Estimating uncertainty in ecosystem budget calculations

© The Authors, 2010. This article is distributed under the terms of the Creative Commons Attribution-Noncommercial License. The definitive version was published in Ecosystems 13 (2010): 239-248, doi:10.1007/s10021-010-9315-8.Ecosystem nutrient budgets often report values for pools and fluxes without any indication of uncertainty, which makes it difficult to evaluate the significance of findings or make comparisons across systems. We present an example, implemented in Excel, of a Monte Carlo approach to estimating error in calculating the N content of vegetation at the Hubbard Brook Experimental Forest in New Hampshire. The total N content of trees was estimated at 847 kg ha−1 with an uncertainty of 8%, expressed as the standard deviation divided by the mean (the coefficient of variation). The individual sources of uncertainty were as follows: uncertainty in allometric equations (5%), uncertainty in tissue N concentrations (3%), uncertainty due to plot variability (6%, based on a sample of 15 plots of 0.05 ha), and uncertainty due to tree diameter measurement error (0.02%). In addition to allowing estimation of uncertainty in budget estimates, this approach can be used to assess which measurements should be improved to reduce uncertainty in the calculated values. This exercise was possible because the uncertainty in the parameters and equations that we used was made available by previous researchers. It is important to provide the error statistics with regression results if they are to be used in later calculations; archiving the data makes resampling analyses possible for future researchers. When conducted using a Monte Carlo framework, the analysis of uncertainty in complex calculations does not have to be difficult and should be standard practice when constructing ecosystem budgets

Excess-entropy scaling in supercooled binary mixtures

Supercooled liquids near the glass transition show remarkable non-Arrhenius transport phenomena, whose origin is yet to be clarified. Here, the authors use GPU molecular dynamics simulations for various binary mixtures in the supercooled regime to show the validity of a quasiuniversal excess-entropy scaling relation for viscosity and diffusion

On the Importance of Complaint Handling Design : A Multi-Level Analysis of the Impact in Specific Complaint Situations

Given the large investments required for high-quality complaint handling design, managers need practical guidance in understanding its actual importance for their particular company. However, while prior research emphasizes the general relevance of complaint handling design, it fails to provide a more differentiated perspective on this interesting issue. This study, which is based on an integrative multi-level framework and a dyadic dataset, addresses this important gap in research. Results indicate that the impact of a company’s complaint handling design varies significantly depending on the characteristics of the complaining customers with which the firm has to deal. Further, this paper shows that, contingent on these characteristics, a company’s complaint handling design can shape complainants’ fairness perceptions either considerably or only slightly. Overall, findings suggest that companies should apply an adaptive approach to complaint handling to avoid misallocation of attention, energy, and resources

E-commerce ethics and its impact on buyer repurchase intentions and loyalty: an empirical study of small and medium Egyptian businesses

The theoretical understanding of e-commerce has received much attention over the years; however, relatively little focus has been directed towards e-commerce ethics, especially the SMEs B2B e-commerce aspect. Therefore, the purpose of this paper is to develop and empirically test a framework that explains the impact of SMEs B2B e-commerce ethics on buyer repurchase intentions and loyalty. Using SEM to analyse the data collected from a sample of SME e-commerce firms in Egypt, the results indicate that buyers’ perceptions of supplier ethics construct is composed of six dimensions (security, non-deception, fulfilment/reliability, service recovery, shared value, and communication) and strongly predictive of online buyer repurchase intentions and loyalty. Furthermore, our results also show that reliability/fulfilment and non-deception are the most effective relationship-building dimensions. In addition, relationship quality has a positive effect on buyer repurchase intentions and loyalty. The results offer important implications for B2B e-commerce and are likely to stimulate further research in the area of relationship marketing