Dr. Rainer Schlosser

Postdoc

Phone:	+49 (331) 5509-1309
Fax:	+49 (331) 5509-579
Email:	rainer.schlosser(at)hpi.de
Room:	Hasso-Plattner-Villa, V-2.05
	ResearchGate, Google Scholar

Research

Data-Driven Decision-Support for Enterprise Applications

The need for automated decision-making is steadily increasing. The goal is to derive and to implement methods for data-driven decision-support for practical applications in changing uncertain environments. Solving problems in practical applications requires bringing together data management, data science, optimization, and risk management. Decision problems can generally be described by given performance criteria, admissible decisions, constraints, and (data-driven) estimations of the interplay of decisions on performance. However, every application has its own specifics, which should be taken into account to solve a problem effectively.

My research focuses on data-driven decision-making using quantitative methods of operations research and data science. I am particularly interested in (i) Operations Management and (ii) Database Optimization.

Keywords: (i) Optimal Control of Dynamic Systems, Risk-Sensitive Decision-Making, Dynamic Pricing Competition, Inventory Management, Data-Driven Demand Learning

(ii) Optimal Resource Allocation, Robust Database Configurations, Workload-Driven Decision-Making, Data Placement, Index Selection, Workload Anticipation

Current Projects

Robust Database Optimization with Stochastic Workloads
Database Replication and Data Placement
Dynamic Pricing on Amazon
Price Wars: An Interactive Simulation Platform

Selected Talks & Presentations

"Dynamic Pricing Competition in E-Commerce with Data-Driven Price Anticipations", 9^th ICIAM 2019, July 2019, Valencia, Spain; Invited Talk: Grant managed within CEREMADE department of the University Paris Dauphine
"Risk-Sensitive Control of Markov Decision Processes in Revenue Management: A Moment-Based Approach with Target Distributions", 19^th INFORMS Revenue Management & Pricing Conference, June 2019, Stanford Graduate School of Business, CA, USA
"Efficient Scalable Multi-Attribute Index Selection Using Recursive Strategies" and
"Workload-Driven Fragment Allocation for Partially Replicated Databases Using Linear Programming",

ICDE 2019, April 2019, Macao SAR, China
"Dynamic Pricing under Competition on Online Marketplaces: A Data-Driven Approach", KDD 2018, August 2018,
London, UK
"How To Survive Dynamic Pricing Competition in E-commerce", RecSys 2016, September 2016,
Massachusetts Institute of Technology (MIT) and the IBM Research campuses in Boston, MA, USA
"Dynamic Pricing with Time-Dependent Elasticities"

15^th INFORMS Revenue Management & Pricing Conference, June 2015,

Columbia University, New York, USA

Education

Ph.D. in Operations Research (summa cum laude), Humboldt-University of Berlin, Germany (05/2014), Topic: Dynamic Pricing and Advertising Models
Master's degree (Dipl.-Math.) in Mathematics (very good), Humboldt-University of Berlin, Institute of Applied Mathematics, Germany (10/2010), Focus: Optimization, Stochastic Models, Numerical Analysis
Master's degree (Dipl.-Kfm.) in Business Administration (very good), Humboldt-University of Berlin, School of Business and Economics, Germany (02/2010), Focus: Operations Research, Econometrics, Risk Management

Grants, Awards, and Research Stays

Research Stay: KEDGE Business School, Marseille, and CESIT Center of Excellence, Bordeaux, France (Oct 2019)
Best Paper Award: Schlosser, R. "Stochastic Dynamic Pricing with Strategic Customers and Reference Price Effects", 8^th International Conference on Operations Research and Enterprise Systems (ICORES 2019), Prague, Czech Republic
Best Paper Award: Schlosser, R., Richly, K. "Dynamic Pricing Strategies in a Finite Horizon Duopoly with Partial Information", 7^th International Conference on Operations Research and Enterprise Systems (ICORES 2018), Funchal, Portugal
Grant: Postdoctoral Scholarship, 2014 - 2015, Humboldt Graduate School
Ph.D. Grant: Elsa-Neumann-Scholarship, 2011 - 2013, Berlin Senate

Teaching

Data-Driven Decision-Making in Enterprise Applications (SS19)
Data-Driven Demand Learning and Dynamic Pricing Strategies in Competitive Markets (SS18)
for more teaching activities, see Archive

Reviewing

European Journal of Operational Research
International Journal of Production Economics
Journal of the Operational Research Society
Journal of Economic Dynamics and Control
IMA Journal of Management Mathematics
Transportation Research (Part E)
OR Spectrum
Economics E-Journal
Complexity
Optimal Control, Applications and Methods
Symmetry
Operational Research
International Journal of Operations & Quantitative Management
Journal of Systems Science and Systems Engineering
Maritime Policy & Management
Omega
Expert Systems with Applications
IISE Transactions
IEEE Access
IEEE Transactions on Knowledge and Data Engineering
Journal of Cleaner Production
Management Science

Scientific Communities: INFORMS, GOR, ACM, IEEE

Patent Applications

Schlosser, R., Boissier, M., Uflacker, M., Plattner, H. (2018). Data Placement in Hybrid Data Layouts for Tiered HTAP Databases (EP18164052, US16/364,869)
Schlosser, R., Kossmann, J., Boissier, M., Uflacker, M., Plattner, H. (2019). Iterative Multi-Attribute Index Selection for Large Database Systems (EP19167157)

Publications

Schlosser, R.: Stochastic Dynamic Pricing with Waiting and Forward-Looking Consumers. Communications in Computer and Information Science (CCIS), to appear. Springer (2020).

[ BibTeX ]

@inbook{schlosser2019stochastic, author = {Schlosser, Rainer}, booktitle = {Communications in Computer and Information Science (CCIS), to appear}, keywords = {myown pricing}, publisher = {Springer}, title = {Stochastic Dynamic Pricing with Waiting and Forward-Looking Consumers}, year = 2020 }
Schlosser, R.: Stochastic Dynamic Pricing with Strategic Customers and Reference Price Effects. 8th International Conference on Operations Research and Enterprise Systems, ICORES 2019. pp. 179-188 (2019).

[ BibTeX ]

@conference{schlosser2019stochastic, author = {Schlosser, Rainer}, booktitle = {8th International Conference on Operations Research and Enterprise Systems, ICORES 2019}, keywords = {myown pricing}, pages = {179-188}, title = {Stochastic Dynamic Pricing with Strategic Customers and Reference Price Effects}, year = 2019 }
Schlosser, R., Richly, K.: Dynamic Pricing under Competition with Data-Driven Price Anticipations and Endogenous Reference Price Effects. Journal of Revenue & Pricing Management, to appear. 1-14 (2019).

[ BibTeX ]

@article{schlosser2019dynamic, author = {Schlosser, Rainer and Richly, Keven}, journal = {Journal of Revenue & Pricing Management, to appear}, keywords = {myown competition pricing}, pages = {1-14}, title = {Dynamic Pricing under Competition with Data-Driven Price Anticipations and Endogenous Reference Price Effects}, year = 2019 }
Schlosser, R.: Data-Driven Stochastic Dynamic Pricing and Ordering. Operations Research Proceedings 2018. pp. 397-403 (2019).

[ BibTeX ]

@inproceedings{schlosser2019datadriven, author = {Schlosser, Rainer}, booktitle = {Operations Research Proceedings 2018}, keywords = {myown ordering pricing}, pages = {397-403}, title = {Data-Driven Stochastic Dynamic Pricing and Ordering}, year = 2019 }
Schlosser, R., Walther, C., Boissier, M., Uflacker, M.: Automated Repricing and Ordering Strategies in Competitive Markets. AI Communications. 32, 15-29 (2019).

[ BibTeX ] [ Download ]

@article{schlosser2019automated, abstract = {Merchants on modern e-commerce platforms face a highly competitive environments. They compete against each other using automated dynamic pricing and ordering strategies. Successfully managing both inventory levels as well as offer prices is a challenging task as (i) demand is uncertain, (ii) competitors strategically interact, and (iii) optimized pricing and ordering decisions are mutually dependent. We show how to derive optimized data-driven pricing and ordering strategies which are based on demand learning techniques and efficient dynamic optimization models. We verify the superior performance of our self-adaptive strategies by comparing them against different rule-based as well as data-driven strategies in duopoly and oligopoly settings. Further, to study and to optimize joint dynamic ordering and pricing strategies on online marketplaces, we built an interactive simulation platform. To be both flexible and scalable, the platform has a microservice-based architecture and allows handling dozens of competing merchants and streams of consumers with configurable characteristics.}, author = {Schlosser, Rainer and Walther, Carsten and Boissier, Martin and Uflacker, Matthias}, journal = {AI Communications}, keywords = {myown ordering pricing}, pages = {15-29}, title = {Automated Repricing and Ordering Strategies in Competitive Markets}, volume = 32, year = 2019 }
Schlosser, R., Richly, K.: Dynamic Pricing Competition with Unobservable Inventory Levels: A Hidden Markov Model Approach. Communications in Computer and Information Science. pp. 15-36. Springer (2019).

[ BibTeX ]

@inbook{schlosser2018dynamic, author = {Schlosser, Rainer and Richly, Keven}, booktitle = {Communications in Computer and Information Science}, keywords = {myown competition pricing}, pages = {15-36}, publisher = {Springer}, title = {Dynamic Pricing Competition with Unobservable Inventory Levels: A Hidden Markov Model Approach}, volume = 966, year = 2019 }
Halfpap, S., Schlosser, R.: A Comparison of Allocation Algorithms for Partially Replicated Databases. IEEE 35th International Conference on Data Engineering (ICDE 2019). pp. 2008-2011 (2019).

[ BibTeX ] [ Download ]

@inproceedings{klauck2019comparison, author = {Halfpap, Stefan and Schlosser, Rainer}, booktitle = {IEEE 35th International Conference on Data Engineering (ICDE 2019)}, keywords = {myown replication}, pages = {2008-2011}, title = {A Comparison of Allocation Algorithms for Partially Replicated Databases}, year = 2019 }
Kossmann, J., Schlosser, R.: A Framework for Self-Managing Database Systems. ICDE workshop (Self-Managing Databases). pp. 100-106 (2019).

[ BibTeX ]

@conference{kossmann2019framework, author = {Kossmann, Jan and Schlosser, Rainer}, booktitle = {ICDE workshop (Self-Managing Databases)}, keywords = {myown self-driving}, pages = {100-106}, title = {A Framework for Self-Managing Database Systems}, year = 2019 }
Halfpap, S., Schlosser, R.: Workload-Driven Fragment Allocation for Partially Replicated Databases Using Linear Programming. IEEE 35th International Conference on Data Engineering (ICDE 2019). pp. 1746-1749 (2019).

[ BibTeX ] [ Download ]

@inproceedings{klauck2019workloaddriven, author = {Halfpap, Stefan and Schlosser, Rainer}, booktitle = {IEEE 35th International Conference on Data Engineering (ICDE 2019)}, keywords = {myown replication}, pages = {1746-1749}, title = {Workload-Driven Fragment Allocation for Partially Replicated Databases Using Linear Programming}, year = 2019 }
Schlosser, R., Kossmann, J., Boissier, M.: Efficient Scalable Multi-Attribute Index Selection Using Recursive Strategies. IEEE 35th International Conference on Data Engineering (ICDE 2019). pp. 1238-1249. IEEE (2019).

[ BibTeX ] [ Download ]

@conference{schlosser2019efficient, author = {Schlosser, Rainer and Kossmann, Jan and Boissier, Martin}, booktitle = {IEEE 35th International Conference on Data Engineering (ICDE 2019)}, keywords = {myown}, month = {apr}, pages = {1238-1249}, publisher = {IEEE}, title = {Efficient Scalable Multi-Attribute Index Selection Using Recursive Strategies}, year = 2019 }
Schlosser, R., Boissier, M.: Dealing with the Dimensionality Curse in Dynamic Pricing Competition: Using Frequent Repricing to Compensate Imperfect Market Anticipations. Computers and Operations Research. 100, 26-42 (2018).

[ BibTeX ] [ Download ]

@article{schlosser2018dealing, abstract = {Most sales applications are characterized by competition and limited demand information. For success- ful pricing strategies, frequent price adjustments as well as anticipation of market dynamics are crucial. Both effects are challenging as competitive markets are complex and computations of optimized pricing adjustments can be time-consuming. We analyze stochastic dynamic pricing models under oligopoly competition for the sale of perishable goods. To circumvent the curse of dimensionality, we propose a heuristic approach to efficiently compute price adjustments. To demonstrate our strategy’s applicability even if the number of competitors is large and their strategies are unknown, we consider different competitive settings in which competitors frequently and strategically adjust their prices. For all settings, we verify that our heuristic strategy yields promising results. We compare the performance of our heuristic against upper bounds, which are obtained by optimal strategies that take advantage of perfect price an- ticipations. We find that price adjustment frequencies can have a larger impact on expected profits than price anticipations. Finally, our approach has been applied on Amazon for the sale of used books. We have used a seller’s historical market data to calibrate our model. Sales results show that our data-driven strategy outperforms the rule-based strategy of an experienced seller by a profit increase of more than 20%.}, author = {Schlosser, Rainer and Boissier, Martin}, journal = {Computers and Operations Research}, keywords = {myown competition pricing}, pages = {26-42}, title = {Dealing with the Dimensionality Curse in Dynamic Pricing Competition: Using Frequent Repricing to Compensate Imperfect Market Anticipations}, volume = 100, year = 2018 }
Schlosser, R., Boissier, M.: Dynamic Pricing under Competition on Online Marketplaces: A Data-Driven Approach. KDD '18 Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. pp. 705-714 (2018).

[ BibTeX ] [ Download ]

@inproceedings{schlosser2018dynamic, abstract = {Most online markets are characterized by competitive settings and limited demand information. Due to the complexity of such markets, efficient pricing strategies are hard to derive. We analyze stochastic dynamic pricing models in competitive markets with multiple offer dimensions, such as price, quality, and rating. In a first step, we use a simulated test market to study how sales probabilities are affected by specific customer behaviors and the strategic interaction of price reaction strategies. Further, we show how different state-of-the-art learning techniques can be used to estimate sales probabilities from partially observable market data. In a second step, we use a dynamic programming model to compute an effective pricing strategy which circumvents the curse of dimensionality. We demonstrate that the strategy is applicable even if the number of competitors is large and their strategies are unknown. We show that our heuristic can be tuned to smoothly balance profitability and speed of sales. Further, our approach is currently applied by a large seller on Amazon for the sale of used books. Sales results show that our data-driven strategy outperforms the rule-based strategy of an experienced seller by a profit increase of more than 20%.}, author = {Schlosser, Rainer and Boissier, Martin}, booktitle = {{KDD} '18 Proceedings of the 24th {ACM} {SIGKDD} International Conference on Knowledge Discovery & Data Mining}, keywords = {myown competition pricing}, pages = {705-714}, title = {Dynamic Pricing under Competition on Online Marketplaces: A Data-Driven Approach}, year = 2018 }
Schlosser, R., Walther, C., Boissier, M., Uflacker, M.: Data-Driven Inventory Management and Dynamic Pricing Competition on Online Marketplaces. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI 2018). pp. 5856-5858 (2018).

[ BibTeX ] [ Download ]

@inproceedings{schlosser2018datadriven, author = {Schlosser, Rainer and Walther, Carsten and Boissier, Martin and Uflacker, Matthias}, booktitle = {Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI 2018)}, keywords = {myown ordering pricewars pricing}, pages = {5856-5858}, title = {Data-Driven Inventory Management and Dynamic Pricing Competition on Online Marketplaces}, year = 2018 }
Boissier, M., Schlosser, R., Uflacker, M.: Hybrid Data Layouts for Tiered HTAP Databases with Pareto-Optimal Data Placements. IEEE 34th International Conference on Data Engineering (ICDE 2018). pp. 209-220 (2018).

[ BibTeX ] [ Download ]

@inproceedings{boissier2018hybrid, abstract = {Recent developments in database research intro- duced HTAP systems that are capable of handling both transactional and analytical workloads. These systems achieve their performance by storing the full data set in main memory. An open research question is how far one can reduce the main memory footprint without losing the performance superiority of main memory-resident databases. In this paper, we present a hybrid main memory-optimized database for mixed workloads that evicts cold data to less expensive storage tiers. It adapts the storage layout to mitigate the negative performance impact of secondary storage. A key challenge is to determine which data to place on which storage tier. We introduce a novel workload-driven model that determines Pareto-optimal allocations while also considering reallocation costs. We evaluate our concept for a production enterprise system as well as reproducible data sets.}, author = {Boissier, Martin and Schlosser, Rainer and Uflacker, Matthias}, booktitle = {IEEE 34th International Conference on Data Engineering (ICDE 2018)}, keywords = {myown uncompressed column}, month = 4, pages = {209-220}, title = {Hybrid Data Layouts for Tiered HTAP Databases with Pareto-Optimal Data Placements}, year = 2018 }
Schlosser, R., Richly, K.: Dynamic Pricing Strategies in a Finite Horizon Duopoly with Partial Information. 7th International Conference on Operations Research and Enterprise Systems, ICORES 2018. pp. 21-30 (2018).

[ BibTeX ]

@inproceedings{schlosser2018dynamic, author = {Schlosser, Rainer and Richly, Keven}, booktitle = {7th International Conference on Operations Research and Enterprise Systems, ICORES 2018}, keywords = {Pricing}, month = {January}, pages = {21-30}, title = {Dynamic Pricing Strategies in a Finite Horizon Duopoly with Partial Information}, volume = {Vol. 1 - 978-989-758-285-1}, year = 2018 }
Schlosser, R.: Stochastic Dynamic Multi-Product Pricing under Competition. Operations Research Proceedings 2017. pp. 527-533 (2018).

[ BibTeX ]

@inproceedings{schlosser2017stochastic, author = {Schlosser, Rainer}, booktitle = {Operations Research Proceedings 2017}, keywords = {myown pricing}, pages = {527-533}, title = {Stochastic Dynamic Multi-Product Pricing under Competition}, year = 2018 }
Schlosser, R., Boissier, M.: Optimal Repricing Strategies in a Stochastic Infinite Horizon Duopoly. Communications in Computer and Information Science (CCIS). pp. 129-150. Springer (2018).

[ BibTeX ] [ Download ]

@inbook{schlosser2017optimal, author = {Schlosser, Rainer and Boissier, Martin}, booktitle = {Communications in Computer and Information Science (CCIS)}, keywords = {imported myown pricing}, pages = {129-150}, publisher = {Springer}, title = {Optimal Repricing Strategies in a Stochastic Infinite Horizon Duopoly}, volume = 884, year = 2018 }
Uflacker, M., Schlosser, R., Meinel, C.: Ertragsmanagement im Wandel - Potentiale der In-Memory Technologie. In: Gläß, R. and Leukert, B. (eds.) Handel 4.0: Die Digitalisierung des Handels. Strategien, Technologien, Transformation. pp. 177-190. Springer Gabler (2017).

[ BibTeX ]

@inbook{Matthias2017a, author = {Uflacker, Matthias and Schlosser, Rainer and Meinel, Christoph}, booktitle = {Handel 4.0: Die Digitalisierung des Handels. Strategien, Technologien, Transformation}, edition = 1, editor = {Gläß, R. and Leukert, B.}, keywords = {imported}, pages = {177-190}, publisher = {Springer Gabler}, title = {Ertragsmanagement im Wandel - Potentiale der In-Memory Technologie}, year = 2017 }
Schlosser, R., Boissier, M.: Optimal Price Reaction Strategies in the Presence of Active and Passive Competitors. Proceedings of the 6th International Conference on Operations Research and Enterprise Systems (ICORES), Porto, Portugal. pp. 47-56 (2017).

[ BibTeX ] [ Download ]

@inproceedings{Rainer2017a, author = {Schlosser, Rainer and Boissier, Martin}, booktitle = {Proceedings of the 6th International Conference on Operations Research and Enterprise Systems (ICORES), Porto, Portugal}, keywords = {imported pricewars pricing}, month = 2, pages = {47-56}, title = {Optimal Price Reaction Strategies in the Presence of Active and Passive Competitors}, year = 2017 }
Zimmermann, T., Djürken, T., Mayer, A., Janke, M., Boissier, M., Schwarz, C., Schlosser, R., Uflacker, M.: Detecting Fraudulent Advertisements on a Large E-Commerce Platform. Proceedings of the Nineteenth International Workshop on Data Warehousing and OLAP, DOLAP, Venice, Italy, March 21, 2017 (2017).

[ BibTeX ] [ Download ]

@conference{Tim2017a, author = {Zimmermann, Tim and Djürken, Timo and Mayer, Arne and Janke, Michael and Boissier, Martin and Schwarz, Christian and Schlosser, Rainer and Uflacker, Matthias}, booktitle = {Proceedings of the Nineteenth International Workshop on Data Warehousing and OLAP, DOLAP, Venice, Italy, March 21, 2017.}, keywords = {imported}, month = 3, title = {Detecting Fraudulent Advertisements on a Large E-Commerce Platform}, year = 2017 }
Schlosser, R.: Stochastic Dynamic Pricing and Advertising in Isoelastic Oligopoly Models. European Journal of Operational Research. 259, 1144-1155 (2017).

[ BibTeX ]

@article{Rainer2017a, author = {Schlosser, Rainer}, journal = {European Journal of Operational Research}, keywords = {imported competition pricing}, number = 3, pages = {1144-1155}, title = {Stochastic Dynamic Pricing and Advertising in Isoelastic Oligopoly Models}, volume = 259, year = 2017 }
Seiffert, M., Holstein, F., Schlosser, R., Schiller, J.: Next Generation Cooperate Wearables: Generalized Activity Assessment Computed Fully Distributed Within a Wireless Body Area Network. IEEE Access Journal. 5, 16793-16807 (2017).

[ BibTeX ]

@article{seiffert2017generation, author = {Seiffert, Martin and Holstein, Flavio and Schlosser, Rainer and Schiller, Jochen}, journal = {IEEE Access Journal}, keywords = {imported myown}, pages = {16793-16807}, title = {Next Generation Cooperate Wearables: Generalized Activity Assessment Computed Fully Distributed Within a Wireless Body Area Network}, volume = 5, year = 2017 }
Serth, S., Podlesny, N., Bornstein, M., Lindemann, J., Latt, J., Selke, J., Schlosser, R., Boissier, M., Uflacker, M.: An Interactive Platform to Simulate Dynamic Pricing Competition on Online Marketplaces. 21st IEEE International Enterprise Distributed Object Computing Conference, EDOC 2017, Quebec City, QC, Canada, October 10-13, 2017. pp. 61-66. IEEE (2017).

[ BibTeX ] [ Download ]

@inproceedings{edoc2017pricewars, author = {Serth, Sebastian and Podlesny, Nikolai and Bornstein, Marvin and Lindemann, Jan and Latt, Johanna and Selke, Jan and Schlosser, Rainer and Boissier, Martin and Uflacker, Matthias}, booktitle = {21st IEEE International Enterprise Distributed Object Computing Conference, EDOC 2017, Quebec City, QC, Canada, October 10-13, 2017}, keywords = {myown price pricewars dynamic wars pricing platform}, month = 10, pages = {61-66}, publisher = {IEEE}, title = {An Interactive Platform to Simulate Dynamic Pricing Competition on Online Marketplaces}, year = 2017 }
Boissier, M., Schlosser, R., Podlesny, N., Serth, S., Bornstein, M., Latt, J., Lindemann, J., Selke, J., Uflacker, M.: Data-Driven Repricing Strategies in Competitive Markets: An Interactive Simulation Platform. Proceedings of the Eleventh ACM Conference on Recommender Systems (RecSys '17). pp. 355-357. ACM, New York, NY, USA (2017).

[ BibTeX ] [ Download ]

@inproceedings{recsysdemo2017dynpri, address = {New York, NY, USA}, author = {Boissier, Martin and Schlosser, Rainer and Podlesny, Nikolai and Serth, Sebastian and Bornstein, Marvin and Latt, Johanna and Lindemann, Jan and Selke, Jan and Uflacker, Matthias}, booktitle = {Proceedings of the Eleventh ACM Conference on Recommender Systems (RecSys '17)}, keywords = {myown Dynamic Pricing RecSys Recommender pricewars Systems Demonstration}, month = 10, pages = {355-357}, publisher = {ACM}, series = {RecSys '17}, title = {Data-Driven Repricing Strategies in Competitive Markets: An Interactive Simulation Platform}, year = 2017 }
Schlosser, R.: Stochastic Dynamic Multi-Product Pricing with Dynamic Advertising and Adoption Effects. Journal of Revenue and Pricing Management. 15, 153-169 (2016).

[ BibTeX ]

@article{Rainer2016b, author = {Schlosser, Rainer}, journal = {Journal of Revenue and Pricing Management}, keywords = {imported pricing multi}, number = 2, pages = {153-169}, title = {Stochastic Dynamic Multi-Product Pricing with Dynamic Advertising and Adoption Effects}, volume = 15, year = 2016 }
Schlosser, R., Boissier, M., Schober, A., Uflacker, M.: How To Survive Dynamic Pricing Competition in E-commerce. Proceedings of the Poster Track of the 10th ACM Conference on Recommender Systems (RecSys 2016), Boston, USA, September 17, 2016 (2016).

[ BibTeX ] [ Download ]

@conference{Rainer2016a, author = {Schlosser, Rainer and Boissier, Martin and Schober, Andre and Uflacker, Matthias}, booktitle = {Proceedings of the Poster Track of the 10th {ACM} Conference on Recommender Systems (RecSys 2016), Boston, USA, September 17, 2016}, keywords = {imported amazon pricewars pricing}, month = 9, title = {How To Survive Dynamic Pricing Competition in E-commerce}, year = 2016 }
Boissier, M., Djürken, T., Schlosser, R., Faust, M.: A Cost-Aware and Workload-Based Index Advisor for Columnar In-Memory Databases. 22nd International Conference, ICIST 2016, Druskininkai, Lithuania, October 13-15, 2016, Proceedings, CCIS 639. p. 285--299 (2016).

[ BibTeX ] [ Download ]

@conference{Martin2016a, author = {Boissier, Martin and Djürken, Timo and Schlosser, Rainer and Faust, Martin}, booktitle = {22nd International Conference, {ICIST} 2016, Druskininkai, Lithuania, October 13-15, 2016, Proceedings, {CCIS} 639}, keywords = {imported}, month = 10, pages = {285--299}, title = {A Cost-Aware and Workload-Based Index Advisor for Columnar In-Memory Databases}, year = 2016 }
Schlosser, R.: Joint Stochastic Dynamic Pricing and Advertising with Time-Dependent Demand. Journal of Economic Dynamics and Control. 73, 439-452 (2016).

[ BibTeX ]

@article{schlosser2016joint, author = {Schlosser, Rainer}, journal = {Journal of Economic Dynamics and Control}, keywords = {imported advertising pricing}, pages = {439-452}, title = {Joint Stochastic Dynamic Pricing and Advertising with Time-Dependent Demand}, volume = 73, year = 2016 }
Schlosser, R.: Dynamic Pricing with Time-Dependent Elasticities. Journal of Revenue and Pricing Management. 14, 365-383 (2015).

[ BibTeX ]

@article{Rainer2015a, author = {Schlosser, Rainer}, journal = {Journal of Revenue and Pricing Management}, keywords = {myown pricing}, number = 5, pages = {365-383}, title = {Dynamic Pricing with Time-Dependent Elasticities}, volume = 14, year = 2015 }
Schlosser, R.: A Stochastic Dynamic Pricing and Advertising Model under Risk Aversion. Journal of Revenue and Pricing Management. 14, 451-468 (2015).

[ BibTeX ]

@article{Rainer2015b, author = {Schlosser, Rainer}, journal = {Journal of Revenue and Pricing Management}, keywords = {imported risk pricing}, number = 6, pages = {451-468}, title = {A Stochastic Dynamic Pricing and Advertising Model under Risk Aversion}, volume = 14, year = 2015 }
Helmes, K., Schlosser, R.: Oligopoly Pricing and Advertising in Isoelastic Adoption Models. Dynamic Games and Applications. 5, 334-360 (2015).

[ BibTeX ]

@article{Kurt2015a, author = {Helmes, Kurt and Schlosser, Rainer}, journal = {Dynamic Games and Applications}, keywords = {imported}, number = 3, pages = {334-360}, title = {Oligopoly Pricing and Advertising in Isoelastic Adoption Models}, volume = 5, year = 2015 }
Schlosser, R.: Dynamic Pricing and Advertising Models with Inventory Holding Costs. Journal of Economic Dynamics and Control. 57, 163-181 (2015).

[ BibTeX ]

@article{Rainer2015c, author = {Schlosser, Rainer}, journal = {Journal of Economic Dynamics and Control}, keywords = {imported advertising pricing}, pages = {163-181}, title = {Dynamic Pricing and Advertising Models with Inventory Holding Costs}, volume = 57, year = 2015 }
Helmes, K., Schlosser, R.: Dynamic Advertising and Pricing with Constant Demand Elasticities. Journal of Economic Dynamics and Control. 37, 2814-2832 (2013).

[ BibTeX ]

@article{Kurt2013a, author = {Helmes, Kurt and Schlosser, Rainer}, journal = {Journal of Economic Dynamics and Control}, keywords = {imported}, number = 12, pages = {2814-2832}, title = {Dynamic Advertising and Pricing with Constant Demand Elasticities}, volume = 37, year = 2013 }
Helmes, K., Schlosser, R., Weber, M.: Dynamic Advertising and Pricing in a Class of General New-Product Adoption Models. European Journal of Operational Research. 229, 433-443 (2013).

[ BibTeX ]

@article{Kurt2013b, author = {Helmes, Kurt and Schlosser, Rainer and Weber, Martin}, journal = {European Journal of Operational Research}, keywords = {imported}, number = 2, pages = {433-443}, title = {Dynamic Advertising and Pricing in a Class of General New-Product Adoption Models}, volume = 229, year = 2013 }

Dr. Rainer Schlosser

Postdoc

Research

Data-Driven Decision-Support for Enterprise Applications

Current Projects

Selected Talks & Presentations

Education

Grants, Awards, and Research Stays

Teaching

Reviewing

Patent Applications

Publications

Chair of Prof. Hasso Plattner

News

14.10.2019 | 2019 Bachelor's Project featured in SAP TechEd Keynote

23.07.2019 | Presentation of 2019 Bachelor's Project

12.06.2019 | Global Team-based Innovation Final Presentations

25.02.2019 | Best Paper Award received at ICORES 2019

Open Positions

Literature