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This study aims to investigate the variation in overvaluation proxies and volatility across industry sectors and time.

Using industry sector data from the S&P Capital IQ database, this study applies traditional cross-sectional regressions to investigate the relationship between overvaluation and volatility over the 2001–2020 time period.

This study finds that the most volatile industry sectors generally do not coincide with overvalued industry sectors in the cross-section, implying that there are limitations to price-multiple methods for forecasting future volatility. Rather, this study finds that historical volatility significantly increases the goodness-of-fit when modeling volatility in the cross section of industry sectors. The findings of this study imply that firms should increase disclosures and transparency about corporate practices to decrease downside risk that stems from bad news. In addition, the findings underline the consistency between market efficiency and high levels of volatility in periods of significant uncertainty.

This study proposes a novel approach to examining the cross section of volatility across time for industry sectors.

This paper aims to study the yarn cross-section shape which is a very important yarn physical parameter and has a dominant effect on the physical structure of the yarn. Four factors affecting the yarn cross section, i.e. twist multiplier, Roving hank, spinning system and doubling technique, were investigated.

In past researches, the yarn cross-sectional area was calculated by considering any one yarn radius giving the approximate yarn cross-sectional area by assuming the yarn as a circular one.

In this study, a testing instrument is fabricated as shown in Plates 1 and 2 for yarn cross-section measurement and a novel method for calculating the correct yarn cross-sectional area of the yarn was developed.

In the past, no such studies have been conducted on the yarn cross-section studies because of the various limitations of the yarn cross-section measuring or testing instruments.

High-involvement work processes (HIWPs) are associated with high levels of employee influence over the work process, such as high levels of control over how to handle individual job tasks or a high level of involvement at team or workplace level in designing work procedures. When implementations of HIWPs are accompanied by companion investments in human capital – for example, in better information and training, higher pay and stronger employee voice – it is appropriate to talk not only of HIWPs but of “high-involvement work systems” (HIWSs). This chapter reviews the theory and practice of HIWPs and HIWSs. Across a range of academic perspectives and societies, it has regularly been argued that steps to enhance employee involvement in decision-making create better opportunities to perform, better utilization of skill and human potential, and better employee motivation, leading, in turn, to various improvements in organizational and employee outcomes.

However, there are also costs to increased employee involvement and the authors review the important economic and sociopolitical contingencies that help to explain the incidence or distribution of HIWPs and HIWSs. The authors also review the research on the outcomes of higher employee involvement for firms and workers, discuss the quality of the research methods used, and consider the tensions with which the model is associated. This chapter concludes with an outline of the research agenda, envisaging an ongoing role for both quantitative and qualitative studies. Without ignoring the difficulties involved, the authors argue, from the societal perspective, that the high-involvement pathway should be considered one of the most important vectors available to improve the quality of work and employee well-being.

This paper assesses the strength of the evidence on the impact of the physical environment on mental health and well‐being. Using a systematic review methodology, quantitative and qualitative evaluative studies of the effect of the physical environment on child and adult mental health published in English between January 1990 and September 2005 were sought from citation databases. The physical environment was defined in terms of built or natural elements of residential or neighbourhood environments; mental health was defined in terms of psychological symptoms and diagnoses. A total of 99 papers were identified. The strength of the evidence varied and was strongest for the effects of urban birth (on risk of schizophrenia), rural residence (on risk of suicide for males), neighbourhood violence, housing and neighbourhood regeneration, and neighbourhood disorder. The strength of the evidence for an effect of poor housing on mental health was weaker. There was a lack of robust research, and of longitudinal research in many areas, and some aspects of the environment have been very little studied to date. The lack of evidence of environmental effects in some domains does not necessarily mean that there are no effects: rather, that they have not yet been studied or studied meaningfully.

Undergraduate students are known to be a high-risk group for mental health problems. The purpose of this paper is to constitute a repeated cross-sectional study on the trend of depression over the years and factors associated with depression among undergraduates.

Cross-sectional data from five surveys between 2013 and 2020 (N = 1,578) among the undergraduates of Universiti Tunku Abdul Rahman, a private university in Kampar Malaysia, were combined. The Depression Anxiety and Stress Scale-21 was used to screen for depression. Cochran’s Armitage test was used to detect trend in depression. Logistic regression, random forest regression and extra gradient boosting regression were used to identify risk factors and classification.

The prevalence of depressive symptoms was found to be between 26.4% and 36.8% between the years with an average of 29.9%. There was no significant time trend in the prevalence. The risk of depressive symptoms was higher among female students, those who were dependent on family for financial support and those who were stressed.

Periodical screening for depression is warranted for the identification of students at risk for depression. Professional cognitive-behavioral therapies, peer support and consulting services should be made available to the students in need.

Depression among students had been studied widely, but the trend over years remains unexplored, especially in developing countries.

Longitudinal regression analysis is conducted to clarify causal relations and control for unwanted influences from actor heterogeneity and state dependence on theoretically important coefficient estimates. Because strategic management contains theory on how firms differ and how firm actions are influenced by their current strategic position and recent experiences, consistency of theory and methodology often requires use of longitudinal methods. We describe the theoretical motivation for longitudinal methods and outline some common methods. Based on a survey of recent articles in strategic management, we argue that longitudinal methods are now used more frequently than before, but the use is still inconsistent and insufficiently justified by theoretical or empirical considerations. In particular, strategic management researchers should use dynamic models more often, and should test for the presence of actor effects, autocorrelation, and heteroscedasticity before applying corrections.

Strategy researchers typically avoid using data more than a few years old for estimation of cross-sectional models. However, problems that might be caused by older data generally reflect more basic weaknesses in research design. This chapter develops criteria for evaluating the importance of the age of data used in cross-sectional research and indicates ways that better research design may be more effective than the substitution of newer data sets.

This chapter aims to provide nuance into the issue of generational cohort differences at work by focusing on the role of contextual moderator variables. Theory and hypotheses derived from the research on generational differences, psychological contracts, and work values are contrasted to a countervailing set of hypotheses derived from theory and research on the confluence of age and Person-Environment (P-E) fit. Complex patterns of interactive effects are posited for both alternatives. The results favored a generational hypothesis regarding the positively valenced construct of job satisfaction but an age-based hypothesis for the negatively valenced construct of turnover intentions. Results are tested using a subset from a large and nationally representative sample of adults from the US workforce (n = 476). Results offer mixed support for both age and generational cohorts, qualified by the specific type of outcome at hand.

The purpose of this paper is to conduct a critical review of the mediation studies published in the field of Human Resource Development (HRD) to discern if the study designs, the nature of data collection and the choice of statistical methods justify the causal claims made in those studies.

This paper conducts a critical review of published refereed articles that examined mediation in Human Resource Development Quarterly, Human Resource Development International, Advances in Developing Human Resources and European Journal of Training and Development. Mediation studies published in these journals from 2000 to 2015 were identified and coded. The four journals sampled were chosen to provide breadth of coverage of the different types of empirical studies published in the field of HRD.

The review findings imply that HRD scholars are not employing experimental or longitudinal designs in their studies when randomized experiments and longitudinal studies with at least three waves of data collection are regarded as the golden standards of causal research. Further, the findings indicate that sophisticated statistical modeling approaches like structural equation modeling are widely used to examine mediation in cross-sectional studies and most importantly, a large number of such studies do not acknowledge that cross-sectional data does not allow definite causal claims.

Although the findings urge us to rethink the inferences of mediation effects reported over the past 15 years in the field of HRD, this study also serves as a guide in thinking about framing and testing causal mediation models in future HRD research and even argues for a paradigm shift from a positivist orientation to critical and postmodern perspectives that can accommodate mixed methods designs for mediation research in HRD.

This paper presents a critical review of the trends in examining mediation models in the HRD discipline, suggests best practices for researchers examining the causal process of mediation and directs readers to recent methodological articles that have discussed causal issues in mediation studies.

This study aimed to know the effect of cross-sectional risk, which comprises business-specific risk and stock market volatility, as a variable for estimating macroeconomic risk in Indonesia. This study observes public companies in Indonesia and Indonesian macroeconomic data from 2004 to 2020. In this study, the author uses term spread as the dependent variable that reflects macroeconomic risk. The cross-sectional risk comprises financial friction (FF), cash flow (CF), debt–service ratio, and stock market volatility as independent variables. By using the Autoregressive Distributed Lag (ARDL) Model method, this study shows that business-specific and stock market risk can estimate macroeconomic risk, so that it becomes an early signal of economic shock, such as recession or high inflation, in the future. The model in this study also examines the cross-sectional risk relationship with other macroeconomic indicators, such as the Consumer Confidence Index (CCI), money supply (M0), and Indonesia’s trade balance (TB).