The relation between work motivation and project management success : an empirical investigation

The content and context of work significantly influences an employees’ satisfaction. While managers see work motivation as a tool to engage the employees so that they perform better, academicians value work motivation for its contribution to human behaviour. Though the relationship between employee motivation and project success has been extensively covered in the literature, more research focusing on the nature of job design on project success may have been wanting. We address this gap through this study. The present study contributes to the extant literature by suggesting an operational framework of work motivation for project—based organizations. We are also advancing the conceptual understanding of this variable by understanding how the different facets of work motivation have a differing impact of the various parameters of project performance. A survey instrument using standardized scales of work motivation and project success was used. 199 project workers from various industries completed the survey. We first ‘operationalized’ the definition of work motivation for the purpose of our study through a principal component analysis of work motivation items. We obtained a five factor structure that had items pertaining to employee development, work climate, goal clarity, and job security. We then performed a Pearson’s correlation analysis which revealed moderate to significant relationship between project outcomes ad work climate; project outcomes & employee development. In order to establish a causality between work motivation and project management success, we employed linear regression analysis. The results show that work climate is a significant predictor of client satisfaction, while it moderately influences the project quality. Further, bringing in objectivity to project work is important for a successful implementation.

Evaluating the economics of the Australian National Hand Hygiene Initiative

The National Hand Hygiene Initiative, implemented in Australia in 2009, is currently being evaluated for effectiveness and cost-effectiveness by a multidisciplinary team of researchers. Data from a wide range of sources are being harvested to address the research questions. The data are observational and appropriate statistical and economic modelling methods are being used. Decision makers will be provided with new knowledge about how hand hygiene interventions should be organised and what investment decisions are justified. This is novel research and the authors are unaware of any other evaluation of hand hygiene improvement initiatives. This paper describes the evaluation currently underway.

Introductory Chapter to The Economics of Nonprofit Enterprises

Nonprofit organizations present the analyst with a slew of puzzles. To an economist conditioned to think in terms of objectives and constraints, even the mathematical definition of the beast is a problem. What is a nonprofit organization? How does this definition shape the elaboration of objectives and constraints?

The economics of happiness : a lifetime perspective

The three studies in this thesis focus on happiness and age and seek to contribute to our understanding of happiness change over the lifetime. The first study contributes by offering an explanation for what was evolving to a ‘stylised fact’ in the economics literature, the U-shape of happiness in age. No U-shape is evident if one makes a visual inspection of the age happiness relationship in the German socio-economic panel data, and, it seems counter-intuitive that we just have to wait until we get old to be happy. Eliminating the very young, the very old, and the first timers from the analysis did not explain away regression results supporting the U-shape of happiness in age, but fixed effect analysis did. Analysis revealed found that reverse causality arising from time-invariant individual traits explained the U-shape of happiness in age in the German population, and the results were robust across six econometric methods. Robustness was added to the German fixed effect finding by replicating it with the Australian and the British socio-economic panel data sets. During analysis of the German data an unexpected finding emerged, an exceedingly large negative linear effect of age on happiness in fixed-effect regressions. There is a large self-reported happiness decline by those who remain in the German panel. A similar decline over time was not evident in the Australian or the British data. After testing away age, time and cohort effects, a time-in-panel effect was found. Germans who remain in the panel for longer progressively report lower levels of happiness. Because time-in-panel effects have not been included in happiness regression specifications, our estimates may be biased; perhaps some economics of the happiness studies, that used German panel data, need revisiting. The second study builds upon the fixed-effect finding of the first study and extends our view of lifetime happiness to a cohort little visited by economists, children. Initial analysis extends our view of lifetime happiness beyond adulthood and revealed a happiness decline in adolescent (15 to 23 year-old) Australians that is twice the size of the happiness decline we see in older Australians (75 to 86 yearolds), who we expect to be unhappy due to declining income, failing health and the onset of death. To resolve a difference of opinion in the literature as to whether childhood happiness decreases, increases, or remains flat in age; survey instruments and an Internet-based survey were developed and used to collect data from four hundred 9 to 14 year-old Australian children. Applying the data to a Model of Childhood Happiness revealed that the natural environment life-satisfaction domain factor did not have a significant effect on childhood happiness. However, the children’s school environment and interactions with friends life-satisfaction domain factors explained over half a steep decline in childhood happiness that is three times larger than what we see in older Australians. Adding personality to the model revealed what we expect to see with adults, extraverted children are happier, but unexpectedly, so are conscientious children. With the steep decline in the happiness of young Australians revealed and explanations offered, the third study builds on the time-invariant individual trait finding from the first study by applying the Australian panel data to an Aggregate Model of Average Happiness over the lifetime. The model’s independent variable is the stress that arises from the interaction between personality and the life event shocks that affect individuals and peers throughout their lives. Interestingly, a graphic depiction of the stress in age relationship reveals an inverse U-shape; an inverse U-shape that looks like the opposite of the U-shape of happiness in age we saw in the first study. The stress arising from life event shocks is found to explain much of the change in average happiness over a lifetime. With the policy recommendations of economists potentially invoking unexpected changes in our lives, the ensuing stress and resulting (un)happiness warrant consideration before economists make policy recommendations.

An empirical investigation of health information system failure in regional Sri Lanka

Public health decision making is critically dependant on accurate, timely and reliable information. There is a widespread belief that most of the national and sub-national health information systems fail in providing much needed information support for evidence based health planning and interventions. This situation is more acute in developing nations where resources are either stagnant or decreasing, coupled with the situations of demographic transition and double burden of diseases. Literature abounds with publications, which provide information on misguided health interventions in developing nations, leading to failure and waste of resources. Health information system failure is widely blamed for this situation. Nevertheless, there is a dearth of comprehensive evaluations of existing national or sub-national health information systems, especially in the region of South-East Asia. This study makes an attempt to bridge this knowledge gap by evaluating a regional health information system in Sri Lanka. It explores the strengths and weaknesses of the current health information system and related causative factors in a decentralised health system and then proposes strategic recommendations for reform measures. A mix methodological and phased approach was adopted to reach the objectives. An initial self administered questionnaire survey was conducted among health managers to study their perceptions in relation to the regional health information system and its management support. The survey findings were used to establish the presence of health information system failure in the region and also as a precursor to the more in-depth case study which was followed. The sources of data for the case study were literature review, document analysis and key stake holder interviews. Health information system resources, health indicators, data sources, data management, data quality, and information dissemination were the six major components investigated. The study findings reveal that accurate, timely and reliable health information is unavailable and therefore evidence based health planning is lacking in the studied health region. Strengths and weaknesses of the current health information system were identified and strategic recommendations were formulated accordingly. It is anticipated that this research will make a significant and multi-fold contribution for health information management in developing countries. First, it will attempt to bridge an existing knowledge gap by presenting the findings of a comprehensive case study to reveal the strengths and weaknesses of a decentralised health information system in a developing country. Second, it will enrich the literature by providing an assessment tool and a research method for the evaluation of regional health information systems. Third, it will make a rewarding practical contribution by presenting valuable guidelines for improving health information systems in regional Sri Lanka.

Empirical analysis on relationship between traffic conditions and crash occurrences

This paper investigates relationship between traffic conditions and the crash occurrence likelihood (COL) using the I-880 data. To remedy the data limitations and the methodological shortcomings suffered by previous studies, a multiresolution data processing method is proposed and implemented, upon which binary logistic models were developed. The major findings of this paper are: 1) traffic conditions have significant impacts on COL at the study site; Specifically, COL in a congested (transitioning) traffic flow is about 6 (1.6) times of that in a free flow condition; 2)Speed variance alone is not sufficient to capture traffic dynamics’ impact on COL; a traffic chaos indicator that integrates speed, speed variance, and flow is proposed and shows a promising performance; 3) Models based on aggregated data shall be interpreted with caution. Generally, conclusions obtained from such models shall not be generalized to individual vehicles (drivers) without further evidences using high-resolution data and it is dubious to either claim or disclaim speed kills based on aggregated data.

Empirical evaluation of alternative approaches in identifying crash hot spots

This study proposes a framework of a model-based hot spot identification method by applying full Bayes (FB) technique. In comparison with the state-of-the-art approach [i.e., empirical Bayes method (EB)], the advantage of the FB method is the capability to seamlessly integrate prior information and all available data into posterior distributions on which various ranking criteria could be based. With intersection crash data collected in Singapore, an empirical analysis was conducted to evaluate the following six approaches for hot spot identification: (a) naive ranking using raw crash data, (b) standard EB ranking, (c) FB ranking using a Poisson-gamma model, (d) FB ranking using a Poisson-lognormal model, (e) FB ranking using a hierarchical Poisson model, and (f) FB ranking using a hierarchical Poisson (AR-1) model. The results show that (a) when using the expected crash rate-related decision parameters, all model-based approaches perform significantly better in safety ranking than does the naive ranking method, and (b) the FB approach using hierarchical models significantly outperforms the standard EB approach in correctly identifying hazardous sites.

Empirical IEEE 802.11p performance evaluation on test tracks

IEEE 802.11p is the new standard for inter-vehicular communications (IVC) using the 5.9 GHz frequency band; it is planned to be widely deployed to enable cooperative systems. 802.11p uses and performance have been studied theoretically and in simulations over the past years. Unfortunately, many of these results have not been confirmed by on-tracks experimentation. In this paper, we describe field trials of 802.11p technology with our test vehicles. Metrics such as maximum range, latency and frame loss are examined.

Detecting common dynamics in transitory components

This paper considers VECMs for variables exhibiting cointegration and common features in the transitory components. While the presence of cointegration between the permanent components of series reduces the rank of the long-run multiplier matrix, a common feature among the transitory components leads to a rank reduction in the matrix summarizing short-run dynamics. The common feature also implies that there exists linear combinations of the first-differenced variables in a cointegrated VAR that are white noise and traditional tests focus on testing for this characteristic. An alternative, however, is to test the rank of the short-run dynamics matrix directly. Consequently, we use the literature on testing the rank of a matrix to produce some alternative test statistics. We also show that these are identical to one of the traditional tests. The performance of the different methods is illustrated in a Monte Carlo analysis which is then used to re-examine an existing empirical study. Finally, this approach is applied to provide a check for the presence of common dynamics in DSGE models.

Instructing foreign language learners how to listen through metacognitive strategies : an empirical study

This study uses a mixed method approach to investigate the impact of metacognitive strategies instruction on listening comprehension. An experimental group (N = 30) of university students are guided through a process-approach pedagogy over one semester (10 weeks) in Iran. IELTS listening tests are used to track development of listening comprehension in participants who are then asked to complete a Metacognitive Awareness Listening Questionnaire (MALQ). The questionnaire examines students’ employment of metacognitive strategies in listening comprehension. Finally, interviews are used to explore students’ use of strategies in listening. Results indicate that participants develop listening comprehension, but no metacognitive awareness in listening. Students reported in the interviews that they use multiple strategies (cognitive and metacognitive) to approach listening comprehension.

Forecasting volatility and correlation : the role of option implied measures

Forecasts of volatility and correlation are important inputs into many practical financial problems. Broadly speaking, there are two ways of generating forecasts of these variables. Firstly, time-series models apply a statistical weighting scheme to historical measurements of the variable of interest. The alternative methodology extracts forecasts from the market traded value of option contracts. An efficient options market should be able to produce superior forecasts as it utilises a larger information set of not only historical information but also the market equilibrium expectation of options market participants. While much research has been conducted into the relative merits of these approaches, this thesis extends the literature along several lines through three empirical studies. Firstly, it is demonstrated that there exist statistically significant benefits to taking the volatility risk premium into account for the implied volatility for the purposes of univariate volatility forecasting. Secondly, high-frequency option implied measures are shown to lead to superior forecasts of the intraday stochastic component of intraday volatility and that these then lead on to superior forecasts of intraday total volatility. Finally, the use of realised and option implied measures of equicorrelation are shown to dominate measures based on daily returns.