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Organizational researchers have become increasingly interested in multi-level constructs – that is, constructs that are meaningful at multiple levels of analysis. However, despite the plethora of theoretical and empirical work on multi-level topics, explicit frameworks for validation of multi-level constructs have yet to be fully developed. Moreover, available principles for conducting construct validation assume that the construct resides at a single level of analysis. We propose a five-step framework for conceptualizing and testing multi-level constructs by integrating principles of construct validation with recent advancements in multi-level theory, research, and methodology. The utility of the framework is illustrated using theoretical and empirical examples.

This chapter reviews research on multi-level organizational justice. The first half of the chapter provides the historical context for this issue, discusses organizational-level antecedents to individual-level justice perceptions (i.e., culture and organizational structure), and then focuses on the study of justice climate. A summary model depicts the justice climate findings to date and gives recommendations for future research. The second half of the chapter discusses the process of justice climate emergence. Pulling from classical bottom-up and top-down climate emergence models as well as contemporary justice theory, it outlines a theoretical model whereby individual differences and environmental characteristics interact to influence justice judgments. Through a process of information sharing, shared and unique experiences, and interactions among group members, a justice climate emerges. The chapter concludes by presenting ideas about how such a process might be empirically modeled.

“Multi-Level Issues in Strategy and Methods” is Volume 4 of Research in Multi-Level Issues, an annual series that provides an outlet for the discussion of multi-level problems and solutions across a variety of fields of study. Using a scientific debate format of a key scholarly essay followed by two commentaries and a rebuttal, we present, in this series, theoretical work, significant empirical studies, methodological developments, analytical techniques, and philosophical treatments to advance the field of multi-level studies, regardless of disciplinary perspective.

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.

For many of the current leadership theories, models, and approaches, the answer to the question posed in the title, “Is leadership more than ‘I like my boss’?,” is “no,” as there appears to be a hierarchy of leadership concepts with Liking of the leader as the primary dimension or general factor foundation. There are then secondary dimensions or specific sub-factors of liking of Relationship Leadership and Task Leadership; and subsequently, tertiary dimensions or actual sub-sub-factors that comprise the numerous leadership views as well as their operationalizations (e.g., via surveys). There are, however, some leadership views that go beyond simply liking of the leader and liking of relationship leadership and task leadership. For these, which involve explicit levels of analysis formulations, often beyond the leader, or are multi-level in nature, the answer to the title question is “yes.” We clarify and discuss these various “no” and “yes” leadership views and implications of our work for future research and personnel and human resources management practice.

The purpose of this paper is to empirically explore the underlying mechanisms through which empowerment affects organizational outcomes via a multi-dimensional model. Specifically, the paper suggests that empowerment climate (EC) is positively related to psychological empowerment (PE) and the effect of PE on the outcome variable of job satisfaction is mediated by justice perceptions and role clarity.

In total, 765 employees at the executive level across 26 distinct groups in a large manufacturing firm participated in the survey. Multi-level analyses based on both hierarchical linear modeling and multi-level structural equation modeling techniques were utilized to test the hypotheses.

This research demonstrated that EC significantly affected PE and that perceptions of justice and role clarity mediated the relationship between PE and job satisfaction. Additional analyses demonstrated that EC did not significantly affect organizational outcomes above and beyond PE, justice, and role clarity.

The current study suggests that managers concerned with increasing employee perceptions of justice may be able to do so by increasing perceptions of employee empowerment. As only individual employee perceptions of empowerment related directly to organizational outcomes, this demonstrates the importance for managers to understand perceptions of employees.

Exploring these mechanisms will strengthen the knowledge regarding how empowerment works to enhance organizational effectiveness. This will enable practitioners to better determine how and when empowerment will be most effective.

Facing the aging workforce but older workers’ vulnerability in the labor market, this chapter empirically explores factors and policy implications to enhance older workers’ entered employment rates (EER) after exiting the national workforce program. After reviewing older workers’ attributes and the unique methods to train them, the chapter examines demographic, socioeconomic, and program attributions to older workers’ EER, controlling for cyclical changes in the labor market. The chapter relies on three sets of models including logistic regression, multi-level mixed-effect regression, and multilevel mixed effect logistic regression models, as well as longitudinal Workforce Investment Act Standardized Record Data and Bureau of Labor Statistics unemployment data. Older dislocated workers and older adults are examined separately. Some Workforce Innovation and Opportunity Act training and related service combinations are identified to contribute to older adults and older dislocated workers’ EER and to inform strategic decision-making about future allocations of funds and policy efforts to serve older workers.

The paper introduces a multi-level model to reduce prejudice through supporting diversity, equity, and inclusion (DEI) at the institutional, organizational, and individual levels. The purpose of the model is to provide theoretically undergirded pathways to explain how societal events calling for systemic changes in DEI practices can engage and inculcate such systemic changes in organizations and institutions.

The model draws upon macro-level (i.e. institutional theory and institutional logics) theories from sociology and strategic management, meso-level theories from leadership and strategy, and micro-level organizational behavior and human resource management theories.

Resting on open systems theory (Katz and Kahn, 1966) as a backdrop, the authors address how institutional changes result in organizational level changes driving multi-level outcomes of increased DEI, reduced prejudice in work-related settings, and performance gains. The authors suggest the recursive nature of the model can trigger institutional level shifts in logics or result in isomorphic pressures that further change organizational fields and organizations.

The contribution rests in a multi-level examination to help understand how environmental pressures can motivate organizations to enact broader changes related to social justice, specifically increasing efforts in DEI inside the operational aspects of the organization. By enacting these changes, the authors suggest the resultant positive changes in organizations will enhance culture and performance, creating isomorphic pressure for industry wide changes that may begin to move the needle on addressing systemic problems that feed prejudicial behavior in the workplace.

The purpose of this paper is to illustrate the value of extended time span coverage of state longitudinal education and workforce data system to inform and improve the effectiveness of future high impact expenditure decisions.

It used an analytical 29-year data file created by the author that links seven already-in-place education and workforce administrative record sources. Relying on the path dependency theory, multi-level mixed-effect logistic and multi-level mixed-effect linear regression models are used to test three hypotheses.

The findings are consistent with the hypotheses: inclusion of the multiple steps along a post-secondary education pathway and prior job histories are both critical to understanding workforce outcomes mechanisms; it takes time for the employment outcome effect to be evident and strong following education attainment.

The study concludes with research limitations and implications for decision makers to call for retaining and investing in administrative records with extended time span coverage, particularly for the already-in-place historical administrative records.

The paper is one of the first to demonstrate the value of extended time span coverage in a longitudinal state integrated data system through econometric modeling, using longitudinally integrated data linking seven administrative records covering continuously for 29 years. No matter for prior education or employment pathway, it is only through extended time span coverage that employment outcomes can be well measured and the rich nuances interpreting the mechanisms of education return on investment can be revealed.

Chen, Mathieu and Bliese (this volume) propose a useful framework for conceptualizing, testing, and validating multi-level constructs. Their framework focuses on the differences in constructs that occur between individuals and groups. One key question arises with their approach: What happens if the validity of constructs is viewed as potentially varying not only between individuals and between groups but also within individuals and within groups? The focus on within-individuals and within-groups variations is called “frog-pond effects.” Based on such frog-pond effects, this chapter reconsiders the approach of Chen et al. and discusses some of the implications of adding this perspective to multi-level research.