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In recent years, the use of structural equation modeling (SEM) has become widespread in tourism and hospitality research. Because there are two different approaches to SEM (i.e., covariance-based SEM and variance-based, partial least squares SEM), this brings challenges for researchers about which SEM to use and what to report in each SEM approach. Therefore, the purpose of this chapter is to discuss the differences between CB-SEM and PLS-SEM and to provide comprehensive guidelines for researchers on how to apply each SEM. Within this context, the authors first briefly summarize the fundamentals and advantages of using SEM. Then, the authors explain in detail the major issues that should be considered when selecting between CB-SEM and PLS-SEM. Finally, to ensure rigorous research practices, the authors provide step-by-step guidelines for the application of both CB-SEM and PLS-SEM.

This chapter proposes a vector autoregressive VAR model with structural shocks (SVAR) that are identified using sign restrictions, and whose distribution is subject to time varying skewness. The authors also present an efficient Bayesian algorithm to estimate the model. The model allows tracking joint asymmetric risks to macroeconomic variables included in the SVAR, and provides a structural narrative to the evolution of those risks. When faced with euro area data, our estimation suggests that there has been a significant variation in the skewness of demand, supply and monetary policy shocks. Such variation can explain a significant proportion of the joint dynamics of real GDP growth and inflation, and also generates important asymmetric tail risks in those macroeconomic variables. Finally, compared to the literature on growth- and inflation-at-risk, the authors find that financial stress indicators are not enough to explain all the macroeconomic tail risks.

The paper aims to leverage the importance of the integrated automatic structural design for tall buildings at the early stage. It proposes to use an automatic prototype to perform the structural design, analysis and optimisation in a building information modelling (BIM)-based platform. This process starts with extracting the required information from the architectural model in Revit Autodesk, such as boundary conditions and designs different options of the structural models in Robot Autodesk. In this process, Dynamo for Revit is used to define the mathematical functions to use different variables and generate various structural models. The paper aims to expand the domain of automation in the BIM platform to reduce the iterative process in different areas such as conceptual structural design and collaboration between architects and structural engineers to reduce the time and cost at the early stages.

The paper begins with an exploratory research by adopting a qualitative methodology and using open-ended questions to achieve more information about the phenomenon of automation and interoperability between structural engineers and architects and gain new insight into this area. Furthermore, correlation research is used by adopting quantitative and short questions to compare the proposed prototype with the traditional process of the structural design and optimisation and the interoperability between architects and engineers and consequently, validate the research.

As an outcome of the research, a structural design optimisation (SDO) prototype was developed to semi-automate the structural design process of tall buildings at the early stages. Moreover, the proposed prototype can be used during the early stage of structural design in different areas such as residential buildings, bridges, truss, reinforced concrete detailing, etc. Moreover, comprehensive literature regarding using automation in structural design, optimisation process and interoperability between architects and engineers is conducted that provides a new insight to contribute to future research and development.

Due to the time limit, the paper results may lack in a comprehensive automatic structural design process. Therefore, the researchers are encouraged to expand the workability of the prototype for a comprehensive automatic design check such as automatic design for the minimum deflection, displacement of different types of buildings.

The prototype includes implications for the development of different automatic designs.

The focus of this paper is the optimisation of the structural design in the BIM platform by using automation. This combination is one of the novelties of this paper, and the existing literature has a very limited amount of information and similar work in this area, especially interoperability between architects and engineers.

Nowadays, residential buildings have become increasingly important due to the growing communities. The purpose of this study is to investigate the behavior of a steel structural framing system that incorporates lightweight load-bearing walls and slabs, and to compare the weight of materials used in cold-formed and hot-finished steel structural systems for affordable housing.

Four types of models consisting of 243 members were simulated. Model 1 is a cold-formed steel structural framing system, while Model 2 is a hot-finished steel structural framing system. Both Models 1 and 2 use lightweight wall panels and lightweight composite slabs. Models 3 and 4 are made with brick walls and precast reinforced concrete systems, respectively. These structures use different wall and slab materials, namely, brick walls and precast reinforced concrete. The analysis includes bending behavior, buckling resistance, shear resistance and torsional rotation analysis.

This study found that using thinner steel sections can increase the deflection value. Meanwhile, increasing member length and the ratio of slenderness will decrease buckling resistance. As the applied load increases, buckling deformation also increases. Furthermore, decreasing shear area causes a reduction in shear resistance. Thicker sections and the use of lightweight materials can decrease the torsional rotation value.

The weight comparison of the steel structures shows that Model 1, which is a cold-formed steel structure with lightweight wall panels and lightweight composite slabs, is the most suitable model due to its lightweight and affordability for housing. This model can also be used as a reference for the optimal design of modular structural framing using cold-formed steel materials in the field of civil engineering and as a promotional tool.

The purpose of this paper is to examine the impact of structural breaks on the conditional variance of carbon emission allowance prices.

The authors employ the symmetric GARCH model, and two asymmetric models, namely the exponential GARCH and the threshold GARCH.

The authors show that the forecast performance of GARCH models improves after accounting for potential structural changes. Importantly, we observe a significant drop in the volatility persistence of emission prices. In addition, the effects of positive and negative shocks on carbon market volatility increase when breaks are taken into account. Overall, the findings reveal that when structural breaks are ignored in the emission price risk, the volatility persistence is overestimated and the news impact is underestimated.

The authors are the first to examine how the conditional variance of carbon emission allowance prices reacts to structural breaks.

The purpose of this paper is to, first, analyse to what extent the default probability based on structural models provides additional information and that accounting ratios do not contemplate. Second, to design hybrid models by including the default probability from structural models as explanatory variable, in addition to accounting ratios, in order to evaluate the differences in the accuracy of default predictions using an accounting‐based model and a hybrid model.

The authors calculated the scores from the accounting models annually during the period from 2003 to 2007 and estimated several structural models.

The results show that the market information obtained from the structural models includes additional information not reflected in the accounting information. Also, it can be concluded that including default probability from structural models as an explanatory variable allows the out‐sample predictive capacity of accounting‐based models to be improved.

The study highlights the importance of combining a structural model with an accounting model rather than expending energy on determining which of the two provides a greater predictive capacity. In fact, recent literature demonstrates no superiority of one approach over the other because both approaches capture different aspects related to the risk of bankruptcy in companies and they should be combined to improve credit risk management.

This study expands on the existing literature on the probability of business failure in the real estate sector. The authors present a comparative analysis of the accuracy of default predictions using accounting‐based models and hybrid models which will consider the default probability implicit in market information.

The aim of this paper is to demonstrate that supply chain social capital has an effect on supply chain integration, which in turn has a significant on firm performance, and then supply chain integration mediates the relationship between supply chain social capital and firm performance.

The authors validated their model and tested the hypotheses using the partial least squares (PLS) structural equation model (SEM).

Empirical results reveal that the three dimensions of supply chain social capital – structural, relational, and cognitive – had significant effects, directly or indirectly, on supply chain integration and performance, and supply chain integration played a mediating role in the relationships between structural capital and firm performance, between relational capital and firm performance, and between cognitive capital and firm performance.

Since the survey data were collected at various industries in Korea, it is difficult to gain social network benefits for a specific industry through worldwide. Therefore, to obtain more meaningful results, the authors would collect the data for special product family in the special industry. But the study suggests that supply chain integration among supply chain partners can be improved by building up social capital, firm performance can be enhanced by improving supply chain integration, and consequently, supply chain integration should serve to enhance firm's profitability.

The main contribution of this paper investigates whether supply chain integration mediates the relationship between supply chain social capital and firm performance in the supply chain using the PLS and Baron and Kenny's approach.

Reinforced concrete structural frames with masonry infills (infill-frames) are commonly used for construction worldwide. While the behavior of such frames has been studied extensively in the context of earthquake loading, studies related to their fire performance are limited. Therefore, this study aims to characterize the behavior of infill-frames under fire exposure by presenting a state-of-the-art literature review of the same.

Both experimental and computational studies have been included with a special emphasis on numerical modeling (simplified as well as advanced). The cold behavior of the infill-frame and its design requirements in case of fire exposure are first reviewed to set the context. Subsequently, the applicability of numerical modeling strategies developed for modeling cold infill-frames to simulate their behavior under fire is critically examined.

The major hurdles in developing generic numerical models for analyzing thermo-mechanical behavior of infill-frames are identified as: lack of temperature-dependent material properties, scarcity of experimental studies for validation and idealizations in coupling between thermal and structural analysis.

This study presents one of the most popular research problems connected with practical and reliable utilization of numerical models, as a good alternative to expensive traditional furnace testing, in assessing fire resistance of infill-frames. It highlights major challenges in thermo-mechanical modeling of infill-frames and critically reviews the available approaches for modeling infill-frames subjected to fire.

We examine the role of structural breaks in forecasting stock return volatility. We begin by testing for structural breaks in the unconditional variance of daily returns for the S&P 500 market index and ten sectoral stock indices for 9/12/1989–1/19/2006 using an iterative cumulative sum of squares procedure. We find evidence of multiple variance breaks in almost all of the return series, indicating that structural breaks are an empirically relevant feature of return volatility. We then undertake an out-of-sample forecasting exercise to analyze how instabilities in unconditional variance affect the forecasting performance of asymmetric volatility models, focusing on procedures that employ a variety of estimation window sizes designed to accommodate potential structural breaks. The exercise demonstrates that structural breaks present important challenges to forecasting stock return volatility. We find that averaging across volatility forecasts generated by individual forecasting models estimated using different window sizes performs well in many cases and appears to offer a useful approach to forecasting stock return volatility in the presence of structural breaks.