Michael H. Breitner

Personal Details

First Name:	Michael
Middle Name:	Hans
Last Name:	Breitner
Suffix:
RePEc Short-ID:	pbr59
	http://www.iwi.uni-hannover.de/professor.html
	Institut fuer Wirtschaftsinformatik Universitaet Hannover Koenigsworther Platz 1 D-30167 Hannover
	+49-(0)511-762 4901

Affiliation

(50%) Wirtschaftswissenschaftliche Fakultät
Leibniz Universität Hannover

Hannover, Germany
http://www.wiwi.uni-hannover.de/
RePEc:edi:fwhande (more details at EDIRC)

(50%) Institut für Wirtschaftsinformatik
Wirtschaftswissenschaftliche Fakultät
Leibniz Universität Hannover

Hannover, Germany
http://www.iwi.uni-hannover.de/
RePEc:edi:iwhande (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

1. Christian von Spreckelsen & Patrick Bartels & Prof. Dr. Michael H. Breitner, 2006. "Geschäftsprozessorientierte Analyse und Bewertung der Potentiale des Nomadic Computing," IWI Discussion Paper Series 17, Institut für Wirtschaftsinformatik, Universität Hannover.

   Cited by:

   1. Stanis£Aw Brzeziñski & Piotr Stefañczyk, 2013. "Use Of Smartphone’S Possibilities In Construction Of Logistics System Of Vending Machines," Advanced Logistic systems, University of Miskolc, Department of Material Handling and Logistics, vol. 7(1), pages 21-30, December.

2. Hoppe, Gabriela & Breitner, Michael H., 2003. "Business Models for E-Learning," Hannover Economic Papers (HEP) dp-287, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

   Cited by:

   1. Nina Schumacher, 2022. "CAN BUSINESS MODEL COMPONENTS EXPLAIN DIGITAL START-UP SUCCESS? A Qualitative Analysis of the Business Models of Start-ups from the Perspective of German Venture Investors," Economic Thought and Practice, Department of Economics and Business, University of Dubrovnik, vol. 31(1), pages 81-98, june.
   2. Alberto Onetti & Antonella Zucchella & Marian Jones & Patricia McDougall-Covin, 2012. "Internationalization, innovation and entrepreneurship: business models for new technology-based firms," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 16(3), pages 337-368, August.
   3. Alireza Nasiri, 2014. "Mobile Learning Business Model Framework," Information Management and Business Review, AMH International, vol. 6(2), pages 72-87.
   4. Maria Francesca SAVARESE & Luciano PILOTTI & Fiorenza BELUSSI, 2012. "Business model emergenti: dalla gestione della complessità all’ecologia del valore. Una rassegna della letteratura," Departmental Working Papers 2012-06, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.

3. Michael H. Breitner, 2003. "Rufus Philip Isaacs and the Early Years of Differential Games," IWI Discussion Paper Series 1, Institut für Wirtschaftsinformatik, Universität Hannover.

   Cited by:

   1. M. H. Breitner, 2005. "The Genesis of Differential Games in Light of Isaacs’ Contributions," Journal of Optimization Theory and Applications, Springer, vol. 124(3), pages 523-559, March.

4. Gabriela Hoppe & Michael H. Breitner, 2003. "Classification and Sustainability Analysis of E-Learning Applications," IWI Discussion Paper Series 2, Institut für Wirtschaftsinformatik, Universität Hannover.

   Cited by:

   1. Hoppe, Gabriela & Breitner, Michael H., 2003. "Business Models for E-Learning," Hannover Economic Papers (HEP) dp-287, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

Articles

1. Stetter, Chris & Piel, Jan-Hendrik & Hamann, Julian F.H. & Breitner, Michael H., 2020. "Competitive and risk-adequate auction bids for onshore wind projects in Germany," Energy Economics, Elsevier, vol. 90(C).

   Cited by:

   1. Đukan, Mak & Kitzing, Lena, 2023. "A bigger bang for the buck: The impact of risk reduction on renewable energy support payments in Europe," Energy Policy, Elsevier, vol. 173(C).
   2. Stetter, Chris & Wielert, Henrik & Breitner, Michael H., 2022. "Hidden repowering potential of non-repowerable onshore wind sites in Germany," Energy Policy, Elsevier, vol. 168(C).
   3. del Río, Pablo & Kiefer, Christoph P., 2023. "Academic research on renewable electricity auctions: Taking stock and looking forward," Energy Policy, Elsevier, vol. 173(C).
   4. Geßner, Daniel, 2023. "Performance of Renewable Energy Policies - Evidence from Germany's Transition to Auctions," W.E.P. - Würzburg Economic Papers 105, University of Würzburg, Department of Economics.
   5. Min-Ji Park & Eul-Bum Lee & Seung-Yeab Lee & Jong-Hyun Kim, 2021. "A Digitalized Design Risk Analysis Tool with Machine-Learning Algorithm for EPC Contractor’s Technical Specifications Assessment on Bidding," Energies, MDPI, vol. 14(18), pages 1-31, September.
   6. Sheykhha, Siamak & Borggrefe, Frieder & Madlener, Reinhard, 2022. "Policy implications of spatially differentiated renewable energy promotion: A multi-level scenario analysis of onshore wind auctioning in Germany," Energy Policy, Elsevier, vol. 169(C).

2. Antje Janssen & Jens Passlick & Davinia Rodríguez Cardona & Michael H. Breitner, 2020. "Virtual Assistance in Any Context," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 62(3), pages 211-225, June.

   Cited by:

   1. Hitesh Dhiman & Christoph Wächter & Michael Fellmann & Carsten Röcker, 2022. "Intelligent Assistants," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(5), pages 645-665, October.
   2. Dennis Kundisch & Jan Muntermann & Anna Maria Oberländer & Daniel Rau & Maximilian Röglinger & Thorsten Schoormann & Daniel Szopinski, 2022. "An Update for Taxonomy Designers," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(4), pages 421-439, August.
   3. Stefan Morana & Jella Pfeiffer & Marc T. P. Adam, 2020. "User Assistance for Intelligent Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 62(3), pages 189-192, June.
   4. Gkinko, Lorentsa & Elbanna, Amany, 2023. "Designing trust: The formation of employees’ trust in conversational AI in the digital workplace," Journal of Business Research, Elsevier, vol. 158(C).

3. Hübler, Clemens & Piel, Jan-Hendrik & Stetter, Chris & Gebhardt, Cristian G. & Breitner, Michael H. & Rolfes, Raimund, 2020. "Influence of structural design variations on economic viability of offshore wind turbines: An interdisciplinary analysis," Renewable Energy, Elsevier, vol. 145(C), pages 1348-1360.

   Cited by:

   1. Li, He & Teixeira, Angelo P. & Guedes Soares, C., 2020. "A two-stage Failure Mode and Effect Analysis of offshore wind turbines," Renewable Energy, Elsevier, vol. 162(C), pages 1438-1461.
   2. Yi Zhang & Dapeng Zhang & Haoyu Jiang, 2023. "A Review of Offshore Wind and Wave Installations in Some Areas with an Eye towards Generating Economic Benefits and Offering Commercial Inspiration," Sustainability, MDPI, vol. 15(10), pages 1-32, May.
   3. Stetter, Chris & Piel, Jan-Hendrik & Hamann, Julian F.H. & Breitner, Michael H., 2020. "Competitive and risk-adequate auction bids for onshore wind projects in Germany," Energy Economics, Elsevier, vol. 90(C).

4. Max Leyerer & Marc-Oliver Sonneberg & Maximilian Heumann & Tim Kammann & Michael H. Breitner, 2019. "Individually Optimized Commercial Road Transport: A Decision Support System for Customizable Routing Problems," Sustainability, MDPI, vol. 11(20), pages 1-21, October.

   Cited by:

   1. Rafidah Md Noor & Nadia Bella Gustiani Rasyidi & Tarak Nandy & Raenu Kolandaisamy, 2020. "Campus Shuttle Bus Route Optimization Using Machine Learning Predictive Analysis: A Case Study," Sustainability, MDPI, vol. 13(1), pages 1-24, December.

5. Sonja Dreyer & Daniel Olivotti & Benedikt Lebek & Michael H. Breitner, 2019. "Focusing the customer through smart services: a literature review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(1), pages 55-78, March.

   Cited by:

   1. Sanjit K. Roy & Gaganpreet Singh & Corey Hatton & Bidit Dey & Nisreen Ameen & Satish Kumar, 2023. "Customers’ motives to co-create in smart services interactions," Electronic Commerce Research, Springer, vol. 23(3), pages 1367-1400, September.
   2. Mai Ngoc Khuong & Do Thanh Tung & Thai Hoang Quoc, 2022. "Review of Empirical Research on Leadership and Firm Performance," SAGE Open, , vol. 12(3), pages 21582440221, July.
   3. Edvard Tijan & Marija Jović & Ana Panjako & Dražen Žgaljić, 2021. "The Role of Port Authority in Port Governance and Port Community System Implementation," Sustainability, MDPI, vol. 13(5), pages 1-14, March.
   4. Bernd W. Wirtz & Wilhelm M. Müller & Florian W. Schmidt, 2021. "Digital Public Services in Smart Cities – an Empirical Analysis of Lead User Preferences," Public Organization Review, Springer, vol. 21(2), pages 299-315, June.
   5. Henkens, Bieke & Verleye, Katrien & Larivière, Bart, 2021. "The smarter, the better?! Customer well-being, engagement, and perceptions in smart service systems," International Journal of Research in Marketing, Elsevier, vol. 38(2), pages 425-447.
   6. Rainer Alt & Haluk Demirkan & Jan Fabian Ehmke & Anne Moen & Alfred Winter, 2019. "Smart services: The move to customer orientation," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(1), pages 1-6, March.
   7. Valerie Graf-Drasch & Maximilian Röglinger & Annette Wenninger & Sabiölla Hosseini, 2022. "A Contextualized Acceptance Model for Proactive Smart Services," Schmalenbach Journal of Business Research, Springer, vol. 74(3), pages 345-387, September.
   8. Tijan, Edvard & Jović, Marija & Aksentijević, Saša & Pucihar, Andreja, 2021. "Digital transformation in the maritime transport sector," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
   9. Jürgen Anke & Jens Poeppelbuss & Rainer Alt, 2020. "It Takes More than Two to Tango: Identifying Roles and Patterns in Multi-Actor Smart Service Innovation," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 72(4), pages 599-634, October.
   10. Lucie Kaňovská & Veronika Bumberová, 2021. "The Differences in the Propensity of Providing Smart Services by SMEs from the Electrical Engineering Industry with Regard to Their Cooperation and Innovation Flexibility," Sustainability, MDPI, vol. 13(9), pages 1-23, April.
   11. Lei Shen & Cong Sun & Muhammad Ali, 2021. "Path of Smart Servitization and Transformation in the Textile Industry: A Case Study of Various Regions in China," Sustainability, MDPI, vol. 13(21), pages 1-15, October.
   12. Lei Shen & Cong Sun & Muhammad Ali, 2021. "Role of Servitization, Digitalization, and Innovation Performance in Manufacturing Enterprises," Sustainability, MDPI, vol. 13(17), pages 1-17, September.
   13. Marija Jović & Edvard Tijan & Dražen Žgaljić & Saša Aksentijević, 2020. "Improving Maritime Transport Sustainability Using Blockchain-Based Information Exchange," Sustainability, MDPI, vol. 12(21), pages 1-19, October.
   14. Rongbin Yang & Santoso Wibowo, 2022. "User trust in artificial intelligence: A comprehensive conceptual framework," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2053-2077, December.
   15. Koldewey, Christian & Hemminger, Anja & Reinhold, Jannik & Gausemeier, Jürgen & Dumitrescu, Roman & Chohan, Nadia & Frank, Maximilian, 2022. "Aligning strategic position, behavior, and structure for smart service businesses in manufacturing," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
   16. Michel Muschkiet & Tobias Wulfert & Robert Woroch & Gero Strobel & Leonardo Banh, 2023. "Unleashing the digital building bricks," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-22, December.
   17. Minjun Kim & Silvana Trimi, 2023. "Transforming data into information for smart services: integration of morphological analysis and text mining," Service Business, Springer;Pan-Pacific Business Association, vol. 17(1), pages 257-280, March.
   18. Nicola Bilstein & Christian Stummer, 2020. "Special Section: Multidisciplinary Perspectives on Challenges in Managing Smart Products and Services," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 72(4), pages 479-483, October.

6. Christoph Gleue & Dennis Eilers & Hans-Jörg Mettenheim & Michael H. Breitner, 2019. "Decision Support for the Automotive Industry," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(4), pages 385-397, August.

   Cited by:

   1. Renxi Gong & Siqiang Li & Weiyu Peng, 2020. "Research on Multi-Attribute Decision-Making in Condition-Based Maintenance for Power Transformers Based on Cloud and Kernel Vector Space Models," Energies, MDPI, vol. 13(22), pages 1-11, November.

7. Max Leyerer & Marc-Oliver Sonneberg & Maximilian Heumann & Michael H. Breitner, 2019. "Decision support for sustainable and resilience-oriented urban parcel delivery," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 7(3), pages 267-300, November.

   Cited by:

   1. Riharsono Prastyantoro & Heru Purboyo Hidayat Putro & Gatot Yudoko & Puspita Dirgahayani, 2022. "E-Commerce Parcel Distribution in Urban Areas with Sustainable Performance Indicators," Sustainability, MDPI, vol. 14(23), pages 1-23, December.
   2. Andrea Ferrari & Giulio Mangano & Anna Corinna Cagliano & Alberto De Marco, 2023. "4.0 technologies in city logistics: an empirical investigation of contextual factors," Operations Management Research, Springer, vol. 16(1), pages 345-362, March.
   3. Magdalena Mucowska, 2021. "Trends of Environmentally Sustainable Solutions of Urban Last-Mile Deliveries on the E-Commerce Market—A Literature Review," Sustainability, MDPI, vol. 13(11), pages 1-26, May.
   4. Mashalah, Heider Al & Hassini, Elkafi & Gunasekaran, Angappa & Bhatt (Mishra), Deepa, 2022. "The impact of digital transformation on supply chains through e-commerce: Literature review and a conceptual framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).

8. Daniel Olivotti & Sonja Dreyer & Benedikt Lebek & Michael H. Breitner, 2019. "Creating the foundation for digital twins in the manufacturing industry: an integrated installed base management system," Information Systems and e-Business Management, Springer, vol. 17(1), pages 89-116, March.

   Cited by:

   1. Kamble, Sachin S & Gunasekaran, Angappa & Parekh, Harsh & Mani, Venkatesh & Belhadi, Amine & Sharma, Rohit, 2022. "Digital twin for sustainable manufacturing supply chains: Current trends, future perspectives, and an implementation framework," Technological Forecasting and Social Change, Elsevier, vol. 176(C).

9. Rouven-B. Wiegard & Michael H. Breitner, 2019. "Smart services in healthcare: A risk-benefit-analysis of pay-as-you-live services from customer perspective in Germany," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(1), pages 107-123, March.

   Cited by:

   1. Yuho Shimizu & Aimi Ishizuna & Shin Osaki & Takaaki Hashimoto & Mitsuharu Tai & Tetsushi Tanibe & Kaori Karasawa, 2022. "The Social Acceptance of Smart Health Services in Japan," IJERPH, MDPI, vol. 19(3), pages 1-11, January.
   2. Tran, Cong Duc & Nguyen, Tin Trung, 2021. "Health vs. privacy? The risk-risk tradeoff in using COVID-19 contact-tracing apps," Technology in Society, Elsevier, vol. 67(C).
   3. Angela Zeier Röschmann & Matthias Erny & Joël Wagner, 2022. "On the (future) role of on-demand insurance: market landscape, business model and customer perception," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(3), pages 603-642, July.
   4. Rainer Alt & Haluk Demirkan & Jan Fabian Ehmke & Anne Moen & Alfred Winter, 2019. "Smart services: The move to customer orientation," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(1), pages 1-6, March.
   5. Christiane Lehrer & U. Yeliz Eseryel & Annamina Rieder & Reinhard Jung, 2021. "Behavior change through wearables: the interplay between self-leadership and IT-based leadership," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(4), pages 747-764, December.
   6. Shang, Dawei & Wu, Weiwei & Schroeder, Daniel, 2023. "Exploring determinants of the green smart technology product adoption from a sustainability adapted value-belief-norm perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
   7. Rainer Alt, 2021. "Electronic Markets on platform complexity," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(4), pages 737-742, December.
   8. Nora Nahr & Marikka Heikkilä, 2022. "Uncovering the identity of Electronic Markets research through text mining techniques," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1257-1277, September.
   9. Davide Lanfranchi & Laura Grassi, 2022. "Examining insurance companies’ use of technology for innovation," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(3), pages 520-537, July.

10. Kenan Degirmenci & Sandra Lapin & Michael H. Breitner, 2017. "Critical success factors of carsharing and electric carsharing: findings from expert interviews in Continental Europe," International Journal of Automotive Technology and Management, Inderscience Enterprises Ltd, vol. 17(3), pages 294-315.

    Cited by:

    1. Hongqiang Guo & Jinyong Shangguan & Juan Tang & Qun Sun & Hongting Wu, 2018. "Receding horizon control strategy for an electric vehicle with dual-motor coupling system in consideration of stochastic vehicle mass," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-20, October.
    2. Lucia Rotaris & Marko Bumbulovic, 2020. "Carsharing: Business models, and role of the decision maker," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 0(1), pages 63-94.

11. Angelica Cuylen & Lubov Kosch & Michael H. Breitner, 2016. "Development of a maturity model for electronic invoice processes," Electronic Markets, Springer;IIM University of St. Gallen, vol. 26(2), pages 115-127, May.

    Cited by:

    1. Rainer Alt & Carsta Militzer-Horstmann & Hans-Dieter Zimmermann, 2016. "Electronic Markets on the impact factor," Electronic Markets, Springer;IIM University of St. Gallen, vol. 26(2), pages 95-101, May.
    2. Zhang Bin & Wang Shuhua, 2017. "The Influence of Electronic Invoice on Tax Collection and Tax Reform in China," Journal of Tax Reform, Graduate School of Economics and Management, Ural Federal University, vol. 3(3), pages 158-169.
    3. Caiado, Rodrigo Goyannes Gusmão & Scavarda, Luiz Felipe & Gavião, Luiz Octávio & Ivson, Paulo & Nascimento, Daniel Luiz de Mattos & Garza-Reyes, Jose Arturo, 2021. "A fuzzy rule-based industry 4.0 maturity model for operations and supply chain management," International Journal of Production Economics, Elsevier, vol. 231(C).
    4. Rainer Alt, 2020. "Electronic Markets on sustainability," Electronic Markets, Springer;IIM University of St. Gallen, vol. 30(4), pages 667-674, December.

12. Michael H. Breitner & Christian Dunis & Hans-Jörg Mettenheim & Christopher Neely & Georgios Sermpinis & Azizah Abu Bakar & Antonios Siganos & Evangelos Vagenas‐Nanos, 2014. "Does Mood Explain the Monday Effect?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(6), pages 409-418, September.

    Cited by:

    1. Umara Noreen & Attayah Shafique & Usman Ayub & Syed Kashif Saeed, 2022. "Does the Adaptive Market Hypothesis Reconcile the Behavioral Finance and the Efficient Market Hypothesis?," Risks, MDPI, vol. 10(9), pages 1-14, August.
    2. Ausloos, Marcel & Nedic, Olgica & Dekanski, Aleksandar & Mrowinski, Maciej J. & Fronczak, Piotr & Fronczak, Agata, 2017. "Day of the week effect in paper submission/acceptance/rejection to/in/by peer review journals. II. An ARCH econometric-like modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 462-474.
    3. Agarwal, Shweta & Kumar, Shailendra & Goel, Utkarsh, 2019. "Stock market response to information diffusion through internet sources: A literature review," International Journal of Information Management, Elsevier, vol. 45(C), pages 118-131.
    4. Ali, Fahad & Ülkü, Numan, 2020. "Weekday seasonality of stock returns: The contrary case of China," Journal of Asian Economics, Elsevier, vol. 68(C).
    5. Gavriilidis, Konstantinos & Kallinterakis, Vasileios & Tsalavoutas, Ioannis, 2016. "Investor mood, herding and the Ramadan effect," Journal of Economic Behavior & Organization, Elsevier, vol. 132(S), pages 23-38.
    6. Yılmaz, Emrah Sıtkı & Ozpolat, Aslı & Destek, Mehmet Akif, 2022. "Do Twitter Sentiments Really Effective on Energy Stocks? Evidence from Intercompany Dependency," MPRA Paper 114155, University Library of Munich, Germany.
    7. Autore, Don M. & Jiang, Danling, 2019. "The preholiday corporate announcement effect," Journal of Financial Markets, Elsevier, vol. 45(C), pages 61-82.
    8. Patrick Houlihan & Germán G. Creamer, 2017. "Can Sentiment Analysis and Options Volume Anticipate Future Returns?," Computational Economics, Springer;Society for Computational Economics, vol. 50(4), pages 669-685, December.
    9. Richards, Daniel W. & Willows, Gizelle D., 2018. "Who trades profusely? The characteristics of individual investors who trade frequently," Global Finance Journal, Elsevier, vol. 35(C), pages 1-11.
    10. Richards, Daniel W. & Willows, Gizelle D., 2019. "Monday mornings: Individual investor trading on days of the week and times within a day," Journal of Behavioral and Experimental Finance, Elsevier, vol. 22(C), pages 105-115.
    11. Yuliang Yao & Martin Dresner & Kevin Xiaoguo Zhu, 2019. "“Monday Effect” on Performance Variations in Supply Chain Fulfillment: How Information Technology–Enabled Procurement May Help," Information Systems Research, INFORMS, vol. 30(4), pages 1402-1423, December.
    12. Reboredo, Juan C. & Ugolini, Andrea, 2018. "The impact of Twitter sentiment on renewable energy stocks," Energy Economics, Elsevier, vol. 76(C), pages 153-169.
    13. Pedersen, Michael, 2019. "Anomalies in macroeconomic prediction errors–evidence from Chilean private forecasters," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1100-1107.
    14. Sakhr Miss & Michel Charifzadeh & Tim A. Herberger, 2020. "Revisiting the monday effect: a replication study for the German stock market," Management Review Quarterly, Springer, vol. 70(2), pages 257-273, May.
    15. Shanaev, Savva & Shuraeva, Arina & Fedorova, Svetlana, 2022. "The Groundhog Day stock market anomaly," Finance Research Letters, Elsevier, vol. 47(PA).
    16. Liu, Tianhao, 2021. "A study on day-of-week effect of submission: Based on the data of JSFST," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    17. Liang Meng & Haifeng Wang & Pengfei Han, 2020. "Getting a head start: turn-of-the-month submission effect for accepted papers in management journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2577-2595, September.
    18. Ausloos, Marcel & Nedic, Olgica & Dekanski, Aleksandar, 2016. "Day of the week effect in paper submission/acceptance/rejection to/in/by peer review journals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 197-203.

13. Michael H. Breitner & Christian Dunis & Hans-Jörg Mettenheim & Christopher Neely & Georgios Sermpinis & Rafael Rosillo & Javier Giner & David De la Fuente, 2014. "Stock Market Simulation Using Support Vector Machines," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(6), pages 488-500, September.

    Cited by:

    1. Aleesha Mohamudally-Boolaky & Teemulsingh Luchowa & Kesseven Padachi, 2019. "Applying the Support Vector Machine for Testing Pricing Inefficiency on the Stock Exchange of Mauritius," Applied Economics and Finance, Redfame publishing, vol. 6(5), pages 177-192, September.
    2. Dhruhi Sheth & Manan Shah, 2023. "Predicting stock market using machine learning: best and accurate way to know future stock prices," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 1-18, February.
    3. Zhou, Zhongbao & Gao, Meng & Liu, Qing & Xiao, Helu, 2020. "Forecasting stock price movements with multiple data sources: Evidence from stock market in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    4. Mostafaei, Kamran & maleki, Shaho & Zamani Ahmad Mahmoudi, Mohammad & Knez, Dariusz, 2022. "Risk management prediction of mining and industrial projects by support vector machine," Resources Policy, Elsevier, vol. 78(C).
    5. Hao Sun & Bo Yu, 2020. "Forecasting Financial Returns Volatility: A GARCH-SVR Model," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 451-471, February.
    6. Martín García, Rodrigo & Ventura Pérez, Enrique & Arguedas Sanz, Raquel, 2020. "Temporal optimisation of signals emitted automatically by securities exchange indicators," Cuadernos de Gestión, Universidad del País Vasco - Instituto de Economía Aplicada a la Empresa (IEAE).
    7. Zhang, Yongjie & Chu, Gang & Shen, Dehua, 2021. "The role of investor attention in predicting stock prices: The long short-term memory networks perspective," Finance Research Letters, Elsevier, vol. 38(C).
    8. Charalampos Stasinakis & Georgios Sermpinis & Ioannis Psaradellis & Thanos Verousis, 2016. "Krill-Herd Support Vector Regression and heterogeneous autoregressive leverage: evidence from forecasting and trading commodities," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1901-1915, December.
    9. Sermpinis, Georgios & Stasinakis, Charalampos & Rosillo, Rafael & de la Fuente, David, 2017. "European Exchange Trading Funds Trading with Locally Weighted Support Vector Regression," European Journal of Operational Research, Elsevier, vol. 258(1), pages 372-384.

14. Michael H. Breitner & Christian Dunis & Hans-Jörg Mettenheim & Christopher Neely & Georgios Sermpinis & Hamad Alsayed & Frank McGroarty, 2014. "Ultra‐High‐Frequency Algorithmic Arbitrage Across International Index Futures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(6), pages 391-408, September.

    Cited by:

    1. Takaki Hayashi & Yuta Koike, 2017. "No arbitrage and lead-lag relationships," Papers 1712.09854, arXiv.org.
    2. Hudson, Robert & McGroarty, Frank & Urquhart, Andrew, 2017. "Sampling frequency and the performance of different types of technical trading rules," Finance Research Letters, Elsevier, vol. 22(C), pages 136-139.
    3. Takaki Hayashi & Yuta Koike, 2016. "Wavelet-based methods for high-frequency lead-lag analysis," Papers 1612.01232, arXiv.org, revised Nov 2018.
    4. Kyungsub Lee & Byoung Ki Seo, 2019. "Marked Hawkes process modeling of price dynamics and volatility estimation," Papers 1907.12025, arXiv.org.
       • Lee, Kyungsub & Seo, Byoung Ki, 2017. "Marked Hawkes process modeling of price dynamics and volatility estimation," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 174-200.
    5. Zanin, Massimiliano & Belkoura, Seddik, 2018. "On the applicability of the Lead/Lag Ratio in causality assessment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 186-196.
    6. Hayashi, Takaki & Koike, Yuta, 2019. "No arbitrage and lead–lag relationships," Statistics & Probability Letters, Elsevier, vol. 154(C), pages 1-1.
    7. Batten, Jonathan A. & Lucey, Brian M. & McGroarty, Frank & Peat, Maurice & Urquhart, Andrew, 2018. "Does intraday technical trading have predictive power in precious metal markets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 102-113.

15. Benedikt Lebek & Jörg Uffen & Markus Neumann & Bernd Hohler & Michael H. Breitner, 2014. "Information security awareness and behavior: a theory-based literature review," Management Research Review, Emerald Group Publishing Limited, vol. 37(12), pages 1049-1092, November.

    Cited by:

    1. Saad Alahmari & Karen Renaud & Inah Omoronyia, 2023. "Moving beyond cyber security awareness and training to engendering security knowledge sharing," Information Systems and e-Business Management, Springer, vol. 21(1), pages 123-158, March.
    2. Dawn Branley-Bell & Yolanda Gómez & Lynne Coventry & José Vila & Pam Briggs, 2021. "Developing and Validating a Behavioural Model of Cyberinsurance Adoption," Sustainability, MDPI, vol. 13(17), pages 1-16, August.
    3. Alfiero, Simona & Battisti, Enrico & Ηadjielias, Elias, 2022. "Black box technology, usage-based insurance, and prediction of purchase behavior: Evidence from the auto insurance sector," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    4. Murilo Catussi Almeida & Adilson Carlos Yoshikuni & Rajeev Dwivedi & Cláudio Luís Carvalho Larieira, 2022. "Do Leadership Styles Influence Employee Information Systems Security Intention? A Study of the Banking Industry," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 23(4), pages 535-550, December.
    5. Myriam Dunn Cavelty, 2018. "Cybersecurity Research Meets Science and Technology Studies," Politics and Governance, Cogitatio Press, vol. 6(2), pages 22-30.
    6. Noor Suhani Sulaiman & Muhammad Ashraf Fauzi & Walton Wider & Jegatheesan Rajadurai & Suhaidah Hussain & Siti Aminah Harun, 2022. "Cyber–Information Security Compliance and Violation Behaviour in Organisations: A Systematic Review," Social Sciences, MDPI, vol. 11(9), pages 1-17, August.

16. Cornelius Köpp & Hans-Jörg Mettenheim & Michael Breitner, 2014. "Decision Analytics with Heatmap Visualization for Multi-step Ensemble Data," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 6(3), pages 131-140, June.

    Cited by:

    1. Christoph Gleue & Dennis Eilers & Hans-Jörg Mettenheim & Michael H. Breitner, 2019. "Decision Support for the Automotive Industry," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(4), pages 385-397, August.

17. Michael H. Breitner & Christian Dunis & Hans-Jörg Mettenheim & Christopher Neely & Georgios Sermpinis & Klaus Schredelseker, 2014. "Pascal's Wager and Information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(6), pages 455-470, September.

    Cited by:

    1. Paolo Pellizzari, 2024. "Learning Whether to Be Informed in an Agent-Based Evolutionary Market Model," Working Papers 2024: 03, Department of Economics, University of Venice "Ca' Foscari".
    2. Hauser, Florian & Schredelseker, Klaus, 2018. "Who benefits from insider regulation?," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 203-210.
    3. Weissensteiner, Alex, 2019. "Correlated noise: Why passive investment might improve market efficiency," Journal of Economic Behavior & Organization, Elsevier, vol. 158(C), pages 158-172.

18. Michael H. Breitner & Christian Dunis & Hans-Jörg Mettenheim & Christopher Neely & Georgios Sermpinis & Bartosz Kurek, 2014. "The Information Content of Equity Block Trades on the Warsaw Stock Exchange: An Estimation of Shares' Returns with the Usage of Simple Linear Regression and Multivariate Adaptive Regression Splines," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(6), pages 433-454, September.

    Cited by:

    1. Onur Enginar & Kazim Baris Atici, 2022. "Optimal forecast error as an unbiased estimator of abnormal return: A proposition," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 158-166, January.

19. Michael H. Breitner & Christian Dunis & Hans-Jörg Mettenheim & Christopher Neely & Georgios Sermpinis & Christian Spreckelsen & Hans‐Jörg Mettenheim & Michael H. Breitner, 2014. "Real‐Time Pricing and Hedging of Options on Currency Futures with Artificial Neural Networks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(6), pages 419-432, September.

    Cited by:

    1. Christoph Gleue & Dennis Eilers & Hans-Jörg Mettenheim & Michael H. Breitner, 2019. "Decision Support for the Automotive Industry," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(4), pages 385-397, August.
    2. Haibin Xie & Xinyu Wu & Pengying Fan, 2021. "Accelerating FHS Option Pricing Under Linear GARCH," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 395-411, August.
    3. Khan Najeeb Alam & Hameed Tooba & Razzaq Oyoon Abdul, 2018. "A Metaheuristic Approach to Optimize European Call Function with Boundary Conditions," Journal of Systems Science and Information, De Gruyter, vol. 6(3), pages 260-268, June.
    4. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Regional tourism demand forecasting with machine learning models: Gaussian process regression vs. neural network models in a multiple-input multiple-output setting”," AQR Working Papers 201701, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2017.
       • Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Regional tourism demand forecasting with machine learning models: Gaussian process regression vs. neural network models in a multiple-input multiple-output setting"," IREA Working Papers 201701, University of Barcelona, Research Institute of Applied Economics, revised Jan 2017.
    5. Adriano S. Koshiyama & Nikan Firoozye & Philip Treleaven, 2019. "A derivatives trading recommendation system: The mid‐curve calendar spread case," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 26(2), pages 83-103, April.
    6. Huck, Nicolas, 2019. "Large data sets and machine learning: Applications to statistical arbitrage," European Journal of Operational Research, Elsevier, vol. 278(1), pages 330-342.
    7. Roman Matkovskyy & Taoufik Bouraoui, 2019. "Application of Neural Networks to Short Time Series Composite Indexes: Evidence from the Nonlinear Autoregressive with Exogenous Inputs (NARX) Model," Post-Print hal-02155402, HAL.
       • Roman Matkovskyy & Taoufik Bouraoui, 2019. "Application of Neural Networks to Short Time Series Composite Indexes: Evidence from the Nonlinear Autoregressive with Exogenous Inputs (NARX) Model," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(2), pages 433-446, June.
    8. Adriano Soares Koshiyama & Nick Firoozye & Philip Treleaven, 2018. "A Machine Learning-based Recommendation System for Swaptions Strategies," Papers 1810.02125, arXiv.org.

20. Michael H. Breitner & Christian Dunis & Hans-Jörg Mettenheim & Christopher Neely & Georgios Sermpinis & Georgios Sermpinis & Charalampos Stasinakis & Konstantinos Theofilatos & Andreas Karathanasopoul, 2014. "Inflation and Unemployment Forecasting with Genetic Support Vector Regression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(6), pages 471-487, September.

    Cited by:

    1. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Working Papers 20-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Aug 2020.
       • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
       • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022. "How is machine learning useful for macroeconomic forecasting?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
       • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Papers 2008.12477, arXiv.org.
    2. Mustafa Yurtsever, 2023. "Unemployment rate forecasting: LSTM-GRU hybrid approach," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 57(1), pages 1-9, December.
    3. Hajirahimi, Zahra & Khashei, Mehdi & Etemadi, Sepideh, 2022. "A novel class of reliability-based parallel hybridization (RPH) models for time series forecasting," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    4. Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2019. "Nowcasting New Zealand GDP using machine learning algorithms," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
       • Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2018. "Nowcasting New Zealand GDP using machine learning algorithms," CAMA Working Papers 2018-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
       • Richardson, Adam & van Florenstein Mulder, Thomas & Vehbi, Tuğrul, 2021. "Nowcasting GDP using machine-learning algorithms: A real-time assessment," International Journal of Forecasting, Elsevier, vol. 37(2), pages 941-948.
    5. Han Lin Shang & Yang Yang & Fearghal Kearney, 2019. "Intraday forecasts of a volatility index: functional time series methods with dynamic updating," Annals of Operations Research, Springer, vol. 282(1), pages 331-354, November.
    6. Denis Shibitov & Mariam Mamedli, 2021. "Forecasting Russian Cpi With Data Vintages And Machine Learning Techniques," Bank of Russia Working Paper Series wps70, Bank of Russia.
    7. Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2019. "Nowcasting GDP using machine learning algorithms: A real-time assessment," Reserve Bank of New Zealand Discussion Paper Series DP2019/03, Reserve Bank of New Zealand.
       • Richardson, Adam & van Florenstein Mulder, Thomas & Vehbi, Tuğrul, 2021. "Nowcasting GDP using machine-learning algorithms: A real-time assessment," International Journal of Forecasting, Elsevier, vol. 37(2), pages 941-948.
    8. Pedro Correia S. Bezerra & Pedro Henrique M. Albuquerque, 2017. "Volatility forecasting via SVR–GARCH with mixture of Gaussian kernels," Computational Management Science, Springer, vol. 14(2), pages 179-196, April.
    9. Periklis Gogas & Theophilos Papadimitriou & Emmanouil Sofianos, 2022. "Forecasting unemployment in the euro area with machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 551-566, April.
    10. Psaradellis, Ioannis & Sermpinis, Georgios, 2016. "Modelling and trading the U.S. implied volatility indices. Evidence from the VIX, VXN and VXD indices," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1268-1283.
    11. Paranhos, Livia, 2021. "Predicting Inflation with Neural Networks," The Warwick Economics Research Paper Series (TWERPS) 1344, University of Warwick, Department of Economics.

21. Cornelius Köpp & Hans-Jörg Mettenheim & Michael Breitner, 2013. "Load Management in Power Grids," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 5(1), pages 35-44, February.

    Cited by:

    1. Arno E. Scheepens & Joost G. Vogtländer, 2018. "Insulation or Smart Temperature Control for Domestic Heating: A Combined Analysis of the Costs, the Eco-Costs, the Customer Perceived Value, and the Rebound Effect of Energy Saving," Sustainability, MDPI, vol. 10(9), pages 1-24, September.

22. M. H. Breitner, 2005. "The Genesis of Differential Games in Light of Isaacs’ Contributions," Journal of Optimization Theory and Applications, Springer, vol. 124(3), pages 523-559, March.

    Cited by:

    1. Valerii Patsko & Varvara Turova, 2020. "Antony Merz and His Works," Dynamic Games and Applications, Springer, vol. 10(1), pages 157-182, March.

23. Breitner, M.H. & Koslik, B. & von Stryk, O. & Pesch, H.J., 1995. "Iterative design of economic models via simulation, optimization and modeling," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 39(5), pages 527-532.

    Cited by:

    1. B. Koslik & M. H. Breitner, 1997. "In Optimal Control Problem in Economics with Four Linear Controls," Journal of Optimization Theory and Applications, Springer, vol. 94(3), pages 619-634, September.
    2. Susanne Winderl, 2000. "On A Complex Microeconomical Model For The Optimal Control Of A Concern," Computing in Economics and Finance 2000 234, Society for Computational Economics.

24. Christian Thimann & Michael Breitner, 1995. "Eastern Germany and the conflict between wage adjustment, investment, and employment: A numerical analysis," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 131(3), pages 446-469, September.
    • Thimann, C & Breitner, M-H, 1995. "Eastern Germany and the Conflict between Wage Adjustment, Investment and Employment : A Numerical Analysis," Papers 02, American Institute for Contemporary German Studies-.

    Cited by:

    1. Gerling, Katja & Schmidt, Klaus-Dieter, 1997. "On the competitive position of Eastern German manufacturing: Why is catching-up so slow?," Kiel Working Papers 825, Kiel Institute for the World Economy (IfW Kiel).
    2. Noland, Marcus & Robinson, Sherman & Wang, Tao, 2000. "Modeling Korean Unification," Journal of Comparative Economics, Elsevier, vol. 28(2), pages 400-421, June.
       • Marcus Noland & Sherman Robinson & Tao Wang, 1999. "Modeling Korean Unification," Working Paper Series WP99-7, Peterson Institute for International Economics.
    3. Hughes Hallett, A & Ma, Y & Melitz, J, 1995. "Unification and the Policy Predicament in Gemany," Papers 01, American Institute for Contemporary German Studies-.
       • Hughes Hallett, Andrew & Ma, Yue & Melitz, Jacques, 1994. "Unification and the Policy Predicament in Germany," CEPR Discussion Papers 956, C.E.P.R. Discussion Papers.
       • Hughes Hallett, A. & Ma, Y. & Melitz, J., 1996. "Unification and the policy predicament in Germany," Economic Modelling, Elsevier, vol. 13(4), pages 519-544, October.
    4. Marcus Noland & Sherman Robinson & Ligang Liu, 1999. "The economics of korean unification," Journal of Economic Policy Reform, Taylor & Francis Journals, vol. 3(3), pages 255-299.
       • Marcus Noland & Sherman Robinson & Li-Gang Liu, 1997. "The Economics of Korean Unification," Working Paper Series WP97-5, Peterson Institute for International Economics.

Chapters

1. Chris Stetter & Maximilian Heumann & Martin Westbomke & Malte Stonis & Michael H. Breitner, 2020. "A Real Options Approach to Determine the Optimal Choice Between Lifetime Extension and Repowering of Wind Turbines," Operations Research Proceedings, in: Janis S. Neufeld & Udo Buscher & Rainer Lasch & Dominik Möst & Jörn Schönberger (ed.), Operations Research Proceedings 2019, pages 291-297, Springer.

   Cited by:

   1. Stetter, Chris & Wielert, Henrik & Breitner, Michael H., 2022. "Hidden repowering potential of non-repowerable onshore wind sites in Germany," Energy Policy, Elsevier, vol. 168(C).
   2. Isabel C. Gil-García & Ana Fernández-Guillamón & M. Socorro García-Cascales & Angel Molina-García, 2021. "A Multi-Factorial Review of Repowering Wind Generation Strategies," Energies, MDPI, vol. 14(19), pages 1-25, October.

2. Hans-Jörg Mettenheim & Michael H. Breitner, 2014. "Forecasting Daily Highs and Lows of Liquid Assets with Neural Networks," Operations Research Proceedings, in: Stefan Helber & Michael Breitner & Daniel Rösch & Cornelia Schön & Johann-Matthias Graf von der Schu (ed.), Operations Research Proceedings 2012, edition 127, pages 253-258, Springer.

   Cited by:

   1. Huiwen Wang & Wenyang Huang & Shanshan Wang, 2021. "Forecasting open-high-low-close data contained in candlestick chart," Papers 2104.00581, arXiv.org.

3. Alexis Papathanassis & Michael Breitner, 2009. "Online booking in the cruise sector: Determinants of online trust & implications," Springer Books, in: Alexis Papathanassis (ed.), Cruise Sector Growth, chapter 11, pages 133-154, Springer.

   Cited by:

   1. Papathanassis, Alexis, 2012. "Guest-to-guest interaction on board cruise ships: Exploring social dynamics and the role of situational factors," Tourism Management, Elsevier, vol. 33(5), pages 1148-1158.

Books

1. Stefan Helber & Michael Breitner & Daniel Rösch & Cornelia Schön & Johann-Matthias Graf von der Schu (ed.), 2014. "Operations Research Proceedings 2012," Operations Research Proceedings, Springer, edition 127, number 978-3-319-00795-3, June.

   Cited by:

   1. Schwarz, Hannes & Bertsch, Valentin & Fichtner, Wolf, 2015. "Two-stage stochastic, large-scale optimization of a decentralized energy system - a residential quarter as case study," Working Paper Series in Production and Energy 10, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
   2. Bertsch, Valentin & Geldermann, Jutta & Lühn, Tobias, 2017. "What drives the profitability of household PV investments, self-consumption and self-sufficiency?," MPRA Paper 78644, University Library of Munich, Germany.
      • Bertsch, Valentin & Geldermann, Jutta & Lühn, Tobias, 2017. "What drives the profitability of household PV investments, self-consumption and self-sufficiency?," Applied Energy, Elsevier, vol. 204(C), pages 1-15.
   3. Goeke, Dominik, 2019. "Granular tabu search for the pickup and delivery problem with time windows and electric vehicles," European Journal of Operational Research, Elsevier, vol. 278(3), pages 821-836.
   4. Esther Mohr & Robert Dochow, 2017. "Risk management strategies for finding universal portfolios," Annals of Operations Research, Springer, vol. 256(1), pages 129-147, September.
   5. Bierwirth, Christian & Meisel, Frank, 2015. "A follow-up survey of berth allocation and quay crane scheduling problems in container terminals," European Journal of Operational Research, Elsevier, vol. 244(3), pages 675-689.
   6. Goeke, D. & Schneider, M., 2015. "Routing a Mixed Fleet of Electric and Conventional Vehicles," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 65939, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
   7. Goeke, Dominik & Schneider, Michael, 2015. "Routing a mixed fleet of electric and conventional vehicles," European Journal of Operational Research, Elsevier, vol. 245(1), pages 81-99.
   8. Pelletier, Samuel & Jabali, Ola & Laporte, Gilbert & Veneroni, Marco, 2017. "Battery degradation and behaviour for electric vehicles: Review and numerical analyses of several models," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 158-187.
   9. Dahlbeck, Mirko, 2021. "A mixed-integer linear programming approach for the T-row and the multi-bay facility layout problem," European Journal of Operational Research, Elsevier, vol. 295(2), pages 443-462.

More information

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NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-EDU: Education (2) 2003-11-09 2007-04-21
2. NEP-CMP: Computational Economics (1) 2004-08-02
3. NEP-HRM: Human Capital and Human Resource Management (1) 2007-04-21

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