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This study aims to investigate the factors that lead to the failure of some rewards to induce knowledge sharing behavior among employees, with much focus on employees’ attitudes and leadership’s knowledge of employees’ preferences, and presents a model that depicts the linkages.

To investigate why the provision of some rewards fails to induce knowledge sharing behavior among employees, this study uses the preferred reporting items for systematic reviews and meta-analyses framework to identify and analyze 56 articles published from 2000 to 2021.

Knowledge sharing is positively linked to organizational performance. Further, employees’ negative attitudes toward a reward system negatively relate to knowledge sharing behavior. Furthermore, management’s lack of knowledge of employees’ preferences regarding rewards leads to the provision of incorrect rewards that do not enhance knowledge sharing behavior. Finally, a conceptual model depicting the linkages among the variables under consideration has been presented.

Through the present study, employees’ attitudes toward rewards and leadership’s knowledge of employees’ preferences have been presented as critical factors that can lead to the failure of some rewards to induce knowledge sharing behavior. Further, the conceptual framework that can guide managers and leaders in strategizing on how best to develop and implement correct reward systems has been presented.

The present study is a significant contribution to the literature by focusing on the negative side of rewards toward knowledge sharing behavior with a focus on employees’ attitudes and leadership’s awareness of employees’ preferences regarding rewards.

This study aims to investigate the situational factors that intensify the impact of leader bottom-line mentality (BLM) on employee pro-self-unethical behavior. In particular, the moderating role of contingent rewards and punishments is evaluated under the lens of situational strength theory.

Data were collected from 218 full-time employees working in the USA in a time-lagged study and analyzed using SPSS Process Macro.

Statistical analysis reveal contingent rewards and punishments significantly moderate the positive relationship between BLM and pro-self-unethical behavior.

This paper highlights the need for more balanced reward systems that incorporate moral conduct into work performance. It also emphasizes the role of robust accountability and monitoring systems in minimizing employees’ unethical behavior.

To the best of the authors’ knowledge, this is the first study to investigate the moderating role of contingent rewards and punishments on the relationship between leader BLM and subordinate pro-self-unethical behavior. Moreover, it provides significant empirical support to situational strength theory.

This paper aims to develop and validate a scale to measure knowledge-sharing motives at work. It is aimed to construct a scale which is explicitly different from knowledge-sharing behavior and to develop a comprehensive and domain-specific scale for this special kind of work motivation.

The constructed scale was tested in two studies. Survey data (n = 355) were used to perform an exploratory factor analysis. Results were further tested on survey data from the core public sector (n = 314) and the health sector (n = 315). A confirmatory factor analysis confirms the results in both samples. The developed scale was further validated internally and externally.

The analysis underlines that knowledge-sharing motivation and knowledge-sharing behavior are different constructs. The data suggest three dimensions of knowledge-sharing motives: appreciation, growth and altruism and tangible rewards. While it is suggested that the developed scale works in the public as well as the private sector context, it is found that knowledge sharing of public employees is merely driven by “growth and altruism” and “appreciation of coworkers.”

No comprehensive and reproducible scale to measure knowledge-sharing motives, which is different from behavior and domain-specific as well, was available in the literature. Therefore, such a scale has been constructed in this study. Furthermore, this study uses samples from different organizational sectors to deepen the understanding of knowledge sharing in context.

Online retailers are pioneering the incentivization of customers to generate more product reviews by rewarding them. However, little is known about the impact of reward types on customers' review behavior, including review frequency and sentiment. To address this gap, we investigated the effects of different reward types on customers' review behavior and how these rewards influence customers' review behavior.

We collected secondary data and empirically tested the hypothesis by analyzing the change in reward policy. Regression and two-stage Heckman models were applied to investigate the effects, with the latter used to control potential selection issues.

The results revealed that monetary rewards can stimulate customers to generate more positive product reviews. Furthermore, the reward amount has a negative moderating effect on the aforementioned relationship. Additionally, customer tenure negatively moderates the relationship between monetary rewards and review behavior.

This study contributes to the understanding of user-generated content motivation and provides managerial implications for reward programs.

This study aims to examine the influence of reward personalization on financing outcomes in the Industry 5.0 era, where reward-based crowdfunding meets the personalized needs of individuals.

The study utilizes a corpus of 218,822 crowdfunding projects and 1,276,786 reward options on Kickstarter to investigate the effect of reward personalization on investors’ willingness to participate in crowdfunding. The research draws on expectancy theory and employs quantitative and qualitative approaches to measure reward personalization. Quantitatively, the number of reward options is calculated by frequency; whereas text-mining techniques are implemented qualitatively to extract novelty, which serves as a proxy for innovation.

Findings indicate that reward personalization has an inverted U-shaped effect on investors’ willingness to participate, with investors in life-related projects having a stronger need for reward personalization than those interested in art-related projects. The pledge goal and reward text readability have an inverted U-shaped moderating effect on reward personalization from the perspective of reward expectations and reward instrumentality.

This study refines the application of expectancy theory to online financing, providing theoretical insight and practical guidance for crowdfunding platforms and financiers seeking to promote sustainable development through personalized innovation.

The purpose of this paper is to study the relationship between trait self-control (TSC) and emotional exhaustion, and to examine the mediating role of effort–reward imbalance (ERI) and emotional demands.

A quantitative study was conducted using data from 441 employees working in different organizations in the information technology sector in India. PROCESS macro with a bootstrap sample size of 5,000 was used for mediation analysis.

TSC demonstrated a significant negative relationship with emotional exhaustion. Results indicated the crucial role played by ERI and emotional demands in influencing the emotional exhaustion of employees with higher TSC.

This study adds substantially to our knowledge of the role of TSC in employee experiences of emotional exhaustion. Results suggest how employees’ ERI perceptions and experiences of emotional demands determine whether higher TSC would reduce experiences of exhaustion. This adds to the knowledge of positive outcomes of self-control while throwing some light on why the use of self-control does not always incur a psychological cost, as suggested by some studies. The findings suggest that self-control is an individual resource that has the ability to alleviate emotional exhaustion through its influence on employees‘ effort–reward perceptions and experiences of emotional demands.

The main goal of this study is to determine the role of employee commitment in the relations between the compensation system and turnover intentions of employees in the Republic of Serbia, as well as to investigate whether there is a mediating effect of employee commitment in this relation.

The primary methodology implemented in the research was data gathering, obtaining theoretical research works on the proposed relations and empirical studies based on the PLS-SEM, analysed by IBM SPSS Statistics and SmartPLS data processing software. The data for the analysis was obtained from a total sample of 764 employees, collected in the Republic of Serbia via an online questionnaire.

The results indicated a positive statistically significant relationship between the formative construct (compensation system) and reflective construct (commitment), as well as a negative statistically significant relationship between the compensation system and reflective construct (turnover intentions). Employee commitment partially mediates the relationship between the compensation system and turnover intentions of employees.

The study was conducted in Serbia and is thus rooted in the specific national context which is characterized by high power distance and high uncertainty avoidance and more collectivistic society with feminine values more expressed. Most of the previous investigations related to the mentioned constructs were performed in companies from more developed countries, including Western Europe and the United States of America, whereas there has been no such research conducted in Serbia to date. The results portrayed a mismatch between the expected relations regarding the attitudes of employees to the rewards and the proposed national context. Modern companies in Serbia need to follow a modern reward mechanism to build stronger commitment and decrease turnover intentions. Moreover, in most earlier research works, compensation was examined in terms of satisfaction with rewards, while this study was based on questions related to perceptions of employees toward HR compensation practices (“The organization offers me”-type questions), not related to their satisfaction. Further, in the majority of previous research works, the compensation system was examined as a variable in combination with other HR processes (staffing, training and development, career development, employee relations, HR planning, communication, etc.), as a HPWP, while in this case the authors used only the practice of compensation (reward elements and employee performance evaluation) to investigate relations with commitment and turnover intentions.

The goal of this study is to investigate the mediating effect of referral rewards on consumer willingness to recommend poverty-alleviating products and to identify the most effective referral rewards for incentivizing consumers to recommend poverty-alleviating products.

Tournament rewards and piece-rate rewards are designed based on the theory of indebtedness, the related literature and the actual background. SPSS 26.0 and AMOS 17.0 are used to analyze the structural equation model.

According to the structural equation analysis, the following findings were found: under the tournament reward condition, social image, feelings of indebtedness and perceived reward value negatively affect consumer willingness to recommend. Under the piece-rate reward condition, social image and feelings of indebtedness significantly negatively affect consumer recommendation willingness, while perceived reward value significantly positively affects consumer recommendation willingness. The mean recommendation willingness of the tournament reward group is significantly lower than that of the control group. In contrast, the mean recommendation willingness of the piece-rate rewards group is significantly higher than that of the control group.

Based on the study findings, the authors propose that enterprises apply piece-rate rewards to incentivize consumers to recommend poverty-alleviating products when designing such rewards. In this way, the sale of poverty-alleviating products can be improved.

The purpose of this study is to examine how crowdfunding backer perceptions of market orientation and foreignness impact crowdfunding performance in emerging economies.

Using content analysis software, the authors analyzed 756 Kickstarter campaign narratives from the emerging economies of Brazil, Russia, India, China, and South Africa for the period between 2009 and 2019.

The authors’ results show that behavioral market orientation signals are positively related to amounts raised while decision criteria signals are negatively related. The authors also find that foreign entrepreneur status interacts with the two market orientations to impact funding amounts.

When creating crowdfunding campaigns in emerging economies, domestic entrepreneurs should use high levels of behavioral market orientation rhetoric but low levels of decision criteria rhetoric within their campaign narratives.

This study unpacks the components of market orientation and examines their positive and negative effects on crowdfunding success in the context of emerging economies.

The purpose of the paper is to propose and demonstrate a novel approach for addressing the challenges of path planning and obstacle avoidance in the context of mobile robots (MR). The specific objectives and purposes outlined in the paper include: introducing a new methodology that combines Q-learning with dynamic reward to improve the efficiency of path planning and obstacle avoidance. Enhancing the navigation of MR through unfamiliar environments by reducing blind exploration and accelerating the convergence to optimal solutions and demonstrating through simulation results that the proposed method, dynamic reward-enhanced Q-learning (DRQL), outperforms existing approaches in terms of achieving convergence to an optimal action strategy more efficiently, requiring less time and improving path exploration with fewer steps and higher average rewards.

The design adopted in this paper to achieve its purposes involves the following key components: (1) Combination of Q-learning and dynamic reward: the paper’s design integrates Q-learning, a popular reinforcement learning technique, with dynamic reward mechanisms. This combination forms the foundation of the approach. Q-learning is used to learn and update the robot’s action-value function, while dynamic rewards are introduced to guide the robot’s actions effectively. (2) Data accumulation during navigation: when a MR navigates through an unfamiliar environment, it accumulates experience data. This data collection is a crucial part of the design, as it enables the robot to learn from its interactions with the environment. (3) Dynamic reward integration: dynamic reward mechanisms are integrated into the Q-learning process. These mechanisms provide feedback to the robot based on its actions, guiding it to make decisions that lead to better outcomes. Dynamic rewards help reduce blind exploration, which can be time-consuming and inefficient and promote faster convergence to optimal solutions. (4) Simulation-based evaluation: to assess the effectiveness of the proposed approach, the design includes a simulation-based evaluation. This evaluation uses simulated environments and scenarios to test the performance of the DRQL method. (5) Performance metrics: the design incorporates performance metrics to measure the success of the approach. These metrics likely include measures of convergence speed, exploration efficiency, the number of steps taken and the average rewards obtained during the robot’s navigation.

The findings of the paper can be summarized as follows: (1) Efficient path planning and obstacle avoidance: the paper’s proposed approach, DRQL, leads to more efficient path planning and obstacle avoidance for MR. This is achieved through the combination of Q-learning and dynamic reward mechanisms, which guide the robot’s actions effectively. (2) Faster convergence to optimal solutions: DRQL accelerates the convergence of the MR to optimal action strategies. Dynamic rewards help reduce the need for blind exploration, which typically consumes time and this results in a quicker attainment of optimal solutions. (3) Reduced exploration time: the integration of dynamic reward mechanisms significantly reduces the time required for exploration during navigation. This reduction in exploration time contributes to more efficient and quicker path planning. (4) Improved path exploration: the results from the simulations indicate that the DRQL method leads to improved path exploration in unknown environments. The robot takes fewer steps to reach its destination, which is a crucial indicator of efficiency. (5) Higher average rewards: the paper’s findings reveal that MR using DRQL receive higher average rewards during their navigation. This suggests that the proposed approach results in better decision-making and more successful navigation.

The paper’s originality stems from its unique combination of Q-learning and dynamic rewards, its focus on efficiency and speed in MR navigation and its ability to enhance path exploration and average rewards. These original contributions have the potential to advance the field of mobile robotics by addressing critical challenges in path planning and obstacle avoidance.