The European challenge of KMN and innovation: a skills and competence portfolio for knowledge worker in SME's

Versão editor: http://www.isegi.unl.pt/docentes/acorreia/documentos/European_Challenge_KM_Innovation_2004.pdf

Sustainability and economic evaluation of microalgae grown in brewery wastewater

This article evaluates the sustainability and economic potential of microalgae grown in brewery wastewater for biodiesel and biomass production. Three sustainability and two economic indicators were considered in the evaluation within a life cycle perspective. For the production system the most efficient process units were selected. Results show that harvesting and oil separation are the main process bottlenecks. Microalgae with higher lipid content and productivity are desirable for biodiesel production, although comparable to other biofuel’s feedstock concerning sustainability. However, improvements are still needed to reach the performance level of fossil diesel. Profitability reaches a limit for larger cultivation areas, being higher when extracted biomass is sold together with microalgae oil, in which case the influence of lipid content and areal productivity is smaller. The values of oil and/or biomass prices calculated to ensure that the process is economically sound are still very high compared with other fuel options, especially biodiesel.

Performance of state space and ARIMA models for consumer retail sales forecasting

Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.

Is low worker mobility evidence for monopsony power?

Major in Competition and Regulation

Modeling and optimization of extracellular polysaccharides production by Enterobacter A47

Polysaccharides are gaining increasing attention as potential environmental friendly and sustainable building blocks in many fields of the (bio)chemical industry. The microbial production of polysaccharides is envisioned as a promising path, since higher biomass growth rates are possible and therefore higher productivities may be achieved compared to vegetable or animal polysaccharides sources. This Ph.D. thesis focuses on the modeling and optimization of a particular microbial polysaccharide, namely the production of extracellular polysaccharides (EPS) by the bacterial strain Enterobacter A47. Enterobacter A47 was found to be a metabolically versatile organism in terms of its adaptability to complex media, notably capable of achieving high growth rates in media containing glycerol byproduct from the biodiesel industry. However, the industrial implementation of this production process is still hampered due to a largely unoptimized process. Kinetic rates from the bioreactor operation are heavily dependent on operational parameters such as temperature, pH, stirring and aeration rate. The increase of culture broth viscosity is a common feature of this culture and has a major impact on the overall performance. This fact complicates the mathematical modeling of the process, limiting the possibility to understand, control and optimize productivity. In order to tackle this difficulty, data-driven mathematical methodologies such as Artificial Neural Networks can be employed to incorporate additional process data to complement the known mathematical description of the fermentation kinetics. In this Ph.D. thesis, we have adopted such an hybrid modeling framework that enabled the incorporation of temperature, pH and viscosity effects on the fermentation kinetics in order to improve the dynamical modeling and optimization of the process. A model-based optimization method was implemented that enabled to design bioreactor optimal control strategies in the sense of EPS productivity maximization. It is also critical to understand EPS synthesis at the level of the bacterial metabolism, since the production of EPS is a tightly regulated process. Methods of pathway analysis provide a means to unravel the fundamental pathways and their controls in bioprocesses. In the present Ph.D. thesis, a novel methodology called Principal Elementary Mode Analysis (PEMA) was developed and implemented that enabled to identify which cellular fluxes are activated under different conditions of temperature and pH. It is shown that differences in these two parameters affect the chemical composition of EPS, hence they are critical for the regulation of the product synthesis. In future studies, the knowledge provided by PEMA could foster the development of metabolically meaningful control strategies that target the EPS sugar content and oder product quality parameters.

Russian Enterprise Restructuring - the Effect of Privatisation and Market Liberalisation on the Performance of Large Enterprises

The fundamental question in the transitional economies of the former Eastern Europe and Soviet Union has been whether privatisation and market liberalisation have had an effect on the performance of former state-owned enterprises. This study examines the effect of privatisation, capital market discipline, price liberalisation and international price exposure on the restructuring of large Russian enterprises. The performance indicators are sales, profitability, labour productivity and stock market valuations. The results do not show performance differences between state-owned and privatised enterprises. On the other hand, the expansion of the de novo private sector has been strong. New enterprises have significantly higher sales growth, profitability and labour productivity. However, the results indicate a diminishing effect of ownership. The international stock market listing has a significant positive effect on profitability, while the effect of domestic stock market listing is insignificant. The international price exposure has a significant positive increasing effect on profitability and labour productivity. International enterprises have higher profitability only when operating on price liberalised markets, however. The main results of the study are strong evidence on the positive effects of international linkages on the enterprise restructuring and the higher than expected role of new enterprises in the Russian economy.

The Influence of Burnout Symptoms on the Relationship between Work-Life Balance and Self-Rated Health

The effects of stress at work are estimated to cost Canadian employers more than 20 billion dollars annually through absenteeism, sick leave and decreased productivity. Over the past two decades, Canadians have reported higher stress levels, increased work hours and more work performed outside of normal business hours. This work-life imbalance has far-reaching repercussions–affecting an employee’s performance as well as their health. Chronic exposure to these high levels of stress can also lead to burnout. The primary purpose of this study was to determine the magnitude in which burnout symptoms influence the relationship between work-life balance and self-rated health. The secondary purpose of this study was to determine if gender and age interactions exist in the relationship between burnout, work-life balance, and self-rated health. This cross-sectional study involved secondary analysis of 220 managers, workers and human service professionals who completed an Occupational Health Clinics for Ontario Workers’ Mental Injury Toolkit (MIT) survey for the launch of the MIT. The MIT survey is a modified form of the short version of the Copenhagen Psychosocial Questionnaire and includes expanded questioning around burnout, stress, sleep troubles, cognitive, and somatic symptoms. There were no significant differences in self-rated health based on a respondent’s gender or age, indicating that no interaction of gender and age would be required. Respondents with low self-rated health reported significantly higher burnout and work-life imbalance compared to those with high self-rated health. The regression analysis demonstrated that the magnitude in which burnout mediates the relationship between work-life balance and self-rated health was 96%. These findings support previous studies that associate high levels of work-life imbalance or burnout with poor self-rated health or health outcomes. In this study, the shared variance between work-life balance and burnout also supports recent efforts to redefine the context and causes of burnout to include non-work factors. Based on our findings, the potential exists for the development of workplace health promotion strategies that address maintaining a balance between work and home as they may improve employee health and reduce burnout.

Wage Policy of Firms: an Empirical Investigation.

This paper analyzes the dynamics of wages and workers' mobility within firms with a hierarchical structure of job levels. The theoretical model proposed by Gibbons and Waldman (1999), that combines the notions of human capital accumulation, job rank assignments based on comparative advantage and learning about workers' abilities, is implemented empirically to measure the importance of these elements in explaining the wage policy of firms. Survey data from the GSOEP (German Socio-Economic Panel) are used to draw conclusions on the common features characterizing the wage policy of firms from a large sample of firms. The GSOEP survey also provides information on the worker's rank within his firm which is usually not available in other surveys. The results are consistent with non-random selection of workers onto the rungs of a job ladder. There is no direct evidence of learning about workers' unobserved abilities but the analysis reveals that unmeasured ability is an important factor driving wage dynamics. Finally, job rank effects remain significant even after controlling for measured and unmeasured characteristics.

Sector-Specific on-the-Job Training: Evidence from U.S. Data.

Using data from the National Longitudinal Survey of Youth (NLSY), we re-examine the effect of formal on-the-job training on mobility patterns of young American workers. By employing parametric duration models, we evaluate the economic impact of training on productive time with an employer. Confirming previous studies, we find a positive and statistically significant impact of formal on-the-job training on tenure with the employer providing the training. However, the expected net duration of the time spent in the training program is generally not significantly increased. We proceed to document and analyze intra-sectoral and cross-sectoral mobility patterns in order to infer whether training provides firm-specific, industry-specific, or general human capital. The econometric analysis rejects a sequential model of job separation in favor of a competing risks specification. We find significant evidence for the industry-specificity of training. The probability of sectoral mobility upon job separation decreases with training received in the current industry, whether with the last employer or previous employers, and employment attachment increases with on-the-job training. These results are robust to a number of variations on the base model.