A multilevel approach for assessing business strategies on climate change

The need for an interdisciplinary and integrative approach for doing research on business strategies and climate change is gaining increasing recognition. However, there is a consensus that such crossfertilization is currently missing. Multilevel research methods by virtue of being interdisciplinary in nature may address this need. This paper proposes to advance the adoption of multilevel research approach in the context of business strategies and climate change. As a guide for conducting multilevel assessment, a flexible analytical framework is presented. The framework is developed through a process of structured literature review. The framework consists of thirteen contextual factors spread across five levels and identifies the key multilevel relationships that moderate organisational level climate change related strategy formulation. Level specificities of several theories across these five levels are also identified to facilitate application of the framework in building multilevel hypotheses for business strategies on climate change. In addition, a concise summary of the fundamental concepts of multilevel modelling techniques is provided to help researchers in selecting suitable multilevel models during the operationalization of the framework. The operationalization of the framework is demonstrated by building and testing a three level hypotheses on corporate lobbying activities on climate change issues. It is observed that irrespective of their locations, financially underperforming companies with a larger workforce and belonging to sectors with higher Green House Gas emission intensities particularly lobby intensely on climate change issues. In conclusion, the potential challenges and opportunities in applying the framework for building multilevel theories in the context of business strategies and climate change are discussed. (C) 2017 The Authors. Published by Elsevier Ltd

A new approach to model tyre/road contact

In the Structural Dynamics and Acoustics group at the University of Twente, we aim to develop a quantitative tyre/road noise model. An essential part of this model is an accurate contact algorithm which is fast enough to simulate tyre vibrations up to the acoustic frequencies. In this paper we present a contact algorithm, describing the contact between a tyre and a road surface, which has the potential to be made very fast using the multigrid techniques developed in the field of elasto-hydrodynamic lubrication. For the development of the algorithm a flexible ring model is used to describe the tyre. The friction model is based on Coulomb’s friction. We present (quasi-)static results obtained from the algorithm for various friction coefficients, as well as frictionless results for a rotating tyre. The vibrations of the tyre obtained by this model have been used to calculate the radiated sound field by means of a boundary element program (BEMSYS)

Multilevel (ML-ICLV) & Single Level Integrated Discrete Choice and Latent Variable (ICLV) Models Using Alternative Latent Structures' Conceptualizations

The aim of the present endeavor is to experiment on integrating discrete choice with latent variable (ICVL) models using alternative factorial structures’ conceptualizations and do so at both Single Level (Level 0) and Multilevel (ML-ICVL). In doing, specific independent variables amenable to alternative latent variables’ conceptualization were selected. These included: a) 1st-order latent variables (1st-order factors) (FM; FW), b) 1st-order latent variables (1st-order factors) (FM; FW) forming a 2nd-order factor (F), c) Multi-level (two-level) factorial structures (FML0; FML1 and FWL0; FWL1), and d) Bi-Factor factorial structures (FM; FW; FG). The results may be of use to researchers interested in using valid, reliable, and accurate structures of latent variables in ICLV models. We confirm that alternative latent structures of divergent factorial nature exist for the same observed variables, and may have different impact upon the dependent observed choice variable in the ICLV models. Second, DCE utility is conceptualized and estimated at both Level 0 and Level 1 and the differences are evident

Multilevel (ML-ICLV) & Single Level Integrated Discrete Choice and Latent Variable (ICLV) Models Using Alternative Latent Structures' Conceptualizations

The aim of the present endeavor is to experiment on integrating discrete choice with latent variable (ICVL) models using alternative factorial structures’ conceptualizations and do so at both Single Level (Level 0) and Multilevel (ML-ICVL). In doing, specific independent variables amenable to alternative latent variables’ conceptualization were selected. These included: a) 1st-order latent variables (1st-order factors) (FM; FW), b) 1st-order latent variables (1st-order factors) (FM; FW) forming a 2nd-order factor (F), c) Multi-level (two-level) factorial structures (FML0; FML1 and FWL0; FWL1), and d) Bi-Factor factorial structures (FM; FW; FG). The results may be of use to researchers interested in using valid, reliable, and accurate structures of latent variables in ICLV models. We confirm that alternative latent structures of divergent factorial nature exist for the same observed variables, and may have different impact upon the dependent observed choice variable in the ICLV models. Second, DCE utility is conceptualized and estimated at both Level 0 and Level 1 and the differences are evident