Journal ArticleDOI
Common Method Bias in Regression Models With Linear, Quadratic, and Interaction Effects:
TLDR
In this article, the effects of common method variance (CMV) on parameter estimates in bivariate linear and multivariate linear, quadratic, and interaction regression models are analyzed. But the authors do not consider the effect of additional independent variables suffering from CMV.Abstract:
This research analyzes the effects of common method variance (CMV) on parameter estimates in bivariate linear, multivariate linear, quadratic, and interaction regression models. The authors demonstrate that CMV can either inflate or deflate bivariate linear relationships, depending on the degree of symmetry with which CMV affects the observed measures. With respect to multivariate linear relationships, they show that common method bias generally decreases when additional independent variables suffering from CMV are included in a regression equation. Finally, they demonstrate that quadratic and interaction effects cannot be artifacts of CMV. On the contrary, both quadratic and interaction terms can be severely deflated through CMV, making them more difficult to detect through statistical means.read more
Citations
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Journal ArticleDOI
Sources of Method Bias in Social Science Research and Recommendations on How to Control It
TL;DR: The meaning of the terms "method" and "method bias" are explored and whether method biases influence all measures equally are examined, and the evidence of the effects that method biases have on individual measures and on the covariation between different constructs is reviewed.
Journal ArticleDOI
Common Method Bias in Marketing: Causes, Mechanisms, and Procedural Remedies
TL;DR: This paper identifies a series of factors that may cause method bias by undermining the capabilities of the respondent, making the task of responding accurately more difficult, decreasing the motivation to respond accurately, and making it easier for respondents to satisfice.
Journal ArticleDOI
Drivers of consumer–brand identification
TL;DR: The concept of consumer-brand identification (CBI) is central to our understanding of how, when, and why brands help consumers articulate their identities as discussed by the authors, and it has been shown that consumers have stronger causal relationships with CBI when consumers have higher involvement with the brand's product category.
Journal ArticleDOI
Danger Zone Entrepreneurs: The Importance of Resilience and Self‐Efficacy for Entrepreneurial Intentions
TL;DR: The authors empirically examined the effects of perceived danger, entrepreneurial self-efficacy, and resilience on entrepreneurial intentions in adverse conditions with primary survey data from Afghanistan and found that perceived danger is negatively related to an individual's entrepreneurial intentions, but marginally less so among highly resilient individuals.
References
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Journal ArticleDOI
Common method biases in behavioral research: a critical review of the literature and recommended remedies.
TL;DR: The extent to which method biases influence behavioral research results is examined, potential sources of method biases are identified, the cognitive processes through which method bias influence responses to measures are discussed, the many different procedural and statistical techniques that can be used to control method biases is evaluated, and recommendations for how to select appropriate procedural and Statistical remedies are provided.
Book
Structural Equations with Latent Variables
TL;DR: The General Model, Part I: Latent Variable and Measurement Models Combined, Part II: Extensions, Part III: Extensions and Part IV: Confirmatory Factor Analysis as discussed by the authors.
Journal ArticleDOI
Convergent and discriminant validation by the multitrait-multimethod matrix.
TL;DR: This transmutability of the validation matrix argues for the comparisons within the heteromethod block as the most generally relevant validation data, and illustrates the potential interchangeability of trait and method components.
Journal ArticleDOI
Accounting for common method variance in cross-sectional research designs.
TL;DR: A model is presented that allows partial correlation analysis to adjust the observed correlations for CMV contamination and determine if conclusions about the statistical and practical significance of a predictor have been influenced by the presence of CMV.
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