Critical Success Factors for Implementing Artificial Intelligence (AI) Projects in Dubai Government United Arab Emirates (UAE) Health Sector: Applying the Extended Technology Acceptance Model (TAM)

2019 ◽  
pp. 393-405 ◽  
Author(s):  
Shaikha F. S. Alhashmi ◽  
Said A. Salloum ◽  
Sherief Abdallah
Keyword(s):  
Artificial Intelligence ◽  
Technology Acceptance ◽  
United Arab Emirates ◽  
Technology Acceptance Model ◽  
Critical Success Factors ◽  
Success Factors ◽  
Health Sector ◽  
Critical Success ◽  
Acceptance Model

scholarly journals Acceptance and resistance to e-learning adoption in developing countries: a literature review

2021 ◽  
Author(s):  
Eduardo Bizzo
Keyword(s):  
Developing Countries ◽  
Literature Review ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Success Factors ◽  
Critical Success ◽  
Use Of Technology ◽  
E Learning ◽  
Acceptance Model ◽  
Do So

Abstract This article aims at understanding how research on acceptance and resistance to e-learning in developing countries is undertaken. To do so, it performs a systematic literature review of articles from 2007 to 2019. As a result, 44 analyzed studies have shown the evolvement of e-learning acceptance literature in developing countries in the last decade, mainly grounded on the Technology Acceptance Model (TAM) framework, with minor use of Unified Theory of Acceptance and Use of Technology (UTAUT) and critical success factors perspective. None of the reviewed studies used an explicit framework of resistance to adoption. Also, most of the applications of TAM and UTAUT did not explore the specificities of developing countries in the acceptance of e-learning. Furthermore, the review has found a concentration of studies focusing on students, Higher Education, and developing countries with the highest income levels.

scholarly journals Acceptance of artificial intelligence in German agriculture: an application of the technology acceptance model and the theory of planned behavior

2021 ◽  
Author(s):  
Svenja Mohr ◽  
Rainer Kühl
Keyword(s):  
Artificial Intelligence ◽  
Theory Of Planned Behavior ◽  
Technology Acceptance ◽  
Planned Behavior ◽  
Technology Acceptance Model ◽  
Structural Equation ◽  
Perceived Behavioral Control ◽  
Labor Costs ◽  
Online Questionnaire ◽  
Acceptance Model

AbstractThe use of Artificial Intelligence (AI) in agriculture is expected to yield advantages such as savings in production resources, labor costs, and working hours as well as a reduction in soil compaction. However, the economic and ecological benefits of AI systems for agriculture can only be realized if farmers are willing to use them. This study applies the technology acceptance model (TAM) of Davis (1989) and the theory of planned behavior (TPB) of Ajzen (1991) to investigate which behavioral factors are influencing the acceptance of AI in agriculture. The composite model is extended by two additional factors, expectation of property rights over business data and personal innovativeness. A structural equation analysis is used to determine the importance of factors influencing the acceptance of AI systems in agriculture. For this purpose, 84 farmers were surveyed with a letter or an online questionnaire. Results show that the perceived behavioral control has the greatest influence on acceptance, followed by farmers’ personal attitude towards AI systems in agriculture. The modelled relationships explain 59% of the total variance in acceptance. Several options and implications on how to increase the acceptance of AI systems in agriculture are discussed.

Critical success factors for integrating artificial intelligence and robotics

2020 ◽  
Vol 22 (4) ◽  
pp. 307-331 ◽  
Author(s):  
Umar Bashir Mir ◽  
Swapnil Sharma ◽  
Arpan Kumar Kar ◽  
Manmohan Prasad Gupta
Keyword(s):  
Artificial Intelligence ◽  
Multinational Enterprises ◽  
Critical Success Factors ◽  
Success Factors ◽  
Autonomous Systems ◽  
Building Blocks ◽  
Content Type ◽  
Clear Cut ◽  
Critical Success ◽  
Societal Problems

Purpose This paper aims to enlighten stakeholders about critical success factors (CSFs) in developing intelligent autonomous systems (IASs) by integrating artificial intelligence (AI) with robotics. It suggests a prioritization hierarchy model for building sustainable ecosystem for developing IASs. Design/methodology/approach This paper is based on the existing literature and on the opinion of 15 experts. All the experts have minimum of eight years of experience in AI and related technologies. The CSF theory is used as a theoretical lens and total interpretative structure modelling (TISM) is used for the prioritization of CSFs. Findings Developing countries like India could leverage IASs and associated technologies for solving different societal problems. Policymakers need to develop basic policies regarding data collection, standardized hardware, skilled manpower, funding and start-up culture that can act as building blocks in undertaking sustainable ecosystem for developing IASs and implementing national AI strategy. Clear-cut regulations need to be in place for the proper functioning of the ecosystem. Any technology that can function properly in India has better chances of working at the global level considering the size of the population. Research limitations/implications This paper had all its experts from India only, and that makes the limitation of this paper, as there is a possibility that some of the factors identified may not hold same significance in other countries. Practical implications Stakeholders will understand the critical factors that are important in developing sustainable ecosystem for IASs and what should be the possible order of activities corresponding to each CSF. Originality/value The paper is the first of its kind that has used the CSF theory and TISM methodology for the identification and prioritization of CSFs in developing IASs. Further, eight significant factors, that is, emerging economy multinational enterprises (EMNEs), governance, utility, manpower, capital, software, data and hardware, have come up as the most important factors in integrating AI with robotics in India.

Electronic Transformation of Local Government

2011 ◽  
Vol 7 (1) ◽  
pp. 20-37 ◽  
Author(s):  
Teta Stamati ◽  
Drakoulis Martakos
Keyword(s):  
Local Government ◽  
Technology Acceptance ◽  
Local Governments ◽  
Success Factors ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Perceived Ease Of Use ◽  
Critical Success ◽  
Actual Use ◽  
Acceptance Model

The paper examines the critical success factors for employees’ adoption of the unified Local Government Access Framework (LGAF), deployed for the Central Union of Municipalities and Communities of Greece. Following an extensive bibliographical survey, an initial conceptual framework (CF1) based on the Technology Acceptance Model (TAM) for LGAF adoption is proposed, which is empirically explored within sixteen Local Governments Organizations. The CF1 is revised using the structured-case approach. New concepts discovered during each research cycle revealed that LGAF adoption is a procedure of experiential judgement. The applicability of the TAM is investigated and the model is enhanced, exploring additional variables that affect perceived ease of use, perceived usefulness and actual use. A final complementary CF2 is presented and the evaluation of this model according to the data received from the case studies is discussed.

scholarly journals Implementasi Technology Acceptance Model terhadap Adopsi Teknologi Artificial Intelligence pada Startup Digital

2021 ◽  
Vol 9 (2) ◽  
pp. 173-181
Author(s):  
Margo Purnomo ◽  
Erna Maulina ◽  
Aulia Rizki Wicaksono ◽  
Muhamad Rizal
Keyword(s):  
Artificial Intelligence ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Structural Equation ◽  
Simple Random Sampling ◽  
Sem Analysis ◽  
Perceived Usefulness ◽  
Equation Modeling ◽  
Artificial Intelligence Technology ◽  
Acceptance Model

The purpose of this study is to describe and analyze the implementation of the technology acceptance model on the adoption of artificial intelligence technology in digital startups. By using simple random sampling, a sample of 109 out of 143 populations, which are startups in Greater Jakarta, was obtained. Based on an analysis using Structural Equation Modeling (SEM) analysis with the SmartPLS tool. The results show that the adoption of artificial intelligence in digital startups is influenced by attitudes, perceptions of convenience and perceptions of usefulness. Likewise, perceived convenience and perceived usefulness are significantly affected by external pressures.

scholarly journals Application of Expanded Technology Acceptance Model for Enhancing the HRIS Usage in SMEs

2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Serkan Bayraktaroglu ◽  
Vasfi Kahya ◽  
Erhan Atay ◽  
Habibe Ilhan
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
User Satisfaction ◽  
Technology Use ◽  
Information Technologies ◽  
Success Factors ◽  
Successful Implementation ◽  
Use Of Technology ◽  
Acceptance Model ◽  
New Applications

Rapid developments and change have culminated new applications of information technologies. This trend is reflected in the plethora of innovative studies. Literature indicates that small- to medium-sized enterprises (SMEs) perceive human resources information systems (HRIS) as complicated and time consuming, resulting in resistance from both users and employees. The purpose of this article is to identify necessary acceptance conditions for a successful implementation of the HRIS software within SMEs in Turkey. SMEs compose 99% of all companies in Turkey. Fierce rivalry within sectors gives rise to increased technology use to gain a competitive advantage. This study contributes to an efficient implementation of widely used HRIS in SMEs and offers solutions for implementation failures, including user resistance and idle system problems. This study attempts to apply the technology acceptance model to 112 SMEs that implement HRIS exclusively with all the submodules. This research analyzes success factors for an effective HRIS implementation by testing the latest integrated model of expanded technology acceptance. It concludes that there is a positive and robust correlation between acceptance and use of technology variables and user satisfaction. The results of this study are useful not only for the managers but also for the manufacturers, technical support, online support, and aftersales services as they are advised to develop strategies for user satisfaction.

scholarly journals Using the Technology Acceptance Model to Identify Factors That Predict Likelihood to Adopt Tele-Neurorehabilitation

2020 ◽  
Vol 11 ◽  
Author(s):  
Marlena Klaic ◽  
Mary P. Galea
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Computer Anxiety ◽  
New Technology ◽  
Health Sector ◽  
Theoretical Frameworks ◽  
Related Quality ◽  
Health Related ◽  
Human Decision ◽  
Acceptance Model

Tele-neurorehabilitation has the potential to reduce accessibility barriers and enhance patient outcomes through a more seamless continuum of care. A growing number of studies have found that tele-neurorehabilitation produces equivalent results to usual care for a variety of outcomes including activities of daily living and health related quality of life. Despite the potential of tele-neurorehabilitation, this model of care has failed to achieve mainstream adoption. Little is known about feasibility and acceptability of tele-neurorehabilitation and most published studies do not use a validated model to guide and evaluate implementation. The technology acceptance model (TAM) was developed 20 years ago and is one of the most widely used theoretical frameworks for predicting an individual's likelihood to adopt and use new technology. The TAM3 further built on the original model by incorporating additional elements from human decision making such as computer anxiety. In this perspective, we utilize the TAM3 to systematically map the findings from existing published studies, in order to explore the determinants of adoption of tele-neurorehabilitation by both stroke survivors and prescribing clinicians. We present evidence suggesting that computer self-efficacy and computer anxiety are significant predictors of an individual's likelihood to use tele-neurorehabilitation. Understanding what factors support or hinder uptake of tele-neurorehabilitation can assist in translatability and sustainable adoption of this technology. If we are to shift tele-neurorehabilitation from the research domain to become a mainstream health sector activity, key stakeholders must address the barriers that have consistently hindered adoption.

scholarly journals Success Models of Information Technology Outsourcing

2020 ◽  
Vol 3 (2) ◽  
pp. 37-52
Author(s):  
Sushil Paudel ◽  
H. S. Sharma
Keyword(s):  
Technology Acceptance ◽  
Business Strategy ◽  
Global Economy ◽  
Success Factors ◽  
Information Systems Success ◽  
Is Success ◽  
External Resources ◽  
Critical Success ◽  
Acceptance Model ◽  
Outsourcing Decision

Outsourcing is described as the strategic use of external resources to carry out tasks that have traditionally been performed by internal staff and resources. It is considered to be the best-known phenomena of modern times and business strategy to drive the global economy.  Outsourcing offers enormous benefits to companies only if the outsourcing decision is correct and factors that affect the outsourcing decision are adequately considered, otherwise irreparable harm may be caused. A study to identify the critical success factors of IT outsourcing in Nepal from the vendor's perspective has been initiated. This study examines different models about the effectiveness of outsourcing for the reason. All these models have their own advantages and drawbacks, so a careful review is important to reach at conclusions for the organizations that wish to follow such models. This article is based on4 comprehensive literature review of the success factors for outsourcing that led to the discovery of six different outsourcing models. The study has reviewed Leavitt’s model, McKinsey 7-S framework, The Nadler-Tushman Congruence Model, Technology Acceptance Model, DeLone and McLean's IS-Success Model and IS-Impact Model. Revised DeLone and McLean Model of Information Systems Success, however, are widely debated and considered to be the most promising.  

Critical success factors for public–private partnerships in affordable housing in the United Arab Emirates

2019 ◽  
Vol 13 (5) ◽  
pp. 753-768 ◽  
Author(s):  
Khalifa Alteneiji ◽  
Sabah Alkass ◽  
Saleh Abu Dabous
Keyword(s):  
United Arab Emirates ◽  
Affordable Housing ◽  
Critical Success Factors ◽  
Success Factors ◽  
Public Private Partnerships ◽  
Public And Private ◽  
Content Type ◽  
The Public ◽  
Critical Success ◽  
Gcc Countries

Purpose This study aims to identify the critical success factors (CSFs) in the implementation of the public–private partnerships (PPPs) in the United Arab Emirates’ (UAE) affordable housing sector. Design/methodology/approach A questionnaire survey was conducted to assess 17 CSFs for PPP projects derived from previous international and local studies. The collected data were analyzed using the relative importance index technique to establish the most significant factors based on feedback from 48 respondents from the public and private sectors. Findings The most identified CSFs were good governance, government guarantees, commitment and responsibility of the public and private sectors, favorable and efficient legal frameworks, political support and stability, and demand for and the debt-paying ability of the project. Research limitations/implications There has been rapid momentum in the UAE and other Gulf Cooperation Council (GCC) countries towards engaging the private sector in the provision of infrastructure and housing after increased pressure on government budgets and falling oil prices. Thus, this study encourages strong consideration of the highest-ranked CSFs in the absence of any prior experiences or studies. On a broader scale, these CSFs are an effective policy tool for the GCC countries, which share similar contexts. Originality/value This paper represents the first empirical study in the GCC region and the UAE on the CSFs for PPPs in affordable housing, which is experiencing growing demand in the region to overcome the large deficit in housing supply.

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