Machine learning algorithms to empower Indian women entrepreneur in E-commerce clothing

Hamsagayathri, P.; Rajakumari, K.

doi:10.1109/iccci48352.2020.9104111

Cited by 8 publications

(9 citation statements)

References 4 publications

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“…Another emerging area where we found a lack of research is the use of big data and artificial intelligence among Indian WEs for a better understanding of their customers and forecasting supply chain issues (Hamsagayathri and Rajakumari, 2020 is an exception). There were no papers that dealt with the entry of WEs into technology-driven innovation enterprises in the Indian context.…”

Section: Where Is the Research Happening?mentioning

confidence: 99%

Women entrepreneurs in India: a systematic literature review

Baral

Dey²,

Manavazhagan³

et al. 2023

IJGE

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PurposeThis paper aims to organize the existing empirical research on women entrepreneurs (WEs) in India, highlight the research areas that have not received attention and present opportunities for future research.Design/methodology/approachA systematic literature review (SLR) was performed on 74 scholarly articles focusing on WEs in India and published between 1993 and 2020. This review is structured around the 4W framework used in previous SLRs. The review is directed by the following foci: what do we know about academic research on WEs in India? How were these studies conducted? Where were these studies conducted? Why should academicians and practitioners consider WE research?FindingsThe authors arrived at four main themes underlying the empirical research on WEs: success factors for WEs, challenges faced by WEs, factors that attract and motivate WEs and performance measures for WEs. While challenges and success factors have received attention from researchers, there is a distinct lack of papers on factors that attract or motivate WE and performance measures. The main gaps identified were a lack of theoretical basis in studies, reliance on interview and survey-based methodology and a lack of context-specific studies.Research limitations/implicationsThe findings of this review are limited to WEs operating in India. Only Scopus-indexed journals listed in the Australian Business Dean's Council Journal Quality List (ABDC JQL) were included in the final SLR list.Originality/valueThis is one of the first studies to use a systematic approach to provide a detailed account of the state of the literature on women's entrepreneurship research in India.

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Section: Where Is the Research Happening?mentioning

confidence: 99%

Women entrepreneurs in India: a systematic literature review

Baral

Dey²,

Manavazhagan³

et al. 2023

IJGE

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“…In order to transition the traditional buying experience to e-commerce, NLP is mostly utilized for fashion advice and recommendations [34,78,79,124,126,[155][156][157][158][159][160][161][162][163][164][165][166][167][168]. Another significant area of study focuses on gathering data from consumers using sentiment analysis techniques, such as via reviews or social media [42,44,[169][170][171][172][173][174][175][176][177][178][179][180]. Finally, studies on picture tagging using textual content analysis have been conducted [55,61,73,89,94,95,98,104,107,113,116,118,[181][182]…”

Section: Ai In B2c Retail and Application Areas Of The Techniquesmentioning

confidence: 99%

“…Many studies [42,169] use CNN for sentiment analysis, and occasionally [44] a final fine-tuning algorithm like BERT is constructed. The studies employ both SVM [172] and NB [179] for classifying opinions [179].…”

Section: Customer Behavior Forecastingmentioning

confidence: 99%

“…Recommender [201] Regressionmodels [142,174] RepTree [203] review [121,138,188,190,204,248] RFM [207] R-GCN [242] RNN [80] Robotandpressuremeasurements [146] SEM [239] siamesenetwork [46,75,79,156] SSD [35,92] Survey [53,127,143,150,162,181,191,196,210,219,221] Survey:kanomodel [139] SVM [64,87,153,179] SVM.REPTree [172] SVP [222] UCB [233] VAR [207] VGG-IE [65] Viola-Jones [148] word2vec [98,102,167] word2vecSVMperf [180] XGBoost [176] Table 6<...…”

Section: R-cnn [59]mentioning

confidence: 99%

“…Summary of purposes with references. Sentimentanalysis [42,44,[169][170][171][172][173][174][175][176][177][178][179][180] Virtualfitting [32,[129][130][131][132][133][134][135][136][138][139][140][141][142][143][144][145][146][149][150][151][152] Table 7. Summary of databases with references.…”

Section: R-cnn [59]mentioning

confidence: 99%

See 2 more Smart Citations

Artificial Intelligence in Business-to-Customer Fashion Retail: A Literature Review

Goti,

Querejeta-Lomas,

Almeida

et al. 2023

Mathematics

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Many industries, including healthcare, banking, the auto industry, education, and retail, have already undergone significant changes because of artificial intelligence (AI). Business-to-Customer (B2C) e-commerce has considerably increased the use of AI in recent years. The purpose of this research is to examine the significance and impact of AI in the realm of fashion e-commerce. To that end, a systematic review of the literature is carried out, in which data from the Web Of Science and Scopus databases were used to analyze 219 publications on the subject. The articles were first categorized using AI techniques. In the realm of fashion e-commerce, they were divided into two categories. These categorizations allowed for the identification of research gaps in the use of AI. These gaps offer potential and possibilities for further research.

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