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There is currently a great deal of attention in psychometric and statistical methods on ensuring measurement invariance when examining measures across time or populations. When measurement invariance is established, changes in scores over time or across groups can be attributed to changes in the construct rather than changes in reaction to or interpretation of the measurement instrument. When measurement in not invariant, it is possible that measured differences are due to the measurement instrument itself and not to the underlying phenomenon of interest. This chapter discusses the importance of establishing measurement invariance specifically in postsecondary settings, where it is anticipated that individuals' perspectives will change over time as a function of their higher education experiences. Using examples from several measures commonly used in higher education research, the concepts and processes underlying tests of measurement invariance are explained and analyses are interpreted using data from a US-based longitudinal study on bioscience PhD students. These measures include sense of belonging over time and across groups, mental well-being over time, and perceived mentorship quality over time. The chapter ends with a discussion about the implications of longitudinal and group measurement invariance as an important conceptual property for moving forward equitable, reproducible, and generalizable quantitative research in higher education. Invariance methods may further be relevant for addressing criticisms about quantitative analyses being biased toward majority populations that have been discussed by critical theorists engaging quantitative research strategies.

In business and management, cross-national and cross-cultural comparisons between countries have been a topic of interest for many decades. Not only do firms engage in business in different countries around the world but also within countries. The population has become more diversified over time, making cross-cultural comparisons within country boundaries increasingly relevant. In comparisons across cultural groups, measurement invariance (MI) is a prerequisite; however, in practice, MI is not always attained or even tested. Our study consists of three parts. First, we provide a bibliometric analysis of articles on cross-cultural and cross-national topics in marketing to provide insight into the connections between the articles and the main themes. Second, we code articles to assess whether researchers follow the recommended steps as outlined in the multigroup confirmatory factor analysis (MGCFA) approach. The results indicate that MI testing is incorporated in the toolbox of many empirical researchers in marketing and that articles often report the level of invariance. Yet, most studies find partial invariance, meaning that some items are not comparable across the cultural groups studied. Researchers understand that MI is required, but they often ignore noninvariant items, which may decrease the validity of cross-cultural comparisons made. Third, we analyze the dissemination of MI in the broader literature based on co-citations with Steenkamp and Baumgartner (1998), a widely cited article on MI in the field of marketing. We conclude by noting methodological developments in cross-cultural research to enable addressing noninvariance and providing suggestions to further advance our insight into cross-cultural differences and similarities.

Economic globalization is leading large companies to focus on international strategic management. Nowadays, the assets referred to as “corporate intangibles,” such as corporate reputation, are becoming increasingly important because they are considered a key factor for the viability of an organization, and companies therefore need to incorporate them into their scorecards for management. The problem is that their measurement is subjective and latent. These two characteristics impede direct international comparison and require demonstrating the accuracy of comparison via a minimum of two tests – construct equivalence and metric equivalence. As regards corporate reputation, construct equivalence was verified by Naomi Gardberg (2006). However, the subsequent studies did not address metric equivalence. Based on the results of a survey provided by the Reputation Institute (n = 5,950, 50 firms evaluated in 17 countries in the Americas, Europe, Asia and Australia), the degree of RepTrak metric equivalence has been tested, using two different methodologies, multigroup analysis (structural equation model), and a new technique from 2016, the Measurement Invariance of Composite Model procedure from the Partial Least Square Path Modeling family. As one would expect from other cross-cultural studies, reputation metrics do not meet the full metric equivalence, which is why they require standardization processes to ensure international comparability. Both methodologies have identified the same correction parameters, which have allowed validation of the mean and variance of response style by country.

This chapter describes how to use popular software programs (Hierarchical Linear Modeling, LISREL) to analyze multiwave panel data. We review prevailing methods for panel data analyzes in strategic management research and identify their limitations. Then, we explain how multilevel and latent growth modeling provide more rigorous methodologies for studying dynamic phenomena. We present an example illustrating how firm performance can initiate temporal change in the human and social capital of members of Board of Directors, using hierarchical linear modeling. With the same data set, we replicate this test with first-order factor latent growth modeling (LGM). Next, we explain how to use second-order factor LGM with panel data on employee cognitions. Finally, we review the relative advantages and disadvantages of these new data-analytical approaches.

Multivariate latent growth modeling (multivariate LGM) provides a flexible data analytic framework for representing and assessing cross-domain (i.e., between-constructs) relationships in intraindividual changes over time, which also allows incorporation of multiple levels of analysis. Using the chapter by Cortina, Pant, and Smith-Darden (this volume) as a point of departure, this chapter discusses important preliminary data analysis and interpretation issues prior to performing multivariate LGM analyses.

The study addresses the mechanism of how cultural dimensions influence the different dimensions of emotional intelligence. Building on the cascading model described by Joseph and Newman (2010), we extend our previous findings (Gunkel, Schlaegel, & Engle, 2014) by exploring the influence of cultural dimensions on a cascading model of emotional intelligence.

We use survey data from 2,067 business students in nine countries (China, Colombia, Germany, India, Italy, Russia, Spain, Turkey, and the United States), representing 8 of the 11 cultural clusters identified by Ronen and Shenkar (2013).

We find that uncertainty avoidance and long-term orientation have a positive influence on self-emotional appraisal, which in turn influence regulation of emotion, which then has a positive influence on the use of emotion. At the same time, others’ emotional appraisal mediates the relationship between all cultural dimensions except power distance and use of emotion. We also find that uncertainty avoidance, masculinity, and long-term orientation directly influence the use of emotion, suggesting a partial mediation effect.

Our findings have to be interpreted in the light of the limitations of our approach owing to the cross-sectional study design and the limited generalizability of the sample.

We contribute to the existing literature by examining the mechanism through which culture influences the different facets of emotional intelligence and whether and how the different facets affect each other. The proposed influence of culture on a cascading model of emotional intelligence provides a more detailed and nuanced understanding of the mechanism and the pathways in which culture affects emotional intelligence.

This study investigates the determinants of students’ intention to major in accounting (IMA) in pre-recessionary, recessionary, and post-recessionary time periods. By examining four factors (perceived professional ethics (PE), job market consideration (JMC), social influence (SI), and self-efficacy (SE)) in accordance with the theory of planned behavior (TPB), we address two primary research questions. The first question concerns whether the four factors are related to students’ IMA before, during, and after the recession. The second deals with whether there is a shift in the relative importance of the factors between the pre-recessionary, recessionary, and post-recessionary periods. We use structural equation modeling and multigroup analysis of structural invariance to analyze these issues. The results show that all four factors have significant structural weights in each period, with the exception of perceived PE in the pre-recessionary period. In terms of students’ IMA over the three periods, perceived PE, JMC, and SI become factors of greater importance during the recessionary and post-recessionary periods, while SE decreases in relative importance.