A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.     

Easing the assessment of emerging technologies in technology observatories. Findings about patterns of dissemination of emerging technologies on the internet

This paper considers the Web as a big data container that can be used by Technology Observatories and administrations to track emerging issues and more specifically emerging technologies. It considers information that is available on the Internet for free from different sources, and proposes a framework that can be useful to characterise them and to detect patterns of dissemination. This framework is made up of 30 metrics obtained from different kinds of sources (general web, patents, scholars?…). Some of them are obtained directly as the number of hits retrieved by queries on a search engine, and other ones calculated by means of ratios. This paper contains the development of a complete case that utilises this framework to characterise emerging technologies included in the well-known Hype Cycle for Emerging Technologies, in this case the 2015 release¹ and to analyze patterns of dissemination of these technologies on the Internet.     

Determinants of total efficiency in water utilities in Mexico

By using panel data analysis across 368 water utilities in Mexico over the period 2010–2014, we find that small firms are more efficient than medium and large providers and that increasing production is associated with less efficiency. Billing, income collection and profitability are relevant factors to improve efficiency. Medium and large firms require to measure consumption by service with meters in order to increase efficiency, while small firms do not require it.     

Towards an operations strategy model of servitization: the role of sustainability pressure

Servitization requires an important strategic shift to drive changes in the operations of manufacturing firms. Using a large-scale survey, the purpose of this paper is (1) to build and validate an operations strategy model of servitization confirming previous case study findings on servitization as a strategic action and (2) to explore the role of sustainability pressures in, and the sustainability performance effects of, pursuing service-based operations strategies. To reach these objectives, a dataset including the responses of 735 manufacturing plants from 21 different countries is analyzed using the PLS-SEM method. The results indicate that the sustainability pressures of stakeholders can push manufacturers to adopt a service-based operations strategy, materializing in the provision of both basic (product-oriented) and advanced (customer-oriented) services (BAS and ADS). Our analysis further indicates that while offering BAS is a precondition for ADS provision, only ADS can offer a competitive edge for manufacturers, both in terms of service and sustainability-related operational performance.     

New methods of evaluating physical demand at work areas

The manufacturer's requirement of increasing productivity results in the need to design work stations that are increasingly more effective and specialized. However, this procedure can bring about an overloading of the worker, a lack of motivation, and, consequently, a reduction in productivity.Ergonomics adapts the work station to the worker with the object of improving his welfare and satisfaction at his post. One aspect that this science concerns itself with is the evaluation of physical demands connected to productive tasks. Mechanical movements are also studied in order to perform tasks efficiently.We here propose a new method of physical demand analysis that determines the risk factor for muscular skeletal lesion. This method uses, as a base, the system of predetermined times, MTM-UAS. It includes a computer system that allows us to easily analyse the operations at a work station and generates charts similar to those of UAS, but, instead of times, it measures the quantity of mechanical work necessary for each movement.The information that the method provides can be used by different divisions within companies in making decisions about improvements at work stations.     

Estimation of the mean in ranked set sampling with non responses

The estimation of the population mean when ranked set sampling [rss] is used for selecting the sample and non responses [nr] are present, is studied. The nr stratum is sub sampled using simple random sampling with replacement. Two strategies are analyzed. One of them is based on the selection of a sub sample from the nr in each cycle. The other uses sub samples selected among the nr in each rank.  The accuracy of the proposed estimators is characterized by the corresponding expected variances. Simulations and real life data are used for analyzing the behavior of them. Acknowledgements: This paper was developed partially during the visit of the author to Université des Antilles et Gouyane. The author gratefully acknowledges the helpful suggestions of the referees and thanks the support of DAAD for visiting Humboldt University where a version of the paper version was made.     

Analysing the factors influencing clean technology adoption: a study of the Spanish pulp and paper industry

Technological change has a relevant role to play in the transition towards a sustainable industry. However, slow diffusion of clean technologies can be observed in OECD countries. The analysis of the determinants and barriers to clean technology adoption should be a main goal of economists and social scientists. This paper shows that three sets of interrelated factors prevent but also stimulate the widespread adoption and diffusion of clean technology: these are factors external and internal to the firm, conditions of the potential adopters and characteristics of the environmental technology. These factors are included in the so‐called ‘triangular model’, which is further applied to the analysis of clean technology adoption in the pulp and paper industry in Spain. The empirical study shows that clean technology adoption decisions are the result of an interaction between these factors, often involving contradictory signals for the potential adopter. The paper closes with some public policy recommendations for the effective and efficient promotion of clean technology diffusion. Copyright © 2005 John Wiley & Sons, Ltd and ERP Environment.     

CREDIT CYCLES REDUX*

Theoretical studies have shown that under unorthodox assumptions on preferences and production technologies, collateral constraints can act as a powerful amplification and propagation mechanism of exogenous shocks. We investigate whether or not this result holds under more standard assumptions. We find that collateral constraints typically generate small output amplification. Large amplification is obtained as a “knife‐edge” type of result.     

Regional innovation and small high technology firms in peripheral regions

This paper highlights the difficulty of developing HT firms in a peripheral region of Spain. Although the endogenous development of HT firms in these regions is possible, their evolution depends on more central regions. The firm's geographical location and the type of HT production are the most important endogenous factors governing the firm's success.