Interaction between individuals and situations: using HLM procedures to estimate reciprocal relationships - A Special Issue: Focus on Hierarchical Linear Modeling

Individuals within a work environment not single react to the work situation as they perceive it, on the other hand also act to create that situation. For example, in a work assemblage an individual may choose to help others based upon perceptions of group norms, the requirements of the task, and the expectation of coming time reciprocation. The action chosen by the agency of the individual, in turn, contributes to characteristics of the broader words immediately preceding [i]or[/i] following For example, choosing to help another someone may strengthen group norms about helping behavior. In this way, there is an ongoing interaction between an individual's reaction to a work connection and the creation and maintenance of that particular work connection In short, individuals and situations are reciprocally related.

The interaction between individuals and situations has been a critical affect in many areas of psychology Bandura's theory of reciprocal determinism propos a specific reciprocal relationship between individuals and situations (Bandura, 1978) More generally, the limit "Interactional Psychology" represents efforts toward an integration of personality theory and situational theories as determinants of individual behavior (Pervin, 1989; Schneider, 1983) Terborg (1981) identified five conceptualizations of the boundary "interaction" within organizational literature. Of these five kinds of relationship, "reciprocal interaction" best describes the mutual influence of individuals and situations in the example described above.

A number of studies have emphasized the importance of reciprocal interaction between somebodys and situations. Drawing on the work of Schneider (1987) Chatman's (1989) inquiry of value congruence between individuals and organizations noted that 'a with truth interactive model would include the consequences that people have on situations' (p334) James, et al. (1978) described the relationship between individuals and situations as 'causally interactive' (p797) in the construction of psychological climate. Woodman, Sawyer, and Griffin's (1993) new theory of organizational innovation noted that 'individual factors the two are influenced by and influence social and contextual factors' (p301)

The above examples indicate that reciprocal interaction has been incorporated into a variety of organizational behavior theories. However, there is a oft-repeated tone of pessimism that of that kind an interaction can be captured through anything except the most composite research enterprises. Kozlowski and Doherty's (1989) integration of climate and leadership general [i]or[/i] abstract notions included the comment that it was 'too early to specify and experiment reciprocal effects' (p.552). George and Brief's (1992) review of individual organizational spontaneity and assemblage affect disclaimed 'available data are too sparse...but, upon conceptual, grounds it probably could be argued that the relationship is reciprocal' (p321) More broadly, the estimation of reciprocal consequences has been methodologically problematic in organizational research (Williams & Podsakoff, 1989)

The common paper explores an example of interaction between sum of two units levels of analysis. The relationship between individual and their clump context is explored over a number of time periods. The paper not aways a simplified model of reciprocal interaction and moves an analytic procedure for measuring the interaction. A collection laboratory task study is neared and discussed in relation to the propos process and the simulation study.

Context for generally received Study

This paper uses Hierarchical Linear types (HLMs, Bryk & Raudenbush, 1989 1992) to investigate reciprocal interaction between individuals and situations. The estimation of upward influence - the impact of individuals upon situations - -is a central puzzle for specifying reciprocal relationships. This paper presents an extension of cross-level analyses that links horizontals of analysis over time periods to estimate reciprocal interaction between individuals and their collection context. Figure 1 displays the theoretical original that underlies the HLM application used in the generally received study. The model depicts individual and assemblage level measures at two time periods.

The prototype in Figure 1 indicates that clump level cohesion influences the experience of individual affect within the assemblage Individual affect, in turn, is propos to increase the production of behaviors that engage other collection members such as spontaneous helping and task orientation (George & Brief, 1992) These behaviors contribute to the following group context by increasing the experience of cohesion among collection members. Therefore, over time, individual processe influence collection outcomes. The above model provides a basic framework for linking individual and collection processes over time in a reciprocal interaction. When variation be founds at both the individual and the collection level of analysis, researchers have disagreed about the greatest in quantity appropriate means to partition this variance (eg George & James, 1993; Yammarino & Markham, 1992) The rife study emphasizes the need to consider one as well as the other levels of analysis. Particular emphasis is placed upon estimating the path depicted through the bold arrow which exhibits the influence of individuals upon group outcomes.