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Forthcoming and Online First Articles
International Journal of Revenue Management
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International Journal of Revenue Management (3 papers in press)
Optimal hedging in a processing environment: A case of ethanol production by William Wilson, Kristopher Skadberg, Iddrisu Awudu, Bruce Dahl, Mariama Yakubu Abstract: Hedging is an important strategy to reduce risk for most processing firms. In this paper, we determine optimal hedging strategies for an ethanol processing firm with input (corn), and outputs [ethanol, distillers dried grain soluble (DDGs), and corn oil]. Strategic decisions regarding alternative underlying cash and futures positions, in addition to hedge ratios, quantity of ethanol and corn to buy or sell, and co-products are considered in this work. We develop portfolio optimisation models with different risk (hedging) specifications that incorporate copula distributions to evaluate among alternative hedging strategies. The results indicate lower standard deviations for traditional hedges with higher returns using ethanol futures (specifically ethanol platt futures). Meanwhile, we find that hedging ethanol using a short position has a higher standard deviation and a lower value-at-risk (VaR) than an unhedged ethanol position. Keywords: revenue; renewable energy; hedging; copula. DOI: 10.1504/IJRM.2021.10038256
A machine learning approach to itinerary-level booking prediction in competitive airline markets by Daniel Hopman, Ger Koole, Rob Van Der Mei Abstract: Demand forecasting is extremely important in revenue management. After all, it is one of the inputs to an optimisation method which aim is to maximise revenue. Most, if not all, forecasting methods use historical data to forecast the future, disregarding the why. In this paper, we combine data from multiple sources, including competitor data, pricing, social media, safety and airline reviews. Next, we study five competitor pricing movements that, we hypothesise, affect customer behaviour when presented a set of itineraries. Using real airline data for ten different OD-pairs and by means of extreme gradient boosting, we show that customer behaviour can be categorised into price-sensitive, schedule-sensitive and comfort ODs. Through a simulation study, we show that this model produces forecasts that result in higher revenue than traditional, time series forecasts. Keywords: demand forecasting; effects of competition; traditional statistics; machine learning. DOI: 10.1504/IJRM.2021.10039492
The impact of national culture on overinvestment by Naima Lassoued, Issam Ben Osman Abstract: The purpose of this paper is to explore the link between national culture and investment efficiency through a cross-country study. Based on a sample of 3,216 firms operating in 23 countries and observed over the 2009-2018 period, the study uses national culture Hofstede dimensions and overinvestment as operationalised in Biddle et al. (2009) model. To this end, a logit model and a GMM regression are applied. The results indicate that individualism and masculinity dimensions reinforce the likelihood that managers overinvest and tend to increase overinvestment levels since people from these cultures are known by their individual and money-oriented aspirations. However, managers from power distance cultures and high uncertainty avoidance engage less in overinvestment. This study provides additional cross-country factors that explain overinvestment not determined by agency theory. Manager's investment decisions are not only perceived through an objective financial perspective but also through beliefs and perceptions which are inherited from manager's culture. Keywords: Overinvestment; national culture; cross countries study. DOI: 10.1504/IJRM.2021.10040810