Demand estimation in airline revenue management:
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis Book |
| Language: | English |
| Published: |
2014
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| Subjects: | |
| Online Access: | Volltext Inhaltsverzeichnis |
| Item Description: | Nebentitel: Nachfrageprognose für das Revenue-Management in der Luftfahrtbranche |
| Physical Description: | 145 Bl. graph. Darst. |
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| 245 | 1 | 0 | |a Demand estimation in airline revenue management |c by Philipp Bartke |
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Record in the Search Index
| _version_ | 1804152023866671104 |
|---|---|
| adam_text | CONTENTS
LIST OF FIGURES 9
LIST OF TABLES 11
LIST OF SYMBOLS AND ACRONYMS 12
I. MOTIVATION 15
1. INTRODUCTION TO REVENUE MANAGEMENT 16
1.1. COMPLEMENTS AND SUBSTITUTES 18
1.2. INDUSTRIES 20
1.3. OUTLINE 20
2. LITERATURE REVIEW 22
2.1. REVENUE MANAGEMENT WITH DEMAND LEARNING 22
2.2. DATA SPARSITY AND SMALL NUMBERS IN FORECASTING , 26
3. RESEARCH GAP 29
II.
DEMAND ESTIMATION 33
4. STATE-SPACE MODEL FOR DEMAND ESTIMATION 34
4.1. A GENERAL MODEL OF REVENUE MANAGEMENT 34
4.1.1. THE FORECASTER 35
4.1.2. THE OPTIMIZER 37
4.1.3. THE INVENTORY 37
4.1.4. THE FEEDBACK LOOP 37
4.1.5. CHOICE FUNCTIONS 38
6
HTTP://D-NB.INFO/1052099580
CONTENTS
4.2. DEMAND ESTIMATION, FORECASTING AND EXPECTED BOOKINGS 42
4.3. STATE-SPACE MODEL FOR DEMAND ESTIMATION 43
4.4. THE POSTERIOR CRAMER-RAO BOUND AND THE INFORMATION MATRIX 47
5. DATA-DRIVEN SIMULATION SETUP 51
5.1. SIMULATION ENVIRONMENT 51
5.2. SIMULATION SCENARIOS 52
5.3. CUSTOMER CHOICE 53
5.4. APPROXIMATING DEMAND PARAMETERS FROM REAL WORLD DATA 54
5.4.1. ANALYSIS OF YIELD DATA 55
5.4.2. ANALYSIS OF PASSENGER COUNT DATA 58
5.4.3. PRICE ELASTICITY OVER THE BOOKING HORIZON 59
5.4.4. NUMBER OF PRICE-SENSITIVE CUSTOMERS 59
5.5. SUMMARY 61
6. NEW METHODS FOR DEMAND ESTIMATION 63
6.1. UNSCENTED KALMAN FILTER 63
6.1.1. BACKGROUND 63
6.1.2. UNSCENTED KALMAN FILTER FOR DEMAND ESTIMATION 65
6.2. PARTICLE FILTER 68
6.2.1. BACKGROUND 68
6.2.2. PARTICLE FILTER FOR DEMAND ESTIMATION 70
6.3. ACTIVE ESTIMATION 72
6.3.1. BACKGROUND 73
6.3.2. NEW ACTIVE ESTIMATION HEURISTIC 74
6.4. SIMULATION SETUP 74
6.4.1. BASELINE METHODS 74
6.4.2. FORECAST INITIALIZATION 77
6.5. SIMULATION RESULTS 78
6.5.1. COMPARISON OF FILTER DESIGN PARAMETERS 79
6.5.2. COMPARISON TO BENCHMARK METHODS 82
6.5.3. FASTER DEMAND CHANGE 86
6.6. DISCUSSION OF SIMULATION RESULTS 87
7
CONTENTS
III. THE PROBLEM
OF SMALL NUMBERS 90
7. QUANTIFYING THE PROBLEM OF SMALL NUMBERS 91
7.1. A PROPERTY OF THE POSTERIOR CRAMER-RAO BOUND 92
7.2. SIMULATION STUDY 95
7.2.1. SIMULATION SETUP 95
7.2.2. SIMULATION RESULTS 98
7.3. CHAPTER CONCLUSION 100
8. FORECAST MERGING 101
8.1. MULTIPLE LEVELS OF CLUSTERING AND AGGREGATION 101
8.2. BACKGROUND 103
8.3. OUR METHOD FOR FORECAST MERGING 105
8.3.1. MERGING TWO ESTIMATION CLUSTERS A AND B 106
8.3.2. COMPARING THE MEAN-SQUARED ERRORS BEFORE AND AFTER MERGING . .
107
8.3.3. INITIAL CLUSTERING 109
8.3.4. MERGING ESTIMATES ILL
8.4. SIMULATION STUDY ILL
8.5. DISCUSSION OF FORECAST MERGING 117
IV. CONCLUSION AND APPENDIX 119
9. CONCLUSION 120
9.1. SUMMARY OF FINDINGS 120
9.2. LIMITATIONS 123
9.3. DIRECTIONS FOR FUTURE RESEARCH 126
10.APPENDIX 129
10.1. TECHNICAL DETAILS FOR THE UNSCENTED KALMAN FILTER 129
10.1.1. UPPER TRIANGULAR CHOLESKY DECOMPOSITION 129
10.1.2. UNSCENTED KALMAN FILTER FOR HYBRID CHOICE MODELS 129
10.2. DATA ANALYSIS: ADDITIONAL CHARTS 132
10.3. FISHER INFORMATION: AGGREGATING OBSERVATIONS 134
REFERENCES 136
8
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| any_adam_object | 1 |
| author | Bartke, Philipp |
| author_GND | (DE-588)1048497577 |
| author_facet | Bartke, Philipp |
| author_role | aut |
| author_sort | Bartke, Philipp |
| author_variant | p b pb |
| building | Verbundindex |
| bvnumber | BV041737240 |
| collection | ebook |
| ctrlnum | (OCoLC)888454499 (DE-599)BVBBV041737240 |
| dewey-full | 387.7420681 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 387 - Water, air, space transportation |
| dewey-raw | 387.7420681 |
| dewey-search | 387.7420681 |
| dewey-sort | 3387.7420681 |
| dewey-tens | 380 - Commerce, communications, transportation |
| discipline | Wirtschaftswissenschaften |
| format | Thesis Book |
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| spelling | Bartke, Philipp Verfasser (DE-588)1048497577 aut Demand estimation in airline revenue management by Philipp Bartke Nachfrageprognose für das Revenue-Management in der Luftfahrtbranche 2014 145 Bl. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Nebentitel: Nachfrageprognose für das Revenue-Management in der Luftfahrtbranche Berlin, Freie Univ., Diss., 2014 Luftverkehrsgesellschaft (DE-588)4036559-1 gnd rswk-swf Revenue Management (DE-588)4444408-4 gnd rswk-swf Prognoseverfahren (DE-588)4358095-6 gnd rswk-swf Nachfrage (DE-588)4041036-5 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Revenue Management (DE-588)4444408-4 s Nachfrage (DE-588)4041036-5 s Prognoseverfahren (DE-588)4358095-6 s Luftverkehrsgesellschaft (DE-588)4036559-1 s DE-188 Erscheint auch als Online-Ausgabe urn:nbn:de:kobv:188-fudissthesis000000096263-6 http://www.diss.fu-berlin.de/diss/receive/FUDISS_thesis_000000096263 kostenfrei Volltext DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027183904&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Bartke, Philipp Demand estimation in airline revenue management Luftverkehrsgesellschaft (DE-588)4036559-1 gnd Revenue Management (DE-588)4444408-4 gnd Prognoseverfahren (DE-588)4358095-6 gnd Nachfrage (DE-588)4041036-5 gnd |
| subject_GND | (DE-588)4036559-1 (DE-588)4444408-4 (DE-588)4358095-6 (DE-588)4041036-5 (DE-588)4113937-9 |
| title | Demand estimation in airline revenue management |
| title_alt | Nachfrageprognose für das Revenue-Management in der Luftfahrtbranche |
| title_auth | Demand estimation in airline revenue management |
| title_exact_search | Demand estimation in airline revenue management |
| title_full | Demand estimation in airline revenue management by Philipp Bartke |
| title_fullStr | Demand estimation in airline revenue management by Philipp Bartke |
| title_full_unstemmed | Demand estimation in airline revenue management by Philipp Bartke |
| title_short | Demand estimation in airline revenue management |
| title_sort | demand estimation in airline revenue management |
| topic | Luftverkehrsgesellschaft (DE-588)4036559-1 gnd Revenue Management (DE-588)4444408-4 gnd Prognoseverfahren (DE-588)4358095-6 gnd Nachfrage (DE-588)4041036-5 gnd |
| topic_facet | Luftverkehrsgesellschaft Revenue Management Prognoseverfahren Nachfrage Hochschulschrift |
| url | http://www.diss.fu-berlin.de/diss/receive/FUDISS_thesis_000000096263 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027183904&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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