MMRCDISCUSSION PAPER SERIES
No. 506

The Interaction Effect of Customer–Product
Diversification on Firm Performance
Seungkee MIN
Manufacturing Management Research Center
Graduate School of Economics, The University of Tokyo
Email: petrosmin@gmail.com

December,2018

東京大学ものづくり経営研究センター
Manufacturing Management Research Center (MMRC)
Discussion papers are in draft form distributed for purposes of comment and discussion. Contact the author for
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http://merc.e.u-tokyo.ac.jp/mmrc/dp/index.html

The Interaction Effect of Customer–Product
Diversification on Firm Performance

Seungkee MIN
Manufacturing Management Research Center
Graduate School of Economics, The University of Tokyo
Email: petrosmin@gmail.com

ABSTRACT:This paper investigates the interaction effect of customer scope strategy and productdiversification strategy on firm performance. The result provides a support for a positive
moderating effect for product diversity on the relationship between customer scope andfirm performance in 2005, while pursuing only product diversity has a negative but
insignificant influence on performance. This result indicates that the combination
strategy, which refers to implementing the both strategies (broadening customer scopeand product diversity), improves firm performance under certain conditions. In the main
body of the discussion, this paper suggests some theoretical implications based on theempirical results.

Keywords: product diversity, within-industry diversification, product scope, customer
scope, combination strategy, transaction costs, coordination cost, automotive industry

INTRODUCTION
Previous studies on strategic management have expounded the antecedents which
affect positively firm performance. Studies on interorganizational relationships havesuggested that the most important sources of innovation are resulted from customers andhaving a broader customer scope positively affects firm performance, especially within
the Japanese automotive industry (Clark & Fujimoto, 1991; Dyer & Chu, 2011; Dyer &Nobeoka, 2000; Konno, 2017; Martin, Mitchell, & Swaminathan, 1995; Nobeoka et al.,
2002; Sako & Helper, 1998; von Hippel, 1988). Those studies have basically assumed
that interorganizational learning through interactions with multiple customers is criticalfor achieving competitive advantage and outstanding performance. Prior research oninterorganizational relationships indicates a positive relationship between customer scope
and firm performance; yet, a study examining the relationship in different fiscal years has
founded an inconsistent result with the previous research (Min & Song, 2017).
Meanwhile, scholars on diversification strategy have empirically demonstrated theimpact of within-industry diversification or intra-industry diversification on firm
performance (Hashai, 2015; Min & Mitsuhashi, 2016; Stern & Henderson, 2004;
Tanriverdi & Lee, 2008; Zahavi & Lavie, 2013). These studies have examined if productdiversification within a particular market or industry enhances firm performance, but thefindings on the linkage between product diversity and performance have remained
somewhat inconsistent.
This study suggests that customer scope can be a critical factor to moderate therelationship between product diversification and firm performance positively; however, inthe existing literature, how the interaction of two strategies affects performance remains
unclear since there has been no examination of the outcomes of simultaneously pursuingcustomer scope and product diversity.
To examine the interaction effect of customer and product diversification strategy on
performance, the remainder of this paper is arranged as follows. Following thisintroduction, the next section reviews the previous literature on the effects of customer

scope and product diversity on firm performance. After briefly describing the researchmethod including the data, variables, and the model, the study presents the empiricalresults and concludes with discussing some theoretical implications.

LITERATURE REIVEW
Product Diversity on Performance: Within-industry Diversification
After the pioneering research on diversification strategy by Ansoff (1957) andChandler (1962), over the past several decades, strategic management scholars haveempirically examined whether the diversification across industries has a positive effect onfirm performance at the corporate level (Markides, 1995; Palepu, 1985; Palich, 2000;
Rumelt, 1982).
However, firms diversify not only across industries, but also diversify withinindustry. In a lot of cases, small to medium-sized high technology firms are likely to
pursue product diversification strategy within their industry to strengthen the engine of
growth. This kind of diversification is described by terms such as intra-industry
diversification or within-industry diversification (Hashai, 2015; Min & Mitsuhashi, 2016;
Stern & Henderson, 2004; Tanriverdi & Lee, 2008; Zahavi & Lavie, 2013). In fact, mostof the suppliers, which dealt with in Nobeoka et al. (2002) and Min & Song (2017),
remained focused on the automotive industry; at the same time, some of those might had
diversified product scope (product categories) within the industry.
Little was known about the link between product diversity within-industry and firm
performance, but recently several studies on performance consequences of the withinindustry product diversification have appeared in the literature. The findings on the effectof within-industry diversification on firm performance is somewhat mixed andinconsistent. This mixed evidence might be caused by methodological differences
including variables and measures or some latent contingencies.

One study, analyzing the relationship with the data of Canadian general insurance
industry, found that there is no relationship between within-industry diversification andprofit performance measured by ROA (Li & Greenwood, 2004). An analysis that reports
mixed effect including a negative effect also exists. Tanriverdi & Lee (2008) analyzed thedata of 884 firms in the software industry and concluded that implementing only marketrelated diversification or only platform-related diversification reduces performance (sales
growth), while implementing the two strategies in combination has a positive effect on
performance.
In contrast, several studies reported positive relationships between within-industry
diversification and firm performance. For example, Nobeoka & Cusumano (1997) findthat product diversity has a positive effect on sales growth that because technology
sharing enhance economies of scope. One study reports that product diversity as well as
introduction rate of new products have positive relationships with firm survival byanalyzing the personal U.S. personal computer industry, though the impact of productdiversification on survival is weaker when environments are unstable (Stern &Henderson, 2004). Meanwhile, Zahavi & Lavie (2013) examines that U.S. software
firms’ product diversity initially has a negative effect on performance at a low level
because of negative transfer effects but then improve performance to enlarge economies
of scope. In this vein, they contend that the degree of within-industry diversification has a
U-shaped relationship with sale growth. Further, recent research on small and mediumsized high technology firms shows that there is a S-shaped relationship between withinindustry diversification and ROS (Hashai, 2015). Hashai (2015) points out that a higher
level of within-industry diversification hampers firm performance, resulting from theinfluence of adjustment costs and coordination costs.

Customer Scope on Performance
Customers are a valuable source of innovation because suppliers acquire external
knowledge and information for new product development, thus helping them creating

product innovation(von Hippel, 1977; von Hippel, 1978; von Hippel, 1988). von Hippel(1988) investigated the sources of the innovation in the semiconductor industry, founding
the primary sources of innovative ideas come from firms' customers. This means thatclose relationships with customers help suppliers acquire knowledge that might bevaluable to create new value for them. Thus, we can assume that suppliers with multiple
customers are more likely to develop innovative new products that meet the needs ofcustomers, thus resulting in outstanding performance.
In the Japanese automobile industry, automotive suppliers acquired the mostimportant sources of technical knowledge for new product developments through supplierassociations that Japanese automakers established(Nishiguchi, 1994). The Japanesesupplier associations have a critical role to play in sharing technologies and ideas between
the suppliers and the assemblers (Clark & Fujimoto, 1991; Cusumano & Takeishi, 1991;
Dyer & Chu, 2011; Dyer & Nobeoka, 2000; Konno, 2017; Sako & Helper, 1998). More
importantly, Martin, Mitchell, & Swaminathan (1995) indicate that a supplier withbroader customers might achieve a greater profits because it could develop negotiation
skills from experiences in transactions with multiple customers.
Based upon the above arguments, pointing out that leading Japanese automotive
suppliers have actually a broader range of customers, Nobeoka, Dyer, & Madhok (2002)
examine the effect of customer scope strategy on firm performance of the suppliers. In the
research by Nobeoka et al. (2002), customer scope is measured by the number of
automakers to whom components were supplied and the Herfindahl index (theconcentration ratio of automakers) with the data from Japanese Automotive Parts
Industry. Their results confirm that suppliers with a broader customer scope achieve
superior performance. This is because interactions with multiple customers makesuppliers take advantages of economies of scope through increases of learning
opportunities and acquire relation-specific knowledge, thus receiving the benefit ofreduction in transaction costs (Dyer, 1997; Nishiguchi, 1994; Nobeoka et al., 2002).
Recently, pointing out the methodological limitation of Nobeoka et al. (2002) in thatthe analysis is only based on a single-year data for 1995, Min & Song (2017) examinedthe impact of customer scope on performance at different fiscal years. In order to enhance
the theoretical reliability of the research result, they composed multiple-year dataset bygathering additional data from Japanese Automotive Parts Industry for 1985 (the fiscal
year ending in 1984) and 2005 (the fiscal year ending in 2004) in addition to the data for1995(the fiscal year ending in 1994). The results for 1985 and 1995 are basicallyconsistent with the resultant of Nobeoka et al. (2002); however, no significant
relationship between customer scope and performance is observed for 2005. In short, theempirical research reviewed above show that while there was a support for the
relationship between customer scope and firm performance in 1984 and 1994, therelationship could not be found in the 21st century 1.
In order to grasp the insignificant result for 2005, Min & Song (2017) in thediscussion of the paper noted that no one argues relation-specific skill (Asanuma, 1989)
can be re-deployed to other customers with no additional adjustment costs, thus proposeda plausible hypothesis that the level of costs to coordinate and redeploy went on
increasing as the number of customers grew up. In the previous literature, though themost studies stand on the buyer side, strategic management scholars pointed out thatcoordination costs may increase with a rise in the number of transactional firms at thesame time (i.e., Bakos & Brynjolfsson, 1993).
In the context of costs, Nobeoka et al. (2002) also pointed out that suppliers having
multiple customers can take advantage of relation-specific knowledge which leads to cost
reduction, even though the optimum degree of customer scope to maximize is still a
subject to debate. Generally, it is considered that the relation-specific knowledge enables
suppliers to conduct transactions more efficiently.
On this point, this study assumes that not only customer diversity, but also productdiversity within-industry can positively influence the firm performance by enlarging theeffects of economies of scope. Therefore, it is worthwhile to consider the way in which

1

Another recent study shows that higher customer concentration, which means lower
customer diversity, negatively affect the supplier’s performance (Kim, 2017).

product diversity affects the relationship between customer scope strategy and firm
performance.
In combination with the literature above, this paper assumes that simultaneously
pursuing customer-product diversification strategies may lead to enhance firm
performance by enlarging economies of scope resulting from complementary effects; ofcourse, pursuing two strategies simultaneously might inhibit the firm performance byraising costs such as coordination or adjustment. Surprisingly, there is no empiricalresearch to demonstrate the outcomes of pursuing both strategies simultaneously with the
exception of Konno (2017). Thus, this paper examines the relationship following a
research question: Does broadening customer diversity or product diversity enhance
performance? Does pursuing both customer and product diversity enhance performance?

RESEARCH METHODS
Sample and Data Collection
This paper collects the data from Japanese Automotive Parts Industry (Japanese
Automotive Parts Industries Association [JAPIA], 2005), which covers the transactionaland financial information of the Japanese automotive component suppliers. This research
consists of the data set based on automotive component suppliers that have more than
50% of the total sales to automotive assemblers. We exclude automotive component
suppliers with missing information regarding products, sales, profits, or shipment ratios(customer proportions - aggregated percent sales to automotive assemblers) from the data.
The final numbers of suppliers in the sample is 81. Data on products, customer
proportions and the numbers of employees are based on the annual data for the fiscal year
ending in 2004. The annual data on performance (i.e., sales and profits) is based on thefiscal year ending in 2004 and 2005.

Operational Measure
Dependent variable
In this research, suppliers’ profit-sales ratios are the firm performance as thedependent variable, following the method of existing research (Nobeoka et al., 2002). In
general, profit-sales ratio is calculated by dividing the operating income by total sales. To
reduce concerns about the problem of reverse causality, this paper includes a time lag
between the dependent variable and independent variables. Thus, profit-sales ratio in thispaper is calculated as the average value during a two-year period (t0+t1).

Independent variable
Product diversity is measured by the natural logarithm of the number of productcategories in each year (Hashai, 2015). The data book, Japanese Automotive Parts
Industry, classifies products that Japanese automotive suppliers produce into 148
categories and provides the information of what products each supplier deal with. Thus,
this study uses those numbers to measure product scope for each supplier in each year.
Customer scope is measured by the number of automotive customers. This is a
simple count of customers, to whom a supplier provides its own components among
seven automotive assembler groups. This study adopts the customer classification by
Nobeoka et al. (2002) that classified Japanese automotive assemblers into the following 7
groups: the Toyota group (Toyota, Toyota Auto Body, Daihatsu, Hino, and Kanto Auto
Works), the Nissan group (Nissan, Nissan Shatai, Nissan Diesel Motor, Fuji Heavy
Industries, and Aichi Machine Industry), Mitsubishi, Honda, Mazda, Suzuki, and Isuzu.

Control variable
Following prior research, this study includes control variables to consider otherfactors that might affect firm performance (Lieberman & Demeester, 1999; Nobeoka etal., 2002). First, as some suppliers sell components to other automobile suppliers or tonon-automobile customers, the model includes control variables for related customer
ratio, a ratio of supplier's sales to other automobile suppliers divided by total sales, andfor unrelated customer ratio, which is a ratio of a supplier's sales to non-automotive firms
divided by total sales. Also, this paper considers customer-proportions with the ratio of a
supplier's sales volume to each customer divided by total sales to the seven assemblers,
scale effects with the natural logarithm of the total sales of each supplier, andcompetitiveness of each supplier with natural logarithm of the sales per employee andsales growth in the past four years.

ANALYSIS AND RESULTS
To investigate the effects of broadening customer scope and product diversity on
firm performance, this study conducted multiple regression analyses. Tables 1 summarize
descriptive statistics and correlations across the variables. The means, standard
deviations, correlations among the variables are described. The average of profit-sales
ratio in which the sampled firms were involved is 0.042, which means 4.2%, with astandard deviation of 0.025. The mean value of customer scope is 2.840 and productdiversity is 1.171.

0.208 -.383.027 -.083.058 -.158 -.162 -.227 * -.190 -.060 -.151

0.336
0.240
0.154
0.153
1.347
0.478

0.085
0.202
0.083
0.053
0.039
10.2133.734
0.213

6 Mitsubishi

7 Honda8 Mazda9 Suzuki

10 Isuzu

12 Sales/Employee (Log)

13 Sales Growth

14 Related Customer Scope

15 Unrelated Customer Scope.006.170 -.109
.050
.045

.033 -.139 .310

.090-.013 -.055.253 * -.114-.004 -.380 ** -.094-.015 -.043 -.110

0.257

1

9

0.084
0.034

0.057
0.018

.222

*

-.124

.102 -.136 -.109
**

1

10

.056

.213 -.044

1

12

*

.063 -.147 -.018.060-.112 .526

**

1

11

.117 -.116 -.189 -.244.125 -.185.023 -.187-.059 -.258*.220 * -.072 -.234 * -.190.157 -.099 -.119.104.035 -.118.100 .351 ** .590 **.054

Note : **p < 0.01; *p < 0.05. n = 81

11 Sales (Log).076 -.007 -.075 -.140 -.099 -.072 -.091

1

8.017 -.002 -.090 -.126 -.087 -.009 -.144 -.063 -.057

-.196

-.270

-.174

.165 -.356

1

*

**

.032 -.050 -.177 -.144.045 -.032 -.396 **

1

-.094

0.352

0.248

5 Nissan

.052
1

.307

0.381

0.290

4 Toyota

**

.083

**

1

.125

-.004

0.790

1.171

3 Product Diversity (Log)

1

1

.098

1.699

2.840

7

2 Customer Scope

6

1

5

0.026

4

0.042

3

1 Profit-Sales Ratio

2

1

s.d.

Mean

Variables1

14.061 -.063

.033

1

13

Table 1. Descriptive Statistics and Correlations Matrix

Table 2 shows the results of the regression analyses. As explained previously, thisstudy has used profit-sales ratios as the dependent variable of firm performance. Since thevariance inflation factors (VIF) of all variables observed in the regression analyses were
below 10, there is no evidence of multicollinearity to be a problem.
Model 1 is the analysis to check the effects of the control variables. These control
variables account for 20.8% of the variation in firm performance. For the ratio of
Mitsubishi (β = -0.444, p < 0.05), the ratio of Suzuki (β = -0.258, p < 0.1), sales growth (β= 0.183, p < 0.05), the regression coefficients were statistically significant. The ratios of
Mitsubishi and Suzuki have negative effects on performance, while sales growth has apositive relationship with performance.
Model 2 and Model 3 are the direct effects of customer scope and product diversity
on performance. The results show that customer scope has a positive and significant
effect on performance (β = 0.218, p < 0.1), while product diversity has a negative but
insignificant effect on performance respectively (β = -0.036, p > 0.1).
Model 4 and 5 include the interaction term of customer scope and product diversity
on performance. The result of Model 5 shows significant positive relationship between
the interaction term and the performance (β = 0.268, p < 0.05). Furthermore, the effect of
product diversity on performance changed from a negative sign to a positive sign.

-0.055

Sales (Log)

0.100

Unrelated Customer Ratio***p < 0.01; **p < 0.05; *p < 0.10.

Note : n =81. Standardized coefficients are shown.

2.92 ***

1.70

0.95

-0.43

2.15

0.73

-1.24

-1.68

0.31

0.21

2.99 ***

0.230

0.208

Adjusted R -Squared

F -value

0.345

0.218 *

0.105

-0.0480.244 **

0.096

-0.186-0.243 *

0.058

0.052

0.317

0.89

-1.08

1.68

0.16

-0.43

-1.76

0.05

-0.11

-0.50

0.70

t -Value-0.424 ** -2.38-0.1220.186

βM o de l 2

R -Squared

Customer Scope X Product Diversity (Log)

Product Diversity (Log)

Customer Scope-0.115

Related Customer Ratio

0.183 *

-0.258 *Suzuki

Sales Growth

0.010

Mazda

0.020

-0.027

Honda

Sales/Employee (Log)-0.444 ** -2.46

Mitsubishi-0.59-0.146

Nissan0.53

t -Value

0.142

β

M o de l 1

ToyotaIn de pe n de n t
var iable

-0.59

0.52

t -Value

-0.28

0.87

-1.05

1.65

0.09

-0.18

-1.72

0.02

-0.11

2.64 ***

0.198

0.318

-0.0360.098-0.113

0.182

0.012

-0.029-0.254 *0.004-0.027-0.443 ** -2.44-0.1490.140

βM o de l 3

-0.48

0.70

t -Value

0.15

1.67

0.95

-0.42

2.13

0.74

-1.07

-1.68

0.33

0.22

2.72 ***

0.218

0.345

0.020

0.223 *

0.106

-0.0480.246 **

0.102

-0.203-0.245 *

0.062

0.054

-0.424 ** -2.36-0.1200.188

βM o de l 4

-0.03

1.12

t -Value

2.41

0.04

2.03

1.12

-0.46

2.41

1.55

-1.85

-1.42

0.57

0.77

3.12 ***

0.271

0.398

0.268 **

0.006

0.263 **

0.121

-0.0510.269 **

0.220

-0.363 *-0.202

0.105

0.189

-0.380 ** -2.17-0.0070.294

β

M o de l 5

Table 2. Regression Results (dependent variable: profit-sales ratio)

DISCUSSION
The effects of pursuing customer-product diversity simultaneously on firm
performance is a topic that has not been examined in the field of strategic management.
To date, the literature has examined the effect of each product diversity or customer scopeon performance separately. This paper has examined in detail the issue of whether
pursuing two strategies (customer scope strategy and product diversification strategy)
simultaneously affect firm performance or not with a sample of Japanese automotive
suppliers.
The result shows that customer scope has a statistically significant positive effect on
performance, while product diversity has a negative effect on performance though it is
not statistically significant; However, the interaction term of customer scope and productdiversity has a statistically significant positive effect of performance.
This paper has made two main contributions to the existing literature. First,
regarding the inconsistent results among the literature (Min & Song, 2017; Nobeoka etal., 2002), it has been empirically examined that product diversification strengthens theeffect of customer scope strategy on performance. The combination strategy of pursuingboth customer diversity and product diversity may help increase the effect of economies
of scope under certain specified conditions. Second, in regard to the conflicting
arguments that prior studies on within-industry diversification have also shown (Hashai,
2015; Li & Greenwood, 2004; Stern & Henderson, 2004; Tanriverdi & Lee, 2008; Zahavi& Lavie, 2013), the result of this paper provides a new perspective that pursuing both two
strategies at the same time could produce complementary effects to maximize economies
of scope under a certain condition. Briefly, this paper provides a clue to grasp theinconsistent results in the literature by shedding light on the interaction effect ofsimultaneously pursuing customer-product diversification strategies.
To make the results more robust, this study also conducted a regression analysis
using the data for 1995 (for details, see Appendix 1). Compared to the result in 2005, theanalysis in 1995 shows that customer scope is significantly correlated with performance(profit-sales ratio), while the effect of product diversity and the interaction term on
performance does not exist. These results may be better explained by the contingent
perspectives. A major difference is that the average profit-sales ratio of assemblers islower than suppliers in 1995, but the average profit-sales ratio of assemblers is higher
than suppliers in 2005. This difference indicates the comparative performance between
suppliers and assemblers or customers might affect the effect of diversification strategies.
Like all studies, this research has limitations. First, some issues nonetheless remain.
This paper could not explain why the impact of product diversity on performance is not
significant. Also, since this paper did not uncover the certain conditions, further study
should investigate the relationship including these variables so to figure out theconditions to make the combination strategy effective in maximizing economies of scope.
In order to explain these issue, future research is required to examine time-series analyses
so that we could better understand the dynamic interaction between product diversity andfirm performance. Second, since this research uses the number of product categories formeasuring product diversity, further work should be carried out to use the other indicatorssuch as the Herfindahl-Hirschman index and entropy measures (Hashai, 2015; Miller,
2006; Park & Jang, 2013; Suzuki & Kodama, 2004). As for the dependent variable, whilesome of previous studies uses ROA, EVA, Tobin's q or sales growth to measure firm
performance(Chen, Yang, & Lin, 2013; Miller, 2006; Montgomery & Wernerfelt, 1988),
this research adopts profit-sales ratio from limitations on the data. Also, considering
cooperative performance might make analysis results more robust like Wu, Chang, &Weng (2009). We might obtain different results of the effect of product diversity on firm
performance with from this paper if one analyzes the relationship using the othervariables.

0.0420.423 *
0.235
0.174

Mitsubishi

Honda

Mazda

Suzuki-0.169Unrelated Customer Ratio***p < 0.01; **p < 0.05; *p < 0.10.

1.58

2.80 ***

0.231

0.082

Adjusted R -Squared

Note : n =81. Standardized coefficients are shown.

-0.80

-0.10

2.35

2.46

0.428 *** 3.59

-0.092-0.0120.296 **

0.303 **

0.359

F -value

0.84

1.12

2.00

-0.04

1.99

1.49

t -Value-0.350 ** -2.37

0.128

0.151

0.450 *

-0.0070.465 *

0.378

β

0.222

-1.37

-0.77

2.40

1.53

-1.23

1.05

1.62

1.72

0.23

1.74

1.18

t -ValueM o de l A2

R -Squared

Customer Scope X Product Diversity (Log)

Product Diversity (Log)

Customer Scope-0.1010.330 **

Sales Growth

Related Customer Ratio

0.200

Sales/Employee (Log)-0.1890.443 *

NissanSales (Log)

0.327

β

M o de l A1

ToyotaIn de pe n de n t
var iable

0.07

0.074

0.228

-0.104-0.156-0.1110.319 *

0.177

-0.128

0.171

0.196

0.377

0.028

0.394

0.261

β

-0.70

-1.24

-0.84

2.30

1.31

-0.72

1.02

1.26

1.48

0.15

1.48

0.89

t -ValueM o de l A3

-0.73

-0.15

2.28

2.25

-1.84

0.83

0.90

1.81

-0.09

1.79

1.26

t -Value-0.43

2.57 ***

0.221

0.361

-0.0580.423 *** 3.50

-0.085-0.0190.290 **

0.289 **

-0.314 *

0.127

0.130

0.424 *

-0.0150.437 *0.340

β

M o de l A4

-0.89

0.04

2.18

2.28

-1.99

0.81

1.07

1.92

0.02

1.91

1.48

t -Value

-0.99

0.04

2.45 ***

0.220

0.372

-0.1210.007

0.443 *** 3.62

-0.1060.005

0.279 **

0.293 **

-0.346 *

0.125

0.158

0.453 *

0.004

0.470 *0.415

β

M o de l A5

APPENDIX
Appendix 1. Regression Results in 1995 (dependent variable: profit-sales ratio)ACKNOWLEDGEMENTS
This work was supported by Japan Society for the Promotion of Science (JSPS)
KAKENHI Grant Numbers 18H05694 (Grant-in-Aid for Research Activity Start-up).

REFERENCES
Ansoff, H. I. (1957). Strategies for diversification. Harvard Business Review, 35(5), 113–
124.
Asanuma, B. (1989). Manufacturer-supplier relationships in japan and the concept ofrelation-specific skill. Journal of the Japanese and International Economies, 3(1),1–30.
Bakos, J. Y., & Brynjolfsson, E. (1993). Information technology, incentives and the
optimal number of suppliers. Journal of Management Information Systems, 10(2),37–53.
Chandler, A. D. (1962). Strategy and structure. The MIT Press, Cambridge, MA.
Chen, Y.-M., Yang, D.-H., & Lin, F.-J. (2013). Does technological diversification matterto firm performance? the moderating role of organizational slack. Journal ofBusiness Research, 66(10), 1970–1975.
Clark, K. B., & Fujimoto, T. (1991). Product development performance. Harvard
Business School Press.
Cusumano, M. A., & Takeishi, A. (1991). Supplier relations and management: a surveyof japanese, japanese-transplant, and us auto plants. Strategic Management Journal,
12(8), 563–588.
Dyer, J. H. (1997). Effective interfirm collaboration: how firms minimize transaction
costs and maximize transaction value. Strategic Management Journal, 18(7), 535–

556.
Dyer, J. H., & Chu, W. (2011). The determinants of trust in supplier-automaker relationsin the us, japan, and korea: a retrospective. Journal of International BusinessStudies, 42(1), 28–34.
Dyer, J. H., & Nobeoka, K. (2000). Creating and managing a high-performanceknowledge-sharing network: the toyota case. Strategic Management Journal,21(21), 345–367.
Hashai, N. (2015). Within-industry diversification and firm performance—an s-shaped
hypothesis. Strategic Management Journal, 36, 1378–1400.
Kim, Y. H. (2017). The effects of major customer networks on supplier profitability.
Journal of Supply Chain Management, 53(1), 26–40.
Konno, Y. (2017). Impact of “product scope” and “customer scope.” Annals of Business
Administrative Science, 16(1), 15–28.
Li, S. X., & Greenwood, R. (2004). The effect of within-industry diversification on firm
performance: synergy creation, multi-market contact and market structuration.
Strategic Management Journal, 25(12), 1131–1153.
Markides, C. C. (1995). Diversification, restructuring and economic performance.
Strategic Management Journal, 16(2), 101–118.
Martin, X., Mitchell, W., & Swaminathan, A. (1995). Recreating and extending japanese
automobile buyer-supplier links in north america. Strategic Management Journal,
16(8), 589–619.
Miller, D. J. (2006). Technological diversity, related diversification, and firm
performance. Strategic Management Journal, 27(7), 601–619.
Min, J., & Mitsuhashi, H. (2016). Sources of transfer problems in within-industry
diversification. Industrial and Corporate Change, 25(4), 591–609.
Min, S., & Song, W. (2017). Customer scope and supplier performance: the japanese
automotive industry. Annals of Business Administrative Science, 16(4), 165–176.
Nishiguchi, T. (1994). Strategic industrial sourcing: The Japanese advantage. Oxford
University Press.

Nobeoka, K., & Cusumano, M. A. (1997). Multiproduct strategy and sales growth: thebenefits of rapid design transfer in new product development. Strategic
Management Journal, 18(3), 169–186.
Nobeoka, K., Dyer, J. H., & Madhok, A. (2002). The influence of customer scope on
supplier learning and performance in the japanese automobile industry. Journal ofInternational Business Studies, 33(4), 717–736.
Park, K., & Jang, S. (2013). Effects of within-industry diversification and related
diversification strategies on firm performance. International Journal of Hospitality
Management, 34, 51–60.
Rumelt, R. P. (1982). Diversification strategy and profitability. Strategic Management
Journal, 3(4), 359–369.
Sako, M., & Helper, S. (1998). Determinants of trust in supplier relations: evidence fromthe automotive industry in japan and the united states. Journal of Economic
Behavior & Organization, 34(3), 387–417.
Stern, I., & Henderson, A. D. (2004). Within-business diversification in technologyintensive industries. Strategic Management Journal, 25(5), 487–505.
Suzuki, J., & Kodama, F. (2004). Technological diversity of persistent innovators injapan: two case studies of large japanese firms. Research Policy, 33(3), 531–549.
Tanriverdi, H., & Lee, C. H. (2008). Within-industry diversification and firm
performance in the presence of network externalities: evidence from the software
industry. Academy of Management Journal, 51(2), 381–397.
von Hippel, E. (1977). Dominant role of the user in semiconductor and electronic
subassembly process innovation. IEEE Transactions on Engineering Management,
EM-24(2), 60–71.
von Hippel, E. (1978). Successful industrial products from customer ideas. Journal ofMarketing, 42(1), 39–49.
von Hippel, E. (1988). The sources of innovation. New York: Oxford University Press.
Wu, M., Chang, Y., & Weng, Y. (2009). Effects of partner characteristic, partnership
quality, and partnership closeness on cooperative performance: A study of supply

chains in high-tech industry. Management Review: An International Journal, 4(2),29–57.
Zahavi, T., & Lavie, D. (2013). Intra-industry diversification and firm performance.
Strategic Management Journal, 34(8), 978–998.