Strategic rationing and freshness keeping of perishable products under transportation disruptions and demand learning

This paper considers a retailer who sells perishable fresh products directly to customers through an online channel and encounters a transportation disruption. Products shipped during the disruption period come with an uncontrollable delivery lead time, resulting in product quality degradation. To balance the compensation price provided to customers because of quality losses, the retailer might employ freshness-keeping efforts to reduce the quality loss during transportation. Therefore, it raises several fundamental questions for the retailer in mitigating the disruption. Is it always optimal to satisfy those customers who are willing to purchase during disruption? If it is profitable to fulfill orders along with an extra delivery lead time, and with a quality loss compensation, what is the optimal freshness-keeping effort? If it is preferable to deliberately create unsatisfied demand by announcing shortages (rationing) to customers, when is the optimal time to do so? To answer these questions, we first present the dynamics of post-disruption inventory and demand, taking into account the demand learning effect facilitated from negative word-of-mouth during disruption and the demand recovery after disruption ends. Afterward, we develop a model to achieve the optimal selling strategy for maximizing post-disruption profit, identifying the joint decision of the rationing period and freshness-keeping effort. Finally, by numerical analysis, three types of selling strategies are visually provided to hedge against disruptions of different lengths.

Dynamic Inventory Control with Stockout Substitution and Demand Learning

We consider an inventory control problem with multiple products and stockout substitution. The firm knows neither the primary demand distribution for each product nor the customers’ substitution probabilities between products a priori, and it needs to learn such information from sales data on the fly. One challenge in this problem is that the firm cannot distinguish between primary demand and substitution (overflow) demand from the sales data of any product, and lost sales are not observable. To circumvent these difficulties, we construct learning stages with each stage consisting of a cyclic exploration scheme and a benchmark exploration interval. The benchmark interval allows us to isolate the primary demand information from the sales data, and then this information is used against the sales data from the cyclic exploration intervals to estimate substitution probabilities. Because raising the inventory level helps obtain primary demand information but hinders substitution demand information, inventory decisions have to be carefully balanced to learn them together. We show that our learning algorithm admits a worst-case regret rate that (almost) matches the theoretical lower bound, and numerical experiments demonstrate that the algorithm performs very well. This paper was accepted by J. George Shanthikumar, big data analytics.

Project Based Learning Pedagogical Design in STEAM Art Education

This paper explores the potential of Project-Based Learning (PBL) approach in a multidisciplinary art classroom involving STEAM (Science, Technology, Engineering, Art, and Mathematics) education. The PBL approach involves a dynamic classroom approach, which emphasises on long-term learning, interdisciplinary and student-centred art activities. This implementation would benefit the teaching strategies in art projects; helping students understand lessons, improving communication and soft skills, as well as enhancing leadership skills and creativity. However, there are some concerns related to the PBL approach: i) difficulties in finding appropriate teaching strategies, ii) choosing suitable projects, iii) selecting relevant measurement tools or assessing rubrics, and iv) developing learning content to suit the objective and the main purpose of the art curriculum. In identifying this approach’s potential, a study was carried out involving two art teachers in their respective classrooms. Data was collected through interviews, observations, and document analysis of their teaching strategies, which included three main phases of PBL implementation in creating art projects. The findings suggest that the PBL pedagogical design has the ability to improve teaching strategies and with potential to replace a traditional, teacher-led art classroom. The approach is effective in guiding teachers to manoeuvre an authentic art lesson while benefiting the students through emphasis on the artistic process of creating a STEAM project, while focusing on culminating the necessary art content through active collaboration, exploration of real-world challenges and curricular activities’ problem-solving. However, a number of challenges were identified, such as curriculum demand, learning content, teachers’ and students’ attitude, and access to instruments. Hence, a number of suggestions and recommendations are proposed to help resolve the challenges. The implications of the study on arts curriculum, school systems and other higher institutions are also discussed. Keywords: Project-Based Learning, Art Education, STEAM