Development of a Distributed Collaborative Research Tool for University-Industry Partnership

Development of a Distributed Collaborative Research Tool for University-Industry Partnership

Samuel O. Oladimeji, Idongesit E. Eteng
Copyright: © 2022 |Pages: 25
DOI: 10.4018/IJeC.304374
OnDemand:
(Individual Articles)
Available
$37.50
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

This research study aims at developing a collaborative research tool using distributed servers to enhance collaborative research among Universities and Industries to promote innovation. The Adaptive Software Development model was employed due to the innovative nature of the study. Requirements were gathered from key stakeholders to determine the system architecture and various models that supported the system development process. The testing procedure demonstrated that three (3) separately located servers representing University A, University B and Industry Players worked together as one unit such that all users could form Research Teams and collaboratively conduct research work on the platform to boost University-Industry partnership for innovation.
Article Preview
Top

Introduction

Due to the strategic role of academia in leading technology creation and transfer, there has been an increase in collaborations between Universities and the Industry (Giones, 2019; Ankrah and AL-Tabbaa, 2015). Research has shown that deploying web-based platforms for collaborative research can significantly support technology creation and transfer activities in academia (Brody, 2017; Eteng and Oladimeji, 2019). This implies that a web-based collaborative research tool will enhance multidisciplinary interaction between lecturers and students, which will translate to increased productivity in research collaboration processes. Distributed computing has transformed the University landscape making collaborative research possible and creating more opportunities for universities to implement systems comprising of new sets of structures that can be accessed through the Internet (Boronenko & Alexandrov, 2009). A distributed computer system has been defined as an assembly of autonomous computing components (van Steen & Tanenbaum, 2016).

University-Industry Partnership (UIP) has become a critical component of efficient innovation systems (World Bank, 2013). Subsequently, examining the barriers and facilitators for cooperation between Universities and Industries has become very essential. Reciprocal communication has been identified as very effective in establishing positive expectations among partners (Bstieler et al., 2017). Also, national and international research conventions have accepted the fact that multidimensional innovations for the future significantly rely on distributed research collaborations that consist of sharing and integration of data, resources and knowledge, remote collaborative access to scientific instruments, and pooled human expertise (Hey et al., 2009). Therefore, an improvement in the capacity for research in Universities to drive innovation will enable researchers to compete with other countries in today’s global village (Nwakpa, 2015). Unfortunately, knowledge transfer through UIPs has faced significant challenges due to weaknesses in the area of collaboration and communication between universities and industries and therefore promoting effective communication should be emphasized (Marinho et al., 2020; Yusuf, 2012). The “European paradox”, which refers to having a strong capacity for research and yet lacking the capacity to translate it into innovative products, perfectly describes this challenge (Ranga et al., 2013).

The major contributions of this research paper are:

  • 1.

    The development of web-based distributed collaborative tool that brings Universities and the Industry together to conduct collaborative research on the same platform.

  • 2.

    The design of an architectural model for the distributed collaboration tool and creating a distributed database for UIP, which enables each University to take full ownership of its database as well as monitor the activities of its lecturers and students for subsequent evaluation and analysis.

  • 3.

    The implementation of a system testing procedure to validate the collaborative system.

Moving forward with this paper, related literature was reviewed, after which the contribution to knowledge this research study made was presented. This was followed by the description of the models employed and the analyses conducted in the study. The implementation tools and system evaluation procedure adopted for the study was then presented. Finally, the research study was concluded with recommendations that will support future related works.

Complete Article List

Search this Journal:
Reset
Volume 20: 1 Issue (2024)
Volume 19: 7 Issues (2023)
Volume 18: 6 Issues (2022): 3 Released, 3 Forthcoming
Volume 17: 4 Issues (2021)
Volume 16: 4 Issues (2020)
Volume 15: 4 Issues (2019)
Volume 14: 4 Issues (2018)
Volume 13: 4 Issues (2017)
Volume 12: 4 Issues (2016)
Volume 11: 4 Issues (2015)
Volume 10: 4 Issues (2014)
Volume 9: 4 Issues (2013)
Volume 8: 4 Issues (2012)
Volume 7: 4 Issues (2011)
Volume 6: 4 Issues (2010)
Volume 5: 4 Issues (2009)
Volume 4: 4 Issues (2008)
Volume 3: 4 Issues (2007)
Volume 2: 4 Issues (2006)
Volume 1: 4 Issues (2005)
View Complete Journal Contents Listing