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Testing the fit of the hypothesized model and finding no signs of misspecification allowed testing of the hypotheses made in the hypothesized model. Table 5-30 presents the standardized maximum likelihood parameter estimates and their statistical significance levels for the hypothesized path model. In the hypothesized model, 17 relationships are tested. Sixteen out of seventeen hypotheses received at least weak support from the empirical data.

Table 5-30 Structural equation modeling tests of hypotheses

Hypothesis Description of Path Coefficient

Model on the value-added mechanisms

Resource and knowledge acquisition model

H4 Complementarities
(+) Social interaction .42 ***

H5a Complementarities
(+) Acquisition of

production-related resources .19 * H5b Complementarities
(+) Acquisition of

distribution-related resources .30 ***

H6a Social interaction
(+) Acquisition of

production-related resources .34 ***

H6b Social interaction
(+) Acquisition of

distribution-related resources .42 ***

H7 Social interaction
(+) Knowledge acquisition .37 ***

H9a Acquisition of production-related resources

(+) Knowledge acquisition

.16 * H9b Acquisition of

distribution-related resources

(+) Knowledge acquisition

.20 *

Model on the Value-added Mechanisms

The first set of hypotheses predicts the mechanisms through which corporate venture capital investments may add value to portfolio companies. The first hypothesis (Hypothesis 1) predicts the influences of two different types of resource acquisition.

Hypothesis 1a, which states that acquisition of production-related resources is positively related to value-added, received strong support from the data (β = .22, p ≤ .01).

Hypothesis 1b states that acquisition of distribution-related resources is positively related to value-added. In this data acquisition of distribution-related resources was not significantly related to value-added (β = .02, n.s.). I will discuss potential reasons for this surprising result in the discussion of the results in Chapter 6.1.1. Hypothesis 2 states that that knowledge acquisition is positively related to value-added. This hypothesis received strong support from the data (β = .52, p ≤ .001). The last hypothesis in this set of hypotheses (Hypothesis 3) states that endorsement is positively related to value-added. This hypothesis also received strong support from the data (β = .21, p ≤ .01). Overall, all the three main mechanisms of value-added (knowledge acquisition,

resource acquisition, and endorsement) were positively related to the perceived value-added.

Resource and Knowledge Acquisition Model

The second set of hypotheses concerns the factors affecting resource and knowledge acquisition by portfolio companies from their corporate investors. The first hypothesis in this set of hypotheses (Hypothesis 4) states that complementarities between the venture and the corporate investor is positively related to social interaction. This hypothesis received strong support from the data (β = .42, p ≤ .001).

The next four hypotheses predict the factors influencing acquisition of two types of resources. Hypothesis 5a states that complementarities are positively related to acquisition of production-related resources. This hypothesis received strong support from the data (β = .19, p ≤ .05). Similarly, Hypothesis 5b states that complementarities are positively related to acquisition of distribution-related resources. Also this hypothesis received strong support from the data (β = .30, p ≤ .001). Hypothesis 6a states that social interaction is positively related to acquisition of production-related resources. This hypothesis received strong support from the data (β = .34, p ≤ .001).

Finally, Hypothesis 6b states that social interaction is positively related to acquisition of distribution-related resources. Also this hypothesis received strong support from the data (β = .42, p ≤ .001).

The next three hypotheses predict the roles of factors influencing knowledge acquisition. Hypothesis 7 states that social interaction is positively related to knowledge acquisition. This hypothesis received strong support from the data (β = .37, p ≤ .001).

Predicting the role of resource acquisition influencing knowledge acquisition, Hypothesis 9a states that acquisition of production-related resources is positively related to knowledge acquisition. This hypothesis received strong support from the data (β = .16, p ≤ .05). Similarly, Hypothesis 8b states that acquisition of distribution-related resources is positively related to knowledge acquisition. This hypothesis also received strong support from the data (β = .20, p ≤ .05).

Endorsement Model

The third set of hypotheses concerns the factors affecting endorsement benefits received by portfolio companies from their association with their corporate investors.

Predicting the role of corporate investor characteristics, Hypothesis 10 states that investor prominence is positively related to endorsement. This hypothesis received strong support from the data (β = .21, p ≤ .01). Predicting the role of strength of tie influencing the credibility of the endorsement, Hypothesis 11a states that acquisition of production-related resources is positively related to endorsement. This hypothesis received strong support from the data (β = .24, p ≤ .01). Similarly, Hypothesis 11b states that acquisition of distribution-related resources is positively related to endorsement. Also this hypothesis received strong support from the data (β = .31, p ≤

value of the endorsement, Hypothesis 13 states that venture age is negatively related to the endorsement. This hypothesis received weak support from the data (β = -.13, p ≤ .10). Predicting the role of customer risks influencing the value of endorsements, Hypothesis 14 states that customer switching costs is positively related to endorsement.

This hypothesis received strong support from the data (β = .31, p ≤ .001).

Mediation Effects

Hypothesis 8 predicts that social interaction mediates the influence of complementarities on knowledge acquisition. I tested this hypothesis by first examining the results of the nested model tests and then analyzing the specific relationships between the constructs. In the nested model tests (Table 5-29), the hypothesized mediation model (Model 2) provided a better fit than the alternative partial mediation model in which a direct path was added to the hypothesized model between complementarities and knowledge acquisition (Model 3). This result provides evidence in support of a mediating role of social interaction in mediating the effects of complementarities. To demonstrate mediation for specific relationships, I followed the four steps discussed in the methods section for establishing mediation (Chapter 4.3.3).

The statistical results are presented in Table 5-31. First, the independent variable (complementarities) was shown to be related to the mediator (social interaction).

Second, the mediator was shown to be related to the dependent variable (knowledge acquisition). Third, the relationship between the independent variable (complementarities) and the dependent variable (knowledge acquisition) was shown to be insignificant when the mediator is accounted for. Thus, it appears that social interaction mediates the relationship between complementarities and knowledge acquisition.

Table 5-31 Test of Hypothesis 8: social interaction mediating complementarity benefits to knowledge acquisition

Path description Model 2

Hypothesized model

Model 3

Direct path added between complementarities and

knowledge acquisition Complementarities
(+) Social interaction .42 *** .42 ***

Social interaction
(+) Knowledge acquisition .37 *** .37 ***

Complementarities
(+) Knowledge acquisition .01

*** p ≤ .001, ** p ≤ .01, * p ≤ .05, + p ≤ .10, hypothesized paths one-tailed tests

Hypothesis 12 predicts that resource acquisition mediates the influence of complementarities on endorsement. I tested also this hypothesis by first examining the results of the nested model tests and thereafter analyzing the specific relationships between the constructs. In the nested model tests (Table 5-29), the hypothesized mediation model (Model 2) provided a better fit than the alternative partial mediation model in which a direct path was added to the hypothesized model between complementarities and endorsement (Model 4). This result provides evidence in support of a mediating role of resource acquisition in mediating the effects of

complementarities. To demonstrate mediation for specific relationships, I followed again the same four steps discussed earlier. The results are presented in Table 5-32.

First, the independent variable (complementarities) was shown to be related to the mediators (both types of resource acquisition). Second, the mediators were shown to be related to the dependent variable (endorsement). Third, the relationship between the independent variable (complementarities) and the dependent variable (endorsement) was shown to be insignificant when the mediators are accounted for. Thus, it appears that social interaction mediates the relationship between complementarities and knowledge acquisition.

Table 5-32 Test of Hypotheses 12a and 12b: resource acquisition mediating complementarity benefits to endorsement

Path description Model 2

Hypothesized model

Model 4

Direct path added between complementarities and

endorsement Complementarities
(+) Acquisition of

production-related resources

.19 * .19 *

Complementarities
(+) Acquisition of distribution-related resources

.30 *** .30 ***

Acquisition of production-related resources

(+) Endorsement .24 ** .23 **

Acquisition of distribution-related resources

(+) Endorsement .31 *** .27 **

Complementarities
(+) Endorsement .11

*** p ≤ .001, ** p ≤ .01, * p ≤ .05, + p ≤ .10, hypothesized paths one-tailed tests

Table 5-33 provides further evidence of the critical role of complementarities. In this table, the indirect effects of complementarities on all endogenous variables are estimated on the basis of the structural equation model results for the hypothesized model. The coefficients are relatively high (above .14) for all endogenous variables.

The indirect effects of complementarities on knowledge acquisition were high (.31) as was predicted in Hypothesis 8. Also indirect effects of complementarities on endorsement are quite high (.29) as predicted in Hypothesis 12.

Table 5-33 The critical role of complementarities: indirect effects of complementarities on endogenous variables

Path description Model 2

Hypothesized model Complementarities
(+) Acquisition of production-related resources .14 Complementarities
(+) Acquisition of distribution-related resources .20

Complementarities
(+) Knowledge acquisition .30

Complementarities
(+) Endorsement .19

Complementarities
(+) Value-added .28

Standardized estimates of indirect effects