THE IMPACT OF INTER-FIRM COLLABORATION ON THE PERFORMANCE OF SUPPLY CHAIN MANAGEMENT

Seung-Chul Kim

Hanyang University, School of Business, Seoul, South Korea.

Tel: (822) 2220-1069; Fax: (822) 2220-1169; E-mail: sckim888 @ hanyang.ac.kr

Se-Hyung Cho

Konyang University, Department of Management Information Systems, South Korea

Tel: (8241) 730-5180; Fax: (8241)733-2070; E-mail: shcho@kytis.konyang.ac.kr

Yong-Kyun Chung

Kangwon National University, Div. of Econ. and Int. Trade, South Korea

Tel: (8233) 250-6187; Fax: (8233) 256-4088; E-mail: ykchung@kangwon.ac.kr

July 11-13, 2007

International Conference on Business and Information (BAI2007)

organized by International Business Academics Consortium

Selected Track Area : Operations Management

Address all correspondence to:

Seung-Chul Kim

Hanyang University, School of Business

17 Haengdang-dong, Seongdong-gu, Seoul 133-791, Korea

TEL: (822) 2220-1069; FAX: (822) 2220-1169; E-MAIL: sckim888 @ hanyang.ac.kr

THE IMPACT OF INTER-FIRM COLLABORATION ON THE PERFORMANCE OF SUPPLY CHAIN

Seung-Chul Kim

Hanyang University, School of Business, Seoul, South Korea.

Tel: (822) 2220-1069; Fax: (822) 2220-1169; E-mail: sckim888 @ hanyang.ac.kr

Se-Hyung Cho

Konyang University, Department of Management Information Systems, South Korea

Tel: (8241) 730-5180; Fax: (8241)733-2070; E-mail: shcho@kytis.konyang.ac.kr

Yong-Kyun Chung

Kangwon National University, Div. of Econ. and Int. Trade, South Korea

Tel: (8233) 250-6187; Fax: (8233) 256-4088; E-mail: ykchung@kangwon.ac.kr

ABSTRACT

Inter-firm collaboration has a strong influence on the efficiency and the performance

of a supply chain as firms can achieve competitive advantage by working together with

their suppliers. There are many factors that can affect the inter-firm collaboration, and

the effect of each factor needs to be studied and understood for building an efficient

supply chain.

Automotive parts manufacturing industry consists of several layers of suppliers, and

they interact with one another in a network of complex relationships. It is a very ideal

industry to study the effect of inter-firm collaboration on supply chain management.

This paper examines the impact of inter-firm collaboration on the supply chain

performance in the context of automotive industry. We use the data collected from

Korean automotive parts manufacturers through survey questionnaires. This study will

be able to provide useful insights about how the buyer-supplier relationship should be

managed to make a more efficient supply chain and to improve supply chain

performance.

Key words: inter-firm collaboration; supply chain performance; auto parts

manufacturing industry; buyer-supplier relationship.

1

INTRODUCTION

Inter-firm collaboration has become an important issue in supply chain management

since implementing supply chain management(SCM) successfully requires companies

to develop close collaborative relationships with their suppliers. Firms produce better

quality products at lower costs by working together with their suppliers and achieve a

strategic advantage in the competition as can be portrayed, for example, in the concept

of collaborative planning, forecasting and replenishment (CPFR). It is not, however,

easy to work with other companies which have different organizational cultures,

missions, IT systems, values, etc.

It is imperative to have a close collaboration between firms to build an efficient supply

chain as coordination through strategic partnerships replaces the vertical integration,

i.e. the conventional way, to attain the desired efficiency in the supply chain. Inter-firm

collaboration may be measured by the level of trust and satisfaction about the

relationship between two firms. Also, there are many factors that can affect the inter-

firm collaboration such as information system maturity, asset specific investment,

opportunistic behavior, communication, etc. Some factors have more influence on the

inter-firm collaboration while others might not be as important for maintaining it. The

effect of each factor needs to be studied and understood for effective supply chain

management.

Auto parts manufacturing industry consists of automobile manufacturers and several

layers of parts suppliers, and they interact with one another in a network of complex

relationships. The results of good collaboration between buyer and supplier firms are

often reflected in the performance of the supply chain which the buyer and supplier

firms belong to. One common form of the inter-firm collaboration that was developed

and extensively implemented in auto industry is Just-In-Time delivery (JIT) in which

we could observe close cooperation between buyer and supplier firms. In this regard, it

is a very ideal industry to study the effect of inter-firm collaboration on supply chain

management.

This paper examines the effect of inter-firm collaboration on the efficiency of supply

chain in the context of auto parts manufacturing industry. First, we identify the

important factors that affect inter-firm collaboration. Second, the impact of inter-firm

collaboration is measured on the performance of a supply chain. We use the data

collected from Korean automotive parts manufacturers through survey questionnaires.

Korea has a very sizable automobile industry with several world class auto

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manufacturers such as Hyundai Auto Co., Kia Auto Co., GM Daewoo, and Renault

Samsung. Also there are a large number of parts manufacturers and their suppliers in

the upstream of the Korean auto industry supply chain. This study will be able to

provide useful insights about how the buyer-supplier relationship should be managed

to achieve a better supply chain.

LITERATURE REVIEW

In recent times, no one question the importance of SCM for improving the firms’

performance in a networked economy. Usually, many firms cooperate to produce a

final product. In particular, an automobile manufacturer does not make every

component of a car in automobile manufacturing industry. Naturally car makers

purchase auto parts from many suppliers. In this structure, SCM is an important tool to

realize the efficiency in auto industry. Many previous studies investigated the

relationships between buyer firms and supplier firms, and found that both groups will

benefit more from the cooperative relationships than the competitive relationships.

Table 1 contains some of the previous research that investigated various types of the

buyer-supplier relationship and its impact on the firms.

TABLE 1. Summary of previous studies.

Researcher Content

Dyer(1996); Nishiguchi and

Brookfield (1997)

Compared U.S. and Japanese auto industries.

Japanese auto industry has more cooperative buyer-

supplier relationships.

Dywer, Schurr and Oh(1987)

Anderson and Narus(1990)

Maloni and Benton (1997)

Emphasized the importance of the buyer-supplier

cooperation.

Boddy et al. (1998)

Akintoye et al.(2000)

Wathne and Heide(2004)

Investigates key success factors in implementing

supply chain

Cooper (1993)

Lambert and Cooper(2000)

Reasons that firms form a supply chain (inventory

reduction, improving service, etc.).

Lamming (1993) Suggest a lean supply chain model in auto industry

to understand the buyer and supplier relationship.

Han (1993); Fisher et al.

(1994); Imne and Morris

(1993);Jap(1999)

The importance of buyer-supplier relationship for a

firm’s competitive advantage.

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Shapiro (1985); Spekman

(1988); Landeros and

Monczka (1989);Burt

(1989); Bensaou and

Venkatraman (1995); Helper

(1991); Helper and Sako

(1995)

Investigate the various types of buyer-supplier

relationship:

competitive vs. cooperative

open market negotiation vs. vertical integration

integrated vs. structural

Morgan and Hunt(1994)

Smith et al. (1995)

Akintoye et al.(2000)

Trust and cooperation among firms.

Landeros (1993) Define the cooperative relationships.

RESEARCH METHODOLOGY

Research model and hypotheses

A research model is constructed to depict the relationship among the factors as shown

in Figure 1. It shows the relationship between the success factors, inter-firm

collaboration, and SCM performance. The variables representing each factor of the

model will be identified from the analysis, and the relationship will be tested by using

statistical analysis.

The level of inter-firm collaboration is measured by surveying the supplier firms. That

is, first-tier supplier firms evaluate the first-level relationship (auto manufacturers and

first-tier parts suppliers), and second-tier supplier firms evaluate the second-level

relationship (first-tier parts suppliers and second-tier parts suppliers).

Figure 1 contains the research model showing the relationships between the tiers of

firms in the supply chain, and hypotheses are constructed as below for each of the

relationships indicated as H1 through H3.

H1: Success factors affect the collaboration level between firms.

H2: Important factors affecting collaboration are different between the first-level and

the second-level relationships.

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H3: SCM performance is positively related to the collaboration level between firms.

High level of inter-firm collaboration will result in high SCM performance.

FIGURE 1. Research model.

Data collection

Data for this study were collected from automotive parts manufacturers through survey

in 2006. The survey questionnaire consists of eighty two questions. The survey was

conducted by mails. The respondents are the staff of the sales department in the

supplier firms, and thus familiar with the relationships between their own company

and their buyer company. In this study, we analyze the impact of inter-firm

collaboration on the SCM performance. The inter-firm collaboration was measured

from the viewpoint of supplier firms because supplier firms are normally in a weaker

position in the relationships, and thus, we expect that it is possible to obtain more

conservative assessment of the inter-firm collaboration between supplier and buyer

firms.

About five hundred fifty questionnaires were mailed out to the companies listed on the

Korea Auto Industries Cooperation Association member directory, and seventy

responses were returned. A total of sixty five responses were used for this study after

five were discarded due to incomplete responses. They were divided into two groups

depending on their relationship with the automobile manufacturers. Fifty companies

were the first-tier suppliers, and fifteen companies were the second-tier suppliers. The

profile of the firms is shown in Table 2.

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The survey questions are answered by 7-point Likert-type scale except those requiring

single-item answers. We used descriptive statistics, factor analysis, correlation test,

and regression to analyze the data.

TABLE 2. Profile of the firms

Frequency Proportion

Sales in dollars 0 ~ $50 million 34 53.1%

$50 ~ $100 mil. 9 14.1

$100 ~ $200 mil. 8 12.5

$200 mil. ~ 13 20.3

No. of

employees

0 ~ 200 33 52.4%

200 ~ 500 16 25.4

500 ~ 1000 9 14.3

1000 ~ 5 7.9

Relationship

with Auto

manufacturer

1st-tier supplier 50 78.1%

2nd-tier supplier 10 15.6

Others 4 6.3

Length of

relationship

with the buyer

0 ~ 10 years 12 19.0%

10 ~ 20 years 20 31.7

20 ~ 30 years 18 28.6

30 years ~ 13 20.7

*The numbers do not add up to 65 since there are a few firms that did not

answer certain questions.

ANALYSES AND RESULTS

Statistical tests are conducted on the data to identify factors and to group them for

further analyses.

Identification of the factors and variables

The internal consistency reliabilities are tested for the measured variables, and the

results (Cronbach α> 0.6) show that all of them are above the acceptance level. Factor

analyses were conducted to identify the groupings of the variables for success factors,

inter-firm collaboration, and SCM performance. We used eigenvalue of 1 and the

factor loading of 0.5 as the selection criteria. The results yielded six factors that

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provide four variables for success factors and two variables for the level of inter-firm

collaboration. They are named as follows: IT maturity, asset specific investment,

opportunistic behavior, communication , trust, and satisfaction. Another factor analysis

produced three factors for SCM performance, and they are the efficiency, speed, and

effectiveness of SCM. The results are shown in Tables 3 and 4. Based on the results of

the factor analyses, factor groupings of the variables are made as shown in Table 5.

TABLE 3. Results of factor analysis to extract the success factors.

Factor

 Quest.

Factor 

Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6

IT util 54 .874 .125 .155 .198 -4.756E-02 9.802E-02

IT util 55 .850 -7.483E-02 1.035E-03 9.037E-02 -8.007E-02 .213

IT util 53 .844 .147 .173 .186 .167 4.987E-04

IT util 50 .827 1.864E-02 -.186 9.565E-02 1.847E-02 -.144

IT util 49 .810 1.952E-02 -.124 6.376E-02 5.018E-02 -7.863E-02

IT util 52 .746 .203 9.858E-02 5.446E-02 .282 -2.843E-02

Success-Relationship 16 1.538E-02 .859 6.644E-02 3.082E-02 .190 .198

Success-Relationship 17 .150 .855 .268 .121 8.990E-02 7.656E-02

Success-Relationship 19 .114 .844 .159 7.076E-02 2.236E-02 -1.011E-03

Success-Relationship 7 -3.287E-02 2.572E-02 .818 -.126 -.135 -3.749E-02

Success-Relationship 12 6.573E-02 .152 .730 -.264 .169 .227

Success-Relationship 15 -.161 .232 .707 5.329E-02 .166 -.355

Success-Relationship 14 .148 .249 .692 .247 -1.611E-02 -.126

Success-Coordination 28 .242 .104 -.174 .849 1.570E-03 -4.000E-02

Success-Coordination 25 .178 .190 -4.722E-02 .809 -9.984E-02 .261

Success-Coordination 29 9.314E-02 -4.997E-02 .107 .766 .205 .121

Success-Relationship 5 4.483E-02 .157 -7.205E-02 9.596E-02 .918 1.291E-02

Success-Relationship 4 .214 .108 .162 4.902E-03 .810 .342

Success-Relationship 23 -.137 .127 -8.016E-02 7.994E-02 .214 .827

Success-Relationship 21 .139 .159 -.102 .413 6.701E-02 .658

Reliability(Cronbach α) 0.9174 0.8666 0.7690 0.8096 0.7575 0.6318

Note: Principal component and Varimax rotation with Kaiser normalization.

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TABLE 4. Factor analysis for SCM performance variables.

Factor 

 Quest.

Factor

Factor 1 Factor 2 Factor 3

SCM Perf 10 .849 .255 -3.629E-02

SCM Perf 9 .795 .115 .161

SCM Perf 8 .754 .202 .316

SCM Perf 6 .737 .192 .335

SCM Perf 3 .161 .820 -7.923E-02

SCM Perf 4 .162 .693 .192

SCM Perf 1 .256 .691 .260

SCM Perf 7 .150 .424 .765

SCM Perf 5 .374 -.278 .658

SCM Perf 2 .148 .512 .649

Reliability(Cronbach α) 0.8509 0.7300 0.6416

Note: Principal component. Varimax rotation with Kaiser normalization.

TABLE 5. Composition of the factors and variables

Factor Variables Related studies

Success

factors

IT maturity

Asset specific investment Heide and John(1988),

Morgan and Hunt(1995),

Dyer et al.(1996), Heide(2003)

Opportunistic behavior Klein et al.(1990),

Stump and Heide(1996)

Communication Anderson and Narus(1990)

Morgan and Hunt(1995)

Ballou et al.(2000)

Collaboration Trust Anderson and Narus(1990)

Morgan and Hunt(1995)

Akintoye et al.(2000)

Smith et al.(1995),

Spekman et al.(2005)

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Satisfaction Anderson and Narus(1984)

Anderson and Narus(1990)

Morgan and Hunt(1995)

SCM

performance

Overall SCM performance

Efficiency

Speed

Effectiveness

Test of Hypotheses

Regression analyses were performed to determine the acceptance of the three hypotheses,

and the results are presented in Tables 6 through 9.

For Hypothesis 1, a multiple regression test was conducted to find out which of the four

variables representing success factors had significant impact on the inter-firm

collaboration level. Among the four variables, asset specific investment and

communication turned out to have significant impacts at α = 0.05 or α = 0.10 on the inter-

firm collaboration level respectively. Thus, two of the success factors are found to be

important for inter-firm collaboration, but IT maturity and opportunistic behavior do not

seem to affect inter-firm collaboration.

For Hypothesis 2, data were divided into two groups, that is, 1st-tier suppliers and 2nd-

tier suppliers, according to the firm’s relationship with the auto makers. Again, multiple

regression tests were conducted on the data to find out the relationship between the

success factors and the inter-firm collaboration level. None of the success factors turned

out to have significant impact on inter-firm collaboration for both 1st-tier and 2nd-tier

groups. Thus, it was not possible to determine whether important factors affecting inter-

firm collaboration are different between the first-level and the second-level supplier-buyer

relationships.

For Hypothesis 3, the result of the regression test showed that inter-firm collaboration

seemed to have a positive and significant impact on the SCM performance although the

significance level is very marginal with p-value = 0.1089. Thus, we can say that SCM

performance will improve as the level of inter-firm collaboration increases.

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TABLE 6. Collaboration vs. the success factors.

coefficient t p-value

IT maturity 0.0167 0.2803 0.7802

Asset specific investment 0.1857 2.0465 0.0453**

Opportunistic behavior -0.0912 -0.9730 0.3346

Communication 0.1961 1.8325 0.0720*

F = 2.865, p-value = 0.0311, r2 = 0.167, df = 61

* : p < 0.10, ** : p < 0.05

TABLE 7. 1st-level relationship: Collaboration vs. the success factors.

coefficient t p-value

IT maturity 0.0514 0.7516 0.4561

Asset specific investment 0.1570 1.4377 0.1574

Opportunistic behavior -0.0955 -0.8188 0.4172

Communication 0.1543 1.2266 0.2263

F = 1.3206, p-value = 0.2768, r2 = 0.0255, df = 49

TABLE 8. 2nd-level relationship: Collaboration vs. the success factors.

coefficient t p-value

IT maturity -0.1169 -0.8288 0.4345

Asset specific investment 0.2291 1.0832 0.3146

Opportunistic behavior -0.0327 -0.1472 0.8870

Communication 0.4412 1.4755 0.1835

F = 1.9421, p-value = 0.2082, r2 = 0.2551, df = 11

TABLE 9. SCM performance vs. Collaboration.

계수 t p-value

Collaboration 0.5325 1.6271 0.1089

F = 2.647, p-value = 0.1089, r2 = 0.026, df = 61

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Path analysis and test of Hypotheses

We used correlation test and regression analyses to find out the relationships among the

success factors, inter-firm collaboration and SCM performance, and the results are

presented in Figure 2. In this analysis, the inter-firm collaboration is defined as the sum of

the three variables of trust, satisfaction and communication. From the analyses, it seems

that IT maturity and asset specific investment affect the inter-firm collaboration level and

also has direct effect on the SCM performance as well while opportunistic behavior seems

to affect only asset specific investment. Inter-firm collaboration is also found to have a

direct influence on the SCM performance.

FIGURE 2. Path analysis.

CONCLUSION

In this paper, we attempted to identify the important factors affecting inter-firm

collaboration, and assessed the impact of inter-firm collaboration on the performance

of supply chain management. First, we found that asset specific investment and

communication were the two important factors that would have significant impact on

inter-firm collaboration. The result shows that the inter-firm collaboration level will

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increase when firms make investments that are designed to be used specifically for

their supplier and buyer firms and when firms are actively engaged in communication

with their suppliers and buyers. Second, inter-firm collaboration was found to have a

marginally significant impact on the SCM performance. Thus, the SCM performance

can be improved through the collaboration with the supplier and buyer firms in the

upstream or downstream of the supply chain.

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