دانلود رایگان مقاله پارک علم و فناوری و همکاری برای نوآوری: شواهد تجربی از اسپانیا

عنوان فارسی
پارک علم و فناوری و همکاری برای نوآوری: شواهد تجربی از اسپانیا
عنوان انگلیسی
Science and Technology Parks and cooperation for innovation: Empirical evidence from Spain
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
11
سال انتشار
2016
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
کد محصول
E4936
رشته های مرتبط با این مقاله
مدیریت
گرایش های مرتبط با این مقاله
مدیریت فناوری اطلاعات و مدیریت تکنولوژی
مجله
سیاست تحقیق - Research Policy
دانشگاه
آزمایشگاه تجزیه و تحلیل و ارزیابی تغییرات فنی، دانشگاه مادرید، اسپانیا
کلمات کلیدی
پارک علم و فناوری، همکاری، نوآوری، اثر، آگلومرها
چکیده

abstract


Science and Technology Parks (STPs) are one of the most important innovation policy initiatives. Previous studies show that location in a park promotes cooperation for innovation, but do not investigate whether this cooperation produces better results. We extend this literature by analyzing the effect of location on an STP on the results of cooperation for innovation and the mechanism facilitating this effect. We rely on a much larger sample of firms and STPs than previous studies, and, where necessary, accountfor selection bias and endogeneity. The results show that location in an STP increases the likelihood of cooperation for innovation, and the intangible benefits of cooperation with the main innovation partner, due mainly to a more diverse relationship.

نتیجه گیری

6. Conclusions


This paper analyzed the effect of location in an STP on the likelihood and results of cooperation for innovation and explored the mechanism of this influence. Previous studies analyze the influence of STPs on the likelihood of cooperation, using small samples of firms and STPs, and usually ignoring endogeneity and sample selection issues. The present study contributes by analyzing the influence of STPs on both the likelihood of cooperation and on the results of cooperation. We use a very large sample of firms located in several different STPs; the characteristics of the data allow us to use a large set of already proven covariates and, where necessary, to account for endogeneity and sample selection issues.


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