The Experts below are selected from a list of 110751 Experts worldwide ranked by ideXlab platform
Teresa A Treat - One of the best experts on this subject based on the ideXlab platform.
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quantifying the information value of clinical assessments with signal detection theory
Annual Review of Psychology, 1999Co-Authors: Richard M. Mcfall, Teresa A TreatAbstract:The aim of clinical assessment is to gather data that allow us to Reduce Uncertainty regarding the probabilities of events. This is a Bayesian view of assessment that is consistent with the well-known concept of incremental validity. Conventional approaches to evaluating the accuracy of assessment
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QUANTIFYING THE INFORMATION VALUE OF CLINICAL ASSESSMENTS WITH SIGNAL DETECTION THEORY
Annual Review of Psychology, 1999Co-Authors: Richard M. Mcfall, Teresa A TreatAbstract:The aim of clinical assessment is to gather data that allow us to Reduce Uncertainty regarding the probabilities of events. This is a Bayesian view of assessment that is consistent with the well-known concept of incremental validity. Conventional approaches to evaluating the accuracy of assessment methods are confounded by the choice of cutting points, by the base rates of the events, and by the assessment goal (e.g. nomothetic vs idiographic predictions). Clinical assessors need a common metric for quantifying the information value of assessment data, independent of the cutting points, base rates, or particular application. Signal detection theory (SDT) provides such a metric. We review SDT's history, concepts, and methods and provide examples of its application to a variety of assessment problems.
Richard M. Mcfall - One of the best experts on this subject based on the ideXlab platform.
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quantifying the information value of clinical assessments with signal detection theory
Annual Review of Psychology, 1999Co-Authors: Richard M. Mcfall, Teresa A TreatAbstract:The aim of clinical assessment is to gather data that allow us to Reduce Uncertainty regarding the probabilities of events. This is a Bayesian view of assessment that is consistent with the well-known concept of incremental validity. Conventional approaches to evaluating the accuracy of assessment
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QUANTIFYING THE INFORMATION VALUE OF CLINICAL ASSESSMENTS WITH SIGNAL DETECTION THEORY
Annual Review of Psychology, 1999Co-Authors: Richard M. Mcfall, Teresa A TreatAbstract:The aim of clinical assessment is to gather data that allow us to Reduce Uncertainty regarding the probabilities of events. This is a Bayesian view of assessment that is consistent with the well-known concept of incremental validity. Conventional approaches to evaluating the accuracy of assessment methods are confounded by the choice of cutting points, by the base rates of the events, and by the assessment goal (e.g. nomothetic vs idiographic predictions). Clinical assessors need a common metric for quantifying the information value of assessment data, independent of the cutting points, base rates, or particular application. Signal detection theory (SDT) provides such a metric. We review SDT's history, concepts, and methods and provide examples of its application to a variety of assessment problems.
Ignacio E Grossmann - One of the best experts on this subject based on the ideXlab platform.
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a multistage stochastic programming approach with strategies for Uncertainty reduction in the synthesis of process networks with uncertain yields
Computers & Chemical Engineering, 2008Co-Authors: Bora Tarhan, Ignacio E GrossmannAbstract:We consider in this paper the synthesis of process networks with time-varying uncertain yields in which investment in pilot plants can be considered to Reduce Uncertainty of the yields. We formulate this problem as a multistage stochastic program with decision dependent elements where investment strategies are considered to Reduce Uncertainty, and time-varying distributions are used to describe Uncertainty. We propose a new mixed-integer/disjunctive programming model which is reformulated as a mixed-integer linear program. Since the model can only be solved through an LP-based branch and bound for smaller instances, we propose a duality-based branch and bound algorithm for solving larger problems. Two numerical examples are presented to illustrate the application of the proposed method.
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a multistage stochastic programming approach with strategies for Uncertainty reduction in the synthesis of process networks with uncertain yields
Computer-aided chemical engineering, 2006Co-Authors: Bora Tarhan, Ignacio E GrossmannAbstract:In this paper we consider multistage stochastic programs with endogenous parameters where investment strategies are considered to Reduce Uncertainty, and time-varying distributions are used to describe Uncertainty. We present the proposed ideas in the context of the planning of process networks with uncertain yields. We propose a new mixed-integer/disjunctive programming mdoel which is reformulated as a mixed-integer linear program. The model can be solved, through an LP-based branch and bound for smaller instances or with a duality-based branch and bound for larger problems.
Yuliya Snihur - One of the best experts on this subject based on the ideXlab platform.
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lean startup and the business model experimenting for novelty and impact
Long Range Planning, 2019Co-Authors: Yuliya SnihurAbstract:Abstract Lean Startup has been impacting how startups and incumbents innovate their business models. However, academic understanding of Lean Startup and the associated experimentation process is only emerging. Recent academic critique of Lean Startup by Felin and colleagues (in press) highlights the inadequate guidance provided for hypotheses generation; limits of experiential learning from customer feedback; and the incremental nature of experimentation outcomes. Yet, Lean Startup has not been conceived for ideation, but rather for fostering iterative experimentation to Reduce Uncertainty, engage stakeholders, and promote collective learning. Taking a process perspective on experimentation, we suggest that novel business models can emerge during experimentation. We contribute a more positive perspective on the opportunities of Lean Startup and highlight how it can enable continuous innovation and stakeholder engagement for novelty and impact.
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an ecosystem level process model of business model disruption the disruptor s gambit
Journal of Management Studies, 2018Co-Authors: Yuliya Snihur, Llewellyn D W Thomas, Robert A BurgelmanAbstract:Based on a longitudinal case study, this paper presents an ecosystem‐level process model of the interlocking key activities of the business model disruptor, other ecosystem participants (customers, partners, media, analysts), and the incumbent. Together these constitute a strategic process of ecosystem evolution from incumbent‐centred to disruptor‐centred. We identify the phenomenon of a ‘disruptor's gambit’, where the disruptor reveals its intentions early on through effective framing, followed by rapid adaptation of its business model to satisfy ecosystem needs. These processes generate a virtuous framing‐adaptation cycle, where feed‐forward and feedback enable rapid response to customers and partners, while engaging them as force multipliers during new ecosystem creation. Our findings suggest that framing constitutes a dynamic strategic process enabling disruptors to Reduce Uncertainty, dislodge powerful incumbents, and shape new ecosystems through business model innovation.
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an ecosystem level process model of business model disruption the disruptor s gambit
Research Papers, 2018Co-Authors: Yuliya Snihur, Llewellyn D W Thomas, Robert A BurgelmanAbstract:Based on a longitudinal case study, this paper presents an ecosystem-level process model of the interlocking key activities of the business model disruptor, other ecosystem participants (customers, partners, media, analysts), and the incumbent. Together these constitute a strategic process of ecosystem evolution from incumbent-centered to disruptor-centered. We identify the phenomenon of a "disruptor's gambit," where the disruptor reveals its intentions early on through effective framing, followed by rapid adaptation of its business model to satisfy ecosystem needs. These processes generate a virtuous framing-adaptation cycle, where feed-forward and feedback enable rapid response to customers and partners, while engaging them as force multipliers during new ecosystem creation. Our findings suggest that framing constitutes a dynamic strategic process enabling disruptors to Reduce Uncertainty, dislodge powerful incumbents, and shape new ecosystems through business model innovation.
Arie W. Kruglanski - One of the best experts on this subject based on the ideXlab platform.
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leader group prototypicality and leadership effectiveness the moderating role of need for cognitive closure
Leadership Quarterly, 2005Co-Authors: Antonio Pierro, Lavinia Cicero, Marino Bonaiuto, Daan Van Knippenberg, Arie W. KruglanskiAbstract:Abstract The moderator effect of need for closure on the relations between leader group prototypicality and different aspects of leadership effectiveness (perceived effectiveness, job satisfaction, self-rated performance, and turnover intentions) was examined. Need for closure, reflecting a desire to Reduce Uncertainty, was proposed to lead people to turn to their group memberships, thus making leadership effectiveness more contingent on the extent to which leaders are group prototypical. This hypothesis was tested in a survey of N = 242 employees of 3 Italian companies. Results indicated the expected 2-way interaction between need for closure and leader group prototypicality in predicting leadership effectiveness: the relationship between leader group prototypicality and leadership effectiveness is stronger for high need for closure than for low need for closure employees. The way in which these findings extend the social identity theory of leadership, as well as more applied implications is discussed.
