Martingale generalizations and preservation of martingale properties

This article investigates circumstances under which seven important martingale properties are preserved by the following six martingale generalizations: quasimartingales, amarts, martingales in the limit, games fairer with time, progressive martingales, and eventual martingales.     

An application of catastrophe theory to management science process

Practicing management scientists often complain of the alleged irrational behavior on the part of the managers they are trying to serve, particularly when a manager suddenly and unexpectedly shifts behavior from one of support to one of resistance. The authors feel such behavior is only believed to be irrational because the management scientist is using the wrong mental model when projecting past behavioral patterns into the future. This paper attempts to solve this problem by using the newly developed catastrophe theory to develop a different model where sudden shifts in behavior are considered perfectly rational and explainable. The basic implication that is drawn from this new model is that successful implementation of management science depends on a sequence of interactions with the ultimate model user and that care in the structuring of these interactions can greatly enhance the probability of eventual user acceptance.     

Econometric analysis and managerial decision making

Econometric analysis is concerned with the quantitative relationships between economic variables and it can provide an important input into the decision making process of managers. Typically econometrics differs from other apsects of management science in that it considers problems primarily, though not exclusively, from a background of economics rather than of other disciplines and behaviour is usually dealt with at higher levels of data aggregation than the individual firm.This paper considers some applications of typical econometrics to the general area of managerial decision making, where primarily the techniques have a role to play in assisting the general process of data analysis. Initially discussion is pointed towards the use of the analysis for predictive purposes and the contrast with time series methods. Subsequently examples are presented where the objective is to obtain a better understanding of individual economic relationships that aim to be important inputs into the decision making process, for example cost and revenue analysis. Finally, an example is given of how these ideas contribute more generally to the activity of model building for the firm as a whole both for the purpose of forecasting and policy simulation.     

Local volunteers respond to the Rena oil spill in Maketū, New Zealand

Following the MV Rena grounding and oil spill in the Bay of Plenty, New Zealand in October 2011, the Māori community of Maketū were quick to respond to the arrival of oil on their beaches. They asserted their rangatiratanga by establishing their marae as a base and successfully coordinated a clean-up by more than 450 volunteers, feeding these volunteers every day. We interviewed 11 clean-up leaders and volunteers in Maketū to gather information about how the oil spill affected people in the community and how they ensured the success of their clean-up efforts. Many volunteers returned to help with the clean-up day after day over several weeks. Concepts of kaitiakitanga and manaakitanga underpinned the work of the Maketū clean-up organisers. Participants attributed the success of the Maketū clean-up to the speed with which they responded, the support they received from their community and local businesses, and their local knowledge.     

CEO Age and Top Executive Pay: A UK Empirical Study

This study examines the implications that CEO age has onexecutive pay regarding data collected in a UK setting. Whereprior research has typically focused on total pay (salary plusbonus), this study offers a more complete conceptual model bysplitting pay into salary, annual bonus, and share options. Indoing so, we found that the relationship between CEO salaries andage are significantly related with this association weakeningover time. Another interesting finding not captured by priorresearch was that the relationship between CEO age and bonusappears to be non-linear in nature. Figures 2 which depicts thisnon-linear function suggest at about age 53, the proportion ofbonus as a percentage of salary begins to decrease at anincreasing rate. As a whole, these findings suggest corporate paycommittees should consider family and the financial circumstancesof the executive when designing remuneration schemes.