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An Evaluation of Technological, Organizational and Environmental Determinants of Emerging Technologies Adoption Driving SMEs’ Competitive Advantage
Get PDFThis research evaluates the technological, organizational, and environmental determinants of emerging technologies adoption represented by Artificial Intelligence (AI) and Internet of Things (IoT) driving SMEs’ competitive advantage within a resource-based view (RBV) theoretical approach supported by the technological-organizational-environmental (TOE)-framework setting. Current literature on SMEs competitive advantage as outcome of emerging technologies in the technological, organisational, and environmental contexts presents models focused on these contexts individual components. There are no models in the literature to represent the TOE framework as an integrated structure with gradual levels of complexity, allowing for incremental evaluation of the business context in support of decision making towards emerging technologies adoption supporting the firm competitive advantage. This research gap is addressed with the introduction of a new concept, the IT resource-based renewal, underpinned by the RBV, and supported by the TOE framework for providing a holistic understanding of the SMEs strategic renewal decision through information technology. This is achieved through a complex measurement model with four level constructs, leading into a parsimonious structural model that evaluates the relationships between IT resource-based renewal, and emerging technologies adoption driving SMEs competitive advantage. The model confirms the positive association between the IT resource-based renewal and emerging technologies adoption, and between the IT resource-based renewal and SME competitive advantage for the SMEs managers model, with the SME owners model outcomes are found not being supportive towards emerging technologies adoption driving SME competitive advantage.
As methodology, PLS-SEM is used for its capabilities of assessing complex paths among model variables. Analysis is done on three models, one for the full sample, with two subsequent ones for owners and managers, respectively, as SME decision makers, with data collected using a web-based survey in Canada, the UK, and the US, that has provided 510 usable answers. This research has a theoretical contribution represented by the introduction of the IT resource-based renewal concept, that integrates the RBV perspective and the TOE framework for supporting organization’s decision on emerging technologies adoption driving SMEs competitive advantage. As practical implications, this thesis provides SMEs with a reference framework on adopting emerging technologies, offering SME managers and owners a comprehensive model of hierarchical factors contributing to SMEs competitive advantage acquired as outcome of AI and IoT adoption. This research makes an original contribution to the enterprise management, information systems adoption, and SME competitive advantage literature, with an empirical approach that verifies a model of emerging technologies adoption determinants driving SMEs competitive advantage
Study of the Continuous Intention to use Artificial Intelligence Based Internet of Medical Things (IoMT) During Concurrent Diffusion. The Influence Diffusion of Innovation Factors Has as Determinants of Continuous Intention to Use Ai-Based IoMT
No full textThis research was about the continuous intention of healthcare professionals to use
internet of medical things (IoMT) embedded with artificial intelligence (AI). IoMT and AI
are evolving innovations and diffusing at the same time. It was not known in what way the
two complex technologies diffusing concurrently could influence continuous intention to
use IoMT. In addition, behavioural aspects namely motivation and training to use IoMT
have been argued to intervene in the relationship between an AI based IoMT and
continuous intention to use IoMT. Diffusion of Innovation theory was applied to explain
the relationship between diffusion factors that aid the diffusion of AI based IoMT and
continuous intention to use IoMT. The five factors relative advantage, compatibility,
complexity, observability and trialability were chosen as determinants of continuous
intention to use IoMT using DoI theory. Self-determination theory and theory of planned
behaviour were used to introduce the interventions in the relationship between diffusion
factors and continuous intention to use IoMT. UTAUT was used to explain the influence
of the moderators artificial intelligence awareness, novelty seeking behaviour and age of healthcare professionals. The central issue investigated was the determinants of
continuous intention of healthcare professionals to use IoMT with behavioural attributes
of motivation and training conceived as mediators of the relationship between diffusion
factors and continuous intention to use IoMT in the presence of moderators.
Quantitative research methodology was used to test the research model developed to
understand the relationship between the five diffusion of innovation theory factors and
continuous intention to use IoMT when AI based IoMT is still diffusing. The concurrent
diffusion of two new technologies was investigated using a research model that was
developed for studying the healthcare professionals and their intention. The research was conducted in Bahrain in the healthcare sector. A sample of 354 healthcare professionals
participated in the research. Structural equation modelling was used to analyse the data
and test the hypothesis.
The research showed that healthcare professionals will continue to use concurrently
diffusing technologies depending on the relative advantage, complexity and compatibility
of the innovations that diffuse. In addition, the results show that healthcare professionals
will be motivated by the compatibility of AI-based IoMT if they have to continuously use
IoMT. Furthermore, training enables both the organization and the healthcare
professionals to overcome dilemma in case they have to continue to use an innovation
during its diffusion or when new innovation surface in the market. Finally, artificial
intelligence awareness is able to moderate the relationship between relative advantage,
complexity and training to use IoMT. Thus, this research contributes to the discipline of
behavioural intention of healthcare professionals in determining the influence of an
artificial intelligence based IoMT on continuous intention to use IoMT when artificial
intelligence embedded in IoMT diffuses concurrently with IoMT. Where IoMT diffusion factors can be used as a determine of continuous intention to use IoMT, artificial intelligence could be understood as a moderator of the relationship between diffusion factors and training to use IoMT, thus demonstrating the combined diffusion of the two technologies diffusing concurrently
3D simulation of the Hierarchical Multi-Mode Molecular Stress Function constitutive model in an abrupt contraction flow
Get PDFYesA recent development of the Molecular Stress Function constitutive model, the Hierarchical Multi-Mode Molecular Stress Function (HMMSF) model has been shown to fit a large range of rheometrical data with accuracy, for a large range of polymer melts. We develop a 3D simulation of the HMMSF model and compare it to experimental data for the flow of Lupolen 1840H LDPE through an abrupt 3D contraction flow. We believe this to be the first finite element implementation of the HMMSF model. It is shown that the model gives a striking agreement with experimental vortex opening angles, with very good agreement to full-field birefringence measurements, over a wide range of flow rates.
A method to give fully-developed inlet boundary conditions is implemented (in place of using parabolic inlet boundary conditions), which gives a significantly improved match to birefringence measurements in the inlet area, and in low stress areas downstream from the inlet.
Alternative constitutive model parameters are assessed following the principle that extensional rheometer data actually provides a ‘lower bound’ for peak extensional viscosity. It is shown that the model robustly maintains an accurate fit to vortex opening angle and full-field birefringence data, provided that both adjustable parameters are kept such that both shear and extensional data are well fitted
Exploratory study of fathers providing Kangaroo Care in a Neonatal Intensive Care Unit
Get PDFYesAim and Objectives: To explore fathers' views and experiences of providing Kangaroo Care (KC) to their baby cared for in a Neonatal Intensive Care Unit (NICU).
Kangaroo Care has been known to improve the health outcome for preterm, low birth weight and medically vulnerable term infants and achieve the optimal perinatal health wellbeing for parents and infants. Historically, mothers are considered as the dominant KC providers, whereas fathers are spectators and have been overlooked. Little is known about the fathers' perspectives in providing KC in NICUs.
Methods: Individual semi-structured interviews were conducted with 10 fathers who delivered KC to their baby when in the NICU. Data were analysed using Braun and Clarke's six-phase thematical framework. The Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist was followed to report this qualitative study. Findings: Fathers in this study identified they were passing a silent language of love and connecting with their baby by the act of KC in a challenging environment. Three themes emerged: ‘Positive psychological connection’, ‘Embracing father-infant Kangaroo Care’ and ‘Challenges to father-infant Kangaroo Care’.
Conclusion: The findings of this study show KC enhances the bonding and attachment between fathers and infants. The conceptualisation of the paternal role in caregiving to a newborn is evolving as a contemporary practice. Further research is warranted to confirm or refute the study findings. Policies and facilities should be modified to include father–infant KC within the fields of neonatal care. Relevance to Clinical Practice: It is important for nurses and other health professionals to support and enable fathers to give KC. Father–infant KC is recommended in neonatal care settings.Open access publishing facilitated by University of South Australia, as part of the Wiley - University of South Australia agreement via the Council of Australian University Librarians
Perceptions of dental health professionals (DHPs) on job satisfaction in Fiji: a qualitative study
Get PDFYesReviewing job satisfaction is crucial as it has an impact on a person's physical and mental wellbeing, as well as leading to a better organizational commitment of employees that enhances the organizations succession and progress as well as better staff retention. This study aimed to explore the perceptions of job satisfaction amongst Dental Health Professionals (DHPs) in Fiji and associated factors.
This study used a phenomenological qualitative method approach commencing from August to November, 2021. The target group for this study were the DHPs who provide prosthetic services. This study was conducted among DHPs from 4 purposively selected clinics in Fiji. A semi- structured open-ended questionnaire was used to collect data. Thematic analysis was used to transcribe and analyze the audio qualitative data collected from the interviews.
Twenty-nine DHPs took part in the in-depth interview and the responses were grouped into three themes. The findings from the study indicate that DHPs are most satisfied with their teamwork and the relationship they have with their colleagues and co-workers, followed by the nature of the work and the supervision they received. The participants indicated that they were less satisfied with professional development opportunities and least satisfied with their pay and organizational support they receive.
The results of this study have identified gaps and areas for improvement of job satisfaction for DHPs who provide prosthetic services in Fiji such as need for more career and professional development pathways, improved infrastructure to support prosthetic service delivery in Fiji and improve remuneration for DHPs. Understanding the factors that affect satisfaction levels and being able to act accordingly are likely to lead to positive outcomes both for DHPs and their organization
Grid connected hybrid renewable energy systems for urban households in Djibouti: An economic evaluation
Get PDFYesThe cost of electricity produced by thermal power plants in Republic of Djibouti is relatively high at about 337, 1,025/year, respectively. When compared with the average cost of grid-only connection
of $0.32/kWh, the optimal hybrid renewable energy system is more economical and will save 51 % of the cost
that the customer must pay when using only the electricity from the grid
Process simulation of fluidized bed granulation: effect of process parameters on granule size distribution
Get PDFYesThe purpose of granulation is to improve the flowability of powders, whilst reducing the dustiness and potential of segregation. The focus of this project is to understand the effects of the process parameters of fluidized bed granulation on the granule size distribution of the final product using gFP simulation software (Siemens PSE, UK). The wet granulation process has become predominant and important in the pharmaceutical industry, due to its cost-effectiveness and its robustness in product formulation. The process parameters that were subject of this study include the air flow rate of 20, 40 and 60 m3/hr., the binder concentration of 6, 9 and 12 wt.%, and the binder spray rate of 7.14, 14.28 and 21.42 ml/min. The results show that binder spray rate has the most impact on the granule size distribution, where an increase in binder spray rate is associated with a higher incidence of larger granules in the product. The air flow rate and the binder concentration have a negligible impact on the granule size distribution when agglomeration and consolidation models are not implemented in the simulation.Ghana Scholarship Secretariat and Siemens PSE UK for providing the software resource force this research
The relationship between financial inclusion, economic growth and poverty: A study of Jordan
No full textThis thesis empirically investigates the relationship between financial inclusion, economic growth and poverty in Jordan during the period 1980-2020. The study argues that providing financial services to individuals is an effective way to enhance economic growth and reduce poverty. It investigates the access to and usage of financial services in Jordan. This study applies the Autoregressive Distributed Lag (ARDL) model to examine the annual time-series data collected from the CBJ, World Bank, and IMF. The Augmented Dickey Fuller test is used to test the stationarity of variables used in the ARDL model.
The study shows that financial inclusion has a significant positive effect on economic growth. Moreover, the study also indicates that financial inclusion has a significant positive effect on income per capita, which reduces poverty. Finally, the outcome shows that economic growth enhances financial inclusion.
Consequently, the study confirms finance and growth theory, which asserts that financial services are a positive function of economic growth and reduce poverty. Consequently, this study recommends that extending and enhancing financial inclusion in Jordan needs to be afforded greater effort due to its positive effect on the Jordanian economy generally and on economic growth specifically.Mut’ah University (Jordan
Inclusive hyper- to dilute-concentrated suspended sediment transport study using modified rouse model: parametrized power-linear coupled approach using machine learning
No full textYesThe transfer of suspended sediment can range widely from being diluted to being hyperconcentrated, depending on the local flow and ground conditions. Using the Rouse model and the
Kundu and Ghoshal (2017) model, it is possible to look at the sediment distribution for a range of hyper-concentrated and diluted flows. According to the Kundu and Ghoshal model, the sediment flow follows a linear profile for the hyper-concentrated flow regime and a power law applies for the dilute concentrated flow regime. This paper describes these models and how the Kundu and Ghoshal parameters (linear-law coefficients and power-law coefficients) are dependent on sediment flow parameters using machine-learning techniques. The machine-learning models used are XGboost Classifier, Linear Regressor (Ridge), Linear Regressor (Bayesian), K Nearest Neighbours, Decision Tree Regressor, and Support Vector Machines (Regressor). The models were implemented on Google Colab and the models have been applied to determine the relationship between every Kundu and Ghoshal parameter with each sediment flow parameter (mean concentration, Rouse number, and size parameter) for both a linear profile and a power-law profile. The models correctly calculated the suspended sediment profile for a range of flow conditions ( 0.268 ≤ 50 ≤ 2.29 , 0.00105 3 ≤ particle density ≤ 2.65 3 , 0.197 ≤ ≤ 96 , 7.16 ≤ ∗ ≤ 63.3 , 0.00042 ≤ ̅≤ 0.54), including a range of Rouse numbers (0.0076 ≤ ≤ 23.5). The models showed particularly good accuracy for testing at low and extremely high concentrations for type I to III profiles
CellsDeepNet: A Novel Deep Learning-Based Web Application for the Automated Morphometric Analysis of Corneal Endothelial Cells
No full textYesThe quantification of corneal endothelial cell (CEC) morphology using manual and semi-automatic software enables an objective assessment of corneal endothelial pathology. However, the procedure is tedious, subjective, and not widely applied in clinical practice. We have developed the CellsDeepNet system to automatically segment and analyse the CEC morphology. The CellsDeepNet system uses Contrast-Limited Adaptive Histogram Equalization (CLAHE) to improve the contrast of the CEC images and reduce the effects of non-uniform image illumination, 2D Double-Density Dual-Tree Complex Wavelet Transform (2DDD-TCWT) to reduce noise, Butterworth Bandpass filter to enhance the CEC edges, and moving average filter to adjust for brightness level. An improved version of U-Net was used to detect the boundaries of the CECs, regardless of the CEC size. CEC morphology was measured as mean cell density (MCD, cell/mm2), mean cell area (MCA, µm2), mean cell perimeter (MCP, µm), polymegathism (coefficient of CEC size variation), and pleomorphism (percentage of hexagonality coefficient). The CellsDeepNet system correlated highly significantly with the manual estimations for MCD (r = 0.94), MCA (r = 0.99), MCP (r = 0.99), polymegathism (r = 0.92), and pleomorphism (r = 0.86), with