No description available.

Thesis (M.S.)--Montana State University--Bozeman, 2008. / Typescript. Chairperson, Graduate Committee: Randal R. Rucker. Includes bibliographical references (leaves 144-171).

Reducing customer churn while simultaneously increasing prices is a challenge in need of a successful intervention. This study takes an in-depth look into successful interventions that assist a business in retaining their customers while increasing prices. By identifying such successful methods, business can continue to have price optimisation strategies that can increase the value of the business through the growth in customer equity. By using an experimental design that takes place in a live setting on over 50,000 customers, interventions are tested to research whether they can have a causal relationship between the intervention and improved customer retention. Three different interventions target improving customer loyalty by offering them an additional benefit, providing justification of the increase through a personal phone call or both. The results of this research found that by simultaneously offering a customer an additional benefit and also creating a personal touch point by communicating directly with the customer telephonically in order to justify the increase had a significantly positive impact on customer retention. As an outcome, an additional level of depth can be added to the academic literature and a deeper insight into customer relationship management exists for businesses to learn from and grow their firm value. / Dissertation (MBA)--University of Pretoria, 2013. / lmgibs2014 / Gordon Institute of Business Science (GIBS) / MBA / Unrestricted

Thesis (Ph. D.)--Florida State University, 2004. / Advisor: Dr. R. Mark Isaac, Florida State University, College of Social Sciences, Dept. of Economics. Title and description from dissertation home page (viewed Jan. 12, 2005). Includes bibliographical references.

Thesis (Ph. D.)--University of Texas at Austin, 1998. / Vita. Includes bibliographical references (leaves 143-150). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.)--West Virginia University, 2004. / Title from document title page. Document formatted into pages; contains vi, 98 p. : ill. Includes abstract. Includes bibliographical references (p. 95-98).

No description available.

Thesis ( M.Sc.(Agricultural Economics)) --University of Limpopo, 2019. / Potato is perceived as an excellent crop in the fight against hunger and poverty. The recent high potato price in South Africa has pushed the vegetable out of reach of the poorest of the poor. The study attempts to analyse potato price volatility in South Africa and furthermore assess how various factors were responsible for the recent potato price volatility. Quarterly data for potato price, number of hectares planted, rainfall and temperature levels from 2006q1 to 2017q4 was collected from various sources and were used for analysis. The total observation of 48. The volatility in the series was determined by performing ARCH/GARCH model. GARCH model indicates an evidence of GARCH effect in the series, meaning that GARCH model influences potato price volatility in South Africa. The Johansen cointegration used both trace and eigenvalue to test the existence of a long run relationship between potato price and various variables. The cointegration results were positive indicating that there exists long run relationship amongst variables. The study further used Johansen cointegration as well as standard error to determine the number of cointegrating variables in the long run. The results indicated that the number of hectares planted and rainfall level have significant relationship with potato price. Wald tests was used to check whether the past values of number of hectares planted and rainfall level influenced the current value of potato price. The Walt test results concluded that there is no evidence of short run causality running from number of hectares planted and rainfall level to potato price. In the study, ECM model was used to forecast the potato price fluctuation in South Africa. The study recommends that farmers need to engage in contract market so as to minimize the risk of potato price volatility. The Department of Agriculture should forecast agricultural commodities price volatility and make information accessible to the farmers so that they are able to adopt strategies that will assist them to overcome crisis.

Wholesale electricity markets now operate in many countries around the world. These markets determine a spot price for electricity as the clearing price when generators bid in energy at various prices. As the trading in a wholesale electricity market can be seen as a dynamic repeated game, it would be expected that profit maximising generators learn to engage in tacit collusion to profitably increase spot market prices. This thesis investigates this tacit collusion of generators in oligopolistic electricity markets. We do not follow the approach of previous work in game theory that presupposes firms' collusive strategies to enforce collusion in an oligopoly. Instead, we develop a co-evolutionary approach (extending previous work in this area) using a genetic algorithm (GA) to co-evolve strategies for all generators in some stylised models of an electricity market. The bidding strategy of each generator is modelled as a set of bidding actions, one for each possible discrete state of the state space observed by the generator. The market trading interactions are simulated to determine the fitness of a particular strategy. The tacitly collusive outcomes and strategies emerging from computational experiments are thus obtained from the learning or evolutionary process instead of from any pre-specification. Analysing many of those emergent collusive outcomes and strategies. we are able to specify the mechanism of tacit collusion and investigate how the market environment can affect it. We find that the learned collusive strategies are similar to the forgiving trigger strategies of classical supergame theory (Green and Porter, 1984). Also using computational experiments, we can determine which characteristics of the market environment encourage or hinder tacit collusion. The findings from this thesis provide insights on tacit collusion in an oligopoly and policy implications from a learning perspective. With modelling flexibility, our co-evolutionary approach can be extended to study strategic behaviour in an oligopoly considering many other market characteristics.

Wholesale electricity markets now operate in many countries around the world. These markets determine a spot price for electricity as the clearing price when generators bid in energy at various prices. As the trading in a wholesale electricity market can be seen as a dynamic repeated game, it would be expected that profit maximising generators learn to engage in tacit collusion to profitably increase spot market prices. This thesis investigates this tacit collusion of generators in oligopolistic electricity markets. We do not follow the approach of previous work in game theory that presupposes firms' collusive strategies to enforce collusion in an oligopoly. Instead, we develop a co-evolutionary approach (extending previous work in this area) using a genetic algorithm (GA) to co-evolve strategies for all generators in some stylised models of an electricity market. The bidding strategy of each generator is modelled as a set of bidding actions, one for each possible discrete state of the state space observed by the generator. The market trading interactions are simulated to determine the fitness of a particular strategy. The tacitly collusive outcomes and strategies emerging from computational experiments are thus obtained from the learning or evolutionary process instead of from any pre-specification. Analysing many of those emergent collusive outcomes and strategies. we are able to specify the mechanism of tacit collusion and investigate how the market environment can affect it. We find that the learned collusive strategies are similar to the forgiving trigger strategies of classical supergame theory (Green and Porter, 1984). Also using computational experiments, we can determine which characteristics of the market environment encourage or hinder tacit collusion. The findings from this thesis provide insights on tacit collusion in an oligopoly and policy implications from a learning perspective. With modelling flexibility, our co-evolutionary approach can be extended to study strategic behaviour in an oligopoly considering many other market characteristics.