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The purpose of this study is to examine how luxury brand descriptions influence millennials’ impression of luxury, impression of sustainability, attitude toward brand and purchase intention using the impression formation theory.

A between-subjects experimental design was used to test the research model, wherein two randomly assigned groups received an online experiment with either a luxury-only or a sustainable-luxury brand description.

Findings included that the impression of luxury did not change for a sustainable-luxury brand describing the use of recycled materials as compared to a luxury-only brand without the description of recycled materials present. Therefore, millennials perceived the luxury-only and sustainable-luxury brands to provide an impression of luxury, which was the sole impression to significantly predict attitude toward the brand. In addition, the results indicated that attitude positively influenced purchase intention for both brand descriptions.

This study provides support for luxury brands to transition toward sustainable efforts of using recycled materials in their goods as the impression of luxury is preserved, and provide marketing communication that favors sustainable brand positioning. This is one of the first empirical studies that focused on exploring sustainability strategies for luxury brands targeting a specific market segment (i.e. millennials in the United States of America).

The purpose of this paper is to test for bubbles in the US hard red spring (HRS) wheat market from 2004 to 2014, with particular focus on 2007-2008 when the market experienced record-high price volatility.

The authors apply a recently developed bubble testing procedure to cash, rolling nearby futures contract, and individual futures contract prices of HRS wheat sampled at daily, weekly, and monthly frequencies. Two critical value (CV) sequences are derived to date-stamp bubbles, one from Monte Carlo simulations, and the other from recursive wild bootstrap procedure.

The authors find that regardless of the price series adopted, sampling frequency chosen, or CVs used, bubbles account for only a small fraction of the HRS wheat price behavior during 2004-2014. However, much sharper differences are detected regarding the key policy question of bubble behavior during 2007-2008. Individual futures contract prices during this period suggest only a minimal number of bubble days, while rolling nearby futures and cash prices indicate bubbles lasting much longer. Since theory suggests that prices for individual futures contracts are more likely to provide a clearer test of bubble components, the authors conclude there is little evidence that the spike in spring wheat prices to $25 per bushel in 2007-2008 was a bubble.

This paper is the first in the literature to examine the sensitivity of bubble testing to different types of data, sampling frequencies, and inference procedures.

This paper aims to present the development of prediction models for aircraft actuator failure impact on flight envelope within the artificial immune system (AIS) paradigm.

Simplified algorithms are developed for estimating ranges of flight envelope-relevant variables using an AIS in conjunction with the hierarchical multi-self strategy. The AIS is a new computational paradigm mimicking mechanisms of its biological counterpart for health management of complex systems. The hierarchical multi-self strategy consists of building the AIS as a collection of low-dimensional projections replacing the hyperspace of the self to avoid numerical and conceptual issues related to the high dimensionality of the problem.

The proposed methodology demonstrates the capability of the AIS to not only detect and identify abnormal conditions (ACs) of the aircraft subsystem but also evaluate their impact and consequences.

The prediction of altered ranges of relevant variables at post-failure conditions requires failure-specific algorithms to correlate with the characteristics and dimensionality of self-projections. Future investigations are expected to expand the types of subsystems that are affected and the nature of the ACs targeted.

It is expected that the proposed methodology will facilitate the design of on-board augmentation systems to increase aircraft survivability and improve operation safety.

The AIS paradigm is extended to AC evaluation as part of an integrated and comprehensive health management process system, also including AC detection, identification and accommodation.

The fundamental friction studies of rubber have generally dealt with single contact sliders or rollers. It has been demonstrated abundantly that the lubricated friction of rubber is mainly the ‘deformation loss’ component of friction. At moderate sliding speeds where thin film lubrication exists and the interface shear drag is small, the friction is the same as in rolling. The rubber substrate is continually deforming ahead of, and recovering behind, the contact in both rolling or sliding cases. Since the deformation of rubber is partially irreversible, energy is lost which is irreversible, energy is lost which is reflected as the ‘deformation loss’ component of friction at the contact. This deformation loss component of friction has been correlated with the “elastic hysteresis” or the “visco‐elastic losses”. The elastic hysteresis consideration alone does not fully explain rubber substrate deformation and friction behaviour. The assumptions used are incompatible. For example, the delayed or incomplete recovery of the rubber substrate behind the contact leads to residual strains which result in the contact area asymmetry as shown in Fig. 1. In contrast, the elastic hysteresis approach assumes Hertzian elastic contact which is symmetric. It may be noted that all ‘lossy’ materials whether plastic or visco‐elastic in nature must involve frictional contact area asymmetry. Various simplified visco‐elastic considerations of the rolling contact have been illustrated, only qualitatively, the contact deformation and frictional loss behaviour. Direct experimental and quantitive verifications have not been attempted, however. Some rigorous visco‐elastic, two dimensional, continuum analyses of the rolling contact are available in the literature and are very complex. It is difficult to use the results of these analyses to the problem of frictional loss evaluation, primarily because linear and simplified visco‐elastic models have been employed. Moreover, for the general friction problem of rubberlike elastomers which are nonlinear visco‐elastic solids of complex descriptions, physical quantification and interpretation of the parameters used in the above analyses are not possible. Employing the method of a visco‐elastic operator, a semi‐analytical technique has been used recently to express the asymmetry of the sliding contact area and the associated deformation loss component of friction. The results of the analyses agree reasonably with the experimental observations. Dynamic material property parameters used in the analyses are obtained from an indentation test arrangement under closely controlled conditions.

This paper gives a review of the finite element techniques (FE) applied in the area of material processing. The latest trends in metal forming, non‐metal forming, powder metallurgy and composite material processing are briefly discussed. The range of applications of finite elements on these subjects is extremely wide and cannot be presented in a single paper; therefore the aim of the paper is to give FE researchers/users only an encyclopaedic view of the different possibilities that exist today in the various fields mentioned above. An appendix included at the end of the paper presents a bibliography on finite element applications in material processing for 1994‐1996, where 1,370 references are listed. This bibliography is an updating of the paper written by Brannberg and Mackerle which has been published in Engineering Computations, Vol. 11 No. 5, 1994, pp. 413‐55.

In this chapter we discuss model selection and predictive accuracy tests in the context of parameter and model uncertainty under recursive and rolling estimation schemes. We begin by summarizing some recent theoretical findings, with particular emphasis on the construction of valid bootstrap procedures for calculating the impact of parameter estimation error. We then discuss the Corradi and Swanson (2002) (CS) test of (non)linear out-of-sample Granger causality. Thereafter, we carry out a series of Monte Carlo experiments examining the properties of the CS and a variety of other related predictive accuracy and model selection type tests. Finally, we present the results of an empirical investigation of the marginal predictive content of money for income, in the spirit of Stock and Watson (1989), Swanson (1998) and Amato and Swanson (2001).

The purpose of this paper is to understand better the formation of an industry and the movement toward agglomeration by examining the development of the furniture manufacturing industry of Western North Carolina and Virginia.

In this general review, the initiation and growth of the furniture industry is traced, applying the theory of agglomeration and noting isomorphic tendencies and the primacy of the search for legitimacy among constituents.

The paper finds first of all, the pioneering efforts of Thomas Wrenn in High Point brought the industry to the region. An initial wave of furniture manufacturers followed closely behind Wrenn as the industry gained legitimacy and status in North Carolina. Important elements in building the industry included the establishment of the Southern Furniture Manufacturers Association and the Southern Furniture Market in High Point. A second wave of furniture producers arrived on the scene after the First World War. This group benefited from cooperative actions of the survivors of the first wave and brought the Western North Carolina and Virginia area to the forefront of the furniture manufacturing industry in the USA. Finally, the paper comments on the current state of the industry in relation to the threat of foreign competition.

The furniture industry is not alone in the need to understand the impact of globalization. Practitioners and researchers alike should be aware of the costs to stakeholder groups, such as employees and local communities.

Contact problems are among the most difficult ones in mechanics. Due to its practical importance, the problem has been receiving extensive research work over the years. The finite element method has been widely used to solve contact problems with various grades of complexity. Great progress has been made on both theoretical studies and engineering applications. This paper reviews some of the main developments in contact theories and finite element solution techniques for static contact problems. Classical and variational formulations of the problem are first given and then finite element solution techniques are reviewed. Available constraint methods, friction laws and contact searching algorithms are also briefly described. At the end of the paper, a bibliography is included, listing about seven hundred papers which are related to static contact problems and have been published in various journals and conference proceedings from 1976.

We aim to examine two issues. First, we intend to identify the best performing expected return proxies. Second, we investigate whether the expected return proxies for individual stocks can track the corresponding realized returns during extremely good or extremely bad times of the economic environment related to business conditions, stock market valuation and broad market performance.

We construct four sets of expected return proxies, including: (1) characteristic-based proxies; (2) standard risk-factor-based proxies; (3) risk-factor-based proxies that allow betas to vary with firm characteristics and (4) macroeconomic-variable-based proxies. First, we estimate expected returns for individual stocks using newly developed methods and evaluate the performance of these expected return proxies based on the minimum variance criterion of Lee et al. (2020). Second, we regress expected return proxies and realized returns on indicator variables that capture the extreme phases of the economic environment. Then we compare the estimated coefficients from these two sets of regressions and see if they are similar in magnitude via formal hypothesis testing.

We find that characteristic-based proxies and risk-factor-based proxies that allow betas to vary with firm characteristics are the two best performing proxies. Therefore, it is important to allow betas to vary with firm characteristics in constructing expected return proxies. We also find that model-based expected return proxies do a reasonably good job capturing actual returns during extremely bad and extremely good phases of business cycles measured by leading economic indicators, consumer confidence and business confidence. However, there is a large gap between the adjustment of model-based expected returns and realized returns during extreme episodes of stock market valuation or broad market performance.

We examine four types of expected return proxies and use the newly developed methodology as in Lee et al. (2020) to see which one is the best. In addition, we document whether model-based expected returns from individual stocks adjust partially or fully to keep pace with actual returns in response to changing economic conditions. No prior studies have examined these two issues.