Smart Pricing: Linking Pricing Decisions with Operational Insights

The past decade has seen a virtual explosion of information about customers and their preferences. This information potentially allows companies to increase their revenues, in particular since modern technology enables price changes to be effected at minimal cost. At the same time, companies have taken major strides in understanding and managing the dynamics of the supply chain, both their internal operations and their relationships with supply chain partners. These two developments are narrowly intertwined. Pricing decisions have a direct effect on operations and visa versa. Yet, the systematic integration of operational and marketing insights is in an emerging stage, both in academia and in business practice. This article reviews a number of key linkages between pricing and operations. In particular, it highlights different drivers for dynamic pricing strategies. Through the discussion of key references and related software developments we aim to provide a snapshot into a rich and evolving field.supply chain management;inventory;capacity;dynamic pricing;operations-marketing interface

Periodic Review, Push Inventory Policies for Remanufacturing

Sustainability has become a major issue in most economies, causing many leading companies to focus on product recovery and reverse logistics. This research is focused on product recovery, and in particular on production control and inventory management in the remanufacturing context. We study a remanufacturing facility that receives a stream of returned products according to a Poisson process. Demand is uncertain and also follows a Poisson process. The decision problems for the remanufacturing facility are when to release returned products to the remanufacturing line and how many new products to manufacture. We assume that remanufactured products are as good as new. In this paper, we employ a "push" policy that combines these two decisions. It is well known that the optimal policy parameters are difficult to find analytically; therefore, we develop several heuristics based on traditional inventory models. We also investigate the performance of the system as a function of return rates, backorder costs and manufacturing and remanufacturing lead times; and we develop approximate lower and upper bounds on the optimal solution. We illustrate and explain some counter-intuitive results and we test the performance of the heuristics on a set of sample problems. We find that the average error of the heuristics is quite low.inventory;reverse logistics;remanufacturing;environment;heuristics

Dynamic pathfinding for a swarm intelligence based UAV control model using particle swarm optimisation

In recent years unmanned aerial vehicles (UAVs) have become smaller, cheaper, and more efficient, enabling the use of multiple autonomous drones where previously a single, human-operated drone would have been used. This likely includes crisis response and search and rescue missions. These systems will need a method of navigating unknown and dynamic environments. Typically, this would require an incremental heuristic search algorithm, however, these algorithms become increasingly computationally and memory intensive as the environment size increases. This paper used two different Swarm Intelligence (SI) algorithms: Particle Swarm Optimisation and Reynolds flocking to propose an overall system for controlling and navigating groups of autonomous drones through unknown and dynamic environments. This paper proposes Particle Swarm Optimisation Pathfinding (PSOP): a dynamic, cooperative algorithm; and, Drone Flock Control (DFC): a modular model for controlling systems of agents, in 3D environments, such that collisions are minimised. Using the Unity game engine, a realtime application, simulation environment, and data collection apparatus were developed and the performances of DFC-controlled drones—navigating with either the PSOP algorithm or a D* Lite implementation—were compared. The simulations do not consider UAV dynamics. The drones were tasked with navigating to a given target position in environments of varying size and quantitative data on pathfinding performance, computational and memory performance, and usability were collected. Using this data, the advantages of PSO-based pathfinding were demonstrated. PSOP was shown to be more memory efficient, more successful in the creation of high quality, accurate paths, more usable and as computationally efficient as a typical incremental heuristic search algorithm when used as part of a SI-based drone control model. This study demonstrated the capabilities of SI approaches as a means of controlling multi-agent UAV systems in a simple simulation environment. Future research may look to apply the DFC model, with the PSOP algorithm, to more advanced simulations which considered environment factors like atmospheric pressure and turbulence, or to real-world UAVs in a controlled environment

Periodic Review, Push Inventory Policies for Remanufacturing

Sustainability has become a major issue in most economies, causing many leading companies to focus on product recovery and reverse logistics. This research is focused on product recovery, and in particular on production control and inventory management in the remanufacturing context. We study a remanufacturing facility that receives a stream of returned products according to a Poisson process. Demand is uncertain and also follows a Poisson process. The decision problems for the remanufacturing facility are when to release returned products to the remanufacturing line and how many new products to manufacture. We assume that remanufactured products are as good as new. In this paper, we employ a "push" policy that combines these two decisions. It is well known that the optimal policy parameters are difficult to find analytically; therefore, we develop several heuristics based on traditional inventory models. We also investigate the performance of the system as a function of return rates, backorder costs and manufacturing and remanufacturing lead times; and we develop approximate lower and upper bounds on the optimal solution. We illustrate and explain some counter-intuitive results and we test the performance of the heuristics on a set of sample problems. We find that the average error of the heuristics is quite low

A Dynamic Pricing Model for Coordinated Sales and Operations

Recent years have seen advances in research and management practice in the area of pricing, and particularly in dynamic pricing and revenue management. At the same time, researchers and managers have made dramatic improvements in operations and supply chain management. The interactions between pricing and operations/supply chain performance, however, are not as well understood. In this paper, we examine this linkage by developing a deterministic, finite-horizon dynamic programming model that captures a price/demand effect as well as a stockpiling/consumption effect – price and market stockpile influence demand, demand influences consumption, and consumption influences the market stockpile. The decision variable is the unit sales price in each period. Through the market stockpile, pricing decisions in a given period explicitly depend on decisions in prior periods. Traditional operations models typically assume exogenous demand, thereby ignoring some of the market dynamics. Herein, we model endogenous demand, and we develop analytical insights into the nature of optimal prices and promotions. We develop conditions under which the optimal prices converge to a constant. In other words, price promotion is suboptimal. We also analytically and numerically illustrate cases where the optimal prices vary over time. In particular, we show that price dynamics may be driven by both (a) revenue effects, due to nonlinear market responses to prices and/or inventory, and (b) cost effects, due to economies of scale in operations. The paper concludes with a discussion of directions for future research

Knowing what they know is half the battle: Investigating student conceptions of stoichiometry

Stoichiometry is a core topic in high school chemistry, yet it is often one of the most daunting for students as the extensive range of chemical and mathematical concepts required for understanding make this topic complex and challenging for student learning (Wink & Ryan, 2019; Ramful & Narod, 2014). The long-standing interest in research into student learning has afforded conceptions, misconceptions and alternative conceptions as vehicles through which researchers can investigate student understanding (Taber, 2015; Gilbert & Watts, 1983). Two-tier diagnostic instruments have been used extensively in previous research for this purpose where they have been useful in obtaining data regarding students’ conceptions of the relevant subject matter (Treagust, 1988; Soeharto et al., 2019). This study involved development of a two-tier diagnostic instrument to investigate the interplay between stoichiometry and mathematics. There were four steps to the development and refinement of the two-tier diagnostic instrument: defining the scope of the project, constructing the first tier, obtaining alternative conceptions, and developing the second tier. With multiple refinements during the design phase, the development of the instrument was informed by face validation from ten ‘critical friends’ alongside written responses from both undergraduate and graduate students (n = 24) and think-aloud interviews (n = 12). The final version of the two-tier diagnostic instrument contains 21 items comprising 14 chemistry items and 7 mathematics items. Development of a two-tier diagnostic instrument that addresses two interrelated subject matter areas is a novel application of the two-tier diagnostic approach and the implications of this will be presented.  REFERENCES Gilbert, J. K., & Watts, D. M. (1983). Concepts, Misconceptions and Alternative Conceptions: Changing Perspectives in Science Education. Studies in Science Education, 10(1), 61-98. Ramful, A., & Narod, F. B. (2014). Proportional reasoning in the learning of chemistry: levels of complexity, Mathematics Education Research Journal, 26(1), 25-46. Soeharto, S., Csapó, B., Sarimanah, E., Dewi, F., & Sabri, T. (2019). A Review of Students’ Common Misconceptions in Science and Their Diagnostic Assessment Tools. Jurnal Pendidikan IPA Indonesia. 8(2), 247-266. Taber, K. S. (2015). Alternative conceptions/frameworks/misconceptions. Encyclopedia of Science Education, pp 37-41. Treagust, D. F. (1988). Development and use of diagnostic tests to evaluate students’ misconceptions in science. International Journal of Science Education, 10(2), 159-169. Wink, D. J., & Ryan, S. A. C. (2019). The Logic of Proportional Reasoning and Its Transfer into Chemistry. It’s Just Math: Research on Students’ Understanding of Chemistry and Mathematics, pp 157-171

Smart Pricing: Linking Pricing Decisions with Operational Insights

The past decade has seen a virtual explosion of information about customers and their preferences. This information potentially allows companies to increase their revenues, in particular since modern technology enables price changes to be effected at minimal cost. At the same time, companies have taken major strides in understanding and managing the dynamics of the supply chain, both their internal operations and their relationships with supply chain partners. These two developments are narrowly intertwined. Pricing decisions have a direct effect on operations and visa versa. Yet, the systematic integration of operational and marketing insights is in an emerging stage, both in academia and in business practice. This article reviews a number of key linkages between pricing and operations. In particular, it highlights different drivers for dynamic pricing strategies. Through the discussion of key references and related software developments we aim to provide a snapshot into a rich and evolving field

Introducing commencing students to “being a scientist” – A review of a new compulsory academic literacies course

The Bachelor of Science program at The University of Adelaide was reviewed by an external expert panel in 2007. One of the key recommendations to come from this review was the requirement to introduce a common compulsory course in the first year of study focussing on the development of academic literacies. This new course (‘Principles & Practice of Science I’) was offered for the first time in Semester 1, 2011. Students were introduced to the idea of what it means to “be a scientist” through discussion of the broad array of scientific endeavour, the integrated nature of scientific disciplines, the importance of scientific process and critical thinking. Academic writing was used as the key vehicle for assessment of the desired learning outcomes. This presentation will focus on some of the tools and activities used in ‘Principles & Practice of Science I’ to develop student’s academic writing skills

The Party’s Over: Sustaining Support Programs When the Funding is Done

In the lifecycle of an engineering education grant, the phase where best practices are sustained and disseminated is perhaps the most crucial stage for maximizing impact. Yet this transition phase often receives the least attention as project team enthusiasm can wane, while funding tapers off, and faculty priorities are pulled in other directions. There are numerous obstacles associated with sustaining program changes, even those perceived as very valuable. Typical challenges are: What happens when the funding runs out? What grant-developed programs should be sustained by the university? Does the institution need to internally allocate resources in an annual budget large enough to replace the grant? Ultimately, sustaining successful programmatic improvements is about “change management” in an institution. In this paper, we will review the literature relating to institutional change in engineering education. We will build on current curriculum change models, in the context of a major engineering education grant at Boise State University that included a variety of curricular enhancements, academic support, and outreach efforts. Over the past two years, the project team focused considerable effort on institutionalizing the most successful programs, and met with mixed results. While many programs will continue and benefit students long-term, other programs, even ones with stellar success and solid assessment, have not been entirely adopted for a number of reasons that we will examine. We will review the role assessment played in the process of program transfer (from the grant to the university) and lessons learned about building alliances with other campus partners to achieve university-level buy-in, well before the last stage of the grant. Finally, we will discuss two factors that are not identified in institutional change literature, but that contributed significantly to the successful transition of our programs—the importance of taking a research based approach, and flexibility in time and resource allocation