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Work-life flexibility policies (e.g., flextime, telework, part-time, right-to-disconnect, and leaves) are increasingly important to employers as productivity and well-being strategies. However, policies have not lived up to their potential. In this chapter, the authors argue for increased research attention to implementation and work-life intersectionality considerations influencing effectiveness. Drawing on a typology that conceptualizes flexibility policies as offering employees control across five dimensions of the work role boundary (temporal, spatial, size, permeability, and continuity), the authors develop a model identifying the multilevel moderators and mechanisms of boundary control shaping relationships between using flexibility and work and home performance. Next, the authors review this model with an intersectional lens. The authors direct scholars’ attention to growing workforce diversity and increased variation in flexibility policy experiences, particularly for individuals with higher work-life intersectionality, which is defined as having multiple intersecting identities (e.g., gender, caregiving, and race), that are stigmatized, and link to having less access to and/or benefits from societal resources to support managing the work-life interface in a social context. Such an intersectional focus would address the important need to shift work-life and flexibility research from variable to person-centered approaches. The authors identify six research considerations on work-life intersectionality in order to illuminate how traditionally assumed work-life relationships need to be revisited to address growing variation in: access, needs, and preferences for work-life flexibility; work and nonwork experiences; and benefits from using flexibility policies. The authors hope that this chapter will spur a conversation on how the work-life interface and flexibility policy processes and outcomes may increasingly differ for individuals with higher work-life intersectionality compared to those with lower work-life intersectionality in the context of organizational and social systems that may perpetuate growing work-life and job inequality.

This paper aims to examine the interconnectedness between stakeholder expectations (SE), inter-organizational coordination (IOC) and procurement practices within humanitarian organizations (HOs) based in Uganda.

Employing a quantitative cross-sectional design, data were gathered from 43 HOs and analyzed using SmartPLS 4.0.8.3. Variance-based structural equation models (VB-SEMs) were employed to examine both direct and indirect effects.

The findings show a significantly positive relationship between SE, IOC and procurement practices. Additionally, the mediating role of IOC in the relationship between SE and procurement practices is evident.

While this study offers insights into procurement practices in HOs, the use of a quantitative approach might limit capturing dynamic changes over time. Future research could benefit from a nuanced approach involving interviews and longitudinal studies to uncover incremental changes.

During relief management, HOs need to understand their SE through information sharing and capacity building. This understanding can aid in selecting procurement practices that align with SE and ensure the delivery of relief.

Leveraging stakeholder theory, this research contributes to the understanding of how SE and IOC influence the adoption of procurement practices in HOs during relief delivery.

People seem to function according to different models, which implies that in business and social sciences, heterogeneity is a rule rather than an exception. Researchers can investigate such heterogeneity through multigroup analysis (MGA). In the context of partial least squares path modeling (PLS-PM), MGA is currently applied to perform multiple comparisons of parameters across groups. However, this approach has significant drawbacks: first, the whole model is not considered when comparing groups, and second, the family-wise error rate is higher than the predefined significance level when the groups are indeed homogenous, leading to incorrect conclusions. Against this background, the purpose of this paper is to present and validate new MGA tests, which are applicable in the context of PLS-PM, and to compare their efficacy to existing approaches.

The authors propose two tests that adopt the squared Euclidean distance and the geodesic distance to compare the model-implied indicator correlation matrix across groups. The authors employ permutation to obtain the corresponding reference distribution to draw statistical inference about group differences. A Monte Carlo simulation provides insights into the sensitivity and specificity of both permutation tests and their performance, in comparison to existing approaches.

Both proposed tests provide a considerable degree of statistical power. However, the test based on the geodesic distance outperforms the test based on the squared Euclidean distance in this regard. Moreover, both proposed tests lead to rejection rates close to the predefined significance level in the case of no group differences. Hence, our proposed tests are more reliable than an uncontrolled repeated comparison approach.

Current guidelines on MGA in the context of PLS-PM should be extended by applying the proposed tests in an early phase of the analysis. Beyond our initial insights, more research is required to assess the performance of the proposed tests in different situations.

This paper contributes to the existing PLS-PM literature by proposing two new tests to assess multigroup differences. For the first time, this allows researchers to statistically compare a whole model across groups by applying a single statistical test.

Research serves to elucidate and tackle real-world issues (e.g. capitalizing opportunities and solving problems). Critical to research is the concept of validity, which gauges the extent to which research is adequate and appropriate in representing what it intends to measure and test. In this vein, this article aims to present a typology of validity to aid researchers in this endeavor.

Employing a synthesis approach informed by the 3Es of expertise, experience, and exposure, this article maintains a sharp focus on delineating the concept of validity and presenting its typology.

This article emphasizes the importance of validity and explains how and when different types of validity can be established. First and foremost, content validity and face validity are prerequisites assessed before data collection, whereas convergent validity and discriminant validity come into play during the evaluation of the measurement model post-data collection, while nomological validity and predictive validity are crucial in the evaluation of the structural model following the evaluation of the measurement model. Additionally, content, face, convergent and discriminant validity contribute to construct validity as they pertain to concept(s), while nomological and predictive validity contribute to criterion validity as they relate to relationship(s). Last but not least, content and face validity are established by humans, thereby contributing to the assessment of substantive significance, whereas convergent, discriminant, nomological and predictive validity are established by statistics, thereby contributing to the assessment of statistical significance.

This article contributes to a deeper understanding of validity’s multifaceted nature in research, providing a practical guide for its application across various research stages.

Crises such as the Coronavirus pandemic pose extraordinary challenges to the decision making in management teams. Teams need to integrate available information quickly to make informed decisions on the spot and update their decisions as new information becomes available. Moreover, making good decisions is hard as it requires sacrifices for the common good, and finally, implementing the decisions made is not easy as it requires persistence in the face of strong counterproductive social pressures.

We provide a “psychology of action” perspective on making team-based management decisions in crisis by introducing collective implementation intentions (We-if-then plans) as a theory-based intervention tool to improve decision processes. We discuss our program of research on forming and acting on We-if-then plans in ad hoc teams facing challenging situations.

Teams with We-if-then plans consistently made more informed decisions when information was socially or temporally distributed, when decision makers had to make sacrifices for the common good, and when strong social pressures opposed acting on their decisions. Preliminary experimental evidence indicates that assigning simple We-if-then plans had similar positive effects as providing a leader to steer team processes.

Our analysis of self-regulated team decisions helps understand and improve how management teams can make and act on good decisions in crises such as the Coronavirus pandemic.