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Bricolage and MSEs in emerging economies
This conceptual paper focuses on bricolage and it pays particular attention on the context of micro and small enterprises (MSEs) in resource-constrained environments – a common feature of most emerging economies. Knowledge about the underlying factors that determine bricolage as a common practice among MSEs operating in emerging economies is yet to advance and develop within the mainstream entrepreneurship literature. Much of this scholarship tends to focus on multi-national enterprises (MNEs) in advanced economies and it discusses bricolage as their strategic choice. Such an approach has led to a lack of meaningful theoretical paradigms for defining the business approaches MSEs adopt as a way of mitigating their perennial operational issues inherent in their environment. Thus, in this conceptual paper, which adopts a scoping review approach, we study the constructs of bricolage particularly their application in MSEs operating in emerging economies. From our analysis a fresh deterministic model mapping out the causal factors that give rise to bricolage behaviour in MSEs that operate in difficult conditions emerged. Thus, we contribute to entrepreneurial behaviour theories by identifying distinctive business methods MSEs adopt to withstand operational difficulties inherent in their environments
Estimation and optimal designing under latent variable models for paired comparisons studies via a multiplicative algorithm
We consider:<BR/>
1. The problem of estimating the parameters of latent variable models such as the Bradley Terry or Thurstone Model by the method of maximum likelihood, given data from a paired comparisons experiment. The parameters of these models can be taken to be weights which are positive and sum to one;<BR/>
2. The problem of determining approximate locally optimal designs for good estimation of these parameters; i.e of determining optimal design weights which are also positive and sum to one
The spectrum for Higgs production via heavy quark annihilation at NLL+aNLO
We study the transverse momentum () spectrum of the Higgs boson produced
via the annihilation of heavy quarks () in proton-proton collisions.
Using soft-collinear effective theory (SCET) and working in the five-flavour
scheme, we provide predictions at three-loop order in resummed perturbation
theory (NLL). We match the resummed calculation to full fixed-order
results at next-to-next-to-leading order (NNLO), and introduce a decorrelation
method to enable a consistent matching to an approximate NLO (aNLO)
result. Since the -quark initiated process exhibits large nonsingular
corrections, it requires special care in the matching procedure and estimation
of associated theoretical uncertainties, which we discuss in detail. Our
results constitute the most accurate predictions to date for these processes in
the small region and could be used to improve the determination of Higgs
Yukawa couplings from the shape of the measured Higgs spectrum.Comment: 25 pages + 11 appendix + references, 18 figure
Estimating mangrove aboveground biomass from airborne LiDAR data: a case study from the Zambezi River delta
Mangroves are ecologically and economically important forested wetlands with the highest carbon (C) density of all terrestrial ecosystems. Because of their exceptionally large C stocks and importance as a coastal buffer, their protection and restoration has been proposed as effective mitigation strategy for climate change. The inclusion of mangroves in mitigation strategies requires the quantification of C stocks (both above and belowground) and changes to accurately calculate emissions and sequestration. A growing number of countries are becoming interested in using mitigation initiatives, such as REDD+, in these unique coastal forests. However, it is not yet clear how methods to measure C traditionally used for other ecosystems can be modified to estimate biomass in mangroves with the precision and accuracy needed for these initiatives. Airborne lidar (ALS) data has often been proposed as the most accurate way for larger-scale assessments but, the application of ALS for coastal wetlands is scarce, primarily due to a lack of contemporaneous ALS and field measurements. Here, we evaluated the variability in field and lidar-based estimates of aboveground biomass (AGB) through the combination of different local and regional allometric models and standardized height metrics that are comparable across spatial resolutions and sensor types. The end result being a simplified approach for accurately estimating mangrove AGB at large-scales and determining the uncertainty by combining multiple allometric models. We then quantified wall-to-wall aboveground biomass stocks of a tall mangrove forest in the Zambezi Delta, Mozambique. Our results indicate that the Lidar H100 height metric correlates well with AGB estimates, with R2 between 0.80 and 0.88 and RMSE of 33% or less. When comparing lidar H100 AGB derived from three allometric models, mean AGB values range from 192 Mg. ha-1 up to 252 Mg. ha-1. We suggest the best model to predict AGB was based on the East Africa specific allometry and a power based regression that used Lidar H100 as the height input with a R2 of 0.85 and a RMSE of 122 Mg.ha-1 or 33%. The total AGB of the lidar inventoried mangrove area (6654 ha) was 1,350,902 Mg with a mean AGB 203 Mg. ha-1. Because the allometry suggested here was developed using standardized height metrics, it is recommended that the models can generate AGB estimates using other remote sensing instruments that are more readily accessible over other mangrove ecosystems on a large scale, and as part of future carbon monitoring efforts in mangroves
Some improved estimators of finite population quantile using auxiliary information in sample surveys
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