دانلود رایگان مقاله متغیرهای موفقیت در پارک های علم و فناوری

عنوان فارسی
متغیرهای موفقیت در پارک های علم و فناوری
عنوان انگلیسی
Success variables in science and technology parks
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
6
سال انتشار
2016
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
کد محصول
E4302
رشته های مرتبط با این مقاله
مدیریت
مجله
مجله تحقیقات بازاریابی - Journal of Business Research
دانشگاه
دانشکده مهندسی، دانشگاه سویا، سویل، اسپانیا
کلمات کلیدی
پارک علم و فناوری، نوآوری استراتژیک، خوشه، تجزیه و تحلیل تطبیقی کیفی مجموعه ای فازی
چکیده

abstract


Science and technology parks are of great importance in the business context of the region in which they carry out their activity. They are the main mechanisms of public and private initiatives for the promotion of research, development and innovation, and technology transfer. The main goal of this type of institutions is not a purely economic benefit, but also social and cultural, which makes them an appropriate investment from the public institutions' viewpoint. They promote the creation of companies and agreements with universities and research centers, generate employment, and attract technology-based companies. Therefore, they require in-detail assessment to understand their operation to generate action plans and models that new parks or those who are still in their initial growth phase may follow. This study establishes a series of models—or operation strategies—to identify the strategies of successful parks; that is, parks that have overcome the initial stage and handle high revenue volumes, high rates of land occupation, and a large number of employees.

نتیجه گیری

5. Discussion


During the period between the creation of a STP until that STP reaches a critical number of hosted companies that grant financial independence, the advancement and growth of the park are slow and complex. To overcome this situation, thus becoming a sustainable success case and a model for other parks, the manager should decide which strategy to follow, which is a complex task. The QCA method allows defining groups of parks, identifying (a) the variables that positively influence their behavior, (b) variables that have a lower value than the average value—which therefore have no relevant importance in the final configuration—and (c) non-existent variables, which do not appear in the model.


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