Competitive Reward Research Articles

DEVELOPING A COMPETITIVE REWARD SYSTEM TO ATTRACT QUALIFIED TEACHERS

The quality of education plays an important role in determining educational outcomes, as competent and dedicated educators are able to provide effective teaching, motivate students, and help them reach their full potential. However, in many countries, including Indonesia, there are still challenges in attracting and retaining quality educators. Therefore, it is important for educational institutions to formulate a reward system that is not only financially competitive, but also includes non-financial aspects that can improve the satisfaction and motivation of educators. This study employs a descriptive qualitative approach. Data collection was conducted through a literature review, focusing on relevant written sources such as books, journal articles, research reports, theses, and dissertations. Data analysis was conducted using triangulation to compare and confirm information from various sources, providing a more comprehensive and reliable understanding of the topic being studied. The results show that the development of a competitive reward system is critical to attracting quality educators, who are key to improving the quality of educational education. Education institutions can create an atmosphere that supports the improvement of teaching quality and education as a whole by implementing a balanced reward system and considering feedback from educators.

Cultivating a Joyful Workplace: The Power of Supportive Management, Competitive Rewards, Emotional Well-being, and Self-Esteem

Cultivating a Joyful Workplace: The Power of Supportive Management, Competitive Rewards, Emotional Well-being, and Self-Esteem

Impact of relative and absolute values on orienting attention in time.

Reward has been known to render the reward-associated stimulus more salient to block effective attentional orienting in space. However, whether and how reward influences goal-directed attention in time remains unclear. Here, we used a modified attentional cueing paradigm to explore the effect of reward on temporal attention, in which the valid targets were given a low monetary reward and invalid targets were given a high monetary reward. The results showed that the temporal cue validity effect was significantly smaller when the competitive reward structure was employed (Experiment 1), and we ruled out the possibility that the results were due to the practice effect (Experiment 2a) or a reward-promoting effect (Experiment 2b). When further strengthening the intensity of the reward from 1:10 to 1:100 (Experiment 3), we found a similar pattern of results to those in Experiment 1. These results suggest that reward information which was based on relative instead of absolute values can weaken, but not reverse, the orienting attention in time.

When competitive rewards create obsessions with bottom‐line outcomes: A social interdependence theory perspective of the mediating role of bottom‐line mentality

SummaryWe rely on social interdependence theory to examine bottom‐line mentality (BLM) as a motivational state that explains the effects of competitive rewards on oppositional actions in the forms of decreases in interpersonal organizational citizenship behavior (OCBI) and increases in social undermining. In line with social interdependence theory, we also examine learning goal orientation as a motivational attribute that can weaken these effects, suggesting that in comparison to employees low on learning goal orientation, employees high on the attribute are less likely to respond to their BLMs (that result from competitive rewards) with dysfunctional behaviors, because these employees will pursue their bottom‐line outcomes with an innate motivation to learn. We tested our hypotheses with three studies: an experimental study, a multisource, field study from a U.S. corporation, and a diverse, multisource, time‐lagged field study. Results from the experimental study and first field study revealed that BLM mediated the negative relationship between competitive rewards and OCBI; the second field study replicated these findings and demonstrated support for our full moderated mediation model. We provide theoretical and empirical support for the notion that BLM can serve as a motivational state that explains the effects of competition on workplace behaviors and learning goal orientation influences these effects.

Factors Associated with Nurses’ Intention to Leave in Saudi Arabia: A Literature Review

The nursing workforce represents a critical component of the healthcare system in Saudi Arabia, which is facing significant challenges related to retention and job satisfaction. High turnover rates among nurses not only compromise patient care quality but also place additional strain on the healthcare system. This study aims to investigate the factors associated with nurses' intention to leave their positions in Saudi Arabia, providing insights into the underlying causes of nursing turnover and suggesting potential strategies for retention. A comprehensive literature review was conducted, examining peer-reviewed articles, official reports, and relevant studies up to December 2023. The review focused on empirical research that specifically addressed the factors influencing nurses' intention to leave, including work environment, job satisfaction, leadership styles, recognition, societal norms, workload, opportunities for growth, work-life balance, and technological advancements. Quality assessment was performed using established checklists to ensure the reliability and validity of included studies. In this review, 28 quantitative studies met our inclusion criteria and were included in the final analysis. The findings revealed moderate levels of job satisfaction among nurses and a corresponding moderate intention to leave their current positions. Key factors influencing these outcomes included income level, nationality, work-life balance, and opportunities for professional development. Notably, a significant inverse relationship was observed between job satisfaction and the intention to leave, highlighting the importance of addressing these factors to enhance retention. Addressing nurses' intention to leave requires a multifaceted approach, focusing on improving work conditions, offering competitive rewards and recognition, fostering positive leadership and organizational culture, and providing opportunities for professional growth and work-life balance. Implementing targeted strategies that address these factors is essential for enhancing nurse retention, improving job satisfaction, and ensuring the provision of high-quality patient care in the healthcare sector of Saudi Arabia.

Enhancing urban metro system resilience under disruptive events through multi-agent reinforcement learning

With urban rail transit (URT) systems playing an increasingly crucial role in megacity mobility, the rising frequency of service disruptions may pose substantial passenger delays and safety concerns. This emphasizes the need to prioritize resilience enhancements for the URT system. Bus bridging, an effective resilience-enhancing measure, faces challenges that effectively capture the unique features of bridging buses and stranded passengers, and rely on predetermined routes and fixed frequencies, diminishing service flexibility and efficiency in dynamic bridging environments. To overcome these challenges, we propose a novel approach using a multi-agent reinforcement learning model. This model treats bus bridging as a collaborative multi-agent task with the competition. Specifically, it enables bridging buses to adaptively select the next visiting station based on environmental characteristics. Furthermore, a competitive reward function is introduced to facilitate effective collaboration among all agents while preventing malicious competition. The case study results demonstrate that the proposed enhancing resilience method outperforms traditional reinforcement learning method and classic bus bridging strategy and can reduce the average waiting time and average travel time, especially in resource-limited and complex scenarios.

Does artificial intelligence kill employment growth: the missing link of corporate AI posture.

An intense debate has been on-going about how artificial intelligence (AI) technology investments have an impact on employment. The debate has often focused on the potential of AI for human task automation, omitting the strategic incentive for firms to cooperate with their workers as to exploit AI technologies for the most relevant benefit of new product and service innovation. We calibrate an empirical probit regression model of how changes in employment relate to AI diffusion, based on formalizing a game-theoretical model of a firm exploiting the twin role of AI innovation and AI automation for both absolute and competitive advantage. The theoretical game-theory prediction is that employment following AI technology adoption is not negative, and ultimately depends on how AI leads to new success in innovation, competition which defines the competitive reward of innovation and profit sharing between workers and firms. Our estimation, is based on a global survey of 3,000 large companies across 10 countries, demonstrates that a firm employment growth depends on two strategic postures, that is, the firm relative maturity of AI adoption as well as its relative bias toward AI-based product innovation. The contribution of this research is to highlight the twin role of firm and workers in shaping how technology will affect employment. AI in particular marries the potential of task automation with even more potential for expansion.

A meta-analysis of determinants influencing bank employees’ satisfaction

Job satisfaction is an important factor in the success of any organization, and the banking industry is no exception. This study conducted a meta-analysis of 34 empirical studies to identify the key factors that influence job satisfaction among bank employees. The results showed that seven factors were most frequently cited as important: leadership, intrinsic motivation, reward, organizational commitment, work ethic, HRM activities, and working conditions. These factors were all found to have a positive impact on job satisfaction, with leadership having the strongest effect. The meta-analysis also found that the effect sizes of these factors were relatively large, indicating that they have a significant impact on job satisfaction. This suggests that banks can improve job satisfaction among their employees by focusing on these factors. For example, banks can provide employees with strong leadership, offer competitive rewards, and create a positive work environment. By doing so, banks can boost employee morale and productivity, which can lead to improved customer service and financial performance.

Cooperating in Innovation Contests: Effects and Boundary Conditions of Competitive Reward Structures

Cooperating in Innovation Contests: Effects and Boundary Conditions of Competitive Reward Structures

Optimising collective accuracy among rational individuals in sequential decision-making with competition

Theoretical results underpinning the wisdom of the crowd, such as the Condorcet Jury Theorem, point to substantial accuracy gains through aggregation of decisions or opinions, but the foundations of this theorem are routinely undermined in circumstances where individuals are able to adapt their own choices based after observing what other agents have chosen. In sequential decision-making, rational agents use the choices of others as a source of information about the correct decision, creating powerful correlations between different agents’ choices that violate the assumptions of independence on which the Condorcet Jury Theorem depends. In this paper, I show how such correlations emerge when agents are rewarded solely based on their individual accuracy, and the impact of this on collective accuracy. I then demonstrate how a simple competitive reward scheme, where agents’ rewards are greater if they correctly choose options that few have already chosen, can induce rational agents to make independent choices, returning the group to optimal levels of collective accuracy. I further show that this reward scheme is robust, offering improvements to collective accuracy across wide range of competition strengths, suggesting that such schemes could be effectively implemented in real-world contexts to improve collective wisdom.

RS Competition Rewards Sustainable Technology Innovators

RS Competition Rewards Sustainable Technology Innovators

Motivating the Motivationally Diverse Crowd: Social Value Orientation and Reward Structure in Crowd Idea Generation

ABSTRACT Some people contribute ideas for prosocial reasons in crowdsourcing; others do so for selfish reasons. Extending the theory of motivated information processing, the research posits that prosocial and proself individuals respond differently to reward structures in crowd idea generation. Two online experiments measured participants’ prosocial versus proself orientation and manipulated whether participants received a competitive or cooperative reward structure. Study 2 also manipulated whether participants viewed an original or a common peer idea. Proselfs produced more ideas when receiving competitive rewards; the idea generation of prosocials was not affected by the reward structure. This interaction effect was mediated by task effort and moderated the impact of peer ideas. Proselfs generated the most ideas when viewing an original peer idea and receiving competitive rewards; this effect was not observed for prosocials. The study contributes to crowdsourcing research by demonstrating that participants’ response to reward structures depends on their social value orientation. The implication is that crowdsourcing organizers should design tasks and rewards so they motivate participants with both prosocial and proself orientations.

Philosothons: Rewarding collaborative thinking

Competition, and its effect on educational environments, has been widely debated. On the one hand, it is argued that competition raises attainment and, on the other, it is said that whilst it may raise attainment for some, it exists at the expense of a supportive school environment. Should philosophy undertaken as a subject in schools, such as P4C, involve any level of competition if there is a chance of it raising performance? Scholars have argued that communities of inquiry within P4C conflict with the notion of competition, using competition as a contrast to cooperation, as competition implies that only certain voices will be heard and, without it, participation is more welcome and inclusive. Perhaps there is already too much competition in schools, in which case philosophy should be the one place students need not worry about competing with their peers and instead focus purely on collaboration. But what if the very skills that competition undermines are rewarded in a competition? While it stands that competition can silence particular voices and conflict with cooperation, I will argue that competition can avoid these outcomes and improve philosophical performance if such competition rewards collaboration and inquiry, therefore encouraging it.

Editorial

Editorial

Looking beyond person-specific cues indicative of credibility: Reward rules and executive function predict preschoolers’ acceptance of (un)reliable assertions

We tested whether 3- and 4-year-olds (N = 88) can deduce individuals’ credibility exclusively from situational cues such as game rules that reward competitive or cooperative behavior—and whether children’s inferences are predicted by their executive function (EF) and theory of mind (ToM) skills. When presented with the game rules, children endorsed a partner’s claims more often if the rules incentivized cooperation between participants and partners (e.g., by giving them prizes when trusting each other) versus when the rules incentivized deception (e.g., by giving prizes to partners who tricked the children). Notably, children’s appropriate responses to partners’ claims increased as their EF skills improved regardless of whether the rules supported trust or skepticism. ToM was not related to children’s rule-based selectivity. Preschoolers’ ability to make inferences based on cooperative versus competitive reward rules to determine whether the children’s partner can be trusted is key to learning from individuals whose reputation or past behavior is completely unknown. In addition, findings of associations between EF and vigilance about others’ claims contribute to the epistemological debate of whether people start in life as credulous learners.

Engaging Gen Z in professional selling: a systematic literature review

PurposeEmployee engagement literature pertaining to professional salespeople has revealed several antecedents and consequences that lead to greater performance and turnover reduction. However, engagement literature in the field of human resource development (HRD) does not account for Generation Z (Gen Z), the latest in the workforce who has been noted to be vastly different from previous generations. This study aims to explore how to engage Gen Z in the context of professional selling by identifying the antecedents and consequences of employee engagement based on individual characteristics and organizational needs of this group.Design/methodology/approachA systematic literature review was conducted. In total, 21 papers relevant to employee engagement, professional selling and Gen Z were critically analyzed.FindingsFindings indicate that Gen Z’s organizational need for mentoring and their individual characteristic of wanting job control and ownership are vital antecedents that could increase employee engagement. In addition, competitive rewards are important consequences that could improve individual sales performance.Practical implicationsHRD practitioners and organizational leaders must understand the unique characteristics of Gen Z to effectively engage them in the workplace. For sales organizations, there is a critical need to offer mentoring opportunities and competitive rewards from the start of Gen Z salespeople’s employment.Originality/valueThis research expands current engagement literature by addressing an emerging, under-explored issue – how to engage the newest workforce, Gen Z, in the context of professional selling.

Punishing Vices or Rewarding Virtues? The Motivations for and Benefits of Ethical Ratings for Private Italian Companies

In A Treatise on Virtues and Rewards, Dragonetti (1769) advances a theory of action based on rewards for virtues. The idea of rewards, especially of awards, relies on the hypothesis that intrinsic motivations drive the actions of good or virtuous citizens. We apply this theory to virtuous entrepreneurs who voluntarily adopt ethical principles as promoted by a recent Italian law. These firms receive an ethical rating (ER) by the Italian Competition Authority (ICA) and can access a set of economic and non-economic benefits (i.e. rewards). We survey a sample of 152 private companies with an ER and examine their views on the economic and social motivations and benefits as well as the perceived usefulness of the ER for improving ethical behaviour. An exploratory factor analysis detects four categories of motivation (economic, competitive, social, and responsiveness) and two categories of benefits (economic and competitive), which we use in regression models to test Dragonetti’s theory. Overall, respondents see the ER as an effective tool, except in terms of improving economic performance. We also find that entrepreneurs with lower economic and higher responsiveness motivations attain higher ERs. However, in the respondents’ opinions, the ER is (still) not producing any concrete benefits since we find no relationship between the ER and economic or competitive rewards. These findings have implications for the ICA as well as for private companies.

Reputation, Self-Esteem, and Competitive Rewards

In Rewarding in International Law, Anna van Aaken and Betül Simsek organize and refocus much of the existing literature on international cooperation and compliance highlighting the set of positive and negative tools available. In this essay, I extend the Rewarding framework, making some additional distinctions between the concepts, which both highlight the possibility of rewarding in international law and sketch the limits for such analysis. The first part differentiates rationalistic conceptions of reputation, on the one hand, and behavioral notions of self-esteem, on the other, as analytically distinct mechanisms for rewarding. By pulling these concepts apart, this essay emphasizes the different causal paths for influencing government actors and makes the case for an independent place for self-esteem in the Rewarding framework. In the second part, this essay questions whether rewards are always positive (and thus Pareto efficient) in light of third-party effects. Some rewards are competitive; a reward to one party is a relative punishment to third parties who are competitively disadvantaged by an exclusion from the reward. The incorporation of third-party analysis underscores the political limits of rewarding stemming from third-party resistance to rewarding or, alternatively, demands for additional rewards from third parties that can create capacity concerns for rewarding states.

Accelerating reinforcement learning with a Directional-Gaussian-Smoothing evolution strategy

<p style='text-indent:20px;'>The objective of reinforcement learning (RL) is to find an optimal strategy for solving a dynamical control problem. Evolution strategy (ES) has been shown great promise in many challenging reinforcement learning (RL) tasks, where the underlying dynamical system is only accessible as a black box such that adjoint methods cannot be used. However, existing ES methods have two limitations that hinder its applicability in RL. First, most existing methods rely on Monte Carlo based gradient estimators to generate search directions. Due to low accuracy of Monte Carlo estimators, the RL training suffers from slow convergence and requires more iterations to reach the optimal solution. Second, the landscape of the reward function can be deceptive and may contain many local maxima, causing ES algorithms to prematurely converge and be unable to explore other parts of the parameter space with potentially greater rewards. In this work, we employ a Directional Gaussian Smoothing Evolutionary Strategy (DGS-ES) to accelerate RL training, which is well-suited to address these two challenges with its ability to (i) provide gradient estimates with high accuracy, and (ii) find nonlocal search direction which lays stress on large-scale variation of the reward function and disregards local fluctuation. Through several benchmark RL tasks demonstrated herein, we show that the DGS-ES method is highly scalable, possesses superior wall-clock time, and achieves competitive reward scores to other popular policy gradient and ES approaches.</p>

Safe Optimal Design with Applications in Policy Learning

Motivated by practical needs in online experimentation and off-policy learning, we study the problem of safe optimal design, where we develop a data logging policy that efficiently explores while achieving competitive rewards with a baseline production policy. We first show, perhaps surprisingly, that a common practice of mixing the production policy with uniform exploration, despite being safe, is sub-optimal in maximizing information gain. Then we propose a safe optimal logging policy for the case when no side information about the actions’ expected rewards is available. We improve upon this design by considering side information and also extend both approaches to a large number of actions with a linear reward model. We analyze how our data logging policies impact errors in off-policy learning. Finally, we empirically validate the benefit of our designs by conducting extensive experiments.