Advances in Spatial Science - Editorial Board Manfred M. Fischer Geoffrey J.D. Hewings Phần 8

Doanh nghiệp đa quốc gia và khả năng hấp thụ của công ty conMặt khác, tất cả các biến khác cho thấy công nghệ bắt nguồn từ nhóm doanh nghiệp đa quốc hoặc công ty con chính nó cho thấy bằng chứng của sự chuyển đổi và khai thác kiến thức thu được vào các nhu cầu cụ thể của các doanh nghiệp đa quốc gia và công ty con.
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Advances in Spatial Science - Editorial Board Manfred M. Fischer Geoffrey J.D. Hewings Phần 812 Multinational Enterprise and Subsidiaries’ Absorptive Capacity 267 On the other hand, all other variables that indicate technology stemming fromeither the MNE group or the subsidiary itself show evidence of the transformationand exploitation of acquired knowledge into particular needs of the MNE and thesubsidiary.3 The model employed for RQ1 is the following: RDLi ¼ b0 þ bj RAC þ bk PAC þ bl ROLE þ bm CV þ ei (12.1)where RDL is the existence of a R&D laboratory, RAC stands for variablesmeasuring realized absorptive capacity, PAC for those measuring potential absorp-tive capacity, ROLE identifies various subsidiary roles assigned by the MNE groupand CV for all control variables taken into consideration. In line with the citedliterature, we use industry’s technology intensity, mode of entry (new company orjoint venture), years of operation and region of origin (whether the MNE originatesfrom the EU, the USA or the Pacific Rim), as control variables. For RQ2, the dependent variable is the ordered answer (from 4 to 1) of question7c (R&D carried out by own laboratory), as the source of technology based on theformulation discussed above. In particular, this RQ considers the second stage inthe developmental process of a subsidiary’s AC, (once it already runs an own R&Dlaboratory), to check for factors affecting the intensity of its RAC. In this model wealso use measures of potential and realized AC that we used in RQ1. However, thefirm has now another element of RAC, namely, the scientific personnel hired toequip the laboratory, thus we also include here the number of scientific personnel asan extra variable of RAC. The equation used for RQ2 is the following: OWNRDi ¼ b0 þ bj RAC þ bk PAC þ bl ROLE þ bm SROLE þ bn ei (12.2)where the dependent variable is OWNRAD (the importance of sourcing the R&Dfrom own R&D lab as indicated in questionnaire response 7c). Once again, RACstands for variables measuring realized absorptive capacity, PAC for those measur-ing potential absorptive capacity, ROLE identifies various subsidiary roles assignedby the MNE group and CV for all control variables taken into consideration. In thisRQ we also include as explanatory variables the roles assigned to the existing R&Dlabs. As control variables, we use industry’s technology intensity, the age of theR&D lab (years of operation)4 and the region of origin. The dependent variable employed for investigating the impact of PAC and RAC ofthe subsidiary is the total turnover.5 In this stage, the R&D laboratory is in operation,3 For a description of variables falling into either of the two categories, see Appendix 1.4 As we examine the intensity of own RAC (own R&D lab), and unlike RQ1, the years of operationof the subsidiary is not relevant, while the age of the R&D lab is.5 A number of performance variables are plausible. Our focus on turnover from sales is in line withthe focus of the resource-based view (RBV), in particular Penrose’s view (see Pitelis 2002, for anextensive discussion).268 C. Kottaridi et al.thus, besides RAC belonging primarily to the MNE group, the subsidiary has furtherenhanced its AC by developing its own research unit hence in addition to variables ofRAC and PAC used above, we hereby include the presence of an R&D laboratory.6 The equation used for RQ3 is the following: PERFi ¼ b0 þ bj RAC þ bk PAC þ bl ROLE þ bn ei (10.3)where PERF stands for performance (the subsidiary’s total turnover) and the othervariables are previously explained.ResultsEach one of the three RQs was estimated by using three independent regressionmodels. The definition of the variables used in the tables below as well as selectedsample correlation matrices showing the strength of association between groups ofvariables may be found in Appendix A. The results of conditional X2 tests thatexamine the lack of independence among pairs of variables of interest are alsoavailable on request. RQ1: Model 1: The impact of AC on the likelihood of establishing an R&D lab –Table 12.1. Our results show that the likelihood of establishing an R&D lab depends on priorPAC of the subsidiary: the higher the dependence of the subsidiary is on R&Dcarried out for it by local scientific institutions, thus the higher is its PAC the higherthe likelihood is of establishing an R&D lab (note that other measures of either PACor RAC do no enter significantly in the equation although it appears that the higherthe dependence of the subsidiary is on existing AC, the lower the likelihood ofestablishing an R&D lab). It follows that PAC measured as the subsidiary’sexposure to external knowledge, seems to enhance AC by inducing subsidiariesto develop their own R&D lab in order to be able to transform acquired knowledgeto their own procedures and technologies adopted to their own needs, in line withthe fourth dimension of Zahra and George (2002). Our results indicate that subsidiaries aiming at developing and producing newproducts (WPM) and subsidiaries aiming at producing and exporting already exist-ing products (SMR) are more likely to develop an R&D laboratory, as compared tosubsidiaries that target the internal (UK) market only (TMR). As regards to the control variables, we find that the longer a subsidiary operatesin a particular location the more likely it is to create its own R&D unit. We also note6 We do not include the number of scientific personnel here, because this belongs to the R&D lab,so by including the existence of the laboratory by definition we account for the scientific personnelengaged in the lab.1 ...