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SMART OPERATIONS: IMPLEMENTING AI-DRIVEN TECHNOLOGIES FOR ENHANCED EFFICIENCY IN SUPPLY CHAIN MANAGEMENT

Branding: Jurnal Manajemen dan Bisnis · Vol. 3 No. 1 (2024)

DOI
10.15575/jb.v3i1.35118
ISSN
2963-8852, 2963-8852
Published
2024-05-24
Publisher
UIN Sunan Gunung Djati Bandung
Language
eng

Abstract

Supply chain management is a vital element in a company's overall operations, but is faced with complex challenges such as fluctuations in market demand, logistical complexity, resource limitations, and the risk of disruption. This research aims to explore the role of artificial intelligence (AI)-based technology in overcoming these challenges. This research will be carried out using a qualitative approach, collecting data from various relevant sources and then analyzing it systematically. Through this approach, this research aims to gain a deep understanding of the long-term impact of applying AI to the supply chain, including improving operational efficiency, competitive advantage, supporting sustainability, and the evolution of the human role. The research results show that AI makes a significant contribution to improving companies' operational efficiency, providing competitive advantage through enhanced responsiveness, supporting more sustainable business practices, and enabling the evolution of the role of humans in the supply chain. The practical implication of this research is that the application of AI technology can help companies achieve better performance and prepare for future challenges in an increasingly complex and dynamic business environment.

Keywords

Collaboration network of the authors

40 authors · 101 co-authorship links · 4 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Cenderawasih University
  • Universitas Gadjah Mada
  • Universitas Jember
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Mashudi MashudiAffiliation unknown3
Reni Sara IndrawatiAffiliation unknown2
MashudiAffiliation unknown2
Nyoman Ngurah AryaAffiliation unknown2
Syech IdrusAffiliation unknown2
Hikmah SekarningtyasAffiliation unknown2
M. Imron Mas'udAffiliation unknown2
Suharno SuharnoCenderawasih University1
Chris D. SembayAffiliation unknown1
Verena AgustiniCenderawasih University1
Lisiard DimaraCenderawasih University1
Maryani MaryaniUniversitas Jember1
Utaminingsih UtaminingsihAffiliation unknown1
Sulhan EtfantiAffiliation unknown1
Putri AnditasariAffiliation unknown1
Agus Dedi SubagjaAffiliation unknown1
Yogi Syarif HidayatAffiliation unknown1
Yusti PujisariAffiliation unknown1
Farida AkbarinaAffiliation unknown1
Denpharanto Agung KrisprimandoyoAffiliation unknown1
Muh TabranAffiliation unknown1
Endang FatmawatiAffiliation unknown1
R. Ayu Erni JusnitaAffiliation unknown1
I Made SurahartaAffiliation unknown1
Nico DjajasingaAffiliation unknown1
Sri Umiatun AndayaniAffiliation unknown1
Nurhamzah NurhamzahAffiliation unknown1
Radi RadiAffiliation unknown1
Aprilya FitrianiAffiliation unknown1
Nico Djundharto DjajasingaAffiliation unknown1
Dasmadi DasmadiAffiliation unknown1
Yane MayasariAffiliation unknown1
Sri SuparniAffiliation unknown1
Jemmy RinaldyAffiliation unknown1
I Ketut MahaputraAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.uinsgd.ac.id/index.php/branding/oai, first harvested 7 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">SMART OPERATIONS: IMPLEMENTING AI-DRIVEN TECHNOLOGIES FOR ENHANCED EFFICIENCY IN SUPPLY CHAIN MANAGEMENT</dc:title>
	<dc:creator>Fauziah, Luluk</dc:creator>
	<dc:creator>Suharyanto, Suharyanto</dc:creator>
	<dc:creator>Herlina, R. Lisye</dc:creator>
	<dc:creator>Sutisna, Adang</dc:creator>
	<dc:creator>Gymnastiar, Iman Ahmad</dc:creator>
	<dc:subject xml:lang="en-US">Artificial Intelligence</dc:subject>
	<dc:subject xml:lang="en-US">Supply Chain Management</dc:subject>
	<dc:subject xml:lang="en-US">Logistics.</dc:subject>
	<dc:description xml:lang="en-US">Supply chain management is a vital element in a company's overall operations, but is faced with complex challenges such as fluctuations in market demand, logistical complexity, resource limitations, and the risk of disruption. This research aims to explore the role of artificial intelligence (AI)-based technology in overcoming these challenges. This research will be carried out using a qualitative approach, collecting data from various relevant sources and then analyzing it systematically. Through this approach, this research aims to gain a deep understanding of the long-term impact of applying AI to the supply chain, including improving operational efficiency, competitive advantage, supporting sustainability, and the evolution of the human role. The research results show that AI makes a significant contribution to improving companies' operational efficiency, providing competitive advantage through enhanced responsiveness, supporting more sustainable business practices, and enabling the evolution of the role of humans in the supply chain. The practical implication of this research is that the application of AI technology can help companies achieve better performance and prepare for future challenges in an increasingly complex and dynamic business environment.</dc:description>
	<dc:publisher xml:lang="en-US">UIN Sunan Gunung Djati Bandung</dc:publisher>
	<dc:date>2024-05-24</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.uinsgd.ac.id/index.php/branding/article/view/35118</dc:identifier>
	<dc:identifier>10.15575/jb.v3i1.35118</dc:identifier>
	<dc:source xml:lang="en-US">Branding: Jurnal Manajemen dan Bisnis; Vol. 3 No. 1 (2024): BRANDING: Jurnal Manajemen dan Bisnis</dc:source>
	<dc:source xml:lang="id-ID">Branding: Jurnal Manajemen dan Bisnis; Vol 3 No 1 (2024): BRANDING: Jurnal Manajemen dan Bisnis</dc:source>
	<dc:source>2963-8852</dc:source>
	<dc:source>2963-8852</dc:source>
	<dc:source>10.15575/jb.v3i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.uinsgd.ac.id/index.php/branding/article/view/35118/10714</dc:relation>
	<dc:relation>10.15575/jb.v3i1.35118.g10714</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2024 Branding: Jurnal Manajemen dan Bisnis</dc:rights>
</oai_dc:dc>