Business Administration - Research Publications
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ItemGender equality in the Finance industry: The challenging ‘last mile’(ANZAM, 2021-12-03)Organisational efforts to increase gender equality in leadership have had limited success, and Australia’s ranking in the global gender equality index has slipped since 2006. We call this challenging stage in gender equality efforts the ‘last mile’. To understand what hinders or assists organisational efforts in the ‘last mile’ we conducted an in-depth study of the diversity efforts in a business unit of a large Australian bank. Interviews, focus groups and archival data analyses demonstrated that the bank’s gender equality performance was better than their institutional field, and the workforce was more optimistic about gender equality outcomes than executives. Ironically, these illusions of progress hindered the bank’s ability to travel the ‘last mile’.
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ItemInterdependent scheduling games(AAAI Press / International Joint Conferences on Artificial Intelligence, 2016-01-01)We propose a model of interdependent scheduling games in which each player controls a set of services that they schedule independently. A player is free to schedule his own services at any time; however, each of these services only begins to accrue reward for the player when all predecessor services, which may or may not be controlled by the same player, have been activated. This model, where players have interdependent services, is motivated by the problems faced in planning and coordinating large-scale infrastructures, e.g., restoring electricity and gas to residents after a natural disaster or providing medical care in a crisis when different agencies are responsible for the delivery of staff, equipment, and medicine. We undertake a game-theoretic analysis of this setting and in particular consider the issues of welfare maximization, computing best responses, Nash dynamics, and existence and computation of Nash equilibria.
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ItemAsymptotic Optimality of Myopic Optimization in Trial-Offer Markets with Social Influence(AAAI Press / International Joint Conferences on Artificial Intelligence, 2016)We study dynamic trial-offer markets, in which participants first try a product and later decide whether to purchase it or not. In these markets, social influence and position biases have a greater effect on the decisions taken in the sampling stage than those in the buying stage. We consider a myopic policy that maximizes the market efficiency for each incoming participant, taking into account the inherent quality of products, position biases, and social influence. We prove that this myopic policy is optimal and predictable asymptotically.