The case of the unpopular pay plan

Three years after launching the team-based Quality For All program, Top Chemical Company CEO Sam Verde was searching for a team-based compensation system that would reflect his company's new philosophy. With a committee gathered to discuss the issue, Verde confronts the fact that changing pay plans is an issue few people can agree on. "Very simply," explains vice president for compensation Gilbert Porterfield, "the plan is designed to give employees working on teams real incentives for constant improvement and overall excellence. The variable aspect of the system pays employees for the performance of their group." This doesn't sit well with the others. "It's going to punish teams like mine for the failings of others instead of rewarding us for the work we do and have already done," says packaging team representative Ruth Gibson. Another committee member feels that team-based anything is a "motivational happy land that doesn't square with how people really work." While Verde likes the proposed pay plan, he has doubts over whether his employees will accept the risk. Upper management has no problem basing 60% of its pay on TopChem's performance. But getting line employees to risk part of their salaries--even as little as 4%--on the ups and downs of the chemical industry may be more trouble than it's worth. Four experts on compensation reveal where Top Chemical went wrong in its plan and how Sam Verde might bring about change successfully.     

The savings potential of 24-hour coverage

In summary, there are costs to maintaining separate systems to cover both work- and non-work-related injuries and illnesses; there are also significant costs associated with achieving coordination--if not integration--of the two plans. Overall, the financial data do not indicate that the overlap between workers' compensation and health benefits is of such magnitude as to justify integration regardless of cost; however, the data do suggest that judicious exploitation of opportunities to coordinate the two programs, especially in regard to managing health care providers, may generate significant savings.     

On the variance of the ratio estimator

Summary In an earlier paper [Rao 1966] an exact expression for the variance of the ratio estimator under theMidzuno-Sen sampling scheme is obtained and here we study some of the interesting properties of the coefficients involved in this expression which depend on the auxiliary information. Use of these coefficients is made of in finding out an exact expression for the Bias and Mean Square Error of the ratio estimator under Simple Random Sampling With-Out Replacement (SRSWOR) scheme.     

Characterizations of negative multinomial distributions based on conditional distributions

In this paper characterizations of negative multinomial distributions based on conditional distributions have been studied.     

Party alternation,divided government,and fiscal performance within US States

The literature on US state government fiscal performance has examined the role of institutional factors such as budget rules and divided government, but has largely ignored the impact of party alternation. This paper primarily focuses on whether party alternation in the governor’s office affects fiscal performance. Our hypothesis is that frequent party changes create a political environment that impacts fiscal performance. To further assess the impact of party alternation on fiscal performance, we consider our primary hypothesis in conjunction with the degree of division that exists between the governor’s office and the legislature. Using panel data from 37 states between 1971 and 2000 we test the hypothesis that frequent party alternation can be expected to affect fiscal performance and find strong support for the hypothesis. An earlier version of this paper was presented at the 2005 Public Choice Society Meetings. The authors would like to thank the conference participants, William Shughart, Charles Register, Jocelyn Evans, John D. Jackson, Amihai Glazer, and two anonymous referees for their comments. We would also like to thank Craig R. Stiller for his help in the collection of data. Any remaining errors remain the responsibility of the authors.     

Lower Bound Restrictions on Intensities in Data Envelopment Analysis

We propose an extension to the basic DEA models that guarantees that if an intensity is positive then it must be at least as large as a pre-defined lower bound. This requirement adds an integer programming constraint known within Operations Research as a Fixed-Charge (FC) type of constraint. Accordingly, we term the new model DEA_FC. The proposed model lies between the DEA models that allow units to be scaled arbitrarily low, and the Free Disposal Hull model that allows no scaling. We analyze 18 datasets from the literature to demonstrate that sufficiently low intensities—those for which the scaled Decision-Making Unit (DMU) has inputs and outputs that lie below the minimum values observed—are pervasive, and that the new model ensures fairer comparisons without sacrificing the required discriminating power. We explain why the low-intensity phenomenon exists. In sharp contrast to standard DEA models we demonstrate via examples that an inefficient DMU may play a pivotal role in determining the technology. We also propose a goal programming model that determines how deviations from the lower bounds affect efficiency, which we term the trade-off between the deviation gap and the efficiency gap.     

Anchor stores

Planned shopping malls usually have one or more department (anchor) stores and multiple specialized retailers selling substitutable commodities in each commodity category. If consumers know their taste for the anchor's commodity and its price, but learn about a retailer's commodity only by costly search, collocation may benefit both store types. Intra-mall competition reduces markups, but anchors guarantee a minimum surplus from search. A mall with many retailers makes finding a suitable specialized commodity highly probable. For some parameters, additional consumer search dominates the loss in retail markups, so a profit-maximizing land developer would rent mall space to both store types.     

Developing a tutoring module for presentation of computerized patient management problems

The simulation problem is one of the most commonly used formats in computer-assisted instruction (CAI). In medical education, a patient simulation problem is known as a patient management problem (PMP). A number of computerized PMP systems are currently available. However, to date, there is no record of PMP systems having been developed using artificial intelligence. This is noteworthy since artificial intelligence techniques could help in the generation of more effective and intelligent instructional systems.

This paper analyzes and evaluates existing instructional simulation software in clinical medicine in terms of effective educational design attributes. Components of effective PMP systems thus identified are incorporated into a computerized instructional system which uses artificial intelligence techniques for teaching problem-solving and diagnostic skills to undergraduate medical students.