Trends in eBusiness and eGovernment

• URL: http://arxiv.org/abs/2104.01176v1
• Date: Fri, 2 Apr 2021 17:53:17 GMT
• Title: Trends in eBusiness and eGovernment
• Authors: Antonio S\'anchez-Bay\'on, Miguel \'Angel Garc\'ia-Ramos Lucero, Annie Ng Cheng San, Choy Johnn Yee, Krishna Moorthy, Alex Foo Tun Lee, Angelita Kithatu-Kiwekete, Shikha Vyas-Doorgapersad, Anthony Kiryagana Isabirye, Nobukhosi Dlodlo, Lydia Mbati, Edmore Tarambiwa, Chengedzai Mafini, Anastas Djurovski, Ephrem Habtemichael Redda, Jhalukpreya Surujlal
• Abstract summary: The first chapter is a critical review and a case study in eBusiness, with special attention to the digital currencies resource. The second chapter attempts to incorporate the UTAUT model with perceived risk theory to explore its impact on the intention to use m-government services. The third chapter aims to assess the level of gender inclusivity in the municipal e-procurement processes in the City of Johannesburg.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: The first chapter is a critical review and a case study in eBusiness, with special attention to the digital currencies resource and its possibilities. 2. chapter attempts to incorporate the UTAUT model with perceived risk theory to explore its impact on the intention to use m-government services. 3. chapter aims to assess the level of gender inclusivity in the municipal e-procurement processes in the City of Johannesburg as a case study. It uses a GAD approach. 4. chapter examines the impediments that derail the intensive uptake of eLearning programmes in a particular higher education institution. The study adopted an inductive research paradigm that followed a qualitative research strategy. Data were collected by means of one-on-one in-depth interviews from selected faculty members at a nominated institution of higher learning. 5. chapter investigated the role of KMS in enhancing the export performance of firms operating within the manufacturing sector in Zimbabwe. The study used a quantitative approach in which a survey questionnaire was distributed to 555 managers drawn from 185 manufacturing firms based in Harare. Data analyses involved the use of descriptive statistics, Spearman correlations and regression analysis. In the sixth chapter, a survey was undertaken on 131 SMEs from the Pelagonija region in order to determine the current level of SME digitalization within the region. It is aimed to compare with the EU average and to make conclusions on the impact of the SME digitalization on region GDP growth as well as revenues collection. The last chapter s purpose was to develop a measuring and modelling framework, an instrument of IBSQ for the South African banking sector. Snowball and convenience sampling, both non-probability techniques were used to recruit participants for the study. A total of 310 Internet banking customer responses were utilised in the analysis.

Related papers

• KemenkeuGPT: Leveraging a Large Language Model on Indonesia's Government Financial Data and Regulations to Enhance Decision Making [0.0]
  This study investigates the potential of Large Language Models to address Indonesia's financial data and regulations. This study undertakes an iterative process to develop KemenkeuGPT using the LangChain with Retrieval-Augmented Generation (RAG), prompt engineering and fine-tuning. The model's accuracy improved from 35% to 61%, with correctness increasing from 48% to 64%.
  arXiv  Detail & Related papers  (2024-07-31T09:16:33Z)
• Chain-of-Thought Prompting for Demographic Inference with Large Multimodal Models [58.58594658683919]
  Large multimodal models (LMMs) have shown transformative potential across various research tasks. Our findings indicate LMMs possess advantages in zero-shot learning, interpretability, and handling uncurated 'in-the-wild' inputs. We propose a Chain-of-Thought augmented prompting approach, which effectively mitigates the off-target prediction issue.
  arXiv  Detail & Related papers  (2024-05-24T16:26:56Z)
• Evaluating Interventional Reasoning Capabilities of Large Language Models [58.52919374786108]
  Large language models (LLMs) can estimate causal effects under interventions on different parts of a system. We conduct empirical analyses to evaluate whether LLMs can accurately update their knowledge of a data-generating process in response to an intervention. We create benchmarks that span diverse causal graphs (e.g., confounding, mediation) and variable types, and enable a study of intervention-based reasoning.
  arXiv  Detail & Related papers  (2024-04-08T14:15:56Z)
• The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark [6.116258355914058]
  This study conduct an extensive Brain-computer interfaces (BCI) analysis on open electroencephalography datasets. The need for such benchmark lies in the rapid industrial progress that has given rise to undisclosed proprietary solutions.
  arXiv  Detail & Related papers  (2024-04-03T15:18:50Z)
• A Survey on Interpretable Cross-modal Reasoning [64.37362731950843]
  Cross-modal reasoning (CMR) has emerged as a pivotal area with applications spanning from multimedia analysis to healthcare diagnostics. This survey delves into the realm of interpretable cross-modal reasoning (I-CMR) This survey presents a comprehensive overview of the typical methods with a three-level taxonomy for I-CMR.
  arXiv  Detail & Related papers  (2023-09-05T05:06:48Z)
• Mapping Computer Science Research: Trends, Influences, and Predictions [0.0]
  We employ advanced machine learning techniques, including Decision Tree and Logistic Regression models, to predict trending research areas. Our analysis reveals that the number of references cited in research papers (Reference Count) plays a pivotal role in determining trending research areas. The Logistic Regression model outperforms the Decision Tree model in predicting trends, exhibiting higher accuracy, precision, recall, and F1 score.
  arXiv  Detail & Related papers  (2023-08-01T16:59:25Z)
• Surveying (Dis)Parities and Concerns of Compute Hungry NLP Research [75.84463664853125]
  We provide a first attempt to quantify concerns regarding three topics, namely, environmental impact, equity, and impact on peer reviewing. We capture existing (dis)parities between different and within groups with respect to seniority, academia, and industry. We devise recommendations to mitigate found disparities, some of which already successfully implemented.
  arXiv  Detail & Related papers  (2023-06-29T12:44:53Z)
• A Study of Situational Reasoning for Traffic Understanding [63.45021731775964]
  We devise three novel text-based tasks for situational reasoning in the traffic domain. We adopt four knowledge-enhanced methods that have shown generalization capability across language reasoning tasks in prior work. We provide in-depth analyses of model performance on data partitions and examine model predictions categorically.
  arXiv  Detail & Related papers  (2023-06-05T01:01:12Z)
• Investigating Fairness Disparities in Peer Review: A Language Model Enhanced Approach [77.61131357420201]
  We conduct a thorough and rigorous study on fairness disparities in peer review with the help of large language models (LMs) We collect, assemble, and maintain a comprehensive relational database for the International Conference on Learning Representations (ICLR) conference from 2017 to date. We postulate and study fairness disparities on multiple protective attributes of interest, including author gender, geography, author, and institutional prestige.
  arXiv  Detail & Related papers  (2022-11-07T16:19:42Z)
• Cloud Computing Adoption: Opportunities and Challenges for Small, Medium and Micro Enterprises in South Africa [0.0]
  The study shows that relative advantage is an important factor in the consideration of cloud computing adoption by SMMEs. The study has revealed that cloud computing presents opportunities to SMMEs and improves their competitiveness.
  arXiv  Detail & Related papers  (2021-08-23T11:21:40Z)
• Going Paperless -- Main Challenges in EDRMS Implementation -- Case of Georgia [0.0]
  This study is to inquire Electronic Documents and Records Management Systems (EDRMS) in the context of eGovernment. The centre of the investigation is howMS could raise efficiency in public service delivery. Different ICT adoption theories and case study examples were analysed, among which the Estonian case was taken as a successful model.
  arXiv  Detail & Related papers  (2020-10-07T06:37:53Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.