Integrating digitization technologies into resource efficiency driven industrial learning environments

Scholz, Michael; Franke, Jörg; Sauer, Alexander

doi:10.1016/j.promfg.2018.03.158

Cited by 16 publications

(8 citation statements)

References 5 publications

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“…The estimated results in columns (1) and (3) display that a significant decrease in the regression coefficient of Digital , which imply that enterprise's environmental governance is a mediating mechanism for digital transformation to affect the enterprise's EPIN , thus indicating that H5 is verified. This also approves the study of Böhner et al (2018), which argues that digital technologies provide an environmentally friendly work environment for European industries, thus contributing to the integration of resource efficiency.…”

Section: Resultssupporting

confidence: 84%

“…Table 10 suggests the results of the test for the mediating effect of that H5 is verified. This also approves the study of Böhner et al (2018), which argues that digital technologies provide an environmentally friendly work environment for European industries, thus contributing to the integration of resource efficiency.…”

Section: The Mediating Effect Of Human Capital Accumulationsupporting

confidence: 65%

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Digital transformation and environmental performance: Evidence from Chinese resource‐based enterprises

Guo

2023

Corp Soc Responsibility Env

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Digitalization is of great significance for resource-based enterprises to break through the dual constraints of resource and environment. Based on the data of China's A-share resource-based listed enterprises, this study empirically examines the direct effect and transmission mechanism of digital transformation on the enterprises' environmental performance. The study finds that digital transformation significantly enhances the environmental performance of enterprises by stimulating green technology innovation, accelerating human capital accumulation, increasing environmental information disclosure, and strengthening environmental governance. The environmental performance of state-owned, large-size and high-tech resource-based enterprises is more prominently affected by digital transformation. In the eastern region and areas with higher environmental regulation, the impact of digital transformation on the environmental performance of resource-based enterprises is more significant. This study provides targeted suggestions for resource-based enterprises to make full use of the digital dividends and achieve high-quality development.

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Section: Resultssupporting

confidence: 84%

Section: The Mediating Effect Of Human Capital Accumulationsupporting

confidence: 65%

Digital transformation and environmental performance: Evidence from Chinese resource‐based enterprises

Guo

2023

Corp Soc Responsibility Env

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“…Similarly, smart intralogistics systems can enable the flow of real‐time data. As a result, forecasting and calculating the required inventory needed for a specific day and adjusting operations to meet demand levels become more convenient and efficient (Böhner et al, 2018). This decreases operational costs and optimizes raw materials usage (Bayhan et al, 2020; Fusko et al, 2017; Karamanos et al, 2019; Winkler & Zinsmeister, 2019; Wior et al, 2018).…”

Section: Resultsmentioning

confidence: 99%

Autonomous and IoT‐driven intralogistics for Industry 4.0 warehouses: A thematic analysis of the literature

Grover,

Ashraf

2024

Transp. j.

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Eyeing superior operational performance, transportation, and warehousing management, researchers have turned their much‐needed attention to autonomous and IoT‐driven intralogistics systems. Despite its potential, a systematic evaluation of its overall business needs and the criteria for its success at each stage of adoption is missing in the literature. Using the business analysis framework, augmented by the technology adoption model, this study seeks to provide the business context for adopting autonomous and IoT‐driven intralogistics by identifying business requirements and critical success factors for such systems. We thematically analyze 85 recent research articles on autonomous and IoT‐driven intralogistics systems to identify business requirements that are linked to the mission of maximizing operational profit for the warehousing and storage industry. Then, using the identified business requirements as a base, we thematically analyze those 85 research articles again to identify critical success factors at different stages of technology adoption, namely information, analysis, acquisition, and utilization. We use the findings to develop propositions for future researchers. These findings provide a foundation for developing empirical, descriptive, and normative research on adopting and managing these systems for the warehousing and storage industry.

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“…Die Trennung in mehrere Modelle erlaubt es, dass jedes mit anderen Features trainiert werden kann, sodass beispielsweise unterschiedliche Untermesszählermodelle spezifische Wettervariablen oder Produktionsplanungsdaten erhalten, angepasst an örtliche oder logistische Bereiche. Zudem können diese Modelle besser an die spezifischen Lasten angepasst werden [11,12]. Im Unternehmenskontext weisen die Unternehmensbereiche, zusammengefasst durch je einen Zähler, typischerweise unterschiedliche Variablenabhängigkeiten auf.…”

Section: Bottom-up-prognose: Chancen Und Herausforderungenunclassified

Bottom-Up Lastprognose im industriellen Kontext/Bottom-up load forecasting in the industrial context

Baur¹,

Kaymakci²,

Sauer³

2023

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In Zeiten volatiler und steigender Energiepreise gewinnt die Lastprognose als Entscheidungsgrundlage zunehmend an Bedeutung. Die fortschreitende Digitalisierung erlaubt zudem ein detailliertes Aufzeichnen von Verbrauchsdaten auf mehreren Abstraktionsebenen. In diesem Beitrag werden zwei Ansätze, die eine Messzählertopologie in die Prognose integrieren, mit dem Standardansatz auf Hauptzählerebene verglichen. Die Ergebnisse auf den Unternehmensdaten motivieren für einen flächendeckenden Einsatz. Increasingly volatile and rising energy prices make load forecasting increasingly important as a basis for decision-making. Moreover, the advancing digitalization allows a detailed recording of consumption data on several abstraction levels. This paper compares two approaches that integrate a metering topology into load forecasting with the standard approach at the main meter level. The results on enterprise data motivate widespread deployment.

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Integrating digitization technologies into resource efficiency driven industrial learning environments

Cited by 16 publications

References 5 publications

Digital transformation and environmental performance: Evidence from Chinese resource‐based enterprises

Digital transformation and environmental performance: Evidence from Chinese resource‐based enterprises

Autonomous and IoT‐driven intralogistics for Industry 4.0 warehouses: A thematic analysis of the literature

Bottom-Up Lastprognose im industriellen Kontext/Bottom-up load forecasting in the industrial context

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