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Amid a persistent shortage of midwives in Germany, this dissertation investigates how preference-based care can inform sustainable and equitable solutions for both childbearing women and midwifery professionals. Integrating four studies, this work employs mixed-methods research—including discrete choice experiments (DCEs), qualitative content analysis, and systematic literature review—to explore mothers’ and midwives’ preferences, willingness to pay, and perceptions of care in times of professional scarcity and systemic disruption.
Study I applies a discrete choice experiment to evaluate the preferences of mothers regarding different configurations of midwifery care and their willingness to pay (WTP) for those services. The study reveals that women place the greatest value on continuity of care, personal consultations during pregnancy and postpartum, and guaranteed access to a known midwife. Notably, mothers showed a willingness to pay substantial out-of-pocket costs to secure such preferred services. Best-worst scaling further prioritized features such as accessibility and empathy, underscoring the significance of relational continuity in maternal care.
Study II builds on these insights by analyzing how maternal care preferences shifted during the COVID-19 pandemic. Using a follow-up survey and qualitative content analysis, this study highlights a clear trend: women increasingly sought flexible, hybrid (online and offline) midwifery models, emphasizing safety, availability, and professional trust. The crisis intensified structural challenges in accessing care, but also accelerated openness to digital formats, such as video consultations, which many women viewed as viable complements to in-person support. The findings point to the pandemic as a turning point in shaping expectations for future maternity care.
Study III shifts the focus from care recipients to providers, examining why qualified midwives choose not to offer birth assistance, especially in clinical settings. A discrete choice experiment with inactive midwives reveals that unfavorable working conditions—characterized by low autonomy, high liability risk, understaffing, and rigid hospital hierarchies—are key deterrents. The study identifies policy levers that could incentivize midwives' return to the delivery room, including flexible scheduling, fair pay, and institutional support. These insights provide evidence-based recommendations to address the declining number of active birth-assisting midwives.
Study IV adds a broader diversity perspective through a systematic experiential literature review on male midwives. Historically underrepresented and often marginalized, male midwives face gendered barriers within an overwhelmingly female profession. Themes emerging from the synthesis include identity struggles, mixed acceptance by female colleagues and clients, and restricted professional visibility. However, the inclusion of men in midwifery was also seen to bring unique interpersonal strengths and foster a more inclusive care environment. This final chapter argues for structural changes to midwifery education, public perception, and workplace integration to support gender diversity.
Together, these studies illustrate the multifaceted nature of preference-based midwifery care. They offer a comprehensive, empirically grounded foundation for policy reforms aimed at improving maternal healthcare provision in Germany. The research emphasizes that addressing midwifery shortages requires more than numerical staffing increases; it demands a systemic transformation rooted in the preferences, values, and lived realities of both care recipients and providers.
This dissertation investigates the value of customer behavior in supply chain management through the application of (big) data analytics in demand forecasting. The use of advanced analytics in supply chain management is not novel. However, the growing expansion of data volumes provides companies with new opportunities to optimize their supply chain. Despite the rising interest from both academia and practice and the recent increase in publications in this area, empirical insights are still limited. At the same time, changes in customer expectations towards instant product delivery require companies to rethink their supply chain, where accurate demand forecasts are often at the core of enabling efficient and flexible processes. This makes the development of demand prediction models that can be used in practice especially relevant. We1 analyze the use of customer behavior in demand forecasting in three separate research papers. Leveraging data from research partners in the online fashion and construction industry, we assess the potential of the developed prediction models in three areas of application in supply chain management, namely order fulfillment, order picking, and inventory planning. In the first paper, we develop a prediction model for anticipatory shipping in the fashion industry, which predicts customers’ online purchases with the aim of shipping products in advance, and subsequently minimizing delivery times. Using various forecasting methods and data on customers’ behavior on the website, we test if, and how early, it is possible to predict online purchases. Results indicate that customer purchases are, to a certain extent, predictable, but anticipatory shipping comes at a high cost due to wrongly sent products. The second paper assesses the extent to which clickstream data can improve forecast accuracy for fashion products. Specifically, we assess which clickstream variables are most suitable for predicting demand, and identify the products that benefit most from this. Results indicate that clickstream data is especially useful for forecasting medium- and certain intermittent-demand products. A simulation of order picking for these products shows that using clickstream data in the forecast substantially decreases picking times. The third paper investigates how sequential pattern mining can be used to determine products with correlated demand, and how to leverage this as an input into forecasting for a supplier in the construction industry. We find that sequential pattern mining may be beneficial when used in combination with traditional forecasting methods, and that support vector regression models seem especially suited to forecast intermittent-demand products. An application to inventory planning shows that our developed forecasting model might reduce the company’s costs of inventory holding and lost sales by up to 6.9%. Overall, our research highlights the value of using customer behavior to enhance demand forecasting and the benefit of using improved forecasts in various applications in supply chain management.
1Referring to the authors of the respective chapters as noted at the beginning of each chapter.
With the start of digitalization and the initiation of a whole new industry of digital services, some of the well-established marketing wisdoms are now under scrutiny. This also holds for the importance of customer win-back for any firm – a belief that has actually never really been questioned. While related research focuses on mature industries and highlights the profitability of win-back, to date no study known to the authors has addressed the role of reacquired customers compared to first-lifetime customers in the interplay of acquisition and retention for digital firms. This is especially important when assessing firms’ current winback strategy and forecasting the development of acquisition and retention success of reacquired compared to first-lifetime customers. This study proposes a win-back assessment framework that enables firms to assess their win-back strategy and to detect problems in acquisition or retention of first-lifetime and reacquired customers. The authors demonstrate the use of framework on transaction data from a digital subscription service and data from a field experiment with that same service provider. They analyze the data from a new analytical perspective compared to extant research, which they call “cohort perspective” and jointly investigates acquisition and retention of first-lifetime and reacquired customers, who started their subscription around the same time (i.e. cohort). The results show the need for the cohort perspective by unveiling the contradiction that reacquired customers can “live” longer than in their previous lifetime (on average 328 days), but that they “live” shorter than first-lifetime customers of the same cohort ( ̶ 19%). The authors explain the rationale of this observation and discuss its implications.
Airport slot allocation
(2023)
This dissertation addresses the concept of airport slot allocation as a major regulatory directive in air transport management. In three sequential parts, today’s slot allocation procedure, addressing the assignment of time windows for departure and landing operations at coordinated airports, is being assessed and critically evaluated. The three sections evolve from the evaluation and revision of a suitable criteria set to the development and implementation of a network solution. As a key feature, a carbon emissions price including the air carriers’ CO2 emissions is being provided, serving as the allocation principle. In all three parts, explicit reference to the IATA Worldwide Slot Guidelines, representing today’s regulatory framework, is being provided, highlighting explicit deficits and drawbacks of that solution. In the first part, the Analytic Hierarchy Process (AHP), as a concept of decision making based on a comparison of criteria and alternatives, is being applied guiding the allocation decision at a single airport. In this section, a set of multiple criteria is being proposed and weighted according a set of slot coordinators’ preferences. As a key feature, the concept of Analytic Hierarchy Process (AHP) is being extended by the conduction of a Pairwise Comparison-based Preference Measurement (PCPM) representing one stage of the Analytic Hierarchy Process (AHP). In part two, the perspective of the dissertation changes from a single-point to a multiple-point allocation environment. In this part, a model is being provided that includes the allocation of slots in an airport network. As a key feature, slots are being allocated such that the two complementary cost functions are being minimized. On one hand, the developed carbon cost function includes the minimization of the carbon footprint per traveling passenger. On the other hand, the developed handling cost function is being minimized incorporating a dedicated airport perspective to the solution. In part three, the proposed model is being further extended by the incorporation of a third directive, the minimization of connection cost, related to the application of solution in a hub-and-spoke network. As a result, the study demonstrates how slot allocation can be conducted efficiently in an airport network, and how the consideration of the carbon footprint per traveling passenger serves to calculate the allocation optimum.
The Veblen effect revisited
(2018)
This dissertation revisits the Veblen Effect, a phenomenon in which higher prices increase consumer demand due to perceived prestige, particularly in the context of luxury goods and experiences. Combining qualitative insights, a comprehensive literature review, experimental methods, and real-world data analysis, the dissertation aims to deepen the theoretical and empirical understanding of this counterintuitive consumption behavior. The work contributes to the growing body of research on conspicuous and status-driven consumption, with direct implications for marketing, pricing strategies, and luxury brand management.
The study begins with a qualitative pre-study that explores consumer perceptions and motivations related to luxury purchases. Interviews and open-ended surveys confirm the relevance of the Veblen Effect in real-world settings and identify status signaling and social comparison as core drivers. This exploratory phase provides foundational insights for the design of subsequent empirical work.
The second part presents a literature review that maps the evolution of research on the Veblen Effect and related constructs such as (in)conspicuous consumption. The review categorizes and critiques both empirical and conceptual contributions, highlighting a gap in empirical studies that consider the interaction of intrinsic and extrinsic motivations in luxury consumption.
To address this gap, a quantitative pre-study follows, identifying appropriate product categories and brands for empirical testing. This informs the main experimental study, which investigates how intrinsic motivations (perfectionism, hedonism) and extrinsic motivations (Veblenian status signaling, snob appeal, bandwagon effects) interact with price perception. Results show that price increases can enhance desirability, especially among consumers driven by extrinsic motives, validating the Veblen hypothesis in controlled settings.
The final empirical chapter analyzes transactional data from the luxury hotel industry, providing evidence of the Veblen Effect in real purchase contexts. By segmenting consumer behavior into motivational clusters (e.g., Veblenian, snob, hedonist), the study reveals that higher room prices are associated with increased demand in status-driven contexts, while intrinsic motivations (e.g., quality seeking) moderate this effect. This chapter demonstrates the practical relevance of Veblenian consumption in real markets and provides actionable insights for revenue management and pricing strategies.
In sum, this dissertation offers a multi-method investigation into how and why the Veblen Effect persists in modern consumer behavior. It shows that while luxury consumption is often driven by social signaling, the interplay of psychological motivations determines the strength and presence of price-driven desirability. The findings advance theoretical models of luxury demand and offer strategic recommendations for luxury brand positioning, pricing, and segmentation.
In increasingly saturated and fast-paced markets, the perceived newness of products—rather than objective innovativeness—plays a critical role in influencing consumer decision-making. This dissertation explores the concept of Perceived Product Newness (PPN) from the consumer’s perspective, combining a comprehensive literature review with a series of empirical studies to investigate the determinants, mechanisms, and outcomes of PPN at the point of sale. The aim is to offer both theoretical clarity and practical insights for marketers seeking to strategically leverage newness perceptions.
Chapter 2 presents a systematic literature review of the PPN concept. Drawing on empirical, conceptual, and meta-analytical research, the chapter synthesizes findings on the antecedents and consequences of PPN. Key determinants include product design elements (e.g., packaging, labeling, innovation claims), marketing communications, and contextual factors like market trends and consumer involvement. The review also identifies PPN's outcomes, such as increased attention, product evaluation, purchase intention, and willingness to pay. A significant contribution of this chapter is the identification of ambiguity in the use of the term “newness”, which spans objective innovation, subjective perception, and contextual novelty. It concludes with a structured agenda for future research and managerial implications for creating consistent and effective PPN strategies.
Chapter 3 reports a series of experimental studies testing how product design cues at the point of sale influence PPN and downstream consumer responses. Grounded in consumer psychology and marketing theory, the experiments manipulate package shape deviation, benefit claims (functional vs. emotional), and explicit newness cues, and examine their effects on perceived newness, perceived value, and purchase intention. Findings from four studies reveal that deviations from the category prototype—particularly in packaging shape—enhance PPN, especially when coupled with benefit claims or newness signals. Importantly, the type of benefit claim (emotional vs. functional) moderates the strength of the effect, and a monetary evaluation study confirms that consumers are willing to pay more for products they perceive as new. Mediation analyses show that perceived value and product uniqueness serve as psychological mechanisms underlying the effect of design cues on purchase behavior.
Chapter 4 synthesizes the key insights from the literature review and experimental analyses. It concludes that PPN is a multi-dimensional, context-sensitive construct that can be deliberately shaped through product and packaging design, communication strategies, and category management. The dissertation offers three primary contributions:
A conceptual clarification of PPN that integrates scattered research and resolves definitional inconsistencies.
Empirical evidence demonstrating how subtle design elements and positioning strategies can be used to enhance perceptions of newness.
A set of managerial implications for developing more effective product launches and in-store marketing initiatives.
Overall, this dissertation deepens the understanding of how consumers form perceptions of newness and provides actionable insights for firms seeking to stand out in increasingly competitive retail environments. It calls for more attention to subjective consumer perceptions in innovation research and offers a roadmap for future exploration of this critical yet underexamined construct.