FEMM - Working Paper Series - 2023


Working Paper Series auf der OVGU-Journals-Plattform


Hans-Peter Burghof, Horst Gischer

Competition, Resilience, and Stability – Implications for Institutional Protection Schemes and Systemic Risk in the European Banking Union


The finalization of the European Banking Union (EBU) requires the completion of the third pillar, the system of depositor protection. However, whereas the two first pillars, while set-ting common standards, allow for elements of decentralization and institutional diversity, some authors claim that the third pillar is only established with a single and joint deposit guarantee scheme (DSG) for all countries in the Monetary Union. Limits to joint liability, or alternative concepts like the existing institutional protection schemes (IPS) in some member states, are seen as imperfections that can only be temporarily accepted for political reasons. According to this view, such elements of compromise and differentiation should be over-come.

In our paper, we argue that neither the DGS nor the IPS is always efficient. Choosing an IPS is a response to a special way to organize banking business. It contains no element of regulato-ry arbitrage, as it represents a cost-efficient mean to protect depositors in decentralized banking networks marked by a larger number of regional banks and by a business model with a strong focus on long-term client relationships. Making decentralized banking and rela-tionship banking costlier through discriminating regulations (like the non-recognition of IPS) would thus have a negative impact on the common market, as it distorts the competition between different organizational concepts of banking.

JEL:  G21, G28, L22, L51
Keywords:  European Banking Union, banking industry, regulation, systems competition


Shohre Zehtabian, Marlin W. Ulmer

Consistent Time Window Assignments for Stochastic Multi-Depot Multi-Commodity Pickup and Delivery


In this paper, we present the problem of assigning consistent time windows for the collection of multiple fresh products from local farmers and delivering them to distribution centers for consolidation and further distribution in a short agri-food supply chain with stochastic demand. We formulate the problem as a two-stage stochastic program. In the first stage, the time windows are assigned from a set of discrete time windows to farmers and in the second stage, after the demand is realized, the collection routes are planned by solving yet a newly introduced multi-depot multi-commodity team orienteering problem with soft time windows. The objective is to minimize the overall travel time and the time window violations. To solve our problem, we design a (heuristic) progressive hedging algorithm to decompose the deterministic equivalent problem into subproblems for a sampled set of demand scenarios and guide the scenarios toward consensus time windows. Through numerical experiments, we show the value of considering demand uncertainty over solving the deterministic expected value problem and the superiority of our approach over benchmarks when it comes to reducing the routing cost as well as the inconvenience for farmers.

Keywords:  Agri-food supply chains, Time window assignment, Consistency, Two-stage stochastic programming, Progressive hedging algorithm


Marlin W. Ulmer, Justin C. Goodson, Barrett W. Thomas

Optimal Service Time Windows


Because customers must usually arrange their schedules to be present for home services, they desire an accurate estimate of when the service will take place. However, even when firms quote large service time windows, they are often missed, leading to customer dissatisfaction. Wide time windows and frequent failures occur because time windows must be communicated to customers in the face of several uncertainties: future customer requests are unknown, final service plans are not yet determined, and when fulfillment is outsourced to a third party, the firm has limited control over routing procedures. Even when routing is performed in-house, time windows typically do not receive explicit consideration. In this paper, we show how companies can communicate reliable and narrow time windows to customers in the face of arrival time uncertainty. Under mild assumptions, our main result characterizes the optimal policy, identifying structure that reduces a high-dimensional stochastic non-linear optimization problem to a root-finding problem in one dimension. The result inspires a practice-ready heuristic for the more general case. Relative to the industry standard of communicating uniform time windows to all customers, and to other policies applied in practice, our method of quoting customer-specific time windows yields a substantial increase in customer convenience without sacrificing reliability of service, providing results that nearly achieve the lower bound on the optimal solution. Our results show that (i) time windows should be tailored to individual customers, (ii) time window sizes should be proportional to the service level, (iii) larger time windows should be assigned to earlier requests and smaller time windows to later requests, (iv) larger time windows should be assigned to customers further from the depot of operation and smaller time windows to closer customers, and (v) two time windows for one customer are helpful in some cases.

Keywords:  time windows, service routing, non-linear optimization

Letzte Änderung: 03.02.2023 - Ansprechpartner: Webmaster