Estimation method

5.2 EMPIRICAL STUDY ON THE DETERMINANTS OF EXTERNAL KNOWLEDGE SEARCH STRATEGY

5.2.1 Econometric specification

In order to respond to the first question of our investigation, that is, the determinants of external knowledge search strategy, we will take into consideration variables making reference to the firm’s environmental context, dynamism (Dyn) and competitiveness (Com), and to the internal firm’s dimensions, that is, technological resources (TR), decentralization of decision-making (Dec) and formalization of organizational processes (For), plus the variables related to size, age and group. These variables will explain external knowledge search strategy (EKSS), which will represent our dependent variable. Figure 5.1 shows the econometric specification.

Figure 5.1 Econometric specification. Determinants of external knowledge search strategy

𝐸𝐾𝑆𝑆_𝑖^𝑑 = 𝛽₀ + 𝛽₁𝐷𝑦𝑛_𝑖 + 𝛽₂𝐶𝑜𝑚_𝑖 + 𝛽₃𝑇𝑅_𝑖 + 𝛽₄𝐷𝑒𝑐_𝑖 + 𝛽₅𝐹𝑜𝑟_𝑖 + 𝛽₆𝑆𝑖𝑧𝑒_𝑖 + 𝛽₇𝐴𝑔𝑒_𝑖 + 𝛽₈𝐺𝑟𝑜𝑢𝑝_𝑖 + 𝜀_𝑖^𝑑

Source: Authors’ elaboration

Taking into consideration the variables exposed above, in this specific analysis the initial sample of 105 firms was reduced to 101 firms due to the fact that some of the cases in these variables were missing.

5.2.2 Estimation method

Our dependent variable takes mutually exclusive and unordered values, thus the multinomial logit distribution is most appropriate to investigate our hypotheses. In addition to the low collinearity found between the

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variables in Chapter 4, we calculated variance inflation factors and the maximum value was 1.56, which is below the rule-of-thumb of 10 (Neter et al., 1996). These indicators show that there are no multicollinearity problems (See Annex IV).

Moreover, this distribution assumes the independence of irrelevant alternatives (IIA) is satisfied (Hausman and McFadden, 1984). This means that adding or deleting outcome categories has no effect on the odds of the remaining outcomes. To ensure IIA we compare the multinomial logit and probit models. Both models produce similar estimates and goodness of fit measures (For complete analyses of the IIA assumption see Annex II).

5.2.3 Results

Tables 5.1 and 5.2 present the multinomial logit regressions. Table 5.1 shows the results calculated with category 1 as the reference category, that is, the probability of not pursuing external search; Table 5.2 takes category 2 as the reference that is the probability of pursuing exploitative search.

The former indicates the extent to which the independent variables matters for external search; the latter reflects the extent to which the variables predict more or less exploratory search compared to exploitative search. Annex III, shows the marginal effects derived from estimation of the multinomial logit in Tables 5.1 and 5.2. These are calculated holding all other variables at their means (Long, 1997). The results for each variable of interest are detailed below.

In line with our central thesis the results show that structure matters for external knowledge search and the strategy pursued. Although formalization is not significant (which rejects hypothesis 1), decentralization has a positive and significant impact on exploratory oriented search, taking both categories as the reference. According to the theory, structures characterized by decentralized processes explain external knowledge sourcing (see Table 5.1). More importantly, our results

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also show that decentralization is a determinant of an exploratory rather than an exploitative strategy (see Table 5.2). Marginal effects corroborate these results, showing a change from negative to positive values as the search becomes less exploitative and more exploratory (see Annex III). In the specific case of category 4 the results for marginal effects show that a unit increase in decentralization increases the predicted probability of exploration by 23%. This supports hypothesis 2.

A dynamic environment results in negative and significant coefficients for exploitative and balanced searches compared to no external search, suggesting a higher probability of internal search (see Table 5.1).

Moreover, a dynamic environment seems not to determine the type of external search strategy pursued (See Table 5.2). This is corroborated by the results for marginal effects (see Annex III), and rejects hypothesis 3.

A competitive environment results in negative and significant coefficients of exploratory search, when considering both categories as the reference.

In line with the theory, competition has negative effects for exploratory search compared to the probability of no external search (see Table 5.1). In relation to the results for the probability of pursuing an exploratory strategy rather than an exploitative strategy we find a negative coefficient (see Table 5.2). This indicates that in highly competitive environments exploratory search is less likely. Marginal effects (see Annex III) corroborate these results and indicate that as competition increases the probability of pursuing a more exploratory search strategy decreases by 39% compared to a more exploitative search strategy. These results support hypothesis 4.

Technological resources have an impact on the search for external knowledge, which is in line with the literature on the role of R&D for accessing external knowledge (see Table 5.1). Specifically, results show positive and significant coefficients of exploitation search. In the case of

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R&D role in the choice between an exploratory or exploitative strategy results are not significant (see Table 5.2). However, results tend to indicate that R&D explains exploitative searches rather than exploratory oriented ones. Thus, hypothesis 5 is not accepted.

In relation to the control variables the results show the following. The firm’s size is positively associated with the probability of accessing external knowledge. This result is in line with predictions suggesting that large firms count with more resources and thus, greater chances to access external sources of knowledge. Firm’s age also tends to be associated to greater external search because of added benefits in terms of experience.

Lastly, belonging to a group also tends to be positive for external knowledge sourcing. In this sense, these firms have more opportunities to access additional resources.

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Table 5.1 Multinomial logit regression, explaining the use of external knowledge sources in detriment of internal sources of knowledge

Variable Category of reference(1) Category(2) Category(3) Category(4)

Estimate p-value Estimate p-value Estimate p-value Estimate p-value

Formalization of organizational

processes - - 0.468 0.525 1.240 0.115 -0.259 0.718

Decentralization of decision making - - 0.299 0.577 0.854 0.128 1.308*** 0.009

Dynamic environment - - -1.733* 0.073 -2.153** 0.039 -1.135 0.239

Competitive environment - - -0.328 0.742 -0.517 0.610 -1.919** 0.039

Technological resources - - 0.152** 0.037 0.110 0.118 0.092 0.228

Size - - 2.687*** 0.001 1.542** 0.050 2.780*** 0.000

Group - - -0.449 0.717 1.627 0.123 1.115 0.279

Age - - 0.048 0.173 0.061* 0.093 0.056 0.105

Intercept - - -7.930 0.156 -6.007 0.311 -4.546 0.389

*p<0,10 **p<0,05 ***p<0,01 N=101

Log-likelihood: -90.353071 χ2 :0.0000

Pseudo R²: 0.3107

Source: Authors’ elaboration

111 Table 5.2 Multinomial logit regression, explaining the use of more balanced and exploratory strategies vs. exploitative

Variable Category (1) Category of reference (2) Category (3) Category(4)

Estimate p-value Estimate p-value Estimate p-value Estimate p-value

Formalization of organizational processes -0.468 0.525 - - 0.772 0.250 -0.727 0.192

Decentralization of decision making -0.299 0.577 - - 0.556 0.285 1.009** 0.020

Dynamic environment 1.733* 0.073 - - -0.419 0.604 0.599 0.383

Competitive environment 0.328 0.742 - - -0.188 0.842 -1.591** 0.047

Technological resources -0.152** 0.037 - - -0.042 0.415 -0.061 0.126

Size -2.687*** 0.001 - - -1.145** 0.058 0.093 0.858

Group 0.449 0.717 - - 2.076** 0.053 1.565 0.102

Age -0.048 0.173 - - 0.013 0.626 0.008 0.729

Intercept 7.930 0.156 - - 1.923 0.695 3.384 0.393

*p<0,10 **p<0,05 ***p<0,01 N=101

Log-likelihood: -90.353071 χ2:0.0000

Pseudo R²: 0.3107

Source: Authors’ elaboration

112 Table 5.3 Summary of hypotheses and results on the determinants of external search strategy

Hypothesis: Probability of pursuing an exploratory oriented external search strategy Results H1 Formalization of organizational processes exerts a negative effect

H2 Decentralization of decision-making exerts a positive effect H3 Environmental dynamism exerts a positive effect

H4 Environmental competitiveness exerts a negative effect H5 Technological resources exerts a positive effect

Source: Authors' elaboration

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5.3 EMPIRICAL STUDY ON THE EFFECTS OF EXTERNAL