University of Hartford

About: University of Hartford is a education organization based out in West Hartford, Connecticut, United States. It is known for research contribution in the topics: Population & Health care. The organization has 1244 authors who have published 2481 publications receiving 48973 citations. The organization is also known as: UHart.

Intrinsic motivation and extrinsic incentives jointly predict performance: A 40-year meta-analysis.

Abstract: More than 4 decades of research and 9 meta-analyses have focused on the undermining effect: namely, the debate over whether the provision of extrinsic incentives erodes intrinsic motivation. This review and meta-analysis builds on such previous reviews by focusing on the interrelationship among intrinsic motivation, extrinsic incentives, and performance, with reference to 2 moderators: performance type (quality vs. quantity) and incentive contingency (directly performance-salient vs. indirectly performance-salient), which have not been systematically reviewed to date. Based on random-effects meta-analytic methods, findings from school, work, and physical domains (k = 183, N = 212,468) indicate that intrinsic motivation is a medium to strong predictor of performance (ρ = .21-45). The importance of intrinsic motivation to performance remained in place whether incentives were presented. In addition, incentive salience influenced the predictive validity of intrinsic motivation for performance: In a "crowding out" fashion, intrinsic motivation was less important to performance when incentives were directly tied to performance and was more important when incentives were indirectly tied to performance. Considered simultaneously through meta-analytic regression, intrinsic motivation predicted more unique variance in quality of performance, whereas incentives were a better predictor of quantity of performance. With respect to performance, incentives and intrinsic motivation are not necessarily antagonistic and are best considered simultaneously. Future research should consider using nonperformance criteria (e.g., well-being, job satisfaction) as well as applying the percent-of-maximum-possible (POMP) method in meta-analyses.

A Meta-Analytic Review of the Consequences Associated with Work–Family Enrichment

Abstract: This study investigated the relationship between work-to-family enrichment (WFE) and family-to-work enrichment (FWE) with work-related, non work-related, and health-related consequences using meta-analysis. We conducted a meta-analytic review of 21 studies (54 correlations) for WFE and 25 studies (57 correlations) for FWE. We found that both WFE and FWE were positively related to job satisfaction, affective commitment, and family satisfaction but not turnover intentions. WFE was more strongly related to work-related variables, whereas FWE was more strongly related to non work-related variables. We also found that both WFE and FWE were positively related to physical and mental health. Additionally, relationships appear to depend on moderating variables including the proportion of women in the sample as well as the construct label (e.g., enrichment, facilitation, positive spillover). Our work indicates that organizations need to consider ways to not only reduce conflict, but also increase enrichment, which will drive many important outcome variables. This is the first meta-analysis on the positive side of the work–family interface.

State Infrastructure and Productive Performance

Abstract: The impact of public infrastructure investment on the productive performance of firms has been an important focus of the recent literature on productivity growth. The size of this impact has important implications for policymakers' decisions to invest in public capital, and productivity analysts' evaluation of productivity growth fluctuations and declines. However, detailed evaluation of the infrastructure impact is difficult using existing studies which rely on restricted models of firms' technology and behavior. In this paper we construct a more complete production theory model of firms' production and input decisions. We then apply our framework to state-level data on the output production and input (capital, nonproduction and production labor and energy) use of manufacturing firms to evaluate the contribution of infrastructure to firms' costs and productivity growth. We find that infrastructure investment does provide a significant direct benefit to manufacturing firms and thus augments productivity growth. We also show, however, that this evidence should be interpreted taking into account the social cost of such capital (which is not reflected in firms' costs), and the indirect impact resulting from scale effects.