کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1032724 | 943258 | 2013 | 13 صفحه PDF | دانلود رایگان |
کلید واژه ها
1. مقدمه
2. تحقیقات گذشته
3. مدل نظریه زنجیره ارزش R&D
3.1. ویژگی متغیرهای ورودی و خروجی
شکل. 1. مفهوم اصلی از زنجیره ارزش R & D
3.2 ویژگی های مدل DEA زنجیره ارزش R&D
4. نتایج تجربی و تحلیل ها
4.1. منابع داده
4.2. تحلیل سودآوری و اثربخشی قابلیت عرضه به بازار
جدول 1. آمارهای توصیفی 65 شرکت برتر با فناوری بالا در سال های 2007-2006
جدول 2. خلاصه آماری امتیازات اثربخشی 65 شرکت برتر با فناوری بالا
4.3. خروجی های واسطه و ماتریس تصمیم گیری تلاش های R&D
جدول 3. آزمون کروسکال والیس برای سال های 2006 و 2007
شکل. 2. ماتریس تصمیم گیری تلاش های R&D
4.3.1. ربع اول
4.3.2. ربع دوم
4.3.3. ربع سوم
4.3.4. ربع چهارم
4.4 تحلیل های حساسیت
5. نتیجه گیری و کاربردها
5.1. کاربردهای مدیریتی و سیاستی
5.2 محدودیت ها و تحقیقات آتی
ضمیمه A. جهت اثربخشی اولیه ارزش ها از سال 2006 تا 2007، بنگرید به جدول A1
ضمیمه B. جهت یافته های اندازه های واسطه مناسب تحت مدل DEA زنجیره ارزش، بنگرید به جدول B1
جدول A1. امتیاز اثربخشی و رتبه زنجیره ارزش R&D از سال 2006 تا 2007
جدول B1. سطوح مناسب خروجی های واسطه سال 2007
Although prior research has addressed the influence of production activity and research and development (R&D) on productivity, it is not clear whether production and R&D affect the market value of a firm. This study proposes and verifies an R&D value chain framework to explore the relationship among productivity, R&D, and firm market values, as measured by Tobin's q theory. By doing so, we attempt to link new theoretical insights and empirical evidence on the effects of R&D efforts and basic production activities to the market valuations of high-technology firms. The value chain data envelopment analysis approach was proposed to estimate parallel-serial processes of basic operations and R&D efforts. This approach can be used to simultaneously estimate the profitability efficiency and marketability efficiency of high-technology firms. This area has rarely been studied, but it is particularly important for high-technology R&D policies and for further industrial development. Using the R&D value chain perspectives of model innovations and extensions proposed in several previous studies, we examined the appropriate levels of intermediate outputs. Production efficiency and R&D were combined to estimate the appropriate levels of intermediate outputs for high-technology firms. Based on the intermediate output analyses, we developed an R&D efforts decision matrix to explore and identify operational and R&D efficiency for high-technology firms. Our sample firms are displayed on a four-quadrant action grid that provides visual information on current short-term operational efficiency and decision making on long-term R&D strategic positions. The empirical findings from the R&D value chain model can provide information for policymakers and managers and suggest the adoption of various policies that place more emphasis on profitability and marketability strategies.
► We model the value chain DEA to determine intermediate products and outputs.
► We develop R&D efforts decision matrix to assist firm strategic position.
► The intermediate outputs level and relative efficiency were estimated.
► Results highlight the role of long-term R&D and short-term operational efficiency.
► The results have implications for high-tech firm managers and decision makers.
Journal: Omega - Volume 41, Issue 1, January 2013, Pages 143–155