Recent research work in school leadership highlighting the importance of principals' organizational management skills has prompted scholars to consider their importance in relation to instructional leadership skills. However, there is limited empirical work that directly compares these leadership skills and their importance for school outcomes. In this study, we use principals' self-ratings to construct typologies of effectiveness in both domains and compare their relationship to student achievement. Our results show that principals view themselves as either strong or weak on instructional leadership and organizational management skills simultaneously. We also find that learning gains vary significantly across the principal profiles.

Implementing treatments to create structural complexity and spatial heterogeneity within forest stands can be difficult and time consuming. We asked if real-time implementation monitoring with an Android OS tablet application can facilitate successful implementation of such treatments. We compared two tree-marking methods—free selection (FS) and individuals, clumps and openings (ICO)—which were used to implement the same silvicultural prescription. ICO marking guidelines differed from FS in one way: inclusion of targets describing the number of tree clumps of different sizes to be left, with real-time monitoring of progress towards these targets using the tablet app. ICO trials were more successful at producing desired conditions. FS trials resulted in stand densities below the target and lacked large and very large tree clumps. Implementation efficiency (trees marked per person-hour) was similar between the two systems. Real-time implementation monitoring of quantitative targets can increase the likelihood of treatment success.

This research was driven by the need for a more efficient production scheduling system in a consumable liquid product division of a large consumer products company. The manufacturing process under inspection consists of continuous and discrete elements, on both production and packaging lines. The production lines are split into continuous production lines and batch production lines which produce the product in fixed batch amounts. Then there are several bottling lines, some of which package a particular bottle size and others that can package multiple bottle sizes. The main objective of this research was to reduce the amount of time it takes for the client to create production and bottling schedules. An optimization model was developed to automate this process and provide the client with the best possible schedule. The objective of the model is to minimize cost by minimizing the number of switches across the production and bottling lines, as well as minimizing the amount of overproduction. Inputs into the model include model parameters, like the number of shifts to schedule, and monthly demand numbers for each stock keeping unit (SKU). The variables being solved for are the amount of each flavor to be produced across the production lines during each shift, and the number of bottles of each SKU to be bottled across the bottling lines during each shift. Due to the unique constraints and resources of the client, a custom formulation using mixed integer programming was necessary to achieve these objectives. Overall, our model fell short in some areas but succeeded in others. Our analysis showed that the model had a 13% average decrease in production switches but an 87% average increase in bottling switches compared to the current manual scheduling system. However, the ability of our system to create a good enough initial schedule reduces the time it takes expert human schedulers to develop a final schedule by up to 85%. Runtime and computational constraints barred us from creating an optimal, cost-minimized solution for our client, and future work can be directed toward solving these issues.