Is everyone in agreement? An exploration of within-group agreement in employee perceptions of the work environment.

Klein, Katherine J.; Conn, Amy Buhl; Smith, Doug; Sorra, Joann

doi:10.1037/0021-9010.86.1.3

Cited by 437 publications

(440 citation statements)

References 43 publications

(74 reference statements)

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“…In addition, Schneider and Reichers (1983) attribute the emergence of collective constructs largely to the attractionselection-attrition (ASA) process, which predicts that individuals gravitate toward, are selected by, and remain in organizations composed of similar others. Despite these theoretical propositions, studies examining the impact of homogeneity on consensus have yielded mixed results (e.g., Klein et al, 2001;Naumann & Bennett, 2000;Roberson & Colquitt, 2005).…”

Section: Emergent Processesmentioning

confidence: 99%

“…In terms of structure, factors such as team size, HR practices, work interdependence, job routinization, and job formalization have been related to the emergence of unit-level constructs (Bowen & Ostroff, 2004;Colquitt et al, 2002;Klein et al, 2001;Zohar & Luria, 2005). These factors can influence and constrain the effects of other emergent processes and how the emergence takes shape (Kozlowski & Chao, in press;Morgeson & Hofmann, 1999).…”

Section: Emergent Processesmentioning

confidence: 99%

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Getting on the Same Page: How Leaders Build Trust Consensus in Teams and Its Consequences

Fulmer

2015

AMPROC

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Existing organizational research has demonstrated that team members' trust in leaders is positively related to a team's bottom-line outcomes. However, little is known about how collective trust in leaders develops among team members. To address this gap, the present study examines the effects of multiple emergent processes on the extent to which team members exhibit consensus in trust in their leader. In particular, it was proposed that the most important factors for the emergence, and the degree of consensus, of collective trust in leaders should have the same referent target as the collective construct (i.e., the leader) and concern behaviors that involve interactions between the leader and team members. Thus, the leader behavior and interactions variables of showing concern, leading by example, and monitoring were expected to exert stronger influence on the consensus in trust in leaders than leader attributes (ability and integrity) and team factors (open communication and demographic diversity). Further, the degree of consensus in trust in leaders was predicted to have both an independent and interaction effect with the mean level of trust in leaders in influencing team performance and voice behavior. Three waves of survey data were collected from teams with new leadership in a large academic military institution. Data from 719 team members from 105 teams were used to test these predictions by analyzing consensus concurrently and changes in consensus over time.The results generally supported the relative importance of leader showing concern and leading by example on the degree of consensus in trust in leaders in the concurrent model. For changes in consensus, leading by example was particularly important. In addition, while consensus was not independently related to the team performance and voice behaviors, it interacted with the mean level in influencing the outcomes in both the concurrent and change models. Taken together, the findings suggest that some leader behaviors are important for the development of collective trust or consensus in trust in leaders, and further suggest that consensus can act as a boundary condition for the effect of the mean level of trust in leaders on team outcomes. By focusing on the consensus in trust in leaders, this research begins to shed light on how consensus in trust develops among team members with respect to their leader and has implications for understanding trust, leadership, and emergence.

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Section: Emergent Processesmentioning

confidence: 99%

Section: Emergent Processesmentioning

confidence: 99%

Getting on the Same Page: How Leaders Build Trust Consensus in Teams and Its Consequences

Fulmer

2015

AMPROC

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“…(Designs 1 to 3 in Table 1) In two-level designs, it is possible to partition the variance of a variable in clustered data into two orthogonal latent components, the Between (cluster) component and the Within (cluster) component (Asparouhov & Muthén, 2006 Ordinary applications of multilevel modeling do not distinguish Between effects from Within effects and instead report a single mean slope estimate that combines the two (see, relatedly, Chan, 1998;Cheung & Au, 2005;Klein, Conn, Smith, & Sorra, 2001). This is an important issue for mediation researchers to consider; the use of slopes that combine Between and Within effects can easily lead to indirect effects that are biased relative to their true values, because the component paths may conflate effects that are relevant to mediation with effects that are not.…”

Section: First Limitation Of Mlm Framework For Multilevel Mediation: mentioning

confidence: 99%

A general multilevel SEM framework for assessing multilevel mediation.

Preacher

Zyphur

Zhang

2010

Psychological Methods

2,991

3,051

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Several methods for testing mediation hypotheses with 2-level nested data have been proposed by researchers using a multilevel modeling (MLM) paradigm. However, these MLM approaches do not accommodate mediation pathways with Level-2 outcomes and may produce conflated estimates of between-and within-level components of indirect effects. Moreover, these methods have each appeared in isolation, so a unified framework that integrates the existing methods, as well as new multilevel mediation models, is lacking. Here we show that a multilevel structural equation modeling (MSEM) paradigm can overcome these 2 limitations of mediation analysis with MLM. We present an integrative 2-level MSEM mathematical framework that subsumes new and existing multilevel mediation approaches as special cases. We use several applied examples and accompanying software code to illustrate the flexibility of this framework and to show that different substantive conclusions can be drawn using MSEM versus MLM. Researchers in behavioral, educational, and organizational research settings often are interested in testing mediation hypotheses with hierarchically clustered data. For example, Bacharach, Bamberger, and Doveh (2008) investigated the mediating role of distress in the relationship between the intensity of involvement in work-related incidents and problematic drinking behavior among firefighting personnel. They used data in which firefighters were nested within ladder companies and all three variables were assessed at the subject level. Using data from customer service engineers working in teams, Maynard, Mathieu, Marsh, and Ruddy (2007) found that team-level interpersonal processes mediate the relationship between team-level resistance to empowerment and individual job satisfaction. Both of these examples-and many others-involve data that vary both within and between higher level units. Traditional methods for assessing mediation (e.g., Baron & Kenny, 1986;MacKinnon, Lockwood, Hoffman, West, & Sheets, 2002;MacKinnon, Warsi, & Dwyer, 1995) are inappropriate in these multilevel settings, primarily because the assumption of independence of observations is violated when clustered data are used, leading to downwardly biased standard errors if ordinary regression is used. For this reason, several methods have been proposed for addressing mediation hypotheses when the data are hierarchically organized.These recommended procedures for testing multilevel mediation have been developed and framed almost exclusively within the standard multilevel modeling (MLM) paradigm (for thorough treatments of MLM, see Bryk, 2002, andSnijders &Bosker, 1999) and implemented with commercially available MLM software, such as SAS PROC MIXED, HLM, or MLwiN. For example, some authors have discussed models in which the independent variable X, mediator M, and dependent variable Y all are measured at Level 1 of a two-level hierarchy (a 1-1-1 design, adopting notation proposed by Krull & MacKinnon, 2001), 1 and slopes either are fixed (Pituch, Whittaker, & Stapleton, 2005...

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“…Con respecto a la última hipótesis ("El programa de intervención mejorará el clima laboral de los profesores"), ésta se confirma mediante los resultados obtenidos, siendo concordante con los planteamientos de Klein et al (2001), según quienes la comunicación y las repetidas interacciones sociales entre miembros de En definitiva, se concluye un impacto positivo del programa de intervención diseñado para profesores en base al entrenamiento en Habilidades Sociales y Psicología Positiva sobre las variables estudiadas (satisfacción vital, satisfacción laboral y clima organizacional) respecto a la no intervención, por ende, es posible señalar que la implementación del programa produce cambios favorables y significativos en profesores referente a las variables ya mencionadas, y que dichas variables no mejoran por si solas o por efecto alguna otra circunstancia como quedo demostrado en los resultados del grupo control o no intervenido.…”

Section: Ex Perimental Controlunclassified