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This paper aims to develop a geometry of moral systems. Existing social choice mechanisms predominantly employ simple structures, such as rankings. A mathematical metric among moral systems allows us to represent complex sets of views in a multidimensional geometry. Such a metric can serve to diagnose structural issues, test existing mechanisms of social choice or engender new mechanisms. It also may be used to replace active social choice mechanisms with information-based passive ones, shifting the operational burden.

Under reasonable assumptions, moral systems correspond to computational black boxes, which can be represented by conditional probability distributions of responses to situations. In the presence of a probability distribution over situations and a metric among responses, codifying our intuition, we can derive a sensible metric among moral systems.

Within the developed framework, the author offers a set of well-behaved candidate metrics that may be employed in real applications. The author also proposes a variety of practical applications to social choice, both diagnostic and generative.

The proffered framework, derived metrics and proposed applications to social choice represent a new paradigm and offer potential improvements and alternatives to existing social choice mechanisms. They also can serve as the staging point for research in a number of directions.

In 1951, Kenneth Arrow proved that it is not possible to have a group decision-making procedure that satisfies reasonable requirements like fairness. From the theoretical viewpoint, this is a great result – well-deserving the Nobel Prize that was awarded to Professor Arrow. However, from the practical viewpoint, the question remains – so how should we make group decisions? A usual way to solve this problem is to provide some reasonable heuristic ideas, but the problem is that different seemingly reasonable idea often lead to different group decision – this is known, e.g. for different voting schemes.

In this paper we analyze this problem from the viewpoint of decision theory, the basic theory underlying all our activities – including economic ones.

We show how from the first-principles decision theory, we can extract explicit recommendations for group decision making.

Most of the resulting recommendations have been proposed earlier. The main novelty of this paper is that it provides a unified coherent narrative that leads from the fundamental first principles to practical recommendations.

With data from the 2003 and 2005 National Minority Business Owners Survey, we examined the extent to which minority business owners differ from nonminority business owners in their reported use of adjustment strategies, and the relationship between the use of adjustment strategies and perceived business success. The sample consisted of 193 African American, 200 Mexican American, 200 Korean American, and 210 white business owners. Mexican American and Korean American business owners reported higher levels of adjustment strategy use than African American and white business owners. The ordinary least squares show that reallocating family resources to meet business needs and reallocating business resources to meet family needs were negatively associated with perceived business success, whereas hiring paid help was positively associated with perceived business success.

This study adopts an institutional entrepreneurship perspective in the context of public–private partnerships (P3s) to highlight the role of social actors in enacting institutional change in a complex organizational setting. By studying the actions of two prominent social actors, the authors argue that successful institutional change is the result of dynamic managerial activity supported by political clout, organizational authority and the social positioning of actors.

The authors conducted a field-based case study in a complex institutional and organizational setting in Alberta, Canada. The authors employed an institutional entrepreneurship perspective to identify and analyze the activities of two allied actors motivated to transform the institutional environment for public infrastructure delivery.

The empirical study suggests that the implementation of institutional change is both individualistic and collaborative. Moreover, it is grounded in everyday organizational practices and activities and involves a coalition of allies invested in enacting lasting change in organizational practice(s), even when maintaining the status quo seems advantageous.

The authors critique the structural explanations that dominate the literature on public–private partnership implementation, which downplays the role of agency and minimizes its interplay with institutional logics in effecting institutional change. Rather, the authors demonstrate that, given the observed impact of social actors, public–private partnership adoption and implementation can be theorized as a social phenomenon.

Marksmanship data is a staple of military and law enforcement evaluations. This ubiquitous nature creates a critical need to use all relevant information and to convey outcomes in a meaningful way for the end users. The purpose of this study is to demonstrate how simple simulation techniques can improve interpretations of marksmanship data.

This study uses three simulations to demonstrate the advantages of small arms combat modeling, including (1) the benefits of incorporating a Markov Chain into Monte Carlo shooting simulations; (2) how small arms combat modeling is superior to point-based evaluations; and (3) why continuous-time chains better capture performance than discrete-time chains.

The proposed method reduces ambiguity in low-accuracy scenarios while also incorporating a more holistic view of performance as outcomes simultaneously incorporate speed and accuracy rather than holding one constant.

This process determines the probability of winning an engagement against a given opponent while circumventing arbitrary discussions of speed and accuracy trade-offs. Someone wins 70% of combat engagements against a given opponent rather than scoring 15 more points. Moreover, risk exposure is quantified by determining the likely casualties suffered to achieve victory. This combination makes the practical consequences of human performance differences tangible to the end users. Taken together, this approach advances the operations research analyses of squad-level combat engagements.

For more than a century, marksmanship evaluations have used point-based systems to classify shooters. However, these scoring methods were developed for competitive integrity rather than lethality as points do not adequately capture combat capabilities. The proposed method thus represents a major shift in the marksmanship scoring paradigm.