Mind your E-manners: Impact of cyber incivility on employees’ work attitude and behavior

We examined cyber incivility in the workplace of Singapore and also examined its impact on employee job satisfaction, organizational commitment, quit intention, and workplace deviance. Data were collected from 192 employees. Results of the survey showed that male supervisors engaged in active forms of cyber incivility while female supervisors engaged in passive cyber incivility. Regression analyses also showed that cyber incivility was negatively related to employees’ job satisfaction and organizational commitment. Employees who experienced cyber incivility were also more likely to quit their jobs or engaged in deviant behavior against their organization. Thus, cyber incivility has negative consequences on both individuals and organizations. Consequently, it is important that firms educate employees and have appropriate policies to discourage cyber incivility.     

What do software practitioners really think about project success: A cross-cultural comparison

Due to the increasing globalization of software development we are interested to discover if there exist significant cultural differences in practitioners’ definition of a successful software project. This study presents the results of a survey in which Chilean software practitioners’ perceptions of project success are compared with previous research with US practitioners. Responses from both groups of practitioners indicate that there is a relationship between team-work and success; our results also indicate that there are similar perceptions related to the importance of job satisfaction and project success. However, Chilean responses suggest that if a practitioner is allowed too much freedom within the work environment, job stress results; this in turn is reflected in increasing demands for both job satisfaction and good environmental conditions. This may indicate the potential for the attribution of failure to conditions outside the team, thus preventing a search for problematic team issues and technical problems. In contrast, the data suggests peer control inside the US teams indicating a less stressful environment.     

Examining the integrated influence of fairness and quality on learners' satisfaction and Web-based learning continuance intention

Abstract.  As with any other information system (IS), the success of Web-based learning depends largely on user satisfaction and other factors that eventually increase users' intentions to continue using the service (continuance intention). This research integrates the IS success model and fairness theory to construct a model for investigating the motivations behind learners' intentions to continue using Web-based learning. Our model theorizes that the three dimensions of quality (i.e. information, system and service) and the three dimensions of fairness (i.e. distributive, procedural and interactional) affect learners' satisfaction. We also argue that satisfaction and the three dimensions of fairness will influence learners' intention to continue using Web-based learning. The hypothesized model is validated empirically using data collected from 289 learners of a Web-based learning service. The results show that information quality, system quality, system use, distributive fairness and interactional fairness exhibit significant positive effects on satisfaction. Also, procedural fairness and satisfaction play significant roles in shaping learners' intention to continue using Web-based learning.     

An empirical analysis of the antecedents of web-based learning continuance

Like any other product, service and Web-based application, the success of Web-based learning depends largely on learners’ satisfaction and other factors that will eventually increase learners’ intention to continue using it. This paper integrates the concept of subjective task value and fairness theory to construct a model for investigating the motivations behind learners’ intention to continue using Web-based learning. The model theorizes that four components of subjective task value (i.e., attainment, utility, intrinsic, and cost) and three dimensions of fairness (i.e., distributive, procedural, and interactional) affect learners’ satisfaction. We also argue that satisfaction and four distinct components of subjective task value influence learners’ intention to continue using Web-based learning. The hypothesized model is validated empirically using data collected from 202 learners of a Web-based learning program designed for continuing education. The results showed that attainment value, utility value, intrinsic value, distributive fairness, and interactional fairness exhibited significant positive effects on satisfaction. Utility value and satisfaction play significant roles in shaping learners’ intention to continue using Web-based learning.     

Social support and leaving intention among computer professionals

Although prior studies have established a number of reasons why computer professionals leave their organizations, they have rarely suggested that lack of social support may be one reason. This study attempted to explain why social support is salient to computer professionals’ leaving intention. It developed a model that posits that (i) social support is positively related to job satisfaction, (ii) social support is negatively related to leaving intention, and (iii) social affiliation needs moderate the relationship between social support and leaving intention. The model was tested using data from a questionnaire. The results indicated that social support from supervisor and colleagues were negatively related to leaving intention for computer professionals with high social affiliation needs, and that job satisfaction mediated the relationship between social support and leaving intention. Social support from family and friends was not related to leaving intention, but it was positively related to job satisfaction.     

Understanding customers' loyalty intentions towards online shopping: an integration of technology acceptance model and fairness theory

As with any other information system (IS), the success of online shopping depends largely on customer satisfaction and other factors that will eventually increase customers' loyalty intentions. This article integrates two major variables of technology acceptance model (TAM), trust, and fairness to construct a model for investigating the motivations behind customers' loyalty intentions towards online shopping. The hypothesised model is validated empirically using data collected from 311 customers of an online shopping store. The results indicated that distributive, procedural and interactional fairness were strong predictors of trust, which in turn influenced satisfaction. Distributive fairness and interactional fairness exhibited significant positive effects on satisfaction. Perceived usefulness and satisfaction influenced loyalty intention towards online shopping. Perceived ease of use acts indirectly on loyalty intention through the mediating effect of perceived usefulness. Implications for theory and practice and future research directions are discussed.     

A metric of fairness for parallel job schedulers

Fairness is an important aspect in queuing systems. Several fairness measures have been proposed in queuing systems in general and parallel job scheduling in particular. Generally, a scheduler is considered unfair if some jobs are discriminated whereas others are favored. Some of the metrics used to measure fairness for parallel job schedulers can imply unfairness where there is no discrimination (and vice versa). This makes them inappropriate. In this paper, we show how the existing approach misrepresents fairness in practice. We then propose a new approach for measuring fairness for parallel job schedulers. Our approach is based on two principles: (i) as jobs have different resource requirements and find different queue/system states, they need not have the same performance for the scheduler to be fair and (ii) to compare two schedulers for fairness, we make comparisons of how the schedulers favor/discriminate individual jobs. We use performance and discrimination trends to validate our approach. We observe that our approach can deduce discrimination more accurately. This is true even in cases where the most discriminated jobs are not the worst performing jobs. Copyright © 2008 John Wiley & Sons, Ltd.     

How social media usage affects employees’ job satisfaction and turnover intention: An empirical study in China

Social media are frequently used in enterprises for both work-related and non-work-related (social) purposes. Drawing on the organizational commitment theory, we developed a research model to explore how different purposes of social media usage affect employees’ job satisfaction and turnover intention in the Chinese context. Online and offline surveys were conducted in China, generating 298 valid responses for analysis. The results suggest that the following: (1) work-related and social-related social media usage positively affects employees’ organizational commitment through their organizational engagement; (2) social media usage improves job satisfaction and reduces employees’ turnover intention through improving their engagement and organizational commitment; and (3) in the process of social media usage influencing employees’ job satisfaction and turnover intention, employees of different genders show significant differences.     

Job orientation,perceptions, and satisfaction a study of information technology professionals in Singapore

In this paper, we develop a conceptual model for job satisfaction vis-a-vis technical or managerial orientation of the information technology (IT) professional's job. We suggest that the linkage is mediated by perceptions of the professional on the “micro-environment” of the job (occupational pay fairness and occupational advancement prospects) as well as on the “macro-environment” of the job (organizational progressiveness posture and organizational cohesiveness). The model was supported empirically by testing a sample of 140 IT professionals in Singapore. We found that a high degree of technical orientation results in the perception that moving into management would bring better pay and advancement prospects; this then leads to job dissatisfaction. Further, a technical orientation brings a perception that the organization is a less progressive place and is held together by an emphasis on procedures rather than on accomplishments. On a broader perspective, our findings would be useful for Singapore policy makers in national IT manpower planning as well as in fine-tuning its implementation of the current vision of Singapore as an “intelligent” island by the turn of the century.     

The Relationship between Coworker Incivility,Emotional Exhaustion,and Organizational Outcomes: The Mediating Role of Emotional Exhaustion

The aim of this research is to investigate the relationship between coworker incivility, emotional exhaustion, and organizational outcomes measured by job satisfaction, job performance, and turnover intention. Working with a sample of 286 retail bank employees in South Korea, structural equation modeling is employed to test four hypotheses drawing on conservation of resources (COR) theory and affective events theory (AET). According to the analyses, while employee incivility positively affects emotional exhaustion, emotional exhaustion has a negative effect on job satisfaction and job performance. In addition, emotional exhaustion has a positive impact on turnover intention among organizational employees. These results imply that to better understand the relationship between coworker incivility and organizational outcomes, it is necessary to consider emotional exhaustion as an important mediating variable. The theoretical and practical implications of this study are discussed, together with its limitations and future research directions.     

Fairness performance of dynamic weights in the ATM ABR service

Traditional schemes fail to achieve fair distribution of bandwidth among available bit rate connections. In this paper, a new scheme called Active Fairness is proposed which substantially improves fairness in bandwidth allocation. Contrary to one set of weights used in traditional schemes, Active Fairness maintains two sets of weights at each link. The first set is the same as that used in traditional schemes, which represents the relative bandwidth allocation desired out of the available bandwidth at the link. If these weights are used directly in bandwidth allocation, the actual proportion of the bandwidth utilized by an individual connection can deviate substantially due to factors such as the number of links traversed by the connection, its round-trip propagation delay, etc. In order to take into account these factors, another set of weights (dynamic in nature) is derived at each link, which is used in bandwidth allocation. Active Fairness achieves significant fairness improvement which is demonstrated through simulations involving bursty background traffic, network bottlenecks, dynamic VC mixes and different fairness definitions.     

The proportional fairness scheduling algorithm on multi-classes

In this paper, we study resource management models and algorithms that satisfy multiple performance objects simultaneously. We realize the proportional fairness principle based QoS model, which defines both delay and loss rate requirements of a class, to include fairness, which is important for the integration of multiple service classes. The resulting Proportional Fairness Scheduling model formalizes the goals of the network performance, user's QoS requirement and system fairness and exposes the fundamental tradeoffs between these goals. In particular, it is difficult to simultaneously provide these objects. We propose a novel scheduling algorithm called Proportional Fairness Scheduling (PFS) that approximates the model closely and efficiently. We have implemented the PFS scheduling in Linux. By performing simulation and measurement experiments, we evaluate the delay and loss rate proportional fairness of PFS, and determine the computation overhead.     

Fairness-related challenges in mobile opportunistic networking

The fundamental challenge in opportunistic networking, regardless of the application, is when and how to forward a message. Rank-based forwarding techniques currently represent one of the most promising methods for addressing this message forwarding challenge. While these techniques have demonstrated great efficiency in performance, they do not address the rising concern of fairness amongst various nodes in the network. Higher ranked nodes typically carry the largest burden in delivering messages, which creates a high potential of dissatisfaction amongst them. In this paper, we adopt a real-trace driven approach to study and analyze the trade-offs between efficiency, cost, and fairness of rank-based forwarding techniques in mobile opportunistic networks.Our work comprises three major contributions. First, we quantitatively analyze the trade-off between fair and efficient environments. Second, we demonstrate how fairness coupled with efficiency can be achieved based on real mobility traces. Third, we propose FOG, a real-time distributed framework to ensure efficiency–fairness trade-off using local information. Our framework, FOG, enables state-of-the-art rank-based opportunistic forwarding algorithms to ensure a better fairness–efficiency trade-off while maintaining a low overhead. Within FOG, we implement two real-time distributed fairness algorithms; Proximity Fairness Algorithm (PFA), and Message Context Fairness Algorithm (MCFA). Our data-driven experiments and analysis show that mobile opportunistic communication between users may fail with the absence of fairness in participating high-ranked nodes, and an absolute fair treatment of all users yields inefficient communication performance. Finally our analysis shows that FOG-based algorithms ensure relative equality in the distribution of resource usage among neighbor nodes while keeping the success rate and cost performance near optimal.     

Job and organizational determinants of nursing home employee commitment,job satisfaction and intent to turnover

The purpose of this study was to examine whether job characteristics, the work environment, participation in quality improvement activities and facility quality improvement environment predicted employee commitment and job satisfaction in nursing homes, and whether those same predictors and commitment and satisfaction predicted turnover intention. A total of 6584 nursing home employees from 76 nursing homes in a midwestern state participated. A self-administered questionnaire was used to collect the data. The results supported the hypotheses that job and organizational factors predicted commitment and satisfaction while commitment and satisfaction predicted turnover intentions. The implications for retaining nursing home employees are discussed.     

Job and organizational determinants of nursing home employee commitment, job satisfaction and intent to turnover

The purpose of this study was to examine whether job characteristics, the work environment, participation in quality improvement activities and facility quality improvement environment predicted employee commitment and job satisfaction in nursing homes, and whether those same predictors and commitment and satisfaction predicted turnover intention. A total of 6,584 nursing home employees from 76 nursing homes in a midwestern state participated. A self-administered questionnaire was used to collect the data. The results supported the hypotheses that job and organizational factors predicted commitment and satisfaction while commitment and satisfaction predicted turnover intentions. The implications for retaining nursing home employees are discussed.     

多媒体传感器网络中服务感知的公平调度算法

针对多媒体传感器网络中基于异常事件驱动的服务模式和基于用户查询驱动的服务模式,分析不同服务的流量模式,提出一种服务感知的公平调度策略,采用基于流量预测的动态公平缓冲共享机制和速率分配算法实现2类数据QoS的公平保障。仿真实验表明,该算法在传输延迟和成功到达率方面实现了公平性目标。     

Learning non-cooperative game for load balancing under self-interested distributed environment

Resources in large-scale distributed systems are distributed among several autonomous domains. These domains collaborate to produce significantly higher processing capacity through load balancing. However, resources in the same domain tend to be cooperative, whereas those in different domains are self-interested. Fairness is the key to collaboration under a self-interested environment. Accordingly, a fairness-aware load balancing algorithm is proposed. The load balancing problem is defined as a game. The Nash equilibrium solution for this problem minimizes the expected response time, while maintaining fairness. Furthermore, reinforcement learning is used to search for the Nash equilibrium. Compared with static approaches, this algorithm does not require a prior knowledge of job arrival and execution, and can adapt dynamically to these processes. The synthesized tests indicate that our algorithm is close to the optimal scheme in terms of overall expected response time under different system utilization, heterogeneity, and system size; it also ensures fairness similar to the proportional scheme. Trace simulation is conducted using the job workload log of the Scalable POWERpallel2 system in the San Diego Supercomputer Center. Our algorithm increases the expected response time by a maximum of 14%. But it improves fairness by 12–27% in contrast to Opportunistic Load Balancing, Minimum Execution Time, Minimum Completion Time, Switching Algorithm, and k-Percent Best.     

Self-stabilizing strong fairness under weak fairness

Fairness assumptions have a great impact on distributed algorithms. They play a major role in determining the time complexity and the correctness of algorithms, since progress or freedom from various types of starvation may not be guaranteed without fairness assumptions. In this paper, we present a stabilizing deterministic algorithm allowing simultaneous execution of actions for strong fairness under weak fairness assumption, in addition, we show that the proposed algorithm yields a high degree of concurrency. We conclude the paper with some remarks on issues such as time optimal implementation of strong fairness and open problems related to fairness     

An investigation of the impact of abusive supervision on technology end-users

Although they are likely to occur in many organizations, few research efforts have examined the impact of negative supervisor behaviors on technology end-users. In this study we investigate abusive supervision, and the effects it has on perceptions about the work and psychological, attitudinal, and behavioral intention outcomes. Our sample consisted of 225 technology end-users from a large variety of organizations. Results revealed that abusive supervision has a positive impact on perceived pressure to produce, time pressure, and work overload, and a negative impact on liking computer work, and ultimately these variables impact job strain, frustration, turnover intentions, and job satisfaction.     

The relationships among service quality,perceived value,customer satisfaction,and post-purchase intention in mobile value-added services

The purposes of this study are to construct an instrument to evaluate service quality of mobile value-added services and have a further discussion of the relationships among service quality, perceived value, customer satisfaction, and post-purchase intention. Structural equation modeling and multiple regression analysis were used to analyze the data collected from college and graduate students of 15 major universities in Taiwan. The main findings are as follows: (1) service quality positively influences both perceived value and customer satisfaction; (2) perceived value positively influences on both customer satisfaction and post-purchase intention; (3) customer satisfaction positively influences post-purchase intention; (4) service quality has an indirect positive influence on post-purchase intention through customer satisfaction or perceived value; (5) among the dimensions of service quality, “customer service and system reliability” is most influential on perceived value and customer satisfaction, and the influence of “content quality” ranks second; (6) the proposed model is proven with the effectiveness in explaining the relationships among service quality, perceived value, customer satisfaction, and post-purchase intention in mobile added-value services.