How Institutions Shape Uncertainty and Risk

Purpose: The study proposes a conceptual framework on how institutions influence risk and uncertainty. Beyond the nuances in defining the concepts in the existing literature, the role of institutions in shaping risks and uncertainties remains understudied. This paper adopts the new institutional economics (NIE) perspective to revisit the concepts of risk and uncertainty and provide a deeper reflection about its interactions with formal and informal institutions. Method: Our conceptual model is based on four propositions that support a theoretical explanation about the relationships between institutions and uncertainties, institutions and risks, and uncertainties and risks. Findings: While formal institutions have a primary role in reducing uncertainties, informal institutions can be seen as a source of risk. These findings imply firms’ strategic decisions. In this regard, we also provide a research agenda for future empirical studies in the area. Originality/value: The study highlights the importance of institutions for companies to deal with risk and uncertainties. The institutions have a primary role in defining the “known part” of the uncertainty, allowing the companies to evaluate the different scenarios for decision-making. Theoretical/Methodological Contributions: This study differentiates risk and uncertainty interaction according to institutional theory. Additionally, we offer an academic discussion of how formal and informal institutions can shape risks and uncertainties.

An Investigation of Master Student Understanding on Mathematical Literacy Problems

Indonesian government has been promoting the National Literacy Movement since 2016 to response disappointing results of the Program for International Student Assessment on literacy and mathematical literacy skills of students. This movement involves many parties, including educational universities, to prepare mathematics education students of master level, as prospective teachers or lecturers, to understand mathematical literacy. To investigate this condition, this study aims to analyze master student understanding on mathematical literacy problems. To do so, we conducted an online survey via Google Form involving 32 master students from several universities in Bandung. In this survey, each master student was called for sending two mathematics problems and solutions that considered to be literacy problems. The results revealed that 17 (53%) involved master students understand mathematical literacy problems. The most frequent category of literacy problems to appear was Change and Relationship followed by categories of Space and Shape, Uncertainty and Data, and Quantity, respectively. Another result showed that word problems seemed to be regarded as the same as mathematical literacy problems by some students. We conclude that master student understanding of mathematical literacy needs to be improved for facing future educational careers.

Multidisciplinary reliability analysis of turbine blade with shape uncertainty by Kriging model and free-form deformation methods

This work presents an integrated approach for the multidisciplinary reliability analysis of turbine blades with shape uncertainty, including the metamodel, the free-form deformation, and the Monte Carlo simulation. The multidisciplinary analysis of turbine blade includes fluid, structure, and thermal analyses, which is time-consuming during integration with multidisciplinary reliability analysis. The metamodel is constructed by adaptive sampling to reduce computational cost. The shape uncertainty with small size changes in reliability analysis should be considered. The geometry-based multidisciplinary analysis may fail to capture the small size changes during the geometry and mesh regeneration process. The main contribution of this article is to introduce the free-form deformation in multidisciplinary reliability analysis to overcome the aforementioned problems. The mesh-based method supported by free-form deformation is proposed. Failure probability analysis of the multidisciplinary blade system is performed using the Monte Carlo simulation and the surrogate model. Through the numerical simulation, it is found that the failure probability increases as the blade shape uncertainty becomes larger. The methodology in this article provides a valuable and applicative way to calculate the risk of blade in multidisciplinary system.

Initial state radiation correction and its effect on data-taking scheme for σB(e+e−→ ZH) measurement

The measurement of Born cross-section of [Formula: see text] process is one of the major goals of the future Circular Electron Positron Collider, which may reach a precision of 0.5% at 240 GeV. Such unprecedented precision must be guaranteed by both theoretical and experimental sides, such as the calculations of high order corrections, the knowledge of the [Formula: see text] line shape. Uncertainty of the radiative correction factor at 240 GeV caused by the [Formula: see text] line shape is evaluated in this work. Therefore, dedicated data-taking schemes are proposed in order to precisely calculate the ISR correction factor.

A General Method for Estimating Bulk 2D Projections of Ice Particle Shape: Theory and Applications

The orientation of falling ice particles directly influences estimates of microphysical and radiative bulk quantities as well as in situ retrievals of size, shape, and mass. However, retrieval efforts and bulk calculations often incorporate very basic orientations or ignore these effects altogether. To address this deficiency, this study develops a general method for projecting bulk distributions of particle shape for arbitrary orientations. The Amoroso distribution provides the most general bulk aspect ratio distribution for gamma-distributed particle axis lengths. The parameters that govern the behavior of this aspect ratio distribution depend on the assumed relationship between mass, maximum dimension, and aspect ratio. Individual spheroidal geometry allows for eccentricity quantities to linearly map onto ellipse analogs, whereas aspect ratio quantities map nonlinearly. For particles viewed from their side, this analytic distinction leads to substantially larger errors in projected aspect ratio than for projected eccentricity. Distribution transformations using these mapping equations and numerical integration of projection kernels show that both truncation of size distributions and changes in Gaussian dispersion can alter the modality and shape of projection distributions. As a result, the projection process can more than triple the relative entropy between the spheroidal and projection distributions for commonly assumed model and orientation parameters. This shape uncertainty is maximized for distributions of highly eccentric particles and for particles like aggregates that are thought to fall with large canting-angle deviations. As a result, the methods used to report projected aspect ratios and the corresponding values should be questioned.

Affordable Uncertainty Quantification for Industrial Problems: Application to Aero-Engine Fans

Uncertainty quantification (UQ) is an increasingly important area of research. As components and systems become more efficient and optimized, the impact of uncertain parameters is likely to become critical. It is fundamental to consider the impact of these uncertainties as early as possible during the design process, with the aim of producing more robust designs (less sensitive to the presence of uncertainties). The cost of UQ with high-fidelity simulations becomes therefore of fundamental importance. This work makes use of least-squares approximations in the context of appropriately selected polynomial chaos (PC) bases. An efficient technique based on QR column pivoting has been employed to reduce the number of evaluations required to construct the approximation, demonstrating the superiority of the method with respect to full-tensor quadrature (FTQ) and sparse-grid quadrature (SGQ). Orthonormal polynomials used for the PC expansion are calculated numerically based on the given uncertainty distribution, making the approach optimal for any type of input uncertainty. The approach is used to quantify the variability in the performance of two large bypass-ratio jet engine fans in the presence of shape uncertainty due to possible manufacturing processes. The impacts of shape uncertainty on the two geometries are compared, and sensitivities to the location of the blade shape variability are extracted. The mechanisms at the origin of the change in performance are analyzed in detail, as well as the differences between the two configurations.