انتقال دانش بین کسب و کار و دانشگاه
ترجمه نشده

انتقال دانش بین کسب و کار و دانشگاه

عنوان فارسی مقاله: کاربرد فناوری کلان داده در فرآیند انتقال دانش بین کسب و کار و دانشگاه
عنوان انگلیسی مقاله: Application of Big Data Technology in Knowledge Transfer Process between Business and Academia
مجله/کنفرانس: پروسیدیای مالی و اقتصاد – Procedia Economics and Finance
رشته های تحصیلی مرتبط: مدیریت
گرایش های تحصیلی مرتبط: مدیریت دانش
کلمات کلیدی فارسی: کلان داده، انتقال دانش، مشارکت، انتقال فناوری
کلمات کلیدی انگلیسی: Big Data, knowledge transfer, cooperation, technology transfer
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
شناسه دیجیتال (DOI): https://doi.org/10.1016/S2212-5671(16)30305-7
دانشگاه: Faculty of Management Science and Informatics, University of Zilina, Univerzitna 8215/1, 010 26 Zilina, Slovakia
صفحات مقاله انگلیسی: 7
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2016
شناسه ISSN: 2212-5671
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E13808
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (انگلیسی)

Abstract

1-Introduction

2-BigData

3-Knowledge Transfer

4-Discussion

Acknowledgements

References

بخشی از مقاله (انگلیسی)

Abstract

New data and information are being constantly produced as a result of technological development. The data and information are used by many companies as a source for creating knowledge in their sphere of business. The important part of the knowledge creating process is both adequate amount of relevant data, and an ability to transform this data to information. Various technologies are helpful, such as Big Data technology. Mostly big companies with sufficiency of money dispose of Big Data by reason of its complexity and significant expenses in terms of maintenance, specialized staff, technology infrastructure etc. Constantly changing demands of customers together with a strong competitive environment is forcing companies to innovate, for instance by designing new products, improving internal processes, or implementing new technologies. By obtaining such innovation is very helpful cooperation with research and development (R&D) institutions from academia. Universities are in a large extent dealing with R&D activities, on which companies don’t have capacities, but the results from these R&D activities are for companies interesting and mostly usable in practice. The purpose of this paper is following findings obtained from analysis of the knowledge transfer and Big Data theory finding and describing the possibility of connecting these two areas in practice. The paper is focusing on knowledge transfer creation within cooperation of companies and universities through access for university to company’s database during contract research with usage of Big Data. Knowledge of cooperating subjects is filling up, deepening and verifying through united access to collecting, storing, processing and interpreting available data, whereby emerging knowledge transfer between cooperating subjects.

Introduction

The information context of the modern organization is rapidly evolving in the face of intense global competition. Decision making of managers is on the present largely depend on timely, accessible and relevant information within the context of solved problem. The most comprehensive information represent knowledge for managers. The knowledge can be obtained either from own resources of the organization or from the available data. Continuous development of information and communication technologies gave rise to new systems and platforms that are generating plenty of data every second. The data can be potentially carrier of important information necessary for the creation of subsequent knowledge related to the problem. Thanks to the openness of the Internet and its interconnection with almost all devices both at consumers or businesses, unstructured data are gaining ground. The unstructured data are such data that do not have a specific structure, and which are not stored in the relational database model. Large amounts of unstructured data have different characteristics from data generated by the own systems of organization or academia, and their database structures (e.g. data warehousing) and their tools for data management cannot efficiently process and analyze these volumes in terms of reasonable time and cost perspective (Dolak , 2011).