Reward Score Research Articles

Blockchain-Based Model for Incentivized Cyber Threat Intelligence Sharing

Sharing cyber threat intelligence (CTI) can significantly improve the security of information technology (IT) in organizations. However, stakeholders and practitioners are not keen on sharing CTI data due to the risk of exposing their private data and possibly losing value as an organization on the market. We present a model for CTI data sharing that maintains trust and confidentiality and incentivizes the sharing process. The novelty of the proposed model is that it combines two incentive mechanisms: money and reputation. The reputation incentive is important for ensuring trust in the shared CTI data. The monetary incentive is important for motivating the sharing and consumption of CTI data. The incentives are based on a subscription fee and a reward score for activities performed by a user. User activities are considered in the following three fields: producing CTI data, consuming CTI data, and reviewing CTI data. Each instance of user activity is rewarded with a score, and this score generates some value for reputation. An algorithm is proposed for assigning reward scores and for recording the accumulated reputation of the user. This model is implemented on the Hyperledger Fabric blockchain and the Interplanetary File System for storing data off-chain. The implemented prototype demonstrates the feasibility of the proposed model. The provided simulation shows that the selected values and the proposed algorithm used to calculate the reward scores are in accordance with economic laws.

DynaGlaucoDetect: Leveraging Dyna-Q learning for glaucoma detection

Glaucoma is an eye disease that requires early detection and proper diagnosis for timely intervention and treatment which can help slow down further progression and to manage intraocular pressure. This paper aims to address the problem by proposing a novel approach that combines a model-based Reinforcement Learning (RL) approach, called DynaGlaucoDetect, with ocular gaze data. By leveraging the RL algorithms to simulate and predict the dynamics of glaucoma, a model-based approach can improve the accuracy and efficiency of glaucoma detection by enabling better preservation of visual health. The RL agent is trained using real experiences and synthetic experiences which are generated using the model-based algorithm Dyna-Q. Two different Q-table generation methods have been discussed: the Direct Synthesis Method (DSM) and the Indirect Synthesis Method (IdSM). The presence of glaucoma has been detected by comparing the reward score a patient obtains with the threshold values obtained through the performed experimentation. The scores obtained using DSM and IdSM have been compared to understand the learning of the agent in both cases. Finally, hyperparameter tuning has been performed to identify the best set of hyperparameters.

Differential effects of reward and punishment on reinforcement-based motor learning and generalization.

Reward and punishment have long been recognized as potent modulators of human behavior. Although reinforcement learning is a significant motor learning process, the exact mechanisms underlying how the brain learns movements through reward and punishment are not yet fully understood. Beyond the memory of specific examples, investigating the ability to generalize to new situations offers a better understanding of motor learning. This study hypothesizes that reward and punishment engage qualitatively different motivational systems with different neurochemical and neuroanatomical substrates, which would have differential effects on reinforcement-based motor learning and generalization. To test this hypothesis, two groups of participants learn a motor task in one direction and then relearn the same task in a new direction, receiving only performance-based reward or punishment score feedback. Our findings support our hypothesis, showing that reward led to slower learning but promoted generalization. On the other hand, punishment led to faster learning but impaired generalization. These behavioral differences may be due to different tendencies of movement variability in each group. The punishment group tended to explore more actively than the reward group during the initial learning phase, possibly due to loss aversion. In contrast, the reward group tended to explore more actively than the initial learning phase during the generalization test phase, seemingly recalling back the strategy that led to reward. These results suggest that reward and punishment may engage different neural mechanisms during reinforcement-based motor learning and generalization, with important implications for practical applications such as sports training and motor rehabilitation.

The synchronized multi-assignment orienteering problem

<p style='text-indent:20px;'>We introduce the Synchronized Multi-Assignment Orienteering Problem (SMOP), a vehicle routing problem that requires jointly selecting a set of jobs while synchronizing the assignment and transportation of agents to roles to form ad-hoc teams at different job locations. Agents must be assigned only to roles for which they are qualified. Each job requires a certain number of agents in each role within a time window and contributes a reward score if selected. The task is to maximize the total reward attained. SMOP can model many real-world scenarios requiring coordinated transportation of resources and accommodates traditional depot-based workforces, depot workforces supplemented by ad-hoc workers, and fully ad-hoc workforces alike. The same problem formulation can be used for initial planning and mid-course replanning. We develop a mixed integer programming formulation (MIP) and an Adaptive Large Neighborhood Search algorithm (ALNS). In computational experiments covering a range of considerations, ALNS consistently found very near-optimal solutions on smaller problems and surpassed a commercial MIP solver substantially on larger problems. ALNS also found 24 new best solutions on a set of benchmark problems from the literature for the related Cooperative Orienteering Problem with Time Windows.</p>

Engineering Spiking Neurons Using Threshold Switching Devices for High-Efficient Neuromorphic Computing.

Inspired by the human brain, the spike-based neuromorphic system has attracted strong research enthusiasm because of the high energy efficiency and powerful computational capability, in which the spiking neurons and plastic synapses are two fundamental building blocks. Recently, two-terminal threshold switching (TS) devices have been regarded as promising candidates for building spiking neurons in hardware. However, how circuit parameters affect the spiking behavior of TS-based neurons is still an open question. Here, based on a leaky integrate-and-fire (LIF) neuron circuit, we systematically study the effect of both the extrinsic and intrinsic factors of NbOx -based TS neurons on their spiking behaviors. The extrinsic influence factors contain input intensities, connected synaptic weights, and parallel capacitances. To illustrate the effect of intrinsic factors, including the threshold voltage, holding voltage, and high/low resistance states of NbOx devices, we propose an empirical model of the fabricated NbOx devices, fitting well with the experimental results. The results indicate that with enhancing the input intensity, the spiking frequency increases first then decreases after reaching a peak value. Except for the connected synaptic weights, all other parameters can modulate the spiking peak frequency under high enough input intensity. Also, the relationship between energy consumption per spike and frequency of the neuron cell is further studied, leading guidance to design neuron circuits in a system to obtain the lowest energy consumption. At last, to demonstrate the practical applications of TS-based neurons, we construct a spiking neural network (SNN) to control the cart-pole using reinforcement learning, obtaining a reward score up to 450. This work provides valuable guidance on building compact LIF neurons based on TS devices and further bolsters the construction of high-efficiency neuromorphic systems.

Delayed circadian rhythms and substance abuse: dopamine transmission's time has come.

Disrupted sleep and circadian rhythms are linked with substance abuse risk. Human studies that investigate relationships between sleep, circadian rhythm, and substance use reward generally rely on indirect means to infer dopaminergic function, such as functional magnetic resonance imaging. In this issue of the JCI, Zhang and colleagues used positron emission tomography (PET) to image striatal dopamine D1 (D1R) and D2/3 receptor (D/3R) availability in healthy adults. The authors assessed rest-activity rhythms, then conducted PET scans using radioligand antagonists selective for D1 receptors or D2/D3 receptors to measure D1R and D2/3R availability. They also measured the subjective drug effects of oral methylphenidate. Higher D1R availability in caudate and a greater methylphenidate reward sensitivity were associated with delayed rest-activity rhythms. Unexpectedly, lower overall activity was associated with higher D2/3R availability in the nucleus accumbens, which coincided with greater methylphenidate reward score. These findings may inform personalized prevention and/or treatment interventions.

Effort-Reward Imbalance and Its Effects on Satisfaction With Working Conditions and Sleep-Related Problems: Comparison of Nurses and Other Occupations.

This study aimed to compare effort-reward imbalance (ERI) among registered nurses, social workers, and elementary school teachers, and to analyze the effects of ERI on satisfaction with working conditions and sleep-related problems. A secondary data analysis was conducted using cross-sectional data from the Korean Working Conditions Survey collected in 2017. The study sample included 276 registered nurses, 97 social workers, and 229 elementary school teachers. The effort index was measured using two dimensions (work intensity and working time quality) with seven subdimensions. The reward index consisted of three dimensions (social support, earning, and prospects) with five subdimensions. The ERI index was computed by dividing the average effort score by the average reward score. Linear or logistic regression analysis was conducted to compare efforts, rewards, and ERI among the three occupations and to examine the effects of ERI on satisfaction and sleep-related problems. Nurses had a significantly higher effort score than the other two groups. However, nurses had a lower reward score than elementary school teachers, but a higher score than social workers. The highest ERI index was found among nurses (0.47 ± 0.16), followed by social workers (0.39 ± 0.30) and elementary school teachers (0.30 ± 0.15). All three occupations showed an inverse relationship between ERI and satisfaction with working conditions and positive relationships between ERI and sleep-related problems. The high ERI (i.e., more effort relative to reward) perceived by nurses was associated with diminished satisfaction and increased sleep-related problems. To attract future generations to nursing as a career choice and to ensure a sustainable nurse workforce, the nurse-perceived ERI should be decreased by reducing work demands and increasing both monetary and nonmonetary rewards.

Dynamic distributed trust management scheme for the Internet of Things

The Internet of Things (IoT) comprises of a diverse network of homogeneous and heterogeneous nodesthat can be accessed through network ubiquitously. In unattended environments, the IoT devices are prone to variousattacks including ballot-stu?ing, bad-mouthing, self-promotion, on-off, opportunistic behavior attacks, etc. The on-offattack is di?icult to detect as nodes switch their behavior from normal to malicious alternatively. A trust managementmodel is a tool to defend the IoT system against malicious activities and provide reliable data exchange. The majorityof existing IoT trust management techniques are based on static reward and punishment values in pursuit of trustcomputation thereby allowing the misbehaving nodes to deliberately perform on-off attacks. Due to the static nature ofawarding scores, these schemes fail to identify malicious nodes in certain cases. In this paper, a dynamic and distributedtrust management scheme (DDTMS) is proposed where nodes can autonomously evaluate peer nodes' behavior anddynamically grant reward and penalty score. The proposed scheme successfully detects the on-off attack and isolates themisbehaving nodes thereby classifying them into three distinct categories based on their severity levels i.e. low, mild,and severe. Simulation-based performance evaluation shows improved performance of the proposed DDTMS againstother state-of-the-art schemes thereby requiring less time and fewer interactions for successfully identifying malevolentbehavior of compromised nodes.

Identification of Top-K Influencers Based on Upper Confidence Bound and Local Structure

Abstract We study the problem of identifying top-K influencers when we have only local knowledge of the network structure. More specifically, the selection of top-K influencers is performed sequentially over a number of rounds. We propose an efficient algorithm called strength network similarity-based upper confidence bound (SNS_UCB1) for the identification of top-K influencers based on upper confidence bound (UCB1) from the multi-armed bandit's framework. Considering feedback in online decision-making, we rely on edge (arm) strength on falling within a large number of other edges and how edge members are similar to each other and can thus convince other users to adopt the promoted behaviours. Thus, this feedback is considered as a reward score at each pull of the arm of how likely this selection is to contribute to the increase in the cumulative reward. We evaluate the proposed algorithm under the independent cascade (IC) model on four large-scale datasets that differ in size and density. We compare our algorithm to a centrality measure-based UCB1 and several well-known state-of-the-art approaches, demonstrating its superior performance in terms of influence spread achieved with the less required time and storage space.

Semantic-Based Self-Critical Training for Question Generation

Question generation is a conditioned language generation task that consists in generating a context-aware question given a context and the targeted answer. Train language modelling with a mere likelihood maximization has been widely used while suffering from exposure bias and the discordance between the training and the test metrics. In the way of addressing this issue, The presented work portrays a fully Transformer-based reinforcement learning generator-evaluation architecture for neural question generation. To edge the flexibility of the generation, a semantic-based reward score was externally infused during the training to drive the training of the language model. The global architecture is laid out in a generator-evaluator fashion optimized directly to n-gram and semantic-based metrics. Evaluation metrics for language modelling only based on n-gram overlapping do not consider semantic relations between reference and candidate sequences. To improve the evaluation step, a two-fold evaluation was carried out. On the one side, an n-gram overlapping evaluation using the BLEU score. On the other side, a semantic-based assessment using BERTScore and NUBIA. The results were corroborated by a binary human evaluation of the semantic relatedness of the generated question and the ground truth. The results obtained showed that use a semantic-based REINFORCE algorithm for the question generation syntactically reshapes the generated questions while preserving their underlying semantic meaning. Many downstream applications can be drawn from a successful question generation including the enlargement of question answering datasets, the improvement of conversational systems, the enhancement of autonomous educational assessment systems, and so forth.

The mediating role of psychological capital between occupational stress and suicidal ideation

Objective: To analyze the mediating effect of psychological capital (PsyCap) between occupational stress and suicidal ideation. Methods: In September 2017, stratified-cluster sampling method was adopted to select employees of an electronic manufacturing service industry as respondents for a questionnaire survey in Jiangsu province. The demographic characteristics of employees were collected. A total of 2 465 employees were investigated, and 2 216 valid questionnaires were collected. The level of occupational stress and PsyCap was assessed by the Effort-Reward Imbalance Scale(ERI)and PsyCap Questionnaire. Results: The age of 2 216 employees was (28.70±5.26) years old, including 1 230 males (55.5%). The scores of occupational stress on effort, reward and over-commitment were (3.08±0.63), (3.73±0.60) and (2.51±0.68), respectively. The average ERI index (ratio of effort to return) was (0.88±0.39). The total score of PsyCap was (86.62±15.23). The detection rate of suicidal ideation within two weeks was 13.9% (309/2 216). The average score of effort and over-commitment and the ERI index were positively correlated with the number of suicidal ideation detected within two weeks, with correlation coefficients about 0.081, 0.141 and 0.164, respectively. The average score of reward and total score of PsyCap were negatively correlated with the number of suicidal ideation detected within two weeks, with correlation coefficients about -0.206 and -0.228, respectively. The mediating effect results showed that PsyCap had mediating effect on the effort, reward, over-commitment and suicidal ideation of occupational stress respectively, with mediating effect values of -0.087 (95%CI: -0.018,-0.019), -0.299 (95%CI: -0.428,-0.200) and 0.096 (95%CI: 0.0394, -0.170). The mediating effect percentages were 9.43%, 17.92%, and 9.54%, respectively. Conclusion: PsyCap has a mediating effect between effort, reward, over-commitment of occupational stress and suicidal ideation.

Sleep quality and occupational stress relationship analysis of field gas recovery workers

Objective: To explore the relationship between sleep quality and occupational stress in field gas recovery workers. Methods: In October 2018, cluster sampling method was adopted to conduct cross-sectional survey on 1726 field workers in a gas production oilfield. The individual characteristics, occupational stress factors, stress regulation factors, stress response and sleep quality, social support and coping strategies were evaluated by occupational stress measurement tools and job content questionnaire. Mann Whitney U test and Kruskal Wallis H test were used to compare sleep quality scores between the groups. Spearman rank correlation analysis was used to analyze the correlation between sleep quality and occupational stress, and logistic regression analysis was used to analyze multiple factors. Results: There were significant differences in sleep quality scores among different positions, gender, marital status, age, length of service, smoking and drinking (P<0.05) . There were no significant differences in sleep quality scores between different education levels and work shift groups (P>0.05) . Spearman rank correlation analysis showed that sleep quality score was negatively correlated with job satisfaction, reward, job stability, promotion opportunity, positive emotion, respect, self-esteem, control strategy, support strategy and self-efficacy score (r(s)=-0.361, -0.311, -0.238, -0.261, -0.248, -0.212, -0.139, -0.188, -0.152, -0.226, P<0.01) , and was positively correlated with social support, giving, daily tension, negative emotion, work monotony and depression symptom (r(s)=0.312, 0.279, 0.547, 0.493, 0.429, 0.599, P<0.01) . Compared with the high sleep quality score group, the middle and low sleep quality score groups had lower giving, work monotony, daily tension, depressive symptoms, negative emotions and social support (P<0.01) , while the scores of respect, reward, job satisfaction, positive emotion, self-efficacy, job stability, promotion opportunity, control strategy and support strategy were higher (P<0.01) . Multiple depressive symptoms, high daily tension, high negative emotion and high work monotony were the risk factors for sleep disorders (OR=3.417, 2.659, 2.913, 1.543) . Conclusion: Depressive symptoms, daily tension and negative emotion have great influence on sleep quality of field gas recovery workers.

MABRESE: A New Server Selection Method for Smart SDN-Based CDN Architecture

A content delivery network (CDN) is able to handle high traffic and offer reliable services by geographically bringing the content data to the edge network, where replica servers are installed closer to the end users. The traditional CDN architecture lacks a global view of the whole network and, thus, cannot dynamically and optimally perform the server selection task. In this letter, we propose to integrate a software-defined network (SDN) into the CDN architecture. Our intuitive motivation is to decouple the control plane from the forwarding plane in order to offer flexibility and programmability by using the centralized controller. This letter also develops a novel server selection algorithm that is based on the so-called multi-armed bandit problem. Such an algorithm is proved to optimize the server selection function and provide a good experimental result in terms of both average response time and reward score.

Abstract MP56: Social Role Stress, Reward and the American Heart Association Life’s Simple 7 in Midlife Women: The Study of Women’s Health Across the Nation

Introduction: American women can occupy multiple social roles, such as employee, caregiver, mother and spouse during midlife. These roles can be both stressful and rewarding, which may influence adherence to heart-healthy behaviors and risk factors. The aim of this study was to test the association of social role stress and reward with achievement of the American Heart Association Life’s Simple 7 risk factors in a cohort of midlife women in the United States. Methods: The Study of Women’s Health Across the Nation (SWAN) is an longitudinal cohort study initiated in in 1996-1997 of women aged 42-52 who were premenopausal. At the fifth annual follow-up visit women first were asked if they occupied four social roles (employee, caregiver, spouse, mother), and then were asked to rate how stressful and how rewarding each occupied role was, using five point scales. Average role-related stress and reward were calculated for each woman (range 1-5). Ideal cardiovascular risk factors were assessed at the same follow-up visit using anthropometric measurement (body mass index, blood pressure), blood draw (glucose, cholesterol), and validated questionnaires (physical activity, diet and smoking). Multivariate linear regression was used for cross-sectional analyses of the number of ideal factors, using average role stress and reward as exposures. Adjusted logistic regression models were used to estimate odds of achieving the ideal level of each individual risk factor. Models were adjusted for age, race, site, education and menopause status. Results: At the fifth SWAN follow-up visit, 1,777 women had data on all seven risk factors, and reported occupying at least one social role. The mean (standard deviation) of the number of ideal factors was 3.2 (1.3). Only 5% of the sample had five or more ideal factors. Women who reported greater role-related stress achieved fewer ideal factors, and a higher reward score was related to more ideal factors. A one unit higher role stress score was associated with 18% lower odds of having a healthy diet, and 18% reduced odds of having a BMI under 30. Women with a one unit higher role reward score had 56% greater odds of ideal physical activity, and 34% greater odds of being a non-smoker. Higher job stress was associated with 13% reduced odds of having a healthy blood pressure. There was no evidence of an interaction between stress and reward. Adjusting for depression and social support attenuated, but did not eliminate the significant relationships between role stress and reward and cardiovascular risk. Conclusion: Midlife women experience stress from multiple social roles while simultaneously deriving reward from these roles, which may be beneficial for their cardiovascular disease risk factors. Understanding the influence and determinants of role stress and reward may be important when designing interventions to improve diet, physical activity and smoking behaviors in midlife women.

Precision Medicine in Alcohol Dependence: A Controlled Trial Testing Pharmacotherapy Response Among Reward and Relief Drinking Phenotypes.

Randomized trials of medications for alcohol dependence (AD) often report no differences between active medications. Few studies in AD have tested hypotheses regarding which medication will work best for which patients (ie, precision medicine). The PREDICT study tested acamprosate and naltrexone vs placebo in 426 randomly assigned AD patients in a 3-month treatment. PREDICT proposed individuals whose drinking was driven by positive reinforcement (ie, reward drinkers) would have a better treatment response to naltrexone, whereas individuals whose drinking was driven by negative reinforcement (ie, relief drinkers) would have a better treatment response to acamprosate. The goal of the current analysis was to test this precision medicine hypothesis of the PREDICT study via analyses of subgroups. Results indicated that four phenotypes could be derived using the Inventory of Drinking Situations, a 30-item self-report questionnaire. These were high reward/high relief, high reward/low relief, low reward/high relief, and low reward/low relief phenotypes. Construct validation analyses provided strong support for the validity of these phenotypes. The subgroup of individuals who were predominantly reward drinkers and received naltrexone vs placebo had an 83% reduction in the likelihood of any heavy drinking (large effect size). Cutoff analyses were done for clinical applicability: individuals are reward drinkers and respond to naltrexone if their reward score was higher than their relief score AND their reward score was between 12 and 31. Using naltrexone with individuals who are predominantly reward drinkers produces significantly higher effect sizes than prescribing the medication to a more heterogeneous sample.

Scoring on Multiple-Choice Test and Achievement Motivation on Geography Learning Outcomes

This research aims to determine the effect of scoring on multiple-choice test and achievement motivation on geography learning outcomes. The research used an experimental method with treatment by level 3 x 2 design. Scoring on a multiple choice test is as treatment, achievement motivation is as variable of attributes and geography learning outcomes are as the dependent variable. Research sample consists of students of class XI-IIS 3 SMA N 30 Jakarta, students of class XI-IIS 1 SMA N 77 Jakarta and students of class XI-IIS 1 SMA N 05 Jakarta determined by cluster random sampling with 72 respondents (students). Analysis technique used a two way anava to test the main effect and interaction effect. Based on the research results, reward score and punishment score are more effective in improving the student’s learning outcomes than the correct score. In giving a multiple-choice test, reward score and punishment score can be used as scoring prioritized, especially in students who have high achievement motivation, while correct score can be used as scoring prioritized, especially in students who have low achievement motivation.

Effort-reward imbalance at work, over-commitment personality and diet quality in Central and Eastern European populations.

The aims of this study were to investigate the associations between work stress defined by the effort-reward imbalance (ERI) model and diet quality and to examine the potential role of over-commitment (OC) personality in ERI-diet relationships. A cross-sectional study was conducted in random population samples of 6340 men and 5792 women (age 45-69 years) from the Czech Republic, Russia and Poland. Dietary data were collected using FFQ. The healthy diet indicator (HDI) was constructed using eight nutrient/food intakes (HDI components) to reflect the adherence to WHO dietary guideline. The extent of imbalance between effort and reward was measured by the effort:reward (ER) ratio; the effort score was the numerator and the reward score was multiplied by a factor adjusting for unequal number of items in the denominator. Logistic regression and linear regression were used to assess the associations between exposures (ER ratio and OC) and outcomes (HDI components and HDI) after adjustment for confounders and mediators. The results showed that high ER ratio and high OC were significantly associated with unhealthy diet quality. For a 1-SD increase in the ER ratio, HDI was reduced by 0·030 and 0·033 sd in men and women, and for a 1-SD increase in OC, HDI was decreased by 0·036 and 0·032 sd in men and women, respectively. The modifying role of OC in ERI-diet relationships was non-significant. To improve diet quality at workplace, a multiple-level approach combining organisational intervention for work stress and individual intervention for vulnerable personality is recommended.

Pengaruh Jumlah Alternatif Jawaban dan Teknik Penskoran terhadap Reliabilitas Tes

&lt;p&gt;This study aimed to determine the effect of the number of alternative answers &lt;br /&gt;and scoring techniques to reliability test. Forms of this test includes multiple choice test three answer choice and multiple choice test four answer choices with penalty scoring techniques (Punishment Score) and scoring techniques compensation (Reward Score). The method uses the experiment, while the designused istreatment bylevel 2 x 2. Research hypotheses were tested using two way analysis of variance (ANOVA). The result concluded that: (1) reliability tests with three multiple choice answer options is higher than the multiple choice test four answer choices, (2) reliability tests with scoring techniques penalty higher than the reliability of the technique of scoring compensation, &lt;br /&gt;and (3) No interaction between the number of alternative answers to the scoring &lt;br /&gt;technique. The results of this study can be considered for the teacher to give test using a form of multiple choice test three answer choice and multiple choice test four answer choices test scoring with a penalty techniques. &lt;br /&gt; &lt;br /&gt;Keywords : reliability, scoring techniques, alternative answers.&lt;/p&gt;

Leadership Styles of General Managers and Job Satisfaction Antecedent of Middle Managers in 5-Star Hotels in Kuala Lumpur, Malaysia

Leadership styles may differ across countries particularly in aspects such as culture, approach, and language. Expatriate managers in Malaysian 5-star hotels, may have a different approach from local managers, hence the levels of the job satisfaction of middle managers may differ too. Information is still lacking on the influence of expatriate managers leadership styles on employees’ job satisfaction in Malaysian 5-star hotels. The purpose of this paper was twofold, to shed light on employees’ job satisfaction under the leadership of expatriate managers as well as the differences in leadership styles of local and expatriate managers. Results showed that transformational leadership styles such as; idealized influence (behavior), intellectual stimulation, inspirational motivation had a significant positive effect on employees job satisfaction. Even transactional leadership styles of expatriates such as contingent reward produced significant positive effect on employees job satisfaction. However transactional leadership of management by exception (passive) of expatriate managers had a significant negative effect on job satisfaction. The combination of five leadership styles of expatriate managers, was able to produce 92.2% of employees’ job satisfaction. Except for management by exception (passive), the other four leadership styles had a positive effect on job satisfaction. Results further revealed that expatriate managers have different leadership styles, with higher individual consideration, and contingent reward score, but lower management by exception (passive) score compared to local managers. The difference in leadership styles enabled expatriate managers to achieve higher job satisfaction scores compared to local managers.

Effort-reward imbalance, overcommitment, and cellular immune measures among white-collar employees

We investigated whether chronic job stress, i.e., effort-reward imbalance (ERI) and overcommitment is associated with cellular immunity among 190 male and 157 female white-collar daytime employees (mean age 38; range 22–69 years). Participants provided a blood sample for the measurement of circulating immune (natural killer (NK), B, and T) cell counts and NK cell cytotoxicity (NKCC) and completed a questionnaire survey during April to June 2002. Stepwise multiple linear regression analyses revealed that NK cells were associated with effort ( β = −.230; p = .013), reward ( β = .169; p = .047), and ERI ( β = −.182; p = .047) scores but not with overcommitment in men; reward score was positively associated with NKCC ( β = .167; p = .049) and inversely associated with B cells ( β = −.181; p = .030). No significant associations were found in women. Although the picture remains less clear in women, our findings suggest a potential immunological pathway linking adverse working conditions and stress-related disorders in men.