Explaining the Big Data adoption decision in Small and Medium Sized Enterprises: Cape Town case studies

Problem Statement: Small and Medium-Sized Enterprises (SMEs) play an integral role in the economy of developed and developing countries. SMEs are constantly searching for innovative technologies that will not only reduce their overhead costs but also improve product development, customer relations and profitability. Literature has revealed that some SMEs around the world have incorporated a fairly new technology called Big Data to achieve higher levels of operational efficiency. Therefore, it is interesting to observe the reasons why some organizations in developing countries such as South Africa are not adopting this technology as compared to other developed countries. A large portion of the available literature revealed that there isa general lack of in-depth information and understanding of Big Data amongst SMEs in developing countries such as South Africa. The main objective of this study is to explain the factors that SMEs consider during the Big Data decision process. Purpose of the study: This research study aimed to identify the factors that South African SMEs consider as important in their decision-making process when it comes to the adoption of BigData. The researcher used the conceptual framework proposed by Frambach and Schillewaert to derive an updated and adapted conceptual framework that explained the factors that SMEs consider when adopting Big Data. Research methodology: SMEs located in the Western Province of South Africa were chosen as the case studies. The interpretive research philosophy formed the basis of this research. Additionally, the nature of the phenomenon being investigated deemed it appropriate that the qualitative research method and research design be applied to this thesis. Due to constraints such as limited time and financial resources this was a cross-sectional study. The research strategy in this study was multiple in-depth case studies. The qualitative approach was deemed appropriate for this study. The researcher used two methods to collect data, namely, the primary research method and the secondary research method. The primary research method enabled the researcher to obtain rich data that could assist in answering the primary research questions, whilst the secondary research method included documents which supplemented the primary data collected. Data was analyzed using the NVivo software provided by the University of Cape Town. Key Findings: The findings suggest that the process that influences the decision to adopt Big Data by SMEs follows a three-step approach namely: 1.) Awareness, 2.) Consideration, 3.) Intention. This indicates that for Big Data to be adopted by SMEs there must be organizational readiness to go through the process. This study identified the main intention for SMEs to adopt Big Data is to ensure operational stability. Improved operational efficiency was identified as the supporting sub-theme. This study has raised awareness about the process that SMEs, academic researchers, IT practitioners and government need to place emphasis on to improve the adoption of Big Data by SMEs. Furthermore, this study has raised awareness about the opportunities and challenges that SMEs, academic researchers, IT practitioners and government need to place emphasis on to improve the adoption of Big Data by SMEs. Value of the study: The study adds value in both academia and the business industry as it provides more insight into the factors that SMEs consider in the Big Data adoption decision

Total column CO_2 measurements at Darwin, Australia – site description and calibration against in situ aircraft profiles

An automated Fourier Transform Spectroscopic (FTS) solar observatory was established in Darwin, Australia in August 2005. The laboratory is part of the Total Carbon Column Observing Network, and measures atmospheric column abundances of CO_2 and O_2 and other gases. Measured CO_2 columns were calibrated against integrated aircraft profiles obtained during the TWP-ICE campaign in January–February 2006, and show good agreement with calibrations for a similar instrument in Park Falls, Wisconsin. A clear-sky low airmass relative precision of 0.1% is demonstrated in the CO2 and O2 retrieved column-averaged volume mixing ratios. The 1% negative bias in the FTS X_(CO_2) relative to the World Meteorological Organization (WMO) calibrated in situ scale is within the uncertainties of the NIR spectroscopy and analysis

Carbon dioxide column abundances at the Wisconsin Tall Tower site

We have developed an automated observatory for measuring atmospheric column abundances of CO_2 and O_2 using near-infrared spectra of the Sun obtained with a high spectral resolution Fourier Transform Spectrometer (FTS). This is the first dedicated laboratory in a new network of ground-based observatories named the Total Carbon Column Observing Network. This network will be used for carbon cycle studies and validation of spaceborne column measurements of greenhouse gases. The observatory was assembled in Pasadena, California, and then permanently deployed to northern Wisconsin during May 2004. It is located in the heavily forested Chequamegon National Forest at the WLEF Tall Tower site, 12 km east of Park Falls, Wisconsin. Under clear sky conditions, ∼0.1% measurement precision is demonstrated for the retrieved column CO_2 abundances. During the Intercontinental Chemical Transport Experiment–North America and CO_2 Boundary Layer Regional Airborne Experiment campaigns in summer 2004, the DC-8 and King Air aircraft recorded eight in situ CO_2 profiles over the WLEF site. Comparison of the integrated aircraft profiles and CO_2 column abundances shows a small bias (∼2%) but an excellent correlation

Sources of Carbon Monoxide and Formaldehyde in North America Determined from High-Resolution Atmospheric Data

We analyze the North American budget for carbon monoxide using data for CO and formaldehyde concentrations from tall towers and aircraft in a model-data assimilation framework. The Stochastic Time-Inverted Lagrangian Transport model for CO (STILT-CO) determines local to regional-scale CO contributions associated with production from fossil fuel combustion, biomass burning, and oxidation of volatile organic compounds (VOCs) using an ensemble of Lagrangian particles driven by high resolution assimilated meteorology. In many cases, the model demonstrates high fidelity simulations of hourly surface data from tall towers and point measurements from aircraft, with somewhat less satisfactory performance in coastal regions and when CO from large biomass fires in Alaska and the Yukon Territory influence the continental US. Inversions of STILT-CO simulations for CO and formaldehyde show that current inventories of CO emissions from fossil fuel combustion are significantly too high, by almost a factor of three in summer and a factor two in early spring, consistent with recent analyses of data from the INTEX-A aircraft program. Formaldehyde data help to show that sources of CO from oxidation of CH4 and other VOCs represent the dominant sources of CO over North America in summer.Earth and Planetary Science

Mesoscale covariance of transport and CO2 fluxes: Evidence from observations and simulations using the WRF-VPRM coupled atmosphere-biosphere model

We developed a modeling system which combines a mesoscale meteorological model, the Weather Research and Forecasting (WRF) model, with a diagnostic biospheric model, the Vegetation Photosynthesis and Respiration (VPRM). The WRF-VPRM modeling system was designed to realistically simulate high-resolution atmospheric CO₂ concentration fields. In the system, WRF takes into account anthropogenic and biospheric CO₂ fluxes and realistic initial and boundary conditions for CO₂ from a global model. The system uses several “tagged” tracers for CO₂ fields from different sources. VPRM uses meteorological fields from WRF and high-resolution satellite indices to simulate biospheric CO₂ fluxes with realistic spatiotemporal patterns. Here we present results from the application of the model for interpretation of measurements made within the CarboEurope Regional Experiment Strategy (CERES). Simulated fields of meteorological variables and CO₂ were compared against ground-based and airborne observations. In particular, the characterization by aircraft measurements turned out to be crucial for the model evaluation. The comparison revealed that the model is able to capture the main observed features in the CO₂ distribution reasonably well. The simulations showed that daytime CO₂ measurements made at coastal stations can be strongly affected by land breeze and subsequent sea breeze transport of CO₂ respired from the vegetation during the previous night, which can lead to wrong estimates when such data are used in inverse studies. The results also show that WRF-VPRM is an effective modeling tool for addressing the near-field variability of CO₂ fluxes and concentrations for observing stations around the globe

Seasonal pattern of regional carbon balance in the central Rocky Mountains from surface and airborne measurements

[1] High-elevation forests represent a large fraction of potential carbon uptake in North America, but this uptake is not well constrained by observations. Additionally, forests in the Rocky Mountains have recently been severely damaged by drought, fire, and insect outbreaks, which have been quantified at local scales but not assessed in terms of carbon uptake at regional scales. The Airborne Carbon in the Mountains Experiment was carried out in 2007 partly to assess carbon uptake in western U.S. mountain ecosystems. The magnitude and seasonal change of carbon uptake were quantified by (1) paired upwind-downwind airborne CO2 observations applied in a boundary layer budget, (2) a spatially explicit ecosystem model constrained using remote sensing and flux tower observations, and (3) a downscaled global tracer transport inversion. Top-down approaches had mean carbon uptake equivalent to flux tower observations at a subalpine forest, while the ecosystem model showed less. The techniques disagreed on temporal evolution. Regional carbon uptake was greatest in the early summer immediately following snowmelt and tended to lessen as the region experienced dry summer conditions. This reduction was more pronounced in the airborne budget and inversion than in flux tower or upscaling, possibly related to lower snow water availability in forests sampled by the aircraft, which were lower in elevation than the tower site. Changes in vegetative greenness associated with insect outbreaks were detected using satellite reflectance observations, but impacts on regional carbon cycling were unclear, highlighting the need to better quantify this emerging disturbance effect on montane forest carbon cycling

The CO2 tracer clock for the Tropical Tropopause Layer

Observations of CO2 were made in the upper troposphere and lower stratosphere in the deep tropics in order to determine the patterns of large-scale vertical transport and age of air in the Tropical Tropopause Layer (TTL). Flights aboard the NASA WB-57F aircraft over Central America and adjacent ocean areas took place in January and February, 2004 (Pre-AURA Validation Experiment, Pre-AVE) and 2006 (Costa Rice AVE, CR-AVE), and for the same flight dates of 2006, aboard the Proteus aircraft from the surface to 15 km over Darwin, Australia (Tropical Warm Pool International Cloud Experiment, TWPICE). The data demonstrate that the TTL is composed of two layers with distinctive features: (1) the lower TTL, 350–360 K (potential temperature(θ); approximately 12–14 km), is subject to inputs of convective outflows, as indicated by layers of variable CO2 concentrations, with air parcels of zero age distributed throughout the layer; (2) the upper TTL, from θ=~360 K to ~390 K (14–18 km), ascends slowly and ages uniformly, as shown by a linear decline in CO2 mixing ratio tightly correlated with altitude, associated with increasing age. This division is confirmed by ensemble trajectory analysis. The CO2 concentration at the level of 360 K was 380.0(±0.2) ppmv, indistinguishable from surface site values in the Intertropical Convergence Zone (ITCZ) for the flight dates. Values declined with altitude to 379.2(±0.2) ppmv at 390 K, implying that air in the upper TTL monotonically ages while ascending. In combination with the winter slope of the CO2 seasonal cycle (+10.8±0.4 ppmv/yr), the vertical gradient of –0.78 (±0.09) ppmv gives a mean age of 26(±3) days for the air at 390 K and a mean ascent rate of 1.5(±0.3) mm s−1. The TTL near 360 K in the Southern Hemisphere over Australia is very close in CO2 composition to the TTL in the Northern Hemisphere over Costa Rica, with strong contrasts emerging at lower altitudes (<360 K). Both Pre-AVE and CR-AVE CO2 observed unexpected input from deep convection over Amazônia deep into the TTL. The CO2 data confirm the operation of a highly accurate tracer clock in the TTL that provides a direct measure of the ascent rate of the TTL and of the age of air entering the stratosphere

Total Column CO2CO_2 Measurements at Darwin, Australia – Site Description and Calibration Against In Situ Aircraft Profiles

An automated Fourier Transform Spectroscopic (FTS) solar observatory was established in Darwin, Australia in August 2005. The laboratory is part of the Total Carbon Column Observing Network, and measures atmospheric column abundances of $CO_2$ and $O_2$ and other gases. Measured $CO_2$ columns were calibrated against integrated aircraft profiles obtained during the TWP-ICE campaign in January–February 2006, and show good agreement with calibrations for a similar instrument in Park Falls, Wisconsin. A clear-sky low airmass relative precision of 0.1% is demonstrated in the $CO_2$ and $O_2$ retrieved column-averaged volume mixing ratios. The 1% negative bias in the FTS $X_{CO_2}$ relative to the World Meteorological Organization (WMO) calibrated in situ scale is within the uncertainties of the NIR spectroscopy and analysis.Earth and Planetary SciencesEngineering and Applied Science