A Parent-Led Contingent Reward Desensitization Intervention for Children With a Feeding Problem Resulting From Sensory Defensiveness

We meta-analytically examine the relationships between three forms of leader influence, contingent reward (transactional), leader-member exchange (LMX; relational), and transformational (change-oriented) on subordinates’ proactive behaviors. Using non-self-reported data from a combined sample of more than 9,000 employees, we confirm positive relationships between leader influences and employee proactive outcomes. We examine the extent to which one leadership influence is stronger than the others in promoting subordinate proactivity. By combining our new meta-analytic data with existing meta-analytic correlations, we further investigate the extent to which various leadership predictors are differentially related to proactive and prosocial contextual performance, and to task performance. For all outcomes, there are only minimal differences between the contingent reward, LMX, and transformational leadership predictors. Using our results, we propose future research directions for the relationship between leader influences and subordinate work effectiveness.

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Prospect of performance-contingent reward distorts the action relevance of predictive context information.

Journal of Experimental Psychology Learning Memory and Cognition ◽

10.1037/xlm0000727 ◽

2020 ◽

Vol 46 (2) ◽

pp. 380-399 ◽

Cited By ~ 1

Author(s):

Carmen Hefer ◽

Gesine Dreisbach

Keyword(s):

Context Information ◽

Contingent Reward

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Supplemental Material for How Performance-Contingent Reward Prospect Modulates Cognitive Control: Increased Cue Maintenance at the Cost of Decreased Flexibility

Journal of Experimental Psychology Learning Memory and Cognition ◽

10.1037/xlm0000397.supp ◽

2017 ◽

Keyword(s):

Cognitive Control ◽

Contingent Reward ◽

The Cost

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Exploring the application of machine learning to the assembly line feeding problem

Operations Management Research ◽

10.1007/s12063-021-00201-3 ◽

2021 ◽

Author(s):

Moretti Emilio ◽

Tappia Elena ◽

Limère Veronique ◽

Melacini Marco

Keyword(s):

Machine Learning ◽

Assembly Line ◽

Optimal Solution ◽

Product Variety ◽

Supervised Machine Learning ◽

Assembly System ◽

Optimization Approach ◽

Feeding Problem ◽

Managerial Implications ◽

Multiple Feeding

AbstractAs a large number of companies are resorting to increased product variety and customization, a growing attention is being put on the design and management of part feeding systems. Recent works have proved the effectiveness of hybrid feeding policies, which consist in using multiple feeding policies in the same assembly system. In this context, the assembly line feeding problem (ALFP) refers to the selection of a suitable feeding policy for each part. In literature, the ALFP is addressed either by developing optimization models or by categorizing the parts and assigning these categories to policies based on some characteristics of both the parts and the assembly system. This paper presents a new approach for selecting a suitable feeding policy for each part, based on supervised machine learning. The developed approach is applied to an industrial case and its performance is compared with the one resulting from an optimization approach. The application to the industrial case allows deepening the existing trade-off between efficiency (i.e., amount of data to be collected and dedicated resources) and quality of the ALFP solution (i.e., closeness to the optimal solution), discussing the managerial implications of different ALFP solution approaches and showing the potential value stemming from machine learning application.

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In the Eye of the Beholder: How Self-Other Agreements Influence Leadership Training Outcomes as Perceived by Leaders and Their Followers

Journal of Business and Psychology ◽

10.1007/s10869-020-09730-3 ◽

2021 ◽

Author(s):

Karina Nielsen ◽

Susanne Tafvelin ◽

Ulrica von Thiele Schwarz ◽

Henna Hasson

Keyword(s):

Transformational Leadership ◽

Leadership Styles ◽

Leadership Training ◽

Leadership Behaviors ◽

Forest Industry ◽

Training Outcomes ◽

Contingent Reward ◽

Leaders And Followers ◽

A Prospective Study ◽

Prospective Study Design

AbstractBased on Yammarino and Atwater’s self-other agreement typology of leaders, we explored whether leaders’ and followers’ agreement influenced their ratings of leadership behaviors after training where leaders received multi-source feedback to stimulate behavior change. We used a prospective study design including 68 leaders and 237 followers from a Swedish forest industry company. Leaders underwent training to increase their transformational leadership and contingent reward styles and reduce management-by-exception passive and laissez-faire leadership. We found that self-other agreement influences followers and leaders reporting changes in leadership styles. We also found that although some leader types were perceived to improve their leadership behaviors, leaders and followers reported differential patterns in which types of leaders improved the most. Our results have important implications for how feedback should be used to support training to achieve changes in leadership styles.

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