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Sambas Sundana
Program Studi Teknik Industri, Fakultas Teknik, Universitas Pancasila

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PENGEMBANGAN MODEL PERAN TRIPLE-HELIX TERHADAP PENGEMBANGAN ECOCANVAS CLEANTECH STARTUP BERBASIS GREEN INNOVATION & TECHNOLOGY ADOPTION Kirana Rukmayuninda Ririh; Sambas Sundana; Amalia Kusumawati; Desinta Rahayu Ningtyas
BAROMETER Vol 7 No 2 (2022): Barometer
Publisher : Fakultas Teknik, Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35261/barometer.v7i2.6630

Abstract

Startups play an important role in the disruptive transformation of several industrial sectors towards a circular economy of sustainability.  Cleantech Startup (CS) is one of the major business players in green innovation and technology, which is based on generating or utilizing clean energy.  To achieve sustainable green innovation success, collaboration between actors in green innovation systems such as universities, government institutions and industry (including CS) must be optimal.  Coupled with the CS business model, it is necessary to implement a green business model canvas (EcoCanvas).  This literature study will review how the Triple-Helix (TH) collaboration towards innovation and adoption of green technology is carried out by CS. In addition, the EcoCanvas will be formulated from examples of CS cases in Indonesia.  This study uses a desk review of 51 major articles from reputable journals.  It can be seen that the TH collaboration focuses on: government regulations, market focus, supplier participation, coordination between functions, and technology development.  In addition, licensing alliances and technology development will affect the pattern of financial investment and patent activity. The EcoCanvas model on CS also shows that environmental issues such as waste and abundant resources in Indonesia are the main focus in the sustainable business model adopted by CS.  The findings in this study need to be studied more deeply by using empirical evidence from the field and other supporting historical data.