Themenausschreibungen

The ongoing digital transformation is reshaping traditional supply chains into intelligent, interconnected systems, often referred to as „Supply Chain 4.0.“ In this context, the digital proficiency of employees becomes a critical success factor. This thesis aims to explore how organizations can implement effective strategies to develop digital skills among their workforce, aligning with the demands of modern supply chains. The focus will be on analyzing training programs, digital learning platforms, and change management processes.

The ongoing digital transformation is reshaping traditional supply chains into intelligent, interconnected systems, often referred to as „Supply Chain 4.0.“ In this context, the digital proficiency of employees becomes a critical success factor. This thesis aims to explore how organizations can implement effective strategies to develop digital skills among their workforce, aligning with the demands of modern supply chains. The focus will be on analyzing training programs, digital learning platforms, and change management processes.

In today’s globalized economy, a company’s human capital is pivotal in effectively harnessing digital transformations within global supply chains. This thesis investigates how specific dimensions of human capital, such as analytical skills and social competencies, enhance competitiveness in a dynamic global business environment.

In today’s globalized economy, a company’s human capital is pivotal in effectively harnessing digital transformations within global supply chains. This thesis investigates how specific dimensions of human capital, such as analytical skills and social competencies, enhance competitiveness in a dynamic global business environment.

This thesis examines the importance of cultural competence in global supply chain operations, focusing on how cultural awareness and communication skills influence collaboration and overall performance. Through a review of relevant literature and real-world case examples, the study aims to identify strategies that help diverse teams overcome cultural barriers, build trust, and enhance information sharing. The findings will shed light on best practices for fostering cultural competence, ultimately guiding organizations to improve operational efficiency, strengthen global partnerships, and drive sustainable competitive advantage.

This thesis explores the role of leadership and team development in shaping the efficiency and effectiveness of supply chain operations. By examining various human capital initiatives – such as leadership training, team-building activities, and professional development programs – the study aims to determine how these investments in personnel skills and collaboration enhance operational performance. Drawing on relevant literature and case examples, the research will highlight best practices that empower teams, foster innovation, and drive sustainable competitive advantages in supply chain management.

Collaborative Planning, Forecasting, and Replenishment (CPFR) promotes joint planning and forecasting between suppliers and buyers to boost supply chain efficiency. This thesis examines the implementation of CPFR models across various industries, identifying success factors and analyzing challenges in their adoption.

Collaborative Planning, Forecasting, and Replenishment (CPFR) promotes joint planning and forecasting between suppliers and buyers to boost supply chain efficiency. This thesis examines the implementation of CPFR models across various industries, identifying success factors and analyzing challenges in their adoption.

Strategic partnerships between companies and their suppliers can significantly enhance the efficiency and competitiveness of the entire supply chain. This thesis explores the key factors for successful supplier partnerships, including clearly defined shared objectives, top management support, and mutual trust.

Strategic partnerships between companies and their suppliers can significantly enhance the efficiency and competitiveness of the entire supply chain. This thesis explores the key factors for successful supplier partnerships, including clearly defined shared objectives, top management support, and mutual trust.

This thesis examines how heightened trade tariffs and protectionist measures are reshaping global supply chain dynamics, with a specific focus on supplier collaboration strategies. Through expert interviews, the study will explore how businesses adapt sourcing practices, renegotiate contracts, and streamline communication to mitigate the risks posed by evolving tariff regulations. The findings will illuminate best practices and strategic insights for effectively collaborating with suppliers in an era of increased protectionism, ultimately guiding organizations to maintain competitiveness and resilience amid changing trade policies.

Small and medium-sized enterprises (SMEs) are vital components of global supply chains. However, with advancing digitalization, they face unique challenges. This thesis investigates how SMEs can be effectively integrated into digital supply chains, the technologies involved, and strategies to overcome barriers.

Small and medium-sized enterprises (SMEs) are vital components of global supply chains. However, with advancing digitalization, they face unique challenges. This thesis investigates how SMEs can be effectively integrated into digital supply chains, the technologies involved, and strategies to overcome barriers.

The platform economy is fundamentally transforming the structure of traditional supply chains. This thesis analyzes how digital platforms influence interactions between suppliers, manufacturers, and customers, and the consequent effects on existing business models.

The platform economy is fundamentally transforming the structure of traditional supply chains. This thesis analyzes how digital platforms influence interactions between suppliers, manufacturers, and customers, and the consequent effects on existing business models.

Small and medium-sized enterprises (SMEs) are particularly vulnerable to geopolitical disruptions but can also demonstrate significant resilience. This thesis will explore how SMEs from various sectors have adapted their supply chain strategies in response to events such as Brexit, the US-China trade conflict, and the Russia-Ukraine war. Through expert interviews and an in-depth analysis of selected case studies, the research will uncover the challenges faced by SMEs and the strategic adaptations they implemented to maintain competitiveness. The findings will offer recommendations for strengthening SME resilience in future disruptive scenarios.

This thesis will explore how the size of firms—ranging from small enterprises to large multinational corporations—impacts their ability to build and sustain supply chain resilience across different industries. Through expert interviews, the study will assess how resources, organizational agility, and collaboration networks influence resilience strategies. The findings will provide a nuanced understanding of how firm size shapes resilience and offer recommendations for improving supply chain resilience based on the characteristics of different industries and organizational scales.

Sustainable Supply Chain Finance (SSCF) merges financial strategies with sustainability goals by linking financing conditions to the environmental and social performance of suppliers. This thesis examines the implementation of SSCF instruments, their impact on the supply chain, and associated challenges.

Sustainable Supply Chain Finance (SSCF) merges financial strategies with sustainability goals by linking financing conditions to the environmental and social performance of suppliers. This thesis examines the implementation of SSCF instruments, their impact on the supply chain, and associated challenges.

The use of algorithmic forecasting to identify risks in supply chains is gaining prominence. This thesis explores how such technologies affect labor standards and the role of workers‘ representation in this context.

This thesis aims to analyze the existing literature on the integration of Environmental, Social, and Governance (ESG) considerations in supplier selection processes. By systematically reviewing and synthesizing scholarly articles, industry reports, and relevant case studies, the study seeks to identify key themes, methodologies, and emerging trends in ESG-focused procurement. The findings will provide an understanding of best practices and challenges, offering insights for organizations looking to incorporate ESG factors into their supplier selection strategies and laying the groundwork for further research in sustainable supply chain management.

The research topic “Environmental, Social, and Governance (ESG) Factors in Supplier Selection – Multiple Case Study” focuses on examining how organizations integrate ESG considerations into their supplier selection processes. Using a multiple case study approach, this thesis aims to identify best practices, challenges, and strategic implications of prioritizing ESG factors in different industries and contexts. By analyzing real-world examples, the study will explore how companies balance financial objectives with sustainability, ethical conduct, and responsible governance. The findings will offer insights into effective ESG-driven supplier selection criteria and highlight pathways for organizations to foster more sustainable, socially responsible, and transparent supply chains.

Predictive analytics enables companies to anticipate potential risks in the supply chain and take proactive measures. This thesis investigates the implementation of predictive analytics in supply chain risk management and evaluates its effectiveness.

This thesis investigates how Environmental, Social, and Governance (ESG) factors are expected to shape global supply chains by the year 2035. Employing a Delphi method, this research will gather expert insights to forecast future developments, identify emerging challenges, and explore strategic opportunities for ESG integration within supply chain management. By capturing perspectives from industry leaders, policymakers, and academic experts, the study aims to provide a forward-looking framework for understanding and responding to evolving sustainability demands. The findings will help guiding organizations in proactively adapting to, and capitalizing on, ESG-related trends to ensure resilient and responsible supply chains over the coming decade.

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.

This thesis explores how digital technologies can be harnessed to enhance supply chain risk assessment during mergers and acquisitions (M&A). By conducting expert interviews with industry professionals, the study aims to uncover the most effective tools and practices for identifying, evaluating, and mitigating potential supply chain vulnerabilities in M&A transactions. The findings will offer insights into how emerging digital solutions – such as advanced analytics, artificial intelligence, and real-time monitoring – can streamline due diligence processes, optimize decision-making, and ultimately foster more resilient and successful post-merger integrations.

This bachelor thesis aims to discuss the theoretical foundations of AI in the context of SCM and to illustrate its practical application using best-practice examples. The potential of implementing AI solutions in supply chains will be examined.

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 „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 „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 – 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.