Which Factors Contribute to the Global Expansion of M-Commerce?

Ciupac-Ulici, Maria; Beju, Daniela-Georgeta; Bresfelean, Vasile Paul; Zanellato, Gianluca

doi:10.3390/electronics12010197

Cited by 6 publications

(4 citation statements)

References 92 publications

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“…The variable 𝓊 𝑛 represents the overall products under consideration. Further, the set of consumers encompassing various demographic categories such as males, females, and children, and others can be represented using in (2). The variable 𝓋 𝑛 represents the overall count of consumers under consideration.…”

Section: System Modelmentioning

confidence: 99%

“…The convenience of online shopping, coupled with a vast array of products available at one's fingertips, has led to a paradigm shift in consumer behaviour. The growth of e-commerce is propelled by various factors, including the widespread availability of high-speed internet, increased smartphone penetration, and evolving consumer preferences [2]. People now rely on e-commerce platforms not only for traditional retail purchases but also for services ranging from food delivery to digital subscriptions.…”

Section: Introductionmentioning

confidence: 99%

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Dual-blend insight recommendation system for e-commerce recommendations and enhance personalization

Silvester,

Kurain

2024

IJEECS

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E-commerce, short for electronic commerce, refers to the buying and selling of goods and services over the internet. This digital transaction model has revolutionized the way businesses operate and consumers shop. In response to the burgeoning complexity of e-commerce datasets, this work addresses the need for advanced recommendation systems. This work introduces the dual-blend insight recommendation system (DIRS) model for personalized e-commerce recommendation system. The DIRS model involves dataset loading, preprocessing, and feature extraction, enabling training with recurrent neural network (RNN) and Bayesian personalized ranking (BPR) models. Recommendations are generated based on user-defined functions, i.e., location and session, and evaluation metrics such as hit rate (HR) and mean reciprocal rate (MRR) highlight DIRS’s superior performance. The model is evaluated using the Tmall dataset. Results reveal DIRS consistently outperforms alternative algorithms, showcasing its effectiveness in 10k and 20k recommendation sets. This study provides valuable insights into optimizing e-commerce recommendations, emphasizing DIRS as a powerful model for enhancing user experience and engagement.

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Section: System Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dual-blend insight recommendation system for e-commerce recommendations and enhance personalization

Silvester,

Kurain

2024

IJEECS

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“…With much faster download and upload speeds, users can easily access multimedia content and stream high-quality videos without interruption. Second, in the last ten years, the number of people who can access the Internet has increased significantly [3]. Many countries that previously did not have internet access have attempted to expand their network coverage.…”

Section: Introductionmentioning

confidence: 99%

The Influence of Artificial Intelligence Technology, Infrastructure and Human Resource Competence on Internet Access Networks

Awaludin,

Yasin,

Risyda

2024

Inf. J. Ilm. Bid. Teknol. Inf. dan Komun.

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The influence of artificial intelligence technology, infrastructure, and human resource competence on Internet access networks has been examined in a scientific publication, which is the outcome of a literature review in the information systems sector. The purpose of this study is to generate an influence hypothesis related to factors that can be applied in further investigations. The research's subjects include academic media, Google Scholar, Mendeley, and online libraries. Publicly accessible e-books and e-journals are the source of the research methodology that makes use of library institution searches. The following is a descriptive qualitative analysis of this article's findings: The influence of artificial intelligence technology on networks for Internet access, the influence of infrastructure on networks for Internet access, and the Influence of HR Competency on Internet Access Networks. Research findings regarding the impact of advances in infrastructure, human resource competence, and artificial intelligence technology on internet network access include improving user experience, extensive network scalability, increasing network efficiency and security, as well as increasing human resource knowledge and developing network architecture research findings regarding the impact of advances in infrastructure, human resource competence, and artificial intelligence technology on internet network access include improving user experience, extensive network scalability, increasing network efficiency and security, as well as increasing human resource knowledge and developing network architecture.

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“…There are few studies on the e-commerce phenomenon in terms of Internet purchases made by individuals, and our research objective is to cover these gaps [30][31][32].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Disparities in Internet Purchases by Individuals at the EU State Level

2023

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In recent years, the trend of digital transformation of commerce has been extremely dynamic, and the COVID-19 pandemic has generated a strong impetus for the development of digitalization. However, there is a large difference in the use of e-commerce in European Union (EU) countries. The objective of this article is to explain the complex evolution of e-commerce in terms of B2C using econometric methods, especially regarding Internet purchases made by individuals according to six social and technological factors considered basic factors in purchase decisions. Thus, we propose a conceptual model for the analysis of disparities in Internet purchases, taking into account both factors related to demand (consumer) and factors related to supply (supplier). Based on the data provided by Eurostat for all 27 EU countries for the period 2012–2021, the empirical findings of cluster analysis suggest changes in the grouping of countries at the beginning and end of the analysed period. Socioeconomic factors that can explain the transition of EU states from one group to another in terms of development level of Internet purchases by individuals were identified. The results of this study can serve as a starting point for future adaptation strategies of e-commerce in the context of global economic development with a focus on increasing digitisation, the existence of for which a digital convergence in the process of digital transformation is essential.

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Which Factors Contribute to the Global Expansion of M-Commerce?

Cited by 6 publications

References 92 publications

Dual-blend insight recommendation system for e-commerce recommendations and enhance personalization

Dual-blend insight recommendation system for e-commerce recommendations and enhance personalization

The Influence of Artificial Intelligence Technology, Infrastructure and Human Resource Competence on Internet Access Networks

Analysis of Disparities in Internet Purchases by Individuals at the EU State Level

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