اثرات ساختار شبکه، ذخیره دانش و ظرفیت جذب بر عملکرد نوآورانۀ شرکت‌های دانش‌بنیان
محورهای موضوعی : عمومى
مرتضی اکبری
1
,
صاحب ایمانی
2
,
رویا محمودی
3
,
هدی عابدی
4
,
هادی طلوع اصل
5
1 -
2 - مدیریت بازرگانی، واحد بین الملل خرمشهر، خلیج فارس، دانشگاه آزاد اسلامی خرمشهر، ایران
3 - دانشکده کارآفرینی دانشگاه تهران
4 - دانشکده کارآفرینی دانشگاه تهران
5 - دانشکده کارآفرینی دانشگاه تهران
کلید واژه: ظرفیت جذب, ذخیرة دانش, ساختار شبکه, عملکرد نوآورانه,
چکیده مقاله :
مقاله حاضر با تکیه بر اهمیت ارتقا پیوستۀ عملکرد نوآورانۀ سازمانها، در پوشش دادن به تحقیقاتی که به دنبال شناسایی پیشایندهای عملکرد نوآورانه شرکتها هستند، سهیم است. از این منظر، پژوهش حاضر با هدف بررسی اثرات ساختار شبکه، ذخیره دانش و ظرفیت جذب بر عملکرد نوآورانه سازمان در جامعه آماری به تعداد 200 شرکت انتخابی صورت گرفته است که با استفاده از فرمول حجم نمونه کوکران، 132 شرکت دانش بنیان مستقر در شهر تهران از طریق روش نمونه گیری ساده به عنوان نمونماری انتخاب گردید. در پژوهش حاضر، به منظور جمع آوری داده ها از پرسشنامه های استاندارد عملکرد نوآورانه با 10 سوال، ظرفیت جذب با 8 سوال، ساختار شبکه با 4 سوال و ذخیره دانش نیز با 7 سوال بر حسب طیف پنج درجه ای لیکرت استفاده شد. روایی هر دو پرسشنامه به صورت محتوایی و سازه تأیید شد. ضریب پایایی نیز از طریق ضریب آلفای کرونباخ و پایایی ترکیبی برآورد گردید. تجزیه و تحلیل اطلاعات با استفاده از روش مدل‌سازی معادلات ساختاری (SEM) و نرمافزار Smart-PLS 2.0 صورت پذیرفت. نتایج حاکی از آن است که ساختار شبکه، ذخیره دانش و ظرفیت جذب بر عملکرد نوآورانه مؤثرند. همچنین، ظرفیت جذب نقش میانجیگری جزیی و میانجیگری کلی را به ترتیب در رابطه بین ذخیره دانش با عملکرد نوآورانه و ساختار شبکه با عملکرد نوآورانه ایفا میکند. ضمن اینکه ظرفیت جذب با ضریب مسیر 0.48 بیشترین سهم و ساختار شبکه نیز کمترین سهم را در مدل پژوهش، در تبیین عملکرد نوآورانه ایفا میکنند.
The innovative performance of companies has been studied quite extensively and for a long period of time. The aim of this study was to investigate the effects of network structure, knowledge stock and absorptive capacity on innovative performance of Tehran knowledge- based companies. About 132 companies were selected as the sample in Tehran province, Iran. In order to collect data, standard questionnaires of innovative performance with 10 questions, absorption capacity with 8 questions, network structure with 4 questions, and knowledge stock were also used with 7 questions. In all items were measured using a five-point Likert scale ranging from 1 (totally disagree) to 5 (totally agree). Data collected through a questionnaire which its validity confirmed by experts and its reliability was confirmed by Cronbach's alpha coefficient. Data were analyzed using structural equation modeling (SEM) software Smart- PLS 2.0. The results showed that the network structure, knowledge stock and absorptive capacity effect on performance knowledge-based companies. Also, the absorptive capacity have had partial and complete (perfect) mediating role on the relationship between knowledge stock with innovative performance and network structure with innovative performance. In addition, the absorptive capacity (0.48) has the largest and network structure has the lowest rank in explaining performance of innovative companies.
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