AN ANALYSIS OF PORTFOLIO REVISION STRATEGIES UTILIZING VARIABLE REVISION INTERVALS*

This paper investigates portfolio revision with an emphasis on the decision of when to revise. A statistical technique based on the sequential analysis of the time series of portfolio return relatives determines when revision is to occur. The technique detects changes in the time series which are an indication that the underlying generating process of the time series has changed and that the portfolio should be, if necessary, revised. Thus, the length of the revision interval is variable and a function of the data. The statistical technique is utilized in conjunction with three portfolio revision strategies. These three revision strategies are compared to a buy and hold policy over three nonoverlapping, 12-year investment horizons. The basis of comparison is the net terminal values which include adjustments for transaction costs and taxes. The sensitivity of the statistical technique to its parameters is also analyzed.     

A DYNAMIC OPTIMIZATION MODEL FOR PLANNING IN A MULTI-PRODUCT ENVIRONMENT

This paper describes an extension of the product mix problem and explicitly considers situations where demand can fluctuate over time. The additional decision variables and constraints that must be considered are described, and a revised objective function is discussed. The solution to the proposed linear programming formulation is compared to the traditional simulation and illustrates the potential for increased profits.     

Management Policies to Improve the Effectiveness of Multi-Station Service Organizations*

A SLAM based simulation model of a multi-station, tandem queuing structure characteristic of a variety of service systems is employed to test various design options for the system. The model is based on an extensive study of the State of Florida driver licensing offices. The multiple objectives of low time in the system for customers and the efficient use of personnel resources are employed to measure the benefits of policy options. The use of simulation analysis permits the incorporation of complex system characteristics, therefore providing a realistic representation of the effects of possible management actions. Effective methods to control labor in such systems are suggested.     

Leveraging risk assessment for foodborne outbreak investigations: The Quantitative Risk Assessment-Epidemic Curve Prediction Model

Root cause analysis can be used in foodborne illness outbreak investigations to determine the underlying causes of an outbreak and to help identify actions that could be taken to prevent future outbreaks. We developed a new tool, the Quantitative Risk Assessment-Epidemic Curve Prediction Model (QRA-EC), to assist with these goals and applied it to a case study to investigate and illustrate the utility of leveraging quantitative risk assessment to provide unique insights for foodborne illness outbreak root cause analysis. We used a 2019 Salmonella outbreak linked to melons as a case study to demonstrate the utility of this model (Centers for Disease Control and Prevention [CDC], 2019). The model was used to evaluate the impact of various root cause hypotheses (representing different contamination sources and food safety system failures in the melon supply chain) on the predicted number and timeline of illnesses. The predicted number of illnesses varied by contamination source and was strongly impacted by the prevalence and level of Salmonella contamination on the surface/inside of whole melons and inside contamination niches on equipment surfaces. The timeline of illnesses was most strongly impacted by equipment sanitation efficacy for contamination niches. Evaluations of a wide range of scenarios representing various potential root causes enabled us to identify which hypotheses, were likely to result in an outbreak of similar size and illness timeline to the 2019 Salmonella melon outbreak. The QRA-EC framework can be adapted to accommodate any food–pathogen pairs to provide insights for foodborne outbreak investigations.     

The Effects of Knowledge Management on Team Members' Ratings of Project Success and Impact*

Many organizations are trying to improve the generation and utilization of knowledge. The activities associated with these efforts are identified as organizational knowledge management (KM). While much has been written about knowledge management from the organizational level, the success of such efforts over the long run will depend upon on how KM activities impact important outcomes as perceived by those at the employee level who actually implement the activities. This study used the input‐process‐output framework of team effectiveness to investigate the relationship between selected KM‐related activities on integrated product and process development team members' satisfaction with their project's success and the impact they expected it to have on the organization. The results indicate that team‐level leadership and support (i.e., inputs), along with knowledge generation and dissemination (i.e., processes), are key drivers of member performance‐related ratings (i.e., outputs). Finally, and possibly most importantly, a number of interactions were evident suggesting that the KM processes moderate the effects of the KM inputs. These findings and their implications are discussed.     

Cost Efficiency Benchmarking for Operational Units with Multiple Cost Drivers

We consider the activity‐based costing situation, in which for each of several comparable operational units, multiple cost drivers generate a single cost pool. Our study focuses on published data from a set of property tax collection offices, called rates departments, for the London metropolitan area. We define what may be called benchmark or most efficient costs per unit of driver. A principle of maximum performance efficiency is proposed, and an approach to estimating the benchmark unit costs is derived from this principle. A validation approach for this estimation method is developed in terms of what we call normal‐like‐or‐better performance effectiveness. Application to longitudinal data on a single unit is briefly discussed. We also consider some implications for the more routine case when costs are disaggregated to subpools associated with individual cost drivers.     

Estimation When a Parameter is on a Boundary

This paper establishes the asymptotic distribution of an extremum estimator when the true parameter lies on the boundary of the parameter space. The boundary may be linear, curved, and/or kinked. Typically the asymptotic distribution is a function of a multivariate normal distribution in models without stochastic trends and a function of a multivariate Brownian motion in models with stochastic trends. The results apply to a wide variety of estimators and models. Examples treated in the paper are: (i) quasi-ML estimation of a random coefficients regression model with some coefficient variances equal to zero and (ii) LS estimation of an augmented Dickey-Fuller regression with unit root and time trend parameters on the boundary of the parameter space.     

Evaluation of hazard brochures using topic viewing durations: Application to tsunami evacuation brochures

This study describes a novel method of assessing risk communication effectiveness by reporting an evaluation of a tsunami information brochure by 90 residents of three Pacific coast communities that are vulnerable to a Cascadia Subduction Zone earthquake and tsunami—Commencement Bay, Washington; Lincoln City, Oregon; and Eureka, California. Study participants viewed information that was presented in DynaSearch, an internet-based computer system that allowed them to view text boxes and tsunami inundation zone maps. DynaSearch recorded the number of times each text box or map was clicked and the length of time that it was viewed. This information viewing phase was followed by questionnaire pages assessing important aspects of tsunami hazard and sources of tsunami warnings. Participants gave the longest click durations to what to do in the emergency period during earthquake shaking and in its immediate aftermath before a tsunami arrives—topics that should be displayed prominently in tsunami brochures and emphasized in talks to community groups. The smallest adjusted click durations were associated with advance preparations for a tsunami—topics that can be posted on websites whose URLs are printed in the brochures.     

Evidence on the Superiority of Analysts Quarterly Earnings Forecasts for Small Capitalization Firms*

Financial analysts provide information to support investment analysis and decisions for an ever increasing number of firms. As part of their services they also produce earnings forecasts for covered firms. While there has been much research investigating the determinants of financial analyst earnings forecast superiority for large, widely-followed firms, little research has focused on smaller firms. Until recently, these smaller firms have been largely ignored. This study focuses exclusively on small firms and provides evidence of differing behavior for such firms compared to results previously reported for large firms. Errors in quarterly earnings per share forecasts of small firms obtained from a univariate time-series model are also examined. Regression results indicate that time-series model parameters possess information content with respect to forecast accuracy for analyst-covered firms only. These results are obtained after controlling for firm size, model adequacy, and industry, quarter, and year effects. This suggests that analysts are more likely to cover small firms for which they are able to decipher information correlated with that impounded in the “shocks” in the quarterly earnings time series as captured by the time-series model parameters.     

How are policies implemented in children's services? Developing an initial programme theory to evaluate the implementation of the new Child Sexual Exploitation guidance in Wales

Although children's social care is an area rich in guidance, there is very little research looking at the implementation of new policies in the United Kingdom. In this article, we report on the first stage of a realist evaluation of the implementation of the new Safeguarding Children from Child Sexual Exploitation guidance in Wales. We discuss the development of an initial programme theory, for which we conducted semi-structured interviews with practitioners and managers in three local authorities. We developed programme theories across three areas: policy nature and development, implementation plans and organizational context. Findings suggest that, for policies to produce a significant impact on practice, they need to be sufficiently different to social workers' current perceptions of practice. Second, we found that the coordination between national and local policies is critical for successful implementation as contradictions between them might lead to confusion in what local teams should prioritize. Finally, our findings highlight the importance of effective communication of policy changes, as well as a supportive organizational culture to strengthen implementation in local contexts. These findings illustrate the complexity of policy implementation and the need for policymakers to consider the meaningful involvement of local practitioners in national policy development.