The Problem

2a:T4fa, The Problem

To better understand Human Resource Development (HRD), it is critical to understand human behavior and perspectives on subjective topics. Q methodology provides a view of subjectivity from the point of view that is self-referenced.

The Solution

This article provides a description of a method to identify similarities and differences in the subjective perceptions across a sample. This is distinctly different from traditional factor analysis that examines correlation between items. A step-by-step description of Q methodology is included that describes defining the concourse, developing the Q-set, selecting the P-set (sample), Q-sorting (collecting data), as well as analyzing and interpreting the data.

The Stakeholders

Both researchers and practitioners will benefit by understanding how to implement and interpret Q methodology in both research and practice to understand human subjectivity. The article can be used as a guide by researchers and practitioners who want to conduct Q methodology in the field of HRD to better understand subjective viewpoints.

2b:T4da, The Problem

While nested structures occur naturally in organizational and educational settings, past research has failed to recognize these nested structures. Ordinary least squares (OLS) methods assume independence of observation, fixing the intercepts and slopes across all groups. By not accounting for nested structures, errors of inference can occur with the risk of compromising the validity of the results.

The Solution

As new theories become more complex multilevel representations of phenomena, testing these complex theories require hierarchical linear modeling (HLM). HLM provides human resource development (HRD) practitioners with a better method to test multilevel theories while taking into account nested structures, providing a more accurate representation across the different levels.

The Stakeholders

The intended audience includes HRD scholars, scholar-practitioners, and students interested in testing multilevel theories, conducting research using HLM, or those who are involved in reviewing/editing HLM research articles.

2c:T487, The Problem

Flexible work arrangements (FWAs) have long been heralded as antecedent to numerous positive organizational attitudes and outcomes. However, results on FWAs benefits are mixed which may be due to differences in employee characteristics. Not all individuals may desire such arrangements. This can confound group comparisons and may bias the results used in the development of human resource development (HRD) theory.

The Solution

Propensity score analysis is a statistical approach that utilizes covariates to match participants (e.g., FWAs vs. non-FWAs) on their likelihood of group assignment. Once matched, these differences are mitigated thus improving the ability to more precisely estimate program effects.

The Stakeholders

The intended audience for this article includes HRD scholars and scholar-practitioners interested in reducing non-equivalent group design bias in the context of flexible working arrangements and other HRD-related theory.

2d:T443, The Problem

Research syntheses are rarely used in the field of human resource development (HRD). There are notable exceptions, but our search of the related literature found relatively few instances where procedures like meta-analyses are used to advance theory and empirically informed practice.