Academic Entrepreneurship: Time for a Rethink?

Academic entrepreneurship, which refers to efforts undertaken by universities to promote commercialization on campus and in surrounding regions of the university, has changed dramatically in recent years. Two key consequences of this change are that more stakeholders have become involved in academic entrepreneurship and that universities have become more ‘strategic’ in their approach to this activity. The authors assert that the time is ripe to rethink academic entrepreneurship. Specifically, theoretical and empirical research on academic entrepreneurship needs to take account of these changes, so as to improve the rigour and relevance of future studies on this topic. We outline such a framework and provide examples of key research questions that need to be addressed to broaden understanding of academic entrepreneurship.     

A property of coefficients of variation for ordered bivariate log-normal variables

This paper considers the maximum and minimum of a pair of log-normal variables with equal mean. It shows that either order statistic has a smaller coefficient of variation than the two original log-normal variables provided the latter are of equal variance. When the variances are unequal, as the variance ratio increases, the minimum (maximum), has a smaller coefficient of variation if the correlation coefficient of the log-normal variables is small (small) and the variances are large (small).     

A Diamond-Stiglitz approach to the demand for self-protection

The existing research concerning the relationship between risk aversion and prudence and the demand for self-protection assumes that the loss variable follows a Bernoulli distribution, and that changes in the level of self-protection are mean preserving. The analysis here replaces these two very strong conditions with ones which are more general. When doing this, the method of analysis is also significantly modified. This modification includes representing a change in the level of self-protection using the procedure developed by Diamond and Stiglitz (Journal of Economic Theory 8:337-360, 1974) for representing a change in risk. This alternate representation allows the existing findings to be generalized considerably, and also simplifies the analysis.     

Relationship of interpersonal behaviors and health-related control appraisals to patient satisfaction and compliance in a university health center

OBJECTIVE: The authors' aim was to evaluate patient-provider relationships in a college health center. PARTICIPANTS: Eighty student patients and their health-care providers. METHODS: Patients completed a measure of perceived health competence before a consultation and measures of provider participatory behavior and interpersonal behavior before and after the consultation. They evaluated their satisfaction with care and compliance after the consultation and again 2 weeks later. Providers completed measures of their participatory behavior and patients' interpersonal behavior after the consultation. RESULTS: Patients preferred to be well informed and to have their preferences taken into account, and generally felt competent at managing their own health affairs. They indicated they obtained the high level of participation they desired. Patients desired and actually experienced friendly and submissive providers. Degree of match between patients' desired and actual level of involvement in their care was associated with greater satisfaction. A greater match between the extent to which they desired the provider to be affiliative and the provider's actual affiliative behavior was associated with more satisfaction. No variables were predictive of patient compliance. CONCLUSION: The authors discuss results in terms of the influence of situational factors characteristic of a college health center.     

The self-perceptions and interpersonal relationships of persons with significant physical disabilities: a qualitative pilot study

This exploratory, qualitative research was conducted to obtain the perspectives of people with significant physical disabilities regarding factors that have facilitated and hindered the development of a positive self-concept, participation in the broader society, and the formation of interpersonal relationships. The sample was high achieving in terms of education and/or career and attributed positive self-perceptions and their success in the broader society and interpersonal relationships to the attitudes and perceptions regarding their abilities, talents, and potential modeled in supportive family relationships. Females reported the influence of significant others most often, and males the effectiveness of their personality characteristics. Societal barriers, both practical and attitudinal, were reported along with the process for developing a positive selfperception despite these.     

Racial Difference in the Determinants of Smoking Onset

The large differences in youth smoking behavior across ethnic and racial groups are often overlooked in debates about prevention. This study examines how the determinants of the onset of smoking vary by race and ethnicity. Academic success is strongly associated with lower smoking rates among white youth, but this is not as true for Hispanics and African-Americans. Cultural assimilation may be an important determinant of smoking for Hispanics. Price increases do not appear to reduce smoking onset among white youth, but the results provide some support that higher prices will reduce smoking among Hispanic and African-American youth.     

A Stochastic Goal Program for Employee Scheduling*

Deterministic goal programs for employee scheduling decisions attempt to minimize expected operating costs by assigning the ideal number of employees to each feasible schedule. For each period in the planning horizon, managers must first determine the amount of labor that should be scheduled for duty. These requirements are often established with marginal analysis techniques, which use estimates for incremental labor costs and shortage expenses. Typically, each period in the planning horizon is evaluated as an independent epoch. An implicit assumption is that individual employees can be assigned to schedules with as little as a single period of work. If this assumption violates local work rules, the labor requirements parameters for the deterministic goal program may be suboptimal. As we show in this research, this well-known limitation can lead to costly staffing and scheduling errors. We propose an employee scheduling model that overcomes this limitation by integrating the labor requirements and scheduling decisions. Instead of a single, externally determined staffing goal for each period, the model uses a probability distribution for the quantity of labor required. The model is free to choose an appropriate staffing level for each period, eliminating the need for a separate goal-setting procedure. In most cases this results in better, less costly decisions. In addition, the proposed model easily accommodates both linear and nonlinear under- and overstaffing penalties. We use simple examples to demonstrate many of these advantages and to illustrate the key techniques necessary to implement our model. We also assess its performance in a study of more than 1,700 simulated stochastic employee scheduling problems.     

A Bayesian sequential design with binary outcome

Several researchers have proposed solutions to control type I error rate in sequential designs. The use of Bayesian sequential design becomes more common; however, these designs are subject to inflation of the type I error rate. We propose a Bayesian sequential design for binary outcome using an alpha‐spending function to control the overall type I error rate. Algorithms are presented for calculating critical values and power for the proposed designs. We also propose a new stopping rule for futility. Sensitivity analysis is implemented for assessing the effects of varying the parameters of the prior distribution and maximum total sample size on critical values. Alpha‐spending functions are compared using power and actual sample size through simulations. Further simulations show that, when total sample size is fixed, the proposed design has greater power than the traditional Bayesian sequential design, which sets equal stopping bounds at all interim analyses. We also find that the proposed design with the new stopping for futility rule results in greater power and can stop earlier with a smaller actual sample size, compared with the traditional stopping rule for futility when all other conditions are held constant. Finally, we apply the proposed method to a real data set and compare the results with traditional designs.