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Für mehr als 70% der Patienten spielt die Empfehlung des Arztes bei der Wahl einer Klinik für einen elektiven Eingriff eine Rolle. Eine langfristige Bindung zu den einweisenden Ärzten als Gatekeeper und Lenker von Patientenströmen ist aus Kliniksicht essentiell. Ziel der Arbeit ist es, Einflussfaktoren und Wirkmechanismen der Einweiserbindung auf den wirtschaftlichen Erfolg im Krankenhaus am Beispiel der Region 10 zu untersuchen. Das Konstrukt der Einweiserbindung wird operationalisiert als bisheriges Verhalten und zukünftiges Verhalten. Als Erfolgsgrößen werden Erlöskennzahlen wie der Case Mix Index herangezogen. Zur Beantwortung der Forschungsfragen wurden drei Datenquellen erhoben. Die Ergebnisse zeigen, dass der einweisende Arzt durch sein bisheriges Verhalten die Krankenhauswahl seiner Patienten positiv beeinflussen kann. Weiterhin ergeben die Analysen, dass jährlich ca. 17% der Patienten, die in der Region 10 leben, die Region für einen Krankenhausaufenthalt verlassen. Darunter auch Indikationen, die durchaus in einem regionalen Krankenhaus behandelbar sind. Die Wirkung eines Einweiserportals zur Bindung der niedergelassenen Ärzte konnte nicht nachgewiesen werden.
This cumulative dissertation examines possible applications of digital assistants and their optimal design. The first article analyzes whether the emotional support from a digital assistant has a positive effect on the customer’s satisfaction with the service or his persistence. The second article examines digital assistants in their possible role as companions. The effects of the presence of a digital companion on customer satisfaction are examined. The third article deals with digital assistants in their possible role as instrumental supporters. While digital assistants appear through written/recorded language or a visualized embodiment in the context of emotional support or as a companion, they act more inconspicuously while providing instrumental support (e.g. as an autopilot of an autonomous vehicle). Therefore, the article focuses on a possible anthropomorphization of the autonomous digital assistant and examines whether the perceived risk of the user is reduced and his satisfaction with the service can be increased.
This study comprises three individual contributions to the research focus on pricing of auditing services. Using German and European data sets, the empirical investigation examines, among other things, how different dimensions of size, possible interactions from a so-called Big 4 premium or fee cutting behavior, as well as different financial risk factors affect the level of auditing services.
The study 'Size effects and audit pricing: Evidence from Germany' shows, among other things, that of those auditors who also provide consulting services for their clients, only Big 4 auditors achieve higher fees for auditing services. Furthermore, the results of the study suggest that the Big 4 premium shown in previous studies for the German market is strongly influenced by a market leader premium. Taking into account the high relevance of company size as a factor in the pricing of audit services, the study also concludes that company size should rather be represented by non-financial variables such as the natural logarithm of the number of employees in order to exclude any interdependencies with other financial variables.
The study entitled 'The Big 4 premium: Does it survive an auditor change? Evidence from Europe' presents new findings on the impact of auditor changes on audit fees, with a special focus on a possible Big 4 premium. This combines the previous research on the Big 4 premium and fee cutting. Matching analyses are used to compare the audit fees of companies that switch to a Big 4 auditor with those companies that switch to a non-Big 4 auditor. As a result, a Big 4 premium can only be shown for those companies that do not change auditors. In the case of a change of auditor, the results show that Big 4 auditors are willing to give up this bonus or even accept a discount on non-Big 4 auditors. This discount usually persists in the first few years. Accordingly, the assumption is that Big 4 auditors are pursuing a "foot-in-the-door" strategy to win new clients. Based on these results, the existence of a Big 4 premium is strongly dependent on the decision of the respective company to change auditors.
The study 'Variation of financial risk over time and the impact on audit pricing' focuses on the consideration of financial risk factors and their development over time. The key assumption of the study is that continuity of relevant financial ratios reduces the risk position of the auditor and should be positively reflected in the audit fees. For companies that do not change auditors, the results show an influence of increased volatility of financial ratios on the level of audit fees. This leads to the assumption that in case of increased volatility in the financial ratios, companies could deliberately not change the auditor in order to send a sign of stability to third parties and, if necessary, accept a premium on the existing auditor's fees. In the case of a change of auditor, however, new auditors could waive a corresponding premium in order to win new clients.
Order picking and delivery are integral parts of many supply chains, especially those of retail and online trade. They are mostly non-value-adding, downstream processes, but they are responsible for the majority of logistics costs. Accordingly, the academic literature deals with both order picking and vehicle routing in a diverse and detailed manner. However, a holistic view of both processes is mostly not sufficiently taken into account. The interdependent effects on the operational planning level are only considered to a limited extent since the processes are usually considered isolated or sequential planning is assumed. This thesis examines different order picking and vehicle routing problems. Furthermore, it shows the advantages of integrative planning and develops exact and heuristic solution methods for the investigated problems.
The first paper develops a structural understanding of the subproblems of picking and delivery. In addition, the article illustrates the development of the research branch of integrative order picking and vehicle routing.
Further contributions examine practice-oriented problems in the field of micro-store deliveries (contribution 2), same-day deliveries (contribution 3), and the supply of supermarkets (contribution 4). In each case, different real-world constraints are included and different objectives are addressed. Furthermore, problem-specific integrative solution methods are developed and compared to classical approaches.
In many countries today, a rising life expectancy and the associated demographic shift, coupled with the advancements of modern medicine, has fueled an ever-increasing cost pressure on healthcare systems. A driving factor for these rising costs can be seen in inpatient stays in hospitals that in many cases are connected to cost-intensive treatments. A central concern of any hospital management in such an environment is therefore to understand how to make the best possible use of available resources. A decisive factor in this regard is the management of bed capacities.
The present cumulative dissertation comprises four contributions, which address
open research questions in the field of strategic, tactical and operative bed planning:
1 Walther, M., 2020. Strategical, tactical, and operational aspects of bed
planning problems in hospital environments. Submission planned to
Social Science Research Network (SSRN)
2 Hübner, A., Kuhn, H., Walther, M., 2018. Combining clinical departments
and wards in maximum-care hospitals. OR Spectrum 40, 679-709
3 Schäfer, F., Walther, M., Hübner, A., Kuhn, H., 2019. Operational
patient-bed assignment problem in large hospital settings including overflow
and uncertainty management. Flexible Services and Manufacturing
Journal 31, 1012–1041
4 Schäfer, F., Walther, M., Hübner, A., Grimm, D., 2020. Machine learning
and pilot method: tackling uncertainty in the operational patient-bed
assignment problem. Submitted to OR Spectrum on 13 February 2020
The first contribution sets out to provide an overview over the different hierarchical planning levels on which bed planning problems may be addressed. It should be noted in this context that several different aspects may be combined under the collective term “bed planning”. These may be delimited in terms of their scope and their planning horizon. A frequently used taxonomy in this context is the hierarchical subdivision of typical problems in health care into strategical, tactical and operational levels as provided by Hulshof et al. (2012). In the context of bed planning, a typical strategical problem is how to combine departments and wards to obtain benefits from pooled ward capacity. On a tactical level, an exemplary problem setting related to bed planning can be seen in devising master surgery schedules that optimize downstream bed occupancy levels as patients returning from surgery will require a bed for post-surgical recovery and monitoring. Finally,
on an operational level, patient-bed allocations need to be optimized while taking the objectives and constraints of patients and medical staff alike into account.
To start, the second contribution deals with the strategical problem of combining departments into groups and assigning pooled ward capacity to these groups with the goal of balancing bed occupancy levels within a hospital. Specifically, one of the underlying goals is to minimize the amount of beds required to meet a predetermined service level. However, merging ward capacities with the aim of simultaneously accommodating patients from different medical departments increases the complexity of organizing and ensuring proper care for these patients. This leads to so-called pooling costs. To tackle this problem, a modeling and solution approach is developed which is based on a generalized partitioning problem and is solved by integer
linear programming (ILP). This enables hospital management to determine the cost-optimal combination of all departments and wards in a hospital, while ensuring that predetermined thresholds with regard to maximum
walking distances for doctors and patients are adhered to.
Once pooled ward capacities are established, the solution space for allocating incoming patients to beds is greatly increased and the underlying allocation problem quickly becomes too complex to be handled without computational support. In this regard the third contribution ties in with the second contribution in that it deals with optimizing the operational patient-bed allocation problem. In order to enable optimal allocation of patients to beds, it is important to identify and take into account the individual needs and
limitations of the three main stakeholders involved, namely patients, doctors, and nursing staff. All of these stakeholders exhibit different and sometimes contradicting objectives and constraints, such that a trade-off has to be made that maximizes the overall utility for the hospital. In addition, the complexity of the problem is increased by the high volatility and uncertainty regarding patient arrivals, types of illnesses, and the resulting remaining lengths of stay of newly arriving patients. In order to address this situation,
a mathematical model and solution approach for the patient-bed allocation problem is developed that is designed to generate solutions for large, real-life operative planning situations. In addition to being able to deal with overflow situations, this solution approach further takes different patient types into account, for example by anticipating emergency patient arrivals.
Finally, the fourth contribution builds on the third contribution in that the modeling and solution approach to allocate patients to beds is extended by several aspects. As mentioned above, hospitals have to deal with uncertainty regarding the actual demand for beds. Here, the fourth contribution improves the anticipation of emergency patients by using machine learning. Specifically, weather data, seasons, important local and regional events, and current and historical occupancy rates are combined to better anticipate emergency inpatient arrivals. In addition, a hyper-heuristic approach is developed based on the pilot method defined by Voß et al. (2005). By combining the improved anticipation of emergency patients with this hyperheuristic approach significant improvements can be achieved compared to the solution approach presented in the third contribution.
In this cumulative dissertation, I investigate the relation between the cognitive complexity of work tasks and economic outcomes such as earnings, migration, and aggregate income growth. Existing theoretical and empirical research firmly established that human capital plays a major role in determining these outcomes. However, the literature to date has focused on a limited set of human capital measures, such as education, years of work experience, and basic demographic characteristics, and has largely ignored considerable individual variation attributable to occupational skills. By introducing novel skill measures derived from work tasks and using theoretical models combined with empirical evidence, I demonstrate the determining role played by occupational skills.
The first paper examines the connection between problem solving and lifecycle wage dynamics. I introduce a model of learning-by-doing which relates the intensity of complex tasks to the growth of problem solving skills and labour productivity. Using German administrative data, I find that workers in complex jobs receive static and dynamic wage premia and acquire relatively more human capital throughout life.
The second paper examines the selection pattern of Mexican migrants to the United States and shows that Mexican migrants have lower cognitive skills and higher manual skills compared to non-migrants. Using an extended version of the Roy-Borjas model, I show that differences in the returns to occupational skills explain the selection pattern better than differences in the returns to education and basic characteristics.
The third paper explores the role that complexity plays in economic development. I develop a regional model of endogenous growth which relates aggregate problem solving skills to the rate of technology adoption. In the model, migration costs and spillovers in technology adoption create persistent differences in regional income. By estimating growth regressions, I find that problem solving skills strongly predict per capita income growth in a sample of European regions.
The results collected in the dissertation have implications for economic development policies focused on human capital, projection and analysis of international migration, and evaluating long-term effects of recessions.
Die kumulative Dissertation befasst sich im Rahmen der holistischen Customer Experience (CX) zum einen mit unterbewussten Einflussfaktoren auf die CX und wie negative Effekte in diesem Zusammenhang gelindert werden können. Zum anderen wird die Customer Experience von einer Business-to-Business Perspektive analysiert. Insgesamt umfasst die Dissertation vier Beiträge:
Beitrag 1:
Stereotypes in Services – A Systematic Literature Review to Move from Scattered Insights to Generalizable Knowledge
Beitrag 2:
Overcoming Vulnerability: Channel Design Strategies to Alleviate Vulnerability Perceptions in Customer Journeys
Beitrag 3:
Are You Right for the Job? The Influence of Service Provider Stereotypes on Customer’s Willingness to Engage in Co-Production
Beitrag 4:
The Business-to-Business Customer Experience – An aggregated Company Experience Based on Multiple Department and Employee Journeys
Basierend auf der Annahme, dass die Customer Experience im Rahmen vieler Einflussfaktoren auch durch soziale Standards, Normen und Ideale beeinflusst werden kann, konzentriert sich der erste Artikel auf die Wirkung von Stereotypen in Dienstleistungsinteraktionen. Der Literaturüberblick identifiziert dabei zahlreiche Auswirkungen von Stereotypen, stellt dabei jedoch fest, dass Maßnahmen, um diese Auswirkungen zu mildern deutlich weniger untersucht wurden. Vor diesem Hintergrund untersucht der zweite Beitrag konzeptionell wie das Channel Management dazu beitragen kann, die CX von benachteiligten Kundengruppen zu verbessern. Der dritte Beitrag adressiert eine weitere Forschungslücke die in Beitrag 1 identifiziert wurde, nämlich fehlende Einblicke in den Prozess, wie soziale Beurteilungen zu negativen Kundenerlebnissen führen. Mittels zweier Studien zeigt der Beitrag, dass Kunden auf Grund von Stereotypen weniger bereit sind mit Mitarbeitern zu interagieren, was den Erfolg der Dienstleistungserbringung gefährdet. Der vierte Beitrag nimmt eine deutlich abweichende Perspektive im Rahmen der CX ein und untersucht die bisher wenig beachtete CX in einem gewerblichen Business-to-Business Kontext.