Abstract Prescriptive process monitoring methods recommend interventions during the execution of a case that, if followed, can improve performance. Research on prescriptive so far has focused mainly improving underlying algorithms and providing suitable explanations for recommendations. Empirical works indicate, though, that workers often do not follow recommendations even they understand them....

• The impact of big data analytics (BDA) on firm performance is conceptualized in a research model. BDA viewed as sociotechnical system consisting social and technical components. A meta-analysis conducted to examine the performance. Both factors strongly More advanced concepts contribute more enhancing Big has recently gained importance an emerging technology for handling data. use techniques ...

This paper focuses on the first step in combining prescriptive analytics with scenario techniques in order to provide strategic development after the use of InSciTe, a data prescriptive analytics application. InSciTe supports the improvement of researchers ‘individual performance by recommending new research directions. Standardized influential factors are presented as a foundation for automate...

This article takes the form of a research proposal. The paper seeks to address the problem faced by investors of how best to deal with decision making under risk. The methodology utilizes a normative model from economics—expected utility theory—and a descriptive model from psychology—prospect theory—to formulate a rational but realistic compromise between the two: a prescriptive model of risk p...

Prescription drug spending is growing faster than any other sector of healthcare. However, very little is known about patterns of prescribing and cost of prescribing between general practices. In this study, we examined variation in prescription rates and prescription costs through time for 55 GP surgeries in Northern Ireland Western Health and Social Care Trust. Temporal changes in variability...

Predictive analyses taking advantage of the recent explosion in the availability and accessibility of data have been made possible through flexible machine learning methodologies that are often well-suited to the variety and velocity of today’s data collection. This can be witnessed in recent works studying the predictive power of social media data and in the transformation of business practice...

People's beliefs about normality play an important role in many aspects of cognition and life (e.g., causal cognition, linguistic semantics, cooperative behavior). But how do people determine what sorts of things are normal in the first place? Past research has studied both people's representations of statistical norms (e.g., the average) and their representations of prescriptive norms (e.g., t...

Neuroethics applies cognitive neuroscience for prescribing alterations to conceptions of self and society, and for prescriptively judging the ethical applications of neurotechnologies. Plentiful normative premises are available to ground such prescriptivity, however prescriptive neuroethics may remain fragmented by social conventions, cultural ideologies, and ethical theories. Herein we offer t...

Decision theory has changed considerably in the last decade. In behavioral decision theory, a large number of studies have shown that human decision making is inherently adaptive and constructive. In prescriptive decision theory, we have witnessed a move from an alternative-focused approach to a value-focused approach. In this paper, we discuss the implications of these new ideas in behavioral ...

Scientists and philosophers have long wrestled with the problem of how we understand and make sense of our world. There are both descriptive and prescriptive approaches to understanding our world. On the descriptive side, theories of cognition, perception and thinking describe how we humans organize stimuli and make sense out of them. On the prescriptive side, there are two approaches to making...