Kyle is an Assistant Professor at the Ivey Business School. Kyle’s research focuses on how to apply Revenue Management techniques to the live entertainment industry. His research asks how entertainment products become a success and how to engage in operational allocation and pricing decisions. His work has been presented at numerous conferences, including the Institute for Operational Research and Management Sciences and at the Canadian Operational Research Society.
Prior to joining Ivey, Kyle was a Workflow Consultant at Thomson Reuters, where he provided VBA solutions to reduce labor and improve work quality, resulting in man hours saved as well as increased responsiveness to clients.
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Maclean, K.; Bayley, T., (Forthcoming), "That’s Incorrect and Let Me Tell You Why: A Scalable Assessment to Evaluate Higher Order Thinking Skills", INFORMS Transactions on Education
Abstract: We introduce a novel type of assessment that allows for efficient grading of higher order thinking skills. In this assessment, a student reviews and corrects a technical memo that has errors in its formulation or process. To overcome the grading challenges imposed by essay-type responses in large undergraduate courses, we provide a Visual Basic for Applications Excel tool for instructors, ensuring efficient grading of student submissions. We report our experience using this type of assessment in a multisection introductory business analytics course over several years and present survey-based evidence indicating that students perceive it to be clear and beneficial for learning. Supplemental Material: Data is available at https://www.informs.org/Publications/Subscribe/Access-Restricted-Materials
Link(s) to publication:
http://dx.doi.org/10.1287/ited.2023.0020
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Odegaard, F.; Maclean, K., 2023, "Revenue implications of celebrities on Broadway theatre", Journal of Revenue and Pricing Management, June 22(3): 207 - 218.
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Maclean, K., 2021, "Value of Stars on Broadway: A Case Study", Service Science, June 13(2): 77 - 87.
Abstract: Highly qualified employees are a critical element of a service experience. Utilizing the theatre metaphor, we showcase a method to value these employees with a case study on Broadway. Using a novel data set that includes Broadway show revenues, private expense data, and actor usage, our case study shows that stars were associated with increased revenues in the weeks they were present. However, after taking into account their effects on surrounding weeks’ revenues, their impact was significantly less. After accounting for the costs of hiring a star, we estimate a positive but not statistically significant impact on profit. We discuss managerial implications for designers of service experiences.
Link(s) to publication:
http://dx.doi.org/10.1287/serv.2021.0273
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Maclean, K.; Odegaard, F., 2020, "Dynamic capacity allocation for group bookings in live entertainment", European Journal of Operational Research, December 287(3): 975 - 988.
Abstract: A persistent problem within live entertainment is lost revenue due to unsold seats. One reason behind this problem is that venues generally permit customers, of varying group size, to freely choose seats, and thus causing a sub-optimal seating allocation with sparsely stranded single seats. Due to the experiential attribute of live entertainment, ticket requests are predominantly groups wishing sets of contiguous seats. Consequently, the sparse single seats remain unsold. To solve this operational problem we analyze a capacity based revenue management control problem that explicitly accounts for group size and customer choice. We formulate the problem as a discrete-time Markov Decision Process with the objective to maximize total expected profit. Each period, and for a given arriving group size, the manager decides which price-differentiated segments to make available. Given the offered segments, customers select seats from a particular segment or choose not to purchase any. We discuss three selection models and provide algorithms to determine the optimal solution for each. Motivated by ad hoc provisions observed in practice and due to the curse of dimensionality we provide and analyze via simulation a heuristic. Finally, based on transactional sales data from a large annual North American sporting event we showcase how the model parameters can empirically be estimated.
Link(s) to publication:
http://dx.doi.org/10.1016/j.ejor.2020.02.017
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van de Geer, R.; V. den Boer, A.; Bayliss, C.; Currie, C.; Ellina, A.; Esders, M.; Haensel, A.; Lei, X.; Maclean, K.; Martinez-Sykora, A., et al., 2019, "Dynamic Pricing and Learning with Competition: Insights from the Dynamic Pricing Challenge at the 2017 INFORMS RM & Pricing Conference", Journal of Revenue and Pricing Management, June 18(3): 185 - 203.
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Maclean, K.; Wilson, J. G.; Krishnamoorthy, S., 2017, "Pricing of excess inventory on Groupon", International Journal of Revenue Management, May 10(1): 52 - 74.
Abstract: We consider the problem faced by a business that is considering using the Groupon platform to sell excess inventory. We discuss how demand functions can be derived using management knowledge. Then, using a single period model where excess inventory is exogenous, we show that the decision to use Groupon and the price to set on that channel depend on two parameters: the relative price sensitivity of Groupon customers as compared to the retailer's regular customers and the relative size of the Groupon market as compared to the regular market. Under a two-period model, when initial inventory is a decision, we show optimal inventory quantities. Our two-period model suggests that managers may plan on using Groupon and order inventory accordingly. We discuss the implications on third party channels as well as retail managers.
Link(s) to publication:
https://doi.org/10.1504/IJRM.2017.084152
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