One of the most important decisions regarding reverse logistics (RL) is whether to outsource such functions or not, due to the fact that RL does not represent a production or distribution firm's core activity. To explore the hypothesis that outsourcing RL functions is more suitable when returns are more variable, we formulate and analyse a Markov decision model of the outsourcing decision. The reward function includes capacity and operating costs of either performing RL functions internally or outsourcing them and the transitions among states reflect both the sequence of decisions taken and a simple characterization of the random pattern of returns over time. We identify sufficient conditions on the cost parameters and the return fraction that guarantee the existence of an optimal threshold policy for outsourcing. Under mild assumptions, this threshold is more likely to be crossed, the higher the uncertainty in returns. A numerical example illustrates the existence of an optimal threshold policy even when the sufficient conditions are not satisfied and shows how the threshold for outsourcing decreases while the probability of crossing any fixed threshold increases with the return fraction. KeywordsMarkov decision model, monotone policy, outsourcing, product life cycle, reverse logistics Abstract.One of the most important decisions regarding reverse logistics (RL) is whether to outsource such functions or not, due to the fact that RL does not represent a production or distribution firm's core activity. To explore the hypothesis that outsourcing RL functions is more suitable when returns are more variable, we formulate and analyze a Markov decision model of the outsourcing decision. The reward function includes capacity and operating costs of either performing RL functions internally or outsourcing them, and the transitions among states reflect both the sequence of decisions taken and a simple characterization of the random pattern of returns over time. We identify sufficient conditions on the cost parameters and the return fraction that guarantee the existence of an optimal threshold policy for outsourcing. Under mild assumptions, this threshold is more likely to be crossed, the higher the uncertainty in returns. A numerical example illustrates the existence of an optimal threshold policy even when the sufficient conditions are not satisfied and shows how the threshold for outsourcing decreases while the probability of crossing any fixed threshold increases with the return fraction.
The state of Michoacán, one of the states with the lowest economic development in Mexico, has been historically recognized because of its potential for tourism activities. The revenues coming from this economic sector, as well as the number of tourists who visit this state have significantly increased during the last few years. A survey was conducted on tourists who visited Michoacán, in order to determine the visitors' profile and their satisfaction levels during their visit. A cluster analysis was then used to categorize the lifestyle of these tourists into five different segments, to be able to develop the best tourism products, marketing strategies and aid the decision‐making process of government and private organizations related to this sector. A regression analysis was also performed to identify the variables that determine the satisfaction of these tourists. The results are satisfactory in the sense that the actions taken, which were based on this research and led by the Ministry of Tourism of Michoacán and the Ministry of Tourism of Mexico, have attracted more national and international groups, and have also increased the revenues, profits and new investments reported by private organizations related to this economic sector.
Through this research, a categorization and analysis of resources and actions taken by each Mexican state that contribute towards tourism competitiveness is developed. Such competitiveness is evaluated through one hundred and twelve variables, which are grouped in ten categories defined as dimensions. An overall competitiveness index is developed for each state, as well as complementary indexes for each state under the ten dimensions considered. The results of the research are satisfactory, since governmental authorities reported improvements on the number of tourists and the average expenditure. Such results were Business and Economic Research ISSN 2162-4860 2013 www.macrothink.org/ber 389 achieved by developing new initiatives and projects defined by identifying the strengths and opportunity areas in each state regarding tourism competitiveness, which are outlined through this research.
Natural disasters represent a latent threat for every country in the world. Due to climate change and other factors, statistics show that they continue to be on the rise. This situation presents a challenge for the communities and the humanitarian organizations to be better prepared and react faster to natural disasters. In some countries, in-kind donations represent a high percentage of the supply for the operations, which presents additional challenges. This research proposes a Markov Decision Process (MDP) model to resemble operations in collection centers, where in-kind donations are received, sorted, packed, and sent to the affected areas. The decision addressed is when to send a shipment considering the uncertainty of the donations’ supply and the demand, as well as the logistics costs and the penalty of unsatisfied demand. As a result of the MDP a Monotone Optimal Non-Decreasing Policy (MONDP) is proposed, which provides valuable insights for decision-makers within this field. Moreover, the necessary conditions to prove the existence of such MONDP are presented.
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