Junior Management Science, Volume 5, Issue 1, March 2020

Fachbereich Wirtschaftsinformatik

Stochastic Optimization of Bioreactor Control Policies Using a Markov Decision Process Model

Quirin Stockinger, Technische Universität München (Masterarbeit)
Junior Management Science 5(1), 2020, 50-80

Biopharmaceuticals are the fastest-growing segment of the pharmaceutical industry. Their manufacture is complicated by the uncertainty exhibited therein. Scholars have studied the planning and operation of such production systems under some uncertainties, but the simultaneous consideration of fermentation and resin yield uncertainty is lacking so-far. To study the optimal operation of biopharmaceutical production and purification systems under these uncertainties, a stochastic, dynamic approachisnecessary. This thesis provides such a model by extending an existing discret estate-space, infinite horizon Markov decision process model of upstream fermentation. Tissue Plasminogen Activator fermentation and chromatography was implemented. This example was used to discuss the optimal policy for operating different fermentation setups. The average per-cycle operating profit of a serial setup was 1,272 $; the parallel setup produced negative average rewards. Managerial insights were derived from a comparison to a basic, titer maximizing policy and process sensitivities. In conclusion, the integrated stochastic optimization of biopharma production and purification control aids decision making. However, the model assumptions pose room for further studies.

Keywords: Markov decision process; biopharmaceuticals production; fermentation uncertainty; chromatography resin; stochastic performance decay.

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Mobile App Service Quality Dimensions and Requirements for Mobile Shopping Companion Apps

Tobias Wulfert, Westphalian Wilhelms-University Münster (Masterarbeit)
Junior Management Science 4(3), 2019, 339-391

The increasing utilization of mobile apps for shopping leads retailers to provide customers with dedicated mobile shopping companion apps to create an omni-channel shopping experience involving traditional brick-and-mortar, electronic and mobile business. Mobile shopping companion apps extend the traditional and electronic services of brick-and-mortar retailers by an additional mobile channel providing the customer with a digital companion supporting the shopping within and outside the stores using mobile technology. A twofold approach is pursued in this thesis. Firstly, a structured literature review is conducted to identify candidate dimensions for developing a scale for measuring the service quality of mobile shopping companion apps. Secondly, design requirements for improving the service quality ofthese mobile apps are deduced from online customer reviews of three exemplary mobile shopping companion apps applying a qualitative content analysis. The mobile app service quality of mobile shopping companion apps can be measured using a hierarchical and multi-dimensional scale consisting of three primary dimensions, seven secondary dimensions and 22 related items. The primary dimensions interaction quality, environment quality and outcome quality structure the secondary dimensions responsiveness, information, security and privacy, design, performance, technical reliability and valence. Based on these dimensions, 22 implementation guidelines and 14 service design requirements are derived as potential areas for optimizing the mobile app service quality of mobile shopping companion apps and achieving a high overall service quality. A mobile shopping companion app should include a set of features consisting of 16 features from three different areas. Results show that measuring the service quality of mobile shopping companion apps require for a tailored measurement scale. Equally, design requirements are proposed for this particular category of mobile apps. Retailers should provide a single mobile shopping companion app providing all features and mobile services to the customer.

Keywords: mobile service; mobile commerce; shopping companion; service quality.

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Extending Kolkata Paise Restaurant Problem to Dynamic Matching in Mobility Markets

Layla Martin, Technische Universität München (Masterarbeit)
Junior Management Science 4(1), 2019, 1-34

In mobility markets – especially vehicle for hire markets – drivers offer individual transportation by car to customers. Drivers individually decide where to go to pick up customers to increase their own utilization (probability of carrying a customer) and utility (profit). The utility drivers retrieve from customers comprises both costs of driving to another location and the revenue from carrying a customer and is thus not shared between different drivers. In this thesis, I present the Vehicle for Hire Problem (VFHP) as a generalization of the Kolkata Paise Restaurant Problem (KPRP) to evaluate different strategies for drivers in vehicle for hire markets. The KPRP is a multi-round game model presented by Chakrabarti et al. (2009) in which daily laborers constitute agents and restaurants constitute resources. All agents decide simultaneously, but independently where to eat. Every restaurant can cater only one agent and agents cannot divert to other resources if their first choice is overcrowded. The number of agents equals the number of resources. Also, there is a ranking of restaurants all agents agree upon, and no two resources yield the same utility. The VFHP relaxes assumptions on capacity and utility: Resources (customers) are grouped in districts, agents (drivers) can redirect to other resources in the same district. As the distance between agent and resource reduces the agent’s utility and the location is not identical for all agents, the utility of a given resource is not identical for all agents. To study the impact of the different assumptions, I build four different model variants: Individual Preferences (IP) replaces the shared utility of the KPRP with uniformly distributed utilities per agent. The Mixed Preferences (MP) model variant uses the utility assumption of the VFHP, but the capacity of all districts remains 1. The Individual Preferences with Multiple Customers per District (IPMC) model variant groups customers in districts, and uses the uniform utilities introduced in the IP model variant. Mixed Preferences and Multiple Customers per District (MPMC) implements all assumptions of the VHFP. In this thesis, I study different strategies for the KPRP and all variants of the VFHP to build a foundation for an incentive scheme for dynamic matching in mobility markets. The strategies comprise history-dependent and utility-dependent strategies. In history-dependent strategies, agents incorporate their previous decisions and the utilization of resources in previous iterations in their decision. Agents adapting utility-dependent strategies choose the resource offering the highest utility with a given probability.

Keywords: vehicle for hire markets; distributed decision making; agent-based modelling; congestion game; limited

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