Climate quality and climate consensus as mediators of the relationship between organizational antecedents and outcomes.

By Michael K. Lindell, Christina J. Brandt. Journal of Applied Psychology, 2000

596 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Social Psychology

View Paper: https://www.semanticscholar.org/paper/c6b40a54389492e2767ca6d32b24d2c9bf13a805

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In Management Science and Operations Research

In Social Psychology

Citations in the corpus

A New Look at the Corporate Social–Financial Performance Relationship (2013, background): “There have recently been studies of climate strength, which refers to the degree of dispersion in climate perceptions among a group (similar to our construct of consistency; Colquitt, Noe, & Jackson, 2002; Lindell & Brandt, 2000; Schneider, Salvaggio, & Subirats, 2002).”
Organizational climate, relative psychological climate and job satisfaction: The example of supportive leadership climate (2009, background): “This variance is now known as climate strength ( Lindell and Brandt, 2000”
Parsing organizational culture: How the norm for adaptability influences the relationship between culture consensus and financial performance in high-technology firms (2014, background): “They typically measure culture strength as the inverse of the variance (dispersion) in questionnaire responses about a specific norm across members (Lindell & Brandt, 2000; Schneider, Salvaggio, & Subirats, 2002).”
Measuring State, Effect, and Response Uncertainty: Theoretical Construct Development and Empirical Validation (2010, methodology): “This is a more stringent test than the Harman technique and involves the use of a marker-variable to assess the extent of method bias in self-report surveys (Lindell & Brandt, 2000; Lindell & Whitney, 2001).”
Increasing diversity as an HRM change strategy (2003, background): “Valence measures the direction of group members’ perceptions, akin to what Lindell and Brandt (2000) identify as climate quality.”
Does the Measure of Dispersion Matter in Multilevel Research? A Comparison of the Relative Performance of Dispersion Indexes (2007, methodology): “Accordingly, r*wg can be used as an index of agreement (see Lindell & Brandt, 2000), or disagreement.”
On the nature and importance of cultural tightness-looseness. (2006, background): “…can be tested by examining the relationship of societal culture measures with measures of climate and culture strength (e.g., standard deviation, variance, or average deviation indices; Gonzalez-Roma, Peiro, & Tordera, 2002; Lindell & Brandt, 2000; Schneider, Sal-vaggio, & Subirats, 2002).”
Statistical Remedies for Common Method Biases (2004, background): “2 分离出一个标签变量 Lindell 认为,如果一个变量在理论上不与任何其他变量相关,那么这个变量可以当作 “标签”,其他任何变量与它的相关都可以归因于共同方法偏差。将标签变量作为协变量, 并比较预测与效标变量的偏相关与其零阶相关的差异可以检验方法偏差的效应,更进一步, 将标签变量与研究中其他变量的平均相关分离出来,可以使研究者对方法偏差的效应实现控制([9,10])。”
Work value fit and turnover intention: same‐source or different‐source fit (2007, background): “This latter point-of-view can be best elucidated with theory that serves as a base for multilevel research ( Lindell and Brandt, 2000”
Common method bias in applied settings: The dilemma of researching in organizations (2020, background): “Temporal separation of the independent and dependent variables in the form of a longitudinal design (see Menard, 2008) is viewed particularly favourably in management research, and there is strong evidence that it reduces CMB (e.g. Lindell and Brandt, 2000).”
Linking leader behavior and leadership consensus to team performance: Integrating direct consensus and dispersion models of group composition (2011, background): “Within the leadership domain, the extent to which team members agree about the quality of their managers’ leadership behavior has been dubbed leadership consensus (Feinberg, Ostroff, & Burke 2005; see also Lindell & Brandt 2000).”
LEVEL AND DISPERSION OF SATISFACTION IN TEAMS: USING FOCI AND SOCIAL CONTEXT TO EXPLAIN THE SATISFACTION-ABSENTEEISM RELATIONSHIP (2007, background): “…properties were changed in such a way that (1) X and Z were normally distributed and completely uncorrelated and (2) X was normally distributed, with Z a symmetrical inverse U-shaped function of X, reflecting the theoretical relationship between mean and standard deviation (Lindell & Brandt, 2000).”