Try a fund-raising triage

Not-for-profit organizations which strengthen society and the individuals who make up that society both face times of crisis in their lives. The struggle of charitable endeavors may lack the breath and blood drama of the catastrophe scene, but their need for professional gift support priority decisions may prove to be equally crucial for their future existence.     

Initial thoughts: international fund-raising consulting

There is a growing demand to secure private sector funding. Consequently, non-profit organizations in other countries need to create professional programs to support their philanthropic needs.     

Characteristics of an effective fund-raising letter

When you set out to write a fund-raising letter, make sure you know precisely to whom you're writing and why--and be certain your letter makes that point just as clear to them as it is to you.     

Complete fund-raising software systems vs. donor databases

When evaluating fund-raising software packages, it is important to understand the distinctions between them. Not all fund-raising software is created equal. In fact, there is a whole new breed of fund-raising software that has just entered the market.     

Powerful fund-raising letters--from A to Z. Part 2

Despite all the new technology and media we have available today, the letter remains one of the best ways to solicit funds from a wide audience. It's personal, direct, and cost-effective.     

Learning by imitation

This paper introduces a learning algorithm that allows for imitation in recursive dynamic games. The Kiyotaki–Wright model of money is a well-known example of such decision environments. In this context, learning by experience has been studied before. Here, we introduce imitation as an additional channel for learning. In numerical simulations, we observe that the presence of imitation either speeds up social convergence to the theoretical Markov–Nash equilibrium or leads every agent of the same type to the same mode of suboptimal behavior. We observe an increase in the probability of convergence to equilibrium, as the incentives for optimal play become more pronounced.     

Learning by a dominant firm

This paper is concerned with the optimal output decisions of a dominant firm in the presence of imperfect information about the rival's reactions. The model is multi-period with the profits in each period being independent of those in other periods. Consequently, if the rival's reaction parameter were known to the dominant firm, a myopic policy would be optimal, In the presence of imperfect information about the rival's unknown reaction parameter, the dominant firm acts in a Bayesian manner by updating its prior distribution based on the observations of the rival's outputs. Because of the multiplicative shape of the rival's reaction function, the Bayesian updating rule is a function of the dominant firm's decision variable, i.e. its output decisions. This creates a dependence of the future value of the dominant firm on the present output decision, and hence a myopic policy is not, in general, optimal. It is shown that through output experimentation the dominant firm will tend to overproduce and, consequently, will increase its expected discounted profits (market value).