Low back pain disability and stay at work: contradiction or necessity?

The incidence of occupational diseases in the population is high and factors such as long working hours, poor posture, psychological and physical stress can contribute to its development. Among work-related musculoskeletal disorders, back pain has a high prevalence. The aim of the present study was to quantify and characterize pain complaints and to identify individuals with low back pain, in order to assess the degree of disability. Participated 226 employees of an institution of higher education. They answered a general questionnaire about location and quantification of pain complaints visual analog scale for pain and the Quebec Disability Questionnaire. Of all the workers, 69.60% had some type of musculoskeletal complaint; of those, 15.41% had low back pain. Considering workers who had back pain, 54.9% were female, 52.94% are under 30 years old and 43.14% between 1 and 5 years of work. As for the final score for the degree of disability, 41.17% had minimal disability and 37.25% moderate disability. The present study found large number of pain complaints and high prevalence of low back pain, resulting in individual's inability and difficulties in performing work activities.     

A note on defining organisational systems for contingency theory in OM

Abstract

This paper aims to improve the applicability and relevance of contingency theory research in the field of Operations Management. Based on the results of previous studies, we have identified a systems-based single definition of organisation types that could describe the fit between organisational environment and organisational structure. This definition of organisation type, which we call an ‘organisational system’, regards the organisation as an integrated whole instead of as a sum of its parts and can help to better classify organisations in order to identify fits between organisation types and emerging practices in Operations Management.     

Macroeconomic Uncertainty Through the Lens of Professional Forecasters

ABSTRACT

We analyze the evolution of macroeconomic uncertainty in the United States, based on the forecast errors of consensus survey forecasts of various economic indicators. Comprehensive information contained in the survey forecasts enables us to capture a real-time measure of uncertainty surrounding subjective forecasts in a simple framework. We jointly model and estimate macroeconomic (common) and indicator-specific uncertainties of four indicators, using a factor stochastic volatility model. Our macroeconomic uncertainty estimates have three major spikes has three major spikes aligned with the 1973–1975, 1980, and 2007–2009 recessions, while other recessions were characterized by increases in indicator-specific uncertainties. We also show that the selection of data vintages affects the estimates and relative size of jumps in estimated uncertainty series. Finally, our macroeconomic uncertainty has a persistent negative impact on real economic activity, rather than producing “wait-and-see” dynamics.     

Copper mining productivity: Lessons from Chile

Chile represents almost one third of the world’s copper production. Mining is one of the main industries that contributes to our country’s development with resources and is globally recognized. Due to the end of the commodity cycle, improving productivity will be a key variable in mining performance in incoming years. This paper studies mining productivity in Chile by relying on two indicators: measure of the total factor productivity (TFP) using the traditional Solow methodology, and labor productivity. Since 2000, we found a decrease in TFP, explained mainly by the participation of capital as well as diverse factor adjustments to labor and capital inputs. Average labor productivity also decreases 42% from 1999 to 2010, a decrease explained by four determinants: real mining wages, electricity prices, copper prices and mineral grade. Since 2010, average labor productivity has increased 30%, and there is also an opportunity for additional improvement by reducing energy costs as well as by aligning productivity and labor performances.     

Structured Coupling of Probability Loss Distributions: Assessing Joint Flood Risk in Multiple River Basins

Losses due to natural hazard events can be extraordinarily high and difficult to cope with. Therefore, there is considerable interest to estimate the potential impact of current and future extreme events at all scales in as much detail as possible. As hazards typically spread over wider areas, risk assessment must take into account interrelations between regions. Neglecting such interdependencies can lead to a severe underestimation of potential losses, especially for extreme events. This underestimation of extreme risk can lead to the failure of riskmanagement strategies when they are most needed, namely, in times of unprecedented events. In this article, we suggest a methodology to incorporate such interdependencies in risk via the use of copulas. We demonstrate that by coupling losses, dependencies can be incorporated in risk analysis, avoiding the underestimation of risk. Based on maximum discharge data of river basins and stream networks, we present and discuss different ways to couple loss distributions of basins while explicitly incorporating tail dependencies. We distinguish between coupling methods that require river structure data for the analysis and those that do not. For the later approach we propose a minimax algorithm to choose coupled basin pairs so that the underestimation of risk is avoided and the use of river structure data is not needed. The proposed methodology is especially useful for large‐scale analysis and we motivate and apply our method using the case of Romania. The approach can be easily extended to other countries and natural hazards.     

Employing the Components of the Human Development Index to Drive Resources to Educational Policies

A new form of composition of the indicators employed to generate the United Nations Human Development Index (HDI) is presented here. This form of composition is based on the assumption that random errors affect the measurement of each indicator. This assumption allows for replacing the vector of evaluations according to each indicator by vectors of probabilities of being the best or the worst according to such attribute. The probabilistic composition of such probabilities of preference according to each indicator into probabilities of being the best or the worst according to all of them generates indices that may unveil, on one hand, performances to be followed and, on the other hand, extreme conditions that an additive composition would hide. Differences between the results of application of the diverse forms of composition are examined in the case of the HDI and in the case of the districts version of the HDI employed to compare Brazilian municipalities. It is verified that the smallest correlation between the education enrolment rate and the other indicators in the Brazilian case enlarges such differences.     

Deprivation Index for Small Areas Based on Census Data in Argentina

Social Indicators Research - This paper presents the construction and estimation of a deprivation index based on Principal Factors Analysis for the 2010 Argentina Population and Housing Census in a...     

A new continuous distribution on the unit interval applied to modelling the points ratio of football teams

We introduce a new flexible distribution to deal with variables on the unit interval based on a transformation of the sinh–arcsinh distribution, which accommodates different degrees of skewness and kurtosis and becomes an interesting alternative to model this type of data. We also include this new distribution into the generalised additive models for location, scale and shape (GAMLSS) framework in order to develop and fit its regression model. For different parameter settings, some simulations are performed to investigate the behaviour of the estimators. The potentiality of the new regression model is illustrated by means of a real dataset related to the points rate of football teams at the end of a championship from the four most important leagues in the world: Barclays Premier League (England), Bundesliga (Germany), Serie A (Italy) and BBVA league (Spain) during three seasons (2011–2012, 2012–2013 and 2013–2014).