Search results for "certainty"
showing 10 items of 1057 documents
An effectual approach to executing dynamic capabilities under unexpected uncertainty
2022
This study investigates how business-to-business (B2B) firms navigate contexts of unexpected uncertainty. Building on the theories of effectuation and dynamic capabilities, the study develops a model that highlights how effectual decision-making logic is manifested in the activities B2B firms employ to sense and seize new opportunities and threats and transform existing business operations. The qualitative data were collected in two phases (before and after the COVID-19 outbreak) and consisted of 24 interviews with 13 B2B firms. The findings demonstrate a strong reliance on managers' effectual decision-making in situations of unexpected uncertainty and provide a set of key activities that h…
L’affectif, les valeurs et le matching dans les choix des investisseurs individuels en incertitude : le cas de l’equity crowdfunding
2018
Our research focuses on the emotional and axiological determinants of investment choice in equity crowdfunding. We defend the thesis of a projects choice determined in part by the values and emotions of the individual investor. Our literature review is transversal to several fields of social sciences. Thus, the established theoretical framework articulates finance, marketing, HRM and psychology. An explanatory model using structural equations is proposed and tested empirically using data from a laboratory experiment. Our results confirm that values and interest in the project, an affective variable, have a significant effect on investor choices and dominate analytical judgment in the absenc…
Sensitivity analysis and uncertainty assessment of a SMBR model
2008
Over the last decade new technologies are emerging even more for wastewater treatment. Among the new technologies, a recent possible solution regards membrane bioreactors (MBRs) that represent a promising alternative to conventional processes. Nowadays, the recurrence to mathematical models as reliable tools in planning as well as management issues is of growing interest in Wastewater Treatment Plants field. Regarding MBR modelling, due to the intrinsic complexity and uncertainty in some processes, basic models that can provide a holistic understanding of the technology at a fundamental level are of great necessity. Many mathematical models have been developed for modelling the MBR which ba…
A Simple Indicator Based Evolutionary Algorithm for Set-Based Minmax Robustness
2018
For multiobjective optimization problems with uncertain parameters in the objective functions, different variants of minmax robustness concepts have been defined in the literature. The idea of minmax robustness is to optimize in the worst case such that the solutions have the best objective function values even when the worst case happens. However, the computation of the minmax robust Pareto optimal solutions remains challenging. This paper proposes a simple indicator based evolutionary algorithm for robustness (SIBEA-R) to address this challenge by computing a set of non-dominated set-based minmax robust solutions. In SIBEA-R, we consider the set of objective function values in the worst c…
Complementary Judgment Matrix Method with Imprecise Information for Multicriteria Decision-Making
2018
The complementary judgment matrix (CJM) method is an MCDA (multicriteria decision aiding) method based on pairwise comparisons. As in AHP, the decision-maker (DM) can specify his/her preferences using pairwise comparisons, both between different criteria and between different alternatives with respect to each criterion. The DM specifies his/her preferences by allocating two nonnegative comparison values so that their sum is 1. We measure and pinpoint possible inconsistency by inconsistency errors. We also compare the consistency of CJM and AHP trough simulation. Because preference judgments are always more or less imprecise or uncertain, we introduce a way to represent the uncertainty throu…
Inventory Control Under Parametric Uncertainty of Underlying Models
2013
A large number of problems in inventory control, production planning and scheduling, location, transportation, finance, and engineering design require that decisions be made in the presence of uncertainty of underlying models. In the present paper we consider the case, where it is known that the underlying distribution belongs to a parametric family of distributions. The problem of determining an optimal decision rule in the absence of complete information about the underlying distribution, i.e., when we specify only the functional form of the distribution and leave some or all of its parameters unspecified, is seen to be a standard problem of statistical estimation. Unfortunately, the clas…
Interactive multiobjective optimization with NIMBUS for decision making under uncertainty
2013
We propose an interactive method for decision making under uncertainty, where uncertainty is related to the lack of understanding about consequences of actions. Such situations are typical, for example, in design problems, where a decision maker has to make a decision about a design at a certain moment of time even though the actual consequences of this decision can be possibly seen only many years later. To overcome the difficulty of predicting future events when no probabilities of events are available, our method utilizes groupings of objectives or scenarios to capture different types of future events. Each scenario is modeled as a multiobjective optimization problem to represent differe…
Modelling agricultural risk in a large scale positive mathematical programming model
2020
International audience; Mathematical programming has been extensively used to account for risk in farmers' decision making. The recent development of the positive mathematical programming (PMP) has renewed the need to incorporate risk in a more robust and flexible way. Most of the existing PMP-risk models have been tested at farm-type level and for a very limited sample of farms. This paper presents and tests a novel methodology for modelling risk at individual farm level in a large scale model, called individual farm model for common agricultural policy analysis (IFM-CAP). Results show a clear trade-off between including and excluding the risk specification. Albeit both alternatives provid…
Multi-scenario multi-objective robust optimization under deep uncertainty: A posteriori approach
2021
This paper proposes a novel optimization approach for multi-scenario multi-objective robust decision making, as well as an alternative way for scenario discovery and identifying vulnerable scenarios even before any solution generation. To demonstrate and test the novel approach, we use the classic shallow lake problem. We compare the results obtained with the novel approach to those obtained with previously used approaches. We show that the novel approach guarantees the feasibility and robust efficiency of the produced solutions under all selected scenarios, while decreasing computation cost, addresses the scenario-dependency issues, and enables the decision-makers to explore the trade-off …
Hydrological post-processing based on approximate Bayesian computation (ABC)
2019
[EN] This study introduces a method to quantify the conditional predictive uncertainty in hydrological post-processing contexts when it is cumbersome to calculate the likelihood (intractable likelihood). Sometimes, it can be difficult to calculate the likelihood itself in hydrological modelling, specially working with complex models or with ungauged catchments. Therefore, we propose the ABC post-processor that exchanges the requirement of calculating the likelihood function by the use of some sufficient summary statistics and synthetic datasets. The aim is to show that the conditional predictive distribution is qualitatively similar produced by the exact predictive (MCMC post-processor) or …