Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Part-Time Workers vs Gig-Contractors: Impact of Worker Availability on Performance of Contingent Workers in Online Retail
Reeju Guha, Daniel Corsten
IE Business School, Spain
Companies operating under gig-contractor models are offering part-time job requiring longer work availability. This ensures quicker delivery & better service quality. Using data from an online retailer we find that workers with similar level of experience perform differently. This is explained through the role of worker availability. At similar levels of experience, workers in high-work group perform better than those in the low-work group after controlling for task and worker characteristics.
Effect of a sustainable firm’s entry on customer channel choices and existing retailers' market shares
Hans Sebastian Heese1, Eda Kemahlioglu-Ziya1, Olga Perdikaki2
1NC State University, United States of America; 2University of South Carolina, United States of America
New sustainability-marketed firms have emerged in the grocery and consumer packaged goods categories responding to consumers’ rising preferences for sustainable products. Motivated by this trend in the retail industry, we study how the entry of a new firm that sells an assortment of sustainable consumer goods affects the consumers’ channel choices and the existing retailers’ market shares in two different types of product offerings -- packaged and fresh goods.
When is the next order? Forecasting the timing of retail orders using Point-of-Sales data and channel inventory estimations
Tim Schlaich, Kai Hoberg
Kuehne Logistics University, Germany
Slow-moving items constitute a large share of the retail assortment and often result in intermittent orders by the retailer. We estimate retail channel inventories based on prior orders and Point-of-Sales data to predict the timing of future orders. We demonstrate both theoretically and empirically that this an inventory modeling approach outperforms the Croston's method and thus provides a viable alternative to conventional time-series models.