Johannes Hangl

Abstract
This study explored the challenges and recommendations for implementing Artificial Intelligence (AI) in SC Management (SCM). The experts identified several drivers for AI adoption in SCM, including increased efficiency, improved decision-making, and reduced costs. However, they highlighted several barriers to AI adoption, such as data quality and management issues, resistance to change, and lack of understanding and trust in AI. To overcome these barriers and ensure successful AI… Mehr anzeigen

Abstract
This study explored the challenges and recommendations for implementing Artificial Intelligence (AI) in SC Management (SCM). The experts identified several drivers for AI adoption in SCM, including increased efficiency, improved decision-making, and reduced costs. However, they highlighted several barriers to AI adoption, such as data quality and management issues, resistance to change, and lack of understanding and trust in AI. To overcome these barriers and ensure successful AI implementation, companies should involve all stakeholders, focus on data quality and management, and ensure the AI solution integrates with existing processes and workflows. In addition, companies should also avoid common mistakes when implementing AI, such as neglecting the importance of explainability and transparency in AI decision-making, underestimating the importance of involving all stakeholders, and rushing into large-scale implementation without conducting small-scale pilot projects. By following the recommendations and avoiding common mistakes, companies can harness the benefits of AI in SCM while minimizing risks and challenges. Weniger anzeigen

Background: The number of publications in supply chain management (SCM) and artificial intelligence (AI) has risen significantly in the last two decades, and their quality and outcomes vary widely. This study attempts to synthesise the existing literature in this research area and summarise the findings regarding barriers, drivers, and social implications of using AI in SCM. Methods: The methodology used for this meta-study is based on Kitchenham and Charters guidelines, resulting in a… Mehr anzeigen

Background: The number of publications in supply chain management (SCM) and artificial intelligence (AI) has risen significantly in the last two decades, and their quality and outcomes vary widely. This study attempts to synthesise the existing literature in this research area and summarise the findings regarding barriers, drivers, and social implications of using AI in SCM. Methods: The methodology used for this meta-study is based on Kitchenham and Charters guidelines, resulting in a selection of 44 literature reviews published between 2000 and 2021. Results: As a summary of the results, the main areas of AI in SCM were algorithms, followed by the Internet of Things (IoT). The main barriers to AI adoption in SCM are change management, existing technical limitations, and the acceptance of humans for these techniques. The main drivers of AI in SCM are saving costs and increasing efficiency in combination with reducing time and resources. The main social factor is human–robot collaboration. As a result, there will be a decreased amount of labour needed in the future, impacting many existing jobs, especially in low-income areas. Conclusions: Therefore, it is essential for organisations that implement new technology to start as early as possible to inform the organisation about the changes and help them successfully implement them. It is also important to mention that constant learning and improvement of the employees are critical for adopting and successfully using new AI tools. Before investing in new technology, a solid Return on Investment calculation (ROI) and monitoring costs and value are critical to transforming the business successfully. Weniger anzeigen

The aim of the work is to provide a comprehensive picture of the state of current and future development as well as trends in the use of artificial intelligence. Furthermore, it will be shown what possibilities, effects, opportunities and risks artificial intelligence has for supply chain management.

In order to meet the aforementioned objective, the following sub-objectives are defined:

- Creating a fundamental understanding of supply chain management
- Creating a fundamental… Mehr anzeigen

The aim of the work is to provide a comprehensive picture of the state of current and future development as well as trends in the use of artificial intelligence. Furthermore, it will be shown what possibilities, effects, opportunities and risks artificial intelligence has for supply chain management.

In order to meet the aforementioned objective, the following sub-objectives are defined:

- Creating a fundamental understanding of supply chain management
- Creating a fundamental understanding of artificial intelligence
- Explanation of developments over time
- Current use of artificial intelligence along the supply chain
- Explaining the opportunities and risks of artificial intelligence Weniger anzeigen

Die Industrialisierung hat das Leben der Menschen seit dem achtzehnten Jahrhundert stark verändert. Damals verlagerte sich der Schwerpunkt der Tätigkeiten vom Körperlichem zum Kognitiven. Inzwischen befinden wir uns in der vierten industriellen Revolution. Durch die Entwicklung immer besserer künstlicher Systeme werden immer mehr kognitive Tätigkeiten durch Maschinen ausgeführt. Doch was genau bedeutet künstliche Intelligenz? Welche Veränderungen hat sie im Supply-Chain-Management bereits… Mehr anzeigen

Die Industrialisierung hat das Leben der Menschen seit dem achtzehnten Jahrhundert stark verändert. Damals verlagerte sich der Schwerpunkt der Tätigkeiten vom Körperlichem zum Kognitiven. Inzwischen befinden wir uns in der vierten industriellen Revolution. Durch die Entwicklung immer besserer künstlicher Systeme werden immer mehr kognitive Tätigkeiten durch Maschinen ausgeführt. Doch was genau bedeutet künstliche Intelligenz? Welche Veränderungen hat sie im Supply-Chain-Management bereits geschaffen und was ist in Zukunft noch möglich? Mit welchen Risiken ist die fortschreitende Digitalisierung verbunden? Johannes Hangl schafft in seiner Publikation ein umfassendes Bild über den Stand der aktuellen und zukünftigen Entwicklung sowie über Trends beim Einsatz von künstlicher Intelligenz. Er zeigt auf, welche Möglichkeiten, Auswirkungen, Chancen und Risiken sie für das Supply-Chain-Management hat. Aus dem Inhalt: - KI; - AI; - Internet of Things; - Logistik; - Cyber-Physikalische Systeme Weniger anzeigen