Advance planning models in managing coalition loyalty programs

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Loyalty reward programs (LRPs) are marketing programs aimed at rewarding customers for repeat buying behavior. While there is a cost in offering them, they are ultimately beneficial to the firm. They serve to attract new customers, and to nurture and encourage long-term relationships with existing customers. Hence, LRPs have grown in popularity in recent years across a spectrum of industries. New ones continue to be established worldwide and existing ones continue to be restructured. AEROPLANr, is Canada's premier LRP. It reports 4.6 million active members in its program and is a joint venture with more than 75 partners. The cost of redeemed Aeroplan rewards is estimated at $1.382 billion for 2012 and 2013. Aeroplan is an example of a coalition loyalty program (CLP), the most complex loyalty-based systems, in terms of the membership enrollment size, diversification of customer sources for the collection of points, diversification of reward offerings, and operating costs and risks. Managing such a complex system requires advanced solutions technologies.***This research program will study and provide support for operational, tactical, and strategic decisions that arise when managing CLPs. The work will be centered around three short and medium-term objectives:***1)  Modelling reward ordering decisions for single or multiple period planning horizons under various option contract settings and redemption demand scenarios.***2) Developing predictive models of redemption, liability and breakage for revenue recognition under multiple product and reward structures.***3) Modelling cooperative advertising and coordination decisions in the context of an LRP firm seeking to enter a partnership to promote the partner's products or services.****In order to achieve these objectives, a range of methodologies will be used. These include approximation, exact (e.g., L-shaped decomposition methods), robust optimization, Markov chain, simulation, and game-theory based approaches. Within some of these methodologies, other decomposition methods such as lagrangean relaxation and Dantzig-Wolfe, will be applied. The research program's long-term objective consists of embedding these solutions within a decision support system to provide practical guidance to LRP decision-makers with the aim of improving their efficiency and effectiveness.***While the initial outcomes will be specifically directed at managing coalition loyalty reward programs, the methodologies that will be developed will advance our knowledge in stochastic programming, robust optimization, and large-scale optimization. They will have applicability in the general context of supply chain management in evaluating, at the tactical and operational levels, different contract types and structures under various demand assumptions, while simultaneously considering multiple partner relationships rather than a single partner relationship.**