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Addresses the standardization of the measurements and the labels for concepts commonly used in the study of work organizations. As a reference handbook and research tool, seeks to improve measurement in the study of work organizations and to facilitate the teaching of introductory courses in this subject. Focuses solely on work organizations, that is, social systems in which members work for money. Defines measurement and distinguishes four levels: nominal, ordinal, interval and ratio. Selects specific measures on the basis of quality, diversity, simplicity and availability and evaluates each measure for its validity and reliability. Employs a set of 38 concepts ‐ ranging from “absenteeism” to “turnover” as the handbook’s frame of reference. Concludes by reviewing organizational measurement over the past 30 years and recommending future measurement reseach.

The purpose of this paper is to provide evidence for a “leadership big five”, a model of leadership behaviour integrating existing theories of leadership and conceptually aligned with the most established model of personality, the big five. Such a model provides researchers and practitioners with a common language to describe leadership behaviour in a field with a plethora of leadership models. The model also describes a wider range of leadership behaviour than other models of leadership, and presents dimensions that correlate with important organisational outcomes as demonstrated in this study.

In total, 1,186 employees completed the Voice Leadership 360, a survey designed to measure the leadership big five, collectively rating 193 managers from a range of different sectors and industries, using a 360-degree survey methodology.

Confirmatory factor analyses and internal reliability analyses provide evidence for 22 lower-order factors of leadership behaviour that aggregate into five higher-order factors of leadership aligned with the big five personality descriptors. Further evidence for the validity of the model is indicated by significant correlations between 360-degree survey ratings and raters’ judgements of leaders’ personality, and significant correlations between 360-degree survey ratings and both work unit engagement levels and manager reports of work unit performance.

The cross-sectional design is the main limitation of the present study, limiting conclusions that changes in leadership behaviours will lead to changes in organisational outcomes. The primary research implications of this study include the support for an integrating model of leadership behaviour that aligns with a large body of psychological research, as well as the development of a survey that can be used for future exploration of the model.

Practitioners may use the results of the study to rethink how they develop competency frameworks and measure leadership behaviour in organisation development contexts. This broad model of leadership and the familiarity of its dimensions could increase the effectiveness of behaviour change interventions, and the presented survey provides a reliable and valid tool for 360-degree assessments.

The study provides evidence that leadership can be described in a structurally similar way to human personality. It presents a leadership model that consists of a broader range of leadership behaviours related to organisational outcomes compared with previous models of leadership.

This paper aims to investigate the explanatory power of the Fama-French five-factor model and compares it to the other asset pricing models. In addition, the paper examines the contributions of two additional factors: profitability and investment factor. The authors test the alternative four-factor models.

The authors use stock returns data of BSE-500 listed firms for the Indian market, an emerging market, from 1999 to 2020, thus covering the post-Asian crisis and pre- and post-financial crisis (2007–2008) periods. The authors employ 75 and 96 portfolios based on different factors. To check the performance of asset pricing models, the authors also used the GRS F-statistics and factor spanning tests.

The authors find that the five-factor model and alternative four-factor model outperform the three-factor model. Contrary to the findings for the US, but similar to the Chinese stock market, the value factor is significant for the Indian stock market. Simultaneously, the authors also find that the investment factor has no explanatory power in the presence of the profitability factor in their sample.

To the best of the authors' knowledge, this is the most comprehensive study using data more than two decades. These results are based on 75 (25 × 3) portfolios based on size, value, profitability and investment. The authors also tested these results based on 96 (32 × 3) portfolios to check robustness, and these results still hold. Furthermore, the authors find that factors based on 2 × 3 sorting have higher explanatory power than those based on 2 × 2 and 2 × 2 × 2 × 2 sorting.

The purpose of this paper is to determine the best conditional asset pricing model for the Tokyo Stock Exchange sample by utilizing long‐run daily data. It aims to investigate whether there are any other firm‐specific variables that can explain abnormal returns of the estimated asset pricing model.

The individual firm sample was used to conduct various cross‐sectional tests of conditional asset pricing models, at the same time as using test portfolios in order to confirm the mean variance efficiency of basic unconditional models.

The paper's multifactor models in unconditional forms are rejected, with the exception of the five‐factor model. Further, the five‐factor model is better overall than the Fama and French model and other alternative models, according to both the Gibbons, Ross, and Shanken test and the Hansen and Jagannathan distance measure test. Next, using the final conditional five‐factor model as the de facto model, it was determined that the turnover ratio and the size can consistently predict Jensen's alphas. The book‐to‐market ratio (BM) and the past one‐year returns can also significantly predict the alpha, albeit to a lesser extent.

In the literature related to Japanese data, there has never been a comprehensive test of conditional asset pricing models using the long‐run data of individual firms. The conditional asset pricing model derived for this study has led to new findings about the predictability of past one‐year returns and the turnover ratio.

The purpose of this paper is to investigate the return performance of a portfolio of US “vice stocks,” firms that manufacture and sell products such as alcohol, tobacco, gaming services, national defense and firearms, adult entertainment, and payday lenders.

Using daily return data from a portfolio of vice stocks over the period 1987-2016, the author computes the Jensen’s α (capital asset pricing model (CAPM)), Fama-French Three-Factor, Carhart Four-Factor, and Fama-French Five-Factor results for the complete portfolio, and each vice industry individually.

The results from the CAPM, Fama-French Three-Factor Model, and the Carhart Four-Factor Model show a positive and significant α for the vice portfolio throughout the sample period. However, the α’s significance disappears with the addition of the explanatory variables from the Fama-French Five-Factor Model.

The author provides academics and practitioners with results from a new model. As of this writing, the author is unaware of any articles published in peer-reviewed academic journals that investigate vice stocks within the framework of the Fama-French Five-Factor Model (2015). First, the existing literature does not shed light on the relationship between “profitability” and “aggressiveness” (the fourth and fifth factors of the Fama-French Model) and vice stock returns. Second, within the framework of the Fama-French Five-Factor Model, the author shows results not only from a portfolio of vice stocks, but from various vice industries as well.

The purpose of this paper is to compare the performance of various multifactor asset pricing models across ten emerging and developed markets.

The general methodology to test asset pricing models involves regressing test asset returns (left-hand side assets) on pricing factors (right-hand side assets). Then the performance of different models is evaluated based on how well they price multiple test assets together. The parameters used to compare relative performance of different models are their pricing errors (GRS statistic and average absolute intercepts) and explained variation (average adjusted R²).

The Fama-French five-factor model improves the pricing performance for stocks in Australia, Canada, China and the USA. The pricing in these countries appears to be more integrated. However, the superior performance in these four countries is not consistent across a variety of test assets and the magnitude of reduction in pricing errors vis-à-vis three- or four-factor models is often economically insignificant. For other markets, the parsimonious three-factor model or its four-factor variants appear to be more suitable.

Unlike most asset pricing studies that use test assets based on variables that are already used to construct RHS factors, this study uses test assets that are generally different from RHS sorts. This makes the tests more robust and less biased to be in favour of any multifactor model. Also, most international studies of asset pricing tests use data for different markets and combine them into regions. This study provides the evidence from ten countries separately because prior research has shown that locally constructed factors are more suitable to explain asset prices. Further, this study also tests for the usefulness of adding a quality factor in the existing asset pricing models.

The purpose of this paper is to address the statistical issues associated with the hierarchically structured data in previous studies that focused on servant leadership. To resolve these issues, multilevel modeling methods were applied to re-visit the construct validity of the servant leadership questionnaire developed by Barbuto and Wheeler (2006) and investigate the relationship between servant leadership and job satisfaction under a multilevel framework.

The survey data was obtained from a sample of 2,089 teachers from 117 primary and secondary schools in Hong Kong. The analyses were conducted using multilevel confirmatory factor analysis (MLCFA) and multilevel structural equation modeling (MLSEM).

The results revealed the significant and non-trivial variances that were explained at the organization level in the items measuring servant leadership, which justified the use of MLCFA and MLSEM. The results of MLCFA provided empirical support for the multidimensional construct as well as the second-order factorial structure of servant leadership measures at both the individual and organization levels. In addition, the positive relationships between servant leadership and the followers’ job satisfaction were found to vary at different levels.

This study reiterates the importance of using appropriate methods to capture a solid definition of the construct of servant leadership and provides new insights into the conceptual framework of servant leadership as well as the effects of servant leadership on individual and organizational outcomes.

The purpose of this paper is to focus on one of the major emerging Asian economies – India – to examine the role of human capital in asset prices.

The analysis uses various statistical techniques (e.g. multifactor regression model, 3D graphs, GRS test and residual graphs) to test the role of human capital in asset prices.

A six-factor model designed for capturing the size, value, profitability, investment and human capital patterns in average portfolio returns performs better than both Fama–French’s (1993) three- and Fama–French’s (2015) five-factor model. The main problem of six-factor model is its failure in capturing the average returns on “microcap with low-value stocks that are highly profitable invests aggressively for asset growth but invests much lesser for human growth” and “microcap with unprofitable stocks whose returns behave like those of low-value firms with conservative investment”. The study finds the investment factor (CMA) of Fama–French’s (2015) five-factor model as the redundant factor for describing the portfolio average returns in the study sample.

The paper argues that human capital also plays a role in predicting returns. This has significant public policy content.

The present study is novel for several reasons: first, it includes six-factor model descriptions; second, no comprehensive asset pricing study is done with human capital in Asian emerging markets, especially in India. Perhaps, this is the first study to examine whether portfolio returns are affected by the human capital in the Indian context. Third, the study period and methodology used are completely different from the previous studies.

This study aims to examine the attractiveness of the regional Dow Jones Sustainability Indexes (DJSI) and several renewable energy indexes during December 31, 2010 to December 31, 2019. This study uses a risk-return analysis and a set of explanatory factors. Lastly, this study conducts a comparative analysis of these indexes with conventional indexes.

This study uses data from Eikon, a Thomson Reuters database. To analyze the indexes’ behavior, this study uses the indexes’ annual return as of December 31 for each year. Next, this study estimates the Fama and French’s five-factor model using an ordinary least squares regression for regional DJSI and renewable energy indexes.

The results show that regional DJSIs delivered returns both above and below conventional indexes. In contrast, renewable energy indexes had high betas and negative returns, making them unattractive to investors.

The results imply the need for public financing programs that support the transition to a sustainable economy and reduce risk and increase the return on private investment.

This study provides insights for policymakers regarding the importance of sustainability indexes in the transition to a green economy.

This study contributes to the growing literature on Fama and French’s five-factor model of sustainability indexes, especially in the current context characterized by intense green political changes. In particular, this study complements the few studies that have addressed the economic implications of renewable energy indexes in markets.

This paper aims to investigate whether Islamic and conventional equity indices offer some alpha. These indices are expected to offer no alpha being value-weighted, passive and unmanaged.

This paper used monthly data from 1996 to 2016 of four Dow Jones (DJ) and one financial times stock exchange (FTSE) Islamic equity indices and five conventional Morgan Stanley Capital International (MSCI) equity indices. This study used a simple ordinary least square (OLS) rolling window regressions to generate the alphas and risk loadings when adjusting for prominent pricing factor models.

The findings from OLS regressions suggest that DJ Islamic indices of Japan, Europe and World generate significant alphas, whereas, MSCI conventional indices of Asia/Pacific, USA and World generate significant alpha when risk-adjusted for pricing factor models. However, in 36-month rolling window regressions, all Islamic indices generate significant alpha and factor loading. The magnitude of alpha and factor loading changes over time.

The finding shows that the Shari’ah-compliant investment fund’s alpha must be adjusted with the respective benchmark index alpha to measure the fund manager’s skill performance quantitatively.

To the best of the author’s knowledge, this is the first study that investigates and compares the Islamic, as well as conventional indices for abnormal returns, which are adjusted for both Fama–French five and q-theory-based four assets pricing risk factors and as a benchmark for Shari’ah-compliant fund’s performance.