Using a second-order latent variable approach with 3,570 participants across 49 organizations, the current study examined the impact of high involvement work processes upon organizational effectiveness. Using a structural model of higher order influences, and taking into consideration mixed-level effects, the analyses supported a model in which a collection of organizational practices positively influenced high involvement work processes. In turn, the high involvement processes influenced organizational effectiveness (defined through return on equity [ROE] and turnover) both directly and indirectly through positive influence on employee morale. The implications of these findings for expanding this perspective of high involvement are presented as well as issues needing immediate attention in the research literature.

This paper presents an initial test and validation of a model of healthy work organization. A questionnaire based on the proposed model was completed by 1,130 employees of a national retailer. The instrument measured 29 first-order constructs underlying the six higher-order domains of the model. The overall model fit and relationships among the second-order factors were examined using AMOS structural equation-modelling procedures. The structural analyses presented here support the proposed model. An acceptable overall fit was demonstrated, and all second-order, and second-to first-order, relationships were significant. Employees' perceptions of their organization affect their perception of the climate, which impacts the way people relate to their job and see their future in the organization, ultimately impacting their work adjustment, health and well-being. This model has implications for both research and practice.

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.

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.

We propose linkages among human resource (HR) systems, relational climates, and employee helping behavior. We suggest that HR systems promote relational climates varying in terms of the motivation and sustenance of helping behavior, and we expect HR systems to indirectly influence the nature of relationships and the character of helping within organizations. By considering HR systems and their respective relational climates together, researchers can gain a better understanding of expectations and dynamics surrounding helping behavior.