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All Journal Juriti Prima (Jurnal Ilmiah Teknik Industri Prima) Jurnal Pengabdian Masyarakat Sains dan Teknologi Jurnal Riset Rumpun Ilmu Teknik (JURRITEK) Ardhi: Jurnal Pengabdian dalam Negri Manufaktur: Publikasi Sub Rumpun Ilmu Keteknikan Industri Dinamika Sosial: Jurnal Pengabdian Masyarakat Dan Transformasi Kesejahteraan Svarga Pena: Jurnal Pengabdian Kepada Masyarakat Karawo : Journal of Community Service (KJCS) TechTalent & Business Review International Journal of Economics and Management Research Proceeding of The International Conference on Economics, Accounting, and Taxation
Jusra Tampubolon
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Journal : techtalent

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Data-Driven Operations Management and Supply Chain Innovation in the Retail Industry Jusra Tampubolon
TechTalent & Business Review Vol. 2 No. 2 (2026): TTBR-July 2026
Publisher : Asosiasi Peneliti dan Inovasi Nusantara (APIN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63985/ttbr.v2i2.119

Abstract

This study examines how data-driven operations management capabilities shape supply chain innovation performance among retail firms operating in volatile, digitally mediated markets. Despite enthusiasm for analytics, artificial intelligence, and real-time visibility tools, retailers still struggle to convert data investments into measurable innovation outcomes, and the mechanisms linking specific data-driven capabilities to innovation remain fragmented across the literature. Drawing on the resource-based view and dynamic capabilities theory, this research proposes and empirically tests a model linking three data-driven capabilities, namely data analytics capability, real-time supply chain visibility, and artificial intelligence/machine learning adoption, to supply chain innovation performance, with data-driven decision-making culture as a mediating mechanism. A quantitative, cross-sectional survey design was employed, collecting responses from 215 operations and supply chain managers in retail organizations, analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results indicate that all three capabilities exert significant positive effects on supply chain innovation performance, with data-driven decision-making culture partially mediating these relationships. Real-time visibility emerged as the strongest direct predictor, followed by AI/ML adoption and data analytics capability. These findings extend supply chain innovation theory by clarifying the differentiated contribution of distinct data-driven capabilities and offer practical guidance for retail operations managers seeking to prioritize digital investments that generate innovation returns rather than incremental efficiency gains alone.
Co-Authors Andi Setiadi Manalu anita c sembiring Arwin Tannuary Daniel Natanael Manalu Darwin Li Dea A. Persada Sinaga Demak Claudia Yosephine Simanjuntak Dion Saputra H Doris Yolanda Saragih Elfina Okto Posmaida Damanik Erwin Sirait febrianti G.P Handi Firinta Togatorop Hengki Mangiring Parulian Simarmata Henry Dunan Pardede Heru Sugara Jon Judiarto Siregar Jongkers Tampubolon Jufri Antoni Parulian, Hengki Poltak Pardamean Simarmara Poltak Pardamean Simarmata Purnama Yanti Purba Rensus A. Pardede Rido Sinaga Sabar Duma Sihombing Sabar Dumayanti Sihombing Sandi Maiko Sihite Uni Pratama Pebrina Br Tarigan Yusuf Ronny Edward