Themenausschreibungen
Themenausschreibungen
Die Bewerbungsfrist für das Wintersemester 2024/2025 läuft vom 04. September bis zum 30. September 2024.
Die Bewerbung für eine Abschlussarbeit am Lehrstuhl für Supply Chain Management erfolgt in zwei Schritten:
- Wählen Sie zunächst online mittels der nachfolgenden Links drei Themen (Prio 1 bis 3) aus (Bachelorarbeit / Masterarbeit)
- Zusätzlich zur Themenauswahl senden Sie bitte Ihren tabellarischen Lebenslauf und Notenauszug an Masoud Mirzaei (masoud.mirzaei@fau.de)
Bitte beachten Sie, dass nur vollständige Bewerbungen berücksichtigt werden können.
Die verbindliche Zusage für die Vergabe einer Abschlussarbeit erfolgt bis spätestens 04. Oktober 2024.
Bachelorstudierende müssen zusätzlich das „Seminar zur Bachelorarbeit“ belegen. An allen Terminen des Seminars herrscht Anwesenheitspflicht.
Zusätzliche Hinweise für Ihre Bewerbung finden Sie hier.
Aktuelle Themen für Abschlussarbeiten:
Die ausgeschriebenen Themen für Bachelor -und Masterarbeiten orientieren sich an den fünf Forschungsbereichen des Lehrstuhls. Darüber hinaus sind auch einige weitergehende Themen ausgeschrieben.
Themenbereich #1: Human capital
Themen:
The concept of the metaverse, while often associated with virtual reality (VR) and gaming, holds potential applications across various industries, including supply chain management. The metaverse provides opportunities for immersive training and education in supply chain management. Employees can undergo virtual simulations and interactive training modules to learn about complex supply chain processes, logistics, and inventory management in a risk-free environment. The aim of this master thesis is to investigate this topic using a case study research approach.
Industry 4.0 refers to the ongoing transformation of traditional manufacturing and industrial practices through the integration of smart technology, automation, and data exchange. It encompasses technologies such as the Internet of Things (IoT), artificial intelligence (AI), machine learning, robotics, and advanced data analytics. This revolution is characterized by the blurring of boundaries between the physical and digital worlds, leading to the creation of smart factories and cyber-physical systems. While Industry 4.0 offers significant benefits, including increased efficiency, productivity, and innovation, it also introduces a range of societal challenges, such as the impact on the workforce. As machines and AI take over more tasks, workers may experience increased stress and burnout due to the demand for new skills, continuous adaptation, and the potential loss of jobs to automation. The job market is undergoing a transformation where traditional roles may disappear, and new, tech-centric roles emerge, necessitating continuous learning and reskilling. The aim of this master thesis is to investigate this topic using a case study research approach or a future-oriented rsearch design.
In today’s globalized economy, the efficiency of supply chains depends not only on technologies and processes, but also to a large extent on the skills and qualifications of employees. Well-trained employees can identify bottlenecks, drive process optimization and thus make a significant contribution to a company’s competitiveness. This thesis should analyze the relationship between employee qualifications and supply chain efficiency. The focus is on analyzing existing data and conducting surveys to find out how different skill levels influence the performance of supply chains.
Themenbereich #2: Collaboration
Themen:
Tracking and monitoring scope 1, 2, and 3 emissions in real-time requires robust digital tools and platforms that can collect, analyze, and visualize data from various sources across the organization and its supply chain. By leveraging these digital tools and platforms, organizations can gain greater visibility into their emissions across scope 1, 2, and 3 categories, track progress towards reduction targets, and make data-driven decisions to improve sustainability performance. The aim of this master thesis is to investigate this topic using a case study research approach.
Collaboration between suppliers and buyers is a critical factor for the success of supply chains. But what makes this collaboration effective? Factors such as trust, communication, common goals and technological support can make the difference. This bachelor thesis is dedicated to analyzing key factors that enable successful collaboration. The aim is to find out how companies can optimize their partnerships to improve the overall performance of the supply chain. This thesis should conduct Literature review, best practices. For the master students, triangulation of data by conducting of interviews is obligatory.
With the advent of new technologies such as blockchain, IoT and artificial intelligence, completely new opportunities for collaboration in the supply chain are emerging. These technologies can improve transparency, optimize communication and strengthen trust between partners. This master’s thesis should examine how technological innovations are changing and improving collaboration between companies in the supply chain. The focus is on analyzing case studies that document the use of these technologies in real business processes.
The role of open innovation in Electric Vehicle (EV) ecosystems is pivotal as it fosters collaboration between automakers, tech companies, and energy providers, leading to accelerated technological advancements and cost efficiencies. By embracing open innovation, businesses can develop new business models that leverage shared resources, intellectual property, and data, thereby enhancing the overall value proposition of EVs. This approach not only drives competitive advantage but also promotes sustainability and user-centric innovations within the rapidly evolving EV market.
The topic „Role of open innovation in Electric Vehicle (EV) Ecosystems – A literature review“ invites you to systematically explore and synthesize existing research on how open innovation is shaping the development and integration of EV technologies. The review will focus on identifying the current status on literature that illustrates the impact of collaborative efforts across industries in advancing EV ecosystems. This comprehensive analysis will highlight gaps in current literature (Focus: the EV ecosystem compared to other innovation ecosystems) and propose future research directions, making it a valuable contribution to the field.
Themenbereich #3: Supply ecosystems
Themen:
The concept of the metaverse, while often associated with virtual reality (VR) and gaming, holds potential applications across various industries, including supply chain management. Digital twins, virtual representations of physical assets or processes, can be leveraged in the metaverse to simulate and optimize supply chain operations. By creating digital twins of factories, warehouses, transportation networks, and products, companies can identify bottlenecks, optimize workflows, and forecast demand more accurately. The aim of this master thesis is to investigate this topic using a case study research approach.
Supply chains are increasingly transforming into technology-driven, digital ecosystems, where various industries intersect and share common resources such as suppliers, manufacturers, and warehouses. This convergence of industries within a single ecosystem marks a significant shift in supply chain dynamics and introduces a new and relevant area of research focused on supply chain viability in a cross-industry context. By using a case study approach, the aim of this master thesis is to investigate these interactions within ecosystems, as as they are critical for the future of efficient and resilient supply chain management.
The concept of the metaverse, while often associated with virtual reality (VR) and gaming, holds potential applications across various industries, including supply chain management. Blockchain technology, which provides secure and transparent record-keeping, can be integrated into the metaverse to enhance supply chain visibility and traceability. Through blockchain-enabled metaverse platforms, stakeholders can track the movement of goods, verify product authenticity, and ensure compliance with regulatory requirements. The aim of this master thesis is to investigate this topic using a case study research approach.
The concept of the metaverse, while often associated with virtual reality (VR) and gaming, holds potential applications across various industries, including supply chain management. Metaverse platforms equipped with advanced analytics tools can process vast amounts of supply chain data in real-time. By analyzing data streams from IoT devices, sensors, and other sources, companies can gain insights into supply chain performance, identify emerging trends, and predict potential disruptions. The aim of this master thesis is to investigate this topic using a case study research approach.
Artificial intelligence (AI) has revolutionized logistics and supply chain management (SCM) by offering advanced capabilities to optimize processes, enhance decision-making, and improve overall efficiency. A pivotal aspect of embracing AI involves the potential restructuring of supply chain frameworks, marked by heightened efficiency, flexibility, and digital innovation in Logistics and Supply Chain Management (L&SCM). This emerging frontier necessitates thorough exploration, delineating the possible pathways and consequences of AI integration within supply chain practices. The aim of this master thesis is to investigate how AI can contribute to creating more responsive, resilient, and adaptable supply chain networks and what are the strategies to leverage AI for optimizing inventory management, demand forecasting, and logistics planning using a case study research approach. The aim of the bachelor thesis is to investigate the topic using existing literature.
Small and medium-sized enterprises (SMEs) often play a crucial role in the supply ecosystems of large corporations. These SMEs act as suppliers, innovators and partners in supply chains, contributing to value creation and influencing the flexibility and agility of the entire supply chain. This bachelor thesis should examine the role of SMEs in the supply ecosystems of large companies and analyzes how they are integrated and what contribution they make to overall performance. The aim is to identify the challenges and opportunities for SMEs in these networks – As method, it is expected to conduct quantitative survey and secondary data analysis.
Themenbereich #4: Sustainability
The concept of the metaverse, while often associated with virtual reality (VR) and gaming, holds potential applications across various industries, including supply chain management. With increasing emphasis on sustainability and risk management in supply chains, the metaverse can facilitate the implementation of eco-friendly practices and resilience strategies. Companies can use virtual simulations to assess the environmental impact of their operations, evaluate alternative sourcing options, and mitigate supply chain risks related to natural disasters, geopolitical events, and pandemics. The aim of this master thesis is to investigate this topic using a case study research approach.
Artificial intelligence (AI) plays a significant role in advancing sustainability initiatives within logistics and supply chain management (SCM). AI algorithms assess supplier performance, evaluate sustainability metrics, and identify opportunities for ethical sourcing and procurement practices. By partnering with suppliers that adhere to environmental and social responsibility standards, companies promote sustainability throughout their supply chains. The aim of this master thesis is to investigate this topic using a case study research approach.
Artificial intelligence (AI) plays a significant role in advancing sustainability initiatives within logistics and supply chain management (SCM). AI technologies such as blockchain enable transparent and traceable supply chains by recording transactions and product movements in immutable ledgers. By providing visibility into product origins, manufacturing processes, and supply chain intermediaries, companies enhance accountability, reduce the risk of unethical practices, and ensure compliance with sustainability standards. The aim of this master thesis is to investigate this topic using a case study research approach.
Scope 1, 2, and 3 emissions refer to different categories of greenhouse gas emissions associated with an organization’s activities, including those in its supply chain. By addressing Scope 1, 2, and 3 emissions across their operations and supply chain, organizations can work towards comprehensive greenhouse gas reduction goals and contribute to mitigating climate change. Nevertheless, these activities often conflict with other performance metrics. The aim of this master thesis is to investigate the trade-offs between emissions reduction and other supply chain performance metrics, such as cost, quality, and delivery time using a case study research approach.
In the context of regulatory compliance and reporting for emission reduction, several complexities arise, such as myriad regulatory frameworks, different scope definitions, data collection and measurement as well as verification and measurement. Addressing these complexities requires a holistic approach to emission reduction that integrates technical expertise, regulatory knowledge, stakeholder engagement, and robust governance mechanisms. Organizations must invest in effective management systems, capacity building, and strategic partnerships to navigate the complexities of regulatory compliance and reporting for emission reduction effectively. The aim of this master thesis is to investigate this topic using a case study research approach. The aim of the bachelor thesis is an analysis of secondary data in which sustainability reports are to be examined and evaluated.
Digitalization offers companies numerous opportunities to reduce their environmental footprint while increasing the efficiency of their supply chains. By using digital technologies such as IoT, big data and blockchain, companies can monitor and optimize their environmental performance in real time. This bachelor thesis examines how digital technologies can be used to improve environmental efficiency in supply chains. The focus is on analyzing how companies can become more sustainable and at the same time more competitive by using these technologies by exploring the existing literature and quantitative analysis.
Reducing the carbon footprint in global supply chains has become a key goal for many companies, especially in the context of increasing regulatory and stakeholder pressure. This master thesis examines which strategies companies use to make their supply chains climate-neutral. The focus is on analyzing initiatives and measures that contribute to the reduction of greenhouse gas emissions along the entire value chain. The aim is to evaluate the effectiveness of these strategies and derive recommendations for practical action by triangulation of literature review, best practices and expert interviews.
Themenbereich #5: Foresight
Themen:
Für das Wintersemester 2024/2025 sind in diesem Bereich keine Themen ausgeschrieben.
Sonder-Themenbereich im WiSe 2024/2025: Artificial intelligence in supply chain management
Themen:
The topic „Digital colleagues in supply chain management – Expert interviews“ offer you the opportunity to investigate the role and impact of AI-driven technologies, such as chatbots and robotic process automation, within supply chain operations through in-depth expert interviews. By engaging with industry professionals, you will gather insights on how these digital colleagues are enhancing efficiency, decision-making, and collaboration across the supply chain. The findings will provide a nuanced understanding of the challenges and opportunities associated with integrating AI into supply chain management, contributing valuable perspectives to both academic and practical discussions.
The topic „AI in supply chain management – An ethical framework for deployment of AI systems in supply chains“ invites you to develop a comprehensive ethical framework addressing the challenges and considerations associated with implementing AI technologies in supply chain operations. This framework will focus on issues such as data privacy, bias in decision-making, transparency, and the social implications of AI-driven automation. By establishing guidelines for responsible AI deployment, the research aims to ensure that supply chain innovations are aligned with ethical standards and ideally contribute positively to society.
The topic „AI in supply chain management – AI fostering sustainable and environmentally friendly supply chain practices“ offers you the opportunity to explore how AI technologies can be leveraged to enhance sustainability in supply chain operations. This research will focus on how AI-driven tools, such as predictive analytics, optimization algorithms, and machine learning, can reduce waste, improve resource efficiency, and lower the carbon footprint of supply chains. By examining real-world applications (mentioned by experts) and case studies, the study will highlight the potential of AI to drive environmentally responsible practices, contributing to both business efficiency and global sustainability goals.
The topic „An ethical framework for deployment of AI systems in supply chains – A literature review“ encourages you to critically analyze existing research on the ethical implications of integrating AI into supply chain management. This review will identify key ethical concerns, such as bias, transparency, and accountability, as discussed in current literature, and evaluate proposed frameworks and guidelines for addressing these issues. By synthesizing insights from various studies, the research will provide a comprehensive understanding of the ethical challenges in AI deployment within supply chains and suggest areas for future exploration and refinement.
The topic „How will AI enhance productivity in specific areas of supply chain operations (SCOR) – A foresight perspective“ invites you to explore the future impact of AI technologies on key components of the SCOR model. This research will involve forecasting potential advancements in AI and their ability to optimize processes, reduce costs, and increase agility across these supply chain functions. By adopting a foresight perspective, the study aims to provide strategic insights into how AI will reshape supply chain operations, offering a roadmap for businesses to prepare for and capitalize on these emerging trends.
The topic „Barriers of implementing AI in supply chains – Expert interviews“ offers you the chance to investigate the challenges that organizations face when integrating AI technologies into supply chain operations, through direct insights from industry experts. By conducting interviews with supply chain professionals, you will identify key obstacles such as technological limitations, workforce readiness, data quality, and resistance to change. The research will provide a detailed understanding of these barriers and offer practical recommendations to overcome them, contributing valuable knowledge to the field of AI adoption in supply chains.
The topic „Barriers of implementing AI in supply chains – A literature review“ invites you to conduct a comprehensive analysis of existing research on the challenges associated with AI integration in supply chain management. This review will focus on identifying common barriers, such as technological constraints, data management issues, ethical concerns, and organizational resistance, as discussed in current literature. By synthesizing these findings, the research will provide a clear overview of the obstacles hindering AI adoption in supply chains and suggest areas where further investigation or innovation is needed to facilitate smoother implementation.
The topic „How can AI enhance customer experience in the L&SCM sector – A literature review“ challenges you to explore and synthesize existing research on the role of AI in improving customer interactions within logistics and supply chain management. This review will focus on how AI-driven technologies, such as chatbots, predictive analytics, and personalized services, are being utilized to meet customer expectations, streamline communication, and optimize delivery processes. By analyzing the current literature, the research will provide insights into the effectiveness of AI in enhancing customer satisfaction and identify opportunities for further innovation in the L&SCM sector.
For your research on „How AI can enhance customer experience in the L&SCM sector through expert interviews,“ you will explore how artificial intelligence can be leveraged to improve various touchpoints in logistics and supply chain management, from predictive analytics to real-time decision-making. This study will involve conducting in-depth interviews with industry professionals to gather insights on current AI applications, challenges, and future trends in enhancing customer satisfaction and operational efficiency. Your findings will contribute to understanding the transformative role of AI in optimizing customer experience within this critical industry sector.
The topic „How can AI assist organizations in complying with sustainability-related regulations and policies“ invites an exploration of how artificial intelligence can be leveraged to enhance an organization’s adherence to evolving environmental standards. By conducting a literature review, you will examine existing research on AI-driven tools and systems that facilitate compliance monitoring, data management, and reporting, ultimately supporting organizations in meeting sustainability goals more efficiently. This study will also identify potential challenges and limitations in the integration of AI within the regulatory landscape, providing a comprehensive understanding of its impact on sustainable business practices.
The research topic „How can AI assist organizations in complying with sustainability-related regulations and policies“ focuses on exploring the potential of artificial intelligence to streamline and enhance regulatory compliance within organizations. Through expert interviews, this study aims to gather insights from industry professionals and thought leaders on the practical applications of AI in managing sustainability requirements, identifying challenges, and developing best practices. The findings will contribute to a deeper understanding of how AI can be effectively leveraged to ensure organizations not only meet but exceed regulatory expectations in the sustainability domain.