Application of E-Commerce Technologies in accelerating the Success of
SME Operation
- URL: http://arxiv.org/abs/2110.10836v2
- Date: Sat, 26 Feb 2022 03:20:05 GMT
- Title: Application of E-Commerce Technologies in accelerating the Success of
SME Operation
- Authors: Ziad Hmwd A Almtiri, Shah J Miah, Nasimul Noman
- Abstract summary: This study introduces a conceptual framework of the application of e-Commerce technologies in accelerating the SME operation.
Content analysis methodology was adopted for generating the outcome associated with the success of the technologies in SMEs.
- Score: 1.1602089225841632
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Electronic commerce (e-Commerce) technologies have been increased over the
past two decades in different business sectors. In particular, the technologies
of B2C operations have significantly improved the productivity of online small
businesses such as SMEs. Systematic literature review in this domain
categorized different benefits but a limited number of studies on SME success
from a view of an information systems (IS) research exists, which needs to be
taken for further attention. Informing through a comprehensive analysis this
study introduces a conceptual framework of the application of e-Commerce
technologies in accelerating the SME operation. Content analysis methodology
was adopted for generating the outcome associated with the success of the
technologies in SMEs.
Related papers
- The Enhancement of Software Delivery Performance through Enterprise DevSecOps and Generative Artificial Intelligence in Chinese Technology Firms [0.4532517021515834]
This study investigates the impact of integrating DevSecOps and Generative Artificial Intelligence on software delivery performance within technology firms.
The findings reveal significant enhancements in R&D efficiency, improved source code management, and heightened software quality and security.
arXiv Detail & Related papers (2024-11-04T16:44:01Z) - A Review of AI and Machine Learning Contribution in Predictive Business Process Management (Process Enhancement and Process Improvement Approaches) [4.499009117849108]
We perform a systematic review of academic literature to investigate the integration of AI/ML in business process management.
In business process management and process map, AI/ML has made significant improvements using operational data on process metrics.
arXiv Detail & Related papers (2024-07-07T18:26:00Z) - From Data to Decisions: The Transformational Power of Machine Learning
in Business Recommendations [0.0]
This research aims to explore the impact of Machine Learning (ML) on the evolution and efficacy of Recommendation Systems (RS)
The research identifies the increasing expectation of users for a seamless, intuitive online experience, where content is personalized and dynamically adapted to changing preferences.
arXiv Detail & Related papers (2024-02-12T22:56:18Z) - Quantum Computing Enhanced Service Ecosystem for Simulation in Manufacturing [56.61654656648898]
We propose a framework for a quantum computing-enhanced service ecosystem for simulation in manufacturing.
We analyse two high-value use cases with the aim of a quantitative evaluation of these new computing paradigms for industrially-relevant settings.
arXiv Detail & Related papers (2024-01-19T11:04:14Z) - Knowledge Editing for Large Language Models: A Survey [51.01368551235289]
One major drawback of large language models (LLMs) is their substantial computational cost for pre-training.
Knowledge-based Model Editing (KME) has attracted increasing attention, which aims to precisely modify the LLMs to incorporate specific knowledge.
arXiv Detail & Related papers (2023-10-24T22:18:13Z) - Trends and Challenges Towards an Effective Data-Driven Decision Making
in UK SMEs: Case Studies and Lessons Learnt from the Analysis of 85 SMEs [0.0]
Data Science can support SMEs to optimise production processes, anticipate customers' needs, predict machinery failures and deliver efficient smart services.
integrating data science decisions into an SME requires both skills and IT investments.
This paper presents trends and challenges towards an effective data-driven decision making for organisations based on a case study of 85 SMEs.
arXiv Detail & Related papers (2023-05-24T17:23:32Z) - A Review of Off-Policy Evaluation in Reinforcement Learning [72.82459524257446]
We primarily focus on off-policy evaluation (OPE), one of the most fundamental topics inReinforcement learning.
We provide a discussion on the efficiency bound of OPE, some of the existing state-of-the-art OPE methods, their statistical properties and some other related research directions.
arXiv Detail & Related papers (2022-12-13T03:38:57Z) - The Technological Emergence of AutoML: A Survey of Performant Software
and Applications in the Context of Industry [72.10607978091492]
Automated/Autonomous Machine Learning (AutoML/AutonoML) is a relatively young field.
This review makes two primary contributions to knowledge around this topic.
It provides the most up-to-date and comprehensive survey of existing AutoML tools, both open-source and commercial.
arXiv Detail & Related papers (2022-11-08T10:42:08Z) - Impact of Business technologies on the success of Ecommerce Strategies:
SMEs Perspective [0.0]
The primary task of the study is to inspect the affiliation between the implementation of technology and e-commerce success.
It is imperative to study such an important relationship that directly impacts the rapid growth of Internet technology.
The Saudi Arabia community has been recognized as a potential hub for advancing technology-based programs.
arXiv Detail & Related papers (2020-12-11T09:47:45Z) - Constraint Programming Algorithms for Route Planning Exploiting
Geometrical Information [91.3755431537592]
We present an overview of our current research activities concerning the development of new algorithms for route planning problems.
The research so far has focused in particular on the Euclidean Traveling Salesperson Problem (Euclidean TSP)
The aim is to exploit the results obtained also to other problems of the same category, such as the Euclidean Vehicle Problem (Euclidean VRP), in the future.
arXiv Detail & Related papers (2020-09-22T00:51:45Z) - Deep Technology Tracing for High-tech Companies [67.86308971806322]
We develop a novel data-driven solution, i.e., Deep Technology Forecasting (DTF) framework, to automatically find the most possible technology directions customized to each high-tech company.
DTF consists of three components: Potential Competitor Recognition (PCR), Collaborative Technology Recognition (CTR), and Deep Technology Tracing (DTT) neural network.
arXiv Detail & Related papers (2020-01-02T07:44:12Z)
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.