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Several inherent limitations should be considered regarding the results of this study. First, supplier innovation was measured using subjective measurements, and focused only on radical innovation. Future studies should also include objective measures of supplier innovation, such as patents or number of new products development. In addition, previous studies have shown that different conceptualizations may have various antecedents and outcomes. Hence, future research could examine other innovation types, such as incremental versus radical innovation or

technological versus administrative innovation, and identify their antecedents and performance outcomes in the supply chain. For example, Jansen et al. (2006) developed and tested a model of antecedents, moderators, and performance outcomes of exploratory and exploitative innovation in the intra-organizational context.

In addition, this study tested only the moderating effects of dependence and supplier design responsibility on the drivers and outcomes of innovation. Future research should explore other moderators, such as the cultural differences among international exchange partners engaged in supply chain relationships (Rosenbusch, Brinckmann, and Bausch 2011).

For methodology, this study relies on data collected from Taiwanese OEM suppliers.

Because of the limited scope of this sample, generalizing our findings to other international customer–supplier relationships is difficult, especially in other industrial contexts. Future research should consider obtaining data from other industries from both the customers and their suppliers to cross-check the validity of our proposed model. This may prove challenging because

the identity of customers is sensitive in these types of international relationships. Overcoming these obstacles would contribute to the thorough understanding of innovation generation in glboal supply chains. Another limitation of this study is its cross-sectional design. Although the results of this study reveal the drivers and performance outcomes of supplier innovation

generation, their causality can only be implied. Future studies could overcome this limitation by using experiments or longitudinal data collection, although such studies might only be possible for relatively short periods.

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Table 1: Measures and Composite Reliabilities Construct (Composite Reliability: CR)

Item (Loading)

Social Capital (CR = .81) (1 = strongly disagree; 7 = strongly agree)

We expect the relationship with our major international customer to continue a long time. (.81)  Our key customer is trustworthy. (.60) 

The goals and objectives of both parties in the relationship with our international customers are compatible. (.74) 

Our relationship with our major international customer is a long-term alliance. (.85)  

Proactive Customer Orientation (CR = .89) (1 = strongly disagree; 7 = strongly agree) We excel at anticipating changes in what our key international customer needs before they even

ask. (.78)

We are able to successfully anticipate changes in our international customers’ needs. (.80)

We are able to present new solutions to our international customer that they actually need but did not think to ask about. (.92)

We are always looking for clues that might reveal changes in what our international customers value beyond what they currently ask of us. (.76)

Joint Learning Capability (CR = .92)

Our relationship with key international customer has established strong capacity and organizational procedures to develop new knowledge sets. (.84)

Our relationship with key international customer is very good at developing rules, directives, formulas, and expert systems to create new knowledge base for our relationship. (.92)

Our relationship with key international customer has developed superior capability to make appropriate changes of organizational structure to incorporate and distribute the developed knowledge and skills.

(.89)

Relationship-based Radical Innovation (CR = .96) (1 = strongly disagree; 7 = strongly agree) Our relationship with this international customer has helped increase sales from radical new products

introduced by our firm in the last three years. (.92)

Our relationship with this international customer has helped our company frequently introduce radical new products into new markets in the last three years. (.96)

Compared with our major competitors, our relationship with this international customer has helped introduce more radical new products in the last three years. (.96)

Supplier Dependence (CR = .88) (1 = strongly disagree; 7 = strongly agree) Our company is strongly dependent on this key international customer. (.79)

It would be very difficult for our company to replace sales and profits realized from this international customer. (.92)

Our international customer would be costly to replace. (.80)  _________________________

Fit Indexes:

Chi-Square = 154.807 on 109 d.f.

TLI = .977 CFI = .982 SRMR = .061

________________________________________________________________________

Table 2: Intercorrelations, Shared Variances, and Average Variances Extracted

F1 F2 F3 F4 F5 F6 F7

Social Capital (F1) .52 .21 .34 .07 .22 .00 .00 Customer Orientation (F2) .46 .67 .36 .18 .10 .00 .00 Joint Learning (F3) .58 .60 .80 .25 .10 .00 .00 Rel.-based Innovation (F4) .27 .42 .50 .90 .07 .02 .01 Supplier Dependence (F5) .47 .31 .31 .27 .70 .00 .00 R&D Scale (F6) .06 .05 .03 .15 -.03 -- .00 Initial Firm Size* (F7) -.03 -.01 -.06 -.08 .05 .00 --

Note: Correlations are included in the lower triangle of the matrix and shared variances are included in the upper triangle of the matrix. Average variance

extracted for each construct is reported in the diagonal.

* = Marker Variable

Figure 1: Conceptual Framework

Figure 2: Results of Mediation Tests

* p < .05

** p < .01

Note: Control variable not depicted

Table 3: Results of Multi-group Analyses

Relationship-based Innovation

ODM-Yes ODM-No

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