Organizations are hierarchical in nature. Specifically, individuals in the workplace are entrenched in work groups, which are entrenched in departments, which are entrenched in organizations, which are in turn entrenched in the larger environment. Hence, hierarchical linear modeling (HLM) is a statistical technique available to researchers that is ideally suited for the study of such cross-level issues. The purpose of this article is to provide market researchers with an overview and detailed description of HLM as well as a practical illustration of its usage. The long-term aim of the Americans with Disabilities Act (ADA) is for publicly available services along a public street to be accessible to people with disabilities via a continuous, unobstructed pedestrian circulation network. Many countries believe in the underlying concept of the ADA and have implemented relevant laws. This study assumes that government policies will affect the “barrier-free sidewalk” environment, where government policies are at the organization level and the accessibility of sidewalks is at the individual level. As a result, a related law will not influence the in situ performance of sidewalks, and only the management of sidewalk plans and budgeting will have mediational effects. This means that laws have a long-term effect and the sidewalk accessibility assessment process will be modified. Those interested in the study of teams and cross-level research questions should find HLM advantageous in their research because of its ability to simultaneously investigate relationships within a particular hierarchy level, as well as relationships between or across hierarchical levels.

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