Channels of interaction and past collaborative experience as imperatives in academia–industry collaboration

Bhullar, Supreet; Nangia, Vinay Kumar; Batish, Ajay

doi:10.1080/09537325.2016.1277694

Cited by 10 publications

(2 citation statements)

References 32 publications

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“…The importance of economic, institutional, and social contest for academia-industrial collaboration is confirmed for studies (Ankrah et al,2015). In some works, there is an insight into the positive influence of experience with collaborations on academia's outcomes -industry tie-ups (Bhullar et al,2017). A collaborative scheme is follows defines on past engagements and future anticipation with high tackling of complexities.…”

Section: B Experienced Based Motivational Intellectual Collaboratormentioning

confidence: 92%

The Significant Contextual Predictors of Industrial Academic Collaboration in Engineering

Sridharan¹,

Ramrao²,

Murugan³

et al. 2021

Journal of Engineering Education Transformations

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In a Modern Economy, transforming academics into competitive advantages is pivotal. The present work discusses the impact and challenges of academia-industry collaboration on academic output and campus placement preparation. This study explores the contextual predictors related to core placement and industrial-academic collaboration requirements among undergraduate students in Engineering. Industrial -academic training and placement intent are defined as the core competence and the students undergo these trainings to develop the skills in order to get placement in the core domains of RTL Verification using System Verilog, SOC-ASIC physical design, Embedded system design, IoT and Artificial intelligence for Cyber security. Overall, 509 students have been included as participants and they are students of second year, third year, and final year engineering from the Department of Electronics and Communication Engineering of Kalasalingam Academy of Research and Education. This work examines the Collaborative Success in Learning New Application, Teaching Research Level Collaboration, and Preparation for First Campus Placement. The statistical Analysis of Regression has been utilized to address the relationships. Skill training from industry and participation in domain-specific activities are more strongly intended for engineering undergraduate students during their course. The analysis pertains that both are significant parameters. However, the level of significance is more in Collaborative Success in Learning New Application (CSLNA) compared to Teaching Research Level Collaboration (TRLC) for the confidence level in Preparation for First Campus Placement (PFCP).

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Section: B Experienced Based Motivational Intellectual Collaboratormentioning

confidence: 92%

The Significant Contextual Predictors of Industrial Academic Collaboration in Engineering

Sridharan¹,

Ramrao²,

Murugan³

et al. 2021

Journal of Engineering Education Transformations

View full text Add to dashboard Cite

show abstract

“…Studies also point towards collaboration between academia and industry as a way to form deeper insights into real industrial problems (Bhullar, Nangia and Batish, 2017). Tijssen, Lamers and Yegros (2017) introduce the concept of university-industry crossover researchers, who combine one or more university affiliation and business affiliation in recent years.…”

Section: Research and Industry Experiencementioning

confidence: 99%

Divide, Switch, Blend. Exploring two hats for industry entrepreneurship and academic practice-based textile design research

Hall

Earley

2019

The Design Journal

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This paper explores different approaches taken when 'wearing two hats'; that of academic researcher and the industry entrepreneur. It considers the barriers and opportunities in combining these two roles in order to acquire new knowledge. To understand how future researchers could best do this and why this might be desirable, the paper presents Author1's insights from field research experience; wearing both hats within a textile industry context. A literature review, reflective practice and an annotated portfolio method enabled the authors to identify three approaches -Divide, Switch and Blend. These form a model for researching with any two hats on: Divide entails wearing both hats separately on different occasions; Switch is wearing both hats but interchanging between the two on a single occasion; Blend is wearing both hats simultaneously. The authors conclude that fluidity between approaches and an understanding of the dominant hat is vital.

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Scientific publications from non-academic sectors and their impact

2021

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Channels of interaction and past collaborative experience as imperatives in academia–industry collaboration

Cited by 10 publications

References 32 publications

The Significant Contextual Predictors of Industrial Academic Collaboration in Engineering

The Significant Contextual Predictors of Industrial Academic Collaboration in Engineering

Divide, Switch, Blend. Exploring two hats for industry entrepreneurship and academic practice-based textile design research

Scientific publications from non-academic sectors and their impact

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