactions” is not

Suzuki, Daihatsu, Fuji Heavy Industries, and Isuzu.

a straightforward performance index, however, we

We dropped from sample any kind of auto parts not

adopt this as passive performance index believing

outsourced, partially or totally. This is because wethatcannot compare indexes correctly between parts

suggests “performance was not poor” at least.

“maintained

existing

parts

transactions”

which is totally outsourced and those that are not.

On the other hand, first, we adopt as

Besides, other types of parts were excluded; forindependent variable Regarded Important from Main

example, partial data flaw, not procured by every

Customer (RIMC) and Customer Scope (CS). Bothcompany, lack of data in either time period, or partvariables take values between 0 and 1, and increase

category changed. As a result, we obtained 90 types

when “regarded important from main customer” orof parts with satisfactory data.

“customer scope” increase. Additionally, we define

In addition, for data on each supplier company

main customer as the automaker who receive largest

unit, we referred to Nihon no Jidosha Buhin Kogyo:

number of units of delivery from the supplier for

1992-1993, IRC Co., Nihon no Jidosha Buhin

each parts in 1993.

Sangyo no Jittai, 93-nendo Ban, financial report ofSecond, we conduct an analysis applying

each company, Nihon Keizai Shinbunsha, Kaisha

RIMC*CS, which is the interaction term of

Soran: Tento, Mijojo Kaisha Ban, 1993, respectively.

“regarded important from main customer” andNumbers of sample is mentioned later.

“customer scope,” as the third independent variable.
However, if three variables are applied without

3.2. Dependent Variable and Independent Variable

modification,

multicollinearity

problemoccur

We will then explain the variables applied in logistic

between variables and their interaction term.

regression analysis. See Table 1 for calculation

Therefore, we fix both variables’ average value to 0

methods of each variable.

and adopt this resolved variables and theirinteraction term.

In this paper, we applied Continuity of Parts

To sum up discussions in Section 2.1 and 2.2,

Transactions (CPT) as suppliers’ performance index,

there are three working hypotheses to test.

which is dependent variable. This is a discretevariable coded as ‘1’ if parts transaction between

Hypothesis 1: RIMC has positive effect on CPT
Hypothesis 2: CS has positive effect on CPT
Hypothesis 3: RIMC*CS has positive effect on CPT

supplier and automakers which existed in 1993 has
still been continued in 1999, and ‘0’ if not continued
in 1999. Transactions which did not exist in 1993

3.3. Customer Segment

and had been established in 1999 are excluded fromIn testing above hypotheses, we divide all parts

sample.
5

KonnoTable 1. Calculation Method of Variables
Variables
Dependent
variable

CPT
RIMC

Independent
variableCS
RIMC*CS
Total volume of partstransactions
Parts market HF
Market rate

Parts level
controlvariable

Importance to Customer
Automaker dummyParts category dummy
Main customer dummy
Degree of dispersion
Degree of concentration

Corporatelevel control
variable

Diversification rate
Capital relation dummy
Sales amount
Sales amount per
employeeCalculation Method
Discrete variable denoted ‘1’ if parts transactions between automaker andsupplier which existed in 1993 continued in 1999; ‘0’ if not continued.
Suppliers’ share in total procurement divided by 100 in supplier-maincustomer parts transactions.
Sum of square values of each automaker’s share in number of parts
delivered from supplier in 1993 divided by 100 (as in Herfindahl Index),then deducted from 1.
Deducting mean from each dependent variable RIMC and CS, then multiply
one with the other.
Log value of suppliers’ total parts transactions with 9 automakers in 1993.
Sum of square values of suppliers’ share in volume of delivery to either of 9
automakers in parts market divided by 100 (Herfindahl Index).
Transition of total parts procurement of 9 automakers through 1993-99,
divided by total parts procurement of 9 automakers in 1993.
Suppliers’ share in total procurement made by customer automaker for eachauto parts in 1993.
Dummy value given to 9 automakers except Isuzu concerning which makertransaction continued or did not continue in each parts transaction.
Dummy value given to 5 of 6 categories of auto parts: engine part, engine
electrical component part, car body part, exterior trim part, internal trim
part: car body electrical component part excluded.
Dummy value given to 9 automakers except Isuzu concerning who is the
supplier’s main customer company with each parts transaction unit.
Ratio of numbers of categories supplied by each supplier in above 6
categories in 1993.
Ratio of numbers of types of parts supplied within the category by eachsupplier in 1993.
Ratio of sales in monetary amounts of non auto parts in total sales of eachsupplier company in 1992.
Dummy value denoted ‘1’ if customer automaker held stock of the supplier,‘0’ if not in each parts transaction unit in 1992.
Log value of each supplier’s sales amount in monetary amounts in 1992.
Sales amount per employee in monetary amounts in each supplier company
in 1992.

transactions in two groups, that is, transaction witheffect on “main maker transaction” is in some sense

main customer (Main Maker Transaction) andunquestionable. Thus we took the other samples fortransaction with other customers (Other Maker

testing hypotheses.

Transaction). We conducted logistic regression

Furthermore, 319 supplier companies delivered

analysis on the latter group alone because “mainat least one of 90 parts dealt in this paper to either 9customer importance” having continuous positive

car companies in 1993. Among them, 13 were 100%6

Suppliers’ Performance
Table 2. Descriptive Statistics and Correlation Matrix① Status of Transactions
continue

not continue

total

Actual frequency

982

137

1119

Relative frequency

0.88

0.12

1.00

② Descriptive Statistics and Correlation Matrix of Main Variables
sample size n=1119
Variables
1
RIMC
2
CS
3
RIMC*CS
4
Total volume of parts transactions
5
Parts market HF
6Market rate
7
Importance to customer
8
Degree of dispersion
9
Degree of concentration
10 Diversification rate
11 Sales amount
12 Sales amount per employee

M.D
0.63
0.60
-0.01
5.38
0.30
-0.12
0.38
0.33
0.20
0.19
11.74
42.62

S.D
0.29
0.21
0.06
0.92
0.11
0.44
0.31
0.16
0.19
0.23
1.49
24.72

1
1.00
-0.19
-0.05
0.33
0.24
0.12
0.29
0.35
0.35
-0.30
0.15
-0.09

2

3

3’

4

5

1.00
0.06
0.33
0.20
-0.09
0.19
-0.29
-0.18
0.22
-0.02
0.10

0.29
0.47
0.38
0.02
0.38
0.13
0.17
-0.12
0.10
-0.02

1.00
-0.07
0.18
-0.08
0.03
0.08
-0.03
-0.02
-0.02
-0.02

1.00
0.27
0.10
0.33
0.17
0.11
-0.04
0.15
-0.02

1.00
0.06
0.23
0.14
0.12
-0.07
0.08
-0.14

Variables
6
7
8
9
10
11
12
1
RIMC
2
CS
3
RIMC*CS
4
Total volume of parts transactions
5
Parts market HF
6Market rate
1.00
7Importance to customer
0.05 1.00
8
Degree of dispersion
0.13 0.09 1.00
9Degree of concentration-0.05 0.09 0.54 1.00
10 Diversification rate
0.02 -0.11 -0.36 -0.31 1.00
11 Sales amount0.00 0.04 0.54 0.65 -0.06 1.00
12 Sales amount per employee-0.01 -0.02 -0.09 -0.07 0.05 0.21 1.00
Note: Significant at 1% when absolute value of correlation coefficient is above 0.08, significant at 5% whenabsolute value of correlation coefficient is above 0.06.

foreign capital supplier and we excluded them from

customers other than main as our test sample.

sample because “regarded important from main

As for control variables, we applied many parts

customer” and “customer scope” in mother country

level variables and corporate level variables.

must be more important. Also for 76 suppliers,
company unit data could not be attained, thus

3.4. Results

suppliers data used in this paper is 230. Then 79

Table 3 shows the result of logistic regression

have main customer transaction alone, which leaves

analysis. In model 1 RIMC and CS is the

151 companies and 1119 parts transactions withindependent variable and in model 2 interaction term
7

KonnoTable 3. Logistic Regression Analysis Results (n=1119)
Model

1 (a)

Customer dummy

RIMC
CS
RIMC*CS
Total volume of parts transactions
Parts market HF
Market rate
Importance to customer
Transaction with Toyota
Transaction with Nissan
Transaction with Honda
Transaction with Mitsubishi
Transaction with Mazda
Transaction with Suzuki
Transaction with Daihatsu
Transaction with Fuji Heavy
Industries
Engine partEngine electrical equipment part
Car body part
External trim part
Internal trim part
ToyotaNissanHonda
Mitsubishi
Mazda
SuzukiDaihatsu
Fuji Heavy Industries
Degree of dispersion
Degree of concentration
Diversification rate
Sales amount
Sales amount per employee
Capital relation
Constant term
-2logL
Negelkerke R2

1 (b)

2 (a)

2 (b)

Main customer
dummy

β

S.E.

P

β

S.E.

P

β

S.E.

P

β

S.E.

P

1.38
2.66

0.53
0.58

0.01
0.00

1.39
2.86

0.59
0.62

0.02
0.00

0.07
3.21
0.51
4.48
0.92
1.45
0.14
0.62
0.52
0.43
0.89

0.16
1.15
0.40
0.70
0.64
0.54
0.44
0.39
0.39
0.40
0.46

0.64
0.01
0.20
0.00
0.15
0.01
0.74
0.11
0.18
0.28
0.05

0.07
3.34
0.51
4.41
0.84
1.49
0.18
0.55
0.51
0.38
0.85

0.16
1.18
0.40
0.71
0.65
0.56
0.45
0.40
0.40
0.40
0.46

0.66
0.00
0.20
0.00
0.19
0.01
0.69
0.16
0.20
0.35
0.06

1.77
3.02
2.86
0.06
2.84
0.56
4.45
0.94
1.45
0.16
0.65
0.52
0.43
0.88

0.58
0.63
1.70
0.16
1.17
0.41
0.71
0.65
0.54
0.44
0.39
0.39
0.40
0.45

0.00
0.00
0.09
0.72
0.02
0.16
0.00
0.15
0.01
0.72
0.10
0.18
0.28
0.05

1.91
3.19
3.13
0.05
2.99
0.56
4.36
0.86
1.49
0.19
0.59
0.50
0.38
0.85

0.67
0.66
1.78
0.16
1.19
0.40
0.71
0.66
0.56
0.45
0.40
0.40
0.40
0.46

0.00
0.00
0.08
0.76
0.01
0.16
0.00
0.20
0.01
0.67
0.14
0.21
0.34
0.06

-0.10

0.37

0.79

-0.12

0.37

0.74

-0.11

0.37

0.76

-0.15

0.37

0.69

-0.86
-0.91
-0.63
-0.03
-0.99
0.33
0.20
-0.52
0.28
0.77
-0.51
-1.19
-7.41

0.39
0.48
0.40
0.43
0.45
0.76
0.74
0.77
0.78
0.85
0.86
0.98
20.70

0.03
0.06
0.12
0.95
0.03
0.67
0.78
0.50
0.72
0.37
0.56
0.23
0.72

0.04
0.08
0.14
0.96
0.03
0.49
0.61
0.69
0.62
0.28
0.60
0.23
0.72

0.01

0.01
0.20
0.17
0.80
0.01
0.38
0.54
0.63
0.60
0.20
0.86
0.50
0.74
0.80
0.55
0.02
0.54
0.56
0.46
0.18

0.40
0.49
0.40
0.43
0.45
0.76
0.74
0.77
0.77
0.85
0.86
0.98
20.74

0.92

0.41
0.56
0.41
0.43
0.47
0.80
0.78
0.81
0.81
0.90
0.90
1.02
20.87
1.05
1.07
0.51
0.11
0.01
0.62
1.34

-0.82
-0.85
-0.60
0.02
-1.00
0.53
0.38
-0.31
0.38
0.91
-0.45
-1.17
-7.39

-2.57
608.0
0.35

-1.07
-0.71
-0.57
-0.11
-1.18
0.71
0.47
-0.39
0.42
1.15
-0.16
-0.69
-6.98
-0.26
-0.63
-1.24
-0.07
0.00
0.46
-1.81
598.7
0.36

0.01
605.2
0.35

1.03

0.99

-1.04
-0.66
-0.56
-0.06
-1.17
0.94
0.65
-0.17
0.51
1.33
-0.11
-0.72
-6.97
-0.65
-0.75
-1.29
-0.05
0.00
0.41
0.86
595.6
0.36

0.41
0.56
0.42
0.43
0.47
0.80
0.77
0.81
0.80
0.90
0.90
1.01
20.94
1.07
1.07
0.51
0.11
0.01
0.62
1.44

0.01
0.24
0.18
0.90
0.01
0.24
0.40
0.84
0.53
0.14
0.90
0.48
0.74
0.55
0.49
0.01
0.67
0.67
0.51
0.55

Note: Yellow cells are p<0.10

is added besides RIMC and CS as independent

supported. Second, in models 1 and 2, CS hasvariable. In each model (a) is parts level variables

positive effect on CPT and all are significant at 1%.

only and (b) include corporate level variables.

Therefore, hypothesis 2 is supported. Third, in modelFirst, in models 1 and 2, RIMC has positive

2, RIMC*CS has positive effect on CPT and all are

effect on CPT. Besides, model 1 (b) is statisticallysignificant at 10%. Therefore, hypothesis 3 issignificant at 5% while others are statisticallysupported.

significant at 1%. Therefore, hypothesis 1 isThis paper will conclude from above analysis
8Suppliers’ Performancethat suppliers who is important to main customer

competence would only develop, and improve,

automaker at the same time maintaining businessthrough learning by doing in numbers of actual

relationship with numbers of other customers, tend

dealings with customers. Thus, it is crucial not only

to have advantage over others in parts transactions

to be prove important to main customers, but tocontinuity.

broaden customer scope and multiply learning
opportunity.

4. Conclusion

Recently, news media loudly report theIn plain words, the results suggest how important it“collapse of ‘Keiretsu’ relationship,” nevertheless,is for suppliers to build stable business relation withdiscussions in this paper suggest that such point of

the main customer and broaden transaction withview is superficial.

other various customers. In other words, it isSurely, many suppliers are increasing thesignificant for suppliers to broaden customer scope,

number of customers, and as a result, competition

but if with the sacrifice of existing relation with theamong suppliers has become intent than ever.

main customer, it is not a preferable option.

However, on the other hand, as clarified in this paper,
advanced

it is nonetheless important for suppliers to maintaintechnology issues which could only be dealt inand develop intimate relations with main customers,

collaboration with car manufacturing companies.

and as for car manufacturers, it is meaningful to

Therefore, it is crucial for suppliers to prove

maintain and develop relationships with highly

important in the eyes of main customers and gain

competent core suppliers. Thus, at least between

more

on

automakers and suppliers who consist Japanese auto

technology and needs, or join co-development

parts supplier system, “long term, continuing andprojects on new technology. However, this only will

collaborative

maker-supplier

not be sufficient in suppliers’ learning process. If“competition

amongsuppliers reserve the number of customers, theyencouraged

could get caught in learning bias or become too“Keiretsu” is not collapsing but its principle

dependent on specific customer company and lose an

characteristic, that is “co-existence of competition

attitude to develop and exercise their own strategy.

and collaboration,” would be purified and further

Moreover, in order to manage transaction amongdeveloped.

In

fact,

accesssuppliers

to

face

confidential

much

information

relation”

suppliers”

simultaneously.

In

and

shouldotherbewords,

different firms, suppliers must be able to adapt thetechnology or product platform of a specific product
to

meet

different

customers’

demand.

〔Received October 10, 2002; accepted January 21, 2003〕

Such

9

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