TY - GEN A1 - Pannhorst, Matthias A1 - Dost, Florian T1 - Marketing innovations to old-age consumers: A dynamic Bass model for different life stages T2 - Technological Forecasting and Social Change Y1 - 2019 U6 - https://doi.org/10.1016/j.techfore.2018.12.022 SN - ‎0040-1625 VL - 140 IS - 2 SP - 315 EP - 327 ER - TY - GEN A1 - Dost, Florian A1 - Maier, Erik T1 - E-Commerce Effects on Energy Consumption – A Multi-Year Ecosystem-Level Assessment T2 - Journal of Industrial Ecology Y1 - 2018 U6 - https://doi.org/10.1111/jiec.12639 SN - 1530-9290 VL - 22 IS - 4 SP - 799 EP - 812 ER - TY - GEN A1 - Maier, Erik A1 - Dost, Florian T1 - Fluent Contextual Image Backgrounds Enhance Mental Imagery and Evaluations of Experience Products T2 - Journal of Retailing and Consumer Services Y1 - 2018 U6 - https://doi.org/https://doi.org/10.1016/j.jretconser.2018.09.006 SN - 0969-6989 VL - 45 SP - 207 EP - 220 ER - TY - GEN A1 - Maier, Erik A1 - Dost, Florian T1 - The positive effect of contextual image backgrounds on fluency and liking T2 - Journal of Retailing and Consumer Services Y1 - 2018 U6 - https://doi.org/10.1016/j.jretconser.2017.09.003 SN - 0969-6989 VL - 40 SP - 109 EP - 116 ER - TY - GEN A1 - Dost, Florian A1 - Geiger, Ingmar T1 - Value-based pricing in competitive situations with multi-product price-response maps T2 - Journal of Business Research Y1 - 2017 U6 - https://doi.org/10.1016/j.jbusres.2017.01.004 SN - 0148- 2963 VL - 76 SP - 219 EP - 236 ER - TY - GEN A1 - Bogodistov, Yevgen A1 - Dost, Florian T1 - Proximity Begins with a Smile, But Which One? Associating Non-duchenne Smiles with Higher Psychological Distance T2 - Frontiers in Psychology Y1 - 2017 U6 - https://doi.org/10.3389/fpsyg.2017.01374 SN - 1664-1078 IS - 8 ER - TY - GEN A1 - Rennie, Nicola A1 - Cleophas, Catherine A1 - Sykulski, Adam A1 - Dost, Florian T1 - Identifying and responding to outlier demand in revenue management T2 - European Journal of Operational Research N2 - Revenue management strongly relies on accurate forecasts. Thus, when extraordinary events cause outlier demand, revenue management systems need to recognise this and adapt both forecast and controls. Many passenger transport service providers, such as railways and airlines, control the sale of tickets through revenue management. State-of-the-art systems in these industries rely on analyst expertise to identify outlier demand both online (within the booking horizon) and offline (in hindsight). So far, little research focuses on automating and evaluating the detection of outlier demand in this context. To remedy this, we propose a novel approach, which detects outliers using functional data analysis in combination with time series extrapolation. We evaluate the approach in a simulation framework, which generates outliers by varying the demand model. The results show that functional outlier detection yields better detection rates than alternative approaches for both online and offline analyses. Depending on the category of outliers, extrapolation further increases online detection performance. We also apply the procedure to a set of empirical data to demonstrate its practical implications. By evaluating the full feedback-driven system of forecast and optimisation, we generate insight on the asymmetric effects of positive and negative demand outliers. We show that identifying instances of outlier demand and adjusting the forecast in a timely fashion substantially increases revenue compared to what is earned when ignoring outliers. Y1 - 2021 U6 - https://doi.org/10.1016/j.ejor.2021.01.002 VL - 293 IS - 3 SP - 1015 EP - 1030 ER - TY - GEN A1 - Schmidt, Lennard A1 - Dost, Florian A1 - Maier, Erik T1 - Filtering Survey Responses from Crowdsourcing Platforms: Current Heuristics and Alternative Approaches T2 - International Conference on Information Systems N2 - Information Systems research continues to rely on survey participants from crowdsourcing platforms (e.g., Amazon MTurk). Satisficing behavior of these survey participants may reduce attention and threaten validity. To address this, the current research paradigm mandates excluding participants through filtering heuristics (e.g., time, instructional manipulation checks). Yet, both the selection of the filter and the filtering threshold are not standardized. This flexibility may lead to suboptimal filtering and potentially “p-hacking”, as researchers can pick the most “successful” filter. This research is the first to tests a comprehensive set of established and new filters against key metrics (validity, reliability, effect size, power). Additionally, we introduce a multivariate machine learning approach to identify inattentive participants. We find that while filtering heuristics require high filter levels (33% or 66% of participants), machine learning filters are often superior, especially at lower filter levels. Their “black box” character may also help prevent strategic filtering. KW - Survey Research KW - Filtering KW - Amazon MTurk KW - Reliability KW - Validity KW - Effect Size Y1 - 2019 UR - https://aisel.aisnet.org/icis2019/research_methods/research_methods/8 ER - TY - GEN A1 - Isaak, Karina A1 - Wilken, Robert A1 - Dost, Florian A1 - Bürgin, David T1 - Improving pricing scope through consumers’ construal level – evidence based on consumers’ willingness-to-pay ranges T2 - Die Unternehmung N2 - How can the pricing scope be further leveraged in times of increased price transparency and growing price awareness on the consumer side? To answer this question, this paper uses the concept of willingness-to-pay ranges (as opposed to points). Three quantit� ative studies show that various marketing activities that allow con� sumers to assess a product on a more abstract (less concrete) level shift the upper limits of the intervals upwards and thus increase the scope for price setting. These (price) upper limits are particularly high when the central product advantages are emphasized. Y1 - 2020 U6 - https://doi.org/10.5771/0042-059X-2020-4-365 SN - 0042-059X SN - 0042-059x VL - 74 IS - 4 SP - 365 EP - 383 ER - TY - GEN A1 - Boden, Joe A1 - Maier, Erik A1 - Dost, Florian T1 - The Effect of Electronic Shelf Labels on Store Revenue T2 - International Journal of Electronic Commerce N2 - Today’s retailers have a strategic imperative to integrate their channels. Some have implemented electronic shelf labels (ESL) to replace paper tags to technologically enable the omnichannel transformation by aligning the presentation of price and product information between online and offline channels. However, consumer reactions to ESL are yet unexplored. They could be positive or negative: on one hand, the fear of frequent price changes, a known phenomenon in e-commerce, could spread to offline channels and reduce consumer purchase intent and overall revenue; on the other hand, ESL could prevent showrooming by signaling price consistency and offering consistent information (e.g., including reviews) between the on- and offline channels. We explore a retailer data set that allows isolating the “mere ESL effect”, as the retailer’s pricing strategy remained unchanged over the introduction of ESL (i.e., no dynamic pricing), but the presentation of the price and product information was integrated through ESL. A difference-in-difference analysis establishes that revenue in product categories in which ESL was introduced grows at the expense of those product categories in which it was not introduced. Visitor numbers are not affected by introducing ESL. This finding supports the adoption of e-commerce capabilities in a brick-and-mortar store as it could help prevent shopper behavior aimed at exploiting channel differences (i.e., showrooming for price or more information). KW - multichannel retailing KW - online retail KW - pricing Y1 - 2020 U6 - https://doi.org/10.1080/10864415.2020.1806472 SN - 1557-9301 SN - 1086-4415 VL - 24 IS - 4 SP - 527 EP - 550 ER -