@article{ReimersJacksohnAppenfelleretal.2021,
  author    = {Reimers, Hanna and Jacksohn, Anke and Appenfeller, Dennis and Lasarov, Wassili and H{\"u}ttel, Alexandra and Rehdanz, Katrin and Balderjahn, Ingo and Hoffmann, Stefan},
  title     = {Indirect rebound effects on the consumer level},
  series = {Cleaner and responsible consumption},
  volume    = {3},
  journal   = {Cleaner and responsible consumption},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {2666-7843},
  doi       = {10.1016/j.clrc.2021.100032},
  pages     = {16},
  year      = {2021},
  abstract  = {Indirect rebound effects on the consumer level occur when potential greenhouse gas emission savings from the usage of more efficient technologies or more sufficient consumption in one consumption area are partially or fully offset through the consumers' adverse behavioral responses in other areas. As both economic (e.g., price effects) and psychological (e.g., moral licensing) mechanisms can stimulate these indirect rebound effects, they have been studied in different fields, including economics, industrial ecology, psychology, and consumer research. Consequently, the literature is highly fragmented and disordered. To integrate the body of knowledge for an interdisciplinary audience, we review and summarize the previous literature, covering the microeconomic quantification of indirect rebounds based on observed expenditure behavior and the psychological processes underlying indirect rebounds. The literature review reveals that economic quantifications and psychological processes of indirect rebound effects have not yet been jointly analyzed. We derive directions for future studies, calling for a holistic research agenda that integrates economic and psychological mechanisms.},
  language  = {en}
}
@article{Schlosser2020,
  author    = {Schlosser, Rainer},
  title     = {Scalable relaxation techniques to solve stochastic dynamic multi-product pricing problems with substitution effects},
  series = {Journal of revenue and pricing management},
  volume    = {20},
  journal   = {Journal of revenue and pricing management},
  number    = {1},
  publisher = {Palgrave Macmillan},
  address   = {Basingstoke},
  issn      = {1476-6930},
  doi       = {10.1057/s41272-020-00249-z},
  pages     = {54 -- 65},
  year      = {2020},
  abstract  = {In many businesses, firms are selling different types of products, which share mutual substitution effects in demand. To compute effective pricing strategies is challenging as the sales probabilities of each of a firm's products can also be affected by the prices of potential substitutes. In this paper, we analyze stochastic dynamic multi-product pricing models for the sale of perishable goods. To circumvent the limitations of time-consuming optimal solutions for highly complex models, we propose different relaxation techniques, which allow to reduce the size of critical model components, such as the state space, the action space, or the set of potential sales events. Our heuristics are able to decrease the size of those components by forming corresponding clusters and using subsets of representative elements. Using numerical examples, we verify that our heuristics make it possible to dramatically reduce the computation time while still obtaining close-to-optimal expected profits. Further, we show that our heuristics are (i) flexible, (ii) scalable, and (iii) can be arbitrarily combined in a mutually supportive way.},
  language  = {en}
}