Testing hypotheses with fuzzy data: The fuzzy <Emphasis Type="Bold">p</Emphasis>-value

Statistical hypothesis testing is very important for finding decisions in practical problems. Usually, the underlying data are assumed to be precise numbers, but it is much more realistic in general to consider fuzzy values which are non-precise numbers. In this case the test statistic will also yield a non-precise number. This article presents an approach for statistical testing at the basis of fuzzy values by introducing the fuzzy p-value. It turns out that clear decisions can be made outside a certain interval which is determined by the characterizing function of the fuzzy p-values.     

Measuring Productivity and Quality Changes Using Data Envelopment Analysis: An Application to Catalan Hospitals

This paper focuses on hospital performance using Data Envelopment Analysis (DEA) and Malmquist index numbers. We present a new approach that restricts achievement in productivity if quality is reduced. Results present an apparent negative evolution in productivity. The decomposition on the Malmquist index shows a clear improvement in technical quality, a convergence in efficiency between frontier and non-frontier hospitals and a theoretical fall in technical change (drop of the best practice frontier between years). The conclusions present reasoning justifying these results and propose the use of this methodology for the appraisal of effectiveness in the public sector.     

Assessment of alternative railway systems for sustainable transportation using an integrated IRN SWARA and IRN CoCoSo model

The long-term sustainability of the railway transportation system is determined by a set of criteria that must be considered. For this reason, multi-criteria decision-making (MCDM) techniques have been used because of their high possibility of providing complementary instruments with successful flexibility. Keeping this in mind, we developed a multi-criteria method to conduct an assessment of currently operational railway systems in West Africa for sustainable transportation based on the examination of key challenges affecting the railway system. This study presents the interval rough step-wise weight assessment ratio analysis-combined compromise solution (IR-SWARA-CoCoSo) model. We have adapted the model to group decision-making by incorporating a new technique for dealing with ambiguity and the utilization of interval rough numbers (IRNs). To evaluate the importance coefficients of criteria in the group decision-making procedure, a new interval rough SWARA method has been introduced as an improvement to handle the issues related to MCDM. For the evaluation of the railway transportation system for sustainable transportation, a novel interval rough CoCoSo method was used. According to the findings, information systems is the most critical challenge to the railway transportation system, while the railway system in Nigeria is the best among others. The results were validated in two stages of sensitivity analysis: a comparison with different interval rough approaches, and the calculation of Spearman's correlation coefficient and WS coefficient for all ranks in the comparative analysis.     

Aggregate accounting research and development expenditures and the prediction of real gross domestic product

The role of accounting information for public policy making has received increased attention in recent years. Konchitchki and Patatoukas, 2014a, Konchitchki and Patatoukas, 2014b demonstrate that growth in aggregate accounting earnings can predict future growth in nominal and real Gross Domestic Product (GDP). We extend the micro to macro literature by decomposing earnings into the R&D and pre-R&D components. Using the Almon (1965) finite distributed lag model, we find that both components can predict future real GDP growth with different lead-lag structures. Importantly, this decomposition significantly increases the explanatory power of the predictive model using accounting information. Aggregate accounting R&D can predict real GDP through the personal consumption, business investment, and net export channels of GDP. Our study extends prior research on the forecasting usefulness of accounting information at the aggregate level and has practical implications for macro forecasting and for public policy making regarding innovative activities of publicly listed firms.     

基于ARIMA模型的海南旅游者人数预测

根据历年海南接待旅游者人数相关数据,分析海南接待旅游者人数的长期趋势、季节性和随机扰动等特征,应用SPSS软件,建立ARIMA时间序列模型,对海南旅游者人数进行预测。