Five strategic foresight tools to enhance business model innovation teaching

We discuss our lessons from 8 years of teaching business model innovation to executives in our part-time MBA program. We inspect how the usage of 5 strategic foresight tools has supported students to innovate business models and discuss the advantages and disadvantages of using student-owned live cases

Scenario Planning for Restorative Justice in Lakeland

Final project for URSP708: Community Planning Studio (Fall 2022). University of Maryland, College Park.This report begins with a discussion of the concept of restorative justice and the three themes that guided and organized our work — community infrastructure, housing and land use, and climate change adaptation and mitigation. Following this introduction of the three guiding themes, the report contains a summary of our analysis of existing conditions, including a review of different planning sectors, a brief history of Lakeland, and a summary of plans and policies that have influenced the course of Lakeland. The next section of the report is a summary of the findings of our various community engagement approaches, including recommendations for future best practices for the city and the Restorative Justice Commission as they continue this work. Finally, we present the three planning scenarios — Status Quo, Reform, and Revolutionary — that envision various alternative futures for Lakeland.City of College Par

Multidimensional signals and analytic flexibility: Estimating degrees of freedom in human speech analyses

Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis which can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling, but also from decisions regarding the quantification of the measured behavior. In the present study, we gave the same speech production data set to 46 teams of researchers and asked them to answer the same research question, resulting insubstantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further find little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system and calibrate their (un)certainty in their conclusions