WORKPLACE HAPPINESS: ORGANIZATIONAL ROLE AND THE RELIABILITY OF SELF-REPORTING

Happier employees are more productive. Organizations across industry, no doubt, try to improve their employees’ happiness with the objective to achieve higher profitability and company value. While this issue has drawn increasing attention in high tech and other industries, little is known about the happiness of project management professionals. More research is needed to explore the current situation of workplace happiness of project management professionals and the driving factors behind it. This thesis explores the workplace happiness (subjective well-being) of project management professionals based on the exploratory statistical analysis of a survey 225 professionals in the state of Maryland, conducted in October 2014. The thesis applies Structural Equation Modeling and multiple regression analysis to the dataset and shows no significant impact of gender, age, work experience, and some other demographic traits on workplace happiness, also named well-being. Statistically significant factors for workplace happiness include: creating pleasant work environment, promoting open organization and well-managed team, and good organization to work for. With respect to the reliability of self-reporting, the study finds that the comprehensive appraisal tool designed by Happiness Works and New Economics Foundation can give a more reliable happiness evaluation. Two key factors, i.e. career perspectives and free to be self, can help alleviate the overconfidence of workplace happiness.

Temporal variations of IEEE 802.11b signal strengths in an in-building environment

Recent popularity of the IEEE 802.11b Wireless Local Area Networks (WLANs) in a host of current-day applications has instigated a suite of research challenges. The 802.11b WLANs are highly reliable and wide spread. In this work, we study the temporal characteristics of RSSI in the real-working environment by conducting a controlled set of experiments. Our results indicate that a significant variability in the RSSI can occur over time. Some of this variability in the RSSI may be due to systematic causes while the other component can be expressed as stochastic noise. We present an analysis of both these aspects of RSSI. We treat the moving average of the RSSI as the systematic causes and the noise as the stochastic causes. We give a reasonable estimate for the moving average to compute the noise accurately. We attribute the changes in the environment such as the movement of people and the noise associated with the NIC circuitry and the network access point as causes for this variability. We find that the results of our analysis are of primary importance to active research areas such as location determination of users in a WLAN. The techniques used in some of the RF-based WLAN location determination systems, exploit the characteristics of the RSSI presented in this work to infer the location of a wireless client in a WLAN. Thus our results form the building blocks for other users of the exact characteristics of the RSSI.