Hettie A. Richardson

A Tale of Three Perspectives: Examining Post Hoc Statistical Techniques for Detection and Correction of Common Method Variance

Many researchers who use same-source data face concerns about common method variance (CMV). Although post hoc statistical detection and correction techniques for CMV have been proposed, there is a lack of empirical evidence regarding their efficacy. Because of disagreement among scholars regarding the likelihood and nature of CMV in self-report data, the current study evaluates three post hoc strategies and the strategy of doing nothing within three sets of assumptions about CMV: that CMV does not exist, that CMV exists and has equal effects across constructs, and that CMV exists and has unequal effects across constructs. The implications of using each strategy within each of the three assumptions are examined empirically using 691,200 simulated data sets varying factors such as the amount of true variance and the amount and nature of CMV modeled. Based on analyses of these data, potential benefits and likely risks of using the different techniques are detailed.

Does Decentralization Make a Difference for the Organization? An Examination of the Boundary Conditions Circumbscribing Decentralized Decision-Making and Organizational Financial Performance

Recently, there has been increased interest in the organizational gains that can be achieved by decentralizing decision-making authority to lower level employees. Yet, literature examining the relationship of decentralization to organizational performance is both scarce and equivocal. The current study examines decentralization’s influence on financial performance in a sample of behavioral healthcare treatment centers. As expected, the decentralization-financial performance relationship is moderated by key organizational characteristics. Implications of the findings are presented.

Marker Variable Choice, Reporting, and Interpretation in the Detection of Common Method Variance: A Review and Demonstration

This article investigates in two ways the use and reporting of marker variables to detect common method variance (CMV) in organizational research. First, a review of 398 empirical articles and 41 unpublished dissertations that employ marker variables indicates that authors are not reporting adequate information regarding marker variable choice and use, are choosing inappropriate marker variables, and are possibly making errors in their assessment of CMV effects. Second, two data sets are presented that investigate the properties of six prospective markers to assess the degree to which they capture specific, measurable causes of CMV and the conclusions these markers produce when applied to substantive relationships. Results from the review and empirical investigation are used to expand the set of conditions scholars should consider when determining whether to employ a marker technique over other alternatives for detecting and controlling CMV and how best to do so.

Perceived organizational support's role in stressor‐strain relationships

Purpose – The purpose of this study is to examine when perceived organizational support (POS) may be more likely to play a mediator versus moderator role in stressor and strain relationships by considering POS relative to challenge and hindrance stressors, cognitive/emotional and physical strains.Design/methodology/approach – This cross‐sectional survey research was conducted in two samples (n=720, 829) of employees working for a large retail organization in the USA. Hypotheses were tested using structural equation modeling.Findings – As hypothesized, results indicate POS mediates relationships between hindrance stressors and cognitive/emotional strains, but does not mediate relationships between challenge stressors and physical strains. POS does not moderate any of the relationships examined.Originality/value – This paper is one of few studies to examine challenge and hindrance stressors and to examine POS relative to physical strains.

A New Perspective on Method Variance: A Measure-Centric Approach

A widespread methodological concern in the organizational literature is the possibility that observed results are due to the influence of common-method variance or mono-method bias. This concern is based on a conception of method variance as being produced by the nature of the method itself, and therefore, variables assessed with the same method would share common-method variance that inflates observed correlations. In this paper, we argue for a more complex view of method variance that consists of multiple sources that affect each measured variable in a potentially unique way. Shared sources among measures (common-method variance) act to inflate correlations, whereas unshared sources (uncommon-method variance) act to attenuate correlations. Two empirical examples, one from a simulation study and the other from a single-source survey, are presented to illustrate the complex action of multiple sources of method variance. A five-step approach is suggested whereby a theory of the measure is generated for each measured variable that would inform strategies to control for method variance by assessing and modeling the actions of identified method variance sources.