Assessing the reversal of investor sentiment

Assessing the reversal of sentiment in stock markets is needed because, according to the social mood cycle, the change of social mood over time is an antecedent of price movements. The purpose of this study is to empirically assess reversal of investor sentiment, to show the phases of social mood cycle from increasing mood to decreasing mood, and to explain the dynamic change in market inefficiency from increasing to decreasing. Growth modeling, developed particularly for dealing with the change over time, is used in this study for assessing the reversal of investor sentiment. The autocovariance structure of errors and the variances/covariances of the random coefficients are all taken into account in the model. The results have indicated that the change in investor sentiment over time is inverted U-shaped for the entire market. Moreover, arbitrage constraint and stock characteristics exert a joint moderating effect on sentiment reversal. Less arbitrage constraint can strengthen sentiment reversal only when the market for individual stocks is dominated by noise traders. Based on the results obtained, we discuss asset pricing, liquidity management, and market intervention.     

Small system dynamics model for alleviating the general practitioners rural care gap in Ontario,Canada

The disproportionate concentration of healthcare professionals in urban areas is a concern in many countries, including Canada. A need to address this rural care gap has driven a large number of government led initiatives worldwide over the years. This paper presents a model that can be used as a tool to examine the efficacy of such policies on the workforce distribution in the long term. A small system dynamics model is employed to simulate the current and future distribution of general physicians at a jurisdictional level. The model represents the transition of general practitioners to provide insight into the dynamics of care provision over time. The movement, and competition, between rural and urban areas is modeled to enable detailed exploration of the ability for proposed measures to alleviate the care gap in the future. Among the tested policies are such commonly used initiatives as financial incentives to rural professionals, promotion of medical education in rural areas, expansion of rural education programs and the engagement of international medical graduates etc. We demonstrate how the model can be used as a tool to determine an efficient and well-chosen combination of policies which can help alleviate the rural care gap in the future, given that some policies are more effective than others alone but also combined with other initiatives. The presented small system dynamics model is tested on Canada's reality, but its simple nature lends itself to easy application to other countries that experience a similar problem.     

The effect of controversial global sourcing practices on the ethical judgments and intentions of U.S. consumers

Global sourcing has led to lower cost and more effective supply chains for many companies. However, when the cost-driven practices of many suppliers in these chains come to light there is often considerable debate over the ethics of these practices. This research uses the well-known Hunt–Vitell framework as the theoretical foundation for a structural equation model of the deontological and teleological evaluations used by consumers when making ethical judgments of a firm's controversial cost-driven global sourcing practices. Data from a large-scale U.S. consumer survey show the importance of deontological and teleological evaluations in forming consumers’ ethical judgments of global sourcing practices, and establish a strong relationship between ethical judgment and the intention of consumers to alter consumption of a firm's products. Extensions to the framework and demographic analyses for age, gender, and income provide insights as to how perceptions of these practices affect consumer evaluations of a company involved in global sourcing and how consumers actualize their resultant intentions.     

Model Comparison for Temperature-Based Weather Derivatives in Mainland China

Abstract:

In this paper, we provide a comparison of two models of temperature-based weather derivatives. The Alaton et al. model (2002) and the continuous-time autoregressive (CAR) model of Benth et al. (2007) are applied to temperature data from twelve cities in China. The objective is to determine which is the better model for temperature derivative modeling in Chinese cities. We found the CAR model to be more accurate in terms of normality of residuals and smaller relative errors. However, the shortcomings of both the Alaton et al. model and the CAR model are revealed in this study as well.     

A cellular automata-based land-use model as an integrated spatial decision support system for urban planning in developing cities: The case of the Bogotá region

Bogotá and the 17 neighboring municipalities make up one of the biggest metropolitan areas in Latin America. However, despite strong functional interactions within the area, there is no official government body at this level in charge of coordinating authorities and providing solutions to the wide variety of issues arising in the regional urban land system. Aiming at providing an insight on future land-use developments linked to new transport infrastructures and at offering a tool to support territorial decision-making, this paper presents a cellular automata-based (CA) model based in Metronamica® software, that allows testing different scenarios based on potential land-use policies, environmental suitability and transport alternatives.There has not been, so far, an urban planning tool that accounts for the complexities of this region. CA-based land-use simulations constitute a useful approach to understanding the impacts of urban planning policies and regulations. This tool can help to improve inter-territorial and inter-institutional coordination, which through planning and management policies seek a spatially integrated development, with a long-term perspective.The CA-based model proposed was calibrated to reproduce land-use changes between 2007 and 2016 using different methods and indicators. The model was used to simulate and analyze eight scenarios with different policy directions of transport infrastructure in the future of the region. The results of the simulations reflect the dynamics of territorial occupation. The calibration indices in the experiment indicate a high degree of suitability for the CA Bogotá model, proving its effectiveness and potential as a useful tool for decision-making. The results show that occupation scenarios with restricted developable zones within the city, tend to have the greater dispersion rate in the study area, compared to scenarios where land development plans are promoted in Bogotá, which representing a more compact development.     

Partial least squares structural equation modeling in HRM research

Abstract

Partial least squares structural equation modeling (PLS-SEM) has become a key multivariate analysis technique that human resource management (HRM) researchers frequently use. While most disciplines undertake regular critical reflections on the use of important methods to ensure rigorous research and publication practices, the use of PLS-SEM in HRM has not been analyzed so far. To address this gap in HRM literature, this paper presents a critical review of PLS-SEM use in 77 HRM studies published over a 30-year period in leading journals. By contrasting the review results with state-of-the-art guidelines for use of the method, we identify several areas that offer room of improvement when applying PLS-SEM in HRM studies. Our findings offer important guidance for future use of the PLS-SEM method in HRM and related fields.     

悬臂式掘进机回转机构的分析与建模

基于悬臂式掘进机回转机构的结构特点,对其液压控制系统的运行原理展开分析,并结合假设条件建立液压元件的基本方程,通过机理建模最后得到了系统的传递函数,为实现掘进机自动控制提供了实用的简化模型。     

Latent vs. Observed Variables: Analysis of Irrigation Water Efficiency Using SEM and SUR

In this paper we compare conceptualising single factor technical and allocative efficiency as indicators of a single latent variable, or as separate observed variables. In the former case, the impacts on both efficiency types are analysed by means of structural equation modeling (SEM), in the latter by seemingly unrelated regression (SUR). We compare estimation results of the two approaches based on a dataset on single factor irrigation water use efficiency obtained from a survey of 360 farmers in the Guanzhong Plain, China. The main methodological findings are that SEM allows identification of the most important dimension of irrigation water efficiency (technical efficiency) via comparison of their factor scores and reliability. Moreover, it reduces multicollinearity and attenuation bias. It thus is preferable to SUR. The SEM estimates show that perception of water scarcity is the most important positive determinant of both types of efficiency, followed by irrigation infrastructure, income and water price. Furthermore, there is a strong negative reverse effect from efficiency on perception.     

Carbon and energy prices under uncertainty: A theoretical analysis of fuel switching with heterogenous power plants

European power producers have a major influence on the EU ETS, given that both their CO₂ emissions and their EUA (European Union Allowance) allocations account for more than half of the total volumes of the scheme. Fuel switching is often considered as the main short-term abatement measure under the EU ETS. It consists in substituting combined cycle gas turbines (CCGTs) for hard-coal plants in power generation. Thereby coal plants run for shorter periods, and CO₂ emissions are reduced. This paper provides the first theoretical analysis of fuel switching, in a context where power plants involved are not equally efficient. We begin with a preliminary work using illustrative examples and sensitivity analyses, which enables us to observe how differences in the efficiency of power plants impact the cost of fuel switching, and how this is related to the level of switching effort. Based on this, we build a theoretical model taking into account the effect of differences in the efficiency of power plants involved in fuel switching. We also investigate the effect of the timing of fuel switching abatements, within the temporally defined environment of our dynamic model. Results demonstrate that the gas price and uncontrolled CO₂ emissions act together on the carbon price. We show that the influence of the gas price on the carbon price depends on the level of uncontrolled CO₂ emissions, due to heterogeneity of power plants that are used in the fuel switching process. Furthermore, we show that the time of occurrence of uncontrolled emissions matters so that shocks have a stronger impact when they occur in a period that is closed to the end of the phase.     

Assessing the Effects of Climate Change Regulations on the Business Community: A System Dynamic Approach

Based on the business environmental literature and system dynamics, this paper develops a simulation model for managing the business risks derived from climate change. In particular, the purpose of this paper is to transform the valuable findings from the literature regarding climate change and corporate implications into an effective business management model with a broad applicability, regardless of the size of the business or the sector in which it operates. A methodology consistent with the basic principles of the system dynamic modeling process is developed, and a case study is designed to determine the level of completeness of the simulation model and its ability to address different aspects of business performance. To do so, three different scenarios have been simulated to analyze the reactive, proactive and inactive stance of managers against climate change risks. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment