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Although the logistics sector is already experiencing an unprecedented lack of qualified staff, the environment is becoming more unstable in the future, necessitating competent leaders. Investigating elements that support the successful establishment of women in leadership roles is of utmost importance and is a chance to reach into a new pool of leadership abilities given how underrepresented women are in positions of power. This thesis aims to elaborate on the male perspective on female leadership by conducting interviews with decision-makers in the logistics industry.

Women are still underrepresented in logistics and especially in management positions. In view of increasing challenges, the logistics sector urgently needs more female decision-makers. Especially against the background of the shortage of skilled workers, many companies are already dealing with the question of how they can recruit more women. But what role do universities play in this? How do they try to inspire more women to study SCM? The aim of this work is to compare existing approaches within the framework of a case study and to work out challenges and missing aspects.

In Germany, the current shortage of professional drivers is estimated at 80,000. In addition, 32.4 percent of professional drivers are currently over 55 years old. When these 182,000 people retire in the next ten years, the existing shortage of skilled workers in the logistic will become even worse (FAZ, 2022). Truck driver is a typically male profession and the proportion of women is therefore still very low. In their new study, Scott and Davis-Sramek (2023) conduct a comprehensive empirical analysis of women in the US truck industry. The aim of this work is to examine female truck drivers in Europe/Germany and to work out what challenges they face and what changes they wish for in the future.

Due to globalization and the associated growing demand for talented supply chain managers, companies in SCM are increasingly focusing on HRM issues (Hohenstein et al., 2014). The aim of this work is to give an up-to-date overview of the state of research (literature review), to identify different research streams and to propose exciting topics for future research.

In the coming years, there will be a high gap between demanded and offered sustainable transportation solutions. Customers of logistics firms will strive to improve their environmental footprint through sustainable transportation. Logistics companies will increasingly buy sustainable transportation technologies like electric or hydrogen powertrains. As a result, logistics companies will come into a unique negotiating power. How will they react? Will customers of logistics companies, who for example pay the highest prices make the deals or will existing customers who have always behaved as partners in existing, long-term relationships be the winners?

The master’s thesis will develop important findings for logistics buyers. The insights will be conducted through a literature review and interviews with SCM experts.

Supply chain transparency is the practice of disclosing detailed and accurate information about products and supply chain operations to the public (Chen et al., 2015b; Swift et al., 2019; Gualandris et al., 2021). It is acknowledged that more companies than ever before are disclosing information about their products and supply chains to external stakeholders (Montecchi et al., 2021; Yang et al., 2021). However, seeking supply chain transparency can also be challenging and risky, despite these potential benefits. The major issue is that organizations find it difficult, time-consuming, and costly to collect accurate data from thousands of contractual ties with supply chain members and disclose comprehensive information (Foerstl et al., 2015; Shao et al., 2018), leading to much confusion and operational complexity (Montecchi et al., 2021). However, despite an increase in supply chain transparency related literature over the past decade, it is still under-researched and lacks sufficient practical and theoretical implications, compared with other topics in operations and supply chain management (Montecchi et al., 2021; Sodhi and Tang, 2019). For example, the role of emerging technologies in enabling supply chain transparency has been underplayed in current literature. Industry 4.0 is happening now and describes the trend toward automation and data exchange in production and operational processes (Hofmann et al., 2019), which include Internet of Things (IoT), cloud computing, blockchain, artificial intelligence (AI), big data analytics, etc. The aim of this master thesis is to investigate the application and implementation of information communication technologies designed to support information traceability and achieve supply chain transparency.

Customer engagement and more generally, the concept of engagement has emerged as a critical concept in marketing in the last decade as a means to create competitive advantage primarily focusing in how to build longer lasting and more relevant connections with customers (Kumar and Pansari, 2016; Wiersema, 2013). Initially defined as a customer’s cognitive, emotional, and behavioral responses toward brands or firms (Brodie et al., 2011), the concept has been explored in a range of consumer contexts, primarily to date as an individual phenomenon that occurs in dyadic interactions (Brodie et al., 2011; Vivek et al., 2016). Recent research also highlights importance and relevance of engagement in business-to-business (B2B) contexts (Alexander et al., 2018; Ekman et al., 2021; Jaakkola and Aarikka-Stenroos, 2019; Reinartz and Berkmann, 2018). In this regard, different conceptualizations such as actor engagement, (Brodie et al., 2019; Storbacka, 2019; Storbacka et al., 2016), collective engagement (Kleinaltenkamp et al., 2019), multi-actor engagement (Li et al., 2017; Verleye et al., 2014) or business actor engagement (Ekman et al., 2021) have emerged to reflect the diverse nature of the involved individuals in engagement creation processes. Despite those recent valuable contributions there is still a need to further explore and deepen knowledge in B2B engagement, to provide practical insights about how engagement can be facilitated and sustained in organizational settings. Specifically, viewing all ecosystem actors as able to interact, means that engagement applies to a much richer, and more diverse, set of actor combinations in B2B networks which may not only include humans but also technology and machines as actors (Storbacka et al., 2016). The aim of this master thesis is to explore the characteristics and motivations of the B2B engagement in various network structures (e.g., online, offline, internal, external, and intraorganizational).

Trust has become one of the most widely researched topics in organization studies (de Jong, et al., 2017). Often broadly understood as the willingness to make oneself vulnerable to the actions of another party (Mayer, et al., 1995; Rousseau, et al., 1998), trust plays a central role in virtually all intra- and inter-organizational interactions. Prior research suggests that trust can alleviate concerns of opportunism, which reduces inter-partner conflict and transaction costs (Anderson, et al., 2017; Zaheer, et al., 1998). Although the study of trust represents a long-standing area of inquiry in organization studies, several recent technological advancements and have dramatically changed the landscape in which trust is embedded, pointing to the need for a re-examination and extension of earlier accounts. Specifically, there are reasons to believe that digital technologies may cause trust to become more institution-based (Lumineau, et al., 2020), with formal mechanisms substituting for a history of interpersonal exchange as the source of trust. For instance, digital platforms facilitate trust between strangers (Abrahao, et al., 2017; Kuwabara, 2015; Mikołajewska-Zając, et al., forthcoming), blockchains can automate agreements with unknown partners (Hsieh, et al., 2018; Lumineau, et al., 2021), and artificial intelligence (AI) helps in assessing partners’ trustworthiness (Liu, et al., 2014). As a result, trust may become comparatively less personal (Seidel, 2018; Vanhala, et al., 2011) and more embedded in the institutional environment (Bachmann & Inkpen, 2011). Several aspects of digital technologies—including blockchains, big data, and AI—may have critical implications for trust in organizational settings. The aim of this master thesis is to investigate the concept of trust in relation to digital industrial platforms within the context of SCM and logistics.

To compete today, companies often resort to radical innovations in products, processes, services, profit models, supply chain configurations, and more (Bellamy, Dhanorkar, & Subramanian, 2020). At the same time, extreme turbulence caused by natural disasters and man-made disruptions pushes firms to build resilient supply chains (Sodhi & Tang, 2020). Both radical innovations and extreme disruptions, create a high level of uncertainty. Hence, these two seemingly opposite forces drive organizations and individuals to constantly evolve, adapt and improve in order to survive and thrive (Ketchen Jr & Craighead, 2021; Wieland, 2020). Radical innovations are man-made uncertainty that are usually associated with creating growth opportunities: upward uncertainty. Extreme disruptions could be either man-made or natural uncertainty that are usually associated with large decreases in performance: downward uncertainty. Despite these differences, both affect supply chain management by significantly disrupting routines and creating ambiguity about outcomes. Therefore, radical innovations and extreme disruptions have been well studied by supply chain scholars. However, these two streams of research very rarely intersect. High levels of uncertainty, either as a driving force or a consequence, are associated with both radical innovations and extreme disruptions. Hence, the occurrence of one could trigger the emergence of the other. Innovations could either trigger or prevent disruptions. For instance, the development, production and distribution of new products or services introduces new suppliers, processes or even business models, thus increasing the likelihood of supply chain disruptions. Equally, disruptions could create opportunities and motivations for firms to innovate. A new environmental policy could disrupt supply chains by banning the sourcing of certain materials, which would then motivate firms to invest in green innovations. The aim of this master thesis is to explore the mutual causality between innovations and disruption by bridging the supply chain innovation and disruption literatures.

In the face of climate change and growing resource scarcity, global supply chains must fundamentally change their behaviour in the sourcing, production, delivery, use and recovery of materials to maintain current consumption habits (Hazen et al. 2017). In this context, circular supply chain models offer enormous sustainability potential compared to classical linear forms (Farooque et al. 2019). Industry 4.0 technologies are expected to have a positive impact on circular economy capabilities in companies (Da Hennemann Hilario Silva und Sehnem 2022) and enable circular supply chains (Hettiarachchi et al. 2021). While technologies such as big data analytics or artificial intelligence enable recycling, waste reduction and process efficiency (Bag et al. 2021), the internet of things supports energy management and smart transportation (Esmaeilian et al. 2020). Accordingly, research interest in the synergies and potentials of circular supply chains and industry 4.0 technologies is growing (Nascimento et al. 2019; Dev et al. 2020; Lopes de Sousa Jabbour et al. 2018), establishing the concept of smart circular supply chains (Kayikci et al. 2022). Since industry 4.0 technologies are highly reliant on information and data, the questions arises as to what information processing requirements emerge on the way to smart circular supply chains and what capacities companies will need to develop to meet them (Galbraith 1974; Tushman und Nadler 1978). The aim of this master thesis is to develop future projections by conducting a literature review, expert interviews and an expert workshop.

Artificial intelligence has become a cornerstone of numerous business models and has been integrated into the strategies of many companies in industries such as healthcare, retail, and manufacturing. The technology is also already being used by large companies in supply chain management, for example for forecasting and fulfilment tasks. (Dwivedi et al. 2021) Artificial intelligence can further be used in various supply chain tasks including supply chain disruption prevention (Akhtar et al. 2022), supplier selection, inventory management or vehicle routing (Vishwakarma und Singh 2022). Apart from optimization, automation and performance improvements, Artificial intelligence can also play an important role in sustainable supply chain management (Dhamija und Bag 2020). Fields of application reach from carbon emission assessments and data analytics to sustainable transportation and reverse logistics  models (Naz et al. 2022). Against the backdrop of increasing pressure from stakeholders such as customers and governments (Seuring und Müller 2008), achieving sustainability in the supply chain is gaining strategic importance. Thus, it is of interest to analyse why and how sustainable companies are adopting and implementing artificial intelligence technologies for sustainable supply chain management. The aim of this master thesis is to conduct a multiple case study to investigate the constraints and opportunities of artificial intelligence for sustainable supply chain management and its context.

Artificial intelligence has become a cornerstone of numerous business models and has been integrated into the strategies of many companies in industries such as healthcare, retail, and manufacturing. The technology is also already being used by large companies in supply chain management, for example for forecasting and fulfilment tasks. (Dwivedi et al. 2021) Artificial intelligence can further be used in various supply chain tasks including supply chain disruption prevention (Akhtar et al. 2022), supplier selection, inventory management or vehicle routing (Vishwakarma und Singh 2022). Apart from optimization, automation and performance improvements, Artificial intelligence can also play an important role in sustainable supply chain management (Dhamija und Bag 2020). Fields of application reach from carbon emission assessments and data analytics to sustainable transportation and reverse logistics  models (Naz et al. 2022). Against the backdrop of increasing pressure from stakeholders such as customers and governments (Seuring und Müller 2008), achieving sustainability in the supply chain is gaining strategic importance. Thus, it is of interest to analyse why and how companies are adopting and implementing artificial intelligence technologies for sustainable supply chain management. The aim of this bachelor thesis is to conduct a systematic literature review on the current state of research on artificial intelligence and its application for sustainable supply chain management.

Increasing regulatory reporting requirements such as the German supply chain due diligence law or the European Sustainability Reporting Standards pose major challenges for affected companies. Since a large part of the required sustainability information, such as product carbon footprints, waste generation or energy consumption encompasses the entire supply chain, companies are dependent on data provided by their suppliers (Genovese et al. 2013). The quality and trustworthiness of the supplied sustainability information is difficult to verify, leading to information asymmetries between suppliers and buying companies (Delbufalo und Bastl 2018; Dahlmann und Roehrich 2019). Digital technologies are expected to change the prevailing interaction and governance mechanisms between buyers and suppliers leading to more visible and verifiable information (Barbieri et al. 2021). However, research on the impact of different digital solutions on the reliability of supply chain sustainability information is scarce. Thus, it is worth investigating how digitalization can help overcome the prevailing information asymmetries. The aim of this bachelor thesis is thus, to conduct a multiple case study to investigate how companies can reduce sustainability information asymmetries between buyers and suppliers with the use of digital solutions.

In the face of global warming, reducing CO₂-emissions has become a key challenge for researchers, governments and practitioners around the world (Kovacikova et al. 2021). An increasing number of countries is committing to net-zero emission targets (IEA 2020). Their goal is to create net-zero systems, which “emit no CO₂, encompassing energy and industry processes.” (Azevedo et al. 2021, S. 1) However, supply chain activities of all kind, such as procurement, production or distribution, are associated with the emission of CO₂ (Mishra et al. 2022). A factor possibly influencing the reduction of supply chain emissions and thus the achievement of the net-zero goal is digitalization, i.e. emerging digital technologies such as industry 4.0 or blockchain (Singh et al. 2022; Mishra et al. 2022). It is therefore of interest to examine drivers, approaches and barriers to achieve the net-zero target in global supply chains with the help of innovative digital technologies. The aim of this bachelor thesis is to conduct a systematic literature review to investigate the current state of research on digitalization and its potential to achieve the net-zero target in global supply chains.