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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.

The process approach to multi-level organizational behavior is based on the assumption that multi-level organizational behavior is processual in nature. This article defines group and organizational processes and their representation as process frameworks. Both functional and inclusional classes of levels exist, each of which has at least five categories of levels. All ten categories are special cases of process frameworks. This article provides examples of each category level, which it uses to illustrate new models of organizational work, extended models of interdependence, a new typology of theories based on their levels of processes, and a new tool for survey research called knobby analyses. After explaining the basic idea of knobby analysis, the article briefly describes the processual theory of the organizational hologram, the use of linear programming, and causal-chain analysis to provide multi-level explanations of employee opinion data. These ideas are embodied in conducting a strategic organizational diagnosis, which is the first stage of organizational design. Organizational design encompasses multiple stages, each of which itself involves multiple, multi-level phenomena and analyses. The basic point is that the processual nature of multi-level organizational phenomena gives more hope for improvements in theory building and their application if one uses the process approach rather than a variable approach.

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.

Sport participation is not exclusively determined by individual socio‐demographic factors (micro level) since infrastructure factors such as the availability of sport facilities and sport programmes (macro level) can also play a role in this regard. The purpose of this paper is to provide evidence for these determinants of sport participation using multi‐level analyses.

A survey among the resident population in the city of Munich was carried out in 2008 (n=11,715). Furthermore, secondary data on the available sport infrastructure in every urban district of Munich (n=25) were collected. Multi‐level analyses were conducted to find the micro and macro level determinants of sport participation.

The results show that aside from micro level factors, the availability of swimming pools and parks is especially important for residents’ sport activity. Moreover, sport activity in non‐profit sport clubs can be enhanced by both a good supply of sport programmes offered by sport clubs as well as a poor supply of programmes from commercial sport providers and the municipality.

Multi‐level analyses can be recommended for future research on sport participation. The use of GIS data would be fruitful in this regard.

It can be recommended that municipalities invest in the construction of swimming pools and parks.

The paper shows that multi‐level analyses are a relatively new method of analysis for research on sport participation and that they represent the most suitable approach for analysing multi‐level data.

This paper aims to explore the impact of a recent earthquake activity on house prices and their spatial distribution in the Istanbul housing market.

The paper uses a multi-level approach within an event study framework to model changes in the pattern of house prices in Istanbul. The model allows the isolation of the effects of earthquake risk and explores the differential impact in different submarkets in two study periods – one before (2007) and one after (2012) recent earthquake activity in the Van region, which although in Eastern Turkey served to alter the perceptions of risk through the wider geographic region.

The analysis shows that there are variations in the size of price discounts in submarkets resulting from the differential influence of a recent earthquake activity on perceived risk of damage. The model results show that the spatial impacts of these changes are not transmitted evenly across the study area. Rather it is clear that submarkets at the cheaper end of the market have proportionately larger negative impacts on real estate values.

The robustness of the models would be enhanced by the addition of further spatial levels and larger data sets.

The methods introduced in this study can be used by real estate agents, valuers and insurance companies to help them more accurately assess the likely impacts of changes in the perceived risk of earthquake activity (or other environmental events such as flooding) on the formation of house prices in different market segments.

The application of these methods is intended to inform a fairer approach to setting insurance premiums and a better basis for determining policy interventions and public investment designed to mitigate potential earthquake risk.

The paper represents an attempt to develop a novel extension of the standard use of hedonic models in event studies to investigate the impact of natural disasters on real estate values. The value of the approach is that it is able to better capture the granularity of the spatial effects of environmental events than the standard approach.

“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.

The purpose of this paper is to develop and test a multi-level healthcare service quality (HSQ) model in Jakarta, Indonesia.

The research used a quantitative research method. Data were collected via a survey with questionnaire. The respondents are 154 patients of a healthcare institution in Jakarta, Indonesia.

The research result shows a multi-level HSQ model. The HSQ model consists of three primary dimensions, namely, healthcare service outcome, healthcare service interaction, and healthcare service environment. Healthcare service outcome has three subdimensions, i.e. waiting time, medicine, and effectiveness. Healthcare service interaction has three dimensions, namely, soft interaction, medical personnel expertise, and hard interaction. Healthcare service environment has two dimensions, which are equipment condition and ambient condition.

This research was only conducted in one healthcare institution in Jakarta, Indonesia. The data collection using convenience sampling method as well as the use of small sample size caused the limitation of the research results in representing across the customer of the healthcare institution. This study can be replicated with larger sample size and involving more healthcare institutions in order to examine the stability of the HSQ model.

Healthcare institution’s managers can use the HSQ model to monitor, measure, and improve their service quality.

There is a lack of research that develops and tests HSQ model based on multi-level approach in the context of developing country. This paper has fulfilled the gap.

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.

The Moldoveanu, Baum & Rowley approach highlights the importance of developing a multi-level theory of network evolution that explicitly accounts for strategic agency and (bounded) rationality. I discuss intriguing questions raised by their model about structure vs. topology, feedback loops in evolution, and network resources other than information.